Biology subjects

Myung, W.

Publications and source records attributed to Myung, W..

3 recordsLinked to original sources

bioRxiv2025

10,239 whole genomes with multiomic and clinical health information as the Korean population multiomic reference dataset

We present Korea10K, the largest genomic dataset of the Korean population, comprising 10,239 high-coverage whole genomes (mean depth 30x) with matched multiomic profiles and phenotype data. Korea10K achieves complete and near-complete discovery of very rare and ultra-rare alleles, respectively, at 9,000 Korean genomes. This dataset provides the high-quality population-specific imputation panel, enabling accurate inference of low-frequency variants. Admixture analyses confirm the genetic homogeneity of the Korean population, despite its diverse Y-chromosomal, mitochondrial, and HLA repertoires. This pattern reflects a long and continuous lineage history characterized by persistent internal admixture and genomic homogenization over thousands of years on the Korean peninsula. We also identified 16.8 million genomic variants that directly modify CG sites by creating or abolishing CG dinucleotides, providing the population-scale evidence of coordinated genomic-epigenomic regulatory mechanism in Koreans.

genomics↗

bioRxiv2022

Genetic architecture of creativity and extensive genetic overlap with psychiatric disorders revealed from genome-wide association analyses of 241,736 individuals

Creativity is heritable and exhibits familial aggregation with psychiatric disorders, but its genomic basis and genetic relationship with psychiatric disorders remain largely unknown. Here, we conducted a genome-wide association study (GWAS) using an expanded, machine learning-based definition of creativity in individuals of European ancestry from the UK Biobank (n = 241,736) and identified 25 creativity-associated loci. Extensive genetic overlap with psychiatric disorders, including schizophrenia, major depression, bipolar I disorder, attention deficit/hyperactivity disorder, and anorexia nervosa, was demonstrated by the genetic correlation, polygenic risk score, and MiXeR analyses. The condFDR and conjFDR analyses identified additional loci for creativity and psychiatric disorders, as well as shared genetic loci between creativity and psychiatric disorders. This GWAS showed significant correlations with GWASs using traditional definitions of creativity and GWASs adjusted for educational attainment. Our findings contribute to the understanding of the genetic architecture of creativity and reveal its polygenic relationships with psychiatric disorders.

genomics↗

bioRxiv2019

Causal relationship of cerebrospinal fluid biomarkers with the risk of Alzheimer’s disease: A two-sample Mendelian randomization study

Whether the epidemiological association of amyloid beta (A{beta}) and tau pathology with Alzheimers disease (AD) is causal remains unclear. The recent failures to demonstrate the efficacy of several amyloid beta-modifying drugs may indicate the possibility that the observed association is not causal. These failures also led to efforts to develop tau-directed treatments whose efficacy is still tentative. Herein, we conducted a two-sample Mendelian randomization analysis to determine whether the relationship between the cerebrospinal fluid (CSF) biomarkers for amyloid and tau pathology and the risk of AD is causal. We used the summary statistics of a genome-wide association study (GWAS) for CSF biomarkers (A{beta}1-42, phosphorylated tau 181 [p-tau], and total tau [t-tau]) in 3,146 individuals and for late-onset AD (LOAD) in 21,982 LOAD cases and 41,944 cognitively normal controls. We tested the association between the change in the genetically predicted CSF biomarkers and LOAD risk. We found a modest decrease in the LOAD risk per one standard deviation (SD) increase in the genetically predicted CSF A{beta} (odds ratio [OR], 0.63 for AD; 95% confidence interval [CI], 0.38-0.87; P = 0.02). In contrast, we observed a significant increase in the LOAD risk per one SD increase in the genetically predicted CSF p-tau (OR, 2.37; 95% CI, 1.46-3.28; P = 1.09x10-5). However, no causal association was observed of the CSF t-tau with the LOAD risk (OR, 1.15; 95% CI, 0.85-1.45; P = 0.29). Our findings need to be validated in future studies with more genetic variants identified in larger GWASs for CSF biomarkers.

genomics↗