Identification of Novel and Recurrent Variants in BTD , GBE1 , AGL and ASL Genes in Families with Metabolic Disorders in Saudi Arabia.
Muhammad LatifJamil Amjad HashmiAbdulfatah M AlayoubiArusha AyubSulman BasitPublished in: Journal of clinical medicine (2024)
Background and Objectives: Inherited metabolic disorders (IMDs) are a group of genetic disorders characterized by defects in enzymes or transport proteins involved in metabolic processes. These defects result in an abnormal accumulation of metabolites and thus interfere with the body's metabolism. A variety of IMDs exist and differential diagnosis is often challenging. Our objective was to gain insight into the genetic basis of IMDs and the correlations between specific genetic mutations and clinical presentations in patients admitted at various hospitals in the Madinah region of the Kingdom of Saudi Arabia. Material and Methods: Whole exome sequencing (WES) has emerged as a powerful tool for diagnosing IMDs and allows for the identification of disease-causing genetic mutations in individuals suspected of IMDs. This ensures accurate diagnosis and appropriate management. WES was performed in four families with multiple individuals showing clinical presentation of IMDs. Validation of the variants identified through WES was conducted using Sanger sequencing. Furthermore, various computational analyses were employed to uncover the disease gene co-expression and metabolic pathways. Results: Exome variant data analysis revealed missense variants in the BTD (c.1270G > C), ASL (c.1300G > T), GBE1 (c.985T > G) and AGL (c.113C > G) genes. Mutations in these genes are known to cause IMDs. Conclusions: Thus, our data showed that exome sequencing, in conjunction with clinical and biochemical characteristics and pathological hallmarks, could deliver an accurate and high-throughput outcome for the diagnosis and sub-typing of IMDs. Overall, our findings emphasize that the integration of WES with clinical and pathological information has the potential to improve the diagnosis and understanding of IMDs and related disorders, ultimately benefiting patients and the medical community.
Keyphrases
- copy number
- genome wide
- data analysis
- dna methylation
- bioinformatics analysis
- saudi arabia
- high throughput
- single cell
- healthcare
- high resolution
- ejection fraction
- genome wide identification
- mental health
- end stage renal disease
- pulmonary embolism
- poor prognosis
- gene expression
- risk assessment
- machine learning
- cerebral blood flow
- social media
- peritoneal dialysis
- health information
- transcription factor