Cognitive and Brain Aging in the Baltimore Longitudinal Study of Aging Susan M. Resnick, Ph.D. Laboratory of Personality and Cognition National Institute.

Cognitive and Brain Aging in the Baltimore Longitudinal Study of Aging

Susan M. Resnick, Ph.D.Laboratory of Personality and Cognition

National Institute on Aging

Cognitive and Brain Aging in Older Adults

What is the background upon which drug abuse is superimposed?

Which aspects of cognition show age-related decline in individuals without dementia?

How does the brain change with age?Structural changesFunctional changesfMR probes of specific regions

Baltimore Longitudinal Study of AgingBLSA

Study initiated in 1958

Women studied since 1978

Highly educated community-dwelling sample

GRC visits every 2 years for 2 1/2 days

Behavioral and physical assessments

Prospective diagnoses of dementia

Information on alcohol and smoking but no systematic information on other substance abuse

Age Effects Vary Across Specific Cognitive Functions

Some abilities are preserved throughout the lifespan, e.g. over-learned skills such as Vocabulary

Vocabulary

Other specific functions show declines

–Different abilities may begin declining at different ages

–Different abilities may decline at different rates

Benton Visual Retention Test BVRT

Age Effects Vary Across Specific Cognitive Functions

Age Differences and Longitudinal Changes on the BVRT

Cross-sectional Longitudinal

California Verbal Learning Test

60 65 70 75 80 85

Age

5

7

9

11

13

15FemaleMale

Longitudinal Change in Delayed Verbal Memory

N = 266N = 345

Neurology 2003

CVLT Long Delay Free Recall:Rates of Change are Variable Across Individuals

Age > 60Mean 72.3

Prior Cognitive Testing

Annual EvaluationMen and Women (Age 55-85)

MRIBrain StructureIschemic Change

PET-CBFRest

Verbal MemoryFigural Memory

NeuropsychologicalTesting

LPC Neuroimaging StudyEarly Markers of Alzheimer’s Disease and Cognitive Decline

Without Prior Neurologic or Severe Cardiovascular Disease

LPC Neuroimaging Assessments: 2/10/94 through 6/03/04

ASSESSMENT MEN WOMEN TOTAL1 94* 69* 163

2 88 63 151

3 82 59 141

4 77 59 136

5 73 57 130

6 71 55 126

7 68 53 121

8 61 45 106

9 48 38 86

10 16 13 29

TOTAL 678 511 1189

Goals

To determine the rates of structural and functional brain changes as a prerequisite for identification of disease.

To determine whether some regions are more vulnerable to tissue loss and functional changes.

To identify brain changes that predict cognitive impairment and dementia.

To identify factors that modify brain-behavior associations in aging.

Variability in BLSA Brain Morphology (N = 18)

1 2 3

4

OriginalOriginal Automated Skull-StrippingAutomated Skull-Stripping Manual EditingManual Editing

SegmentationSegmentation

MR Image Processing Using RAVENS

158 Average Model

Cross-sectional: Both Gray and White Matter Volumes Are Negatively Correlated with Age

Gray Volume White Volume

300

400

500

600

700

50 60 70 80 90

cm3

AGE

r = -.23

300

400

500

600

700

50 60 70 80 90cm

3

AGE

r = -.29

WOMEN MENResnick et al. Cerebral Cortex

2000;10:464N = 116; Mean Age 70.4 (7.5)

Longitudinal: Brain and CSF Volumes are Measured with High Reliability over Four Years

Brain (G+W) Ventricles

(n = 92, Mean Age= 70.4)

Brain Gray White Ventricles-8

-6

-4

-2

0

2

4

An

nu

al

Ra

te o

f C

han

ge (

cm

3)

1.221.451.39

-2.4-3.29

-3.06

-1.32

-2.76-2.39

-3.72

-6.05

-5.45

All (n = 92)

Some Medical (n = 68)

Healthy (n = 24)

Annual Changes in Brain Volumes over 4 Years Resnick et al. J Neuroscience 2003

BRAIN GRAY WHITE VENTRICLES-8

-6

-4

-2

0

2

4

-5.28-5.79

-2.40 -2.49-2.89

-3.30

1.141.75

<70 (N = 55)

70+ (N = 39)

An

nu

al R

ate

of

Ch

ang

e (c

m3)

Longitudinal Brain Changes are Evident in Younger and Older Individuals

***

*** p < .001

4-year Gray Matter Loss in Specific Regions

Longitudinal Decreases and Increases in GM

Qualitative Changes in Tissue Composition Measured by Signal Intensity

Age Effects on Tissue Composition:Decreased Gray-White Signal Contrast

0.22

0.24

0.26

0.28

0.30

0.32

50 60 70 80 90

AGE

W

M

r = -.49

Tis

su

e C

on

tra

st

Year 1 Year 3 Year 50.260

0.265

0.270

0.275

0.280

***p < .001

Cross-sectional Longitudinal

Age Differences and Age Changes in Regional Cerebral Blood Flow (rCBF)

PET Sample Characteristics

MenMen WomenWomen

N 4646 37

Age (yrs) 70.9 ± 7.3 70.6 ± 7.9

ApoE e4 (No. -/+) 34/12 24/13

Mild memory loss* (No. -/+) 41/5 31/6

*Clinical Dementia Rating (CDR) > 0.5

PET Results: Cross-sectional Effects ofAge on Resting rCBF

L

L

R

R

Older compared with younger individuals show selective decreases in rCBF in insular (INS), cingulate (CG), and inferior temporal (IT) regions.

INS

CG

IT

Longitudinal Age Changes in Resting rCBF

L

L

R

R

Longitudinal declines in rCBF over 4 years are observed in bilateral superior temporal, right middle temporal, inferior parietal and midline occipital regions.

Age Influences the RATE of rCBF Decline in the Mesial Temporal Lobe

L

L

R

R

Older individuals show faster rates of decline in mesial temporal rCBF.

Functional Brain Changes with PET

Regional decreases in resting rCBF are observed in older individuals, with the greatest differences apparent in insular, cingulate and temporal regions, including hippocampus.

These changes reflect a combination of structural and functional brain changes.

With increasing longitudinal interval, we are investigating associations between specific brain and cognitive changes.

fMR Probes for Regions Vulnerable to Aging

fMR OFC Sample

Younger Adults Older Adults

n 20 (10M/10F) 20 (10M/10F)

Age (yrs) 28.7 (6.4) 69.3 (5.2) (range) 20-40 60-80

Education (yrs) 15.2 (2.4) 15.0 (3.6)MMSE 29.4 (1.0) 28.9 (1.6)CESD 7.5 (4.1) 4.7 (5.2)

Younger Adults Activate Predicted OFC RegionsLamar, Yousem, Resnick NeuroImage 2004

Medial OFC (p<.01) Lateral OFC (p=.01)

Match - NonMatch NonMatch - Match

Older Adults Activate Posterior RegionsLamar, Yousem, Resnick NeuroImage 2004

Match - NonMatch NonMatch - MatchAssociation Cortices (ns) DLPFC (p=.006)

Conclusions

Cognitive and brain changes associated with drug abuse in the elderly will be superimposed upon a changing brain.

Some but not all cognitive functions show age changes.

Many but not all individuals show age changes in cognition and brain structure and function.

BLSA Cognition and Neuroimaging Study: Possibilities for Studies of Drug Abuse

Assessments of older adults continue and neuroimaging studies will be expanded with the NIA IRP MRI facility.

Potential to include additional assessments.

Abuse of prescription medications, including pain-killers will be most informative in this sample.

Collaborators: Neuroimaging Project

NIA JHU

Alberto Goldszal, PhD Christos Davatzikos, PhD Dzung Pham, PhD Michael Kraut, MD, PhDMelissa Lamar, PhD R. Nick Bryan, MD, PhDScott Moffat, PhD Jerry Prince, PhDStephanie Golski, PhD

JHU PET Facility

Robert Dannals, PhDHayden Ravert, PhD

Neuroimaging Participant Selection

Inclusion:• Age 55-85• Prior cognitive and memory assessment

Exclusion:• Existing neurologic disease, including dementia

(mild cognitive decline is not exclusionary)

• Severe cardiovascular disease (hypertension alone is not exclusionary)

• Metastatic cancer• Weight greater than 300 lbs or other factors precluding

neuroimaging assessment

-4.0

-3.5

-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

4- 4+

An

nu

al R

ate

of

Ch

an

ge

(%

)Risk Factor: APOE 4 genotype is associated

with accelerated hippocampal volume loss

Neurology 2000;55:134-136.

N = 13 N = 13

Temporal Horn Brain

N = 82 N = 12 N = 82 N = 12

***

Increases in Temporal Horn Volumes Predict Mild Cognitive Impairment by CDR Score

Annual percentage changes from baseline, respectively for brain, gray, white, and ventricular volumes:

entire sample -0.55 (0.5), -0.42 (0.9), -0.67 (1.5), 4.82 (2.5); subgroup with some medical problems -0.62 (0.5), -0.50 (0.9), -0.73 (1.6), 4.97 (2.7);

very healthy -0.36 (0.4), -0.19 (0.8), -0.48 (1.4), 4.39 (1.5).

Automated analysis of specific regions with HAMMER and brain atlas*

Template brain

(*regional outlines provided by Noor Kabani)

BLSA brain

Gray White

Age Differences and Age Changes in Spatial Rotation: Card Rotations Test

Age Effects on Regional White Matter Signal Intensities

L

L

L R

R

L

L

L RR

Age differences 4-year decline

Davatzikos and Resnick. Cerebral Cortex 2002;12:767-771

Analysis of 4-Year Change in MRI Volumes:Sample Characteristics

MEN WOMEN TOTAL

N 50 42 92

Age (yrs) 70.5 ± 6.4 70.4 ± 7.7 70.4 ± 7.0

Education (yrs) 16.0 ± 3.2 16.2 ± 2.4 16.1 ± 2.8

Handedness (R:L) 47:3 40:2 87:5 Race (White:

Nonwhite) 48:2 36:6 84:8

PET Analysis

IMAGE PROCESSING AND STATISTICAL ANALYSIS:

Preprocessing using SPM99 and the STAR algorithm for elastic stereotaxic normalization

Voxel-based statistical analysis using customized SPM99 software

– Cross-sectional analysis: mean CBF across Years 1, 3, and 5

– Longitudinal analysis: rates of change over time

Significance threshold: p < .01 and cluster size > 35

Summary:Age-Related Structural Changes

Regional brain structure can be measured reliably over time.

Both gray and white matter volumes show longitudinal declines even in the healthy elderly.

Increases in ventricular volumes are greater in older than younger individuals.

There are regional patterns to both tissue loss and qualitative changes in tissue composition.