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Genetic & Genomic MedicinemedRxiv
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Identification of a Novel SLC2A9 Gene Association with LDL-C levels and Evaluation of Polygenic Scores in a Multi-Ancestry Genome Wide Association Study

Umm‐Kulthum Ismail UmlaiiD, Salman M. TooriD, Yasser A. Al-SarrajiD, Shaban Mohammed, Moza S H Al Hail, Ehsan UllahiD, Khalid B. KunjiiD, Ayman Ahmed El-MenyariD, Mohammed Gomaa, Amin JayyousiiD, Mohamad SaadiD, Nadeem QureshiiD, Jassim M. S. Al SuwaidiiD, Omar AlbaghaiD

Abstract

The genetic determinants of low-density lipoprotein cholesterol (LDL-C) levels in blood have been predominantly explored in European populations and remain poorly understood in Middle Eastern populations. We investigated the genetic architecture of LDL-C variation in the Middle Eastern population of Qatar. Whole genome sequencing data of 13,701 individuals (discovery; n=5939, replication; n=7762) from the population-based Qatar Biobank (QBB) cohort was used to conduct a genome-wide association study (GWAS) on serum LDL-C levels. We replicated 168 previously reported loci from the largest LDL-C GWAS conducted by the Global Lipids Genetics Consortium (GLGC), with high correlation in allele frequencies (R2=0.77) and moderate correlation in effect sizes (Beta; R2=0.53). We also performed a multi-ancestry meta-analysis with the GLGC study using MR-MEGA (Meta-Regression of Multi-Ethnic Genetic Association). The multi-ancestry meta-analysis identified one novel LDL-C-associated locus; rs10939663 (SLC2A9; genomic control-corrected P=1.25x10-8). Lastly, we developed Qatari-specific polygenic score (PGS) panels from our discovery dataset and tested their performance in the replication dataset against PGS derived from other ancestries. The multi-ancestry derived PGS (PGS000889) performed best at predicting LDL-C levels, whilst the Qatari-derived PGS panels also showed comparable performance. Overall, we report one novel gene variant associated with LDL-C levels, which may be explored further to decipher its potential role in the etiopathogenesis of cardiovascular diseases. Our findings also highlight the importance of population-based genetics in developing PGS panels for clinical utilization.

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