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.
Katarína KušíkováAndrea ŠoltýsováAndrej FicekRené Günther FeichtingerJohannes Adalbert MayrMartina ŠkopkováDaniela GasperikovaMiriam KolníkováKaroline OrnigOgnian KalevSerge WeisDenisa WeisPublished in: Genes (2023)
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.
Keyphrases
- end stage renal disease
- ejection fraction
- newly diagnosed
- genome wide
- copy number
- chronic kidney disease
- machine learning
- prognostic factors
- peritoneal dialysis
- genome wide identification
- deep learning
- late onset
- gene expression
- patient reported outcomes
- transcription factor
- neural network
- early onset
- patient reported
- genome wide analysis