# Human Longevity Associations, Trajectories and Predictions

> **NIH NIH U19** · TRANSLATIONAL GENOMICS RESEARCH INST · 2024 · $921,553

## Abstract

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.

## Key facts

- **NIH application ID:** 11022976
- **Project number:** 2U19AG023122-16
- **Recipient organization:** TRANSLATIONAL GENOMICS RESEARCH INST
- **Principal Investigator:** JODI A LAPIDUS
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $921,553
- **Award type:** 2
- **Project period:** 2004-09-30 → 2029-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11022976

## Citation

> US National Institutes of Health, RePORTER application 11022976, Human Longevity Associations, Trajectories and Predictions (2U19AG023122-16). Retrieved via AI Analytics 2026-05-29 from https://api.ai-analytics.org/grant/nih/11022976. Licensed CC0.

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