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HIV infection and cardiovascular diseases
Matthew S. Freiberg, MD, MSc
University of Pittsburgh School of Medicine and Graduate School of Public Health
Yale GIM Research in ProgressSeptember 8th, 2011
DISCLOSURE & ACCREDITATION
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DISCLOSURE & ACCREDITATION
Acknowledgement is made on behalf of the Department that:
~ There is no commercial support for this Grand Rounds.
Confirmation is also made that today’s lecture and faculty disclosure have been peer reviewed and:
~There are no conflicts of interest.
By 2015, what percentage of HIV infected people living in the U.S. will be 50 years of age or older
15%
25%
35%
50%
http://www.cdc.gov/hiv/resources/factsheets/
By 2015, what percentage of HIV infected people living in the U.S. will be 50 years of age or older
15%
25%
35%
50%
http://www.cdc.gov/hiv/resources/factsheets/
At the end of 2006, African Americans accounted for what percentage of all new HIV infection diagnoses
15%
35%
45%
50%
http://www.cdc.gov/hiv/topics/aa/
At the end of 2006, African Americans accounted for what percentage of all new HIV infection diagnoses
15%
35%
45%
50%
http://www.cdc.gov/hiv/topics/aa/
In 2006, the rate of new HIV infection for black women was nearly __ times as high as that of white women and nearly __ times that of Hispanic/Latina women.
3 and 2
5 and 3
10 and 3
15 and 4
http://www.cdc.gov/hiv/topics/aa/
In 2006, the rate of new HIV infection for black women was nearly __ times as high as that of white women and nearly __ times that of Hispanic/Latina women.
3 and 2
5 and 3
10 and 3
15 and 4
http://www.cdc.gov/hiv/topics/aa/
Background
HIV infection is associated with– Increased coronary calcium1
– Progression of carotid IMT2
– Endothelial dysfunction as measured by FMD3
Antiretroviral therapy (ARV) is associated with AMI risk in observational studies4
Intermittent ARV, however, is associated with a greater risk of AMI than continuous ARV for viral suppression5
1. Lai et al. Archives of Internal Medicine 2005; 2. Hsue et al. Circulation 2004; 3. Solages et al. CID 2006; 4. DAD study group. NEJM 2007; 5. SMART study group. NEJM 2006.
11
The SMART Study
The Strategies for Management of ART (SMART) study is a RCT of 5472 HIV+ Participants who were assigned either to drugConservation or viral suppression
Participants were followed for 16 months
Primary end points was opportunistic diseaseor death from any cause (n=167)
Secondary endpoints were major CVD, renal,or hepatic disease (n=104 of which 79 were CVD)
12
The SMART Study
The Strategies for Management of Antiretroviral Therapy (SMART) Study Group. N Engl J Med 2006;355:2283-2296
Important Questions
Is HIV infection an independent risk factor for AMI?
Does HIV infection increase the risk of other cardiovascular diseases?
If HIV does increase the risk of CVD what is the mechanism? Do ARVs play a role?
Do non-traditional risk factors play a role?
If so, does the Framingham risk score apply to those with HIV infection?
Is HIV as an independent risk factor for AMI
Prior studies suggesting HIV is associated with a significant AMI risk
Triant et al.1
– AMI rate ratio=1.75 (95% CI=1.51-2.02, p<0.001)
Klein et al.2
– AMI rate ratio=1.4 (95% CI=1.3-1.7, p<0.001)
Obel et al.3
– IHD hospitalization RR=2.12 (95% CI=1.62-2.76)
Currier et al.4
– CHD RR=2.16 (95% CI=1.81-2.58) for men 25-34– CHD RR=1.53 (95% CI=1.10-2.13) for women 25-34
1. Triant et al. J Clin Endo Metab 2007; 2. Klein et al. CROI. Boston, 2011; 3. Odell et al. CID. 2007 4. Currier et al. JAIDS 2003
Veterans Aging Cohort Study Virtual Cohort and Ischemic Heart Disease Quality Enhance Research Initiative
Cohort of HIV+ and 1:2 matched age, gender, race/ethnicity, and clinical site matched Veterans
All participants alive in 2003 eligible and free of baseline CVD (n=84,832, 33% HIV+)
All AMI outcomes clinically confirmed by IHD QUERI
Validated smoking data, blood pressure and lipid measurements were used
Baseline characteristics of cohort
Characteristics, n (%)
HIV+ n=28,134
HIV- n=56698
Age, years (mean ± SD) 48.5±9.5 49.1±9.3 Men (%) Race/ethnicity African American White Hispanic
97.3 47.5 38.0 7.1
97.3 47.4 38.1 7.8
CHD risk factors Hypertension 22.1 32.5 Diabetes 14.3 21.2 Hypercholesterolemia 33.2 38.8 Current Smoker Other risk factors
60.2 54.0
Hepatitis C infection 35.1 15.8 EGFR<30ml/min/1.73m2 1.4 0.5 BMI ≥ 30 (kg/m2) 13.8 37.7 Hx of Substance Use Cocaine abuse or dependence 11.3 7.3 Alcohol abuse or dependence 14.1 13.4 Laboratory Analysis Median CD4 count 352 Median HIV-1 RNA 1070
Freiberg et al. CROI. Boston, 2011
HIV status and the risk of AMI
Risk Factors HR for AMI with 95% CI
HIV infection 1.95 (1.60-2.38) Age (10 yrs) 1.43 (1.28-1.57) Female gender 0.35 (0.11-1.09) Race/ethnicity African American Hispanic Other
0.79 (0.64-0.97) 1.51 (1.12-2.04) 0.43 (0.23-0.81)
Hypertension 1.58 (1.29-1.94) Diabetes 2.08 (1.70-2.55) Hyperlipidemia 1.34 (1.10-1.64) Current Smoking 1.98 (1.52-2.57) HCV infection 1.06 (0.85-1.33) EGFR<30 ml/min/1.73m2 4.28 (2.72-6.72) BMI ≥ 30kg/m2 0.91 (0.73-1.14) History of cocaine abuse or dependence
1.40 (0.96-2.05)
History of alcohol abuse or dependence
0.76 (0.54-1.06)
Freiberg et al. CROI. Boston, 2011
HIV and the risk of AMI in subpopulations
Among never smokers (HR=2.82, 95% CI=1.60-2.38)
Among those not on Statin therapy (HR=1.88, 95% CI=1.51-2.34)
Among those without hepatitis C, renal disease, or obesity (HR=1.82, 95% CI=1.37-2.40)
Freiberg et al. CROI. Boston, 2011
HIV and HCV Co-infection and the Risk of Incident CHD
* Incidence rates are age and race/ethnicity adjusted per 1000 person-years Model 1 adjusted for age, race/ethnicity, education, BMI, traditional CHD risk factors, and substance use Model 2 adjusted for all in model 1 plus competing risk of death
Mortality
Rates
Adj. CHD
Rates*
HR for CHD
95% CI
Model 1
HR for CHD
95% CI
Model 2
HIV+HCV+
HIV+HCV-
HIV-HCV+
HIV-HCV-
6.11 (5.91-6.31)
3.92 (3.78-4.07)
2.08 (2.02-2.15)
1.29 (1.26-1.31)
6.24 (6.05-6.43)
3.99 (3.85-4.13)
3.01 (2.92-3.09)
3.26 (3.20-3.31)
2.01 (1.28-3.21)
1.42 (0.97-2.06)
0.97 (0.54-1.73)
1.0
2.45 (1.83-3.27)
1.90 (1.52-2.37)
1.15 (0.77-1.71)
1.0
Freiberg et al. Circ Cardiovascular Quality and Outcomes, in press
HCV, ARV, and the risk of AMI among HIV infected men
Duration of ART
HR for CHD with 95% CI‡
Recent ART
HR for CHD with 95% CI‡
death is
censored
death is a
competing risk
death is
censored
death is a
competing risk
HCV+HIV+ 2.13
(1.12-4.05)
1.60
(1.03-2.48)
2.05
(1.09-3.82)
1.57
(1.02-2.40)
HIV+HCV- 1.0 1.0 1.0 1.0
‡Models adjusted for age, race/ethnicity, education, BMI, traditional CHD risk factors, and substance use Class of ARV (either duration or recent use), HIV viral load, CD4 count, and adjustment for death as a Censoring event or a competing risk
Freiberg et al. Circ Cardiovascular Quality and Outcomes, in press
Does HIV infection increase the risk of other cardiovascular diseases?
2
Increasing incidence of ischemic stroke in patients with HIV
Figure 1 Trends in stroke hospitalization by type among persons with a diagnosis of HIV in the United States population 1997-2006(A) Ischemic stroke: trend p value p value = 0.27. (C) Intracerebral hemorrhage: trend p value = 0.88.
Ovbiagele et al. Neurology 2011
Alcohol Abuse or Dependence, HIV, and the Risk of Incident Ischemic Stroke
Incidence rates are age and race/ethnicity adjusted per 1000 person-years
Model adjusted for age, race/ethnicity, education, CVD risk factors, hepatitis C; and DX of cocaine abuse or dependence
Stroke
events
N (%)
Adjusted Stroke
Incidence Rate*
HR for Stroke
with 95% CI
HIV+ and alcohol DX (n=818)
HIV+ and no alcohol DX (n=1584)
HIV- and alcohol DX (n=1995)
HIV- and no alcohol DX (n=4112)
25 (3.1%)
33 (2.1%)
45 (2.3%)
57 (1.4%)
5.36 (5.16-5.70)
3.71 (3.50-3.93)
3.49 (3.38-3.61)
2.14 (2.07-2.21)
2.51 (1.42-4.46)
1.95 (1.24-3.05)
1.68 (1.07-2.65)
1.0
Freiberg et al. Research Society on Alcoholism Conference, San Antonio, 2010
Which of the following is NOT true about HIV and failure
HIV is associated with a nearly two fold increased risk of heart failure
Ongoing HIV viral replication may play a role
HIV is not associated with heart failure after adjusting for CHD, ischemic cardiomyopathy, and hazardous alcohol consumption
Which of the following is NOT true about HIV and failure
HIV is associated with a nearly two fold increased risk of heart failure
Ongoing HIV viral replication may play a role
HIV is not associated with heart failure after adjusting for CHD, ischemic cardiomyopathy, and hazardous alcohol consumption
HIV and the Risk of Heart Failure
Butt et al. Archives of Internal Medicine, 2011
HIV and the Risk of Heart Failure by viral load status
Butt et al. Archives of Internal Medicine, 2011
Echocardiographic
Parameters by HIV Status
Hsue et al. Circ Heart Failure 2010
HIV infection is associated with diastolic dysfunction
Hsue et al. Circ Heart Failure 2010
If HIV does increase the risk of CVD what is the mechanism? Do ARVs play a role?
Conceptual Model for HIV and Vascular Risk
Baker et al. European Heart Journal 2011
Chronic HIV infection and microbial translocation
Brenchley et al. Nature Medicine 2006
Microbial translocation and mortality among HIV infected people*
Sandler et al. JID. 2011
*No adjustment for liver disease or alcohol
Biomarkers associated with Fatal and Non-Fatal CVD from the SMART Study
Hs CRP HR=1.6 (95% CI=0.8-3.1) p=0.20
IL-6 HR=2.8 (95% CI=1.4-5.5) p=0.003
Amyloid A HR=1.6 (95% CI=0.9-2.9) p=0.12
Amyloid P HR=2.8 (95% CI=1.4-5.3) p=0.002
D-dimer HR=2.0 (95% CI=1.0-3.9) p=0.06
Kuller et al. CROI. Boston, 2008
2
Biomarkers associated with CVD risk amongthose chronically infectedwith HIV
Ford et al. AIDS 2010
2
ART Use, Viral Suppression, and CD4 Change Over Follow-Up
Baker et al. JAIDS 2011
2
Median levels of hsCRP (A), IL-6 (B), and D-dimer (C) are presented for VS and DC groups at each visit. Error bars represent the interquartile range (IQR).
*P values represent the difference between treatment groups in the change from baseline (on loge scale) and are adjusted for baseline biomarker level.
Baker et al. JAIDS 2011
Average change to 1 month in the DC versus VS group in total, large, medium and small HDL-p (μmol/L) by treatment group among HIV infected people.
Duprez et al. Atherosclerosis 2009
ARV Therapy and Levels of Inflammatory Biomarkers
Baker et al. CROI. Boston, 2011
Do non-traditional risk factors play a role?
The role of alcohol, hepatitis C, and HIV and the risk of AMI
Freiberg and Kraemer. Alcohol Research and Health. 2010
Current Alcohol Consumption and HIV VL and Levels of sCD14, IL-6, D-dimer, and Fib4 Score
Current drinking category
HIV VL
sCD14 ng/ml
IL-6 pg/ml
D-dimer ug/ml
Fib4 score
Non-hazardous 75 (50, 485) 1709 (1410, 2060) 1.78 (1.25, 2.73) 0.23 (0.15, 0.39) 1.27 (0.93, 1.79)
Hazardous 400 (75, 4380) 1734 (1485, 2071) 2.17 (1.49, 3.64) 0.25 (0.13, 0.42) 1.32 (0.98, 1.97)
Abuse or dependence diagnosis
406 (75, 10702) 1740 (1514, 2110) 2.42 (1.61, 3.59) 0.29 (0.18, 0.59) 1.51 (1.07, 2.49)
P value 0.0001 0.18 0.0001 0.004 P=0.0005
HIV VL
sCD14 ng/ml
IL-6 pg/ml
D-dimer ug/ml
Fib4 score
1st Tertile 1676 (1414, 2074) 1.96 (1.30, 3.11) 0.22 (0.13, 0.37) 1.33 (0.98, 1.98)
2nd Tertile 1717 (1503, 2070) 2.02 (1.42, 3.43) 0.26 (0.16, 0.45) 1.33 (0.97, 1.97)
3rd Tertile 1878 (1579, 2265) 2.43 (1.66, 4.28) 0.38 (0.22, 0.71) 1.50 (1.08, 2.22)
P Value 0.0001 0.0001 0.0001 P=0.004
All values are median (25th,75th percentiles)
Freiberg et al. ISBRA Conference. Paris, 2010
HCV Status and Levels of sCD14, IL-6, D-dimer, and FIB4 Score
1600
1650
1700
1750
1800
1850
sCD14
HCV infected
HCV uninfected
0
0.5
1
1.5
2
2.5
IL-6
HCV infected
HCV uninfected
0.23
0.24
0.25
0.26
0.27
0.28
D-dimer
HCV infected
HCV uninfected
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
FIB4
HCV infected
HCV uninfected
Median values for all biomarkers, p values ≤ 0.001 for all
ng
/ml
pg
/ml
ug
/ml
Freiberg et al. ISBRA Conference. Paris, 2010
FIB4 Score and Levels of sCD14, IL-6, and D-dimer
Fib4 Score sCD14 ng/ml
IL-6 pg/ml
D-dimer ug/ml
<1.45 1651 (1408, 2007) 1.83 (1.24, 2.81) 0.22 (0.13, 0.39)
1.45-3.25 1822 (1547, 2177) 2.16 (1.55, 3.76) 0.29 (0.18, 0.54)
>3.25 1929 (1586, 2378) 3.35 (2.37, 5.19) 0.37 (0.21, 0.66)
P value P=0.0001 P=0.0001 P=0.0001
Freiberg et al. ISBRA Conference. Paris, 2010
The association between HIV and HCV viral load and biomarkers in the HIV LIVE Study
Viral Load (VL)
Biomarker Category
HIV+ HCV+ N=127
HIV+ HCV-N=122
HIV- HCV+ N=53
HIV- HCV-N=59
P value
Percentage of participants with >75th percentile of Biomarker
IL-6 32.3 16.0 42.5 12.5 <0.01
CRP 21.3 26.8 25.6 24.0 0.81
Cystatin C 40.7 17.0 23.3 12.0 <0.01
SSA 26.2 22.2 19.5 26.1 0.78
TNF alpha 35.2 22.3 20.9 6.0 <0.01
MCP-1 23.2 26.8 23.4 18.0 0.67
IL-10 37.0 23.2 25.6 6.0 <0.01
INF gamma 11.1 16.1 18.6 12.0 0.56
Samet et al. ISBRA Conference. Paris, 2010
Correlation between D-dimer, sCD14, IL-6 biomarkers in the VACS*
Biomarker Spearman Rank Coefficients D-dimer sCD14 IL-6 D-dimer -- 0.24 0.40 sCD14 0.24 -- 0.45 IL-6 0.40 0.45 --
* All associations are significant p<0.001
So, what might you predict next….
Characteristics of SMART, CARDIA, and MESA Study Participants.
Neuhaus J et al. J Infect Dis. 2010.
Median Levels and Interquartile Ranges (IQRs) of Biomarkers for SMART, CARDIA, and MESA Study
Participants.
Neuhaus J et al. J Infect Dis. 2010.
Biomarkers Levels in SMART Study Participants Receiving Antiretroviral Therapy (ART) Who Had an HIV
RNA Level ≤400 Copies/mL and Percentage Differences in Levels Versus CARDIA and MESA Study Participants
Neuhaus J et al. J Infect Dis. 2010.
00.
40.
81.
21.
6 22.
42.
80
5
10
15
20
25
30
35
00.
40.
81.
21.
6 22.
42.
80
5
10
15
20
25
30
35
150
750
1350
1950
2550
3150
3750
4350
4950
02468
10121416
150
750
1350
1950
2550
3150
3750
4350
4950
02468
10121416
02.
5 57.
5 1012
.5 1517
.5 200
5
10
15
20
25
02.
5 57.
5 1012
.5 1517
.5 200
5
10
15
20
25
HIV +
HIV -
HIV Variable N Median 25th 75th 1st 99th Min MaxPos DD 1526 0.26 0.15 0.49 0.01 3.24 0.01 20
sCD14 1528 1718 1447 2086 875 3624 198 5000IL6 1524 2.08 1.42 3.38 0.48 19 0.48 210
Neg DD 831 0.30 0.21 0.53 0.06 3.54 0.03 20sCD14 834 1733 1480 2051 977 3300 660 3314IL6 826 1.785 1.16 3.16 0.42 32.66 0.42 379.31
D-dimer sCD14 IL-6
The association between biomarkers and HIV status in the VACS
Does the Framingham risk score apply to those with HIV infection?
Yes but it probably overestimates the risk
Yes but it probably underestimates the risk
No, because middle aged Caucasians from Framingham, Massachusetts cannot generalize to an HIV population
I have no idea
Does the Framingham risk score apply to those with HIV infection?
Yes but it probably overestimates the risk
Yes but it probably underestimates the risk
No, because middle aged Caucasians from Framingham, Massachusetts cannot generalize to an HIV population
I have no idea
HIV status and the risk of AMI
Risk Factors HR for AMI with 95% CI
HIV infection 1.95 (1.60-2.38) Age (10 yrs) 1.43 (1.28-1.57) Female gender 0.35 (0.11-1.09) Race/ethnicity African American Hispanic Other
0.79 (0.64-0.97) 1.51 (1.12-2.04) 0.43 (0.23-0.81)
Hypertension 1.58 (1.29-1.94) Diabetes 2.08 (1.70-2.55) Hyperlipidemia 1.34 (1.10-1.64) Current Smoking 1.98 (1.52-2.57) HCV infection 1.06 (0.85-1.33) EGFR<30 ml/min/1.73m2 4.28 (2.72-6.72) BMI ≥ 30kg/m2 0.91 (0.73-1.14) History of cocaine abuse or dependence
1.40 (0.96-2.05)
History of alcohol abuse or dependence
0.76 (0.54-1.06)
Freiberg et al. CROI. Boston, 2011
Additional Framingham Risk Score Data
Median Baseline Framingham Risk score– HIV+ 6.0– uninfected 6.0
HIV infected Veterans have an increased risk of AMI ( HR=1.95, 95% CI=1.60-2.38)
This risk persisted among never smokers
This risk persisted among those without HCV, renal disease, or obesity
Predicting MI with the Framingham risk equation
Law et al. HIV Med 2006
Important Questions
Is HIV infection an independent risk factor for AMI?
Does HIV infection increase the risk of other cardiovascular diseases?
If HIV does increase the risk of CVD what is the mechanism? Do ARVs play a role?
Do non-traditional risk factors play a role?
If so, does the Framingham risk score apply to those with HIV infection?
AcknowledgementsVeteran Aging Cohort Study (VACS) Participants
Mentors– Amy Justice, MD, PHD– Lewis Kuller, MD, Dr.PH
Project Officers– Cheryl McDonald, MD, NHLBI– Kendal Bryant, PhD, NIAAA
NHLBI HL095136-03; 03S1; 03S2
NIAAA AA0159136-06S1
Project Coordinators: Carol Rogina and Glory Koerbel
Collaborators: – Jason Baker MD, MPH, University of Minnesota– Russ Tracy, PhD, University of Vermont– Jeffrey Samet, MD, MA, MPH, Boston University
2
Cardiovascular and metabolic markers before and after a median of 8 months of combination antiretroviral therapy and their correlation with HIV-RNA before combination antiretroviral therapy.
Calmy et al. AIDS 2009.
Correlation of Lipid Measures with Human Immunodeficiency Virus (HIV) RNA and Biomarkers
among HIV-Infected Participants.
Baker J et al. J Infect Dis. 2010.