# Pathogenesis and treatment of sporadic Inclusion Body Myositis in mouse models.

> **NIH NIH R01** · JOHNS HOPKINS UNIVERSITY · 2020 · $413,993

## Abstract

PROJECT SUMMARY
Sporadic Inclusion Body Myositis (IBM) is the most common muscle disease in adults over age
50, yet the cause of the disease is unknown, and there are no treatments. To better
understand the pathogenesis of this disease and to identify therapeutic targets, we have
developed two novel mouse models. First, by implanting human IBM biopsy tissue into
immunocompromised mice, we have developed a human xenograft model that recapitulates
key features of the disease including atrophy, endomysial inflammation, protein aggregates,
and TDP-43 pathology. Second, by deleting TDP-43 specifically in skeletal muscle of mice, we
replicated key IBM features including atrophy, rimmed vacuoles and protein aggregates. The
goal of this proposal is to better understand the pathogenesis of IBM using these two mouse
models and to validate therapeutic targets.
We believe we have created the first clinically relevant mouse models of sporadic IBM. Such
models have the potential to be useful for IBM studies including mechanistic studies and target
validation. This project will independently and rigorously test both the role of the inflammatory
response and the role of compromised TDP-43 splicing repression in IBM pathogenesis.

## Key facts

- **NIH application ID:** 9865653
- **Project number:** 1R01AR076390-01
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Thomas E. Lloyd
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $413,993
- **Award type:** 1
- **Project period:** 2020-06-22 → 2025-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9865653

## Citation

> US National Institutes of Health, RePORTER application 9865653, Pathogenesis and treatment of sporadic Inclusion Body Myositis in mouse models. (1R01AR076390-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9865653. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*