# Leveraging Correlated Traits to Identify Genetic Associations with Sleep Disordered Breathing

> **NIH NIH R21** · BRIGHAM AND WOMEN'S HOSPITAL · 2020 · $134,250

## Abstract

PROJECT SUMMARY/ABSTRACT
Sleep Disordered Breathing (SDB) is a complex disorder that is common in the population and is associated
with significant adverse health outcomes. Despite considerable heritability, elucidation of the genetic basis of
this disorder has been limited by relatively small samples - due to under diagnosis and under reporting of
SDB, and paucity of overnight measurements of SDB traits - and potential heterogeneity. Given that SDB is
physiologically and metabolically related to other traits, there is an opportunity to increase power in the
relatively-small genetic association studies of SDB traits by leveraging large association studies in correlated
traits. Using correlated traits will also be useful for identifying SDB mechanisms captured by these traits, as
a first step in explaining, at the genetic level, the heterogeneity of SDB. Therefore, we propose to utilize
genetic associations for traits that correlate with SDB to dissect genetically-determined mechanisms of SDB,
that are attributable to different molecular/physiological pathways, and are captured by different traits.
 We will take two approaches. First, we will study the genetic correlations between multiple
cardiopulmonary and metabolic traits and SDB traits in the largest cohort with overnight measurements of
SDB traits, the Hispanic Community Health Study/Study of Latinos. Based on these correlations, we will
identify genetic loci associated with SDB from those that were previously implicated with the correlated traits.
Second, we will study and implement approaches based on Polygenic Risk Scores (PRSs) in multiple,
diverse, NHLBI cohorts. We will use previously known associations to construct PRSs for the detected
correlated traits, and study their association with SDB traits. We will implement causal analyses using
recently proposed methodologies of Mendelian Randomization in the presence of pleiotropy to study whether
traits such as BMI, blood pressure, dyslipidemia, and insulin resistance are causally associated with SDB.
These analyses will reveal specific genetically-determined mechanisms of SDB, setting the foundation for
the ultimate goal of identifying subtypes of the disorder and consequently developing personalized therapies

## Key facts

- **NIH application ID:** 9999643
- **Project number:** 5R21HL145425-02
- **Recipient organization:** BRIGHAM AND WOMEN'S HOSPITAL
- **Principal Investigator:** Tamar Sofer
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $134,250
- **Award type:** 5
- **Project period:** 2019-09-01 → 2022-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9999643

## Citation

> US National Institutes of Health, RePORTER application 9999643, Leveraging Correlated Traits to Identify Genetic Associations with Sleep Disordered Breathing (5R21HL145425-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9999643. Licensed CC0.

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