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Prognostic Value of Genotype-Phenotype Correlations in X-linked Myotubular Myopathy and Use of the Face2Gene Application as an Effective Non-Invasive Diagnostic Tool
Kušíková, K.; Šoltýsová, A.; Ficek, A.; Feichtinger, R.G.; Mayr, J.A.; Škopková, M.; Gašperíková, D.; Kolníková, M.; Ornig, K.; Kalev, O.; Weis, S.; Weis, D. 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. Genes2023, 14, 2174.
Kušíková, K.; Šoltýsová, A.; Ficek, A.; Feichtinger, R.G.; Mayr, J.A.; Škopková, M.; Gašperíková, D.; Kolníková, M.; Ornig, K.; Kalev, O.; Weis, S.; Weis, D. 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. Genes 2023, 14, 2174.
Kušíková, K.; Šoltýsová, A.; Ficek, A.; Feichtinger, R.G.; Mayr, J.A.; Škopková, M.; Gašperíková, D.; Kolníková, M.; Ornig, K.; Kalev, O.; Weis, S.; Weis, D. 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. Genes2023, 14, 2174.
Kušíková, K.; Šoltýsová, A.; Ficek, A.; Feichtinger, R.G.; Mayr, J.A.; Škopková, M.; Gašperíková, D.; Kolníková, M.; Ornig, K.; Kalev, O.; Weis, S.; Weis, D. 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. Genes 2023, 14, 2174.
Abstract
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. Regarding wide phenotypic variability, we investigated the genotype-phenotype correlations in newly diagnosed XLMTM patients in a patients' cohort (previously published data plus three novel variants, n=414). We found a significant association 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). On the contrary, missense variants were significantly associated with the mild and moderate phenotype (p < 0.001). We found no significant association between phenotype and the MTM1-specific functional domain, contrasting with previously published data. Based on the significant facial gestalt difference between XLMTM patients and unaffected controls (p = 0.001), we consider the Face2Gene application as an effective diagnostic tool in XLMTM when using the correct algorithm. The Face2Gene application seems to be a practical, non-invasive diagnostic approach in XLMTM.
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