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Sato S, Yu Z, Sakai M, Motoike IN, Saigusa D, Hirayama R, Kikuchi Y, Abe T, Kinoshita K, Koshiba S, Tomita H. Decreased β-hydroxybutyrate and ketogenic amino acid levels in depressed human adults. Eur J Neurosci 2023; 57:1018-1032. [PMID: 36750311 DOI: 10.1111/ejn.15931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Revised: 01/24/2023] [Accepted: 01/29/2023] [Indexed: 02/09/2023]
Abstract
β-hydroxybutyrate (BHB) is a major ketone body synthesized mainly in the liver mitochondria and is associated with stress and severity of depression in humans. It is known to alleviate depressive-like behaviors in mouse models of depression. In this study, plasma BHB, ketogenic and glucogenic amino acids selected from the Tohoku Medical Megabank Project Community-Based Cohort Study were analysed and measured using nuclear magnetic resonance spectroscopy. The Center for Epidemiologic Studies Depression Scale (CES-D) was utilized to select adult participants with depressive symptoms (CES-D ≥ 16; n = 5722) and control participants (CES-D < 16; n = 18,150). We observed significantly reduced plasma BHB, leucine, and tryptophan levels in participants with depressive symptoms. Using social defeat stress (SDS) mice models, we found that BHB levels in mice sera increased after acute SDS, but showed no change after chronic SDS, which differed from human plasma results. Furthermore, acute SDS increased mitochondrial BHB levels in the prefrontal cortex at 6 h. In contrast, chronic SDS significantly increased the amount of food intake but reduced hepatic mitochondrial BHB levels in mice. Moreover, gene transcriptions of voltage-dependent anion-selective channel 1 (Vdac1) and monocarboxylic acid transporter 1 (Mct1), major molecules relevant to mitochondrial biogenesis and BHB transporter, significantly decreased in the liver and PFC after chronic SDS exposure. These results provide evidence that hepatic and prefrontal mitochondrial biogenesis plays an important role in BHB synthesis under chronic stress and in humans with depressive symptoms.
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Affiliation(s)
- Shiho Sato
- Department of Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Zhiqian Yu
- Department of Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Mai Sakai
- Department of Psychiatric Nursing, Graduate School of Health Science, Tohoku University, Sendai, Japan
| | - Ikuko N Motoike
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, Sendai, Japan.,Department of System Bioinformatics, Tohoku University Graduate School of Information Sciences, Tohoku University, Sendai, Japan
| | - Daisuke Saigusa
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, Sendai, Japan.,Department of Medical Biochemistry, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Ryo Hirayama
- Department of Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Yoshie Kikuchi
- Department of Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Takaaki Abe
- Department of Biomedical Engineering Regenerative and Biomedical Engineering Medical Science, Graduate School of Biomedical Engineering, Tohoku University, Sendai, Japan
| | - Kengo Kinoshita
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, Sendai, Japan.,Department of System Bioinformatics, Tohoku University Graduate School of Information Sciences, Tohoku University, Sendai, Japan
| | - Seizo Koshiba
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, Sendai, Japan.,Department of Medical Biochemistry, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Hiroaki Tomita
- Department of Psychiatry, Graduate School of Medicine, Tohoku University, Sendai, Japan.,Department of Preventive Medicine and Epidemiology, Tohoku University Tohoku Medical Megabank Organization, Sendai, Japan.,Department of Psychiatry, Tohoku University Hospital, Sendai, Japan
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2
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Iwasaki T, Kamatani Y, Sonomura K, Kawaguchi S, Kawaguchi T, Takahashi M, Ohmura K, Sato TA, Matsuda F. Genetic influences on human blood metabolites in the Japanese population. iScience 2023; 26:105738. [PMID: 36582826 PMCID: PMC9792902 DOI: 10.1016/j.isci.2022.105738] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 10/08/2022] [Accepted: 12/01/2022] [Indexed: 12/12/2022] Open
Abstract
An increase in ethnic diversity in genetic studies has the potential to provide unprecedented insights into how genetic variations influence human phenotypes. In this study, we conducted a quantitative trait locus (QTL) analysis of 121 metabolites measured using gas chromatography-mass spectrometry with plasma samples from 4,888 Japanese individuals. We found 60 metabolite-gene associations, of which 13 have not been previously reported. Meta-analyses with another Japanese and a European study identified six and two additional unreported loci, respectively. Genetic variants influencing metabolite levels were more enriched in protein-coding regions than in the regulatory regions while being associated with the risk of various diseases. Finally, we identified a signature of strong negative selection for uric acid ( S ˆ = -1.53, p = 6.2 × 10-18). Our study expanded the knowledge of genetic influences on human blood metabolites, providing valuable insights into their physiological, pathological, and selective properties.
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Affiliation(s)
- Takeshi Iwasaki
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan.,Department of Rheumatology and Clinical Immunology, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Yoichiro Kamatani
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Kazuhiro Sonomura
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan.,Life Science Research Center, Shimadzu Corporation, Kyoto 604-8511, Japan
| | - Shuji Kawaguchi
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Takahisa Kawaguchi
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Meiko Takahashi
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Koichiro Ohmura
- Department of Rheumatology and Clinical Immunology, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Taka-Aki Sato
- Life Science Research Center, Shimadzu Corporation, Kyoto 604-8511, Japan
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
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3
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dbTMM: an integrated database of large-scale cohort, genome and clinical data for the Tohoku Medical Megabank Project. Hum Genome Var 2021; 8:44. [PMID: 34887386 PMCID: PMC8660797 DOI: 10.1038/s41439-021-00175-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 09/08/2021] [Accepted: 09/08/2021] [Indexed: 11/08/2022] Open
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. A database integrating 1.3 trillion genome cohort data entries from 157,191 individuals in Japan will facilitate research into the gene-environment interactions underlying common diseases. The Tohoku Medical Megabank integrated database called dbTMM was developed by Soichi Ogishima, Masayuki Yamamoto and colleagues at Tohoku University in Japan. It incorporates the genome, metabolome, proteome, clinical, sociodemographic, lifestyle and environmental data from 84,073 adults, and 73,529 pregnant women and their families, including children. Blood and urine samples were collected from participants and analysed, then obtained genome/multiomics data were stored in dbTMM. Users can stratify the entire population into smaller populations based on multiple data variables, including whole genome variants, to search for statistically significant differences that might warrant further research. The dbTMM is expected to help clarify the genes and gene-environment interactions underlying common diseases and improve disease risk prediction.
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4
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Saigusa D, Hishinuma E, Matsukawa N, Takahashi M, Inoue J, Tadaka S, Motoike IN, Hozawa A, Izumi Y, Bamba T, Kinoshita K, Ekroos K, Koshiba S, Yamamoto M. Comparison of Kit-Based Metabolomics with Other Methodologies in a Large Cohort, towards Establishing Reference Values. Metabolites 2021; 11:652. [PMID: 34677367 PMCID: PMC8538467 DOI: 10.3390/metabo11100652] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 09/16/2021] [Accepted: 09/17/2021] [Indexed: 12/18/2022] Open
Abstract
Metabolic profiling is an omics approach that can be used to observe phenotypic changes, making it particularly attractive for biomarker discovery. Although several candidate metabolites biomarkers for disease expression have been identified in recent clinical studies, the reference values of healthy subjects have not been established. In particular, the accuracy of concentrations measured by mass spectrometry (MS) is unclear. Therefore, comprehensive metabolic profiling in large-scale cohorts by MS to create a database with reference ranges is essential for evaluating the quality of the discovered biomarkers. In this study, we tested 8700 plasma samples by commercial kit-based metabolomics and separated them into two groups of 6159 and 2541 analyses based on the different ultra-high-performance tandem mass spectrometry (UHPLC-MS/MS) systems. We evaluated the quality of the quantified values of the detected metabolites from the reference materials in the group of 2541 compared with the quantified values from other platforms, such as nuclear magnetic resonance (NMR), supercritical fluid chromatography tandem mass spectrometry (SFC-MS/MS) and UHPLC-Fourier transform mass spectrometry (FTMS). The values of the amino acids were highly correlated with the NMR results, and lipid species such as phosphatidylcholines and ceramides showed good correlation, while the values of triglycerides and cholesterol esters correlated less to the lipidomics analyses performed using SFC-MS/MS and UHPLC-FTMS. The evaluation of the quantified values by MS-based techniques is essential for metabolic profiling in a large-scale cohort.
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Affiliation(s)
- Daisuke Saigusa
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan; (E.H.); (N.M.); (J.I.); (S.T.); (I.N.M.); (K.K.); (S.K.); (M.Y.)
- Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan
| | - Eiji Hishinuma
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan; (E.H.); (N.M.); (J.I.); (S.T.); (I.N.M.); (K.K.); (S.K.); (M.Y.)
- Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
| | - Naomi Matsukawa
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan; (E.H.); (N.M.); (J.I.); (S.T.); (I.N.M.); (K.K.); (S.K.); (M.Y.)
- Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan
| | - Masatomo Takahashi
- Division of Metabolomics, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan; (M.T.); (Y.I.); (T.B.)
| | - Jin Inoue
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan; (E.H.); (N.M.); (J.I.); (S.T.); (I.N.M.); (K.K.); (S.K.); (M.Y.)
- Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
| | - Shu Tadaka
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan; (E.H.); (N.M.); (J.I.); (S.T.); (I.N.M.); (K.K.); (S.K.); (M.Y.)
- Graduate School of Information Sciences, Tohoku University, 6-3-09, Aramaki Aza-Aoba, Aoba-ku, Sendai 980-8579, Japan
| | - Ikuko N. Motoike
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan; (E.H.); (N.M.); (J.I.); (S.T.); (I.N.M.); (K.K.); (S.K.); (M.Y.)
- Graduate School of Information Sciences, Tohoku University, 6-3-09, Aramaki Aza-Aoba, Aoba-ku, Sendai 980-8579, Japan
| | - Atsushi Hozawa
- Department of Preventive Medicine and Epidemiology, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan;
| | - Yoshihiro Izumi
- Division of Metabolomics, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan; (M.T.); (Y.I.); (T.B.)
- Department of Systems Life Sciences, Graduate School of Systems Life Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
| | - Takeshi Bamba
- Division of Metabolomics, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan; (M.T.); (Y.I.); (T.B.)
- Department of Systems Life Sciences, Graduate School of Systems Life Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan
| | - Kengo Kinoshita
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan; (E.H.); (N.M.); (J.I.); (S.T.); (I.N.M.); (K.K.); (S.K.); (M.Y.)
- Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
- Graduate School of Information Sciences, Tohoku University, 6-3-09, Aramaki Aza-Aoba, Aoba-ku, Sendai 980-8579, Japan
| | - Kim Ekroos
- Lipidomics Consulting Ltd., 02230 Espoo, Finland;
| | - Seizo Koshiba
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan; (E.H.); (N.M.); (J.I.); (S.T.); (I.N.M.); (K.K.); (S.K.); (M.Y.)
- Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
| | - Masayuki Yamamoto
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan; (E.H.); (N.M.); (J.I.); (S.T.); (I.N.M.); (K.K.); (S.K.); (M.Y.)
- Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8575, Japan
- Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai 980-8573, Japan
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5
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Odagiri S, Kabata D, Tomita S, Kudo S, Sakaguchi T, Nakano N, Yamamoto K, Shintaku H, Hamazaki T. Clinical and Genetic Characteristics of Patients with Mild Hyperphenylalaninemia Identified by Newborn Screening Program in Japan. Int J Neonatal Screen 2021; 7:ijns7010017. [PMID: 33803550 PMCID: PMC8006226 DOI: 10.3390/ijns7010017] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 03/13/2021] [Accepted: 03/15/2021] [Indexed: 11/22/2022] Open
Abstract
Phenylketonuria (PKU) and hyperphenylalaninemia (HPA), both identified in newborn screening, are attributable to variants in PAH. Reportedly, the p.R53H(c.158G>A) variant is common in patients with HPA in East Asia. Here, we aimed to define the association between p.R53H and HPA phenotype, and study the long-term outcome of patients with HPA carrying p.R53H. We retrospectively reviewed the genotype in 370 patients detected by newborn screening, and identified the phenotype in 280 (117, HPA; 163, PKU). p.R413P(c.1238G>C) was the most frequently found (n = 117, 31.6%) variant, followed by p.R53H (n = 89, 24.1%). The odds ratio for heterozygous p.R53H to cause HPA was 48.3 (95% CI 19.410-120.004). Furthermore, we assessed the non-linear association between the phenylalanine (Phe) value and elapsed time using the follow-up data of the blood Phe levels of 73 patients with HPA carrying p.R53H. The predicted levels peaked at 161.9 μmol (95% CI 152.088-172.343) at 50-60 months of age and did not exceed 360 μmol/L during the 210-month long observation period. The findings suggest that patients with HPA, carrying p.R53H, do not need frequent Phe monitoring as against those with PKU. Our study provides convincing evidence to determine clinical management of patients detected through newborn screening in Japan.
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Affiliation(s)
- Shino Odagiri
- Department of Pediatrics, Osaka City University Graduate School of Medicine, Osaka 545-8585, Japan; (S.O.); (S.K.); (T.S.); (N.N.)
| | - Daijiro Kabata
- Department of Medical Statistics, Osaka City University Graduate School of Medicine, Osaka 545-8585, Japan; (D.K.); (S.T.)
| | - Shogo Tomita
- Department of Medical Statistics, Osaka City University Graduate School of Medicine, Osaka 545-8585, Japan; (D.K.); (S.T.)
| | - Satoshi Kudo
- Department of Pediatrics, Osaka City University Graduate School of Medicine, Osaka 545-8585, Japan; (S.O.); (S.K.); (T.S.); (N.N.)
| | - Tomoko Sakaguchi
- Department of Pediatrics, Osaka City University Graduate School of Medicine, Osaka 545-8585, Japan; (S.O.); (S.K.); (T.S.); (N.N.)
| | - Noriko Nakano
- Department of Pediatrics, Osaka City University Graduate School of Medicine, Osaka 545-8585, Japan; (S.O.); (S.K.); (T.S.); (N.N.)
| | - Kouji Yamamoto
- Department of Biostatistics, Yokohama City University School of Medicine, Yokohama 236-0004, Japan;
| | - Haruo Shintaku
- Donated Course “Disability Medicine and Regenerative Medicine”, Osaka City University Graduate School of Medicine, Osaka 545-8585, Japan;
| | - Takashi Hamazaki
- Department of Pediatrics, Osaka City University Graduate School of Medicine, Osaka 545-8585, Japan; (S.O.); (S.K.); (T.S.); (N.N.)
- Correspondence: ; Tel.: +81-6-6645-3815
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6
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Saigusa D, Matsukawa N, Hishinuma E, Koshiba S. Identification of biomarkers to diagnose diseases and find adverse drug reactions by metabolomics. Drug Metab Pharmacokinet 2020; 37:100373. [PMID: 33631535 DOI: 10.1016/j.dmpk.2020.11.008] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 11/24/2020] [Accepted: 11/25/2020] [Indexed: 12/12/2022]
Abstract
Metabolomics has been widely used for investigating the biological functions of disease expression and has the potential to discover biomarkers in circulating biofluids or tissue extracts that reflect in phenotypic changes. Metabolic profiling has advantages because of the use of unbiased techniques, including multivariate analysis, and has been applied in pharmacological studies to predict therapeutic and adverse reactions of drugs, which is called pharmacometabolomics (PMx). Nuclear magnetic resonance (NMR)- and mass spectrometry (MS)-based metabolomics has contributed to the discovery of recent disease biomarkers; however, the optimal strategy for the study purpose must be selected from many established protocols, methodologies and analytical platforms. Additionally, information on molecular localization in tissue is essential for further functional analyses related to therapeutic and adverse effects of drugs in the process of drug development. MS imaging (MSI) is a promising technology that can visualize molecules on tissue surfaces without labeling and thus provide localized information. This review summarizes recent uses of MS-based global and wide-targeted metabolomics technologies and the advantages of the MSI approach for PMx and highlights the PMx technique for the biomarker discovery of adverse drug effects.
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Affiliation(s)
- Daisuke Saigusa
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan.
| | - Naomi Matsukawa
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan.
| | - Eiji Hishinuma
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
| | - Seizo Koshiba
- Department of Integrative Genomics, Tohoku University Tohoku Medical Megabank Organization, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan; Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan; Advanced Research Center for Innovations in Next-Generation Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
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7
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Koshiba S, Motoike IN, Saigusa D, Inoue J, Aoki Y, Tadaka S, Shirota M, Katsuoka F, Tamiya G, Minegishi N, Fuse N, Kinoshita K, Yamamoto M. Identification of critical genetic variants associated with metabolic phenotypes of the Japanese population. Commun Biol 2020; 3:662. [PMID: 33177615 PMCID: PMC7659008 DOI: 10.1038/s42003-020-01383-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2020] [Accepted: 10/18/2020] [Indexed: 02/07/2023] Open
Abstract
We performed a metabolome genome-wide association study for the Japanese population in the prospective cohort study of Tohoku Medical Megabank. By combining whole-genome sequencing and nontarget metabolome analyses, we identified a large number of novel associations between genetic variants and plasma metabolites. Of the identified metabolite-associated genes, approximately half have already been shown to be involved in various diseases. We identified metabolite-associated genes involved in the metabolism of xenobiotics, some of which are from intestinal microorganisms, indicating that the identified genetic variants also markedly influence the interaction between the host and symbiotic bacteria. We also identified five associations that appeared to be female-specific. A number of rare variants that influence metabolite levels were also found, and combinations of common and rare variants influenced the metabolite levels more profoundly. These results support our contention that metabolic phenotyping provides important insights into how genetic and environmental factors provoke human diseases.
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Affiliation(s)
- Seizo Koshiba
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
- Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan.
- The Advanced Research Center for Innovations in Next-Generation Medicine (INGEM), Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
| | - Ikuko N Motoike
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan
- Graduate School of Information Sciences, Tohoku University, 6-3-09, Aramaki Aza-Aoba, Aoba-ku, Sendai, 980-8579, Japan
| | - Daisuke Saigusa
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan
- Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan
| | - Jin Inoue
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan
- Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan
| | - Yuichi Aoki
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan
- Graduate School of Information Sciences, Tohoku University, 6-3-09, Aramaki Aza-Aoba, Aoba-ku, Sendai, 980-8579, Japan
| | - Shu Tadaka
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan
- Graduate School of Information Sciences, Tohoku University, 6-3-09, Aramaki Aza-Aoba, Aoba-ku, Sendai, 980-8579, Japan
| | - Matsuyuki Shirota
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan
- Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan
| | - Fumiki Katsuoka
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan
- Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan
- The Advanced Research Center for Innovations in Next-Generation Medicine (INGEM), Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan
| | - Gen Tamiya
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan
- Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan
- The Advanced Research Center for Innovations in Next-Generation Medicine (INGEM), Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan
| | - Naoko Minegishi
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan
- Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan
- The Advanced Research Center for Innovations in Next-Generation Medicine (INGEM), Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan
| | - Nobuo Fuse
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan
- Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan
- The Advanced Research Center for Innovations in Next-Generation Medicine (INGEM), Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan
| | - Kengo Kinoshita
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan
- The Advanced Research Center for Innovations in Next-Generation Medicine (INGEM), Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan
- Graduate School of Information Sciences, Tohoku University, 6-3-09, Aramaki Aza-Aoba, Aoba-ku, Sendai, 980-8579, Japan
| | - Masayuki Yamamoto
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
- Graduate School of Medicine, Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8575, Japan.
- The Advanced Research Center for Innovations in Next-Generation Medicine (INGEM), Tohoku University, 2-1, Seiryo-machi, Aoba-ku, Sendai, 980-8573, Japan.
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8
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Nrf2 contributes to the weight gain of mice during space travel. Commun Biol 2020; 3:496. [PMID: 32901092 PMCID: PMC7479603 DOI: 10.1038/s42003-020-01227-2] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 08/13/2020] [Indexed: 12/27/2022] Open
Abstract
Space flight produces an extreme environment with unique stressors, but little is known about how our body responds to these stresses. While there are many intractable limitations for in-flight space research, some can be overcome by utilizing gene knockout-disease model mice. Here, we report how deletion of Nrf2, a master regulator of stress defense pathways, affects the health of mice transported for a stay in the International Space Station (ISS). After 31 days in the ISS, all flight mice returned safely to Earth. Transcriptome and metabolome analyses revealed that the stresses of space travel evoked ageing-like changes of plasma metabolites and activated the Nrf2 signaling pathway. Especially, Nrf2 was found to be important for maintaining homeostasis of white adipose tissues. This study opens approaches for future space research utilizing murine gene knockout-disease models, and provides insights into mitigating space-induced stresses that limit the further exploration of space by humans. Using Nrf2 knockout mice, Suzuki, Uruno, Yumoto et al. show that space travel activates Nrf2 signaling, which contributes to the weight gain of mice by regulating fat metabolism of white adipose tissues. This study provides insights into potential interventions to mitigate stresses that accompany space travels.
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9
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Tadaka S, Saigusa D, Motoike IN, Inoue J, Aoki Y, Shirota M, Koshiba S, Yamamoto M, Kinoshita K. jMorp: Japanese Multi Omics Reference Panel. Nucleic Acids Res 2019; 46:D551-D557. [PMID: 29069501 PMCID: PMC5753289 DOI: 10.1093/nar/gkx978] [Citation(s) in RCA: 75] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2017] [Accepted: 10/10/2017] [Indexed: 12/12/2022] Open
Abstract
We developed jMorp, a new database containing metabolome and proteome data for plasma obtained from >5000 healthy Japanese volunteers from the Tohoku Medical Megabank Cohort Study, which is available at https://jmorp.megabank.tohoku.ac.jp. Metabolome data were measured by proton nuclear magnetic resonance (NMR) and liquid chromatography–mass spectrometry (LC–MS), while proteome data were obtained by nanoLC–MS. We released the concentration distributions of 37 metabolites identified by NMR, distributions of peak intensities of 257 characterized metabolites by LC–MS, and observed frequencies of 256 abundant proteins. Additionally, correlation networks for the metabolites can be observed using an interactive network viewer. Compared with some existing databases, jMorp has some unique features: (i) Metabolome data were obtained using a single protocol in a single institute, ensuring that measurement biases were significantly minimized; (ii) The database contains large-scale data for healthy volunteers with various health records and genome data and (iii) Correlations between metabolites can be easily observed using the graphical viewer. Metabolites data are becoming important intermediate markers for evaluating the health states of humans, and thus jMorp is an outstanding resource for a wide range of researchers, particularly those in the fields of medical science, applied molecular biology, and biochemistry.
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Affiliation(s)
- Shu Tadaka
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Miyagi 980-8575, Japan.,Graduate School of Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Miyagi 980-8573, Japan
| | - Daisuke Saigusa
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Miyagi 980-8575, Japan.,Graduate School of Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Miyagi 980-8573, Japan
| | - Ikuko N Motoike
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Miyagi 980-8575, Japan.,Graduate School of Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Miyagi 980-8573, Japan.,Graduate School of Information Sciences, Tohoku University, 6-3-09, Aramaki aza Aoba, Aoba-ku, Miyagi 980-8579, Japan
| | - Jin Inoue
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Miyagi 980-8575, Japan.,Graduate School of Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Miyagi 980-8573, Japan
| | - Yuichi Aoki
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Miyagi 980-8575, Japan.,Graduate School of Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Miyagi 980-8573, Japan.,Graduate School of Information Sciences, Tohoku University, 6-3-09, Aramaki aza Aoba, Aoba-ku, Miyagi 980-8579, Japan
| | - Matsuyuki Shirota
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Miyagi 980-8575, Japan.,Graduate School of Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Miyagi 980-8573, Japan.,Graduate School of Information Sciences, Tohoku University, 6-3-09, Aramaki aza Aoba, Aoba-ku, Miyagi 980-8579, Japan
| | - Seizo Koshiba
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Miyagi 980-8575, Japan.,Graduate School of Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Miyagi 980-8573, Japan
| | - Masayuki Yamamoto
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Miyagi 980-8575, Japan.,Graduate School of Medicine, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Miyagi 980-8573, Japan
| | - Kengo Kinoshita
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Miyagi 980-8575, Japan.,Graduate School of Information Sciences, Tohoku University, 6-3-09, Aramaki aza Aoba, Aoba-ku, Miyagi 980-8579, Japan.,Institute of Development, Aging and Cancer, Tohoku University, 4-1, Seiryo-machi, Aoba-ku, Miyagi 980-8575, Japan
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10
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Fuse N, Sakurai-Yageta M, Katsuoka F, Danjoh I, Shimizu R, Tamiya G, Nagami F, Kawame H, Higuchi S, Kinoshita K, Kure S, Yamamoto M. Establishment of Integrated Biobank for Precision Medicine and Personalized Healthcare: The Tohoku Medical Megabank Project. JMA J 2019; 2:113-122. [PMID: 33615021 PMCID: PMC7889718 DOI: 10.31662/jmaj.2019-0014] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2019] [Accepted: 04/12/2019] [Indexed: 12/30/2022] Open
Abstract
The Tohoku Medical Megabank (TMM) project was established to provide creative reconstruction of the Tohoku area that suffered from a huge earthquake and ensuing tsunami (the Great East Japan Earthquake, GEJE). TMM aims to establish two large-scale genome cohorts and an integrated biobank managing biospecimen and related information. It supports community medicine by establishing next-generation medical systems through a combination of the prospective genome cohort studies with a total of 150,000 participants and genomic medicine. The strategies for genome analyses in TMM are to develop an elaborate genome reference panel by means of high-fidelity Japanese whole-genome sequence, to design custom single nucleotide polymorphism (SNP) arrays based on the reference panel, and to obtain genotype data for all the TMM cohort participants subsequently. Disease-associated genomic information and omics data, including metabolomics and microbiome analysis, provide an essential platform for precision medicine and personalized healthcare (PHC). Ethical, legal, and social issues (ELSI) and education are important for implementing genomic medicine. The major considerations of ELSI regarding each participant of the cohort studies are the respect for the autonomy and the protection of privacies. Moreover, developing and provide human resources not only for the TMM project but also for the social implementation of precision medicine and PHC is required. We started a pilot study of the return of genomic results for familial hypercholesterolemia (FH) as a target disease. TMM aims to establish solid platforms that support precision medicine and PHC based on the genomic and omics information and environmental and lifestyle factors of the individuals, which is one of the most advanced medical care beyond the evidenced-based medicine in the near future.
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Affiliation(s)
- Nobuo Fuse
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Mika Sakurai-Yageta
- Department of Education and Training, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Fumiki Katsuoka
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Inaho Danjoh
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Ritsuko Shimizu
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.,Department of Molecular Hematology, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Gen Tamiya
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.,Statistical Genetics Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
| | - Fuji Nagami
- Department of Public Relations and Planning, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Hiroshi Kawame
- Department of Education and Training, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Shinichi Higuchi
- Department of Public Relations and Planning, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Kengo Kinoshita
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.,Department of Applied Information Sciences, Graduate School of Information Sciences, Tohoku University, Sendai, Japan
| | - Shigeo Kure
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.,Department of Pediatrics, Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Masayuki Yamamoto
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.,Department of Medical Biochemistry, Graduate School of Medicine, Tohoku University, Sendai, Japan
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11
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Estimating carrier frequencies of newborn screening disorders using a whole-genome reference panel of 3552 Japanese individuals. Hum Genet 2019; 138:389-409. [PMID: 30887117 DOI: 10.1007/s00439-019-01998-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2019] [Accepted: 03/06/2019] [Indexed: 12/19/2022]
Abstract
Incidence rates of Mendelian diseases vary among ethnic groups, and frequencies of variant types of causative genes also vary among human populations. In this study, we examined to what extent we can predict population frequencies of recessive disorders from genomic data, and explored better strategies for variant interpretation and classification. We used a whole-genome reference panel from 3552 general Japanese individuals constructed by the Tohoku Medical Megabank Organization (ToMMo). Focusing on 32 genes for 17 congenital metabolic disorders included in newborn screening (NBS) in Japan, we identified reported and predicted pathogenic variants through variant annotation, interpretation, and multiple ways of classifications. The estimated carrier frequencies were compared with those from the Japanese NBS data based on 1,949,987 newborns from a previous study. The estimated carrier frequency based on genomic data with a recent guideline of variant interpretation for the PAH gene, in which defects cause hyperphenylalaninemia (HPA) and phenylketonuria (PKU), provided a closer estimate to that by the observed incidence than the other methods. In contrast, the estimated carrier frequencies for SLC25A13, which causes citrin deficiency, were much higher compared with the incidence rate. The results varied greatly among the 11 NBS diseases with single responsible genes; the possible reasons for departures from the carrier frequencies by reported incidence rates were discussed. Of note, (1) the number of pathogenic variants increases by including additional lines of evidence, (2) common variants with mild effects also contribute to the actual frequency of patients, and (3) penetrance of each variant remains unclear.
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12
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Yasuda J, Kinoshita K, Katsuoka F, Danjoh I, Sakurai-Yageta M, Motoike IN, Kuroki Y, Saito S, Kojima K, Shirota M, Saigusa D, Otsuki A, Kawashima J, Yamaguchi-Kabata Y, Tadaka S, Aoki Y, Mimori T, Kumada K, Inoue J, Makino S, Kuriki M, Fuse N, Koshiba S, Tanabe O, Nagasaki M, Tamiya G, Shimizu R, Takai-Igarashi T, Ogishima S, Hozawa A, Kuriyama S, Sugawara J, Tsuboi A, Kiyomoto H, Ishii T, Tomita H, Minegishi N, Suzuki Y, Suzuki K, Kawame H, Tanaka H, Taki Y, Yaegashi N, Kure S, Nagami F, Kosaki K, Sutoh Y, Hachiya T, Shimizu A, Sasaki M, Yamamoto M. Genome analyses for the Tohoku Medical Megabank Project towards establishment of personalized healthcare. J Biochem 2019; 165:139-158. [PMID: 30452759 DOI: 10.1093/jb/mvy096] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2018] [Accepted: 11/10/2018] [Indexed: 12/29/2022] Open
Abstract
Personalized healthcare (PHC) based on an individual's genetic make-up is one of the most advanced, yet feasible, forms of medical care. The Tohoku Medical Megabank (TMM) Project aims to combine population genomics, medical genetics and prospective cohort studies to develop a critical infrastructure for the establishment of PHC. To date, a TMM CommCohort (adult general population) and a TMM BirThree Cohort (birth+three-generation families) have conducted recruitments and baseline surveys. Genome analyses as part of the TMM Project will aid in the development of a high-fidelity whole-genome Japanese reference panel, in designing custom single-nucleotide polymorphism (SNP) arrays specific to Japanese, and in estimation of the biological significance of genetic variations through linked investigations of the cohorts. Whole-genome sequencing from >3,500 unrelated Japanese and establishment of a Japanese reference genome sequence from long-read data have been done. We next aim to obtain genotype data for all TMM cohort participants (>150,000) using our custom SNP arrays. These data will help identify disease-associated genomic signatures in the Japanese population, while genomic data from TMM BirThree Cohort participants will be used to improve the reference genome panel. Follow-up of the cohort participants will allow us to test the genetic markers and, consequently, contribute to the realization of PHC.
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Affiliation(s)
- Jun Yasuda
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Kengo Kinoshita
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan.,Department of Applied Information Sciences, Graduate School of Information Sciences, Tohoku University, 6-6-05 Aramaki Aza Aoba, Aoba-ku, Sendai, Japan.,Institute of Development, Aging, and Cancer, Tohoku University, 4-1, Seiryo-machi, Aoba-ku, Sendai, Japan
| | - Fumiki Katsuoka
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Inaho Danjoh
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Mika Sakurai-Yageta
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Ikuko N Motoike
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Yoko Kuroki
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Sakae Saito
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Kaname Kojima
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Matsuyuki Shirota
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan.,United Centers for Advanced Research and Translational Medicine
| | - Daisuke Saigusa
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Akihito Otsuki
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Junko Kawashima
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Yumi Yamaguchi-Kabata
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Shu Tadaka
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Yuichi Aoki
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Takahiro Mimori
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Kazuki Kumada
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Jin Inoue
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Satoshi Makino
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Miho Kuriki
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Nobuo Fuse
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Seizo Koshiba
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Osamu Tanabe
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Masao Nagasaki
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Gen Tamiya
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Ritsuko Shimizu
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan.,Department of Molecular Hematology, Tohoku University Graduate School of Medicine, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Takako Takai-Igarashi
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Soichi Ogishima
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Atsushi Hozawa
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Shinichi Kuriyama
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan.,International Research Institute of Disaster Science, Tohoku University, 468-1, Aramaki Aza Aoba, Aoba-ku, Sendai, Japan
| | - Junichi Sugawara
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Akito Tsuboi
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Hideyasu Kiyomoto
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Tadashi Ishii
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan.,Department of Education and Support for Community Medicine, Tohoku University Graduate School of Medicine, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Hiroaki Tomita
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan.,International Research Institute of Disaster Science, Tohoku University, 468-1, Aramaki Aza Aoba, Aoba-ku, Sendai, Japan
| | - Naoko Minegishi
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Yoichi Suzuki
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Kichiya Suzuki
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Hiroshi Kawame
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Hiroshi Tanaka
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan.,Medical Data Science Promotion Office, Tokyo Medical and Dental University, 2-3-10 Kandasurugadai, Chiyoda-ku, Tokyo, Japan
| | - Yasuyuki Taki
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan.,Institute of Development, Aging, and Cancer, Tohoku University, 4-1, Seiryo-machi, Aoba-ku, Sendai, Japan
| | - Nobuo Yaegashi
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan.,Department of Obstetrics and Gynecology
| | - Shigeo Kure
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan.,Department of Pediatrics, Tohoku University Graduate School of Medicine, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | - Fuji Nagami
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
| | | | - Kenjiro Kosaki
- Center for Medical Genetics, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, Japan
| | - Yoichi Sutoh
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center
| | - Tsuyoshi Hachiya
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center
| | - Atsushi Shimizu
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center
| | - Makoto Sasaki
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center.,Division of Ultrahigh Field MRI, Institute for Biomedical Sciences Iwate Medical University, 2-1-1 Nishitokuta, Yahaba, Shiwa, Iwate, Japan
| | - Masayuki Yamamoto
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan.,Department of Medical Biochemistry, Tohoku University Graduate School of Medicine, 2-1, Seiryo-Machi, Aoba-ku, Sendai, Japan
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13
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Sugawara J, Ochi D, Yamashita R, Yamauchi T, Saigusa D, Wagata M, Obara T, Ishikuro M, Tsunemoto Y, Harada Y, Shibata T, Mimori T, Kawashima J, Katsuoka F, Igarashi-Takai T, Ogishima S, Metoki H, Hashizume H, Fuse N, Minegishi N, Koshiba S, Tanabe O, Kuriyama S, Kinoshita K, Kure S, Yaegashi N, Yamamoto M, Hiyama S, Nagasaki M. Maternity Log study: a longitudinal lifelog monitoring and multiomics analysis for the early prediction of complicated pregnancy. BMJ Open 2019; 9:e025939. [PMID: 30782942 PMCID: PMC6398744 DOI: 10.1136/bmjopen-2018-025939] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
PURPOSE A prospective cohort study for pregnant women, the Maternity Log study, was designed to construct a time-course high-resolution reference catalogue of bioinformatic data in pregnancy and explore the associations between genomic and environmental factors and the onset of pregnancy complications, such as hypertensive disorders of pregnancy, gestational diabetes mellitus and preterm labour, using continuous lifestyle monitoring combined with multiomics data on the genome, transcriptome, proteome, metabolome and microbiome. PARTICIPANTS Pregnant women were recruited at the timing of first routine antenatal visits at Tohoku University Hospital, Sendai, Japan, between September 2015 and November 2016. Of the eligible women who were invited, 65.4% agreed to participate, and a total of 302 women were enrolled. The inclusion criteria were age ≥20 years and the ability to access the internet using a smartphone in the Japanese language. FINDINGS TO DATE Study participants uploaded daily general health information including quality of sleep, condition of bowel movements and the presence of nausea, pain and uterine contractions. Participants also collected physiological data, such as body weight, blood pressure, heart rate and body temperature, using multiple home healthcare devices. The mean upload rate for each lifelog item was ranging from 67.4% (fetal movement) to 85.3% (physical activity), and the total number of data points was over 6 million. Biospecimens, including maternal plasma, serum, urine, saliva, dental plaque and cord blood, were collected for multiomics analysis. FUTURE PLANS Lifelog and multiomics data will be used to construct a time-course high-resolution reference catalogue of pregnancy. The reference catalogue will allow us to discover relationships among multidimensional phenotypes and novel risk markers in pregnancy for the future personalised early prediction of pregnancy complications.
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Affiliation(s)
- Junichi Sugawara
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Daisuke Ochi
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Research Laboratories, NTT DoCoMo, Inc, Yokosuka, Japan
| | - Riu Yamashita
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Takafumi Yamauchi
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Research Laboratories, NTT DoCoMo, Inc, Yokosuka, Japan
| | - Daisuke Saigusa
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Maiko Wagata
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Taku Obara
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Mami Ishikuro
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | | | - Yuki Harada
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Tomoko Shibata
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Takahiro Mimori
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Junko Kawashima
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Fumiki Katsuoka
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | | | - Soichi Ogishima
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | | | - Hiroaki Hashizume
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Nobuo Fuse
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Naoko Minegishi
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Seizo Koshiba
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Osamu Tanabe
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Radiation Effects Research Foundation, Hiroshima, Japan
| | - Shinichi Kuriyama
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Kengo Kinoshita
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Shigeo Kure
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Nobuo Yaegashi
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Tohoku University Hospital, Sendai, Japan
| | - Masayuki Yamamoto
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Satoshi Hiyama
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Research Laboratories, NTT DoCoMo, Inc, Yokosuka, Japan
| | - Masao Nagasaki
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Tohoku University Graduate School of Medicine, Sendai, Japan
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14
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Koshiba S, Motoike I, Saigusa D, Inoue J, Shirota M, Katoh Y, Katsuoka F, Danjoh I, Hozawa A, Kuriyama S, Minegishi N, Nagasaki M, Takai-Igarashi T, Ogishima S, Fuse N, Kure S, Tamiya G, Tanabe O, Yasuda J, Kinoshita K, Yamamoto M. Omics research project on prospective cohort studies from the Tohoku Medical Megabank Project. Genes Cells 2018; 23:406-417. [PMID: 29701317 DOI: 10.1111/gtc.12588] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2018] [Accepted: 03/22/2018] [Indexed: 01/05/2023]
Abstract
Population-based prospective cohort studies are indispensable for modern medical research as they provide important knowledge on the influences of many kinds of genetic and environmental factors on the cause of disease. Although traditional cohort studies are mainly conducted using questionnaires and physical examinations, modern cohort studies incorporate omics and genomic approaches to obtain comprehensive physical information, including genetic information. Here, we report the design and midterm results of multi-omics analysis on population-based prospective cohort studies from the Tohoku Medical Megabank (TMM) Project. We have incorporated genomic and metabolomic studies in the TMM cohort study as both metabolome and genome analyses are suitable for high-throughput analysis of large-scale cohort samples. Moreover, an association study between the metabolome and genome show that metabolites are an important intermediate phenotype connecting genetic and lifestyle factors to physical and pathologic phenotypes. We apply our metabolome and genome analyses to large-scale cohort samples in the following studies.
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Affiliation(s)
- Seizo Koshiba
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Ikuko Motoike
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Graduate School of Information Sciences, Tohoku University, Sendai, Japan
| | - Daisuke Saigusa
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Jin Inoue
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Matsuyuki Shirota
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Yasutake Katoh
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Fumiki Katsuoka
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Inaho Danjoh
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Atsushi Hozawa
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Shinichi Kuriyama
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
- International Research Institute of Disaster Science, Tohoku University, Sendai, Japan
| | - Naoko Minegishi
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Masao Nagasaki
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
- Graduate School of Information Sciences, Tohoku University, Sendai, Japan
| | - Takako Takai-Igarashi
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Soichi Ogishima
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Nobuo Fuse
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Shigeo Kure
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Gen Tamiya
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
- RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
| | - Osamu Tanabe
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Jun Yasuda
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Kengo Kinoshita
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Graduate School of Information Sciences, Tohoku University, Sendai, Japan
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Masayuki Yamamoto
- Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
- Graduate School of Medicine, Tohoku University, Sendai, Japan
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15
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Evaluation of reported pathogenic variants and their frequencies in a Japanese population based on a whole-genome reference panel of 2049 individuals. J Hum Genet 2017; 63:213-230. [PMID: 29192238 DOI: 10.1038/s10038-017-0347-1] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2017] [Revised: 08/25/2017] [Accepted: 08/29/2017] [Indexed: 01/07/2023]
Abstract
Clarifying allele frequencies of disease-related genetic variants in a population is important in genomic medicine; however, such data is not yet available for the Japanese population. To estimate frequencies of actionable pathogenic variants in the Japanese population, we examined the reported pathological variants in genes recommended by the American College of Medical Genetics and Genomics (ACMG) in our reference panel of genomic variations, 2KJPN, which was created by whole-genome sequencing of 2049 individuals of the resident cohort of the Tohoku Medical Megabank Project. We searched for pathogenic variants in 2KJPN for 57 autosomal ACMG-recommended genes responsible for 26 diseases and then examined their frequencies. By referring to public databases of pathogenic variations, we identified 143 reported pathogenic variants in 2KJPN for the 57 ACMG recommended genes based on a classification system. At the individual level, 21% of the individuals were found to have at least one reported pathogenic allele. We then conducted a literature survey to review the variants and to check for evidence of pathogenicity. Our results suggest that a substantial number of people have reported pathogenic alleles for the ACMG genes, and reviewing variants is indispensable for constructing the information infrastructure of genomic medicine for the Japanese population.
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16
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Takai-Igarashi T, Kinoshita K, Nagasaki M, Ogishima S, Nakamura N, Nagase S, Nagaie S, Saito T, Nagami F, Minegishi N, Suzuki Y, Suzuki K, Hashizume H, Kuriyama S, Hozawa A, Yaegashi N, Kure S, Tamiya G, Kawaguchi Y, Tanaka H, Yamamoto M. Security controls in an integrated Biobank to protect privacy in data sharing: rationale and study design. BMC Med Inform Decis Mak 2017; 17:100. [PMID: 28683736 PMCID: PMC5501115 DOI: 10.1186/s12911-017-0494-5] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2016] [Accepted: 06/27/2017] [Indexed: 01/08/2023] Open
Abstract
Background With the goal of realizing genome-based personalized healthcare, we have developed a biobank that integrates personal health, genome, and omics data along with biospecimens donated by volunteers of 150,000. Such a large-scale of data integration involves obvious risks of privacy violation. The research use of personal genome and health information is a topic of global discussion with regard to the protection of privacy while promoting scientific advancement. The present paper reports on our plans, current attempts, and accomplishments in addressing security problems involved in data sharing to ensure donor privacy while promoting scientific advancement. Methods Biospecimens and data have been collected in prospective cohort studies with the comprehensive agreement. The sample size of 150,000 participants was required for multiple researches including genome-wide screening of gene by environment interactions, haplotype phasing, and parametric linkage analysis. Results We established the TohokuMedicalMegabank (TMM) data sharing policy: a privacy protection rule that requires physical, personnel, and technological safeguards against privacy violation regarding the use and sharing of data. The proposed policy refers to that of NCBI and that of the Sanger Institute. The proposed policy classifies shared data according to the strength of re-identification risks. Local committees organized by TMM evaluate re-identification risk and assign a security category to a dataset. Every dataset is stored in an assigned segment of a supercomputer in accordance with its security category. A security manager should be designated to handle all security problems at individual data use locations. The proposed policy requires closed networks and IP-VPN remote connections. Conclusion The mission of the biobank is to distribute biological resources most productively. This mission motivated us to collect biospecimens and health data and simultaneously analyze genome/omics data in-house. The biobank also has the mission of improving the quality and quantity of the contents of the biobank. This motivated us to request users to share the results of their research as feedback to the biobank. The TMM data sharing policy has tackled every security problem originating with the missions. We believe our current implementation to be the best way to protect privacy in data sharing. Electronic supplementary material The online version of this article (doi:10.1186/s12911-017-0494-5) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Takako Takai-Igarashi
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan.
| | - Kengo Kinoshita
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan.,Graduate School of Information Sciences, Tohoku University, Sendai, Japan
| | - Masao Nagasaki
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan
| | - Soichi Ogishima
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan
| | - Naoki Nakamura
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan.,Graduate School of Medicine, Tohoku University, Sendai, Japan.,Tohoku University Hospital, Tohoku University, Sendai, Japan
| | - Sachiko Nagase
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan.,Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Satoshi Nagaie
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan
| | - Tomo Saito
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan
| | - Fuji Nagami
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan.,Graduate School of Medicine, Tohoku University, Sendai, Japan.,Tohoku University Hospital, Tohoku University, Sendai, Japan
| | - Naoko Minegishi
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan.,Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Yoichi Suzuki
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan.,Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Kichiya Suzuki
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan.,Graduate School of Medicine, Tohoku University, Sendai, Japan.,Tohoku University Hospital, Tohoku University, Sendai, Japan
| | - Hiroaki Hashizume
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan
| | - Shinichi Kuriyama
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan.,Graduate School of Medicine, Tohoku University, Sendai, Japan.,International Research Institute of Disaster Science, Tohoku University, Sendai, Japan
| | - Atsushi Hozawa
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan.,Graduate School of Medicine, Tohoku University, Sendai, Japan
| | - Nobuo Yaegashi
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan.,Graduate School of Medicine, Tohoku University, Sendai, Japan.,Tohoku University Hospital, Tohoku University, Sendai, Japan
| | - Shigeo Kure
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan.,Graduate School of Medicine, Tohoku University, Sendai, Japan.,Tohoku University Hospital, Tohoku University, Sendai, Japan
| | - Gen Tamiya
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan
| | - Yoshio Kawaguchi
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan
| | - Hiroshi Tanaka
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan
| | - Masayuki Yamamoto
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Japan. .,Graduate School of Medicine, Tohoku University, Sendai, Japan.
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