Limb-Girdle Muscular Dystrophy Type 2B (LGMD2B) caused by Pathogenic Splice and Missense Variants of DYSF Gene among Iranians with Muscular Dystrophy.

Abstract

Background: The phenotypic range of limb-girdle muscular dystrophies (LGMDs) varies significantly because of genetic heterogeneity ranging from very mild to severe forms. Molecular analysis of the DYSF gene is challenging due to the wide range of mutations and associated complications in interpretations of novel DYSF variants with uncertain significance. Thus, in the current study, we performed the NGS analysis and its results are confirmed with Sanger sequencing to find the plausible disease-causing variants in patients with muscular dystrophy and their relatives via segregation analysis.

Materials and methods: Nine patients with LGMD type 2B (LGMD2B) characteristics were screened for putative mutations by the whole-exome sequencing (WES) test. Either the patients themselves or their parents and first relatives were investigated in the segregation analysis through Sanger sequencing. The majority of variants were classified as pathogenic through American College of Medical Genetics and Genomics (ACMG) guidelines, segregation results, and in silico predictions.

Results: Results revealed eight variants in DYSF gene, including three splicing (c.1149+4A>G, c.2864+1G>A, and c.5785-7G>A), two nonsense (p.Gln112Ter and p.Trp2084Ter), two missense (p.Thr1546Pro and p.Tyr1032Cys), and one frameshift (p.Asp1067Ilefs), among nine Iranian families. One of the eight identified variants was novel, including p.Asp1067Ilefs, which was predicted to be likely pathogenic based on the ACMG guidelines. Notably, prediction tools suggested the damaging effects of studied variants on dysferlin structure.

Conclusion: Conclusively, the current report introduced eight variants including a novel frameshift in DYSF gene with noticeable pathogenic effects. This study significantly can broaden the diagnostic spectrum of LGMD2B in combination with previous reports about DYSF mutations and may pave the way for a rapidly high-ranked identification of the accurate type of dysferlinopathy.