Genetic links between sleep apnea, insomnia, and other health conditions

Genetic Epidemiology of Sleep Apnea and Comorbidities in Biobanks

NIH-funded research Brigham and Women's Hospital · NIH-11176255

Researchers will use large medical databases, sleep test results, and genetic data to find patterns that explain different types of sleep apnea and insomnia for people with sleep problems.

Quick facts

Grant typeR01 grant
Study typeNIH-funded research
Funding institutionBrigham and Women's Hospital NIH-funded
Lab location1 site (Boston, United States)
Project IDNIH-11176255 on NIH RePORTER

What this research studies

This project combines health system biobank data with research sleep testing (polysomnography) and advanced machine learning to define more precise sleep apnea and insomnia subtypes. The team will apply natural language processing to medical records to better identify cases and increase sample size, aiming for over 11 times the participants of prior genetic studies. They will search for genetic variants, build polygenic risk scores, and link genetic subtypes to clinical outcomes and physiological mechanisms. Findings are intended to reduce how mixed-up current sleep diagnoses are and help guide more personalized care.

Who could benefit from this research

Good fit: People with diagnosed obstructive sleep apnea or chronic insomnia, or individuals willing to share their health records and genetic samples or attend research sleep testing, would be most relevant to this work.

Not a fit: People without sleep disorders or those who cannot or will not provide access to medical records or genetic samples are unlikely to see direct benefit from this genetics-focused project.

Why it matters

Potential benefit: If successful, this work could enable more accurate diagnosis, personalized risk scores, and better-targeted treatments for people with sleep apnea or insomnia.

How similar studies have performed: Previous genetic studies have identified some risk variants for sleep disorders but were much smaller, and this larger, machine-learning-driven approach is novel and designed to expand on those findings.

Where this research is happening

Boston, United States

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Conditions Blood DiseasesCardiac DiseasesCardiac DisordersChronic Disease
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.