Carotid artery intima-media thickness progression is associated with human immunodeficiency virus replication as well as with exposure to certain antiretroviral therapy regimens.
Abstract
Background. Persons with human immunodeficiency virus (HIV) infection are at risk for premature cardiovascular disease (CVD). Predictors of atherosclerotic disease progression in contemporary patients have not been well described.
Methods. Using data from a prospective observational cohort of adults infected with HIV (Study to Understand the Natural History of HIV/AIDS in the Era of Effective Therapy), we assessed common carotid artery intima-media thickness (CIMT) at baseline and year 2 by ultrasound. We examined HIV-associated predictors of CIMT progression after adjusting for age, sex, race/ethnicity, body mass index, smoking, hypertension, diabetes, low-density lipoprotein cholesterol level, and baseline CIMT using linear regression.
Results. Among 389 participants (median age at baseline, 42 years; male sex, 77%; median CD4+ cell count at baseline, 485 cells/mm3; 78% receiving antiretroviral therapy), the median 2-year CIMT change was 0.016 mm (interquartile range, −0.003 to 0.033 mm; P < .001). Lesser CIMT progression was associated with a suppressed viral load at baseline (−0.009 mm change; P = .015) and remaining virologically suppressed throughout follow-up (−0.011 mm change; P < .001). After adjusting for additional risk factors and a suppressed viral load during follow-up, nonnucleoside reverse transcriptase inhibitor versus protease inhibitor exposure was associated with lesser CIMT progression (−0.011 mm change; P = .02).
Conclusions. Suppressing HIV replication below clinical thresholds was associated with less progression of atherosclerosis. The proatherogenic mechanisms of HIV replication and the net CVD benefit of different antiretroviral drugs should be a focus of future research.
Cardiovascular disease (CVD) is now a leading cause of morbidity and mortality for persons with human immunodeficiency virus (HIV) infection [1]. Proatherogenic risk factors among adults infected with HIV include a greater prevalence of traditional risk factors (eg, smoking), direct consequences of HIV infection itself, and exposure to specific components of combination antiretroviral therapy (cART) [2–4]. Identifying treatment strategies that might slow atherogenesis has become important for clinical management.
Ultrasound estimates of carotid artery intima-media thickness (CIMT) are associated with coronary artery atherosclerosis and predict risk for vascular events [5, 6]. Factors that associate with CIMT measures among patients infected with HIV have been reported in numerous cross-sectional studies [7–14]. In the largest such comparison of CIMT between HIV-infected and -uninfected persons, the degree of greater CIMT associated with HIV infection was of similar magnitude than was being a smoker or having diabetes [11].
We report here a longitudinal analysis of CIMT changes among participants in the Study to Understand the Natural History of HIV/AIDS in the Era of Effective Therapy (the SUN Study). Our purpose was to examine whether HIV replication and exposure to specific classes of cART influenced progression of subclinical atherosclerosis independent of traditional CVD risk factors among contemporary patients at low risk for AIDS.
METHODS
Study Design
The SUN Study is a Centers for Disease Control and Prevention (CDC)–funded prospective observational cohort study of HIV-infected participants enrolled in 4 US cities (Denver, Minneapolis, Providence, and St. Louis) from March 2004 through June 2006 [15]. The protocol was approved by human subjects research committees at the CDC and at each clinical site, and all participants provided written informed consent. Patients were eligible if they were naive to cART or their prior antiretroviral exposure consisted solely of cART (≥3 nucleoside reverse-transcriptase inhibitors [NRTI] or ≥3 antiretroviral drugs from at least 2 different classes) and were expected to survive ≥2 years. The SUN Study design has been reported elsewhere [15].
In brief, participants were evaluated at baseline and every 6 months thereafter. Clinical data, including all medications and diagnoses, were abstracted from medical charts and entered into a database (Clinical Practice Analyst; Cerner). Additional data were collected through study-specific physical examination and laboratory testing and an audio computer-assisted self-interview that, in part, assessed use of tobacco and alcohol. At each visit, fasting serum and whole-blood specimens were shipped to the CDC for storage at −70°C.
Clinical site laboratory testing included measurement of serum lipids, plasma HIV RNA viral load (VL), and CD4+ cell counts. The following biomarkers were measured from stored plasma using immunoturbidometric assays on a Hitachi 917 analyzer at the Diabetes Research and Training Center Radioimmunoassay Core Laboratory (Washington University School of Medicine): high-sensitivity C-reactive protein (hsCRP; Kamiya Biomedical), cystatin-C (Dakocytomation), and apolipoprotein A1 and B (ApoA-1 and ApoB, respectively; Wako Diagnostics). Homeostasis model assessment of insulin resistance (HOMA-IR) was defined as the serum insulin-glucose product divided by the constant 405. The presence of hypertension was defined as a blood pressure >140/90 mm Hg, prescription of antihypertensives, or a diagnosis of hypertension. We estimated glomerular filtration rate (GFR) using the Cockcroft-Gault equation and Framingham 10-year coronary heart disease risk score (FRS) using published score sheets [16].
Participants were included in this analysis if they had a baseline and 2-year CIMT measure. CIMT was assessed at the far wall of the right distal common carotid artery using high-resolution B-mode ultrasound. Sonographers at each site were trained to interrogate the same portion of the arterial wall with repeated measures, and certified by the University of Southern California’s Atherosclerosis Research Unit (ARU) Core Imaging and Reading Center (CIRC). CIMT was measured centrally at the ARU CIRC with an automated computerized edge detection algorithm [17–19] using methods specifically designed to track change in atherosclerosis over time (patents 2005, 2006, 2011). These methods have been used for previous HIV studies [7–10], and the median coefficient of variation with these methods is <3% [20]. Ultrasound images were analyzed blinded to study participant.
Statistical Methods
Change in CIMT was defined as the difference between the baseline and year 2 measures. Log transformation did not influence results, so untransformed values were used for analyses. Values are reported as medians with interquartile range (IQR). The χ2 or Student t test was used to compare categorical and continuous characteristics, respectively. Linear regression was used to examine associations with CIMT progression. Our multivariate models considered traditional CVD risk factors: age, sex, race/ethnicity, body mass index (BMI), smoking, hypertension, diabetes, low-density lipoprotein cholesterol (LDL-C) level, and baseline CIMT measure. Additional models incorporated the ratio of total to high-density lipoprotein cholesterol (HDL-C), prescribed use lipid-lowering therapy, and a parsimonious model considering FRS alone. Sensitivity analyses were also performed by sex and excluding those not receiving ART at baseline or those taking lipid-lowering therapy. HIV-related factors considered included time since HIV infection diagnosis, duration of cART exposure, history of AIDS per the 1993 CDC case definition [21], baseline and nadir CD4+ cell count, HIV RNA VL, baseline cART regimen, and biomarker levels (Table 1). For analyses, we defined HIV RNA VL as (1) suppressed (<400 copies/mL) at baseline versus not suppressed and (2) persistently suppressed throughout the follow-up period versus detectable at ≥1 visit during follow-up. Comparisons of nonnucleoside reverse-transcriptase inhibitor (NNRT)– and protease inhibitor (PI)–based cART or those taking tenofovir or abacavir excluded participants taking both or neither (n = 23 and n = 206, respectively). Regression coefficients represent a greater (or lesser) 2-year CIMT change associated with the per unit change of the covariate. Statistical significance was defined at a P value of ≤.05. All statistical analyses were performed using SAS software, version 9.2 (SAS).
Table 1.
Characteristics of Study to Understand the Natural History of HIV/AIDS in the Era of Effective Therapy Participants With Carotid Artery Intima-Media Thickness Assessment at the Baseline and 2-Year Visits
| Demographic characteristic | Baseline visit (n = 389) | Two-year visit (n = 389) |
| Age, median years (IQR) | 42 (36–48) | 44 (38–50) |
| Male sex | 300 (77) | … |
| Race/ethnicity | 234 (60) | |
| White, non-Hispanic | 103 (26) | … |
| Black, non-Hispanic | 45 (12) | |
| Hispanic, other | 7 (2) | |
| Clinical characteristics | ||
| Weight, median lbs (IQR) | 171 (149–195) | 174 (152–197) |
| BMI, median value (IQR) | 25.6 (22.6–28.6) | 26.0 (23.3–29.4) |
| Systolic BP, median mmHg (IQR) | 120 (110–130) | 120 (110–130) |
| Diastolic BP, median mmHg (IQR) | 78 (70–84) | 78 (70–84) |
| Hypertension (diagnosis or treatment) | 127 (33) | 180 (46) |
| Diabetes (diagnosis or treatment) | 34 (9) | 42 (11) |
| Hepatitis B or C coinfection | 100 (26) | 106 (27) |
| Tobacco smoking | ||
| Current | 144 (38) | 145 (37) |
| Ever | 233 (61) | … |
| Injection drug use (ever) | 44 (12) | 50 (13) |
| Noninjection illicit drug use (ever) | 267 (69) | … |
| Prescribed antihypertensive therapy | 81 (21) | 106 (27) |
| Prescribed lipid-lowering therapy | 48 (12) | 74 (19) |
| Framingham Risk Score, median score (IQR) | 3 (0–5) | 2 (0–4) |
| Proportion with score <5% | 61 | 58 |
| Proportion with score ≥5% | 39 | 42 |
| Serum lipids and biomarkers | ||
| Total cholesterol, median mg/dL (IQR) | 182 (157–210) | 184 (160–213.5) |
| Triglycerides, median mg/dL (IQR) | 138.5 (96–209) | 138 (92.5–211) |
| LDL-C, median mg/dL (IQR) | 108 (87–132) | 107 (89–132) |
| HDL-C, median mg/dL (IQR) | 41 (34–50) | 42.5 (35–52) |
| ApoA-1, median mg/dL (IQR) | 135 (120–153) | … |
| ApoB, median mg/dL (IQR) | 87 (74–101) | … |
| ApoB/ApoA-1, median (IQR) | 0.64 (0.52–0.58) | … |
| HOMA-IR, median (IQR) | 1.94 (1.13–3.07) | … |
| Serum creatinine level, median mg/dL (IQR) | 0.9 (0.8–1.0) | 0.9 (0.8–1.1) |
| GFR, median mL/min/1.73 m2 (IQR) | 97 (84–114) | 97 (80–120) |
| Cystatin-C, median mg/dL (IQR) | 0.88 (0.80–0.97) | … |
| hsCRP, median mg/L (IQR) | 1.7 (0.7–4.2) | … |
| HIV-specific parameters | ||
| Time since HIV infection diagnosis, median years (IQR) | 4.7 (2.1–7.9) | 6.7 (4.2–9.9) |
| Prior AIDS-defining event | 88 (22) | 94 (24) |
| Baseline CD4+ cell count, median cells/mm3 (IQR) | 485 (344–680) | 513 (367–685) |
| Nadir CD4+ cell count, median cells/mm3 (IQR) | 215 (87–323) | 198 (72–300) |
| HIV RNA viral load <400 copies/mL | 278 (72) | 320 (84) |
| Antiretroviral exposure | ||
| Duration of cART exposure, median years (IQR) | 2.7 (1.1–5.4) | 4.3 (2.6–6.8) |
| Current cART exposure | 302 (78) | 334 (86) |
| Abacavir exposure | 90 (23) | 91 (23) |
| Tenofovir exposure | 141 (36) | 200 (51) |
| NNRTI exposure | 153 (39) | 165 (42) |
| Efavirenz | 115 (30) | 130 (33) |
| Nevirapine | 38 (10) | 35 (9) |
| PI exposure | 136 (35) | 161 (41) |
| Lopinavir-ritonavir | 64 (16) | 50 (13) |
| Atazanavir-ritonavir | 34 (9) | 60 (15) |
| Any ritonavir-boosted PI regimen | 111 (29) | 128 (33) |
Data are no. (%) of patients unless otherwise indicated.
Abbreviations: BMI, body mass index defined as the weight in kilograms divided by height in meters squared; BP, blood pressure; hypertension, clinical diagnosis, prescribed BP lowering medication, or BP >140/90 mmHg; cART, combination antiretroviral therapy; GFR, glomerular filtration rate; HDL-C, high-density lipoprotein cholesterol; hepatitis C, immunoglobulin G antibody positive; HIV, human immunodeficiency virus; HOMA-IR, homeostasis model assessment of insulin resistance (see Methods for equation); hsCRP, high-sensitivity C-reactive protein; illicit drugs, cocaine, methamphetamine, “club drugs”; IQR, interquartile range; LDL-C, low-density lipoprotein cholesterol; NNRTI, nonnucleoside reverse-transcriptase inhibitor; PI, protease inhibitor.
RESULTS
Data from 389 SUN study participants with CIMT measures at baseline and year 2 visits were available for this analysis. At baseline in SUN, 659 participants had a CIMT measure, but 270 of these did not have year 2 data available. Of these, 40% withdrew consent, with the most common reason cited being the time commitment required to complete study visits. When compared with SUN Study participants with missing data at either baseline or 2-year visit (n = 304), the analysis cohort was slightly older (median age, 42 vs 40 years; P = .019), had fewer black individuals (26% vs 34%; P = .03), fewer current tobacco smokers (38% vs 51%; P < .001), and a lower prevalence of prior injection drug use (12% vs 19%; P = .043).
The median time from baseline to the 2-year follow-up was 24.2 months (range, 22.3–30.6 months). The median age was 42 years, and 60% of the patients were non-Hispanic white (Table 1). The prevalence of hypertension and current tobacco smoking at baseline were 33% and 38%, respectively, and 53 participants (14%) were given a new diagnosis of hypertension during follow-up. Median total cholesterol and LDL-C at baseline were within desired ranges for persons without known CVD (67% with TC <200 mg/dL and 73% with LDL-C <130 mg/dL); 161 participants (43%) had triglyceride levels >150 mg/dL, and 139 men (48%) and 57 women (66%) had HDL-C levels <40 mg/dL or <50 mg/dL, respectively [22].
The median baseline and nadir CD4+ cell count were 485 and 215 cells/mm3, respectively (Table 1). At baseline, most (78%) of the participants were prescribed cART, of whom 88% (266) had a suppressed HIV RNA VL and 61% (184) then remained suppressed throughout follow-up. The proportions of participants prescribed NNRTI– or PI–based cART were similar, and more participants were prescribed tenofovir (36%) than abacavir (23%). Of participants prescribed cART at baseline, 43% changed ≥1 component of their regimen during follow-up; use of abacavir remained constant, but several participants started tenofovir therapy. Fifty-two (60%) of 87 participants not prescribed cART at baseline (44 [51%] of whom were cART naive and 43 (49%) of whom had prior cART exposure) started cART at a median of 7.7 months (IQR, 2.8–13.7 months) after baseline.
Two-Year Progression in Carotid Artery Intima-Media Thickness
Median CIMT measures at baseline and at the 2-year visit were 0.707 mm (IQR, 0.642–0.789 mm) and 0.721 mm (IQR, 0.654–0.901 mm), respectively. The median 2-year change in CIMT was 0.016 mm (IQR, −0.003 to 0.033; P <.001) (Figure 1). A notable difference between participants with 2-year CIMT change >0 versus ≤0 mm was a lower median GFR (94 vs 105 mL/min/1.73 m2, respectively; P = .004), although other traditional CVD risk factors were not different.
Figure 1.
Distribution of 2-year carotid artery intima-media thickness (CIMT) change among Study to Understand the Natural History of HIV/AIDS in the Era of Effective Therapy participants (n = 389). Histogram includes distribution of the 2-year change in CIMT.
Less CIMT progression was present for participants who were prescribed cART (vs not) at baseline (0.014 mm vs 0.019 mm; P = .060) and for participants with a suppressed (versus detectable) HIV RNA VL at baseline (0.013 mm vs 0.021 mm; P = .074), although differences did not reach statistical significance. However, participants who maintained a suppressed VL throughout follow-up had significantly less CIMT progression, compared with those with a detectable VL at ≥1 follow-up visit (0.015 mm vs 0.019 mm; P < .001; Figure 2A). CIMT progression was also less for those prescribed NNRTI- versus PI-based therapy at baseline (0.011 mm vs 0.019 mm; P = .012; Figure 2B).
Figure 2.
Two-year carotid artery intima-media thickness (CIMT) progression, human immunodeficiency virus (HIV) RNA viral load and baseline combined antiretroviral therapy (cART) use among Study to Understand the Natural History of HIV/AIDS in the Era of Effective Therapy (SUN Study) participants (n = 389). Median 2-year change in CIMT is plotted in mm for the following subgroups: SUN cohort overall (A, black square); participants stratified by suppressed viral load at all follow-up visits versus detectable viral load at ≥1 visit (A, dark gray diamonds); participants with a detectable viral load during follow-up stratified by cART use at baseline (A, dark gray triangles); participants receiving cART at baseline (B, white square); participants receiving cART stratified by exclusively nonnucleoside reverse-transcriptase inhibitor (NNRTI)–based versus protease inhibitor (PI)–based cART use at baseline (B, light gray diamond); participants receiving cART stratified by exclusively tenofovir versus abacavir use at baseline (B, light gray triangle). Error bars represent interquartile range for change. 1. Adjusted for age, sex, race/ethnicity, body mass index (defined as weight in kilograms divided by the square of height in meters), smoking status, hypertension, diabetes, low-density lipoprotein cholesterol (LDL-C), and baseline CIMT. 2. Adjusted for same covariates above and a suppressed viral load (<400 copies/mL) throughout follow-up. 3. Comparison excludes participants receiving both an NNRTI and a PI (n = 5) or those receiving neither (n = 105). 4. Comparison excludes participants taking both tenofovir and abacavir (n = 24) or neither (n = 182)
Predictors of Carotid Artery Intima-Media Thickness Progression From Univariate Regression Models
Results of analyses from univariate regression models are shown in Table 2. Among traditional CVD risk factors, only a BMI (defined as the weight in kilograms divided by the square of height in meters) >25 (vs ≤25) was associated with greater CIMT progression. None of the lipid or lipoprotein measures were associated with CIMT progression, including when men and women were analyzed separately (data not shown). Among biomarker levels, renal function was inversely associated with CIMT progression when assessed by serum creatinine or cystatin-C level, but not by a GFR <60 mL/min/1.73m2. CD4+ cell count (either nadir or at baseline) was not associated with CIMT change, but a suppressed VL throughout follow-up was associated with less CIMT progression. Baseline prescription of an NNRTI- versus PI-based regimen was associated with less CIMT progression, but no significant differences were observed between prescription of tenofovir or abacavir.
Table 2.
Univariate Associations With 2-Year Carotid Artery Intima-Media Thickness Progression Among Study to Understand the Natural History of HIV/AIDS in the Era of Effective Therapy Participants
| Baseline clinical characteristics | Regression coefficienta, mm (95% CI) | P |
| Age (per 10 years older) | 0.002 (−.012 to.006) | .186 |
| Male sex (vs female sex) | −0.001 (−.009 to.006) | .731 |
| Race/ethnicity (non-Hispanic white vs other) | 0.001 (−.006 to .007) | .842 |
| Tobacco smoking (current smoker vs not) | 0.002 (−.005 to .009) | .544 |
| Illicit drug use (ever vs never) | 0.003 (−.004 to .010) | .458 |
| BMI (>25 vs ≤25) | 0.009 (.003–.016) | <.01 |
| Systolic BP (per 10 mmHg higher) | −0.00003 (−.002 to .002) | .808 |
| Hypertension (vs not) | 0.004 (−.003 to .011) | .282 |
| Diabetes (vs not) | 0.003 (−.009 to .014) | .663 |
| Framingham Risk Score (per unit higher) | 0.001 (−.0003 to .001) | .063 |
| Baseline lipid and biomarker levels | ||
| Total cholesterol (per mg/dL higher) | 0.00001 (−.0005 to .00008) | .696 |
| LDL-C (per mg/dL higher) | −0.000003 (−.00001 to .00009) | .946 |
| HDL-C (per mg/dL higher) | −0.0001 (−.0003 to .0001) | .369 |
| Triglycerides (per mg/dL higher) | 0.00001 (−.00001 to .00002) | .832 |
| Total cholesterol/HDL-C (per unit higher) | 0.001 (−.001 to .003) | .263 |
| LDL-C/HDL-C (per unit higher) | 0.001 (−.018 to .004) | .527 |
| ApoA-1 (per mg/dL higher) | −0.00000 (−.0001 to .0002) | .995 |
| ApoB (per mg/dL higher) | 0.00008 (−.00007 to .0002) | .311 |
| ApoB/ApoA-1 (per unit higher) | 0.0078 (−.0094 to .011) | .880 |
| HOMA-IR (per unit higher) | −0.0004 (−.001 to .0003) | .252 |
| Serum creatinine (per mg/dL higher) | 0.017 (.002–.032) | .029 |
| GFR (<60 vs ≥60 mL/min/1.73 m2) | 0.0002 (−.020 to .020) | .983 |
| Cystatin-C (per mg/dL higher) | 0.028 (.005–.052) | .018 |
| hsCRP (per mg/dL higher) | 0.0002 (−.0002 to .0007) | .285 |
| HIV-specific parameters | ||
| Time since HIV infection diagnosis (per year longer) | 0.0003 (−.0004 to .001) | .477 |
| cART exposure (per year longer) | −0.022 (−.060 to .014) | .238 |
| Prior AIDS (vs not) | 0.004 (−.004 to .011) | .354 |
| CD4+ cell count nadir <200 cells/mm3 (vs not) | 0.002 (−.004 to .009) | .524 |
| Baseline CD4+ cell count (per 100 cells/mm3 higher) | −0.001 (−.002 to .001) | .350 |
| Baseline suppressed HIV RNA viral load (<400 copies/mL vs not) | −0.006 (−.014 to .0006) | .074 |
| Persistently suppressed HIV RNA viral load (<400 copies/mL throughout follow-up vs ≥400 copies/mL at ≥1 visit) | −0.008 (−.014 to −.001) | .023 |
| Baseline cART prescription (vs not) | −0.007 (−.015 to −.0003) | .060 |
| Baseline tenofovir prescription (vs abacavir) | −0.002 (−.011 to .008) | .742 |
| Baseline NNRTI prescription (vs PI prescription) | −0.012 (−.020 to −.004) | .004 |
Abbreviations: ApoB/A-1, apolipoprotein B/A-1; BMI, body mass index, defined as weight in kilograms divided by height in meters squared; BP, blood pressure; CI, confidence interval; HDL-C, high-density lipoprotein cholesterol; HOMA-IR, homeostasis model assessment of insulin resistance (see Methods for equation); hsCRP, high-sensitivity C-reactive protein; LDL-C, low-density lipoprotein cholesterol; NNRTI, nonnucleoside reverse-transcriptase inhibitor; PI, protease inhibitor.
Regression coefficients represent a greater or lesser change in carotid artery intima-media thickness (in mm) over 2 years per difference in the corresponding parameter.
HIV Replication and Carotid Artery Intima-Media Thickness Progression
For characterizing VL during follow-up, all but 1 participant had ≥2 VL measurements, and 90% (n = 349) had ≥5 measures (median no. of VL measurements, 7.0; IQR, 6.0–9.0). After adjustment for traditional risk factors in Table 3, both a suppressed VL at baseline and remaining suppressed throughout follow-up were independently associated with less CIMT progression (Figure 2A). Results were similar for maintaining a suppressed VL when adjusted models incorporated total cholesterol-to-HDL-C ratio instead of ldl-C (−0.010 mm; P = .005) or added baseline prescription of lipid-lowering therapy (−0.010 mm; P = .003). In a sensitivity analysis excluding those prescribed lipid-lowering therapy at baseline, the association between CIMT change and persistently suppressed VL remained (−0.010 mm; P = .005). Finally, this association persisted in a more parsimonious model, adjusting only for FRS (P < .001).
Table 3.
Multivariate Associations for 2-Year Carotid Artery Intima-Media Thickness (CIMT) Progression With Traditional Risk Factors and With Human Immunodeficiency Virus Parameters Among Study to Understand the Natural History of HIV/AIDS in the Era of Effective Therapy Participants
| Variable | Regression coefficient (95% confidence interval) | P |
| Traditional risk factora | ||
| Age (per 10 years older) | 0.003 (−.001 to .008) | .131 |
| Male sex (vs female sex) | −0.004 (−.013 to .005) | .360 |
| Race/ethnicity (non-Hispanic white vs not) | −0.001 (−.009 to .0008) | .752 |
| Tobacco smoking (current smoker vs not) | 0.004 (−.003 to .011) | .232 |
| BMI (>25 vs ≤25) | 0.013 (.006–.020) | <.001 |
| Diabetes (vs not) | −0.001 (−.013 to .011) | .835 |
| Hypertension (vs not) | 0.002 (−.0009 to .010) | .544 |
| LDL-C (per 10 mg/dL higher) | 0.00002 (−.0007 to .0001) | .969 |
| HIV-specific parameters (adjusted for traditional risk factors)b | ||
| Baseline CD4+ cell count (per 100 cells/mm3 higher) | −0.0006 (−.002 to .0007) | .361 |
| Baseline suppressed HIV RNA viral load (<400 copies/mL vs not) | −0.009 (−.017 to −.002) | .015 |
| Persistently suppressed HIV RNA viral load (<400 copies/mL throughout follow-up vs ≥400 copies/mL at ≥1 visit) | −0.011 (−.018 to −.004) | <.001 |
| Baseline cART exposure (vs not) | −0.007 (−.015 to .0007) | .075 |
Model includes the traditional risk factors listed above and baseline CIMT. BMI, body mass index, defined as weight in kilograms divided by the square of height in meters; cART, combination antiretroviral therapy; ldl-C, low-density lipoprotein cholesterol.
Model includes the traditional risk factors listed above, baseline CIMT, and the individual HIV parameter listed (ie, the model was run 4 times, once per covariate listed).
Among persons with a suppressed VL throughout follow-up (n = 235), compared with those without (n = 153), median baseline CD4+ cell count was higher (522 vs 451 cells/mm3; P = .019), but serum hsCRP values were not different. Among the 153 participants with a detectable VL, CIMT progression did not differ between those receiving cART (n = 80) and those not receiving cART (n = 73; Figure 2A) at baseline. In a sensitivity analysis that excluded the 73 participants not prescribed ART at baseline, the association of less CIMT change with a persistently suppressed VL was maintained (−0.012 mm; P = .009). Finally, among these 73 participants, CIMT change over this short-term follow-up did not differ between those who subsequently started cART and those who did not (P = .49; data not shown).
Antiretroviral Therapy Exposure and Carotid Artery Intima-Media Thickness Progression
We then explored the influence of cART exposure among the 302 SUN participants prescribed cART at baseline (Figures 2B and 3). When adjusting for traditional risk factors (Table 3) as well as a persistently suppressed VL, baseline exposure to NNRTI- versus PI-based cART was independently associated with lesser CIMT progression (−0.010 mm; 95% CI, −.018 to .002; P = .011). This association persisted when restricted to participants who did not switch between NNRTI and PI regimens (n = 272) during follow-up (−0.010 mm; P = .020). Finally, estimates for associations between NNRTI- versus PI-based ART and CIMT change were similar in univariate (Table 2) and fully adjusted models.
Figure 3.
Median carotid artery intima-media thickness (CIMT) progression among Study to Understand the Natural History of HIV/AIDS in the Era of Effective Therapy (SUN Study) participants (n = 274) stratified by viral suppression and combined antiretroviral therapy (cART). Median 2-year CIMT change is reported for the following subgroups of SUN participants: (a) nonnucleoside reverse-transcriptase inhibitor (NNRTI)–based cART use at baseline with a suppressed human immunodeficiency virus (HIV) RNA viral load throughout follow-up (white), (b) protease inhibitor (PI)–based cART use at baseline with a suppressed HIV viral load throughout follow-up (dark gray), (c) NNRTI-based cART use at baseline with ≥1 detectable HIV viral load during follow-up (light gray), and (d) PI-based cART use at baseline with ≥1 detectable HIV viral load during follow-up (black). In a multivariate model adjusting for traditional risk factors (see Table 3 for covariates), regression coefficients (95% confidence intervals) were: 0.009 mm (−.0003 to .018 mm; P = .059) for b versus a; 0.008 mm (−.004 to .022 mm; P = .174) for c versus a; 0.014 mm (−.0000 to .027 mm; P = .05) for d versus b; and 0.013 mm (−.003 to .030 mm; P = .112) for d versus c.
CIMT progression did not differ between participants prescribed abacavir versus tenofovir at baseline (Figure 2B), and this comparison remained nonsignificant after excluding participants who switched from abacavir or tenofovir after the baseline visit (0.007; 95% CI, −0.003 to 0.017; P = .155). Furthermore, when restricted to those prescribed PIs, CIMT change was not different between prescription of abacavir (n = 27) and tenofovir (n = 54) after adjusting for CVD risk factors and serum creatinine (0.008; P =.37).
For the 274 participants prescribed exclusively an NNRTI- or PI-based regimen at baseline, we further stratified median 2-year CIMT change by whether VL was persistently suppressed (Figure 3). We observed qualitatively that participants exposed to NNRTI-based cART who maintained a suppressed HIV RNA VL exhibited the lowest rate of CIMT progression, whereas participants who were prescribed PI-based cART and had a detectable VL at any visit exhibited the greatest progression. When restricted to participants who maintained viral suppression, the difference in CIMT progression between PI and NNRTI use at baseline approached significance (0.009 mm greater progression; P = .059; see Figure 3 for all comparisons).
DISCUSSION
We studied HIV-related factors associated with CIMT progression, an established marker of CVD, over a 2-year period within a contemporary cohort of HIV-infected participants. Overall, the degree of subclinical atherosclerotic progression was modest, consistent with the young age of the cohort, and an emphasis on traditional CVD risk factor modification in current HIV practice. Our findings suggest that maintaining a clinically suppressed HIV VL protects against atherosclerotic progression. After adjusting for the protective effects of viral suppression, use of NNRTI-based cART was associated with less CIMT progression than was PI-based cART. These findings support the notion that both HIV replication and exposure to certain antiretroviral medications contribute to CVD risk.
Estimates of CIMT progression in the general population have generally included patients older (age, 45–64 years) than those in the SUN Study [23, 24]. Differences in methodology preclude reliable comparisons across studies, but crude rates of CIMT progression from these studies correspond to the rate observed in our younger HIV cohort (age, 36–47 years). One prior study of 133 subjects infected with HIV had failed to show an effect of HIV status or PI exposure on CIMT progression [25], whereas another study involving 211 participants reported greater CIMT progression among HIV-infected patients than among uninfected patients [26]. With additional follow-up (n = 285), this later study by Hsue et al [27] reported the greatest CIMT progression in the carotid bulb and bifurcation, which was associated with hsCRP levels. A potential differential effect of HIV infection on atherosclerosis at different vascular regions has been suggested by other studies [11], but the clinical significance of this observation requires clarification. Our findings add to these studies by demonstrating that clinically detectable HIV replication is associated with greater CIMT progression.
Findings from the Strategic Management of AntiRetroviral Therapy (SMART) trial have fundamentally changed our understanding of HIV-related CVD pathogenesis. In SMART, a strategy of intermittent cART treatment was associated with a 60% increased risk for CVD events when compared with a strategy of continuous viral suppression [2]. Our findings supplement the SMART findings by characterizing the influence of uncontrolled HIV replication on the atherosclerotic disease process at the level of the arterial wall.
In general, our findings are consistent with the hypothesis that HIV treatment with ART may reduce atherogenesis, in part, by attenuating HIV-related inflammation. Among person infected with HIV, T-cell activation is associated with subclinical atherosclerosis [9], and inflammatory markers are both elevated, compared with those in uninfected persons, and remain predictive of CVD events [28, 29]. The importance of immune depletion itself as a contributor to CVD risk is less clear, because some epidemiologic data have demonstrated higher CVD risk with lower CD4+ cell counts [30, 31], whereas others have not [1, 32]. The relatively narrow distribution of CD4+ cell counts among SUN participants limited our ability to characterize the effect on differences in CIMT progression.
To complicate matters, HIV treatment with cART may in fact both reduce and increase CVD risk by suppressing viral replication while concurrently adding drug-specific toxicities [3, 33–35]. The typical proatherogenic phenotype associated with PI therapy has included hypertriglyceridemia, lipodystrophy (eg, increased visceral adiposity), and insulin resistance [33, 36]. These factors, in turn, have been associated with inflammation and premature vascular disease [36–40]. Consistent with this, the Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) study report an increased risk of myocardial infarction per year of PI exposure and with recent exposure to the NRTI abacavir [3, 34]. Our findings implicating PI exposure are consistent with data from the D:A:D study, but we observed no differences in CIMT progression between abacavir and tenofovir exposure.
Our findings are limited by the lack of an HIV-uninfected control group and the fact that most SUN study participants were prescribed cART. More importantly, our analysis does not represent a direct comparison of cART-treated versus untreated HIV infection per se. As with any cohort study, causation cannot be established, and channeling bias and other unmeasured confounding may be present. Specifically, excellent adherence is required to maintain a persistently undetectable HIV VL, and adherence may coassociate with other risk factors. Ultimately, we believe that we were able to account for many potentially confounding factors because of the comprehensive data collection in SUN, and a randomized trial is ongoing that will study CVD risk with a strategy of early ART initiation versus deferral until CD4+ cell counts reach 350 cells/mm3 (START trial). In addition, CIMT was assessed only at a single site in the common carotid artery (ie, far wall), because measurements obtained from other carotid segments demonstrate significant variability and are less desirable for longitudinal assessments. Finally, important associations may have been missed because of the relatively short follow-up period (eg, small changes in CIMT) and the small numbers available for subgroup analyses. For example, sex, hypertension, and ldl-C level were significantly associated with CIMT measures at baseline but not 2-year progression.
In summary, persistent suppression of HIV replication below clinical thresholds was associated with less atherosclerotic progression. Future controlled studies are needed that replicate these findings and better characterize the proatherogenic mechanisms of HIV replication as well as evaluate the net benefit of specific antiretrovirals on long-term CVD risk.
Acknowledgments
Acknowledgments. We thank all of the SUN Study participants as well as all the clinical site investigators and staff.
The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention.
Financial support. This work was supported by the Centers for Disease Control and Prevention (contracts 200-2002-00610/00611/00612/00613 and 200-2007-3633/23634/23635/23636) and the National Institutes of Health (K12 RR023247).
Potential conflicts of interest. J. V. B. has received research support from Gilead, ViiV, and Tibotec. K. H. has received research support from Bristol-Meyers Squibb, Gilead, ViiV, and Tibotec. M. B. serves on speakers Bureau for General Electric. All other authors report no potential conflicts.
All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.
References
- 1.Mocroft A, Reiss P, Gasiorowski J, et al. Serious fatal and nonfatal non-AIDS-defining illnesses in Europe. J Acquir Immune Defic Syndr. 2010;55:262–70. doi: 10.1097/QAI.0b013e3181e9be6b. [DOI] [PubMed] [Google Scholar]
- 2.El-Sadr WM, Lundgren JD, Neaton JD, et al. CD4+ count-guided interruption of antiretroviral treatment. N Engl J Med. 2006;355:2283–96. doi: 10.1056/NEJMoa062360. [DOI] [PubMed] [Google Scholar]
- 3.Friis-Moller N, Reiss P, Sabin CA, et al. Class of antiretroviral drugs and the risk of myocardial infarction. N Engl J Med. 2007;356:1723–35. doi: 10.1056/NEJMoa062744. [DOI] [PubMed] [Google Scholar]
- 4.Saves M, Chene G, Ducimetiere P, et al. Risk Factors for coronary heart disease in patients treated for human immunodeficiency virus infection compared with the general population. Clin Infect Dis. 2003;37:292–8. doi: 10.1086/375844. [DOI] [PubMed] [Google Scholar]
- 5.Craven TE, Ryu JE, Espeland MA, et al. Evaluation of the associations between carotid artery atherosclerosis and coronary artery stenosis: a case-control study. Circulation. 1990;82:1230–42. doi: 10.1161/01.cir.82.4.1230. [DOI] [PubMed] [Google Scholar]
- 6.Hodis HN, Mack WJ, LaBree L, et al. The role of carotid arterial intima-media thickness in predicting clinical coronary events. Ann Intern Med. 1998;128:262–9. doi: 10.7326/0003-4819-128-4-199802150-00002. [DOI] [PubMed] [Google Scholar]
- 7.Currier JS, Kendall MA, Zackin R, et al. Carotid artery intima-media thickness and HIV infection: traditional risk factors overshadow impact of protease inhibitor exposure. AIDS. 2005;19:927–33. doi: 10.1097/01.aids.0000171406.53737.f9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Kaplan RC, Kingsley LA, Gange SJ, et al. Low CD4+ T-cell count as a major atherosclerosis risk factor in HIV-infected women and men. AIDS. 2008;22:1615–24. doi: 10.1097/QAD.0b013e328300581d. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Kaplan RC, Sinclair E, Landay AL, et al. T cell activation and senescence predict subclinical carotid artery disease in HIV-infected women. J Infect Dis. 2011;203:452–63. doi: 10.1093/infdis/jiq071. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Tien PC, Schneider MF, Cole SR, et al. Association of hepatitis C virus and HIV infection with subclinical atherosclerosis in the women's interagency HIV study. AIDS. 2009;23:1781–4. doi: 10.1097/QAD.0b013e32832d7aa8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Grunfeld C, Delaney JA, Wanke C, et al. Preclinical atherosclerosis due to HIV infection: carotid intima-medial thickness measurements from the FRAM study. AIDS. 2009;23:1841–9. doi: 10.1097/QAD.0b013e32832d3b85. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Johnsen S, Dolan SE, Fitch KV, et al. Carotid intimal medial thickness in human immunodeficiency virus-infected women: effects of protease inhibitor use, cardiac risk factors, and the metabolic syndrome. J Clin Endocrinol Metab. 2006;91:4916–24. doi: 10.1210/jc.2006-1140. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Ross AC, Rizk N, O'Riordan MA, et al. Relationship between inflammatory markers, endothelial activation markers, and carotid intima-media thickness in HIV-infected patients receiving antiretroviral therapy. Clin Infect Dis. 2009;49:1119–27. doi: 10.1086/605578. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Sankatsing RR, Wit FW, Vogel M, et al. Increased carotid intima-media thickness in HIV patients treated with protease inhibitors as compared to non-nucleoside reverse transcriptase inhibitors. Atherosclerosis. 2009;202:589–95. doi: 10.1016/j.atherosclerosis.2008.05.028. [DOI] [PubMed] [Google Scholar]
- 15.Vellozzi C, Brooks JT, Bush TJ, et al. The study to understand the natural history of HIV and AIDS in the era of effective therapy (SUN Study) Am J Epidemiol. 2009;169:642–52. doi: 10.1093/aje/kwn361. [DOI] [PubMed] [Google Scholar]
- 16.Anderson KM, Wilson PW, Odell PM, Kannel WB. An updated coronary risk profile: a statement for health professionals. Circulation. 1991;83:356–62. doi: 10.1161/01.cir.83.1.356. [DOI] [PubMed] [Google Scholar]
- 17.Selzer RH, Hodis HN, Kwong-Fu H, et al. Evaluation of computerized edge tracking for quantifying intima-media thickness of the common carotid artery from B-mode ultrasound images. Atherosclerosis. 1994;111:1–11. doi: 10.1016/0021-9150(94)90186-4. [DOI] [PubMed] [Google Scholar]
- 18.Hodis H, Mack W. Carotid artery intimi-media thickness and risk of cardiovascular events. Curr Pract Med. 1999;2:171–4. [Google Scholar]
- 19.Hodis HN, Mack WJ, LaBree L, et al. Alpha-tocopherol supplementation in healthy individuals reduces low-density lipoprotein oxidation but not atherosclerosis: the Vitamin E Atherosclerosis Prevention Study (VEAPS) Circulation. 2002;106:1453–9. doi: 10.1161/01.cir.0000029092.99946.08. [DOI] [PubMed] [Google Scholar]
- 20.Selzer RH, Mack WJ, Lee PL, Kwong-Fu H, Hodis HN. Improved common carotid elasticity and intima-media thickness measurements from computer analysis of sequential ultrasound frames. Atherosclerosis. 2001;154:185–93. doi: 10.1016/s0021-9150(00)00461-5. [DOI] [PubMed] [Google Scholar]
- 21.1993 revised classification system for HIV infection and expanded surveillance case definition for AIDS among adolescents and adults. MMWR Recomm Rep. 1992;41:1–19. [PubMed] [Google Scholar]
- 22.Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). Executive summary of the third report of the National Cholesterol Education Program (NCEP) expert panel on detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel III) JAMA. 2001;285:2486–97. doi: 10.1001/jama.285.19.2486. [DOI] [PubMed] [Google Scholar]
- 23.Howard G, Sharrett AR, Heiss G, et al. Carotid artery intimal-medial thickness distribution in general populations as evaluated by B-mode ultrasound. ARIC Investigators. Stroke. 1993;24:1297–304. doi: 10.1161/01.str.24.9.1297. [DOI] [PubMed] [Google Scholar]
- 24.Chambless LE, Folsom AR, Davis V, et al. Risk factors for progression of common carotid atherosclerosis: the Atherosclerosis Risk in Communities Study, 1987–1998. Am J Epidemiol. 2002;155:38–47. doi: 10.1093/aje/155.1.38. [DOI] [PubMed] [Google Scholar]
- 25.Currier JS, Kendall MA, Henry WK, et al. Progression of carotid artery intima-media thickening in HIV-infected and uninfected adults. AIDS. 2007;21:1137–45. doi: 10.1097/QAD.0b013e32811ebf79. [DOI] [PubMed] [Google Scholar]
- 26.Hsue PY, Lo JC, Franklin A, et al. Progression of atherosclerosis as assessed by carotid intima-media thickness in patients with HIV infection. Circulation. 2004;109:1603–8. doi: 10.1161/01.CIR.0000124480.32233.8A. [DOI] [PubMed] [Google Scholar]
- 27.Hsue PY, Hunt PW, Schnell A, et al. Role of viral replication, antiretroviral therapy, and immunodeficiency in HIV-associated atherosclerosis. AIDS. 2009;23:1059–67. doi: 10.1097/QAD.0b013e32832b514b. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Kuller LH, Tracy R, Belloso W, et al. Inflammatory and coagulation biomarkers and mortality in patients with HIV infection. PLoS Med. 2008;5:e203. doi: 10.1371/journal.pmed.0050203. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Neuhaus J, Jacobs DR, Jr, Baker JV, et al. Markers of inflammation, coagulation, and renal function are elevated in adults with HIV infection. J Infect Dis. 2010;201:1788–95. doi: 10.1086/652749. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Lichtenstein KA, Armon C, Buchacz K, et al. Low CD4+ T cell count is a risk factor for cardiovascular disease events in the HIV outpatient study. Clin Infect Dis. 2010;51:435–47. doi: 10.1086/655144. [DOI] [PubMed] [Google Scholar]
- 31.Triant VA, Regan S, Lee H, Sax PE, Meigs JB, Grinspoon SK. Association of immunologic and virologic factors with myocardial infarction rates in a US healthcare system. J Acquir Immune Defic Syndr. 2010;55:615–19. doi: 10.1097/QAI.0b013e3181f4b752. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Achhra AC, Amin J, Law MG, et al. Immunodeficiency and the risk of serious clinical endpoints in a well studied cohort of treated HIV-infected patients. AIDS. 2010;24:1877–86. doi: 10.1097/QAD.0b013e32833b1b26. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Grinspoon S, Carr A. Cardiovascular risk and body-fat abnormalities in HIV-infected adults. N Engl J Med. 2005;352:48–62. doi: 10.1056/NEJMra041811. [DOI] [PubMed] [Google Scholar]
- 34.Sabin CA, Worm SW, Weber R, et al. Use of nucleoside reverse transcriptase inhibitors and risk of myocardial infarction in HIV-infected patients enrolled in the D:A:D study: a multi-cohort collaboration. Lancet. 2008;371:1417–26. doi: 10.1016/S0140-6736(08)60423-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Freedman DS, Otvos JD, Jeyarajah EJ, Barboriak JJ, Anderson AJ, Walker JA. Relation of lipoprotein subclasses as measured by proton nuclear magnetic resonance spectroscopy to coronary artery disease. Arterioscler Thromb Vasc Biol. 1998;18:1046–53. doi: 10.1161/01.atv.18.7.1046. [DOI] [PubMed] [Google Scholar]
- 36.Grunfeld C, Pang M, Doerrler W, Shigenaga JK, Jensen P, Feingold KR. Lipids, lipoproteins, triglyceride clearance, and cytokines in human immunodeficiency virus infection and the acquired immunodeficiency syndrome. J Clin Endocrinol Metab. 1992;74:1045–52. doi: 10.1210/jcem.74.5.1373735. [DOI] [PubMed] [Google Scholar]
- 37.Stein JH, Klein MA, Bellehumeur JL, et al. Use of human immunodeficiency virus-1 protease inhibitors is associated with atherogenic lipoprotein changes and endothelial dysfunction. Circulation. 2001;104:257–62. doi: 10.1161/01.cir.104.3.257. [DOI] [PubMed] [Google Scholar]
- 38.Boger MS, Shintani A, Redhage LA, et al. Highly sensitive C-reactive protein, body mass index, and serum lipids in HIV-infected persons receiving antiretroviral therapy: a longitudinal study. J Acquir Immune Defic Syndr. 2009;52:480–7. doi: 10.1097/qai.0b013e3181b939e5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Mondy KE, de las Fuentes L, Waggoner A, et al. Insulin resistance predicts endothelial dysfunction and cardiovascular risk in HIV-infected persons on long-term highly active antiretroviral therapy. AIDS. 2008;22:849–56. doi: 10.1097/QAD.0b013e3282f70694. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Gazzaruso C, Bruno R, Garzaniti A, et al. Hypertension among HIV patients: prevalence and relationships to insulin resistance and metabolic syndrome. J Hypertens. 2003;21:1377–82. doi: 10.1097/01.hjh.0000059071.43904.dc. [DOI] [PubMed] [Google Scholar]