TCTEX1D1 is a genetic modifier of disease progression in Duchenne muscular dystrophy
AuthorSpitali, P; Zaharieva, I; Bohringer, S; Hiller, M; Chaouch, A; Roos, A; Scotton, C; Claustres, M; Bello, L; McDonald, CM; ...
Source TitleEuropean Journal of Human Genetics
PublisherNATURE PUBLISHING GROUP
Document TypeJournal Article
CitationsSpitali, P., Zaharieva, I., Bohringer, S., Hiller, M., Chaouch, A., Roos, A., Scotton, C., Claustres, M., Bello, L., McDonald, C. M., Hoffman, E. P., Koeks, Z., Suchiman, H. E., Cirak, S., Scoto, M., Reza, M., 't Hoen, P. A. C., Niks, E. H., Tuffery-Giraud, S. ,... Duong, T. (2020). TCTEX1D1 is a genetic modifier of disease progression in Duchenne muscular dystrophy. EUROPEAN JOURNAL OF HUMAN GENETICS, 28 (6), pp.815-825. https://doi.org/10.1038/s41431-019-0563-6.
Access StatusOpen Access
Open Access at PMChttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC7253478
Duchenne muscular dystrophy (DMD) is caused by pathogenic variants in the DMD gene leading to the lack of dystrophin. Variability in the disease course suggests that other factors influence disease progression. With this study we aimed to identify genetic factors that may account for some of the variability in the clinical presentation. We compared whole-exome sequencing (WES) data in 27 DMD patients with extreme phenotypes to identify candidate variants that could affect disease progression. Validation of the candidate SNPs was performed in two independent cohorts including 301 (BIO-NMD cohort) and 109 (CINRG cohort of European ancestry) DMD patients, respectively. Variants in the Tctex1 domain containing 1 (TCTEX1D1) gene on chromosome 1 were associated with age of ambulation loss. The minor alleles of two independent variants, known to affect TCTEX1D1 coding sequence and induce skipping of its exon 4, were associated with earlier loss of ambulation. Our data show that disease progression of DMD is affected by a new locus on chromosome 1 and demonstrate the possibility to identify genetic modifiers in rare diseases by studying WES data in patients with extreme phenotypes followed by multiple layers of validation.
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