With over a third of persons living with HIV (PLWH) being over 50 and cardiovascular disease (CVD) occurring at a higher rate in PLWH, we are likely to witness a dramatic rise in the incidence of CVD in this population over the next decade. The underlying pathogenesis of cardiometabolic complications in PLWH has not yet been fully elucidated with the unique risk factors only partially accounting for increased CVD-related risks among PLWH. In recent years, there has been rapid growth in understanding the genetic basis for CVD in the general population;however, there is very limited data related to the impact of genetics on CVD in PLWH. The small sample size and lack of matched HIV- controls for most HIV studies, as well as the cost associated with large-scale genetic analyses, likely explain this fundamental gap in knowledge. While multiple loci previously established in the general population have also been implicated in HIV-related CVD risks, other variants may exist that interact with HIV infection. The objectives of this application are to assess if the genetic risk burden can help explain a higher risk of CVD in PLWH with exposure to antiretroviral therapy (ART) and identify therapeutic opportunities to mitigate CVD-related complications using the shared HIV/CVD molecular networks. The central hypothesis is that the increased risk of CVD complications in HIV can be at least in part explained by a burden of known and novel susceptibility loci that interact with HIV itself and/or exacerbate effects of ART. Guided by strong preliminary data and taking advantage of the large well-characterized prospective cohort recruited though the Center for AIDS Research's (CFAR) Network of Integrated Clinical Systems (CNICS) project and three independent replication cohorts, we will pursue the following specific aims: 1) Identify genetic variants associated with CVD-related traits in the setting of HIV in 5,000 PLWH and investigate differences and commonalities in the mechanisms of cardiometabolic complications between HIV+ and HIV- individuals;2) Explore whether exacerbating effects of ART on cardiovascular health can be at least in part explained by variation at genetic loci, and 3) Identify drugs compounds with overlapping therapeutic activity in HIV infection and CVD-related traits. This is the largest application of the high-throughput genotyping in PLWH, including functional variants. Using genomic and systems biology approaches, our proposed studies will be able to address the following questions: a) which biological pathways lead to cadiometabolic complications in HIV and how they compare to those detected in the general population, b) which genetic variants exacerbate or mitigate cardiometabolic risks associated with ART, and c) what are the most effective combinations of ART and CVD therapies. The proposed research is expected to advance our understanding of HIV-related pathways involved in CVD complications in PLWH and determine alternative therapeutic strategies that can help mitigate CVD risks. Ultimately, such knowledge has the potential to enhance the care and reduce the growing problem of adverse cardiometabolic outcomes in PLWH.
The investigators propose to conduct an integrative analysis of extensive clinical and genomic data to further our understanding of cardiovascular and metabolic derangements leading to an increased risk of cardiovascular disease (CVD) in HIV-infected individuals as compared to HIV-negative persons. The proposed studies will also identify networks of genes that mitigate and/or exacerbate response to antiretroviral therapy (ART) and determine the most effective combinations of ART and CVD therapies to reduce the growing problem of adverse cardiometabolic outcomes in PLWH.
|Crane, Heidi M; Paramsothy, Pathmaja; Drozd, Daniel R et al. (2017) Types of Myocardial Infarction Among Human Immunodeficiency Virus-Infected Individuals in the United States. JAMA Cardiol 2:260-267|
|Crane, H M; Heckbert, S R; Drozd, D R et al. (2014) Lessons learned from the design and implementation of myocardial infarction adjudication tailored for HIV clinical cohorts. Am J Epidemiol 179:996-1005|