DbTMM: an integrated database of large-scale cohort, genome and clinical data for the Tohoku Medical Megabank Project

Fumiki Katsuoka ,Kengo Kinoshita ,Soichi Ogishima ,Gen Tamiya ,S Koshiba ,Masaru Sakurai ,Satoshi Makino ,Maiko Kageyama ,Yuki Harada ,Kazuyuki Kitatani ,Mana Kogure ,Masahiro Hiratsuka ,Hirohito Metoki ,Inaho Danjoh ,Takehide Onuma ,Atsushi Hozawa ,Naoto Ishii ,Nobuo Fuse ,Yayoi Aizawa ,Keiko Murakami ,Miho Kuriki ,Kazuyuki Kojima ,Kazuharu Misawa ,Takahiro Nobukuni ,Tomohiro Nakamura ,Hideyasu Kiyomoto ,Atsushi Shimizu ,Norihide Maikusa ,Hiroko Matsubara ,Hisaaki Kudo ,Yoshio Kuroki ,Tadashi Ishii ,Yosuke Aoki ,Junko Kawashima ,Kazuhiko Igarashi ,Takumi Hirata ,Naho Tsuchiya ,Naoki Nakamura ,Tsuneyo Mimori ,Hiroyuki Matsui ,Takako Toda ,Hiroshi Tanaka ,Sachiko Hirano ,Sachiko Nagase ,Shinichi Higuchi ,Sachie Koreeda ,Naoki Nakaya ,Noriko Ishida ,Masayuki Yamamoto ,Tomoko Kobayashi ,Taku Obara ,Hiroshi Kawame ,Masahiro Kikuya ,Kazuki Kumada ,Koichi Chida ,Shunji Mugikura ,Tomomi Kiyama ,Sadayoshi Ito ,Ikuko N Motoike ,Keita Iida ,Kuniyasu Shimokawa ,Hiroaki Tomita ,Koichi Asahi ,Akira Narita ,Eiichi N Kodama ,Shu Tadaka ,Satoshi Nagaie ,Fumihiko Ueno ,Ryosuke Ishiwata ,Kichiya Suzuki ,Hideki Ohmomo ,Fuji Nagami ,Yohei Hamanaka ,Naoko Minegishi ,Shihoko Koyama ,Kozo Tanno ,Akira Uruno ,Makoto Sasaki ,Ritsuko Shimizu ,Kiyoshi Itō ,Jin Inoue ,Shigeo Kure ,Hiroaki Hashizume ,Shinichi Kuriyama ,Satoshi Mizuno ,Mami Ishikuro ,Akito Tsuboi

doi:10.1038/s41439-021-00175-5

Abstract

To reveal gene-environment interactions underlying common diseases and estimate the risk for common diseases, the Tohoku Medical Megabank (TMM) project has conducted prospective cohort studies and genomic and multiomics analyses. To establish an integrated biobank, we developed an integrated database called “dbTMM” that incorporates both the individual cohort/clinical data and the genome/multiomics data of 157,191 participants in the Tohoku Medical Megabank project. To our knowledge, dbTMM is the first database to store individual whole-genome data on a variant-by-variant basis as well as cohort/clinical data for over one hundred thousand participants in a prospective cohort study. dbTMM enables us to stratify our cohort by both genome-wide genetic factors and environmental factors, and it provides a research and development platform that enables prospective analysis of large-scale data from genome cohorts.

Highlights

Genome-wide association studies (GWASs), a genome-wide approach for identifying genetic variants associated with a trait[1], have accelerated investigations of the genetic architecture of complex diseases
The Japonica array provides better participants in a prospective cohort study, which allows us to stratify our cohort by both genome-wide genetic factors and environmental factors. database TMM (dbTMM) allows researchers to generate hypotheses and begin assessing the potential of Tohoku Medical Megabank (TMM) data for their studies
Database, which we refer to as database TMM

Summary

Introduction

Genome-wide association studies (GWASs), a genome-wide approach for identifying genetic variants associated with a trait[1], have accelerated investigations of the genetic architecture of complex diseases. To search genome data on a variant-by-variant basis and to precisely stratify the cohort population by using gene variant and environmental data, we need to establish an integrated database. DbTMM is the first database to store individual whole-genome data on a variant-byvariant basis and cohort/clinical data for over a hundred thousand

Results

Conclusion