1
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Thorpe HHA, Fontanillas P, Pham BK, Meredith JJ, Jennings MV, Courchesne-Krak NS, Vilar-Ribó L, Bianchi SB, Mutz J, Elson SL, Khokhar JY, Abdellaoui A, Davis LK, Palmer AA, Sanchez-Roige S. Genome-wide association studies of coffee intake in UK/US participants of European ancestry uncover cohort-specific genetic associations. Neuropsychopharmacology 2024; 49:1609-1618. [PMID: 38858598 PMCID: PMC11319477 DOI: 10.1038/s41386-024-01870-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Revised: 04/03/2024] [Accepted: 04/17/2024] [Indexed: 06/12/2024]
Abstract
Coffee is one of the most widely consumed beverages. We performed a genome-wide association study (GWAS) of coffee intake in US-based 23andMe participants (N = 130,153) and identified 7 significant loci, with many replicating in three multi-ancestral cohorts. We examined genetic correlations and performed a phenome-wide association study across hundreds of biomarkers, health, and lifestyle traits, then compared our results to the largest available GWAS of coffee intake from the UK Biobank (UKB; N = 334,659). We observed consistent positive genetic correlations with substance use and obesity in both cohorts. Other genetic correlations were discrepant, including positive genetic correlations between coffee intake and psychiatric illnesses, pain, and gastrointestinal traits in 23andMe that were absent or negative in the UKB, and genetic correlations with cognition that were negative in 23andMe but positive in the UKB. Phenome-wide association study using polygenic scores of coffee intake derived from 23andMe or UKB summary statistics also revealed consistent associations with increased odds of obesity- and red blood cell-related traits, but all other associations were cohort-specific. Our study shows that the genetics of coffee intake associate with substance use and obesity across cohorts, but also that GWAS performed in different populations could capture cultural differences in the relationship between behavior and genetics.
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Affiliation(s)
- Hayley H A Thorpe
- Department of Anatomy and Cell Biology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- Department of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
| | | | - Benjamin K Pham
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - John J Meredith
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Mariela V Jennings
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | | | - Laura Vilar-Ribó
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Sevim B Bianchi
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Julian Mutz
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | | | - Jibran Y Khokhar
- Department of Anatomy and Cell Biology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- Department of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
| | - Abdel Abdellaoui
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Lea K Davis
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA.
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA.
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Murakami K, Ishihara J, Takachi R, Sugawara S, Aizawa M, Takahashi I, Obara T, Ishikuro M, Noda A, Ogino M, Hoshina Y, Kito K, Nakadate M, Maruya S, Matsuno T, Yonezawa Y, Yamashita T, Suzuki S, Yamamoto M, Kuriyama S. Validity and reproducibility of food group intakes in a self-administered food frequency questionnaire for genomic and omics research: the Tohoku Medical Megabank Project. J Epidemiol 2024:JE20240064. [PMID: 39098038 DOI: 10.2188/jea.je20240064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/06/2024] Open
Abstract
BACKGROUND The Tohoku Medical Megabank Project (TMM) was established to realize personalized healthcare and medicine using genomic and omics data. This study evaluated the validity and reproducibility of food group intakes derived from a self-administered food frequency questionnaire (TMM-FFQ) that included the response option "constitutionally unable to eat/drink it" among community-dwelling Japanese adults. METHODS Participants comprised 89 men and 124 women aged ≥20 years from Miyagi Prefecture. Participants completed weighed food records (WFRs) for 3 consecutive days per season as reference intake and FFQs in 2019 (FFQ1) and 2021 (FFQ3). Spearman's rank correlation coefficients (CCs) were calculated for correlations between food group intakes estimated from the 12-day WFR and FFQ3 (validity), and for correlations between those estimated from the FFQ1 and FFQ3 (reproducibility). Cross-classification according to quintiles using FFQ and WFR data was also performed. RESULTS The percentage of participants who chose the "constitutionally unable to eat/drink it" option was non-negligible for some food groups. In the validity analysis, CCs were >0.40 for many food groups; the median across 21 food groups was 0.49 in men and 0.45 in women. The median percentages of cross-classification into exact plus adjacent quintiles were 73.0% in men and 66.9% in women. In the reproducibility analysis, CCs were >0.50 for many food groups; the median across 21 food groups was 0.60 in men and 0.51 in women. CONCLUSIONS The validity of the TMM-FFQ compared with 12-day WFR and the reproducibility of the TMM-FFQ were reasonable for food groups in the TMM cohort studies.
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Affiliation(s)
| | - Junko Ishihara
- Graduate School of Environmental Health, Azabu University
| | - Ribeka Takachi
- Department of Food Science and Nutrition, Nara Women's University Graduate School of Humanities and Sciences
| | - Shiori Sugawara
- Department of Health and Nutrition, Sendai Shirayuri Women's College
| | | | | | - Taku Obara
- Tohoku Medical Megabank Organization, Tohoku University
- Graduate School of Medicine, Tohoku University
- Tohoku University Hospital
| | - Mami Ishikuro
- Tohoku Medical Megabank Organization, Tohoku University
- Graduate School of Medicine, Tohoku University
| | - Aoi Noda
- Tohoku Medical Megabank Organization, Tohoku University
- Graduate School of Medicine, Tohoku University
- Tohoku University Hospital
| | - Mako Ogino
- Department of Food Science and Nutrition, Nara Women's University Graduate School of Humanities and Sciences
| | | | - Kumiko Kito
- Graduate School of Environmental Health, Azabu University
| | | | - Sachiko Maruya
- Department of Food Science and Nutrition, Nara Women's University Graduate School of Humanities and Sciences
| | - Tomoka Matsuno
- Department of Food Science and Nutrition, Nara Women's University Graduate School of Humanities and Sciences
| | - Yudai Yonezawa
- Graduate School of Medicine, Tohoku University
- Innovation Division, KAGOME CO., LTD
| | | | | | | | - Shinichi Kuriyama
- Tohoku Medical Megabank Organization, Tohoku University
- Graduate School of Medicine, Tohoku University
- International Research Institute of Disaster Science, Tohoku University
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3
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Xiao R, Dong L, Xie B, Liu B. A diet-wide Mendelian randomization analysis: causal effects of dietary habits on type 2 diabetes. Front Nutr 2024; 11:1414678. [PMID: 39119465 PMCID: PMC11306177 DOI: 10.3389/fnut.2024.1414678] [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: 05/04/2024] [Accepted: 07/09/2024] [Indexed: 08/10/2024] Open
Abstract
Background Traditional clinical studies have indicated a link between certain food intakes and type 2 diabetes (T2D), but the causal relationships between different dietary habits and T2D remain unknown. Using Mendelian randomization (MR) approaches, we investigated the potential causal association between dietary habits and T2D risk. Methods We collected publicly available genome-wide association studies' summary statistics for 18 dietary habits from the UK Biobank and T2D data from the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) consortium. We applied the inverse variance weighted (IVW) method, supplemented with the MR-Egger method, weighted median method (WMM), simple method, weighted mode, MR-Egger regression, and the MR pleiotropy residual sum and outlier test to determine whether a particular diet was causal for T2D. Results Reliable and robust MR estimates demonstrated that poultry intake has a causal effect on a higher risk of T2D (IVW: OR 6.30, 95% CI 3.573-11.11, p = 2.02e - 10; WMM: OR 5.479, 95% CI 0.2758-10.88, p = 1.19e - 06). Conversely, dried fruit intake (IVW: OR 0.380, 95% CI 0.237-0.608, p = 5.57e - 05; WMM: OR 0.450, 95% CI 0.321-0.630, p = 3.33e - 06) and cereal intake (IVW: OR 0.455, 95% CI 0.317-0.653, p = 1.924e - 05; WMM: OR 0.513, 95% CI 0.379-0.694, p = 1.514e - 05) were causally associated with T2D as protective factors. Sensitivity analyses confirmed the reliability and robustness of these findings. Discussion Our study established the causal effects of poultry intake, dried fruit intake, and cereal intake on T2D, identifying poultry intake as a risk factor and the other two as protective factors. Further research into potential mechanisms is required to validate these novel findings.
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Affiliation(s)
- Rui Xiao
- Department of General Practice, Yongchuan Hospital of Chongqing Medical University, Chongqing Medical University, Chongqing, China
| | - Li Dong
- Department of Nephrology and Rheumatology, Yongchuan Hospital of Chongqing Medical University, Chongqing Medical University, Chongqing, China
| | - Bo Xie
- Department of General Practice, Yongchuan Hospital of Chongqing Medical University, Chongqing Medical University, Chongqing, China
| | - Beizhong Liu
- Central Laboratory of Yongchuan Hospital, Chongqing Medical University, Chongqing, China
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4
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Liang Q, Peng Z. Evaluating the effect of green tea intake on cardiovascular diseases: A Mendelian randomization study in European and East Asian populations. Medicine (Baltimore) 2024; 103:e38977. [PMID: 39029022 PMCID: PMC11398782 DOI: 10.1097/md.0000000000038977] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 07/21/2024] Open
Abstract
Previous research shows that more than 70% of cardiovascular diseases (CVDs) are attributed to modifiable risk factors. Here, we investigated relationship between consumption of green tea in European and East Asian populations and risk of CVDs using Mendelian randomization (MR). Instrumental variables for green tea intake were obtained from genome-wide association studies (GWASs) of 64,949 Europeans and 152,653 East Asians. GWASs for CVDs were derived from UK BioBank and BioBank Japan projects. The main method selected for MR analysis was either the inverse variance weighted (IVW) or Wald ratio, depending on the quantity of single nucleotide polymorphisms. Furthermore, we performed sensitivity analyses to confirm the reliability of the findings. Based on the results of IVW, there is no causal relationship between consumption of green tea and risk of 4 CVDs among Europeans (atrial fibrillation: OR = 1.000, 95% CI: 0.995-1.005, P = .910; heart failure: OR = 1.003, 95% CI: 0.994-1.012, P = .542; ischemic stroke: OR = 1.002, 95% CI: 0.993-1.011, P = .690; coronary artery disease: OR = 1.001, 95% CI: 0.996-1.007, P = .677). Sensitivity analyses and supplementary MR analyses also verify the robustness of the findings. Likewise, there was no correlation between the consumption of green tea and the occurrence of CVDs in East Asians. The consumption of green tea is not associated with a reduced risk of CVDs in populations from Europe and East Asia. This means that those who are trying to reduce their risk of CVDs by drinking more green tea may not benefit from doing so.
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Affiliation(s)
- Qiaoli Liang
- Doumen Qiaoli Hospital of Traditional Chinese Medicine, Zhuhai, Guangdong, China
| | - Ziming Peng
- Fangchenggang Hospital of Traditional Chinese Medicine, Fangchenggang, Guangxi, China
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5
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Brasher MS, Grotzinger AD, Friedman NP, Smolker HR, Evans LM. Disentangling differing relationships between internalizing disorders and alcohol use. Am J Med Genet B Neuropsychiatr Genet 2024; 195:e32975. [PMID: 38375614 PMCID: PMC11147714 DOI: 10.1002/ajmg.b.32975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 12/14/2023] [Accepted: 02/08/2024] [Indexed: 02/21/2024]
Abstract
Both internalizing disorders and alcohol use have dramatic, wide-spread implications for global health. Previous work has established common phenotypic comorbidity among these disorders, as well as shared genetic variation underlying them both. We used genomic structural equation modeling to investigate the shared genetics of internalizing, externalizing, and alcohol use traits, as well as to explore whether specific domains of internalizing symptoms mediate the contrasting relationships with problematic alcohol use compared to alcohol consumption. We also examined patterns of genetic correlations between similar traits within additional Finnish and East Asian ancestry groups. When the shared genetic influence of externalizing psychopathology was accounted for, the genetic effect of internalizing traits on alcohol use was reduced, suggesting the important role of common genetic factors underlying multiple psychiatric disorders and their genetic influences on comorbidity of internalizing and alcohol use traits. Individual internalizing domains had contrasting effects on frequency of alcohol consumption, which demonstrate the complex system of pleiotropy that exists, even within similar disorders, and can be missed when evaluating only relationships among formal diagnoses. Future work must consider the broad effects of shared psychopathology along with the fine-scale effects of heterogeneity within disorders to more fully understand the biology underlying complex traits.
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Affiliation(s)
- Maizy S Brasher
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
- Department of Ecology and Evolutionary Biology, Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
| | - Andrew D Grotzinger
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
- Department of Psychology and Neuroscience, Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
| | - Naomi P Friedman
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
- Department of Psychology and Neuroscience, Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
| | - Harry R Smolker
- Institute of Cognitive Science, University of Colorado Boulder, Boulder, Colorado, USA
| | - Luke M Evans
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
- Department of Ecology and Evolutionary Biology, Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
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6
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Francis M, Westerman KE, Manning AK, Ye K. Gene-vegetarianism interactions in calcium, estimated glomerular filtration rate, and testosterone identified in genome-wide analysis across 30 biomarkers. PLoS Genet 2024; 20:e1011288. [PMID: 38990837 PMCID: PMC11239071 DOI: 10.1371/journal.pgen.1011288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 05/03/2024] [Indexed: 07/13/2024] Open
Abstract
We examined the associations of vegetarianism with metabolic biomarkers using traditional and genetic epidemiology. First, we addressed inconsistencies in self-reported vegetarianism among UK Biobank participants by utilizing data from two dietary surveys to find a cohort of strict European vegetarians (N = 2,312). Vegetarians were matched 1:4 with nonvegetarians for non-genetic association analyses, revealing significant effects of vegetarianism in 15 of 30 biomarkers. Cholesterol measures plus vitamin D were significantly lower in vegetarians, while triglycerides were higher. A genome-wide association study revealed no genome-wide significant (GWS; 5×10-8) associations with vegetarian behavior. We performed genome-wide gene-vegetarianism interaction analyses for the biomarkers, and detected a GWS interaction impacting calcium at rs72952628 (P = 4.47×10-8). rs72952628 is in MMAA, a B12 metabolic pathway gene; B12 has major deficiency potential in vegetarians. Gene-based interaction tests revealed two significant genes, RNF168 in testosterone (P = 1.45×10-6) and DOCK4 in estimated glomerular filtration rate (eGFR) (P = 6.76×10-7), which have previously been associated with testicular and renal traits, respectively. These nutrigenetic findings indicate genotype can modify the associations between vegetarianism and health outcomes.
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Affiliation(s)
- Michael Francis
- Institute of Bioinformatics, University of Georgia, Athens, Georgia, United States of America
| | - Kenneth E. Westerman
- Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Boston, Massachusetts, United States of America
| | - Alisa K. Manning
- Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Boston, Massachusetts, United States of America
| | - Kaixiong Ye
- Institute of Bioinformatics, University of Georgia, Athens, Georgia, United States of America
- Department of Genetics, University of Georgia, Athens, Georgia, United States of America
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7
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Cooke NP, Murray M, Cassidy LM, Mattiangeli V, Okazaki K, Kasai K, Gakuhari T, Bradley DG, Nakagome S. Genomic imputation of ancient Asian populations contrasts local adaptation in pre- and post-agricultural Japan. iScience 2024; 27:110050. [PMID: 38883821 PMCID: PMC11176660 DOI: 10.1016/j.isci.2024.110050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 03/25/2024] [Accepted: 05/17/2024] [Indexed: 06/18/2024] Open
Abstract
Early modern humans lived as hunter-gatherers for millennia before agriculture, yet the genetic adaptations of these populations remain a mystery. Here, we investigate selection in the ancient hunter-gatherer-fisher Jomon and contrast pre- and post-agricultural adaptation in the Japanese archipelago. Building on the successful validation of imputation with ancient Asian genomes, we identify selection signatures in the Jomon, particularly robust signals from KITLG variants, which may have influenced dark pigmentation evolution. The Jomon lacks well-known adaptive variants (EDAR, ADH1B, and ALDH2), marking their emergence after the advent of farming in the archipelago. Notably, the EDAR and ADH1B variants were prevalent in the archipelago 1,300 years ago, whereas the ALDH2 variant could have emerged later due to its absence in other ancient genomes. Overall, our study underpins local adaptation unique to the Jomon population, which in turn sheds light on post-farming selection that continues to shape contemporary Asian populations.
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Affiliation(s)
- Niall P Cooke
- School of Medicine, Trinity College Dublin, Dublin, Ireland
| | | | - Lara M Cassidy
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Ireland
| | | | - Kenji Okazaki
- Department of Anatomy, Faculty of Medicine, Tottori University, Yonago, Japan
| | - Kenji Kasai
- Toyama Prefectural Center for Archaeological Operations, Toyama, Japan
| | - Takashi Gakuhari
- Institute for the Study of Ancient Civilizations and Cultural Resources, Kanazawa University, Kanazawa, Japan
| | - Daniel G Bradley
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin, Ireland
| | - Shigeki Nakagome
- School of Medicine, Trinity College Dublin, Dublin, Ireland
- Institute for the Study of Ancient Civilizations and Cultural Resources, Kanazawa University, Kanazawa, Japan
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8
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Nie D, He X, Zheng H, Deng D, He F, Li R, Ni X, Li S, Xu F. Association between green tea intake and digestive system cancer risk in European and East Asian populations: a Mendelian randomization study. Eur J Nutr 2024; 63:1103-1111. [PMID: 38319384 DOI: 10.1007/s00394-023-03312-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 12/18/2023] [Indexed: 02/07/2024]
Abstract
PURPOSE Previous observational studies have shown that green tea consumption is associated with a reduced incidence of digestive system cancers (DSCs). However, the observed association could be due to confounding factors. Therefore, we used a two-sample Mendelian randomization (MR) approach to assess the causal effect of green tea intake on the risk of five common DSCs. METHODS Independent genetic variants strongly associated with green tea consumption in European and East Asian populations were selected as instrumental variables in genome-wide association studies involving up to 64,949 European individuals and 152,653 East Asian individuals, respectively. The associations between genetic variants and DSCs were extracted from the FinnGen study and the Japan Biobank. The primary analysis was performed using random-effects inverse variance weighting (IVW). Other MR analyses, including weighted mode-based estimate, weighted-median, MR-Egger regression, Mendelian Randomization-Pleiotropy Residual Sum and Outlier (MR-PRESSO) analysis, were used for sensitivity analyses. In addition, a multivariate MR design was performed to adjust for smoking and alcohol consumption. RESULTS The IVW results showed no causal relationship between tea intake and DSCs risk in European population (esophagus cancer: odds ratio (OR) = 1.044, 95% confidence interval (CI) 0.992-1.099, p = 0.096; stomach cancer: OR = 0.988, 95% CI 0.963-1.014, p = 0.368; colorectal cancer: OR = 1.003, 95% CI 0.992-1.015, p = 0.588; liver cancer: OR = 0.996, 95% CI 0.960-1.032, p = 0.808; pancreatic cancer: OR = 0.990, 95% CI 0.965-1.015, p = 0.432). The MR-Egger regression, MR-PRESSO analysis and other methods also confirmed the reliability of the conclusion. Similarly, no significant association was found between green tea consumption and the incidence of DSCs among East Asians. This relationship is not significant even after adjusting for smoking and alcohol consumption (P > 0.05). CONCLUSION Our study provides evidence that genetically predicted green tea intake is not causally associated with the development of DSCs in the European and East Asian population.
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Affiliation(s)
- Duorui Nie
- College of Pharmacy, Hunan University of Chinese Medicine, Changsha, China
| | - Xiaoyu He
- Department of Hematology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Hao Zheng
- First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Deyu Deng
- College of Pharmacy, Hunan University of Chinese Medicine, Changsha, China
| | - Fanghui He
- College of Pharmacy, Hunan University of Chinese Medicine, Changsha, China
| | - Ruyi Li
- College of Pharmacy, Hunan University of Chinese Medicine, Changsha, China
| | - Xiaoting Ni
- College of Pharmacy, Hunan University of Chinese Medicine, Changsha, China
| | - Shunxiang Li
- College of Pharmacy, Hunan University of Chinese Medicine, Changsha, China.
- Hunan Engineering Technology Research Center for Bioactive Substance Discovery of Chinese Medicine, Changsha, China.
- Hunan Province Sino-US International Joint Research Center for Therapeutic Drugs of Senile Degenerative Diseases, Changsha, China.
| | - Fei Xu
- College of Pharmacy, Hunan University of Chinese Medicine, Changsha, China.
- Hunan Engineering Technology Research Center for Bioactive Substance Discovery of Chinese Medicine, Changsha, China.
- Hunan Province Sino-US International Joint Research Center for Therapeutic Drugs of Senile Degenerative Diseases, Changsha, China.
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Rosário R, Agostinis-Sobrinho C, Padrão P, Lopes O, Moreira P. The relationship between height and fruit/vegetable intakes in adults: A nationwide cross-sectional study. Nutr Health 2024; 30:235-241. [PMID: 35702038 PMCID: PMC11141095 DOI: 10.1177/02601060221108152] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: Worldwide, fruit and vegetable intake is below recommendations. There is increasing evidence to suggest an association between height and diet. Aim: to analyse the associations of fruit and vegetable intake with attained height in Portuguese adults. Methods: A representative sample of 17 480 Portuguese adults (56.7% women) participated in this cross-sectional study. The survey comprised sociodemographic characteristics and self-reported height and weight. We performed regression models to assess the associations between height and fruit and vegetable consumption. Results: Compared with no intakes, those men with higher fruit and vegetables intake had 0.54 cm (95% CI 0.04; 1.04) greater height. Also, women with higher intakes of vegetables, fruit and vegetables combined were directly associated with a greater height of 0.29 cm (95% CI 0.03; 0.56 in vegetables) and 0.51 cm (95% CI 0.09; 0.93 in fruit and vegetables combined). Conclusion: Greater consumption of fruit and vegetables was directly associated with higher height in adults. From a health promotion perspective, intervention programmes aiming at improving fruit and vegetable intake should be highlighted so that full height potential is achieved.
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Affiliation(s)
- Rafaela Rosário
- School of Nursing, University of Minho, Portugal
- Health Sciences Research Unit: Nursing (UICISA: E), Nursing School of Coimbra (ESEnfC), Portugal
- Research Center in Child Studies, University of Minho, Portugal
| | - Cesar Agostinis-Sobrinho
- Research Centre in Physical Activity, Health and Leisure, Faculty of Sport, University of Porto, Portugal
- Faculty of health Sciences - Klaipeda University – Lithuania
- Physical Education, Physiotherapy and Dance, Federal University of the South of Brazil, Porto Alegre, Rio Grande do Sul, Brazil
| | - Patrícia Padrão
- Faculty of Nutrition and Food Sciences, University of Porto, Portugal
- Institute of Public Health, University of Porto, Portugal
| | | | - Pedro Moreira
- Research Centre in Physical Activity, Health and Leisure, Faculty of Sport, University of Porto, Portugal
- Faculty of Nutrition and Food Sciences, University of Porto, Portugal
- Institute of Public Health, University of Porto, Portugal
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10
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Jennings MV, Martínez-Magaña JJ, Courchesne-Krak NS, Cupertino RB, Vilar-Ribó L, Bianchi SB, Hatoum AS, Atkinson EG, Giusti-Rodriguez P, Montalvo-Ortiz JL, Gelernter J, Artigas MS, Elson SL, Edenberg HJ, Fontanillas P, Palmer AA, Sanchez-Roige S. A phenome-wide association and Mendelian randomisation study of alcohol use variants in a diverse cohort comprising over 3 million individuals. EBioMedicine 2024; 103:105086. [PMID: 38580523 PMCID: PMC11121167 DOI: 10.1016/j.ebiom.2024.105086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 03/01/2024] [Accepted: 03/11/2024] [Indexed: 04/07/2024] Open
Abstract
BACKGROUND Alcohol consumption is associated with numerous negative social and health outcomes. These associations may be direct consequences of drinking, or they may reflect common genetic factors that influence both alcohol consumption and other outcomes. METHODS We performed exploratory phenome-wide association studies (PheWAS) of three of the best studied protective single nucleotide polymorphisms (SNPs) in genes encoding ethanol metabolising enzymes (ADH1B: rs1229984-T, rs2066702-A; ADH1C: rs698-T) using up to 1109 health outcomes across 28 phenotypic categories (e.g., substance-use, mental health, sleep, immune, cardiovascular, metabolic) from a diverse 23andMe cohort, including European (N ≤ 2,619,939), Latin American (N ≤ 446,646) and African American (N ≤ 146,776) populations to uncover new and perhaps unexpected associations. These SNPs have been consistently implicated by both candidate gene studies and genome-wide association studies of alcohol-related behaviours but have not been investigated in detail for other relevant phenotypes in a hypothesis-free approach in such a large cohort of multiple ancestries. To provide insight into potential causal effects of alcohol consumption on the outcomes significant in the PheWAS, we performed univariable two-sample and one-sample Mendelian randomisation (MR) analyses. FINDINGS The minor allele rs1229984-T, which is protective against alcohol behaviours, showed the highest number of PheWAS associations across the three cohorts (N = 232, European; N = 29, Latin American; N = 7, African American). rs1229984-T influenced multiple domains of health. We replicated associations with alcohol-related behaviours, mental and sleep conditions, and cardio-metabolic health. We also found associations with understudied traits related to neurological (migraines, epilepsy), immune (allergies), musculoskeletal (fibromyalgia), and reproductive health (preeclampsia). MR analyses identified evidence of causal effects of alcohol consumption on liability for 35 of these outcomes in the European cohort. INTERPRETATION Our work demonstrates that polymorphisms in genes encoding alcohol metabolising enzymes affect multiple domains of health beyond alcohol-related behaviours. Understanding the underlying mechanisms of these effects could have implications for treatments and preventative medicine. FUNDING MVJ, NCK, SBB, SSR and AAP were supported by T32IR5226 and 28IR-0070. SSR was also supported by NIDA DP1DA054394. NCK and RBC were also supported by R25MH081482. ASH was supported by funds from NIAAA K01AA030083. JLMO was supported by VA 1IK2CX002095. JLMO and JJMM were also supported by NIDA R21DA050160. JJMM was also supported by the Kavli Postdoctoral Award for Academic Diversity. EGA was supported by K01MH121659 from the NIMH/NIH, the Caroline Wiess Law Fund for Research in Molecular Medicine and the ARCO Foundation Young Teacher-Investigator Fund at Baylor College of Medicine. MSA was supported by the Instituto de Salud Carlos III and co-funded by the European Union Found: Fondo Social Europeo Plus (FSE+) (P19/01224, PI22/00464 and CP22/00128).
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Affiliation(s)
- Mariela V Jennings
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - José Jaime Martínez-Magaña
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, Orange, West Haven, CT, USA
| | | | - Renata B Cupertino
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Laura Vilar-Ribó
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain; Department of Mental Health, Hospital Universitari Vall d'Hebron, Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Madrid, Spain
| | - Sevim B Bianchi
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Alexander S Hatoum
- Department of Psychology & Brain Sciences, Washington University in St. Louis, St Louis, MO, USA
| | - Elizabeth G Atkinson
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Paola Giusti-Rodriguez
- Department of Psychiatry, University of Florida College of Medicine, Gainesville, FL, USA
| | - Janitza L Montalvo-Ortiz
- Division of Human Genetics, Department of Psychiatry, Yale University School of Medicine, Orange, West Haven, CT, USA; National Center of Posttraumatic Stress Disorder, VA CT Healthcare Center, West Haven, CT, USA
| | - Joel Gelernter
- VA CT Healthcare Center, Department Psychiatry, West Haven, CT, USA; Departments Psychiatry, Genetics, and Neuroscience, Yale Univ. School of Medicine, New Haven, CT, USA
| | - María Soler Artigas
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain; Department of Mental Health, Hospital Universitari Vall d'Hebron, Barcelona, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Madrid, Spain; Department of Genetics, Microbiology, and Statistics, Faculty of Biology, Universitat de Barcelona, Barcelona, Spain
| | | | - Howard J Edenberg
- Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA; Division of Genetic Medicine, Department of Medicine, Vanderbilt University, Nashville, TN, USA.
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11
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Cai X, Li X, Liang C, Zhang M, Dong Z, Yu W. The effect of metabolism-related lifestyle and clinical risk factors on digestive system cancers in East Asian populations: a two-sample Mendelian randomization analysis. Sci Rep 2024; 14:9474. [PMID: 38658636 PMCID: PMC11043381 DOI: 10.1038/s41598-024-60122-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Accepted: 04/18/2024] [Indexed: 04/26/2024] Open
Abstract
Metabolic factors play a critical role in the development of digestive system cancers (DSCs), and East Asia has the highest incidence of malignant tumors in the digestive system. We performed a two-sample Mendelian randomization analysis to explore the associations between 19 metabolism-related lifestyle and clinical risk factors and DSCs, including esophageal, gastric, colorectal, hepatocellular, biliary tract, and pancreatic cancer. The causal association was explored for all combinations of each risk factor and each DSC. We gathered information on the instrumental variables (IVs) from various sources and retrieved outcome information from Biobank Japan (BBJ). The data were all from studies of east Asian populations. Finally, 17,572 DSCs cases and 195,745 controls were included. Our analysis found that genetically predicted alcohol drinking was a strong indicator of gastric cancer (odds ratio (OR) = 0.95; 95% confidence interval (CI): 0.93-0.98) and hepatocellular carcinoma (OR = 1.11; 95% CI: 1.05-1.18), whereas coffee consumption had a potential protective effect on hepatocellular carcinoma (OR = 0.69; 95% CI: 0.53-0.90). Triglyceride was potentially associated with a decreased risk of biliary tract cancer (OR = 0.53; 95% CI: 0.34-0.81), and uric acid was associated with pancreatic cancer risk (OR = 0.59; 95% CI: 0.37-0.96). Metabolic syndrome (MetS) was associated with esophageal and gastric cancer. Additionally, there was no evidence for a causal association between other risk factors, including body mass index, waist circumference, waist-to-hip ratio, educational levels, lipoprotein cholesterol, total cholesterol, glycine, creatinine, gout, and Graves' disease, and DSCs. The leave-one-out analysis revealed that the single nucleotide polymorphism (SNP) rs671 from the ALDH2 gene has a disproportionately high contribution to the causal association between alcohol drinking and gastric cancer and hepatocellular carcinoma, as well as the association between coffee consumption and hepatocellular carcinoma. The present study revealed multiple metabolism-related lifestyle and clinical risk factors and a valuable SNP rs671 for DSCs, highlighting the significance of metabolic factors in both the prevention and treatment of DSCs.
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Affiliation(s)
- Xianlei Cai
- Department of Gastrointestinal Surgery, Ningbo Medical Center Lihuili Hospital, The Lihuili Affiliated Hospital, Ningbo University, Ningbo, 315000, Zhejiang, China
| | - Xueying Li
- Department of Gastroenterology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, 310003, China
- Department of Gastroenterology, Ningbo First Hospital, Ningbo, 315000, Zhejiang, China
| | - Chao Liang
- Department of Gastrointestinal Surgery, Ningbo Medical Center Lihuili Hospital, The Lihuili Affiliated Hospital, Ningbo University, Ningbo, 315000, Zhejiang, China
| | - Miaozun Zhang
- Department of Gastrointestinal Surgery, Ningbo Medical Center Lihuili Hospital, The Lihuili Affiliated Hospital, Ningbo University, Ningbo, 315000, Zhejiang, China
| | - Zhebin Dong
- Department of Gastrointestinal Surgery, Ningbo Medical Center Lihuili Hospital, The Lihuili Affiliated Hospital, Ningbo University, Ningbo, 315000, Zhejiang, China
| | - Weiming Yu
- Department of Gastrointestinal Surgery, Ningbo Medical Center Lihuili Hospital, The Lihuili Affiliated Hospital, Ningbo University, Ningbo, 315000, Zhejiang, China.
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12
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Liu X, Koyama S, Tomizuka K, Takata S, Ishikawa Y, Ito S, Kosugi S, Suzuki K, Hikino K, Koido M, Koike Y, Horikoshi M, Gakuhari T, Ikegawa S, Matsuda K, Momozawa Y, Ito K, Kamatani Y, Terao C. Decoding triancestral origins, archaic introgression, and natural selection in the Japanese population by whole-genome sequencing. SCIENCE ADVANCES 2024; 10:eadi8419. [PMID: 38630824 PMCID: PMC11023554 DOI: 10.1126/sciadv.adi8419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2023] [Accepted: 03/07/2024] [Indexed: 04/19/2024]
Abstract
We generated Japanese Encyclopedia of Whole-Genome/Exome Sequencing Library (JEWEL), a high-depth whole-genome sequencing dataset comprising 3256 individuals from across Japan. Analysis of JEWEL revealed genetic characteristics of the Japanese population that were not discernible using microarray data. First, rare variant-based analysis revealed an unprecedented fine-scale genetic structure. Together with population genetics analysis, the present-day Japanese can be decomposed into three ancestral components. Second, we identified unreported loss-of-function (LoF) variants and observed that for specific genes, LoF variants appeared to be restricted to a more limited set of transcripts than would be expected by chance, with PTPRD as a notable example. Third, we identified 44 archaic segments linked to complex traits, including a Denisovan-derived segment at NKX6-1 associated with type 2 diabetes. Most of these segments are specific to East Asians. Fourth, we identified candidate genetic loci under recent natural selection. Overall, our work provided insights into genetic characteristics of the Japanese population.
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Affiliation(s)
- Xiaoxi Liu
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
| | - Satoshi Koyama
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | - Kohei Tomizuka
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Sadaaki Takata
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yuki Ishikawa
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shuji Ito
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory for Bone and Joint Diseases, RIKEN Center for Medical Sciences, Tokyo, Japan
- Department of Orthopedic Surgery, Faculty of Medicine, Shimane University, Izumo, Japan
| | - Shunichi Kosugi
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Kunihiko Suzuki
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Keiko Hikino
- Laboratory for Pharmacogenomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Masaru Koido
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yoshinao Koike
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory for Bone and Joint Diseases, RIKEN Center for Medical Sciences, Tokyo, Japan
- Department of Orthopedic Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Momoko Horikoshi
- Laboratory for Genomics of Diabetes and Metabolism, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Takashi Gakuhari
- Institute for the Study of Ancient Civilizations and Cultural Resources, College of Human and Social Sciences, Kanazawa University, Kanazawa, Japan
| | - Shiro Ikegawa
- Laboratory for Bone and Joint Diseases, RIKEN Center for Medical Sciences, Tokyo, Japan
| | - Kochi Matsuda
- Laboratory of Genome Technology, Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo, Japan
- Laboratory of Clinical Genome Sequencing, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Kaoru Ito
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- The Department of Applied Genetics, The School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
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13
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Hishida A, Nakatochi M, Sutoh Y, Nakano S, Momozawa Y, Narita A, Tanno K, Shimizu A, Hozawa A, Kinoshita K, Yamaji T, Goto A, Noda M, Sawada N, Ikezaki H, Nagayoshi M, Hara M, Suzuki S, Koyama T, Koriyama C, Katsuura-Kamano S, Kadota A, Kuriki K, Yamamoto M, Sasaki M, Iwasaki M, Matsuo K, Wakai K. GWAS meta-analysis of kidney function traits in Japanese populations. J Epidemiol 2024:JE20230281. [PMID: 38583947 DOI: 10.2188/jea.je20230281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/09/2024] Open
Abstract
BACKGROUND Genetic epidemiological evidence for the kidney function traits in East Asian population including Japanese remain still relatively unclarified. Especially, the number of GWASs for kidney traits reported still remains limited, and the sample size of each independent study is relatively small. Given the genetic variability between ancestries/ethnicities, implementation of GWAS with sufficiently large sample sizes in specific population of Japanese is considered meaningful. METHODS We conducted the GWAS meta-analyses of kidney traits by leveraging the GWAS summary data of the representative large genome cohort studies with about 200,000 Japanese participants (n = 202,406 for estimated glomerular filtration rate [eGFR] and n = 200,845 for serum creatinine [SCr]). RESULTS In the present GWAS meta-analysis, we identified 110 loci with 169 variants significantly associated with eGFR (on chromosomes 1-13 and 15-22; p < 5×10-8), whereas we also identified 112 loci with 176 variants significantly associated with SCr (on chromosomes 1-22; p < 5×10-8), of which one locus (more than 1Mb distant from known loci) with one variant (CD36 rs146148222 on chromosome 7) for SCr was considered as the truly novel finding. CONCLUSIONS The present GWAS meta-analysis of largest genome cohort studies in Japanese provided some original genomic loci associated with kidney function in Japanese, which may contribute to the possible development of personalized prevention of kidney diseases based on genomic information in the near future.
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Affiliation(s)
- Asahi Hishida
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine
| | - Masahiro Nakatochi
- Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine
| | - Yoichi Sutoh
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization
- Division of Biomedical Information Analysis, Iwate Medical University
| | - Shiori Nakano
- Division of Epidemiology, National Cancer Center Institute for Cancer Control
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, Center for Integrative Medical Sciences, RIKEN
| | - Akira Narita
- Tohoku Medical Megabank Organization, Tohoku University
| | - Kozo Tanno
- Division of Clinical Research and Epidemiology, Iwate Tohoku Medical Megabank Organization
- Department of Hygiene and Preventive Medicine, Iwate Medical University
| | - Atsushi Shimizu
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization
- Division of Biomedical Information Analysis, Iwate Medical University
| | | | | | - Taiki Yamaji
- Division of Epidemiology, National Cancer Center Institute for Cancer Control
| | - Atsushi Goto
- Department of Public Health, School of Medicine, Yokohama City University
| | - Mitsuhiko Noda
- Department of Diabetes, Metabolism and Endocrinology, Ichikawa Hospital, International University of Health and Welfare
- Department of Endocrinology and Diabetes, Saitama Medical University
| | - Norie Sawada
- Division of Cohort Research, National Cancer Center Institute for Cancer Control
| | - Hiroaki Ikezaki
- Department of Comprehensive General Internal Medicine, Graduate School of Medical Sciences, Kyushu University
- Department of General Internal Medicine, Kyushu University Hospital
| | - Mako Nagayoshi
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine
| | - Megumi Hara
- Department of Preventive Medicine, Faculty of Medicine, Saga University
| | - Sadao Suzuki
- Department of Public Health, Nagoya City University Graduate School of Medical Sciences
| | - Teruhide Koyama
- Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine
| | - Chihaya Koriyama
- Department of Epidemiology and Preventive Medicine, Kagoshima University Graduate School of Medical and Dental Sciences
| | | | - Aya Kadota
- Center for Epidemiologic Research in Asia, Shiga University of Medical Science
| | - Kiyonori Kuriki
- Laboratory of Public Health, Division of Nutritional Sciences, School of Food and Nutritional Sciences, University of Shizuoka
| | | | - Makoto Sasaki
- Iwate Tohoku Medical Megabank Organization, Disaster Reconstruction Center, Iwate Medical University
- Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University
| | - Motoki Iwasaki
- Division of Epidemiology, National Cancer Center Institute for Cancer Control
- Division of Cohort Research, National Cancer Center Institute for Cancer Control
| | - Keitaro Matsuo
- Division of Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute
- Department of Cancer Epidemiology, Nagoya University Graduate School of Medicine
| | - Kenji Wakai
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine
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14
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Fujii R, Nakatochi M, Del Greco M. F. Coffee Intake, Plasma Caffeine Levels, and Kidney Function: Two-Sample Mendelian Randomization Among East Asian and European Ancestries. Kidney Int Rep 2024; 9:1083-1092. [PMID: 38765557 PMCID: PMC11101828 DOI: 10.1016/j.ekir.2024.01.024] [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: 10/02/2023] [Revised: 01/08/2024] [Accepted: 01/11/2024] [Indexed: 05/22/2024] Open
Abstract
Introduction Previous Mendelian randomization (MR) studies for the coffee-kidney association have reported inconsistent relationships in European populations and never examined mediators of this association. We aimed to evaluate this causal relationship using two-sample MR among both East Asian and European ancestries and to explore underlying mechanisms using plasma caffeine levels. Methods Among East Asians, the largest genome-wide association study (GWAS) results for coffee intake, plasma caffeine levels, and kidney outcomes were obtained from 152,634; 8940; and 47,070 Japanese adults. Among Europeans, summary statistics were acquired from European GWAS with 428,860; 7719; and 564,470 adults for each trait. We applied different MR methods (inverse-variance weighted [IVW] with random effects, weighted median, weighted mode, and MR-Egger). Results After excluding possible pleiotropic variants, among East Asian ancestry, drinking an extra coffee intake per week showed a protective association on serum creatinine-based estimated glomerular filtration rate (eGFRcre) (β = 0.077; 95% confidence interval [CI] = 0.003 to 0.150). Analysis in European ancestry also showed a causal relationship between drinking an extra coffee intake per day and eGFRcre (β = 0.052; 95% CI = 0.027 to 0.078). These results were consistent across different MR methods accounting for invalid instruments. Higher plasma caffeine levels were associated with lower eGFRcre among both East Asian (β = -0.071; 95% CI = -0.137 to -0.006) and European ancestries (β = -0.048; 95% CI = -0.057 to -0.040). Conclusions Our cross-ancestry MR study found beneficial effects of coffee intake on eGFRcre. However, given the possible adverse effects of plasma caffeine levels on eGFRcre, interpretation of the results should be carefully considered and further investigations on noncaffeine and biological pathways are needed.
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Affiliation(s)
- Ryosuke Fujii
- Institute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Bolzano/Bozen, Italy
- Department of Preventive Medical Science, Fujita Health University School of Medical Sciences, Toyoake, Japan
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Masahiro Nakatochi
- Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Fabiola Del Greco M.
- Institute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Bolzano/Bozen, Italy
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15
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Zhu Y, Zhuang Z, Lv J, Sun D, Pei P, Yang L, Millwood IY, Walters RG, Chen Y, Du H, Liu F, Stevens R, Chen J, Chen Z, Li L, Yu C. A genome-wide association study based on the China Kadoorie Biobank identifies genetic associations between snoring and cardiometabolic traits. Commun Biol 2024; 7:305. [PMID: 38461358 PMCID: PMC10924953 DOI: 10.1038/s42003-024-05978-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Accepted: 02/27/2024] [Indexed: 03/11/2024] Open
Abstract
Despite the high prevalence of snoring in Asia, little is known about the genetic etiology of snoring and its causal relationships with cardiometabolic traits. Based on 100,626 Chinese individuals, a genome-wide association study on snoring was conducted. Four novel loci were identified for snoring traits mapped on SLC25A21, the intergenic region of WDR11 and FGFR, NAA25, ALDH2, and VTI1A, respectively. The novel loci highlighted the roles of structural abnormality of the upper airway and craniofacial region and dysfunction of metabolic and transport systems in the development of snoring. In the two-sample bi-directional Mendelian randomization analysis, higher body mass index, weight, and elevated blood pressure were causal for snoring, and a reverse causal effect was observed between snoring and diastolic blood pressure. Altogether, our results revealed the possible etiology of snoring in China and indicated that managing cardiometabolic health was essential to snoring prevention, and hypertension should be considered among snorers.
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Affiliation(s)
- Yunqing Zhu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Zhenhuang Zhuang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Jun Lv
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
| | - Dianjianyi Sun
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, OX3 7LF, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, United Kingdom
| | - Iona Y Millwood
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, OX3 7LF, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, United Kingdom
| | - Robin G Walters
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, OX3 7LF, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, United Kingdom
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, OX3 7LF, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, United Kingdom
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, OX3 7LF, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, United Kingdom
| | - Fang Liu
- Suzhou Centers for Disease Control, NO.72 Sanxiang Road, Gusu District, Suzhou, 215004, Jiangsu, China
| | - Rebecca Stevens
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, United Kingdom
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, 100022, China
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, United Kingdom
| | - Liming Li
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
| | - Canqing Yu
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
- Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, 100191, China.
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China.
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16
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Kim MJ, Jin HS, Eom YB. Coffee consumption affects kidney function based on GCKR polymorphism in a Korean population. Nutr Res 2024; 122:92-100. [PMID: 38215572 DOI: 10.1016/j.nutres.2023.12.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 12/19/2023] [Accepted: 12/19/2023] [Indexed: 01/14/2024]
Abstract
Kidney function can be preserved through pharmacological interventions and nonpharmacological strategies, such as lifestyle and dietary adjustments. Among these, coffee has been linked to protective effects on kidney function. However, few studies have investigated the effect of coffee consumption on kidney function according to specific genes. We hypothesized that the impact of coffee consumption on kidney function might vary depending on GCKR polymorphism. GCKR rs1260326 polymorphism was examined using the Korean genome and epidemiology data from 656 chronic kidney disease (CKD) cases and 38,540 individuals without CKD (non-CKD). GCKR polymorphism has been previously associated with both coffee consumption and kidney function in Europeans. We replicated the associations between GCKR rs1260326 and coffee consumption and kidney function in Korean individuals. We also explored the effect of coffee consumption on kidney function by multivariate logistic regression analysis. Individuals with the rs1260326 (TC/CC) genotype did not experience significant changes in CKD risk based on their coffee consumption habits. In contrast, individuals with the TT genotype exhibited a significantly lower risk of CKD based on coffee consumption. Interestingly, in the non-CKD group, a beneficial effect on estimated glomerular filtration rate was observed in individuals with the T allele as coffee consumption increased. Our findings supported the hypothesis and revealed that the impact of coffee consumption habits on kidney function may vary based on the GCKR rs1260326 genotype of Korean individuals.
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Affiliation(s)
- Min-Jeong Kim
- Department of Medical Sciences, Graduate School, Soonchunhyang University, Asan, Chungnam 31538, Republic of Korea
| | - Hyun-Seok Jin
- Department of Biomedical Laboratory Science, College of Life and Health Sciences, Hoseo University, Asan, Chungnam 31499, Republic of Korea
| | - Yong-Bin Eom
- Department of Medical Sciences, Graduate School, Soonchunhyang University, Asan, Chungnam 31538, Republic of Korea; Department of Biomedical Laboratory Science, College of Medical Sciences, Soonchunhyang University, Asan, Chungnam 31538, Republic of Korea.
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17
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Koyanagi YN, Nakatochi M, Namba S, Oze I, Charvat H, Narita A, Kawaguchi T, Ikezaki H, Hishida A, Hara M, Takezaki T, Koyama T, Nakamura Y, Suzuki S, Katsuura-Kamano S, Kuriki K, Nakamura Y, Takeuchi K, Hozawa A, Kinoshita K, Sutoh Y, Tanno K, Shimizu A, Ito H, Kasugai Y, Kawakatsu Y, Taniyama Y, Tajika M, Shimizu Y, Suzuki E, Hosono Y, Imoto I, Tabara Y, Takahashi M, Setoh K, Matsuda K, Nakano S, Goto A, Katagiri R, Yamaji T, Sawada N, Tsugane S, Wakai K, Yamamoto M, Sasaki M, Matsuda F, Okada Y, Iwasaki M, Brennan P, Matsuo K. Genetic architecture of alcohol consumption identified by a genotype-stratified GWAS and impact on esophageal cancer risk in Japanese people. SCIENCE ADVANCES 2024; 10:eade2780. [PMID: 38277453 PMCID: PMC10816704 DOI: 10.1126/sciadv.ade2780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 12/26/2023] [Indexed: 01/28/2024]
Abstract
An East Asian-specific variant on aldehyde dehydrogenase 2 (ALDH2 rs671, G>A) is the major genetic determinant of alcohol consumption. We performed an rs671 genotype-stratified genome-wide association study meta-analysis of alcohol consumption in 175,672 Japanese individuals to explore gene-gene interactions with rs671 behind drinking behavior. The analysis identified three genome-wide significant loci (GCKR, KLB, and ADH1B) in wild-type homozygotes and six (GCKR, ADH1B, ALDH1B1, ALDH1A1, ALDH2, and GOT2) in heterozygotes, with five showing genome-wide significant interaction with rs671. Genetic correlation analyses revealed ancestry-specific genetic architecture in heterozygotes. Of the discovered loci, four (GCKR, ADH1B, ALDH1A1, and ALDH2) were suggested to interact with rs671 in the risk of esophageal cancer, a representative alcohol-related disease. Our results identify the genotype-specific genetic architecture of alcohol consumption and reveal its potential impact on alcohol-related disease risk.
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Affiliation(s)
- Yuriko N. Koyanagi
- Division of Cancer Epidemiology and Prevention, Department of Preventive Medicine, Aichi Cancer Center Research Institute, Nagoya, Japan
| | - Masahiro Nakatochi
- Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Shinichi Namba
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Isao Oze
- Division of Cancer Epidemiology and Prevention, Department of Preventive Medicine, Aichi Cancer Center Research Institute, Nagoya, Japan
| | - Hadrien Charvat
- Faculty of International Liberal Arts, Juntendo University, Tokyo, Japan
- Division of International Health Policy Research, Institute for Cancer Control, National Cancer Center, Tokyo, Japan
- Cancer Surveillance Branch, International Agency for Research on Cancer, Lyon, France
| | - Akira Narita
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Takahisa Kawaguchi
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Hiroaki Ikezaki
- Department of General Internal Medicine, Kyushu University Hospital, Fukuoka, Japan
- Department of Comprehensive General Internal Medicine, Faculty of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Asahi Hishida
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Megumi Hara
- Department of Preventive Medicine, Faculty of Medicine, Saga University, Saga, Japan
| | - Toshiro Takezaki
- Department of International Island and Community Medicine, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan
| | - Teruhide Koyama
- Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine, Kyoto, 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
| | - Sakurako Katsuura-Kamano
- Department of Preventive Medicine, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan
| | - Kiyonori Kuriki
- Laboratory of Public Health, Division of Nutritional Sciences, School of Food and Nutritional Sciences, University of Shizuoka, Shizuoka, Japan
| | - Yasuyuki Nakamura
- Department of Public Health, Shiga University of Medical Science, Otsu, Japan
| | - Kenji Takeuchi
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
- Department of International and Community Oral Health, Tohoku University Graduate School of Dentistry, Sendai, Japan
- Division for Regional Community Development, Liaison Center for Innovative Dentistry, Tohoku University Graduate School of Dentistry, Sendai, Japan
| | - Atsushi Hozawa
- Department of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Kengo Kinoshita
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Yoichi Sutoh
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
| | - Kozo Tanno
- Department of Hygiene and Preventive Medicine, School of Medicine, Iwate Medical University, Iwate, Japan
- Division of Clinical Research and Epidemiology, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
| | - Atsushi Shimizu
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
- Division of Biomedical Information Analysis, Institute for Biomedical Sciences, Iwate Medical University, Iwate, Japan
| | - Hidemi Ito
- Division of Cancer Information and Control, Department of Preventive Medicine, Aichi Cancer Center Research Institute, Nagoya, Japan
- Department of Descriptive Cancer Epidemiology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Yumiko Kasugai
- Division of Cancer Epidemiology and Prevention, Department of Preventive Medicine, Aichi Cancer Center Research Institute, Nagoya, Japan
- Department of Cancer Epidemiology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Yukino Kawakatsu
- Division of Cancer Epidemiology and Prevention, Department of Preventive Medicine, Aichi Cancer Center Research Institute, Nagoya, Japan
| | - Yukari Taniyama
- Division of Cancer Information and Control, Department of Preventive Medicine, Aichi Cancer Center Research Institute, Nagoya, Japan
| | - Masahiro Tajika
- Department of Endoscopy, Aichi Cancer Center Hospital, Nagoya, Japan
| | - Yasuhiro Shimizu
- Department of Gastroenterological Surgery, Aichi Cancer Center Hospital, Nagoya, Japan
| | - Etsuji Suzuki
- Department of Epidemiology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Yasuyuki Hosono
- Department of Pharmacology, Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan
| | - Issei Imoto
- Aichi Cancer Center Research Institute, Nagoya, Japan
| | - Yasuharu Tabara
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
- Graduate School of Public Health, Shizuoka Graduate University of Public Health, Shizuoka, Japan
| | - Meiko Takahashi
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Kazuya Setoh
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | | | - Koichi Matsuda
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Shiori Nakano
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, Tokyo, Japan
| | - Atsushi Goto
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, Tokyo, Japan
- Department of Health Data Science, Graduate School of Data Science, Yokohama City University, Yokohama, Japan
| | - Ryoko Katagiri
- Division of Cohort Research, National Cancer Center Institute for Cancer Control, Tokyo, Japan
- National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan
| | - Taiki Yamaji
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, Tokyo, Japan
| | - Norie Sawada
- Division of Cohort Research, National Cancer Center Institute for Cancer Control, Tokyo, Japan
| | - Shoichiro Tsugane
- Division of Cohort Research, National Cancer Center Institute for Cancer Control, Tokyo, Japan
- National Institute of Health and Nutrition, National Institutes of Biomedical Innovation, Health and Nutrition, Tokyo, Japan
| | - Kenji Wakai
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Masayuki Yamamoto
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Makoto Sasaki
- Division of Ultrahigh Field MRI, Institute for Biomedical Sciences, Iwate Medical University, Iwate, Japan
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan
- Center for Infectious Disease Education and Research (CiDER), Osaka University, Suita, Japan
| | - Motoki Iwasaki
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, Tokyo, Japan
- Division of Cohort Research, National Cancer Center Institute for Cancer Control, Tokyo, Japan
| | - Paul Brennan
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
| | - Keitaro Matsuo
- Division of Cancer Epidemiology and Prevention, Department of Preventive Medicine, Aichi Cancer Center Research Institute, Nagoya, Japan
- Department of Cancer Epidemiology, Nagoya University Graduate School of Medicine, Nagoya, Japan
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18
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Yang M, Gao X, Xie L, Lin Z, Ye X, Ou J, Peng J. Causal associations between dietary habits and CVD: a Mendelian randomisation study. Br J Nutr 2023; 130:2104-2113. [PMID: 37381916 DOI: 10.1017/s000711452300140x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/30/2023]
Abstract
Over the years, numerous observational studies have substantiated that various dietary choices have opposing effects on CVD. However, the causal effect has not yet been established. Thus, we conducted a Mendelian randomisation (MR) analysis to reveal the causal impact of dietary habits on CVD. Genetic variants strongly associated with 20 dietary habits were selected from publicly available genome-wide association studies conducted on the UK Biobank cohort (n 449 210). Summary-level data on CVD were obtained from different consortia (n 159 836-977 323). The inverse-variance weighted method (IVW) was the primary outcome, while MR-Egger, weighted median and MR Pleiotropy RESidual Sum and Outlier were used to assess heterogeneity and pleiotropy. We found compelling evidence of a protective causal effect of genetic predisposition towards cheese consumption on myocardial infarction (IVW OR = 0·67; 95 % CI = 0·544, 0·826; P = 1·784 × 10-4) and heart failure (IVW OR = 0·646; 95 % CI = 0·513, 0·814; P = 2·135 × 10-4). Poultry intake was found to be a detrimental factor for hypertension (IVW OR = 4·306; 95 % CI = 2·158, 8·589; P = 3·416 × 10-5), while dried fruit intake was protective against hypertension (IVW OR = 0·473; 95 % CI = 0·348, 0·642; P = 1·683 × 10-6). Importantly, no evidence of pleiotropy was detected. MR estimates provide robust evidence for a causal relationship between genetic predisposition to 20 dietary habits and CVD risk, suggesting that well-planned diets may help prevent and reduce the risk of CVD.
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Affiliation(s)
- Miaomiao Yang
- Department of Cardiology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, People's Republic of China
| | - Xiong Gao
- Department of Cardiology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, People's Republic of China
| | - Liangzhen Xie
- Department of Geriatrics, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, People's Republic of China
| | - Zhizhan Lin
- Department of Cardiology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, People's Republic of China
| | - Xingsheng Ye
- Department of Cardiology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, People's Republic of China
| | - Jianyan Ou
- Department of Cardiology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, People's Republic of China
| | - Jian Peng
- Department of Cardiology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, People's Republic of China
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19
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Cui H, Srinivasan S, Gao Z, Korkin D. The Extent of Edgetic Perturbations in the Human Interactome Caused by Population-Specific Mutations. Biomolecules 2023; 14:40. [PMID: 38254640 PMCID: PMC11154503 DOI: 10.3390/biom14010040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 11/30/2023] [Accepted: 12/03/2023] [Indexed: 01/24/2024] Open
Abstract
Until recently, efforts in population genetics have been focused primarily on people of European ancestry. To attenuate this bias, global population studies, such as the 1000 Genomes Project, have revealed differences in genetic variation across ethnic groups. How many of these differences can be attributed to population-specific traits? To answer this question, the mutation data must be linked with functional outcomes. A new "edgotype" concept has been proposed, which emphasizes the interaction-specific, "edgetic", perturbations caused by mutations in the interacting proteins. In this work, we performed systematic in silico edgetic profiling of ~50,000 non-synonymous SNVs (nsSNVs) from the 1000 Genomes Project by leveraging our semi-supervised learning approach SNP-IN tool on a comprehensive set of over 10,000 protein interaction complexes. We interrogated the functional roles of the variants and their impact on the human interactome and compared the results with the pathogenic variants disrupting PPIs in the same interactome. Our results demonstrated that a considerable number of nsSNVs from healthy populations could rewire the interactome. We also showed that the proteins enriched with interaction-disrupting mutations were associated with diverse functions and had implications in a broad spectrum of diseases. Further analysis indicated that distinct gene edgetic profiles among major populations could shed light on the molecular mechanisms behind the population phenotypic variances. Finally, the network analysis revealed that the disease-associated modules surprisingly harbored a higher density of interaction-disrupting mutations from healthy populations. The variation in the cumulative network damage within these modules could potentially account for the observed disparities in disease susceptibility, which are distinctly specific to certain populations. Our work demonstrates the feasibility of a large-scale in silico edgetic study, and reveals insights into the orchestrated play of population-specific mutations in the human interactome.
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Affiliation(s)
- Hongzhu Cui
- Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA;
- Chromatography and Mass Spectrometry Division, Thermo Fisher Scientific, San Jose, CA 95134, USA
| | - Suhas Srinivasan
- Data Science Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA;
- Program in Epithelial Biology, Stanford School of Medicine, Stanford, CA 94305, USA
- Center for Personal Dynamic Regulomes, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Ziyang Gao
- Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA;
| | - Dmitry Korkin
- Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA;
- Data Science Program, Worcester Polytechnic Institute, Worcester, MA 01609, USA;
- Computer Science Department, Worcester Polytechnic Institute, Worcester, MA 01609, USA
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20
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He Y, Koido M, Sutoh Y, Shi M, Otsuka-Yamasaki Y, Munter HM, Morisaki T, Nagai A, Murakami Y, Tanikawa C, Hachiya T, Matsuda K, Shimizu A, Kamatani Y. East Asian-specific and cross-ancestry genome-wide meta-analyses provide mechanistic insights into peptic ulcer disease. Nat Genet 2023; 55:2129-2138. [PMID: 38036781 PMCID: PMC10703676 DOI: 10.1038/s41588-023-01569-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 10/12/2023] [Indexed: 12/02/2023]
Abstract
Peptic ulcer disease (PUD) refers to acid-induced injury of the digestive tract, occurring mainly in the stomach (gastric ulcer (GU)) or duodenum (duodenal ulcer (DU)). In the present study, we conducted a large-scale, cross-ancestry meta-analysis of PUD combining genome-wide association studies with Japanese and European studies (52,032 cases and 905,344 controls), and discovered 25 new loci highly concordant across ancestries. An examination of GU and DU genetic architecture demonstrated that GUs shared the same risk loci as DUs, although with smaller genetic effect sizes and higher polygenicity than DUs, indicating higher heterogeneity of GUs. Helicobacter pylori (HP)-stratified analysis found an HP-related host genetic locus. Integrative analyses using bulk and single-cell transcriptome profiles highlighted the genetic factors of PUD being enriched in the highly expressed genes in stomach tissues, especially in somatostatin-producing D cells. Our results provide genetic evidence that gastrointestinal cell differentiations and hormone regulations are critical in PUD etiology.
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Affiliation(s)
- Yunye He
- Laboratory of Complex Trait Genomics, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Masaru Koido
- Laboratory of Complex Trait Genomics, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yoichi Sutoh
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
| | - Mingyang Shi
- Laboratory of Complex Trait Genomics, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | | | - Hans Markus Munter
- Victor Phillip Dahdaleh Institute of Genomic Medicine and Department of Human Genetics, McGill University, Montreal, Québec, Canada
| | - Takayuki Morisaki
- Division of Molecular Pathology, Institute of Medical Science, The University of Tokyo, Tokyo, Japan
- Laboratory of Clinical Genome Sequencing, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Akiko Nagai
- Department of Public Policy, Institute of Medical Sciences, The University of Tokyo, Tokyo, Japan
| | - Yoshinori Murakami
- Division of Molecular Pathology, Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Chizu Tanikawa
- Laboratory of Clinical Genome Sequencing, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Tsuyoshi Hachiya
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
| | - Koichi Matsuda
- Laboratory of Clinical Genome Sequencing, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Atsushi Shimizu
- Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Iwate, Japan
| | - Yoichiro Kamatani
- Laboratory of Complex Trait Genomics, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan.
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21
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Kawai Y, Watanabe Y, Omae Y, Miyahara R, Khor SS, Noiri E, Kitajima K, Shimanuki H, Gatanaga H, Hata K, Hattori K, Iida A, Ishibashi-Ueda H, Kaname T, Kanto T, Matsumura R, Miyo K, Noguchi M, Ozaki K, Sugiyama M, Takahashi A, Tokuda H, Tomita T, Umezawa A, Watanabe H, Yoshida S, Goto YI, Maruoka Y, Matsubara Y, Niida S, Mizokami M, Tokunaga K. Exploring the genetic diversity of the Japanese population: Insights from a large-scale whole genome sequencing analysis. PLoS Genet 2023; 19:e1010625. [PMID: 38060463 PMCID: PMC10703243 DOI: 10.1371/journal.pgen.1010625] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Accepted: 10/24/2023] [Indexed: 12/18/2023] Open
Abstract
The Japanese archipelago is a terminal location for human migration, and the contemporary Japanese people represent a unique population whose genomic diversity has been shaped by multiple migrations from Eurasia. We analyzed the genomic characteristics that define the genetic makeup of the modern Japanese population from a population genetics perspective from the genomic data of 9,287 samples obtained by high-coverage whole-genome sequencing (WGS) by the National Center Biobank Network. The dataset comprised populations from the Ryukyu Islands and other parts of the Japanese archipelago (Hondo). The Hondo population underwent two episodes of population decline during the Jomon period, corresponding to the Late Neolithic, and the Edo period, corresponding to the Early Modern era, while the Ryukyu population experienced a population decline during the shell midden period of the Late Neolithic in this region. Haplotype analysis suggested increased allele frequencies for genes related to alcohol and fatty acid metabolism, which were reported as loci that had experienced positive natural selection. Two genes related to alcohol metabolism were found to be 12,500 years out of phase with the time when they began to increase in the allele frequency; this finding indicates that the genomic diversity of Japanese people has been shaped by events closely related to agriculture and food production.
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Affiliation(s)
- Yosuke Kawai
- Genome Medical Science Project, Research Institute, National Center for Global Health and Medicine, Shinjuku-ku, Tokyo, Japan
| | - Yusuke Watanabe
- Genome Medical Science Project, Research Institute, National Center for Global Health and Medicine, Shinjuku-ku, Tokyo, Japan
| | - Yosuke Omae
- Genome Medical Science Project, Research Institute, National Center for Global Health and Medicine, Shinjuku-ku, Tokyo, Japan
- Central Biobank, National Center Biobank Network, Shinjuku-ku, Tokyo, Japan
| | - Reiko Miyahara
- Central Biobank, National Center Biobank Network, Shinjuku-ku, Tokyo, Japan
| | - Seik-Soon Khor
- Genome Medical Science Project, Research Institute, National Center for Global Health and Medicine, Shinjuku-ku, Tokyo, Japan
| | - Eisei Noiri
- Central Biobank, National Center Biobank Network, Shinjuku-ku, Tokyo, Japan
| | - Koji Kitajima
- Central Biobank, National Center Biobank Network, Shinjuku-ku, Tokyo, Japan
- Department of Data Science Center for Clinical Sciences, National Center for Global Health and Medicine, Shinjuku-ku, Tokyo, Japan
| | - Hideyuki Shimanuki
- Central Biobank, National Center Biobank Network, Shinjuku-ku, Tokyo, Japan
- Department of Data Science Center for Clinical Sciences, National Center for Global Health and Medicine, Shinjuku-ku, Tokyo, Japan
| | - Hiroyuki Gatanaga
- AIDS Clinical Center, National Center for Global Health and Medicine, Shinjuku-ku, Tokyo, Japan
| | - Kenichiro Hata
- Department of Maternal-Fetal Biology, National Center for Child Health and Development, Setagaya-ku, Tokyo, Japan
| | - Kotaro Hattori
- Department of Bioresources, Medical Genome Center, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan
| | - Aritoshi Iida
- Department of Clinical Genome Analysis, Medical Genome Center, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan
| | | | - Tadashi Kaname
- Department of Genome Medicine, National Center for Child Health and Development, Setagaya-ku, Tokyo, Japan
| | - Tatsuya Kanto
- Department of Liver Disease, Research Center for Hepatitis and Immunology, National Center for Global Health and Medicine, Ichikawa, Chiba, Japan
| | - Ryo Matsumura
- Department of Bioresources, Medical Genome Center, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan
| | - Kengo Miyo
- Center for Medical Informatics Intelligence, National Center for Global Health and Medicine, Shinjuku-ku, Tokyo, Japan
| | - Michio Noguchi
- NCVC Biobank, National Cerebral and Cardiovascular Center, Suita, Osaka, Japan
| | - Kouichi Ozaki
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
- RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Masaya Sugiyama
- Department of Viral Pathogenesis and Controls, Research Institute, National Center for Global Health and Medicine, Shinjuku-ku, Tokyo, Japan
| | - Ayako Takahashi
- NCVC Biobank, National Cerebral and Cardiovascular Center, Suita, Osaka, Japan
| | - Haruhiko Tokuda
- Core Facility Administration, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
- Department of Metabolic Research, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
- Department of Clinical Laboratory, Hospital, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
| | - Tsutomu Tomita
- NCVC Biobank, National Cerebral and Cardiovascular Center, Suita, Osaka, Japan
| | - Akihiro Umezawa
- Center for Regenerative Medicine, Research Institute, National Center for Child Health and Development, Setagaya-ku, Tokyo, Japan
| | - Hiroshi Watanabe
- Core Facility Administration, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
- Innovation Center for Translational Research, Hospital, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
| | - Sumiko Yoshida
- Department of Bioresources, Medical Genome Center, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan
| | - Yu-ichi Goto
- Medical Genome Center, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan
| | - Yutaka Maruoka
- Department of Oral and Maxillofacial Surgery, National Center for Global Health and Medicine, Shinjuku-ku, Tokyo, Japan
| | - Yoichi Matsubara
- National Center for Child Health and Development, Setagaya-ku, Tokyo, Japan
| | - Shumpei Niida
- Core Facility Administration, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
| | - Masashi Mizokami
- Genome Medical Science Project, Research Institute, National Center for Global Health and Medicine, Ichikawa, Chiba, Japan
| | - Katsushi Tokunaga
- Genome Medical Science Project, Research Institute, National Center for Global Health and Medicine, Shinjuku-ku, Tokyo, Japan
- Central Biobank, National Center Biobank Network, Shinjuku-ku, Tokyo, Japan
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22
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Liu X, Li Y. Genetic correlation for alcohol consumption between Europeans and East Asians. BMC Genomics 2023; 24:652. [PMID: 37904118 PMCID: PMC10614326 DOI: 10.1186/s12864-023-09766-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Accepted: 10/25/2023] [Indexed: 11/01/2023] Open
Abstract
Genome-wide association studies (GWAS) have identified many genetic variants associated with alcohol consumption in Europeans and East Asians, as well as other populations. However, the genetic homogeneity and heterogeneity between these populations have not been thoroughly investigated, despite evidence of varying effect sizes of variants between ethnicities and the presence of population-specific strong signals of selection on loci associated with alcohol consumption. In order to better understand the relationship between Europeans and East Asians in the genetic architecture of alcohol consumption, we compared their heritability and evaluated their genetic correlation using GWAS results from UK Biobank (UKB) and Biobank Japan (BBJ). We found that these two populations have low genetic correlation due to the large difference on chromosome 12. After excluding this chromosome, the genetic correlation was moderately high ([Formula: see text] = 0.544, p = 1.12e-4) and 44.31% of the genome-wide causal variants were inferred to be shared between Europeans and East Asians. Given those observations, we conducted a meta-analysis on UKB and BBJ and identified new signals, including the CADM2 gene on chromosome 3, which has been associated with various behavioral and metabolic traits. Overall, our findings suggest that the genetic architecture of alcohol consumption is largely shared between Europeans and East Asians, but there are exceptions such as the enrichment of heritability on chromosome 12 in East Asians.
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Affiliation(s)
- Xuan Liu
- Department of Neurology, The First People's Hospital of Wenling, Taizhou, China
| | - Yongang Li
- Department of Neurology, The First People's Hospital of Wenling, Taizhou, China.
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23
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Kim S, Jeon HK, Lee G, Kim Y, Yoo HY. Associations between the Genetic Heritability of Dyslipidemia and Dietary Patterns in Korean Adults Based on Sex Differences. Nutrients 2023; 15:4385. [PMID: 37892463 PMCID: PMC10609770 DOI: 10.3390/nu15204385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 10/11/2023] [Accepted: 10/14/2023] [Indexed: 10/29/2023] Open
Abstract
Dyslipidemia can be defined as an abnormality in serum lipid levels that is substantially linked to genetic variations and lifestyle factors, such as diet patterns, and has distinct sex-specific characteristics. We aimed to elucidate the genetic impact of dyslipidemia according to sex and explore the associations between genetic variants and dietary patterns in large-scale population-based cohorts. After performing genome-wide association studies (GWASs) in male, female, and entire cohorts, significant single nucleotide polymorphisms (SNPs) were identified in the three groups, and genetic risk scores (GRSs) were calculated by summing the risk alleles from the selected SNPs. After adjusting for confounding variables, the risk of dyslipidemia was 2.013-fold and 2.535-fold higher in the 3rd quartile GRS group in the male and female cohorts, respectively, than in the 1st quartile GRS group. While instant noodle and soft drink intake were significantly associated with GRS related to hyperlipidemia in male cohorts, coffee consumption was substantially related to GRS related to hyperlipidemia in female cohorts. Considering the influence of genetic factors and dietary patterns, the findings of this study suggest the potential for implementing sex-specific strategic interventions to avoid dyslipidemia.
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Affiliation(s)
- Sei Kim
- Graduate School, Chung-Ang University, Seoul 06974, Republic of Korea; (S.K.); (G.L.); (Y.K.)
| | - Hye Kyung Jeon
- Department of Nursing, Ansan University, Ansan 15328, Republic of Korea;
| | - Gyeonghee Lee
- Graduate School, Chung-Ang University, Seoul 06974, Republic of Korea; (S.K.); (G.L.); (Y.K.)
| | - Youbin Kim
- Graduate School, Chung-Ang University, Seoul 06974, Republic of Korea; (S.K.); (G.L.); (Y.K.)
| | - Hae Young Yoo
- Department of Nursing, Chung-Ang University, Seoul 06974, Republic of Korea
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24
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Thorpe HHA, Fontanillas P, Pham BK, Meredith JJ, Jennings MV, Courchesne-Krak NS, Vilar-Ribó L, Bianchi SB, Mutz J, Elson SL, Khokhar JY, Abdellaoui A, Davis LK, Palmer AA, Sanchez-Roige S. Genome-Wide Association Studies of Coffee Intake in UK/US Participants of European Ancestry Uncover Gene-Cohort Influences. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.09.09.23295284. [PMID: 37745582 PMCID: PMC10516045 DOI: 10.1101/2023.09.09.23295284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Coffee is one of the most widely consumed beverages. We performed a genome-wide association study (GWAS) of coffee intake in US-based 23andMe participants (N=130,153) and identified 7 significant loci, with many replicating in three multi-ancestral cohorts. We examined genetic correlations and performed a phenome-wide association study across thousands of biomarkers and health and lifestyle traits, then compared our results to the largest available GWAS of coffee intake from UK Biobank (UKB; N=334,659). The results of these two GWAS were highly discrepant. We observed positive genetic correlations between coffee intake and psychiatric illnesses, pain, and gastrointestinal traits in 23andMe that were absent or negative in UKB. Genetic correlations with cognition were negative in 23andMe but positive in UKB. The only consistent observations were positive genetic correlations with substance use and obesity. Our study shows that GWAS in different cohorts could capture cultural differences in the relationship between behavior and genetics.
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Affiliation(s)
- Hayley H A Thorpe
- Department of Anatomy and Cell Biology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- Department of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
| | | | - Benjamin K Pham
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - John J Meredith
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Mariela V Jennings
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | | | - Laura Vilar-Ribó
- Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Vall d’Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Sevim B Bianchi
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Julian Mutz
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, UK
| | - 23andMe Research Team
- Department of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
| | - Sarah L Elson
- Department of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
| | - Jibran Y Khokhar
- Department of Anatomy and Cell Biology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- Department of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
| | - Abdel Abdellaoui
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Lea K Davis
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
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25
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Lu J, Wang Z. C-reactive protein partially mediates the inverse effect of coffee consumption on risk of type 2 diabetes: Evidence from two-stage Mendelian randomization analysis. Clin Nutr 2023; 42:1747-1748. [PMID: 37542952 DOI: 10.1016/j.clnu.2023.07.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Accepted: 07/28/2023] [Indexed: 08/07/2023]
Affiliation(s)
- Jiawen Lu
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Zhenqian Wang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, China.
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26
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Qi L, Heianza Y, Li X, Sacks FM, Bray GA. Toward Precision Weight-Loss Dietary Interventions: Findings from the POUNDS Lost Trial. Nutrients 2023; 15:3665. [PMID: 37630855 PMCID: PMC10458797 DOI: 10.3390/nu15163665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 08/13/2023] [Accepted: 08/18/2023] [Indexed: 08/27/2023] Open
Abstract
The POUNDS Lost trial is a 2-year clinical trial testing the effects of dietary interventions on weight loss. This study included 811 adults with overweight or obesity who were randomized to one of four diets that contained either 15% or 25% protein and 20% or 40% fat in a 2 × 2 factorial design. By 2 years, participants on average lost from 2.9 to 3.6 kg in body weight in the four intervention arms, while no significant difference was observed across the intervention arms. In POUNDS Lost, we performed a series of ancillary studies to detect intrinsic factors particular to genomic, epigenomic, and metabolomic markers that may modulate changes in weight and other cardiometabolic traits in response to the weight-loss dietary interventions. Genomic variants identified from genome-wide association studies (GWASs) on obesity, type 2 diabetes, glucose and lipid metabolisms, gut microbiome, and dietary intakes have been found to interact with dietary macronutrients (fat, protein, and carbohydrates) in relation to weight loss and changes of body composition and cardiometabolic traits. In addition, we recently investigated epigenomic modifications, particularly blood DNA methylation and circulating microRNAs (miRNAs). We reported DNA methylation levels at NFATC2IP, CPT1A, TXNIP, and LINC00319 were related to weight loss or changes of glucose, lipids, and blood pressure; we also reported thrifty miRNA expression as a significant epigenomic marker related to changes in insulin sensitivity and adiposity. Our studies have also highlighted the importance of temporal changes in novel metabolomic signatures for gut microbiota, bile acids, and amino acids as predictors for achievement of successful weight loss outcomes. Moreover, our studies indicate that biochemical, behavioral, and psychosocial factors such as physical activity, sleep disturbance, and appetite may also modulate metabolic changes during dietary interventions. This review summarized our major findings in the POUNDS Lost trial, which provided preliminary evidence supporting the development of precision diet interventions for obesity management.
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Affiliation(s)
- Lu Qi
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70118, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Yoriko Heianza
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70118, USA
| | - Xiang Li
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70118, USA
| | - Frank M. Sacks
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - George A. Bray
- Department of Clinical Obesity, Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA 70808, USA
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Akiyama M, Miyake M, Momozawa Y, Arakawa S, Maruyama-Inoue M, Endo M, Iwasaki Y, Ishigaki K, Matoba N, Okada Y, Yasuda M, Oshima Y, Yoshida S, Nakao SY, Morino K, Mori Y, Kido A, Kato A, Yasukawa T, Obata R, Nagai Y, Takahashi K, Fujisawa K, Miki A, Nakamura M, Honda S, Ushida H, Yasuma T, Nishiguchi KM, Mori R, Tanaka K, Wakatsuki Y, Yamashiro K, Kadonosono K, Terao C, Ishibashi T, Tsujikawa A, Sonoda KH, Kubo M, Kamatani Y. Genome-Wide Association Study of Age-Related Macular Degeneration Reveals 2 New Loci Implying Shared Genetic Components with Central Serous Chorioretinopathy. Ophthalmology 2023; 130:361-372. [PMID: 36423732 DOI: 10.1016/j.ophtha.2022.10.034] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 09/27/2022] [Accepted: 10/17/2022] [Indexed: 11/23/2022] Open
Abstract
PURPOSE To investigate the genetic architecture of age-related macular degeneration (AMD) in a Japanese population. DESIGN Genome-wide association study (GWAS). PARTICIPANTS Three thousand seven hundred seventy-two patients with AMD and 16 770 control participants from the Japanese population were enrolled in the association analyses. METHODS We conducted a meta-analysis of 2 independent GWASs that included a total of 2663 patients with AMD and 9471 control participants using the imputation reference panel for genotype imputation specified for the Japanese population (n = 3541). A replication study was performed using an independent set of 1109 patients with AMD and 7299 control participants. MAIN OUTCOME MEASURES Associations of genetic variants with AMD. RESULTS A meta-analysis of the 2 GWASs identified 6 loci significantly associated with AMD (P < 5.0 × 10-8). Of these loci, 4 were known to be associated with AMD (CFH, C2/FB, TNFRSF10A, and ARMS2), and 2 were novel (rs4147157 near WBP1L and rs76228488 near GATA5). The newly identified associations were confirmed in a replication study (P < 0.01). After the meta-analysis of all datasets, we observed strong associations in these loci (P = 1.88 × 10-12 and P = 1.35 × 10-9 for meta-analysis for rs4147157 and rs76228488, respectively). When we looked up the associations in the reported central serous chorioretinopathy (CSC) GWAS conducted in the Japanese population, both loci were associated significantly with CSC (P = 4.86 × 10-3 and P = 4.28 × 10-3 for rs4147157 and rs76228488, respectively). We performed a genetic colocalization analysis for these loci and estimated that the posterior probabilities of shared causal variants between AMD and CSC were 0.39 and 0.60 for WBP1L and GATA5, respectively. Genetic correlation analysis focusing on the epidemiologically suggested clinical risk factors implicated shared polygenic architecture between AMD and smoking cessation (rg [the measure of genetic correlation] = -0.33; P = 0.01; false discovery rate, 0.099). CONCLUSIONS Our findings imply shared genetic components conferring the risk of both AMD and CSC. FINANCIAL DISCLOSURE(S) Proprietary or commercial disclosure may be found after the references.
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Affiliation(s)
- Masato Akiyama
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan; Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan; Department of Ocular Pathology and Imaging Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan; Department of Ophthalmology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.
| | - Masahiro Miyake
- Department of Ophthalmology and Visual Sciences, Kyoto University, Graduate School of Medicine, Kyoto, Japan; Center for Genomic Medicine, Kyoto University, Graduate School of Medicine, Kyoto, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Satoshi Arakawa
- Department of Ophthalmology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan; Japan Community Health care Organization Kyushu Hospital, Fukuoka, Japan; Arakawa Eye Clinic, Fukuoka, Japan
| | - Maiko Maruyama-Inoue
- Department of Ophthalmology and Micro-technology, Yokohama City University, Yokohama, Japan
| | - Mikiko Endo
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Yusuke Iwasaki
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Kazuyoshi Ishigaki
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Nana Matoba
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina; UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan; Department of Genome Informatics, Graduate School of Medicine, University of Tokyo, Tokyo, Japan; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Miho Yasuda
- Department of Ophthalmology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan; Kurakazu Eye Clinic, Fukuoka, Japan
| | - Yuji Oshima
- Department of Ophthalmology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan; Section of Ophthalmology, Department of Medicine, Fukuoka Dental College, Fukuoka, Japan
| | - Shigeo Yoshida
- Department of Ophthalmology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan; Department of Ophthalmology, Kurume University School of Medicine, Fukuoka, Japan
| | - Shin-Ya Nakao
- Department of Ophthalmology and Visual Sciences, Kyoto University, Graduate School of Medicine, Kyoto, Japan
| | - Kazuya Morino
- Department of Ophthalmology and Visual Sciences, Kyoto University, Graduate School of Medicine, Kyoto, Japan
| | - Yuki Mori
- Department of Ophthalmology and Visual Sciences, Kyoto University, Graduate School of Medicine, Kyoto, Japan
| | - Ai Kido
- Department of Ophthalmology and Visual Sciences, Kyoto University, Graduate School of Medicine, Kyoto, Japan
| | - Aki Kato
- Department of Ophthalmology and Visual Science, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Tsutomu Yasukawa
- Department of Ophthalmology and Visual Science, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Ryo Obata
- Department of Ophthalmology, University of Tokyo School of Medicine, Tokyo, Japan
| | - Yoshimi Nagai
- Department of Ophthalmology, Kansai Medical University, Osaka, Japan
| | - Kanji Takahashi
- Department of Ophthalmology, Kansai Medical University, Osaka, Japan
| | - Kimihiko Fujisawa
- Japan Community Health care Organization Kyushu Hospital, Fukuoka, Japan
| | - Akiko Miki
- Department of Surgery, Division of Ophthalmology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Makoto Nakamura
- Department of Surgery, Division of Ophthalmology, Kobe University Graduate School of Medicine, Kobe, Japan
| | - Shigeru Honda
- Department of Surgery, Division of Ophthalmology, Kobe University Graduate School of Medicine, Kobe, Japan; Department of Ophthalmology and Visual Sciences, Osaka Metropolitan University Graduate School of Medicine, Osaka, Japan
| | - Hiroaki Ushida
- Department of Ophthalmology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Tetsuhiro Yasuma
- Department of Ophthalmology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Koji M Nishiguchi
- Department of Ophthalmology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Ryusaburo Mori
- Division of Ophthalmology, Nihon University School of Medicine, Tokyo, Japan
| | - Koji Tanaka
- Division of Ophthalmology, Nihon University School of Medicine, Tokyo, Japan
| | - Yu Wakatsuki
- Division of Ophthalmology, Nihon University School of Medicine, Tokyo, Japan
| | - Kenji Yamashiro
- Department of Ophthalmology and Visual Sciences, Kyoto University, Graduate School of Medicine, Kyoto, Japan; Department of Ophthalmology and Visual Science, Kochi Medical School, Kochi University, Kochi, Japan
| | - Kazuaki Kadonosono
- Department of Ophthalmology and Micro-technology, Yokohama City University, Yokohama, Japan
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Tatsuro Ishibashi
- Department of Ophthalmology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Akitaka Tsujikawa
- Department of Ophthalmology and Visual Sciences, Kyoto University, Graduate School of Medicine, Kyoto, Japan
| | - Koh-Hei Sonoda
- Department of Ophthalmology, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan; Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan; Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, Japan
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Watanabe T, Arisawa K, Nguyen TV, Ishizu M, Katsuura-Kamano S, Hishida A, Tamura T, Kato Y, Okada R, Ibusuki R, Koriyama C, Suzuki S, Otani T, Koyama T, Tomida S, Kuriki K, Takashima N, Miyagawa N, Wakai K, Matsuo K. Coffee and metabolic phenotypes: A cross-sectional analysis of the Japan multi-institutional collaborative cohort (J-MICC) study. Nutr Metab Cardiovasc Dis 2023; 33:620-630. [PMID: 36710119 DOI: 10.1016/j.numecd.2022.12.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 12/07/2022] [Accepted: 12/23/2022] [Indexed: 12/31/2022]
Abstract
BACKGROUND AND AIMS To date, the relationship between coffee consumption and metabolic phenotypes has hardly been investigated and remains controversial. Therefore, the aim of this cross-sectional study is to examine the associations between coffee consumption and metabolic phenotypes in a Japanese population. METHODS AND RESULTS We analyzed the data of 26,363 subjects (aged 35-69 years) in the baseline survey of the Japan Multi-Institutional Collaborative Cohort Study. Coffee consumption was assessed using a questionnaire. Metabolic Syndrome (MetS) was defined according to the Joint Interim Statement Criteria of 2009, using body mass index (BMI) instead of waist circumference. Subjects stratified by the presence or absence of obesity (normal weight: BMI <25 kg/m2; obesity: BMI ≥25 kg/m2) were classified by the number of MetS components (metabolically healthy: no components; metabolically unhealthy: one or more components) other than BMI. In multiple logistic regression analyses adjusted for sex, age, and other potential confounders, high coffee consumption (≥3 cups/day) was associated with a lower prevalence of MetS and metabolically unhealthy phenotypes both in normal weight (OR 0.83, 95% CI 0.76-0.90) and obese subjects (OR 0.83, 95% CI 0.69-0.99). Filtered/instant coffee consumption was inversely associated with the prevalence of MetS and metabolically unhealthy phenotypes, whereas canned/bottled/packed coffee consumption was not. CONCLUSION The present results suggest that high coffee consumption, particularly filtered/instant coffee, is inversely associated with the prevalence of metabolically unhealthy phenotypes in both normal weight and obese Japanese adults.
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Affiliation(s)
- Takeshi Watanabe
- Department of Preventive Medicine, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan.
| | - Kokichi Arisawa
- Department of Preventive Medicine, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan
| | - Tien Van Nguyen
- Department of Preventive Medicine, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan
| | - Masashi Ishizu
- Department of Preventive Medicine, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan
| | - Sakurako Katsuura-Kamano
- Department of Preventive Medicine, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan
| | - Asahi Hishida
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Takashi Tamura
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Yasufumi Kato
- 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
| | - Rie Ibusuki
- Department of International Island and Community Medicine, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan
| | - Chihaya Koriyama
- Department of Epidemiology and Preventive Medicine, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan
| | - Sadao Suzuki
- Department of Public Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Takahiro Otani
- Department of Public Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Teruhide Koyama
- Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Satomi Tomida
- Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan; Department of Endocrine and Breast Surgery, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Kiyonori Kuriki
- Laboratory of Public Health, Division of Nutritional Sciences, School of Food and Nutritional Sciences, University of Shizuoka, Shizuoka, Japan
| | - Naoyuki Takashima
- Department of Public Health, Faculty of Medicine, Kindai University, Osaka, Japan; Department of Public Health, Shiga University of Medical Science, Otsu, Japan
| | - Naoko Miyagawa
- Department of Public Health, Shiga University of Medical Science, Otsu, Japan; Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
| | - Kenji Wakai
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Keitaro Matsuo
- Division of Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan; Department of Cancer Epidemiology, Nagoya University Graduate School of Medicine, Nagoya, Japan
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29
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Deng Y, Huang J, Wong MCS. Associations of alcohol and coffee with colorectal cancer risk in East Asian populations: a Mendelian randomization study. Eur J Nutr 2023; 62:749-756. [PMID: 36239790 DOI: 10.1007/s00394-022-03002-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 09/07/2022] [Indexed: 11/26/2022]
Abstract
PURPOSE Previous observational studies have shown that alcohol and coffee were associated with colorectal cancer (CRC) risk, but the causal relationships have not been adequately explored. This study aimed to assess the potential causal associations of alcohol and coffee with CRC risk using Mendelian randomization (MR) analyses in an East Asian population. METHODS Publicly available summary-level genome-wide association studies data on ever/never alcohol drinker (n = 165,084), alcohol consumption (n = 58,610), coffee consumption (n = 152,634), and CRC (7062 cases and 195,745 controls) were obtained from the BioBank Japan (BBJ). Single-nucleotide polymorphisms (SNPs) that were significantly related to the exposures were identified as instrumental variables. Five, two, and six SNPs were used for ever/never alcohol drinkers, alcohol consumption, and coffee consumption, respectively. The inverse variance weighted method was used as the main MR method to calculate the odds ratios (ORs) and 95% confidence intervals (95% CIs) of CRC risk per one-unit change in exposures. RESULTS Genetically predicted ever/never alcohol drinkers (OR: 1.08; 95% CI 1.06, 1.11; P < 0.001) and alcohol consumption (OR: 1.39; 95% CI 1.21, 1.60; P < 0.001) were positively associated with CRC risk. Conversely, genetically predicted coffee consumption was inversely related to CRC risk, with an OR (95% CI) of 0.80 (0.64, 0.99) (P = 0.037). CONCLUSION Genetically predicted alcohol use and consumption were risk factors for CRC while genetically predicted coffee consumption was a protective factor. Our findings highlight the effectiveness of keeping healthy dietary habits to prevent CRC. Further studies with more valid SNPs and CRC cases are needed. Validation of our findings is also recommended.
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Affiliation(s)
- Yunyang Deng
- The Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, 999077, China
| | - Junjie Huang
- The Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, 999077, China
| | - Martin Chi Sang Wong
- The Jockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, 999077, China.
- School of Public Health, The Chinese Academy of Medical Sciences and the Peking Union Medical College, Beijing, 100000, China.
- School of Public Health, Peking University, Beijing, 100000, China.
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30
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Iwasaki T, Kamatani Y, Sonomura K, Kawaguchi S, Kawaguchi T, Takahashi M, Ohmura K, Sato TA, Matsuda F. Genetic influences on human blood metabolites in the Japanese population. iScience 2023; 26:105738. [PMID: 36582826 PMCID: PMC9792902 DOI: 10.1016/j.isci.2022.105738] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 10/08/2022] [Accepted: 12/01/2022] [Indexed: 12/12/2022] Open
Abstract
An increase in ethnic diversity in genetic studies has the potential to provide unprecedented insights into how genetic variations influence human phenotypes. In this study, we conducted a quantitative trait locus (QTL) analysis of 121 metabolites measured using gas chromatography-mass spectrometry with plasma samples from 4,888 Japanese individuals. We found 60 metabolite-gene associations, of which 13 have not been previously reported. Meta-analyses with another Japanese and a European study identified six and two additional unreported loci, respectively. Genetic variants influencing metabolite levels were more enriched in protein-coding regions than in the regulatory regions while being associated with the risk of various diseases. Finally, we identified a signature of strong negative selection for uric acid ( S ˆ = -1.53, p = 6.2 × 10-18). Our study expanded the knowledge of genetic influences on human blood metabolites, providing valuable insights into their physiological, pathological, and selective properties.
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Affiliation(s)
- Takeshi Iwasaki
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan.,Department of Rheumatology and Clinical Immunology, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Yoichiro Kamatani
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Kazuhiro Sonomura
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan.,Life Science Research Center, Shimadzu Corporation, Kyoto 604-8511, Japan
| | - Shuji Kawaguchi
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Takahisa Kawaguchi
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Meiko Takahashi
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Koichiro Ohmura
- Department of Rheumatology and Clinical Immunology, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
| | - Taka-Aki Sato
- Life Science Research Center, Shimadzu Corporation, Kyoto 604-8511, Japan
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
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31
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Genetic footprints of assortative mating in the Japanese population. Nat Hum Behav 2023; 7:65-73. [PMID: 36138222 PMCID: PMC9883156 DOI: 10.1038/s41562-022-01438-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2021] [Accepted: 07/20/2022] [Indexed: 02/03/2023]
Abstract
Assortative mating (AM) is a pattern characterized by phenotypic similarities between mating partners. Detecting the evidence of AM has been challenging due to the lack of large-scale datasets that include phenotypic data on both partners, especially in populations of non-European ancestries. Gametic phase disequilibrium between trait-associated alleles is a signature of parental AM on a polygenic trait, which can be detected even without partner data. Here, using polygenic scores for 81 traits in the Japanese population using BioBank Japan Project genome-wide association studies data (n = 172,270), we found evidence of AM on the liability to type 2 diabetes and coronary artery disease, as well as on dietary habits. In cross-population comparison using United Kingdom Biobank data (n = 337,139) we found shared but heterogeneous impacts of AM between populations.
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32
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Causal influence of dietary habits on the risk of major depressive disorder: A diet-wide Mendelian randomization analysis. J Affect Disord 2022; 319:482-489. [PMID: 36162666 DOI: 10.1016/j.jad.2022.09.109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 06/20/2022] [Accepted: 09/20/2022] [Indexed: 11/22/2022]
Abstract
BACKGROUND Extensive observational evidence links diet quality to the risk for major depressive disorder (MDD), while clinical trials show that dietary improvement can improve depressive symptoms. However, due to issues with blinding dietary trials, confirming a causal relationship for diet's influence on MDD requires further research. Thus, we systemically investigated the bi-directional causal relationships between dietary habits and MDD by using two-sample Mendelian randomization (MR). METHODS We collected publicly available genome-wide association studies' summary statistics for dietary habits from UK Biobank (n = 449,210) and MDD from the Psychiatric Genomics Consortium (n = 142,646). We used a weighted median approach to synthesize MR estimates across genetic instruments. For the robustness of our results, we compared weighted median results with results from the inverse-variance weighted, the weighted mode, and MR-PRESSO. RESULTS There was moderate evidence that beef intake has a protective effect on MDD. There was weak but detectable evidence that cereal intake has a protective effect on MDD, while non-oily fish intake might increase the risk of MDD. We did not observe any causal effect of MDD on dietary habits. LIMITATIONS Our study may suffer from the violation of assumptions of MR due to horizontal pleiotropy; therefore, we did several sensitivity analyses to detect and minimize the bias. CONCLUSIONS In this two-sample MR analysis, we observed that higher beef intake may be protective against MDD. However, MDD did not appear to affect dietary habits. Potential mechanisms need to be further investigated to support our novel findings.
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33
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TogoVar: A comprehensive Japanese genetic variation database. Hum Genome Var 2022; 9:44. [PMID: 36509753 PMCID: PMC9744889 DOI: 10.1038/s41439-022-00222-9] [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: 09/01/2022] [Revised: 11/03/2022] [Accepted: 11/07/2022] [Indexed: 12/14/2022] Open
Abstract
TogoVar ( https://togovar.org ) is a database that integrates allele frequencies derived from Japanese populations and provides annotations for variant interpretation. First, a scheme to reanalyze individual-level genome sequence data deposited in the Japanese Genotype-phenotype Archive (JGA), a controlled-access database, was established to make allele frequencies publicly available. As more Japanese individual-level genome sequence data are deposited in JGA, the sample size employed in TogoVar is expected to increase, contributing to genetic study as reference data for Japanese populations. Second, public datasets of Japanese and non-Japanese populations were integrated into TogoVar to easily compare allele frequencies in Japanese and other populations. Each variant detected in Japanese populations was assigned a TogoVar ID as a permanent identifier. Third, these variants were annotated with molecular consequence, pathogenicity, and literature information for interpreting and prioritizing variants. Here, we introduce the newly developed TogoVar database that compares allele frequencies among Japanese and non-Japanese populations and describes the integrated annotations.
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34
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Lazareva TE, Barbitoff YA, Changalidis AI, Tkachenko AA, Maksiutenko EM, Nasykhova YA, Glotov AS. Biobanking as a Tool for Genomic Research: From Allele Frequencies to Cross-Ancestry Association Studies. J Pers Med 2022; 12:2040. [PMID: 36556260 PMCID: PMC9783756 DOI: 10.3390/jpm12122040] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 11/19/2022] [Accepted: 11/28/2022] [Indexed: 12/14/2022] Open
Abstract
In recent years, great advances have been made in the field of collection, storage, and analysis of biological samples. Large collections of samples, biobanks, have been established in many countries. Biobanks typically collect large amounts of biological samples and associated clinical information; the largest collections include over a million samples. In this review, we summarize the main directions in which biobanks aid medical genetics and genomic research, from providing reference allele frequency information to allowing large-scale cross-ancestry meta-analyses. The largest biobanks greatly vary in the size of the collection, and the amount of available phenotype and genotype data. Nevertheless, all of them are extensively used in genomics, providing a rich resource for genome-wide association analysis, genetic epidemiology, and statistical research into the structure, function, and evolution of the human genome. Recently, multiple research efforts were based on trans-biobank data integration, which increases sample size and allows for the identification of robust genetic associations. We provide prominent examples of such data integration and discuss important caveats which have to be taken into account in trans-biobank research.
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Affiliation(s)
- Tatyana E. Lazareva
- Departemnt of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, 199034 St. Petersburg, Russia
- Department of Genetics and Biotechnology, St. Petersburg State University, 199034 St. Petersburg, Russia
| | - Yury A. Barbitoff
- Departemnt of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, 199034 St. Petersburg, Russia
- Department of Genetics and Biotechnology, St. Petersburg State University, 199034 St. Petersburg, Russia
| | - Anton I. Changalidis
- Departemnt of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, 199034 St. Petersburg, Russia
- Faculty of Software Engineering and Computer Systems, ITMO University, 197101 St. Petersburg, Russia
| | - Alexander A. Tkachenko
- Departemnt of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, 199034 St. Petersburg, Russia
| | - Evgeniia M. Maksiutenko
- Departemnt of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, 199034 St. Petersburg, Russia
| | - Yulia A. Nasykhova
- Departemnt of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, 199034 St. Petersburg, Russia
| | - Andrey S. Glotov
- Departemnt of Genomic Medicine, D.O. Ott Research Institute of Obstetrics, Gynaecology, and Reproductology, 199034 St. Petersburg, Russia
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35
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Igarashi M, Nogawa S, Hachiya T, Furukawa K, Takahashi S, Jia H, Saito K, Kato H. Association between Dietary Behaviors and BMI Stratified by Sex and the ALDH2 rs671 Polymorphism in Japanese Adults. Nutrients 2022; 14:nu14235116. [PMID: 36501145 PMCID: PMC9741124 DOI: 10.3390/nu14235116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 11/20/2022] [Accepted: 11/23/2022] [Indexed: 12/03/2022] Open
Abstract
The rs671 polymorphism, unique to East Asians, is well known to change the sensitivity to alcohol. Moreover, this polymorphism is associated not only with alcohol intake but also with several dietary behaviors (DBs), chronic diseases, and BMI, but the triadic association among the rs671 genotype, DBs, and BMI is unclear. This study included 12,271 Japanese subjects and aimed to observe this three-way association using the rs671 polymorphism, data of 56 DBs, and BMI. All analyses were stratified by participant sex. First, linear regression analyses resulted in significant associations between 18 and 21 DBs and BMI in males and females, respectively. Next, genetic heterogeneity was observed in all sub-groups via interaction analysis of the rs671 genotype stratified by drinking habits. Finally, we observed the characteristics of BMI-related DBs based on the rs671 genotype via stepwise regression analyses stratified by the rs671 genotype and drinking habits. Notably, positive associations were observed between lactobacillus beverage intake and BMI among participants with the rs671 polymorphism AA genotype in both sexes. This study suggests that the rs671 polymorphism modifies the association between DBs and BMI independently of drinking habits, providing evidence for the potential use of rs671 polymorphism information for precision nutrition with East Asians.
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Affiliation(s)
- Maki Igarashi
- Laboratory 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
| | - Shun Nogawa
- Research and Development Department, Genequest Inc., 5-29-11 Siba, Minato-ku, Tokyo 108-0014, Japan
| | - Tsuyoshi Hachiya
- Research and Development Department, Genequest Inc., 5-29-11 Siba, Minato-ku, Tokyo 108-0014, Japan
- Department of Genomic Data Analysis Service, Genome Analytics Japan Inc., 15-1-3205 Toyoshima-cho, Shinjuku-ku, Tokyo 162-0067, Japan
| | - Kyohei Furukawa
- Laboratory 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
| | - Shoko Takahashi
- Research and Development Department, Genequest Inc., 5-29-11 Siba, Minato-ku, Tokyo 108-0014, Japan
| | - Huijuan Jia
- Laboratory 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
- Laboratory 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
- Research and Development Department, Genequest Inc., 5-29-11 Siba, Minato-ku, Tokyo 108-0014, Japan
| | - Hisanori Kato
- Laboratory 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
- Correspondence: ; Tel.: +81-3-5841-1607
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36
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Maj C, Staerk C, Borisov O, Klinkhammer H, Wai Yeung M, Krawitz P, Mayr A. Statistical learning for sparser fine-mapped polygenic models: The prediction of LDL-cholesterol. Genet Epidemiol 2022; 46:589-603. [PMID: 35938382 DOI: 10.1002/gepi.22495] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 06/03/2022] [Accepted: 06/07/2022] [Indexed: 11/10/2022]
Abstract
Polygenic risk scores quantify the individual genetic predisposition regarding a particular trait. We propose and illustrate the application of existing statistical learning methods to derive sparser models for genome-wide data with a polygenic signal. Our approach is based on three consecutive steps. First, potentially informative loci are identified by a marginal screening approach. Then, fine-mapping is independently applied for blocks of variants in linkage disequilibrium, where informative variants are retrieved by using variable selection methods including boosting with probing and stochastic searches with the Adaptive Subspace method. Finally, joint prediction models with the selected variants are derived using statistical boosting. In contrast to alternative approaches relying on univariate summary statistics from genome-wide association studies, our three-step approach enables to select and fit multivariable regression models on large-scale genotype data. Based on UK Biobank data, we develop prediction models for LDL-cholesterol as a continuous trait. Additionally, we consider a recent scalable algorithm for the Lasso. Results show that statistical learning approaches based on fine-mapping of genetic signals result in a competitive prediction performance compared to classical polygenic risk approaches, while yielding sparser risk models.
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Affiliation(s)
- Carlo Maj
- Institute for Genomic Statistics and Bioinformatics, Medical Faculty, University Bonn, Bonn, Germany
- Centre for Human Genetics, University of Marburg, Marburg, Germany
| | - Christian Staerk
- Institute for Medical Biometry, Informatics and Epidemiology, Medical Faculty, University Bonn, Bonn, Germany
| | - Oleg Borisov
- Institute for Genomic Statistics and Bioinformatics, Medical Faculty, University Bonn, Bonn, Germany
| | - Hannah Klinkhammer
- Institute for Genomic Statistics and Bioinformatics, Medical Faculty, University Bonn, Bonn, Germany
- Institute for Medical Biometry, Informatics and Epidemiology, Medical Faculty, University Bonn, Bonn, Germany
| | - Ming Wai Yeung
- Institute for Genomic Statistics and Bioinformatics, Medical Faculty, University Bonn, Bonn, Germany
- Department of Cardiology, University of Groningen, Groningen, The Netherlands
| | - Peter Krawitz
- Institute for Genomic Statistics and Bioinformatics, Medical Faculty, University Bonn, Bonn, Germany
| | - Andreas Mayr
- Institute for Medical Biometry, Informatics and Epidemiology, Medical Faculty, University Bonn, Bonn, Germany
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37
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Tomofuji Y, Kishikawa T, Maeda Y, Ogawa K, Otake-Kasamoto Y, Kawabata S, Nii T, Okuno T, Oguro-Igashira E, Kinoshita M, Takagaki M, Oyama N, Todo K, Yamamoto K, Sonehara K, Yagita M, Hosokawa A, Motooka D, Matsumoto Y, Matsuoka H, Yoshimura M, Ohshima S, Shinzaki S, Nakamura S, Iijima H, Inohara H, Kishima H, Takehara T, Mochizuki H, Takeda K, Kumanogoh A, Okada Y. Prokaryotic and viral genomes recovered from 787 Japanese gut metagenomes revealed microbial features linked to diets, populations, and diseases. CELL GENOMICS 2022; 2:100219. [PMID: 36778050 PMCID: PMC9903723 DOI: 10.1016/j.xgen.2022.100219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 06/27/2022] [Accepted: 10/31/2022] [Indexed: 12/03/2022]
Abstract
We reconstructed 19,084 prokaryotic and 31,395 viral genomes from 787 Japanese gut metagenomes as Japanese metagenome-assembled genomes (JMAG) and Japanese Virus Database (JVD), which are large microbial genome datasets for a single population. Population-specific enrichment of the Bacillus subtilis and β-porphyranase among the JMAG could derive from the Japanese traditional food natto (fermented soybeans) and nori (laver), respectively. Dairy-related Enterococcus_B lactis and Streptococcus thermophilus were nominally associated with the East Asian-specific missense variant rs671:G>A in ALDH2, which was associated with dairy consumption. Of the species-level viral genome clusters in the JVD, 62.9% were novel. The β crAss-like phage composition was low among the Japanese but relatively high among African and Oceanian peoples. Evaluations of the association between crAss-like phages and diseases showed significant disease-specific associations. Our large catalog of virus-host pairs identified the positive correlation between the abundance of the viruses and their hosts.
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Affiliation(s)
- Yoshihiko Tomofuji
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita 565-0871, Japan,Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita 565-0871, Japan,Corresponding author
| | - Toshihiro Kishikawa
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita 565-0871, Japan,Department of Otorhinolaryngology-Head and Neck Surgery, Osaka University Graduate School of Medicine, Suita 565-0871, Japan,Department of Head and Neck Surgery, Aichi Cancer Center Hospital, Nagoya 464-8681, Japan
| | - Yuichi Maeda
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita 565-0871, Japan,Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan,Laboratory of Immune Regulation, Department of Microbiology and Immunology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Kotaro Ogawa
- Department of Neurology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Yuriko Otake-Kasamoto
- Department of Gastroenterology and Hepatology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Shuhei Kawabata
- Department of Neurosurgery, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Takuro Nii
- Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan,Laboratory of Immune Regulation, Department of Microbiology and Immunology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Tatsusada Okuno
- Department of Neurology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Eri Oguro-Igashira
- Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan,Laboratory of Immune Regulation, Department of Microbiology and Immunology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Makoto Kinoshita
- Department of Neurology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Masatoshi Takagaki
- Department of Neurosurgery, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Naoki Oyama
- Department of Stroke Medicine, Kawasaki Medical School, Kurashiki 701-0192, Japan
| | - Kenichi Todo
- Department of Neurology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Kenichi Yamamoto
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita 565-0871, Japan,Department of Pediatrics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan,Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita 565-0871, Japan
| | - Kyuto Sonehara
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita 565-0871, Japan,Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita 565-0871, Japan
| | - Mayu Yagita
- Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan,Laboratory of Immune Regulation, Department of Microbiology and Immunology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Akiko Hosokawa
- Department of Neurology, Suita Municipal Hospital, Suita 564-8567, Japan
| | - Daisuke Motooka
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita 565-0871, Japan,Department of Infection Metagenomics, Research Institute for Microbial Diseases, Osaka University, Suita 565-0871, Japan
| | - Yuki Matsumoto
- Department of Infection Metagenomics, Research Institute for Microbial Diseases, Osaka University, Suita 565-0871, Japan
| | - Hidetoshi Matsuoka
- Department of Rheumatology and Allergology, NHO Osaka Minami Medical Center, Kawachinagano 586-8521, Japan
| | - Maiko Yoshimura
- Department of Rheumatology and Allergology, NHO Osaka Minami Medical Center, Kawachinagano 586-8521, Japan
| | - Shiro Ohshima
- Department of Rheumatology and Allergology, NHO Osaka Minami Medical Center, Kawachinagano 586-8521, Japan
| | - Shinichiro Shinzaki
- Department of Gastroenterology and Hepatology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Shota Nakamura
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita 565-0871, Japan,Department of Infection Metagenomics, Research Institute for Microbial Diseases, Osaka University, Suita 565-0871, Japan
| | - Hideki Iijima
- Department of Gastroenterology and Hepatology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Hidenori Inohara
- Department of Otorhinolaryngology-Head and Neck Surgery, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Haruhiko Kishima
- Department of Neurosurgery, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Tetsuo Takehara
- Department of Gastroenterology and Hepatology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Hideki Mochizuki
- Department of Neurology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Kiyoshi Takeda
- Laboratory of Immune Regulation, Department of Microbiology and Immunology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan,WPI Immunology Frontier Research Center, Osaka University, Suita 565-0871, Japan
| | - Atsushi Kumanogoh
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita 565-0871, Japan,Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita 565-0871, Japan,Department of Immunopathology, Immunology Frontier Research Center, Osaka University, Suita 565-0871, Japan
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita 565-0871, Japan,Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita 565-0871, Japan,Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita 565-0871, Japan,Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Tsurumi 230-0045, Japan,Center for Infectious Disease Education and Research, Osaka University, Suita 565-0871, Japan,Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan,Corresponding author
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38
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Sugimoto M, Tabata H, Kaga H, Someya Y, Kakehi S, Abudurezake A, Naito H, Ito N, Shi H, Otsuka H, Umemura F, Yoshizawa Y, Kawamori R, Watada H, Tamura Y. Association of ALDH2 Genotypes and Alcohol Intake with Dietary Patterns: The Bunkyo Health Study. Nutrients 2022; 14:4830. [PMID: 36432517 PMCID: PMC9695626 DOI: 10.3390/nu14224830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 11/04/2022] [Accepted: 11/10/2022] [Indexed: 11/18/2022] Open
Abstract
Dietary habits are associated with various diseases and assessed by dietary patterns (DPs). Since the ALDH2 genotype is correlated with alcohol and several food preferences, this genotype is probably associated with DPs. In this cross-sectional study of 1612 elderly adults, we investigated the effects of the ALDH2 genotype on DPs and the mediating role of alcohol intake. We identified the ALDH2 genotype and conducted a dietary history survey, then used principal component analysis to determine DPs for each gender. We performed multiple regression analysis to determine the independent contribution of the ALDH2 genotype and alcohol intake to DP scores. We identified three DPs: the "Japanese side dish type" (DP1), the "Japanese dish with alcohol type" (DP2), and the "Western dish with alcohol type" (DP3). In men, the single nucleotide polymorphism ALDH2 rs671 was significantly associated with all DP scores. When alcohol intake was added as a covariate, ALDH2 rs671 was still significantly correlated with the DP2 score but not with the DP1 or DP3 score, and alcohol intake was significantly correlated with all DP scores. In women, ALDH2 rs671 was significantly associated with the DP2 and DP3 scores; however, after adding alcohol intake as a covariate, these associations disappeared, and alcohol intake significantly correlated with all DP scores. In conclusion, the ALDH2 genotype was associated with several DPs in elderly adults, but most associations were mediated by alcohol intake.
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Affiliation(s)
- Mari Sugimoto
- Department of Sports Medicine and Sportology, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Hiroki Tabata
- Sportology Center, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Hideyoshi Kaga
- Metabolism and Endocrinology, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Yuki Someya
- Sportology Center, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Saori Kakehi
- Department of Sports Medicine and Sportology, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
- Sportology Center, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Abulaiti Abudurezake
- Sportology Center, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Hitoshi Naito
- Metabolism and Endocrinology, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Naoaki Ito
- Metabolism and Endocrinology, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Huicong Shi
- Department of Sports Medicine and Sportology, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Hikaru Otsuka
- Department of Sports Medicine and Sportology, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Futaba Umemura
- Department of Sports Medicine and Sportology, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Yasuyo Yoshizawa
- Center for Healthy Life Expectancy, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Ryuzo Kawamori
- Department of Sports Medicine and Sportology, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
- Sportology Center, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
- Metabolism and Endocrinology, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
- Center for Healthy Life Expectancy, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Hirotaka Watada
- Sportology Center, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
- Metabolism and Endocrinology, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
| | - Yoshifumi Tamura
- Department of Sports Medicine and Sportology, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
- Sportology Center, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
- Metabolism and Endocrinology, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
- Center for Healthy Life Expectancy, Graduate School of Medicine, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
- Faculty of International Liberal Arts, Juntendo University, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421, Japan
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Zhou W, Kanai M, Wu KHH, Rasheed H, Tsuo K, Hirbo JB, Wang Y, Bhattacharya A, Zhao H, Namba S, Surakka I, Wolford BN, Lo Faro V, Lopera-Maya EA, Läll K, Favé MJ, Partanen JJ, Chapman SB, Karjalainen J, Kurki M, Maasha M, Brumpton BM, Chavan S, Chen TT, Daya M, Ding Y, Feng YCA, Guare LA, Gignoux CR, Graham SE, Hornsby WE, Ingold N, Ismail SI, Johnson R, Laisk T, Lin K, Lv J, Millwood IY, Moreno-Grau S, Nam K, Palta P, Pandit A, Preuss MH, Saad C, Setia-Verma S, Thorsteinsdottir U, Uzunovic J, Verma A, Zawistowski M, Zhong X, Afifi N, Al-Dabhani KM, Al Thani A, Bradford Y, Campbell A, Crooks K, de Bock GH, Damrauer SM, Douville NJ, Finer S, Fritsche LG, Fthenou E, Gonzalez-Arroyo G, Griffiths CJ, Guo Y, Hunt KA, Ioannidis A, Jansonius NM, Konuma T, Lee MTM, Lopez-Pineda A, Matsuda Y, Marioni RE, Moatamed B, Nava-Aguilar MA, Numakura K, Patil S, Rafaels N, Richmond A, Rojas-Muñoz A, Shortt JA, Straub P, Tao R, Vanderwerff B, Vernekar M, Veturi Y, Barnes KC, Boezen M, Chen Z, Chen CY, Cho J, Smith GD, Finucane HK, Franke L, Gamazon ER, Ganna A, Gaunt TR, Ge T, Huang H, Huffman J, Katsanis N, Koskela JT, Lajonchere C, Law MH, Li L, Lindgren CM, Loos RJF, MacGregor S, Matsuda K, Olsen CM, Porteous DJ, Shavit JA, Snieder H, Takano T, Trembath RC, Vonk JM, Whiteman DC, Wicks SJ, Wijmenga C, Wright J, Zheng J, Zhou X, Awadalla P, Boehnke M, Bustamante CD, Cox NJ, Fatumo S, Geschwind DH, Hayward C, Hveem K, Kenny EE, Lee S, Lin YF, Mbarek H, Mägi R, Martin HC, Medland SE, Okada Y, Palotie AV, Pasaniuc B, Rader DJ, Ritchie MD, Sanna S, Smoller JW, Stefansson K, van Heel DA, Walters RG, Zöllner S, Martin AR, Willer CJ, Daly MJ, Neale BM. Global Biobank Meta-analysis Initiative: Powering genetic discovery across human disease. CELL GENOMICS 2022; 2:100192. [PMID: 36777996 PMCID: PMC9903716 DOI: 10.1016/j.xgen.2022.100192] [Citation(s) in RCA: 99] [Impact Index Per Article: 49.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 06/19/2022] [Accepted: 09/09/2022] [Indexed: 11/05/2022]
Abstract
Biobanks facilitate genome-wide association studies (GWASs), which have mapped genomic loci across a range of human diseases and traits. However, most biobanks are primarily composed of individuals of European ancestry. We introduce the Global Biobank Meta-analysis Initiative (GBMI)-a collaborative network of 23 biobanks from 4 continents representing more than 2.2 million consented individuals with genetic data linked to electronic health records. GBMI meta-analyzes summary statistics from GWASs generated using harmonized genotypes and phenotypes from member biobanks for 14 exemplar diseases and endpoints. This strategy validates that GWASs conducted in diverse biobanks can be integrated despite heterogeneity in case definitions, recruitment strategies, and baseline characteristics. This collaborative effort improves GWAS power for diseases, benefits understudied diseases, and improves risk prediction while also enabling the nomination of disease genes and drug candidates by incorporating gene and protein expression data and providing insight into the underlying biology of human diseases and traits.
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Affiliation(s)
- Wei Zhou
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Masahiro Kanai
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Kuan-Han H Wu
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Humaira Rasheed
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Division of Medicine and Laboratory Sciences, University of Oslo, Oslo, Norway
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Bristol, UK
| | - Kristin Tsuo
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jibril B Hirbo
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ying Wang
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Arjun Bhattacharya
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Huiling Zhao
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Bristol, UK
| | - Shinichi Namba
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
| | - Ida Surakka
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA
| | - Brooke N Wolford
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
| | - Valeria Lo Faro
- University of Groningen, UMCG, Department of Ophthalmology, Groningen, the Netherlands
- Department of Clinical Genetics, Amsterdam University Medical Center (AMC), Amsterdam, the Netherlands
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | | | - Kristi Läll
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | | | - Juulia J Partanen
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Sinéad B Chapman
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Juha Karjalainen
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Mitja Kurki
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Mutaamba Maasha
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Ben M Brumpton
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger, Norway
- Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Sameer Chavan
- University of Colorado - Anschutz Medical Campus, Aurora, CO, USA
| | - Tzu-Ting Chen
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli, Taiwan
| | - Michelle Daya
- University of Colorado - Anschutz Medical Campus, Aurora, CO, USA
| | - Yi Ding
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
| | - Yen-Chen A Feng
- Division of Biostatistics, Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
| | - Lindsay A Guare
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Sarah E Graham
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA
| | - Whitney E Hornsby
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA
| | - Nathan Ingold
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- Faculty of Health, School of Biomedical Sciences, Queensland University of Technology, Brisbane, QLD, Australia
| | - Said I Ismail
- Qatar Genome Program, Qatar Foundation Research, Development and Innovation, Qatar Foundation, Doha, Qatar
| | - Ruth Johnson
- Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Triin Laisk
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Kuang Lin
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Iona Y Millwood
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | | | - Kisung Nam
- Graduate School of Data Science, Seoul National University, Seoul, South Korea
| | - Priit Palta
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Anita Pandit
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Michael H Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Chadi Saad
- Qatar Genome Program, Qatar Foundation Research, Development and Innovation, Qatar Foundation, Doha, Qatar
| | - Shefali Setia-Verma
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | | | - Anurag Verma
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, USA
| | - Matthew Zawistowski
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Xue Zhong
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nahla Afifi
- Qatar Biobank for Medical Research, Qatar Foundation for Education, Science, and Community, Doha, Qatar
| | - Kawthar M Al-Dabhani
- Qatar Biobank for Medical Research, Qatar Foundation for Education, Science, and Community, Doha, Qatar
| | - Asma Al Thani
- Qatar Biobank for Medical Research, Qatar Foundation for Education, Science, and Community, Doha, Qatar
| | - Yuki Bradford
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Kristy Crooks
- University of Colorado - Anschutz Medical Campus, Aurora, CO, USA
| | - Geertruida H de Bock
- Department of Epidemiology, University Medical Center Groningen, Groningen, the Netherlands
| | - Scott M Damrauer
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Corporal Michael Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Nicholas J Douville
- Department of Anesthesiology, Michigan Medicine, Ann Arbor, MI, USA
- Institute of Healthcare Policy & Innovation, University of Michigan, Ann Arbor, MI, USA
| | - Sarah Finer
- Wolfson Institute of Population Health, Queen Mary University of London, London, UK
| | - Lars G Fritsche
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Eleni Fthenou
- Qatar Biobank for Medical Research, Qatar Foundation for Education, Science, and Community, Doha, Qatar
| | | | | | - Yu Guo
- Chinese Academy of Medical Sciences, Beijing, China
| | - Karen A Hunt
- Blizard Institute, Queen Mary University of London, London, UK
| | - Alexander Ioannidis
- Galatea Bio, Inc., Hialeah, FL, USA
- Stanford University School of Medicine, Stanford, CA, USA
| | - Nomdo M Jansonius
- University of Groningen, UMCG, Department of Ophthalmology, Groningen, the Netherlands
| | - Takahiro Konuma
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
- Central Pharmaceutical Research Institute, Japan Tobacco, Inc., Takatsuki 569-1125, Japan
| | | | - Arturo Lopez-Pineda
- Galatea Bio, Inc., Hialeah, FL, USA
- Amphora Health, Morelia, Michoacan, Mexico
| | | | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | | | | | | | - Snehal Patil
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Nicholas Rafaels
- University of Colorado - Anschutz Medical Campus, Aurora, CO, USA
| | - Anne Richmond
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | | | | | - Peter Straub
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ran Tao
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Brett Vanderwerff
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | | | - Yogasudha Veturi
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Marike Boezen
- Department of Epidemiology, University Medical Center Groningen, Groningen, the Netherlands
| | - Zhengming Chen
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | | | - Judy Cho
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, Bristol, UK
| | - Hilary K Finucane
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Lude Franke
- University of Groningen, UMCG, Department of Genetics, Groningen, the Netherlands
| | - Eric R Gamazon
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Andrea Ganna
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Tom R Gaunt
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, Bristol, UK
| | - Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Hailiang Huang
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jennifer Huffman
- Centre for Population Genomics, VA Boston Healthcare System, Boston, MA, USA
| | | | - Jukka T Koskela
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Clara Lajonchere
- Institute of Precision Health, University of California, Los Angeles, Los Angeles, CA, USA
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Matthew H Law
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- Faculty of Health, School of Biomedical Sciences, Queensland University of Technology, Brisbane, QLD, Australia
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Cecilia M Lindgren
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Medicine and Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Stuart MacGregor
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Koichi Matsuda
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | | | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Jordan A Shavit
- University of Michigan, Department of Pediatrics, Ann Arbor, MI 48109, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Harold Snieder
- Department of Epidemiology, University Medical Center Groningen, Groningen, the Netherlands
| | | | - Richard C Trembath
- School of Basic and Medical Biosciences, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Judith M Vonk
- Department of Epidemiology, University Medical Center Groningen, Groningen, the Netherlands
| | - David C Whiteman
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Stephen J Wicks
- University of Colorado - Anschutz Medical Campus, Aurora, CO, USA
| | - Cisca Wijmenga
- University of Groningen, UMCG, Department of Genetics, Groningen, the Netherlands
| | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals National Health Service (NHS) Foundation Trust, Bradford, UK
| | - Jie Zheng
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Bristol, UK
| | - Xiang Zhou
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Philip Awadalla
- Ontario Institute for Cancer Research, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Carlos D Bustamante
- Galatea Bio, Inc., Hialeah, FL, USA
- Stanford University School of Medicine, Stanford, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Nancy J Cox
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Segun Fatumo
- The African Computational Genomics (TACG) Research Group, MRC/UVRI and LSHTM, Entebbe, Uganda
- London School of Hygiene & Tropical Medicine, London, UK
- Medical Research Council/Uganda Virus Research Institute/London School of Hygiene and Tropical Medicine (MRC/UVRI/LSHTM) Uganda Research Unit, Entebbe, Uganda
| | - Daniel H Geschwind
- Institute of Precision Health, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Levanger, Norway
| | - Eimear E Kenny
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Seunggeun Lee
- Graduate School of Data Science, Seoul National University, Seoul, South Korea
| | - Yen-Feng Lin
- Center for Neuropsychiatric Research, National Health Research Institutes, Miaoli, Taiwan
- Department of Public Health & Medical Humanities, School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Institute of Behavioral Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Hamdi Mbarek
- Qatar Genome Program, Qatar Foundation Research, Development and Innovation, Qatar Foundation, Doha, Qatar
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Hilary C Martin
- Human Genetics Programme, Wellcome Sanger Institute, Hinxton, UK
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita 565-0871, Japan
- Department of Genome Informatics, Graduate School of Medicine, The University of Tokyo, Tokyo 113-0033, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita 565-0871, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita 565-0871, Japan
| | - Aarno V Palotie
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Bogdan Pasaniuc
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
- Institute of Precision Health, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Daniel J Rader
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Marylyn D Ritchie
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Serena Sanna
- University of Groningen, UMCG, Department of Genetics, Groningen, the Netherlands
- Institute for Genetics and Biomedical Research (IRGB), National Research Council (CNR), Cagliari, Italy
| | - Jordan W Smoller
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Precision Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | | | | | - Robin G Walters
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- MRC Population Health Research Unit, University of Oxford, Oxford, UK
| | - Sebastian Zöllner
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Alicia R Martin
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Cristen J Willer
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Internal Medicine, Division of Cardiology, University of Michigan, Ann Arbor, MI, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Mark J Daly
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Benjamin M Neale
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
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40
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Li Y, Ye D, Zhou W, Liu B, Mao Y, Sun X. Alcohol consumption and colorectal cancer risk: A mendelian randomization study. Front Genet 2022; 13:967229. [PMID: 36212149 PMCID: PMC9540194 DOI: 10.3389/fgene.2022.967229] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Accepted: 08/26/2022] [Indexed: 11/24/2022] Open
Abstract
Background: Previous observational studies have provided inconsistent evidence for the association between alcohol consumption and the risk of colorectal cancer (CRC). To assess this potential causal effect, we performed bidirectional Mendelian randomization (MR) analysis. Methods: We selected six single nucleotide polymorphisms (SNPs) as instrumental variables (IVs) associated with alcohol consumption (ever versus never drinker) and two SNPs representing the number of drinks per week from a genome-wide association study (GWAS) of the Japanese population. Summary data for CRC were obtained from a GWAS meta-analysis in the Japanese population of 6,692 CRC cases and 27,178 controls. MR analysis was performed by the inverse-variance weighted (IVW) method primarily, supplemented with several sensitivity methods including the weighted median method, maximum likelihood method, MR pleiotropy residual sum and outlier (MR-PRESSO) test, MR-Egger regression, Causal Analysis Using Summary Effect estimates (CAUSE) method, as well as constrained maximum likelihood and model averaging and Bayesian information criterion (cML-MA-BIC) method. Multivariable Mendelian randomization (MMR) analyses were used to adjust for potential confounders. Reverse MR analyses were also performed to assess the potential causal effect of CRC on alcohol consumption. Results: Genetically predicted alcohol consumption (ever versus never drinker) was positively associated with the risk of CRC (odds ratio (OR) = 1.08, 95% confidence interval (CI): 1.05–1.12, p = 1.51 × 10–5 by IVW). The number of alcoholic drinks per week was also associated with an increased risk of CRC (OR = 1.39, 95%CI: 1.27–1.52, p = 5.29 × 10–13 by IVW). Sensitivity analysis yielded similar results. Reverse MR analyses found no evidence that CRC contributes to either ever drinkers (OR = 1.00, 95%CI: 0.99–1.00, p = 0.339 by IVW) or added number of drinks per week (OR = 1.01, 95%CI: 0.98–1.05, p = 0.545 by IVW). Conclusion: Our study suggested a potential causal association between alcohol consumption and the risk of CRC among Asians. Reducing drinking may be beneficial to the prevention and management of CRC.
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Affiliation(s)
| | | | | | | | | | - Xiaohui Sun
- *Correspondence: Yingying Mao, ; Xiaohui Sun,
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Saunders GRB, McGue M, Iacono WG, Vrieze S. Longitudinal effects and environmental moderation of ALDH2 and ADH1B gene variants on substance use from age 14 to 40. Dev Psychopathol 2022; 34:1-9. [PMID: 36102130 PMCID: PMC10011021 DOI: 10.1017/s0954579422000712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Alcohol use and dependence are strongly affected by variation in aldehyde dehydrogenase (ALDH2) and, to a lesser extent, alcohol dehydrogenase (ADH1B) genes. We use this genetic variation with an adoption design to test the causal role of alcohol use on other drug use, as well as the moderating role of adoptive parent, sibling, and peer alcohol use. Longitudinal models were run on 412 genotyped adopted individuals of East Asian ancestry with multiple assessments between ages 14 and 40. We found robust associations between alcohol frequency, quantity, and maximum drinks and ALDH2, but not ADH1B, status. The magnitude of the ALDH2 protective effect increased with age, particularly for maximum drinks, though estimates were smaller than previously reported in ancestrally similar individuals in East/North-East Asian countries. These results suggest that sociocultural factors in Minnesota may reduce the protective effects of ALDH2. We found that peer alcohol use, but not parent or sibling use, predicted adopted offspring's use, and that these environmental influences did not vary by ALDH2 status. Finally, we did not find strong evidence of associations between ALDH2 status and tobacco, marijuana, or illegal drug use, contrary to expectation if alcohol serves as a gateway to use of other drugs.
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Affiliation(s)
| | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, MN55455, USA
| | - William G Iacono
- Department of Psychology, University of Minnesota, Minneapolis, MN55455, USA
| | - Scott Vrieze
- Department of Psychology, University of Minnesota, Minneapolis, MN55455, USA
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Nakamura Y, Tamura T, Narita A, Shimizu A, Sutoh Y, Takashima N, Matsui K, Miyagawa N, Kadota A, Miura K, Otonari J, Ikezaki H, Hishida A, Nagayoshi M, Okada R, Kubo Y, Tanaka K, Shimanoe C, Ibusuki R, Nishimoto D, Oze I, Ito H, Ozaki E, Matsui D, Mikami H, Kusakabe M, Suzuki S, Watanabe M, Arisawa K, Katsuura-Kamano S, Kuriki K, Nakatochi M, Momozawa Y, Kubo M, Takeuchi K, Wakai K. A genome-wide association study on adherence to low-carbohydrate diets in Japanese. Eur J Clin Nutr 2022; 76:1103-1110. [PMID: 35132194 DOI: 10.1038/s41430-022-01090-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2021] [Revised: 01/19/2022] [Accepted: 01/24/2022] [Indexed: 11/09/2022]
Abstract
BACKGROUND/OBJECTIVES Low-carbohydrate diets (LCD) are useful for weight reduction, and 50-55% carbohydrate consumption is associated with minimal risk. Genetic differences were related to nutritional consumption, food preferences, and dietary patterns, but whether particular genetic differences in individuals influence LCD adherence is unknown. SUBJECTS/METHODS We conducted a GWAS on adherence to LCD utilizing 14,076 participants from the Japan Multi-Institutional Collaborative Cohort study. We used a previously validated semiquantitative food frequency questionnaire to estimate food consumption. Association of the imputed variants with the LCD score by Halton et al. we used linear regression analysis adjusting for sex, age, total dietary energy consumption, and components 1 to 10 by principal component analysis. We repeated the analysis with adjustment for alcohol consumption (g/day) in addition to the above-described variables. RESULTS Men and women combined analysis without adjustment for alcohol consumption; we found 395 variants on chromosome 12 associated with the LCD score having P values <5 × 10-8. A conditional analysis with the addition of the dosage data of rs671 on chromosome 12 as a covariate, P values for all 395 SNPs on chromosome 12 turned out to be insignificant. In the analysis with additional adjustment for alcohol consumption, we did not identify any SNPs associated with the LCD score. CONCLUSION We found rs671 was inversely associated with adherence to LCD, but that was strongly confounded by alcohol consumption.
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Affiliation(s)
- Yasuyuki Nakamura
- Department of Public Health, Shiga University of Medical Science, Otsu, Japan. .,Yamashina Racto Clinic and Medical Examination Center, Kyoto, Japan.
| | - Takashi Tamura
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Akira Narita
- Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan
| | - Atsushi Shimizu
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Shiwa-gun, Iwate, Japan.,Division of Biomedical Information Analysis, Institute for Biomedical Sciences, Iwate Medical University, Shiwa-gun, Iwate, Japan
| | - Yoichi Sutoh
- Division of Biomedical Information Analysis, Iwate Tohoku Medical Megabank Organization, Iwate Medical University, Shiwa-gun, Iwate, Japan
| | - Naoyuki Takashima
- Department of Public Health, Shiga University of Medical Science, Otsu, Japan.,Department of Public Health, Kindai University Faculty of Medicine, Osaka-Sayama, Japan
| | - Kenji Matsui
- Department of Public Health, Shiga University of Medical Science, Otsu, Japan.,Division of Bioethics and Healthcare Law, The National Cancer Center, Tokyo, Japan
| | - Naoko Miyagawa
- Department of Public Health, Shiga University of Medical Science, Otsu, Japan.,Department of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan
| | - Aya Kadota
- Department of Public Health, Shiga University of Medical Science, Otsu, Japan.,NCD Epidemiology Research Center, Shiga University of Medical Science, Otsu, Japan
| | - Katsuyuki Miura
- Department of Public Health, Shiga University of Medical Science, Otsu, Japan.,NCD Epidemiology Research Center, Shiga University of Medical Science, Otsu, Japan
| | - Jun Otonari
- Department of Psychosomatic Medicine, International University of Health and Welfare Narita Hospital, Narita, Japan.,Department of Psychosomatic Medicine, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | - Hiroaki Ikezaki
- Department of Comprehensive General Internal Medicine, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.,Department of General Internal Medicine, Kyushu University Hospital, Fukuoka, Japan
| | - Asahi Hishida
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Mako Nagayoshi
- 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
| | - Yoko Kubo
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Keitaro Tanaka
- Department of Preventive Medicine, Faculty of Medicine, Saga University, Saga, Japan
| | | | - Rie Ibusuki
- School of Health Sciences, Faculty of Medicine, Kagoshima University, Kagoshima, Japan
| | - Daisaku Nishimoto
- School of Health Sciences, Faculty of Medicine, Kagoshima University, Kagoshima, Japan.,Department of International Island and Community Medicine, Kagoshima University Graduate School of Medical and Dental Sciences, Kagoshima, Japan
| | - Isao Oze
- Division of Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan
| | - Hidemi Ito
- Division of Cancer Information and Control, Aichi Cancer Center Research Institute, Nagoya, Japan.,Division of Descriptive Cancer Epidemiology, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Etsuko Ozaki
- Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Daisuke Matsui
- Department of Epidemiology for Community Health and Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Haruo Mikami
- Cancer Prevention Center, Chiba Cancer Center Research Institute, Chiba, Japan
| | - Miho Kusakabe
- 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
| | - Miki Watanabe
- Department of Public Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan
| | - Kokichi Arisawa
- Department of Preventive Medicine, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan
| | - Sakurako Katsuura-Kamano
- Department of Preventive Medicine, Tokushima University Graduate School of Biomedical Sciences, Tokushima, Japan
| | - Kiyonori Kuriki
- Laboratory of Public Health, Division of Nutritional Sciences, School of Food and Nutritional Sciences, University of Shizuoka, Shizuoka, Japan
| | - Masahiro Nakatochi
- Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Michiaki Kubo
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Kenji Takeuchi
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Kenji Wakai
- Department of Preventive Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
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43
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Deng Y, Huang J, Wong MCS. Associations between six dietary habits and risk of hepatocellular carcinoma: A Mendelian randomization study. Hepatol Commun 2022; 6:2147-2154. [PMID: 35670026 PMCID: PMC9315115 DOI: 10.1002/hep4.1960] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 03/10/2022] [Accepted: 03/26/2022] [Indexed: 11/08/2022] Open
Abstract
Diet is reported to be associated with hepatocellular carcinoma (HCC), but whether there is a causal relationship remains unclear. This study aimed to explore the potential causal associations between dietary habits and HCC risk using Mendelian randomization in an East Asian population. From the BioBank Japan, we obtained summary-level genome-wide association studies data for the following six dietary habits: ever/never drinker (n = 165,084), alcohol consumption (n = 58,610), coffee consumption (n = 152,634), tea consumption (n = 152,653), milk consumption (n = 152,965), and yoghurt consumption (n = 152,097). We also obtained data on HCC (1866 cases and 195,745 controls). Single-nucleotide polymorphisms (SNPs) that were associated with exposures (p < 5 × 10-8 ) were selected as instrumental variables (IVs). Five, two, and six SNPs were identified for ever/never drinkers, alcohol consumption, and coffee consumption. One SNP was used for consumption of tea, milk, and yoghurt. The odds ratios (ORs) and 95% confidence intervals (CIs) were calculated by inverse variance weighted (for an IV with more than one SNP) or Wald ratio (for an IV with one SNP). Ever/never drinkers (OR, 1.11; 95% CI, 1.05-1.18; p < 0.001) and alcohol consumption (OR, 1.57; 95% CI, 1.32-1.86; p < 0.001) were positively associated with HCC risk. Conversely, coffee consumption was inversely related to HCC risk (OR, 0.69; 95% CI, 0.53-0.90; p = 0.007). Similar inverse associations were observed for consumption of tea, milk, and yoghurt, with ORs (95% CIs) of 0.11 (0.05-0.26), 0.18 (0.09-0.34), and 0.18 (0.09-0.34), respectively (all p < 0.001). Conclusion: There are potential causal associations between six dietary habits and HCC risk. Our findings inform clinical practice by providing evidence on the impact of dietary habits on HCC.
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Affiliation(s)
- Yunyang Deng
- The Jockey Club School of Public Health and Primary CareFaculty of MedicineChinese University of Hong KongHong Kong SARChina
| | - Junjie Huang
- The Jockey Club School of Public Health and Primary CareFaculty of MedicineChinese University of Hong KongHong Kong SARChina
| | - Martin C S Wong
- The Jockey Club School of Public Health and Primary CareFaculty of MedicineChinese University of Hong KongHong Kong SARChina.,School of Public HealthChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina.,School of Public HealthPeking UniversityBeijingChina
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44
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Abstract
The association between a dietary pattern characterised by high alcohol intake and dyslipidaemia has not been fully investigated. Therefore, the present study aimed to investigate the association between alcohol dietary patterns and the prevalence of dyslipidaemia and its components. This cross-sectional study enrolled 2171 men and women aged ≥40 years who were alumni of a Japanese university. To identify dietary patterns, a principal component analysis was performed based on the energy-adjusted food intake estimated by a brief-type self-administered diet history questionnaire. Three dietary patterns were identified, the second of which was named the alcohol dietary pattern and was characterised by a high intake of alcoholic beverages, liver, chicken and fish. This alcohol dietary pattern was associated with reduced LDL-cholesterol levels. The fully adjusted OR (95 % CI) of high LDL-cholesterol for the lowest through highest quartile of alcohol dietary pattern score were 1·00 (reference), 0·83 (0·64, 1·08), 0·84 (0·64, 1·10) and 0·68 (0·49, 0·94), respectively. Subgroup analysis showed that the alcohol dietary pattern was inversely associated with the prevalence of dyslipidaemia in women, whereas it was positively associated with high TAG levels in men. In conclusion, the alcohol dietary pattern, characterised by a high intake of alcoholic beverages, liver, chicken and fish, was associated with the prevalence of dyslipidaemia and its components. This finding provides useful information for the prevention and treatment of dyslipidaemia by modifying the diet.
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45
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Abstract
The ALDH2*2 missense variant that commonly causes alcohol flushing reactions is the single genetic polymorphism associated with the largest number of traits in humans. The dysfunctional ALDH2 variant affects nearly 8% of the world population and is highly concentrated among East Asians. Carriers of the ALDH2*2 variant commonly present alterations in a number of blood biomarkers, clinical measurements, biometrics, drug prescriptions, dietary habits and lifestyle behaviors, and they are also more susceptible to aldehyde-associated diseases, such as cancer and cardiovascular disease. However, the interaction between alcohol and ALDH2-related pathology is not clearly delineated. Furthermore, genetic evidence indicates that the ALDH2*2 variant has been favorably selected for in the past 2000-3000 years. It is therefore necessary to consider the disease risk and mechanism associated with ALDH2 deficiency, and to understand the possible beneficial or protective effect conferred by ALDH2 deficiency and whether the pleiotropic effects of ALDH2 variance are all mediated by alcohol use.
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Affiliation(s)
- Che-Hong Chen
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | | | - Daria Mochly-Rosen
- Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA 94305, USA
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46
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Genome-wide association and Mendelian randomization study of blood copper levels and 213 deep phenotypes in humans. Commun Biol 2022; 5:405. [PMID: 35501403 PMCID: PMC9061855 DOI: 10.1038/s42003-022-03351-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 04/10/2022] [Indexed: 11/29/2022] Open
Abstract
Metal elements are present in the human body, and their levels in the blood have important impacts on health. In this study, 2488 Chinese individuals were included in a genome-wide association study of 21 serum metal levels, with approximately 179,000 East Asian individuals in a bidirectional two-sample Mendelian randomization (MR) analysis, and 628,000 Europeans in a two-sample MR analysis. We identified two single nucleotide polymorphisms (SNPs) rs35691438 and rs671 that were significantly associated with serum copper levels (SCLs). The bidirectional two-sample MR analysis in the East Asian population showed that gamma-glutamyl transpeptidase levels have a causal effect on SCLs. SCLs have causal effects on six outcomes, namely risks of esophageal varix, glaucoma, sleep apnea syndrome, and systemic lupus erythematosus, white blood cell count, and usage of drugs affecting bone structure and mineralization. The two-sample MR analyses in the European population showed causal effects of erythrocyte copper levels on risks of carpal tunnel syndrome and compression fracture. Our results provide original insights into the causal relationship between blood metal levels and multiple human phenotypes. A genome-wide association study in a Chinese population identifies SNPs associated with serum copper levels. Mendelian randomization analysis reveals causal effects on multiple human phenotypes in East Asian and European populations.
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47
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Feng G, Feng H, Qi Y, Wang T, Ni N, Wu J, Yuan H. Interaction analysis between germline genetic variants and somatic mutations in head and neck cancer. Oral Oncol 2022; 128:105859. [DOI: 10.1016/j.oraloncology.2022.105859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 03/24/2022] [Accepted: 04/05/2022] [Indexed: 10/18/2022]
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48
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Fujita K, Matsushita M, Banno E, De Velasco MA, Hatano K, Nonomura N, Uemura H. Gut microbiome and prostate cancer. Int J Urol 2022; 29:793-798. [PMID: 35388531 DOI: 10.1111/iju.14894] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 03/23/2022] [Indexed: 12/16/2022]
Abstract
The gut microbiome is linked to several diseases such as Alzheimer's disease, rheumatoid arthritis, and colon cancer. The gut microbiome is also associated with the modulation of immune function, resulting in a different response to immune checkpoint therapy. The gut microbiome differs according to lifestyle, diet, sex, race, genetic background, and country. Lifestyle, especially diet, plays an important role in the development and progression of prostate cancer. Recent studies have revealed a connection between the gut microbiome and prostate cancer. A high-fat diet causes gut dysbiosis and gut bacterial metabolites, such as short-chain fatty acids and phospholipids that enter systemic circulation result in promoting prostate cancer growth. Additionally, the gut microbiota can serve as a source of testosterone, which affects prostate cancer progression. Men with castration-resistant prostate cancer have an increased abundance of gut bacteria with androgenic functions. Men with high-risk prostate cancer share a specific gut microbial profile and profiling gut microbiota could be a potentially effective tool to screen men with high-risk prostate cancer. Lifestyle modifications can improve the gut microbiome. Furthermore, altering the gut microbiome using prebiotic or probiotic interventions may prevent or delay prostate cancer development. Further study into the "Gut-Prostate Axis" would help in the discovery of new strategies for the prevention, screening, and treatment of prostate cancer.
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Affiliation(s)
- Kazutoshi Fujita
- Department of Urology, Kindai University Faculty of Medicine, Osakasayama, Japan
| | - Makoto Matsushita
- Department of Urology, Osaka University Graduate School of Medicine, Suita, Japan
| | - Eri Banno
- Department of Urology, Kindai University Faculty of Medicine, Osakasayama, Japan
| | - Marco A De Velasco
- Department of Genome Biology, Kindai University Faculty of Medicine, Osakasayama, Osaka, Japan
| | - Koji Hatano
- Department of Urology, Osaka University Graduate School of Medicine, Suita, Japan
| | - Norio Nonomura
- Department of Urology, Osaka University Graduate School of Medicine, Suita, Japan
| | - Hirotsugu Uemura
- Department of Urology, Kindai University Faculty of Medicine, Osakasayama, Japan
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49
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Shirai Y, Nakayama A, Kawamura Y, Toyoda Y, Nakatochi M, Shimizu S, Shinomiya N, Okada Y, Matsuo H. Coffee Consumption Reduces Gout Risk Independently of Serum Uric Acid Levels: Mendelian Randomization Analyses Across Ancestry Populations. ACR Open Rheumatol 2022; 4:534-539. [PMID: 35348303 PMCID: PMC9190218 DOI: 10.1002/acr2.11425] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 01/16/2022] [Accepted: 01/26/2022] [Indexed: 12/02/2022] Open
Abstract
Objective The effects of coffee consumption on serum uric acid (SUA) levels and gout risk are controversial. There have hitherto been no reports based on Mendelian randomization (MR) analysis of its effects that consider pleiotropy. Here, we evaluated the effects of coffee consumption across ancestry populations, taking pleiotropy into account. Methods We performed the first MR analyses for coffee consumption on SUA levels and gout, considering pleiotropy. We used the following summary statistics of genome‐wide association studies from a Japanese population: habitual coffee consumption (152,634 subjects), gout (3053 cases and 4554 controls), and SUA levels (121,745 subjects). In addition to fixed‐effect inverse variance weighted (IVW) meta‐analysis, we performed a robust evaluation of heterogeneity and removed several instruments for reasons of possible pleiotropy. Previous European datasets were also reevaluated while heterogeneity was considered. Results Habitual coffee consumption was significantly and inversely associated with gout (odds ratio [OR] = 0.29, 95% confidence interval [95% CI]: 0.16‐0.51, P = 1.9 × 10−5) in random‐effect IVW (Phet = 5.5 × 10−19). Excluding pleiotropic instruments, the protective effect on gout was confirmed in fixed‐effect IVW analysis (OR = 0.75, 95% CI: 0.58‐0.97, P = 0.026) without heterogeneity (Phet = 0.39). However, we observed no significance in the previous European datasets when heterogeneity was considered. Associations were not observed between coffee consumption and SUA levels in either ancestry in MR analyses that considered pleiotropy. Multivariable MR analysis showed that increased coffee consumption significantly reduced gout risk, even after adjusting for SUA levels (OR = 0.50, 95% CI: 0.31‐0.81, P = 0.0046). Conclusion With pleiotropy taken into account, our MR analyses revealed that coffee consumption can causally reduce gout risk, and that it may reduce gout risk independently of SUA levels.
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Affiliation(s)
- Yuya Shirai
- Osaka University Graduate School of Medicine, Suita, Japan
| | | | | | - Yu Toyoda
- National Defense Medical College, Tokorozawa, Japan
| | | | | | | | - Yukinori Okada
- Osaka University Graduate School of Medicine and Osaka University, Suita, Japan, and RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
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50
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Sasaki K. Diversity of Japanese consumers' requirements, sensory perceptions, and eating preferences for meat. Anim Sci J 2022; 93:e13705. [PMID: 35266248 PMCID: PMC9287063 DOI: 10.1111/asj.13705] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 02/18/2022] [Accepted: 02/24/2022] [Indexed: 02/05/2023]
Abstract
Japanese consumers are generally characterized as preferring high marbling in beef and pork and choosing domestic products. However, the Japanese food market is not homogenous. Understanding the diversity of Japanese consumers will provide benefits for the optimization of meat production and distribution in Japan. This article focuses on three factors affecting purchasing decisions and eating satisfaction, namely, requirements, sensory perception, and eating preferences, in order to understand the diversity of Japanese consumers in a simplified manner. Diversity was observed in Japanese consumers in all three of these factors (requirements, perception, and preference) using a questionnaire survey, sensory and biological procedures, and an eating preference test. These diversities are due to not only sociodemographic characteristics but also biological and physiological factors, background culture, and individual attitudes and criteria. Although consumer variation based on sociodemographic characteristics is of course important, it is equally important to understand diversity by focusing on the individual differences among consumers.
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Affiliation(s)
- Keisuke Sasaki
- Animal Products Research Group, Institute of Livestock and Grassland Science, National Agriculture and Food Research Organization, Tsukuba, Japan
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