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Matsumoto A. The Bidirectional Effect of Defective ALDH2 Polymorphism and Disease Prevention. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019; 1193:69-87. [PMID: 31368098 DOI: 10.1007/978-981-13-6260-6_4] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Despite the role of aldehyde dehydrogenase 2 (ALDH2) in the detoxification of endogenous aldehydes, the defective polymorphism (rs671), which is highly prevalent among East Asians, does not show a serious phenotype, such as congenital abnormality. However, unfavorable and favorable impacts of the variant allele, ALDH2*2, on various disease risks have been reported. The underlying mechanisms are often complicated due to the compensatory aldehyde detoxification systems. As the phenotypes emerge due to overlapping environmental factors (e.g., alcohol intake and tobacco smoke) or individual vulnerabilities (e.g., aging and apolipoprotein E ε4 allele), polymorphism is therefore considered to be important in the field of preventative medicine. For example, it is important to recognize that ALDH2*2 carriers are at a high risk of alcohol drinking-related cancers; however, their drinking habit has less adverse effects on physiological indices, such as blood pressure, body mass index, levels of lipids, and hepatic deviation enzymes in the blood, than in non-ALDH2*2 carriers. Therefore, opportunities to reconsider their excessive drinking habit before adverse events occur can be missed. To perform effective disease prevention, the effects of ALDH2*2 on various diseases and the biological mechanisms should be clarified.
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Affiliation(s)
- Akiko Matsumoto
- Department of Social Medicine, Saga University School of Medicine, Saga, Japan.
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52
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Naimi TS. Comment on Rehm: Alcohol, cohort studies and all-cause mortality: Where to from here? Drug Alcohol Rev 2018; 38:9-10. [PMID: 30588738 DOI: 10.1111/dar.12892] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Accepted: 12/05/2018] [Indexed: 12/15/2022]
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53
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Yun KE, Chang Y, Yun SC, Davey Smith G, Ryu S, Cho SI, Chung EC, Shin H, Khang YH. Alcohol and coronary artery calcification: an investigation using alcohol flushing as an instrumental variable. Int J Epidemiol 2018; 46:950-962. [PMID: 28073952 DOI: 10.1093/ije/dyw237] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/27/2016] [Indexed: 01/21/2023] Open
Abstract
Background We examined whether alcohol flushing could be used as an instrumental variable (IV) and investigated the effect of alcohol consumption on coronary calcification using alcohol flushing status as an IV. Methods We analysed cross-sectional data from 24 681 Korean adults (20 696 men and 3985 women) who had been administered a questionnaire assessing alcohol consumption and alcohol flushing, as well as a coronary artery calcium (CAC) measurement. The associations of alcohol flushing status with potential confounders and alcohol consumption were examined. We employed two-stage predictor substitution methodology for the IV analysis. Results The prevalence of alcohol flushing did not differ depending on gender, education, household income, cigarette smoking or physical activity. Balanced levels of confounders were observed between alcohol flushers and non-flushers. Alcohol flushing was closely related to alcohol consumption and levels of liver enzymes. In men, a doubling in alcohol consumption was associated with increased odds of coronary calcification in both the IV analysis [odds ratio (OR) of CAC scores of 1 or over = 1.11; 95% confidence interval (CI) = 1.03-1.20) and the multivariable regression analysis (OR = 1.04; 95% CI = 1.01-1.07). For cardiovascular risk factors, the IV analysis showed a positive association between alcohol consumption and blood pressure and high-density lipoprotein-cholesterol. Conclusions Alcohol flushing can be used as an IV in studies evaluating the health impact of alcohol consumption, especially in East Asian countries. Through such an analysis, we found that increased alcohol consumption was associated with an increased risk of subclinical coronary atherosclerosis.
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Affiliation(s)
| | - Yoosoo Chang
- Center for Cohort Studies, Total Healthcare Center.,Department of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Sung-Cheol Yun
- Department of Clinical Epidemiology and Biostatistics, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - George Davey Smith
- MRC Integrative Epidemiology Unit.,School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Seungho Ryu
- Center for Cohort Studies, Total Healthcare Center.,Department of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Sung-Il Cho
- Department of Epidemiology, Graduate School of Public Health and Institute of Health and Environment, Seoul National University, Seoul, South Korea
| | | | - Hocheol Shin
- Department of Family Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Young-Ho Khang
- Department of Health Policy and Management, Seoul National University College of Medicine, and Institute of Health Policy and Management, Seoul National University Medical Research Center, Seoul, South Korea
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54
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Cornelis MC, Munafo MR. Mendelian Randomization Studies of Coffee and Caffeine Consumption. Nutrients 2018; 10:E1343. [PMID: 30241358 PMCID: PMC6213346 DOI: 10.3390/nu10101343] [Citation(s) in RCA: 52] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Revised: 09/12/2018] [Accepted: 09/17/2018] [Indexed: 12/26/2022] Open
Abstract
Habitual coffee and caffeine consumption has been reported to be associated with numerous health outcomes. This perspective focuses on Mendelian Randomization (MR) approaches for determining whether such associations are causal. Genetic instruments for coffee and caffeine consumption are described, along with key concepts of MR and particular challenges when applying this approach to studies of coffee and caffeine. To date, at least fifteen MR studies have investigated the causal role of coffee or caffeine use on risk of type 2 diabetes, cardiovascular disease, Alzheimer's disease, Parkinson's disease, gout, osteoarthritis, cancers, sleep disturbances and other substance use. Most studies provide no consistent support for a causal role of coffee or caffeine on these health outcomes. Common study limitations include low statistical power, potential pleiotropy, and risk of collider bias. As a result, in many cases a causal role cannot confidently be ruled out. Conceptual challenges also arise from the different aspects of coffee and caffeine use captured by current genetic instruments. Nevertheless, with continued genome-wide searches for coffee and caffeine related loci along with advanced statistical methods and MR designs, MR promises to be a valuable approach to understanding the causal impact that coffee and caffeine have in human health.
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Affiliation(s)
- Marilyn C Cornelis
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA.
| | - Marcus R Munafo
- MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, UK Centre for Tobacco and Alcohol Studies, School of Psychological Science, University of Bristol, Bristol BS8 1TU, UK.
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55
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Burgess S, Foley CN, Zuber V. Inferring Causal Relationships Between Risk Factors and Outcomes from Genome-Wide Association Study Data. Annu Rev Genomics Hum Genet 2018; 19:303-327. [PMID: 29709202 PMCID: PMC6481551 DOI: 10.1146/annurev-genom-083117-021731] [Citation(s) in RCA: 138] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
An observational correlation between a suspected risk factor and an outcome does not necessarily imply that interventions on levels of the risk factor will have a causal impact on the outcome (correlation is not causation). If genetic variants associated with the risk factor are also associated with the outcome, then this increases the plausibility that the risk factor is a causal determinant of the outcome. However, if the genetic variants in the analysis do not have a specific biological link to the risk factor, then causal claims can be spurious. We review the Mendelian randomization paradigm for making causal inferences using genetic variants. We consider monogenic analysis, in which genetic variants are taken from a single gene region, and polygenic analysis, which includes variants from multiple regions. We focus on answering two questions: When can Mendelian randomization be used to make reliable causal inferences, and when can it be used to make relevant causal inferences?
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Affiliation(s)
- Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge CB2 0SR, United Kingdom;
- Cardiovascular Epidemiology Unit, University of Cambridge, Cambridge CB1 8RN, United Kingdom
| | - Christopher N Foley
- MRC Biostatistics Unit, University of Cambridge, Cambridge CB2 0SR, United Kingdom;
| | - Verena Zuber
- MRC Biostatistics Unit, University of Cambridge, Cambridge CB2 0SR, United Kingdom;
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56
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O'Neill D, Britton A, Hannah MK, Goldberg M, Kuh D, Khaw KT, Bell S. Association of longitudinal alcohol consumption trajectories with coronary heart disease: a meta-analysis of six cohort studies using individual participant data. BMC Med 2018; 16:124. [PMID: 30131059 PMCID: PMC6103865 DOI: 10.1186/s12916-018-1123-6] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Accepted: 07/10/2018] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Studies have shown that alcohol intake trajectories differ in their associations with biomarkers of cardiovascular functioning, but it remains unclear if they also differ in their relationship to actual coronary heart disease (CHD) incidence. Using multiple longitudinal cohort studies, we evaluated the association between long-term alcohol consumption trajectories and CHD. METHODS Data were drawn from six cohorts (five British and one French). The combined analytic sample comprised 35,132 individuals (62.1% male; individual cohorts ranging from 869 to 14,247 participants) of whom 4.9% experienced an incident (fatal or non-fatal) CHD event. Alcohol intake across three assessment periods of each cohort was used to determine participants' intake trajectories over approximately 10 years. Time to onset for (i) incident CHD and (ii) fatal CHD was established using surveys and linked medical record data. A meta-analysis of individual participant data was employed to estimate the intake trajectories' association with CHD onset, adjusting for demographic and clinical characteristics. RESULTS Compared to consistently moderate drinkers (males: 1-168 g ethanol/week; females: 1-112 g ethanol/week), inconsistently moderate drinkers had a significantly greater risk of incident CHD [hazard ratio (HR) = 1.18, 95% confidence interval (CI) = 1.02-1.37]. An elevated risk of incident CHD was also found for former drinkers (HR = 1.31, 95% CI = 1.13-1.52) and consistent non-drinkers (HR = 1.47, 95% CI = 1.21-1.78), although, after sex stratification, the latter effect was only evident for females. When examining fatal CHD outcomes alone, only former drinkers had a significantly elevated risk, though hazard ratios for consistent non-drinkers were near identical. No evidence of elevated CHD risk was found for consistently heavy drinkers, and a weak association with fatal CHD for inconsistently heavy drinkers was attenuated following adjustment for confounding factors. CONCLUSIONS Using prospectively recorded alcohol data, this study has shown how instability in drinking behaviours over time is associated with risk of CHD. As well as individuals who abstain from drinking (long term or more recently), those who are inconsistently moderate in their alcohol intake have a higher risk of experiencing CHD. This finding suggests that policies and interventions specifically encouraging consistency in adherence to lower-risk drinking guidelines could have public health benefits in reducing the population burden of CHD. The absence of an effect amongst heavy drinkers should be interpreted with caution given the known wider health risks associated with such intake. TRIAL REGISTRATION ClinicalTrials.gov, NCT03133689 .
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Affiliation(s)
- Dara O'Neill
- CLOSER, Department of Social Science, Institute of Education, University College London, London, UK.
| | - Annie Britton
- Research Department of Epidemiology and Public Health, University College London, London, UK
| | - Mary K Hannah
- MRC/CSO Social and Public Health Sciences Unit, Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Marcel Goldberg
- Inserm UMS 011, Villejuif, France and Paris Descartes University, Villejuif, France
| | - Diana Kuh
- Research Department of Epidemiology and Public Health, University College London, London, UK
- UK MRC Unit for Lifelong Health & Ageing at UCL, London, UK
| | - Kay Tee Khaw
- Cambridge Institute of Public Health, University of Cambridge, Cambridge, UK
| | - Steven Bell
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
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57
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Wood AM, Kaptoge S, Butterworth AS, Willeit P, Warnakula S, Bolton T, Paige E, Paul DS, Sweeting M, Burgess S, Bell S, Astle W, Stevens D, Koulman A, Selmer RM, Verschuren WMM, Sato S, Njølstad I, Woodward M, Salomaa V, Nordestgaard BG, Yeap BB, Fletcher A, Melander O, Kuller LH, Balkau B, Marmot M, Koenig W, Casiglia E, Cooper C, Arndt V, Franco OH, Wennberg P, Gallacher J, de la Cámara AG, Völzke H, Dahm CC, Dale CE, Bergmann MM, Crespo CJ, van der Schouw YT, Kaaks R, Simons LA, Lagiou P, Schoufour JD, Boer JMA, Key TJ, Rodriguez B, Moreno-Iribas C, Davidson KW, Taylor JO, Sacerdote C, Wallace RB, Quiros JR, Tumino R, Blazer DG, Linneberg A, Daimon M, Panico S, Howard B, Skeie G, Strandberg T, Weiderpass E, Nietert PJ, Psaty BM, Kromhout D, Salamanca-Fernandez E, Kiechl S, Krumholz HM, Grioni S, Palli D, Huerta JM, Price J, Sundström J, Arriola L, Arima H, Travis RC, Panagiotakos DB, Karakatsani A, Trichopoulou A, Kühn T, Grobbee DE, Barrett-Connor E, van Schoor N, Boeing H, Overvad K, Kauhanen J, Wareham N, Langenberg C, Forouhi N, Wennberg M, Després JP, Cushman M, Cooper JA, Rodriguez CJ, Sakurai M, Shaw JE, Knuiman M, Voortman T, Meisinger C, Tjønneland A, Brenner H, Palmieri L, Dallongeville J, Brunner EJ, Assmann G, Trevisan M, Gillum RF, Ford I, Sattar N, Lazo M, Thompson SG, Ferrari P, Leon DA, Smith GD, Peto R, Jackson R, Banks E, Di Angelantonio E, Danesh J. Risk thresholds for alcohol consumption: combined analysis of individual-participant data for 599 912 current drinkers in 83 prospective studies. Lancet 2018; 391:1513-1523. [PMID: 29676281 PMCID: PMC5899998 DOI: 10.1016/s0140-6736(18)30134-x] [Citation(s) in RCA: 715] [Impact Index Per Article: 119.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2017] [Revised: 11/03/2017] [Accepted: 12/05/2017] [Indexed: 02/02/2023]
Abstract
BACKGROUND Low-risk limits recommended for alcohol consumption vary substantially across different national guidelines. To define thresholds associated with lowest risk for all-cause mortality and cardiovascular disease, we studied individual-participant data from 599 912 current drinkers without previous cardiovascular disease. METHODS We did a combined analysis of individual-participant data from three large-scale data sources in 19 high-income countries (the Emerging Risk Factors Collaboration, EPIC-CVD, and the UK Biobank). We characterised dose-response associations and calculated hazard ratios (HRs) per 100 g per week of alcohol (12·5 units per week) across 83 prospective studies, adjusting at least for study or centre, age, sex, smoking, and diabetes. To be eligible for the analysis, participants had to have information recorded about their alcohol consumption amount and status (ie, non-drinker vs current drinker), plus age, sex, history of diabetes and smoking status, at least 1 year of follow-up after baseline, and no baseline history of cardiovascular disease. The main analyses focused on current drinkers, whose baseline alcohol consumption was categorised into eight predefined groups according to the amount in grams consumed per week. We assessed alcohol consumption in relation to all-cause mortality, total cardiovascular disease, and several cardiovascular disease subtypes. We corrected HRs for estimated long-term variability in alcohol consumption using 152 640 serial alcohol assessments obtained some years apart (median interval 5·6 years [5th-95th percentile 1·04-13·5]) from 71 011 participants from 37 studies. FINDINGS In the 599 912 current drinkers included in the analysis, we recorded 40 310 deaths and 39 018 incident cardiovascular disease events during 5·4 million person-years of follow-up. For all-cause mortality, we recorded a positive and curvilinear association with the level of alcohol consumption, with the minimum mortality risk around or below 100 g per week. Alcohol consumption was roughly linearly associated with a higher risk of stroke (HR per 100 g per week higher consumption 1·14, 95% CI, 1·10-1·17), coronary disease excluding myocardial infarction (1·06, 1·00-1·11), heart failure (1·09, 1·03-1·15), fatal hypertensive disease (1·24, 1·15-1·33); and fatal aortic aneurysm (1·15, 1·03-1·28). By contrast, increased alcohol consumption was log-linearly associated with a lower risk of myocardial infarction (HR 0·94, 0·91-0·97). In comparison to those who reported drinking >0-≤100 g per week, those who reported drinking >100-≤200 g per week, >200-≤350 g per week, or >350 g per week had lower life expectancy at age 40 years of approximately 6 months, 1-2 years, or 4-5 years, respectively. INTERPRETATION In current drinkers of alcohol in high-income countries, the threshold for lowest risk of all-cause mortality was about 100 g/week. For cardiovascular disease subtypes other than myocardial infarction, there were no clear risk thresholds below which lower alcohol consumption stopped being associated with lower disease risk. These data support limits for alcohol consumption that are lower than those recommended in most current guidelines. FUNDING UK Medical Research Council, British Heart Foundation, National Institute for Health Research, European Union Framework 7, and European Research Council.
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Affiliation(s)
- Angela M Wood
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
| | - Stephen Kaptoge
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Adam S Butterworth
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Peter Willeit
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK; Medical University Innsbruck, Innsbruck, Austria
| | - Samantha Warnakula
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Thomas Bolton
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Ellie Paige
- National Centre for Epidemiology and Population Health, Australian National University, Canberra, Australia
| | - Dirk S Paul
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Michael Sweeting
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Stephen Burgess
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK; MRC Biostatistics Unit, Cambridge Institute of Public Health, University of Cambridge, Cambridge, UK
| | - Steven Bell
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - William Astle
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - David Stevens
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Albert Koulman
- NIHR BRC Nutritional Biomarker Laboratory, University of Cambridge, Cambridge, UK
| | | | - W M Monique Verschuren
- National Institute for Public Health and the Environment, Bilthoven, Netherlands; Julius Centre for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
| | - Shinichi Sato
- Chiba Prefectural Institute of Public Health, Chiba, Japan
| | - Inger Njølstad
- Department of Community Medicine, University of Tromsø, Tromsø, Norway
| | - Mark Woodward
- Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK; The George Institute for Global Health, University of Sydney, Sydney, NSW, Australia; Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Veikko Salomaa
- THL-National Institute for Health and Welfare, Helsinki, Finland
| | - Børge G Nordestgaard
- Copenhagen University Hospital, Copenhagen, Denmark; Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Bu B Yeap
- School of Medicine, University of Western Australia, Perth, WA, Australia; Fiona Stanley Hospital, Perth, WA, Australia; Harry Perkins Institute of Medical Research, Perth, WA, Australia
| | | | - Olle Melander
- Department of Clinical Sciences, Malmö, Lund University, Malmö, Sweden
| | - Lewis H Kuller
- Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Michael Marmot
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Wolfgang Koenig
- 92 Deutsches Herzzentrum München, Technische Universität München, Munich, Germany, DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany; University of Ulm Medical Center, Ulm, Germany
| | | | - Cyrus Cooper
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
| | - Volker Arndt
- German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Oscar H Franco
- Erasmus University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Patrik Wennberg
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - John Gallacher
- Department of Primary Care and Public Health, Cardiff University, Cardiff, UK
| | | | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | | | - Caroline E Dale
- Farr Institute of Health Informatics Research, UCL Institute of Health Informatics, University College London, London, UK
| | | | - Carlos J Crespo
- School of Community Health, Portland State University, Portland, OR, USA
| | - Yvonne T van der Schouw
- Julius Centre for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
| | - Rudolf Kaaks
- German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Leon A Simons
- St Vincent's Clinical School, University of New South Wales, Sydney, NSW, Australia
| | - Pagona Lagiou
- Hellenic Health Foundation, Athens, Greece; National and Kapodistrian University of Athens, Athens, Greece; Harvard TH Chan School of Public Health, Boston, MA, USA
| | | | - Jolanda M A Boer
- National Institute for Public Health and the Environment, Bilthoven, Netherlands
| | - Timothy J Key
- Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Beatriz Rodriguez
- Office of Public Health Studies, University of Hawaii, Honolulu, HI, USA
| | - Conchi Moreno-Iribas
- Instituto de Salud Pública de Navarra, IdiSNA - Navarra Institute for Health Research, Pamplona, Spain; Red de Investigación en Servicios de Salud en Enfermedades Crónicas (REDISSEC), Pamplona, Spain
| | | | | | | | - Robert B Wallace
- College of Public Health, The University of Iowa, Iowa City, IA, USA
| | - J Ramon Quiros
- Consejería de Sanidad del Principado de Asturias, Oviedo, Asturias, Spain
| | | | - Dan G Blazer
- Duke Divinity School, Duke University, Durham, NC, USA
| | - Allan Linneberg
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Makoto Daimon
- Global Center of Excellence Program Study Group, Yamagata University Faculty of Medicine, Yamagata, Japan
| | - Salvatore Panico
- Department of Clinical and Experimental Medicine, Federico II University, Naples, Italy
| | | | - Guri Skeie
- Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway
| | - Timo Strandberg
- University of Helsinki and Helsinki University Hospital, Helsinki, Finland; Center for Life Course Health Research, University of Oulu, Oulu, Finland
| | - Elisabete Weiderpass
- Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway; Cancer Registry of Norway, Institute of Population-Based Cancer Research, Oslo, Norway; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Genetic Epidemiology Group, Folkhälsan Research Center, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Paul J Nietert
- Medical University of South Carolina, Charleston, SC, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Seattle, WA, USA; Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Daan Kromhout
- Department of Agrotechnology and Food Sciences, University of Wageningen, Wageningen, Netherlands; Faculty of Medical Sciences, University of Groningen, Groningen, Netherlands
| | - Elena Salamanca-Fernandez
- Escuela Andaluza de Salud Pública, Instituto de Investigación Biosanitaria ibs.GRANADA, Hospitales Universitarios de Granada/Universidad de Granada, Granada, Spain; CIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | | | | | - Sara Grioni
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Domenico Palli
- Cancer Research and Prevention Institute (ISPO), Florence, Italy
| | - José M Huerta
- CIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain; Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain
| | - Jackie Price
- Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Johan Sundström
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Larraitz Arriola
- CIBER de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain; Instituto BIO-Donostia, Basque Government, San Sebastian, Spain
| | - Hisatomi Arima
- The University of Sydney and Royal Prince Alfred Hospital, Sydney, NSW, Australia; Department of Preventive Medicine and Public Health, Kyushu University, Fukuoka, Japan
| | - Ruth C Travis
- Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | | | - Anna Karakatsani
- Hellenic Health Foundation, Athens, Greece; National and Kapodistrian University of Athens, Athens, Greece
| | - Antonia Trichopoulou
- Hellenic Health Foundation, Athens, Greece; National and Kapodistrian University of Athens, Athens, Greece
| | - Tilman Kühn
- German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Diederick E Grobbee
- Julius Centre for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands
| | | | - Natasja van Schoor
- EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, Netherlands
| | - Heiner Boeing
- German Institute of Human Nutrition, Potsdam-Rehbrüke, Germany
| | - Kim Overvad
- Department of Public Health, Aarhus University, Aarhus, Denmark; Aalborg University Hospital, Aalborg, Denmark
| | - Jussi Kauhanen
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | - Nick Wareham
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Claudia Langenberg
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Nita Forouhi
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Maria Wennberg
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | | | - Mary Cushman
- Department of Medicine, University of Vermont, Burlington, VT, USA
| | - Jackie A Cooper
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Carlos J Rodriguez
- Wake Forest University School of Medicine, Winston-Salem, NC, USA; Wake Forest Baptist Medical Center, Winston-Salem, NC, USA
| | - Masaru Sakurai
- Department of Social and Environmental Medicine, Kanazawa Medical University, Ishikawa, Japan
| | - Jonathan E Shaw
- Baker IDI Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Matthew Knuiman
- Busselton Population Medical Research Institute, Busselton, WA, Australia; School of Population and Global Health, The University of Western Australia, Perth, WA, Australia
| | - Trudy Voortman
- Erasmus University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Christa Meisinger
- Helmholtz Zentrum München German Research Center for Environmental Health, Germany
| | | | - Hermann Brenner
- German Cancer Research Center (DKFZ), Heidelberg, Germany; Division of Clinical Epidemiology and Aging Research, University of Heidelberg, Heidelberg, Germany
| | | | | | - Eric J Brunner
- Department of Epidemiology and Public Health, University College London, London, UK
| | - Gerd Assmann
- Assmann-Stiftung für Prävention, Münster, Germany
| | | | | | - Ian Ford
- Institute of Cardiovascular & Medical Sciences, University of Glasgow, Glasgow, UK
| | - Naveed Sattar
- Institute of Cardiovascular & Medical Sciences, University of Glasgow, Glasgow, UK
| | - Mariana Lazo
- School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Simon G Thompson
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Pietro Ferrari
- International Agency for Research on Cancer, Lyon, France
| | - David A Leon
- London School of Hygiene & Tropical Medicine, London, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
| | - Richard Peto
- Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, UK
| | - Rod Jackson
- School of Population Health, The University of Auckland, Auckland, New Zealand
| | - Emily Banks
- National Centre for Epidemiology and Population Health, Australian National University, Canberra, Australia
| | | | - John Danesh
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
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58
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Katikireddi SV, Green MJ, Taylor AE, Davey Smith G, Munafò MR. Assessing causal relationships using genetic proxies for exposures: an introduction to Mendelian randomization. Addiction 2018; 113:764-774. [PMID: 28921935 PMCID: PMC5873430 DOI: 10.1111/add.14038] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2017] [Revised: 04/12/2017] [Accepted: 09/11/2017] [Indexed: 01/05/2023]
Abstract
BACKGROUND AND AIMS Studying the consequences of addictive behaviours is challenging, with understanding causal relationships from observational data being particularly difficult. For example, people who smoke or drink excessively are often systematically different from those who do not, are less likely to participate in research and may misreport their behaviours when they do. Furthermore, the direction of causation between an addictive behaviour and outcome may be unclear. Mendelian randomization (MR) offers potential solutions to these problems. METHODS We describe MR's principles and the criteria under which it is valid. We identify challenges and potential solutions in its application (illustrated using two applied examples) and describe methodological extensions in its application. RESULTS MR is subject to certain assumptions, and requires the availability of appropriate genetic data, large sample sizes and careful design and conduct. However, it has already been applied successfully to the addiction literature. The relationship between alcohol consumption (proxied by a variant in the ADH1B gene) and cardiovascular risk has been investigated, finding that alcohol consumption increases risk, with no evidence of a cardioprotective effect at moderate consumption levels. In addition, heaviness of smoking (proxied by a variant in the CHRNA5-A3-B4 gene cluster) and risk of depression and schizophrenia have been investigated, with no evidence of a causal effect of smoking on depression but some evidence of a causal effect on schizophrenia. CONCLUSIONS Mendelian randomization analyses are already producing robust evidence for addiction-related practice and policy. As genetic variants associated with addictive behaviours are identified, the potential for Mendelian randomization analyses will grow. Methodological developments are also increasing its applicability.
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Affiliation(s)
| | - Michael J. Green
- MRC/CSO Social and Public Health Sciences UnitUniversity of GlasgowGlasgowUK
| | - Amy E. Taylor
- MRC Integrative Epidemiology UnitUniversity of BristolBristolUK
- UK Centre for Tobacco and Alcohol Studies, School of Experimental PsychologyUniversity of BristolBristolUK
| | | | - Marcus R. Munafò
- MRC Integrative Epidemiology UnitUniversity of BristolBristolUK
- UK Centre for Tobacco and Alcohol Studies, School of Experimental PsychologyUniversity of BristolBristolUK
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59
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Difference in sensitivities of blood HDL cholesterol and LDL cholesterol levels to alcohol in middle-aged Japanese men. Alcohol 2018; 67:45-50. [PMID: 29425958 DOI: 10.1016/j.alcohol.2017.08.011] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2017] [Revised: 08/18/2017] [Accepted: 08/18/2017] [Indexed: 11/20/2022]
Abstract
Blood HDL cholesterol and LDL cholesterol levels are known to be higher and lower, respectively, in drinkers than in nondrinkers, and the beneficial effects of alcohol on cholesterol metabolism are thought to mainly explain the lower risk for ischemic heart disease in light-to-moderate drinkers than in nondrinkers. However, it remains unknown whether sensitivities of HDL and LDL cholesterol levels to alcohol are different or not. The subjects of this study were 21,572 middle-aged Japanese men, and they were divided into three tertile groups for blood HDL cholesterol levels. The relationships between habitual alcohol intake and LDL cholesterol levels were investigated in each tertile for HDL cholesterol. In all of the tertile groups for HDL cholesterol, mean LDL cholesterol levels were significantly lower in the drinking subgroups than in the nondrinking subgroup and tended to be lower with an increase of alcohol intake. In all of the tertile groups for HDL cholesterol, odds ratios for high LDL cholesterol of each drinking subgroup vs. the nondrinking subgroup were significantly lower than the reference level of 1.00, and also tended to be lower with an increase of alcohol intake. The odds ratios of each drinking subgroup tended to be lower in the 1st tertile group for HDL cholesterol than in the 3rd tertile group. Drinkers in the 1st tertile for HDL cholesterol are thought to have relatively low sensitivity of HDL cholesterol to alcohol, but clearly showed lower LDL cholesterol levels than those found in nondrinkers. Therefore, the sensitivity of LDL cholesterol level to alcohol is different from the sensitivity of HDL cholesterol level to alcohol.
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60
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Münzel T, Daiber A. The potential of aldehyde dehydrogenase 2 as a therapeutic target in cardiovascular disease. Expert Opin Ther Targets 2018; 22:217-231. [PMID: 29431026 DOI: 10.1080/14728222.2018.1439922] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
INTRODUCTION Mitochondrial aldehyde dehydrogenase (ALDH-2) plays a major role in the ethanol detoxification pathway by removing acetaldehyde. Therefore, ALDH-2 inhibitors such as disulfiram represent the first therapeutic targeting of ALDH-2 for alcoholism therapy. Areas covered: Recently, ALDH-2 was identified as an essential bioactivating enzyme of the anti-ischemic organic nitrate nitroglycerin, bringing ALDH-2 again into the focus of clinical interest. Mechanistic studies on the nitroglycerin bioactivation process revealed that during bioconversion of nitroglycerin and in the presence of reactive oxygen and nitrogen species the active site thiols of ALDH-2 are oxidized and the enzyme activity is lost. Thus, ALDH-2 activity represents a useful marker for cardiovascular oxidative stress, a concept, which has been meanwhile supported by a number of animal disease models. Mechanistic studies on the protective role of ALDH-2 in different disease processes identified the detoxification of 4-hydroxynonenal by ALDH-2 as a fundamental process of cardiovascular, cerebral and antioxidant protection. Expert opinion: The most recent therapeutic exploitation of ALDH-2 includes activators of the enzyme such as Alda-1 but also cell-based therapies (ALDH-bright cells) that deserve further clinical characterization in the future.
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Affiliation(s)
- Thomas Münzel
- a Center for Cardiology, Cardiology 1 , Medical Center of the Johannes Gutenberg University , Mainz , Germany.,b Center for Thrombosis and Hemostasis (CTH) , Medical Center of the Johannes Gutenberg University , Mainz , Germany.,c Partner Site Rhine-Main , German Center for Cardiovascular Research (DZHK) , Mainz , Germany
| | - Andreas Daiber
- a Center for Cardiology, Cardiology 1 , Medical Center of the Johannes Gutenberg University , Mainz , Germany.,b Center for Thrombosis and Hemostasis (CTH) , Medical Center of the Johannes Gutenberg University , Mainz , Germany.,c Partner Site Rhine-Main , German Center for Cardiovascular Research (DZHK) , Mainz , Germany
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61
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Exploring the utility of alcohol flushing as an instrumental variable for alcohol intake in Koreans. Sci Rep 2018; 8:458. [PMID: 29323248 PMCID: PMC5765011 DOI: 10.1038/s41598-017-18856-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2017] [Accepted: 12/15/2017] [Indexed: 01/13/2023] Open
Abstract
Previous studies have indicated an association of higher alcohol intake with cardiovascular disease and related traits, but causation has not been definitively established. In this study, the causal effect of alcohol intake on hypertension in 2,011 men and women from the Ansan-Ansung cohort was estimated using an instrumental variable (IV) approach, with both a phenotypic and genotypic instrument for alcohol intake: alcohol flushing and the rs671 genotype (in the alcohol dehydrogenase 2 [ALDH2] gene), respectively. Both alcohol flushing and the rs671 genotype were associated with alcohol intake (difference in alcohol intake with alcohol flushers vs. non-flushers: −9.07 g/day; 95% confidence interval [CI]: −11.12, −7.02; P-value: 8.3 × 10−18 and with the rs671 GA + AA vs. GG genotype: −7.94 g/day; 95% CI: −10.20, −5.69; P-value: 6.1 × 10−12). An increase in alcohol intake, as predicted by both the absence of alcohol flushing and the presence of the rs671 GG genotype in the IV analyses, was associated with an increase in blood pressure in men from this Korean population. In conclusion, this study supports a causal effect of alcohol intake on hypertension and indicated that alcohol flushing may be a valid proxy for the ALDH2 rs671 polymorphism, which influences alcohol intake in this Korean population.
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62
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Degerud E, Ariansen I, Ystrom E, Graff-Iversen S, Høiseth G, Mørland J, Davey Smith G, Næss Ø. Life course socioeconomic position, alcohol drinking patterns in midlife, and cardiovascular mortality: Analysis of Norwegian population-based health surveys. PLoS Med 2018; 15:e1002476. [PMID: 29293492 PMCID: PMC5749685 DOI: 10.1371/journal.pmed.1002476] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2017] [Accepted: 11/21/2017] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Socioeconomically disadvantaged groups tend to experience more harm from the same level of exposure to alcohol as advantaged groups. Alcohol has multiple biological effects on the cardiovascular system, both potentially harmful and protective. We investigated whether the diverging relationships between alcohol drinking patterns and cardiovascular disease (CVD) mortality differed by life course socioeconomic position (SEP). METHODS AND FINDINGS From 3 cohorts (the Counties Studies, the Cohort of Norway, and the Age 40 Program, 1987-2003) containing data from population-based cardiovascular health surveys in Norway, we included participants with self-reported information on alcohol consumption frequency (n = 207,394) and binge drinking episodes (≥5 units per occasion, n = 32,616). We also used data from national registries obtained by linkage. Hazard ratio (HR) with 95% confidence intervals (CIs) for CVD mortality was estimated using Cox models, including alcohol, life course SEP, age, gender, smoking, physical activity, body mass index (BMI), systolic blood pressure, heart rate, triglycerides, diabetes, history of CVD, and family history of coronary heart disease (CHD). Analyses were performed in the overall sample and stratified by high, middle, and low strata of life course SEP. A total of 8,435 CVD deaths occurred during the mean 17 years of follow-up. Compared to infrequent consumption ( CONCLUSIONS Moderately frequent consumers had a lower risk of CVD mortality compared with infrequent consumers, and we observed that this association was more pronounced among participants with higher SEP throughout their life course. Frequent binge drinking was associated with a higher risk of CVD mortality, but it was more uncertain whether the risk differed by life course SEP. It is unclear if these findings reflect differential confounding of alcohol consumption with health-protective or damaging exposures, or differing effects of alcohol on health across socioeconomic groups.
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Affiliation(s)
| | | | - Eivind Ystrom
- Norwegian Institute of Public Health, Oslo, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
- School of Pharmacy, University of Oslo, Oslo, Norway
| | | | - Gudrun Høiseth
- Norwegian Institute of Public Health, Oslo, Norway
- Diakonhjemmet Hospital, Center for Psychopharmacology, Oslo, Norway
| | - Jørg Mørland
- Norwegian Institute of Public Health, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Øyvind Næss
- Norwegian Institute of Public Health, Oslo, Norway
- Institute of Health and Society, University of Oslo, Oslo, Norway
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63
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Zheng J, Baird D, Borges MC, Bowden J, Hemani G, Haycock P, Evans DM, Smith GD. Recent Developments in Mendelian Randomization Studies. CURR EPIDEMIOL REP 2017; 4:330-345. [PMID: 29226067 PMCID: PMC5711966 DOI: 10.1007/s40471-017-0128-6] [Citation(s) in RCA: 486] [Impact Index Per Article: 69.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
PURPOSE OF REVIEW Mendelian randomization (MR) is a strategy for evaluating causality in observational epidemiological studies. MR exploits the fact that genotypes are not generally susceptible to reverse causation and confounding, due to their fixed nature and Mendel's First and Second Laws of Inheritance. MR has the potential to provide information on causality in many situations where randomized controlled trials are not possible, but the results of MR studies must be interpreted carefully to avoid drawing erroneous conclusions. RECENT FINDINGS In this review, we outline the principles behind MR, as well as assumptions and limitations of the method. Extensions to the basic approach are discussed, including two-sample MR, bidirectional MR, two-step MR, multivariable MR, and factorial MR. We also consider some new applications and recent developments in the methodology, including its ability to inform drug development, automation of the method using tools such as MR-Base, and phenome-wide and hypothesis-free MR. SUMMARY In conjunction with the growing availability of large-scale genomic databases, higher level of automation and increased robustness of the methods, MR promises to be a valuable strategy to examine causality in complex biological/omics networks, inform drug development and prioritize intervention targets for disease prevention in the future.
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Affiliation(s)
- Jie Zheng
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Bristol, UK
| | - Denis Baird
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Bristol, UK
| | - Maria-Carolina Borges
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Bristol, UK
| | - Jack Bowden
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Bristol, UK
| | - Gibran Hemani
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Bristol, UK
| | - Philip Haycock
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Bristol, UK
| | - David M. Evans
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Bristol, UK
- University of Queensland Diamantina Institute, Translational Research Institute, University of Queensland, Brisbane, QLD Australia
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Bristol, UK
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Chao M, Li X, McGue M. The Causal Role of Alcohol Use in Adolescent Externalizing and Internalizing Problems: A Mendelian Randomization Study. Alcohol Clin Exp Res 2017; 41:1953-1960. [PMID: 28876462 DOI: 10.1111/acer.13493] [Citation(s) in RCA: 54] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2017] [Accepted: 08/25/2017] [Indexed: 11/26/2022]
Abstract
BACKGROUND The co-occurrence of alcohol use and externalizing/internalizing problems threatens adolescents' mental health. Research on whether alcohol use and these problems are causal and the direction of the potential causal relationships is needed to understand the mechanisms of the co-occurrence. METHODS A Mendelian randomization analysis was conducted in which the aldehyde dehydrogenase 2 (ALDH2) rs671 polymorphism was used as an instrumental variable for alcohol use phenotypes. In total, 1,608 Chinese adolescents (mean age 14.11 ± 1.83 years) were genotyped for the ALDH2 rs671 polymorphism. Three externalizing problems (aggression, delinquency, and attention problems) were measured with the Youth Self-Report inventory, and 2 internalizing problems (depression and anxiety) were measured with the self-reported Children's Depression Inventory and the Trait subscale of the State-Trait Anxiety Inventory. RESULTS Alcohol use was positively associated with all 3 externalizing and 2 internalizing problems, and the ALDH2 polymorphism had a significant effect on alcohol use. Aggression and attention problems were also significantly affected by the ALDH2 polymorphism, whereas no significant association was observed between the ALDH2 polymorphism and delinquency, anxiety, or depression. CONCLUSIONS The results suggest that alcohol use is a cause of adolescent aggression and attention problems but not adolescent delinquency, anxiety, or depression.
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Affiliation(s)
- Miao Chao
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chaoyang District, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Xinying Li
- CAS Key Laboratory of Mental Health, Institute of Psychology, Chaoyang District, China.,Department of Psychology, University of Chinese Academy of Sciences, Beijing, China
| | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, Minnesota
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65
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Shin MJ, Cho Y, Davey Smith G. Alcohol Consumption, Aldehyde Dehydrogenase 2 Gene Polymorphisms, and Cardiovascular Health in Korea. Yonsei Med J 2017; 58:689-696. [PMID: 28540979 PMCID: PMC5447097 DOI: 10.3349/ymj.2017.58.4.689] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2017] [Revised: 04/27/2017] [Accepted: 05/02/2017] [Indexed: 12/11/2022] Open
Abstract
Alcohol consumption is a serious health issue in Korea in terms of the amount consumed and the behavior related to its consumption. Aldehyde dehydrogenase 2 (ALDH2) is a key enzyme in alcohol metabolism that degrades acetaldehyde to nontoxic acetic acid. The enzyme is coded by the ALDH2 gene, which is commonly polymorphic in East Asian populations. A point mutation in the ALDH2 gene (the rs671 allele) yields an inactive form of ALDH2 that causes acetaldehyde accumulation in the body after alcohol consumption, thereby inhibiting normal alcohol metabolism. Individuals who are homozygous for polymorphism in ALDH2 tend to refrain from drinking alcohol, decreasing their chances of developing alcoholism and exposure to the associated risks. Mendelian randomization (MR) studies have demonstrated that alcohol consumption predicted by ALDH2 genotype is causally related to cardiovascular risks. Moreover, recent MR studies suggest that the ALDH2 variant has mechanistic effects on some disease outcomes or mortality through increased blood levels of acetaldehyde, showing differences therein between heterozygotes (ALDH2*2*2) and homozygotes (ALDH2*1*2) in those who consume alcohol. Accordingly, consideration of ALDH2 genotype in alcohol prevention programs is warranted. In conclusion, strategies that incorporate genetic information and provide an evidential basis from which to help people make informed decisions on alcohol consumption are urgently required.
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Affiliation(s)
- Min Jeong Shin
- Department of Public Health Sciences, BK21PLUS Program in Embodiment: Health-Society Interaction, Graduate School, Korea University, Seoul, Korea.
| | - Yoonsu Cho
- Department of Public Health Sciences, BK21PLUS Program in Embodiment: Health-Society Interaction, Graduate School, Korea University, Seoul, Korea
- MRC Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, UK
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66
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Holmes MV, Ala-Korpela M, Smith GD. Mendelian randomization in cardiometabolic disease: challenges in evaluating causality. Nat Rev Cardiol 2017; 14:577-590. [PMID: 28569269 DOI: 10.1038/nrcardio.2017.78] [Citation(s) in RCA: 390] [Impact Index Per Article: 55.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Mendelian randomization (MR) is a burgeoning field that involves the use of genetic variants to assess causal relationships between exposures and outcomes. MR studies can be straightforward; for example, genetic variants within or near the encoding locus that is associated with protein concentrations can help to assess their causal role in disease. However, a more complex relationship between the genetic variants and an exposure can make findings from MR more difficult to interpret. In this Review, we describe some of these challenges in interpreting MR analyses, including those from studies using genetic variants to assess causality of multiple traits (such as branched-chain amino acids and risk of diabetes mellitus); studies describing pleiotropic variants (for example, C-reactive protein and its contribution to coronary heart disease); and those investigating variants that disrupt normal function of an exposure (for example, HDL cholesterol or IL-6 and coronary heart disease). Furthermore, MR studies on variants that encode enzymes responsible for the metabolism of an exposure (such as alcohol) are discussed, in addition to those assessing the effects of variants on time-dependent exposures (extracellular superoxide dismutase), cumulative exposures (LDL cholesterol), and overlapping exposures (triglycerides and non-HDL cholesterol). We elaborate on the molecular features of each relationship, and provide explanations for the likely causal associations. In doing so, we hope to contribute towards more reliable evaluations of MR findings.
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Affiliation(s)
- Michael V Holmes
- Medical Research Council Population Health Research Unit, University of Oxford, Roosevelt Drive, Oxford OX3 7LF, UK.,Clinical Trial Service Unit &Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Big Data Institute Building, Old Road Campus, Roosevelt Drive, Oxford OX3 7BN, UK.,National Institute for Health Research, Oxford Biomedical Research Centre, Oxford University Hospital, Old Road, Oxford OX3 7LE, UK.,Medical Research Council Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Mika Ala-Korpela
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.,Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, University of Oulu, Aapistie 5A, 90014, Oulu, Finland.,School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.,School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
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67
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Kato K, Miyata S, Ando M, Matsuoka H, Yasuma F, Iwamoto K, Kawano N, Banno M, Ozaki N, Noda A. Influence of sleep duration on cortical oxygenation in elderly individuals. Psychiatry Clin Neurosci 2017; 71:44-51. [PMID: 27696589 DOI: 10.1111/pcn.12464] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2016] [Revised: 08/30/2016] [Accepted: 09/26/2016] [Indexed: 12/31/2022]
Abstract
AIM Short sleep duration is a risk factor for cardiovascular diseases. Cerebral blood flow and its regulation are affected by pathological conditions commonly observed in the elderly population, such as dementia, atherosclerosis, diabetes mellitus (DM), stroke, and hypertension. The purpose of this study was to examine the influence of sleep duration on cortical oxygenated hemoglobin (OxyHb) using near-infrared spectroscopy (NIRS). METHODS Seventy-three individuals (age, 70.1 ± 3.9 years, 51 men and 22 women) participated in this study. Cortical OxyHb levels were measured with NIRS. We evaluated age, body mass index (BMI), smoking status, alcohol intake, sleep duration, hypertension, DM, and hyperlipidemia using a questionnaire. Blood pressure was measured using plethysmography. RESULTS Peak OxyHb and area under the NIRS curve significantly decreased in participants with sleep duration <7 h compared with those with sleep duration ≥7 h (0.136 ± 0.212 mM·mm vs 0.378 ± 0.342 mM·mm, P = 0.001; 112.0 ± 243.6 vs 331.7 ± 428.7, P = 0.012, respectively). Sleep duration was significantly correlated with peak OxyHb level and area under the NIRS curve (r = 0.378, P = 0.001; r = 0.285, P = 0.015, respectively). Multiple regression analysis, including age, BMI, sex, smoking status, alcohol intake, sleep duration, hypertension, DM, and hyperlipidemia revealed that sleep duration was the only significant independent factor associated with peak OxyHb and area under the NIRS curve (β = 0.343, P = 0.004; β = 0.244, P = 0.049, respectively), and smoking status was independently correlated with time to the peak OxyHb (β = -0.319, P = 0.009). CONCLUSION Sleep duration may be an important factor that influences cortical oxygenation in the elderly population.
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Affiliation(s)
- Kazuko Kato
- Chubu University Graduate School of Life and Health Sciences, Aichi, Japan
| | - Seiko Miyata
- Department of Sleep Medicine, Nagoya University Graduate School of Medicine, Aichi, Japan.,Education and Training Center of Medical Technology, Chubu University, Aichi, Japan
| | - Motoo Ando
- Education and Training Center of Medical Technology, Chubu University, Aichi, Japan
| | - Hiroki Matsuoka
- Chubu University Graduate School of Life and Health Sciences, Aichi, Japan
| | - Fumihiko Yasuma
- Department of Internal Medicine, National Hospital Organization Suzuka Hospital, Mie, Japan
| | - Kunihiro Iwamoto
- Department of Psychiatry, Nagoya University Graduate School of Medicine, Aichi, Japan
| | - Naoko Kawano
- Institutes of Innovation for Future Society, Nagoya University, Aichi, Japan
| | - Masahiro Banno
- Department of Psychiatry, Nagoya University Graduate School of Medicine, Aichi, Japan.,Seichiryo Hospital, Aichi, Japan
| | - Norio Ozaki
- Department of Psychiatry, Nagoya University Graduate School of Medicine, Aichi, Japan
| | - Akiko Noda
- Chubu University Graduate School of Life and Health Sciences, Aichi, Japan.,Education and Training Center of Medical Technology, Chubu University, Aichi, Japan
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68
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Tabara Y, Arai H, Hirao Y, Takahashi Y, Setoh K, Kawaguchi T, Kosugi S, Ito Y, Nakayama T, Matsuda F. The causal effects of alcohol on lipoprotein subfraction and triglyceride levels using a Mendelian randomization analysis: The Nagahama study. Atherosclerosis 2016; 257:22-28. [PMID: 28038378 DOI: 10.1016/j.atherosclerosis.2016.12.008] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2016] [Revised: 12/02/2016] [Accepted: 12/08/2016] [Indexed: 11/25/2022]
Abstract
BACKGROUND Light-to-moderate alcohol consumption may increase circulating high-density lipoprotein cholesterol (HDL-C) levels and decrease low-density lipoprotein cholesterol (LDL-C) levels. However, the effect of alcohol on biologically important lipoprotein subfractions remains largely unknown. Here we aimed to clarify the effects of alcohol on lipoprotein subfractions using a Mendelian randomization analysis. METHODS The study subjects consisted of 8364 general Japanese individuals. The rs671 polymorphism in aldehyde dehydrogenase 2 gene, a rate-controlling enzyme of alcohol metabolism, was used as an instrumental variable. Lipoprotein subfractions were measured by a homogeneous assay. RESULTS The biologically active *1 allele of the ALDH2 genotype was strongly associated with alcohol consumption in men (p < 0.001). In a regression analysis adjusted for possible covariates, the *1 allele was positively associated with HDL-C even in a sub-analysis for HDL subfractions (HDL2-C: β = 0.082, p < 0.001; HDL3-C: β = 0.195, p < 0.001). In contrast, the *1 allele was inversely associated with total LDL-C levels (β = -0.049, p = 0.008), while its association with large-buoyant LDL-C (β = -0.124, p < 0.001) and small-dense LDL-C (β = 0.069, p < 0.001) was opposite. Therefore, the ratio of small-dense LDL to large-buoyant LDL exhibited a linear increase with the number of *1 alleles carried (β = 0.127, p < 0.001). Furthermore, the *1 allele was inversely associated with triglyceride levels in an analysis adjusted for LDL subfractions (β = -0.097, p < 0.001), but not for the total LDL (β = 0.014, p = 0.410). CONCLUSIONS Alcohol may increase HDL-C levels irrespective of the particle size. Moreover, alcohol may decrease the total LDL-C, although the proportion of atherogenic small-dense LDL-C increased partially due to a potential inter-relationship with decreased triglyceride levels.
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Affiliation(s)
- Yasuharu Tabara
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.
| | - Hidenori Arai
- National Center for Geriatrics and Gerontology, Obu, Japan
| | - Yuhko Hirao
- Research and Development Center, Denka Seiken Co., Ltd., Tokyo, Japan
| | - Yoshimitsu Takahashi
- Department of Health Informatics, Kyoto University School of Public Health, Kyoto, Japan
| | - Kazuya Setoh
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Takahisa Kawaguchi
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Shinji Kosugi
- Department of Medical Ethics and Medical Genetics, Kyoto University School of Public Health, Kyoto, Japan
| | - Yasuki Ito
- Research and Development Center, Denka Seiken Co., Ltd., Tokyo, Japan
| | - Takeo Nakayama
- Department of Health Informatics, Kyoto University School of Public Health, Kyoto, Japan
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
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69
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Smith CE, Coltell O, Sorlí JV, Estruch R, Martínez-González MÁ, Salas-Salvadó J, Fitó M, Arós F, Dashti HS, Lai CQ, Miró L, Serra-Majem L, Gómez-Gracia E, Fiol M, Ros E, Aslibekyan S, Hidalgo B, Neuhouser ML, Di C, Tucker KL, Arnett DK, Ordovás JM, Corella D. Associations of the MCM6-rs3754686 proxy for milk intake in Mediterranean and American populations with cardiovascular biomarkers, disease and mortality: Mendelian randomization. Sci Rep 2016; 6:33188. [PMID: 27624874 PMCID: PMC5021998 DOI: 10.1038/srep33188] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2016] [Accepted: 08/23/2016] [Indexed: 12/13/2022] Open
Abstract
Controversy persists on the association between dairy products, especially milk, and cardiovascular diseases (CVD). Genetic proxies may improve dairy intake estimations, and clarify diet-disease relationships through Mendelian randomization. We meta-analytically (n ≤ 20,089) evaluated associations between a lactase persistence (LP) SNP, the minichromosome maintenance complex component 6 (MCM6)-rs3754686C>T (nonpersistence>persistence), dairy intake, and CVD biomarkers in American (Hispanics, African-American and Whites) and Mediterranean populations. Moreover, we analyzed longitudinal associations with milk, CVD and mortality in PREDIMED), a randomized Mediterranean diet (MedDiet) intervention trial (n = 7185). The MCM6-rs3754686/MCM6-rs309180 (as proxy), LP-allele (T) was strongly associated with higher milk intake, but inconsistently associated with glucose and lipids, and not associated with CVD or total mortality in the whole population. Heterogeneity analyses suggested some sex-specific associations. The T-allele was associated with higher CVD and mortality risk in women but not in men (P-sex interaction:0.005 and 0.032, respectively), mainly in the MedDiet group. However, milk intake was not associated with CVD biomarkers, CVD or mortality either generally or in sub-groups. Although MCM6-rs3754686 is a good milk intake proxy in these populations, attributing its associations with CVD and mortality in Mediterranean women to milk is unwarranted, as other factors limiting the assumption of causality in Mendelian randomization may exist.
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Affiliation(s)
- Caren E. Smith
- Nutrition and Genomics Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA
| | - Oscar Coltell
- Department of Computer Languages and Systems, School of Technology and Experimental Sciences. University Jaume I, Castellón, Spain
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
| | - Jose V. Sorlí
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, Valencia, Spain
| | - Ramón Estruch
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Internal Medicine, Hospital Clinic, IDIBAPS, Barcelona, Spain
| | - Miguel Ángel Martínez-González
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra-Navarra Institute for Health Research (IdisNa), Pamplona, Navarra, Spain
| | - Jordi Salas-Salvadó
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Human Nutrition Unit, Biochemistry and Biotechnology Department, IISPV, University Rovira i Virgili, Reus, Spain
| | - Montserrat Fitó
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Cardiovascular Epidemiology Unit, Municipal Institut for Medical Research (IMIM), Barcelona, Spain
| | - Fernando Arós
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Cardiology, Hospital Txagorritxu, Vitoria, Spain
| | - Hassan S. Dashti
- Nutrition and Genomics Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA
| | - Chao Q. Lai
- Nutrition and Genomics Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA
| | - Leticia Miró
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Family Medicine, Research Unit. Distrito Sanitario Atención Primaria Sevilla, Spain
| | - Lluís Serra-Majem
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Research Institute of Biomedical and Health Sciences, University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain
| | - Enrique Gómez-Gracia
- Department of Epidemiology, School of Medicine, University of Malaga, Malaga, Spain
| | - Miquel Fiol
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Palma Institute of Health Research (IdISPa). Hospital Son Espases. Palma de Mallorca, Spain
| | - Emilio Ros
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Lipid Clinic, Endocrinology and Nutrition Service, Institut d’Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clinic, Barcelona, Spain
| | - Stella Aslibekyan
- Department of Epidemiology, School of Public Health, University of Alabama, Birmingham, Alabama, USA
| | - Bertha Hidalgo
- Department of Epidemiology, School of Public Health, University of Alabama, Birmingham, Alabama, USA
| | | | - Chongzhi Di
- Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Katherine L. Tucker
- Department of Clinical Laboratory & Nutritional Sciences, University of Massachusetts Lowell, Massachusetts, USA
| | - Donna K. Arnett
- Department of Epidemiology, School of Public Health, University of Alabama, Birmingham, Alabama, USA
| | - José M. Ordovás
- Nutrition and Genomics Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA
- Department of Epidemiology and Population Genetics, Centro Nacional Investigación Cardiovasculares (CNIC), Madrid, Spain
- Instituto Madrileño de Estudios Avanzados en Alimentación, Madrid, Spain
| | - Dolores Corella
- CIBER Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, Valencia, Spain
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Tabara Y, Ueshima H, Takashima N, Hisamatsu T, Fujiyoshi A, Zaid M, Sumi M, Kohara K, Miki T, Miura K. Mendelian randomization analysis in three Japanese populations supports a causal role of alcohol consumption in lowering low-density lipid cholesterol levels and particle numbers. Atherosclerosis 2016; 254:242-248. [PMID: 27575649 DOI: 10.1016/j.atherosclerosis.2016.08.021] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2016] [Revised: 07/21/2016] [Accepted: 08/19/2016] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND AIMS While alcohol consumption is known to increase plasma high-density lipoprotein (HDL) cholesterol levels, its relationship with low-density lipoprotein (LDL) cholesterol levels is unclear. Aldehyde dehydrogenase 2 (ALDH2) is a rate-controlling enzyme in alcohol metabolism, but a large number of Japanese people have the inactive allele. Here, we conducted a Mendelian randomization analysis using the ALDH2 genotype to clarify a causal role of alcohol on circulating cholesterol levels and lipoprotein particle numbers. METHODS This study was conducted in three independent general Japanese populations (men, n = 2289; women, n = 1940; mean age 63.3 ± 11.2 years). Alcohol consumption was assessed using a questionnaire. Lipoprotein particle numbers were determined by nuclear magnetic resonance spectroscopy. RESULTS Alcohol consumption increased linearly in proportion to the number of subjects carrying the enzymatically active *1 allele in men (p < 0.001). The *1 allele was also positively associated with HDL cholesterol level (adjusted mean ± standard error, *1*1: 60 ± 0.5, *1*2: 56 ± 0.6, *2*2: 55 ± 1.3 mg/dl, p < 0.001) and inversely associated with LDL cholesterol level (116 ± 0.9, 124 ± 1.1, 130 ± 2.6 mg/dl, p < 0.001). The *1 allele was also positively associated with HDL particle numbers (per-allele: 2.60 ± 0.32 μmol/l, p < 0.001) and inversely associated with LDL particle numbers (-67.8 ± 19.6 nmol/l, p = 0.001). Additional Mendelian randomization analysis failed to clarify the involvement of cholesteryl ester transfer protein in alcohol-related changes in lipoprotein cholesterol levels. No significant association was observed in women, presumably due to their small amount of alcohol intake. CONCLUSIONS Alcohol consumption has a causal role in not only increasing HDL cholesterol levels but also decreasing LDL cholesterol levels and particle numbers.
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Affiliation(s)
- Yasuharu Tabara
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto 606-8507, Japan; Department of Geriatric Medicine, Ehime University Graduate School of Medicine, Toon City, Ehime 791-0295, Japan.
| | - Hirotsugu Ueshima
- Department of Public Health, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192, Japan; Center for Epidemiologic Research in Asia, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192, Japan
| | - Naoyuki Takashima
- Department of Public Health, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192, Japan
| | - Takashi Hisamatsu
- Department of Public Health, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192, Japan; Center for Epidemiologic Research in Asia, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192, Japan
| | - Akira Fujiyoshi
- Department of Public Health, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192, Japan
| | - Maryam Zaid
- Department of Public Health, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192, Japan
| | - Masaki Sumi
- Department of Public Health, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192, Japan
| | - Katsuhiko Kohara
- Department of Regional Resource Management, Faculty of Collaborative Regional Innovation, Ehime University, Matsuyama, Ehime 790-8577, Japan
| | - Tetsuro Miki
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Sakyo-ku, Kyoto 606-8507, Japan; Department of Geriatric Medicine, Ehime University Graduate School of Medicine, Toon City, Ehime 791-0295, Japan
| | - Katsuyuki Miura
- Department of Public Health, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192, Japan; Center for Epidemiologic Research in Asia, Shiga University of Medical Science, Seta Tsukinowa-cho, Otsu, Shiga 520-2192, Japan
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71
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Würtz P, Cook S, Wang Q, Tiainen M, Tynkkynen T, Kangas AJ, Soininen P, Laitinen J, Viikari J, Kähönen M, Lehtimäki T, Perola M, Blankenberg S, Zeller T, Männistö S, Salomaa V, Järvelin MR, Raitakari OT, Ala-Korpela M, Leon DA. Metabolic profiling of alcohol consumption in 9778 young adults. Int J Epidemiol 2016; 45:1493-1506. [PMID: 27494945 PMCID: PMC5100616 DOI: 10.1093/ije/dyw175] [Citation(s) in RCA: 78] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/26/2016] [Indexed: 11/18/2022] Open
Abstract
Background: High alcohol consumption is a major cause of morbidity, yet alcohol is associated with both favourable and adverse effects on cardiometabolic risk markers. We aimed to characterize the associations of usual alcohol consumption with a comprehensive systemic metabolite profile in young adults. Methods: Cross-sectional associations of alcohol intake with 86 metabolic measures were assessed for 9778 individuals from three population-based cohorts from Finland (age 24–45 years, 52% women). Metabolic changes associated with change in alcohol intake during 6-year follow-up were further examined for 1466 individuals. Alcohol intake was assessed by questionnaires. Circulating lipids, fatty acids and metabolites were quantified by high-throughput nuclear magnetic resonance metabolomics and biochemical assays. Results: Increased alcohol intake was associated with cardiometabolic risk markers across multiple metabolic pathways, including higher lipid concentrations in HDL subclasses and smaller LDL particle size, increased proportions of monounsaturated fatty acids and decreased proportion of omega-6 fatty acids, lower concentrations of glutamine and citrate (P < 0.001 for 56 metabolic measures). Many metabolic biomarkers displayed U-shaped associations with alcohol consumption. Results were coherent for men and women, consistent across the three cohorts and similar if adjusting for body mass index, smoking and physical activity. The metabolic changes accompanying change in alcohol intake during follow-up resembled the cross-sectional association pattern (R2 = 0.83, slope = 0.72 ± 0.04). Conclusions: Alcohol consumption is associated with a complex metabolic signature, including aberrations in multiple biomarkers for elevated cardiometabolic risk. The metabolic signature tracks with long-term changes in alcohol consumption. These results elucidate the double-edged effects of alcohol on cardiovascular risk.
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Affiliation(s)
- Peter Würtz
- Computational Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland
| | - Sarah Cook
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Qin Wang
- Computational Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland.,NMR Metabolomics Laboratory, University of Eastern Finland, Kuopio, Finland
| | - Mika Tiainen
- Computational Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland.,NMR Metabolomics Laboratory, University of Eastern Finland, Kuopio, Finland
| | - Tuulia Tynkkynen
- Computational Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland.,NMR Metabolomics Laboratory, University of Eastern Finland, Kuopio, Finland
| | - Antti J Kangas
- Computational Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland
| | - Pasi Soininen
- Computational Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland.,NMR Metabolomics Laboratory, University of Eastern Finland, Kuopio, Finland
| | - Jaana Laitinen
- Finnish Institute of Occupational Health, Helsinki, Finland
| | - Jorma Viikari
- Division of Medicine, University of Turku and Turku University Hospital, Turku, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, University of Tampere and Tampere University Hospital, Tampere, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and School of Medicine, University of Tampere, Tampere, Finland
| | - Markus Perola
- National Institute for Health and Welfare, Helsinki, Finland.,Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland.,University of Tartu, Estonian Genome Center, Tartu, Estonia
| | - Stefan Blankenberg
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland.,Clinic for General and Interventional Cardiology, University Heart Center Hamburg, Hamburg, Germany.,German Center for Cardiovascular Research, Lübeck, Kiel, Germany
| | - Tanja Zeller
- Clinic for General and Interventional Cardiology, University Heart Center Hamburg, Hamburg, Germany.,German Center for Cardiovascular Research, Lübeck, Kiel, Germany
| | - Satu Männistö
- National Institute for Health and Welfare, Helsinki, Finland
| | - Veikko Salomaa
- National Institute for Health and Welfare, Helsinki, Finland
| | - Marjo-Riitta Järvelin
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, Imperial College London, London, UK.,Center for Life Course Health Research and Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Olli T Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland.,Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Mika Ala-Korpela
- Computational Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland.,NMR Metabolomics Laboratory, University of Eastern Finland, Kuopio, Finland.,Computational Medicine, University of Bristol, Bristol, UK.,Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - David A Leon
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK.,Department of Community Medicine, UiT Arctic University of Norway, Tromsø, Norway
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