Chronic infection of HIV and its treatment with antiretrovirals have impacted the neurobehavioral and psychosocial functioning and resulted in complicated profiles of central nervous system. In order to understand and analyze these, advanced statistical approaches and larger integrated datasets are required for analyzing interactions among the multidimensional and multidisciplinary data. Furthermore, these approaches need to apply both the baseline and longitudinal data sets to predict the risk and progression of neuropathology, neurobehavioral and neuropsychological consequences for the identification and development of novel preventative and therapeutic interventions. In this R03 application we propose to do secondary analyses of already collected diverse HIV-associated data from well-studied and well-characterized CHARTER (CNS HIV Anti-Retroviral Therapy Effects Research) cohort by integrating and organizing these data for elucidating their complex interactions (aim 1) and develop predictive quantitative model (aim 2) that can identify subjects who are at greater risk for adverse neurobehavioral and/or psychosocial outcomes as a consequence of HIV and its treatments. We propose to focus on complement activation pathway - a specific innate immune response mechanism that is implicated in several neurodegenerative and neuroinflammatory diseases and it also mounts a critical anti-HIV response in peripheral blood and CNS. All three complement activation pathways, namely classical pathway through C1q, alternate pathway through HIV envelope proteins;and mannose binding lectin- mediated pathway activated by the MBL binding to the mannose residues on HIV gp120 or gp41 proteins;potentially interact with HIV.
The aim of this proposal is to maximize the full value of previously collected data from CHARTER cohort as well as ongoing data collection to enhance our understanding of etiology and trajectories of HIV-associated neurobehavioral and neuropsychosocial consequences and to help identify novel markers for effective prevention and treatment. We propose to integrate and analyze diverse complement activation pathway genetics, inflammatory response, virologic and immunologic and neuropsychological data and brain imaging records to develop quantitative predictive models to identify subjects at greater risk for adverse neurocognitive outcomes as a consequence of HIV infection and antiretroviral treatment at the time of enrollment and in the longitudinal CHARTER cohort. The secondary analysis and pilot predictive modeling developed form these studies will be further tested for larger number of genes and in collaboration with larger cohorts such as Multicenter AIDS Cohort Study (MACS). Integration and analyses of multi-disciplinary data will better inform the predictability and management of HIV-associated neurocognitive disorders.
Proposed studies will help to understand complex interactions between diverse multi-disciplinary HIV- associated data for the development of quantitative predictive models to identify subjects at greater risk for adverse neurocognitive outcomes as a consequence of HIV infection and antiretroviral treatment. Thus, integration and analyses of multi-disciplinary data will better inform the predictability and management of HIV- associated neurocognitive disorders.