Research ID
hum0014-v18Release info
This page is a past version (v18). The latest version is v37.
Latest version (v37)Research title
Bio Bank Japan project
Research overview
- Aims
- Identify disease-related genes in Japanese
- Methods
- Genomic DNA samples were genotyped by following methods: Human610-Quad BeadChip, HumanHap550v3 Genotyping BeadChip, HumanOmniExpress-12 BeadChip, HumanExome BeadChip, OmniExpressExome BeadChip (Illumina), high-density oligonucleotide arrays (Perlegen Sciences), or Invader (Hologic Japan). Genome-Wide Association Studies (GWAS) for myocardial infarction (MI) , type II diabetes mellitus (T2DM), Atopic dermatitis (AD), atrial fibrillation (AF), Body Mass Index (BMI), primary open-angle glaucoma (POAG), 58 quantitative traits, age at menarche / menopause, smoking behaviour, height, and 41 diseases (among them, the samples of 4 diseases were partially overlapped with those of previous release) were performed using about 500-2700K variants. Meta analyses for T2DM with diabetic nephropathy and for T2DM were also performed. A whole-genome sequencing analysis for 1,026 patients, who were registered Bio Bank Japan from 2003 - 2007 was performed with Illumina HiSeq2500. Target sequencing analyses of 11 hereditary breast cancer genes in 7,104 breast cancer patients and 23,731 controls, and 8 hereditary prostate cancer genes in 7,636 prostate cancer patients and 12,366 controls were also performed with Illumina HiSeq2500. A new reference panel was build with WGS data of the biobank Japan project (N=1,037) and the 1KGP p3v5 ALL (N=2,504).
- Participants/materials
- Participants for the Tailor-made Medical Treatment Program (BioBank Japan: BBJ)
Datasets
The list is the one this version published; each dataset's content is shown as it is now.
| Cart | Dataset ID | Type of data | Analysis method | Access criteria | Date published |
|---|---|---|---|---|---|
| NHA000001 | GWAS for MI |
| Unrestricted-access | 2014-09-30 | |
| NHA000008 | Genotype frequencies in 934 healthy individuals (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000031 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000014 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000040 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000017 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000035 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000028 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000032 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000041 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000039 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000011 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000012 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000019 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000015 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000030 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000037 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000013 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000018 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000027 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000016 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000025 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000023 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000036 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000043 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000033 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000042 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000022 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000034 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000038 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000010 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000026 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000009 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000020 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000029 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000021 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000024 | Genotype frequencies in each disease (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000006 | Genotype frequencies in 182 esophageal cancer patients (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000007 | Genotype frequencies in 92 amyotrophic lateral sclerosis (ALS) patients (JSNP data) |
| Unrestricted-access | 2015-12-28 | |
| NHA000044 | GWAS for T2DM [1] |
| Unrestricted-access | 2016-01-28 | |
| NHA000045 | GWAS for T2DM [2] |
| Unrestricted-access | 2016-01-28 | |
| NHA000046 | GWAS for AD |
| Unrestricted-access | 2016-02-02 | |
| JGAD000101 | Genotype and phenotype data for 8180 AF patients |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000102 | Genotype and phenotype data for 8180 AF patients |
| Controlled-access (Type I) | 2020-09-28 | |
| NHA000052 | GWAS for AF |
| Unrestricted-access | 2017-05-18 | |
| JGAD000124 | BMI data for 158,284 individuals Genotype data for 182,505 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000123 | BMI data for 158,284 individuals Genotype data for 182,505 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| NHA000053 | GWAS for BMI |
| Unrestricted-access | 2017-09-08 | |
| JGAD000144 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000145 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000146 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000147 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000148 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000149 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000150 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000151 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000152 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000153 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000154 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000155 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000156 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000157 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000158 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000159 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000160 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000161 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000162 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000163 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000164 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000165 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000166 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000167 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000168 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000169 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000170 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000171 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000172 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000173 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000174 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000175 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000176 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000177 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000178 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000179 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000180 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000181 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000182 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000183 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000184 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000185 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000186 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000187 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000188 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000189 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000190 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000191 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000192 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000193 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000194 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000195 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000196 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000197 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000198 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000199 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000200 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000201 | 58 quantitative traits data for 200,849 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| JGAD000220 | WGS for 1,026 individuals |
| Controlled-access (Type I) | 2020-09-28 | |
| NHA000068 | GWAS for POAG |
| Unrestricted-access | 2018-04-04 | |
| NHA000070 | GWAS for 58 quantitative traits |
| Unrestricted-access | 2018-05-01 | |
| NHA000073 | GWAS for age at menarche and menopause |
| Unrestricted-access | 2018-08-07 | |
| NHA000072 | GWAS for age at menarche and menopause |
| Unrestricted-access | 2018-08-07 | |
| JGAD000209 | target sequencing of 11 hereditary breast cancer genes in 7,104 breast cancer patients and 23,731 controls |
| Controlled-access (Type I) | 2020-09-28 | |
| NHA000075 | meta analysis of 2 GWASs for T2DM with diabetic nephropathy |
| Unrestricted-access | 2018-12-10 | |
| NHA000078 | meta analysis of 4 GWASs for T2DM |
| Unrestricted-access | 2019-01-25 | |
| NHA000084 | GWAS for smoking behaviour |
| Unrestricted-access | 2019-03-26 | |
| NHA000080 | GWAS for smoking behaviour |
| Unrestricted-access | 2019-03-26 | |
| NHA000081 | GWAS for smoking behaviour |
| Unrestricted-access | 2019-03-26 | |
| NHA000082 | GWAS for smoking behaviour |
| Unrestricted-access | 2019-03-26 | |
| NHA000083 | GWAS for smoking behaviour |
| Unrestricted-access | 2019-03-26 | |
| NHA000088 | GWAS for height |
| Unrestricted-access | 2019-09-27 | |
| JGAD000288 | target sequencing of 8 hereditary prostate cancer genes in 7,636 prostate cancer patients and 12,366 controls |
| Controlled-access (Type I) | 2020-09-28 | |
| NHA000090 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000091 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000089 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000107 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000098 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000092 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000099 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000094 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000095 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000097 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000100 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000093 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000110 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000101 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000126 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000104 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000105 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000103 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000106 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000109 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000108 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000111 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000115 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000113 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000096 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000114 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000116 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000117 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000119 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000118 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000123 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000121 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000120 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000112 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000124 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000122 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000125 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000102 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000128 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000127 | GWAS for 40 diseases |
| Unrestricted-access | 2019-10-08 | |
| NHA000129 | GWAS for 40 diseases |
| Unrestricted-access | 2019-11-26 |
Data provider
- Principal investigator
- Michiaki Kubo
- Affiliation
- RIKEN Center for Integrative Medical Sciences
Research projects
| Name | URL |
|---|---|
Tailor-made Medical Treatment Program (Bio Bank Japan: BBJ) |
Grants
| Name | Title | Project number |
|---|---|---|
Ministry of Education, Culture, Sports, Science and Technology in Japan | Tailor-made Medical Treatment Program (the 3rd phase) | N/A |
Tailor-Made Medical Treatment with the BioBank Japan Project (BBJ), Japan Agency for Medical Research and Development (AMED) | Generating large-scale data of genetic polymorphism to identify disease-related genes |
|
Related publications
| Title | DOI | Dataset ID |
|---|---|---|
A genome-wide association study identifies PLCL2 and AP3D1-DOT1L-SF3A2 as new susceptibility loci for myocardial infarction in Japanese. | ||
A functional variant in ZNF512B is associated with susceptibility to amyotrophic lateral sclerosis in Japanese. | ||
Functional variants in ADH1B and ALDH2 coupled with alcohol and smoking synergistically enhance esophageal cancer risk. | ||
SNPs in KCNQ1 are associated with susceptibility to type 2 diabetes in East Asian and European populations. | ||
Common variants in a novel gene, FONG on chromosome 2q33.1 confer risk of osteoporosis in Japanese. | ||
Genome-wide association studies in the Japanese population identify seven novel loci for type 2 diabetes. | ||
Multi-ancestry genome-wide association study of 21,000 cases and 95,000 controls identifies new risk loci for atopic dermatitis. | ||
Genome-wide association study identifies eight new susceptibility loci for atopic dermatitis in the Japanese population. | ||
Identification of six new genetic loci associated with atrial fibrillation in the Japanese population. | ||
Genome-wide association study identifies 112 new loci for body mass index in the Japanese population. | ||
Genome-wide association study identifies seven novel susceptibility loci for primary open-angle glaucoma. | ||
Genetic analysis of quantitative traits in the Japanese population links cell types to complex human diseases. | ||
Elucidating the genetic architecture of reproductive ageing in the Japanese population | ||
Deep whole-genome sequencing reveals recent selection signatures linked to evolution and disease risk of Japanese. | ||
Germline pathogenic variants of 11 breast cancer genes in 7,051 Japanese patients and 11,241 controls. | ||
A Variant within the FTO confers susceptibility to diabetic nephropathy in Japanese patients with type 2 diabetes | ||
Identification of 28 new susceptibility loci for type 2 diabetes in the Japanese population | ||
GWAS of smoking behaviour in 165,436 Japanese people reveals seven new loci and shared genetic architecture. | ||
Characterizing rare and low-frequency height-associated variants in the Japanese population | ||
Germline pathogenic variants in 7,636 Japanese patients with prostate cancer and 12,366 controls. | ||
In submission | doi: | N/A |
Controlled access users
| Principal investigator | Affiliation | Country/Region | Research title | Period of data use | Dataset ID |
|---|---|---|---|---|---|
| Mark Daly | Broad Institute of MIT and Harvard | Massachusetts, United States | BioBank Japan (BBJ) Dataset | 2018-09-11 – 2028-07-31 | |
| 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 | 2018-09-20 – 2029-03-31 | |
| SHIGEO KAMITSUJI | Statistical Analysis Division, StaGen Co., Ltd. | Japan | Pharmcogenomics study: Study on genetic risks of an adverse event by a new drug | 2018-10-04 – 2019-08-29 | |
| Katsushi Tokunaga | Department of Human Genetics, Graduate School of Medicine, The University of Tokyo | 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 in Japanese individuals | 2018-11-13 – 2027-03-31 | |
| Tatsuhiko Tsunoda | Department of Medical Science Mathematics, Medical Research Institute, Tokyo Medical andDental University | Japan | Research on big data analysis for precision medicine | 2018-12-18 – 2021-06-18 | |
| Liming Liang | Department of Epidemiology, Harvard T.H. Chan School of Public Health | Massachusetts, United States | Genetic effect, genetic correlation and interaction with environmental exposure for complex traits and diseases across populations | 2019-01-21 – 2028-12-31 | |
| Masao Nagasaki | Department of Integrative Genomics, Tohoku Medical Megabank Organization,Tohoku University | Japan | Development and application of bioinformatics methods to facilitate the detection of genes associated with multifactorial disordersbased on large-scale whole genome sequencing data in Japanese individuals | 2019-01-31 – 2021-03-17 | |
| Seishi Ogawa | Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University | Japan | Comprehensive genome analysis in solid tumors | 2019-02-04 – 2021-07-30 | |
| SHIGEO KAMITSUJI | Statistical Analysis Division, StaGen Co., Ltd. | Japan | Genome-wide association study for comitant strabismus susceptibility in Japanese patients | 2019-03-13 – 2022-03-29 | |
| Takashi Kohno | Division of genome biology, National Cancer Research Institute | Japan | Elucidation of immune-system networks between host and tumor based on genomic analysis | 2019-04-15 – 2029-03-31 | |
| Shigeo Horie | Department of Urology, Juntendo University, Graduate School of Medicine | Japan | Disease risk analysis of mosaic loss of chromosome Y in blood cells | 2019-05-14 – 2029-03-31 | |
| Tatsuhiko Tsunoda | Laboratory for Medical Science Mathematics, Department of Biological Sciences, Graduate School of Science, Tokyo University | Japan | Research on sequence, image data analysis for precision medicine | 2019-06-06 – 2023-08-29 | |
| Masayuki Yamamoto | Tohoku Medical Megabank Organization | Japan | Construction of Japanese whole genome database | 2019-06-24 – 2022-04-15 | |
| Kouya Shiraishi | Division of Genome Biology, National Cancer Research Institute | Japan | Elucidation of immune-system networks between host and tumor based on genomic analysis | 2019-08-05 – 2029-03-31 | |
| SHIGEO KAMITSUJI | Statistical Analysis Division, StaGen Co., Ltd. | Japan | Mendelian randomization study using genetic markers of uric acid levels as an instrumental variable | 2019-08-16 – 2024-03-13 | |
| SHIGEO KAMITSUJI | Statistical Analysis Division, StaGen Co., Ltd. | Japan | Mendelian randomization study using 58 clinical laboratory tests and SNP genotype data. | 2019-08-22 – 2024-03-13 | |
| Osamu Ogasawara | Bioinformation and DDBJ Center, National Institute of Genetics | Japan | Evaluation of human genome analysis workflow using JGA/AGD genome data. | 2019-10-11 – 2024-07-05 | |
| Seishi Ogawa | Department of Medical science, Kyoto University | Japan | Comprehensive analysis of genetic alterarions in hematological malignancies | 2019-11-14 – 2024-07-11 | |
| Yasushi Okazaki | Diagnostics and Therapeutics of Intractable Diseases, Graduate School of Medicine, Juntendo University | Japan | Identification of disease biomarkers by disease cohort research network -Whole genome sequencing of epilepsy- | 2020-06-04 – 2023-06-30 | |
| Hata Chihiro | Bioinformation and DDBJ Center, National Institute of Genetics | Japan | Identification of hypomorphic mutations in Japanese breast cancer patients | 2020-06-04 – 2028-03-31 | |
| Yosuke Kawai | Genome Medical Science Project, National Center for Global Health and Medicine | Japan | Large scale genome analysis of modern human genomes to infer the origin of Yaponesians | 2020-06-19 – 2028-03-31 | |
| Nakao Iwata | Department of Psychiatry, Fujita Health University School of Medicine | Japan | Research for investigating susceptibility of mental state, mental disorders, drug efficacy and side effects through genetic analysis | 2020-08-17 – 2024-07-22 | |
| Charleston Chiang | Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California | California, United States | Investigating the evolution of complex genetic architecture in participants of Biobank Japan | 2022-03-03 – 2030-07-01 | |
| Hae Kyung Im | Biological Sciences Division, University of Chicago | Illinois, United States | Predicted Gene Expression: High Power, Mechanism, and Direction of Effect | 2020-09-15 – 2023-11-06 | |
| Atray Dixit | Coral Genomics, Inc. | California, United States | Derivation and Evaluation of Functional Response Scores | 2020-08-24 – 2022-01-17 | |
| SHIGEO KAMITSUJI | Statistical Analysis Division, StaGen Co., Ltd. | Japan | Identifying the genetic risk factors for Stent Thrombosis by genome-wide association study | 2022-03-07 – 2025-02-17 | |
| Kazuhiro Nakayama | Department of Integrated Biosciences, Graduate School of Frontier Sciences, The University of Tokyo | Japan | Investigation of genome variation influening activity of brown adipose tissues | 2022-03-07 – 2027-09-18 | |
| Taisei Mushiroda | RIKEN Center for Integrative Medical Sciences | Japan | SNP analysis of wheat allergy | 2021-03-26 – 2028-03-31 | |
| Hongyu Zhao | Department of Biostatistics, Yale School of Public Health | United States | Leveraging multi-ethnic data and functional annotations in casual variant identification, genetic correlation estimation, and genetic risk prediction | 2024-12-25 – 2030-03-01 | |
| KEISHI FUJIO | Department of Allergy and Rheumatology, Graduate School of Medicine, The University of Tokyo, University of Tokyo | Japan | Integrative analysis of immune-cell eQTL data and large-scaled GWAS data in Japanese | 2020-12-16 – 2026-09-29 | |
| Masataka Kikuchi | Department of Genome Informatics, Graduate School of Medicine, Osaka University | Japan | Imputation analysis using a Japanese reference panel | 2020-12-16 – 2022-10-03 | |
| Fumihiko Matsuda | Center for Genomic Medicine, Kyoto University | Japan | Elucidation of Japanese genetic diversity | 2021-02-08 – 2025-03-31 | |
| Emiko Noguchi | Department of Medical Genetics, Faculty of Medicine, University of Tsukuba | Japan | Exploratory study of genetic factors in allergic diseases | 2021-03-26 – 2032-03-31 | |
| Gil McVean | King Charles House, Genomics plc | United Kingdom | Development of polygenic risk scores in diverse ancestries for diseases, traits and conditions | 2022-07-19 – 2025-06-17 | |
| Masao Nagasaki | Center for Genomic Medicine, Graduate School of Medicine Center for the Promotion of Interdisciplinary Education and Research, Kyoto 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 | 2021-04-01 – 2024-08-23 | |
| Noriko Sato | Department of Molecular Epidemiology Medical Research Institute, Tokyo Medical and Dental University | Japan | Analysis of genetic and environmental risks of obesity and diabetes based on regional cohort longitudinal data | 2021-04-13 – 2022-03-17 | |
| Takashi Kohno | Division of Genome Biology, National Cancer Center Research Institute | Japan | Identification of genetic risk factors in AYA(Adolescence and Young Adult) cancer | 2021-05-26 – 2028-12-31 | |
| Akihiro Fujimoto | School of Integrated Health Sciences, Faculty of Medicine, The University of Tokyo | Japan | Comprehensive analysis of mutations and genetic diversity by analyzing whole-genome sequence data | 2021-09-21 – 2024-12-02 | |
| Yasunobu Nagata | Department of hematology, Nippon Medical School | Japan | Identification of the mechanisms for pathogenesis of hematologic tumors based on novel genetic abnormalities | 2021-06-08 – 2026-03-31 | |
| Atsushi Kawakami | リウマチ・膠原病内科, 長崎大学病院 | Japan | An exploratory study to determine the genetic polymorphisms or mutations associated with type 1 diabetes and interstitial lung disease induced by immune checkpoint inhibitor; nivolumab | 2021-06-16 – 2024-04-02 | |
| Yoshihiro Asano | Department of Cardiovascular Medicine Graduate School of Medicine, Osaka University | Japan | Sensitive gene analysis of hereditary cardiovascular disease | 2021-07-26 – 2027-05-31 | |
| Hironori Masuko | Department of Pulmonary Medicine, University of Tsukuba | Japan | Search for susceptibility genes for chronic inflammatory airway diseases | 2021-08-16 – 2027-03-31 | |
| Takashi Kohno | Division of Genome Biology, National Cancer Center Research Institute | Japan | Identification of genetic risk factors in AYA(Adolescence and Young Adult) cancer | 2021-09-28 – 2028-12-31 | |
| Fumihiko Matsuda | Center for Genomic Medicine, Kyoto University | Japan | Development of personalized medicine | 2021-09-16 – 2028-03-31 | |
| Takashi Matsuda | Advanced Informatics & Analytics, Astellas Pharma Inc. | Japan | Investigation of the correlation between Liver cancer/Hepatitis B and polymorphism | 2021-11-11 – 2022-08-01 | |
| Masanori Arita | Bioinformation and DDBJ Center, National Institute of Genetics | Japan | Provision of processed JGA data analyzed by DDBJ Center and NBDC | 2021-10-07 – 2030-03-31 | |
| Emiko Noguchi | Department of Medical Genetics, Faculty of Medicine, University of Tsukuba | Japan | Identification of the pathogenic factors for food allergy | 2021-12-08 – 2029-03-31 | |
| Joshua Chiou | Internal Medicine Research Unit, Pfizer | Massachusetts, United States | Evaluating GWAS associations from Biobank Japan to Support Confidence in Rationale for Therapeutic Targets | 2022-02-03 – 2025-12-21 | |
| Yosuke Kawai | 人癌病因遺伝子分野, 東京大学医科学研究所 | Japan | Population Genetic Analysis of the Origin of Japanese Populations | 2021-12-15 – 2026-01-22 | |
| Masanori Arita | Bioinformation and DDBJ Center, National Institute of Genetics | Japan | Development of the imputation analysis program and running environment in the NIG supercomputer for personal genome analysis. | 2021-11-29 – 2030-03-31 | |
| Toshiharu Ninomiya | Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Kyushu University | Japan | Japan Prospective Studies Collaboration for Aging and Dementia (JPSC-AD) | 2021-12-13 – 2029-07-31 | |
| Hirofumi Nakaoka | Department of Cancer Genome Research, Sasaki Institute | Japan | Analysis of hypomorphic variants in breast cancer-associated genes by using large-scale sequencing data sets | 2022-08-18 – 2026-07-23 | |
| Gil McVean | King Charles House, Genomics plc | United Kingdom | Using large-scale reference panels for imputation and ancestry analysis to support target discovery and polygenic risk score models | 2022-08-04 – 2025-07-23 | |
| Emiko Noguchi | Department of Medical Genetics, Faculty of Medicine, University of Tsukuba | Japan | Research on genetic predisposition to inflammatory lung disease | 2022-09-21 – 2027-03-31 | |
| Keiko Yamazaki | Department of Public Health, Chiba University Graduate School of Medicine | Japan | Prediction of effectiveness to molecular target drugs in Japanese patients with inflammatory bowel disease | 2022-11-15 – 2030-03-31 | |
| Nuria Lopez-Bigas | Biomedical Genomics Lab Cancer Science, Institute for Research in Biomedicine (IRB Barcelona) | Spain | Study of the genetic basis of clonal hematopoiesis | 2022-11-08 – 2027-09-12 | |
| Masataka Kikuchi | Department of Computational Biology and Medical Sciences, The University of Tokyo | Japan | Imputation analysis using a Japanese reference panel | 2022-10-03 – 2025-10-09 | |
| ryosuke kitoh | 医学部 耳鼻咽喉科頭頸部外科, 信州大学 | Japan | Genome-wide association study of the sudden sensorineural hearing loss | 2022-12-22 – 2027-03-31 | |
| Kei Yura | Natural Science Division, Faculty of Core Research, Ochanomizu University | Japan | Data Analysis for Phenotype Prediction of Cancer Suppressor Gene BRCA1 variants | 2023-03-17 – 2028-03-31 | |
| Shigeo Kamitsuji | Statistical Analysis Division, StaGen Co., Ltd. | Japan | Genome-Wide Association Study to identify genetic factors for strabismus in Japanese population | 2023-02-14 – 2027-02-28 | |
| Yoshihiro Onouchi | Department of Public Health, Chiba University Graduate School of Medicine | Japan | A Multicenter Study to Identify Genetic Factors in Kawasaki Disease | 2023-04-06 – 2030-03-31 | |
| Yoshihiro Onouchi | Department of Public Health, Chiba University Graduate School of Medicine | Japan | A study of the genetic background of differences in antibody response to COVID-19 vaccine. | 2023-04-24 – 2030-03-31 | |
| Masaki Kato | 精神神経科, 関西医科大学 | Japan | Exploratory and validation study of genetic and biological factors for the development of precision medicine algorithms for psychiatric disorders. | 2023-08-25 – 2028-06-30 | |
| 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 | 2023-11-17 – 2028-10-28 | |
| Hiroyuki Mishima | Department of Human Genetics, Atomic Bomb Disease Institute, Nagasaki University | Japan | Development of Methods to Mitigate Batch Effects in Human Whole Genome Sequencing | 2024-04-16 – 2027-03-31 | |
| yasuhiro mochida | Shonan Kamakura General Hospital | Japan | Association between Clonal hematopoiesis of indeterminate potential and Chronic Kidney Disease in Japanese cohort study | 2024-02-07 – 2027-03-31 | |
| Chikashi Terao | Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences | Japan | Research on personalized medicine based on genomics information | 2023-11-21 – 2026-07-10 | |
| Chikashi Terao | Immunology Research, Clinical Research Center, Shizuoka General Hospital | Japan | Investigation of Genetic Factors Associated with Human Phenotypic Traits | 2024-04-25 – 2028-12-03 | |
| 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 | 2024-06-24 – 2027-03-31 | |
| Koichi Matsuda | Clinical genome sequencing, The University of Tokyo | Japan | Disease Cohort Research Network for Disease Marker Exploratory Studies | 2024-06-17 – 2029-03-31 | |
| Norihiro Kato | Gene Diagnostics and Therapeutics, National Center for Global Health and Medicine | Japan | Study of genetic predisposition of primary aldosteronism and its clinical significance | 2024-06-24 – 2029-03-31 | |
| Kouya Shiraishi | Department of Clinical Genomics, National Cancer Center Research Institute | Japan | Search for genes involved in susceptibility to lung cancer | 2024-06-24 – 2025-12-15 | |
| Taisei Mushiroda | Laboratory for Pharmacogenomics, RIKEN Center for Integrative Medical Sciences | Japan | Search of genomic biomarkers associated with drug-induced eruptions | 2024-08-01 – 2028-03-31 | |
| Masahiro Nakatochi | Public Health Informatics Unit Department of Integrated Health Sciences, Nagoya University | Japan | Exploration of factors involved in the onset, progression, and prognosis of amyotrophic lateral sclerosis. | 2024-08-27 – 2030-03-31 | |
| Masanori Arita | Bioinformation and DDBJ Center, National Institute of Genetics | Japan | Provision of processed JGA data analyzed by DDBJ Center and DBCLS | 2025-04-28 – 2030-03-31 | |
| Atsushi Ono | Hiroshima University | Japan | Utilizing Genomic Information to Address Challenges in Liver Diseases | 2025-06-25 – 2034-03-31 | |
| Kouya Shiraishi | Department of Clinical Genomics, National Cancer Center Research Institute | Japan | AYA (Adolescence and Young Adult) Generation Cancer Research Aiming to Identify Genetic Factors that Contribute to Personalized Prevention | 2025-05-02 – 2026-04-07 | |
| Masahiro Miyake | Kyoto University | Japan | Genetic research on ophthalmic diseases | 2025-06-02 – 2027-03-31 | |
| Norihiro Kato | Gene Diagnostics and Therapeutics, National Center for Global Health and Medicine | Japan | Clinical Application of Polygenic Risk Scores for Glaucoma in the Japanese Population | 2025-11-17 – 2030-03-31 | |
| Taku Nakashima | Department of Molecular and Internal Medicine, Hiroshima University | Japan | A Study on the Relationship Between Pulmonary Fibrosis and Clonal Hematopoiesis | 2025-12-11 – 2028-03-31 | |
| Jian Huang | Institute for Human Development and Potential (IHDP), Agency for Science, Technology and Research (A*STAR) | Singapore | Multi-omic causal inference strategy for drug repurposing and pharmacovigilance across the lifespan | 2026-04-13 – 2028-03-31 | |
| Hirofumi Nakaoka | Department of Biomedical Data Science, Kagoshima University Graduate School of Medical and Dental Sciences | Japan | Analysis of hypomorphic variants in breast cancer-associated genes by using large-scale sequencing data sets | 2026-04-13 – 2030-03-31 | |
| Taisuke Ishikawa | Kagoshima University | Japan | Elucidation of the genetic basis of arrhythmia syndromes | 2026-08-05 – 2029-03-31 | |
| Ryota Hashimoto | Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry | Japan | Exploratory research on new diagnostic classification and pathology elucidation of neuropsychiatric disorders based on biological data | 2026-09-10 – 2028-07-31 | |
| Chikashi Terao | Center for Genomic Medicine, Research Promotion Headquarters, Fujita Health University | Japan | Research on Personalized Medicine Leveraging Integrated Genomic Data | 2026-09-03 – 2036-03-31 | |
| Kengo Yoshida | Immunology, Molecular Biosciences, Radiation Effects Research Foundation | Japan | Preliminary study to determine the applicability for GWAS of DNA extractable blood smears and blood-infiltrated paper discs preserved in the past | 2026-10-15 – 2028-01-01 | |
| Masataka Kikuchi | Department of Molecular Genetics, Niigata University | Japan | Imputation analysis using a Japanese reference panel | 2026-09-10 – 2028-03-31 |