Systematic reanalysis of next-generation sequencing data in 101 neuromuscular disorder families enhances diagnostic yield, reveals intronic variants, and identifies a novel disease gene.

doi:10.1007/s00415-026-13994-9

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Article

Systematic reanalysis of next-generation sequencing data in 101 neuromuscular disorder families enhances diagnostic yield, reveals intronic variants, and identifies a novel disease gene.

Journal of neurology - 20 Jul 2026

Malaichamy Sivasankar, Polavarapu Kiran, Thompson Rachel, Idoux Romane, Spendiff Sally, Karcagi Veronika, Herczegfalvi Agnes, Almomen Momen, Scola Rosana Herminia, Lorenzoni Paulo José, Zanoteli Edmar, Zambon Antonio Alberto, Camelo Clara Gontijo, Estephan Eduardo de Paula, Geetha Thenral S, Ramprasad Vedam L, Vengalil Seena, Nashi Saraswati, Keerthipriya Muddassu, Baskar Dipti, Preethish-Kumar Veeramani, Kotambail Ananthapadmanabha, Muhmann David, Schara-Schmidt Ulrike, Laurie Steven, Matalonga Leslie, Beltran Sergi, Roos Andreas, Barić Ivo, Nalini Atchayaram, Lochmüller Hanns

Abstract excerpt

BACKGROUND: Neuromuscular disorders (NMDs) affect approximately 1 in 1,000 individuals and are clinically and genetically heterogeneous. Despite advances in genomic diagnostics, many cases remain unsolved after initial sequencing. Bioinformatic reanalysis approaches provide opportunities to identify missed variants and establish novel disease genes. METHODS: Preexisting next-generation sequencing datasets from...

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Identifiers

PMID: 42474733
DOI: 10.1007/s00415-026-13994-9

Genes

ATP2A2
MYH2
AGRN
CHRND
COL6A3
DOK7
DYSF
GOLGA2
KIF21A
PTPN11
RYR1
SCN4A
SGCA
TTN

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