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Jeon S, Choi H, Jeon Y, Choi WH, Choi H, An K, Ryu H, Bhak J, Lee H, Kwon Y, Ha S, Kim YJ, Blazyte A, Kim C, Kim Y, Kang Y, Woo YJ, Lee C, Seo J, Yoon C, Bolser D, Biro O, Shin ES, Kim BC, Kim SY, Park JH, Jeon J, Jung D, Lee S, Bhak J. Korea4K: whole genome sequences of 4,157 Koreans with 107 phenotypes derived from extensive health check-ups. Gigascience 2024; 13:giae014. [PMID: 38626723 PMCID: PMC11020240 DOI: 10.1093/gigascience/giae014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Revised: 11/28/2023] [Accepted: 03/15/2024] [Indexed: 04/18/2024] Open
Abstract
BACKGROUND Phenome-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. RESULTS Here, 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. CONCLUSIONS Collectively, 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.
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Affiliation(s)
- Sungwon Jeon
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
- Clinomics, Inc., Ulsan 44919, Republic of Korea
| | - Hansol Choi
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
- Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
| | - Yeonsu Jeon
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
- Clinomics, Inc., Ulsan 44919, Republic of Korea
| | - Whan-Hyuk Choi
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
- Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
- Department of Mathematics, Kangwon National University, Chuncheon 24341, Republic of Korea
| | - Hyunjoo Choi
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
- Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
| | - Kyungwhan An
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
- Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
| | - Hyojung Ryu
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
- Clinomics, Inc., Ulsan 44919, Republic of Korea
| | - Jihun Bhak
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
- Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
| | - Hyeonjae Lee
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
- Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
| | - Yoonsung Kwon
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
- Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
| | - Sukyeon Ha
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
- Department of Computer Science & Engineering (CSE), College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
| | - Yeo Jin Kim
- Clinomics, Inc., Ulsan 44919, Republic of Korea
| | - Asta Blazyte
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
- Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
- Lee Gil Ya Cancer and Diabetes Institute, Gachon University, Incheon 21999, Republic of Korea
| | | | | | - Younghui Kang
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
- Clinomics, Inc., Ulsan 44919, Republic of Korea
| | | | - Chanyoung Lee
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
- Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
| | - Jeongwoo Seo
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
- Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
| | - Changhan Yoon
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
- Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
| | - Dan Bolser
- Geromics Ltd., Cambridge CB1 3NF, United Kingdom
| | | | - Eun-Seok Shin
- Department of Cardiology, Ulsan University Hospital, University of Ulsan College of Medicine, Ulsan 44033, Republic of Korea
| | | | - Seon-Young Kim
- Korea Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea
| | - Ji-Hwan Park
- Korea Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea
| | - Jongbum Jeon
- Korea Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea
| | - Dooyoung Jung
- Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
| | - Semin Lee
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
- Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
| | - Jong Bhak
- Korean Genomics Center (KOGIC), Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
- Clinomics, Inc., Ulsan 44919, Republic of Korea
- Department of Biomedical Engineering, College of Information-Bio Convergence Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
- Personal Genomics Institute (PGI), Genome Research Foundation (GRF), Osong 28160, Republic of Korea
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Abstract
Peripheral blood leukocyte alkaline phosphatase (LAP) scores and CA15-3, CA125, and CEA levels in plasma were measured in 57 patients with metastatic breast, ovarian, and colorectal cancer, respectively, and in 79 patients with the same types of nonmetastatic cancer. The mean LAP scores of the metastatic cancer patients (261, 272 and 275 for breast, ovary and colon, respectively) were significantly higher than those of the nonmetastatic cancer group (70, 68 and 57, respectively). There was no overlap between the 95% confidence intervals of the two groups (i.e., metastatic versus nonmetastatic), and no patient known to be metastatic had a LAP score within the normal range. The mean levels of other markers in the metastatic patients (CA15-3, 63.4 μ/ml; CA125, 104.8 μ/ml; and CEA, 51.8 ng/ml for metastatic breast, ovarian, and colon cancer, respectively) were also higher than in the nonmetastatic patients (CA15-3, 24 μ/ml; CA125, 25.3 μ/ml; and CEA, 5.8 ng/ml for nonmetastatic breast, ovarian, and colon cancer, respectively). However, the 95% confidence intervals of the nonmetastatic and the metastatic patients overlapped so that there were false-negatives and/or false-positives when the other markers were used. We therefore conclude that the addition of the LAP score to conventional cancer markers could be helpful for the diagnosis of recurrence and follow-up of cancer patients and suggest that our results be confirmed by further studies on a larger series of patients.
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Affiliation(s)
- N Walach
- Department of Oncology, Assaf Harofeh Medical Center, Zerifin, Israel
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