Tohoku University Tohoku Medical Megabank Organization (Seizo Koshiba)
2019.09.20

1.   Sugawara Junichi, Ochi Daisuke, Yamashita Riu, et al. Maternity Log study: a longitudinal lifelog monitoring and multiomics analysis for the early prediction of complicated pregnancy. BMJ Open. 2019; 9 (2): bmjopen-2018-025939. doi:10.1136/bmjopen-2018-025939  
2.   Wada Yoichi, Kikuchi Atsuo, Arai-Ichinoi Natsuko, et al. Biallelic GALM pathogenic variants cause a novel type of galactosemia. Genetics in Medicine. 2019; 21 (6): 1286-1294. doi:10.1038/s41436-018-0340-x  
3.   Yamaguchi-Kabata Yumi, Yasuda Jun, Uruno Akira, et al. Estimating carrier frequencies of newborn screening disorders using a whole-genome reference panel of 3552 Japanese individuals. Human Genetics. 2019; 138 (4): 389-409. doi:10.1007/s00439-019-01998-7  
4.   Tadaka Shu, Katsuoka Fumiki, Ueki Masao, et al. 3.5KJPNv2: an allele frequency panel of 3552 Japanese individuals including the X chromosome. Human Genome Variation. 2019; 6 (1): 28. doi:10.1038/s41439-019-0059-5  
5.   Sato Tomonori, Kawasaki Yoshihide, Maekawa Masamitsu, et al. Value of global metabolomics in association with diagnosis and clinicopathological factors of renal cell carcinoma. International journal of cancer. 2019; 145 (2): 484-493. doi:10.1002/ijc.32115  
6.   Kuriyama Shinichi, Metoki Hirohito, Kikuya Masahiro, et al. Cohort Profile: Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study (TMM BirThree Cohort Study): Rationale, Progress and Perspective. International Journal of Epidemiology. 2019; : . doi:10.1093/ije/dyz169  
7.   Hitomi Yuki, Ueno Kazuko, Kawai Yosuke, et al. POGLUT1, the putative effector gene driven by rs2293370 in primary biliary cholangitis susceptibility locus chromosome 3q13.33. Scientific reports. 2019; 9 (1): 102. doi:10.1038/s41598-018-36490-1  
8.   Yasuda Jun, Kinoshita Kengo, Katsuoka Fumiki, et al. Genome analyses for the Tohoku Medical Megabank Project towards establishment of personalized healthcare. The Journal of Biochemistry. 2019; 165 (2): 139-158. doi:10.1093/jb/mvy096  
9.   Koshiba Seizo, Motoike Ikuko, Saigusa Daisuke, et al. Omics research project on prospective cohort studies from the Tohoku Medical Megabank Project. Genes to Cells. 2018; 23 (6): 406-417. doi:10.1111/gtc.12588  
10.   Saigusa Daisuke, Suzuki Norio, Matsumoto Yotaro, et al. Detection of novel metabolite for roxadustat doping by global metabolomics. Journal of biochemistry. 2018; 163 (6): e1. doi:10.1093/jb/mvy036  
11.   Saigusa Daisuke, Suzuki Norio, Matsumoto Yotaro, et al. Detection of novel metabolite for Roxadustat doping by global metabolomics. Journal of biochemistry. 2018; : . doi:10.1093/jb/mvy028  
12.   Yamaguchi-Kabata Yumi, Yasuda Jun, Tanabe Osamu, et al. Evaluation of reported pathogenic variants and their frequencies in a Japanese population based on a whole-genome reference panel of 2049 individuals. Journal of Human Genetics. 2018; 63 (2): 213-230. doi:10.1038/s10038-017-0347-1  
13.   Tadaka Shu, Saigusa Daisuke, Motoike Ikuko N., et al. jMorp: Japanese Multi Omics Reference Panel. Nucleic Acids Research. 2018; 46 (D1): D551-D557. doi:10.1093/nar/gkx978  
14.   Tadaka Shu, Saigusa Daisuke, Motoike Ikuko N, et al. jMorp: Japanese Multi Omics Reference Panel. Nucleic acids research. 2018; 46 (D1): D551-D557. doi:10.1093/nar/gkx978  
15.   Sato Kota, Saigusa Daisuke, Saito Ritsumi, et al. Metabolomic changes in the mouse retina after optic nerve injury. Scientific Reports. 2018; 8 (1): 11930. doi:10.1038/s41598-018-30464-z  
16.   Sato Kota, Saigusa Daisuke, Saito Ritsumi, et al. Metabolomic changes in the mouse retina after optic nerve injury. Scientific reports. 2018; 8 (1): 11930. doi:10.1038/s41598-018-30464-z  
17.   Kuriyama Shinichi, Yaegashi Nobuo, Nagami Fuji, et al. The Tohoku Medical Megabank Project: Design and Mission. Journal of Epidemiology. 2016; 26 (9): 493-511. doi:10.2188/jea.JE20150268  
18.   Saigusa Daisuke, Okamura Yasunobu, Motoike Ikuko N., et al. Establishment of Protocols for Global Metabolomics by LC-MS for Biomarker Discovery. PLOS ONE. 2016; 11 (8): e0160555. doi:10.1371/journal.pone.0160555  
19.   Koshiba Seizo, Motoike Ikuko, Kojima Kaname, et al. The structural origin of metabolic quantitative diversity. Scientific Reports. 2016; 6 (1): 31463. doi:10.1038/srep31463  
20.   Kasai Takuma, Koshiba Seizo, Yokoyama Jun, Kigawa Takanori. Stable isotope labeling strategy based on coding theory. Journal of biomolecular NMR. 2015; 63 (2): 213-21. doi:10.1007/s10858-015-9978-8  
21.   Tochio Naoya, Umehara Takashi, Nakabayashi Kazuhiko, et al. Solution structures of the DNA-binding domains of immune-related zinc-finger protein ZFAT. Journal of Structural and Functional Genomics. 2015; 16 (2): 55-65. doi:10.1007/s10969-015-9196-3  
22.   Koizumi Taichi, Terada Tohru, Nakajima Ken-ichiro, et al. Identification of key neoculin residues responsible for the binding and activation of the sweet taste receptor. Scientific reports. 2015; 5 : 12947. doi:10.1038/srep12947