Abstract
Background
Human immunodeficiency virus (HIV)–infected patients are at increased risk of cardiovascular disease, which may be related to chronic inflammation and endothelial dysfunction despite virological control with antiretroviral therapy. The relationship between carotid intima-media thickness (IMT), a surrogate marker for cardiovascular disease, proinflammatory cytokines, and endothelial activation markers has not been fully explored in HIV-infected patients who are receiving antiretroviral therapy.
Methods
We conducted a prospective, cross-sectional, observational study of treated HIV-infected patients and healthy control subjects to evaluate the relationship between carotid IMT, proinflammatory cytokines, endothelial activation biomarkers, and metabolic parameters in treated HIV-infected patients, compared with healthy control subjects.
Results
We enrolled 73 HIV-infected patients and 21 control subjects. Common carotid artery and internal carotid artery IMT measurements, as well as tumor necrosis factor–α, high-sensitivity C-reactive protein, inter-leukin-6, myeloperoxidase, and soluble vascular cell adhesion molecule-1 levels were higher in the HIV-infected group. High-sensitivity C-reactive protein was the only biomarker that was positively correlated with carotid IMT in both groups. In the HIV-infected group, soluble vascular cell adhesion molecule–1 was positively correlated with all inflammatory cytokine levels. In multiple regression analysis, soluble vascular cell adhesion molecule–1, myeloperoxidase, and tumor necrosis factor–α levels were all associated with internal carotid artery IMT in the HIV-infected group, whereas age was associated with both common carotid artery and internal carotid artery IMT.
Conclusions
Enhanced endothelial activation, inflammation, and increased carotid IMT occur in HIV-infected patients despite antiretroviral therapy. Inflammatory markers are associated with endothelial activation, and both are associated with internal carotid artery IMT, supporting a potential role of inflammation in endothelial activation and cardiovascular disease in HIV infection.
HIV-infected individuals appear to be at higher risk of cardiovascular disease (CVD) than the general population [1, 2]. The etiology of the increased risk remains unclear. Some data suggest that long-term protease inhibitors use contributes to risk [3–5], whereas others cite more traditional risk factors, such as smoking, dyslipidemia, and advanced age [6–8]. Measurement of carotid intima-media thickness (IMT) is a well-accepted, noninvasive method of monitoring subclinical atherosclerotic formation and progression, and increased IMT correlates with an increased risk of CVD events, such as myocardial infarction and stroke, in the general population [9–12]. Although no studies to date show prediction of CVD events on the basis of IMT values in the HIV-infected population, several studies demonstrate increased IMT in HIV-infected individuals, compared with healthy control persons [8, 13–15], and IMT progresses more rapidly over time in HIV-infected patients [8, 14, 16]. Likewise, data show that HIV infection status, when controlled for other factors, is associated with increased carotid IMT [15, 17].
There is mounting evidence to support the role of inflammation and endothelial activation and dysfunction in the development of plaque formation and progression of atherosclerosis in the general population [18–27]. For example, elevated levels of the proinflammatory cytokines interleukin (IL)-6 and C-reactive protein (CRP) are associated with subclinical atherosclerosis [18] and are independently predictive of future cardiovascular events [19, 20]. In addition, tumor necrosis factor (TNF)–α has been implicated in myocardial dysfunction after acute coronary syndromes, and levels of TNF-α have been shown to be higher in patients at baseline who experience recurrent myocardial infarctions or cardiac death [21, 22]. The effects of TNF-α are mediated by 2 receptors, TNFR-I and TNFR-II; these soluble receptors are stable in plasma, easily measured, and reflect activity of TNF-α. Myeloperoxidase, a peroxidase enzyme found in leukocytes and released when leukocytes are activated, has also been established as an independent predictor of early risk of myocardial infarction in patients presenting with chest pain [23], and myeloperoxidase levels are associated with the presence of coronary artery disease and endothelial dysfunction in the general population [24]. Likewise, levels of 2 circulating adhesion molecules, soluble vascular cell adhesion molecule–1 (sVCAM-1) and soluble intercellular adhesion molecule–1 (sICAM-1), as well as levels of von Willebrand factor antigen (vWF), arise from shedding or proteolytic cleavage from activated endothelial cells and are useful markers for increased activation of endothelial cells in atherosclerosis [25–27].
Few studies have examined the relationship between markers of inflammation and endothelial activation and measurements of carotid IMT. In the general population, the Offspring Cohort of the Framingham Heart Study found an association between inflammatory markers and IMT [28], whereas studies examining the role of chronic inflammation as a cause of the increased CVD risk in patients with type-2 diabetes have produced conflicting results [29–31]. Nevertheless, increased levels of inflammatory markers and evidence of endothelial dysfunction are evident in HIV-infected individuals [32–35] and may be correlated with increased risk of CVD. Even in patients who are receiving antiretroviral therapy (ART), inflammatory cytokine levels do not completely normalize to that of the general population [33], suggesting that there is ongoing inflammation despite an undetectable virus level.
To date, no study has comprehensively examined the relationship among inflammatory markers, carotid IMT, and endothelial activation markers in HIV-infected individuals. We hypothesized that inflammatory markers are correlated with both carotid IMT and endothelial activation markers in HIV-infected subjects receiving ART and that both inflammatory and endothelial activation markers are associated with carotid IMT. In this study, we measured plasma levels of proinflammatory cytokines, TNF-α, sTNFR-I and -II, IL-6, high-sensitivity CRP (hsCRP), and myeloperoxidase, and of 3 endothelial activation markers, sICAM-1, sVCAM-1, and vWF, to explore their relationship to carotid IMT in HIV-infected individuals receiving ART with virologic control. As a secondary objective, we examined carotid IMT, inflammatory markers, and endothelial activation markers in ART-treated, HIV-infected subjects, compared with a small convenience sample of healthy control subjects.
METHODS
Study design and patient population
This is a cross-sectional, multicentered, observational study. Subjects were enrolled prospectively at the John T. Carey Special Immunology Unit of University Hospitals Case Medical Center/Case Western Reserve University and at the Cleveland Clinic Foundation in Cleveland, Ohio. Inclusion criteria included documented HIV infection, age ≥21 years, and stable receipt of ART for ≥24 weeks. Exclusion criteria included known CVD, diabetes, current opportunistic infection, and acute or chronic inflamma-tory condition. Healthy control subjects were selected from a convenience sample that included hospital staff members and relatives of HIV-infected patients and staff and were eligible if they had no recent or current infection and no uncontrolled chronic conditions. Control subjects were matched so that the median age was within 5 years of that for HIV-infected subjects. Exclusion criteria for control subjects were the same as that for the HIV-infected group.
Study evaluations included physical examination; measurement of blood pressure, height, weight, and waist-to-hip ratio (with standardized measurements based on procedure recommendations from the Metabolic Study Group of the AIDS Clinical Trials Group); blood sampling after ≥8 h of fasting; and carotid ultrasound. Homeostasis model assessment of insulin resistance (HOMA-IR) was calculated by dividing the product of the fasting glucose level (mg/dL) and the fasting insulin level (mU/mL) by 22.5 [36]. Extensive chart review was conducted for HIV-infected subjects, including HIV duration, detailed ART history, past and current medical diagnoses, current medications, and nadir CD4 cell count. Demographic characteristics were collected from both groups, including smoking and relevant family history.
Metabolic, inflammatory, and cardiovascular tests
Fasting blood samples were drawn from all subjects for real-time measurements of insulin, glucose, and lipoprotein profile. We also measured plasma levels of TNF-α, sTNFR-I, sTNFR-II, IL-6, hsCRP, myeloperoxidase, and endothelial markers vWF, sICAM-1, and sVCAM-1 with use of an enzyme-labeled immunosorbent sandwich assay (Searchlight; Thermo Fisher Scientific). The median intra-assay coefficients of variation for TNF-a, sTNFR-I, sTNFR-II, IL-6, hsCRP, vWF, sICAM-1, sVCAM-1, and myeloperoxidase measurements were 14.5%, 8.8%, 8.6%, 11.7%, 6.9%, 13.3%, 8.0%, 8.7%, and 7.5%, respectively. The median interassay coefficients of variation for each assay were 9.8%, 10.8%, 6.0%, 10.4%, 4.5%, 9.0%, 4.2%, 13.4%, and 12.6%, respectively. Finally, CD4 cell counts and HIV RNA levels were measured as markers of HIV disease.
Carotid IMT measurements
All carotid ultrasounds were performed by the same experienced sonographer (J.A.), and read by an experienced radiologist (V.D.). Both investigators were blinded to patient characteristics and results. Carotid IMT methods were used as described elsewhere [13]. Briefly, images of the bilateral distal common carotid arteries (CCA), and internal carotid arteries (ICA) were obtained in longitudinal views separately. Images of the near (proximal) and far wall free of plaques (distal) were acquired with a 7–14 MHz AT 1204 linear array transducer (Toshiba American Medical Systems) operating at 14 MHz with differential harmonics. Three measurements of the IMT were obtained at near and far wall of each CCA and ICA. The mean of 3 measurements at each site (right and left side) was used as final measurement of IMT for that site (for both CCA and ICA, the far and near wall had 3 IMT measurements each, resulting in a total of 12 measurements). Right and left sides were then averaged and reported as a single ICA and CCA measurement. Plaque was defined, measured, and graded as a plaque index according to published protocols from the Cardiovascular Health Study [37].
Statistical methods
Continuous measurements are described as medians and ranges, and nominal variables are described with percentages. Continuous measurements were compared using Wilcoxon rank-sum tests and nominal variables were compared using Fisher's exact test, as appropriate. The level of correlation was estimated using Spearman correlation coefficients.
Two-stage regression analysis was performed within the HIV-infected group for each IMT measure (ICA and CCA) to determine factors associated with IMT. In the first stage, 4 separate models were created for both ICA and CCA, examining different categories expected to affect IMT: (1) clinical characteristics, (2) laboratory values, (3) HIV-related factors, and (4) biomarker values. Variables for inclusion in models were chosen either on the basis of bivariate results or because of clinical significance. All 9 biomarkers were included in the first stage. Departures from normality in these variables were addressed by comparing differences between results when modeling on the raw scale and on log10 scale. It should be noted that the log10 transformations did not achieve normality in most cases, and therefore, models were constructed using the raw scale. Because there is a moderate to high degree of collinearity in the biomarkers, collinearity diagnostics were performed. Any variable from each of the first stage models that was significant at the P ≤ .1 level, or lacking that, the most significant variable in the model, was included in the second stage analysis. The final model included all variables that remained with P < .1. Results are presented as regression coefficients, standard errors of the coefficients, P values, and adjusted R2 values.
All analyses were performed using SAS, version 9.1 (SAS Institute). The level of significance for all analyses was set at .05.
RESULTS
Study population and between-group comparison of clinical characteristics
We enrolled 73 HIV-infected patients and 21 healthy control subjects for this observational cross-sectional study. Demographic, clinical, and HIV-related characteristics and fasting metabolic parameters are shown in Table 1. Groups were similar with regard to age, race, and body mass index (BMI [calculated as weight in kilograms divided by the square of height in meters]); however, male sex, smoking rates, blood pressure, and waist-to-hip ratio were higher in the HIV-infected group. The HIV-infected group also had significantly higher HOMA-IR scores and lower median high-density lipoprotein (HDL) cholesterol levels, but total cholesterol, triglyceride, and non-HDL median levels were similar between groups. There were, however, more HIV-infected patients receiving taking lipid- and triglyceride-lowering medications at the time of study enrollment. Low-dose aspirin (≤80 mg daily) and antihypertensive use were not statistically significantly different between groups. Family history of premature CVD was higher among control subjects, but family history of type-2 diabetes was similar.
Table 1.
Clinical Characteristics and Fasting Metabolic Parameters in Human Immunodeficiency Virus (HIV)–Infected Patients and Healthy Control Subjects
| Characteristic | HIV-infected patients (n = 73) | Control subjects (n = 21) | P |
|---|---|---|---|
| Age | 48 (21–70) | 43 (21–65) | .11 |
| Male sex | 59 (81) | 12 (57) | .03 |
| Race | |||
| African-American | 28 (38) | 5 (24) | .41 |
| White | 33 (45) | 15 (71) | |
| Hispanic | 7 (10) | 1 (5) | |
| Other | 5 (7) | 0 (0) | |
| BMI, median kg/m2 (range) | 26.0 (19.8–40.8) | 27.2 (18.7–34.0) | .82 |
| Systolic blood pressure, median mm Hg (range) | 120 (90–160) | 113 (90–126) | .003 |
| Diastolic blood pressure, median mm Hg (range) | 80 (58–110) | 70 (58–90) | .006 |
| Waist...hip ratio, median (range) | 0.97 (0.83–1.22) | 0.88 (0.69–1.00) | <.001 |
| Total cholesterol, median mg/dL (range) | 182 (103–336) | 207 (120–286) | .07 |
| HDL cholesterol, median mg/dL (range) | 38 (21–93) | 53 (28–87) | <.001 |
| LDL cholesterol, median mg/dL (range) | 107 (23–228) | 131 (54–182) | .08 |
| Non-HDL cholesterol, median mg/dL (range) | 144 (61–280) | 154 (67–258) | .71 |
| Triglycerides, median mg/dL (range) | 169 (42–716) | 78 (38–1138) | .30 |
| HOMA-IR, median value (range) | 2.8 (0.49–37.13) | 1.52 (0.52–3.89) | <.001 |
| Smoking habits | |||
| Current | 25 (38) | 2 (10) | .04 |
| Past | 12 (18) | 3 (15) | |
| Never | 29 (38) | 15 (75) | |
| Low-dose aspirin use | 11 (15) | 0 (0) | .06 |
| Antihypertensive usea | 14 (19) | 3 (14) | .75 |
| Lipid-lowering medication useb | 20 (28) | 0 (0) | .005 |
| Hypertriglyceridemia medication usec | 18 (25) | 0 (0) | .01 |
| Family history of premature CVD | 4 (19) | 0 (0) | <.001 |
| Family history of type-2 diabetes | 4 (19) | 13 (18) | .90 |
| HIV duration, median months (range) | 162 (37–310) | ... | |
| Nadir CD4 cell count, median cells/mm3 (range) | 162 (0–868) | ... | |
| Current CD4 cell count, median cells/mm3 (range) | 624 (154–1718) | ... | |
| HIV-1 RNA level <50 copies/mL | 59 (81) | ... | |
| HIV-1 RNA level in subjects with >50 copies/mL,d median cells/mm3 (range) | 292 (68–1606) | ... | |
| Cumulative duration of PI therapy, median months (range) | 53 (0–201) | ... | |
| Cumulative duration of NRTI therapy, median months (range) | 96 (10–219) | ... | |
| Cumulative duration of NNRTI therapy, median months (range) | 17 (0–95) | ... |
NOTE. Data are no. (%) of patients, unless otherwise indicated. BMI, body mass index (calculated as weight in kilograms divided by the square of height in meters); CVD, cardiovascular disease; HDL, high-density lipoprotein; HOMA-IR, homeostasis model assessment of insulin resistance; LDL, low-density lipoprotein; NNRTI, nonnucleoside analogue reverse-transcriptase inhibitor; NRTI, nucleoside analogue reverse-transcriptase inhibitor; PI, protease inhibitor.
Antihypertensives include diuretics, β-blockers, angiotensive-converting inhibitors, angiotensin II receptor blockers, and calcium channel blockers.
Lipid-lowering medications include statins, niacin, bile acid sequestrants, and cholesterol absorption inhibitors.
Hypertriglyceridemia medications includes fish oil and fibrates.
n = 14.
HIV infection characteristics are described in Table 1. The majority of HIV-infected patients (81%) had HIV RNA levels <50 copies/mL, and the remaining patients had a median HIV RNA level of 292 copies/mL.
Between-group comparison of IMT and plasma biomarkers
The carotid IMT and plasma biomarker results are shown in Table 2. Both CCA and ICA IMT measurements were significantly higher in the HIV-infected group. Also, levels of the inflammatory markers TNF-α, hsCRP, IL-6, and myeloperoxidase were significantly higher in the HIV-infected group; whereas sTNFR-I and sTNFR-II levels were similar between groups. Of the endothelial markers, only sVCAM-1 was significantly higher in the HIV-infected group.
Table 2.
Carotid Intima-Media Thickness and Biomarkers in Human Immunodeficiency Virus (HIV)–Infected Patients and Healthy Controls Subjects
| Median value (range) |
|||
|---|---|---|---|
| Measurement | HIV-infected patients (n = 73) | Control subjects (n = 21) | P |
| ICA IMT, mm | 1.35 (0.7–3.88) | 1.10 (0.55–2.98) | .04 |
| CCA IMT, mm | 1.25 (0.75–3.23) | 1.05 (0.75–1.35) | <.001 |
| TNF-α, pg/mL | 4.0 (0.4–364) | 1.8 (0.4–85.6) | .03 |
| sTNFR-I, pg/mL | 702 (161–17, 328) | 618 (265–1365) | .09 |
| sTNFR-II, pg/mL | 518 (100–3073) | 635 (279–1070) | .89 |
| hsCRP, mg/L | 5.43 (0.13–84.6) | 1.53 (0.05–24.4) | <.001 |
| IL-6, pg/mL | 6.0 (0.8–270) | 2.8 (1.0–8.2) | .008 |
| MPO, pg/mL | 7665 (1022–32,439) | 1561 (1124–10,865) | <.001 |
| sICAM-1, ng/mL | 401 (73–2818) | 403 (195–577) | .25 |
| sVCAM-1, ng/mL | 659 (239–17,145) | 454 (66–1808) | .002 |
| vWF, U/mL | 17.0 (2.0–3121) | 11.8 (6.4–200) | .11 |
NOTE. CCA, common carotid artery; hsCRP high sensitivity C-reactive protein; ICA , internal carotid artery; IL, interleukin; IMT, intima-media thickness; MPO, myeloperoxidase; sICAM-1, soluble intercellular adhesion molecule-1; sTNFR-I , soluble tumor necrosis factor–α receptor I; sTNFR-II, soluble tumor necrosis factor–α receptor II; sVCAM-1, soluble vascular cell adhesion molecule-1; TNF-α, tumor necrosis factor–α; vWF, von Willebrand factor.
Given the significantly higher number of smokers in the HIV-infected group, biomarker values for smokers and nonsmokers from both groups were compared and found to be similar (data not shown). Likewise, because some subjects were taking medications that can potentially affect inflammatory markers (ie, aspirin, antihypertensives, and hypolipemics), subjects taking any of these medications were compared with the rest of the subjects. No differences in biomarkers were found between those receiving these medications versus those who were not (data not shown).
Correlations among IMT, plasma biomarkers, and metabolic parameters
Significant correlations between IMT measurements, plasma biomarkers and fasting metabolic parameters are shown in Table 3. Age was the only variable that was positively correlated with both IMT measurements for both groups. In the HIV-infected group, non-HDL cholesterol level was positively correlated with both CCA and ICA IMT, but this was not the case for the control group. Triglyceride levels and HOMA-IR score were both positively correlated with one of the IMT measurements in each group. Of the inflammatory markers, only hsCRP was positively correlated with IMT in both groups (ICA for HIV-infected group and CCA for control group). Endothelial markers were not correlated with IMT in the HIV-infected group, and only sVCAM-1 was negatively correlated with ICA in the control group.
Table 3.
Significant Univariable Correlations between Carotid Intima-Media Thickness and Biomarkers for HIV-Infected Patients and Healthy Control Subjects
| HIV-infected patients (n = 73) |
Control subjects (n = 21) |
|||||||
|---|---|---|---|---|---|---|---|---|
| Marker | CCA IMTa | P | ICA IMTa | P | CCA IMTa | P | ICA IMTa | P |
| Age | 0.54 | .001 | 0.47 | .001 | 0.66 | .001 | 0.53 | .01 |
| Non-HDL cholesterol | 0.27 | .02 | 0.25 | .04 | ... | ... | ||
| Triglycerides | 0.25 | .03 | ... | 0.6 | .004 | ... | ||
| HOMA-IR score | 0.24 | .04 | ... | ... | 0.44 | .05 | ||
| hsCRP | ... | 0.26 | .03 | 0.47 | .03 | ... | ||
| sVCAM-1 | ... | ... | ... | –0.70 | <.001 | |||
NOTE. No significant correlations were found between IMT and biomarkers not listed in the table (ie, TNF-α, sTNFR-I, sTNFR-II, IL-6, MPO, sICAM-1, and vWF), as well as between IMT and TC, HDL, LDL, or BMI. BMI, body mass index (calculated as weight in kilograms divided by the square of height in meters); CCA, common carotid artery; HDL, high-density lipoprotein; HOMA-IR, homeostasis model assessment of insulin resistance; hsCRP, high-sensitivity C-reactive protein; ICA, internal carotid artery; IL, interleukin; IMT, intima-media thickness; LDL, low-density lipoprotein; MPO, myeloperoxidase; sICAM-1, soluble intercellular adhesion molecule-1; sTNFR-I, soluble tumor necrosis factor-α receptor I; sTNFR-II, soluble tumor necrosis factor-α receptor II; sVCAM-1, soluble vascular cell adhesion molecule-1; TC, total cholesterol; TNF-α, tumor necrosis factor-α; vWF, von Willebrand factor.
Spearman correlation coefficient (ρ).
Regression Analysis
Only the HIV-infected group was included in regression analysis (Table 4). For the first stage, age, BMI, sex, lipid-lowering medication use, waist-to-hip ratio, and systolic blood pressure were chosen for the first stage model of clinical characteristics on the basis of the inclusion criteria described in the Methods. Likewise, non-HDL, triglyceride, and total cholesterol levels and HOMA-IR score were included in the laboratory values model, and current and nadir absolute CD4 cell counts, HIV duration, and the 3 main ARV classes (nonnucleoside reverse-transcriptase inhibitors [NNRTI], nucleoside reverse-transcriptase inhibitors [NRTI], protease inhibitors) were included in HIV characteristics. Finally, all bio-markers were included in the first stage.
Table 4.
Variable Selection of Regression Model for Human Immunodeficiency Virus (HlV)–Infected Patients
| ICA |
CCA |
|||||
|---|---|---|---|---|---|---|
| Model stage, variable | β ± SE | P | Adjusted R2 | β ± SE | P | Adjusted R2 |
| First stage | ||||||
| Demographics characteristic | 0.20 | 0.35 | ||||
| Age | 0.02 ± 0.01 | .15 | 0.02 ± <0.01 | .001 | ||
| BMI | –0.02 ± 0.02 | .39 | ±0.01 ± 0.01 | .95 | ||
| Sex | –0.03 ± 0.27 | .93 | –0.04 ± 0.13 | .73 | ||
| lipid-lowering drug use | 0.36 ± 0.19 | .06 | –0.07 ± 0.09 | .49 | ||
| Waist-to-hip ratio | 2.66 ± 1.39 | .06 | 1.75 ± 0.69 | .01 | ||
| Systolic blood pressure | 0.01 ± <0.01 | .11 | ±0.01 ± <0.01 | .23 | ||
| Laboratory value | <0.01 | 0.02 | ||||
| Non-HDL cholesterol | ±0.01 ± <0.01 | .45 | ±0.01 ± <0.01 | .25 | ||
| Triglycerides | ±0.01 ± <0.01 | .37 | ±0.01 ± <0.01 | .62 | ||
| Total cholesterol | ±0.01 ± <0.01 | .99 | ±0.01 ± <0.01 | .45 | ||
| HOMA-IR | 0.01 ± 0.02 | .56 | ±0.01 ± 0.01 | .56 | ||
| HIV infection measurement | 0.05 | <0.01 | ||||
| Absolute CD4 cell count | ±0.01 ± <0.01 | .44 | ±0.01 ± <0.01 | .67 | ||
| Nadir CD4 cell count | ±0.01 ± <0.01 | .86 | ±0.01 ± <0.01 | .78 | ||
| HIV duration | 0.03 ± 0.02 | .25 | ±0.01 ± 0.01 | .70 | ||
| NNRTI receipt duration | ±0.01 ± <0.01 | .05 | ±0.01 ± <0.01 | .19 | ||
| NRTI receipt duration | ±0.01 ± <0.01 | .05 | ±0.01 ± <0.01 | .20 | ||
| PI receipt duration | ±0.01 ± <0.01 | .03 | ±0.01 ± <0.01 | .40 | ||
| Biomarker | 0.10 | 0.03 | ||||
| sVCAM | ±0.01 ± <0.01 | .04 | ±0.01 ± <0.01 | .02 | ||
| MPO | ±0.01 ± <0.01 | .04 | ±0.01 ± <0.01 | .07 | ||
| vWF | ±0.01 ± <0.01 | .02 | ±0.01 ± <0.01 | .08 | ||
| TNF-α | ±0.01 ± <0.01 | .03 | ±0.01 ± <0.01 | .13 | ||
| sTNFR-I | ±0.01 ± <0.01 | .58 | ±0.01 ± <0.01 | .54 | ||
| sTNFR-II | ±0.01 ± <0.01 | .64 | ±0.01 ± <0.01 | .36 | ||
| ICAM-1 | ±0.01 ± <0.01 | .98 | ±0.01 ± <0.01 | .55 | ||
| hsCRP | ±0.01 ± <0.01 | .79 | ±0.01 ± <0.01 | .36 | ||
| IL-6 | ±0.01 ± <0.01 | .25 | ±0.01 ± <0.01 | .21 | ||
| Second stage | 0.23 | 0.40 | ||||
| Age | 0.03 ± 0.01 | .01 | 0.03 ± <0.01 | <.001 | ||
| Waist-to-hip ratio | 1.13 ± 1.31 | .40 | 1.39 ± 0.61 | .03 | ||
| Lipid-lowering drug use | 0.34 ± 0.18 | .07 | –0.07 ± 0.09 | .43 | ||
| NNRTI receipt duration | ±0.01 ± <0.01 | .81 | ... | |||
| NRTI receipt duration | ±0.01 ± <0.01 | .36 | ... | |||
| PI receipt duration | ±0.01 ± <0.01 | .33 | ... | |||
| sVCAM-1 | ±0.01 ± <0.01 | .02 | ±0.01 ± <0.01 | .34 | ||
| MPO | ±0.01 ± <0.01 | .06 | ±0.01 ± <0.01 | .04 | ||
| vWF | ±0.01 ± <0.01 | .27 | ±0.01 ± <0.01 | .22 | ||
| TNF-α | ±0.01 ± <0.01 | .05 | ±0.01 ± <0.01 | .16 | ||
| Final model | 0.27 | 0.38 | ||||
| Age | 0.03 ± <0.01 | <.001 | 0.03 ± <0.01 | <.001 | ||
| Waist-to-hip ratio | ... | 1.53 ± 0.59 | .01 | |||
| Lipid-lowering drug use | 0.30 ± 0.16 | .07 | ... | |||
| sVCAM-1 | ±0.01 ± <0.01 | .02 | ... | |||
| MPO | ±0.01 ± <0.01 | .03 | ... | |||
| TNF-α | ±0.01 ± <0.01 | .03 | ±0.01 ± <0.01 | .11 | ||
NOTE. BMI, body mass index (calculated as weight in kilograms divided by the square of height in meters); CCA, common carotid artery; HDL, high-density lipoprotein; HOMA-IR, homeostasis model assessment of insulin resistance; hsCRP high-sensitivity C-reactive protein; ICA, internal carotid artery; IL, interleukin; IMT, intima-media thickness; MPO, myeloperoxidase; NNRTI, nonnucleoside analogue reverse-transcriptase inhibitor; NRTI, nucleoside analogue reverse-transcriptase inhibitor; PI, protease inhibitor; SE, standard error; sICAM-1, soluble intercellular adhesion molecule-1; sTNFR-I, soluble tumor necrosis factor-α receptor I; sTNFR-II, soluble tumor necrosis factor-α receptor II; sVCAM-1, soluble vascular cell adhesion molecule-1; TNF-α, tumor necrosis factor-α; vWF, von Willebrand factor.
Next, variables within each model that had a probability value of <.1 were included in the second stage of regression analysis. For ICA IMT, variables included age; waist-to-hip ratio; lipid-lowering medication use; duration of NNRTI, NRTI, or protease inhibitor use; and sVCAM-1, myeloperoxidase, vWF, and TNF-α levels. For CCA IMT, variables included age, waist-to-hip ratio, lipid-lowering medication use, and sVCAM-1, myeloperoxidase, vWF, and TNF-α levels. The final model including variables that remained with P < .1, included only age (P < .001) and sVCAM-1 (P p .02), myeloperoxidase (P = .03), and TNF-α (P = .03) levels for ICA. For CCA, the final model included only age (P < .001) and waist-to-hip ratio (P = .02). It should be noted that none of the models explain a high degree of variability in the outcome measures, the highest R2 being 0.40 for the final model for CCA. At the first level, again on the basis of comparative R2 values, the models that include demographic characteristics appear to explain more variability than the other models at this level.
DISCUSSION
With the advent of highly active ART, patients infected with HIV are living decades longer than before. However, increased cardiovascular risk associated with HIV infection presents new challenges and implications for quality of life and life expectancy.
In this study, we examined the relationship between carotid IMT and biomarkers known in the general population to be abnormal in patients with CVD or predictive of CVD-associated events. As presented elsewhere [8, 13, 14], IMT measurements were higher in the HIV-infected group than in the healthy age-matched control group. Likewise, a number of inflammatory and endothelial activation markers were elevated in the HIV-infected group, compared with the control group. These findings are consistent with other studies [14, 35, 38] and underscore the heightened inflammatory state, enhanced endothelial activation, and increased CVD risk among HIV-infected individuals, even those receiving ART.
Not surprisingly, traditional CVD risk factors were positively correlated with IMT in both groups. More interesting is the fact that hsCRP was the only biomarker that was positively correlated with IMT for both groups. hsCRP has been shown consistently to be a predictor of CVD in the general population [19], and a recent study reported a higher hsCRP in HIV-infected subjects who later experience acute myocardial infarction [38]. We also found a strong correlation between sVCAM-1 level and all measured inflammatory markers, corroborating the role of inflammation in the development of endothelial activation and CVD.
In the multiple regression analysis of the HIV-infected subjects, age remained the most significant factor associated with carotid IMT. Importantly, sVCAM-1, myeloperoxidase, and TNF-α levels were also independently associated with IMT, but only ICA IMT. It is not clear why biomarkers would only be associated with ICA and not CCA IMT, because one would expect the development of atherosclerosis in this setting to occur in a diffuse and systemic process. However, similar findings were noted in the Offspring Cohort of the Framingham Study [28], where as a group, inflammatory markers were significantly associated with ICA but not CCA IMT. There are data to suggest that both ICA and CCA are predictive of CVD events in the general population [39]. However, studies that included both measurements in HIV-infected subjects showed increased IMT over control subjects [14, 15], compared with negative studies that only looked at CCA [7, 40], after adjusting for traditional risk factors.
There are limitations to this study. Foremost, some of the IMT increase found in the HIV-infected group may be accounted for by baseline differences between the groups, such as increased smoking rates, blood pressure, waist-to-hip ratio, and HOMA-IR scores and lower HDL, all of which are known to be associated with higher carotid IMT and CVD risk [41–44]. Ideally, this study would have better controlled for these confounders; however, the baseline differences are representative of the HIV-infected population as a whole and have presented challenges in other studies as well [45]. Likewise, the main objective of this study was to evaluate variables, in particular inflammation and endothelial activation, that may account for increased IMT in the HIV-infected population that we are already assuming is at higher risk of CVD. Ultimately, the inclusion of control subjects was a secondary objective to show that even in a small convenience sample of healthy individuals, IMT measures are worse in HIV-infected patients who therefore are likely at a higher risk of CVD. Moreover, it is unclear how much these differences affected the results, because smoking status did not affect biomarker levels, there was no association between smoking and IMT in bivariate analysis, and lipid profiles (except HDL) were similar between groups.
Another limitation is that, because of the relatively small sample size, it was impossible to comment on the contribution of individual antiretrovirals to carotid IMT values. However, it is reassuring that there were no correlations between antiretroviral classes received and carotid IMT or biomarkers, and antiretroviral classes were not associated with IMT in multiple regression analysis. A significantly larger subject number would be necessary to overcome this limitation. Likewise, because of small sample size, we were unable to show group differences in all of the biomarkers, where there might have been a difference with greater power. It should also be noted that the exaggerated inflammatory response observed in HIV-infected patients is likely multifactorial, and this cross-sectional study cannot prove causality, despite the interesting correlations found. However, this study offers some basic observations that can form the substrate for future research.
To our knowledge, this is the first study specifically designed to investigate the relationship between carotid IMT and inflammation and endothelial biomarkers in HIV-infected adults receiving ART. Our results show a heightened inflammatory state with enhanced endothelial activation in HIV-infected subjects, despite virologic suppression. In addition, significant correlations were found between levels of the inflammation markers, the endothelial activation marker sVCAM-1, and carotid IMT, offering a potential mechanism for the increased CVD risk in this population. Larger, better controlled, longitudinal studies are needed to confirm and further define this relationship. Should these studies show a more definitive role of inflammation and endothelial activation in the increased risk of CVD among HIV-infected individuals, biomarker monitoring, initiation of anti-inflammatory medications, or earlier initiation of highly active ART may be beneficial.
Acknowledgments
Financial support. Partial support provided by Bristol-Myers Squibb.
G.A.M. serves as a consultant and has received research funding from Bristol-Myers Squibb, GlaxoSmithKline, Gilead, and Abbott. A.C.R. has received research funding from Bristol-Myers Squibb.
Footnotes
Potential Conflicts of Interest. All other authors: no conflicts.
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