Using large-scale gene-expression data and AI to map broken gene networks in heart disease
Transfer learning leveraging large-scale transcriptomics to map disrupted gene networks in cardiovascular disease
This project uses AI trained on vast gene-expression datasets to find the gene networks that go wrong in people with heart disease and point to new targets for treatment.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | J. David Gladstone Institutes NIH-funded |
| Lab location | 1 site (San Francisco, United States) |
| Project ID | NIH-11168894 on NIH RePORTER |
What this research studies
You should know researchers will train deep learning models on huge collections of human gene-expression data and then fine-tune those models to work with smaller heart-specific datasets. They will pair those computational network maps with human induced pluripotent stem cell models of heart cells to test which gene networks drive disease. The team aims to identify 'network-correcting' targets that could be turned into therapies addressing the root causes rather than just symptoms. If successful, the work could point to new treatments for both common and rare cardiac conditions and help design future clinical trials.
Who could benefit from this research
Good fit: People with inherited or acquired heart conditions, such as valve disease or cardiomyopathies, who are willing to donate samples or consider future network-targeted trials would be most relevant.
Not a fit: Those without a diagnosed cardiac condition or people seeking immediate clinical care should not expect direct benefit from this early-stage research.
Why it matters
Potential benefit: If successful, this work could lead to therapies that fix the underlying gene-network faults in heart disease instead of only easing symptoms.
How similar studies have performed: The investigators previously used a related network-mapping approach to discover a promising therapy for cardiac valve disease reported in Cell and Science, showing prior translational progress while applying transfer learning to heart disease is a newer advance.
Where this research is happening
San Francisco, United States
- J. David Gladstone Institutes — San Francisco, United States (Active)
Researchers
- Principal investigator: Theodoris, Christina Vicky — J. David Gladstone Institutes
- Study coordinator: Theodoris, Christina Vicky
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.