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University of Groningen
Fatty liver diseaseEdens, Mireille Angélique
IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite fromit. Please check the document version below.
Document VersionPublisher's PDF, also known as Version of record
Publication date:2011
Link to publication in University of Groningen/UMCG research database
Citation for published version (APA):Edens, M. A. (2011). Fatty liver disease: pathophysiology & assessment. s.n.
CopyrightOther than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of theauthor(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons).
Take-down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediatelyand investigate your claim.
Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons thenumber of authors shown on this cover page is limited to 10 maximum.
ter verkrijging van het doctoraat in de Medische Wetenschappen
aan de Rijksuniversiteit Groningen op gezag van de
Rector Magnificus, dr. F. Zwarts, in het openbaar te verdedigen op
woensdag 19 januari 2011 om 16:15 uur
door
Mireille Angélique Edens
geboren op 15 september 1980 te Beerta
Promotor: Prof. dr. R.P. Stolk
Beoordelingscommissie: Prof. dr. F. Kuipers
Prof. dr. M. Oudkerk
Prof. dr. M.H. Hofker
Paranimfen: Li Qin Simona Budulac
6
CONTENTS
Chapter Page 1 General introduction: Historical perspectives on fatty liver disease. 9
Edens MA. 2 Fatty liver disease and cardiovascular risk in the general population of 25
East Anglia: The Fenland Study.
Edens MA, Forouhi NG, Emanuella de Lucia-Rolfe, Wareham NJ, Stolk RP, and other investigators of the Fenland Study; Authors to be determined. In preparation/ awaiting enlargement of database.
3 Non-alcoholic fatty liver disease is associated with cardiovascular disease 55
8.1 Evidence on screening for fatty liver disease: Future perspectives. 165
Edens MA, Stolk RP. Submitted/ under review _ Review Paper 8.2 Additional remarks and recommendations for future research. 191
7
Summaries 197 - English summary 198
- Nederlandse samenvatting (Dutch summary) 202
List of abbreviations 203 Dankwoord (Word of gratitude) 207 Curriculum Vitae 211 - About the author 212 - List of publications 213
8
Chapter 1. General introduction
Historical perspectives on fatty liver disease
Mireille A. Edens
Department of Epidemiology
University Medical Center Groningen University of Groningen
Groningen, the Netherlands
Chapter 1.
10
INTRODUCTION
Development of diagnosis modalities and execution of many studies during the last and
present decade, have substantially increased our knowledge on fatty liver disease (FLD).
Epidemiological studies have revealed a worldwide incidence of obesity 1 and FLD 2, 3. The
present high prevalence of FLD may delineate a major public health risk CHAPTER 2. The
aim of this chapter is to give an overview on the historical development of FLD, and the
contribution of this thesis to our understanding of FLD.
DISCOVERY OF LIVER FAT
Excess fat should be stored in adipocytes (subcutaneous fat), where it functions as producer
of several factors 4. In the case of dietary overflow or pathology, lipids can be stored in the
peritoneal cavity (visceral fat), retro-peritoneal (peri-renal fat), or ectopically, i.e. inside
myocytes and organs (e.g. the liver) as well 5. The presence of fat within the human liver
was first reported by Hartley (1907 and 1909) 6, 7 [source 8].
THE HISTOLOGICAL FATTY LIVER DISEASE SPECTRUM
Classification
Cross-sectional and follow-up studies by histology have revealed that FLD is a broad
spectrum, which includes many histological parameters with varying severity.
Parameters within the spectrum
Younossi ea. (1998) reviewed the literature on histologic FLD parameters, and identified
nineteen histological features, which they grouped into four categories: 1) ‘steatosis’, 2)
‘inflammation’, 3) ‘liver cell injury’, and 4) ‘fibrosis’ 9, which has resulted in the four FLD
subtypes published by Matteoni ea. (1999) 10. Observer variability analysis revealed
however that scoring of ‘inflammation’ was unreliable 9. In the same year, Brunt ea. (1999)
published a semi-quantitative scoring protocol for distinguishing non-alcoholic steatosis
(NAS) and non-alcoholic steatohepatitis (NASH), based on 10 predominant histological
features of NAFLD activity 11. Harrison ea. (2003) presented a modification of the Brunt
protocol, i.e. they divided inflammation score into ‘inflammation’ and ‘degeneration and
necrosis’, similar to the liver cell injury group by Younossi ea., but reliability of this
method was not reported 12. Kleiner ea. (2005) published an update of the Brunt protocol,
Historical perspectives
11
based on 14 histological features 13. Similar to Younossi ea. 9, reliability of scoring was
found to be less than perfect 13.
Terminology
FLD is currently the denominator used to indicate all its subtypes, although the “D” has
been under debate 14. Throughout history many synonyms have been used to indicate the
same subtypes. Table І shows a classification of the FLD spectrum, including terminology
used throughout history.
FAT DISTRIBUTION AND CARDIOVASCULAR DISEASE
In 1947, Vague published about a difference between the cardiovascular disease (CVD) risk
of android (based on male sex) and gynoid obesity (based on female sex) 15.
Liver fat and cardiovascular disease risk
A ‘marker’ for CVD risk includes the metabolic syndrome (MetS). The MetS is associated
with an incidence of CVD events, as reported by a recently published meta-analysis 16. A
close association between non-alcoholic FLD (NAFLD) and the MetS was first published
by Huth ea. (1992) 17. In 2001, Davis & Hui published the following paper: “atherosclerosis
is a liver disease of the heart” 18. Currently, NAFLD is considered the hepatic component of
the MetS 19.
Liver fat, insulin resistance and cardiovascular disease risk
The last two decennia provided some evidence that insulin resistance may be a cornerstone
in fat distribution-associated CVD risk. In 1993, Hotamisligil ea. published: “Adipose
expression of tumour necrosis factor-alpha: direct role in obesity-linked insulin resistance”
20. In CHAPTER 3 21 we review the NAFLD-associated overproduction of CVD risk
markers, including the role of tumour necrosis factor-alpha (TNFα) and hepatic insulin
resistance.
Chapter 1.
12
Table І
. C
lass
ific
atio
n o
f th
e fa
tty liv
er d
isea
se s
pec
trum
, in
cludin
g ter
min
olo
gy u
sed thro
ughout his
tory
EN
TIR
E F
LD
SP
EC
TR
UM
Dia
bet
ic liv
er d
isea
se (
1955)
22
Dia
bet
ic f
atty
liv
er (
1971)
23
FL
D (
1999)
10
Fat
ty liv
er (
2003)
14
Ste
atohep
atit
is
Fat
ty h
epat
itis
(1933)
24
Ste
atonec
rosi
s (1
955)
25
Infl
amm
atory
ste
atonec
rosi
s (1
973)
26
Fat
ty liv
er h
epat
itis
(1979)
27
SH
(1980)
28
Dia
bet
ic h
epat
itis
(1985)
29
Type
2 F
LD
(2002)
30
SH
sco
re ≥
5 (
2005)
13
Cir
rhosi
s w
ithout fa
t
and infl
amm
atio
n
Burn
ed-o
ut F
LD
(2001)
31
Bla
nd C
(2004)
32
HC
C (1
990)
33
C, ci
rrhosi
s; F
, fi
bro
sis;
FL
D, fa
tty liv
er d
isea
se; H
CC
, hep
atoce
llula
r ca
rcin
om
a; M
T, M
atte
oni ty
pe;
S, st
eato
sis;
SH
, st
eato
hep
atitis
Fat
wit
h s
pec
ific
infl
amm
atio
n
and f
ibro
sis
or
cirr
hosi
s
Fat
ty C
(1938)
34
Lae
nnec
’s C
, w
ith e
nla
rged
liv
er (
1939)
35
Nutr
itio
nal
C (
1948)
36
MT
4 (
1999)
10
SH
sta
ge
2; w
ith F
(2009)
37
HC
C (
2005)
37,
38
Fat
wit
h s
pec
ific
infl
amm
atio
n
MT
3 (
1999)
10
SH
sta
ge
1; w
ithout F
(2009)
37
Ste
atosi
s
Hyper
trophic
S (
1935)
39
Type
1 F
LD
(2002)
30
SH
sco
re <
5 (
2005)
13
Fat
wit
h n
on-s
pec
ific
infl
amm
atio
n
MT
2 (
1999)
10
Inte
rmed
iate
SH
(2003)
40
Bord
erli
ne
SH
(2005)
13
Fat
only
Sim
ple
S (
1975)
41
Pure
S (
1991)
42
Pure
fat
ty liv
er (
1995)
43,
44
MT
1 (
1999)
10
Bla
nd S
(2007)
45
Historical perspectives
13
ETIOLOGY/ PATHOGENESIS
Historically, the destructive effect of alcohol on the liver has been well known, which is
deducible by many publications on alcoholic liver disease [source 46]. Therefore alcoholic
FLD (AFLD) and non-alcoholic FLD (NAFLD) are often distinguished, usually using an
ethanol cut-off value of 20 g/d 19, as this value may non-significantly elevate
aminotransferases only 47. However, alcohol is only one of the many etiologic factors of
FLD. In CHAPTER 4 we propose to modify current theories on pathogenesis and
arrangements of risk factors for FLD into the following three categories: 1) risk factors for
hepatic lipid content, 2) risk factors for inhibited hepatic metabolism, and 3) risk factors for
hepatic inflammation.
DIAGNOSIS
Diagnosis modalities for FLD include: biochemical analysis and histological analysis (both
following liver biopsy), and imaging modalities, i.e. magnetic resonance spectroscopy (1H
MRS), magnetic resonance imaging (MRI), computed tomography (CT), and
ultrasonography. Table ІІ shows an overview on these diagnosis modalities.
Historically, 5% liver fat by biochemical analysis (triglycerides in mg 48/ wet liver weight
in g) is considered a threshold for steatosis 49. For 1H MRS, 5.56% based on the 95%
percentile of a low risk group population is considered a cut-off value, which equals 55.6
mg/g 50. Histologically, steatosis is diagnosed when ≥5% of hepatocytes are infiltrated by a
lipid vesicle 13.
Ultrasonography
Ultrasonography has a special place in this thesis. The first publication on ultrasound in its
infancy [source 51] is by Lynn ea. (1942) 52. Several ultrasound scoring measures for diffuse
parenchymal liver disease, including FLD amongst others, have been presented throughout
history. Originally, these measures were based on ‘beam penetration/attenuation’,
‘echogenicity’, ‘vascularity’, and ‘hepatomegaly/live size’ 53. The echogenicity measure
includes hyperechogeneity of liver parenchyma 53 and hyperechogeneity of liver
parenchyma compared to the adjacent structures 53. The vascularity measure includes
decreased vascularity of the liver (blurring or featureless appearance) 53, and increased
vascularity of the liver 53, 54.
Chapter 1.
14
Ultrasonography for assessment fatty liver disease
Ultrasonography is the most often used diagnosis modality for assessment of FLD, and has
been under development for over thirty years. ‘High intensity echoes of a well defined
pattern’ was introduced by Taylor ea. (1976) 55, and later changed to ‘bright liver with
closely packed echoes’ by Joseph ea. (1979) 56, which was then named ‘the bright liver
echo pattern’ 56-58. Thus, the presence of hyperechogeneity with fine, tightly packed echoes
is considered a criterion for steatosis 57, 58. Theoretically, this fine, tightly packed echo
pattern (i.e. increased pixel density) causes the ‘human eye’ to perceive a ‘bright liver’,
even though pixel intensity itself might not be increased 59, 60. Additionally, degree of
steatosis can be assessed by combinations of increased echogenicity as compared to
adjacent structures, loss of echoes of portal vein walls, and posterior beam attenuation 57, 58.
Fat (simple steatosis) is reflected as a fine, tightly packed echo pattern 57, 58. Fat
accompanied by fibrosis is reflected as coarse pin-head echoes within the fine, tightly
packed echo pattern belonging to fat 57, 58. Besides by an irregular outline of the liver
surface 58, 59, cirrhosis is (just like simple steatosis) reflected as bright liver, but portal wall
veins are preserved and posterior beam attenuation is absent 57, 58. Ultrasonography is
usually used as a qualitative method, but in CHAPTER 5 61 we developed and validated a
method to quantify liver fat content by ultrasonography, based on both texture and
attenuation indices, using multi-voxel magnetic resonance spectroscopy as gold standard.
Historical perspectives
15
Table ІІ. Historical overview on diagnosis modalities, selection of the literature
Time period References Purpose GS
Since ≤1846 [source 62]
Histology
Visual/microscopical scoring by microscope: Brunt ea. (1999) 11, updated by Kleiner ea. (2005) 13 Digital calculation: Fiorini ea. (2004) 63, Franzen ea. (2005) 64, Liquori (2009) 65
Method
Method
NA
NA
Since ≤1871 [source 66]
Biochemical analysis
Bligh & Dyer (1959) 48 Method NA
Since ≤1923 [source 67]
Magnetic Resonance
Magnetic Resonance Spectroscopy (since ≤1961 [source 68])
Thomsen (1994) 69 Szczepaniak (1999) 70
Validation Validation
H BA
Sijens ea. (2006) 71; multi-voxel Method -
Magnetic Resonance Imaging (since ≤1968 [source 72])
Dixon (1984) 73 Irwan ea. (2008), i.e. CHAPTER 6 74
Method Validation
- 1H MRS
Since ≤1942 [source 51]
Ultrasonography
Selection of studies is shown in table ΙΙΙ
Since ≤1946 [source 75]
Computed tomography
Phelps ea. (1975) 76 Method -
Mendler ea. (1998); single-energy and dual-energy 77 Validation HMA
Davidson ea. (2006) 78 Method -
Duman ea. (2006) 79 Validation H
BA, biochemical analysis; GS, gold standard; H, histological analysis (qualitative); HMA, histological morphometric analysis (number of hepatocytes infiltrated by lipid vesicles, divided by the total number of hepatocytes); 1H MRS, magnetic resonance spectroscopy; NA, not applicable (gold standard itself).
Table ІІІ. V
alid
atio
n s
tudie
s on u
ltra
sound-d
eter
min
ed f
atty
liv
er d
isea
se, se
lect
ion o
f th
e lite
ratu
re
Pop.
ExCr
GS
Liver state
by the GS (n)
I M
USG m
easures
Alloc.
USG
Validity
qualitative
Validity
quantitative
H
E
L
H
E
L
A
F
T
P
E
D
P
B
A
D
E
W
P
I E
W
P
SM
V
SE
SP
r
Sav
erym
utt
u (
1986)
57
SL
D
H
(ql)
A
bn. (6
7),
Nor.
(18)
Fat
(48),
not Fat
(37)
S
Y&
Y
Y&
Y
Y
Im
pr.
O
rd
87%
94%
89%
84%
Nee
dle
men
(1986)
54
SL
D
H
(ql)
A
bn. (8
8),
Nor.
(22)
FFp (
75),
no F
Fp (
35)
S
Y
Y
Y
Y
Y
Y
Y
Y
Y
Impr.
O
rd
89%
92%
86%
-
Jose
ph (
1991)
58
SL
D
H
(ql)
Fat
(36),
not Fat
(14)
S
Y&
Y
Y&
Y
Y
Im
pr.
O
rd
92%
93%
Gra
if (
2000)
80
SL
D
H
(ql)
G
ener
al (
-)
Ste
atosi
s (-
) S
Y
Y
Y
Y
Impr.
O
rd
82%
100%
$
66%
60%
$
Ham
aguch
i (2
007)
81
SL
D
A, L
D
H; M
Ts (q
l)
FL
D (
64),
Nor.
(30)
I Y
&
Y
Y&
Y
Y
C
um
O
rd
91.7
%
100%
r=
.87, p<
.001
#, obes
e st
udy p
opula
tion;
$, sc
ore
by the
bes
t re
vie
wer
.
USG m
easures:
&, co
uple
d m
easu
res;
HE
L, hyper
echogen
eity
of
liver
par
ench
ym
a; H
EL
A, hyper
echogen
eity
of
liver
par
ench
ym
a co
mpar
ed to the
adja
cent st
ruct
ure
s;
FT
PE
, tightly p
acked
ech
oes
; D
PB
A, ra
te o
f dee
p p
ost
erio
r bea
m a
tten
uat
ion; D
EW
P, dec
reas
ed e
chogen
eity
of
the
wal
ls o
f port
al v
eins;
IE
WP, in
crea
sed e
chogen
eity
of
wal
ls o
f port
al v
eins.
Abbreviations:
A,
alco
holics
; A
bn., a
bnorm
al l
iver
; A
UC
, ar
ea u
nder
the
curv
e; C
um
, cu
mula
tive;
FFp,
fatty-f
ibro
tic
pat
tern
; G
S,
gold
sta
ndar
d;
H,
his
tolo
gy;
1H
MR
S,
mag
net
ic r
esonan
ce s
pec
trosc
opy;
I, i
mag
e(s)
; IM
, im
agin
g m
ethod;
Impr.
, over
all
impre
ssio
n o
f th
e liver
; L
D,
liver
dis
ease
oth
er t
han
FL
D;
MT
, M
atte
oni
types
; N
or.
, norm
al liv
er; O
rd, ord
inal
var
iable
; Pop.: s
tudy p
opula
tion; ql, q
ual
itat
ive;
qt, q
uan
tita
tive;
r, co
rrel
atio
n c
oef
fici
ent; S
, sc
ans;
SE
, se
nsi
tivity; SL
D, su
spec
ted liv
er d
isea
se;
SM
, sc
ori
ng m
ethod; SP, sp
ecif
icity; U
SG
, ultra
sonogra
phy; V
, var
iable
type;
Y, yes
.
16
Chapter 1.
Historical perspectives
17
FAT IN THE LIVER COMPARED TO OTHER TISSUES
In CHAPTER 6 74 we modified and validated a MRI method, using multi-voxel 1H MRS.
This MRI method enabled us to simultaneously compare hepatic fat content with fat
contents of other tissues in CHAPTER 7 82.
SHOULD WE SCREEN FOR FATTY LIVER DISEASE?
In the general discussion of this thesis, i.e. CHAPTER 8.1, we discuss if there is enough
evidence on screening for FLD.
Finally, in CHAPTER 8.2 some additional remarks and recommendations for future research
are given.
Chapter 1.
18
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Chapter 2
Fatty liver disease and cardiovascular risk in the
general population of East Anglia: The Fenland Study
In preparation/ Awaiting enlargement of database
Mireille A. Edens 1
Nita G. Forouhi 2
Emanuella de Lucia-Rolfe 2
Nickolas J. Wareham 2
Ronald P. Stolk 1
Other investigators of the Fenland Study 2
Department of Epidemiology 1
University Medical Center Groningen University of Groningen
Groningen, the Netherlands
MRC Epidemiology Unit 2
Institute of Metabolic Science Addenbrooke’s Hospital
Cambridge, United Kingdom
Chapter 2.
26
ABSTRACT
Objectives Limited population data on fatty liver disease (FLD) in Caucasians have been
published. The main aim of the present study was to determine FLD prevalence and its
association with cardiovascular disease risk in the general population of East Anglia using
the Fenland Study.
Design Population based study, with cross-sectional results.
Setting 3 research centers in Cambridgeshire.
Participants People registered at surgeries in Cambridgeshire aged 30 to 58, excluding
participants with known diabetes mellitus, terminal illness or inability to walk unaided, and
Alcohol status (n) - non-alcoholic; ≤17 units per week - alcoholic; >17 units per week
319 40
93 23
44 13
p<.05
459 76
Alcohol units a week 5 (0–52) 6 (0–60) 4 (0–67) p=ns 5 (0–67)
Smoking status (n) - never/ex/current/not known
239/105/40/12
70/38/12/4
27/23/6/3
p=ns
336/166/58/19
Units in cigarette equivalents a day 10 (0 – 40) 10.9 (8.0) 14.8 (8.2) p<.05 11.3 (8.1)
On any medication (y/n, y%) 141/252 (35.9) 52/68 (43.3) 31/28 (52.5) p<.001 224/348 (39.2)
On lipid medication (n) * On blood pressure medication (n) *
5 14
5 13
2 9
12 36
Data represent mean (sd) when normal distribution, median (min-max) when skewed distribution, or percentage when dichotomous. *, as specified in appendix Ι; ALT, alanine aminotransferase; GGT, gamma glutamyl aminotransferase; m, men; ns, not significant; w, women.
Chapter 2.
The Fenland Study
35
AGREEMENT OF LIVER FAT AND AMINOTRANSFERASES
ALT correlated significantly with liver fat score in both men (r=.37 with p<0.001) and
women (r=.36 with p<0.001). Explained variances were 13.4% in men and 12.9% in
women. Also, GGT correlated significantly with liver fat score in both men (r=.18 with
p<0.01) and women (r=.37 with p<0.001). Explained variances were 3.2% in men and
13.4% in women. Figure ІІІ shows ROC curves of ALT and GGT on diagnosis of fatty
liver.
Sensitivity(‘truepositives’)
1 – Specificity (‘false positives’)
20
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
40
30
30
19
25
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
32
36
Sensitivity(‘truepositives’)
1 – Specificity (‘false positives’)
a. ALT
In men, the ROC curve of ALT has an AUC of .693.
Optimum cut-off value is 25 (i.e. ≤25, >25), with SE
87%, SP 41%, PPV 54.3%, and NPV 79.7%.
In women, the ROC curve of ALT has an AUC of .681.
Optimum cut-off value is 20 (i.e. ≤20, >20), with SE
73.3%, SP 61%, PPV 35.3%, and NPV 88.8%.
b. GGT
In men, the ROC curve of GGT has an AUC of .721.
Optimum cut-off value is 36 (i.e. ≤36, >36), with SE
56.5%, SP 76.1%, PPV 65.6%, and NPV 68.5%.
In women, the ROC curve of GGT has an AUC of .713.
Optimum cut-off value is 32 (i.e. ≤32, >32), with SE
40%, SP 92.3%, PPV 60%, and NPV 84.2%.
Figure ІІІ. ROC curves of ALT and GGT on diagnosis of fatty liver
, men; , women. AUC, area under the curve; NPV, negative predictive value; PPV, positive predictive value; ROC, receiver operating characteristic; SE, sensitivity; SP, specificity.
36
ASSOCIATES OF FATTY LIVER
BMI class, alcohol class and medication
Figure ІV shows associations of BMI class, alcohol class and medication use with liver fat
score and ALT and GGT. In both men and women, an increase in BMI class is associated
with an increase in liver fat category, ALT, and GGT (p<0.001 for all). In men, an increase
in alcohol class is not associated with liver fat score and ALT (p=ns for both), whereas it is
associated with an increase in GGT (p<0.001). In women, an increase in alcohol class is
associated with an increase in liver fat score (p<0.05), whereas it is not associated with
ALT and GGT (p=ns for both). In men, medication use of any kind is associated with an
increase in liver fat score (p<0.001), an increase in ALT (p<0.01), and an increase in GGT
(p<0.001). In women, medication use of any kind is not associated with liver fat score,
ALT, and GGT (p=ns for all).
PREDICTORS OF FATTY LIVER
Table ІІ shows the results of univariate and multiple logistic regression analysis on the
presence of FLD. By multiple logistic regression analysis, only BMI (p<0.05, OR 1.3) was
significantly associated in men, and BMI (p<0.001, OR 1.6), waist circumference (p<0.01,
OR 1.1), and hip circumference (p<0.01, OR .9) were significantly associated in women.
Chapter 2.
The Fenland Study
37
p<0.001 for both men and women, by Kruskal-Wallis test
p<0.001 for both men and women, by Kruskal-Wallis test
p<0.001 for both men and women, by Kruskal-Wallis test
a. BMI class
p=ns for men and p<0.05 for women, by Kruskal-Wallis test
p=ns for both men and women, by Kruskal-Wallis test
p<0.001 for men and p=ns for women, by Kruskal-Wallis test
b. Alcohol class
p<0.001 for men and p=ns for women, by Mann-Whitney U test
p<0.01 for men and p=ns for women, by Mann-Whitney U test
p<0.001 for men and p=ns* for women, by Mann-Whitney U test
c. Medication use
Figure ІV. Associations of BMI class, alcohol class, and medication use
with liver fat score, ALT and GGT, in the population with liver fat scores
Table ІІ. Logistic regression analysis on the presence of fatty liver
Independant variable(s) #
UNIVARIATE MULTIPLE
B p value ExpB (95% CI) B p value ExpB (95% CI)
Men
Age Household income Alcohol units a week Smoking units a day& Body mass index Waist circumference Hip circumference Triglycerides Total cholesterol HDL cholesterol Glucose SBP DBP ALT GGT Alkaline phosphatase Bilirubin Albumin Calcium Constant
Age Household income Alcohol units a week Smoking units a day& Body mass index Waist circumference Hip circumference Triglycerides Total cholesterol HDL cholesterol Glucose SBP DBP ALT GGT Alkaline phosphatase Bilirubin Albumin Calcium Constant
#Dependent variable: normal or fatty liver; *, borderline significant (p<0.1); &, cigarette equivalents a day. B, logistic regression coefficient; CI, confidence interval; ExpB, odds ratio; ns, not significant.
Chapter 2.
The Fenland Study
39
ASSOCIATIONS OF LIVER FAT CATEGORY, ALT QUINTILE AND GGT QUINTILE
WITH SEVERAL CARDIOVASCULAR RISK ESTIMATES
Figures V shows associations of liver fat category, ALT quintile, and GGT quintile with
several CVD risk estimates, in the population with liver fat scores. In both men and women,
an increase in liver fat category is associated with an increase in the number of MetS ATP
III components, the number of MetS IDF components, the MetS Z-score (p<0.001 for all),
and 10-year Framingham CVD risk (p=0.001 for men, p<0.001 for women). In men, an
increase in ALT quintile is associated with an increase in the number of MetS ATP III
components, the number of MetS IDF components, and the MetS Z-score (p<0.001 for all
three), but not with 10-year Framingham CVD risk (p=ns). In women, an increase in ALT
quintile is associated with an increase in the number of MetS ATP III components
(p<0.001), the number of MetS IDF components (p<0.01), the MetS Z-score (p<0.001), and
10-year Framingham CVD risk (p<0.01). In both men and women, an increase in GGT
quintile is associated with an increase in the number of MetS ATP III components, the
number of MetS IDF components, the MetS Z-score (p<0.001 for all three/six), and 10-year
Framingham CVD risk (p<0.01 for men, p<0.001 for women). Results for the Z-score by
Franks et al. (data not shown) were similar to the regular Z-score.
ROC curves of liver fat, ALT, and GGT on diagnosis of the metabolic syndrome
Figure VІ shows ROC curves of liver fat, ALT, and GGT for diagnosis of the MetS ATP
III. The figure shows that liver fat by ultrasound has more diagnostic value than ALT and
GGT. Results for the MetS IDF were similar (data not shown).
PREVALENCE OF METABOLIC SYNDROME COMPONENTS PER LIVER FAT
CATEGORY
Figures VІІ shows prevalence of the number of MetS ATP III components per liver fat
category. With increasing liver fat category the number of MetS ATP III components
increased as well. Of all participants with normal liver, most participants had no
component. Of all participants with mild fatty liver, most had 1 (women) or 2 (men)
components. Of all participants with moderate fatty liver, most participants had 3
components (both men and women). Results were similar for the MetS IDF (data not
shown).
a. Liver fat category
p<
0.0
01 f
or
both
men
and w
om
en,
by c
hi-
squar
e te
st
p<
0.0
01 f
or
both
men
and w
om
en,
by c
hi-
squar
e te
st
p<
0.0
01 f
or
both
men
and w
om
en,
by A
NO
VA
p=
0.0
01 f
or
men
and p
<0.0
01 f
or
wom
en,
by K
rusk
al W
alli
s te
st
b. ALT quintile
p<
0.0
01 f
or
both
men
and w
om
en,
by c
hi-
squar
e te
st
p<
0.0
01 f
or
men
and p
<0.0
1 f
or
wom
en,
by c
hi-
squar
e te
st
p<
0.0
01 f
or
both
men
and w
om
en,
by A
NO
VA
p=
ns
for
men
and p
<0.0
1 f
or
wom
en,
by K
rusk
al W
alli
s te
st
c. GGT quintile
p<
0.0
01 f
or
both
men
and w
om
en,
by c
hi-
squar
e te
st
p<
0.0
01 f
or
both
men
and w
om
en,
by c
hi-
squar
e te
st
p<
0.0
01 f
or
both
men
and w
om
en,
by A
NO
VA
p<
0.0
1 f
or
men
and p
<0.0
01 f
or
wom
en,
by K
rusk
al W
alli
s te
st
Figure V. C
om
par
ison o
f liver
fat
cat
egory
, A
LT
quin
tile
, an
d G
GT
quin
tile
on the
asso
ciat
ion w
ith s
ever
al c
ardio
vas
cula
r ri
sk e
stim
ates
, in
the
popula
tion w
ith liv
er f
at s
core
s
, m
en;
, w
om
en.
AL
T q
uin
tile
s*:
1,
≤23 f
or
men
and ≤
15 f
or
wom
en;
2,
24–29 f
or
men
and 1
6–18 f
or
wom
en;
3,
30–36 f
or
men
and 1
9–22 f
or
wom
en; 4, 37–47 f
or
men
and 2
3–28 f
or
wom
en; 5, ≥48 f
or
men
and ≥
29 f
or
wom
en. G
GT
quin
tile
s*: 1, ≤22 f
or
men
and ≤
15 f
or
wom
en; 2, 23–28 f
or
men
and 1
6–18 f
or
wom
en;
3, 29–37 f
or
men
and 1
9–22 f
or
wom
en;
4, 38–54 f
or
men
and 2
3–31 f
or
wom
en;
5, ≥55 f
or
men
and ≥
32 f
or
wom
en. *, in
ord
er to d
eriv
e both
AL
T a
nd G
GT
quin
tile
s an
d the
cum
ula
tive
Z-s
core
dat
a fr
om
the
tota
l popula
tion w
ere
use
d; ns,
not si
gnif
ican
t.
Chapter 2.
40
Sensitivity(‘truepositives’)
1 –Specificity(‘falsepositives’)
Liverfat score
Liverfat category
4
4
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Sensitivity(‘truepositives’)
1 –Specificity(‘falsepositives’)
ALT
ALT quintile
30
40
19
30
24
27
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Sensitivity(‘truepositives’)
1 –Specificity(‘falsepositives’)
GGT
GGT quintile
22
49
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
a. L
iver
fat
sco
re
In m
en,
the
RO
C c
urv
e of
liver
fat
sco
re h
as a
n A
UC
of
.822 (
.813 f
or
liver
fat
cat
egory
). O
ptim
um
cut-
off
val
ue
is 4
(i.e.
≤4,
>4),
with S
E 9
1.2
%,
SP 6
3%
, PPV
28.7
%, an
d N
PV
97.8
%.
In w
om
en,
the
RO
C c
urv
e of
liver
fat
sco
re h
as a
n
AU
C o
f .8
71 (
.826 f
or
liver
fat
cat
egory
). O
ptim
um
cut-
off
val
ue
is 4
(i
.e.
≤4,
>4),
with SE
77.4
%,
SP
83.4
%, PPV
32.4
%, an
d N
PV
97.3
%.
b. A
LT
In m
en,
the
RO
C c
urv
e of
AL
T h
as a
n A
UC
of
.682
(.671 f
or
AL
T q
uin
tile
). O
ptim
um
cut-
off
val
ue
is 2
7
(i.e
. ≤27,
>27),
w
ith
SE
85.3
%,
SP
41.8
%,
PPV
19.3
%, an
d N
PV
94.6
%.
In w
om
en, th
e R
OC
curv
e of
AL
T h
as a
n A
UC
of
.788
(.761 f
or
AL
T q
uin
tile
). O
ptim
um
cut-
off
val
ue
is 2
4
(i.e
. ≤24,
>24),
w
ith
SE
77.4
%,
SP
74.1
%,
PPV
23.5
%, an
d N
PV
97%
.
c. G
GT
In m
en,
the
RO
C c
urv
e of
GG
T h
as a
n A
UC
of
.693
(.683 f
or
GG
T q
uin
tile
). O
ptim
um
cut-
off
val
ue
is 4
9
(i.e
. ≤49,
>49),
with S
E 5
0%
, SP 8
0.3
%,
PPV
29.3
%,
and N
PV
90.8
%.
In w
om
en,
the
RO
C c
urv
e of
GG
T h
as a
n A
UC
of
.800 (
.794 f
or
GG
T q
uin
tile
). O
ptim
um
cut-
off
val
ue
is
22 (
i.e.
≤22,
>22),
with S
E 8
0.6
%,
SP 6
8.8
%,
PPV
21%
, an
d N
PV
97.2
%.
Figure VІ. R
OC
curv
es o
f liver
fat
, A
LT
and G
GT
on d
iagnosi
s of
AT
P I
II M
etS
, m
en;
, w
om
en.
AU
C, ar
ea u
nder
the
curv
e; N
PV
, neg
ativ
e pre
dic
tive
val
ue;
PPV
, posi
tive
pre
dic
tive
val
ue;
RO
C, re
ceiv
er o
per
atin
g c
har
acte
rist
ic;
SE
,
sensi
tivit
y; SP, sp
ecif
icit
y.
The Fenland Study
41
NORMAL LIV
ER
MIL
D FATTY LIV
ER
MODERATE FATTY LIV
ER
P<
0.0
01 f
or
both
men
and w
om
en, by c
hi-
squar
e te
st
Figure VІІ. P
reval
ence
of
the
num
ber
of
Met
S A
TP I
II c
om
ponen
ts p
er liv
er f
at c
ateg
ory
, m
en;
, w
om
en.
Chapter 2.
42
Table ІІІ. C
om
par
ison o
f W
este
rn g
ener
al p
opula
tion-b
ased
stu
die
s on f
atty
liv
er d
isea
se
Stu
dy
Dat
a
coll
ecti
on
Dia
gnosi
s
modal
ity
USG
E
xcl
usi
on
criter
ia
Incl
usi
on c
rite
ria
n
m
(%)
A
ge
E inta
ke
(g/d
ay)
BM
I T
ota
l
FL
D
A
FL
D
NA
FL
D
Sco
ring
criter
ia
Type
DN
LS 1
st-p
has
e 18
(Ita
ly)
1991 –
1993
1997
USG
1A
1, 1A
2,
2, 3
D
Hep
. B
, C
Cir
rhosi
s
BM
I<25; N
As
67
50.7
46.8
±11.7
5.8
22.3
±1.8
16.4
%
As
69
89.9
49.7
±10.7
71.1
23.3
±1.3
46.4
%
BM
I>30; N
As
66
40.9
47.8
±10.2
6.5
32.3
±2.8
75.8
%
As,
BM
I 55
87.3
51.5
±9.2
77.5
32.5
±2.5
94.5
%
SH
IP 2
0
(Ger
man
y)
1997 –
2001
USG
1A
1, 1A
2
D
Hep
. B
, C
Cir
rhosi
s
4222
49
20–79
29.9
%
39.7
%
27.2
%
DH
S 2
1,
22
(USA
)
2000 –
2002
1H
MR
S
na
na
All
2287
47.2
30–65
≈31%
#
37.6
% ##
Hip
anic
s 401
42.9
41 ±
9
30 ±
7
45%
#
Whit
es
734
51.1
46 ±
9
29 ±
6
33%
#
Bla
cks
1105
45.2
46 ±
10
31 ±
8
24%
#
EM
IL 2
3
(Ger
man
y)
2002
USG
1A
2, 2
D
2187
48%
18–65
27.4
%
DN
LS 2
nd-p
has
e 19
(Ita
ly)
2002 –
2003
USG
1A
1, 1A
2,
2, 3
D
Hep
. B
, C
Cir
rhosi
s
No S
LD
287
54.4
60
11
26.7
±4.7
20%
SL
D
311
62.4
58
9
27.8
±6
25%
Fen
land s
tudy
(UK
) 2005 –
2008
USG
1A
1, 1A
2,
2, 3
C, C
D
M
762
41.8
45.7
±7
0 (
0–72)
25.4
(17.3
–49.4
) 38.5
%
47.4
%
30.5
%
FIN
-D2D
stu
dy 2
4
(Fin
land)
2007
1H
MR
S
na
na
2766
7%
21%
Signs: #
, usi
ng a
cut-
off
val
ue
of
>5.5
% h
epat
ic T
G; ##, usi
ng a
cut-
off
val
ue
of
>5%
hep
atic
TG
.
Scoring criteria:
1A
1,
hyper
echogen
eity
of
liver
par
ench
ym
a; 1
A2,
hyper
echogen
eity
of
liver
par
ench
ym
a co
mpar
ed t
o t
he
adja
cent
stru
cture
s; 2
, dee
p a
tten
uat
ion;
3,
dec
reas
ed v
isib
ility o
f port
al v
eins.
Abbreviations:
A,
alco
holic;
BM
I, b
ody m
ass
index
(kg/m
2);
C,C
, sc
ori
ng i
n a
cum
ula
tive
fash
ion a
nd a
lloca
tion i
nto
cat
egori
es;
D,
dic
hoto
mous;
DH
S,
Dal
las
Hea
rt
Stu
dy; D
NL
S, D
ionyso
s N
utr
itio
n a
nd L
iver
Stu
dy; D
M, know
n d
iabet
es m
ellitu
s; E
, et
han
ol in
take;
EM
IL, Stu
dy o
n E
chin
oco
ccus
Multilocu
lari
s an
d I
nte
rnal
Dis
ease
s in
Leu
tkir
ch; FIN
-D2D
, th
e Fin
nis
h p
reven
tion p
rogra
m f
or
type
2 d
iabet
es; H
ep. B
, C
, hep
atitis
B a
nd C
; 1H
MR
S, pro
ton m
agnet
ic r
esonan
ce s
pec
trosc
opy; m
, per
centa
ge
of
men
; N
A, non-a
lcoholic;
SH
IP, Stu
dy o
f H
ealth in P
om
eran
ia; SL
D, su
spec
ted liv
er d
isea
se; T
G, tr
igly
ceri
de;
USG
, ultra
sonogra
phy.
The Fenland Study
43
Chapter 2.
44
DISCUSSION
The prevalence of FLD due to any etiology we found in the population aged 30 to 58 years
is 38.5%. Men contributed to this high prevalence the most (p<0.001). Importantly, this
high prevalence was found in a relatively healthy general population based study
population (e.g. people with known diabetes excluded). Additionally, BMI in the total
population (median 26.3 with range 16.9–63.5 kg/m2) was higher than BMI in the
population with liver fat scores (median 25.4 with range 17.3– 49.4 kg/m2). Therefore, the
true prevalence of FLD in East Anglia may likely be even higher than the already striking
prevalence reported in this paper.
An increase in liver fat category was associated with an increase in the number of ATP III
MetS components, the number of IDF MetS components, the MetS Z-score, and 10-year
Framingham CVD risk (figure V).
AGREEMENT OF AMINOTRANSFERASES AND LIVER FAT
Aminotransferases ALT and GGT correlated with liver fat, which was also found in other
imaging studies. ALT correlates with liver fat by magnetic resonance spectroscopy in non-
diabetic, non-alcoholic, apparently healthy men (r=0.44–0.62, p<0.0001) and women
(r=0.39–0.49, p<0.0001) 33, 34. The present study is also in line with recently proposed
lowering of ALT cut-off values 27, in order to achieve increased overall diagnostic value for
FLD. A study in blood donors suggested lowering ALT cut-off values from 40 to 30 for
men and from 30 to 19 for women 27. The present study suggests optimal ALT cut-off
values of 25 for men and 20 for women (figure ІІІ). Further lowering cut-off values for
aminotransferases, e.g. for screening studies, will increase sensitivity but cause a decreased
specificity as a consequence.
Additionally, this study suggests that both ALT and GGT are inferior to liver fat by
ultrasound regarding diagnosing the MetS ATP III (and IDF) as shown in figure VІ.
The Fenland Study
45
THE PRESENT STUDY COMPARED TO OTHER STUDIES
FLD prevalence compared to other prevalences
This is the first general population based study on imaging-determined FLD in the UK. Of
all Western general population based studies on FLD using imaging modalities,
chronologically organized in table ІІІ, the present study revealed the highest FLD
prevalence. Reported overall prevalence’s were 29.9% by the SHIP study 20, 31% by the
DHS study (33% in Whites) when using a cut-off value based upon the 95th percentile of a
low risk population 21, 22, 27.4% by the EMIL study 23, and 38.5% in the present Fenland
Study. In the FIN-D2D study using magnetic resonance spectroscopy, a substantial
difference in prevalence of AFLD (7%) and prevalence of NAFLD (21%) was found,
whereas BMI and components of the MetS were similar in both groups. Alcohol is a major
risk factor for advanced FLD, and compared to NAFLD, AFLD is more associated with
advanced FLD 35, 36. It is known that, while the FLD spectrum progresses to its advanced
stages, liver fat content decreases 5, 37. Thus theoretically, the AFLD group could include
more advanced FLD cases which are characterised by low liver fat content, likely causing
magnetic resonance spectroscopy to miss advanced AFLD cases. As cirrhosis (an advanced
stage of FLD) appears as bright liver by ultrasound, advanced FLD cases are most likely
included in the present Fenland Study.
Ultrasonography method compared to other ultrasonography methods
In previous old studies, FLD was scored on a semi-quantitative scale as normal, mild,
moderate, or severe 38, 39. When compared with histology, sensitivity and specificity of this
method range from 89%–94% and 84%–93%, respectively 38, 39. In the present study, liver
fat content was scored in a cumulative fashion, followed by allocation to liver fat
categories, similar to the scoring system by Hamaguchi et al. (2007) 40. A differences
between the two scoring systems is that, as based on older studies 38, 39, Hamaguchi et al.
considered hyperechogeneity as a mandatory component for diagnosis of FLD 40.
Additionally, the authors scored attenuation on a 3-point scale (compared to the present 4-
point scale) and vessel blurring on a 2-point scale (compared to the present 4-point scale)
40. The authors validated their method using histology in a population excluding other liver
disease and alcoholics (total n=94, including NAFLD n=64) 40. Their method revealed an
AUC of 0.980, a sensitivity of 91.2%–92.6%, a specificity of 100%, an intra-observer
reliability by Cohen’s kappa of 0.95 (p<0.001) and an inter-observer reliability by Cohen’s
Chapter 2.
46
kappa of 0.95 (p<0.001) 40. It should be noted that the current used ultrasonography scoring
method has not been validated yet.
Study design compared to other study designs
Besides period of data collection and imaging methods, there are other differences between
these studies regarding study populations. Some important characteristics are included in
table ІІІ. Although derived from the general population, the DNLS 1st-phase 18, DHS 21, 22
and DNLS 2nd-phase 19 were strongly designed on BMI and alcohol intake 18, ethnicity 21, 22,
and presence and absence of suspected liver disease 19. The DNLS study 18, 19 and SHIP
study 20 excluded hepatitis and other known liver disease, whereas these were not
determined in the DHS 21, 22 and the present Fenland Study. Another important difference
between the present and other studies in that known diabetes mellitus is an exclusion factor
in the present Fenland Study.
Weaknesses of the present study
The population with and without liver fat scores differed with respect to sex (females
58.2% versus 53.4% respectively [p<0.05]) and BMI (median 25.4 versus 26.6 kg/m2
respectively [p<0.001]). Analysis on the total population revealed that overall men are more
obese than women. The median BMI of men (27 kg/m2) and women (25.6 kg/m2) in the
total population differed significantly (p<0.001). The mean waist circumference of men
(98.2 cm) and women (86.7 cm) differed significantly (p<0.001) as well. Despite of the
major back log of liver fat scores compared to other data, this difference in sex and BMI
might be attributable to difficulties in scanning obese people, i.e. mostly men, using an
image modality 25, 26, e.g. ultrasonography 41, 42 and magnetic resonance spectroscopy as
well 22. In the DHS, using magnetic resonance spectroscopy, only participants fitting the
scanner could be included 22. Besides, being sometimes not possible, the diagnostic value of
ultrasonography is decreased in obese people as well 41, 42.
ASSOCIATES OF FATTY LIVER
BMI class, alcohol class and medication
BMI (notably peripheral fat depots) 43, alcohol 44, and certain drugs 44 are associated with
the etiology of FLD. Both figure ІV and results of the logistic regression analyses (table ІІ)
indicate that BMI is more strongly associated with liver fat by ultrasound than alcohol use.
This was also found in the DNLS 18. However, it might be important to distinguish AFLD
The Fenland Study
47
and NAFLD as both may follow different clinical courses 35, 36. Studies by histology
suggest that AFLD is overall more associated with progression of liver damage, i.e.
progression of fibrosis stage 35, 36, which may delineate a regression of liver fat content 5, 37.
NAFLD is overall more associated with CVD 45, but it should be noted that even people
with NAFLD are at increased risk for severe liver pathology 5-7. Strangely, follow-up of
participants from the DNLS suggests that alcohol use is the most important predictor of
both incidence and regression of fatty liver by ultrasound 46. However, theoretically this
regression might be attributable to an increase in fibrosis stage (notably not determined by
histology) accompanied by a decrease in liver fat content 5, 37. The association between
medication use and liver fat score, particularly in men (figure ІVc), suggests that the
participants with higher liver fat score are unhealthier. Whereas in the SHIP study,
increased medication use was largely attributable to diabetes and lipid lowering medication
47 this is not possible in the present non-diabetic study population. Smoking was not
associated with liver fat by ultrasound (table ІІ), as also previously found 23, 48.
CARDIOVASCULAR DISEASE RISK ESTIMATES
This study is in line with the idea of FLD being the hepatic component of the MetS 3. The
optimal cut-off value for diagnosis of the MetS ATP III was a liver fat score of 4 (≤4, >4),
which corresponds with the threshold between normal liver and (mild) fatty liver.
Additionally, liver fat was associated with the 10-year Framingham CVD risk (figure V).
Although there is speculation about the value of the MetS for CVD risk prediction, a meta-
analysis of longitudinal studies (37 studies including 43 cohorts) revealed that participants
with the MetS are at increased risk for incident CVD events 49.
CONCLUSION
This study shows a striking prevalence of FLD in East Anglia, particularly in men. As FLD
is associated with several CVD risk estimates, this striking prevalence may delineate an
increased CVD risk in this population.
Chapter 2.
48
ACKLOWLEDGEMENTS
The Fenland Study is funded by the Wellcome Trust and the Medical Research Council.
We are grateful to all the volunteers for their time and help, and to the General Practitioners
and practice staff for help with recruitment. We thank the Fenland Study Investigators,
Fenland Study Co-ordination team and the Epidemiology Field, Data and Technical teams.
Biochemical assays were performed by the National Institute for Health Research,
Cambridge Biomedical Research Centre, Core Biochemistry Assay Laboratory, and the
Cambridge University Hospitals NHS Foundation Trust, Department of Clinical
Biochemistry.
The Fenland Study
49
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Chapter 2.
52
(33) Westerbacka J, Corner A, Tiikkainen M, Tamminen M, Vehkavaara S, Hakkinen AM, Fredriksson J, Yki-Jarvinen H. Women and men have similar amounts of liver and intra-abdominal fat, despite more subcutaneous fat in women: implications for sex differences in markers of cardiovascular risk. Diabetologia 2004 August;47(8):1360-9.
(34) Kotronen A, Westerbacka J, Bergholm R, Pietilainen KH, Yki-Jarvinen H. Liver fat in the metabolic syndrome. J Clin Endocrinol Metab 2007 September;92(9):3490-7.
(35) Mills SJ, Harrison SA. Comparison of the natural history of alcoholic and nonalcoholic fatty liver disease. Curr Gastroenterol Rep 2005 February;7(1):32-6.
(36) Dam-Larsen S, Franzmann MB, Christoffersen P, Larsen K, Becker U, Bendtsen F. Histological characteristics and prognosis in patients with fatty liver. Scand J
Gastroenterol 2005 April;40(4):460-7.
(37) Powell EE, Cooksley WG, Hanson R, Searle J, Halliday JW, Powell LW. The natural history of nonalcoholic steatohepatitis: a follow-up study of forty-two patients for up to 21 years. Hepatology 1990 January;11(1):74-80.
(38) Saverymuttu SH, Joseph AE, Maxwell JD. Ultrasound scanning in the detection of hepatic fibrosis and steatosis. Br Med J (Clin Res Ed) 1986 January 4;292(6512):13-5.
(39) Joseph AE, Saverymuttu SH, al Sam S, Cook MG, Maxwell JD. Comparison of liver histology with ultrasonography in assessing diffuse parenchymal liver disease. Clin Radiol 1991 January;43(1):26-31.
(40) Hamaguchi M, Kojima T, Itoh Y, Harano Y, Fujii K, Nakajima T, Kato T, Takeda N, Okuda J, Ida K, Kawahito Y, Yoshikawa T, Okanoue T. The severity of ultrasonographic findings in nonalcoholic fatty liver disease reflects the metabolic syndrome and visceral fat accumulation. Am J Gastroenterol 2007 December;102(12):2708-15.
(41) Mottin CC, Moretto M, Padoin AV, Swarowsky AM, Toneto MG, Glock L, Repetto G. The role of ultrasound in the diagnosis of hepatic steatosis in morbidly obese patients. Obes Surg 2004 May;14(5):635-7.
(42) Moura Almeida A, Cotrim HP, Barbosa DB, de Athayde LG, Santos AS, Bitencourt AG, De Freitas LA, Rios A, Alves E. Fatty liver disease in severe obese patients: diagnostic value of abdominal ultrasound. World J Gastroenterol 2008 March 7;14(9):1415-8.
(43) Donnelly KL, Smith CI, Schwarzenberg SJ, Jessurun J, Boldt MD, Parks EJ. Sources of fatty acids stored in liver and secreted via lipoproteins in patients with nonalcoholic fatty liver disease. J Clin Invest 2005 May;115(5):1343-51.
The Fenland Study
53
(44) Fromenty B, Pessayre D. Inhibition of mitochondrial beta-oxidation as a mechanism of hepatotoxicity. Pharmacol Ther 1995;67(1):101-54.
(45) Ekstedt M, Franzen LE, Mathiesen UL, Thorelius L, Holmqvist M, Bodemar G, Kechagias S. Long-term follow-up of patients with NAFLD and elevated liver enzymes. Hepatology 2006 October;44(4):865-73.
(46) Bedogni G, Miglioli L, Masutti F, Castiglione A, Croce LS, Tiribelli C, Bellentani S. Incidence and natural course of fatty liver in the general population: the Dionysos study. Hepatology 2007 November;46(5):1387-91.
(47) Baumeister SE, Volzke H, Marschall P, John U, Schmidt CO, Flessa S, Alte D. Impact of fatty liver disease on health care utilization and costs in a general population: a 5-year observation. Gastroenterology 2008 January;134(1):85-94.
(48) Chavez-Tapia NC, Lizardi-Cervera J, Perez-Bautista O, Ramos-Ostos MH, Uribe M. Smoking is not associated with nonalcoholic fatty liver disease. World J
Gastroenterol 2006 August 28;12(32):5196-200.
(49) Gami AS, Witt BJ, Howard DE, Erwin PJ, Gami LA, Somers VK, Montori VM. Metabolic syndrome and risk of incident cardiovascular events and death: a systematic review and meta-analysis of longitudinal studies. J Am Coll Cardiol 2007 January 30;49(4):403-14.
(50) Ford ES. Prevalence of the metabolic syndrome defined by the International Diabetes Federation among adults in the U.S. Diabetes Care 2005 November;28(11):2745-9.
Appen
dix Ι. E
stim
ates
of
met
abolic
card
iovas
cula
r ri
sk, w
ith s
pec
ific
atio
ns
Metabolic
risk
variable
Components/variables
Specification
NC
EP A
TPΙΙ
Ι# 2
9
1. E
levat
ed w
aist
>
102 c
m (
m),
>88 c
m (
f)
2. E
levat
ed T
Gs
TG
s ≥1.7
mm
ol/L
A
nd/o
r tr
eatm
ent w
ith s
tatins
and/o
r fi
bra
tes*
3. D
ecre
ased
HD
L
HD
L <
1.0
3 m
mol/L
(m
) or
<1.2
9 m
mol/L
(f)
4. E
levat
ed b
lood p
ress
ure
E
ither
SB
P≥130 m
mH
g, an
d/o
r D
BP≥85 m
mH
g, an
d/o
r an
ti-h
yper
tensi
ves**
5. E
levat
ed f
asting p
lasm
a glu
cose
≥6.1
6 m
mol/L
IDF## 3
0
1. E
levat
ed w
aist
(m
andatory component)
• For
‘Whites
’, ‘
Bla
cks’
, an
d ‘
mix
ed’,
e.g
. ‘B
lack
Bri
tish
’:
≥94 c
m (
m)
and ≥
80 c
m (
f) 3
0, 50.
• For
‘Asi
ans’
, ‘S
outh
Asi
ans’
, an
d ‘
mix
ed’,
e.g
. ‘A
sian
Bri
tish
’:
≥90 c
m (
m)
and ≥
80 c
m (
f) 3
0, 50.
2. E
levat
ed T
Gs
TG
>1.7
mm
ol/L
A
nd/o
r or
trea
tmen
t w
ith s
tatins
and/o
r fi
bra
tes*
3. D
ecre
ased
HD
L
HD
L <
1.0
3 m
mol/L
(m
) or
<1.2
9 m
mol/L
(f)
4. E
levat
ed b
lood p
ress
ure
E
ither
SB
P≥130 m
mH
g, an
d/o
r D
BP≥85 m
mH
g, an
d/o
r an
ti-h
yper
tensi
ves**
5. E
levat
ed f
asting p
lasm
a glu
cose
≥
5.6
mm
ol/L
Z-s
core
1. B
MI;
2. W
aist
; 3. T
Gs;
4. In
ver
ted H
DL
;
5. SB
P; 6. D
BP; 7. G
luco
se
All v
aria
ble
s w
ere
tran
sform
ed u
sing:
σµ
−Χ
=Ζ
(for
mal
es a
nd f
emal
es s
epar
atel
y),
wher
e X
is
the
ori
gin
al
val
ue,
an
d µ
an
d σ
are
mea
n
and
stan
dar
d
dev
iation
of
the
study
popula
tion,
resp
ectivel
y.
All indiv
idual
Z-s
core
wer
e ad
ded
to f
orm
a c
um
ula
tive
Z-s
core
.
Z-s
core
, bas
ed o
n
Fra
nks
et a
l. 3
1
1. Z
-obes
ity: (B
MI+
wai
st)/
2
2. Z
-dysl
ipid
eam
ia: (T
Gs+
inver
ted H
DL
)/2
3. Z
-hyper
tensi
on: (S
BP+
DB
P)/
2,
4. Z
-glu
cose
: G
luco
se
All Z
-sco
res
wer
e st
andar
diz
ed u
sing:
Ζ
Ζ−
Ζ=
Ζσµ
Fra
nks
(fo
r m
ales
and f
emal
es s
epar
atel
y).
All
indiv
idual
Z-F
ranks
wer
e ad
ded
to f
orm
a c
um
ula
tive
Z-F
ranks
score
10-y
ear
FR
S 3
2
1. A
ge;
2. T
ota
l-C
; 3. H
DL
-C;
4. SB
P w
ith/w
ithout an
ti-h
yper
tensi
ves
**;
5. Sm
oker
(yes
/no);
6. D
iabet
ic (
yes
/no)
Alloca
tion o
f poin
ts a
ccord
ing to D
’Agost
ino e
t al
. (2
008);
ta
ble
s 5 a
nd 7
32
Signs:
#, th
e N
CE
P A
TP
ΙΙΙ
Met
S i
s ‘d
iagnose
d’
if a
t le
ast th
ree
com
ponen
ts a
re p
rese
nt;
##, th
e ID
F M
etS is
‘dia
gnose
d’
if e
levat
ed w
aist
plu
s at
lea
st t
wo o
ther
com
ponen
ts a
re p
rese
nt;
*, B
NF-c
ode:
2.1
2 (
lipid
-reg
ula
ting d
rugs,
i.e.
sta
tins
and f
ibra
tes)
; **,
BN
F-c
odes
: 2.4
(bet
a-ad
renore
cepto
r blo
ckin
g d
rugs)
, 2.5
.1 (
vas
odil
ator
anti
hyper
tensi
ve
dru
gs)
, 2.5
.2 (
centr
ally
act
ing a
nti
hyper
tensi
ve
dru
gs)
, 2.5
.4 (
alpha-
adre
nore
cepto
r blo
ckin
g d
rugs)
, 2.5
.5.1
(angio
tensi
n-c
onver
ting e
nzy
me
inhib
itors
), 2
.5.5
.2 (
angio
tensi
n-I
I-re
cepto
r an
tagonis
t), 2.6
.1 (
nit
rate
s), 2.6
.2 (
calc
ium
-chan
nel
blo
cker
s), 2.6
.3 (
pota
ssiu
m c
han
nel
act
ivat
ors
), a
nd 2
.6.4
(per
ipher
al v
asodil
ators
and r
elat
ed d
rugs)
.
Abbreviations:
BM
I, b
ody m
ass
index
(kg/m
2);
BN
F,
Bri
tish
Nat
ional
Form
ula
ry;
C-c
hole
ster
ol; D
BP,
dia
stolic
blo
od p
ress
ure
; (f
), c
ut-
off
val
ue
for
fem
ales
; FR
S,
Fra
min
gham
ris
k s
core
; H
DL
, hig
h d
ensi
ty l
ipopro
tein
; ID
F,
inte
rnat
ional
dia
bet
es f
eder
atio
n; (m
), c
ut-
off
val
ue
for
mal
es; M
etS, m
etab
oli
c sy
ndro
me;
NC
EP A
TPΙΙ
Ι, N
atio
nal
chole
ster
ol ed
uca
tion p
rogra
m. A
dult
tre
atm
ent pan
el 3
; SB
P, sy
stoli
c blo
od p
ress
ure
; T
G, tr
igly
ceri
des
.
Chapter 2.
54
Chapter 3
Non-alcoholic fatty liver disease is associated with
cardiovascular disease risk markers
Obes Rev 2009; 10(4):412-419 _ Review Paper
Mireille A. Edens 1
Folkert Kuipers 2
Ronald P. Stolk 1
Department of Epidemiology 1 Laboratory of Pediatrics; CLDMD 2
University Medical Center Groningen University of Groningen
Groningen, the Netherlands
Chapter 3.
56
ABSTRACT
Background: Recognition of the link between non-alcoholic fatty liver disease (NAFLD)
and cardiovascular disease (CVD) has boosted research in this area.
Main objective: To review the literature on NAFLD in the context of CVD, focussing on
underlying mechanisms and treatment.
Results: Besides excessive fatty acid influx, etiologic factors may include components of
the metabolic syndrome, cytokines, and mitochondrial dysfunction. NAFLD is associated
with both hepatic and systemic insulin resistance. In the case of NAFLD, the liver
overproduces several atherogenic factors, notably inflammatory cytokines, glucose,
lipoproteins, coagulation factors, and factors increasing blood pressure. Intervention studies
on diet and laparoscopic surgery revealed improvements of hepatic fat content and CVD
risk profile. Pharmacological approaches with potential benefit have been developed as
well, but effects are often confounded by weight change.
Conclusions: NAFLD is associated with an increased CVD risk profile (and hepatic risk).
In order to improve CVD risk profile, prevention and treatment of NAFLD seems
advisable. However, well designed intervention studies, randomised clinical trials, and
long-term follow-up studies are scarce.
Cardiovascular risk of the fatty liver
57
INTRODUCTION
The global increase of overweight and obesity is alarming 1, as obesity is a risk factor for
many diseases including cardiovascular disease (CVD) 2. Obesity has the highest CVD risk
when fat is located in the abdominal region 3.
In the case of obesity accompanied by insulin resistance, triglycerides (TGs) are often
excessively stored ectopically, i.e. in organs and muscles rather than in adipocytes. When
TGs accumulate within hepatocytes (HC in figure І), a pathological condition usually
referred to as fatty liver disease (FLD) will develop. FLD includes a wide spectrum, which
can broadly be divided into steatosis and steatohepatitis 4. Non-alcoholic FLD (NAFLD) is
used to describe FLD in a person who drinks no or little alcohol prior to diagnosis. In the
literature, the amount of ethanol that is allowed for the diagnosis NAFLD varies greatly,
but is maximally 20 g/day for women and 30 g/day for men. The prevalence of NAFLD in
the general adult Western population is relatively high, i.e. 20% 5, 6, whereas the prevalence
of total FLD, including both NAFLD and alcoholic FLD (AFLD), is approximately 30% 5.
In obese non-diabetic Western adults, the prevalence of NAFLD ranges from 80.4% to
97.9% 7, 8.
Although there is a hepatic risk for patients with NAFLD, notably cirrhosis 9 and
hepatocarcinoma 10, the CVD risk for patients with NAFLD may be higher 10. Few studies
have revealed evidence of an association between NAFLD and early CVD markers 11, CVD
events 12, 13 and CVD mortality 10. Follow-up of patients with NAFLD showed a higher
incidence of CVD compared to controls 10, 13. A study by Hamaguchi et al. (2007) revealed
that NAFLD was an independent predictor, even stronger than the metabolic syndrome, for
first time CVD events 13.
The recognition of the CVD risk of NAFLD has boosted research in this area during the
recent years. We have reviewed the literature on NAFLD in the context of CVD risk profile
markers. In this paper, after a short description of the etiology of NAFLD, we provide an
overview of the cardiovascular risk of NAFLD. Finally, the potential need for prevention
and treatment of NAFLD in order to improve CVD risk profile is addressed.
Chapter 3.
58
ETIOLOGY
The etiology of the hepatic lipid imbalance underlying the pathophysiology of NAFLD has
been increasingly unravelled. Besides excessive non-esterified fatty acid (NEFA) influx,
mediating factors may include: i] components of the metabolic syndrome 14, 15, ii] cytokines
16-24, and iii] mitochondrial dysfunction 25 (figure І). A study on the incidence of NAFLD
suggested that the metabolic syndrome precedes NAFLD 14, with insulin resistance as a
cornerstone 15. Animal models, reviewed by Diehl et al. (2005) 16, revealed involvement of
the cytokine tumour necrosis factor alpha (TNFα) and its possible antagonist adiponectin 17
in the pathogenesis of NAFLD. This is reinforced by cross-sectional studies showing
changes in messenger ribonucleic acid (mRNA) of both TNFα receptors (increase) and
adiponectin receptors (decrease) in NAFLD 18-20. TNFα, recently reviewed by Ryden and
Arner (2007), may have numerous mediating actions, amongst others increasing insulin
resistance and inhibiting fatty acid oxidation 22. Several animal studies on adiponectin,
recently reviewed by Lafontan and Viguerie (2006), suggest opposite actions of adiponectin
on energy metabolism, i.e. increasing insulin sensitivity and stimulation of fatty acid
oxidation 23. Additionally, adiponectin might contribute to inhibition of lipogenesis 24.
Polymorphisms in the gene encoding adiponectin receptor 1 are associated with the
presence of high hepatic fat content (and insulin resistance) 21. Mitochondrial dysfunction
(in NASH), recently reviewed by Begriche et al. (2006), can be caused by oxidative stress
amongst others, and may result in TG accumulation and eventually cell death, i.e. necrosis
As the possible antagonists TNFα and adiponectin 17 may be involved in both the etiology
of NAFLD 16-24 and worsening of CVD risk profile 23, 34-38, TNFα-lowering in NAFLD
might be beneficial to improve both NAFLD and CVD risk profile, as suggested by studies
on pentoxifylline 74, 79.
CONCLUSION
NAFLD is associated with an increased CVD risk profile (and hepatic risk). In order to
improve CVD risk profile, prevention and treatment of NAFLD seems advisable. However,
well designed intervention studies, randomised clinical trials and long-term follow-up
studies are scarce.
Table І. Sel
ecti
on o
f in
terv
enti
on s
tudie
s on N
AF
LD
and C
VD
ris
k m
arker
s, lim
ited
to s
tudie
s w
ith a
dia
gnosi
s by h
isto
logy o
r im
agin
g
Studied treatm
ent modality
Patients
n
Length
HFC Tot
BMI
Ref
BE
FO
RE-A
FT
ER
ST
UD
IES
Moderate W
L (
2.6
BM
I-poin
ts) by diet
T2D
M, obes
e *
8
1-3
m
↓
na
↓
66
Moderate W
L (
≈2.7
BM
I-poin
ts) by diet
HF
C>
5%
, G
DM
11
3–6 m
↓
na
↓
67
HF
C<
5%
, G
DM
12
↓
na
↓
Severe WL
(10.4
BM
I-poin
ts) by diet
Morb
idly
obes
e *
41
9 m
↓
- -
69
Severe WL
(17
BM
I-poin
ts) by L-surgery
NA
FL
D
70
15 m
↓
↓
↓
70
Atorvastatin (
10 m
g)
NA
SH
, ↑lipid
s 10
9 m
↓
=
=
74
Metform
in (
max
imum
2 g
) N
AS
H, ↑A
LT
17
12 m
↓
↓
↓
76
Losartan
(50 m
g)
NA
SH
, hyper
tensi
on
12
9 m
↓
↓
=
74
Pentoxifylline
(2*400 m
g)
NA
SH
, T
2D
M
13
9 m
↓
↓
=
74
Pentoxifylline
(3*400 m
g)
N
AS
H, ↑A
LT
9
12 m
-
↓
=#
79
NO
N-R
AN
DO
MIS
ED
CO
NT
RO
LL
ED
TR
IAL
S
Moderate W
L (
3 B
MI-
poin
ts) by diet/ exc. V
S. no d
iet/ e
xc.
N
AF
LD
, A
FL
D *
25
3 m
↓
- ↓
68
UDCA
(13–15 m
g/k
g)
VS. c
lofi
bra
te (
2*1 g
) N
AS
H, C
hole
lith
iasi
s 40
12 m
↓
- =
75
NA
SH
, ↑T
G
n-3 PUFA ethyl ester
(1 g
) VS. n
o n
-3 P
UF
A e
thyl es
ter
NA
FL
D *
56
6–12 m
↓
na
=
80
RA
ND
OM
ISE
D C
LIN
ICA
L T
RIA
LS
Roziglitazone
(2*4 m
g)
VS. m
etfo
rmin
(2*1 g
) T
2D
M
20
4 m
↓
na
↑
77
Sig
ns:
↑ =
sig
nif
ican
t in
crea
se a
nd/
or
signif
ican
tly i
nfe
rior,
↓ =
sig
nif
ican
t dec
reas
e an
d/
or
signif
ican
tly s
uper
ior,
‘=
’ =
no c
han
ge,
- =
mis
sing v
alue,
* =
eth
anol
inta
ke
unre
port
ed o
r hig
her
than
allow
ed f
or
NA
FL
D,
# =
p ≤
0.1
0.
Abbre
via
tions: e
xc.
= e
xer
cise
, G
DM
= g
esta
tional
dia
bet
es m
ellitu
s, H
FC
= h
epat
ic f
at c
onte
nt, L
-surg
ery =
lap
arosc
opic
surg
ery, m
= m
onth
s, n
= a
mount of
subje
cts
who
had
both
pre
and p
ost
mea
sure
men
ts,
na
= n
ot
applica
ble
, PU
FA
= p
oly
unsa
tura
ted f
atty
aci
ds,
Ref
= r
efer
ence
, T
ot. =
tota
l N
ASH
sco
re/
activity i
ndex
, T
2D
M =
type
2
dia
bet
es m
ellitu
s, U
DC
A =
urs
odeo
xych
olic
acid
, VS. =
ver
sus,
WL
= w
eight lo
ss.
Cardiovascular risk of the fatty liver
65
Chapter 3.
66
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74
Chapter 4
Pathogenesis of fatty liver disease: A theory on lipid content, inhibited metabolism, and inflammation
Submitted/ Under review _ Review Paper
Mireille A. Edens 1
Albert K. Groen 2
Ronald P. Stolk 1
Department of Epidemiology 1 Laboratory of Pediatrics; CLDMD 2
University Medical Center Groningen University of Groningen
Groningen, The Netherlands
Chapter 4.
76
ABSTRACT
Background and aims Fatty liver disease (FLD) is the most prevalent hepatic condition
worldwide. Thorough understanding of risk factors and the pathogenesis of FLD is
therefore warranted. Few complete theories on its pathogenesis have been proposed. The
aim of this paper was to critically discuss present theories on the pathogenesis of FLD, and
to arrange risk factors in an easily recognisable manner.
Methods The literature, including behavioural, genetic, and environmental factors
associated with FLD was reviewed, together with their underlying role in the pathogenesis
of FLD. Risk factors for FLD were arranged according to pathogenesis.
Results The following groups of risk factors for FLD were developed: 1) ‘risk factors for
hepatic lipid content’, 2) ‘risk factors for inhibited hepatic metabolism’, and 3) ‘risk factors
for hepatic inflammation’. Some risk factors can be placed in more than one category and
might therefore have a greater effect on FLD than others. These three categories do not
stand alone but interact, forming a downward spiral onto the development and progression
of FLD.
Conclusions We propose to modify current arrangements of risk factors for FLD. The
present arrangement of risk factors may be useful to identify people at high risk for FLD
and to initiate interventions.
Pathogenesis of fatty liver disease
77
INTRODUCTION
The histological spectrum of fatty liver disease (FLD) encompasses a wide range of various
degrees of fatty infiltration, inflammation and fibrosis 1. FLD is broadly dividable into
steatosis (fat accumulation, with or without nonspecific inflammation) and steatohepatitis
(fat accumulation plus inflammation, with or without fibrosis) 2. A liver containing both
fatty infiltration and inflammation which is neither steatosis nor severe enough to be
categorised as steatohepatitis, has been referred to as ‘intermediate’ 3 or ‘borderline’ 2
steatohepatitis. Importantly, while the FLD spectrum progresses in severity (fibrosis stage),
hepatic fat content decreases 4, 5.
Historically, alcoholism is a well known risk factor for FLD. As alcoholic FLD (AFLD)
and non-alcoholic FLD (NAFLD) may follow different clinical courses 6, both are usually
distinguished using an alcohol intake cut-off value of 20 g/d 7. Although non-alcoholic
steatosis (NAS) is often considered a benign condition, at least in the short-term, it leads to
fibrosis in an estimated 8.3% of cases 8. NASH progresses in fibrosis stage in a estimated
37.6% of cases 9. NAFLD is associated with an increased hepatic risk, i.e. cryptogenic
cirrhosis (maximum fibrosis score 2) predisposing to end stage liver disease 5, and/or
hepatocarcinoma 10. Additionally, NAFLD is associated with cardiovascular disease (CVD)
risk factors 11, 12. Longitudinal studies revealed that overall survival of patients with
NAFLD 13, 14 and NASH 14 is significantly reduced, as compared to reference populations.
CVD-related death was found to be the primary cause of death in patients with NAFLD 13,
14. CVD-related death was 7.5% in a reference population, slightly increased to 8.6% in
patients with NAS (p=ns) and significantly increased to 15.5% in patients with NASH
(p<.05 compared to the reference population) 14. Additionally, also liver-related death in
patients with NAFLD 1 and NASH 14 is significantly higher as compared to reference
populations. As the current prevalence of FLD (±30%) and its subtype NAFLD (±20%) in
the general adult Western population are alarmingly high 15, 16 and potentially increasing 17,
18, a good understanding of risk factors and the pathogenesis of FLD is needed.
The reason(s) why some patients progress while others do not is yet unclear, hence
cryptogenic. In an attempt to explain the pathogenesis of FLD a number of hypothesis have
been developed previously 19-23. The aim of this paper was to modify previous theories on
the pathogenesis of fatty liver disease.
Chapter 4.
78
RISK FACTORS AND THEORIES ON PATHOGENESIS
Previously presented risk factors
Historically, conditions associated with FLD were simply presented and not arranged, e.g.
by Lee (1989) 24. Later, several authors presented an arrangement of etiologic factors, e.g.
Mach (2000) 25 and Angulo (2002) 26. These arrangements include: ‘toxic factors’,
‘nutritional factors’, ‘endocrine factors and metabolic diseases’, and ‘other rare causes’ 25
and ‘nutritional’, ‘drugs’, ‘metabolic or genetic’, and ‘other’ 26. Another more often used
arrangement is the division between ‘primary causes’ (e.g. obesity) and ‘secondary causes’
(e.g. alcoholism or hepatitis) 27, 28. However, none of these arrangements is based on the
pathogenesis of FLD.
Previously presented theories
Previously developed theories on the pathogenesis of FLD include: the 2 step model by
Wanless ea. (1989) 19, the ‘2 hits theory’ by Day and James (1998) 20, the modified ‘2 hits
theory’ by Day (2002) 21, and the ‘four-step model’ by Wanless and Shiota (2004) 22.
Insulin is considered the first ‘hit’ or ‘step’ causing steatosis in all theories 22. Day and
James hypothesised that lipid peroxidation 20, later modified to lipid peroxidation and/or
direct lipotoxicity 21, is a second ‘hit’ that causes steatohepatitis. Wanless and Shiota
proposed that intracellular lipid toxicity or lipid peroxidation, or both, modified by alcohol,
drugs, and ischemia can be considered a second ‘hit’ that causes necrosis 22. Additionally,
they added a third and a fourth ‘step’. Step 3 being release of bulk lipid from hepatocytes
into the interstitium leading to direct and inflammatory injury to hepatic veins, and step 4
being venous obstruction with secondary collapse and ultimately fibrous septation and
cirrhosis 22. In 2007, the idea of ‘at least 3 hits’ was published, which suggests that the
pathogenesis of FLD is a complex interaction between behaviour, environment, and genetic
susceptibility 23.
Currently presented arrangement of risk factors and theory on pathogenesis
After reviewing the literature on risk factors associated with FLD, including behaviour, the
environment, and genes 23, we propose to modify current theories on the pathogenesis of
FLD. We propose to arrange risk factors in the following three categories: 1) risk factors
Pathogenesis of fatty liver disease
79
for hepatic lipid content, 2) risk factors for inhibited hepatic metabolism, and 3) risk factors
for hepatic inflammation. Figure І (simplified version) and appendix І (detailed version
including references) show an overview on risk factors arranged in these three categories.
Figure ІІ is a model on intra-hepatic pathogenesis. For each category of risk factors a brief
description of pathogenesis will be provided.
Figure І. Overview on risk factors for fatty liver disease, arranged in the following three categories: 1) risk factors for hepatic lipid
content, 2) risk factors for inhibited hepatic m
etabolism
, and 3) risk factors for hepatic inflam
mation.
For a
detailed list of risk factors and their
references, the reader is referred to appendix І.
Arrows: Closed arrows, stimulatory; interrupted
arrows, inhibitory.
Abbreviations:
BFD,
body fat
distribution;
Dets., determinants; HI; hepatic inflam
mation;
HLC, hepatic lipid content; iHM, inhibited
hepatic
metabolism
; P-I
complex,
pharmacological-interaction
complex;
SAT,
subcutaneous
adipose tissue; SIBO,
small
intestinal bacterial overgrowth; VAT, visceral
adipose tissue.
Chapter 4.
80
Figure ІІ. M
odel on risk factors for fatty liver disease showing intra-hepatic interaction
Arrows: Closed arrows, stimulatory; interrupted
arrows, inhibitory.
Signs: 1, Substrate for microsomes include both
saturated and unsaturated fatty acids; 2, Substrate
for
mitochondria
include
short-chain (<C
8),
medium-chain (C
8-C
11), long-chain (C
12-C
20),
and very long-chain (>C
20)
fatty acids; 3,
Substrate for peroxisomes include straight-chain
saturated fatty acyl-CoAs (>C
20), dicarboxylic
acids, prostanoids, C
27 bile acid interm
ediates;
▲, increase; ▼, decrease.
Abbreviations: B
H, ballooning of hepatocytes;
CARBS,
carbohydrates;
DNL,
de
novo
lipogenesis; ERS, endoplasm
atic reticular stress;
HFFAs, hepatic free fatty acids; HSC, hepatic
stellate cell; HSL, horm
one
sensitive
lipase;
IBD, inflam
matory bowel disease; IR
, insulin
receptor; L
S, lipolysis and secretion from lipid
vesicle; LP, fatty acid-induced production of
TNFα
via
a lysosomal
pathway;
MF,
‘metaflammation’; OS, oxidative
stress; PLs,
phospholipids; PPARα, peroxisome proliferator-
activated receptor alpha; SIBO, sm
all intestinal
bacterial
overload;
TGs,
triglycerides;
TI,
traditional inflam
mation response; TPs, toxic
products origination from oxidation; UO, up-
regulation of oxidation; VLDL, very low density
lipoprotein.
Pathogenesis of fatty liver disease
81
Table Ι. G
enet
ic r
isk f
acto
rs (
incl
. sy
stem
ic a
nd inte
stin
al)
thro
ughout th
e N
AFL
D s
pec
trum
Variable
Correlation
with liver fat
Increasing severity of the NAFLD spectrum →
NAS
vs.
contr
ols
NAFLD
&
vs.
contr
ols
NASH
vs.
contr
ols
NASH
vs.
non-N
ASH
#
NASH
vs.
NA
S
LIPID
Hep
atic
LPL
mR
NA
+ 2
9
▲29
Hep
atic
PPA
Rγ
mR
NA
=●
29
=●
30
Hep
atic
PPA
Rγ2
mR
NA
+
29
▲29
Hep
atic
PG
C1 m
RN
A
▼
29
Hep
atic
PPA
Rδ m
RN
A
=
●29
Hep
atic
LX
Rα m
RN
A
▲31
Hep
atic
SR
EB
P-1
c m
RN
A
=●
30 o
r ▲
31
Hep
atic
ChR
EB
P m
RN
A
▼31
Hep
atic
AC
AC
A m
RN
A
=
●29
Hep
atic
FA
S m
RN
A
=●
30,
31
Hep
atic
AC
C1 m
RN
A
▲30,
31
Hep
atic
AC
SL
4 m
RN
A
+ 2
9
▲29
Hep
atic
DG
AT
1 m
RN
A
=●
30
Hep
atic
AD
RP m
RN
A
=●
30
Hep
atic
HSL
mR
NA
▼
30
Hep
atic
SC
D1 m
RN
A
=
●29
METABOLISM
Hep
atic
PPA
Rα m
RN
A
=
○29
▼30
Hep
atic
AM
PK
mR
NA
=
●31
Hep
atic
AC
C2 m
RN
A
=●
30
Hep
atic
CPT
1a
mR
NA
=●
29
▼30
Hep
atic
UC
P2 m
RN
A *
=
●30
Hep
atic
LC
AD
mR
NA
▲
30
Hep
atic
HA
DH
α m
RN
A
▲30
Hep
atic
AC
OX
mR
NA
=
●30
Hep
atic
BO
X m
RN
A
▲30
Hep
atic
CY
P2E
1 m
RN
A
▲30
Hep
atic
CY
P4A
11 m
RN
A
▲30
Hep
atic
Cat
alas
e m
RN
A
▲30
Hep
atic
SO
D m
RN
A
▲30
Hep
atic
GSS m
RN
A
=30
INFLAMMATION
Hep
atic
TN
Fα m
RN
A
▲32
▲33,
34
SA
T T
NFα m
RN
A
▲32
Syst
emic
TN
Fα lev
el
=
35
▲33
▲35,
36
=
33 o
r ▲
35
Hep
atic
TN
Fα-R
1 m
RN
A
▲32
= 3
4
Hep
atic
TN
Fα-R
2 m
RN
A
= 3
2
= 3
4
Syst
emic
sT
NFα-R
1 lev
el
=
●35
▲
35
Syst
emic
sT
NFα-R
2 lev
el
=
●35
=
●35
Hep
atic
adip
onec
tin m
RN
A *
X 3
7
X
37
▼
34 o
r X
37
VA
T a
dip
onec
tin m
RN
A
=
○37
▼
37
=
○37
SA
T a
dip
onec
tin m
RN
A
=
○37
=
○37
=
●37
Syst
emic
adip
onec
tin lev
el
− 3
8
=○
37
▼
37
=
○34,
37
Hep
atic
adip
o-R
1 m
RN
A
=
●29 =
●37
▲
37
=
●37 o
r =
○34
Hep
atic
adip
o-R
2 m
RN
A
=
●29 =
●37
▲
37
▲
34 o
r =
●37
Chapter 4.
82
Hep
atic
MC
P1 m
RN
A
+ 2
9
▲29
Syst
emic
MC
P1 lev
el
▲
35
=
35
Hep
atic
MIP
1α m
RN
A
+ 2
9
=●
29
Hep
atic
CD
68 m
RN
A
=
●29
Syst
emic
LP
S lev
el
▲33
SIB
O
▲39
▲36
Inte
stin
al p
erm
eabil
ity
▲39
=●
36
Syst
emic
endoto
xin
lev
els
=36
Signs: +
, si
gnif
ican
t posi
tive
corr
elat
ion; −
, si
gnif
ican
t in
ver
se c
orr
elat
ion;
▲,
signif
ican
tly i
ncr
ease
d;
▼,
signif
ican
tly d
ecre
ased
; =
, si
milar
/non-
signif
ican
t; =
●,
sim
ilar
/non-s
ignif
ican
t in
crea
se;
=○
, si
milar
/non-s
ignif
ican
t dec
reas
e; X
, undet
ecta
bly
low
mR
NA
; &,
NA
FL
D i
ncl
udes
both
NA
S a
nd
NA
SH
; * u
sual
ly n
ot ex
pre
ssed
in the
liver
; #, non-N
ASH
incl
udes
both
contr
ols
and N
AS
.
Abbreviations: A
CA
CA
, ac
etyl-
coen
zym
e A
car
bxyla
se-α
; A
CC
1, ac
etyl-
CoA
car
boxyla
se 1
; A
CC
2, ac
etyl-
CoA
car
boxyla
se 2
; A
CS
L4, ac
yl-
CoA
synth
etas
e lo
ng-c
hai
n f
amily m
ember
4; A
CO
X, st
raig
ht-
chai
n a
cyl-
CoA
oxid
ase;
AD
RP
, ad
ipose
dif
fere
ntiat
ion-r
elat
ed p
rote
in (
adip
ophilin
); A
MP
K,
AM
P-a
ctiv
ated
pro
tein
kin
ase;
AT
P, ad
enosi
ne
trip
hosp
hat
e; B
OX
, bra
nch
ed-c
hai
n a
cyl-
CoA
oxid
ase;
CD
68, cl
ust
er o
f dif
fere
ntiat
ion 6
8; C
hR
EB
P,
carb
ohydra
te r
esponsi
ve
elem
ent bin
din
g p
rote
in; C
PT
1a,
car
nitin
e pal
mitoylt
ransf
eras
e 1; C
YP
2E
1, cy
toch
rom
e P
450 2
E1; C
YP
4A
11, cy
toch
rom
e
P450 4
A11; D
AG
, dia
gly
cero
l; D
GA
T1, dia
cylg
lyce
rol O
-acy
ltra
nsf
eras
e 1; E
R, en
dopla
smic
ret
iculu
m; F
AS
, fa
tty a
cid s
ynth
ase;
GS
S, glu
tath
ione
synth
etas
e; H
AD
Hα, L
3-h
ydro
xyac
yl-
CoA
deh
ydro
gen
ase
alpha;
HF
FA
, hep
atic
fre
e fa
tty a
cids;
HO
MA
, hom
eost
asis
model
ass
essm
ent; H
SL
,
horm
one
sensi
tive
lipas
e; incl
., incl
udin
g; L
CA
D, lo
ng-c
hai
n a
cyl-
CoA
deh
ydro
gen
ase;
LP
L, lipopro
tein
lip
ase;
LP
S, lipopoly
sach
arid
e-bin
din
g
pro
tein
, L
XR
α, li
ver
X r
ecep
tor
alpha;
MC
P1, m
onocy
te c
hem
oat
trac
tant pro
tein
1; M
IP1α, m
acro
phag
e in
flam
mat
ory
pro
tein
1α; m
RN
A, m
esse
nger
ribonucl
eic
acid
; n/a
, not ap
plica
ble
; P
GC
1, P
PA
Rγ
coac
tivat
or
1; P
PA
Rα, per
oxis
om
e pro
life
rato
r-ac
tivat
ed r
ecep
tor
alpha;
PP
AR
δ, per
oxis
om
e
pro
life
rato
r-ac
tivat
ed r
ecep
tor
del
ta; P
PA
Rγ2
, per
oxis
om
e pro
life
rato
r-ac
tivat
ed r
ecep
tor
gam
ma
isofo
rm 2
; S
CD
1, st
earo
yl-
coen
zym
e A
des
atura
se;
SO
D, su
per
oxid
e dis
muta
se; S
RE
BP
-1c,
ste
rol re
gula
tory
ele
men
t bin
din
g p
rote
in 1
c; U
CP
2, unco
upling p
rote
in 2
; vs.
, ver
sus.
Pathogenesis of fatty liver disease
83
Chapter 4.
84
PATHOGENESIS OF FATTY LIVER DISEASE
CATEGORY 1. RISK FACTORS FOR HEPATIC LIPID CONTENT
Generally, in the case of more hepatic lipid availability (uptake and de novo synthesis) on
one hand, compared to hepatic lipid disposal (oxidation, and excretion & secretion) on the
other hand, lipids are stored within hepatocytes as neutral triglycerides (TGs).
Uptake and de novo synthesis
Lipid sources and pathways
There are three nutrition-related sources regarding hepatic lipid origin with four pathways:
1) hepatic uptake of dietary fats via chylomicrons (a) and the NEFA pool, i.e. spillover (b),
2) hepatic uptake of dietary carbohydrates followed by de novo lipogenesis, and 3) hepatic
uptake of lipids from the NEFA pool with a peripheral origin (“old fat”) 40. Endotoxins,
which are complex lipopolysaccharides, could be considered another likely minor source of
lipids and carbohydrates 41, 42, but will be discussed in category 3.
Studies on stable isotopes administered in food and/or infused into the blood, have revealed
insight in hepatic lipid origin in the case of suspected NAFLD (by aminotransferases) 40.
After four days of labelling followed by a liver biopsy in the fasting state, the contributions
of peripheral NEFA, de novo lipogenesis, and dietary fats to hepatic fat content were 59%
more lipolysis from adipose tissue may take place. Both visceral adipose tissue (VAT) and
Pathogenesis of fatty liver disease
85
subcutaneous adipose tissue (SAT) correlate with hepatic fat content, but only VAT is
independently associated with hepatic TG content, at least in non-diabetic subjects 38. These
results are in agreement with the ‘portal hypothesis’ which suggests that peripheral fat
depots draining in the portal vein, notably VAT, contribute to hepatic fat content the most
44. Moreover, the fatty acid flow from SAT to the liver is intercepted by muscles, enabling a
protective role of exercise for FLD 45-47.
Dietary composition and de novo lipogenesis
Total energy intake is associated with NAFLD 48. The role of dietary composition for
NAFLD was recently reviewed by Le and Bortolotti (2008) 49. The authors state that the
role of carbohydrates in the pathogenesis of NAFLD has been clearly shown, but that the
role of lipids remains controversial 49. This might be attributable to de novo lipolysis on
average having a larger contribution than dietary fat 40.
Expression of several genes related to de novo lipogenesis (LXRα, SREBP-1c, ChREBP) is
changed in the case of NAFLD (table I). Stable isotope studies have provided evidence that
de novo lipogenesis is chronically elevated in subjects with NAFLD. In controls, the
contribution of de novo lipogenesis to VLDLTG is <5% in the fasting state 50, 51 with
significant postprandial elevation 50. In the case of NAFLD, the contribution of de novo
lipogenesis to VLDLTG is 15% - 25% in the fasting state 40, 51, with no postprandial
elevation 40, 51.
Excretion, secretion and storage
Hepatic free fatty acids (HFFAs) can be excreted in bile as part of phospholipid, secreted
by VLDL, or oxidised. Little is known about the magnitude of lipid excretion by bile in
human subjects with NAFLD 52, and oxidation will be discussed in category 2.
Lipid secretion in VLDL
Due to hepatic insulin resistance, secretion of VLDL (containing particularly TGs but also
cholesterol and phospholipids) may be increased 12, however, this increased secretion may
not be high enough to prevent FLD. In the case of rare storage and secretion disorders, FLD
is likely to occur 53, 54.
Hepatic TG synthesis and storage
HFFAs which are not oxidised, excreted in bile, or secreted in VLDL may be stored as
neutral TGs. Molecular mechanisms underlying TG synthesis and storage have extensively
been reviewed previously 43, 55. Expression of several genes related to TG synthesis (FAS,
Chapter 4.
86
ACC1, DGAT1) and TG storage (ADRP) is changed in the case of NAFLD (table I). Lipids
are stored as neutral TGs while isolated from the cytoplasm by a phospholipid monolayer
forming ‘lipid vesicles’, which can be either microvesicular or macrovesicular 43.
Consequences of elevated hepatic lipid levels
Lipotoxicity and lipoapoptosis
Elevated cellular lipid levels predispose to lipotoxicity (metabolically relevant cellular
dysfunction) which could lead to necrosis, and lipoapoptosis (programmed cell-death) 56.
When discussing lipotoxicity and lipoapoptosis it may be relevant to distinguish HFFAs
and fatty acids stored as neutral TGs within lipid vesicles. HFFAs may exert direct toxicity
by uncoupling phosphorylation and indirect toxicity via production of reactive oxygen
species (ROS) 57, 58, and may induce the production of inflammatory cytokines as well 59-62.
Hepatic microcirculation
Increased TG storage within lipid vesicles may cause ballooning of hepatocytes, which is
hypothesised to pinch off hepatic microcirculation 63. Additionally, in the case of NAFLD
secretion of several atherogenic factors (e.g. lipids and glucose) may be increased 12
predisposing to impaired hepatic microcirculation as well. Impaired microcirculation may
have consequences regarding both transport to hepatocytes (notably supply of oxygen) and
from hepatocytes (draining off any unfavourable products).
CATEGORY 2. RISK FACTORS FOR INHIBITED HEPATIC METABOLISM
Molecular mechanisms of hepatic lipid oxidation have been extensively reviewed
previously 55, 58, thus will be described here very briefly. Oxidation in the liver takes place
in mitochondria, peroxisomes, and endoplasmatic reticular microsomes. The latter two are
usually minor oxidation systems but may become more important in the case of FLD 55.
Many key enzymes involved in fatty acid oxidation are regulated by peroxisome
proliferator-activated receptor alpha (PPARα), excluding enzymes of the non-classical
peroxisomal pathway 55.
Metabolic burden and toxic by-products
In the case of NAFLD, PPARα is downregulated 30, however several enzymes involved in
fatty oxidation localised in mitochondria, peroxisomes and microsomes are upregulated
(table Ι). However, given the increased amount of hepatic substrate, oxidation may be
substantial. Oxidation delineates production of toxic by-products, e.g. ROS (superoxide and
Pathogenesis of fatty liver disease
87
hydrogen peroxide, by all oxidation systems), malondialdehyde and 4-hydroxynonenal (by
peroxisomes and microsomes), and dicarboxylic acids (by microsomes). The higher the
metabolic burden to oxidation systems the higher the amount of toxic by-products. ROS are
neutralised by anti-oxidants, e.g. glutathione, and enzymes; superoxide dismutase (SOD)
and catalase. Dicarboxylic acids, which are toxic for mitochondria, are oxidised by
peroxisomes 55. Some genes related to neutralisation pathways (glutathione synthetase,
SOD, catalase) are upregulated in the case of NAFLD (table Ι) 30, which suggests increased
oxidation and oxidative stress.
Drugs
The liver plays an important role in metabolism and excretion of many drugs and toxins.
Although uncommon, hence idiosyncratic, drug-induced liver injury can be caused by both
prescription drugs 64, 65 (iatrogenic-induced) and over-the-counter drugs 64. Idiosyncratic
drug-induced liver injury may occur particularly in those drugs that have significant hepatic
metabolism 65. Some herbals 64 and environmental toxins and petro-chemicals 66 are
associate with liver injury as well, but their mechanisms are unknown.
Drug excretion
Xenobiotics and endobiotics can be excreted out of hepatocytes into bile or blood (followed
by urinary excretion) by efflux transporters 67. Efflux transporters include e.g. multidrug
resistance-associated proteins (Mrps), bile salt excretory protein (Bsep), and breast cancer
resistance protein (Bcrp) 67. Little is known about the magnitude of drug excretion in
human NAFLD. An animal study on high fat diet-induced NAS and methionine- and
choline-deficient diet-induced NASH and additional Acetaminophen administration may
suggest changes in drug excretion 67. Expression of several efflux transporters was changed,
and excretion shifted from biliary to urinary.
Organelles
Mitochondria
Mitochondrial fatty acid oxidation primarily involves the progressive shortening of straight-
chain fatty acids into acetyl-CoA for generation of adenosine triphosphate (ATP) 55.
Hepatocytes are dependent on aerobic mitochondrial metabolism for production of ATP 58,
which necessitates a proper hepatic microcirculation 63. Although PPARα and transport of
lipids into mitochondria by CPT1a are downregulated, several genes related to
mitochondrial oxidation (LCAD, HADHα, UCP2) are upregulated in the case of NAFLD
Chapter 4.
88
(table Ι). A severely impaired recovery of fructose-induced ATP-depletion in subjects with
NASH compared to controls has been reported 68. NASH, might in some subjects be
associated with structural mitochondrial changes, i.e. enlargement (mega mitochondria) and
development of crystalline inclusions similar to brown adipose tissue 58. Several factors are
believed to underlie inhibition of mitochondrial ATP production, i.e. metabolic burden (via
oxidative stress), TNFα (via increasing mitochondrial membrane permeability), alcohol and
several drugs 57, 69, and impaired hepatic microcirculation (impaired oxygen supply, and
impaired discharge of metabolites) 63. The role of microcirculation in NAFLD was
reviewed by Farrell ea. (2008) 63. The authors state that there is evidence for impaired
perfusion in NAFLD 63, likely caused by ballooning/swelling of hepatocytes 63 and/or the
atherosclerotic milieu 12.
Peroxisomes
Peroxisomes metabolize relatively more toxic and biologically active molecules and hereby
play a role in detoxification 55. Although PPARα is downregulated, ACOX (regulated by
PPARα) and BOX (not regulated by PPARα) are upregulated in the case of NAFLD (table
Ι).
Endoplasmatic reticular microsomes
Microsomes usually play a minor role in oxidation 55. Several genes related to microsomal
oxidation (CYP2E1, CYP4A11) are upregulated in the case of NAFLD (table Ι) 30. Besides
the increased presence of substrate for microsomal oxidation, this might be attributable to
drug use as well. The pathogenesis of drug-induced liver injury is largely unknown, but
phase Ι and/or phase ΙΙ reactions in microsomes are believed to play a role 65. Phase Ι
reactions are catalysed by CYP 450 4A enzymes, predisposing to reactive drug metabolites
65. Phase ΙΙ reactions are involved in detoxifying these toxic metabolites 65.
Consequences of (impaired) hepatic metabolism
Decreased ATP production may predispose to lipid storage, and liver injury and/or necrosis
68. If toxic by-products (either lipid-derived or drug-derived) outweigh neutralisation/
detoxification, organelle damage may occur. Organelle damage may lead to decreased lipid
oxidation or even necrosis. As a response a ‘traditional inflammation’ response will set in,
which will be described in the inflammation paragraph.
Pathogenesis of fatty liver disease
89
CATEGORY 3. RISK FACTORS FOR HEPATIC INFLAMMATION
Inflammation is a key feature of obesity and type 2 diabetes 70, and by definition a
characteristic of advanced NAFLD, i.e. steatohepatitis. Two subclasses of inflammation
distinguished are ‘traditional inflammation’ (short-term response to deal with injury) and
‘metaflammation’ (metabolically triggered inflammation or chronic low-grade
inflammation) 70. Infections may trigger an inflammatory response as well. In addition,
several drugs may induce allergic reactions according to the hapten and prohapten concept
(binding of small pharmacological molecules to larger carriers to gain immunogenicity)
and/or the pharmacological interaction (PI) concept (direct binding of drugs with immune
receptors) 71.
‘Metaflammation’
The primary transcription factor nuclear factor kappa-beta (NF-κB) and its upstream
activator IκB kinase (IKKβ) are considered a ‘master-switch’ for coordination of
‘metaflammation’ in the liver, peripheral adipose tissue, and the central nervous system 59.
IKKβ/NF-κB controls the production of several inflammatory cytokines and other
inflammation mediators 59. Additionally, IKKβ/NF-κB is considered to play a vital role in
inhibition of apoptosis induced by tumour necrosis factor alpha (TNFα) 72, 73.
Pro-inflammatory imbalance
Of all inflammatory cytokines, TNFα has been studied the most and was recently reviewed
70, 74. Cytokines including TNFα are potent activators of IKKβ/NF-κB 59, 75, suggesting
auto-up regulation. Of all anti-inflammatory adipocytokines, the adipose tissue-derived
hormone adiponectin has been studied the most and was recently reviewed by several
authors 76-79. Some studies in animals 80 and humans 81, 82 have provided evidence that
TNFα down regulates adiponectin (and vice versa) at both genetic and cellular level.
Cytokine origin and uptake
TNFα is produced by both cells of the immune system 83, 84 and by fatty acids in either
peripheral adipose tissue 32, 85 or ectopic tissue 60, 61. Likely, most TNFα is produced when
tissues are infiltrated by macrophages. Additionally, certain TNFα polymorphisms have
been associated with NAFLD 86. Both polymorphisms encoding adiponectin receptor 1 87
and adiponectin receptor 2 88 have been found to be associated with hepatic fat content.
Chapter 4.
90
Hepatic-derived cytokines
Hepatic levels of TNFα and adiponectin expression are shown in table І. Throughout the
spectrum, the liver increasingly upregulates production of TNFα 32-34. Adiponectin
expression is either low 34 or undetectable 37. Adiponectin expression is lower in NASH
compared to NAS 34. Additionally, hepatic fat content correlates with hepatic levels of
MCP1 and MIP1α 29, predisposing to hepatic infiltration by monocytes and macrophages.
Peripheral adipose tissue-derived cytokines
The total amount of peripheral fat is increased in the case of NAFLD 38. TNFα expression
is much higher in VAT than SAT 37. In contrast adiponectin expression is much higher in
SAT than VAT 37. However, even in SAT, TNFα expression in the case of NASH is
increased 32. Macrophage infiltration is twice as high in VAT than SAT 85. Additionally,
the number of macrophages infiltrated in VAT, and not SAT, is significantly associated
with steatosis grade, NASH score, fibrosis stage, and fibro-inflammation index 84.
Systemic levels, receptor polymorphisms, and hepatic uptake
Hepatic and systemic levels of TNFα (receptor) and adiponectin (receptor) expression are
shown in table І. In the case of NAFLD, systemic TNFα levels are elevated 33, 35, 36, whereas
systemic adiponectin levels tend to be decreased 34, 37. Systemic soluble TNFα-R1 and
soluble TNFα-R2 tend to be slightly elevated 35. Hepatic TNFα-R1 and TNFα-R2 tend to be
upregulated in NAFLD 32, 34. Results on hepatic adipo-R1 and adipo-R2 are inconclusive 34,
37.
Infections
Endotoxins and the intestinal barrier
The intestine hosts a wide variety of bacteria 41, 42. Gram-negative bacteria have an outer
membrane encorporating endotoxins, which are complex lipopolysaccharides. Depending
on the intestinal barrier and amount of lipopolysacharide-binding protein (a hepatic-derived
acute phase protein), endotoxins are transported to the liver via the portal vein. The
intestinal barrier may be affected by e.g. alcohol 89 and inflammatory bowel disease 39,
predisposing to increased intestinal permeability likely caused by disruption of intestinal
tight junctions 39. Lipopolysacharide-binding protein is a hepatic-derived acute phase
protein. Animal models have shown that the liver is vulnerable to endotoxin-induced liver
damage 73. The damage occurred despite induction of NF-κB, having several anti-apoptotic
Pathogenesis of fatty liver disease
91
transcriptional targets 72, 73, indicating that endotoxin-induced liver damage is likely caused
by necrosis.
Subjects with NAFLD and NASH have an increased prevalence of small intestinal bacterial
overload (table Ι) 36, 39. Subjects with NAFLD 39 and NASH 36 have a non-significantly 36 or
significantly 39 increased intestinal permeability, by lactulose-rhamnose test and by urinary
excretion test, respectively. Subjects with increased intestinal permeability had an increased
prevalence of moderate or severe steatosis, instead of mild steatosis 39. Additionally,
systemic levels of lipopolysacharide-binding protein are elevated in subjects with NAFLD
33. Systemic endotoxin levels were similar in NASH compared to controls, however this
could be attributed by hepatic uptake (figure Ι) 36.
Consequences of hepatic inflammation
Whereas adiponectin has pleiotropic favourable effects 76-79, its down regulator TNFα 80-82
has pleitropic unfavourable opposite effects 70, 74. Adiponectin is associated with insulin
sensitivity and stimulates oxidation by sequential activation of AMPK, MAPK and PPARα
(determined in muscle cells) 90. TNFα causes insulin resistance 91, 92 and impairs oxidation
as well via several pathways. Firstly, TNFα down regulates adiponectin 80-82 and therefore
PPARα 90. Secondly, TNFα increases mitochondrial membrane permeability which
predisposes to cytochrome C-induced apoptosis 72, 73.
Chapter 4.
92
DISCUSSION
This paper reviews the pathogenesis of FLD, leading to the proposition to modify present
theories on the pathogenesis of FLD and to arrange risk factors for FLD based on the
pathogenesis of FLD. Risk factors for FLD are arranged into the following three categories:
1) risk factors for hepatic lipid content, 2) risk factors for inhibited hepatic metabolism, and
3) risk factors for hepatic inflammation. Some risk factors can be placed in more than one
category and might therefore have a greater effect on FLD than others. Importantly, these
three categories do not stand alone but interact, forming a downward spiral onto the
development and progression of FLD.
COMPARISON WITH OTHER THEORIES ON PATHOGENESIS
All previously presented theories 19-22 propose that insulin is a first ‘hit’ that causes steatosis
22. Insulin does facilitate transport of fat and glucose (followed by de novo lipogenesis)
across hepatic cell membranes, but there are non-insulin dependent ways as well. NEFA,
e.g. origination from peripheral fat depots 40, can flip-flop across cell membranes amongst
others 55, 93. Glucose can pass through the non-insulin responsive glucose transporter 2
(GLUT-2). Additionally, FLD is associated with insulin resistance (and hyperinsulinaemia)
12, which may induce the overproduction of VLDL in the case of FLD 94.
Regarding the previously presented second ‘hit(s)’ causing necrosis 19-22, we firstly believe
that the amount of factors should be expanded with inflammation (TNFα) and hepatic
microcirculation 63. Secondly, we believe that particularly in the case of ‘non-toxic’
dosages, initially metabolism will inhibited (rather than immediate necrosis), predisposing
to increased fat storage. Only in the case of prolonged influence of risk factors on
organelles, or in the case of severely toxic factors on organelles, necrosis will set in.
Therefore the present paper suggests that the pathogenesis of the FLD spectrum (i.e. in the
cases with non-severe toxic risk factors) is a gradual process, rather than an abrupt
consequence of separate ‘hits’. A gradual progression would also be in agreement with the
existence of ‘intermediate’ or ‘borderline’ NASH 2, 3.
Regarding the previously presented third and fourth step 22, the present paper proposes that
(besides collapse of veins 22) atherosclerosis causes reduced transport and draining causing
Pathogenesis of fatty liver disease
93
damage/necrosis to the liver. This is followed by an inflammatory response (‘traditional
inflammation’) 70, which results in repair by means of fibrosis.
HEPATIC ADAPTATION TO INCREASED FAT LOAD
Several factors may be produced and/or expressed (mRNA) in fatty livers, e.g. crystalline
inclusions 58, UCP2 58, and adiponectin 34 (table І), whereas these are usually found in
adipose tissue only. These findings may imply that the fat laden hepatocyte both
microscopically and functionally tends to resemble an adipocyte 58. This also strengthens
the hypothesis of the insulin responsive GLUT-4 being present in the case of NAFLD (in
stead of the usual GLUT-2), previously hypothesized to explain the hepatic insulin
resistance present in the case of NAFLD 12. Thus, the potential of the liver to adapt to its
environment 58 might underlie the increased CVD risk 11, 12.
LIMITATIONS OF THIS REVIEW
The studies presented in this paper include various study populations, various study
designs, and various diagnosis modalities. All these study characteristics are given in the
legend to appendix І.
Study populations and designs
Appendix І includes animal models and human populations (both healthy subjects and
patients). This could cause problems regarding ‘generalisation’ to other populations.
Appendix І includes cross-sectional and longitudinal (both prospective and retrospective)
studies. In order to determine a ‘cause-effect’, prospective longitudinal studies may be
needed.
Diagnosis modalities
The entire FLD spectrum can currently be diagnosed by histological analysis only. The first
proposal for scoring histological FLD lesions was published in 1999 95 and updated in 2005
2. Hepatic fat content (thus not inflammation and fibrosis), can be determined by imaging,
but it is important to note that low hepatic fat content can indicate absence or an early place
within the FLD spectrum, but also a progressed place within the FLD spectrum 5, 96.
Aminotransferases are produced and present in many tissues 97, 98, thus are not liver
specific, which means that elevated levels can be attributed to other than liver disease 99, 100.
Chapter 4.
94
CONCLUSION
We propose to modify current theories on the pathogenesis of FLD and to modify current
arrangements of risk factors for FLD. The present arrangement of risk factors may be useful
to identify people at high risk for FLD and to initiate interventions.
Pathogenesis of fatty liver disease
95
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(118) Shimizu I. Impact of oestrogens on the progression of liver disease. Liver Int 2003 February;23(1):63-9.
(119) Bruno S, Maisonneuve P, Castellana P, Rotmensz N, Rossi S, Maggioni M, Persico M, Colombo A, Monasterolo F, Casadei-Giunchi D, Desiderio F, Stroffolini T, Sacchini V, Decensi A, Veronesi U. Incidence and risk factors for non-alcoholic steatohepatitis: prospective study of 5408 women enrolled in Italian tamoxifen chemoprevention trial. BMJ 2005 April 23;330(7497):932.
(120) Jamerson PA. The association between acute fatty liver of pregnancy and fatty acid oxidation disorders. J Obstet Gynecol Neonatal Nurs 2005 January;34(1):87-92.
(121) Reichlin S. Neuroendocrine-immune interactions. N Engl J Med 1993 October 21;329(17):1246-53.
Appen
dix Ι.
Ris
k f
acto
rs f
or
fatty l
iver
dis
ease
, ar
ranged
in t
he
follow
ing t
hre
e ca
tegori
es:
1)
risk
fac
tors
for
hep
atic
lip
id c
onte
nt, 2
) ri
sk
fact
ors
for
inhib
ited
hep
atic
met
aboli
sm, an
d 3
) ri
sk f
acto
rs f
or
hep
atic
infl
amm
atio
n *
Cat
egory
1
Cat
egory
2
Cat
egory
3
RISK FACTORS FOR
HEPATIC
LIPID
CONTENT
RISK FACTORS FOR
INHIB
ITED H
EPATIC
METABOLISM
RISK FACTORS FOR
HEPATIC
INFLAMMATIO
N
G _ STORAGE AND
SECRETIO
N DISEASE
Storage diseases, e.g.:
Lyso
som
al a
cid lip
ase
def
icie
ncy
(W
olm
an d
isea
se o
r C
hole
ster
ol es
ter
stora
ge
dis
ease
) 53
Secretion disease, e.g.:
Hypobet
alip
opro
tein
emia
54
Storage diseases, e.g.:
Hae
moch
rom
atosi
s (I
ron a
ccum
ula
tion)
101
Storage diseases, e.g.:
Wil
son’s
dis
ease
(C
opper
acc
um
ula
tion)
102
A _ THE LIV
ER
Pathophysiology within the liver is shown in figure ІІ and
table І
Pathophysiology within the liver is shown in figure ІІ and
table І
Pathophysiology within the liver is shown in figure ІІ and
table І
B _ (LIPID
) SOURCES
AND EXERCISE
Total calorie intake
48 and lipid sources:
1. Lypolysis from peripheral fat depots
40 particularly in the
case of:
• In
suli
n r
esis
tance
• Fas
ting/r
apid
wei
ght lo
ss/s
tarv
atio
n 2
6
• U
nfa
voura
ble
body f
at d
istr
ibuti
on (
VA
T↑)
cause
d b
y e
.g.:
- L
ipoat
rophy/l
ipodyst
rophy 2
6
- C
ort
isol
103 (
stre
ss-i
nduce
d g
luco
cort
icoid
) -
Est
rogen
def
icie
ncy
(m
ale
sex 3
8, m
enopau
se 1
04 o
r T
urn
er’s
syndro
me
105)
- B
uli
mia
Ner
vosa
106
Reactive oxygen species
55
Fat depot-induced inflammation:
• In
flam
mat
ory
cyto
kin
e pro
duct
ion b
y p
erip
her
al f
at d
epots
par
ticu
larl
y in:
- U
nfa
voura
ble
body f
at d
istr
ibuti
on (
VA
T↑ a
nd S
AT
↓)
32,
37
- M
acro
phag
e in
filtra
tion in a
dip
ocy
tes,
whic
h o
ccurs
par
ticu
larl
y in V
AT
84,
85
2. Dietary carbohydrates
40 (+ DNL)
3. Dietary fat
40
Decreased physical activity 4
5-4
7
C _ SPECIF
IC TYPES O
F
NUTRIT
ION &
INTAKE
Lip
opoly
sacc
har
ides
↑ 4
2
Alcohol
57
Alc
ohol →
inte
stin
al p
erm
eabil
ity↑ 8
9 →
SIB
O/e
ndoto
xin
s/lipopoly
sacc
har
ides
↑ 8
9
Lip
opoly
sacc
har
ides
↑ 4
2
Total parenteral nutrition 2
6, 107 →
SIB
O/e
ndoto
xin
s/lipopoly
sacc
har
ides
107
Lip
opoly
sacc
har
ides
↑ 4
2
Gluten &
Celiac disease (untreated)
→ tig
ht ju
nct
ions↓
39 →
in
test
inal
per
mea
bil
ity↑ 3
9 →
SIB
O/e
ndoto
xin
s/lipopoly
sacc
har
ides
↑ 3
9
Consumption of oxidants e.g. metals 1
01, 102
Consumption of antioxidants e.g. vitamins
Toxic m
ushrooms
26
Hypoglycin (
unusu
al a
min
o a
cid)
57
Cocaine
26
E _ ENVIR
ONMENT
Several (petro)chem
icals e.g.:
• B
enze
ne,
xyle
ne,
vin
yl ch
lori
de
66
Potential P-I response
71
• N
ickel
71
Chapter 4.
106
F _ CARDIO
-VASCULAR
SYSTEM
Anti-arrhythmic dru
g:
• A
mio
dar
oneD
■ 5
7,
69
Several calcium channel blockers 26
Several anti-platelet drugs e.g.:
• A
spir
in 5
7,
69
Potential P-I response
71
F _ CENTRAL NERVOUS
SYSTEM
Several selective serotonin re-uptake inhibitors e.g.:
• A
min
epti
ne
57,
69
• T
ianep
tine
57,
69
P-I response 7
1
Non-opioid analgesics, e.g.:
• Par
acet
amol (a
ceta
min
ophen
) 69, 108
• Sev
eral
2-A
rylp
ropio
nic
aci
ds,
e.g
.:
- Ib
upro
fen 5
7, 69
Strong opioids e.g.:
• B
upre
norp
hin
e■ 6
9
Drug for control of epilepsy:
• V
alpro
ic a
cid
■ 5
7,
69
Drug for control of Parkinson e.g.:
• T
olc
apone■
69 (
cate
chol-
O-m
ethylt
ransf
eras
e in
hib
itor)
Prostaglandine synthase inhibitor
• C
elec
oxib
71
Local analgesics:
• L
idoca
in 7
1
• M
epiv
acai
n 7
1
Drugs for control of epilepsy:
• C
arbam
azep
ine
71
• L
amotr
igin
e 71
D&F _ INFECTIO
NS
HAART-induced lipodystrophy in H
IV 1
09
Several anti-H
IV drugs:
• Sev
eral
Did
eoxynucl
eosi
des
57
• Sev
eral
NR
TIs
■ 6
9, e.
g.:
- D
idan
osi
ne
26
Hepatitis drug:
• In
terf
eron a
lpha
57
Viral infections e.g.:
• H
epat
itis
, par
ticu
larl
y type
C 1
10, 111
Potential P-I response? 7
1
Lip
opoly
sacc
har
ides
↑ 4
2
Several tetracyclines (antibiotics)
57,
69
Anti-TBC e.g.:
• R
ifam
pin
& P
yra
zinam
ide
112
• M
ethotr
exat
e &
Dic
lofe
nac
113, 114
Bacterial infections e.g.:
• SIB
O 3
6,
39 +
inte
stin
al p
erm
eabil
ity↑ 3
9
• T
BC
(dru
g tre
ated
) 112-1
14
Potential P-I response 7
1
Fungal infections
Burn injury
→ infe
ctio
ns↑
D&F _ AUTOIM
MUNE
DISEASE &
MUSCULOSCELETAL/
JOIN
T DISEASE
Glucocorticoid drugs
26 (
ster
oid
horm
ones
) →
unfa
voura
ble
body f
at d
istr
ibution
Several NSAID
s e.g.:
• A
spir
in 5
7,
69
• D
iclo
fenac
69
• N
imes
uli
de
69
IBD drug:
• T
hio
puri
ne
115
Several RA drugs:
• M
ethotr
exat
e &
Dic
lofe
nac
113, 114
• E
tori
coxib
113, 114
Autoim
mune and atopic inflammatory disease e.g.:
• A
uto
imm
une
hep
atit
is 1
16
• IB
D (
dru
g tre
ated
) 115 →
inte
stin
al tig
ht
ju
nct
ions↓
39 →
inte
stin
al p
erm
eabil
ity↑ 3
9
• R
A (
dru
g tre
ated
) 113, 114
Potential P-I response? 7
1
Gout and cytotoxic-induced hyperuricaem
ia drug:
• B
enzb
rom
arone■
69
Gout
117
Potential P-I response
71
D _ SKIN
Adipose tissue inflammation e.g.:
Web
er-C
hri
stia
n s
yndro
me
26
Pathogenesis of fatty liver disease
107
F _ G
YNAECOLOGY
Pote
ntial
chan
ge
in b
ody f
at d
istr
ibuti
on
Natural
118 and synthetic 5
7 estrogens
Potential P-I response 7
1
D&F _ M
ALIG
NANT
DISEASE
Pote
ntial
chan
ge
in b
ody f
at d
istr
ibuti
on
Colorectal cancer dru
g:
• Ir
inote
can 6
9 (
topois
om
eras
e I
inhib
itor)
Potential P-I response 7
1
Several horm
one antagonists in breast cancer i.e.:
• T
amoxif
en■ 6
9,
119
• T
ore
mif
ene
69
H _ RARE SYNDROMES
ASSOCIA
TED W
ITH FLD
Reye’s syndrome
57
Acute fatty liver of pregnancy
57,
120
UNDERLYIN
G:
NERVOUS AND
ENDOCRIN
E SYSTEM
Hypothyroidism →
body f
at↑ 1
05
Overactivity of the HPA axis:
• H
yper
glu
coco
rtic
oid
ism
, e.
g. hyper
cort
icolism
26 →
unfa
voura
ble
body f
at d
istr
ibuti
on 1
05
Neuroendocrine-im
munomodulation 1
21
• In
crea
sed infl
amm
atio
n r
esponse
• D
ecre
ased
infl
amm
atio
n r
esponse
Underactivity of the HPG axis:
• D
ecre
ased
ovar
ial pro
duct
ion o
f es
trogen
s →
unfa
voura
ble
body f
at d
istr
ibution 3
8,
104
• D
ecre
ased
tes
ticu
lar
pro
duct
ion o
f te
stost
eron →
unbal
ance
bet
wee
n f
at a
nd lea
n m
ass
105
Underactivity of the HPG axis:
• D
ecre
ased
ovar
ial pro
duct
ion o
f es
trogen
s →
dec
reas
ed a
nti
-oxid
ants
118
*, th
is tab
le m
ay v
ery lik
ely b
e a
par
tial
lis
t. F
or
all dru
gs
poss
ibly
involv
ed w
ith the
inci
den
ce a
nd p
rogre
ssio
n o
f FL
D the
read
er is
refe
rred
to
the
foll
ow
ing p
aper
s: i
) dru
g-i
nduce
d m
itoch
ondri
al d
ysf
unct
ion 5
7,
69,
ii)
dru
g-
and h
erbal
-induce
d h
epat
oto
xic
ity 6
4,
iii)
dru
g-i
nduce
d
infl
amm
atio
n 7
1, iv
) en
vir
onm
enta
l to
xin
s 66, an
d v
) gen
eral
rev
iew
26.
Study population:
hum
ans
36, 38, 40, 45-4
8, 53, 54, 66, 102-1
04, 106, 108, 109, 112-1
17, 119; an
imal
model
(s)
only
73, 89.
Review papers
26, 42, 55, 57-5
9, 69, 71, 105, 107, 110, 111, 118, 120, 121.
Study design:
pro
spec
tive
40, 47, 53, 73, 89, 108, 113, 115, 116, 119; cr
oss
-sec
tional
36, 38, 39, 45, 46, 54, 102-1
04, 109, 117; re
trosp
ecti
ve
48, 66, 106, 112, 114.
FLD diagnosis modality:
his
tolo
gy 3
9,
48,
66,
102,
103;
1H
MR
S 3
8,
45,
47,
109; ult
raso
nogra
phy 4
6,
53,
54,
66,
104,
115,
117; liver
funct
ion tes
t(s)
only
40,
89,
108, 112-1
14, 116, 119.
Signs:
↑, in
crea
se; ↓, dec
reas
e; →
, le
adin
g to;
■, m
arket
ed d
rug that
has
rec
eived
a b
lack
box w
arnin
g 6
9; D, ca
use
s phosp
holi
pid
osi
s.
Abbreviations:
DN
L, de
novo lip
ogen
esis
; H
AA
RT
, hig
hly
act
ive
antire
trovir
al tre
atm
ents
; H
IV, hum
an im
munodef
icie
ncy
vir
us;
1H
MR
S,
mag
net
ic re
sonan
ce sp
ectr
osc
opy;
HP
A ax
is,
hypoth
alam
o-p
ituitar
y-a
dre
nal
ax
is;
HP
G ax
is,
hypoth
alam
o-p
ituit
ary-g
onad
al ax
is;
IBD
, in
flam
mat
ory
bow
el d
isea
se;
NR
TI,
nucl
eosi
de
rever
se t
ransc
ripta
se i
nhib
itor;
NSA
ID,
non-s
tero
idal
anti-i
nfl
amm
atory
dru
g;
P-I
com
ple
x,
phar
mag
olo
gic
al-i
nte
ract
ion co
mple
x;
PPA
Rα,
per
oxis
om
e pro
life
rato
r-ac
tivat
ed re
cepto
r al
pha;
R
A,
rheu
mat
oid
ar
thri
tis;
SIB
O,
smal
l in
test
inal
bac
teri
al o
ver
gro
wth
; T
BC
, tu
ber
culo
sis;
TN
Fα, tu
mour
nec
rosi
s fa
ctor
alpha;
VA
T, vis
cera
l ad
ipose
tis
sue.
Chapter 4.
108
Chapter 5
Ultrasonography to quantify hepatic fat content:
validation by 1H Magnetic Resonance Spectroscopy
Obesity (Silver Spring) 2009; 17(12):2239-2244
Mireille A. Edens 1
Peter M. van Ooijen 2
Wendy J. Post 1
Mark J. Haagmans 2
Wisnumurti Kristanto 2
Paul E. Sijens 2
Erik J. van der Jagt 2
Ronald P. Stolk 1
Department of Epidemiology 1
Department of Radiology 2 University Medical Center Groningen
University of Groningen Groningen, the Netherlands
Chapter 5.
110
ABSTRACT
An abundance of fat stored within the liver, or steatosis, is the beginning of a broad
hepatological spectrum, usually referred to as fatty liver disease (FLD). For studies on
FLD, quantitative hepatic fat ultrasonography would be an appealing study modality.
Objective of the present study was to developed a technique for quantifying hepatic fat
content by ultrasonography and validate this using proton magnetic resonance spectroscopy
(1H MRS) as gold standard. Eighteen White volunteers (BMI range 21.0 to 42.9) were
scanned by both ultrasonography and 1H MRS. Altered ultrasound characteristics, present
in the case of FLD, were assessed using a specially developed software program. Various
attenuation and textural based indices of FLD were extracted from ultrasound images.
Using linear regression analysis, the predictive power of several models (consisting of both
attenuation and textural based measures) on log 10-transformed hepatic fat content by 1H
MRS were investigated. The best quantitative model was compared with a qualitative
ultrasonography method, as used in clinical care. A model with four ultrasound
characteristics could modestly predict the amount of liver fat (adjusted explained variance
43.2%, p=0.021). Expanding the model to seven ultrasound characteristics increased
adjusted explained variance to 60% (p=0.015), with r=0.789 (p<0.001). Comparing this
quantitative model with qualitative ultrasonography revealed a significant advantage of the
quantitative model in predicting hepatic fat content (p<0.001). This validation study shows
that a combination of computer-assessed ultrasound measures from routine ultrasound
images can be used to quantitatively assess hepatic fat content.
Ultrasonography to quantify hepatic fat content
111
INTRODUCTION
A continuous accumulation of lipids in the liver may result in a broad hepatological
spectrum, usually referred to as fatty liver disease (FLD) 1, 2. An abundance of fat within the
liver, or steatosis, can progress to steatohepatitis (fat and inflammation, with or without
fibrosis) and cirrhosis (maximum fibrosis score) 3, and has also been associated with
hepatocarcinoma 4. Additionally, FLD, particularly non-alcoholic FLD (NAFLD), is an
underlying condition for cardiovascular disease 5, 6. As alcoholic FLD (AFLD) and NAFLD
are histologically indistinct 7, distinction between both is neither possible nor relevant in
relation to measurement of hepatic fat content. The estimated FLD prevalence is one third
of the general adult Western population 8-10, and may have been increasing in parallel with
the global increase of obesity 11.
Hepatic fat content can be determined by histological 2 or biochemical 12, 13 analysis of liver
tissue by biopsy, magnetic resonance techniques 14, computed tomography 15 and
ultrasonography 16, 17. Ultrasonography is, in contrast to other diagnostic modalities, an
appealing method for large population studies on FLD, as is it non-invasive (painless, no
harmful radiation), portable and relatively inexpensive. In the case of parenchymal liver
disease, reflections of liver tissue by ultrasonography are altered 16, 17. In clinical care,
ultrasonography is the most often used diagnostic modality, but in a qualitative way.
Steatosis can be qualitatively assessed by: i] hyperechogenity of liver tissue (‘bright liver’)
as often compared to hypoechogenity of the kidney cortex, ii] fine, tightly packed echoes,
iii] fall of echo amplitude with depth (posterior beam attenuation), iiii] loss of echoes from
the walls of the portal veins (featureless appearance) 16, 17. As this is a qualitative scoring
method and also subjective 18, quantitative approaches for identification of liver disease
have been suggested. However, these methods have never been validated by an appropriate
quantitative gold standard. The purpose of the present study was to develop and validate
quantitative analysis of ultrasonography images, for assessment of hepatic fat content, using
proton magnetic resonance spectroscopy (1H MRS) as gold standard.
Chapter 5.
112
METHODS AND PROCEDURES
VOLUNTEERS
Volunteers were recruited by advertisement, and a heterogenic study population was strived
after. Exclusion criteria were current presence of hepatic pathology, previous hepatic or
renal surgery, and standard MR-contraindications. The volunteers underwent both hepatic
ultrasonography and 1H MRS, and a short physical examination. All volunteers gave
written informed consent. This study was approved by the Medical Ethics Committee of the
University Medical Center Groningen.
ULTRASONOGRAPHY
Ultrasonography was performed using a Philips ATL ultrasound machine (Philips, Best, the
Netherlands), with a 5 – 2 MHz curved array transducer.
Quantitative ultrasonography
Imaging
In one ultrasound image both liver and right kidney were visualised 17, as shown by figure
І. Imaging was performed by an experienced radiologist. One standard image, with ‘persist’
(med), ‘2D opt’ (gen), ‘frame rate’ (high), ‘gain’ (40) and ‘image depth’ (14.7 cm), was
used for analysis.
Analysis
Images were analysed by an operator (operator 1) twice, with a one month interval, and the
average values by operator 1 were used in this study. In order to study inter-operator
reliability, another operator (operator 2) analysed the images, while untrained for the
method and blinded for all study outcomes.
Data extraction and data
Data were extracted from ultrasound images using a modified version of a specially
developed software program (dept. of BME, Technion IIT, Haifa, Israel) in the MATLAB
programming environment, previously described by Gaitini et al. 19. Figure І shows an
example of data extraction. According to a standard protocol, regions of interest and
attenuation lines were interactively placed in the liver images in order to calculate several
attenuation indices and several textural indices. Figure ІІ shows a scheme on quantitative
ultrasonography measures, including the presently validated indices in the white boxes.
Ultrasonography to quantify hepatic fat content
113
Both a region of interest (quadrangle) and an attenuation
line (closed line) were placed according to a standard
protocol.
The region of interest had to be placed in a bright area,
while avoiding large artefacts like rib shadows and large
blood vessels, at a depth of 4 to 6 cm. The attenuation line
had to be placed in a bright pathway, while avoiding large
artefacts, at a straight line from the ‘origin’ of ultrasound
(intermittent line).
The region of interest served for the determination of
several textural indices. The attenuation line was used for
determining attenuation estimates 19.
Figure І. Ultrasonography image analysis
Qualitative ultrasonography
In addition to the quantitative approach, the radiologist made an ultrasound image with
optimum settings, as used in clinical care. This image was qualitatively scored by the
radiologist, according to standard qualitative criteria 16, 17, 26, while blinded for all study
outcomes.
[b]
Texturalbased
[e]
First-order
greyscalestatistics
[k]
•Slope
• •Lenghtof line
[c]
Statisticalmethods
[f]
Second-order
greyscalestatistics
[m]
•Meangreylevel
[i]
Spatial grey level
dependence matrices
[j]
Grey level
difference matrices
[n]
•Co AngSec Mom #
•Co Correlation
•Co DiffEntropy
•Co Energy#
•Co Entropy
•Co Inertia
•Co Loc Homo
•Co SumEntropy
[o]
•DiffAngSec Mom
•DiffContrast
•DiffCovariance
•DiffEntropy
•DiffMean
&
•FP1 &
•HP1
•InvDiffMom
[a]
Attenuationbased
[h]
Linearregression
[g]
Texture feature
coding method
[p]
•TFCM Coarseness
•TFCM Code Entropy
•TFCM Code Similarity
•TFCM Homogenity*
•TFCM Meanconvergence
•TFCM Variance
Quantitative
ultrasonography
[d]
Structuralmethods
[l]
•Offset
Figure ІІ. S
chem
e an
d c
lass
ific
atio
n o
n q
uan
tita
tive
ult
raso
nogra
phy, in
cludin
g the
pre
sently v
alid
ated
mea
sure
s in
the
white
boxes
[k]
to [
p]
Mea
sure
s sh
arin
g s
uper
scri
pts
had
the
sam
e outc
om
e, *
= o
utc
om
e w
as a
lway
s 0.
For
a det
aile
d e
xpla
nat
ion o
n t
he
pre
sently v
alid
ated
quan
tita
tive
ultra
sonogra
phy
mea
sure
s 19, th
e re
ader
is
refe
rred
to the
follow
ing r
efer
ence
s: [
a] 1
9, 20, [b
] 21, [c
] 19, 21, 22, [d
] 19, 21, 22, [e
] 22, [f
] 22-2
4, [g
] 23, [h
] ap
pen
dix
І, [i
] 25, [j
] 25, [k
]and[l
] ap
pen
dix
І, [m
]
19, [n
] ap
pen
dix
ІІ,
[o]
appen
dix
ІІ,
[p]
23.
Chapter 5.
114
Ultrasonography to quantify hepatic fat content
115
MULTI-VOXEL PROTON MAGNETIC RESONANCE SPECTROSCOPY
In general, by means of radiofrequency transmission and reception, a magnetic resonance
scanner detects resonance signals of both hepatic lipids (mainly methylene, i.e. CH2, from
fatty acyl chains) and hepatic water 27. As previously described in detail 14, 28, 1H MRS was
performed, using a 1.5 Tesla whole-body scanner (MAGNETOM Avanto; Siemens
Medical Solutions, Erlangen, Germany) equipped with gradients of up to 40 mTm-1
(maximal slew rate = 200 mT m-1/ms) and a six-channel spine array coil. Subjects were in
supine position with a large flex coil placed over the liver, which was simultaneously used
with the spine array coil as receiver. T1-weighted gradient-echo images were recorded to
assess the anatomy of liver. Using a field of view of 16×16 cm2 and a volume of interest of
5×8×4 cm3 positioned within the liver, hybrid 2D-spectroscopic imaging (chemical shift
imaging or CSI), point resolved spectroscopy (PRESS) with a repetition time (TR) of 5000
ms and an echo time (TE) of 30 ms was performed. The CSI measurement lasted 16×16×5
= 1280 s, corresponding to approximately 21 min. Shimming was automated and water
suppression was not applied in order to be able to calculate the fat-water ratio distributions
in the liver directly. At the used TR of 5 s, T1 saturation of the water and fat signals is
negligible, i.e. TR > 5T1. At the used TE of 30 ms the correction applied to our data to
compensate for the fact that the fat signal has a longer T2 (78 ms) than water (60 ms) was
12.2 %. Hepatic fat content was calculated by the peak CH2 signal (at 1.3 parts/ million)
divided by the sum of the peak CH2 signal and peak H2O signal (at 4.7 parts/ million), using
water as an internal reference 14, 28. 1H MRS has been validated, by comparison with both
histological and biochemical analysis of liver tissue by biopsy 27, 29, 30.
A hepatic fat content of 5.56% by 1H MRS is used as cut-off value for diagnosing FLD,
based on the 95th percentile hepatic fat distribution of a low risk group 10.
STATISTICS
Univariate analysis and multiple regression analysis
As distribution of hepatic fat content by 1H MRS was skewed, values were log 10
transformed. Plotting and correlation (Pearson) was used to explore univariate concordance
with log 10 1H MRS. The classification of variables in figure ІІ (white boxes), followed by
‘backward selection’, was used for variable selection in a linear regression model. Firstly,
the variables from separate boxes of figure ІІ were assessed, i.e. separate ultrasonography
Chapter 5.
116
aspects. Secondly, variables from combinations of boxes of figure ІІ were assessed, i.e.
information from several ultrasonography aspects.
Evaluation and bootstrap
Models were evaluated on adjusted explained variance (adj. R2) and explained variance
(R2). By means of bootstrap, 95% confidence intervals were estimated for regression
coefficients, and adj. R2 and R2. Moreover, a 95% prediction interval was calculated.
Quantitative versus qualitative ultrasonography
The Chi-square test was used to test differences between the two methods. Additionally,
sensitivity and specificity of both methods were calculated. In addition to the 95%
prediction interval of the quantitative method, a 95% prediction interval was calculated for
the qualitative method as well.
Reliability
Both intra-observer and inter-observer reproducibility of algorithms were studied, using the
Bland & Altman method 31.
Statistical analysis was performed using software programs SPSS version 14 and R version
2.6.2.
Ultrasonography to quantify hepatic fat content
117
RESULTS
STUDY POPULATION
Twenty apparently healthy White volunteers were examined. One volunteer was excluded
because of hepatic pathology (haemangioma), and one volunteer was excluded because of
rib shadows over the liver-kidney image.
The study population (n = 18) consisted of 10 males and 8 females, with a mean ±sd age of
46.0 ±14.1 year, body mass index of 28.7 ±6.4 kg/m2 (range 21.0 to 42.9), and waist to hip
ratio of 0.93 ±0.11. Hepatic fat content by 1H MRS ranged from 0.32% – 18.55%, with a
median of 1.75%.
UNIVARIATE ANALYSIS
Plots and correlation coefficients revealed no associations. Only slope and co-entropy were
borderline significantly associated with log 10 1H MRS, with r=−0.423 (p=0.081) and
r=−0.418 (p=0.084), respectively.
MULTIPLE ANALYSIS
Information from separate ultrasonography aspects, i.e. separate boxes from figure ІІ,
revealed no associations with log 10 1H MRS (data not shown). Combining information
from different ultrasonography aspects, i.e. by combining boxes from figure ІІ, was
associated with hepatic fat content by log 10 1H MRS (model 1, table І). Including more
ultrasonography characteristics, further improved the association (model 2, table І).
Intra-operator and inter-operator reproducibility, regarding algorithm 2, are shown in figure
ІV. If we tolerate an operator difference smaller than 0.5, as shown by the interrupted lines,
5 people had a larger intra-operator difference of 0.55 to 2.66 log 10 1H MRSpred. Eleven
people had a larger inter-operant difference of 0.53 to 1.98 log 10 1H MRSpred. These
differences were independent of hepatic fat content (figure ІV).
Chapter 5.
120
a. 1st attempt by op. 1 minus 2nd attempt by op. 1
b. 1st attempt by op. 1 minus attempt by op. 2
Figure ІV. Reliability
op. = operator
Ultrasonography to quantify hepatic fat content
121
DISCUSSION
This study shows that combinations of quantitative ultrasonography measures are
significantly associated with hepatic fat content by (log 10) 1H MRS (table І), and even
better than a qualitative method currently used in clinical care (figure ІІІ). Reliability was
reasonably well (figure ІV).
These results suggest that combinations of computer-assessed ultrasonography measures
quantify the ultrasonographic characteristics of FLD 16, 17, i.e. i] hyperechogenity, by offset
in a certain degree, ii] fine, tightly packed echoes in the case of hepatic fat, and coarse pin
head echoes in the case of fibrosis, by the textural based measures, and iii] fall of echo
amplitude with depth, by slope, and by offset in lesser degree (table І).
VALIDITY
Previously, ‘slope’ 19, 20 and ‘offset’, ‘mean grey level’, ‘co entropy’ and ‘co sum entropy’
19, revealed discriminative power in the FLD spectrum. In the present study, none of the
measures were univariately associated with hepatic fat content by 1H MRS. The attenuation
based measure ‘slope’ did not significantly predict hepatic fat content, whereas the slope
previously did reveal power for discriminating pure fatty livers (steatosis) from healthy
livers, with an area under the curve of 1 19, 20. However, the slope lost discriminative power
in the total FLD spectrum 19, 20. It is known that both hepatic fat content 3, 32, 33 and
(therefore) attenuation 17 are decreased in the case of (advanced) fibrosis and cirrhosis,
which might have caused the fall in discriminative power of the slope in the total FLD
spectrum 19, 20. Fibrosis itself does not produce attenuation 34. This may also explain why, in
models, the attenuation based indices must be accompanied by textural indices of
coarseness/ fibrosis, in particular ‘co entropy’ 19, 35.
In this apparently healthy study population, we obviously did not perform hepatic biopsy
for histological scoring of fibrosis stage, nor magnetic resonance elastography (MRE),
which determines liver stiffness as a marker of fibrosis 36. Therefore, it was not possible to
verify the effect of fibrosis on ultrasonography algorithms. Additionally, because of both
inclusion of the right kidney 17 and rib shadows in ultrasound images, it was not always
possible to draw the attenuation line to the bottom of the liver for realization of a ‘far field’
slope 19, 20. However, inclusion of length of the attenuation line in models on slope did not
Chapter 5.
122
lead to an improvement in the prediction of hepatic fat content by 1H MRS (data not
shown). Adjusting for focus depth and frequency was not possible, because of the small
ranges.
A limitation of the present study is the small study population (n = 18), however, bootstrap
of model 2 revealed good 95% confidence intervals (table І). Additionally, model 1 with
only 4 variables already showed significant results.
Because the performance of a test depends on the prevalence of an underlying disorder, e.g.
FLD, the sensitivity of quantitative ultrasonography may be lower in a clinical population.
RELIABILITY
Intra-operator difference was reasonably well, but inter-operator difference was less (figure
ІV). This may be explained by operator 1 being experienced, while operator 2 was not.
Retrospective analysis of the outliers from figure ІV (print screens’ of analysed images
were saved), revealed insight in the differences in analysis.
FUTURE RESEARCH
While histological scoring of liver tissue by biopsy is often considered the gold standard for
diagnosis of FLD, 1H MRS is more reliable, and may be more valid for quantification of
hepatic fat content. Reproducibility of qualitative histological analysis regarding steatosis
grade is good as weighted kappa scores range from 0.64 to 0.90 2, 37, whereas
reproducibility regarding hepatic fat content by 1H MRS is excellent with reported
correlation coefficients of up to 0.99 (p<0.001) 10. For future studies, 1H MRS combined
with MRE 36 would be an interesting gold standard.
CONCLUSION
This is the first in vivo validation study on quantitative hepatic fat ultrasonography, using
an excellent quantitative gold standard, i.e. multi-voxel 1H MRS 14, 28. Therefore, we feel
that the method needs to be improved before used as clinical diagnosis modality.
This validation study shows that a combination of computer-assessed ultrasound measures
from routine ultrasound images can be used to quantitatively assess hepatic fat content.
Reliability should be improved by more protocolized procedures and training of operators.
Please also see ‘additional remarks and recommendations for future research’
Ultrasonography to quantify hepatic fat content
123
ACKNOWLEDGEMENTS
The authors thank dr. H Azhari, who enabled this study by sharing the software program,
developed by the Department of Biomedical Engineering, Technion Israel Institute of
Technology, Haifa, Israel 19.
The authors thank I Willeboordse, AM van Tienhoven, JH Potze, and P Kappert for
magnetic resonance scanning.
Chapter 5.
124
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(37) Merriman RB, Ferrell LD, Patti MG, Weston SR, Pabst MS, Aouizerat BE, Bass NM. Correlation of paired liver biopsies in morbidly obese patients with suspected nonalcoholic fatty liver disease. Hepatology 2006 October;44(4):874-80.
Chapter 5.
128
Online Appendix І. Realization of attenuation based indices
0 ,6 5
0 ,7 5
0 ,8 5
0 ,9 5
1 ,0 5
1 ,1 5
0 1 2 3 4 5
Depth →
Grey level →
Slope
Offset
Schematic display of offset and slope realization
Along the attenuation line (figure І), each pixel was automatically
selected.
For each pixel under the line, the grey level value was averaged with the
grey level values of 3 pixels to the left and 3 pixels to the right
horizontally, and stored together with depth information. A linear
regression line was applied, using the least-squares approximation, and
its corresponding slope (grey level units/ mm) and offset (grey level)
were generated 19.
Additionally, the length of the attenuation line (number of pixels) was
generated.
Ultrasonography to quantify hepatic fat content
129
Online Appendix ІІ. Realization of textural based indices
Indices of the spatial grey level dependence matrix 19, 21, 22, 24, 25, 35_ The aim of co-occurrence features is to capture
texture characteristics, i.e. heterogeneity. Elements of the co-occurrence matrix (algorithm [1]) designate the
probability that two pixels located within a region, separated by distance d along direction θ , have grey level
values of i and j:
Co-occurrence: ( ) ( ) ( )( ) ( ) ( )( ) [ ]yxd
LLnmlknmlk
djiP ,,,,,,,
,, ∈Ν
Ν=|
θθ , [1]
where θ = 0º and d = 4 pixels 19, θdΝ is the number of pixel pairs, and Ν is the number of grey level
transitions, in a region (Lx, Ly).
• Co-occurrence entropy: ( ) ( )( ) ,|,log, |,1
0
1
0
θθ djiPdjiPGG
ji
∑∑−Ν
=
−Ν
=
⋅ , [2]
• Co-occurrence sum entropy: ( ) ( )( )∑ ⋅k
sumsum kPkP log , [3]
where ( ) ( )θ,|,1
0
1
0
djiPkPGG
ji
sum ∑∑−Ν
=
−Ν
=
= for i + j = k.
Indices of the grey level difference matrix 22, 24, 25_ The aim of difference features is to capture texture
characteristics, i.e. homogeneity. Elements of the difference matrix (algorithm [4]) designate the probability that
after a displacement along vector δ within a region, pixels will have grey level value i:
where ( )yx ∆∆= ,δ and ( ) ( ) ( ) |,-yx,|, yyxxIIyxI ∆+∆+=δ , in a region (Lx, Ly).
• Difference contrast: ( )δ|'1
0
2if
G
ii∑
−Ν
=
[5]
• Inverse difference moment: ( )
∑−Ν
= +
1
02
1
|'G
i i
if δ [6]
• FP1:
MN
yxIM
x
N
y
∑∑= =1 1
),(δ
, where M and N are column and row, respectively. [7]
130
131
Chapter 6
Assessment of the variations in fat content in
normal liver using a fast MR Imaging method in
comparison with results obtained by Spectroscopic
Imaging
Eur Radiol 2008; 18(4):806-813.
Roy Irwan 1
Mireille A. Edens 2
Paul E. Sijens 1
Department of Radiology 1 Department of Epidemiology 2
University Medical Center Groningen University of Groningen
Groningen, the Netherlands
Chapter 6.
132
ABSTRACT
A recently published Dixon-based MRI method for quantifying liver fat content using dual-
echo breath-hold gradient echo imaging was validated by phantom experiments and
compared with results of biopsy in two patients [Radiology 2005;237:1048-1055] 1. We
applied this method in ten healthy volunteers and compared the outcomes with the results
of MR spectroscopy (1H MRS), the gold standard in quantifying liver fat content. Novel
was the use of spectroscopic imaging yielding the variations in fat content across the liver
rather than a single value obtained by single voxel 1H MRS. Compared with results of 1H
MRS, liver fat content according to MRI was too high in nine subjects (range 3.3-10.7% vs.
0.9-7.7%) and correct in one (21.1 vs. 21.3%). Furthermore, in one of the ten subjects the
MRI fat content according to the Dixon-based MRI method was incorrect due to a (100-x)
versus x percent lipid content mix-up. The second problem was fixed by a minor
adjustment of the MRI algorithm. Despite systematic overestimation of liver fat contents by
MRI, Spearman's correlation between the adjusted MRI liver fat contents with 1H MRS was
high (r = 0.927, P < 0.001). Even after correction of the algorithm, the problem remaining
with the Dixon-based MRI method for the assessment of liver fat content, is that, at the
lower end range, liver fat content is systematically overestimated by 4%.
MRI to quantify hepatic fat content
133
INTRODUCTION
Substantial accumulation of fat in the liver (steatosis) can progress into steatohepatitis and
cirrhosis, a spectrum range called fatty liver disease 2, 3. In the general adult Western
population, the prevalence of fatty liver disease (alcoholic plus non-alcoholic) ranges from
30% to 34% 4-6. Evidence of non-alcoholic fatty liver disease (NAFLD) being an early
marker of cardiovascular disease is increasing, and the condition might even be an early
mediator in cardiovascular disease 7. Additionally, an accurate knowledge of liver fat
content can be important in case surgeons want to make sure that steatosis in donor livers
does not exceed 20% 8.
The quantification of liver fat fraction using magnetic resonance imaging (MRI) has gained
attention in the last decade 1, 9, 10, as ultrasound imaging is not considered to be a
sufficiently quantitative tool and computed tomography leads to undesired radiation
exposure in examinations in patients who may have no complications from their fatty liver
11. Among the existing MRI methods for quantifying liver fat content, the recently
presented adaptation of the two-point Dixon method using in-phase (IP) and out-phase (OP)
images, appears accurate 1. However, this fast method for quantifying liver fat content by
the dual-echo breath-hold gradient echo imaging method has not yet been validated in vivo,
apart from being compared with the results of histology in two patients 1. We used 1H-
Magnetic Resonance Spectroscopy (1H MRS), a more time consuming method allowing for
direct quantification of water and fat signals in a selected volume of interest. 1H MRS is
considered to be the gold standard for liver fat quantification in vivo 12 and has recently
been improved by implementing multi-voxel rather than single-voxel measurements 13.
In this study we aimed to compare the above mentioned fast MRI method for quantifying
liver fat content 1 with the results of multi-voxel 1H MRS, obtained in ten healthy
volunteers. Novel is the assessment of the variations in fat content across the liver by
spectroscopic imaging acquisition of a plane of voxels, yielding a plane of water-to-fat
ratios indicative of the heterogeneity in liver fat distributions, rather than using single voxel
1H MRS for sampling a small single volume. In the process, we found a limitation in the
algorithm proposed for estimating fat content causing an invalid value in one of our
volunteers. We propose a simple modification in the algorithm to deal with this problem
Chapter 6.
134
and show that the results of MRI, while correlating well with those of 1H MRS,
systematically overestimate liver fat content in the lower end range.
Figure І. Transverse T1-weighted MR
image of volunteer 9, showing a field of
view of 16×16 cm2 and a volume of interest
(VOI) of 5×8×4 cm3 positioned inside the
liver (the measurements were restricted to
the 32 entire voxels within the blue line).
Figure ІІ. Example of a ROI which was
drawn on both intermediate weighted and
T1-weighted dual-echo image pairs
matching to the whole VOI of the CSI (the
same volunteer as figure І).
Figure ІІІ. Spectral map showing water and fat peaks in the 32 quantified voxels in the
same volunteer as figures І and ІІ.
MRI to quantify hepatic fat content
135
MATERIALS AND METHODS
VOLUNTEER STUDY
Studies were conducted on ten healthy volunteers (all males; mean age = 47 years; range:
22 – 58 years). The Body Mass Index of the volunteers ranged from 20 to 33.5 kg/m2 with a
mean value of 26.4 kg/m2. The studies were performed with informed consent and medical
ethical committee approval.
All volunteers were examined by MRI and 1H MRS in one measurement session, using a
1.5 Tesla whole-body scanner (MAGNETOM Avanto; Siemens Medical Solutions,
Erlangen, Germany) equipped with high performance gradients (maximal gradient strength
= 40 mTm-1; maximal slew rate = 200 mT m-1/ms) and a six-channel spine array coil in the
supine position with the spine along the symmetry axis of the coil system. In both MRI and
1H MRS a large flex coil placed over the liver was used simultaneously with the spine array
coil as receiver. To assess the anatomy of the liver, T1-weighted gradient-echo images were
recorded.
MR IMAGING
MRI of the liver was performed by using a breath-hold dual-echo T1 weighted gradient
echo sequence with a 6 mm slice thickness, section gap 0 mm, matrix 256x160 and a
repetition time (TR) of 155 ms. Dual-echo spoiled gradient recalled images were acquired
with TE = 2.4 ms (OP) and TE = 4.8 ms (IP) and flip angles of 70o and 20o to generate T1-
weighted and intermediate-weighted images, respectively. These images were corrected for
T2* decay using
*2Tcorrected eSS
τ
= (equation 1)
where τ is the echo time difference between IP and OP images, and S represents the signal
intensity in a defined region of interest (ROI) 1. Under these conditions τ = 2.4 ms
combined with T2* = 19.44, calculated from the mean spectral line width of the water peak
in human liver measured by 1H MRS in the ten volunteers (details are given in a next
paragraph), gave a correction factor of 1.13 for Sip relative to Sop.
Chapter 6.
136
The published algorithm for estimating fat content by Hussain et al. 1 consists of the
following three steps:
(step 1) adjustment for T2* relaxation using equation 1.
(step 2) calculation of the apparent fat content using the following equation:
( )%100
2% ×
−=
IP
OPIP
S
SSfat
(equation 2)
for both intermediate or hydrogen density weighted (%fatHwt at 20o flip angle)
and T1-weighted (%fatT1wt at 70o flip angle) image pairs.
(step 3) if %fatHwt ≤ %fatT1wt, then %fat = %fatHwt; otherwise, %fat = 100% - %fatHwt
In this study we propose to modify the third step in the Hussain algorithm for estimating fat
content to:
(step 3corrected) if fatHwt AND %fatT1wt ≤ 20%, then %fat = MIN[%fatHwt, %fatT1wt],
if fatHwt AND %fatT1wt > 20% and %fatHwt ≤ %fatT1wt, then %fat = %fatHwt,
otherwise, %fat = 100% - %fatHwt,
where AND is a logical operator, and MIN[a, b] is a mathematical
operator computing the minimum value between a and b.
MR SPECTROSCOPY
The flex large and spine coils used for MRI were also used for 1H MRS. The subjects were
scanned in the supine position. Movement of the liver with breathing was not suppressed as
in the past we have shown that the quality of liver MR spectra is not affected by this 13.
Hybrid 2D-spectroscopic imaging (chemical shift imaging, CSI) 14, point resolved
spectroscopy (PRESS) with a repetition time (TR) of 5000 ms and an echo time (TE) of 30
ms, was performed using a field of view of 16×16 cm2 and a volume of interest of 5×8×4
cm3 positioned inside the liver (figure І). The CSI measurement lasted 16×16×5 = 1280 s or
approximately 21 min. Shimming was automated and water suppression was not applied in
order to be able to calculate the fat-water ratio distributions in the liver directly.
MRI to quantify hepatic fat content
137
The water-fat analysis was restricted to the transverse plane of 4×8 = 32 entire voxels. Fat
to water ratios, were defined as usual 6, 12, 15-17. The ratio of the curve fitted -CH2- lipid
signal peak area (1.3 ppm) divided by the sum of the same lipid signal and that of H2O (4.7
ppm), is equal to the weight fat/(fat+water) ratio because the relative hydrogen contents of
water and fat are very similar (approximately 11%) 12, 15. The obvious variation of B1
sensitivity over the CSI field affected the water and lipid signals similar, and therefore was
not influencing the
1H MRS results expressed in water-to-fat ratio plus (inter-voxel) standard deviation. Using
standard postprocessing-software provided by the manufacturer, the water and fat peak
areas of all 32 voxels were fitted in the frequency domain with assumption of Lorentzian
line shapes preceded by phase correction and, occasionally, adjustment of the base line.
Determination of the fat contents for each of the above mentioned 32 1H MRS voxels thus
led to estimates of the mean value and heterogeneity (standard deviation) in the liver fat
content of the volunteers. At the used TR of 5 s, T1 saturation of the water and fat signals is
negligible, that is TR > 5T1 12, and at the used TE of 30 ms the correction applied to our
data to compensate for the fact that the fat signal has a longer T2 (78 ms) than water (60 ms)
was 12.2 % 15. The CSI series lasted approximately 21 minutes as compared with less than
5 minutes required for the two series yielding the four sets of images used for liver fat
quantification.
The T2* used for correcting Sip in the above mentioned MRI algorithm, was calculated from
the CSI spectral maps by fitting the line widths of the liver water signals of 16 voxels from
the centers of the volumes of interest to obtain a mean water line width for every subject.
The mean water line width (∆ν) for the group of 10 was 17.05 ± 3.74 Hz.
νπ ∆⋅=
1*2T
(equation 3)
Using equation 3, a mean T2* of 19.4 ± 4.1 ms, was calculated. This value was used for
correcting all MRI fat contents of Table 1. As a double check we also used a gradient-
recalled echo sequence with two IP echoes (4.5 and 18 ms) in analogy to a method applied
by Hussain et al. 1, obtained similar mean T2* values in the ten volunteers (20 ± 3 ms).
Chapter 6.
138
DATA PROCESSING
To co-register the 1H MRS data to the MR images, the coordinates of the anterior right
(AR) and posterior left (PL) at the same height position were used as regional checkpoints.
These coordinates can be determined from the Siemens viewing workstation. Figure І
illustrates a T1-weighted image overlaid by CSI voxels with the starting voxel in the upper
left corner of the blue VOI (i.e. right anterior in the liver) matching the first quantified 1H
MRS voxel. Once the AR and PL were defined, an ROI was drawn on both intermediate
weighted and T1-weighted dual-echo image pairs, as demonstrated in figure ІІ.
Statistical Analysis
Measured MRI data were imported in an Excel Spreadsheet presented as mean ± standard
deviation (SD) of 7 slices. The value for each slice was obtained by averaging 4 samples
per dual-echo image pair. The distributions of the obtained liver fat contents were not
normal, so non-parametric correlations with 1H MRS determined liver fat content were
evaluated by assessment of Spearman's correlation coefficient (with 2-tailed testing of
significance). Note that the standard deviations in the MRI data reflect the spread
(heterogeneity) amongst the seven MRI slice sections contained in the 8x4x4 cm3 1H MRS-
analysis volume of interest, whereas the standard deviations in the 1H MRS determined
liver fat contents reflect the spread amongst 32 1H MRS voxel subvolumes of 1x1x4 cm3.
Automated matching of the 7 summarized MRI slices to the dimensions of the 1H MRS
voxels to obtain the IP and OP values for each 1H MRS voxel was unfortunately not
available for use with the Avanto MRI system. It was therefore not possible to obtain MRI
and 1H MRS standard deviations for the same sets of VOI subvolumes or assess the
MRI/1H MRS correlations for all 320 evaluated voxels rather than for the 10 averaged sets
of results per subject.
MRI to quantify hepatic fat content
139
Table І. MRI fat measurements (means ± SD of 7 slices; T2* corrected) according to the intermediate and T1 weighted gradient echo sequences, Hussain’s algorithm 1, our corrected algorithm and the gold standard 1H MRS (mean ± SD of 32 voxels; T2 corrected). Results shown in ascending order of 1H MRS measurements.
(2) Adams LA, Sanderson S, Lindor KD, Angulo P. The histological course of nonalcoholic fatty liver disease: a longitudinal study of 103 patients with sequential liver biopsies. J Hepatol 2005 January;42(1):132-8.
(3) Dam-Larsen S, Franzmann MB, Christoffersen P, Larsen K, Becker U, Bendtsen F. Histological characteristics and prognosis in patients with fatty liver. Scand J
Gastroenterol 2005 April;40(4):460-7.
(4) Volzke H, Robinson DM, Kleine V, Deutscher R, Hoffmann W, Ludemann J, Schminke U, Kessler C, John U. Hepatic steatosis is associated with an increased risk of carotid atherosclerosis. World J Gastroenterol 2005 March 28;11(12):1848-53.
(5) Browning JD, Szczepaniak LS, Dobbins R, Nuremberg P, Horton JD, Cohen JC, Grundy SM, Hobbs HH. Prevalence of hepatic steatosis in an urban population in the United States: impact of ethnicity. Hepatology 2004 December;40(6):1387-95.
(6) Szczepaniak LS, Nurenberg P, Leonard D, Browning JD, Reingold JS, Grundy S, Hobbs HH, Dobbins RL. Magnetic resonance spectroscopy to measure hepatic triglyceride content: prevalence of hepatic steatosis in the general population. Am
(7) Targher G, Bertolini L, Padovani R, Zenari L, Zoppini G, Falezza G. Relation of nonalcoholic hepatic steatosis to early carotid atherosclerosis in healthy men: role of visceral fat accumulation. Diabetes Care 2004 October;27(10):2498-500.
(8) Kim SH, Lee JM, Han JK, Lee JY, Lee KH, Han CJ, Jo JY, Yi NJ, Suh KS, Shin KS, Jo SY, Choi BI. Hepatic macrosteatosis: predicting appropriateness of liver donation by using MR imaging--correlation with histopathologic findings. Radiology 2006 July;240(1):116-29.
(9) Kawamitsu H, Kaji Y, Ohara T, Sugimura K. Feasibility of quantitative intrahepatic lipid imaging applied to the magnetic resonance dual gradient echo sequence. Magn Reson Med Sci 2003 April 1;2(1):47-50.
(10) Machann J, Thamer C, Schnoedt B, Stefan N, Haring HU, Claussen CD, Fritsche A, Schick F. Hepatic lipid accumulation in healthy subjects: a comparative study using spectral fat-selective MRI and volume-localized 1H-MR spectroscopy. Magn Reson Med 2006 April;55(4):913-7.
Chapter 6.
148
(11) Valls C, Iannacconne R, Alba E, Murakami T, Hori M, Passariello R, Vilgrain V. Fat in the liver: diagnosis and characterization. Eur Radiol 2006 October;16(10):2292-308.
(12) Thomsen C, Becker U, Winkler K, Christoffersen P, Jensen M, Henriksen O. Quantification of liver fat using magnetic resonance spectroscopy. Magn Reson
Imaging 1994;12(3):487-95.
(13) Sijens PE, Smit GP, Borgdorff MA, Kappert P, Oudkerk M. Multiple voxel (1)H MR spectroscopy of phosphorylase-b kinase deficient patients (GSD IXa) showing an accumulation of fat in the liver that resolves with aging. J Hepatol 2006 December;45(6):851-5.
(14) Sijens PE, van den Bent MJ, Nowak PJ, van Dijk P, Oudkerk M. 1H chemical shift imaging reveals loss of brain tumor choline signal after administration of Gd-contrast. Magn Reson Med 1997 February;37(2):222-5.
(15) Longo R, Ricci C, Masutti F, Vidimari R, Croce LS, Bercich L, Tiribelli C, Dalla Palma L. Fatty infiltration of the liver. Quantification by 1H localized magnetic resonance spectroscopy and comparison with computed tomography. Invest Radiol 1993 April;28(4):297-302.
(16) Tiikkainen M, Bergholm R, Vehkavaara S, Rissanen A, Hakkinen AM, Tamminen M, Teramo K, Yki-Jarvinen H. Effects of identical weight loss on body composition and features of insulin resistance in obese women with high and low liver fat content. Diabetes 2003 March;52(3):701-7.
(17) Adiels M, Taskinen MR, Packard C, Caslake MJ, Soro-Paavonen A, Westerbacka J, Vehkavaara S, Hakkinen A, Olofsson SO, Yki-Jarvinen H, Boren J. Overproduction of large VLDL particles is driven by increased liver fat content in man. Diabetologia 2006 April;49(4):755-65.
(18) Biglands JD, Wilson D, Ward J, Treanor D, Gurthry A, Nijhawan A, Smith J, Wyatt J, Robinson P. Comparison of MRI and histopathalogic methods of quantifying hepatic fat fraction. In Proc Intl Soc Magn Reson Med , May 19-25,
2007, Berlin p2703 2007.
(19) Cotler SJ, Guzman G, Layden-Almer J, Mazzone T, Layden TJ, Zhou XJ. Measurement of liver fat content using selective saturation at 3.0 T. J Magn Reson
Imaging 2007 April;25(4):743-8.
Chapter 7
MRI determined fat content of human liver,
pancreas and kidney
World J Gastroenterol 2010; 16(16):1993-1998.
Paul E. Sijens 1
Mireille A. Edens 2
Stephan J. Bakker 3
Ronald P. Stolk 2
Department of Radiology 1
Department of Epidemiology 2 Department of Internal Medicine 3
University Medical Center Groningen University of Groningen
Groningen, the Netherlands
Chapter 7.
150
ABSTRACT
Aim: To assess and correlate the lipid contents of various organs in obese subjects and in
persons with a normal body weight.
Methods: Magnetic resonance spectroscopy and a previously validated gradient echo
magnetic resonance imaging method with Dixon’s two point technique were used in this
study to quantify fat in liver, pancreas as well as kidney.
Results: In 36 volunteers with body mass index (BMI) ranging from 20.0 to 42.9 kg/m² the
median fat contents of liver, pancreas and kidney were 2.3% (interquartile range: 0.2%-
7.8%), 2.7% (1.0%-6.5%) and 0.7%(0.1%-1.4%), respectively. BMI and subcutaneous fat
correlated significantly with liver and pancreas fat contents. Shown for the first time is
significant correlation of the liver and pancreas fat contents in healthy controls (r = 0.43, P
< 0.01). These observations are related to body weight as measured by BMI and the amount
of subcutaneous fat. Kidney fat content is very low and correlates with none of the other fat
depots.
Conclusion: Renal lipid accumulation, unlike the coupled accumulations of fat in liver and
pancreas, is not observed in obese subjects. Unlike what has been suggested in previous
studies, renal lipid accumulation appears not to be involved in the pathogenesis of renal
disease in humans.
MRI-determined fat content of human tissues
151
INTRODUCTION
Storage of fat within the peritoneal cavity (visceral fat) and within other tissues (ectopic fat)
rather than in subcutaneous adipocytes, is accompanied by adverse metabolic and lipotoxic
effects 1, 2. Both visceral fat 1 and liver fat 3 are known for secreting numerous atherogenic
factors into the blood system, e.g. lipids and inflammatory cytokines, predisposing to
The healthy volunteers, who varied in body weight from lean to obese, had kidney fat
contents that were comparatively low and showed little variation between subjects. In the
kidney fat content correlated with none of the other fat depots, indicating that in otherwise
healthy subjects obesity does not affect kidney fat content. In other words, renal lipid
accumulation, unlike the accumulation of fat in liver and pancreas, is not observed in obese
healthy subjects.
In this study we used a previously validated gradient echo MRI method 17 for determining
the fat contents in liver pancreas and kidney. In our liver measurements we compared the
MR spectroscopy results in the thirty-six volunteers with the MRI liver contents to refine
the correction equation needed to adapt the MRI method for quantitative use. That is, we
determined the coefficient of correlation between the two-point Dixon-based MRI method
and the 1H MRS results in liver and used the result to correct all MRI data for systematic
overestimation at the lower end range, a phenomenon also observed by others 24 and most
probably related to Rician-noise distribution related overestimation of the magnitude
images of weak fat signals. Thus we have used our liver data for correcting all MRI data
based on the assumption that the MRI method works out the same for liver and other organs
(pancreas, kidney). This is the best one can do, considering that 1) 1H MRS examinations of
small fat embedded organs are inaccurate and that 2) it is no option to collect tissue
biopsies from healthy volunteers. Furthermore, as stated in Materials and Methods, control
experiments had made sure that with the radiofrequency coils used the MRI signal
intensities in positions corresponding with those of liver, pancreas and kidney corresponded
to the same fat contents.
Renal lipotoxicity and its role in the pathogenesis of renal disease are not fully understood 4,
5. It has been assumed that renal disease progression is promoted by the accumulation of
lipids in the kidneys, a phenomenon in which triglyceride-rich lipoproteins, free fatty acids
and their metabolites, and albumin-loaded free fatty acids appear to be involved.
Quantitative documentation of the content of fat in human kidneys in situ appears not to
exist, so we cannot compare our MRI-determined kidney fat contents to literature data. In a
bovine growth hormone transgenic mouse line, kidney triglycerides, while lower than those
found in liver, recently showed a similar trend of reduced levels as compared with non
Chapter 7.
160
transgenic littermate controls showing overall fat mass increases 25. In rats, also, steatosis of
the kidney was recently associated with an alteration in renal acidification 12. The fat
accumulated in the renal cortex as shown quantitatively by enzymatic triglyceride
measurement and qualitatively by oil red O staining 12. That fitted the notion that, within
the cortex, the proximal tubule is vulnerable to lipid accumulation due to its role in the
reabsorption of free fatty acids bearing albumin 13, 14. Our result in humans, the finding of
very low fat contents (up to 2%) in the cortex of kidneys of both lean and obese individuals,
is not in line with the findings in the above experimental studies.
Our observation of significant correlation between the liver and pancreas fat contents
according to MRI (r = 0.43; P < 0.01) also is in disagreement with a recent study of a
smaller number of volunteers than included by us (17 versus 36) 10, and with another small
study (n = 15) in which the existence of significant correlation between liver and pancreas
fat content is not mentioned 8. The small scale of both earlier studies in humans probably
explains their failure to demonstrate the correlation between the fat contents in liver and
pancreas. The presence of such a correlation does fit a previous demonstration that obese
nondiabetic subjects have increased fat in the pancreas 8. It is also in line with a notion that
lipomatosis of the pancreas reflect early events in the pathogenesis of diabetes 9, conform
what has been shown in numerous publications dealing with the fattening of the liver.
The significant correlations of BMI with both liver and pancreas fat content in this study
are in agreement with a previous report 8. Why would obese subjects tend to accumulate fat
in liver and pancreas and not in the kidney, despite the observation that obesity and the
metabolic syndrome are involved with initiation of chronic kidney disease 4? It seems that
due to specific requirements such as albumin loading needed to facilitate the uptake of fat
into kidney tissue, obese but otherwise healthy subjects do not accumulate fat in the
kidneys.
In conclusion, this is the first demonstration of the use of a MRI method for determining
kidney fat content. Observed for the first time are significantly correlated liver and pancreas
fat contents in (otherwise) healthy persons varying in body weight from lean to obese.
These observations are related to body weight as measured by BMI and the amount of
subcutaneous fat. The amount of fat in the kidney in obese persons is small and not related
to the amount of body fat or the fat content of liver and pancreas. We have thus shown that
in obesity, the first step in the pathogenesis of renal disease, lipid is not accumulated in the
MRI-determined fat content of human tissues
161
kidney. Therefore the role of lipid accumulation in the pathogenesis of renal disease,
diabetes and metabolic disease in humans should be reconsidered. That is not to say that fat
metabolites rather than the triglyceride levels detected here by MRI, may have profound
effects. In future studies we propose to examine patients suffering from the above illnesses
in order to validate our current hypothesis that the lipid content is always low in the
kidneys.
Chapter 7.
162
Reference List (1) Snijder MB, van Dam RM, Visser M, Seidell JC. What aspects of body fat are
particularly hazardous and how do we measure them? Int J Epidemiol 2006 February;35(1):83-92.
(2) Unger RH. Minireview: weapons of lean body mass destruction: the role of ectopic lipids in the metabolic syndrome. Endocrinology 2003 December;144(12):5159-65.
(3) Kotronen A, Yki-Jarvinen H. Fatty liver: a novel component of the metabolic syndrome. Arterioscler Thromb Vasc Biol 2008 January;28(1):27-38.
(4) Wahba IM, Mak RH. Obesity and obesity-initiated metabolic syndrome: mechanistic links to chronic kidney disease. Clin J Am Soc Nephrol 2007 May;2(3):550-62.
(5) Weinberg JM. Lipotoxicity. Kidney Int 2006 November;70(9):1560-6.
(6) Clark JM, Diehl AM. Nonalcoholic fatty liver disease: an underrecognized cause of cryptogenic cirrhosis. JAMA 2003 June 11;289(22):3000-4.
(8) Kovanlikaya A, Mittelman SD, Ward A, Geffner ME, Dorey F, Gilsanz V. Obesity and fat quantification in lean tissues using three-point Dixon MR imaging. Pediatr Radiol 2005 June;35(6):601-7.
(9) Raeder H, Haldorsen IS, Ersland L, Gruner R, Taxt T, Sovik O, Molven A, Njolstad PR. Pancreatic lipomatosis is a structural marker in nondiabetic children with mutations in carboxyl-ester lipase. Diabetes 2007 February;56(2):444-9.
(10) Schwenzer NF, Machann J, Martirosian P, Stefan N, Schraml C, Fritsche A, Claussen CD, Schick F. Quantification of pancreatic lipomatosis and liver steatosis by MRI: comparison of in/opposed-phase and spectral-spatial excitation techniques. Invest Radiol 2008 May;43(5):330-7.
(11) Sinha S, Misra A, Rathi M, Kumar V, Pandey RM, Luthra K, Jagannathan NR. Proton magnetic resonance spectroscopy and biochemical investigation of type 2 diabetes mellitus in Asian Indians: observation of high muscle lipids and C-reactive protein levels. Magn Reson Imaging 2009 January;27(1):94-100.
(12) Bobulescu IA, Dubree M, Zhang J, McLeroy P, Moe OW. Effect of renal lipid accumulation on proximal tubule Na+/H+ exchange and ammonium secretion. Am
(13) Gekle M. Renal tubule albumin transport. Annu Rev Physiol 2005;67:573-94.
(14) Riazi S, Khan O, Tiwari S, Hu X, Ecelbarger CA. Rosiglitazone regulates ENaC and Na-K-2Cl cotransporter (NKCC2) abundance in the obese Zucker rat. Am J
Nephrol 2006;26(3):245-57.
(15) Sijens PE. Parametric exploration of the liver by magnetic resonance methods. European Radiology 2009;19(11):2594-607.
(16) Edens MA, van Ooijen PM, Post WJ, Haagmans MJ, Kristanto W, Sijens PE, van der Jagt EJ, Stolk RP. Ultrasonography to quantify hepatic fat content: validation by 1H magnetic resonance spectroscopy. Obesity (Silver Spring) 2009 December;17(12):2239-44.
(17) Irwan R, Edens MA, Sijens PE. Assessment of the variations in fat content in normal liver using a fast MR imaging method in comparison with results obtained by spectroscopic imaging. Eur Radiol 2008 April;18(4):806-13.
(20) Sijens PE, Smit GP, Borgdorff MA, Kappert P, Oudkerk M. Multiple voxel (1)H MR spectroscopy of phosphorylase-b kinase deficient patients (GSD IXa) showing an accumulation of fat in the liver that resolves with aging. J Hepatol 2006 December;45(6):851-5.
(21) Longo R, Ricci C, Masutti F, Vidimari R, Croce LS, Bercich L, Tiribelli C, Dalla Palma L. Fatty infiltration of the liver. Quantification by 1H localized magnetic resonance spectroscopy and comparison with computed tomography. Invest Radiol 1993 April;28(4):297-302.
(22) Thomsen C, Becker U, Winkler K, Christoffersen P, Jensen M, Henriksen O. Quantification of liver fat using magnetic resonance spectroscopy. Magn Reson
Imaging 1994;12(3):487-95.
(23) Fishbein MH, Mogren C, Gleason T, Stevens WR. Relationship of hepatic steatosis to adipose tissue distribution in pediatric nonalcoholic fatty liver disease. J Pediatr Gastroenterol Nutr 2006 January;42(1):83-8.
(24) Kim H, Taksali SE, Dufour S, Befroy D, Goodman TR, Petersen KF, Shulman GI, Caprio S, Constable RT. Comparative MR study of hepatic fat quantification using
Chapter 7.
164
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Chapter 8.1: General discussion - part 1
Evidence on screening for fatty liver disease: Future perspectives
Submitted/ under review _ Review Paper
Mireille A. Edens
Ronald P. Stolk
Department of Epidemiology
University Medical Center Groningen University of Groningen
Groningen, the Netherlands
Chapter 8.1: General discussion - part 1.
166
ABSTRACT
Background and Aim Fatty liver disease (FLD) is currently (one of) the most prevalent
hepatic condition(s) worldwide and likely increasing. Since FLD initially gives no clinical
symptoms, but does increase morbidity risk, screening could be useful. The aim of this
paper is to discuss if screening for FLD would be effective.
Methods The world health organisation screening criteria, organised into the categories:
‘condition’, ‘diagnosis’, ‘treatment’, and ‘cost’ & ‘screening program’, are discussed.
Results FLD is associated with increased risk for severe liver pathology (cirrhosis and
hepatocellular carcinoma) and cardiovascular pathology (components of the metabolic
syndrome). Compared to reference populations, survival of both patients with non-alcoholic
FLD (NAFLD; including both steatosis and steatohepatitis) and patients with non-alcoholic
steatohepatitis (NASH) is reduced. Moreover, both liver-related mortality and
cardiovascular-related mortality are increased. An estimated 8.3% of patients with NAS
will develop fibrosis, and an estimated 37.6% of patients with NASH will progress in
fibrosis stage. Ultrasonography is an acceptable method for assessing FLD. Most FLD
cases have a behaviour-related etiology, which provides opportunity for treatment. Studies
on cost-effectiveness of screening for FLD lack, but prospects are promising given the
increased costs (both financial and quality of life) of patients with FLD.
Conclusion Based on the evidence presented in this paper, we conclude that screening for
FLD is advisable. However, cost effectiveness studies on screening for fatty liver disease
are yet to be performed.
Screening for fatty liver disease
167
PREFACE
In CHAPTERS 2 and 3 we found that fatty liver disease is highly prevalent, and associated
with an increased cardiovascular disease risk. Therefore, in this chapter, we investigated
whether screening for fatty liver disease would be beneficial.
INTRODUCTION
Excess fat should be stored in adipocytes (subcutaneous fat), where it functions as an
‘adipose organ’ 1. In the case of dietary overflow, lipids can be stored in the peritoneal
cavity (visceral fat), retro-peritoneal (peri-renal fat), or ectopically, i.e. inside myocytes and
organs (e.g. the liver) as well 2. Hepatic free fatty acids (HFFAs), i.e. not oxidated, secreted
as very low density lipoprotein, or excreted as phospholipids into bile, are stored as neutral
triglycerides (TGs) within lipid vesicles [CHAPTER 4] 3. Continuous accumulation of intra-
hepatocellular TGs will result in fatty liver disease (FLD).
FLD, which includes both alcoholic FLD (AFLD) and non-alcoholic FLD (NAFLD; by
≤20g ethanol a day 4), refers to a broad spectrum. Repeated biopsies have revealed that non-
alcoholic steatosis (NAS; fat, with or without non-specific inflammation) can progress to
non-alcoholic steatohepatitis (NASH; fat + inflammation, without of with fibrosis) 5.
Fibrosis progression in the case of NASH, delineating loss of liver fat and inflammation 6,
results in cirrhosis (fibrosis stage 4 7), also referred to as ‘burned out NASH’ 8. It has been
known for many years that cryptogenic cirrhosis can be associated with hepatocellular
carcinoma (HCC) 6, but it only recently discovered that active NASH without cirrhosis can
be accompanied by HCC as well 9, 10. In the case of a NASH background, HCC can be
multi-focal 10. Besides a hepatic risk, NAFLD may also increase cardiovascular disease
(CVD) risk, as a (non-alcoholic) fatty liver overproduces several CVD risk markers
[CHAPTER 3] 11. NAFLD is usually asymptomatic. Non-specific complaints of weakness
and fatigue 12, 13, and a vague right upper abdominal discomfort or epigastric pain are
reported by some patients 6, 13-15. Clinical signs of chronic liver disease are absent, apart
from hepatomegaly in some patients 12, 14, 15. NASH is generally discovered incidentally
during investigation of other (unrelated) medical conditions 12, 15 or after health screening 15.
Chapter 8.1: General discussion - part 1.
168
These risks, may warrant aggressive screening on steatosis 10, 16, in order to prevent
progression to NASH and symptomatic disease.
FLD and NAFLD are highly prevalent worldwide. The estimated current prevalence of
NAFLD by imaging in the Asia-Pacific region was recently reviewed by Amarapurkar ea.
(2007) and ranges from 16% to 42% 17. Two studies in Japan have revealed an incidence of
FLD as well, i.e. from 12.6% in 1989 to 30.3% in 2000 18, and from 33.3% in 2000 to
38.5% in 2005 in men, while the prevalence remained similar in women 19. The estimated
prevalence of FLD and NAFLD by imaging in the Western population varies from 27.4%
to 31% 20-22 and 27% 20, respectively.
However, despite currently being the most common hepatic condition worldwide and likely
increasing, screening on FLD has not been recommended. The World Health Organisation
(WHO) has published screening criteria, originally introduced by Wilson and Jungner 23
and expanded later 24. The aim of this paper is to discuss if screening for FLD would be
effective, by discussing the WHO screening criteria, organised into the following
Overall survival compared to reference populations
A meta-analysis on survival of patients with NAFLD has recently been published 16.
Because of its relevance for screening (detection of an early latent stage), this section
focuses specifically on histological-determined FLD subtypes and age (table ІІ). Compared
to reference populations, overall survival of patients with NAS is non-significantly reduced
28-30, whereas survival of both patients with NAFLD 13, 29 and NASH 29, 30 are significantly
reduced. Additionally, survival of patients with AFLD is significantly reduced as well 30.
Causes of death
The primary cause of death in patients with NAFLD is CVD-related death 13, 29-31. CVD-
related death was 7.5% in a reference population, slightly increased to 8.6% in patients with
NAS (p=ns compared to the reference population) and significantly increased to 15.5% in
patients with NASH (p<.05 compared to the reference population) 29. Compared to
reference populations, patients with NASH 29, 32 have a increased risk for liver-related
death. In severe NASH, i.e. half of the population with cirrhosis, infection is the primary
cause of death 33.
Table ІІ.
Longit
udin
al s
tudie
s on s
urv
ival
of
fatt
y liv
er d
isea
se s
ubty
pes
ALIV
E AT BASELIN
E
FOLLOW
-UP PERIO
D
DECEASED
FLD subtypes, i.e. n and age
mean (±sd) & m
edian (range)
N (N%)
Cause of death
NA
S
NA
SH
A
FL
D
E
xtr
a-hep
atic
H
epat
ic
U
Car
dio
vas
cula
r dis
ease
M
O
LB
D
HC
C
Car
dia
c O
V
IHD
O
C
Mat
teoni ea
. (1
999)
32
Unit
ed S
tate
s of
Am
eric
a
N=
59 (
2C
) A
ge
T1: 53 (
±15)
Age
T2: 46 (
±12)
8.9
(±5.5
) &
NR (
0.4
–17.8
)
48 (
36%
) 9
2
2
10
10
11
1
3
N
=73 (
18C
) A
ge
T3: 49 (
±15)
Age
T4: 56 (
±11)
7.8
(±5.3
) &
NR (
0.1
–18.2
)
Dam
-Lar
sen e
a.
(2004)
34
Den
mar
k
N=
109
Age:
39 (
19–80)
16.7
(0.2
–21.9
) 27 (
25%
)
1
N=
106
§
Age:
50 (
26–72)*
**
9.2
(0.6
–23.1
) 79 (
75%
)
22
Dam
-Lar
sen e
a.
(2005)
28†
Den
mar
k
N=
170
Age:
39 (
19–84)
19 (
0.2
–27.1
) N
R
1
N=
247
§
Age:
50 (
26–76)*
**
12.8
(0.1
–27.1
) N
R
54
Ekst
edt ea
. (2
006)
29
Sw
eden
N=
58
Age:
47 (
±12)
13.7
(±1.3
) &
NR (
10.3
–16.3
)
7 (
12%
) 5
1
1
N
=71 (
4C
) A
ge:
55 (
±12)*
**
19 (
27%
) 11
4
2
1
1
San
yal
ea.
(2006)
33
Unit
ed S
tate
s of
Am
eric
a
N=
152
‡ (
74C
) A
ge
CT
P-A
: 55 (
±N
R)
Age
CT
P-B
: 52 (
±N
R)
Age
CT
P-C
: 60 (
±N
R)
10
29 (
19%
) 2
6
5
14
2
Raf
iq e
a. (
2009)
31
Unit
ed S
tate
s of
Am
eric
a
N=
101
Age:
49 (
±15)
18.5
(≥
5–28.5
) 78 (
49%
) 22
14
2
2
7
N
=57
Age:
52 (
±13)
10
Soder
ber
g e
a.
(2010)
30
Sw
eden
N=
67 (
4C
) A
ge:
45 (
±12)
21 (
±7.7
) &
24 (
0.5
–28)
23 (
34%
) 7
5
4
4
2
1
N
=51 (
5C
) A
ge:
49 (
±N
R)
24 (
47%
) 7
8
6
3
N=
25 (
2C
) ¶
Age:
NR
20 (
80%
) 8
1
4
5
2
***,
p<
.001;
†,
enla
rgem
ent
of
thei
r st
udy f
rom
2004;
‡,
n=
74 C
TP
_A
, n=
43 C
TP
_B
, n=
35 C
TP
_C
); §
, al
coholic
stea
tosi
s; ¶
, al
coholic
fatty l
iver
dis
ease
; C
, ci
rrhotics
; C
TP
, C
hild-T
urc
otte-
Pugh s
core
; H
CC
, hep
atoce
llula
r ca
rcin
om
a; L
BD
, liver
and b
ilia
ry d
isea
se (
excl
udin
g H
CC
); M
, ex
tra-
hep
atic
mal
ignan
cy;
NA
FL
D,
non-a
lcoholic
fatty l
iver
dis
ease
; N
AS,
non-a
lcoholic
stea
tosi
s; N
ASH
, non-a
lcoholic
stea
tohep
atit
is;
NR,
not
report
ed;
OC
, oth
er c
ardia
c ca
use
; O
, oth
er e
xtr
a-hep
atic
cau
se; O
V, oth
er v
ascu
lar
even
ts; U
, unknow
n c
ause
.
Screening for fatty liver disease
171
Table ІІІ. L
ongitudin
al s
tudie
s on f
ibro
sis
pro
gre
ssio
n o
f non-a
lcoholic
fatt
y liv
er d
isea
se, by s
eria
l his
tolo
gic
al a
nal
ysi
s
Country of
origin
First biopsy
Follow up period
Last biopsy
NAS
NAFLD
NASH
mean (±sd) & m
edian (range)
Fibrosis
regression
Fibrosis
stable
Fibrosis progression
↑F
→C
Lee
(1989)
12
US
A
N=
8
2.8
(±1.6
) &
2.4
(1.2
–6.1
)
N=
3
N=
3
N=
2
Pow
ell ea
. (1
990)
6
AU
S
N=
13
4.5
(±1.8
) &
4 (
1–8)
N=
1
N=
8
N=
3
N=
1 &
→H
CC
Bac
on e
a. (
1994)
14
US
A
N=
2
5.5
(±2.1
) &
5.5
(4–7)
N
=1
N
=1
Tel
i ea
. (1
995)
15
UK
N
=12
NR (
7.6
–16)
NR
NR
N=
1
Evan
s ea
. (2
002)
35
UK
N
=7
8.2
(±2.6
) &
7 (
5.5
–11.9
)
N=
3
N=
4
Har
riso
n e
a. (
2003)
5
US
A
N
=22 (
3 N
AS
, 19 N
AS
H)
5.7
(N
R)
& N
R (
1.4
–15.7
) N
=4
N=
11
N=
6
N=
1
Fas
sio e
a. (
2004)
36
AR
G
N=
22
5.3
(±2.7
) &
4.3
(3–14.3
) N
=4
N=
11
N=
7
Hui ea
. (2
005)
37
CH
INA
N=
17 (
3 N
AS
, 14 N
AS
H)
5.8
(±1.4
) &
6.1
(3.8
–8)
N
=8
N=
8
N=
1
Adam
s ea
. (2
005)
38†
US
A
N
=103 (
7 N
AS
, 96 N
AS
H)
3.2
(±3)
& N
R (
0.7
–21.3
) N
=30
N=
35
N=
29
N=
9
†, th
is s
tudy is
a cl
inic
al tri
al b
ut th
e ‘i
nte
rven
tion’
had
no e
ffec
t on h
isto
logy; ↑, in
crea
se to h
igher
sta
ge;
→, pro
gre
ssio
n to.
AR
G, A
rgen
tina;
C, ci
rrhosi
s; F
, fi
bro
sis;
HC
C, hep
atoce
llula
r ca
rcin
om
a; N
AF
LD
, non-a
lcoholic
fatt
y liv
er d
isea
se; N
AS, non-a
lcoholi
c
stea
tosi
s; N
AS
H, non-a
lcoholic
stea
tohep
atitis
; N
R, not re
port
ed; U
K, U
nit
ed K
ingdom
; U
SA
, U
nit
ed S
tate
s of
Am
eric
a; A
US, A
ust
ralia
Chapter 8.1: General discussion - part 1.
172
Screening for fatty liver disease
173
NATURAL HISTORY OF FATTY LIVER DISEASE?
Several studies on fibrosis progression in the case of (non-alcoholic) fatty liver disease have
been performed 5, 6, 12, 14, 15, 35-38 and summarised in table ІІІ. NAS could be considered a
latent stage of FLD as it is relatively non-progressive 15, 28, 29. An estimated one-twelfth
(8.3%) of patients with NAS will develop fibrosis 15. Fibrosis progression in patients with
NASH has recently been systematically reviewed by Argo ea. (2009) 39. Of all NASH
patients (n=221 in total) having a second biopsy after 5.3 (±4.2) year, 37.6% progressed to
a higher fibrosis stage, 41.6% had no change, and 20.8% regressed to a lower fibrosis stage
39.
Fibrosis progression
Mean fibrosis progression rate was 0.03 (±0.53) stages/year 39. However, when cirrhotics
are excluded (as they cannot progress further), mean fibrosis progression will be higher 13.
Importantly, fibrosis progression delineates regression of both fat 6, 36, 38 and inflammation 5
,
6, 38. Figure І shows a theoretical model on the FLD spectrum.
Associates of fibrosis progression
Multivariate analysis, with advanced fibrosis (stage 3 and 4) as dependent variables,
revealed that both age and inflammation on initial biopsy are independent predictors of
progression to advanced fibrosis 39. Although this implies important prognostic value these
results are not surprising, as injury yields an inflammatory response 40 resulting in repair of
the injury by means of fibrosis [CHAPTER 4] 3. If inflammation on initial biopsy (and
cirrhotics) is excluded, low initial fibrosis stage, BMI, and diabetes are predictors of
fibrosis progression 38.
DEFINED TARGET POPULATION?
The aim of screening for FLD would be to detect an increased CVD risk and/or hepatic
risk, thereby increasing opportunity for intervention, in order to prevent progression of
CVD risk and hepatic risk, i.e. secondary prevention. The most efficient/effective approach
would be to screen people with an already increased hepatic risk and/or CVD risk, e.g.
diabetes. Patients with type 2 diabetes and NAFLD (by ultrasonography) have a
significantly higher incidence of CVD events compared to patients with type 2 diabetes
without NAFLD 41. Diabetes predisposes to hormone sensitive lipase-induced breakdown
Chapter 8.1: General discussion - part 1.
174
of TG vesicles, releasing more toxic HFFAs [CHAPTER 4] 3, and is a predictor of fibrosis
progression 38.
Screening high risk groups does raise the question of population screening, i.e. primary
prevention 42. Epidemiological studies have revealed that NAFLD is most common at
middle age and decreases at higher ages 43-45.
Fat
Inflammation
Fibrosis
Infiltration:
INFILTRATION
PROGRESSION OF THE FATTY LIVER DISEASE SPECTRUM (SPEED OF PROGRESSION DEPENDS ON THE AMOUNT OF DETERMINANTS, PER INDIVIDUAL)
Normal NASS NASni NASH-f NASH+f/c Cirrhosis
Increased HCC risk
Figure 1. Schematic model on the natural history of fatty liver disease
The scale of natural progression was estimated from progression throughout the various FLD stages is based on long-term follow up studies (appendix
ІІb). The starting stage may vary between individuals.HCC, hepatocellular carcinoma; NASH-f, non-alcoholic steatohepatitis without fibrosis; NASH+f,
non-alcoholic steatohepatitis with fibrosis, NASni, non-alcoholic steatosis with non-specific inflammation; NASS, non-alcoholic simple steatosis.
Screening for fatty liver disease
175
DIAGNOSIS
METHOD ACCEPTABLE TO THE POPULATION?
A diagnosis modality for screening should firstly be non-invasive, which excludes liver
biopsy and computed tomography (harmful radiation). Secondly, a diagnosis method
should be low-cost, which excludes magnetic resonance spectroscopy and magnetic
resonance imaging. Additionally, a diagnosis method should be liver-specific, which
excludes aminotransferases as aminotransferases are produced and present in numerous
tissues 46, 47. An elevation of aminotransferases can therefore be attributed to other diseases
as well 48, 49. The remaining diagnosis method is ultrasonography.
IS ULTRASONOGRAPHY SUITABLE FOR FATTY LIVER DISEASE?
Within the FLD spectrum, fat can both occur separately and coexist with inflammation
and/or fibrosis (figure І). Therefore, in order to estimate the place within the FLD spectrum,
fat, inflammation, and fibrosis are to be determined ideally.
Fat A selection of ultrasound validation studies is shown in table ΙV. Qualitative
ultrasonography is a valid and reliable method for diagnosing FLD, i.e. an abundance of
liver fat 50-52. Validity is decreased in (morbidly) obese people 53, 54. A quantitative
ultrasonography method has recently been developed as well [CHAPTER 5] 55.
Inflammation Ultrasonography is (currently) unable to determine hepatic inflammation,
which means that it is unable to distinguish steatosis and steatohepatitis. Perhaps it might
be of value to estimate splenomegaly 56, but validation studies using ultrasonography-
determined splenomegaly have not been published.
Fibrosis Ultrasonography can estimate hepatic fibrosis. Two meta-analysis on transient
ultrasonographic elastography (FibroScan), i.e. in all liver diseases 57 and in FLD
specifically 16 have recently been published and show acceptable results (table ΙV). The
success rate (applicability) of ultrasonographic elastography is not perfect, which is mostly
attributed to obesity 16, 57. This suggests that for obese patients an extra large transducer
may be required 58. Additionally, it should theoretically be able to estimate fibrosis using
ultrasonographic texture analysis [CHAPTER 5] 55, but more validation work is needed.
Table ΙV. V
alid
ity o
f ultra
sonogra
phy f
or
asse
ssin
g f
atty
liv
er d
isea
se, se
lect
ion o
f th
e lite
ratu
re
Country of
origin
Gold
Standard
Population
Hepatic fat
Hepatic fibrosis
SE (%)
SP (%)
AUC
r SE (%)
SP (%)
AUC
Qualitative ultrasonography
Sav
erym
utt
u e
a. (
1986)
50,
and J
ose
ph e
a. (
1991)
51
Unit
ed K
ingdom
H
(ql.)
(S)L
D
89–94
84–93
- -
NA
N
A
NA
Ham
aguch
i ea
. (2
007)
52
Japan
H
(ql.)
Excl
. A
s an
d v
H
91.2
–92.6
100
0.9
8
- N
A
NA
NA
Quantitative ultrasonography
Eden
s ea
. (2
009)
[C
HAPTER 5
] 55
The
Net
her
lands
1H
MR
S (
qnt.)
Gen
. (n
o k
now
n
LD
excl
. F
LD
) 66.7
100
- .7
89*
- -
-
Transien
t ultrasonographic elastography †
‡
Met
a-an
alysi
s:
Fri
edri
ch-R
ust
ea.
(2008)
57
All
countr
ies
(n=
50 s
tudie
s)
H (
ql.)
F≥2
NA
N
A
NA
N
A
56 –
100
18 –
100
0.6
8 –
1.0
0
F≥3
NA
N
A
NA
N
A
58 –
95
78 –
97
0.7
2 –
0.9
7
F=
4 (
i.e.
C)
NA
N
A
NA
N
A
73 –
100
78 –
98
0.8
1 –
0.9
9
Wes
tern
reg
ion
(n=
46 s
tudie
s)
F≥2
NA
N
A
NA
N
A
56 –
100
18 –
100
0.6
8 –
1.0
0
F≥3
NA
N
A
NA
N
A
58 –
95
85 –
97
0.7
2 –
0.9
7
F=
4 (
i.e.
C)
NA
N
A
NA
N
A
73 –
100
81 –
98
0.8
7 –
0.9
9
Asi
a-P
acif
ic
regio
n
(n=
4 s
tudie
s)
F≥2
NA
N
A
NA
N
A
79 –
90
78 –
88
0.7
7 –
0.8
1
F≥3
NA
N
A
NA
N
A
86 –
95
78 –
92
0.7
9 –
0.9
3
F=
4 (
i.e.
C)
NA
N
A
NA
N
A
80 –
86
78
0.8
1 –
0.8
8
Met
a-an
alysi
s:
Muss
o e
a. (
2010)
16
All
countr
ies
(n=
6 s
tudie
s)
H (
ql.)
F≥2
NA
N
A
NA
N
A
79 –
100
74 –
93
0.8
4 –
0.9
9
F≥3
NA
N
A
NA
N
A
75 –
100
81 –
100
0.9
0 –
1.0
0
Wes
tern
reg
ion
(n=
2 s
tudie
s)
F≥2
NA
N
A
NA
N
A
81 –
100
78 –
92
0.8
6 –
0.9
9
F≥3
NA
N
A
NA
N
A
100
100
1.0
0
Asi
a-P
acif
ic
regio
n
(n=
4 s
tudie
s)
F≥2
NA
N
A
NA
N
A
79 –
100
74 –
93
0.8
4 –
0.9
9
F≥3
NA
N
A
NA
N
A
75 –
100
81 –
93
0.9
0 –
0.9
9
*, p<
.001;
†, cu
t-off
val
ues
dif
fer
per
stu
dy;
‡, su
cces
s-ra
tes
dif
fer
per
stu
dy.
As,
alc
oholics
; A
UC
, ar
ea u
nder
the
curv
e ra
nge;
C,
cirr
hosi
s; D
VS,
theo
reti
cally p
oss
ible
, but
in n
eed o
f fu
rther
dev
elopm
ent
and
val
idat
ion s
tudie
s; E
xcl
., e
xcl
udin
g; F, fi
bro
sis
stag
e as
det
erm
ined
by M
ET
AV
IR a
nd o
ther
sco
ring s
yst
ems;
FL
D, fa
tty liv
er d
isea
se; G
en.,
gen
eral
popula
tion; H
, his
tolo
gy;
1H
MR
S; M
agnet
ic R
esonan
ce S
pec
trosc
opy; L
D, li
ver
dis
ease
; N
A, not ap
pli
cable
; ql., qual
itat
ive;
qnt.,
quan
tita
tive;
r, co
rrel
atio
n c
oef
fici
ent
by P
ears
on;
SE
, se
nsi
tivity r
ange;
(S)L
D, (s
usp
ecte
d)
liver
dis
ease
; SP, sp
ecif
icity r
ange;
vH
, vir
al
hep
atit
is.
Chapter 8.1: General discussion - part 1.
176
Screening for fatty liver disease
177
TREATMENT
ACCEPTED TREATMENT?
When discussing treatment, it is relevant to distinguish cases with a behavioural etiology
and cases with a non-behavioural etiology. Patients with a behaviour-related etiology can
potentially be treated (‘is controllable’), in contrast to patients with a more complicated
etiology like genetic, drug-related, and/or environment-related (‘partially controllable’). In
order to determine a suitable treatment for the individual patient, etiologic factors per
individual patient should be determined. Risk factors for FLD can be arranged in the
following three categories: 1] risk factors for hepatic lipid content, 2] risk factors for
inhibited hepatic metabolism, and 3] risk factors for hepatic inflammation [CHAPTER 4] 3.
Behavioural etiology, i.e. controllable
Given the link with overnutrition & low physical activity, and alcohol (AFLD) [CHAPTER
4] 3, it is to be expected that most of the FLD cases have a behaviour-related etiology.
These behaviour-related cases may be naturally resolved by breaking off etiologic
behaviour. Weight loss interventions resulting in weight loss of ≥2.6 body mass index-
points, were effective in improving NAFLD [CHAPTER 3] 4, 11. This can be achieved
through diet 59, exercise alone 60, diet & exercise 59, 60, or bariatric surgery 59. Weight loss
should not go too fast, given the risk of accentuation or development of focal fatty change
in liver segment ІV 61. A part of the patients may be able to achieve and maintain weight
loss themselves 62. If needed, general practitioners, nutritionists 63, and cognitive behaviour
therapists 64, 65, may be able to assist people with their weight loss.
Non-behavioural etiology, i.e. partially controllable
In the case of a non-behaviour-related etiology, etiologic factors should be abolished, e.g.
use of hepatotoxic drugs if possible 66, 67 and protection for or change of the environment 68.
Otherwise, the non-natural cases may be in need of pharmacological treatment to either
resolve FLD itself [CHAPTER 3] 11, 59, 69 or to resolve FLD associated pathology [CHAPTER
3] 4, 11, 70. A systematic clinical review has recently been published, which describes the
actions and effects of potential pharmacological treatment modalities for FLD 59. It should
be noted that effects of pharmacological approaches are often confounded by weight loss
[CHAPTER 3] 11. If pharmacological treatment coincides with weight loss, it is difficult to
determine the independent effect of the pharmacological intervention. A meta-analysis on
Chapter 8.1: General discussion - part 1.
178
randomised clinical trials for FLD was recently published as well, reporting that
randomised trials of adequate size and duration using histological endpoints are needed, to
assess long-term safety and efficacy 69.
AGREED POLICY WHO TO TREAT?
Policy decision guidelines are based on increased absolute risks 42. This likely means that
people with known hepatic and/or CVD risk factors should be offered screening and
treatment for FLD.
Screening for fatty liver disease
179
COST AND SCREENING PROGRAM
COST OF FLD?
It has been shown that patients with FLD (by ultrasonography and alanine
aminotransferase) have more consults from specialists and use more medication compared
to subjects without FLD 70, suggesting that screening and treatment might potentially cut
down health care expenditure 70. The increased medication use in FLD was largely
attributable to diabetes and lipid lowering medication 70.
COST OF A SCREENING PROGRAM FOR FLD?
To the best of our knowledge, there are no published studies on the cost-effectiveness of
ultrasonographic screening for FLD. It is important to realise, that with ultrasonographic
screening for FLD, screening for other (un)expected hepatic lesions, e.g. HCC, will
automatically be included as well. Screening for HCC has been reported to be effective, at
least in a high risk group 71. Cost-effectiveness was not studied, but the authors did report
that the estimated costs of the screening program were similar to their national breast
cancer screening program 71.
AFTER FLD DIAGNOSIS?
After having diagnosed FLD it may be wise to determine etiology and/or comorbidity of
FLD. The design of a potential screening program, including potential management and
treatment of discovered cases, is shown in appendix І.
Etiology
As described in the treatment section, it may be relevant to determine etiology for each
individual patient in order to determine the most appropriate action(s). A behavioural
etiology could simply be determined by questionnaires on behaviour, anthropometry, and
ultrasonography. A non-behavioural etiology could be identified by questionnaires on
behaviour, (familiar) diseases, and environment.
Comorbidity
Given the strong association of FLD with components of the MetS [CHAPTER 3] 4, 11,
components of the MetS should be assessed as well.
Chapter 8.1: General discussion - part 1.
180
DISCUSSION
Taken together, the screening criteria regarding ‘condition’, ‘treatment’, ‘diagnosis’, and
‘screening program’ (table І) seem to be reasonable met or possible to meet. Currently cost-
effectiveness studies on screening for FLD lack, but prospects are promising given the
increased cost (both financial 70 and quality of life 27) of patients with FLD. Before
screening prime time, general practioners and specialists should bear FLD in mind and
stimulate weight loss.
STUDIES USED IN THIS PAPER
Histological analysis
Most studies used in this paper used histology as diagnosis modality. It should be noted that
the first histological scoring protocol for internationally uniform scoring of FLD, was
published in 1999 72 and updated in 2005 7. Despite currently being the only modality that
can stage FLD (i.e. distinguish steatosis and steatohepatitis), it has some diagnostic
disadvantages as well. Liver biopsy is subject to sampling bias 73, 74 and histological
analysis is subject to scoring variability (particularly of inflammation) 7, 72, 75.
Risks in the general population
Many studies used in this paper were studies on ‘natural’ NAFLD, which means that,
besides obesity and diabetes, many known etiologic factors were excluded. Obviously,
all/many etiologic factors for FLD [CHAPTER 4] 3 are present in the general population,
which may suggest a (much) faster fibrosis progression rate in the general population.
CONCLUSION
Based on the evidence presented in this paper, we conclude that screening for FLD is
advisable. However, cost effectiveness studies on screening for FLD are yet to be
performed.
Screening for fatty liver disease
181
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states: 1. Introduction. J Am Acad Dermatol 2005 October;53(4):663-70.
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188
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•Alcohol and other drugs (current & recent history)
•Energy expenditure
(Fat +)
F3-F4
Questionnaire on complaints and (potential) diseases:
•Knowndiseases
•Known family disease history (e.g. HH)
Questionnaire on drugs/medicine:
•All drugs used currently
•All drugs used in recent history
Change lifestyle:
•Limit calorie intake [E]
•Limit alcohol and usedrugs
•Exersice[F]
Weightloss [G]:
•2.6 BMI-points[ C]
•Gradual, to prevent worsening [H]
These are likelyalreadybeingtreated
Questionnaire on Environment:
Known exposure to toxins at work or elsewhere
Protect for the environment [L]
Changelifestyle:
•Nutritional counselling[M]
•Rehabilitationprogram
•(Cognitive) behavioural therapy [N]
Weight loss:
•Drugs for weight loss [E]
•Bariatric surgery [E]
Screeningfor(family) disease
Examination of obesity, particularly VAT:
•APM for BMI and waist-to-hip ratio
•USG for VAT/SAT ratio [B]
Blood tests for assessment CVD [C] and/or hepatic risk:
•Glucose
•Lipids
•Blood pressure
•Inflammation
•Coagulation
Treatment for insulin resistance [E]
Examination of small intestinal bacterial overload:
Breath test [D]
Treat infection
Examination of lipodystrophy:
•APM/USG for SAT
•Questionnaire/blood tests on menopausal state
•Angiotensinreceptor blockade [E]
•Anti-TNFα[E]*
Examination of liver disease (other than FLD):
•Autoimmunehepatitis
•Viralhepatitis
Take into account genotype [O]
Correct unfavourable fat distribution:
•via Thiazolidinediones[E]
•via horm
ones(HRT)
t = 5
t = 3
t = 2
Appropriate treatm
ent
Refer to a specialist
Refer to a specialist
Fat +
F2-F3
•Eliminate/minimise drug use if possible[I]
•Use drugs without hepatic metabolism [J]
and/or without immunogeneity[K]
•Change nutrition
•Limit alcohol use
Change the environment [L]
Appen
dix І. P
ote
ntial
des
ign o
f a
scre
enin
g p
rogra
m f
or
fatt
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isea
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ly h
ypoth
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[A],
[CHAPTER 4
] 3; [B],
76-7
8; [C
], [CHAPTER 3
] 11; [D
], 7
9, 80; [E], 5
9; [F], 6
0; [G
], [CHAPTER 3
] 4, 11, 59, 62; [H
], 6
1; [I],
66, 67; [J], 8
1; [K
], 8
2; [L], 6
8; [M
], 6
3; [N
], 6
4, 65; [O
], 8
3.
AP
M,
anth
ropom
etry
; B
MI,
body m
ass
index
; C
VD
, ca
rdio
vas
cula
r dis
ease
; F
, fi
bro
sis
stag
e; F
LD
, fa
tty l
iver
dis
ease
; H
CC
, hep
atoce
llula
r ca
rcin
om
a; H
H,
her
edit
ary h
aem
och
rom
atosi
s; H
RT
, horm
one
repla
cem
ent
ther
apy;
SA
T,
subcu
taneo
us
adip
ose
ti
ssue;
t,
tim
e in
yea
rs;
TN
Fα,
tum
our
nec
rosi
s fa
ctor
alpha;
U
SG
, ult
raso
nogra
phy;
VA
T,
vis
cera
l ad
ipose
ti
ssue.
190
Chapter 8.2: General discussion - part 2
Additional remarks and recommendations for future
research
Chapter 8.2: General discussion - part 2.
192
A few additional remarks and recommendations for future research on selected chapters
will be given.
ADDITIONAL REMARKS AND RECOMMENDATIONS TO CHAPTER 2:
“Fatty liver disease and cardiovascular risk in the general population of East Anglia:
The Fenland Study”.
• Regarding prevalence
As 762 participants is a (relatively) small study group, predominantly from the Ely test site,
one could question whether this sample is representative for the general population of
East Anglia. In order to improve representativeness, the distribution of sex and age should
match the distribution of sex and age of the population of East Anglia.
While writing chapter 2, data collection of the Fenland Study continued. At the time of
writing this section, approximately 2000 liver fat scans were available for analysis. The
analysis performed in chapter 2, will be repeated in this extended database, where after it
will be submitted for publication.
• Regarding the ultrasound method
Although the separate ultrasound measures used in this study are based on the literature, the
entire scoring method has not been validated yet. In a new version of chapter 2, based on
the enlarged database (please see point above), results of a validation study will be given.
• Regarding cardiovascular risk markers
The value of the MetS for predicting CVD events is often questioned. However, as
described in the discussion of this chapter, a recent meta-analysis revealed that presence of
the MetS (a dichotomous variable) is a predictor of future incident CVD events 1. It can,
and should, be studied whether the MetS is 1] a risk factor beyond its specific components
2, and 2] is more than the sum of its components (an ordinal variable) 3. Theoretically, more
atherogenic risk factors means a greater risk for CVD events. When predicting future
incident CVD event, scientists should compare in the same database the predictive value of
various risk factors: 1] specific MetS components 2 and other conventional CVD risk
factors, 2] the MetS dichotomous, 3] the MetS ordinal 3, 4] the MetS continuous (Z-score),
5] the 10 year Framingham risk score, and 6] FLD (which might be a better predictor of
CVD than the MetS dichotomous and conventional CVD risk factors 4).
Remarks and recommendations
193
ADDITIONAL REMARKS AND RECOMMENDATIONS TO CHAPTER 5:
“Ultrasonography to quantify hepatic fat content: validation by 1H magnetic
resonance spectroscopy”.
• Regarding reliability: part 1
As suggested in this chapter, detailed protocols have now been written to improve
reliability. The protocols stress out that this quantitative ultrasonography method is highly
dependant on the quality of the images and the quality of the image analysis. A major part
of the method is based on differences in pixel intensity between pixels. One can imagine
that when the ROI is drawn half in liver parenchyma contaminated by e.g. rib shadow,
this has consequences for validity of the method. Quality control regarding image analysis
has been implemented, in order to verify the quality of the image and image analysis.
Additionally, it would be of value to investigate whether it is possible to develop
computerized methods regarding recognition and exclusion of artefacts.
• Regarding reproducibility by other ultrasound equipment and computer screens
Another point to be discussed is differences in resolution (amount of pixels) between
ultrasound machines and computer screens. Some variables embedded in the algorithm are
based on sum scores, i.e. the sum of spatial distances between all pixels with a different
intensity (indices of the spatial grey level dependence matrix) and the sum of spatial
distances between all pixels with the same intensity (i.e. indices of the grey level difference
matrix). In theory, ultrasound machines and/or computer screens with higher resolutions,
i.e. with more pixels and pixel pairs than used in the present validation study, should
produce higher values of the indices and therefore a (much) higher outcome of the
algorithm. A difference between ultrasound machines is supported by a small experiment
using 3 volunteers and 3 different ultrasound machines, using the same computer screen for
analysis.
Acknowledgement: Jan Visscher for performing ultrasonography.
• Regarding reliability: part 2
While writing the previous section on resolutions, regarding generalisation to other
ultrasound equipment and computer screens, I suddenly realised something. Also in the
case a ROI is drawn larger, more pixels and pixel pairs are included. Thus theoretically,
differences in ROI size could underlie issues regarding intraobserver and interobserver
reliability. When modifying the software, we implemented the amount of pixels of the AL
Chapter 8.2: General discussion - part 2.
194
(which did not improve outcome), but did not think about the amount of pixels included
within the ROI. If the theory described above is true, then perhaps both the issues regarding
reproducibility and reliability part 2 might be solvable by implementing the amount of
pixels or pixel pairs in the formula’s of all indices of the co-occurrence matrix. Perhaps
implementing the average value (in stead of the sum) would improve the method, but this is
for future validation work.
ADDITIONAL REMARKS AND RECOMMENDATIONS TO CHAPTER 7:
“MRI determined fat content of human liver, pancreas and kidney”.
In chapter 7 we concluded that renal lipid accumulation appears not to be involved in the
pathogenesis of renal disease. It should be noted that this chapter was written earlier than
chapter 4 “Pathogenesis of fatty liver disease: A theory on lipid content, inhibited
metabolism, and inflammation”. In chapter 4 is described that the liver transforms severely
toxic fatty acids into little toxic triglycerides, and stores these triglycerides in lipid vesicles
isolated from the cytosol. While writing that, I wondered whether the kidney and pancreas
also possess these protective abilities. Magnetic resonance spectroscopy and imaging do not
distinguish fatty acids and triglycerides. In other words, the little bit of fat measured within
the pancreas and kidney could be of the severely toxic fatty acid type, predisposing to
steatonecrosis. Thus assessment of fat content of the pancreas and kidney might also be
important.
Remarks and recommendations
195
Reference List (1) Gami AS, Witt BJ, Howard DE, Erwin PJ, Gami LA, Somers VK, Montori VM.
Metabolic syndrome and risk of incident cardiovascular events and death: a systematic review and meta-analysis of longitudinal studies. J Am Coll Cardiol 2007 January 30;49(4):403-14.
(2) Inchiostro S, Fadini GP, de Kreutzenberg SV, Citroni N, Avogaro A. Is the metabolic syndrome a cardiovascular risk factor beyond its specific components? J Am Coll Cardiol 2007 June 26;49(25):2465-6.
(3) Kurth T, Logroscino G. The metabolic syndrome: more than the sum of its components? Stroke 2008 April;39(4):1068-9.
(4) Hamaguchi M, Kojima T, Takeda N, Nagata C, Takeda J, Sarui H, Kawahito Y, Yoshida N, Suetsugu A, Kato T, Okuda J, Ida K, Yoshikawa T. Nonalcoholic fatty liver disease is a novel predictor of cardiovascular disease. World J Gastroenterol 2007 March 14;13(10):1579-84.
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Summaries English summary
Nederlandse samenvatting (Dutch summary)
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ENGLISH SUMMARY
CHAPTER 1 is the general introduction to this thesis and gives an overview on the history of
fatty liver disease (FLD) and the contribution of this thesis to our knowledge of FLD. The
livers’ ability to store fat has been known for a long time, as the first publication on human
liver fat dates from 1907. FLD is a broad spectrum, consisting of many subtypes, but is
often divided in steatosis (fat accumulation) and steatohepatitis (fat + inflammation, with or
without fibrosis). Throughout history many synonyms for the spectrum and its subtypes
have been published. Subtypes can be determined by histology only. The first proposal
(protocol) for uniformly scoring the histologic FLD lesions was published in 1999, and
updated in 2005. Other diagnosis methods, for liver fat content only include: biochemical
analysis (after liver biopsy), magnetic resonance spectroscopy (1H MRS), magnetic
resonance imaging (MRI), computed tomography (CT), and ultrasonography. As alcohol is
a historically well known risk factor for liver disease, alcoholic FLD (AFLD) and non-
alcoholic FLD (NAFLD) are often distinguished, usually using an ethanol cut-off value of
20 g/d. In 1992, a close association of NAFLD with the metabolic syndrome, a marker of
cardiovascular disease (CVD), was first reported.
CHAPTER 2 explores baseline data of the Fenland Study, which is an ongoing population
based cohort study with currently cross-sectional results only. The chapter describes the
prevalence of FLD and its association with CVD risk in the general population of East
Anglia, aged 30 to 58 years. Exclusion criteria were: diabetes mellitus, terminal illness,
inability to walk unaided, and pregnancy. FLD was assessed by ultrasonography (scored in
a cumulative fashion and attributed as normal, mild, moderate, and severe FLD). CVD risk
was estimated by the metabolic syndrome (MetS), using several definitions, and the 10-year
Framingham CVD risk score. Liver fat scores were obtained in 762 participants. Overall
prevalence of FLD and non-alcoholic FLD (NAFLD) was 38.5% and 30.5%, respectively.
FLD was more prevalent in men than women (p<0.001). By multiple logistic regression
analysis on the presence of FLD, only BMI (OR 1.3, p<0.05) was significantly associated
in men, and BMI (OR 1.6, p<0.001), waist circumference (OR 1.1, p<0.01), and hip
circumference (OR .9, p<0.01) were significantly associated in women. With increasing
liver fat category, the number of metabolic syndrome components (p<0.001 both ATP III
and IDF), the cumulative MetS Z-score (p<0.001) and the 10-year Framingham risk score
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(p<0.001) increased as well. We conclude that this study shows a striking prevalence of
FLD in East Anglia, particularly in men. As FLD is associated with several CVD risk
estimates, this striking prevalence may delineate an increased CVD risk in this population.
CHAPTER 3 is a review paper on the cardiovascular disease (CVD) risk of non-alcoholic
fatty liver disease (NAFLD). NAFLD is associated with both hepatic and systemic insulin
resistance. In the case of NAFLD, the liver overproduces several atherogenic factors,
notably inflammatory cytokines, glucose, lipoproteins, coagulation factors, and factors
increasing blood pressure. Intervention studies with diet and bariatric surgery revealed
improvements of hepatic fat content and CVD risk profile. Pharmacological approaches to
reduce liver fat have been developed as well, but the effects are often confounded by
weight change. We conclude that NAFLD is associated with an increased CVD risk profile
(and hepatic risk). In order to improve CVD risk profile, prevention and treatment of
NAFLD seems advisable. However, well designed randomised interventions, and long-term
follow-up studies are scarce.
CHAPTER 4 is a review paper on the pathogenesis of FLD. FLD is the most prevalent
hepatic condition worldwide. Thorough understanding of risk factors and the pathogenesis
of FLD is therefore warranted. Few comprehensive theories on its pathogenesis have been
proposed. The aim of this paper was to critically discuss present theories on the
pathogenesis of FLD, and to arrange risk factors in an easily recognisable manner. The
literature, including behavioural, genetic, and environmental factors associated with FLD
was reviewed, together with their underlying role in the pathogenesis of FLD. Risk factors
for FLD were arranged according to pathogenesis. The following groups of risk factors for
FLD were identified: 1) ‘risk factors for hepatic lipid content’, 2) ‘risk factors for inhibited
hepatic metabolism’, and 3) ‘risk factors for hepatic inflammation’. Some risk factors can
be placed in more than one category and might therefore have a greater effect on FLD than
others. These three categories do not stand alone but interact, forming a downward spiral
onto the development and progression of FLD. We propose to modify current arrangements
of risk factors for FLD. The present arrangement of risk factors may be useful to identify
people at high risk for FLD and to initiate interventions.
CHAPTER 5 describes the development of an ultrasonography method for quantitative
assessment of liver fat content, and validation using magnetic resonance spectroscopy (1H
MRS) as gold standard. Eighteen White volunteers (BMI range 21.0 to 42.9) were scanned
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by both ultrasonography and 1H MRS. Altered ultrasound characteristics, present in the
case of fatty liver disease (FLD), were assessed using a specially developed software
program. Various attenuation and textural based indices of FLD were extracted from
ultrasound images. Using linear regression analysis, the predictive power of several models
(consisting of both attenuation and textural based measures) on log 10-transformed hepatic
fat content by 1H MRS were investigated. The best quantitative model was compared with a
qualitative ultrasonography method, as used in clinical care. A model with four ultrasound
characteristics could modestly predict the amount of liver fat (adjusted explained variance
43.2%, p=0.021). Expanding the model to seven ultrasound characteristics increased
adjusted explained variance to 60% (p=0.015), with r=0.789 (p<0.001). Comparing this
quantitative model with qualitative ultrasonography revealed a significant advantage of the
quantitative model in predicting hepatic fat content (p<0.001). This validation study shows
that a combination of computer-assessed ultrasound measures from routine ultrasound
images can be used to quantitatively assess hepatic fat content.
CHAPTER 6 describes the modification and validation of a recently published Dixon-based
magnetic resonance imaging method (MRI) method/algorithm for quantification of liver fat
content using dual-echo breath-hold gradient echo imaging, with multi-voxel proton
magnetic resonance spectroscopy (1H MRS) as gold standard. Ten men were examined by
MRI and 1H MRS in one measurement session. Using a recently published MRI algorithm,
two problems were encountered: 1) MRI liver fat contents were too high in nine volunteers
(range 3.3-10.7% vs. 0.9-7.7%), and correct in the volunteer with the highest liver fat
content (21.1 vs. 21.3%), and 2) in one of the ten subjects the MRI fat content according to
the Dixon-based MRI method was incorrect due to a (100-x) versus x percent lipid content
mix-up. The second problem was fixed by a minor adjustment of the MRI algorithm.
Despite systematic overestimation of liver fat contents by MRI, Spearman's correlation
between the adjusted MRI liver fat contents with 1H MRS was high (r=0.927, P<0.001).
Even after correction of the algorithm, the problem remaining with the Dixon-based MRI
method for the assessment of liver fat content, is that, at the lower end range, liver fat
content is systematically overestimated by 4%.
CHAPTER 7 describes how we used the MRI method which was developed and validated in
chapter 6 to simultaneously compare fat content in the liver, pancreas, kidney, and
subcutaneous adipose tissue. In 36 volunteers with body mass index (BMI) ranging from
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20.0 to 42.9 kg/m², the median fat contents of liver, pancreas and kidney were 2.3%
(interquartile range: 0.2%-7.8%), 2.7% (1.0%-6.5%) and 0.7% (0.1%-1.4%), respectively.
BMI and subcutaneous fat correlated significantly with liver and pancreas fat contents.
Shown for the first time is significant correlation of the liver and pancreas fat contents in
healthy controls (r=0.43, P<0.01). These observations are related to body weight as
measured by BMI and the amount of subcutaneous fat. Kidney fat content is very low and
correlates with none of the other fat depots. We conclude that renal lipid accumulation,
unlike the coupled accumulations of fat in liver and pancreas, is not observed in obese
subjects. Unlike what has been suggested in previous studies, renal lipid accumulation
appears not to be involved in the pathogenesis of renal disease in humans.
CHAPTER 8 is the general discussion of this thesis. As FLD is associated with health risks,
notably CVD risk as described in chapters 2 and 3, we addressed the question if it would be
beneficial to screen for FLD. The world health organisation (WHO) screening criteria,
originally introduced by Wilson and Jungner, were organised as ‘the condition’,
‘diagnosis’, ‘treatment’, and ‘cost & screening program’ and discussed stepwise. Compared
to reference populations, survival of both patients with non-alcoholic FLD (NAFLD;
including both steatosis and steatohepatitis) and patients with non-alcoholic steatohepatitis
(NASH) is reduced. Moreover, both liver-related mortality and cardiovascular-related
mortality are increased. An estimated 8.3% of patients with NAS will develop fibrosis, and
an estimated 37.6% of patients with NASH will progress in fibrosis stage. Ultrasonography
is an acceptable method for assessing FLD. Most FLD cases have a behaviour-related
etiology, which provides opportunity for treatment. Studies on cost-effectiveness of
screening for FLD are lacking, but prospects are promising given the increased costs (both
financial and quality of life) of patients with FLD. Based on the evidence presented in this
paper, we conclude that screening for FLD is advisable. However, cost effectiveness studies
on screening for fatty liver disease are yet to be performed.
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NEDERLANDSE SAMENVATTING (DUTCH SUMMARY)
In het geval van aanhoudend vetopslag in de lever zal fatty liver disease (FLD) ontstaan.
FLD is een breed spectrum dat begint met alleen vetopslag (steatose), wat kan leiden tot
schade en ontstekingen (steatohepatitis). Steatohepatitis kan leiden tot cirrose en/of
levertumoren. FLD is aanwezig bij 25% tot 40% van de Westerse volwassenen. In een
groot bevolkingsonderzoek toonden we aan dat FLD sterk is geassocieerd met markers van
hart- en vaatziekten. Uit ons literatuur overzicht blijkt dat de vervette lever een verhoogde
productie geeft van vele markers van hart- en vaatziekten, zoals lipiden, glucose,
inflammatoire cytokines, stollingsfactoren (productie daalt in het geval van cirrose), en
factoren die de bloeddruk verhogen. Door af te vallen verbeteren zowel FLD als markers
van hart- en vaatziekten. Daarnaast zijn er veelbelovende farmacologische behandelingen.
Op basis van onze studie en de literatuur stellen we dat risicofactoren voor het ontstaan van
FLD bestaan uit drie categorieën: 1] risico’s voor levervet (b.v. calorie inname, beweging),
2] risico’s voor beperkt lever metabolisme (b.v. alcohol, bepaalde medicatie), en 3] risico’s
voor lever ontsteking (b.v. hepatitis, ziekte van Crohn). Beeldvormende technieken voor het
meten van levervet zijn magnetic resonance spectroscopie en imaging, computed
tomografie, en echografie. Doorgaans wordt echografie kwalitatief gebruikt, maar wij
hebben een kwantitatieve methode ontwikkeld en gevalideerd. Gezien de risico’s, de
meetbaarheid, en de behandelbaarheid, concluderen we dat het zinvol is om te screenen op
FLD, door middel van echografie.
Abbreviations
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LIST OF ABBREVIATIONS
A
AFLD, alcoholic fatty liver disease AGEs, advanced glycation endproducts AL, attenuation line ALT, alanine aminotransferase AR, anterior right ATP ΙΙΙ, adult treatment panel 3 B
BMI, body mass index C
(-CH2-)n, methylene CRP, C-reactive protein CSI, chemical shift imaging CT, computed tomography CVD, cardiovascular disease F
FLD, fatty liver disease (including AFLD and NAFLD) G
GGT, gamma-glutamyl aminotransferase GLUT-4, glucose transporter number 4 H
HC, hepatocyte HCC, hepatocellular carcinoma HDL, high density lipoprotein HFFAs, hepatic free fatty acids 1H MRS, magnetic resonance spectroscopy H2O, water HOMA-IR, insulin resistance by homeostatic model assessment HSC, Hepatic Stellate Cell I
IDF, international diabetes federation IL-6, interleukin 6 IP, in-phase K
KC, Kupffer Cell
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L
LDL, low density lipoprotein M
MetS, metabolic syndrome MetS, metabolic syndrome MR, magnetic resonance MRI, magnetic resonance imaging mRNA, messenger ribonucleic acid
N
NAFLD, non-alcoholic fatty liver disease (including NAS and NASH) NAS, non-alcoholic steatosis NASH, non-alcoholic steatohepatitis NEFA, non-esterified fatty acids NF-κB, nuclear factor kappa-beta O
OP, out-phase P
PL, posterior left PPAR, peroxisome proliferator-activated receptor ppm, parts per million PRESS, point resolved spectroscopy R
ROI, region of interest S
SAT, subcutaneous adipose tissue T
TE, echo time TGs, triglycerides TNFα, tumour necrosis factor-alpha TR, repetition time V
VAT, visceral adipose tissue VLDL, very low density lipoprotein
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Dankwoord (Word of gratitude)
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Hoewel ik zelf natuurlijk de meest significante factor ben geweest in het voltooien van dit
proefschrift ;-) , wil ik een aantal mensen bedanken voor hun significante bijdrage aan het
gehele proces en/of aan afzonderlijke hoofdstukken.
Natuurlijk als eerste, betreffende het gehele proces, mijn promotor Ronald Stolk. Ronald,
bedankt voor alles.
Folkert Kuipers _ Naast je bijdrage aan hoofdstuk 3 waren deze samenwerking en de
‘fatty liver group’ de basis voor een deel van de rest van mijn proefschrift. Waarvoor heel
erg veel dank. Bert Groen _ Dank voor je onmisbare input betreffende hoofdstuk 4.
Bij het ontwikkelen van de kwantitatieve echo methode (hoofdstuk 5), waren nogal een
aantal mensen betrokken. Ik dank Mark Haagmans en prof. van der Jagt voor hun echo
bijdrage, Peter van Ooijen en Wisnu Kristanto voor al hun ideeën en onmisbare bijdrage
betreffende de beeldverwerking van echo’s en het aanpassen van de software, en Wendy
Post voor haar statische bijdrage. Wendy, alias ‘coach Wendy’, ik heb veel van je geleerd
en ik vond het super leuk om met je samen te werken. Tevens dank ik Peter Kappert, Jan-
Hendrik Potze, Irene Willeboordse en Annemarie van Tienhoven voor MR scanning, en
Paul Sijens voor MR analyses. Paul Sijens en Roy Irwan _ dank voor het vragen van
mijn bijdrage bij jullie goede ideeën. Daarnaast bedank ik alle proefpersonen voor hun tijd
en bijdrage aan dit hoofdstuk. Moreover, chapter 5 would not have been possible without
the help of Diana Gaitini and Haim Azhari. Thank you for your pioneer work and your
kind gesture to share your software program with us. A deep bow and big thanks to both of
you and to your team(s). Jan Visscher _ Ook jouw echo bijdragen mogen niet
onopgemerkt blijven. Dank voor al je hulp.
Nita Forouhi _ Thank you for having me over in Cambridge for two weeks, and for your
help with chapter 2. I also thank Ema de Lucia-Rolfe, Richard Powell, Ruhul Amin,
Adam Dickinson, and all other people making the Fenland Study possible. Nick
Wareham _ Thank you for giving me the opportunity to work on the Fenland Study.
Tot slot dank ik de leescommissie: prof. dr. F. Kuipers, prof. dr. M. Oudkerk, en prof.
dr. M. H. Hofker, voor het lezen van het manuscript.
Naast het ‘professionele gedeelte’ van dit dankwoord, wil ik nog een aantal mensen
bedanken.
Allereerst de mensen waar ik tijdens mijn AIO schap het allermeeste mee te maken heb
gehad. Mijn kamergenootjes (my dear roomies), tevens vrienden, in chronologische
volgorde: Hanneke, Josien, Li en Sylvia. Thanks for such a nice ‘home’. Every day was a
fun day with you!
‘Kelderbewoners’ en/of E4 ganggenootjes, tevens vrienden, in alfabetische volgorde:
Carianne, Eryn, Hiltje, Ingrid, en Laura. Naast het zijn van pionier Epi AIO’s, was het
erg leuk om jullie als collega’s te hebben. Daarnaast wil ik jullie bedanken voor alle
activiteiten buiten het werk!
Simona, Sacha, en Hans B, ik kijk met heel veel plezier terug op onze bezoeken aan de
sportschool, onze lunch wandelingen, en onze tafeltennis ‘battles’!
Additionally, I thank all members of the Epi volleyball teams for the nice tournaments, all
(old) floor-E4 colleages (Cleo, Matteusz, Marjan, Karin, Dennis, Judith, and all others) for
the nice chats, and also Aukje and Petra!
Dear paranimfen Li and Simona, thanks for supporting me on the 19th!
Als laatste, maar zeker niet als minste, bedank in mijn vrienden en familie (mam, pap
Edwin, oma’s) voor alle steun!
Mireille Edens
December 2010
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210
Curriculum Vitae About the author & List of publications
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ABOUT THE AUTHOR
Mireille Edens was born in 1980 (September 15th) in Beerta, which is a small village in the
North-East of the Netherlands. She received primary education at the Openbare
Basisschool Beerta and secondary education at the Dollard College Winschoten. Starting
with the MAVO, she subsequently climbed up to the HAVO and to the VWO (A-levels).
In 2000 she started the study Movement Sciences at the University of Groningen. She
performed a scientific internship at the Home Mechanical Ventilation Center (Department
of Pulmonology, University Medical Center Groningen), under supervision of dr. P. J.
Wijkstra. This scientific internship has resulted in two papers on which she graduated with
dr. M. H. G. de Greef.
In 2006 she started a PhD at the department of Epidemiology (University Medical Center
Groningen) under supervision of prof. dr. R. P. Stolk. The result of her PhD is currently
lying in front of you ...
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LIST OF PUBLICATIONS
9. Edens MA, Forouhi NG, de Lucia-Rolfe E, Wareham NJ, Stolk RP, and other investigators of the Fenland Study; Authors to be determined.
Fatty liver disease and cardiovascular risk in the general population of East Anglia: The Fenland Study. In preparation/ awaiting enlargement of database.
8. Edens MA, Leegte MC, ter Veen J, van Weert E, Jager PL, de Greef MH, Wijkstra PJ. The clearance ability of cough assisting techniques in patients with a neuromuscular disease: Results of a pilot study. Submitted/ under review.
7. Edens MA, Stolk RP. Evidence on screening for fatty liver disease: Future perspectives.
Submitted/ under review _ Review Paper
6. Edens MA, Groen AK, Stolk RP. Pathogenesis of fatty liver disease: A theory on lipid content, inhibited metabolism, and inflammation.
Submitted/ under review _ Review Paper
5. Sijens PE, Edens MA, Bakker SJ, Stolk RP. MRI-determined fat content of human liver, pancreas and kidney. World J Gastroenterol 2010; 16(16):1993-1998.
4. Edens MA, van Ooijen PM, Post WJ, Haagmans MJ, Kristanto W, Sijens PE, van der Jagt EJ, Stolk RP. Ultrasonography to quantify hepatic fat content: Validation by 1H Magnetic Resonance Spectroscopy.
Obesity (Silver Spring) 2009; 17(12):2239-2244.
3. Edens MA, Kuipers F, Stolk RP. Non-alcoholic fatty liver disease is associated with cardiovascular disease risk markers.
Obes Rev 2009; 10(4):412-419 _ Review Paper
2. Irwan R, Edens MA, Sijens PE. Assessment of the variations in fat content in normal liver using a fast MR imaging method in comparison with results obtained by spectroscopic imaging. Eur Radiol 2008; 18(4):806-813.
1. Edens MA, van Son WJ, de Greef MH, Levtchenko EN, Blijham T, Wijkstra PJ. Successful treatment of respiratory dysfunction in cystinosis by nocturnal non-invasive positive pressure ventilation. Clin Nephrol. 2006 Oct;66(4):306-309.
In addition to the papers listed above, Mireille also hopes to publish (parts of) chapter 1, and some