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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

Umlai, U.-K. I.; Toor, S. M.; Al-Sarraj, Y. A.; Mohammed, S.; Al Hail, M. S. H.; Ullah, E.; Kunji, K.; El-Menyar, A.; Gomaa, M.; Jayyousi, A.; Saad, M.; Qureshi, N.; Al Suwaidi, J. M.; Albagha, O. M. E.

2024-07-07 genetic and genomic medicine
10.1101/2024.07.04.24309936 medRxiv
Show 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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