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Sakashita T, Nakamura Y, Sutoh Y, Shimizu A, Hachiya T, Otsuka-Yamasaki Y, Takashima N, Kadota A, Miura K, Kita Y, Ikezaki H, Otonari J, Tanaka K, Shimanoe C, Koyama T, Watanabe I, Suzuki S, Nakagawa-Senda H, Hishida A, Tamura T, Kato Y, Okada R, Kuriki K, Katsuura-Kamano S, Watanabe T, Tanoue S, Koriyama C, Oze I, Koyanagi YN, Nakamura Y, Kusakabe M, Nakatochi M, Momozawa Y, Wakai K, Matsuo K. Comparison of the loci associated with HbA1c and blood glucose levels identified by a genome-wide association study in the Japanese population. Diabetol Int 2023; 14:188-198. [PMID: 37090135 PMCID: PMC10113415 DOI: 10.1007/s13340-023-00618-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 01/15/2023] [Indexed: 01/28/2023]
Abstract
Aims Hemoglobin A1c (HbA1c) levels are widely employed to diagnose diabetes. However, estimates of the heritability of HbA1c and glucose levels are different. Therefore, we explored HbA1c- and blood glucose-associated loci in a non-diabetic Japanese population. Methods We conducted a two-stage genome-wide association study (GWAS) on variants associated with HbA1c and blood glucose levels in a Japanese population. In the initial stage, data of 4911 participants of the Japan Multi-Institutional Collaborative Cohort (J-MICC) were subjected to discovery analysis. In the second stage, two datasets from the Tohoku Medical Megabank project, with 8175 and 40,519 participants, were used for the replication study. Association of the imputed variants with HbA1c and blood glucose levels was determined via linear regression analyses adjusted for age, sex, body mass index (BMI), smoking, and genetic principal components (PC1-PC10). Moreover, we performed a BMI-stratified GWAS on HbA1c levels in the J-MICC. The discovery analysis and BMI-stratified GWAS results were validated with re-analyses of normalized HbA1c levels adjusted for site in addition to the above, and blood glucose adjusted for fasting time as an additional covariate. Results Genetic variants associated with HbA1c levels were identified in KCNQ1 and TMC6. None of the genetic variants associated with blood glucose levels in the discovery analysis were replicated. Association of rs2299620 in KCNQ1 with HbA1c levels showed heterogeneity between individuals with BMI ≥ 25 kg/m2 and BMI < 25 kg/m2. Conclusions The variant rs2299620 in KCNQ1 might affect HbA1c levels differentially based on BMI grouping in the Japanese population. Supplementary Information The online version contains supplementary material available at 10.1007/s13340-023-00618-0.
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Affiliation(s)
- Takuya Sakashita
- Department of Public Health, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192 Japan
- TAKARA BIO INC., 7-4-38 Nojihigashi, Kusatsu, Shiga 525-0058 Japan
| | - Yasuyuki Nakamura
- Department of Public Health, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192 Japan
- Takeda Hospital Medical Examination Center, Kyoto, Japan
| | - Yoichi Sutoh
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, 1-1-1 Idaidori, Yahaba-cho, Shiwa-gun, Iwate, 028-3694 Japan
| | - Atsushi Shimizu
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, 1-1-1 Idaidori, Yahaba-cho, Shiwa-gun, Iwate, 028-3694 Japan
| | - Tsuyoshi Hachiya
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, 1-1-1 Idaidori, Yahaba-cho, Shiwa-gun, Iwate, 028-3694 Japan
| | - Yayoi Otsuka-Yamasaki
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, 1-1-1 Idaidori, Yahaba-cho, Shiwa-gun, Iwate, 028-3694 Japan
| | - Naoyuki Takashima
- Department of Public Health, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192 Japan
- Department of Public Health, Faculty of Medicine, Kindai University, 377-2 Ohnohigashi, Osaka-Sayama, Osaka 589-8511 Japan
- Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kamigyo- ku, Kyoto, 602-8566 Japan
| | - Aya Kadota
- Department of Public Health, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192 Japan
- NCD Epidemiology Research Center, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192 Japan
| | - Katsuyuki Miura
- Department of Public Health, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192 Japan
- NCD Epidemiology Research Center, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192 Japan
| | - Yoshikuni Kita
- Department of Public Health, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192 Japan
- Faculty of Nursing Science, Tsuruga Nursing University, 78-2-1 Kizaki, Tsuruga, Fukui 914-0814 Japan
| | - Hiroaki Ikezaki
- Department of Comprehensive General Internal Medicine, Faculty of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582 Japan
- Department of General Internal Medicine, Kyushu University Hospital, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582 Japan
| | - Jun Otonari
- Department of Psychosomatic Medicine, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582 Japan
| | - Keitaro Tanaka
- Department of Preventive Medicine, Faculty of Medicine, Saga University, 5-1-1 Nabeshima, Saga, 849-8501 Japan
| | - Chisato Shimanoe
- Department of Pharmacy, Saga University Hospital, 5-1-1 Nabeshima, Saga, 849-8501 Japan
| | - Teruhide Koyama
- Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kamigyo- ku, Kyoto, 602-8566 Japan
| | - Isao Watanabe
- Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine, 465 Kajii-cho, Kamigyo- ku, Kyoto, 602-8566 Japan
| | - Sadao Suzuki
- Department of Public Health, Nagoya City University Graduate School of Medical Sciences, 1 Kawasumi, Mizuho-cho, Mizuho-ku, Nagoya, 467-8601 Japan
| | - Hiroko Nakagawa-Senda
- Department of Public Health, Nagoya City University Graduate School of Medical Sciences, 1 Kawasumi, Mizuho-cho, Mizuho-ku, Nagoya, 467-8601 Japan
| | - Asahi Hishida
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550 Japan
| | - Takashi Tamura
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550 Japan
| | - Yasufumi Kato
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550 Japan
| | - Rieko Okada
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550 Japan
| | - Kiyonori Kuriki
- Laboratory of Public Health, Division of Nutritional Sciences, School of Food and Nutritional Sciences, University of Shizuoka, 52-1 Yada, Suruga-ku, Shizuoka, 422-8526 Japan
| | - Sakurako Katsuura-Kamano
- Department of Preventive Medicine, Tokushima University Graduate School of Biomedical Sciences, 3-18-15 Kuramoto-cho, Tokushima, 770-8503 Japan
| | - Takeshi Watanabe
- Department of Preventive Medicine, Tokushima University Graduate School of Biomedical Sciences, 3-18-15 Kuramoto-cho, Tokushima, 770-8503 Japan
| | - Shiroh Tanoue
- Department of Epidemiology and Preventive Medicine, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544 Japan
| | - Chihaya Koriyama
- Department of Epidemiology and Preventive Medicine, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima, 890-8544 Japan
| | - Isao Oze
- Division of Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya, 464-8681 Japan
| | - Yuriko N. Koyanagi
- Division of Cancer Information and Control, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya, 464-8681 Japan
| | - Yohko Nakamura
- Cancer Prevention Center, Chiba Cancer Center Research Institute, 666-2 Nitona-cho, Chuo-ku, Chiba, 260-8717 Japan
| | - Miho Kusakabe
- Cancer Prevention Center, Chiba Cancer Center Research Institute, 666-2 Nitona-cho, Chuo-ku, Chiba, 260-8717 Japan
| | - Masahiro Nakatochi
- Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, 1-1-20 Daiko-Minami, Higashi-ku, Nagoya, 461-8673 Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, Center for Integrative Medical Sciences, RIKEN, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045 Japan
| | - Kenji Wakai
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550 Japan
| | - Keitaro Matsuo
- Division of Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute, 1-1 Kanokoden, Chikusa-ku, Nagoya, 464-8681 Japan
- Division of Cancer Epidemiology, Nagoya University Graduate School of Medicine, 65 Tsurumai-cho, Showa-ku, Nagoya, 466-8550 Japan
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Impact of diet and host genetics on the murine intestinal mycobiome. Nat Commun 2023; 14:834. [PMID: 36788222 PMCID: PMC9929102 DOI: 10.1038/s41467-023-36479-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 02/01/2023] [Indexed: 02/16/2023] Open
Abstract
The mammalian gut is home to a diverse microbial ecosystem, whose composition affects various physiological traits of the host. Next-generation sequencing-based metagenomic approaches demonstrated how the interplay of host genetics, bacteria, and environmental factors shape complex traits and clinical outcomes. However, the role of fungi in these complex interactions remains understudied. Here, using 228 males and 363 females from an advanced-intercross mouse line, we provide evidence that fungi are regulated by host genetics. In addition, we map quantitative trait loci associated with various fungal species to single genes in mice using whole genome sequencing and genotyping. Moreover, we show that diet and its' interaction with host genetics alter the composition of fungi in outbred mice, and identify fungal indicator species associated with different dietary regimes. Collectively, in this work, we uncover an association of the intestinal fungal community with host genetics and a regulatory role of diet in this ecological niche.
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Ohbe H, Hachiya T, Yamaji T, Nakano S, Miyamoto Y, Sutoh Y, Otsuka-Yamasaki Y, Shimizu A, Yasunaga H, Sawada N, Inoue M, Tsugane S, Iwasaki M. Development and validation of genome-wide polygenic risk scores for predicting breast cancer incidence in Japanese females: a population-based case-cohort study. Breast Cancer Res Treat 2023; 197:661-671. [PMID: 36538246 DOI: 10.1007/s10549-022-06843-6] [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: 09/28/2022] [Accepted: 12/08/2022] [Indexed: 12/24/2022]
Abstract
PURPOSE This study aimed to develop an ancestry-specific polygenic risk scores (PRSs) for the prediction of breast cancer events in Japanese females and validate it in a longitudinal cohort study. METHODS Using publicly available summary statistics of female breast cancer genome-wide association study (GWAS) of Japanese and European ancestries, we, respectively, developed 31 candidate genome-wide PRSs using pruning and thresholding (P + T) and LDpred methods with varying parameters. Among the candidate PRS models, the best model was selected using a case-cohort dataset (63 breast cancer cases and 2213 sub-cohorts of Japanese females during a median follow-up of 11.9 years) according to the maximal predictive ability by Harrell's C-statistics. The best-performing PRS for each derivation GWAS was evaluated in another independent case-cohort dataset (260 breast cancer cases and 7845 sub-cohorts of Japanese females during a median follow-up of 16.9 years). RESULTS For the best PRS model involving 46,861 single nucleotide polymorphisms (SNPs; P + T method with PT = 0.05 and R2 = 0.2) derived from Japanese-ancestry GWAS, the Harrell's C-statistic was 0.598 ± 0.018 in the evaluation dataset. The age-adjusted hazard ratio for breast cancer in females with the highest PRS quintile compared with those in the lowest PRS quintile was 2.47 (95% confidence intervals, 1.64-3.70). The PRS constructed using Japanese-ancestry GWAS demonstrated better predictive performance for breast cancer in Japanese females than that using European-ancestry GWAS (Harrell's C-statistics 0.598 versus 0.586). CONCLUSION This study developed a breast cancer PRS for Japanese females and demonstrated the usefulness of the PRS for breast cancer risk stratification.
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Affiliation(s)
- Hiroyuki Ohbe
- Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan
| | - Tsuyoshi Hachiya
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, 1-1-1 Idaidori, Yahaba, Shiwa, Iwate, 028-3694, Japan.
| | - Taiki Yamaji
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.
| | - Shiori Nakano
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Yoshihisa Miyamoto
- Division of Cohort Research, National Cancer Center Institute for Cancer Control, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Yoichi Sutoh
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, 1-1-1 Idaidori, Yahaba, Shiwa, Iwate, 028-3694, Japan
| | - Yayoi Otsuka-Yamasaki
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, 1-1-1 Idaidori, Yahaba, Shiwa, Iwate, 028-3694, Japan
| | - Atsushi Shimizu
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, 1-1-1 Idaidori, Yahaba, Shiwa, Iwate, 028-3694, Japan
| | - Hideo Yasunaga
- Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan
| | - Norie Sawada
- Division of Cohort Research, National Cancer Center Institute for Cancer Control, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Manami Inoue
- Division of Cohort Research, National Cancer Center Institute for Cancer Control, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.,Division of Prevention, National Cancer Center Institute for Cancer Control, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
| | - Shoichiro Tsugane
- Division of Cohort Research, National Cancer Center Institute for Cancer Control, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.,National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, 162-8636, Japan
| | - Motoki Iwasaki
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan.,Division of Cohort Research, National Cancer Center Institute for Cancer Control, 5-1-1 Tsukiji, Chuo-ku, Tokyo, 104-0045, Japan
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4
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Wade AN, Crowther NJ, Abrahams-Gessel S, Berkman L, George JA, Gómez-Olivé FX, Manne-Goehler J, Salomon JA, Wagner RG, Gaziano TA, Tollman SM, Cappola AR. Concordance between fasting plasma glucose and HbA 1c in the diagnosis of diabetes in black South African adults: a cross-sectional study. BMJ Open 2021; 11:e046060. [PMID: 34140342 PMCID: PMC8212405 DOI: 10.1136/bmjopen-2020-046060] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
OBJECTIVES We investigated concordance between haemoglobin A1c (HbA1c)-defined diabetes and fasting plasma glucose (FPG)-defined diabetes in a black South African population with a high prevalence of obesity. DESIGN Cross-sectional study. SETTING Rural South African population-based cohort. PARTICIPANTS 765 black individuals aged 40-70 years and with no history of diabetes. PRIMARY AND SECONDARY OUTCOME MEASURES The primary outcome measure was concordance between HbA1c-defined diabetes and FPG-defined diabetes. Secondary outcome measures were differences in anthropometric characteristics, fat distribution and insulin resistance (measured using Homoeostatic Model Assessment of Insulin Resistance (HOMA-IR)) between those with concordant and discordant HbA1c/FPG classifications and predictors of HbA1c variance. RESULTS The prevalence of HbA1c-defined diabetes was four times the prevalence of FPG-defined diabetes (17.5% vs 4.2%). Classification was discordant in 15.7% of participants, with 111 individuals (14.5%) having HbA1c-only diabetes (kappa 0.23; 95% CI 0.14 to 0.31). Median body mass index, waist and hip circumference, waist-to-hip ratio, subcutaneous adipose tissue and HOMA-IR in participants with HbA1c-only diabetes were similar to those in participants who were normoglycaemic by both biomarkers and significantly lower than in participants with diabetes by both biomarkers (p<0.05). HOMA-IR and fat distribution explained additional HbA1c variance beyond glucose and age only in women. CONCLUSIONS Concordance was poor between HbA1c and FPG in diagnosis of diabetes in black South Africans, and participants with HbA1c-only diabetes phenotypically resembled normoglycaemic participants. Further work is necessary to determine which of these parameters better predicts diabetes-related morbidities in this population and whether a population-specific HbA1c threshold is necessary.
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Affiliation(s)
- Alisha N Wade
- MRC/Wits Rural Public Health and Health Transitions Research Unit, School of Public Health, University of the Witwatersrand, Johannesburg, South Africa
| | - Nigel J Crowther
- Department of Chemical Pathology, University of the Witwatersrand, Johannesburg, South Africa
- Department of Chemical Pathology, National Health Laboratory Service, Johannesburg, South Africa
| | - Shafika Abrahams-Gessel
- Centre for Health Decision Science, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA
| | - Lisa Berkman
- Harvard Centre for Population and Development Studies, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA
| | - Jaya A George
- Department of Chemical Pathology, University of the Witwatersrand, Johannesburg, South Africa
- Department of Chemical Pathology, National Health Laboratory Service, Johannesburg, South Africa
| | - F Xavier Gómez-Olivé
- MRC/Wits Rural Public Health and Health Transitions Research Unit, School of Public Health, University of the Witwatersrand, Johannesburg, South Africa
| | - Jennifer Manne-Goehler
- Division of Infectious Diseases, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Joshua A Salomon
- Centre for Health Policy, Stanford University, Stanford, California, USA
| | - Ryan G Wagner
- MRC/Wits Rural Public Health and Health Transitions Research Unit, School of Public Health, University of the Witwatersrand, Johannesburg, South Africa
| | - Thomas A Gaziano
- Centre for Health Decision Science, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA
- Division of Cardiovascular Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Stephen M Tollman
- MRC/Wits Rural Public Health and Health Transitions Research Unit, School of Public Health, University of the Witwatersrand, Johannesburg, South Africa
- INDEPTH Network, Accra, Ghana
- Umeå Centre for Global Health Research, Division of Epidemiology and Global Health, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Anne R Cappola
- Division of Endocrinology, Diabetes, and Metabolism, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
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SIX2 Regulates Human β Cell Differentiation from Stem Cells and Functional Maturation In Vitro. Cell Rep 2021; 31:107687. [PMID: 32460030 PMCID: PMC7304247 DOI: 10.1016/j.celrep.2020.107687] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2020] [Revised: 03/24/2020] [Accepted: 05/04/2020] [Indexed: 12/30/2022] Open
Abstract
Generation of insulin-secreting β cells in vitro is a promising approach for diabetes cell therapy. Human embryonic stem cells (hESCs) and human induced pluripotent stem cells (hiPSCs) are differentiated to β cells (SC-β cells) and mature to undergo glucose-stimulated insulin secretion, but molecular regulation of this defining β cell phenotype is unknown. Here, we show that maturation of SC-β cells is regulated by the transcription factor SIX2. Knockdown (KD) or knockout (KO) of SIX2 in SC-β cells drastically limits glucose-stimulated insulin secretion in both static and dynamic assays, along with the upstream processes of cytoplasmic calcium flux and mitochondrial respiration. Furthermore, SIX2 regulates the expression of genes associated with these key β cell processes, and its expression is restricted to endocrine cells. Our results demonstrate that expression of SIX2 influences the generation of human SC-β cells in vitro. Velazco-Cruz et al. characterize the role of SIX2 in stem cell differentiation to β cells. SIX2 expression is restricted to late-stage endocrine cells. Generation of β cells does not require SIX2, but lack of SIX2 impairs maturation, as assessed by glucose-stimulated insulin secretion, calcium flux, mitochondrial respiration, and gene expression.
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Bevacqua RJ, Dai X, Lam JY, Gu X, Friedlander MSH, Tellez K, Miguel-Escalada I, Bonàs-Guarch S, Atla G, Zhao W, Kim SH, Dominguez AA, Qi LS, Ferrer J, MacDonald PE, Kim SK. CRISPR-based genome editing in primary human pancreatic islet cells. Nat Commun 2021; 12:2397. [PMID: 33893274 PMCID: PMC8065166 DOI: 10.1038/s41467-021-22651-w] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Accepted: 03/22/2021] [Indexed: 02/02/2023] Open
Abstract
Gene targeting studies in primary human islets could advance our understanding of mechanisms driving diabetes pathogenesis. Here, we demonstrate successful genome editing in primary human islets using clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein 9 (Cas9). CRISPR-based targeting efficiently mutated protein-coding exons, resulting in acute loss of islet β-cell regulators, like the transcription factor PDX1 and the KATP channel subunit KIR6.2, accompanied by impaired β-cell regulation and function. CRISPR targeting of non-coding DNA harboring type 2 diabetes (T2D) risk variants revealed changes in ABCC8, SIX2 and SIX3 expression, and impaired β-cell function, thereby linking regulatory elements in these target genes to T2D genetic susceptibility. Advances here establish a paradigm for genetic studies in human islet cells, and reveal regulatory and genetic mechanisms linking non-coding variants to human diabetes risk.
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Affiliation(s)
- Romina J Bevacqua
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - Xiaoqing Dai
- Alberta Diabetes Institute and Department of Pharmacology, University of Alberta, Edmonton, AB, Canada
| | - Jonathan Y Lam
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - Xueying Gu
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - Mollie S H Friedlander
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - Krissie Tellez
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - Irene Miguel-Escalada
- Bioinformatics and Genomics Program, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Barcelona, Spain
| | - Silvia Bonàs-Guarch
- Bioinformatics and Genomics Program, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Barcelona, Spain
| | - Goutham Atla
- Bioinformatics and Genomics Program, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Barcelona, Spain
| | - Weichen Zhao
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - Seung Hyun Kim
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - Antonia A Dominguez
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Department of Chemical and Systems Biology, Stanford University, Stanford, CA, USA
| | - Lei S Qi
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Department of Chemical and Systems Biology, Stanford University, Stanford, CA, USA
- Chem-H, Stanford University, Stanford, CA, USA
| | - Jorge Ferrer
- Bioinformatics and Genomics Program, Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology (BIST), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Barcelona, Spain
- Section of Genetics and Genomics, Imperial College London, London, UK
| | - Patrick E MacDonald
- Alberta Diabetes Institute and Department of Pharmacology, University of Alberta, Edmonton, AB, Canada
| | - Seung K Kim
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Medicine (Endocrinology), Stanford University School of Medicine, Stanford, CA, USA.
- Northern California JDRF Center of Excellence, Stanford University School of Medicine, Stanford, CA, USA.
- Stanford Diabetes Research Center, Stanford University School of Medicine, Stanford, CA, USA.
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7
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Abdelalim EM. Modeling different types of diabetes using human pluripotent stem cells. Cell Mol Life Sci 2021; 78:2459-2483. [PMID: 33242105 PMCID: PMC11072720 DOI: 10.1007/s00018-020-03710-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 10/19/2020] [Accepted: 11/11/2020] [Indexed: 12/22/2022]
Abstract
Diabetes mellitus (DM) is a metabolic disease characterized by chronic hyperglycemia as a result of progressive loss of pancreatic β cells, which could lead to several debilitating complications. Different paths, triggered by several genetic and environmental factors, lead to the loss of pancreatic β cells and/or function. Understanding these many paths to β cell damage or dysfunction could help in identifying therapeutic approaches specific for each path. Most of our knowledge about diabetes pathophysiology has been obtained from studies on animal models, which do not fully recapitulate human diabetes phenotypes. Currently, human pluripotent stem cell (hPSC) technology is a powerful tool for generating in vitro human models, which could provide key information about the disease pathogenesis and provide cells for personalized therapies. The recent progress in generating functional hPSC-derived β cells in combination with the rapid development in genomic and genome-editing technologies offer multiple options to understand the cellular and molecular mechanisms underlying the development of different types of diabetes. Recently, several in vitro hPSC-based strategies have been used for studying monogenic and polygenic forms of diabetes. This review summarizes the current knowledge about different hPSC-based diabetes models and how these models improved our current understanding of the pathophysiology of distinct forms of diabetes. Also, it highlights the progress in generating functional β cells in vitro, and discusses the current challenges and future perspectives related to the use of the in vitro hPSC-based strategies.
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Affiliation(s)
- Essam M Abdelalim
- Diabetes Research Center, Qatar Biomedical Research Institute (QBRI), Hamad Bin Khalifa University (HBKU), Qatar Foundation (QF), PO Box 34110, Doha, Qatar.
- College of Health and Life Sciences, Hamad Bin Khalifa University (HBKU), Qatar Foundation (QF), Education City, Doha, Qatar.
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8
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Bevacqua RJ, Lam JY, Peiris H, Whitener RL, Kim S, Gu X, Friedlander MSH, Kim SK. SIX2 and SIX3 coordinately regulate functional maturity and fate of human pancreatic β cells. Genes Dev 2021; 35:234-249. [PMID: 33446570 PMCID: PMC7849364 DOI: 10.1101/gad.342378.120] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 12/08/2020] [Indexed: 12/16/2022]
Abstract
The physiological functions of many vital tissues and organs continue to mature after birth, but the genetic mechanisms governing this postnatal maturation remain an unsolved mystery. Human pancreatic β cells produce and secrete insulin in response to physiological cues like glucose, and these hallmark functions improve in the years after birth. This coincides with expression of the transcription factors SIX2 and SIX3, whose functions in native human β cells remain unknown. Here, we show that shRNA-mediated SIX2 or SIX3 suppression in human pancreatic adult islets impairs insulin secretion. However, transcriptome studies revealed that SIX2 and SIX3 regulate distinct targets. Loss of SIX2 markedly impaired expression of genes governing β-cell insulin processing and output, glucose sensing, and electrophysiology, while SIX3 loss led to inappropriate expression of genes normally expressed in fetal β cells, adult α cells, and other non-β cells. Chromatin accessibility studies identified genes directly regulated by SIX2. Moreover, β cells from diabetic humans with impaired insulin secretion also had reduced SIX2 transcript levels. Revealing how SIX2 and SIX3 govern functional maturation and maintain developmental fate in native human β cells should advance β-cell replacement and other therapeutic strategies for diabetes.
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Affiliation(s)
- Romina J Bevacqua
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Jonathan Y Lam
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Heshan Peiris
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Robert L Whitener
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Seokho Kim
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Xueying Gu
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Mollie S H Friedlander
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Seung K Kim
- Department of Developmental Biology, Stanford University School of Medicine, Stanford, California 94305, USA
- Department of Medicine (Endocrinology), Stanford University School of Medicine, Stanford, California 94305, USA
- Stanford Diabetes Research Center, Stanford University School of Medicine, Stanford, California 94305, USA
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9
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Shahvazian E, Mahmoudi MB, Farashahi Yazd E, Gharibi S, Moghimi B, HosseinNia P, Mirzaei M. The KLF14 Variant is Associated with Type 2 Diabetes and HbA 1C Level. Biochem Genet 2021; 59:574-588. [PMID: 33389382 DOI: 10.1007/s10528-020-10015-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Accepted: 10/30/2020] [Indexed: 12/20/2022]
Abstract
The purpose of this study was to scan variants in coding region of Krȕppel like factor14 (KLF14) locus and assess association related to type 2 diabetes (T2D) in Iranian population. We sequenced the coding region of KLF14 to scan variants in case-sibling study (92 individuals with T2D and 92 healthy older siblings). To confirm, we analyzed rs76603546 association with T2D in a larger unrelated case-control study by PCR-RFLP (475 cases and 512 controls). We analyzed the association of rs76603546 with HbA1C, BMI, fat mass, waist circumference, fasting glucose, cholesterol and HOMA-IR (Homeostatic Model Assessment for Insulin Resistance) using one-way ANOVA analysis. Also, association of genotypes with T2D adjusted for confounding variables was analyzed using logistic regression. HaploReg v 4.1 was used to predict rs76603546 possible function. Sequencing results analysis revealed the association of C allele of rs76603546, synonymous variant C>T, [OR 2.10 (1.38-3.20), P value < 0.001] and CC genotype of rs76603546 [OR 4.3 (1.79-10.23), P value = 0.001] with susceptibility to T2D. PCR-Restriction Fragment Length Polymorphism (RFLP) results analysis confirmed the association of rs76603546 with T2D [C allele, OR 1.91 (1.59-2.29), P value = 0.002, CC genotype, OR 3.27 (2.26-4.73), P value = 0.002 and TC genotype, OR 1.74 (1.31-2.31), P value = 0.001]. The CC genotype of rs76603546 is associated with HbA1C level (P value < 0.001) and BMI (P value = 0.02). After adjustment with confounding variables, we observed association of CC genotype with T2D [OR 2.542 (1.25-3.77), P value = 0.03]. Among over 220 SNPs, rs76603546 was associated with T2D, HbA1C and BMI in our study.
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Affiliation(s)
- Ensieh Shahvazian
- Department of Genetics, Faculty of Medicine, International Campus, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
| | - Mohammad Bagher Mahmoudi
- Department of Genetics, Faculty of Medicine, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
| | - Ehsan Farashahi Yazd
- Department of Genetics, Faculty of Medicine, Shahid Sadoughi University of Medical Sciences, Yazd, Iran. .,Stem Cell Biology Research Center, Yazd Reproductive Sciences Institute, Shahid Sadoughi University of Medical Sciences, Yazd, Iran. .,Yazd Reproductive Sciences Institute, Bu-Ali Ave., Timsar Fallahi St., Safaeieh, Yazd, Iran.
| | - Saba Gharibi
- Department of Genetics, Faculty of Medicine, International Campus, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
| | - Bahram Moghimi
- Department of Genetics, Faculty of Medicine, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
| | | | - Masoud Mirzaei
- Yazd Cardiovascular Research Centre, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
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10
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A genome-wide association study for highly sensitive cardiac troponin T levels identified a novel genetic variation near a RBAK-ZNF890P locus in the Japanese general population. Int J Cardiol 2020; 329:186-191. [PMID: 33321125 DOI: 10.1016/j.ijcard.2020.12.019] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 12/01/2020] [Accepted: 12/03/2020] [Indexed: 11/23/2022]
Abstract
BACKGROUND Cardiovascular disease (CVD) is a major cause of mortality worldwide. High-sensitivity cardiac troponin T (hs-cTnT) is released into the bloodstream due to cardiomyocyte damage and is associated with a high CVD risk. This study aimed to investigate hs-cTnT-related genetic variation and to examine whether this is an associated risk factor for CVD in the Japanese general population. METHODS This was a genome-wide association study (GWAS) based on a cohort from the 2013 Tohoku Medical Megabank Project community study. The GWAS was performed using a HumanOmniExpressExome BeadChip array with 914,035 autosomal single-nucleotide polymorphisms. The Framingham Risk Score and the Suita score were used to evaluate the future risk of CVD. RESULTS The GWAS identified 10 loci reaching suggestive significance in the discovery cohort. A replication analysis confirmed that one of the 10 loci, rs7798496, is associated with elevated hs-cTnT levels. The combined P value in the discovery and replication cohorts for the association between the rs7798496 and hs-cTnT levels was 3.4 × 10-8, which indicates that the novel variant reached genome-wide significance. The rs7798496 loci was located at an intergenic region between the retinoblastoma gene product (RB)-associated Krüppell-associated box (KRAB) zinc finger, zinc finger protein 890, and pseudogene (ZNF890P). Logistic regression analysis revealed that the presence of the rs7798496 T allele was strongly associated with a high risk for CVD. CONCLUSIONS This study provides insights into a link between a novel genetic variant, T allele of rs7798269, and elevated hs-cTnT levels as a future risk for CVD in the general Japanese population.
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11
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Furukawa K, Igarashi M, Jia H, Nogawa S, Kawafune K, Hachiya T, Takahashi S, Saito K, Kato H. A Genome-Wide Association Study Identifies the Association between the 12q24 Locus and Black Tea Consumption in Japanese Populations. Nutrients 2020; 12:nu12103182. [PMID: 33080986 PMCID: PMC7603176 DOI: 10.3390/nu12103182] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 10/09/2020] [Accepted: 10/10/2020] [Indexed: 11/16/2022] Open
Abstract
Several genome-wide association studies (GWASs) have reported the association between genetic variants and the habitual consumption of foods and drinks; however, no association data are available regarding the consumption of black tea. The present study aimed to identify genetic variants associated with black tea consumption in 12,258 Japanese participants. Data on black tea consumption were collected by a self-administered questionnaire, and genotype data were obtained from a single nucleotide polymorphism array. In the discovery GWAS, two loci met suggestive significance (p < 1.0 × 10-6). Three genetic variants (rs2074356, rs144504271, and rs12231737) at 12q24 locus were also significantly associated with black tea consumption in the replication stage (p < 0.05) and during the meta-analysis (p < 5.0 × 10-8). The association of rs2074356 with black tea consumption was slightly attenuated by the additional adjustment for alcohol drinking frequency. In conclusion, genetic variants at the 12q24 locus were associated with black tea consumption in Japanese populations, and the association is at least partly mediated by alcohol drinking frequency.
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Affiliation(s)
- Kyohei Furukawa
- Health Nutrition, Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan; (K.F.); (M.I.); (K.S.)
| | - Maki Igarashi
- Health Nutrition, Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan; (K.F.); (M.I.); (K.S.)
- Department of Molecular Endocrinology, National Research Institute for Child Health and Development, 2-10-1 Okura, Setagaya-ku, Tokyo 157-8535, Japan
| | - Huijuan Jia
- Health Nutrition, Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan; (K.F.); (M.I.); (K.S.)
- Correspondence: (H.J.); (H.K.); Tel./Fax: +81-3-5841-5116 (H.J.); +81-3-5841-1607 (H.K.)
| | - Shun Nogawa
- Research and Development Department, Genequest Inc., 5-29-11 Siba, Minato-ku, Tokyo 108-0014, Japan; (S.N.); (K.K.); (T.H.); (S.T.)
| | - Kaoru Kawafune
- Research and Development Department, Genequest Inc., 5-29-11 Siba, Minato-ku, Tokyo 108-0014, Japan; (S.N.); (K.K.); (T.H.); (S.T.)
| | - Tsuyoshi Hachiya
- Research and Development Department, Genequest Inc., 5-29-11 Siba, Minato-ku, Tokyo 108-0014, Japan; (S.N.); (K.K.); (T.H.); (S.T.)
- Department of Genomic Data Analysis Service, Genome Analytics Japan Inc., 15-1-3205 Toyoshima-cho, Shinjuku-ku, Tokyo 162-0067, Japan
| | - Shoko Takahashi
- Research and Development Department, Genequest Inc., 5-29-11 Siba, Minato-ku, Tokyo 108-0014, Japan; (S.N.); (K.K.); (T.H.); (S.T.)
| | - Kenji Saito
- Health Nutrition, Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan; (K.F.); (M.I.); (K.S.)
- Research and Development Department, Genequest Inc., 5-29-11 Siba, Minato-ku, Tokyo 108-0014, Japan; (S.N.); (K.K.); (T.H.); (S.T.)
| | - Hisanori Kato
- Health Nutrition, Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan; (K.F.); (M.I.); (K.S.)
- Correspondence: (H.J.); (H.K.); Tel./Fax: +81-3-5841-5116 (H.J.); +81-3-5841-1607 (H.K.)
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12
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Sutoh Y, Hachiya T, Suzuki Y, Komaki S, Ohmomo H, Kakisaka K, Wang T, Takikawa Y, Shimizu A. ALDH2 genotype modulates the association between alcohol consumption and AST/ALT ratio among middle-aged Japanese men: a genome-wide G × E interaction analysis. Sci Rep 2020; 10:16227. [PMID: 33004991 PMCID: PMC7530747 DOI: 10.1038/s41598-020-73263-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Accepted: 09/11/2020] [Indexed: 12/19/2022] Open
Abstract
Liver tests (LT), especially to measure AST, ALT and GGT levels, are widely used to evaluate the risk of alcohol-related liver disease (ALD). In this study, we investigated the potential genetic factors that modulate the association between LTs and alcohol consumption. We conducted a genome-wide interaction meta-analysis in 7856 Japanese subjects from Tohoku Medical Megabank Community-Based Cohort (TMM CommCohort) study recruited in 2013, and identified 2 loci (12q24 and 2p16) with genome-wide significance (P > 5 × 10-8). The significant variants in the 12q24 included rs671, a variant associated with alcohol intolerance and located at a coding exon of ALDH2. We found that the amount of alcohol consumption was associated with increased level AST/ALT ratio among the subjects with the rs671 GA genotype. The elevated AST/ALT ratio among subjects with moderate-to-high levels of drinking behavior and the rs671 GA genotype was due to decreased levels of ALT, which was not accompanied with significant differences in AST levels. Although the interaction effect was significant in both men and women, the effect was much larger in men. Our results suggest that the impact of alcohol consumption on LT varies according to the ALDH2 genotype, providing an insight for the accurate screening of ALD in drinkers with the rs671 GA genotype.
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Affiliation(s)
- Yoichi Sutoh
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, 1-1-1 Idaidori, Yahaba, Iwate, 028-3694, Japan
| | - Tsuyoshi Hachiya
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, 1-1-1 Idaidori, Yahaba, Iwate, 028-3694, Japan
| | - Yuji Suzuki
- Division of Hepatology, Department of Internal Medicine, Iwate Medical University, Yahaba, Japan
| | - Shohei Komaki
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, 1-1-1 Idaidori, Yahaba, Iwate, 028-3694, Japan
| | - Hideki Ohmomo
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, 1-1-1 Idaidori, Yahaba, Iwate, 028-3694, Japan
| | - Keisuke Kakisaka
- Division of Hepatology, Department of Internal Medicine, Iwate Medical University, Yahaba, Japan
| | - Ting Wang
- Division of Biomedical Research and Development, Institute of Biomedical Sciences, Iwate Medical University, Morioka, Iwate, Japan
| | - Yasuhiro Takikawa
- Division of Hepatology, Department of Internal Medicine, Iwate Medical University, Yahaba, Japan
| | - Atsushi Shimizu
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, 1-1-1 Idaidori, Yahaba, Iwate, 028-3694, Japan.
- Division of Biomedical Information Analysis, Institute for Biomedical Sciences, Iwate Medical University, 1-1-1 Idaidori, Yahaba, Iwate, 028-3694, Japan.
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13
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Machine learning for effectively avoiding overfitting is a crucial strategy for the genetic prediction of polygenic psychiatric phenotypes. Transl Psychiatry 2020; 10:294. [PMID: 32826857 PMCID: PMC7442807 DOI: 10.1038/s41398-020-00957-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Revised: 06/24/2020] [Accepted: 07/22/2020] [Indexed: 11/08/2022] Open
Abstract
The accuracy of previous genetic studies in predicting polygenic psychiatric phenotypes has been limited mainly due to the limited power in distinguishing truly susceptible variants from null variants and the resulting overfitting. A novel prediction algorithm, Smooth-Threshold Multivariate Genetic Prediction (STMGP), was applied to improve the genome-based prediction of psychiatric phenotypes by decreasing overfitting through selecting variants and building a penalized regression model. Prediction models were trained using a cohort of 3685 subjects in Miyagi prefecture and validated with an independently recruited cohort of 3048 subjects in Iwate prefecture in Japan. Genotyping was performed using HumanOmniExpressExome BeadChip Arrays. We used the target phenotype of depressive symptoms and simulated phenotypes with varying complexity and various effect-size distributions of risk alleles. The prediction accuracy and the degree of overfitting of STMGP were compared with those of state-of-the-art models (polygenic risk scores, genomic best linear-unbiased prediction, summary-data-based best linear-unbiased prediction, BayesR, and ridge regression). In the prediction of depressive symptoms, compared with the other models, STMGP showed the highest prediction accuracy with the lowest degree of overfitting, although there was no significant difference in prediction accuracy. Simulation studies suggested that STMGP has a better prediction accuracy for moderately polygenic phenotypes. Our investigations suggest the potential usefulness of STMGP for predicting polygenic psychiatric conditions while avoiding overfitting.
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14
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Okuda H, Okamoto K, Abe M, Ishizawa K, Makino S, Tanabe O, Sugawara J, Hozawa A, Tanno K, Sasaki M, Tamiya G, Yamamoto M, Ito S, Ishii T. Genome-wide association study identifies new loci for albuminuria in the Japanese population. Clin Exp Nephrol 2020; 24:1-9. [PMID: 32277301 PMCID: PMC7994224 DOI: 10.1007/s10157-020-01884-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2019] [Accepted: 03/25/2020] [Indexed: 12/25/2022]
Abstract
BACKGROUND Urinary albumin excretion (UAE) is a risk factor for cardiovascular diseases, metabolic syndrome, chronic kidney disease, etc. Only a few genome-wide association studies (GWAS) for UAE have been conducted in the European population, but not in the Asian population. Here we conducted GWAS and identified several candidate genes harboring single nucleotide polymorphisms (SNPs) responsible for UAE in the Japanese population. METHODS We conducted GWAS for UAE in 7805 individuals of Asian ancestry from health-survey data collected by Tohoku Medical Megabank Organization (ToMMo) and Iwate Tohoku Medical Megabank Organization (IMM). The SNP genotype data were obtained with a SNP microarray. After imputation using a haplotype panel consisting of 2000 genome sequencing, 4,962,728 SNP markers were used for the GWAS. RESULTS Eighteen SNPs at 14 loci (GRM7, EXOC1/NMU, LPA, STEAP1B/RAPGEF5, SEMA3D, PRKAG2, TRIQK, SERTM1, TPT1-AS1, OR5AU1, TSHR, FMN1/RYR3, COPRS, and BRD1) were associated with UAE in the Japanese individuals. A locus with particularly strong associations was observed on TSHR, chromosome 14 [rs116622332 (p = 3.99 × 10-10)]. CONCLUSION In this study, we successfully identified UAE-associated variant loci in the Japanese population. Further study is required to confirm this association.
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Affiliation(s)
- Hiroshi Okuda
- Department of Education and Support for Regional Medicine, Tohoku University Hospital, 1-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8574, Japan.,Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8573, Japan.,Department of Nephrology, Endocrinology and Vascular Medicine, Graduate School of Medicine, Tohoku University, 1-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8574, Japan
| | - Koji Okamoto
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8573, Japan. .,Department of Nephrology, Endocrinology and Vascular Medicine, Graduate School of Medicine, Tohoku University, 1-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8574, Japan.
| | - Michiaki Abe
- Department of Education and Support for Regional Medicine, Tohoku University Hospital, 1-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8574, Japan.,Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8573, Japan.,Department of Nephrology, Endocrinology and Vascular Medicine, Graduate School of Medicine, Tohoku University, 1-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8574, Japan
| | - Kota Ishizawa
- Department of Education and Support for Regional Medicine, Tohoku University Hospital, 1-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8574, Japan.,Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8573, Japan
| | - Satoshi Makino
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8573, Japan
| | - Osamu Tanabe
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8573, Japan.,Radiation Effects Research Foundation, 5-2 Hijiyama Park, Minami-ku, Hiroshima, Hiroshima, 732-0815, Japan
| | - Junichi Sugawara
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8573, Japan
| | - Atsushi Hozawa
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8573, Japan
| | - Kozo Tanno
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, 1-1-1 Idaidori, Yahaba-cho, Shiwa-gun, Iwate, 028-3694, Japan
| | - Makoto Sasaki
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, 1-1-1 Idaidori, Yahaba-cho, Shiwa-gun, Iwate, 028-3694, Japan
| | - Gen Tamiya
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8573, Japan.,RIKEN Center for Advanced Intelligence Project Nihonbashi, 1-chome Mitsui Bldg. 15F, 1-4-1 Nihonbashi, Chuo-ku, Tokyo, 103-0027, Japan
| | - Masayuki Yamamoto
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8573, Japan
| | - Sadayoshi Ito
- Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8573, Japan.,Department of Nephrology, Endocrinology and Vascular Medicine, Graduate School of Medicine, Tohoku University, 1-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8574, Japan
| | - Tadashi Ishii
- Department of Education and Support for Regional Medicine, Tohoku University Hospital, 1-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8574, Japan.,Tohoku Medical Megabank Organization, Tohoku University, 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi, 980-8573, Japan
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15
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Kawafune K, Hachiya T, Nogawa S, Takahashi S, Jia H, Saito K, Kato H. Strong association between the 12q24 locus and sweet taste preference in the Japanese population revealed by genome-wide meta-analysis. J Hum Genet 2020; 65:939-947. [PMID: 32572145 DOI: 10.1038/s10038-020-0787-x] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Revised: 05/07/2020] [Accepted: 05/07/2020] [Indexed: 11/09/2022]
Abstract
The sweet taste preference of humans is an important adaptation to ensure the acquisition of carbohydrate nutrition; however, overconsumption of sweet foods can potentially lead to diseases such as obesity and diabetes. Although previous studies have suggested that interindividual variation of human sweet taste preference is heritable, genetic loci associated with the trait have yet to be fully elucidated. Here, we genotyped 12,312 Japanese participants using the HumanCore-12+ Custom BeadChip or the HumanCore-24 Custom BeadChip microarrays. The sweet taste preference of the participants was surveyed via an internet-based questionnaire, resulting in a five-point scale of sweet taste preference. The genome-wide meta-analysis of the Japanese participants revealed a strong association between the 12q24 locus and sweet taste preference scale (P = 2.8 × 10-70). The lead variant rs671 is monoallelic in non-East Asian populations and is located in the aldehyde dehydrogenase (ALDH2) gene, encoding an enzyme involved in alcohol metabolism. The association between the minor allele of rs671 and sweet taste preference was attenuated by adjusting for alcohol drinking. The subgroup analysis showed that the effect of rs671 on sweet taste preference was greater in males than in females. In conclusion, we found an association between the 12q24 locus and sweet taste preference in the Japanese population, and showed that the adjustment for drinking habits attenuated the association. This novel genetic association may provide new clues to elucidate mechanisms determining sweet taste preferences.
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Affiliation(s)
- Kaoru Kawafune
- Genequest Inc., Siba 5-29-11, Minato-ku, Tokyo, 108-0014, Japan
| | - Tsuyoshi Hachiya
- Genequest Inc., Siba 5-29-11, Minato-ku, Tokyo, 108-0014, Japan.,Genome Analytics Japan Inc., 15-1-3205 Tomihisa-cho, Shinjuku-ku, Tokyo, 162-0067, Japan
| | - Shun Nogawa
- Genequest Inc., Siba 5-29-11, Minato-ku, Tokyo, 108-0014, Japan
| | - Shoko Takahashi
- Genequest Inc., Siba 5-29-11, Minato-ku, Tokyo, 108-0014, Japan
| | - Huijuan Jia
- Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo, 113-8657, Japan
| | - Kenji Saito
- Genequest Inc., Siba 5-29-11, Minato-ku, Tokyo, 108-0014, Japan.,Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo, 113-8657, Japan
| | - Hisanori Kato
- Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo, 113-8657, Japan.
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16
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Hachiya T, Hata J, Hirakawa Y, Yoshida D, Furuta Y, Kitazono T, Shimizu A, Ninomiya T. Genome-Wide Polygenic Score and the Risk of Ischemic Stroke in a Prospective Cohort. Stroke 2020; 51:759-765. [DOI: 10.1161/strokeaha.119.027520] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Background and Purpose—
Environmental and genetic factors contribute to the development of ischemic stroke (IS). We recently developed a genome-wide polygenic risk score (PRS) for IS using case-control datasets from 4 large-scale observational studies conducted in Japan. Our objective in the present study was to confirm the association between the PRS and the risk of IS with data from an independent prospective cohort recruited from the general Japanese population.
Methods—
A total of 3038 subjects aged ≥40 years were followed up for 10 years (2002–2012). The genome-wide PRS was calculated using genotype data from >350 000 single-nucleotide polymorphisms. The PRS levels were divided into quintiles. High and low genetic risk groups were defined as top 60% and bottom 40% of PRS, respectively. The hazard ratio (HR) for the development of IS was estimated using a Cox proportional hazards model.
Results—
During the follow-up period, 91 cases developed first-ever IS. The age- and sex-adjusted HR for IS increased with higher PRS levels (
P
for trend, 0.03). Subjects with the highest quintile level of PRS had a 2.44-fold (95% CI, 1.16–5.12) greater risk for IS than those with the lowest quintile level after adjusting for age and sex. A similar association was observed after adjusting for environmental risk factors (
P
for trend, 0.03). As compared with low genetic risk group, the age- and sex-adjusted HR in high genetic risk group was 1.63 (95% CI, 1.04–2.55), which was comparable to the HR of hypertension (HR, 1.41), diabetes mellitus (HR, 1.72), and smoking (HR, 1.54). The age- and sex-adjusted HR increased with the number of environmental risk factors in both high and low genetic risk groups without significant interaction.
Conclusions—
A high genome-wide PRS was a significant risk factor for IS independent of environmental risk factors in a general Japanese population. This finding suggests that PRS may be useful to identify individuals at a high risk of IS.
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Affiliation(s)
- Tsuyoshi Hachiya
- From the Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Japan (T.H., A.S.)
| | - Jun Hata
- Department of Epidemiology and Public Health (J.H., D.Y., Y.F., T.N.), Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Yoichiro Hirakawa
- Department of Medicine and Clinical Science (Y.H., T.K.), Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Daigo Yoshida
- Department of Epidemiology and Public Health (J.H., D.Y., Y.F., T.N.), Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Yoshihiko Furuta
- Department of Epidemiology and Public Health (J.H., D.Y., Y.F., T.N.), Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Takanari Kitazono
- Department of Medicine and Clinical Science (Y.H., T.K.), Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Atsushi Shimizu
- From the Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Japan (T.H., A.S.)
| | - Toshiharu Ninomiya
- Department of Epidemiology and Public Health (J.H., D.Y., Y.F., T.N.), Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
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17
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Hozawa A, Tanno K, Nakaya N, Nakamura T, Tsuchiya N, Hirata T, Narita A, Kogure M, Nochioka K, Sasaki R, Takanashi N, Otsuka K, Sakata K, Kuriyama S, Kikuya M, Tanabe O, Sugawara J, Suzuki K, Suzuki Y, Kodama EN, Fuse N, Kiyomoto H, Tomita H, Uruno A, Hamanaka Y, Metoki H, Ishikuro M, Obara T, Kobayashi T, Kitatani K, Takai-Igarashi T, Ogishima S, Satoh M, Ohmomo H, Tsuboi A, Egawa S, Ishii T, Ito K, Ito S, Taki Y, Minegishi N, Ishii N, Nagasaki M, Igarashi K, Koshiba S, Shimizu R, Tamiya G, Nakayama K, Motohashi H, Yasuda J, Shimizu A, Hachiya T, Shiwa Y, Tominaga T, Tanaka H, Oyama K, Tanaka R, Kawame H, Fukushima A, Ishigaki Y, Tokutomi T, Osumi N, Kobayashi T, Nagami F, Hashizume H, Arai T, Kawaguchi Y, Higuchi S, Sakaida M, Endo R, Nishizuka S, Tsuji I, Hitomi J, Nakamura M, Ogasawara K, Yaegashi N, Kinoshita K, Kure S, Sakai A, Kobayashi S, Sobue K, Sasaki M, Yamamoto M. Study Profile of the Tohoku Medical Megabank Community-Based Cohort Study. J Epidemiol 2020; 31:65-76. [PMID: 31932529 PMCID: PMC7738642 DOI: 10.2188/jea.je20190271] [Citation(s) in RCA: 69] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
Background We established a community-based cohort study to assess the long-term impact of the Great East Japan Earthquake on disaster victims and gene-environment interactions on the incidence of major diseases, such as cancer and cardiovascular diseases. Methods We asked participants to join our cohort in the health check-up settings and assessment center based settings. Inclusion criteria were aged 20 years or over and living in Miyagi or Iwate Prefecture. We obtained information on lifestyle, effect of disaster, blood, and urine information (Type 1 survey), and some detailed measurements (Type 2 survey), such as carotid echography and calcaneal ultrasound bone mineral density. All participants agreed to measure genome information and to distribute their information widely. Results As a result, 87,865 gave their informed consent to join our study. Participation rate at health check-up site was about 70%. The participants in the Type 1 survey were more likely to have psychological distress than those in the Type 2 survey, and women were more likely to have psychological distress than men. Additionally, coastal residents were more likely to have higher degrees of psychological distress than inland residents, regardless of sex. Conclusion This cohort comprised a large sample size and it contains information on the natural disaster, genome information, and metabolome information. This cohort also had several detailed measurements. Using this cohort enabled us to clarify the long-term effect of the disaster and also to establish personalized prevention based on genome, metabolome, and other omics information.
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Affiliation(s)
- Atsushi Hozawa
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University
| | - Kozo Tanno
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University.,School of Medicine, Iwate Medical University
| | - Naoki Nakaya
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University.,Saitama Prefectural University
| | - Tomohiro Nakamura
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University
| | - Naho Tsuchiya
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University
| | - Takumi Hirata
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University
| | - Akira Narita
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University
| | - Mana Kogure
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University
| | - Kotaro Nochioka
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University.,Tohoku University Hospital, Tohoku University
| | - Ryohei Sasaki
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University.,School of Medicine, Iwate Medical University
| | - Nobuyuki Takanashi
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University
| | - Kotaro Otsuka
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University.,School of Medicine, Iwate Medical University
| | - Kiyomi Sakata
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University.,School of Medicine, Iwate Medical University
| | - Shinichi Kuriyama
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University.,International Research Institute of Disaster Science, Tohoku University
| | - Masahiro Kikuya
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University.,Teikyo University School of Medicine
| | - Osamu Tanabe
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University.,Radiation Effects Research Foundation
| | - Junichi Sugawara
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University.,Tohoku University Hospital, Tohoku University
| | - Kichiya Suzuki
- Tohoku Medical Megabank Organization, Tohoku University.,Tohoku University Hospital, Tohoku University
| | - Yoichi Suzuki
- Tohoku Medical Megabank Organization, Tohoku University.,Ageo Central General Hospital
| | - Eiichi N Kodama
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University.,Tohoku University Hospital, Tohoku University.,International Research Institute of Disaster Science, Tohoku University
| | - Nobuo Fuse
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University
| | - Hideyasu Kiyomoto
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University
| | - Hiroaki Tomita
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University.,Tohoku University Hospital, Tohoku University.,International Research Institute of Disaster Science, Tohoku University
| | - Akira Uruno
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University
| | - Yohei Hamanaka
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University
| | - Hirohito Metoki
- Tohoku Medical Megabank Organization, Tohoku University.,Faculty of Medicine, Tohoku Medical and Pharmaceutical University
| | - Mami Ishikuro
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University
| | - Taku Obara
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University.,Tohoku University Hospital, Tohoku University
| | - Tomoko Kobayashi
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University
| | - Kazuyuki Kitatani
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University.,Setsunan University
| | - Takako Takai-Igarashi
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University
| | - Soichi Ogishima
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University
| | - Mamoru Satoh
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University.,Institute for Biomedical Sciences, Iwate Medical University
| | - Hideki Ohmomo
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University
| | - Akito Tsuboi
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Dentistry, Tohoku University
| | - Shinichi Egawa
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University.,International Research Institute of Disaster Science, Tohoku University
| | - Tadashi Ishii
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University.,Tohoku University Hospital, Tohoku University
| | - Kiyoshi Ito
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University.,International Research Institute of Disaster Science, Tohoku University
| | - Sadayoshi Ito
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University.,Tohoku University Hospital, Tohoku University
| | - Yasuyuki Taki
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University.,Institute of Development, Aging and Cancer, Tohoku University
| | - Naoko Minegishi
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University
| | - Naoto Ishii
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University
| | - Masao Nagasaki
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University.,Graduate School of Information Sciences, Tohoku University.,Kyoto University Graduate School of Medicine Faculty of Medicine
| | - Kazuhiko Igarashi
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University
| | - Seizo Koshiba
- Tohoku Medical Megabank Organization, Tohoku University
| | - Ritsuko Shimizu
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University
| | - Gen Tamiya
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University.,Center for Advanced Intelligence Project, RIKEN
| | - Keiko Nakayama
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University
| | - Hozumi Motohashi
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University.,Institute of Development, Aging and Cancer, Tohoku University
| | - Jun Yasuda
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University.,Miyagi Cancer Center
| | - Atsushi Shimizu
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University
| | - Tsuyoshi Hachiya
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University
| | - Yuh Shiwa
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University
| | - Teiji Tominaga
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University.,Tohoku University Hospital, Tohoku University
| | - Hiroshi Tanaka
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University.,Tokyo Medical and Dental University
| | - Kotaro Oyama
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University.,School of Medicine, Iwate Medical University
| | - Ryoichi Tanaka
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University.,School of Medicine, Iwate Medical University
| | - Hiroshi Kawame
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University.,The JIKEI University School of Medicine
| | - Akimune Fukushima
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University.,School of Medicine, Iwate Medical University
| | - Yasushi Ishigaki
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University.,School of Medicine, Iwate Medical University
| | - Tomoharu Tokutomi
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University.,School of Medicine, Iwate Medical University
| | - Noriko Osumi
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University
| | | | - Fuji Nagami
- Tohoku Medical Megabank Organization, Tohoku University
| | | | - Tomohiko Arai
- Tohoku Medical Megabank Organization, Tohoku University
| | | | | | | | - Ryujin Endo
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University.,Iwate Medical University School of Nursing
| | - Satoshi Nishizuka
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University.,Institute for Biomedical Sciences, Iwate Medical University
| | - Ichiro Tsuji
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University
| | - Jiro Hitomi
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University.,School of Medicine, Iwate Medical University
| | | | - Kuniaki Ogasawara
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University.,School of Medicine, Iwate Medical University
| | - Nobuo Yaegashi
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University.,Tohoku University Hospital, Tohoku University
| | - Kengo Kinoshita
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Information Sciences, Tohoku University
| | - Shigeo Kure
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University.,Tohoku University Hospital, Tohoku University
| | | | | | | | - Makoto Sasaki
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University.,Institute for Biomedical Sciences, Iwate Medical University
| | - Masayuki Yamamoto
- Tohoku Medical Megabank Organization, Tohoku University.,Graduate School of Medicine, Tohoku University
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18
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Nishida Y, Hachiya T, Hara M, Shimanoe C, Tanaka K, Sutoh Y, Shimizu A, Hishida A, Tsukamoto M, Kadomatsu Y, Oze I, Koyanagi YN, Kuriyama N, Koyama T, Ibusuki R, Takezaki T, Ikezaki H, Furusyo N, Takashima N, Kadota A, Uemura H, Katsuura-Kamano S, Suzuki S, Nakagawa-Senda H, Kuriki K, Mikami H, Nakamura Y, Momozawa Y, Kubo M, Nakatochi M, Naito M, Wakai K. The interaction between ABCA1 polymorphism and physical activity on the HDL-cholesterol levels in a Japanese population. J Lipid Res 2020; 61:86-94. [PMID: 31694877 PMCID: PMC6939595 DOI: 10.1194/jlr.p091546] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Revised: 10/21/2019] [Indexed: 12/15/2022] Open
Abstract
Few studies have investigated the interactions between HDL-C-related SNPs identified by genome-wide association (GWA) study and physical activity (PA) on HDL-C. First, we conducted a sex-stratified GWA study in a discovery sample (2,231 men and 2,431 women) and replication sample (2,599 men and 3,109 women) to identify SNPs influencing log-transformed HDL-C in Japanese participants in the baseline survey of the Japan Multi-Institutional Collaborative Cohort Study. We also replicated previously reported HDL-C-related SNPs in a combined (discovery plus replication) sample (4,830 men and 5,540 women). We then analyzed the interactions of the HDL-C-related SNPs with PA on HDL-C. The sex-stratified GWA analyses identified 11 and 10 HDL-C-related SNPs in men and women as targets for an interaction analysis. Among these, only one interaction of ABCA1 rs1883025 with PA was statistically significant in men, after Bonferroni correction [P-interaction = 0.001 (α = 0.05/21 = 0.002)]. The per-major-allele (C allele) increase in log-transformed HDL-C was lost in men with low PA (β = 0.008) compared with those with medium (β = 0.032) or high PA (β = 0.034). These findings suggest that the benefit of carrying a C allele of ABCA1 rs1883025 on enhancing HDL-C may be attenuated in inactive men.
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Affiliation(s)
- Yuichiro Nishida
- Department of Preventive Medicine, Faculty of Medicine, Saga University, Saga, Japan.
| | - Tsuyoshi Hachiya
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Iwate, Japan
| | - Megumi Hara
- Department of Preventive Medicine, Faculty of Medicine, Saga University, Saga, Japan
| | | | - Keitaro Tanaka
- Department of Preventive Medicine, Faculty of Medicine, Saga University, Saga, Japan
| | - Yoichi Sutoh
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Iwate, Japan
| | - Atsushi Shimizu
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Iwate, Japan
| | - Asahi Hishida
- Departments of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Mineko Tsukamoto
- Departments of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Yuka Kadomatsu
- Departments of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan; Thoracic Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Isao Oze
- Divisions of Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan
| | - Yuriko N Koyanagi
- Cancer Information and Control, Aichi Cancer Center Research Institute, Nagoya, Japan
| | - Nagato Kuriyama
- Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Teruhide Koyama
- Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Rie Ibusuki
- Department of International Island and Community Medicine, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan
| | - Toshiro Takezaki
- Department of International Island and Community Medicine, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan
| | - Hiroaki Ikezaki
- Department of Environmental Medicine and Infectious Disease, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Norihiro Furusyo
- Department of Environmental Medicine and Infectious Disease, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Naoyuki Takashima
- Department of Health Science, Shiga University of Medical Science, Otsu, Japan; Department of Preventive Medicine, Institute of Biomedical Sciences, Tokushima University Graduate School, Tokushima, Japan
| | - Aya Kadota
- Department of Health Science, Shiga University of Medical Science, Otsu, Japan
| | - Hirokazu Uemura
- Thoracic Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | | | - Sadao Suzuki
- Department of Public Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Hiroko Nakagawa-Senda
- Department of Public Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Kiyonori Kuriki
- Laboratory of Public Health, School of Food and Nutritional Sciences, University of Shizuoka, Shizuoka, Japan
| | - Haruo Mikami
- Cancer Prevention Center, Chiba Cancer Center Research Institute, Chiba, Japan
| | - Yohko Nakamura
- Cancer Prevention Center, Chiba Cancer Center Research Institute, Chiba, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Michiaki Kubo
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Masahiro Nakatochi
- Division of Data Science, Data Coordinating Center, Department of Advanced Medicine, Nagoya University Hospital, Nagoya, Japan
| | - Mariko Naito
- Departments of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan; Department of Oral Epidemiology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Kenji Wakai
- Departments of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
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19
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Moon JY, Louie TL, Jain D, Sofer T, Schurmann C, Below JE, Lai CQ, Aviles-Santa ML, Talavera GA, Smith CE, Petty LE, Bottinger EP, Chen YDI, Taylor KD, Daviglus ML, Cai J, Wang T, Tucker KL, Ordovás JM, Hanis CL, Loos RJF, Schneiderman N, Rotter JI, Kaplan RC, Qi Q. A Genome-Wide Association Study Identifies Blood Disorder-Related Variants Influencing Hemoglobin A 1c With Implications for Glycemic Status in U.S. Hispanics/Latinos. Diabetes Care 2019; 42:1784-1791. [PMID: 31213470 PMCID: PMC6702612 DOI: 10.2337/dc19-0168] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Accepted: 05/24/2019] [Indexed: 02/03/2023]
Abstract
OBJECTIVE We aimed to identify hemoglobin A1c (HbA1c)-associated genetic variants and examine their implications for glycemic status evaluated by HbA1c in U.S. Hispanics/Latinos with diverse genetic ancestries. RESEARCH DESIGN AND METHODS We conducted a genome-wide association study (GWAS) of HbA1c in 9,636 U.S. Hispanics/Latinos without diabetes from the Hispanic Community Health Study/Study of Latinos, followed by a replication among 4,729 U.S. Hispanics/Latinos from three independent studies. RESULTS Our GWAS and replication analyses showed 10 previously known and novel loci associated with HbA1c at genome-wide significance levels (P < 5.0 × 10-8). In particular, two African ancestry-specific variants, HBB-rs334 and G6PD-rs1050828, which are causal mutations for sickle cell disease and G6PD deficiency, respectively, had ∼10 times larger effect sizes on HbA1c levels (β = -0.31% [-3.4 mmol/mol]) and -0.35% [-3.8 mmol/mol] per minor allele, respectively) compared with other HbA1c-associated variants (0.03-0.04% [0.3-0.4 mmol/mol] per allele). A novel Amerindian ancestry-specific variant, HBM-rs145546625, was associated with HbA1c and hematologic traits but not with fasting glucose. The prevalence of hyperglycemia (prediabetes and diabetes) defined using fasting glucose or oral glucose tolerance test 2-h glucose was similar between carriers of HBB-rs334 or G6PD-rs1050828 HbA1c-lowering alleles and noncarriers, whereas the prevalence of hyperglycemia defined using HbA1c was significantly lower in carriers than in noncarriers (12.2% vs. 28.4%, P < 0.001). After recalibration of the HbA1c level taking HBB-rs334 and G6PD-rs1050828 into account, the prevalence of hyperglycemia in carriers was similar to noncarriers (31.3% vs. 28.4%, P = 0.28). CONCLUSIONS This study in U.S. Hispanics/Latinos found several ancestry-specific alleles associated with HbA1c through erythrocyte-related rather than glycemic-related pathways. The potential influences of these nonglycemic-related variants need to be considered when the HbA1c test is performed.
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Affiliation(s)
- Jee-Young Moon
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY
| | - Tin L Louie
- Department of Biostatistics, University of Washington, Seattle, WA
| | - Deepti Jain
- Department of Biostatistics, University of Washington, Seattle, WA
| | - Tamar Sofer
- Department of Biostatistics, University of Washington, Seattle, WA
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA
| | - Claudia Schurmann
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Jennifer E Below
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX
| | - Chao-Qiang Lai
- Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA
| | | | - Gregory A Talavera
- Graduate School of Public Health, San Diego State University, San Diego, CA
| | - Caren E Smith
- Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA
| | - Lauren E Petty
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX
| | - Erwin P Bottinger
- Department of Preventive Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, Harbor-UCLA Medical Center, Torrance, CA
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Harbor-UCLA Medical Center, Torrance, CA
| | - Martha L Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL
| | - Jianwen Cai
- Department of Biostatistics and Collaborative Studies Coordinating Center, University of North Carolina, Chapel Hill, NC
| | - Tao Wang
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY
| | - Katherine L Tucker
- Department of Biomedical and Nutritional Sciences, University of Massachusetts Lowell, Lowell, MA
| | - José M Ordovás
- Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA
- IMDEA Food Institute, Campus de Excelencia Internacional Universidad Autónoma de Madrid-Consejo Superior de Investigaciones Científicas, Madrid, Spain
| | - Craig L Hanis
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | | | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Harbor-UCLA Medical Center, Torrance, CA
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY
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20
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Jia H, Nogawa S, Kawafune K, Hachiya T, Takahashi S, Igarashi M, Saito K, Kato H. GWAS of habitual coffee consumption reveals a sex difference in the genetic effect of the 12q24 locus in the Japanese population. BMC Genet 2019; 20:61. [PMID: 31345160 PMCID: PMC6659273 DOI: 10.1186/s12863-019-0763-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2018] [Accepted: 07/08/2019] [Indexed: 01/04/2023] Open
Abstract
Background Studies on genetic effects of coffee consumption are scarce for Asian populations. We conducted a genome-wide association study (GWAS) of habitual coffee consumption in Japan using a self-reporting online survey. Results Candidate genetic loci associated with habitual coffee consumption were searched within a discovery cohort (N = 6,264) and confirmed in a replication cohort (N = 5,975). Two loci achieved genome-wide significance (P < 5 × 10− 8) in a meta-analysis of the discovery and replication cohorts: an Asian population-specific 12q24 (rs79105258; P = 9.5 × 10− 15), which harbors CUX2, and 7p21 (rs10252701; P = 1.0 × 10− 14), in the upstream region of the aryl hydrocarbon receptor (AHR) gene, involved in caffeine metabolism. Subgroup analysis revealed a stronger genetic effect of the 12q24 locus in males (P for interaction = 8.2 × 10− 5). Further, rs79105258 at the 12q24 locus exerted pleiotropic effects on body mass index (P = 3.5 × 10− 4) and serum triglyceride levels (P = 8.7 × 10− 3). Conclusions Our results consolidate the association of habitual coffee consumption with the 12q24 and 7p21 loci. The different effects of the 12q24 locus between males and females are a novel finding that improves our understanding of genetic influences on habitual coffee consumption. Electronic supplementary material The online version of this article (10.1186/s12863-019-0763-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Huijuan Jia
- Health Nutrition, Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-8657, Japan.
| | - Shun Nogawa
- Genequest Inc., 5-29-11 Siba, Minato-ku, Tokyo, 108-0014, Japan
| | - Kaoru Kawafune
- Genequest Inc., 5-29-11 Siba, Minato-ku, Tokyo, 108-0014, Japan
| | - Tsuyoshi Hachiya
- Genequest Inc., 5-29-11 Siba, Minato-ku, Tokyo, 108-0014, Japan.,Genome Analytics Japan Inc., 15-1-3205, Tomihisa-cho, Shinjuku-ku, Tokyo, 162-0067, Japan
| | - Shoko Takahashi
- Genequest Inc., 5-29-11 Siba, Minato-ku, Tokyo, 108-0014, Japan
| | - Maki Igarashi
- Health Nutrition, Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-8657, Japan.,Department of Molecular Endocrinology, National Research Institute for Child Health and Development, 2-10-1 Okura, Setagaya-ku, Tokyo, 157-8535, Japan
| | - Kenji Saito
- Health Nutrition, Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-8657, Japan.,Genequest Inc., 5-29-11 Siba, Minato-ku, Tokyo, 108-0014, Japan
| | - Hisanori Kato
- Health Nutrition, Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo, 113-8657, Japan.
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21
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Igarashi M, Nogawa S, Kawafune K, Hachiya T, Takahashi S, Jia H, Saito K, Kato H. Identification of the 12q24 locus associated with fish intake frequency by genome-wide meta-analysis in Japanese populations. GENES AND NUTRITION 2019; 14:21. [PMID: 31320941 PMCID: PMC6612078 DOI: 10.1186/s12263-019-0646-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Accepted: 06/26/2019] [Indexed: 01/09/2023]
Abstract
Background Japan is traditionally a country with one of the highest levels of fish consumption worldwide, although the westernization of the Japanese diet has resulted in the reduction of fish consumption. A recent meta-analysis of genome-wide association studies (GWASs) on Western populations has identified a single nucleotide polymorphism (SNP) associated with fish intake frequency. Here, we examined the genetic basis for fish intake frequency among Japanese individuals. Results We conducted a meta-analysis of a GWAS including 12,603 Japanese individuals and identified a susceptibility locus for fish intake frequency at 12q24 (lead variant was rs11066015, P = 5.4 × 10-11). rs11066015 was in a strong linkage disequilibrium with rs671, a well-known SNP related to alcohol metabolism. When adjusted for alcohol drinking, the association between rs11066015 and fish intake frequency was substantially attenuated. Subgroup analysis revealed that the effect of the 12q24 variant on fish intake frequency was stronger in males than in females (P for interaction = 0.007) and stronger in the older subgroup than in the younger subgroup (P for interaction = 0.006). Conclusions Our findings suggest that the 12q24 locus is associated with fish intake frequency via alcohol drinking. This study can help contribute to personalized nutrition information, suggesting that fish intake should be promoted to consumers who have the rs11066015 minor allele, which is genetically linked to low fish intake frequency, especially in male and older individuals.
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Affiliation(s)
- Maki Igarashi
- 1Laboratory of Health Nutrition, Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo, 113-8657 Japan.,2Department of Molecular Endocrinology, National Research Institute for Child Health and Development, 2-10-1 Okura, Setagaya-ku, Tokyo, 157-8535 Japan
| | - Shun Nogawa
- Genequest Inc, 5-29-11 Siba, Minato-ku, Tokyo, 108-0014 Japan
| | - Kaoru Kawafune
- Genequest Inc, 5-29-11 Siba, Minato-ku, Tokyo, 108-0014 Japan
| | - Tsuyoshi Hachiya
- Genequest Inc, 5-29-11 Siba, Minato-ku, Tokyo, 108-0014 Japan.,Genome Analytics Japan Inc, 15-1-3205, Tomihisa-cho, Shinjuku-ku, Tokyo, 162-0067 Japan
| | - Shoko Takahashi
- Genequest Inc, 5-29-11 Siba, Minato-ku, Tokyo, 108-0014 Japan
| | - Huijuan Jia
- 1Laboratory of Health Nutrition, Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo, 113-8657 Japan
| | - Kenji Saito
- 1Laboratory of Health Nutrition, Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo, 113-8657 Japan.,Genequest Inc, 5-29-11 Siba, Minato-ku, Tokyo, 108-0014 Japan
| | - Hisanori Kato
- 1Laboratory of Health Nutrition, Department of Applied Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo, 113-8657 Japan
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22
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Hara M, Hachiya T, Sutoh Y, Matsuo K, Nishida Y, Shimanoe C, Tanaka K, Shimizu A, Ohnaka K, Kawaguchi T, Oze I, Matsuda F, Ito H, Kawai S, Hishida A, Okada R, Sasakabe T, Hirata A, Ibusuki R, Nindita Y, Furusyo N, Ikezaki H, Kuriyama N, Ozaki E, Mikami H, Nakamura Y, Suzuki S, Hosono A, Katsuura-Kamano S, Arisawa K, Kuriki K, Endoh K, Takashima N, Kadota A, Nakatochi M, Momozawa Y, Kubo M, Naito M, Wakai K. Genomewide Association Study of Leisure-Time Exercise Behavior in Japanese Adults. Med Sci Sports Exerc 2019; 50:2433-2441. [PMID: 30102679 PMCID: PMC6282671 DOI: 10.1249/mss.0000000000001712] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Supplemental digital content is available in the text. Purpose Although several genetic factors may play a role in leisure-time exercise behavior, there is currently no evidence of a significant genomewide association, and candidate gene replication studies have produced inconsistent results. Methods We conducted a two-stage genomewide association study and candidate single-nucleotide polymorphisms (SNP) association study on leisure-time exercise behavior using 13,980 discovery samples from the Japan Multi-Institutional Collaborative Cohort (J-MICC) study, and 2036 replication samples from the Hospital-based Epidemiologic Research Program at Aichi Cancer Center-2 study. Leisure-time physical activity was measured using a self-administered questionnaire that inquired about the type, frequency and duration of exercise. Participants with ≥4 MET·h·wk−1 of leisure-time physical activity were defined as exhibiting leisure-time exercise behavior. Association testing using mixed linear regression models was performed on the discovery and replication samples, after which the results were combined in a meta-analysis. In addition, we tested six candidate genetic variants derived from previous genomewide association study. Results We found that one novel SNP (rs10252228) located in the intergenic region between NPSR1 and DPY19L1 was significantly associated with leisure-time exercise behavior in discovery samples. This association was also significant in replication samples (combined P value by meta-analysis = 2.2 × 10−9). Several SNP linked with rs10252228 were significantly associated with gene expression of DPY19L1 and DP19L2P1 in skeletal muscle, heart, whole blood, and the nervous system. Among the candidate SNP, rs12612420 in DNAPTP6 demonstrated nominal significance in discovery samples but not in replication samples. Conclusions We identified a novel genetic variant associated with regular leisure-time exercise behavior. Further functional studies are required to validate the role of these variants in exercise behavior.
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Affiliation(s)
- Megumi Hara
- Department of Preventive Medicine, Faculty of Medicine, Saga University, Saga, JAPAN
| | - Tsuyoshi Hachiya
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Iwate, JAPAN
| | - Yoichi Sutoh
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Iwate, JAPAN
| | - Keitaro Matsuo
- Division of Molecular and Clinical Epidemiology, Aichi Cancer Center Research Institute, Nagoya, JAPAN.,Department of Epidemiology, Nagoya University Graduate School of Medicine, Nagoya, JAPAN
| | - Yuichiro Nishida
- Department of Preventive Medicine, Faculty of Medicine, Saga University, Saga, JAPAN
| | - Chisato Shimanoe
- Department of Preventive Medicine, Faculty of Medicine, Saga University, Saga, JAPAN
| | - Keitaro Tanaka
- Department of Preventive Medicine, Faculty of Medicine, Saga University, Saga, JAPAN
| | - Atsushi Shimizu
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Iwate, JAPAN
| | - Keizo Ohnaka
- Department of Geriatric Medicine, Graduate School of Medical Sciences, Kyushu University, Fukuoka, JAPAN
| | - Takahisa Kawaguchi
- Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, JAPAN
| | - Isao Oze
- Division of Molecular and Clinical Epidemiology, Aichi Cancer Center Research Institute, Nagoya, JAPAN
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, JAPAN
| | - Hidemi Ito
- Division of Molecular and Clinical Epidemiology, Aichi Cancer Center Research Institute, Nagoya, JAPAN.,Department of Epidemiology, Nagoya University Graduate School of Medicine, Nagoya, JAPAN.,Division of Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, JAPAN
| | - Sayo Kawai
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, JAPAN.,Department of Public Health, Aichi Medical University, School of Medicine, Aichi, JAPAN
| | - Asahi Hishida
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, JAPAN
| | - Rieko Okada
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, JAPAN
| | - Tae Sasakabe
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, JAPAN.,Department of Public Health, Aichi Medical University, School of Medicine, Aichi, JAPAN
| | - Akie Hirata
- Division of Molecular and Clinical Epidemiology, Aichi Cancer Center Research Institute, Nagoya, JAPAN
| | - Rie Ibusuki
- Department of International Island and Community Medicine Kagoshima University, Graduate School of Medical and Dental Sciences, Kagoshima, JAPAN
| | - Yora Nindita
- Department of International Island and Community Medicine Kagoshima University, Graduate School of Medical and Dental Sciences, Kagoshima, JAPAN.,Department of Pharmacology and Therapeutic, Faculty of Medicine, Diponegoro University, Semarang, INDONESIA
| | - Norihiro Furusyo
- Department of General Internal Medicine, Kyushu University Hospital, Fukuoka, JAPAN
| | - Hiroaki Ikezaki
- Department of General Internal Medicine, Kyushu University Hospital, Fukuoka, JAPAN
| | - Nagato Kuriyama
- Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine Graduate School of Medical Science, Kyoto, JAPAN
| | - Etsuko Ozaki
- Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine Graduate School of Medical Science, Kyoto, JAPAN
| | - Haruo Mikami
- Cancer Prevention Center, Chiba Cancer Center Research Institute, Chiba, JAPAN
| | - Yohko Nakamura
- Cancer Prevention Center, Chiba Cancer Center Research Institute, Chiba, JAPAN
| | - Sadao Suzuki
- Department of Public Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, JAPAN
| | - Akihiro Hosono
- Department of Public Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, JAPAN
| | - Sakurako Katsuura-Kamano
- Department of Preventive Medicine, Institute of Biomedical Sciences, Tokushima University Graduate School, Tsukuba, JAPAN
| | - Kokichi Arisawa
- Department of Preventive Medicine, Institute of Biomedical Sciences, Tokushima University Graduate School, Tsukuba, JAPAN
| | - Kiyonori Kuriki
- Laboratory of Public Health, School of Food and Nutritional Sciences, University of Shizuoka, Shizuoka, JAPAN
| | - Kaori Endoh
- Laboratory of Public Health, School of Food and Nutritional Sciences, University of Shizuoka, Shizuoka, JAPAN
| | - Naoyuki Takashima
- Department of Public Health, Shiga University of Medical Science, Shiga, JAPAN
| | - Aya Kadota
- Department of Public Health, Shiga University of Medical Science, Shiga, JAPAN.,Center for Epidemiologic Research in Asia, Shiga University of Medical Science, Shiga, JAPAN
| | - Masahiro Nakatochi
- Statistical Analysis Section, Center for Advanced Medicine and Clinical Research, Nagoya University Hospital, Nagoya, JAPAN
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, Riken Center for Integrative Medical Sciences, Yokohama, JAPAN
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama, JAPAN
| | - Mariko Naito
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, JAPAN.,Department of Oral Epidemiology, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, JAPAN
| | - Kenji Wakai
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, JAPAN
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23
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Jia X, Hou Y, Xu M, Zhao Z, Xuan L, Wang T, Li M, Xu Y, Lu J, Bi Y, Wang W, Chen Y. Mendelian Randomization Analysis Support Causal Associations of HbA1c with Circulating Triglyceride, Total and Low-density Lipoprotein Cholesterol in a Chinese Population. Sci Rep 2019; 9:5525. [PMID: 30940890 PMCID: PMC6445078 DOI: 10.1038/s41598-019-41076-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2018] [Accepted: 02/25/2019] [Indexed: 01/06/2023] Open
Abstract
Previous observational studies supported a positive association of glycated hemoglobin A1c (HbA1c) level with serum triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C). However, the causal relationship between HbA1c and either one of them was unclear in the East Asians. We performed a Mendelian Randomization (MR) analysis in a community-based study sample in Shanghai, China (n = 11,935). To clarify the cause-and-effect relationships of HbA1c with the four interested lipids, an Expanded HbA1c genetic risk score (GRS) with 17 HbA1c-related common variants and a Conservative score by excluding 11 variants were built and adopted as the Instrumental Variables (IVs), respectively. The Expanded HbA1c-GRS was associated with 0.19 unit increment in log-TG (P = 0.009), 0.42 mmol/L TC (P = 0.01), and 0.33 mmol/L LDL-C (P = 0.01); while the Conservative HbA1c-GRS was associated with 0.22 unit in log-TG (P = 0.03), 0.60 mmol/L TC (P = 0.01), and 0.51 mmol/L LDL-C (P = 0.007). No causal relationship was detected for HDL-C. Sensitivity analysis supported the above findings. In conclusions, MR analysis supports a causal role of increased HbA1c level in increment of circulating TG, TC, and LDL-C in a Chinese population.
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Affiliation(s)
- Xu Jia
- State Key Laboratory of Medical Genomics, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai National Clinical Research Center for Metabolic Diseases, and Collaborative Innovation Center of Systems Biomedicine, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.,Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Rui-Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yanan Hou
- State Key Laboratory of Medical Genomics, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai National Clinical Research Center for Metabolic Diseases, and Collaborative Innovation Center of Systems Biomedicine, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.,Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Rui-Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Min Xu
- State Key Laboratory of Medical Genomics, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai National Clinical Research Center for Metabolic Diseases, and Collaborative Innovation Center of Systems Biomedicine, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.,Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Rui-Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Zhiyun Zhao
- State Key Laboratory of Medical Genomics, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai National Clinical Research Center for Metabolic Diseases, and Collaborative Innovation Center of Systems Biomedicine, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.,Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Rui-Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Liping Xuan
- State Key Laboratory of Medical Genomics, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai National Clinical Research Center for Metabolic Diseases, and Collaborative Innovation Center of Systems Biomedicine, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.,Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Rui-Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Tiange Wang
- State Key Laboratory of Medical Genomics, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai National Clinical Research Center for Metabolic Diseases, and Collaborative Innovation Center of Systems Biomedicine, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.,Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Rui-Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Mian Li
- State Key Laboratory of Medical Genomics, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai National Clinical Research Center for Metabolic Diseases, and Collaborative Innovation Center of Systems Biomedicine, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.,Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Rui-Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yu Xu
- State Key Laboratory of Medical Genomics, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai National Clinical Research Center for Metabolic Diseases, and Collaborative Innovation Center of Systems Biomedicine, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.,Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Rui-Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Jieli Lu
- State Key Laboratory of Medical Genomics, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai National Clinical Research Center for Metabolic Diseases, and Collaborative Innovation Center of Systems Biomedicine, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.,Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Rui-Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yufang Bi
- State Key Laboratory of Medical Genomics, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai National Clinical Research Center for Metabolic Diseases, and Collaborative Innovation Center of Systems Biomedicine, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.,Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Rui-Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Weiqing Wang
- State Key Laboratory of Medical Genomics, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai National Clinical Research Center for Metabolic Diseases, and Collaborative Innovation Center of Systems Biomedicine, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China.,Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Rui-Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yuhong Chen
- State Key Laboratory of Medical Genomics, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Shanghai National Clinical Research Center for Metabolic Diseases, and Collaborative Innovation Center of Systems Biomedicine, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, Shanghai, 200025, China. .,Shanghai Institute of Endocrine and Metabolic Diseases, Department of Endocrine and Metabolic Diseases, Rui-Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
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24
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Hachiya T, Narita A, Ohmomo H, Sutoh Y, Komaki S, Tanno K, Satoh M, Sakata K, Hitomi J, Nakamura M, Ogasawara K, Yamamoto M, Sasaki M, Hozawa A, Shimizu A. Genome-wide analysis of polymorphism × sodium interaction effect on blood pressure identifies a novel 3'-BCL11B gene desert locus. Sci Rep 2018; 8:14162. [PMID: 30242241 PMCID: PMC6155053 DOI: 10.1038/s41598-018-32074-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2018] [Accepted: 08/24/2018] [Indexed: 12/19/2022] Open
Abstract
Excessive sodium intake is a global risk factor for hypertension. Sodium effects on blood pressure vary from person to person; hence, high-risk group targeting based on personal genetic information can play a complementary role to ongoing population preventive approaches to reduce sodium consumption. To identify genetic factors that modulate sodium effects on blood pressure, we conducted a population-based genome-wide interaction analysis in 8,768 Japanese subjects, which was >3 times larger than a similar previous study. We tested 7,135,436 polymorphisms in the discovery cohort, and loci that met suggestive significance were further examined in an independent replication cohort. We found that an interaction between a novel 3'-BCL11B gene desert locus and daily sodium consumption was significantly associated with systolic blood pressure in both discovery and replication cohorts under the recessive model. Further statistical analysis of rs8022678, the sentinel variant of the 3'-BCL11B gene desert locus, showed that differences in mean systolic blood pressure between high and low sodium consumption subgroups were 5.9 mm Hg (P = 8.8 × 10-12) in rs8022678 A carriers and -0.3 mm Hg (P = 0.27) in rs8022678 A non-carriers, suggesting that the rs8022678 genotype can classify persons into sodium-sensitive (A carriers) and sodium-insensitive (A non-carriers) subgroups. Our results implied that rs8022678 A carriers may receive a greater benefit from sodium-lowering interventions than non-carriers.
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Affiliation(s)
- Tsuyoshi Hachiya
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Shiwa, Japan
| | - Akira Narita
- Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Hideki Ohmomo
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Shiwa, Japan
| | - Yoichi Sutoh
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Shiwa, Japan
| | - Shohei Komaki
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Shiwa, Japan
| | - Kozo Tanno
- Division of Clinical Research and Epidemiology, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Shiwa, Japan
- Department of Hygiene and Preventive Medicine, School of Medicine, Iwate Medical University, Morioka, Japan
| | - Mamoru Satoh
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Shiwa, Japan
- Division of Biomedical Information Analysis, Institute for Biomedical Sciences, Iwate Medical University, Shiwa, Japan
| | - Kiyomi Sakata
- Division of Clinical Research and Epidemiology, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Shiwa, Japan
- Department of Hygiene and Preventive Medicine, School of Medicine, Iwate Medical University, Morioka, Japan
| | - Jiro Hitomi
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Shiwa, Japan
- Department of Anatomy, School of Medicine, Iwate Medical University, Shiwa, Japan
| | - Motoyuki Nakamura
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Shiwa, Japan
- Department of Internal Medicine, School of Medicine, Iwate Medical University, Morioka, Japan
| | - Kuniaki Ogasawara
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Shiwa, Japan
- Department of Neurosurgery, School of Medicine, Iwate Medical University, Morioka, Japan
| | - Masayuki Yamamoto
- Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, 980-8573, Japan
| | - Makoto Sasaki
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Shiwa, Japan
- Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Shiwa, Japan
| | - Atsushi Hozawa
- Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
| | - Atsushi Shimizu
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University, Shiwa, Japan.
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Barbitoff YA, Serebryakova EA, Nasykhova YA, Predeus AV, Polev DE, Shuvalova AR, Vasiliev EV, Urazov SP, Sarana AM, Scherbak SG, Gladyshev DV, Pokrovskaya MS, Sivakova OV, Meshkov AN, Drapkina OM, Glotov OS, Glotov AS. Identification of Novel Candidate Markers of Type 2 Diabetes and Obesity in Russia by Exome Sequencing with a Limited Sample Size. Genes (Basel) 2018; 9:genes9080415. [PMID: 30126146 PMCID: PMC6115942 DOI: 10.3390/genes9080415] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2018] [Revised: 08/11/2018] [Accepted: 08/13/2018] [Indexed: 12/22/2022] Open
Abstract
Type 2 diabetes (T2D) and obesity are common chronic disorders with multifactorial etiology. In our study, we performed an exome sequencing analysis of 110 patients of Russian ethnicity together with a multi-perspective approach based on biologically meaningful filtering criteria to detect novel candidate variants and loci for T2D and obesity. We have identified several known single nucleotide polymorphisms (SNPs) as markers for obesity (rs11960429), T2D (rs9379084, rs1126930), and body mass index (BMI) (rs11553746, rs1956549 and rs7195386) (p < 0.05). We show that a method based on scoring of case-specific variants together with selection of protein-altering variants can allow for the interrogation of novel and known candidate markers of T2D and obesity in small samples. Using this method, we identified rs328 in LPL (p = 0.023), rs11863726 in HBQ1 (p = 8 × 10−5), rs112984085 in VAV3 (p = 4.8 × 10−4) for T2D and obesity, rs6271 in DBH (p = 0.043), rs62618693 in QSER1 (p = 0.021), rs61758785 in RAD51B (p = 1.7 × 10−4), rs34042554 in PCDHA1 (p = 1 × 10−4), and rs144183813 in PLEKHA5 (p = 1.7 × 10−4) for obesity; and rs9379084 in RREB1 (p = 0.042), rs2233984 in C6orf15 (p = 0.030), rs61737764 in ITGB6 (p = 0.035), rs17801742 in COL2A1 (p = 8.5 × 10−5), and rs685523 in ADAMTS13 (p = 1 × 10−6) for T2D as important susceptibility loci in Russian population. Our results demonstrate the effectiveness of whole exome sequencing (WES) technologies for searching for novel markers of multifactorial diseases in cohorts of limited size in poorly studied populations.
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Affiliation(s)
- Yury A Barbitoff
- Biobank of the Research Park, Saint Petersburg State University, 199034 Saint Petersburg, Russia.
- Bioinformatics Institute, 194100 Saint Petersburg, Russia.
- Department of Genetics and Biotechnology, Saint Petersburg State University, 199034 Saint Petersburg, Russia.
- Institute of Translation Biomedicine, Saint Petersburg State University, 199034 Saint Petersburg, Russia.
| | - Elena A Serebryakova
- Biobank of the Research Park, Saint Petersburg State University, 199034 Saint Petersburg, Russia.
- Laboratory of Prenatal Diagnostics of Hereditary Diseases, FSBSI «The Research Institute of Obstetrics, Gynaecology and Reproductology Named after D.O. Ott», 199034 Saint Petersburg, Russia.
- City Hospital No. 40, Sestroretsk, 197706 Saint Petersburg, Russia.
| | - Yulia A Nasykhova
- Biobank of the Research Park, Saint Petersburg State University, 199034 Saint Petersburg, Russia.
- Laboratory of Prenatal Diagnostics of Hereditary Diseases, FSBSI «The Research Institute of Obstetrics, Gynaecology and Reproductology Named after D.O. Ott», 199034 Saint Petersburg, Russia.
| | | | - Dmitrii E Polev
- Biobank of the Research Park, Saint Petersburg State University, 199034 Saint Petersburg, Russia.
| | - Anna R Shuvalova
- Biobank of the Research Park, Saint Petersburg State University, 199034 Saint Petersburg, Russia.
| | | | | | - Andrey M Sarana
- Institute of Translation Biomedicine, Saint Petersburg State University, 199034 Saint Petersburg, Russia.
- City Hospital No. 40, Sestroretsk, 197706 Saint Petersburg, Russia.
| | - Sergey G Scherbak
- Institute of Translation Biomedicine, Saint Petersburg State University, 199034 Saint Petersburg, Russia.
- City Hospital No. 40, Sestroretsk, 197706 Saint Petersburg, Russia.
| | | | - Maria S Pokrovskaya
- Federal State Institution «National Medical Research Center for Preventive Medicine» of the Ministry of Healthcare of the Russian Federation, 101990 Moscow, Russia.
| | - Oksana V Sivakova
- Federal State Institution «National Medical Research Center for Preventive Medicine» of the Ministry of Healthcare of the Russian Federation, 101990 Moscow, Russia.
| | - Aleksey N Meshkov
- Federal State Institution «National Medical Research Center for Preventive Medicine» of the Ministry of Healthcare of the Russian Federation, 101990 Moscow, Russia.
| | - Oxana M Drapkina
- Federal State Institution «National Medical Research Center for Preventive Medicine» of the Ministry of Healthcare of the Russian Federation, 101990 Moscow, Russia.
| | - Oleg S Glotov
- Laboratory of Prenatal Diagnostics of Hereditary Diseases, FSBSI «The Research Institute of Obstetrics, Gynaecology and Reproductology Named after D.O. Ott», 199034 Saint Petersburg, Russia.
- City Hospital No. 40, Sestroretsk, 197706 Saint Petersburg, Russia.
| | - Andrey S Glotov
- Biobank of the Research Park, Saint Petersburg State University, 199034 Saint Petersburg, Russia.
- Laboratory of Prenatal Diagnostics of Hereditary Diseases, FSBSI «The Research Institute of Obstetrics, Gynaecology and Reproductology Named after D.O. Ott», 199034 Saint Petersburg, Russia.
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