Predicting who may develop endometriosis and related long-term health problems
Integrative risk modeling for early prediction of endometriosis and its long-term health outcomes
This project will build tools that combine genetic, clinical, and lifestyle information to predict which people are likely to develop endometriosis and later health issues.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Pennsylvania NIH-funded |
| Lab location | 1 site (Philadelphia, United States) |
| Project ID | NIH-11308286 on NIH RePORTER |
What this research studies
From a patient's point of view, researchers will pull together medical records, genetic information, and environmental and inflammatory markers to create risk models that spot people at higher risk for endometriosis. They will train those models on large clinical datasets and biological measurements so the tools can recognize different ways endometriosis shows up. The goal is non-invasive screening that could flag people earlier, before problems become severe. The work will look at both reproductive-age symptoms and long-term health outcomes that can follow endometriosis.
Who could benefit from this research
Good fit: People who are reproductive-age or have pelvic pain, painful periods, fertility problems, or a family history of endometriosis and who can share medical records or genetic information would be the most relevant candidates.
Not a fit: People who already have a confirmed, long-standing endometriosis diagnosis with established irreversible complications or those unwilling to share health or genetic data may not directly benefit from the predictive tool.
Why it matters
Potential benefit: If successful, this could lead to earlier diagnosis, more personalized monitoring, and steps to prevent or reduce long-term complications.
How similar studies have performed: Prior research has linked genes, inflammation, and environmental factors to endometriosis and some early models show promise, but a widely used, reliable early-prediction tool does not yet exist.
Where this research is happening
Philadelphia, United States
- University of Pennsylvania — Philadelphia, United States (Active)
Researchers
- Principal investigator: Verma, Shefali Setia — University of Pennsylvania
- Study coordinator: Verma, Shefali Setia
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.