R01HL153805

Genetic Epidemiology of Sleep Apnea and Comorbidities in Biobanks - Abstract

Sleep apnea (SA) and insomnia are the two most common sleep disorders, and both contribute individually and jointly to the risk of cardiopulmonary, metabolic, and psychiatric diseases. Despite their high prevalence, treatments for SA and insomnia remain suboptimal.

SA and insomnia are thought to be comprised of distinct subtypes, which remain poorly defined and may contribute to differing risks for health outcomes. Our goal is to use machine learning to apply precise phenotyping to biobanks to identify the genetic bases of SA and insomnia and discover SA and insomnia subtypes based on genetics and comorbidities in order to reduce phenotype heterogeneity, guide patient stratification, and aid in the discovery of more personalized treatments.

Our approach is to combine health care system biobank data with research polysomnography (PSG) to achieve statistical power to discover genetic variants for SA and insomnia-related phenotypes and characterize their associated clinical outcomes and endophenotypes (physiological mechanisms). We will use advanced natural language processing (NLP) methods to substantially improve the accuracy of SA and insomnia phenotyping.

Our anticipated sample size will be >11-fold larger than prior genetic studies of SA, providing the necessary statistical power for genetic discovery. Polygenic risk scores derived from our results can be used to quantify sleep disorder risk, even among those without sleep phenotypes. Machine learning methods can identify predictors of diagnosis-clustered patient groups contained within the medical record. Precision deeply-phenotyped PSG data (e.g., hypoxic burden) can characterize endophenotypes at associated genetic loci using genetic localization.

We will derive advanced SA and insomnia phenotypes robust to demographic differences across biobank sites, perform the largest genetic analysis of validated SA and insomnia phenotypes to date, characterize novel loci, and study associations with clinical diagnosis data to improve patient classification in three biobanks. We will explore sex-specific associations and validate lead genetic associations in two biobanks.

Our specific aims are:
1) To construct advanced SA and insomnia phenotyping algorithms across diverse demographic groups and sites;
2) To identify and characterize the genetic associations with SA and insomnia; and
3) To identify and characterize distinct SA and insomnia patient subgroups based on related comorbidity profiles.

The proposed project has a goal of improving the treatment of heart, lung, blood, and sleep disorders by potentially resolving disease heterogeneity, discovering novel genetic associations with sleep disorders, and helping to clarify the overlap of SA and insomnia with cardiopulmonary, metabolic, and psychiatric disease.

Brigham & Womens Hospital

THE NATIONAL CENTER ON SLEEP DISORDERS RESEARCH (NCSDR) SUPPORTS RESEARCH AND RESEARCH TRAINING RELATED TO SLEEP DISORDERED BREATHING, AND THE FUNDAMENTAL FUNCTIONS OF SLEEP AND CIRCADIAN RHYTHMS. THE CENTER ALSO STEWARDS SEVERAL FORUMS THAT FACILITATE THE COORDINATION OF SLEEP RESEARCH ACROSS NIH, OTHER FEDERAL AGENCIES AND OUTSIDE ORGANIZATIONS, INCLUDING THE SLEEP DISORDERS RESEARCH ADVISORY BOARD AND AN NIH-WIDE SLEEP RESEARCH COORDINATING COMMITTEE. THE CENTER ALSO PARTICIPATES IN THE TRANSLATION OF NEW SLEEP RESEARCH FINDINGS FOR DISSEMINATION TO HEALTH CARE PROFESSIONALS AND THE PUBLIC. SMALL BUSINESS INNOVATION RESEARCH (SBIR) PROGRAM: TO STIMULATE TECHNOLOGICAL INNOVATION, USE SMALL BUSINESS TO MEET FEDERAL RESEARCH AND DEVELOPMENT NEEDS, FOSTER AND ENCOURAGE PARTICIPATION IN INNOVATION AND ENTREPRENEURSHIP BY SOCIALLY AND ECONOMICALLY DISADVANTAGED PERSONS, AND INCREASE PRIVATE-SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT FUNDING. SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAM: TO STIMULATE TECHNOLOGICAL INNOVATION, FOSTER TECHNOLOGY TRANSFER THROUGH COOPERATIVE R&D BETWEEN SMALL BUSINESSES AND RESEARCH INSTITUTIONS, AND INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL R&D.

93.837 - Cardiovascular Diseases Research

National Heart Lung and Blood Institute (NHLBI) [HHS - NIH]

Boston, Massachusetts 021156110 United States

Single Zip Code

NIH Research Project Grant (Parent R01 Clinical Trial Not Allowed) (PA-20-185)

Amendment Since initial award the total obligations have increased 360% from $814,166 to $3,744,652.