Epigenetic Risk Scoring for Polysubstance Use and Comorbidity in People with HIV - PROJECT SUMMARY Polysubstance use (PSU) is highly prevalent among people with HIV (PWH) and increases the burden of comorbidities, accelerates HIV progression, and raises mortality. In the U.S., non-AIDS comorbidities such as alcohol-related liver disease and smoking-related pulmonary and cardiovascular conditions are among the leading causes of death among PWH. The interaction between PSU and HIV exacerbates immune dysregulation, chronic inflammation, and susceptibility to infections, creating a cycle that heightens the comorbidity burden. The complex interactions between substances, variations in dosage and frequency, and cumulative health effects make accurate measurement and risk assessment challenging. Despite the clinical importance of PSU, current screening approaches rely on self-report or short-term biomarkers, leaving them vulnerable to recall bias, underreporting, stigma, and limited detection windows. Importantly, no objective, biologically grounded tools exist to assess and stratify PSU risk or to quantify its impact on comorbidity risk in PWH. Prior research has demonstrated that DNA methylation (DNAm), a key epigenetic modification, provides a robust biological marker of internal and external exposures, including substance use. DNAm profiles have been shown to capture cumulative biological impacts and can differentiate between individuals with varying substance use histories. Our prior work demonstrated that DNAm features improved the prediction of hazardous alcohol consumption beyond a traditional alcohol biomarker. However, existing research has focused on individual substances in isolation, overlooking the complexities and interactions of PSU. To date, no DNAm-based tools have been developed to quantify PSU, stratify risk, or assess its contribution to the comorbidity burden in this vulnerable population. To address this gap, we propose to develop and validate the first DNAm-based epigenetic risk score that quantifies the cumulative biological impact of PSU. We hypothesize that distinct PSU patterns are associated with specific DNAm signatures and that integrating these signatures with biological and clinical factors will improve the prediction of comorbidity risk and enable precise risk stratification and early intervention. This approach is innovative because it will leverage cutting-edge epigenetic and predictive modeling techniques to capture the complex, cumulative, and individualized effects of PSU, offering a transformative advance toward precision HIV care. We will test this hypothesis through two specific aims: Aim 1 will develop and validate a DNAm-based risk score for PSU by integrating epigenome-wide data with detailed substance use patterns; Aim 2 will incorporate PSU-associated DNAm markers and key biological and clinical factors into predictive models of comorbidity risk in PWH, with external validation in independent cohorts. This work will provide objective, biologically grounded tools to improve PSU detection and comorbidity risk stratification, laying the foundation for precision HIV care and reducing disease burden in this vulnerable population.
