OBJECTIVES: The relationship between chronic obstructive pulmonary disease (COPD) and cardiovascular disease in people with HIV (PWH) is incompletely understood. We determined whether COPD is associated with risk of myocardial infarction (MI) among PWH, and if this differs for type 1 (T1MI) and type 2 (T2MI). DESIGN: We utilized data from five sites in the Centers for AIDS Research Network of Integrated Clinical Systems (CNICS) cohort, a multisite observational study. METHODS: Our primary outcome was an adjudicated MI, classified as T1MI or T2MI. We defined COPD based on a validated algorithm requiring COPD diagnosis codes and at least 90-day continuous supply of inhalers. We conducted time-to-event analyses to first MI and used multivariable Cox proportional hazards models to measure associations between COPD and MI. RESULTS: Among 12 046 PWH, 945 had COPD. Overall, 309 PWH had an MI: 58% had T1MI ( N  = 178) and 42% T2MI ( N  = 131). In adjusted models, COPD was associated with a significantly increased risk of all MI [adjusted hazard ratio (aHR) 2.68 (95% confidence interval (CI) 1.99-3.60)] even after including self-reported smoking [aHR 2.40 (95% CI 1.76-3.26)]. COPD was also associated with significantly increased risk of T1MI and T2MI individually, and with sepsis and non-sepsis causes of T2MI. Associations were generally minimally changed adjusting for substance use. CONCLUSION: COPD is associated with a substantially increased risk for MI, including both T1MI and T2MI, among PWH. Given the association with both T1MI and T2MI, diverse mechanistic pathways are involved. Future strategies to decrease risk of T1MI and T2MI in PWH who have COPD are needed.

Background

Increases in multimorbidity and obesity have been noted in HIV-infected populations in the current treatment era. Patterns of multimorbid disease clustering and the impact of obesity on multimorbidity are understudied in this population.

Methods

We examined obesity and multimorbidity patterns among 1844 HIV-infected patients in the UAB 1917 Clinic. Exploratory factor analysis was used to identify the underlying factor structure responsible for clustering. Patterns among the resulting morbidity factors by body mass index (BMI) category were explored. Multivariable logistic regression models were fit to identify predictors of multimorbidity cluster patterns.

Results

The prevalence of multimorbidity was 65% (1205/1844). Prevalence increased with progressive BMI categories from underweight (64%) to obese (79%). Three multimorbidity clusters were identified: "metabolic," including hypertension, gout, diabetes mellitus, and chronic kidney disease (range, 0.41-0.84; P < 0.001); "Behavioral," including mood disorders, dyslipidemia, chronic obstructive pulmonary disease, chronic ulcer disease, osteoarthritis, obstructive sleep apnea, and cardiac disorders (range, 0.32-0.57; P < 0.001); "Substance Use," including alcohol abuse, substance abuse, tobacco abuse, and hepatitis C (range, 0.53-0.89; P < 0.001). Obesity was associated with increased odds of multimorbidity (obese vs. normal BMI category: OR = 1.52, 95% CI: 1.15 to 2.00).

Conclusions

Three patterns of disease clustering were identified. Obesity was associated with a higher likelihood of multimorbidity. The management of multimorbidity and obesity will need to be addressed in future clinical practice guidelines to enhance long-term outcomes of HIV-infected patients in the current treatment era.

Objectives

Evaluate differences in weight change by regimen among people living with HIV (PLWH) initiating antiretroviral therapy (ART) in the current era.

Methods

Between 2012 and 2019, 3232 ART-naïve PLWH initiated ≥3-drug ART regimens in 8 Centers for AIDS Research Network of Integrated Clinical Systems sites. We estimated weight change by regimen for 11 regimens in the immediate (first 6 months) and extended (all follow-up on initial regimen) periods using linear mixed models adjusted for time on regimen, interaction between time and regimen, age, sex, race/ethnicity, hepatitis B/C coinfection, nadir CD4, smoking, diabetes, antipsychotic medication, and site. We included more recently approved regimens [eg, with tenofovir alafenamide fumarate (TAF)] only in the immediate period analyses to ensure comparable follow-up time.

Results

Mean follow-up was 1.9 years on initial ART regimen. In comparison to efavirenz/tenofovir disoproxil fumarate (TDF)/emtricitabine (FTC), initiating bictegravir/TAF/FTC {3.9 kg [95% confidence interval (CI): 2.2 to 5.5]} and dolutegravir/TAF/FTC [4.4 kg (95% CI: 2.1 to 6.6)] were associated with the greatest weight gain in the immediate period, followed by darunavir/TDF/FTC [3.7 kg (95% CI: 2.1 to 5.2)] and dolutegravir/TDF/FTC [2.6 kg (95% CI: 1.3 to 3.9)]. In the extended period, compared with efavirenz/TDF/FTC, initiating darunavir/TDF/FTC was associated with a 1.0 kg (95% CI: 0.5 to 1.5) per 6-months greater weight gain, whereas dolutegravir/abacavir/FTC was associated with a 0.6-kg (95% CI: 0.3 to 0.9) and dolutegravir/TDF/FTC was associated with a 0.6-kg (95% CI: 0.1 to 1.1) per 6-months greater gain. Weight gain on dolutegravir/abacavir/FTC and darunavir/TDF/FTC was significantly greater than that for several integrase inhibitor-based regimens.

Conclusions

There is heterogeneity between regimens in weight gain following ART initiation among previously ART-naïve PLWH; we observed greater gain among PLWH taking newer integrase strand transfer inhibitors (DTG, BIC) and DRV-based regimens.

OBJECTIVES: People with HIV have a higher risk of myocardial infarction (MI) than the general population, with a greater proportion of type 2 MI (T2MI) due to oxygen demand-supply mismatch compared with type 1 (T1MI) resulting from atherothrombotic plaque disruption. People living with HIV report a greater prevalence of cigarette and alcohol use than do the general population. Alcohol use and smoking as risk factors for MI by type are not well studied among people living with HIV. We examined longitudinal associations between smoking and alcohol use patterns and MI by type among people living with HIV. DESIGN AND METHODS: Using longitudinal data from the Centers for AIDS Research Network of Integrated Clinical Systems cohort, we conducted time-updated Cox proportional hazards models to determine the impact of smoking and alcohol consumption on adjudicated T1MI and T2MI. RESULTS: Among 13 506 people living with HIV, with a median 4 years of follow-up, we observed 177 T1MI and 141 T2MI. Current smoking was associated with a 60% increase in risk of both T1MI and T2MI. In addition, every cigarette smoked per day was associated with a 4% increase in risk of T1MI, with a suggestive, but not significant, 2% increase for T2MI. Cigarette use had a greater impact on T1MI for men than for women and on T2MI for women than for men. Increasing alcohol use was associated with a lower risk of T1MI but not T2MI. Frequency of heavy episodic alcohol use was not associated with MI. CONCLUSIONS: Our findings reinforce the prioritization of smoking reduction, even without cessation, and cessation among people living with HIV for MI prevention and highlight the different impacts on MI type by gender.

To assess atrial fibrillation risk factors in people with HIV, we identified incident atrial fibrillation in a large clinical cohort of people receiving care. Compared with 970 controls without atrial fibrillation, the 97 with adjudicated incident atrial fibrillation were older, less likely Hispanic, and had more coronary disease, heart failure, and chronic obstructive pulmonary disease. In multivariable analysis, nonuse of antiretroviral therapy and prescription of antiretroviral regimens with multiple core agents were associated with increased atrial fibrillation risk.

Background

Type 1 myocardial infarctions (T1MIs) result from atherosclerotic plaque instability, rupture, and/or erosion. Type 2 MIs (T2MIs) are secondary to causes such as sepsis and cocaine-induced vasospasm resulting in an oxygen demand-supply mismatch and are associated with higher mortality than T1MIs. T2MIs account for a higher proportion of MIs among people living with HIV (PLWH) compared with the general population. We compared MI rates by type among aging PLWH. We hypothesized that increases in MI rates with older age would differ by MI types, and T2MIs would be more common than T1MIs in younger individuals.

Methods

Potential MIs from 6 sites were centrally adjudicated using physician notes, electrocardiograms, procedure results, and laboratory results. Reviewers categorized MIs by type and identified causes of T2MIs. We calculated T1MI and T2MI incidence rates. Incidence rate ratios were calculated for T2MI vs. T1MI rates per decade of age.

Results

We included 462 T1MIs (52%) and 413 T2MIs (48%). T1MI rates increased with older age, although T1MIs occurred in all age decades including young adults. T2MI rates were significantly higher than T1MI rates for PLWH younger than 40 years. T1MI rates were similar or higher than T2MI rates among those older than 40 years (significantly higher for those aged 50-59 and 60-69 years).

Conclusions

Rates of T2MIs were higher than T1MIs until age 40 years among PLWH, differing from the general population, but rates of both were high among older PLWH. Given prognostic differences between MI types, these results highlight the importance of differentiating MI types among PLWH.

OBJECTIVE: To examine associations between frailty and drug, alcohol, and tobacco use among a large diverse cohort of people with HIV (PWH) in clinical care in the current era. METHODS: PWH at 7 sites across the United States completed clinical assessments of patient-reported measures and outcomes between 2016 and 2019 as part of routine care including drug and alcohol use, smoking, and other domains. Frailty was assessed using 4 of the 5 components of the Fried frailty phenotype and PWH were categorized as not frail, pre-frail, or frail. Associations of substance use with frailty were assessed with multivariate Poisson regression. RESULTS: Among 9336 PWH, 43% were not frail, 44% were prefrail, and 13% were frail. Frailty was more prevalent among women, older PWH, and those reporting current use of drugs or cigarettes. Current methamphetamine use (1.26: 95% CI 1.07-1.48), current (1.65: 95% CI 1.39-1.97) and former (1.21:95% CI 1.06-1.36) illicit opioid use, and former cocaine/crack use (1.17: 95% CI 1.01-1.35) were associated with greater risk of being frail in adjusted analyses. Current smoking was associated with a 61% higher risk of being frail vs. not frail (1.61: 95% CI 1.41-1.85) in adjusted analyses. CONCLUSIONS: We found a high prevalence of prefrailty and frailty among a nationally distributed cohort of PWH in care. This study identified distinct risk factors that may be associated with frailty among PWH, many of which, such as cigarette smoking and drug use, are potentially modifiable.

Despite its potential to improve metabolic health outcomes, longitudinal physical activity (PA) patterns and their association with cardiometabolic disease among people living with HIV (PLWH) have not been well characterized. We investigated this relationship among PLWH in the Centers for AIDS Research Network of Integrated Clinical Systems with at least one PA self-report between 2008 and 2015. The 4-item Lipid Research Clinics PA instrument was used to categorize habitual PA levels as: Very Low, Low, Moderate, or High. We analyzed demographic differences in PA patterns. Multivariable generalized estimating equation regression models were fit to assess longitudinal associations of PA with blood pressure, lipid, and glucose levels. Logistic regression modeling was used to assess the odds of being diagnosed with obesity, cardiovascular disease (CVD), cerebrovascular disease, hypertension, diabetes, or multimorbidity. A total of 40,462 unique PA assessments were provided by 11,719 participants. Only 13% of PLWH reported High PA, while 68% reported Very Low/Low PA at baseline and did not increase PA levels during the study period. Compared to those reporting High PA, participants with Very Low PA had almost 2-fold increased risk for CVD. Very Low PA was also associated with several risk factors associated with CVD, most notably elevated triglycerides (odds ratio 25.4), obesity (odds ratio 1.9), hypertension (odds ratio 1.4), and diabetes (odds ratio 2.3; all p < 0.01). Low levels of PA over time among PLWH are associated with increased cardiometabolic disease risk.

BACKGROUND: People with human immunodeficiency virus (HIV) infection (PWH) are at higher risk of myocardial infarction (MI) than those without HIV. About half of MIs in PWH are type 2 (T2MI), resulting from mismatch between myocardial oxygen supply and demand, in contrast to type 1 MI (T1MI), which is due to primary plaque rupture or coronary thrombosis. Despite worse survival and rising incidence in the general population, evidence-based treatment recommendations for T2MI are lacking. We used polygenic risk scores (PRS) to explore genetic mechanisms of T2MI compared to T1MI in PWH. METHODS: We derived 115 PRS for MI-related traits in 9541 PWH enrolled in the Centers for AIDS Research Network of Integrated Clinical Systems cohort with adjudicated T1MI and T2MI. We applied multivariate logistic regression analyses to determine the association with T1MI and T2MI. Based on initial findings, we performed gene set enrichment analysis of the top variants composing PRS associated with T2MI. RESULTS: We found that T1MI was strongly associated with PRS for cardiovascular disease, lipid profiles, and metabolic traits. In contrast, PRS for alcohol dependence and cholecystitis, significantly enriched in energy metabolism pathways, were predictive of T2MI risk. The association remained after the adjustment for actual alcohol consumption. CONCLUSIONS: We demonstrate distinct genetic traits associated with T1MI and T2MI among PWH further highlighting their etiological differences and supporting the role of energy regulation in T2MI pathogenesis.

Background

Advances in antiretroviral therapies have greatly improved the survival of people living with human immunodeficiency virus (HIV) infection (PLWH); yet, PLWH have a higher risk of cardiovascular disease than those without HIV. While numerous genetic loci have been linked to cardiometabolic risk in the general population, genetic predictors of the excessive risk in PLWH are largely unknown.

Methods

We screened for common and HIV-specific genetic variants associated with variation in lipid levels in 6284 PLWH (3095 European Americans [EA] and 3189 African Americans [AA]), from the Centers for AIDS Research Network of Integrated Clinical Systems cohort. Genetic hits found exclusively in the PLWH cohort were tested for association with other traits. We then assessed the predictive value of a series of polygenic risk scores (PRS) recapitulating the genetic burden for lipid levels, type 2 diabetes (T2D), and myocardial infarction (MI) in EA and AA PLWH.

Results

We confirmed the impact of previously reported lipid-related susceptibility loci in PLWH. Furthermore, we identified PLWH-specific variants in genes involved in immune cell regulation and previously linked to HIV control, body composition, smoking, and alcohol consumption. Moreover, PLWH at the top of European-based PRS for T2D distribution demonstrated a > 2-fold increased risk of T2D compared to the remaining 95% in EA PLWH but to a much lesser degree in AA. Importantly, while PRS for MI was not predictive of MI risk in AA PLWH, multiethnic PRS significantly improved risk stratification for T2D and MI.

Conclusions

Our findings suggest that genetic loci involved in the regulation of the immune system and predisposition to risky behaviors contribute to dyslipidemia in the presence of HIV infection. Moreover, we demonstrate the utility of the European-based and multiethnic PRS for stratification of PLWH at a high risk of cardiometabolic diseases who may benefit from preventive therapies.