Evidence map›Paper›PMID 38626723›Full record

ArticleGigaScience2024

Korea4K: whole genome sequences of 4,157 Koreans with 107 phenotypes derived from extensive health check-ups.

Sungwon Jeon, Hansol Choi, Yeonsu Jeon, Whan-Hyuk Choi, Hyunjoo Choi, Kyungwhan An, Hyojung Ryu, Jihun Bhak, Hyeonjae Lee, Yoonsung Kwon and 20 more

Abstract read
In one paragraph

Article in GigaScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–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

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Integrated mapping resolves pathogenicity of 11Journal of the Endocrine Society · 2026
    Article
  4. Article
  5. Blood biomarkers and breed genetics of aging in pet dogs.bioRxiv : the preprint server for biology · 2026
    Article
  6. Neurofibromin 1 (International journal of molecular sciences · 2026
    Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. Rare disease genomics and precision medicine.Genomics & informatics · 2024
    Review
  13. Article
  14. Article
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

30 authors.

Sungwon JeonKorean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.ORCID 0000-0002-2729-9087
Hansol ChoiKorean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.ORCID 0000-0002-3653-1474
Yeonsu JeonKorean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.ORCID 0000-0003-4560-4142
Whan-Hyuk ChoiKorean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.ORCID 0000-0003-1587-5320
Hyunjoo ChoiKorean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.ORCID 0000-0003-2843-0419
Kyungwhan AnKorean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.ORCID 0000-0001-9595-5130
Hyojung RyuKorean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.ORCID 0000-0002-2276-850X
Jihun BhakKorean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.ORCID 0009-0009-1965-8084
Hyeonjae LeeKorean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.ORCID 0000-0003-2683-3804
Yoonsung KwonKorean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.ORCID 0000-0002-7242-2734
Sukyeon HaKorean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.ORCID 0009-0007-8192-3921
Yeo Jin KimClinomics, Inc., Ulsan 44919, Republic of Korea.ORCID 0000-0001-9122-914X
Asta BlazyteKorean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.ORCID 0000-0001-7309-1482
Changjae KimClinomics, Inc., Ulsan 44919, Republic of Korea.ORCID 0000-0002-2018-1561
Yeonkyung KimClinomics, Inc., Ulsan 44919, Republic of Korea.ORCID 0000-0002-0649-916X
Younghui KangKorean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.ORCID 0000-0002-0323-0851
Yeong Ju WooClinomics, Inc., Ulsan 44919, Republic of Korea.ORCID 0000-0002-3049-7762
Chanyoung LeeKorean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.ORCID 0000-0002-8269-3191
Jeongwoo SeoKorean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.ORCID 0000-0002-9163-4310
Changhan YoonKorean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.ORCID 0000-0003-0243-9853
Dan BolserGeromics Ltd., Cambridge CB1 3NF, United Kingdom.ORCID 0000-0002-3991-0859
Orsolya BiroClinomics Europe Ltd., Budapest 1094, Hungary.ORCID 0000-0002-4300-3602
Eun-Seok ShinDepartment of Cardiology, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan 44033, Republic of Korea.ORCID 0000-0002-9169-6968
Byung Chul KimClinomics, Inc., Ulsan 44919, Republic of Korea.ORCID 0000-0002-4891-9679
Seon-Young KimKorea Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea.ORCID 0000-0002-1030-7730
Ji-Hwan ParkKorea Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea.ORCID 0000-0002-6988-6239
Jongbum JeonKorea Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea.ORCID 0000-0003-3533-1363
Dooyoung JungDepartment of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.ORCID 0000-0002-5381-4847
Semin LeeKorean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.ORCID 0000-0002-9015-6046
Jong BhakKorean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.ORCID 0000-0002-4228-1299

Funding

NIH HHS
6 · The paper itself

Abstract

backgroundPhenome-wide association studies (PheWASs) have been conducted on Asian populations, including Koreans, but many were based on chip or exome genotyping data. Such studies have limitations regarding whole genome-wide association analysis, making it crucial to have genome-to-phenome association information with the largest possible whole genome and matched phenome data to conduct further population-genome studies and develop health care services based on population genomics.

resultsHere, we present 4,157 whole genome sequences (Korea4K) coupled with 107 health check-up parameters as the largest genomic resource of the Korean Genome Project. It encompasses most of the variants with allele frequency >0.001 in Koreans, indicating that it sufficiently covered most of the common and rare genetic variants with commonly measured phenotypes for Koreans. Korea4K provides 45,537,252 variants, and half of them were not present in Korea1K (1,094 samples). We also identified 1,356 new genotype-phenotype associations that were not found by the Korea1K dataset. Phenomics analyses further revealed 24 significant genetic correlations, 14 pleiotropic associations, and 127 causal relationships based on Mendelian randomization among 37 traits. In addition, the Korea4K imputation reference panel, the largest Korean variants reference to date, showed a superior imputation performance to Korea1K across all allele frequency categories.

conclusionsCollectively, Korea4K provides not only the largest Korean genome data but also corresponding health check-up parameters and novel genome-phenome associations. The large-scale pathological whole genome-wide omics data will become a powerful set for genome-phenome level association studies to discover causal markers for the prediction and diagnosis of health conditions in future studies.

Indexed as

Genome-Wide Association StudyPolymorphism, Single NucleotideGene FrequencyGenetic Association StudiesGenotypeHumansPhenotypeRepublic of KoreagenomeKorean Genome Projectphenomepopulation genomicsvariome

Identifiers

PMID38626723
PMCPMC11020240

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