Understandable AI to find genes linked to Alzheimer’s
Interpretable machine learning methods for the analysis of Alzheimers disease genetics
Using explainable artificial intelligence to reveal how genetic differences influence Alzheimer’s risk in older adults.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Stanford University NIH-funded |
| Lab location | 1 site (Stanford, United States) |
| Project ID | NIH-11333066 on NIH RePORTER |
What this research studies
From my point of view, researchers will apply modern AI methods to large human genetic datasets to search for variants tied to late-onset Alzheimer’s disease. They plan to focus on making the AI explanations clear so scientists can see which genetic changes matter and how they interact. The work will combine whole-genome sequencing data, models that capture nonlinear effects, and methods that highlight specific contributing variants like APOE. The team will also pay attention to genetic patterns in diverse groups, including African American participants, so findings are more broadly relevant.
Who could benefit from this research
Good fit: Ideal contributors would be people aged 65 and older, including those with late-onset Alzheimer’s or older adults willing to share genetic data or biospecimens for research.
Not a fit: People younger than 65, those with non‑Alzheimer’s causes of cognitive change, or anyone seeking immediate treatment are unlikely to gain direct personal benefit from this genetics methods research.
Why it matters
Potential benefit: If successful, this could help researchers identify new genetic targets for treatments and improve genetic risk information for people at risk of late-onset Alzheimer’s.
How similar studies have performed: Machine learning has helped find genetic signals in other diseases and has been used in some Alzheimer’s genetics work, but applying interpretable AI to whole-genome Alzheimer’s data is still a developing approach.
Where this research is happening
Stanford, United States
- Stanford University — Stanford, United States (Active)
Researchers
- Principal investigator: He, Zihuai — Stanford University
- Study coordinator: He, Zihuai
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.