Whole-Exome and Whole-Genome Sequencing of Candidate Pharmacogenomic and Schizophrenia-Related Genes in Sudanese Families with Schizophrenia.

Abstract

Background: Schizophrenia is considered a neuro-developmental disorder leading to disastrous lifelong disability of the patients and their families. There is a lack of data regarding pharmacogenomics of schizophrenia in Sudan. This study aimed to identify different genes affecting the treatment outcomes in Sudanese patients with schizophrenia.

Methods: A case-control study was conducted on seven families having more than one member diagnosed with schizophrenia. This was a small exploratory family-based sequencing study involving 18 affected individuals and 8 controls from seven families. Ethical clearance and informed consent were obtained. Demographic data were collected using a standardized data collection sheet. DNA was extracted from blood samples collected from patients and control groups. Then, whole-exome and genome sequencing were performed. Sixty-six genes associated with schizophrenia, treatment, and treatment resistance were selected from the variant calling file. Variants showing single-nucleotide polymorphisms (SNPs) were identified. These variants were then classified based on their impact on the protein-coding sequence into high- and moderate-impact. Moreover, indel mutations were also identified.

Results: Twelve variants of seven genes (COMT, FMO1, LPL, CYP2E1, ABCC1, GRM3, CYP2C9) were identified as genes with impact and potential association with schizophrenia (p-value=0.006632). Forty-three genes had a moderate impact, and they showed a potential association with schizophrenia (p-value=0.0004436). Two variants were indel mutations (CYP2D6, DTNBP1) and showed association with schizophrenia (p-value=0.004741). The p-values were generated from different databases.

Conclusion: This exploratory family-based sequencing study identified several potentially relevant pharmacogenomic and schizophrenia-associated variants in Sudanese families, warranting validation in larger and ethnically diverse cohorts.