Abstract
Objectives
People living with HIV are exposed to a higher risk of coronary artery disease (CAD) compared to the general population. Epicardial fat may play a unique role in promoting coronary atherosclerosis. We measured epicardial fat in participants living with HIV and controls and investigated its association with coronary plaque volume and low attenuation plaque, a marker of plaque vulnerability.
Design
This is a cross sectional study, nested in the Canadian HIV and Aging Cohort Study, a large prospective cohort actively following participants with HIV and controls. Participants with low/intermediate cardiovascular risk without symptoms/history of CAD were invited to undergo cardiac computed tomography (CT).
Methods
Volume of epicardial fat, coronary plaque and low attenuation component of the plaque were measured. Association between epicardial fat, coronary plaque volume and low attenuation component was tested using adjusted regression analysis.
Results
A total of 169 participants with HIV and 81 controls underwent cardiac CT. Participants with HIV had a greater epicardial fat volume compared to controls (p=0.019). In participants with HIV, epicardial fat volume was positively associated with duration of non-nucleoside reverse transcriptase inhibitors (NNRTI) (β=2.19, p=0.004). After adjustment for cardiovascular risk factors, epicardial fat volume was positively associated to non-calcified plaque volume (OR=1.09, p=0.028) and to the low attenuation plaque component portion (β=0.38, p=0.026).
Conclusion
The association of epicardial fat volume to non-calcified plaque volume and to low attenuation component plaque may suggest a potential mechanism by which epicardial fat could be a silent driver of CAD in the HIV population.
Keywords: Epicardial fat, CT, Plaque, HIV, ART
INTRODUCTION
Cardiovascular disease is one of the most important cause of death in people living with HIV receiving antiretroviral therapy (ART) (1, 2). An increased risk of coronary artery disease (CAD) in this population has been demonstrated in several large cohort studies (3–5). More recently, studies using coronary computed tomography (CT) angiography (CCTA) have allowed non-invasive characterization of coronary atherosclerosis in people living with HIV (6–9). Most studies showed a higher prevalence of non-calcified coronary plaques as well as plaques with CT markers of vulnerability (high-risk plaques) in individuals with HIV compared to controls (6–9). Non-calcified plaques and high-risk plaques have been associated with an increased risk of cardiovascular events (10, 11). Reasons for higher prevalence of high-risk plaques in HIV are still imprecise, although ART (12) and HIV infection itself may be involved.
People living with HIV are known to experience changes in body fat distribution characterized by visceral fat accumulation (13, 14). Epicardial fat is the visceral fat of the heart, and ex vivo and in vivo studies suggest that this adipose tissue depot may play a unique role in CAD due to its proximity to the coronary arteries. Epicardial fat secretes active mediators in direct vicinity to the coronary arteries that are known to promote inflammation and atherosclerosis (15–18). Recent studies have shown an association between epicardial fat and the presence and progression of coronary artery disease in the general population (19–22). In people living with HIV, studies have demonstrated an association between epicardial fat and coronary artery calcium score, non-calcified plaques and adverse cardiovascular events (23–25).
In the present study, we measured epicardial fat in participants living with HIV and controls from a large prospective multicentric cohort, using CCTA. We investigated its association with coronary artery plaque burden, and, more specifically, with coronary plaque volume and low attenuation plaque, a marker of plaque vulnerability. We hypothesized that the volume of epicardial fat will be increased in individuals living with HIV and that it will be associated to coronary artery plaque volume and low attenuation plaque.
METHODS
Study design
This is a cross sectional study nested in the Canadian HIV and Aging Cohort Study (CHACS), an ongoing, multicenter, controlled prospective cohort study following 1000 participants living with HIV and 200 controls in 10 Canadian centers. The full study protocol of CHACS has been described previously (26).
CHACS recruitment is hospital-based as well as community-based, for both individuals with HIV and controls. Participants living with HIV aged 40 years or older, or who have lived with HIV for 15 years or more, were recruited from the HIV clinics of the participating centers from 2012 to 2018. Controls were also aged 40 years or older. They were selected from an outpatient internal medicine clinic, or from the general population.
Study population
Consecutive participants living with HIV and controls with low to intermediate cardiovascular risk (10-year Framingham risk score 5 – 20 %) and without symptoms or history of CAD were prospectively invited to undergo non-contrast cardiac CT and coronary CT angiography. Exclusion criteria included creatinine clearance of < 50 ml/min and history of contrast media allergy.
Data collection
CHACS participants are followed yearly. At each study visit, participants have a complete medical history and physical examination and have a panel of blood tests. Data from the visit closest to the cardiac CT date were obtained (generally within 6–8 months of the scan) including demographics, CAD risk factors and measures of the activity of HIV disease.
Cardiac CT imaging
A 256-slice CT scanner (Brilliance iCT, Philips Healthcare, Best, The Netherlands) was used to perform non-contrast cardiac CT and CCTA.
The following parameters were used for non-contrast CT: slice thickness 2.5 mm, matrix 512 × 512, field-of-view 250 mm, scan voltage 120 kV and prospective electrocardiographic (ECG) -gating. Patients were given 50–75 mg of metoprolol orally 45–60 minutes prior to CCTA if heart rate was > 60 beats per minute (bpm), and 0.4 mg of nitroglycerin sublingually, in absence of contraindications. For coronary CCTA, contrast agent was injected at a flow rate of 5ml/sec, using 370 mg/mL of iopamidol (Bracco Imaging, Milan, Italy). Images were reconstructed using a hybrid iterative reconstruction algorithm (Philips iDose, Philips Healthcare, level 3).
Exposure of interest: Epicardial fat volume
Epicardial fat volume (cm³) was quantified using non-contrast cardiac CT images. Epicardial fat was defined as the adipose tissue between the myocardium and the visceral pericardium. Volume was measured by tracing manually the pericardium every two to three slices on axial images from the pulmonary artery bifurcation to the apex of the heart, using a semi-automated software (Aquarius Intuition version 4.4.11, TeraRecon Headquarters, Forster City, CA, USA). CT attenuation thresholds between −190 and −30 Hounsfield units (HU) were used to select the epicardial fat and exclude any other tissue. The epicardial fat volumes measured at each level were then summed to obtain the total epicardial fat volume (Figure 1 – Supplemental data). Inter-observer and intra-observer agreement for epicardial fat volume measurement was highly reproducible (intraclass correlation coefficient for inter-observer agreement = 0.75 and for intra-observer agreement= 0.97). Image assessors for epicardial fat and coronary plaque were blinded to HIV status and clinical data.
Outcome of interest: Coronary plaque volume.
Coronary plaque analysis was performed using CCTA images as previously described in Chen et al (27). The coronary segments were defined as reported in the American College of Cardiology / American Heart Association guidelines for coronary angiography (28). Plaques were identified and defined as calcified, non-calcified or mixed. Plaque volumetric analysis was performed in multiplanar reformat (MPR), using the aforementioned semi-automated software. First, proximal and distal plaque boundaries were traced by manual segmentation. Then, the software allowed for semiautomatic delimitations between lumen, vessel wall and plaque followed by manual adjustment. Plaque composition was assessed using attenuation-stratified measurements in the plaque volume: ≤30 HU, 31–50 HU, 51–100 HU, 101–150 HU, 151–350 HU and >350 HU.
Total plaque volume per participant was defined as the sum of aforementioned attenuation-stratified measurements. Calcified, non-calcified and mixed plaque volumes per participant were defined as the sum of volumes of calcified, non-calcified and mixed plaques per participant.
Low-attenuation plaque component was defined as ≤30 HU measurements. Low attenuation plaque component portion per participant was determined as the ratio of low attenuation plaque volume and total plaque volume, in each participant with presence of plaque.
Covariates and effect modifiers
Confounders were defined using clinical reasoning as variables likely to be associated with epicardial fat and coronary atherosclerosis. This included traditional cardiovascular risk factors (age, sex, diabetes, high blood pressure, smoking, cholesterol level and statin use), as well as body mass index (BMI). We also assessed effect modification by HIV status.
Statistical analysis
Continuous data are presented as mean ± standard deviation or median [25th–75th interquartile range (IQR)], as appropriate. Categorical data are presented as numbers and percentages. Differences between participants living with HIV and controls were analysed using Student’s T-test or Mann-Whitney U-test for normally and non-normally distributed continuous variables, and chi-squared test for categorical variables, respectively.
Linear regression analyses were performed to evaluate the associations between cardiovascular risk factors, HIV-related parameters and epicardial fat volume in participants living with HIV. The association between ART exposition duration and epicardial fat volume was first assessed altogether, and then specific ART classes were assessed in a separate model to avoid collinearity.
The association of epicardial fat volume and plaque volume variables (total, calcified, non calcified and mixed) was assessed using zero-inflated Poisson regression. This statistical model is used for continuous distributions with a high prevalence of “zero” and no overdispersion. It performs both logistic regression to examine factors associated to plaque presence and Poisson regression to evaluate factors associated with plaque volume, each with two separate p values, and has been used previously to analyse plaque volume (29). Coronary plaque volume variables were natural-log transformed prior to statistical analysis.
Association of epicardial fat volume with low attenuation plaque component portion was assessed using linear regression analyses.
All multivariate analyses were performed with adjustment for HIV serostatus, cardiovascular risk factors and BMI, which were included if they showed a univariate association with the outcome with a p-value ≤ 0.1. Effect modification by HIV of each association was assessed by inclusion of an interaction term to the fully adjusted models.
For patients with incomplete continuous covariable data, the mean or median value was used to impute the missing data. Values for the following number of participants were missing and imputed: BMI (5), smoking exposure (14), HDL-cholesterol (4), LDL-cholesterol (9), ART exposition duration (7), non-nucleoside reverse transcriptase inhibitors exposition duration (7). A p-value < 0.05 was considered statistically significant. Statistical analyses were performed using R (version 3.3.2; R Foundation for Statistical Computing, Vienna, Austria).
Ethics
This study was approved by the Institutional Review Board of the Medical Center of the University of Montreal (CHUM) and participating centers. All participants gave written informed consent.
RESULTS
Clinical characteristics of participants
A total of 250 consecutive participants were included in the present study. 169 (67.6 %) participants were living with HIV, and 81 (32.4 %) were controls. Figure 2 (Supplemental data) shows the flow chart of participants. Participant’s characteristics stratified by HIV status are described in Table 1. Participants with HIV had a mean age of 55.6 ± 7.0 years while controls had a mean age of 56.6 ± 7.9 years (p=0.323). Of participants with HIV, 92.3 % were male while 79.0 % of controls were male (p=0.005).
Table 1.
Demographic and clinical characteristics of participants, N = 250
| Variables | HIV+ = 169 | HIV− = 81 | P-Value |
|---|---|---|---|
| Age (Years) | 55.6 ± 7.0 | 56.6 ± 7.9 | 0.323 |
| Male sex, n (%) | 156 (92.3 %) | 64 (79.0 %) | 0.005 |
| Race, n (%) | 0.143 | ||
| Asian | 3 (1.8 %) | 0 (0 %) | |
| Black | 15 (8.9 %) | 2 (2.5 %) | |
| Caucasian | 141 (83.4 %) | 76 (93.8 %) | |
| Hispanic | 9 (5.3 %) | 3 (3.7 %) | |
| 10 Year Framingham risk score (%) | 10 [7 – 15] | 10[7 – 15] | 0.617 |
| Diabetes, n (%) | 18 (10.6 %) | 2 (2.5 %) | 0.047 |
| High blood pressure, n (%) | 53 (31.4 %) | 20 (24.7 %) | 0.349 |
| Family history of premature CVD, n (%) | 35 (20.7 %) | 17 (21.0 %) | 1 |
| Smoking status, n (%) | 0.001 | ||
| Current | 53 (31.4 %) | 9 (11.1 %) | |
| Ex | 62 (36.7 %) | 34 (42.0 %) | |
| Never | 51 (30.2 %) | 37 (47.7 %) | |
| Smoking exposure (pack/year) | 6 [0 – 25.9] | 0.1 [0 – 7.9] | <0.001 |
| Total-Cholesterol (mmol/L) | 4.9 ± 1.1 | 5.2 ± 1.0 | 0.011 |
| HDL-Cholesterol (mmol/L) | 1.3 ± 0.4 | 1.4 ± 0.4 | 0.002 |
| LDL-Cholesterol (mmol/L) | 2.8 ± 0.9 | 3.2 ± 0.9 | 0.002 |
| Statin, n (%) | 52 (30.8 %) | 15 (18.5 %) | 0.058 |
| BMI (kg/m2) | 25.3 ± 4.1 | 27.1 ± 4.5 | 0.003 |
| Waist circumference (cm) | 95.0 ± 11.6 | 95.5 ±11.1 | 0.751 |
| HIV specific variables | HIV+= 169 | - | - |
| HIV infection duration (years) | 18.3 ± 7.7 | - | - |
| Participants exposed to ART, n (%) | 159 (94.1 %) | - | - |
| ART exposition duration (Years)1 | 13.5 ± 6.5 | - | - |
| Participants exposed to PIs, n (%) | 128 (75.7 %) | - | - |
| Ritonavir, n (%) | 114 (67.4 %) | ||
| Lopinavir, n (%) | 67 (39.6 %) | ||
| Atazanavir, n (%) | 66 (39.0 %) | ||
| Darunavir, n (%) | 55 (32.5 %) | ||
| Indinavir, n (%) | 49 (30.0 %) | ||
| PIs exposition duration (years)1 | 9.5 ± 5.1 | - | - |
| Participants exposed to NRTIs, n (%) | 159 (94.1 %) | - | - |
| Lamivudine | 136 (80.5 %) | ||
| Tenofovir | 125 (74.0 %) | ||
| Emtricitabine | 116 (68.6 %) | ||
| Abacavir | 105 (62.1 %) | ||
| Zidovudine | 104 (61.5 %) | ||
| Stavudine | 71 (42.0 %) | ||
| NRTIs exposition duration (years)1 | 12.4 ± 6.1 | - | - |
| Participants exposed to NNRTIs, n (%) | 107 (63.3 %) | - | - |
| Efavirenz | 74 (43.8 %) | ||
| Nevirapine | 30 (17.7 %) | ||
| Rilpivirine | 18 (10.6 %) | ||
| Etravirine | 15 (8.9 %) | ||
| Delavirdine | 9 (5.3 %) | ||
| NNRTIs exposition duration (years)1 | 4.4 [1.9 – 7.5] | - | - |
| Participants exposed to INSTIs, n (%) | 78 (46.1 %) | - | - |
| Raltegravir | 55 (32.5 %) | ||
| Dolutegravir | 34 (20.1 %) | ||
| Elvitegravir | 9 (5.3 %) | ||
| INSTIs exposition duration (years)1 | 1.9 [1.0 – 4.2] | - | - |
| Undetectable viral load2, n (%) | 148 (87.6 %) | - | - |
| Viral load among detectable | 632 [69.2 – 25981.2] | - | - |
| Nadir CD4 cell count (cells/mm³) | 200 [100 – 297] | - | - |
| Current CD4 cell count (cells/mm³) | 585 [414 – 786.8] | - | - |
| Current CD8 cell count (cells/mm³) | 760 [570 – 1026] |
CVD : cardiovascular disease, BMI : body mass index, ART : antiretroviral therapy, NRTIs : Nucleoside reverse transcriptase inhibitors, NNRTIs : Non-nucleoside reverse transcriptase inhibitors, PIs : Protease inhibitors, INSTI : Integrase strand transfer inhibitors
In patients exposed to therapy
Defined as viral load =<40 copies/mL
Normally distributed variables are expressed as mean ± standard deviation, non-normally distributed variables are expressed as median [Q1 – Q3], categorical variables are expressed using proportion (percentage). P-values are unadjusted
There was no significant difference in 10-year Framingham risk score between participants living with HIV and controls (median 10[7 – 15] % in participants living with HIV and 10[7 – 15] % in controls, p=0.617). Participants with HIV were more exposed to smoking than controls (6[0 – 25.9] in participants with HIV vs 0.1[0 – 7.9] pack-years in controls, p<0.001). Participants living with HIV had lower total cholesterol, HDL and LDL cholesterol (all p<0.05), and a higher statin exposure (30.8 % vs 18.5 %, p=0.058). Participants living with HIV had lower BMI than controls (25.3 ± 4.1 kg/m2 vs 27.1 ± 4.5 kg/m2 respectively, p=0.003).
At time of enrollment, 94.1 % of the participants living with HIV had initiated ART with a mean duration of 13.5 ± 6.5 years. Viral load was undetectable (< 40 copies/mL) in 87.6%. The median [IQR] CD4+ T-cell count was 585[414 – 786.8] cells/mm3 and the median nadir CD4+ T-cell count was 200[100 – 297] cells/mm3.
Cardiac CT results
Cardiac CT results stratified by HIV status are presented in Table 2. All participants had a non-contrast cardiac CT. Of these, 226 (90.4 %) participants (149 participants living with HIV and 77 controls) underwent CCTA. Twenty-four did not have CCTA for the following reasons: 4 had a history of contrast allergy, 10 had altered renal function, and 10 refused CCTA. Epicardial fat volume was significantly increased in participants living with HIV (134.2 ± 49.4) compared to controls (118.6 ± 48.6) (p=0.019). This difference remained significant even after adjustment for sex, BMI, smoking exposure in pack/year and statin use (p=0.001). No difference in coronary calcium score was observed between individuals living with HIV and controls (14.5[0 – 126.0] and 8.3[0 – 70.5] respectively, p=0.279). Among participants who underwent CCTA, prevalence of non-calcified and mixed plaque was significantly higher in participants living with HIV compared to controls (20.8 % in participants with HIV vs 7.8 % in controls, p=0.028 for non calcified plaque and 47 % in participants with HIV vs 28.9 % in controls, p=0.038 for mixed plaques). However, no difference was observed when comparing total plaque volume and subtypes plaque volume as well as low attenuation plaque percentage among participants with plaques.
Table 2.
Cardiac CT results
| Non contrast cardiac CT (N=250) | HIV+ = 169 | HIV− = 81 | P-value |
|---|---|---|---|
| Epicardial fat volume (cm³) | 134.2 ± 49.4 | 118.6 ± 48.6 | 0.019 |
| Coronary artery calcium score | 14.5 [0 – 126.0] | 8.3 [0 – 70.5] | 0.279 |
| Coronary CT angiography (N=226) | HIV+= 149 | HIV−= 77 | P-value |
| Total plaque prevalence, n (%) | 98 (65.8 %) | 41 (53.2 %) | 0.284 |
| Total plaque volume (mm³)1 | 220.4 [78.2 – 511.2] | 154 [69.6 – 370] | 0.414 |
| Calcified plaque prevalence, n (%) | 61 (40.9 %) | 32(41.6 %) | 0.817 |
| Calcified plaque volume (mm³)1 | 98.4 [50.7 – 223.1] | 111.1 [53.4 – 256.7] | 0.437 |
| Non calcified plaque prevalence, n (%) | 31 (20.8 %) | 6 (7.8 %) | 0.028 |
| Non calcified plaque volume (mm³)1 | 94.4 [31.6 – 155.9] | 31 [15.0 – 90.9] | 0.096 |
| Mixed plaque prevalence, n (%) | 70 (47 %) | 23 (28.9 %) | 0.035 |
| Mixed plaque volume (mm³)1 | 137.5 [75.7 – 341.1] | 120 [67.1 – 286] | 0.497 |
| Low attenuation plaque component portion among participants with plaque (%) (n=139) | 27.4 ± 8.4 | 27.0 ± 10.9 | 0.850 |
CT : computed tomography
In patients with plaque present
Normally distributed variables are expressed as mean ± standard deviation, non-normally distributed variables are expressed as median [Q1 – Q3], categorical variables are expressed using proportion (percentage). P-values are unadjusted.
Predictors of epicardial fat volume in HIV-infected participants
Table 3 shows the cardiovascular risk factors and HIV specific parameters associated with epicardial fat volume in the participants living with HIV. In the non-adjusted regression analysis, epicardial fat volume was positively associated with diabetes (β=38.45, p=0.002), smoking exposure (β=0.40 per additional pack year, p=0.041), statin use (β=9.20, p< 0.001), BMI (β=5.66, p<0.001) and non-nucleoside reverse transcriptase inhibitors (NNRTI) exposure duration (β=2.73 per additional year of exposure, p=0.002). In addition, there was a trend to a positive association between epicardial fat volume and high blood pressure (β=14.72, p=0.072) and ART exposition duration (β=1.01 per additional year of exposure, p=0.083).
Table 3.
Association of epicardial fat volume with cardiovascular risk factors and HIV specific parameters in participants living with HIV (N=169)
| Univariate analysis | Multivariate analysis1 | Multivariate analysis2 | ||||
|---|---|---|---|---|---|---|
| Beta* (95 % CI) | P-value | Beta* (95 % CI) | P-value | Beta* (95 % CI) | P-value | |
| Age (per 1 year increase) | 0.46 (−0.62 – 1.55) | 0.397 | - | - | - | - |
| Male sex | 0.24 (−28.00 – 28.49) | 0.986 | - | - | - | - |
| Diabetes | 38.45 (14.76 – 62.13) | 0.002 | 14.11 (−7.06 – 35.29) | 0.190 | 18.80 (−2.18 – 39.78) | 0.079 |
| High blood pressure | 14.72 (−1.35 – 30.78) | 0.072 | 3.02 (−11.29 – 17.34) | 0.677 | 4.21 (−9.67 – 18.09) | 0.550 |
| Smoking exposure (per 1 pack/year increase) | 0.40 (0.02 – 0.78) | 0.041 | 0.34 (0.01 – 0.67) | 0.044 | 0.37 (0.05 – 0.70) | 0.024 |
| LDL-Chol (per 1 mmol/L increase) | −8.85 (−17.43 – −0.28) | 0.043 | −4.25 (−11.80 – 3.31) | 0.268 | −4.06 (−11.53 – 3.41) | 0.285 |
| HDL-Chol (per 1 mmol/L increase) | −22.73 (−43.56 – −1.91) | 0.033 | −14.89 (−33.10 – 3.30) | 0.108 | −16.77 (−34.65 – 1.10) | 0.066 |
| Statin use | 29.20 (13.51 – 44.89) | <0.001 | 17.77 (3.44 – 32.10) | 0.015 | 14.29 (−0.16 – 28.73) | 0.052 |
| BMI (per 1 kg/m² increase) | 5.66 (4.03 – 7.30) | <0.001 | 5.35 (3.71 – 7.00) | <0.001 | 4.86 (3.29 – 6.43) | <0.001 |
| HIV infection duration (per 1 year increase) | 0.27 (−0.70 – 1.25) | 0.579 | - | - | - | - |
| ART exposition duration (per 1 year increase) | 1.01 (−0.14 – 2.17) | 0.083 | 1.17 (0.14 – 2.20) | 0.026 | - | - |
| NNRTI exposition duration (per 1 year increase) | 2.73 (1.00 – 4.47) | 0.002 | - | - | 2.19 (0.70 – 3.68) | 0.004 |
| NRTI exposition duration (per 1 year increase) | 0.74 (−0.48 – 1.97) | 0.231 | - | - | - | - |
| PI exposition duration (per 1 year increase) | −0.59 (−1.89 – 0.70) | 0.367 | - | - | - | - |
| INSTI exposition duration (per 1 year increase) | 0.15 (−3.68 – 3.98) | 0.939 | - | - | - | - |
| Nadir CD4 count (per 100 cells/mm³) | 2.96 (−2.33 – 8.24) | 0.271 | - | - | - | - |
| Current CD4 count (per 100 cells/mm³) | 0.90 (−1.54 – 3.34) | 0.468 | - | - | - | - |
| Current CD8 count (per 100 cells/mm³) | 0.30 (−1.60 – 2.20) | 0.752 | - | - | - | - |
| Detectable viral load** | −37.42 (−64.38 – −10.46) | 0.007 | −16.15(−39.58 – 7.28) | 0.175 | −18.78 (−41.57 – 4.01) | 0.105 |
BMI: body mass index, ART: antiretroviral therapy, NRTI : Nucleoside reverse transcriptase inhibitors, NNRTI: Non-nucleoside reverse transcriptase inhibitors, PI : Protease inhibitors, INSTI : Integrase strand transfer inhibitors
Beta can be interpreted as the mean increase in epicardial fat volume (in cm3) predicted by the model per each one unit change in the explanatory variable. A negative beta coefficient indicates a decrease.
Defined as viral load > 40 copies/mL (0: No detectable viral load, 1: Detectable viral load)
Multivariate analyses included cardiovascular risk factors and HIV-related parameters if they showed an association with the outcome in the univariable model with a p-value ≤ 0.1
Adjusted for cardiovascular risk factors including diabetes, high blood pressure, smoking, LDL-cholesterol, HDL-cholesterol, statin use, BMI, ART exposition duration and undetectable viral load
Adjusted for cardiovascular risk factors including diabetes, high blood pressure, smoking, LDL-cholesterol, HDL-cholesterol, statin, BMI, NNRTI exposition duration and undetectable viral load
There were inverse association with levels of LDL-cholesterol (β=−8.85 per increase of 1 mmol/L, p=0.043) and HDL-cholesterol (β=−22.73 per increase of 1 mmol/L, p=0.033), and with detectable viral load (β=−37.42, p=0.007).
In multivariate models, only smoking exposure (β=0.34, p=0.044), statin use (β=17.77, p=0.015), BMI (β=5.35, p < 0.001), ART exposure duration (β=1.17, p=0.026) and more specifically NNRTI exposure duration (β=2.19, p=0.004) remained significantly associated with epicardial fat volume.
Epicardial fat volume and coronary plaque
Non adjusted and adjusted associations of epicardial fat volume and coronary plaque including total volume of plaques and volume of calcified, non-calcified and mixed plaque subtypes are presented in Table 4. After adjustment for HIV status, BMI and traditional cardiovascular risk factors, there was no significant association between epicardial fat volume and total plaque volume (OR for logistic regression =0.97 (0.90 – 1.05) per 10 cm³ increase in epicardial fat, p=0.496 and OR for Poisson regression = 1.01 (0.99 – 1.02) per 10 cm³ increase in epicardial fat, p=0.494). However, after stratification of plaque volume according to plaque subtypes, a significant association between epicardial fat volume and non-calcified plaque volume was observed (OR for logistic regression =1.09 (1.01 – 1.18) per 10 cm³ increase in epicardial fat, p=0.028 and OR for Poisson regression =0.99 (0.95 – 1.03) per 10 cm³ increase in epicardial fat, p=0.696) while no association was observed with calcified or mixed plaque volumes. There was no evidence of interaction by HIV status in these analyses.
Table 4.
Association of epicardial fat volume with total coronary plaque and specific subtypes of plaque, using coronary CT angiography, N=226
| All participants with coronary CT angiography, N= 226* | ||||||
|---|---|---|---|---|---|---|
| Univariate analysis | Multivariate analysis | |||||
| Regression | Estimate (95 % IC) | P-value | Regression | Estimate (95 % IC) | P-value | |
| Total plaque volume1 (per 10 cm³ increase) V=0 : 77 V>0 : 139 |
Logistic | 1.02 (0.96 – 1.07) | 0.553 | Logistic | 0.97 (0.90–1.05) | 0.496 |
| Poisson | 1.01 (1.00–1.03) | 0.087 | Poisson | 1.01 (0.99–1.02) | 0.494 | |
| Non-calcified plaque volume2 (per 10 cm³ increase) V=0 : 178 V>0 : 37 |
Logistic | 1.07 (1.00–1.13) | 0.061 | Logistic | 1.09 (1.01 – 1.18) | 0.028 |
| Poisson | 1.00 (0.97 – 1.03) | 0.949 | Poisson | 0.99 (0.95 – 1.03) | 0.696 | |
| Calcified plaque volume3 (per 10 cm³ increase) V=0 : 122 V>0 : 93 |
Logistic | 1.01(0.95 – 1.06) | 0.821 | Logistic | 0.93 (0.85–1.00) | 0.060 |
| Poisson | 1.01 (0.99 – 1.03) | 0.222 | Poisson | 1.00 (0.98–1.03) | 0.753 | |
| Mixed plaque volume4 (per 10 cm³ increase) V=0 : 122 V>0 : 93 |
Logistic | 1.03 (0.97–1.08) | 0.348 | Logistic | 0.99 (0.99–1.03) | 0.292 |
| Poisson | 1.01 (0.99–1.01) | 0.265 | Poisson | 1.00 (0.89–1.01) | 0.279 | |
226 participants with plaque volume and epicardial fat volume assessment with CT; plaque volume measurements were missing in 10 of these participants.
V=0 : Plaque volume = 0 mm3 (cubic millimeters), with number of participants with plaque volume of zero; V> 0 : Plaque volume > 0 mm³, with number of participants with plaque volume more than zero mm³
Multivariate analyses were adjusted for HIV status and BMI. Adjustment also included cardiovascular risk factors when these showed an association with the outcome in the univariable model with a p-value ≤ 0.1
Adjusted for HIV status, BMI, age, smoking exposure and statin use
Adjusted for HIV status, BMI and statin use
Adjusted for HIV status, BMI, age, smoking exposure, LDL cholesterol and statin use
Adjusted for HIV status, BMI, age, smoking exposure and statin use
Table 5 presents linear regression analysis assessing the relationship between epicardial fat volume and low attenuation coronary plaque component portion among 139 participants with at least one plaque (98 participants living with HIV and 41 controls). In univariate regression analysis, epicardial fat volume (β=0.62 per 10 cm³ increase, p<0.001), HDL-cholesterol (β=−4.99, p=0.038), statin use (β=3.84, p=0.020) and BMI (β=0.53, p=0.001) were all associated with low attenuation coronary plaque. After multivariate analysis, only epicardial fat volume remained significantly associated to low attenuation plaque component portion (β=0.38 per 10 cm³ increase in epicardial fat, p=0.026). There was no evidence of interaction by HIV status in these analyses.
Table 5.
. Association of epicardial fat volume with low attenuation coronary plaque component portion in participants with at least one plaque, N=139 (98 HIV+ and 41 HIV−)
| All participants, N= 139 | ||||
|---|---|---|---|---|
| Univariate analysis | Multivariate analysis | |||
| Beta (95 % CI) | P-value | Beta (95 % CI) | P-value | |
| Epicardial fat volume (per 10 cm³ increase) | 0.62 (0.36 – 0.89) | <0.001 | 0.38 (0.05 – 0.72) | 0.026 |
| Age (per 1 year increase) | −0.06 (−0.26 – 0.14) | 0.549 | - | - |
| Sex (men vs women) | 0.52 (−4.30 – 5.34) | 0.832 | - | - |
| HIV (no vs yes) | 0.36 (−3.01 – 3.73) | 0.834 | −0.62 (−4.08 – 2.84) | 0.724 |
| Diabetes (no vs yes) | 5.38 (−0.02 – 10.78) | 0.051 | 2.64 (−2.76 – 8.04) | 0.336 |
| High blood pressure (no vs yes) | 1.46 (−1.81 – 4.74) | 0.379 | - | - |
| Smoking exposure (per 1 pack/year increase) | 0.02 (−0.06 – 0.10) | 0.677 | - | - |
| LDL-Cholesterol (per 1 mmol/L increase) | −1.31 (−2.90 – 0.28) | 0.106 | - | - |
| HDL-Cholesterol (per 1 mmol/L increase) | −4.99 (−9.70 – −0.28) | 0.038 | −3.14 (−7.88 – 1.59) | 0.191 |
| Statin use (no vs yes) | 3.84 (0.62 – 7.06) | 0.020 | 2.41 (−0.87 – 5.68) | 0.149 |
| BMI (per 1 kg/m² increase) | 0.53 (0.21 – 0.86) | 0.001 | 0.25 (−0.12 – 0.63) | 0.187 |
BMI : body mass index
Multivariate analyses included cardiovascular risk factors if they showed an association with the outcome in the univariable model with a p-value ≤ 0.1
Beta can be interpreted as the mean increase in low attenuation plaque component portion (in %) predicted by the model per each one unit change in the explanatory variable. A negative beta coefficient indicates a decrease.
DISCUSSION
Our study involves 250 consecutive participants living with HIV and non-infected controls that underwent prospective CT assessment of epicardial fat volume and subclinical coronary plaque burden, nested in a prospective multicentric cohort. All participants were well-characterized, asymptomatic and with mild to moderate cardiovascular calculated risk. We found that epicardial fat volume was significantly increased in participants living with HIV compared to controls. Among participants with HIV, duration of exposure to ART, especially NNRTI, was associated with increased epicardial fat, whereas no association was found with other markers of HIV infection. Finally, we showed that epicardial fat volume is associated to non-calcified coronary plaque volume and low attenuation plaque component portion, which is a marker of plaque vulnerability, independently of traditional cardiovascular risk factors.
People living with HIV experience changes in body fat distribution, known as lipodystrophy, characterized by greater visceral fat and/or less subcutaneous fat (13, 14, 30). Studies that compared epicardial fat volume in people living with HIV and non-infected controls have shown mixed results. Studies described epicardial fat volume as increased among HIV-infected participants (25, 31–33), whereas such a difference has not been demonstrated by others (34–36). Differences in study samples and populations may explain these results. Of note, the three studies showing no inter-group difference had smaller samples than our study (34–36). In our study, we prospectively included 250 male and female participants living with HIV and controls with similar cardiovascular risk and demonstrated an increased epicardial fat volume in the HIV group and this remained even after adjusting for confounding factors. This finding supports the hypothesis that individuals living with HIV exposed to long-term ART may present unique characteristics beyond traditional risk factors that contribute to ectopic fat accumulation through specific pathways. These pathways may involve the virus itself and its consequences such as the chronic systemic inflammation and immune activation and/or ART.
Since the introduction of highly active ART, several studies have shown that drugs used in these regimens favor the development of metabolic changes including dyslipidemia (37), glucose level impairment (38) and body fat changes (13). Despite improvement of newer generations of therapeutic agents, these complications still exist (39). In our study, we found a positive association between epicardial fat volume and exposure to ART, and more specifically to NNRTIs. While there have been reports of increased epicardial fat with exposure to NRTIs (25, 34, 40), and PIs (41), this finding related to NNRTIs is novel. It should be noted however that combinations of ARTs were used in our participants and therefore we cannot exclude that the increase of epicardial fat associated to NNRTI may result from a combination effect of NNRTI with other classes, in particular the NRTIs. In addition, most of our participants living with HIV were on ART, and ART duration is correlated to HIV infection duration. HIV infection itself may cause an alteration in the distribution of fat that could be due to direct viral effect, and other underlying immune processes (13, 14, 42). Therefore, we are not able to distinguish the effects of HIV-infection from ART in our analyses.
Finally, we found that epicardial fat volume is associated to specific CT features of coronary artery plaque. It has been previously shown that epicardial fat in individuals living with HIV correlates to coronary calcium score (40), plaque prevalence (25) and to an increased risk of adverse cardiovascular events (23). Using CCTA, Brener et al. and Srinivasa et al. showed that epicardial fat volume is associated to non-calcified coronary plaques in HIV patients (25, 34). Our study adds to the current knowledge by demonstrating an independent relationship between epicardial fat volume and non-calcified plaque volume. Furthermore, we present novel data in a study that includes people living with HIV showing an association between low attenuation plaque, a marker of plaque vulnerability, and epicardial fat volume that appears to be independent of other factors known to be associated to coronary atherosclerosis. CT features, such as low attenuation plaque have been proven to be associated to an increased risk of acute coronary syndromes [10, 11, 43]. This finding is of particular interest, since studies using CCTA showed that patients living with HIV harbor more high-risk plaque features (7, 8). Epicardial fat that envelops the coronary arteries may exert changes in the artery wall via secretion of cytokines that promotes inflammation and vulnerable atherosclerotic depots [17, 18, 44]. We may thus hypothesize that epicardial fat could be a driver of increased plaque vulnerability in HIV. Furthermore, we could hypothesize that epicardial fat imaging using CT could eventually be used as a screening tool for high-risk plaque, although this will need further studies with a methodology specifically designed to address this question.
Strengths of our study are worth being noted: we studied a group of individuals living with HIV and controls, men and women. Our data demonstrates for the first time that epicardial fat, volumetrically assessed with cardiac CT, is related to a high-risk plaque feature. We measured epicardial fat on non-contrast cardiac CT images obtained generally for the purpose of measuring coronary calcium score, requiring no supplemental radiation exposure for the evaluation of epicardial fat. In addition, we measured the full epicardial fat volume, which is a more reproducible and superior measure than epicardial fat thickness.
Our study has some limitations. This was a cross-sectional analysis and as such, no cause and effect can be inferred from the associations found. Additionally, as a small group of participants had calcified, non-calcified or mixed plaques, the analyses on plaque sub-types may have lacked statistical power. This was also true for antiretroviral therapy, where a small group of participants were in each sub-class of ART. Some of our participants were on integrase inhibitors (INSTI), and notably, there is mounting evidence that this class is associated with more weight gain [45, 46]. Future studies should investigate the association of INSTI with epicardial fat.
Our study was conducted in participants who were predominantly male. It remains unknown whether these findings can be generalized to women. Finally, the exclusion of participants with renal failure could have underestimated CAD. While this does not bias our results, it limits their generalizability to populations with renal failure.
In conclusion, our study demonstrates that epicardial fat volume is increased in individuals living with HIV. It is associated to ART exposure duration, especially NNRTIs, to non-calcified coronary plaque volume, as well as to the low attenuation component of the plaque, a known marker of plaque vulnerability. These results suggest a potential pathway by which epicardial fat could be a silent driver of subclinical coronary artery disease in the HIV population. These data may steer future studies to investigate further the increased cardiovascular risk in people living with HIV.
Supplementary Material
AKNOWLEDGEMENTS.
We would like to thank all the staff and participants for their contribution in the actual study including: Stéphanie Matte, Annie Chamberland and Nathalie Bellavance.
Source of Funding:
This work was supported by:
Canadian Institutes of Health Research (HIV Clinical Trial Network – CTN 272, TCO-125276, HAL-157985)
National Institutes of Health R01 AG054324-01
Fonds de Recherche Québec - Santé (FRQS), Sida et Maladies infectieuses network
FRQS and Fondation de l’Association des radiologistes du Québec
FRQS, Bio-imagerie du Québec network
Programme de support professoral, Département de radiologie, radio-oncologie et médecine nucléaire, Université de Montréal
Footnotes
Conflicts of Interest: None
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