Late Breaking: Implications of genetic diversity in muscular dystrophy therapeutic and pathophysiology



Poster Number: 210


Anushe Munir, MS, University of Pittsburgh, Marie Johnson, B.S., University of Pittsburgh, Dwi U. Kemaladewi, PhD, University of Pittsburgh

Differences in our genomes give rise to most of human diversity, including the severity of disease presentations and responses to therapeutic interventions. Yet, mouse models used to study pathophysiology and develop therapy in muscular dystrophies are based on single genetic backgrounds, failing to accurately capture the heterogeneity within the human population.
To bridge this shortcoming, we aim to evaluate the impact of genetic variation in modulating the expression of genes implicated in muscular dystrophy pathophysiology and responses to therapy. We hypothesize that genetically diverse mice can be used to model Lama2-deficient congenital muscular dystrophy (LAMA2-CMD), map genetic modifiers underlying phenotypic variations at high resolution, and improve drug developments under controlled environmental conditions.
We leverage the power of advanced intercrosses between C57BL/6J (B6) and DBA/2J (D2) strains, i.e., the BXDs, which over the years resulted in ~150 lines and ~1.8 million fully characterized SNP profiles. Specifically, we crossed several BXD strains with the LAMA2-CMD mouse model to generate genetically diverse CMD-BXD mice.
We are currently assessing a range of dystrophic presentations, including muscle architectures, nerve myelination, mobility, and hindlimb paralysis at different time points representing early to advanced disease stages. Subsequently, we will overlay the collected phenotyping data with whole-genome sequencing to map genetic regions that segregate with the enhanced/suppressed phenotypes. Finally, we will treat the CMD-BXD mice with AAV9 carrying CRISPR activation system to upregulate Lama1 and assess the efficacy and safety of this therapeutic intervention.
This study will hence generate valuable resources that reflect the human population more accurately, allowing genetic diversity to be better represented in disease mouse models.