Prognostic Value of Genotype-Phenotype Correlations in X-Linked Myotubular Myopathy and the Use of the Face2Gene Application as an Effective Non-Invasive Diagnostic Tool

  • Katarina Kusikova
  • , Andrea Soltysova
  • , Andrej Ficek
  • , Rene Günther Feichtinger
  • , Johannes A. Mayr
  • , Martina Skopkova
  • , Daniela Gasperikova
  • , Miriam Kolnikova
  • , Karoline Ornig
  • , Ognian Kalev
  • , Serge Weis
  • , Denisa Weis

Research output: Contribution to journalArticlepeer-review

Abstract

BACKGROUND: X-linked myotubular myopathy (XLMTM) is a rare congenital myopathy resulting from dysfunction of the protein myotubularin encoded by the MTM1 gene. XLMTM has a high neonatal and infantile mortality rate due to a severe myopathic phenotype and respiratory failure. However, in a minority of XLMTM cases, patients present with milder phenotypes and achieve ambulation and adulthood. Notable facial dysmorphia is also present.

METHODS: We investigated the genotype-phenotype correlations in newly diagnosed XLMTM patients in a patients' cohort (previously published data plus three novel variants, n = 414). Based on the facial gestalt difference between XLMTM patients and unaffected controls, we investigated the use of the Face2Gene application.

RESULTS: Significant associations between severe phenotype and truncating variants ( p < 0.001), frameshift variants ( p < 0.001), nonsense variants ( p = 0.006), and in/del variants ( p = 0.036) were present. Missense variants were significantly associated with the mild and moderate phenotype ( p < 0.001). The Face2Gene application showed a significant difference between XLMTM patients and unaffected controls ( p = 0.001).

CONCLUSIONS: Using genotype-phenotype correlations could predict the disease course in most XLMTM patients, but still with limitations. The Face2Gene application seems to be a practical, non-invasive diagnostic approach in XLMTM using the correct algorithm.

Original languageEnglish
Article number2174
Number of pages13
JournalGenes
Volume14
Issue number12
DOIs
Publication statusPublished - 03 Dec 2023

Fields of science

  • 301101 General pathology
  • 301108 Molecular pathology

Cite this