Human Longevity Associations, Trajectories and Predictions

Project Summary. Project 1: Longevity Association Contexts, Trajectories and Predictions Understanding the multifactorial nature of human longevity and aging-related outcomes is crucial for advancing geriatric research and optimizing healthspan. Large-scale genomic, proteomic, and metabolomic studies have identified numerous biomarkers related to age-associated diseases and longevity. However, the influence of sex, genetic diversity, and environmental factors on the predictive value of these biomarkers remains underexplored, particularly in the context of diverse populations. Project 1 (P1) of the Longevity Consortium (LC) seeks to utilize robust integrated approaches to evaluate the mechanistic underpinnings of the predictive relationships between biologic factors and aging-related outcomes, their context dependence, and their relevance to longevity and healthspan separately from the reflection of age, thus addressing Objective 1 of the RFA. P1 will develop and implement a combination of harmonization schemes, statistical analyses, and machine learning techniques in collaboration with other Projects and the Integrative Analysis Core (IAC) through these major activities: 1. Expand the harmonized LC legacy data to include genomics, longitudinal health assessments and chronic condition diagnoses, as well as updated mortality information by utilizing the NIA-LINKAGE program along with data from the Centers for Medicare and Medicaid Services (CMS). 2. Characterize the context-dependency (e.g., sex and genetic background) of the association of factors with longevity and age-related health trajectories. 3. Access additional relevant data sets, including the Health and Retirement Study (HRS), Arivale study, Young Finns Study (YFS), Danish Health Registry (DHS), UK Biobank (UKB), and Study of Muscle, Mobility and Aging (SOMMA) to expand the legacy LC studies and generalize the findings to more diverse populations. We will endeavor to harmonize data across studies as possible, and/or collaborate with international cohort curators on validation studies. 4. Develop and apply methods to build multicomponent predictive models of longevity, aging trajectories and other age-related phenotypes. 5. Assess the performance and utility of the models in different contexts and populations. As a key component of the highly integrated Longevity Consortium, P1 will participate in the exchange and assessment of newly discovered longevity-related factors, variants and/or signatures and determine the nature of their associations with longevity phenotypes, aging trajectories or health decline (frailty). These integrated activities will enable the ultimate goal of LC, which is to identify and develop drug targets, biomarkers, and predictive models of longevity and assess their translational potential.