# Using polygenic risk scores and omics to study how suboptimal sleep accelerates cognitive aging in diverse populations

> **NIH NIH R01** · BETH ISRAEL DEACONESS MEDICAL CENTER · 2024 · $872,809

## Abstract

PROJECT SUMMARY
Suboptimal sleep, characterized by phenotypes such as insomnia, short sleep, and obstructive sleep apnea, is
associated with reduced cognitive performance and increased cognitive decline and dementia risk. There is
strong evidence of sleep disparities between race/ethnic and gender minorities, potentially relating to
downstream disparities in cognitive aging. However, the mechanisms by which sleep phenotypes accelerate
cognitive aging are not well understood. Identifying specific biological pathways and biomarkers of sleep
phenotypes will enable unconfounded quantification of the effect of sleep phenotypes on cognitive aging, risk
stratification, and development of potential intervention targets.
We will establish a collaboration across three longitudinal cohort studies representing the diverse U.S.
population: the Atherosclerosis Risk In Communities (ARIC) study, the Hispanic Community Health
Study/Study of Latinos (HCHS/SOL), and the Multi-Ethnic Study of Atherosclerosis (MESA), to study how
suboptimal sleep accelerates cognitive aging. We will study the associations of sleep disorders (insomnia,
short and long sleep, and obstructive sleep apnea) with harmonized, global measures of cognitive aging. We
will develop polygenic risk scores (PRSs) for sleep phenotypes using novel methodology, that will appropriately
account for heterogeneous genetic ancestry of study individuals, and identify sleep phenotypes that are
genetically strongly associated with cognitive aging based on PRSs. We will use omics (metabolomics and
proteomics) to explain biological pathways underlying the sleep-cognitive aging associations. We expect that
we will identify biomarkers and mediators of the sleep-related effects on cognitive aging, and using Mendelian
Randomization analyses, we will be able to untangle some of the directional associations. Finally, we will study
risk prediction models for cognitive aging that use sleep-related measures. We will study whether the identified
associations and risk prediction models generalize to AD-specific phenotypes in datasets of two cohorts from
the Rush Alzheimer's Disease Center.
This work will result in the identification of omics biomarkers that measure and mediate the genetic risk of
sleep phenotypes on cognitive aging, and new risk models for cognitive aging based on PRSs and omics.
Importantly, our study will include individuals from diverse U.S. populations, and our methodology will ensure
that the findings and models are useful across populations. This work will guide precision medicine initiatives to
improve cognitive health in aging individuals from diverse genetic backgrounds.

## Key facts

- **NIH application ID:** 10931441
- **Project number:** 5R01AG080598-02
- **Recipient organization:** BETH ISRAEL DEACONESS MEDICAL CENTER
- **Principal Investigator:** Tamar Sofer
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $872,809
- **Award type:** 5
- **Project period:** 2023-09-20 → 2028-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10931441

## Citation

> US National Institutes of Health, RePORTER application 10931441, Using polygenic risk scores and omics to study how suboptimal sleep accelerates cognitive aging in diverse populations (5R01AG080598-02). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10931441. Licensed CC0.

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