Tohoku University Tohoku Medical Megabank Organization (Kengo Kinoshita)
2024.04.23

1.   Ikejiri Kazuaki, Suzuki Takafumi, Muto Satsuki, et al. Effects of NRF2 polymorphisms on safety and efficacy of bardoxolone methyl: subanalysis of TSUBAKI study. Clinical and Experimental Nephrology. 2024; 28 (3): 225-234. doi:10.1007/s10157-023-02427-w  
2.   Hozawa Atsushi, Nakaya Kumi, Nakaya Naoki, et al. Progress report of the Tohoku Medical Megabank Community-Based Cohort Study: Study profile of the repeated center-based survey during second period in Miyagi Prefecture. Journal of Epidemiology. 2024; : JE20230241. doi:10.2188/jea.JE20230241  
3.   Harada Sei, Iida Miho, Miyagawa Naoko, et al. Study Profile of the Tsuruoka Metabolomics Cohort Study (TMCS). Journal of Epidemiology. 2024; : JE20230192. doi:10.2188/jea.JE20230192  
4.   Sato Mitsuharu, Hishinuma Eiji, Matsukawa Naomi, et al. Dietary habits and plasma lipid concentrations in a general Japanese population. Metabolomics. 2024; 20 (2): 34. doi:10.1007/s11306-024-02087-1  
5.   Itoh Taito, Omori Yuko, Seino Mitsuru, et al. Gene Rearrangement and Expression of PRKACA and PRKACB Govern Morphobiology of Pancreatobiliary Oncocytic Neoplasms. Modern Pathology. 2024; 37 (1): 100358. doi:10.1016/j.modpat.2023.100358  
6.   Tadaka Shu, Kawashima Junko, Hishinuma Eiji, et al. jMorp: Japanese Multi-Omics Reference Panel update report 2023. Nucleic Acids Research. 2024; 52 (D1): D622-D632. doi:10.1093/nar/gkad978  
7.   Miki Atsuya, Fuse Nobuo, Fujimoto Satoko, et al. Prevalence, Associated Factors, and Inter-Eye Differences of Refractive Errors in a Population-Based Japanese Cohort: The Tohoku Medical Megabank Eye Study. Ophthalmic Epidemiology. 2024; 31 (1): 46-54. doi:10.1080/09286586.2023.2203226  
8.   Koyanagi Yuriko N., Nakatochi Masahiro, Namba Shinichi, et al. Genetic architecture of alcohol consumption identified by a genotype-stratified GWAS and impact on esophageal cancer risk in Japanese people. Science Advances. 2024; 10 (4): . doi:10.1126/sciadv.ade2780  
9.   Aoki Yu-ichi, Taguchi Keiko, Anzawa Hayato, et al. Whole blood transcriptome analysis for age- and gender-specific gene expression profiling in Japanese individuals. The Journal of Biochemistry. 2024; : . doi:10.1093/jb/mvae008  
10.   Hanyuda Akiko, Goto Atsushi, Nakatochi Masahiro, et al. Association Between Glycemic Traits and Primary Open-Angle Glaucoma: A Mendelian Randomization Study in the Japanese Population. American Journal of Ophthalmology. 2023; 245 : 193-201. doi:10.1016/j.ajo.2022.09.004  
11.   Mizuno Satoshi, Nagaie Satoshi, Tamiya Gen, et al. Establishment of the early prediction models of low-birth-weight reveals influential genetic and environmental factors: a prospective cohort study. BMC Pregnancy and Childbirth. 2023; 23 (1): 628. doi:10.1186/s12884-023-05919-5  
12.   Hishinuma Eiji, Shimada Muneaki, Matsukawa Naomi, et al. Identification of predictive biomarkers for endometrial cancer diagnosis and treatment response monitoring using plasma metabolome profiling. Cancer & Metabolism. 2023; 11 (1): 16. doi:10.1186/s40170-023-00317-z  
13.   Hirose Wataru, Horiuchi Makoto, Li Donghan, et al. Selective Elimination of NRF2-Activated Cells by Competition With Neighboring Cells in the Esophageal Epithelium. Cellular and Molecular Gastroenterology and Hepatology. 2023; 15 (1): 153-178. doi:10.1016/j.jcmgh.2022.09.004  
14.   Tatara Yota, Yamazaki Hiromi, Katsuoka Fumiki, et al. Multiomics and artificial intelligence enabled peripheral blood-based prediction of amnestic mild cognitive impairment. Current Research in Translational Medicine. 2023; 71 (1): 103367. doi:10.1016/j.retram.2022.103367  
15.   Hishinuma Eiji, Narita Yoko, Rico Evelyn Marie Gutiérrez, et al. Functional Characterization of 12 Dihydropyrimidinase Allelic Variants in Japanese Individuals for the Prediction of 5-Fluorouracil Treatment-Related Toxicity. Drug Metabolism and Disposition. 2023; 51 (2): 165-173. doi:10.1124/dmd.122.001045  
16.   Sato Yu, Hishinuma Eiji, Yamazaki Shuki, et al. Functional Characterization of 29 Cytochrome P450 4F2 Variants Identified in a Population of 8380 Japanese Subjects and Assessment of Arachidonic Acid ω -Hydroxylation. Drug Metabolism and Disposition. 2023; 51 (12): 1561-1568. doi:10.1124/dmd.123.001389  
17.   Sato Shiho, Yu Zhiqian, Sakai Mai, et al. Decreased β‐hydroxybutyrate and ketogenic amino acid levels in depressed human adults. European Journal of Neuroscience. 2023; 57 (6): 1018-1032. doi:10.1111/ejn.15931  
18.   Zhang Lin, Nishi Hafumi, Kinoshita Kengo. Single-cell RNA-seq public data reveal the gene regulatory network landscape of respiratory epithelial and peripheral immune cells in COVID-19 patients. Frontiers in Immunology. 2023; 14 : . doi:10.3389/fimmu.2023.1194614  
19.   Watarai Gosuke, Suzuki Jun, Motoike Ikuko N, et al. Relationship between age‐related hearing loss and consumption of coffee and tea. Geriatrics & Gerontology International. 2023; 23 (6): 453-456. doi:10.1111/ggi.14589  
20.   Ishikawa Tomohiko, Ogawa Takenori, Shiihara Masahiro, et al. Salivary gland cancer organoids are valid for preclinical genotype-oriented medical precision trials. iScience. 2023; 26 (5): 106695. doi:10.1016/j.isci.2023.106695  
21.   Taira Makiko, Mugikura Shunji, Mori Naoko, et al. Tohoku Medical Megabank Brain Magnetic Resonance Imaging Study: Rationale, Design, and Background. JMA Journal. 2023; 6 (3): 246-264. doi:10.31662/jmaj.2022-0220  
22.   Sato Shuichi, Imaeda Takao, Mugikura Shunji, et al. Association Between Olfactory Test Data with Multiple Levels of Odor Intensity and Suspected Cognitive Impairment: A Cross-Sectional Study. Journal of Alzheimer's Disease. 2023; 95 (4): 1469-1480. doi:10.3233/JAD-230318  
23.   Anzawa Hayato, Kinoshita Kengo. C4S DB: Comprehensive Collection and Comparison for ChIP-Seq Database. Journal of Molecular Biology. 2023; 435 (14): 168157. doi:10.1016/j.jmb.2023.168157  
24.   Hishinuma Eiji, Shimada Muneaki, Matsukawa Naomi, et al. Identification of predictive biomarkers for diagnosis and radiation sensitivity of uterine cervical cancer using wide‐targeted metabolomics. Journal of Obstetrics and Gynaecology Research. 2023; 49 (8): 2109-2117. doi:10.1111/jog.15709  
25.   Yu Zhiqian, Ueno Kazuko, Funayama Ryo, et al. Sex-Specific Differences in the Transcriptome of the Human Dorsolateral Prefrontal Cortex in Schizophrenia. Molecular Neurobiology. 2023; 60 (2): 1083-1098. doi:10.1007/s12035-022-03109-6  
26.   Bui Han Ba, Watanabe Satoshi, Nomura Norimichi, et al. Cryo-EM structures of human zinc transporter ZnT7 reveal the mechanism of Zn2+ uptake into the Golgi apparatus. Nature Communications. 2023; 14 (1): 4770. doi:10.1038/s41467-023-40521-5  
27.   Yamaguchi Shin-Ichiro, Xie Qilin, Ito Fumiya, et al. Carbon nanotube recognition by human Siglec-14 provokes inflammation. Nature Nanotechnology. 2023; 18 (6): 628-636. doi:10.1038/s41565-023-01363-w  
28.   Obayashi Takeshi, Kodate Shun, Hibara Himiko, et al. COXPRESdb v8: an animal gene coexpression database navigating from a global view to detailed investigations. Nucleic Acids Research. 2023; 51 (D1): D80-D87. doi:10.1093/nar/gkac983  
29.   Hanyuda Akiko, Goto Atsushi, Katagiri Ryoko, et al. Investigating the association between glycaemic traits and colorectal cancer in the Japanese population using Mendelian randomisation. Scientific Reports. 2023; 13 (1): 7052. doi:10.1038/s41598-023-33966-7  
30.   Shimokawa Kazuro. A knowledge representation model for family relationship to three generation. Bioinformation. 2022; 18 (12): 1166-1172. doi:10.6026/973206300181166  
31.   Nagai Masayoshi, Iemura Kenji, Kikkawa Takako, et al. Deficiency of CHAMP1 , a gene related to intellectual disability, causes impaired neuronal development and a mild behavioural phenotype. Brain Communications. 2022; 4 (5): . doi:10.1093/braincomms/fcac220  
32.   Iwagami Masao, Goto Atsushi, Katagiri Ryoko, et al. Blood Lipids and the Risk of Colorectal Cancer: Mendelian Randomization Analyses in the Japanese Consortium of Genetic Epidemiology Studies. Cancer Prevention Research. 2022; 15 (12): 827-836. doi:10.1158/1940-6207.CAPR-22-0146  
33.   Iemura Kenji, Anzawa Hayato, Funayama Ryo, et al. High levels of chromosomal instability facilitate the tumor growth and sphere formation. Cancer Science. 2022; 113 (8): 2727-2737. doi:10.1111/cas.15457  
34.   Otsuki Akihito, Okamura Yasunobu, Ishida Noriko, et al. Construction of a trio-based structural variation panel utilizing activated T lymphocytes and long-read sequencing technology. Communications Biology. 2022; 5 (1): 991. doi:10.1038/s42003-022-03953-1  
35.   Hishinuma Eiji, Narita Yoko, Obuchi Kai, et al. Importance of Rare DPYD Genetic Polymorphisms for 5-Fluorouracil Therapy in the Japanese Population. Frontiers in Pharmacology. 2022; 13 : . doi:10.3389/fphar.2022.930470  
36.   Shiga Naomi, Yamaguchi-Kabata Yumi, Igeta Saori, et al. Pathological variants in genes associated with disorders of sex development and central causes of hypogonadism in a whole-genome reference panel of 8380 Japanese individuals. Human Genome Variation. 2022; 9 (1): 34. doi:10.1038/s41439-022-00213-w  
37.   Ohseto Hisashi, Ishikuro Mami, Obara Taku, et al. Preeclampsia prediction model using the dipstick test for proteinuria during early gestation. Hypertension Research in Pregnancy. 2022; 10 (3): HRP2022-002. doi:10.14390/jsshp.HRP2022-002  
38.   Yu Zhiqian, Matsukawa Naomi, Saigusa Daisuke, et al. Plasma metabolic disturbances during pregnancy and postpartum in women with depression. iScience. 2022; 25 (12): 105666. doi:10.1016/j.isci.2022.105666  
39.   Ohneda Kinuko, Hiratsuka Masahiro, Kawame Hiroshi, et al. A Pilot Study for Return of Individual Pharmacogenomic Results to Population-Based Cohort Study Participants. JMA Journal. 2022; 5 (2): . doi:10.31662/jmaj.2021-0156  
40.   Sugawara Junichi, Ishikuro Mami, Obara Taku, et al. Maternal Baseline Characteristics and Perinatal Outcomes: The Tohoku Medical Megabank Project Birth and Three-Generation Cohort Study. Journal of epidemiology. 2022; 32 (2): 69-79. doi:10.2188/jea.JE20200338  
41.   Goto Atsushi, Suzuki Shiori, Katagiri Ryoko, et al. Public Access to Summary Statistics for Genome-wide Association Studies of Body Mass Index, Weight, and Height Among Healthy Japanese Individuals: The Japanese Consortium of Genetic Epidemiology Studies. Journal of Epidemiology. 2022; 32 (2): JE20210459. doi:10.2188/jea.JE20210459  
42.   Kawame Hiroshi, Fukushima Akimune, Fuse Nobuo, et al. The return of individual genomic results to research participants: design and pilot study of Tohoku Medical Megabank Project. Journal of Human Genetics. 2022; 67 (1): 9-17. doi:10.1038/s10038-021-00952-8  
43.   Fuse Nobuo, Sakurai Miyuki, Motoike Ikuko N., et al. Genome-wide Association Study of Axial Length in Population-based Cohorts in Japan. Ophthalmology Science. 2022; 2 (1): 100113. doi:10.1016/j.xops.2022.100113  
44.   Obayashi Takeshi, Hibara Himiko, Kagaya Yuki, et al. ATTED-II v11: A Plant Gene Coexpression Database Using a Sample Balancing Technique by Subagging of Principal Components. Plant and Cell Physiology. 2022; 63 (6): 869-881. doi:10.1093/pcp/pcac041  
45.   Okazaki Keito, Anzawa Hayato, Katsuoka Fumiki, et al. CEBPB is required for NRF2-mediated drug resistance in NRF2-activated non-small cell lung cancer cells. The Journal of Biochemistry. 2022; 171 (5): 567-578. doi:10.1093/jb/mvac013  
46.   Zempo Hirofumi, Kim Su-Jeong, Fuku Noriyuki, et al. A pro-diabetogenic mtDNA polymorphism in the mitochondrial-derived peptide, MOTS-c. Aging. 2021; 13 (2): 1692-1717. doi:10.18632/aging.202529  
47.   Uchida Yasuo, Higuchi Tomoya, Shirota Matsuyuki, et al. Identification and Validation of Combination Plasma Biomarker of Afamin, Fibronectin and Sex Hormone-Binding Globulin to Predict Pre-eclampsia. Biological and Pharmaceutical Bulletin. 2021; 44 (6): 804-815. doi:10.1248/bpb.b20-01043  
48.   Suzuki Shiori, Goto Atsushi, Nakatochi Masahiro, et al. Body mass index and colorectal cancer risk: A Mendelian randomization study. Cancer Science. 2021; 112 (4): 1579-1588. doi:10.1111/cas.14824  
49.   Omori Satoshi, Tsugita Misato, Hoshikawa Yasuto, et al. Tim4 recognizes carbon nanotubes and mediates phagocytosis leading to granuloma formation. Cell Reports. 2021; 34 (6): 108734. doi:10.1016/j.celrep.2021.108734  
50.   Yamada Mitsuhiro, Motoike Ikuko N., Kojima Kaname, et al. Genetic loci for lung function in Japanese adults with adjustment for exhaled nitric oxide levels as airway inflammation indicator. Communications Biology. 2021; 4 (1): 1288. doi:10.1038/s42003-021-02813-8  
51.   Kumondai Masaki, Gutiérrez Rico Evelyn Marie, Hishinuma Eiji, et al. Functional Characterization of 40 CYP3A4 Variants by Assessing Midazolam 1′-Hydroxylation and Testosterone 6 β -Hydroxylation. Drug Metabolism and Disposition. 2021; 49 (3): 212-220. doi:10.1124/dmd.120.000261  
52.   Shiihara Masahiro, Ishikawa Tomohiko, Saiki Yuriko, et al. Development of a system combining comprehensive genotyping and organoid cultures for identifying and testing genotype-oriented personalised medicine for pancreatobiliary cancers. European Journal of Cancer. 2021; 148 : 239-250. doi:10.1016/j.ejca.2021.01.047  
53.   Saito Sakae, Aoki Yuichi, Tamahara Toru, et al. Oral Microbiome Analysis in Prospective Genome Cohort Studies of the Tohoku Medical Megabank Project. Frontiers in Cellular and Infection Microbiology. 2021; 10 : . doi:10.3389/fcimb.2020.604596  
54.   Ogishima Soichi, Nagaie Satoshi, Mizuno Satoshi, et al. dbTMM: an integrated database of large-scale cohort, genome and clinical data for the Tohoku Medical Megabank Project. Human Genome Variation. 2021; 8 (1): 44. doi:10.1038/s41439-021-00175-5  
55.   Nagaoka Shinichi, Yamaguchi-Kabata Yumi, Shiga Naomi, et al. Estimation of the carrier frequencies and proportions of potential patients by detecting causative gene variants associated with autosomal recessive bone dysplasia using a whole-genome reference panel of Japanese individuals. Human Genome Variation. 2021; 8 (1): 2. doi:10.1038/s41439-020-00133-7  
56.   Hozawa Atsushi, Tanno Kozo, Nakaya Naoki, et al. Study profile of the tohoku medical megabank community-based cohort study. Journal of Epidemiology. 2021; 31 (1): 65-76. doi:10.2188/jea.JE20190271  
57.   Shido Kosuke, Kojima Kaname, Shirota Matsuyuki, et al. GWAS Identified IL4R and the Major Histocompatibility Complex Region as the Associated Loci of Total Serum IgE Levels in 9,260 Japanese Individuals. Journal of Investigative Dermatology. 2021; 141 (11): 2749-2752. doi:10.1016/j.jid.2021.02.762  
58.   Kumondai Masaki, Ito Akio, Gutiérrez Rico Evelyn Marie, et al. Functional Assessment of 12 Rare Allelic CYP2C9 Variants Identified in a Population of 4773 Japanese Individuals. Journal of Personalized Medicine. 2021; 11 (2): 94. doi:10.3390/jpm11020094  
59.   Kumondai Masaki, Gutiérrez Rico Evelyn, Hishinuma Eiji, et al. Functional Characterization of 21 Rare Allelic CYP1A2 Variants Identified in a Population of 4773 Japanese Individuals by Assessing Phenacetin O-Deethylation. Journal of Personalized Medicine. 2021; 11 (8): 690. doi:10.3390/jpm11080690  
60.   Saigusa Daisuke, Hishinuma Eiji, Matsukawa Naomi, et al. Comparison of Kit-Based Metabolomics with Other Methodologies in a Large Cohort, towards Establishing Reference Values. Metabolites. 2021; 11 (10): 652. doi:10.3390/metabo11100652  
61.   Otsuki Akihito, Okamura Yasunobu, Aoki Yuichi, et al. Identification of Dominant Transcripts in Oxidative Stress Response by a Full-Length Transcriptome Analysis. Molecular and Cellular Biology. 2021; 41 (2): 1-18. doi:10.1128/MCB.00472-20  
62.   Takayama Jun, Tadaka Shu, Yano Kenji, et al. Construction and integration of three de novo Japanese human genome assemblies toward a population-specific reference. Nature Communications. 2021; 12 (1): 226. doi:10.1038/s41467-020-20146-8  
63.   Tadaka Shu, Hishinuma Eiji, Komaki Shohei, et al. jMorp updates in 2020: large enhancement of multi-omics data resources on the general Japanese population. Nucleic Acids Research. 2021; 49 (D1): D536-D544. doi:10.1093/nar/gkaa1034  
64.   Tokunaga Hideki, Iida Keita, Hozawa Atsushi, et al. Novel candidates of pathogenic variants of the BRCA1 and BRCA2 genes from a dataset of 3,552 Japanese whole genomes (3.5KJPNv2). PLOS ONE. 2021; 16 (1): e0236907. doi:10.1371/journal.pone.0236907  
65.   Kojima Kaname, Shido Kosuke, Tamiya Gen, et al. Facial UV photo imaging for skin pigmentation assessment using conditional generative adversarial networks. Scientific Reports. 2021; 11 (1): 1213. doi:10.1038/s41598-020-79995-4  
66.   Sakurai-Yageta Mika, Kumada Kazuki, Gocho Chinatsu, et al. Japonica Array NEO with increased genome-wide coverage and abundant disease risk SNPs. The Journal of Biochemistry. 2021; 170 (3): 399-410. doi:10.1093/jb/mvab060  
67.   Hishinuma Eiji, Shimada Muneaki, Matsukawa Naomi, et al. Wide-Targeted Metabolome Analysis Identifies Potential Biomarkers for Prognosis Prediction of Epithelial Ovarian Cancer. Toxins. 2021; 13 (7): 461. doi:10.3390/toxins13070461  
68.   Shigemizu Daichi, Mitsumori Risa, Akiyama Shintaro, et al. Ethnic and trans-ethnic genome-wide association studies identify new loci influencing Japanese Alzheimer’s disease risk. Translational Psychiatry. 2021; 11 (1): 151. doi:10.1038/s41398-021-01272-3  
69.   Anzawa Hayato, Yamagata Hitoshi, Kinoshita Kengo. Theoretical characterisation of strand cross-correlation in ChIP-seq. BMC Bioinformatics. 2020; 21 (1): 417. doi:10.1186/s12859-020-03729-6  
70.   Saigusa Daisuke, Motoike Ikuko N., Saito Sakae, et al. Impacts of NRF2 activation in non–small‐cell lung cancer cell lines on extracellular metabolites. Cancer Science. 2020; 111 (2): 667-678. doi:10.1111/cas.14278  
71.   Koshiba Seizo, Motoike Ikuko N., Saigusa Daisuke, et al. Identification of critical genetic variants associated with metabolic phenotypes of the Japanese population. Communications Biology. 2020; 3 (1): 662. doi:10.1038/s42003-020-01383-5  
72.   Ishida Noriko, Aoki Yuichi, Katsuoka Fumiki, et al. Landscape of electrophilic and inflammatory stress-mediated gene regulation in human lymphoblastoid cell lines. Free Radical Biology and Medicine. 2020; 161 : 71-83. doi:10.1016/j.freeradbiomed.2020.09.023  
73.   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. 2020; 49 (1): 18-19m. doi:10.1093/ije/dyz169  
74.   Shirota Matsuyuki, Saigusa Daisuke, Yamashita Riu, et al. Longitudinal plasma amino acid profiling with maternal genomic background throughout human pregnancy. Medical Mass Spectrometry. 2020; 4 (1): 36-49. doi:10.24508/mms.2020.06.001  
75.   Kagaya Yuki, Minei Ryuhei, Duong Ha T T, et al. Metagenome Sequences from the Environment of Diseased Otter Clams, Lutraria rhynchaena, from a Farm in Vietnam. Microbiology Resource Announcements. 2020; 9 (2): . doi:10.1128/MRA.01068-19  
76.   Okazaki Keito, Anzawa Hayato, Liu Zun, et al. Enhancer remodeling promotes tumor-initiating activity in NRF2-activated non-small cell lung cancers. Nature Communications. 2020; 11 (1): 5911. doi:10.1038/s41467-020-19593-0  
77.   Lin Yingsong, Nakatochi Masahiro, Hosono Yasuyuki, et al. Genome-wide association meta-analysis identifies GP2 gene risk variants for pancreatic cancer. Nature Communications. 2020; 11 (1): 3175. doi:10.1038/s41467-020-16711-w  
78.   Kojima Kaname, Tadaka Shu, Katsuoka Fumiki, et al. A genotype imputation method for de-identified haplotype reference information by using recurrent neural network. PLOS Computational Biology. 2020; 16 (10): e1008207. doi:10.1371/journal.pcbi.1008207  
79.   Wagata Maiko, Ishikuro Mami, Obara Taku, et al. Low birth weight and abnormal pre-pregnancy body mass index were at higher risk for hypertensive disorders of pregnancy. Pregnancy Hypertension. 2020; 22 : 119-125. doi:10.1016/j.preghy.2020.08.001  
80.   Amano Ryota, Karashima Akihiro, Motoike Ikuko, et al. Consistency index of daily activity pattern and its correlations with subjective ratings of QOL. Sleep and Biological Rhythms. 2020; 18 (4): 297-304. doi:10.1007/s41105-020-00271-z  
81.   Tsuboi Akito, Matsui Hiroyuki, Shiraishi Naru, et al. Design and Progress of Oral Health Examinations in the Tohoku Medical Megabank Project. The Tohoku Journal of Experimental Medicine. 2020; 251 (2): 97-115. doi:10.1620/tjem.251.97  
82.   Takahashi Yuta, Ueki Masao, Yamada Makoto, et al. Improved metabolomic data-based prediction of depressive symptoms using nonlinear machine learning with feature selection. Translational Psychiatry. 2020; 10 (1): 157. doi:10.1038/s41398-020-0831-9  
83.   Takahashi Yuta, Ueki Masao, Tamiya Gen, et al. Machine learning for effectively avoiding overfitting is a crucial strategy for the genetic prediction of polygenic psychiatric phenotypes. Translational Psychiatry. 2020; 10 (1): 294. doi:10.1038/s41398-020-00957-5  
84.   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): e025939. doi:10.1136/bmjopen-2018-025939  
85.   Mori Minako, Hira Asuka, Yoshida Kenichi, et al. Pathogenic mutations identified by a multimodality approach in 117 Japanese Fanconi anemia patients. Haematologica. 2019; 104 (10): 1962-1973. doi:10.3324/haematol.2018.207241  
86.   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  
87.   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  
88.   Nagasaki Masao, Kuroki Yoko, Shibata Tomoko F., et al. Construction of JRG (Japanese reference genome) with single-molecule real-time sequencing. Human Genome Variation. 2019; 6 (1): 27. doi:10.1038/s41439-019-0057-7  
89.   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  
90.   Sakurai Rieko, Ueki Masao, Makino Satoshi, et al. Outlier detection for questionnaire data in biobanks. International Journal of Epidemiology. 2019; 48 (4): 1305-1315. doi:10.1093/ije/dyz012  
91.   Fuse Nobuo, Sakurai-Yageta Mika, Katsuoka Fumiki, et al. Establishment of Integrated Biobank for Precision Medicine and Personalized Healthcare: The Tohoku Medical Megabank Project. JMA Journal. 2019; 2 (2): 113-122. doi:10.31662/jmaj.2019-0014  
92.   Kiniwa Yukiko, Yasuda Jun, Saito Sakae, et al. Identification of genetic alterations in extramammary Paget disease using whole exome analysis. Journal of Dermatological Science. 2019; 94 (1): 229-235. doi:10.1016/j.jdermsci.2019.03.006  
93.   Mizuguchi Takeshi, Suzuki Takeshi, Abe Chihiro, et al. A 12-kb structural variation in progressive myoclonic epilepsy was newly identified by long-read whole-genome sequencing. Journal of Human Genetics. 2019; 64 (5): 359-368. doi:10.1038/s10038-019-0569-5  
94.   Obayashi Takeshi, Kagaya Yuki, Aoki Yuichi, et al. COXPRESdb v7: a gene coexpression database for 11 animal species supported by 23 coexpression platforms for technical evaluation and evolutionary inference. Nucleic Acids Research. 2019; 47 (D1): D55-D62. doi:10.1093/nar/gky1155  
95.   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  
96.   Mimori Takahiro, Yasuda Jun, Kuroki Yoko, et al. Construction of full-length Japanese reference panel of class I HLA genes with single-molecule, real-time sequencing. The Pharmacogenomics Journal. 2019; 19 (2): 136-146. doi:10.1038/s41397-017-0010-4  
97.   Yamada Kazunori D., Kinoshita Kengo. De novo profile generation based on sequence context specificity with the long short-term memory network. BMC Bioinformatics. 2018; 19 (1): 272. doi:10.1186/s12859-018-2284-1  
98.   Okamura Yasunobu, Kinoshita Kengo. Matataki: an ultrafast mRNA quantification method for large-scale reanalysis of RNA-Seq data. BMC Bioinformatics. 2018; 19 (1): 266. doi:10.1186/s12859-018-2279-y  
99.   Yasuda Jun, Katsuoka Fumiki, Danjoh Inaho, et al. Regional genetic differences among Japanese populations and performance of genotype imputation using whole-genome reference panel of the Tohoku Medical Megabank Project. BMC Genomics. 2018; 19 (1): 551. doi:10.1186/s12864-018-4942-0  
100.   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  
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