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Biochemical Markers of Insulin Sensitivity at 24-28 Weeks of Gestation in Chinese American Population Vanessa Sy 1 , So-Young Kim 1 , Takako Araki 1 , Diana Huang 2 , Anjit Khurana 1 , Emilia Liao 1 , Doris Tan 2 , George Liu 1 , Stephen Wan 2 , Leonid Poretsky 1 , Donna Seto-Young 1 1 Division of Endocrinology and Friedman Diabetes Institute, Department of Medicine; 2 Department of Obstetrics and Gynecology, Beth Israel Medical Center and Albert Einstein College of Medicine, New York, NY 10003
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Jan 30, 2016

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Biochemical Markers of Insulin Sensitivity at 24-28 Weeks of Gestation in Chinese American Population. Vanessa Sy 1 , So-Young Kim 1 , Takako Araki 1 , Diana Huang 2 , Anjit Khurana 1 , Emilia Liao 1 , Doris Tan 2 , George Liu 1 , Stephen Wan 2 , Leonid Poretsky 1 , Donna Seto-Young 1. - PowerPoint PPT Presentation
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Page 1: Introduction

Biochemical Markers of Insulin Sensitivity at 24-28 Weeks of

Gestation in Chinese American Population

Vanessa Sy1, So-Young Kim1, Takako Araki1, Diana Huang2, Anjit Khurana1, Emilia Liao1, Doris Tan2, George Liu1, Stephen Wan2,

Leonid Poretsky1, Donna Seto-Young1

1Division of Endocrinology and Friedman Diabetes Institute, Department of Medicine; 2Department of Obstetrics and Gynecology, Beth Israel Medical Center and Albert Einstein

College of Medicine, New York, NY 10003

Page 2: Introduction

Introduction

Pregnancy is a complex metabolic state that involves remarkable changes in hormone levels (1)

The first trimester is associated with increased insulin sensitivity that promotes adipose tissue accumulation. During this time, pregnant women are at increased risk for hypoglycemia.

Glycogen stores are depleted quickly during the fasting state due to high feto-placental glucose demand. This results in increased lipolysis and ketone production

On the other hand, the second and third trimesters are characterized

by insulin resistance. As levels of cortisol, progesterone, estrogen, prolactin, and human

placental lactogen rise, insulin resistance develops (2)

Page 3: Introduction

Introduction

Placenta-derived hormones are believed to be a major factor in reprogramming maternal physiology to achieve an insulin-resistant state.

Insulin resistance is the inability of a defined concentration of insulin to achieve a predictable biological response of nutrient metabolism at the level of the target tissue

Insulin resistance results in: decreased glucose uptake in skeletal muscle, white adipose tissue and liver decreased suppression of hepatic glucose production inability of insulin to suppress lipolysis decreased ability of insulin to suppress amino acid turnover

Pregravid insulin resistance coupled with inadequate insulin response are underlying factors leading to gestational diabetes (3)

Page 4: Introduction

Introduction

• Insulin resistance markers:

Insulin – increased insulin level is involved in developing insulin resistance and GDM(4)

Insulin-like Growth Factor-I (IGF-I)(4) promotes growth and differentiation has also been shown to mimic metabolic actions of insulin, including

stimulation of glucose and inhibition of gluconeogenesis circulating free IGF-1 has been shown to be elevated in increasing

BMI .

Insulin-like Growth Factor-Binding Protein 1 (IGFBP-1) hyperinsulinemia suppresses IBFBP-1 production and increases

free IGF-I (5)

The roles of IGF-I and IGFBP-I in GDM are not yet clearly understood

Page 5: Introduction

Introduction

• Fibroblast Growth Factor-21 (FGF-21)

protein that stimulates glucose uptake in adipocytes has previously been reported to be associated with markers of insulin

resistance (6-7)

A previous study showed that FGF-21 was significantly correlated with decreased adiponectin and dyslipidemia (increased triglycerides, decreased HDL) (6)

In another study, FGF-21 was found to be significantly greater in DM2

patients compared to control patients (7) The role of FGF-21 in GDM is still unknown

Page 6: Introduction

Introduction

• Inflammatory markers C-Reactive Protein (CRP), and pro-inflammatory cytokines Interleukin-6 (IL-6) and Tumor Necrosis Factor-alpha (TNF-) are elevated in individuals with DM2 (8)

CRP (9)

• Produced primarily in the liver under the stimulation of adipocyte-derived IL-6 and TNF-

• Studies have shown this to be correlated with parameters relevant to diabetes including obesity, lipogenesis and adiponectin.

• It has been consistently associated with the incidence of DM2

Page 7: Introduction

Introduction

IL-6(9)

• Produced by many cell types which include: endothelial cells, monocytes-macrophages, and fibroblasts

• 15-30% of circulating IL-6 are derived from adipose tissue production, to modulate adipocyte glucose and lipid metabolism

• Obesity causes IL-6 upregulation in adipocytes• Studies have shown IL-6 to be correlated with the extent of insulin

resistance

TNF- (9)

• Produced by activated mononuclear phagocytes, T-cells, Natural killer cells, and mast cells

• A previous study has shown a 2.5-fold increase in adipose tissue TNF- mRNA expression in obese subjects; there was also a strong correlation of TNF- mRNA expression with hyperinsulinemia

Page 8: Introduction

Introduction

• Monocyte Chemoattractant Protein-1 (MCP-1) (10)

– Produced by macrophages and endothelial cells, it is a chemokine with an agonistic effect for monocytes, memory T cells and basophils

– It is thought to be a key player in the recruitment of monocytes for atheroma formation

– Studies showed that MCP-1 may be released from adipocytes, with an increased secretion and expression in obesity

– Obesity being a constituent of the metabolic syndrome (along with DM2), has initiated several studies linking MCP-1 to insulin resistance

Page 9: Introduction

Introduction

• Leptin (11)

- An amino acid secreted by adipocytes proportionate to their total tissue mass

- A rise in leptin levels signals satiety to the brain through receptors in the hypothalamic and brainstem neurons

- Aside from its action on the appetite-regulating center of the brain, previous studies have linked leptin to the CNS regulation of glucose metabolism which may relate to the pathogenesis of insulin resistance and DM2 associated with obesity

• Retinol Binding Protein 4 (RBP4) (12) - A transport protein for retinol secreted by adipocytes and the liver

- Previously published studies suggest that RBP4 may be one of the key components in explaining the association between obesity and insulin resistance

- Elevated RBP4 levels have been shown to increase hepatic glucose output and cause increased insulin resistance

Page 10: Introduction

Introduction

• Adiponectin– Secreted solely by adipocytes and has been linked to glucose, lipid, and

cardiovascular regulation (11)

– Reduced adiponectin levels have been associated with obesity, diabetes and, atherosclerosis (13 , 11)

– Adiponectin circulates in human plasma as a low molecular weight hexamer/monomer and a high molecular weight (HMW) multimer (11)

– Some studies suggest that the HMW adiponectin multimer may be an important biomarker for insulin resistance(14)

Page 11: Introduction

Introduction

• Resistin– an adipocyte-derived polypeptide whose role in obesity

and DM2 has been the subject of much controversy as different studies have shown contradictory findings (15)

Page 12: Introduction

Introduction

Some studies have shown an elevation of the following biomarkers in DM2 and GDM:• Insulin• IGF-I• CRP• Leptin • Retinol Binding Protein 4 (RBP4)

Adiponectin was found to be decreased in GDM & metabolic syndrome

Adiponectin multimer, and not the monomer, is a marker for evaluating DM2

The roles of the following remain unclear in GDM & DM2 as various contradicting findings have been reported:• Fibroblast Growth Factor-21 (FGF-21)• Resistin • Insulin Growth Factor Binding Protein-1 (IGFBP-1)

Page 13: Introduction

Introduction

A study found that at a lower BMI, Chinese Americans have: (16)

• Higher fasting insulin level• Increased chronic inflammatory markers• Altered circulating adipokines

Our previous studies (unpublished) showed that there were lower levels of adiponectin monomer and multimer in Chinese Americans with GDM

To our knowledge, there has not yet been a report that examined all of the above mentioned biomarkers in Chinese American pregnant women within a single study

Page 14: Introduction

Goals of the Study

To analyze the relationships among the following markers in Chinese Americans at 24-28 weeks of gestation

Insulin IGF-I IGFBP-1

Adipocytokines: adiponectin monomer, adiponectin multimer, RBP4,

and leptin CRP TNF- IL-6 MCP-1 Resistin FGF-21

Page 15: Introduction

Methods

Beth Israel Medical Center’s Institutional Review Broadapproval was obtained for this project and all consent forms were translated into Chinese.

Inclusion Criteria:

- 18 to 40 years of age - Pregnant (24-28 weeks of pregnancy) - Chinese ethnicity

Page 16: Introduction

Methods

Exclusion Criteria:

• Cognitive impairment• Prior established diagnosis of DM2• Hepatitis B or other infectious diseases• Thyroid dysfunction• Thalassemia • History of miscarriages• Infertility with use of In-Vitro Fertilization

Page 17: Introduction

Methods

Information collected:

• Family history of DM2 or previous GDM• Age• Height• Weight• Blood pressure• 1-hour Glucose Challenge Test (GCT, 50-gram) • 3-hour Glucose Tolerance Test (GTT, 100-gram)• HgA1C

Page 18: Introduction

Methods

For the ELISA procedures, blood samples were drawn 1 hour after the 50-gram oral glucose challenge.

Blood samples were centrifuged at 2000 rpm for 10 mins, and sera were collected and stored at -80 degrees Centigrade until ELISA was performed.

ELISA kits were obtained from the American Laboratory Products Company (ALPCO, Salem, NH), and included the following:

Insulin IGF-1 IGFBP-1 Leptin Adiponectin (monomer) Adiponectin (multimer) Resistin RBP4 FGF-21 CRP

TNF- MCP-1 IL-6

Page 19: Introduction

Statistical Analysis

• Data were analyzed using the SPSS system to calculate the Pearson correlation coefficients of glucose, HbA1C,Insulin, BMI and systolic blood pressure (SBP) against the different biomarkers

Page 20: Introduction

RESULTS

n = 136 mean age: 31.0+ 4.9 years mean glucose levels (1-hr GCT) : 117.5+ 25.9 mg/dL mean HbA1c: 5.3% + 0.4 mean BMI: 24.4 + 3.0

Glucose, HbA1c, Insulin, BMI and SBP were each correlated individually with leptin, adiponectin monomer/multimer, resistin, IGF-1, IGFBP-1, FGF-21, RBP4, CRP, TNF-, IL-6 and MCP-1

Statistically significant correlations are presented in the following figures

Study Population

Page 21: Introduction

RESULTSFigure 1

Glucose (mg/dL)

40 60 80 100 120 140 160 180 200

Syst

olic

blo

od p

ress

ure

(mm

Hg)

80

100

120

140

Glucose vs. Systolic Blood Pressure

Glucose (mg/dL)

40 60 80 100 120 140 160 180 200

Insu

lin (n

g/m

l)

0

100

200

300

Glucose vs. Insulin

R=0.19p<0.025

R=0.489p<0.001

Glucose (mg/dL)

40 60 80 100 120 140 160 180 200

Adi

pone

ctin

mon

omer

( g

/ml)

0

10

20

30 Adiponectin m

ultlimer (

g/m

l)

0

10

20

30

Glucose vs. Adiponectin Monomer Glucose vs Adiponectin Multimer

R= -0.291p<0.001

R= -0.287p<0.001

N=136

Page 22: Introduction

Results

Figure 1: Using the entire cohort, Pearson’s correlation analyses were performed.

• There is positive correlation between glucose level and:systolic blood pressure (SBP) (R=0.19, p<0.025) insulin (R=0.489, p<0.001).

• There is negative correlation between glucose level and:adiponectin monomer (R= -0.291, p<0.001) adiponectin multimer (R= - 0.287, p<0.001).

Page 23: Introduction

RESULTSFigure 2

N=136

Page 24: Introduction

Results

Figure 2:• There is positive correlation between HbA1c and

CRP (R=0.2, p<0.025)

• There is negative correlation between HbA1c and adiponectin monomer (R= -0.256, p<0.003) resistin (R= -0.176, p<0.042).

Page 25: Introduction

RESULTSFigure 3

Insulin (ng/mL)

0 50 100 150 200 250 300 350

IGF-

1 (n

g/m

L)

0

100

200

300

400

500

Insulin vs. IGF-I Insulin vs FGF-21

Insulin (ng/mL)

0 50 100 150 200 250 300 350

IGFB

P-1

(ng

/mL)

0

100

200

300

400

500

Insulin vs. IGFBP-1

Insulin (ng/mL)

0 50 100 150 200 250 300 350

Adi

pon

ectin

Mon

om

er (u

g/m

L)

0

10

20

30

Adip

onectin

Multim

er (ug/m

l)

0

10

20

30

Insulin vs. Adiponectin Monomer Insulin vs Adiponectin Multimer

R=0.346p<0.001

R= -0.318p<0.001

R= -0.23p<0.007

R=0.197p<0.023

R=0.304p<0.001

N=136

Page 26: Introduction

Results

Figure 3:

• There is positive correlation between insulin and IGF-1 (R= 0.346, p<0.001) FGF-21 (R=0.197, p<0.023)

• There is negative correlation between insulin and IGFBP-1 (R=-0.304, p<0.001), adiponectin monomer (R= -0.23, p<0.007) adiponectin multimer (R= -0.318, p<0.001)

Page 27: Introduction

RESULTSFigure 4

BMI (lbs/in2)

16 18 20 22 24 26 28 30 32 34 36

Sys

tolic

Blo

od

Pre

ssu

re (

mm

Hg

)

0

20

40

80

100

120

140

160

Res

istin

(ug

/mL

)

0

20

40

80

100

120

140

160

BMI vs. Systolic Blood Pressure BMI vs Resistin

BMI (lbs/in2)

16 18 20 22 24 26 28 30 32 34 36L

ep

tin

(n

g/m

L)

0

10

20

30

40

50

60

BMI vs. Leptin

BMI (lbs/in2)

16 18 20 22 24 26 28 30 32 34 36

CR

P (

ug

/mL

)

0

20

40

60

RB

P4 (

mg

/L)

0

20

40

60

BMI vs. CRP BMI vs RBP4

R=0.213p<0.014

R=0.216p<0.016

R=0.363p<0.001

R=0.433p<0.001

BMI (lbs/in2)

16 18 20 22 24 26 28 30 32 34 36

Ins

ulin

(n

g/m

L)

0

100

200

300

BMI vs. Insulin BMI vs FGF-21

BMI (lbs/in2)

16 18 20 22 24 26 28 30 32 34 36

IGF

BP

-1 (

ng

/mL

)

0

100

200

300

400

500

BMI vs. IGFBP-1

BMI (lbs/in2)

16 18 20 22 24 26 28 30 32 34 36

Ad

ipo

necti

n M

on

om

er

(ug

/mL

)0

10

20

30

Ad

ipo

nectin

Mo

no

mer (u

g/m

L)

0

10

20

30

BMI vs. Adiponectin Monomer BMI vs Adiponectin Mutimer

R=0.233p<0.007

R= -0.237p<0.008

R=0.266p<0.002

R= -0.181p<0.037

R=0.222p<0.022

R= -0.221p<0.01

N=136

Page 28: Introduction

Figure 4:

• There is positive correlation between BMI and the following:

SBP (R=0.363, p<0.001) resistin (R=0.213, p<0.014) leptin (R= 0.433, p<0.001) CRP (R=0.216, p<0.016) RBP4 (R=0.266, p<0.002) Insulin (R=0.233, p<0.007) FGF-21 (R=0.222, p<0.022)

• There is negative correlation between BMI and the following:

IGFBP-1 (R= -0.237, p<0.008), adiponectin monomer (R= -0.181, p<0.037) adiponectin multimer (R= -0.221, p<0.01)

Results

Page 29: Introduction

Conclusion

For most biomarkers that we examined, the findings in Chinese Americans are similar to those reported in the literature in other populations

The new findings in our study are:• Adiponectin monomer is consistently associated with glucose levels, HbA1c,

insulin and BMI• Resistin is positively correlated with BMI, but negatively correlated with HbA1c• IL-6, TNF-, and MCP-1 did not show any correlation with HbA1c and BMI. Only

CRP is correlated with both HbA1c and BMI

These findings suggest that the mechanisms underlying the development of diabetes in pregnant Chinese Americans may differ from other populations. Larger future studies are needed to confirm this conclusion

Page 30: Introduction

Limitation

Study was limited by:

• Sample size of 136 patients

• Lack of a control group

Page 31: Introduction

Acknowledgements

The Gerald J. Friedman Diabetes Institute

Chinese American Medical Society & Chinese American Independent Practice Association Research Fund

The Yen Family Foundation

Page 32: Introduction

References

• 1. Barbour LA, McCurdy CE, Hernandez TL et al. Cellular mechanism for insulin resistance in normal pregnany and gestational diabetes. Diabetes Care 2007;30:S112-S119.

• 2. Schneider AE, Rayfield EJ, Busta A, Gurevich Y Diabetes in Pregnancy. In: Poretsky, L Principles of Diabetes Mellitus. 2nd Ed. Ney York, NY: Springer.2009; 233.

• 3. Catalano PM, Kirwan JP, de Mouzon SH, et al. 2003 Gestational diabetes and insulin resistance: role in short- and long-term implications for mother and fetus. J Nutr 133: 1674S-1683S

• 4. Sjögren K, Wallenius K, Liu JL, Bohlooly-Y M, Pacini G, Sevensson L, Törnell, Isaksson OGP, Ahrén B, Jansson JO, Ohlsson C. 2001 Liver-derived IGF-I is of impotance of normal carbohydrate and lipid metabolism. Diabetes 50(7) :1539-1545

• 5. Kabir G, Hossain M, Faruque MO, Hassan N, Hassan Z, Nahar Q, Shefin SM, Alauddin M, Ali L. Assocation of serum free IGF-1 and IGFBP-1 with insulin sensitivity in impaired glucose tolerance (IGT). International Journal of Diabetes Mellitus. 2010;2:144-147

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• 7. Matuszek B, Lenart-Lipinska M, Duma D, Solski J, Nowakowski A. Evaluation of concentrations of FGF-21 – a new adipocytokine in type 2 diabetes. 2010; 61 (1): 50-54

• 8. Radaelli T, Varastehpour A, Catalano P, de Mouzon SH. 2003 Gestational diabetes induces placental genes for chronic stress and inflammatory pathways.Diabetes 52: 2951-2958

• 9. Badawi A, Klip A, Haddad P, et al. 2010 Type 2 diabetes mellitus and inflammation: Prospects for biomarkers at risk and nutritional intervention. Diabetes, Metabolic Synd and Obesity: Targets & Therapy 2010: 3 173-186

• 10. Chacon MR, Fernandez JM, Richart C, et al. 2007. Monocyte Chemoattractant Protein-1 in Obesity and type 2 diabetes. Insulin sensitivity study. Obesity 15: 664-672

• 11. Ahima RS 2006 Adipose tissue as an endocrine organ. Obesity Supp 15 242S-249S.

• 12. Klein K, Bancher-Todesca D, Leipold H, Knofler M, Haslinger P, HAndisurya A, Kautzky-Willer A, Worda C. Retinol-Binding Protein 4 in Patients with Gestational Diabetes Mellitus. 2010: 19(3); 517-521.

Page 33: Introduction

References

• 13. Retnakaran R, J.G. Hanley A, Raif N, W.Connelly P, Sermer M, Zinman B. C-Reactive Protien and Gestational Diabetes: The Central Role of Maternal Obesity. 2003 The Journal of Endocrinology and Metabolism 88(8):3507-3512.

• 14. Lara-Castro C, Luo N, Wallace P et. Al. Adiponectin multimeric complexes and the metabolic syndrome trait cluster. 2006 Diabetes 55:249-259.

• 15. Kusminski CM, McTernan PG, Kumar S. Role of resistin in obesity, insulin resistance and Type II diabetes. Clinical Science (2005). 109:243-256 REVIEW ARTICLE

• 16. Liew CF, Seah ES, Yeo KP, Lee KO, Wise SD. 2003 Len, nondiabetic Asian Indians have decreased insulin sensitivity and insulin clearance