1. 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

2. Cognitive and Brain Aging in Older Adults u What is the background upon which drug abuse is superimposed? u Which aspects of cognition show age-related decline in individuals without dementia? u How does the brain change with age?  Structural changes  Functional changes  fMR probes of specific regions

3. Baltimore Longitudinal Study of Aging BLSA u Study initiated in 1958 u Women studied since 1978 u Highly educated community-dwelling sample u GRC visits every 2 years for 2 1/2 days u Behavioral and physical assessments u Prospective diagnoses of dementia u Information on alcohol and smoking but no systematic information on other substance abuse

4. Age Effects Vary Across Specific Cognitive Functions u Some abilities are preserved throughout the lifespan, e.g. over-learned skills such as Vocabulary Vocabulary

5. u 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

6. Age Differences and Longitudinal Changes on the BVRT Cross-sectionalLongitudinal

7. California Verbal Learning Test

8. Longitudinal Change in Delayed Verbal Memory N = 266 N = 345 Neurology 2003

9. CVLT Long Delay Free Recall: Rates of Change are Variable Across Individuals Age > 60 Mean 72.3

10. Prior Cognitive Testing Annual Evaluation Men and Women (Age 55-85) MRI Brain Structure Ischemic Change PET-CBF Rest Verbal Memory Figural Memory Neuropsychological Testing LPC Neuroimaging Study Early Markers of Alzheimer’s Disease and Cognitive Decline Without Prior Neurologic or Severe Cardiovascular Disease

11. LPC Neuroimaging Assessments: 2/10/94 through 6/03/04 ASSESSMENTMENWOMEN TOTAL 1 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 1016 13 29 TOTAL 678 511 1189

12. Goals u To determine the rates of structural and functional brain changes as a prerequisite for identification of disease. u To determine whether some regions are more vulnerable to tissue loss and functional changes. u To identify brain changes that predict cognitive impairment and dementia. u To identify factors that modify brain-behavior associations in aging.

13. Variability in BLSA Brain Morphology (N = 18)

14. 123 4 Original Automated Skull-Stripping Manual Editing Segmentation MR Image Processing Using RAVENS 158 AverageModel

15. Cross-sectional: Both Gray and White Matter Volumes Are Negatively Correlated with Age Gray Volume White Volume 300 400 500 600 700 5060708090 cm 3 AGE r = -.23 300 400 500 600 700 5060708090 cm 3 AGE r = -.29 WOMENMEN Resnick et al. Cerebral Cortex 2000;10:464 N = 116; Mean Age 70.4 (7.5)

16. Longitudinal: Brain and CSF Volumes are Measured with High Reliability over Four Years Brain (G+W)Ventricles (n = 92, Mean Age= 70.4)

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

18. Annual Rate of Change (cm3) Longitudinal Brain Changes are Evident in Younger and Older Individuals *** *** p <.001

19. 4-year Gray Matter Loss in Specific Regions

20. Longitudinal Decreases and Increases in GM

21. Qualitative Changes in Tissue Composition Measured by Signal Intensity

22. Age Effects on Tissue Composition: Decreased Gray-White Signal Contrast Tissue Contrast *** p <.001 Cross-sectionalLongitudinal

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

24. PET Sample Characteristics MenWomen 46 N 4637 Age (yrs)70.9 ± 7.3 70.6 ± 7.9 ApoE e4 (No. -/+) 34/1224/13 Mild memory loss* (No. -/+) 41/5 31/6 *Clinical Dementia Rating (CDR) > 0.5

25. PET Results: Cross-sectional Effects of Age 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

26. 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.

27. 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.

28. Functional Brain Changes with PET u Regional decreases in resting rCBF are observed in older individuals, with the greatest differences apparent in insular, cingulate and temporal regions, including hippocampus. u These changes reflect a combination of structural and functional brain changes. u With increasing longitudinal interval, we are investigating associations between specific brain and cognitive changes.

29. fMR Probes for Regions Vulnerable to Aging

30. fMR OFC Sample Younger AdultsOlder Adults n20 (10M/10F)20 (10M/10F) Age (yrs)28.7 (6.4)69.3 (5.2) (range)20-4060-80 Education (yrs)15.2 (2.4)15.0 (3.6) MMSE29.4 (1.0)28.9 (1.6) CESD 7.5 (4.1) 4.7 (5.2)

31. Younger Adults Activate Predicted OFC Regions Lamar, Yousem, Resnick NeuroImage 2004 Medial OFC (p<.01)Lateral OFC (p=.01) Match - NonMatchNonMatch - Match

32. Older Adults Activate Posterior Regions Lamar, Yousem, Resnick NeuroImage 2004 Match - NonMatchNonMatch - Match Association Cortices (ns)DLPFC (p=.006)

33. Conclusions u Cognitive and brain changes associated with drug abuse in the elderly will be superimposed upon a changing brain. u Some but not all cognitive functions show age changes. u Many but not all individuals show age changes in cognition and brain structure and function.

34. BLSA Cognition and Neuroimaging Study: Possibilities for Studies of Drug Abuse u Assessments of older adults continue and neuroimaging studies will be expanded with the NIA IRP MRI facility. u Potential to include additional assessments. u Abuse of prescription medications, including pain-killers will be most informative in this sample.

35. Collaborators : Neuroimaging Project NIAJHU Alberto Goldszal, PhD Christos Davatzikos, PhD Dzung Pham, PhDMichael Kraut, MD, PhD Melissa Lamar, PhDR. Nick Bryan, MD, PhD Scott Moffat, PhD Jerry Prince, PhD Stephanie Golski, PhD JHU PET Facility Robert Dannals, PhD Hayden Ravert, PhD

36. 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

37. -4.0 -3.5 -3.0 -2.5 -2.0 -1.5 -0.5 0.0 0.5 1.0  4-  4+ Annual Rate of Change (%) Risk Factor: APOE  4 genotype is associated with accelerated hippocampal volume loss Neurology 2000;55:134-136. N = 13

38. Temporal Horn Brain N = 82N = 12N = 82N = 12 *** Increases in Temporal Horn Volumes Predict Mild Cognitive Impairment by CDR Score

39. 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).

40. Automated analysis of specific regions with HAMMER and brain atlas* Template brain (*regional outlines provided by Noor Kabani) BLSA brain

41. GrayWhite

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

43. Age Effects on Regional White Matter Signal Intensities L L LR R L L LR R Age differences4-year decline Davatzikos and Resnick. Cerebral Cortex 2002;12:767-771

44. Analysis of 4-Year Change in MRI Volumes: Sample Characteristics MEN WOMEN TOTAL N504292 Age (yrs)70.5 ± 6.470.4 ± 7.770.4 ± 7.0 Education (yrs)16.0 ± 3.216.2 ± 2.416.1 ± 2.8 Handedness (R:L) 47:340:287:5 Race (White: Nonwhite) 48:236:684:8

45. PET Analysis IMAGE PROCESSING AND STATISTICAL ANALYSIS: u Preprocessing using SPM99 and the STAR algorithm for elastic stereotaxic normalization u 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 u Significance threshold: p 35

46. Summary: Age-Related Structural Changes u Regional brain structure can be measured reliably over time. u Both gray and white matter volumes show longitudinal declines even in the healthy elderly. u Increases in ventricular volumes are greater in older than younger individuals. u There are regional patterns to both tissue loss and qualitative changes in tissue composition.