NBDC Research ID: hum0311.v6
SUMMARY
Aims: The BioBank Japan (BBJ) is a biobank established in the Institute of Medical Science, the University of Tokyo to collect clinical information and biological materials (DNA and serum samples). It collected about 200 thousand participants of 47 diseases started in 2003 (BBJ 1st cohort), and 67 thousand participants of 38 diseases started in 2013 (BBJ 2nd cohort), both in collaboration with 12 medical centers." This project is aiming at further utilization of the materials, and clinical and genomic information managed by BBJ to contribute to precision medicine by storing, managing, and providing the materials and data, as well as identifying biomarkers associated with disease risk, prognosis, and drug sensitivity.
Methods: Asian Screening Array (ASA-24v1-0_A2)
Imputation results based on TOPMed r2 (GRCh38)
Quantification of 250 metabolic biomarkers by NMR spectroscopy
Genome-wide association study (GWAS) for peptic ulcers
Participants/Materials: BBJ 1st cohort (n = 11,716 + 180,882 + 1,285 + 2,570 + 40,907), BBJ 2nd cohort (n = 42,689), ToMMo (n = 49,621), UK biobank (n = 456,327), and FinnGen (n = 230,635)
URL: https://biobankjp.org/en/index.html
| Dataset ID | Type of Data | Criteria | Release Date |
|---|---|---|---|
| JGAS000412 | Genotype data for 11,716 patients from BBJ 1st cohort and 42,689 patients from BBJ 2nd cohort | Controlled-access (Type I) | 2021/11/30 |
| JGAS000541 | Imputation data and index data for 180,882 patients from BBJ 1st cohort | Controlled-access (Type I) | 2022/07/28 |
| JGAS000561 | NMR metabolic biomarkers for 1,285 patients from BBJ 1st cohort | Controlled-access (Type I) | 2022/09/08 |
| JGAS000561 (Data addition) | NMR metabolic biomarkers for 2,570 patients from BBJ 1st cohort | Controlled-access (Type I) | 2023/04/24 |
| hum0311.v5.gwas.v1 | GWAS for peptic ulcers | Unrestricted-access | 2023/07/27 |
| JGAS000561 (Data addition) | NMR metabolic biomarkers for 40,907 patients from BBJ 1st cohort | Controlled-access (Type I) | 2024/05/22 |
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*When the research results including the data which were downloaded from NHA/DRA, are published or presented somewhere, the data user must refer the papers which are related to the data, or include in the acknowledgment. Learn more
MOLECULAR DATA
| Participants/Materials |
11,716 patients from BBJ 1st cohort and 42,689 patients from BBJ 2nd cohort ICD10: C34, C15, C16, C18-C21, C22, C25, C23, C24, C61, C50, C53, C54, C56, C81-C86, C90-C93, I63, G45.9, I67.1, G40, J45, A15-A19, J44.9, J84.1-9, I21.0-9, I20.0, I20.1, I20.8, I20.9, R00, I44.0-3, I45.5-6, I47-I49, I50, I70.9, B18.1, B18.2, K74.6, N04, N20-N23, M80-M81, E10, E11, E88.8, E78.0-5, E78.8-9, E05.0, M05-M06, J30.1, L91.0, L20, L51.1-2, L27.0, D25, N80, R56.0, H40, H25-H26, K05, G12.2, I61, C64 |
| Targets | genome wide SNPs |
| Target Loci for Capture Methods | - |
| Platform | Illumina [Asian Screening Array (ASA-24v1-0_A2)] |
| Library Source | DNAs extracted from peripheral blood cells or saliva |
| Cell Lines | - |
| Reagents (Kit, Version) | Infinium Asian Screening Array-24 v1.0 BeadChip Kit |
| Genotype Call Methods (software) | GenomeStudio |
| Marker Number (after QC) | 657,060 SNVs (GRCh38) |
| Japanese Genotype-phenotype Archive Dataset ID | JGAD000529 |
| Total Data Volume | 1,020 GB (idat, csv, plink binary) |
| Comments (Policies) | NBDC policy |
| Participants/Materials |
180,882 patients from BBJ 1st cohort ICD10: A15-A16, B16-B17.0, B18.0-B18.1, B17.1, B18.2, C15, C16, C18, C22, C23-C24, C25, C33-C34, C50, C53, C54, C56, C61, C81, D25, E05, E10, E78.0-E78.5, G12, G40-G41, H25-H26, H40-H42, I20, I21-I22, I44-I49, I50, I60, I69.0, I63, I69.3, I70, J30, J41-J44, J45-J46, J80-J84, K05, K74.3-K74.6, L00-L99, L20, M05-M06, M80-M82, N04, N20-N23, N80, R00-R9 |
| Targets | genome wide SNVs |
| Target Loci for Capture Methods | - |
| Platform | Illumina [HumanOmniExpressExome, HumanOmniExpress, HumanExome] |
| Library Source | DNAs extracted from peripheral blood cells or saliva |
| Cell Lines | - |
| Reagents (Kit, Version) | HumanOmniExpressExome-8, HumanOmniExpress-12, HumanExome-12 kit |
| Genotype Call Methods (software) |
GenomeStudio Software Eagle software (v2.4.1) without a reference panel Minimac4 software (v1.0.2) |
| Reference Genome Sequence | TOPMed reference panel (Version R2 on GRC38) |
| Filtering Methods |
Before imputation, we excluded SNPs using the following criteria: - Heterozygosity count for each chip < 5 - P-value for Hardy–Weinberg equilibrium (HWE) for each chip < 1.0 x 10^-6 * - Genotype concordance rate with whole-genome sequencing (WGS) for 939 samples < 99.5% and its non-reference discordance rate >= 0.5% - Lower call rate SNPs if the position was the same when merging datasets - Call rate < 99% * P-values for chrX SNPs were calculated by using female samples We also excluded samples using the following criteria ： - Call Rate < 98% - Samples whose inferred sex was not matched with the clinical information - Lower call rate samples for duplicated or monozygotic twin in the dataset - Outliers from East Asian clusters from principal component analysis with 1KGp3v5 samples. |
| Marker Number (after QC) |
autosomes: 515,587 SNVs (GRCh38) X-chromosome: 11,140 SNVs (GRCh38) |
| Japanese Genotype-phenotype Archive Dataset ID | JGAD000660 |
| Total Data Volume | 11.1 TB (vcf, tbi) |
| Comments (Policies) | NBDC policy |
| Participants/Materials |
1,285 + 2,570 + 40,907 patients from BBJ 1st cohort (1,286 + 2,573 + 41,411 samples) Total: 43,830 patients (45,270 samples) ICD10: R00, I44.0-3, I45.5-6, I47-I49, I70.9, L20, J45, I67.1, I63, G45.9, C50, I50, I21.0-9, H25-H26, C53, B18.1, B18.2, C18-C21, J44.9, L51.1-2, L27.0, E10, E11, E88.8, N80, G40, C15, D25, C23, C24, H40, E05.0, K05, R56.0, C81-C86, C90-C93, C22, J30.1, E78.0-5, E78.8-9, J84.1-9, L91.0, K74.6, C34, N04, M80-M81, C56, C25, A15-A19, C61, M05-M06, I20.1, I20.8, I20.9, C16, N20-N23, I20.0, C54 |
| Targets | metabolome (NMR) |
| Target Loci for Capture Methods | - |
| Platform | Bruker [AVANCE III HD] |
| Source | serum samples |
| Cell Lines | - |
| Parameters | Nightingale Health's proprietary software (quantification library 2020) |
| Noise reduction & Data correction | Nightingale Health's proprietary software (quantification library 2020) |
| Annotation | Nightingale Health's proprietary software (quantification library 2020) |
| Quantification Methods (software) | Nightingale Health's proprietary software (quantification library 2020) |
| Metabolic biomarkers | 250 metabolites (List) |
| Japanese Genotype-phenotype Archive Dataset ID | JGAD000683 |
| Total Data Volume | 7.1 + 15.3 + 217.9 MB (xlsx) |
| Comments (Policies) | NBDC policy |
| Participants/Materials |
peptic ulcer (ICD10: K27.9), duodenal ulcer (ICD10: K26.9), gastric ulcer (ICD10: K25.9) - BBJ1-180K: ulcers (n = 19,713), control (n = 153,178) - BBJ1-12K: ulcers (n = 1,001), control (n = 8,617) - BBJ2-42K: ulcers (n = 3,637), control (n = 34,647) - EAS meta-analysis: ulcers (n = 29,739), control (n = 240,675) (BBJ180K, BBJ1-12K, BBJ2-42k, and TMM-50K) - Cross-ancestry meta-analysis (EAS and EUR): ulcers (n = 52,032), control (n = 905,344) (BBJ180K, BBJ1-12K, BBJ2-42k, TMM-50K, FinnGen, and UKB) |
| Targets | genome wide variants |
| Target Loci for Capture Methods | - |
| Platform |
BBJ1-180K: Illumina [HumanOmniExpress、HumanExome、OmniExpressExome BeadChip] BBJ1-12K and BBJ2-42K: Illumina [Infinium Asian Screening Array BeadChip] ToMMo: Thermo Fisher Scientific [Axiom Japonica Array JPAv2] UK Biobank: Applied Biosystems [UK BiLEVE Axiom Array、UK Biobank Axiom Array] FinnGen: Thermo Fisher Scientific [FinnGen1 ThermoFisher Array or other genotyping arrays] |
| Library Source | DNAs extracted from peripheral blood cells |
| Cell Lines | - |
| Reagents (Kit, Version) |
BBJ: HumanOmniExpress, HumanExome, OmniExpressExome BeadChip kit, Infinium Asian Screening Array BeadChip kit ToMMo: Axiom 2.0 Reagent kit UK Biobank: UK BiLEVE Axiom Array、UK Biobank Axiom Array FinnGen: FinnGen1 ThermoFisher Array or other genotyping arrays |
| Genotype Call Methods (software) |
Genotype Call: GenomeStudio Pre-phasing: eagle2 Imputation: minimac4 [reference: 1KGP p3v5 ALL] |
| Association Analysis (software) | SAIGE (v0.44) |
| Filtering Methods |
Variants with imputation quality (Rsq) < 0.3 or MAC < 20 were excluded *Sample QC and Variant QC were described in the Dictionary file |
| Meta-analysis (software) | METAL |
| Marker Number (after QC) |
BBJ1-180K GWAS: ~12,013,066 variants BBJ1-12K GWAS: ~10,836,527 variants BBJ2-42K GWAS: ~11,504,022 variants EAS-specific meta-analysis : ~13,846,852 variants Cross-ancestry meta-analysis : ~19,078,654 variants |
| NBDC Dataset ID |
(Click the Dataset ID to download the files) |
| Total Data Volume |
9.7 GB (txt) |
| Comments (Policies) | NBDC policy |
DATA PROVIDER
Principal Investigator: Koichi Matsuda
Affiliation: Graduate school of Frontier Science, The University of Tokyo
Project / Group Name: Management of disease-oriented biobank in Japan for utilization
URL: https://biobankjp.org/en/index.html
Funds / Grants (Research Project Number):
| Name | Title | Project Number |
|---|---|---|
| Biobank - Construction and Utilization biobank for genomic medicine REalization (B-Cure), Japan Agency for Medical Research and Development (AMED) | Management of disease-oriented biobank in Japan for utilization |
JP20km0605001 JP21km0405215 |
| Platform Program for Promotion of Genome Medicine, Japan Agency for Medical Research and Development (AMED) | Phenotype-wide association study of 180,000 Biobank Japan samples using high density imputation of TOPMED reference panel | JP21km0405215 |
PUBLICATIONS
| Title | DOI | Dataset ID | |
|---|---|---|---|
| 1 | East Asian-specific and cross-ancestry genome-wide meta-analyses provide mechanistic insights into peptic ulcer disease | doi: 10.1038/s41588-023-01569-7 | hum0311.v5.gwas.v1 |
| 2 | Genotype imputation accuracy and the quality metrics of the minor ancestry in multi-ancestry reference panels | doi: 10.1093/bib/bbad509 | JGAS000541 |
USERS (Controlled-access Data)
| Principal Investigator | Affiliation | Country/Region | Research Title | Data in Use (Dataset ID) | Period of Data Use |
|---|---|---|---|---|---|
| Seishi Ogawa | Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University | Japan | Analysis on the relationship between clonal hematopoiesis and COVID-19 infection. | JGAD000529 | 2022/08/15-2026/03/31 |
| Yukinori Okada | Department of Statistical Genetics, Osaka University Graduate School of Medicine | Japan | Development of statistical genetic analysis methods using the whole-genome data from B cell lines of Japanese individuals | JGAD000529, JGAD000660 | 2022/09/12-2025/03/31 |
| Masaki Kato | kansai medical university | Japan | Exploratory and validation study of genetic and biological factors for the development of precision medicine algorithms for psychiatric disorders | JGAD000529 | 2023/08/25-2028/06/30 |
| Koya Fukunaga | Division of Medical Safety Science, National Institute of Health Sciences | Japan | Research on the biomarkers associated with drug-induced interstitial pneumonia | JGAD000529 JGAD000660 |
2023/02/05-2026/03/31 |
| Koya Fukunaga | Division of Medical Safety Science, National Institute of Health Sciences | Japan | Research on the biomarkers associated with drug-induced liver injury | JGAD000529 JGAD000660 |
2023/02/05-2024/03/31 |
| Koya Fukunaga | Division of Medical Safety Science, National Institute of Health Sciences | Japan | Research on the biomarkers associated with drug-induced myopathy | JGAD000529 JGAD000660 |
2023/02/05-2026/03/31 |
| Koya Fukunaga | Division of Medical Safety Science, National Institute of Health Sciences | Japan | Research on the diagnosis, treatment, and biomarkers for severe cutaneous adverse reactions | JGAD000529 JGAD000660 |
2023/02/08-2026/03/31 |
| Shigeo Kamitsuji | Statistical Analysis Division, StaGen Co., Ltd. | Japan | Genome-Wide Association Study to identify genetic factors for strabismus in Japanese population | JGAD000529 | 2023/02/13-2027/02/28 |
| Yuta Kochi | Department of Genomic Function and Diversity, Medical Research Institute, Tokyo Medical and Dental University | Japan | Genetic study of complex diseases through comprehensive analysis of functional genetic variations | JGAD000660 | 2023/04/10-2024/03/31 |
| Hiroki Kimura | Department of Psychiatry, Nagoya University Graduate school of medicine | Japan | Research on elucidation of susceptibility to brain and mental illness (vulnerability to disease onset) and efficacy and side effects of drugs (treatment responsiveness) through genetic analysis | JGAD000529 | 2023/11/17-2025/10/28 |
| Chikashi Terao | Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences | Japan | Research on personalized medicine based on genomics information | JGAD000529 | 2023/11/21-2026/03/31 |
| Yoshihiro Asano | National Cerebral and Cardiovascular Center | Japan | Nationwide Platform for the Promotion of Genomic Medicine in Cardiovascular Diseases | JGAD000529 | 2023/12/14-2035/03/31 |
| Tsukasa Okamoto | The Center for Personilized Medicine for Healthy Aging, Tokyo Medical and Dental University | Japan | Prospective study on analysis of genes causing or related to interstitial pneumonia | JGAD000529 | 2024/04/12-2025/03/31 |
| Chikashi Terao | Clinical Research Center, Shizuoka General Hospital | Japan | Investigation of Genetic Factors Associated with Human Phenotypic Traits | JGAD000529, JGAD000660, JGAD000683 |
2024/04/17-2028/12/03 |
| Emiko Noguchi | Department of Medical Genetics, Faculty of Medicine, University of Tsukuba | Japan | Genome wide association study for WDEIA and exploration of wheat products | JGAD000529 | 2024/05/09-2026/03/31 |
| Masao Nagasaki | Division of Biomedical Information Analysis, Medical Research Center for High Depth Omics, Medical Institute of Bioregulation, Kyushu University | Japan | Development and application of bioinformatics methods to facilitate the detection of genes associated with multifactorial disorders based on large-scale whole genome sequencing data of Japanese individuals | JGAD000529 | 2024/06/24-2027/03/31 |
| Kouya Shiraishi | Department of Clinical Genomics, National Cancer Center Research Institute | Japan | Search for genes involved in susceptibility to lung cancer | JGAD000529 | 2024/06/24-2025/12/31 |
| Norihiro Kato | Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine | Japan | Study of genetic predisposition of primary aldosteronism and its clinical significance | JGAD000529 | 2024/06/24-2029/03/31 |
| Taisei Mushiroda | Laboratory for Pharmacogenomics, RIKEN Center for Integrative Medical Sciences | Japan | Search of genomic biomarkers associated with drug-induced eruptions | JGAD000529, JGAD000660 |
2024/08/01-2028/03/31 |
