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Combination antiretroviral therapy (ART) with at least three different drugs has become the standard of care for people with HIV (PWH) due to its exceptional effectiveness in viral suppression. However, many ART drugs have been reported to associate with neuropsychiatric adverse effects including depression, especially when certain genetic polymorphisms exist. Pharmacogenetics is an important consideration for administering combination ART as it may influence drug efficacy and increase risk for neuropsychiatric conditions. Large-scale longitudinal HIV databases provide researchers opportunities to investigate the pharmacogenetics of combination ART in a data-driven manner. However, with more than 30 FDA-approved ART drugs, the interplay between the large number of possible ART drug combinations and genetic polymorphisms imposes statistical modeling challenges. We develop a Bayesian approach to examine the longitudinal effects of combination ART and their interactions with genetic polymorphisms on depressive symptoms in PWH. The proposed method utilizes a Gaussian process with a composite kernel function to capture the longitudinal combination ART effects by directly incorporating individuals’ treatment histories, and a Bayesian classification and regression tree to account for individual heterogeneity. Through both simulation studies and an application to a dataset from the Women’s Interagency HIV Study, we demonstrate the clinical utility of the proposed approach in investigating the pharmacogenetics of combination ART and assisting physicians to make effective individualized treatment decisions that can improve health outcomes for PWH.

 

Although combination antiretroviral therapy (ART) with three or more drugs is highly effective in suppressing viral load for people with HIV (human immunodeficiency virus), many ART agents may exacerbate mental health‐related adverse effects including depression. Therefore, understanding the effects of combination ART on mental health can help clinicians personalize medicine with less adverse effects to avoid undesirable health outcomes. The emergence of electronic health records offers researchers' unprecedented access to HIV data including individuals' mental health records, drug prescriptions, and clinical information over time. However, modeling such data is challenging due to high dimensionality of the drug combination space, the individual heterogeneity, and sparseness of the observed drug combinations. To address these challenges, we develop a Bayesian nonparametric approach to learn drug combination effect on mental health in people with HIV adjusting for sociodemographic, behavioral, and clinical factors. The proposed method is built upon the subset‐tree kernel that represents drug combinations in a way that synthesizes known regimen structure into a single mathematical representation. It also utilizes a distance‐dependent Chinese restaurant process to cluster heterogeneous populations while considering individuals' treatment histories. We evaluate the proposed approach through simulation studies, and apply the method to a dataset from the Women's Interagency HIV Study, showing the clinical utility of our model in guiding clinicians to prescribe informed and effective personalized treatment based on individuals' treatment histories and clinical characteristics.

 

As the use of Integrase inhibitor (INSTI)-class antiretroviral medications becomes more common to maintain long-term viral suppression, early reports suggest the potential for CNS side-effects when starting or switching to an INSTI-based regimen. In a population already at higher risk for developing mood and anxiety disorders, these drugs may have significant effects on PTSD scale symptom scores, particularly in women with HIV (WWH). A total of 551 participants were included after completing ≥ 1 WIHS study visits before and after starting/switching to an INSTI-based ART regimen. Of these, 14% were ART naïve, the remainder switched from primarily a protease inhibitor (PI) or non-nucleoside reverse transcriptase inhibitor (NNRTI)-based regimen. Using multivariable linear mixed effects models, we compared PTSD Civilian Checklist subscale scores before and after a “start/switch” to dolutegravir (DTG), raltegravir (RAL), or elvitegravir (EVG). Start/switch to EVG improved re-experiencing subscale symptoms (P’s < 0.05). Switching to EVG improved symptoms of avoidance (P = 0.01). Starting RAL improved arousal subscale symptoms (P = 0.03); however, switching to RAL worsened re-experiencing subscale symptoms (P < 0.005). Starting DTG worsened avoidance subscale symptoms (P = 0.03), whereas switching to DTG did not change subscale or overall PTSD symptoms (P’s > 0.08). In WWH, an EVG-based ART regimen is associated with improved PTSD symptoms, in both treatment naïve patients and those switching from other ART. While a RAL-based regimen was associated with better PTSD symptoms than in treatment naïve patients, switching onto a RAL-based regimen was associated with worse PTSD symptoms. DTG-based regimens either did not affect, or worsened symptoms, in both naïve and switch patients. Further studies are needed to determine mechanisms underlying differential effects of EVG, RAL and DTG on stress symptoms in WWH. 

Cognitive complications persist in antiretroviral therapy(ART)-treated people with HIV. However, the pattern and severity of domain- specific cognitive performance is variable and may be exacerbated by ART-mediated neurotoxicity. 929 women with HIV(WWH) from the Women’s Interagency HIV Study who were classified into subgroups based on sociodemographic and longitudinal behavioral and clinical data using semi-parametric latent class trajectory modelling. Five subgroups were comprised of: 1) well-controlled HIV with vascular comorbidities(n = 116); 2) profound HIV legacy effects(CD4 nadir <250 cells/μL; n = 275); 3) primarily <45 year olds with hepatitis C(n = 165); 4) primarily 35–55 year olds(n = 244), and 5) poorly-controlled HIV/substance use(n = 129). Within each subgroup, we fitted a constrained continuation ratio model via penalized maximum likelihood to examine adjusted associations between recent ART agents and cognition. Most drugs were not associated with cognition. However, among the few drugs, non- nucleoside reverse transcriptase inhibitor (NNRTIs) and protease inhibitors(PIs) were most commonly associated with cognition, followed by nucleoside reverse transcriptase inhibitors(NRTIs) and integrase inhibitors(IIs). Directionality of ART-cognition associa- tions varied by subgroup. Better psychomotor speed and fluency were associated with ART for women with well-controlled HIV with vascular comorbidities. This pattern contrasts women with profound HIV legacy effects for whom poorer executive function and fluency were associated with ART. Motor function was associated with ART for younger WWH and primarily 35–55 year olds. Memory was associated with ART only for women with poorly-controlled HIV/substance abuse. Findings demonstrate interindividual variability in ART-cognition associations among WWH and highlight the importance of considering sociodemographic, clinical, and behavioral factors as an underlying contributors to cognition.