Incidental findings in genomic data have been studied in great detail in the recent years, especially from population-scale data sets. However, little is known about the frequency of such findings in ethnic groups, specifically the Middle East, which were not previously covered in global sequencing studies. The availability of whole exome and genome data sets for a highly consanguineous Arab population from Qatar motivated us to explore the incidental findings in this population-scale data. The sequence data of 1005 Qatari individuals were systematically analyzed for incidental genetic variants in the 59 genes suggested by the American College of Medical Genetics and Genomics. We identified four genetic variants which were pathogenic or likely pathogenic. These variants occurred in six individuals, suggesting a frequency of 0.59% in the population, much lesser than that previously reported from European and African populations. Our analysis identified a variant in RYR1 gene associated with Malignant Hyperthermia that has significantly higher frequency in the population compared to global frequencies. Evaluation of the allele frequencies of these variants suggested enrichment in sub-populations, especially in individuals of Sub-Saharan African ancestry. The present study thereby provides the information on pathogenicity and frequency, which could aid in genomic medicine. To the best of our knowledge, this is the first comprehensive analysis of incidental genetic findings in any Arab population and suggests ethnic differences in incidental findings.
Pseudomonas aeruginosa (Pa) is the leading cause of chronic lung infection in Cystic Fibrosis (CF) patients. It is well recognized that CF epithelial cells fail to develop an appropriate response to infection, allowing bacterial colonization and a chronic inflammatory response. Since long non-coding RNAs (lncRNAs), are known to play a key role in regulating mammalian innate immune response, we hypothesized that CF cells exposed to Pa could express a specific lncRNA signature responsible of the maladaptative CF response. We analyzed transcriptomic datasets to compare the expression profiles of lncRNAs in primary CF and non-CF epithelial cells infected with Pa at 0, 2, 4, and 6 h of infection. Our analysis identified temporal expression signatures of 25, 73, 15, and 26 lncRNA transcripts differentially expressed at 0, 2, 4, and 6 h post-infection respectively, between CF and non-CF cells. In addition, we identified profiles specific to CF and non-CF cells. The differential expression of two candidate lncRNAs were independently validated using real-time PCR. We identified a specific CF signature of lncRNA expression in a context of Pa infection that could potentially play a role in the maladaptive immune response of CF patients.
Familial Mediterranean fever (FMF), an autosomal recessive and rare autoinflammatory disease is caused by genetic mutations in the MEFV gene and is highly prevalent in the Mediterranean basin. Although the carrier frequency of specific disease variants in the MEFV gene has been reported from isolated studies, a comprehensive view of variants in the Mediterranean region has not been possible due to paucity of data. The recent availability of whole-genome and whole-exome datasets prompted us to study the genetic epidemiology of MEFV variants in the region. We assembled data from 5 datasets encompassing whole-genome and whole-exome datasets for 2115 individuals from multiple subpopulations in the region and also created a compendium for MEFV genetic variants, which were further systematically annotated as per the American College of Medical Genetics and Genomics (ACMG) guidelines. Our analysis points to significant differences in allele frequencies in the subpopulations, and the carrier frequency for MEFV genetic variants in the population to be about 8%. The MEFV gene appears to be under natural selection from our analysis. To the best of our knowledge, this is the most comprehensive study and analysis of population epidemiology of MEFV gene variants in the Middle East and North African populations.
Middle East and North Africa (MENA) encompass very unique populations, with a rich history and encompasses characteristic ethnic, linguistic and genetic diversity. The genetic diversity of MENA region has been largely unknown. The recent availability of whole-exome and whole-genome sequences from the region has made it possible to collect population-specific allele frequencies. The integration of data sets from this region would provide insights into the landscape of genetic variants in this region. We integrated genetic variants from multiple data sets systematically, available from this region to create a compendium of over 26 million genetic variations. The variants were systematically annotated and their allele frequencies in the data sets were computed and available as a web interface which enables quick query. As a proof of principle for application of the compendium for genetic epidemiology, we analyzed the allele frequencies for variants in transglutaminase 1 (TGM1) gene, associated with autosomal recessive lamellar ichthyosis. Our analysis revealed that the carrier frequency of selected variants differed widely with significant interethnic differences. To the best of our knowledge, al mena is the first and most comprehensive repertoire of genetic variations from the Arab, Middle Eastern and North African region. We hope al mena would accelerate Precision Medicine in the region.
Next generation sequencing (NGS) technologies such as whole genome and whole exome sequencing has enabled accurate diagnosis of genetic diseases through identification of variations at the genome wide level. While many large populations have been adequately covered in global sequencing efforts little is known on the genomic architecture of populations from Middle East, and South Asia and Africa. Incidental findings and their prevalence in populations have been extensively studied in populations of Caucasian descent. The recent emphasis on genomics and availability of genome-scale datasets in public domain for ethnic population in the Middle East prompted us to estimate the prevalence of incidental findings for this population. In this study, we used whole genome and exome data for a total 1005 non-related healthy individuals from Qatar population dataset which contained 20,930,177 variants. Systematic analysis of the variants in 59 genes recommended by the American College of Medical Genetics and Genomics for reporting of incidental findings revealed a total of 2 pathogenic and 2 likely pathogenic variants. Our analysis suggests the prevalence of incidental variants in population-scale datasets is approx. 0.6%, much lower than those reported for global populations. Our study underlines the essentiality to study population-scale genomes from ethnic groups to understand systematic differences in genetic variants associated with disease predisposition.
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