# Genome-Wide Analyses of Health and Well-Being Phenotypes

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2020 · $780,520

## Abstract

Project Summary/Abstract
This proposal, “Genome-Wide Analyses of Health and Well-Being Phenotypes,” is a competing renewal for a
currently funded, three-year R01. The current R01 is focused on advancing the research of the Social Science
Genetic Association Consortium (SSGAC), an interdisciplinary collaboration for conducting large-scale genetic
studies of behavioral phenotypes, which is directed by three of the applicants. All of the aims of the R01 were
achieved. Its results are being widely used in health and aging-related research in social-science genetics,
medical genetics, and epidemiology.
This competing renewal proposes to continue the work of the SSGAC. In brief, we propose to:
• Conduct genetic-association studies of health and aging-relevant behavioral phenotypes in much larger
 samples that have now become available. We will complete our study of dietary intake begun under the
 current R01. In addition, we will undertake large-scale studies of additional phenotypes, including physical
 activity and self-reported general health. Each of these projects will identify genetic variants associated
 with the phenotype, analyze biological pathways that underlie these associations, and construct polygenic
scores (indexes of many genetic variants) that can have substantial predictive power for the phenotype.
• Develop a more powerful method for joint analysis of multiple phenotypes, which will be able to (a)
 estimate the fraction of genetic variants associated with some set of phenotypes but not others, and (b)
 identify genetic variants likely to be associated with some set of phenotypes but not others. The results of
 applying the method will help disentangle different mechanisms by which the genetic variants matter for
 the phenotypes and will enable the construction of more predictive polygenic scores for each phenotype.
• Apply this method to shed light on the shared and unique genetic pathways that influence educational
 attainment and (late-onset) Alzheimer's disease. This analysis will: (a) identify many new genetic variants
 associated with Alzheimer's disease; (b) generate more predictive polygenic scores for Alzheimer's disease,
 facilitating earlier diagnosis and treatment; (c) shed light on hypotheses related to the underlying
 mechanisms driving the genetic relationship between Alzheimer's disease and educational attainment; and
 (d) enable biological annotation of genetic variants identified to affect Alzheimer's risk but not educational
 attainment and which thus may operate through more direct biological pathways on disease risk.

## Key facts

- **NIH application ID:** 9971209
- **Project number:** 2R01AG042568-04A1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** Daniel J Benjamin
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $780,520
- **Award type:** 2
- **Project period:** 2015-09-01 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9971209

## Citation

> US National Institutes of Health, RePORTER application 9971209, Genome-Wide Analyses of Health and Well-Being Phenotypes (2R01AG042568-04A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9971209. Licensed CC0.

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