Publications by authors named "Mi Yeong Hwang"

Hyperuricemia is an essential causal risk factor for gout and is associated with cardiometabolic diseases. Given the limited contribution of East Asian ancestry to genome-wide association studies of serum urate, the genetic architecture of serum urate requires exploration. A large-scale cross-ancestry genome-wide association meta-analysis of 1,029,323 individuals and ancestry-specific meta-analysis identifies a total of 351 loci, including 17 previously unreported loci.

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  • Type 2 diabetes (T2D) is a complex disease influenced by various genetic factors and molecular mechanisms that vary by cell type and ancestry.
  • In a large study involving over 2.5 million individuals, researchers identified 1,289 significant genetic associations linked to T2D, including 145 new loci not previously reported.
  • The study categorized T2D signals into eight distinct clusters based on their connections to cardiometabolic traits and showed that these genetic profiles are linked to vascular complications, emphasizing the role of obesity-related processes across different ancestry groups.
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Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes. To characterise the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study (GWAS) data from 2,535,601 individuals (39.7% non-European ancestry), including 428,452 T2D cases.

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Genotype imputation is essential for enhancing the power of association-mapping and discovering rare and indels that are missed by most genotyping arrays. Imputation analysis can be more accurate with a population-specific reference panel or a multi-ethnic reference panel with numerous samples. The National Institute of Health, Republic of Korea, initiated the Korean Reference Genome (KRG) project to identify variants in whole-genome sequences of ∼20,000 Korean participants.

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Metabolic traits are heritable phenotypes widely-used in assessing the risk of various diseases. We conduct a genome-wide association analysis (GWAS) of nine metabolic traits (including glycemic, lipid, liver enzyme levels) in 125,872 Korean subjects genotyped with the Korea Biobank Array. Following meta-analysis with GWAS from Biobank Japan identify 144 novel signals (MAF ≥ 1%), of which 57.

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  • Common SNPs may account for 40-50% of human height variation, and this study identifies 12,111 SNPs linked to height from a large sample of 5.4 million individuals.
  • These SNPs cluster in 7,209 genomic segments, encompassing about 21% of the genome and showing varying densities enriched in relevant genes.
  • While these SNPs explain a substantial portion of height variance in European populations (40-45%), their predictive power is lower (10-24%) in other ancestries, suggesting a need for more research to enhance understanding in diverse populations.
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  • Researchers studied the genetic connections to blood fats using data from 1.6 million people from different backgrounds to understand why certain fats are higher or lower in the body.
  • They looked at special genes and how they interact in the liver and fat cells, finding that the liver plays a big part in controlling fat levels.
  • Two specific genes, CREBRF and RRBP1, were highlighted as important in understanding how our bodies manage fats due to strong supporting evidence.
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Objective: Genome-wide association studies (GWAS) have identified >100 risk loci for systemic lupus erythematosus (SLE), but the disease genes at most loci remain unclear, hampering translation of these genetic discoveries. We aimed to prioritise genes underlying the 110 SLE loci that were identified in the latest East Asian GWAS meta-analysis.

Methods: We built gene expression predictive models in blood B cells, CD4 and CD8 T cells, monocytes, natural killer cells and peripheral blood cells of 105 Japanese individuals.

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Subjective well-being (SWB) has been explored in European ancestral populations; however, whether the SWB genetic architecture is shared across populations remains unclear. We conducted a cross-population genome-wide association study for SWB using samples from Korean (n = 110,919) and European (n = 563,176) ancestries. Five ancestry-specific loci and twelve cross-ancestry significant genomic loci were identified.

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Human leukocyte antigen (HLA) gene variants in the major histocompatibility complex (MHC) region are associated with numerous complex human diseases and quantitative traits. Previous phenome-wide association studies (PheWAS) for this region demonstrated that HLA association patterns to the phenome have both population-specific and population-shared components. We performed MHC PheWAS in the Korean population by analyzing associations between phenotypes and genetic variants in the MHC region using the Korea Biobank Array project data samples from the Korean Genome and Epidemiology Study cohorts.

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Genome-wide association studies (GWASs) facilitated the discovery of countless disease-associated variants. However, GWASs have mostly been conducted in European ancestry samples. Recent studies have reported that these European-based association results may reduce disease prediction accuracy when applied in non-Europeans.

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Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency < 1%) predicted damaging coding variation by using sequence data from >170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels; some of these genes have not been previously associated with lipid levels when using rare coding variation from population-based samples.

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Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels, heart disease remains the leading cause of death worldwide. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease.

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  • - The study investigates the genetic variants linked to severe monogenic diseases, focusing on the unknown probability (penetrance) of these variants causing disease.
  • - Using exome sequencing data from over 77,000 individuals, researchers examine eight monogenic metabolic diseases, finding that rare variants have a greater impact than common polygenic scores.
  • - Despite the strong effect of rare variants, the average penetrance for monogenic variant carriers is only about 60%, although incorporating polygenic variation helps improve risk prediction for certain conditions.
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  • Scientists studied people's genetics to learn about traits related to blood sugar, which helps diagnose and monitor type 2 diabetes.
  • Most of the earlier studies only looked at people with European backgrounds, but this research included many more individuals from different backgrounds, finding 242 important genetic spots linked to blood sugar levels.
  • By studying a diverse group of people, they discovered new insights about how diabetes works in the body, helping to uncover different biological processes for each glycemic trait.
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Objective: Systemic lupus erythematosus (SLE), an autoimmune disorder, has been associated with nearly 100 susceptibility loci. Nevertheless, these loci only partially explain SLE heritability and their putative causal variants are rarely prioritised, which make challenging to elucidate disease biology. To detect new SLE loci and causal variants, we performed the largest genome-wide meta-analysis for SLE in East Asian populations.

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Background: For a genome-wide association study in humans, genotype imputation is an essential analysis tool for improving association mapping power. When IMPUTE software is used for imputation analysis, an imputation output (GEN format) should be converted to variant call format (VCF) with imputed genotype dosage for association analysis. However, the conversion requires multiple software packages in a pipeline with a large amount of processing time.

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  • The study aimed to enhance understanding of rheumatoid arthritis (RA) by conducting genome-wide association studies (GWAS) in a large cohort of Korean individuals.
  • Researchers generated new genomic data from 4,068 RA patients and 36,487 controls, identifying six novel RA-risk loci and a total of 122 prioritized genes associated with the disease.
  • The findings suggest specific immune-related pathways and tissues involved in RA and provide insights into the genetic factors underlying the condition.
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Meta-analyses of genome-wide association studies (GWAS) have identified more than 240 loci that are associated with type 2 diabetes (T2D); however, most of these loci have been identified in analyses of individuals with European ancestry. Here, to examine T2D risk in East Asian individuals, we carried out a meta-analysis of GWAS data from 77,418 individuals with T2D and 356,122 healthy control individuals. In the main analysis, we identified 301 distinct association signals at 183 loci, and across T2D association models with and without consideration of body mass index and sex, we identified 61 loci that are newly implicated in predisposition to T2D.

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Over the last decade, genome-wide association studies (GWASs) have provided an unprecedented amount of genetic variations that are associated with various phenotypes. However, previous GWAS were mostly conducted in European populations, and these biased results for non-Europeans may result in a significant reduction in risk prediction for non-Europeans. An issue with the early GWAS was the winner's curse problem, which led to misleading results when constructing the polygenic risk scores (PRS).

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Here, we found two genomic safe harbor (GSH) candidates from chromosomes 3 and 8, based on large-scale population-based cohort data from 4,694 Koreans by CNV analysis. Furthermore, estimated genotype of these CNVRs was validated by quantitative real-time PCR, and epidemiological data examined no significant genetic association between diseases or traits and two CNVRs. After screening the GSH candidates by approaches, we designed TALEN pairs to integrate EGFP expression cassette into human cell lines in order to confirm the functionality of GSH candidates in an setting.

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Protein-coding genetic variants that strongly affect disease risk can yield relevant clues to disease pathogenesis. Here we report exome-sequencing analyses of 20,791 individuals with type 2 diabetes (T2D) and 24,440 non-diabetic control participants from 5 ancestries. We identify gene-level associations of rare variants (with minor allele frequencies of less than 0.

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