Evidence map›Paper›PMID 36777999›Full record

ArticleCell genomics2022

Genome-wide study on 72,298 individuals in Korean biobank data for 76 traits.

Kisung Nam, Jangho Kim, Seunggeun Lee

Abstract read
In one paragraph

Article in Cell genomics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed, 6 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

58 citing papers in PubMed, 6 syntheses or guidelines pooled it.

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  10. Genetic basis of Asian diabetes.Journal of diabetes investigation · 2026
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Kisung NamGraduate School of Data Science, Seoul National University, Seoul 08826, Republic of Korea.
Jangho KimGraduate School of Data Science, Seoul National University, Seoul 08826, Republic of Korea.
Seunggeun LeeGraduate School of Data Science, Seoul National University, Seoul 08826, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genome-wide association studies (GWAS) on diverse ancestry groups are lacking, resulting in deficits of genetic discoveries and polygenic scores. We conducted GWAS for 76 phenotypes in Korean biobank data, namely the Korean Genome and Epidemiology Study (KoGES) (n = 72,298). Our analysis discovered 2,242 associated loci, including 122 novel associations, many of which were replicated in Biobank Japan (BBJ) GWAS. We also applied several up-to-date methods for genetic association tests to increase the power, discovering additional associations that are not identified in simple case-control GWAS. We evaluated genetic pleiotropy to investigate genes associated with multiple traits. Following meta-analysis of 32 phenotypes between KoGES and BBJ, we further identified 379 novel associations and demonstrated the improved predictive performance of polygenic risk scores by using the meta-analysis results. The summary statistics of 76 KoGES GWAS phenotypes are publicly available, contributing to a better comprehension of the genetic architecture of the East Asian population.

Indexed as

genome-wide association study (GWAS)Korean Genome and Epidemiology Study (KoGES)meta-analysispleiotropyPolygenic risk score (PRS)

Identifiers

PMID36777999
PMCPMC9903843

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.