AI to predict brain aging and Alzheimer's from genetic and cell-level data
Predicting Phenotype by Deep Learning Heterogeneous Multi-Omics Data
An AI system will learn patterns across genes, single-cell data, and medical records to better predict Alzheimer's risk and brain aging for people with or at risk of Alzheimer's.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Texas Hlth Sci Ctr Houston NIH-funded |
| Lab location | 1 site (Houston, United States) |
| Project ID | NIH-11246813 on NIH RePORTER |
What this research studies
This project will combine many types of human data — genetic, epigenetic, transcriptomic, single-cell profiles, and clinical records — and use deep learning to find hidden patterns linked to brain aging and Alzheimer's. The team will build a multi-scale AI framework called MICA-Brain to link molecules, cell types, tissues, and time points so results reflect real brain biology. The goal is to identify cell-type specific regulatory modules and biomarkers that relate to cognitive function and disease subtypes. Results will come from analyzing large, existing human datasets and integrating them with advanced computational models.
Who could benefit from this research
Good fit: Ideal candidates are older adults with Alzheimer's disease, mild cognitive impairment, or people at higher risk who can contribute genetic, blood, or brain-related data.
Not a fit: People without relevant genetic or omics data, those with non-Alzheimer forms of dementia, or children are unlikely to benefit directly from this project.
Why it matters
Potential benefit: If successful, this work could improve early detection of those at higher Alzheimer's risk and point to new targets for treatments tailored by biological subtype.
How similar studies have performed: AI and omics approaches have shown promise in pieces (like genetics or imaging), but combining heterogeneous multi-omics across cell types and scales at this level is relatively new.
Where this research is happening
Houston, United States
- University of Texas Hlth Sci Ctr Houston — Houston, United States (Active)
Researchers
- Principal investigator: Zhao, Zhongming — University of Texas Hlth Sci Ctr Houston
- Study coordinator: Zhao, Zhongming
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.