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Principal Investigator: Yanxun Xu
Organization: JOHNS HOPKINS UNIVERSITY
Fiscal Year: 2024
Award: $393,839
Funding agency: National Institute of Mental Health
Project Summary/Abstract
The use of combination antiretroviral therapy (cART) has significantly reduced HIV-related morbidity and
mortality. However, cART may exacerbate the central nervous system (CNS)-related adverse effects on mental
health for people with HIV (PWH). These adverse effects may result in ART discontinuation with undesirable
downstream consequences such as HIV disease progression, decreased health outcomes, and increased
likelihood of HIV transmission, causing public health concerns. Depression is the most frequently reported mental
health comorbidity caused by CNS injury in PWH, with prevalence ranging from 20% to 60%. Understanding
factors (e.g., drug-drug interactions) contributing to ART-related depression is critical and remains a high priority
NIMH research area. In addition, since PWH must continue cART indefinitely, optimizing sequential cART
treatments over a long-time span tailored to individuals’ evolving clinical characteristics and treatment histories
is important for improving long-term mental health for PWH. However, there are numerous possible drug
combinations with complicated drug-drug interactions and thus creating complex data patterns, such as
heterogeneity, high-dimensionality, and sparseness, making it highly challenging to develop appropriate
statistical models for these problems - which is a critical gap we aim to fill. This proposal will leverage large
public HIV datasets, including Women's Interagency HIV Study (WIHS), to develop data-driven approaches to
facilitate deciphering cART-depression relations and guide more effective cART treatments. This proposal is
organized into three aims: 1) Develop Bayesian methods to learn longitudinal cART effects on depression and
investigate effect modifiers (e.g., polymorphic drug metabolism, aging); 2) Develop Bayesian decision
frameworks to optimize personalized sequential cART assignments with the goal of improving long-term mental
health outcomes for PWH; (3) encapsulate statistical methods and computational algorithms into user-friendly
open-source software for practical use, clinical translation, and dissemination. Findings from this study are
expected to expand our understanding of cART effects on depression, and have potential clinical utility to
facilitate precision medicine in HIV.
Terms: <AIDS Virus><Acquired Immune Deficiency Syndrome Virus><Acquired Immunodeficiency Syndrome Virus><Address><Adverse effects><Age><Aging><Area><Bayesian Method><Bayesian Methodology><Bayesian Modeling><Bayesian Statistical Method><Bayesian adaptive designs><Bayesian adaptive models><Bayesian approaches><Bayesian belief network><Bayesian belief updating model><Bayesian classification method><Bayesian classification procedure><Bayesian framework><Bayesian hierarchical model><Bayesian network model><Bayesian nonparametric models><Bayesian posterior distribution><Bayesian spatial data model><Bayesian spatial image models><Bayesian spatial models><Bayesian statistical models><Bayesian tracking algorithms><Behavioral><CNS Injury><CNS Nervous System><Caring><Central Nervous System><Characteristics><Chronic Disease><Chronic Illness><Clinical><Complex><Computational algorithm><Computer software><Data><Data Set><Data Sources><Department of Health and Human Services><Dimensions><Disease><Disease Outcome><Disease Progression><Disorder><Drug Combinations><Drug Interactions><Drugs><Elderly><Encapsulated><FDA approved><Genetic><Genetic Polymorphism><Goals><Guidelines><HIV><HIV Infections><HIV therapy><HTLV-III Infections><HTLV-III-LAV Infections><Health><Health Care Costs><Health Costs><Healthcare Costs><Heterogeneity><History><Human Immunodeficiency Viruses><Human T-Lymphotropic Virus Type III Infections><Individual><Knowledge><LAV-HTLV-III><Laboratories><Learning><Link><Long-Term Effects><Longitudinal Studies><Longterm Effects><Lymphadenopathy-Associated Virus><Math><Mathematics><Measurement><Mediating><Medication><Mental Depression><Mental Health><Mental Hygiene><Methods><Modeling><Morbidity><Morbidity - disease rate><NIMH><National Institute of Mental Health><Neuraxis><Outcome><Pattern><Persons><Pharmaceutical Preparations><Physicians><Population><Prevalence><Probabilistic Models><Probability Models><Psychological Health><Public Health><Recommendation><Recording of previous events><Reporting><Research><Risk><Selection for Treatments><Self Care><Software><Statistical Methods><Statistical Models><Structure><Time><Transmission><Trees><Uncertainty><United States Department of Health and Human Services><United States Dept. of Health and Human Services><Viral><Virus-HIV><Women's Interagency HIV Study><advanced age><ages><antiretroviral therapy><antiretroviral treatment><application in practice><central nervous system injury><chronic disorder><clinical translation><clinically translatable><co-morbid><co-morbidity><combinatorial><comorbidity><complex data><computer algorithm><data complexity><demographics><depression><develop software><developing computer software><doubt><drug metabolism><drug/agent><efavirenz><geriatric><high dimensionality><histories><improved><injured CNS><kernel learning><kernel methods><long-term study><longitudinal outcome studies><longterm study><model building><mortality><multi-kernel learning><multiple data sources><online app><open source><personal care><personalization of treatment><personalized medicine><personalized therapy><personalized treatment><polymorphism><practical application><precision medicine><precision-based medicine><prevent><preventing><public health relevance><selection of treatment><senior citizen><side effect><software development><statistic methods><statistical linear mixed models><statistical linear models><study population><success><therapy selection><transmission process><treatment adherence><treatment choice><treatment compliance><treatment planning><treatment selection><user-friendly><web app><web application><web based app><web based application>