1. Professor of Medicine and Public Health
Aging and HIV
Amy C. Justice, MD, PhD
Professor of Medicine and Public Health
Yale University

2. Aging with HIV Background HIV+ ART Virus suppressed but present
This “aging” of the HIV epidemic is mainly due to three factors: the success of antiretroviral therapy in prolonging the lives of people living with HIV; decreasing HIV incidence among younger adults shifting the disease burden to older ages; and the often-unmeasured, and thus often overlooked, fact that people aged 50 years and older exhibit many of the risk behaviours
also found among younger people.
UNAIDS. HIV and Aging. Available at: Accessed 09/16/16
Virus suppressed but present
Immune dysfunction
Long-term ART toxicity
Aging with multimorbidity
HIV = human immunodeficiency virus; ART = antiretroviral therapy.

3. Living with HIV in US by Age Extrapolated from 2014 CDC Data

4. Percentage of Adults Living with HIV Aged 50+ By Year and Region
Western and Central Europe and North America
Eastern Europe and Central Asia
Latin America
Caribbean
Sub-Saharan Africa
Asia and the Pacific
Middle East and North Africa
1995
2012
Percentage (%) 35 30 25 20 15 10 5
Western and Central Europe and North America 33%; Eastern Europe and Central Asia 17%; Latin America 15%; Caribbean 13%; Sub-Saharan Africa 9%; Asia and the Pacific 8%; Middle East and North Africa 6%
United Nations Programme on HIV/AIDS (UNAIDS). HIV and Aging. Accessed 9/22/16.

5. HIV+ Incident Age in VACS
Percent
Age in Years at Entry

6. Probability of Survival (%)
10-year Decreased Life Expectancy in Older HIV+ Adults in Modern ART Era
HIV- Controls
1996–2014
Probability of Survival (%)
HIV+
2006–2014
2000–2005
1996–2000
Age (years)
Legarth RA, et al. J Acquir Immune Defic Syndr. 2016;71(2):

7. Many Age-Associated Morbidities Increased, Not Accelerated, in Treated HIV
Cardiovascular disease
Liver disease
Cancer (non-AIDS)
Kidney disease
Bone fractures and osteoporosis
Cognitive decline
Non-AIDS infections
COPD
AIDS = acquired immune deficiency syndrome; COPD = chronic obstructive pulmonary disease.
Freiberg M, et al. JAMA Int Med. 2013;173(8): ; Tseng Z, et al. J Am Coll Cardiol. 2012;59(21): ; Grinspoon SK, et al. Circulation. 2008;118(2): ; Silverberg M, et al. AIDS. 2009;23(17): ; Triant V, et al. J Clin Endocrinol Metab. 2008;93(9): ;
Arnsten JH, et al. AIDS. 2007;21(5): ; Odden MC, et al. Arch Intern Med. 2007;167(20): ; Choi A, et al. AIDS. 2009;23(16): ;
McCutchan JA, et al. AIDS. 2007;21(9): ; Sogaard OS, et al. Clin Infect Dis. 2008;47(10): ; Desquilbet L, et al. J Gerontol A Biol Sci Med Sci. 2007;62(11): ; Attia EF, et al. Chest. 2014;145(6):

8. Why is HIV-1 RNA suppression not enough?
How can we follow our patient’s disease progression?
What can we do to improve outcomes now and in the future?
RNA = ribonucleic acid.
The Graying of AIDS. Accessed 9/22/16.

9. Why isn’t HIV-1 RNA suppression enough?

10. Does HIV Exacerbate Aging? An Important Clue from Nature
Sooty Mangabey
Infect with SIV
High levels of viral replication
No AIDS, normal lifespan
Minimal immune activation
Rhesus Macaque
Infect with SIV
High levels of viral replication
AIDS and death
Massive immune activation
SIV = simian immunodeficiency virus.
Silvestri G, et al. Immunity. 2003;18(3):

11. ↓Tight Junctions (Epple, Gut, 2009)
Microbial Translocation (“Leaky Gut”) as a Cause of Immune Activation in HIV
Disrupted Gut
Epithelial Barrier
↑EC Apoptosis
(Li, JID, 2008)
↓Tight Junctions (Epple, Gut, 2009)
Loss of
Mucosal Immunity
↓CD4+ T cells
↓Th17 cells
(Veazey, Science, 1998; Brenchley, J Exp Med, 2004; Guadalupe, J Virol, 2003; Mehandru, J Exp Med, 2004)
Brenchley JM, et al.
Nat Med. 2006;12(12):

12. We lack interventions that block HIV expression
HIV Reservoirs Established in First Week of Infection and Continue to Release Virus on ART
Mostly reflects release of virus from infected cells without productive replication
We lack interventions that block HIV expression
107
106
105
104
103
102
101
100
10-1
HIV-1 RNA (copies/mL)
Time (days)
Maldarelli F, et al. PLoS Pathog. 2007;3(4):e46.

13. T-cell Activation Remains Abnormally High During ART-Mediated Viral Suppression60 50 40 30 20 10
HIV-
ART+
VL < 75
ART-
VL > 10K
% CD38+ HLA-DR+
CD8+ T cells
P < 0.001
Hunt PW, et al. J Infect Dis. 2003;187(10): ; Hunt PW, et al. PLoS One. 2011;6(1):e15924.

14. Inflammation and Immune Activation Pre- and Post-ART (MACS 1984–2009)↑
164%
(138%, 192%)
HAART-naïve relative to HIV-
HIV suppressed relative to HIV-
HIV suppressed relative to HAART-naïve
100 80 60 40 20
-20
-40
-60
Percent Difference (%)
CXCL10
sCD27
IL-10
sIL-2Ra
sTNFR2
IFN-V
CXCL-13
TNF-a
IL-12p70
sIL-6R
BAFF
CCL2
IL-6
sCD14
GM-CSF
CCL11
CRP
IL-1B
sGP130
IL-8
CCL13
CCL17
CCL4
Generalized gamma models adjusted for age, race, smoking, HCV, obesity, diabetes, and site
Median ages (years): 42 uninfected, 38 ART-naïve, and 48 suppressed
13 biomarkers “normalized” in 1 year, 12 remained distinct from uninfected
After 1 year, values stabilized
Wada NI, et al. AIDS. 2015;29(4):

15. Inflammation Predicts Disease in Treated HIV Infection
Mortality (Kuller, 2008; Tien, 2010; Justice, 2012; Hunt, 2014)
Cardiovascular Disease (Duprez, 2009)
Cancer (Breen, 2010; Borges, 2013)
Venous Thromboembolism (Musselwhite, 2011)
Type II Diabetes Mellitus (Brown, 2010)
COPD (Attia, 2014)
Renal Disease (Gupta, 2015)
Bacterial Pneumonia (Bjerk, 2013)
Cognitive Dysfunction (Burdo, 2013; Letendre, 2012)
Depression (Martinez, 2014)
Frailty (Erlandson, 2013)
Kuller LH, et al. PLoS Med. 2008;5(10):e203; Tien PC, et al. J Acquir Immune Defic Syndr. 2010;55(3): ; Justice AC, et al. Clin Infect Dis. 2012;54(7): ; Hunt PW, et al. J Infect Dis. 2014;210(8): ; Duprez DA, et al. Atherosclerosis. 2009;207(2): ; Breen EC, et al. Cancer Ep Bio Prev. 2010; Borges AH, et al. AIDS. 2013;27(9): ; Musselwhite LW, et al. AIDS. 2011;25(6): ; Brown TT, et al. Diabetes Care. 2010;33(10): ; Attia EF, et al. Chest. 2014;146(6): ; Gupta SK, et al. HIV Med. 2015;16(10): ; Bjerk SM, et al. PLoS One. 2013;8(2):e56249; Burdo TH, et al. AIDS. 2013;27(9): ; Letendre SL, et al. CROI. 2012; Abstract 82; Martinez P, et al. J Acquir Immune Defic Syndr. 2014;65(1):42-49; Erlandson KM, et al. J Infect Dis. 2013;208(2):

16. How can we monitor disease among those on ART?

17. Many Interacting Factors Play A Role
AGING
HIV
Viral Hepatitis
Substance Use
Immune Dysfunction +
Senescene
Microbial Translocation
“Leaky Gut”
Chronic Inflammation and Platelet
Hypercoagulability
HIV + Non HIV
Treatment
Toxicity
Oxidative Stress
Associated Comorbid Disease
Incremental Depletion in Organ System Reserve
Functional Decline
Organ System Failure
Repeated Hospitalization / Nursing Home Placement
Death
Presenting conditions
VACS Risk Index
Overlapping + Interacting Pathophysiologic Processes
Preclinical + Clinical Organ System Injury
Advanced
Clinical Disease
Health Care Outcomes

18. VACS Index Components Age HIV Specific Biomarkers
Score
Age (years)
< 50
50–64 12
≥ 65 27
CD4
≥ 500
cells/mm3
350–499 6
200–349
100–199 10
50–99 28 29
HIV-1 RNA
< 500
copies/mL
500 to 1 x 105 7
≥ 1 x 105 14
Hemoglobin
≥ 14
g/dL
12–13.9
10–11.9 22
< 10 38
FIB-4
< 1.45
1.45–3.25
> 3.25 25
eGFR mL/min
≥ 60
45–59.9
30–44.9 8
< 30 26
Hepatitis C Infection 5
Age
HIV Specific
Biomarkers
Biomarkers of General
Organ System Injury

19. Biomarkers of Inflammation Correlated with VACS Index (overall and components)
Justice AC, et al. Clin Infect Dis. 2012;54(7):

20. VACS Index is Accurate in Important Subgroups
100 80 60 40 20
VACS Index Score
5-year mortality (%)
NA-ACCORD (N=10,835)
100 80 60 40 20
VACS Index Score
5-year mortality (%)
VACS (N=5,066)
100 80 60 40 20
VACS Index Score
5-year mortality (%)
Age < 50 years (N = 11,191)
100 80 60 40 20
VACS Index Score
5-year mortality (%)
Age > 50 years (N = 4,710)
100 80 60 40 20
VACS Index Score
5-year mortality (%)
Men (N=12,785)
100 80 60 40 20
VACS Index Score
5-year mortality (%)
Women (N=3,116)
100 80 60 40 20
VACS Index Score
5-year mortality (%)
Black (N = 5,878)
100 80 60 40 20
VACS Index Score
5-year mortality (%)
White (N = 6,079)
100 80 60 40 20
VACS Index Score
5-year mortality (%)
Undetectable VL (N = 8,715)
Detectable VL (N = 7,186)
100 80 60 40 20
VACS Index Score
5-year mortality (%)
NA-ACCORD = North American AIDS Cohort Collaboration on Research and Design.
Justice AC, et al. J Acquir Immune Defic Syndr. 2013;62(2):

21. VACS Index Reflects Frailty Indicated By:
Functional Performance (Erlandson, 2012)
Sarcopenia (Oursler, 2013)
Neurocognitive Performance (Marquine, 2014)
Autonomic Neuropathy (Robinson-Papp, 2013)
Fragility Fractures (Womack, 2013; Yin, 2016)
Hospitalizations and ICU Admissions (Akgun, 2013)
ICU = intensive care unit.
Erlandson KM, et al. HIV Clin Trials. 2012;13(6): ; Oursler KK, et al. AIDS Res Hum Retroviruses. 2013;29(9): ; Marquine MJ, et al.
J Acquir Immune Defic Syndr. 2014;65(2): ; Robinson-Papp J, et al. Patient Care STDS. 2013;27(10): ; Womack JA, et al. Clin Infect Dis. 2013;56(10): ; Yin MT, et al. J Acquir Immune Defic Syndr. 2016;72(5): ; Akgun KM, et al. J Acquir Immune Defic Syndr. 2013;62(1):52-59.

22. Time-Updated VACS Index for Predicting Acute Myocardial Infection
*lowest AIC
(best model fit)
HIV Viral Load (copies/mL)
CD4 (cells/mm3)
VACS Index Score
Baseline
Time- updated
Cumulative time-updated
Referent Category
<100,000
<100,000+
≤200
1,000-9,999
1,000+
<1,000
≥200
<200
1,000-14,999
15,000-99,999
100,000+
≥500
<815
815-1,499 1,
≥2,700
<50
50+
<20
20-34
35-54
85-149
265+
<85
55+ HR
Time-updated VACS Index provided better AMI prediction than CD4 count and HIV-1 RNA suggesting that current health determines risk more than prior history and that risk assessment can be improved by biomarkers of organ injury
Crude and adjusted hazard ratios and 95% CI are presented on a log2scale, grey diamonds denotes crude measures, black squares denote adjusted measures.
Adjusting factors: all models age, diabetes, cholesterol low- and high-density lipoprotein, smoking, hypertension; HIV viral load models additionally adjusted for CD4; CD4 models additionally adjusted for HIV viral load.
AMI = acute myocardial infection.
Salinas JL, et al. Clin Infect Dis. 2016; Epub ahead of print.

23. Time-Updated VACS Index
for Predicting All-Cause Mortality
Referent Category
Time-updated VACS Index provided better mortality prediction than CD4 count and HIV-1 RNA suggesting that current health determines risk more than prior history and that risk assessment can be improved by biomarkers of organ injury
Baseline
<100,000
<100,000+
*lowest AIC
(best model fit)
Time- updated
HIV Viral Load (copies/mL)
≤200
1,000-9,999
1,000+
1,000-14,999
Cumulative time-updated
<1,000
15,000-99,999
100,000+
Baseline
≥200
<200
<200
Time- updated
CD4 (cells/mm3)
≥500
<815
Cumulative time-updated
≥2,700
815-1,499 1,
Crude and adjusted hazard ratios and 95% CI are presented on a log2scale, grey diamonds denotes crude measures, black squares denote adjusted measures.
Adjusting factors: all models age, diabetes, cholesterol low- and high-density lipoprotein, smoking, hypertension; HIV viral load models additionally adjusted for CD4; CD4 models additionally adjusted for HIV viral load.
Baseline
<50
50+
20-34
Time- updated
<20
35-54
VACS Index Score
55+
85-149
Cumulative time-updated
<85
265+ HR
Salinas JL, et al. Clin Infect Dis. 2016; Epub ahead of print.

24. VACS Index is Responsive to
Differs by level of
Alcohol use
Adherence to ART
Substance use
Treatment with
ART
DAAs for HCV

25. What can we do now?
Four steps to take now to minimize frailty and maximize quality of life.

26. 1. Diagnose and Treat As Early As Possible

27. Delayed Treatment by Age
*Among individuals in NA-ACCORD.
Althoff KN, et al. AIDS Res Ther. 2010;7:45.

28. HIV-1 RNA Suppression and Cancer
Park LS, et al International Conference on Malignancies in AIDS and Other Acquired Immunodeficiencies [Oral Presentation].

29. 2. Treat HCV (and HBV) Infection

30. HCV Infection Harms More Than the Liver
Hematologic and Autoimmune Diseases
Mixed Cryoglobulinemia
B-cell Lymphoma
Liver
Autoimmune Thyroiditis
Inflammation
Steatosis
Fibrosis/Cirrhosis
Hepatocellular Carcinoma
Cholangiocarcinoma
Membrano-Proliferative Glomerulonephritis
Sicca Syndrome
HCV
CVD/Metabolic Disease
Atherosclerosis
Insulin Resistance/Diabetes
Myocardial Dysfunction
Neurocognitive Diseases
Cognitive Impairment
HCV = hepatitis C virus; CVD = cardiovascular disease.
Negro F, et al. J Hepatol. 2014;61(1 Suppl):S69-S78.
Fibromyalgia

31. 3. Minimize Polypharmacy

32. Polypharmacy Typically defined as > 5 chronic drugs
Associated with diminished marginal benefit from additional medication due to:
Nonadherence
Drug-drug interactions
Cumulative toxicity
Risk of adverse events increases approximately 10% with each additional medication
Interacts with alcohol, tobacco, or other substances
Salazar JA. Expert Opin Drug Saf. 2007;6(6): ; Gandhi TK. N Engl J Med. 2003;348(16):

33. Chronic Medication Count by Age and HIV Status (VACS)
Edelman EJ, et al. Drugs Aging. 2013;30(8):

34. Prescribed Substances Opioids and Benzodiazepines
Co-prescribing particularly problematic
Long-term (> 90 days) requires careful intervention
Partner with addiction specialists
Motivational interviewing and cognitive behavioral therapy
May require medication:
Most commonly buprenorphine

35. Tobacco, Opioids, and Benzodiazepines
Variable
Overall (N = 64,441)
Uninfected (n = 47,452)
HIV-infected (n = 16,989)
HR (95% CI)
P Value
Long-term opioid receipt
1.39 (1.21, 1.60)
< 0.001
1.35 (1.14, 1.61)
0.0006
1.54 (1.21, 1.96)
0.001
Long-term benzodiazepine receipt
1.33 (1.10, 1.62)
0.004
1.41 (1.12, 1.78)
0.003
1.16 (0.80, 1.68)
0.45
Long-term opioid and benzodiazepine receipt
1.51 (1.22, 1.87)
0.0001
1.43 (1.10, 1.86)
0.008
1.82 (1.27, 2.62)
Long-term medication count
1.05 (1.04, 1.07)
1.04 (1.03, 1.06)
1.05 (1.02, 1.08)
0.0002
Alcohol use disorder
1.63 (1.39, 1.90)
1.56 (1.30, 1.88)
1.53 (1.17, 2.02)
0.002
Drug use disorder
0.95 (0.81, 1.13)
0.59
0.88 (0.70, 1.11)
0.28
1.16 (0.89, 1.51)
0.27
Schizophrenia
1.14 (0.92, 1.40)
0.23
1.09 (0.86, 1.38)
0.49
1.45 (0.94, 2.25)
0.09
Bipolar
0.92 (0.74, 1.14)
0.44
0.93 (0.71, 1.22)
0.60
1.03 (0.72, 1.47)
0.88
Major depression
0.95 (0.79, 1.15)
0.62
1.07 (0.84, 1.35)
0.86 (0.63, 1.17)
0.33
PTSD
0.79 (0.68, 0.93)
0.75 (0.63, 0.91)
0.88 (0.64, 1.20)
0.41
Acute pain
1.72 (1.43, 2.08)
1.76 (1.39, 2.23)
1.70 (1.26, 2.31)
Chronic pain
0.93 (0.83, 1.05)
0.24
0.93 (0.81, 1.07)
0.29
0.95 (0.78, 1.17)
0.64
Black vs white
0.86 (0.77, 0.96)
0.006
0.81 (0.70, 0.92)
0.90 (0.74, 1.09)
Hispanic vs white
0.58 (0.45, 0.73)
0.56 (0.42, 0.75)
0.57 (0.38, 0.87)
0.009
Other vs white
0.87 (0.63, 1.18)
0.37
0.88 (0.60, 1.29)
0.51
0.81 (0.47, 1.40)
0.46
VACS Index score
1.12 (1.11, 1.13)
1.23 (1.21, 1.25)
1.08 (1.06, 1.10)
Current smoking vs never
1.87 (1.62, 2.15)
2.01 (1.69, 2.39)
1.80 (1.41, 2.30)
Past smoking vs never
1.43 (1.21, 1.70)
1.37 (1.11, 1.68)
1.43 (1.04, 1.96)
0.03
PTSD = post-traumatic stress disorder.
Weisberg DF, et al. J Acquir Immune Defic Syndr. 2015;69(2):

36. Polypharmacy and Substance Use
Complete Medication Reconciliation
Perform annually and update with medication changes
Assess medications taken, adherence, and related symptoms
Include assessment of over-the-counter medications and supplements
Assess for Tobacco, Alcohol, and Substance Use
Use standardized instruments
Assess and Rank Each Medication According to Risks and Benefits
Prioritize ART and pharmacotherapy for alcohol/substance use disorders
Use risk index, such as VACS index, to assess mortality
Prioritize and Plan with Patient
Incorporate goals and criteria for stopping treatment
Develop strategies to monitor for medication-induced symptoms and other adverse events
Incorporate patient preferences
Edelman EJ, et al. Drugs Aging. 2013;30(8):

37. 4. Council a Healthy Lifestyle

38. Lifestyle Contributes to Immune Activation in Treated HIV
Smoking increases monocyte activation (Valiathan, 2014)
Hazardous EtOH associated with ↑ sCD14 / microbial translocation (Carrico, 2015)
Methamphetamine use increases immune activation and suppresses T-cell function (Massanella, 2015)
Obesity associated with increased inflammation (Koethe, 2013)
Moderate exercise decreases inflammation in pilot trials (Longo, 2014)
EtOH = ethyl alcohol; sCD14 = soluble CD14.
Valiathan R, et al. PloS One. 2014;9(5):e97698; Carrico AW, et al. Alcohol Clin Exp Res. 2015;39(12): ; Massanella M, et al. Sci Rep. 2015;5:13179; Koethe JR, et al. AIDS Res Hum Retroviruses. 2013;29(7): ; Longo V, et al. CROI. 2014; Abstract 763.

39. Weight Change After ART and Mortality
(Normal [N = 2,226] vs Overweight/Obese [N = 1,842])
*Adjusted for VACS Index at ART initiation.
BMI = body mass index.
Yuh B, et al. Clin Infect Dis. 2015;60(12):

40. Alcohol Use More Harmful Among HIV+
Physiologic Frailty
Mortality
Estimated Total Drinks per Month
Mortality Rates per 100 PYs 6 5 4 3 2 1
HIV+
HIV-
Estimated Total Drinks per Month
Mean VACS Score 45 40 35 30 25 20 15
HIV+
HIV-
Justice AC, et al. Drug Alcohol Depend. 2016;161:

41. Exercise Compared to less active adults, greater activity:
Lowers mortality, CAD/CVD, HTN, diabetes, colon/breast cancer, and depression
Decreases hip and vertebral fracture
Improves weight maintenance
WHO recommendations for adults:
Perform 150 mins of moderate (75 mins of vigorous) aerobic/wk:
In bouts of 10+ mins each
Increase to 300 mins of moderate (150 mins of vigorous)/wk
Muscle strengthening (resistance) 2+ days/wk
Inactive people: start small and increase over time
Exercise prescriptions, apps, and partnering with a friend help
CAD = coronary artery disease; HTN = hypertension; WHO = World Health Organization.
WHO. Global strategy on diet, physical activity, and health. Accessed 9/22/16; NIH Senior Health. Exercise: how to get started. Accessed 9/22/16.

42. Future Predictions HIV incidence will rise among 50+ yrs.
In 2014, 17% were 50+yrs.
Presentation may differ from younger individuals
Mainstreamed care for suppressed
Cognition depends more upon psycho-active medication and VACS Index than “HAND”
Liver injury-cirrhosis-HCC, will become major factors in HIV+/HCV+ and in HIV+/HCV-
Ongoing microbial translocation
Long term toxicity
Fatty liver

43. Acknowledgements Consortium PI : AC Justice*
Scientific Collaborator (NIAAA): K Bryant
Affiliated PIs: S Braithwaite, K Crothers*, R Dubrow *, DA Fiellin*, M Freiberg*, V LoRe*
Participating VA Medical Centers: Atlanta (D. Rimland*, V Marconi), Baltimore (M Sajadi, R Titanji), Bronx (S Brown, Y Ponomarenko), Dallas (R Bedimo), Houston (M Rodriguez-Barradas, N Masozera), Los Angeles (M Goetz, D Leaf), Manhattan-Brooklyn (M Simberkoff, D Blumenthal, H Leaf, J Leung), Pittsburgh (A Butt, K Kraemer, M Freiberg, E Hoffman), and Washington DC (C Gibert, R Peck)
Core and Workgroup Chairs: C Brandt, J Edelman, N Gandhi, J Lim, K McGinnis, KA Oursler, C Parikh, J Tate, E Wang, J Womack
Staff: H Bathulapalli, T Bohan, J Ciarleglio, A Consorte, P Cunningham, L Erickson, C Frank, K Gordon, J Huston, F Kidwai-Khan, G Koerbel, F Levin, L Piscitelli, C Rogina, S Shahrir, M Skanderson
Major Collaborators: VA Public Health Strategic Healthcare Group, VA Pharmacy Benefits Management, Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), Yale Center for Interdisciplinary Research on AIDS (CIRA), Center for Health Equity Research and Promotion (CHERP), ART-CC, NA-ACCORD, HIV-Causal
Cross Cohort Collaborators: Richard Moore (NA-ACCORD), Jonathan Sterne (ART-CC), Brian Agan (DoD)
Major Funding by: National Institutes of Health: AHRQ (R01-HS018372), NIAAA (U24-AA020794, U01-AA020790, U01-AA020795, U01-AA020799, U24-AA022001, U24 AA022007), NHLBI (R01-HL095136; R01-HL090342) , NIAID (U01-A ), NIMH (P30-MH062294), NIDA (R01DA035616), NCI (R01 CA173754) and the Veterans Health Administration Office of Research and Development (VA REA , VA IRR Merit Award) and Office of Academic Affiliations (Medical Informatics Fellowship)
*Indicates individual is also the Chair of a Core or Workgroup

44. Acknowledgements QR Codes
COMpAAAS/Veterans Aging Cohort Study, a CHAART Cooperative Agreement, supported by the National Institutes of Health: National Institute on Alcohol Abuse and Alcoholism (U24-AA020794, U01-AA020790, U01-AA020795, U01-AA020799) and in kind by the US Department of Veterans Affairs.  In addition to grant support from NIAAA, we gratefully acknowledge the scientific contributions of Dr. Kendall Bryant, our scientific collaborator.
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45. VACS Project Team 2016