| Autor: |
Katarína Kušíková, Andrea Šoltýsová, Andrej Ficek, René G. Feichtinger, Johannes A. Mayr, Martina Škopková, Daniela Gašperíková, Miriam Kolníková, Karoline Ornig, Ognian Kalev, Serge Weis, Denisa Weis |
| Jazyk: |
angličtina |
| Rok vydání: |
2023 |
| Předmět: |
|
| Zdroj: |
Genes, Vol 14, Iss 12, p 2174 (2023) |
| Druh dokumentu: |
article |
| ISSN: |
2073-4425 |
| DOI: |
10.3390/genes14122174 |
| Popis: |
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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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