HeartShare DeCODE-HF: A data hub to link omics, deep phenotyping, and EHRs for heart failure subtypes
Official title: HeartShare DeCODE-HF: Data translation center to Combine Omics, Deep phenotyping, and Electronic health records for Heart Failure subtypes and treatment targets
Funded at Northwestern University · NIH-11530381 · Data updated 2026-11-12
A data-sharing center is being created to combine genetics and clinical data from many people with heart failure to help identify different subtypes and possible treatment targets.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Northwestern University NIH-funded |
| Lab location | 1 site (Chicago, United States) |
| Project start | September 13, 2021 |
| Project end | December 31, 2027 |
| Funding year | 2026 |
| Award (this year) | $2,067,790 |
| NIH project number | 3U54HL160273-05S1 |
| Project ID | NIH-11530381 on NIH RePORTER |
Who could benefit from this research
✓Could help
Individuals with or at risk for heart failure, particularly HFpEF, who are or could be enrolled in the HeartShare program and related registries.
✕Less likely to help
Participants not connected to the HeartShare resources or those outside the study networks may not directly benefit.
What this research studies
This project builds a centralized resource that links deep phenotyping, multi-omics data, and electronic health records for people with heart failure. It brings together multiple centers, harmonizes existing datasets, and provides scalable data sharing to researchers. Patients contribute biospecimens and health information so that scientists can uncover subtypes of heart failure and potential therapies. The effort relies on robust data infrastructure, core laboratory analyses, and adjudicated clinical events to enable precision insights.
Why it matters
Potential benefit: If successful, patients with heart failure could benefit from more precise subtype identification and targeted therapies in the future.
How similar studies have gone: Previous large-scale heart failure consortia have shown that integrated data platforms can reveal meaningful disease subtypes and targets.
Where this research is happening
-
Northwestern University
Chicago, United States Active
Researchers
- Principal investigator: Shah, Sanjiv J — Northwestern University
- Study coordinator: Shah, Sanjiv J
Related research
Other NIH-funded projects on the same topics.
-
AI-supported heart failure diagnosis and management in Rwanda
Aiming to help people with suspected heart failure in Rwanda get faster, more accurate diagnoses and better care using AI-guided ultrasound and care protocols.
-
AI-assisted heart failure diagnosis in Rwanda using focused ultrasound
An NIH-funded project will test whether AI-enhanced, easy-to-use heart ultrasound can help non-experts diagnose and manage heart failure in Rwanda.
-
HF endotypes in heart failure using ethical multi-modal AI and molecular data
A patient-friendly project that uses advanced AI and multiple kinds of health data to identify distinct heart failure subtypes that could guide personalized care.
-
Triple gene therapy approach to heal the heart after a heart attack
A new therapy combines three genetic approaches delivered by a virus to help the heart heal after a heart attack.
-
Digital-first heart failure care delivery in Uganda
A targeted program in Uganda tests a digital care plan to help people with heart failure manage their symptoms at home.
-
Digital-first heart failure care delivery in Uganda
A study to test digital self-care tools to help people with heart failure in Uganda manage symptoms and stay healthier.
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.