Using long-term metabolic patterns to predict diabetes complications
Predicting complications of diabetes with longitudinal metabolic trajectories
This project uses long-term health measurements and machine learning to spot which people with adult-onset (type 2) diabetes may develop nerve or kidney problems.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Henry Ford Health + Michigan State University Health Sciences NIH-funded |
| Lab location | 1 site (East Lansing, United States) |
| Project ID | NIH-11291820 on NIH RePORTER |
What this research studies
This work looks at how your blood sugar, lipids, weight, and other metabolic measures change over years and uses computer algorithms to find patterns linked to nerve damage and chronic kidney disease. The team will analyze repeated lab results and health records to map each person's metabolic trajectory over time. Machine learning models will be trained to identify who is moving toward complications and which time periods or rates of change matter most. The goal is to help clinicians identify higher-risk patients earlier so prevention could be timed better.
Who could benefit from this research
Good fit: Adults with adult-onset (type 2) diabetes who have multiple years of lab measurements or electronic health records — including participants from the communities the project partners with — are the ideal candidates.
Not a fit: People without regular historical metabolic data, children, those with type 1 diabetes, or patients who already have very advanced kidney or nerve damage may not benefit from the predictive models.
Why it matters
Potential benefit: If successful, the approach could let doctors identify people at higher risk earlier and target treatments to prevent or delay nerve and kidney damage.
How similar studies have performed: Previous research has used metabolic markers and machine learning for diabetes outcomes, but applying long-term metabolic trajectory patterns specifically to predict neuropathy and chronic kidney disease is relatively new.
Where this research is happening
East Lansing, United States
- Henry Ford Health + Michigan State University Health Sciences — East Lansing, United States (Active)
Researchers
- Principal investigator: Reynolds, Evan L — Henry Ford Health + Michigan State University Health Sciences
- Study coordinator: Reynolds, Evan L
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.