Using genetic and brain molecular data to find genes and patient differences in Alzheimer's
Multiomics data integration methods to discover putative causal variants, genes and patient heterogeneity for Alzheimers disease
Using DNA and multiple types of brain molecular data, researchers aim to pinpoint genes and patient subgroups that drive late-onset Alzheimer's disease.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Columbia University Health Sciences NIH-funded |
| Lab location | 1 site (New York, United States) |
| Project ID | NIH-11231233 on NIH RePORTER |
What this research studies
From a patient's point of view, this project brings together many kinds of biological data — DNA changes, gene activity, splicing, methylation, histone marks, and proteins — to find which genetic changes truly cause Alzheimer's and why people with the disease are different from each other. The team develops new statistical models that combine data from large population studies, family-based studies, and brain tissue samples to highlight likely causal variants and affected genes. They will apply these methods to existing and newly assembled multiomics datasets from diverse ancestry groups. The goal is to reveal molecular pathways and patient subtypes that could guide future tests or treatments.
Who could benefit from this research
Good fit: Ideal candidates include people with late-onset Alzheimer's, family members from affected families, or individuals whose genetic or brain molecular data are already in research datasets and who can contribute samples if requested.
Not a fit: People without available genetic or molecular data, those with non-Alzheimer dementias, or those seeking an immediate treatment benefit are unlikely to gain direct benefit from participating.
Why it matters
Potential benefit: If successful, this work could reveal specific genes and molecular processes to target for diagnostics or therapies and help tailor approaches to different groups of Alzheimer's patients.
How similar studies have performed: Genome-wide studies have found many Alzheimer's risk regions, but combining multiple molecular layers with new integrative models is a newer approach intended to move from risk signals to likely causal genes and patient subtypes.
Where this research is happening
New York, United States
- Columbia University Health Sciences — New York, United States (Active)
Researchers
- Principal investigator: Wang, Gao — Columbia University Health Sciences
- Study coordinator: Wang, Gao
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.