This administrative supplement to parent grant R01 AG062393 is submitted for consideration in response to NOT-AG-22-014, Notice of Special Interest: Administrative Supplements for HIV/AIDS and Aging Research and PA-20-272, Administrative Supplements to Existing NIH Grants and Cooperative Agreements. The prevention and management of chronic noncommunicable diseases such as cardiovascular disease (CVD) is a priority for the aging HIV population. Traditional CVD risk factors do not fully explain the increased CVD risk observed among people living with HIV (PWH), and HIV-related inflammation and immune dysregulation are thought to drive excess risk. Indeed, established CVD risk prediction functions have been demonstrated to underestimate risk in HIV. The mechanism of CVD risk in PWH is further complicated in the setting of co-infection with Hepatitis C virus (HCV), which affects cardiometabolic risk factors and confers an inflammatory state. The aims of the parent grant are to investigate the association of HCV with CVD risk among PWH. Completed analyses from Aim 1 of the parent grant indicate that HCV modifies the increasing risk of AMI with age, with a greater AMI risk per ten-year increase in age for PWH with HCV versus those without HCV. In this supplement application, we propose to use these findings to inform new analyses that extend the CVD risk prediction analyses in Aim 3 of the parent grant. The proposed supplement will employ data from the NA-ACCORD cohort and leverage existing research infrastructure to investigate the synergistic impact of HCV infection and age on CVD risk prediction in PWH, with the objective of developing a new risk prediction model for individuals living with HIV and HCV. The findings will answer critical and clinically relevant questions through the following Aims: Specific Aim 1: Assess the synergistic effect of HCV and age on CVD risk prediction in PWH. We will incorporate an interaction term for HCV and age into established CVD risk prediction functions, assessing whether inclusion of the interaction term improves the accuracy of models compared to established risk prediction functions and to a function with HCV alone among a cohort of PWH. The accuracy of newly- developed risk prediction models will be assessed via discrimination and calibration. Specific Aim 2: Develop a tailored CVD risk prediction model for PWH with HCV co-infection. We will incorporate HCV-related variables into established CVD risk prediction functions in a cohort of PWH with HCV. Traditional CVD risk factors and HIV-related factors will also be considered in model development. The accuracy of the new risk prediction function will be assessed and compared with models generated in Aim 1 with the objective of developing an optimal risk prediction function for HIV/HCV co-infected individuals.