Multiomic characterization of disease progression in mice lacking dystrophin.
Mirko SignorelliRoula TsonakaAnnemieke M Aartsma-RusPietro SpitaliPublished in: PloS one (2023)
Duchenne muscular dystrophy (DMD) is caused by genetic mutations leading to lack of dystrophin in skeletal muscle. A better understanding of how objective biomarkers for DMD vary across subjects and over time is needed to model disease progression and response to therapy more effectively, both in pre-clinical and clinical research. We present an in-depth characterization of disease progression in 3 murine models of DMD by multiomic analysis of longitudinal trajectories between 6 and 30 weeks of age. Integration of RNA-seq, mass spectrometry-based metabolomic and lipidomic data obtained in muscle and blood samples by Multi-Omics Factor Analysis (MOFA) led to the identification of 8 latent factors that explained 78.8% of the variance in the multiomic dataset. Latent factors could discriminate dystrophic and healthy mice, as well as different time-points. MOFA enabled to connect the gene expression signature in dystrophic muscles, characterized by pro-fibrotic and energy metabolism alterations, to inflammation and lipid signatures in blood. Our results show that omic observations in blood can be directly related to skeletal muscle pathology in dystrophic muscle.
Keyphrases
- duchenne muscular dystrophy
- skeletal muscle
- rna seq
- single cell
- gene expression
- insulin resistance
- muscular dystrophy
- mass spectrometry
- high fat diet induced
- oxidative stress
- genome wide
- dna methylation
- metabolic syndrome
- optical coherence tomography
- liquid chromatography
- depressive symptoms
- bone marrow
- idiopathic pulmonary fibrosis
- fatty acid
- adipose tissue
- big data
- stem cells
- anti inflammatory
- gas chromatography
- smoking cessation