Objective: To clarify the prevalence, long-term natural history and severity determinants of SEPN1-related myopathy (SEPN1-RM), we analyzed a large international case series.

Methods: Retrospective clinical, histological and genetic analysis of 132 pediatric and adult patients (2-58 years) followed-up for several decades.

Results: The clinical phenotype was marked by severe axial muscle weakness, spinal rigidity and scoliosis (86.1%, from 8.9±4 years), with relatively-preserved limb strength and previously-unreported ophthalmoparesia in severe cases. All patients developed respiratory failure (from 10.1±6 years), 81.7% requiring ventilation while ambulant. Histopathologically, 79 muscle biopsies showed large variability, partly determined by site of biopsy and age. Multi-minicores were the most common lesion (59.5%), often associated with mild dystrophic features and occasionally with eosinophilic inclusions. Identification of 65 SEPN1 mutations, including 32 novel ones and the first pathogenic CNV, unveiled exon 1 as the main mutational hotspot and revealed the first genotype-phenotype correlations, bi-allelic null mutations being significantly associated with disease severity (p=0.017).  SEPN1-RM was more severe and progressive than previously thought, leading to loss of ambulation in 10% cases, systematic functional decline from the end of the third decade and reduced lifespan even in mild cases. The main prognosis determinants were scoliosis/respiratory management, SEPN1 mutations and body mass abnormalities, which correlated with disease severity. Finally, we propose a set of severity criteria, provide quantitative data for outcome identification and establish a need for age stratification.

Conclusion: Our results inform clinical practice, improving diagnosis and management, and represent a major breakthrough for clinical trial readiness in this not-so-rare disease.

We included 132 patients with SEPN1 mutations identified between 2001 and 2017. Thirty-one were previously reported. SEPN1/SELENON was analyzed on genomic DNA from peripheral blood using Sanger sequencing or Next Generation Sequencing-based gene panels [NGS]. Variants were reported according to Human Genome Variation Society recommendations (http://varnomen.hgvs.org/) using the complete SEPN1/SELENON transcript (NM_020451.2; NP_065184.2). Genome Aggregation (http://gnomad.broadinstitute.org/) and Clinvar (http://www.ncbi.nlm.nih.gov/clinvar/) databases were interrogated to identify previously-reported mutations and to determine variant frequency in the population. Alamut-Batch-UI v1.11® (Interactive Biosoftware, North Seattle, WA) was used to predict variant impact.

Supplementary Table 1: Comprehensive summary of mutation data.

rsID: Reference SNP cluster ID from dbSNP database. ClinVarID: ID from ClinVar database. N: number of patients carrying the mutation.