AUTHOR=Akawi Nadia , Al Mansoori Ghadeera , Al Zaabi Anwar , Badics Andrea , Al Dhaheri Noura , Al Shamsi Aisha , Al Tenaiji Amal , Alzohily Bashar , Almesmari Fatmah S. A. , Al Hammadi Hamad , Al Dhahouri Nahid , Irshaid Manal , Kizhakkedath Praseetha , Al Shibli Fatema , Tabouni Mohammed , Allam Mushal , Baydoun Ibrahim , Alblooshi Hiba , Ali Bassam R. , Foo Roger S. , Al Jasmi Fatma 

TITLE=Profiling genetic variants in cardiovascular disease genes among a Heterogeneous cohort of Mendelian conditions patients and electronic health records

JOURNAL=Frontiers in Molecular Biosciences

VOLUME=Volume 11 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/molecular-biosciences/articles/10.3389/fmolb.2024.1451457

DOI=10.3389/fmolb.2024.1451457

ISSN=2296-889X

ABSTRACT=This study addresses the rising cardiovascular disease (CVD) rates in the United Arab Emirates (UAE) by investigating the occurrence and impact of genetic variants in CVD-related genes. The research involves a comprehensive analysis of 735 genes associated with heritable CVD, encompassing various cardiovascular conditions. Enrichment analysis highlights key biological processes and pathways, such as Apelin, FoxO, and Ras signaling, implicated in all heritable CVD forms. Examining a UAE cohort of 3,350 individuals reveals predominantly rare and unique CVD variants specific to the population. The study identifies a burden of pathogenic variants in families with CVD within the Emirati Mendelian cohort and re-evaluates the pathogenicity of 693 variants from national health records, uncovering new CVD-causing variants. This original exploration addresses the underrepresentation of the UAE population in public databases and clinical literature on CVD genetics, providing valuable insights for future research and interventions. Agilent 4200 TapeStation system (D1000 and HS D1000 ScreenTape Assays; Agilent Technologies, USA) were used to determine the libraries' concentrations and fragment size Prior sequencing, The final quantified libraries were pooled, normalized, and then sequenced with paired-end reads (2 x 150 bp) on the NovaSeq 6000 System (Illumina, USA) employing S2 flow cell. A combination of in-house developed pipelines and the Illumina DRAGEN Bio-IT Platform (Illumina, USA) was used for read mapping, alignment, variants calling, and quality checks.Gene annotation was performed using VarSeq 2.2.4 software (Golden Helix, USA). Gene ontology enrichment analysis was conducted in the Gene Ontology (GO) knowledgebase.enrichment analysis was performed using ConsensusPathDB (http://cpdb.molgen.mpg.de). Ensembl Variant Effect Predictor (VEP; https://asia.ensembl.org/info/docs/tools/vep/index.html) and VarSeq 2.2.4 software (Golden Helix, USA) were used for variants' annotation and filtration. Minor allele frequencies (MAFs)of all variants were retrieved from the gnomAD database (http://gnomad.broadinstitute.org).Variants' pathogenicity was classified according to the American College of Medical Genetics and Genomics (ACMG) classification framework (12) and patients' phenotypes. We used Fisher's exact test to assess the enrichment of a particular class of CVD variation in patients.