Cardiovascular Risk Reduction in an Aging HIV-Infected Population: The Impact of HCV Co-Infection

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PROJECT SUMMARY/ABSTRACT The proposed study will investigate how Hepatitis C virus (HCV) impacts cardiovascular disease (CVD) risk among individuals co-infected with HIV and HCV: Specific Aim 1. To quantify the impact of HCV co-infection on acute myocardial infarction (AMI) risk in a cohort of HIV-infected patients followed longitudinally in a large prospective clinical care cohort HIV infection increases CVD risk, and this risk is thought to be driven by non-traditional risk factors. Whether patients co-infected with HCV have further increased CVD risk and whether this interaction is influenced by age and HCV treatment status is not well understood. Importantly, CVD risk may persist even after treated HCV, and this question has not been previously answered. It is hypothesized that the presence of two chronic infections will increase risk beyond that of either infection alone. Specific Aim 2. To investigate whether treating HCV, and reducing its associated chronic inflammation, decreases risk of incident AMI The new era of HCV care has brought extremely effective treatment for HCV, yet access remains limited and barriers to treatment persist in co-infected patients. The extra-hepatic effects of HCV treatment – particularly direct-acting antivirals (DAAs) – are not known. With persistent barriers to HCV treatment, knowledge of whether HCV treatment can reduce CVD risk will have important public health implications for prioritizing patients for curative HCV treatment. Specific Aim 3. To assess the impact of HCV co-infection on CVD risk prediction in HIV Whether established CVD risk prediction algorithms provide an accurate assessment of risk in HIV/HCV co- infected patients remains unclear, particularly among co-infected patients. We propose to assess several established algorithms in a large cohort of co-infected patients. Through innovative analyses, we will incorporate HCV as a novel CVD risk factor into risk prediction functions to attempt to improve model performance in HIV. To complete the proposed aims and maximize the number of HIV/HCV co-infected individuals, we will leverage the largest collaboration of observational HIV cohorts in North America – the North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD). This is a uniquely well-suited cohort given its large sample size, adjudicated CVD events, and rigorously maintained data. Our multidisciplinary team includes internationally regarded epidemiology and biostatistics collaborators with expertise in methods of advanced causal inference and in CVD risk prediction modeling. This timely and clinically relevant study will advance the field by generating new knowledge on the impact of HCV on CVD risk and will directly impact the long-term care of aging HIV populations.