Genomic testing and counseling: The contribution of next-generation sequencing to epilepsy genetics.

INTRODUCTION: Currently, next-generation sequencing (NGS) technology is more accessible and available to detect the genetic causation of diseases. Though NGS technology benefited some clinical phenotypes, for some clinical diagnoses such as seizures and epileptic disorders, adaptation occurred slowly. The genetic diagnosis was mainly based on epilepsy gene panels and not on whole exome and/or genome sequencing. METHOD: We retrospectively analyzed 420 index cases, referred for NGS over a period of 18 months, to investigate the challenges in diagnosing epilepsy. RESULT: Of the 420 cases, 65 (15%) were referred due to epilepsy with one third having a positive family history. The result of the NGS was 14 positive cases (21.5%), 16 inconclusive cases (24%), and 35 (53%) negative cases. No gene has been detected twice in the inconclusive and positive groups. Comparative genomic hybridization has been performed for all 30 NGS negative cases and four cases with pathogenic variants (deletion in 15q11.213.1, deletion of 2p16.3, deletion in Xq22.1, and deletion in 17p13.3) were identified. CONCLUSION: These findings have implications for our understanding of the approach to genetic testing and counseling of patients affected with seizures and epilepsy disorders. The overall diagnostic yield of exome/genome sequencing in our cohort was 23%. The main characteristic is genetic heterogeneity, supporting NGS technology as a suitable testing approach for seizures and epilepsy disorders. Genetic counseling for newly identified disease-causing variants depends on the pedigree interpretation, within the context of disease penetrance and variable expressivity.

MEFV c.2230G>T p.(Ala744Ser) rs61732874 previously misclassified as pathogenic variant due to lack of a population specific database.

BACKGROUND: Familial Mediterranean fever is a hereditary inflammatory disorder caused by variants in MEFV. c.2230G>T p.(Ala744Ser) rs61732874 is considered to be an established pathogenic variant in MEFV, but in this study we provide a complete evaluation that suggests this variant is likely benign. METHODS: Using an in-house exome database from 924 individuals, we extracted all individuals harboring this variant for clinical, laboratory, and familial evaluation. RESULTS: We identified the variant in 58 individuals from 39 families. The allele frequency of this variant in our database is 4.2%. None of the identified individuals match the diagnosis of Familial Mediterranean Fever. Using the American College of Medical Genetics and Genomics guidelines for variant classification, this variant is classified as likely benign and not pathogenic. CONCLUSION: Conflicting evidence about variants creates challenges for testing laboratories and impacts patient care. Sharing information drawn mainly from underrepresented populations and clinical phenotyping are important tools for precise curation of genetic variants.

Eye color prediction using single nucleotide polymorphisms in Saudi population.

BACKGROUND: DNA prediction of eye color represent one application of the externally visible characteristics (EVC), which attained growing interest in the field of DNA forensic phenotyping. This is mainly due to its ability to narrow the pool of suspects without the need to compare any retrieved DNA material from the crime scene to a reference DNA. Several methods and multiplex genetic panel were proposed with variable prediction accuracy between different populations. However, such panel was not previously tested in the Saudi population, nor any populations of the Middle East and North Africa origin. METHOD: A panel of eleven single nucleotide polymorphisms (SNPs) was tested for their association with three eye colors (brown, hazel, and intermediate) in 80 volunteer Saudi individuals. SNPs and haplotype association test with eye colors were performed to identify the top significant SNPs with the three eye colors. Also, multinomial logistic regression was used to construct the prediction model using a training set of 60 subjects, and a validation set of 20 subjects. The goodness of fit parameter of the model to correctly predicts each eye color as compared to the other was performed. RESULTS: Eye color was significantly associated with rs12913832, rs7170852, and rs916977 that are located within HERC2. SNP rs12913832 was the top significant SNP (p-value = 1.78E-15) that accounted for the association in this region, as the other SNPs were not significant after adjusting for rs12913832. A prediction model containing five SNPs showed high prediction accuracy with Area Under the receiver operating characteristic Curves (AUC) equals to 0.95 and 0.83 for brown and intermediate eye colors, respectively. However, the model's performance was very low for predicting the hazel eye color with AUC equals 0.75. DISCUSSION: Despite the small sample size of our study, we reported very significant SNP associations with eye color. Our model to predict eye colors based on DNA material showed high accuracy for brown and intermediate eye colors. The eye color prediction-model underperformed for the hazel eye colors, suggesting that larger sample size, as well as more comprehensive set of SNPs, could improve the model-prediction accuracy.