Finding ways to diagnose light chain amyloidosis earlier
Official title: Early diagnosis of light chain amyloidosis
Funded at Medical College of Wisconsin · NIH-11011349 · Data updated 2026-11-12
This study is looking to help doctors spot light chain amyloidosis earlier, especially in Black individuals who might not get diagnosed as quickly, by using smart technology to find patterns in earlier health issues that could signal the disease.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Medical College of Wisconsin NIH-funded |
| Lab location | 1 site (Milwaukee, United States) |
| Project start | February 1, 2023 |
| Project end | January 31, 2028 |
| Funding year | 2025 |
| Award (this year) | $273,000 |
| NIH project number | 5R01HL166339-03 |
| Project ID | NIH-11011349 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research include individuals who are at risk for light chain amyloidosis, particularly those with precursor conditions like monoclonal gammopathy or those from the Black population.
✕Less likely to help
Patients who have already been diagnosed with advanced light chain amyloidosis may not benefit directly from this research.
What this research studies
This research focuses on improving the early diagnosis of light chain amyloidosis, a serious blood disorder that can lead to heart failure and other organ dysfunction. The team will analyze patterns of precursor diagnoses that often occur before a patient is diagnosed with AL amyloidosis, particularly in Black individuals who may be underdiagnosed. By using advanced Bayesian machine learning algorithms, the researchers aim to develop an alert system that helps doctors recognize the signs of this disease sooner. This could lead to timely interventions and better patient outcomes.
Why it matters
Potential benefit: If successful, this research could significantly reduce the time to diagnosis for patients with light chain amyloidosis, potentially improving survival rates and quality of life.
How similar studies have gone: Other research has shown promise in using machine learning approaches for early diagnosis of various conditions, suggesting that this methodology could be effective for light chain amyloidosis as well.
Where this research is happening
-
Medical College of Wisconsin
Milwaukee, United States Active
Researchers
- Principal investigator: D'souza, Anita — Medical College of Wisconsin
- Study coordinator: D'souza, Anita
Related research
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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.