G.P.20 Transcriptome profiling identifies key regulators of molecular pathogenesis in collagen VI myopathies

Abstract

Ullrich congenital muscular dystrophy (UCMD) and Bethlem myopathy (BM) are inherited disorders of collagen VI characterized by progressive muscle weakness and a combination of joint hyperlaxity and joint contractures. Collagen VI is present at the interface of the basement membrane and the extracellular matrix where it plays an important role in muscle maintenance. Recently, a role for collagen VI has been demonstrated in the regulation of cellular homeostasis including stress responses mediated through the mitochondrial permeability transition pore (mPTP) and autophagy pathways. We hypothesize that fundamental cellular defects resulting from dysfunctional collagen VI will be reflected in patient derived dermal fibroblasts and approachable using a systems biological approach. In this study we used transcriptional profiling to identify key pathways mediating the cellular response to mutations in collagen VI. We used an RNA-Seq approach on the Illuminia, HiSeq platform to deeply sequence poly (A) purified transcripts from cultured fibroblast from UCMD patients and healthy controls. We quantified differential expression levels and assessed alternative splicing and isoform switching. Among the most significantly down-regulated genes in UCMD patients is ATG13, an important initiator of autophagy. In contrast, APAF1, an important initiator of apoptosis was among the most up-regulated transcripts in UCMD patients. These data are consistent with work in animal models suggesting the presence of dysregulated autophagy and apoptosis pathways in collagen VI deficiency. Furthermore transcriptome profiling including gene-set analysis and determination of differential expression and alternative splicing in fibroblasts will identify cellular pathways important in pathogenesis. Identification of differentially expressed and regulated genes in UCMD will provide new targets for development of therapies as well as potential biomarkers to assess the efficacy of treatments.