Coronary artery endothelial function and aging in people with HIV and HIV-negative individuals

Abstract

Coronary artery disease (CAD) is a common comorbidity in people with human immunodeficiency virus (HIV) (PWH) and impaired coronary endothelial function (CEF) plays a central role in the pathogenesis of CAD. Age-related impaired CEF among PWH, however, is not well characterized. We investigated the association between CEF and age in males and females with and without HIV using 3-T magnetic resonance imaging (MRI). We measured the changes in coronary cross-sectional area (CSA) and coronary blood flow during isometric handgrip exercise (IHE), an established endothelial-dependent stressor with smaller increases in CSA and coronary blood flow indicative of impaired CEF. We included 106 PWH and 82 individuals without HIV. Differences in demographic and clinical characteristics between PWH and individuals without HIV were explored using Pearson’s χ² test for categorical variables and Welch’s t test for continuous variables. Linear regression models were used to examine the association between CEF and age. CEF was significantly lower in PWH as compared with individuals without HIV. Coronary endothelial dysfunction was also present at younger ages in PWH than in the individuals without HIV and there were significant differences in CEF between the PWH and individuals without HIV across age groups. Among the individuals without HIV, the percent changes in CSA were inversely related to age in unadjusted and adjusted models. There was no significant association between CEF and age in PWH. To the best of our knowledge, this is the first study to examine the relationship between age and CEF in PWH, and our results suggest that factors other than age significantly impair CEF in PWH across the life span.

NEW & NOTEWORTHY This is the first study to examine the relationship between age and coronary endothelial function (CEF) in people with human immunodeficiency virus (HIV) (PWH). CEF was assessed using magnetic resonance imaging (MRI) in people with and without HIV. Although age and CEF were significantly inversely related in individuals without HIV, there was no association between age and CEF in PWH.

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INTRODUCTION

Coronary artery disease (CAD) is one of the leading causes of mortality worldwide among the general population (1–3) and an increasingly important cause of non-acquired immunodeficiency syndrome (AIDS)-related mortality in people with human immunodeficiency virus (HIV) (PWH) (4). Endothelial cell function is considered a “barometer” of vascular health because endothelial dysfunction is a driver of the development, progression, and clinical manifestations of cardiovascular (CV) and cerebrovascular diseases and as such is considered a major cardiovascular risk factor (5). Endothelial dysfunction is also one of the earliest pathophysiological manifestations of atherosclerosis and predicts CAD events (6).

Previous studies using brachial artery measured flow-mediated dilatation demonstrated an association between age and systemic endothelial dysfunction in the general population (7, 8). However, these systemic measures correlate only modestly with those in the coronary circulation, which is more closely associated with underlying atherosclerosis. Catheterization-based studies using coronary angiography with Doppler flow indicate an age-associated decline in coronary artery endothelial function but are invasive and limited to those performed in patients with known or suspected coronary disease (9, 10). The association between age and coronary endothelial function (CEF) in healthy individuals and those with HIV has not been investigated.

There are several mechanisms that may account for the increase in cardiovascular risk in PWH. These include an increased prevalence of classical risk factors (11, 12), antiretroviral therapies (13), oxidative stress (14), and chronic inflammation (15). One common consequence of these factors is decreased nitric oxide (NO) bioavailability, a critical mediator of normal endothelial-dependent vascular function (16).

Advances in magnetic resonance imaging (MRI) permit noninvasive assessment of CEF, by measuring the endothelial-dependent vasoreactive response of the coronary arteries to isometric handgrip exercise (IHE), a nitric oxide (NO)-mediated, endothelial-dependent stressor (17, 18). Using this technique, our group studied 84 individuals and reported that CEF is reduced in PWH compared with individuals without HIV, even in the absence of coronary atherosclerosis (19, 20). We now include 104 additional participants and examine the relationship between CEF and age in PWH and whether this relationship differs in PWH and those without HIV. In this study, we investigated the association between CEF and age using noninvasive MRI in PWH and individuals without HIV. We hypothesized that the relationship between age and CEF differs in people with and without HIV.

MATERIALS AND METHODS

Study Design and Study Population

In this prospective observational study, participants were recruited from the outpatient clinics of the Johns Hopkins Hospital and the University of Maryland Medical Center. There were 108 men (73 with HIV and 35 without HIV) and 80 women (33 with HIV and 47 without HIV). Participants aged 21 yr and older with no contraindications to MRI were eligible and all provided written informed consent to participate in the protocol, which was approved by the Johns Hopkins Medicine Institutional Review Board. Two groups of participants were recruited: 1) HIV negative: adults without HIV and without CAD, defined as those 50 yr or younger with no history of CAD, diabetes, or more than one CAD risk factor, or those over age 50 yr with an Agatston coronary artery calcium score of 0 or no luminal disease on prior computed tomography (CT) angiography, and no Q waves on an ECG performed within 2 years of the study (available in 70% of participants); 2) PWH: adults with a diagnosis of HIV obtained from medical records, without known CAD, defined as no significant cardiac history and no evidence of prior myocardial infarction on ECG performed at the time of the study, and if clinically available, no significant luminal disease on prior CT angiography (available in 25% of participants). For all participants, there was no self-reported recreational drug use ≥2 mo before the MRI studies. PWH was on stable antiretroviral therapy (ART) for at least 1 year, with the most recent HIV viral load <500 copies/mL and no history of a CD4 count less than 50 cells/mm³.

Outcome of Interest

The outcome of interest was CEF measured noninvasively by quantifying the percent change in coronary blood flow and percent change in coronary cross-sectional area (%CSA) from those measured at rest to those measured during the isometric handgrip exercise stress.

MRI Study Protocol

A commercial whole body MR scanner (Achieva; Philips, Best, The Netherlands) with a 32-element cardiac coil for signal reception and a field strength of 3 T was used. We previously reported the detailed MR parameters (18). Cross-sectional anatomic and velocity-encoded spiral MRI of the coronaries were performed using breathhold cine sequences (21). For the assessment of coronary endothelial function, the temporal resolution for the anatomic images was 15 ms, and for the flow velocity images was 34 ms with velocity encoding of 35 cm/s. Approximately 18–30 cardiac phases were acquired for the coronary flow scan, depending on heart rate. The radiofrequency excitation angle was 20°, variable density spiral interleave sequences were used, and all scans were prospectively triggered. Participants underwent MRI in the morning after fasting for longer than 8 h and before the administration of any prescribed vasoactive medications. Perpendicular images of a proximal or midcoronary arterial segment that appeared straight over a distance of ∼20 mm were obtained (21). Double oblique scout scanning was performed, as previously reported (22), to ensure that slice orientation was perpendicular to the coronary artery. Anatomical images were collected at baseline and during continuous IHE for 4–7 min, depending on the participant’s heart rate, using an MRI-compatible dynamometer (Stoelting, Wood Dale, IL) (3) at 30% of maximum grip strength, under direct supervision. Our prior studies indicated that the coronary vasomotor response observed at 30% of the maximum grip strength was endothelial-dependent, safe, and could be maintained for the 4–7 min required for each scan (18). The handgrip exercise was continuous, and the dynamometer was observed by an investigator to prompt compliance. If one hand became fatigued, the other hand was used at once, and continuous isometric contraction was resumed (23). When images could be taken from two coronary artery segments per participant, the results for each coronary segment were quantified and the average was used. None of the studied segments contained coronary plaque. Noninvasive and MRI-compatible ECG and calf blood pressure monitors (both Invivo; Precess, Orlando, FL) were used throughout the study to measure heart rate and blood pressure.

Image Analysis

Rest and IHE-stress images for coronary CSA were analyzed as previously described (18). We used CINE software for cross-sectional area (v.4.5) and QFlow (Medis Suite 3.1.16.2) for coronary blood flow analysis, which are both commercially available software. Coronary flow velocity was measured in cm/s, and coronary blood flow was calculated using the following equation: coronary artery CSA × coronary artery peak diastolic velocity × 0.3 (24). Four coronary segments with poor image quality (blurring attributable to artifact/patient motion) on the rest or IHE-stress examinations were excluded from the analysis. The MRI analysis was performed by two independent readers (Y.A. and A.H.) who were blinded to age and HIV status.

Covariates

Patient characteristics included age (in yr), sex (male/female), and race/ethnicity (Black, White, Hispanic, or Asian). Data on key CV risk factors included history of hypertension (yes/no), diabetes mellitus (yes/no), body mass index (kg/m²), hyperlipidemia (yes/no), and current smoking (yes/no), and were extracted from research questionnaires and electronic medical records. HIV viral load within 6 mo before the examination in PWH was obtained from electronic medical records.

Statistical Analysis

Differences in demographic and clinical characteristics between the PWH and the HIV-negative groups were explored using Pearson’s χ² test for categorical variables and Student’s t test for continuous variables. Multivariate linear regression models were used to examine the association between CEF (%coronary blood flow and %CSA) and age in PWH and individuals without HIV. Model 1 was unadjusted, model 2 was adjusted for sex and race, and model 3 was additionally adjusted for diabetes mellitus, body mass index, and current smoking. We also assessed whether the MRI findings relating age to CEF differed based on the ART regimen in PWH. All analyses were performed using Stata version 16 (StataCorp, College Station, TX) and GraphPad Prism software version 9.4.1 (GraphPad Software, San Diego, CA). A two-sided α level of <0.05 was used to assess the statistical significance of the results.

RESULTS

A total of 188 participants were included in this study. One hundred six were PWH (age range: 25–72 yr, mean age: 48.2 ± 15.4 yr) and 82 were individuals without HIV (age range: 18–90 yr, mean age: 51.0 ± 10.7 yr). Mean CD4 count in the PWH was 759.7 cells/mL (±389.4) and viral load was undetectable in 92.4%. The majority of PWH were receiving a nucleoside reverse transcriptase inhibitor (80.2%), and an integrase strand transfer inhibitor (78.3%), and fewer were on a nonnucleoside reverse transcriptase inhibitor (16.0%) or a protease inhibitor (4.7%).

Comparison of Patient Demographic and Clinical Characteristics by HIV Status

PWH were more likely to be male (68.9 vs. 42.7%, P < 0.001) and Black (75.5 vs. 40.2%, P < 0.001). In addition, PWH were more likely to have a history of current smoking (58.5 vs. 11.0%, P < 0.001), and prior substance use (39.6 vs. 7.3%) compared with individuals without HIV (Table 1).

Table 1.

Patient characteristics of adults without HIV and PWH

Patient Characteristics	HIV-Negative Individuals	PWH	P Value
N	82	106
Personal statistics, means (SD)
Age	48.2 (15.4)	51.0 (10.7)	0.15
Body mass index	27.5 (5.1)	28.1 (4.6)	0.41
Sex, n (%)			<0.001
Male	35 (42.7)	73 (68.9)
Female	47 (57.3)	33 (31.1)
Race, n (%)			<0.001
White	43 (52.4)	22 (20.7)
Black	33 (40.2)	80 (75.5)
Hispanic	1 (1.2)	4 (3.8)
Asian	5 (6.1)	0 (0)
Medical conditions, n (%)
Hypertension	25 (30.5)	43 (40.6)	0.12
Diabetes mellitus	3 (3.7)	7 (6.6)	0.35
Users, n (%)
Smoking	9 (11.0)	62 (58.5)	<0.001
Prior substances	6 (7.3)	42 (39.6)	<0.001
Statins	23 (28.0)	35 (33.0)	0.53
ART	N/A	96 (90.6)
Protease inhibitors	N/A	5 (4.7)
NRTI	N/A	85 (80.2)
NNRTI	N/A	17 (16.0)
INSTI	N/A	83 (78.3)

Values are number of adults, n (percentages), and means (SD); N, number of adults in examined groups. ART, antiretroviral therapy; INSTI, integrase strand transfer inhibitor; N/A, not applicable; NNRTI, nonnucleoside reverse transcriptase inhibitor; NRTI, nucleoside reverse transcriptase inhibitor; PWH, people with human immunodeficiency virus (HIV).

Association of Coronary Endothelial Function with Age among PWH and Individuals without HIV

CEF as measured by %CSA change and %coronary blood flow change from those measured at rest to those during isometric handgrip exercise was significantly lower in PWH as compared with individuals without HIV [mean %CSA (±SD): −1.4 ± 11.5 vs. 9.6 ± 9.3%; mean %coronary blood flow (±SD): 1.2 ± 17.6 vs. 35.4 ± 24.7%, PWH vs. individuals without HIV, respectively; P < 0.001 for both; Figs. 1 and 2]. Further analysis in different age groups in the PWH and individuals without HIV revealed that CEF was significantly lower in PWH compared with individuals without HIV in participants younger than 45 yr, 45–55 yr, and 56 yr and older (Table 2 and Fig. 3).

Figure 1.

Representative magnetic resonance imaging (MRI) images of the right coronary artery (RCA) in an older and younger human immunodeficiency virus (HIV)-negative person. A scout scan of the RCA is shown in A along with the location for cross-sectional imaging (white dashed line). A view of the RCA cross section is shown (white arrow) in B and E that is perpendicular to image in A. Images in B and E are magnified to show a cross-sectional image of the RCA (yellow circles) at rest (C and F) and during isometric handgrip exercise (D and G). Ao, aorta; LA, left atrium; LV, left ventricle; RA, right atrium; RV, right ventricle.

Figure 2.

Representative magnetic resonance imaging (MRI) images of the right coronary artery (RCA) in an older and younger person with human immunodeficiency virus (HIV). A scout scan of the RCA is shown in A along with the location for cross-sectional imaging (white dashed line). A view of the RCA cross section is shown (white arrow) in B and E that is perpendicular to image in A. These images in B and E are magnified to show a cross-sectional image of the RCA (yellow circles) at rest (C and F) and during isometric handgrip exercise (D and G). Ao, aorta; LA, left atrium; LV, left ventricle; RA, right atrium; RV, right ventricle.

Table 2.

Comparison of mean %CSA and %CBF in adults without HIV and PWH across age groups

	HIV-Negative Individuals		PWH
Age, yr	N		N		P Value
Mean %CSA
<45	33	13.76 (11.68)	27	−1.68 (10.65)	<0.001
45–55	23	7.37 (4.25)	40	−3.11 (11.96)	<0.001
≥56	26	6.23 (7.06)	39	0.45 (11.76)	0.02
Mean %CBF
<45	33	42.90 (31.29)	27	0.38 (15.46)	<0.001
45–55	23	30.54 (12.71)	40	−1.90 (19.96)	<0.001
≥56	26	30.55 (21.43)	39	−1.65 (16.99)	<0.001

Values are means (SD); N, number of adults. %CBF, percent change in coronary blood flow; %CSA, percent change in coronary cross-sectional area; PWH, people with human immunodeficiency virus (HIV).

Figure 3.

Coronary endothelial function as measured by percent change in coronary cross-sectional area (%CSA) change and %coronary blood flow change in individuals without human immunodeficiency virus (HIV) and people with HIV (PWH) in three age groups. Boxes and whiskers outlining median percent changes and minimum and maximum values in coronary cross-sectional area (A) and coronary blood flow (B) in individuals without HIV (blue) and PWH (red) across three age groups: <45 yr [left, N = 33 (17 females) for individuals without HIV and N = 27 (6 females) for PWH], 45–55 yr [middle, N = 23 (18 females) for individuals without HIV and N = 40 (15 females) for PWH], and ≥56 yr [right, N = 26 (12 females) for individuals without HIV and N = 39 (12 females) for PWH]. A: for individuals without HIV vs. PWH, Welch’s t tests were used: **P < 0.001 in those <45 yr and 45–55 yr; and *P = 0.02 in those ≥56 yr. In individuals without HIV: ^^P = 0.006 comparing <45 yr vs. 45–55 yr, ^^P = 0.003 comparing <45 vs. ≥56 yr. B: for individuals without HIV vs. PWH, Welch’s t tests were used: **P < 0.001 in those <45 yr, 45–55 yr, and ≥56 yr.

Among individuals without HIV, %CSA was inversely associated with age in the unadjusted model (β-coefficient = −0.19, P = 0.003), after adjusting for sex and race (β = −0.16, P = 0.017), and after additionally adjusting for traditional cardiovascular risk factors, including diabetes mellitus, body mass index, and current smoking (β = −0.17, P = 0.021; Table 3 and Fig. 4). Among the same individuals without HIV, increasing age was inversely associated with %coronary blood flow in the unadjusted model (β = −0.36, P = 0.047) although not when adjusted for sex and race (β = −0.33, P = 0.085), and when further adjusted for CV risk factors (β = −0.33, P = 0.111; Table 3).

Table 3.

Association of mean %CSA and %CBF with age in adults without HIV and PWH

	HIV-Negative Individuals			PWH
	β	SE	P Value	β	SE	P Value
Mean %CSA
Model 1	−0.19	0.06	0.003	0.05	0.11	0.657
Model 2	−0.16	0.07	0.017	0.06	0.11	0.607
Model 3	−0.15	0.07	0.026	0.11	0.11	0.346
Mean %CBF
Model 1	−0.36	0.18	0.047	−0.07	0.16	0.676
Model 2	−0.33	0.19	0.085	−0.06	0.17	0.721
Model 3	−0.3	0.19	0.126	0.02	0.17	0.93

Values are β-coefficients and standard errors (SE). %CBF, percent change in coronary blood flow; %CSA, percent change in coronary cross-sectional area; PWH, people with human immunodeficiency virus (HIV). Model 1 represents univariate with age. Model 2 represents additionally adjusted for sex and race. Model 3 represents further adjusted for diabetes mellitus, body mass index, and smoking.

Figure 4.

Coronary endothelial function and age in individuals without human immunodeficiency virus (HIV). Scatter plot showing an association of mean percent change in coronary cross-sectional area with age in individuals without HIV. The P value reported is testing the slope of the fit against a null hypothesis of 0, using simple linear regression analysis. Line of fit equation, y = −0.1935x + 18.90, P value = 0.003, N = 82 (47 females): 95% confidence interval for the slope: [−0.3211, −0.0659], 95% confidence interval for y-intercept: [12.45, 25.35], and 95% confidence interval for x-intercept [76.49, 195]. %CSA, percent change in coronary cross-sectional area.

In contrast to the HIV-negative group, there was no significant association in PWH between age and %CSA in the unadjusted model (β = 0.05, P = 0.657), after adjustment for sex, and race (β = 0.06, P = 0.607) and following further adjustment for cardiovascular risk factors (β = 0.14, P = 0.231). The association between age and %CSA among PWH is shown in Fig. 5. Among PWH there was also no significant relationship between age and %coronary blood flow.

Figure 5.

Coronary endothelial and age in people with human immunodeficiency virus (HIV). Scatter plot showing no association of mean percent change in coronary cross-sectional area with age in people with HIV. The P value reported is testing the slope of the fit against a null hypothesis of 0, using simple linear regression analysis. Line of fit equation, y = 0.05035x − 4.003, P value = 0.63, N = 106 (33 females): 95% confidence interval for the slope: [−0.1576, 0.2583], 95% confidence interval for y-intercept: [−14.83, 6.826], and 95% confidence interval for x-intercept [−∞,+∞]. %CSA, percent change in coronary cross-sectional area.

Additional comparison analysis between PWH and participants without HIV showed a significant interaction between HIV diagnosis and age-related changes in CEF (P = 0.04). There is an inverse relationship between age and coronary endothelial function in individuals without HIV, whereas in PWH coronary endothelial function is impaired at all ages and there is no relationship between the two.

Coronary Endothelial Function and Different ART Medication Regimens

Finally, we investigated the effect of different ART regimens, and found no association of individual ART medication classes and CEF in this small sample size (Table 4).

Table 4.

Correlation coefficients and SEs of the relationship between mean %CSA and age and mean %CBF and age in different classes of ART in PWH

ART Class	N	β	SE	P Value
Mean %CSA
ART in general	96	2.72	3.85	0.48
NRTI	85	2.95	2.82	0.30
NNRTI	17	−1.58	3.07	0.61
INSTI	83	0.86	2.74	0.75
Protease inhibitors	5	3.38	5.31	0.53
Mean %CBF
ART in general	96	2.20	5.89	0.71
NRTI	85	−0.65	4.32	0.88
NNRTI	17	−3.87	4.68	0.41
INSTI	83	1.98	4.18	0.64
Protease inhibitors	5	6.11	8.10	0.45

Values are β-coefficients and standard errors (SE). ART, antiretroviral therapy; NRTI, nucleoside reverse transcriptase inhibitor; NNRTI, nonnucleoside reverse transcriptase inhibitor; INSTI, integrase strand transfer inhibitor; PWH, people with human immunodeficiency virus (HIV).

DISCUSSION

We used noninvasive MRI methods to evaluate the relationship of CEF with age in PWH and adults without HIV. We report that CEF is impaired in PWH even at young ages, is significantly decreased compared with HIV-negative individuals in the same age groups, and does not decline further with age. Changes in %CSA are significantly and inversely associated with age among adults without HIV, but not among PWH, even after adjustment for cardiac risk factors. In the same individuals, changes in %coronary blood flow are significantly inversely associated with increasing age in the unadjusted model, but not in models adjusted for age, sex, race, and CV risk factors.

The increased prevalence of traditional CV risk factors in PWH when compared with that in adults without HIV in our study is similar to that reported in the literature (11, 12). A prior study reported that systemic endothelial function, evaluated using brachial artery flow-mediated dilatation, was inversely related to age in PWH (12) and these results differ from our findings of no age impact on CEF in PWH. This may be related to differences in the vascular biology of the two vascular beds as the brachial arteries do not typically develop atherosclerosis whereas the coronary arteries do (25). It is also possible that age adversely impacts systemic endothelial function in PWH throughout the life span, whereas HIV-related factors may play a more important role in causing coronary endothelial dysfunction in PWH at younger ages or accelerating coronary vascular aging in PWH.

Normal CEF is characterized by vasodilatation and increased coronary blood flow in response to the release of nitric oxide initiated by an endothelial-dependent stressor, such as IHE. Conversely, impaired endothelial function is characterized by reduced bioavailable vasodilators, particularly NO, and is known to promote atherosclerosis and thrombosis and predicts adverse CV events (26). The ability of the systemic vascular endothelium to respond to endothelial stressors declines with age (27), and in a prior rodent study, advanced age was associated with impaired NO-mediated vasodilatation in coronary arterioles (28). Our findings of an age-related decline in CEF in HIV-negative persons are consistent with prior invasive coronary studies in people, which also reported an age-associated decline (5, 9, 29, 30).

There are several suggested mechanisms for the age-associated impairment, which are primarily focused on the causes and/or consequences of sterile inflammation (31). These include increased production of mitochondria-derived reactive oxygen species (ROS) resulting, in part, from reduced nicotinamide adenine dinucleotide phosphate oxidases (32). One of the most important consequences of increased ROS is impaired production and activity of endothelial-derived NO production, leading to decreased coronary and cerebral vascular smooth muscle relaxation in response to increases in oxygen and nutrient demand and inappropriate vasoconstriction (33–36). Aging is also associated with a proinflammatory shift in the gene expression profile of endothelial and smooth muscle cells, leading to the production of inflammatory cytokines and mediators (37). Epigenetic alterations, most importantly DNA methylation (38), and posttranslational histone modifications (39) are associated with vascular endothelial aging as well. Furthermore, aging is associated with increased activation of the renin-angiotensin-aldosterone system, which adversely impacts vascular smooth muscle cell relaxation (40). Changes in hormone status associated with menopause may also contribute to age-associated changes in CEF in women (41).

Although prior studies reported impaired CEF in PWH, the impact of age among PWH has not been explored. We found that there was no association between age and CEF in PWH suggesting that the impact of HIV on CEF is substantially greater than that of age alone and attenuates any impact of aging (Table 2 and Fig. 3). The more widespread use of ART has greatly improved long-term survival in PWH and increased the incidence of CAD and other chronic diseases. In addition, the increased prevalence of traditional CV risk factors among PWH, low-grade inflammation, immune activation, and the use of antiretroviral therapy may all predispose individuals who were HIV positive to impaired endothelial function early in life (11, 12, 15, 42). Isolated cell and ex vivo experiments show that the impact of HIV and certain protease inhibitors impair endothelial function by increasing oxidative stress (14). In addition, HIV-encoded proteins, particularly Gp120, Tat, and Nef play an important role in endothelial dysfunction by promoting apoptosis, angiogenesis, and expression of cell adhesion molecule and proinflammatory cytokines (43, 44). Some inflammatory markers remain elevated despite viral suppression (42). Potential causes include continued undetected low-level HIV replication (45, 46), coinfection with other viruses (47), and/or microbial translocation from gut mucosal injury (48). In addition, we previously reported that local epicardial adipose tissue, a proinflammatory fat depot, was strongly related to impaired CEF in PWH (49), indicating a potential role of increased tissue inflammation. Notably, a prior study showed that suboptimal HIV suppression with persistent low levels of viremia was associated with increased CAD progression in PWH (50). There were only eight patients with a detectable viral load in our study and it was not possible, with that sample size, to determine whether there was an association between CEF and viral load. Although medications used in the treatment of HIV, such as protease inhibitors, are associated with a decline in endothelial function (51), only a small percentage of PWH in this cohort were taking protease inhibitors (4.7%), reflective of contemporary treatments. Furthermore, we did not detect any significant influence of different ART regimens (including protease inhibitors) on CEF (Table 4). Therefore, it is possible that factors such as low-level viremia and local inflammation are, at least in part, responsible for adversely impacting CEF at an early age in PWH.

One of the attributes of the study is that noninvasive means were used to measure CEF, making it possible to explore CEF in adults without HIV with low CV risk and for the first time to study the effect of age on CEF in PWH. Our study, however, has several limitations. We can only infer association and not causality for the impact of age. In addition, there were significant differences between PWH and individuals without HIV in terms of race and sex, reflective of the local study community-based population. However, adjusting for race and sex in model 2 did not impact the findings and the primary goal of our study was to focus on the relationship between age and CEF rather than between-group differences, which we previously reported (19). There are also differences in traditional risk factors, e.g., smoking, which were also adjusted for in model 3. Nevertheless, it is possible that factors other than HIV status alone may have contributed to the differences between the two study groups.

Conclusions

Our findings demonstrate that CEF measured noninvasively with MRI is inversely associated with age in adults without HIV but not in PWH. In addition, CEF in PWH was significantly impaired compared with that in the individuals without HIV in all of the examined age groups. Cardiovascular risk is increased in PWH across the life span and our findings suggest that impaired CEF may be one responsible mechanism for this increase. Factors such as chronic persistent inflammation (15), undetected virus (45), ART (13), and other undetermined factors may negatively impact CEF in PWH at an early age. The observation that depressed CEF occurs across the life span in PWH may provide insights regarding mechanisms responsible for the increased CV risk in PWH of all ages and suggest that noninvasive detection of CEF may inform the identification and evaluation of new therapeutic interventions in this high-risk population of patients.

DATA AVAILABILITY

Data will be made available upon reasonable request.

GRANTS

This work was supported by National Institutes of Health (NIH) Grant 1R01HL147660 and Johns Hopkins Center for AIDS Research Grant P30AI094189 (to A.G.H.); the Johns Hopkins University Claude D. Pepper Older Americans Independence Center funded by NIH Grant P30-AG021334 (to G.G. and T.M.L.); NIH Grants AG063661, HL156703, and HL61912 and the Clarence Doodeman Endowment in Cardiology (to R.G.W.); NIH Grant K23 HL133358 (to S.B.); and NIH Grant R01AG060825 (to D.A.P.).

DISCLOSURES

No conflicts of interest, financial or otherwise, are declared by the authors.

AUTHOR CONTRIBUTIONS

E.Z., Y.A.K., R.G.W., G.G., T.M.L., and A.G.H. conceived and designed research; E.Z., Y.A.K., R.G.W., M.S., A.S., G.G., T.M.L., and A.G.H., performed experiments; E.Z., Y.A.K., R.G.W., M.S., T.H., G.G., T.M.L., and A.G.H., analyzed data; E.Z., Y.A.K., R.G.W., M.S., T.T.B., S.B., A.S., T.H., D.A.P., G.G., T.M.L., and A.G.H., interpreted results of experiments; E.Z. and Y.A.K. prepared figures; E.Z., Y.A.K., G.G., T.M.L., and A.G.H. drafted manuscript; E.Z., Y.A.K., R.G.W., M.S., T.T.B., S.B., A.S., T.H., D.A.P., G.G., T.M.L., and A.G.H. edited and revised manuscript; E.Z., Y.A.K., R.G.W., M.S., T.T.B., S.B., A.S., T.H., D.A.P., G.G., T.M.L., and A.G.H. approved final version of manuscript.