Using AI to better understand lupus kidney disease
Official title: Using artificial intelligence to bridge human and murine studies of lupus nephritis progression
Funded at University of Chicago · NIH-11170635 · Data updated 2026-11-12
This project uses advanced computer tools to compare kidney tissue from people and mice with lupus, hoping to find better ways to predict and treat the disease.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Chicago NIH-funded |
| Lab location | 1 site (Chicago, United States) |
| Project start | August 15, 2024 |
| Project end | July 31, 2029 |
| Funding year | 2025 |
| Award (this year) | $801,945 |
| NIH project number | 5R01AI180222-02 |
| Project ID | NIH-11170635 on NIH RePORTER |
Who could benefit from this research
✓Could help
This foundational research does not directly recruit patients but aims to benefit those living with lupus nephritis by improving future diagnostic and treatment strategies.
✕Less likely to help
Patients not affected by lupus nephritis would not directly benefit from this specific research.
What this research studies
Lupus nephritis is a serious kidney condition that affects many people with lupus, and current treatments don't always work well. It's hard to know which patients will respond to treatment or why some get worse. This project uses cutting-edge artificial intelligence and detailed imaging to look closely at kidney tissue from both human patients and animal models. By comparing these tissues, researchers hope to uncover specific disease patterns that are shared between humans and mice. This deeper understanding could help us predict how the disease will progress and find more effective treatments.
Why it matters
Potential benefit: If successful, this work could lead to new ways to predict how lupus nephritis will progress and help doctors choose more effective treatments for patients.
How similar studies have gone: While AI is increasingly used in medical research, this specific approach of using high-dimensional confocal microscopy and AI to bridge human and murine lupus nephritis mechanisms is innovative.
Where this research is happening
-
University of Chicago
Chicago, United States Active
Researchers
- Principal investigator: Clark, Marcus Ramsay — University of Chicago
- Study coordinator: Clark, Marcus Ramsay
Related research
Other NIH-funded projects on the same topics.
-
Glycoprotein urine markers that signal lupus nephritis treatment response
A novel test uses urine glycoprotein patterns to show how well lupus nephritis is responding to standard treatment.
-
PTPRS and lupus nephritis: a new target to reduce kidney damage in lupus
Aims to understand how PTPRS contributes to kidney inflammation and scarring in lupus nephritis and explore targeting it to help patients.
-
Sodium’s effect on kidney B cells in lupus kidney disease
This grant explores how high sodium in the kidneys affects B cells in lupus nephritis and whether blocking a key cellular pump could reduce kidney damage.
-
Oral CD11b Activator for Lupus Nephritis
A new oral CD11b activating drug is being explored to help people with lupus nephritis by targeting immune pathways that cause kidney inflammation.
-
Objective classification of lupus nephritis using computer vision
A new computer vision tool uses deep learning to classify lupus nephritis from kidney tissue images to help doctors predict outcomes for patients with lupus.
-
AI-powered look at lupus nephritis in humans and mice
Researchers will use artificial intelligence to compare kidney tissue from people with lupus nephritis to tissue from mouse models, aiming to understand why treatments work differently in humans.
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.