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Genome-wide association study and fine-mapping on Korean biobank to discover renal trait-associated variantsopen accessGenome-wide association study and fine-mapping on Korean biobank to discover renal trait-associated variants

Other Titles
Genome-wide association study and fine-mapping on Korean biobank to discover renal trait-associated variants
Authors
이동진문종석Song Dae KwonLee Yong Seok김동섭조남준길효욱Lee Eun Young박삼엘
Issue Date
May-2024
Publisher
대한신장학회
Keywords
Chronic kidney disease; Estimated glomerular filtration rate; Genetics; Genome-wide association study; Korean Genome and Epidemiology
Citation
Kidney Research and Clinical Practice, v.43, no.3, pp 299 - 312
Pages
14
Journal Title
Kidney Research and Clinical Practice
Volume
43
Number
3
Start Page
299
End Page
312
URI
https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/26327
DOI
10.23876/j.krcp.23.079
ISSN
2211-9132
2211-9140
Abstract
Background: Chronic kidney disease is a significant health burden worldwide, with increasing incidence. Although several genome- wide association studies (GWAS) have investigated single nucleotide polymorphisms (SNP) associated with kidney trait, most studies were focused on European ancestry. Methods: We utilized clinical and genetic information collected from the Korean Genome and Epidemiology Study (KoGES). Results: More than five million SNPs from 58,406 participants were analyzed. After meta-GWAS, 1,360 loci associated with estimated glomerular filtration rate (eGFR) at a genome-wide significant level (p = 5 × 10–8) were identified. Among them, 399 loci were validated with at least one other biomarker (blood urea nitrogen [BUN] or eGFRcysC) and 149 loci were validated using both markers. Among them, 18 SNPs (nine known ones and nine novel ones) with 20 putative genes were found. The aggregated effect of genes estimated by MAGMA gene analysis showed that these significant genes were enriched in kidney-associated pathways, with the kidney and liver being the most enriched tissues. Conclusion: In this study, we conducted GWAS for more than 50,000 Korean individuals and identified several variants associated with kidney traits, including eGFR, BUN, and eGFRcysC. We also investigated functions of relevant genes using computational methods to define putative causal variants.
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College of Natural Sciences > Department of Biology > 1. Journal Articles
College of Medicine > Department of Internal Medicine > 1. Journal Articles
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