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Korean Biobank Data Analysis Uncovers More Than a Hundred Novel Genetic Associations Through GWAS

NEW YORK — Using data from a large Korean biobank, researchers conducted a series of genome-wide association studies on a range of traits to bolster the representation of East Asian populations in such genetic analyses.

Large biobanks like the UK Biobank and FinnGen have fueled a number of GWAS, but those analyses have included a few samples from non-European individuals, limiting their applicability to populations beyond European ones.

By conducting GWAS for 76 phenotypes using data from a cohort of more than 72,000 Korean individuals from the Korean Genome and Epidemiology Study (KoGES), researchers from Seoul National University uncovered more than 100 novel associations. As they reported on Wednesday in the journal Cell Genomics, they further combined their findings with data from Biobank Japan (BBJ) in a meta-analysis to boost that number of novel associations to more than 370 and to improve the predictive power of polygenic risk scores (PRS) in East Asian populations.

"To better predict and prevent complex diseases, we need large GWAS in diverse populations," senior author Seunggeun Lee and colleagues wrote in their paper.

KoGES is a prospective cohort study that recruits participants from the national health examinee registry. In all, it includes 72,298 individuals, most of whom have undergone genotyping on the customized KoreanChip, have answered numerous questionnaires, and from whom biological samples have also been collected to gauge biochemical marker levels.

In their series of GWAS, the SNU team examined 14 disease endpoints, 31 biomarkers, 23 diet-related traits, and eight alcohol consumption-related traits. They uncovered 1,455 genetic loci associated with 42 phenotypes. Among these, they uncovered 122 novel genetic associations with 32 traits, many of which they could replicate in the BBJ population.

Many of these SNPs are more common in Korean populations than European populations, underscoring the need for better representation of diverse populations in genetic research. For instance, rs939955, an intergenic variant falling between CYP3A4 and CYP3A7 associated with triglyceride levels, is present in the KoGES cohort with a minor allele frequency (MAF) of 0.22, but is much rarer in Europeans, with a MAF of 0.002. Similarly, rs1314013 at the ZEB1 locus, which was linked to weight, is present in the KoGES cohort with a MAF of 0.17 compared to a MAF of 0.04 in Europeans.

Then, in a meta-analysis of nine disease traits and 23 biomarkers in a combined KoGES and BBJ cohort, the researchers uncovered additional significant associations, including 379 novel associations.

Using these East Asian meta-analysis results, the researchers generated PRS for five different traits: systolic blood pressure, diastolic blood pressure, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglyceride levels.

They then compared the performance of those East Asian meta-analysis-derived PRS to PRS generated from BBJ-only data and UKBB-only data to predict disease among East Asians. The East Asian meta-analysis-derived PRS performed better for all phenotypes as compared to the BBJ-based PRS and for three of the five phenotypes as compared to the UKBB-based PRS. That, the researchers noted, could be due to how the PRS were tested — in East Asians from UKBB — and the sheer number of samples used to build the UKBB-based PRS, more than 400,000 compared to 140,000 for BBJ and 210,000 for the meta-analysis.

Still, a multi-ethnic PRS developed by combining the East Asian and European PRS also performed better than the BBJ-based PRS and the UKBB-based PRS alone.

"Overall, our analysis result demonstrates that the meta-analysis, including the KoGES GWAS, can contribute to the improvement of risk prediction for East Asians," the researchers wrote.

They added in their paper that all of their GWAS and meta-analysis results are available on a PheWeb website, and that "[b]y providing East Asian GWAS on many phenotypes, our results will contribute to elucidating the genetic architecture of complex traits."

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