Predicting future alcohol problems from genetics, brain signals, and life history
Predicting AUD development, risk and resilience phenotypes through integration of multi-modal COGA data
Researchers will use brain recordings, genetic markers, and questionnaires to spot people at higher risk of developing alcohol use disorder.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Suny Downstate Medical Center NIH-funded |
| Lab location | 1 site (Brooklyn, United States) |
| Project ID | NIH-11127771 on NIH RePORTER |
What this research studies
This project looks at decades of information collected from people like me in the COGA group, including EEG brain recordings, genetic tests, and detailed questionnaires about behavior and environment. Researchers will apply machine learning to combine these different types of data and search for patterns that predict who goes on to develop alcohol use disorder and who stays resilient. The work includes people of European and African American backgrounds across ages roughly 8 to 68 and uses long-term follow-up to find early warning signs. This project analyzes existing COGA data and does not test new medications or interventions.
Who could benefit from this research
Good fit: People most relevant are adolescents and adults (including African American and European American individuals) with personal or family histories of problematic alcohol use or who can provide genetic or EEG information.
Not a fit: People already well into long-term recovery or those without accessible genetic or brain-recording data are unlikely to receive direct benefit from this data-analysis project.
Why it matters
Potential benefit: If successful, the work could help identify people at risk earlier so they can get prevention, monitoring, or support before serious problems start.
How similar studies have performed: Previous studies have used machine learning to tell apart people with current alcohol use disorder and controls, but using multimodal data to predict future development is less tested and relatively novel.
Where this research is happening
Brooklyn, United States
- Suny Downstate Medical Center — Brooklyn, United States (Active)
Researchers
- Principal investigator: Kinreich, Sivan — Suny Downstate Medical Center
- Study coordinator: Kinreich, Sivan
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.