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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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2
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Kityo A, Lee SA. Independent and additive effects of binge drinking and obesity on liver enzymes: a cross-sectional analysis using the Korean National Health Insurance Service data. Gastroenterol Rep (Oxf) 2024; 12:goad074. [PMID: 38222462 PMCID: PMC10784631 DOI: 10.1093/gastro/goad074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 12/07/2023] [Accepted: 12/10/2023] [Indexed: 01/16/2024] Open
Abstract
Background Binge drinking (BD) has been associated with elevated liver enzymes, but the joint association of BD and adiposity with liver enzymes is understudied. We aimed to examine the combined association of BD and obesity with elevated liver enzymes. Methods Data were obtained from 285,600 patients in the Korean National Health check-up program during 2009-2015. Level I BD (BD I) was defined as alcohol consumption of >60 g (men) or >40 g (women) on one occasion in the previous year. High-intensity BD (HIBD) corresponded to at least two times the BD I levels. General and abdominal obesity were defined by body mass index and waist circumference. Logistic regression was used to examine the independent and joint associations of BD and obesity with elevated alanine aminotransferase (ALT), aspartate aminotransferase (AST), and gamma-glutamyl transferase (GGT) levels. Relative excess risk (RERI), attributable proportion (AP), and synergy index (SI) were calculated to estimate the additive interaction effects. Results The mean age was 42.1 ± 0.03 years and 50.2% were women. Elevated ALT [odds ratio (OR) 1.09, 95% confidence interval (CI) 1.02-1.16], AST (OR 1.16, 95% CI 1.11-1.23), and GGT (OR 1.84, 95% CI 1.05-1.94) were associated with HIBD. Higher odds of elevated ALT (OR 3.57, 95% CI 3.43-3.71), AST (OR 3.47, 95% CI 3.37-3.58), and GGT (OR 2.10, 95% CI 1.98-2.12) were observed in individuals with general obesity. A similar trend was observed for abdominal obesity. The RERI, AP, and SI for the interaction effect of BD and general obesity were 23%, 7%, and 13% for elevated AST levels, and 67%, 24%, and 58% for elevated GGT levels, respectively. Similar effects were observed for the interaction between BD and abdominal obesity. Conclusions Obesity aggravated the odds of elevated liver AST and GGT levels in HIBD.
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Affiliation(s)
- Anthony Kityo
- Department of Preventive Medicine, School of Medicine, Kangwon National University, Gangwon, Republic of Korea
| | - Sang-Ah Lee
- Department of Preventive Medicine, School of Medicine, Kangwon National University, Gangwon, Republic of Korea
- Interdisciplinary Graduate Program in Medical Bigdata Convergence, Kangwon National University, Gangwon, Republic of Korea
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Abstract
The medical disorders of alcoholism rank among the leading public health problems worldwide and the need for predictive and prognostic risk markers for assessing alcohol use disorders (AUD) has been widely acknowledged. Early-phase detection of problem drinking and associated tissue toxicity are important prerequisites for timely initiations of appropriate treatments and improving patient's committing to the objective of reducing drinking. Recent advances in clinical chemistry have provided novel approaches for a specific detection of heavy drinking through assays of unique ethanol metabolites, phosphatidylethanol (PEth) or ethyl glucuronide (EtG). Carbohydrate-deficient transferrin (CDT) measurements can be used to indicate severe alcohol problems. Hazardous drinking frequently manifests as heavy episodic drinking or in combinations with other unfavorable lifestyle factors, such as smoking, physical inactivity, poor diet or adiposity, which aggravate the metabolic consequences of alcohol intake in a supra-additive manner. Such interactions are also reflected in multiple disease outcomes and distinct abnormalities in biomarkers of liver function, inflammation and oxidative stress. Use of predictive biomarkers either alone or as part of specifically designed biological algorithms helps to predict both hepatic and extrahepatic morbidity in individuals with such risk factors. Novel approaches for assessing progression of fibrosis, a major determinant of prognosis in AUD, have also been made available. Predictive algorithms based on the combined use of biomarkers and clinical observations may prove to have a major impact on clinical decisions to detect AUD in early pre-symptomatic stages, stratify patients according to their substantially different disease risks and predict individual responses to treatment.
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Affiliation(s)
- Onni Niemelä
- Department of Laboratory Medicine and Medical Research Unit, Seinäjoki Central Hospital and Tampere University, Seinäjoki, Finland.
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Niemelä O, Aalto M, Bloigu A, Bloigu R, Halkola AS, Laatikainen T. Alcohol Drinking Patterns and Laboratory Indices of Health: Does Type of Alcohol Preferred Make a Difference? Nutrients 2022; 14:4529. [PMID: 36364789 PMCID: PMC9658819 DOI: 10.3390/nu14214529] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 10/23/2022] [Accepted: 10/25/2022] [Indexed: 09/10/2023] Open
Abstract
Although excessive alcohol consumption is a highly prevalent public health problem the data on the associations between alcohol consumption and health outcomes in individuals preferring different types of alcoholic beverages has remained unclear. We examined the relationships between the amounts and patterns of drinking with the data on laboratory indices of liver function, lipid status and inflammation in a national population-based health survey (FINRISK). Data on health status, alcohol drinking, types of alcoholic beverages preferred, body weight, smoking, coffee consumption and physical activity were recorded from 22,432 subjects (10,626 men, 11,806 women), age range 25-74 years. The participants were divided to subgroups based on the amounts of regular alcohol intake (abstainers, moderate and heavy drinkers), patterns of drinking (binge or regular) and the type of alcoholic beverage preferred (wine, beer, cider or long drink, hard liquor or mixed). Regular drinking was found to be more typical in wine drinkers whereas the subjects preferring beer or hard liquor were more often binge-type drinkers and cigarette smokers. Alcohol use in all forms was associated with increased frequencies of abnormalities in the markers of liver function, lipid status and inflammation even at rather low levels of consumption. The highest rates of abnormalities occurred, however, in the subgroups of binge-type drinkers preferring beer or hard liquor. These results demonstrate that adverse consequences of alcohol occur even at moderate average drinking levels especially in individuals who engage in binge drinking and in those preferring beer or hard liquor. Further emphasis should be placed on such patterns of drinking in policies aimed at preventing alcohol-induced adverse health outcomes.
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Affiliation(s)
- Onni Niemelä
- Department of Laboratory Medicine and Medical Research Unit, Seinäjoki Central Hospital and Tampere University, 60220 Seinäjoki, Finland
| | - Mauri Aalto
- Department of Psychiatry, Seinäjoki Central Hospital, Tampere University, 33100 Tampere, Finland
| | - Aini Bloigu
- Center for Life Course Health Research, University of Oulu, 90570 Oulu, Finland
| | - Risto Bloigu
- Infrastructure of Population Studies, Faculty of Medicine, University of Oulu, 90570 Oulu, Finland
| | - Anni S. Halkola
- Department of Laboratory Medicine and Medical Research Unit, Seinäjoki Central Hospital and Tampere University, 60220 Seinäjoki, Finland
| | - Tiina Laatikainen
- Department of Public Health Solutions, National Institute for Health and Welfare (THL), 00271 Helsinki, Finland
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, 70210 Kuopio, Finland
- Joint Municipal Authority for North Karelia Social and Health Services, 80210 Joensuu, Finland
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5
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Liu Y, Gao Y, Fang R, Cao H, Sa J, Wang J, Liu H, Wang T, Cui Y. Identifying complex gene-gene interactions: a mixed kernel omnibus testing approach. Brief Bioinform 2021; 22:6346804. [PMID: 34373892 DOI: 10.1093/bib/bbab305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 07/01/2021] [Accepted: 07/17/2021] [Indexed: 11/12/2022] Open
Abstract
Genes do not function independently; rather, they interact with each other to fulfill their joint tasks. Identification of gene-gene interactions has been critically important in elucidating the molecular mechanisms responsible for the variation of a phenotype. Regression models are commonly used to model the interaction between two genes with a linear product term. The interaction effect of two genes can be linear or nonlinear, depending on the true nature of the data. When nonlinear interactions exist, the linear interaction model may not be able to detect such interactions; hence, it suffers from substantial power loss. While the true interaction mechanism (linear or nonlinear) is generally unknown in practice, it is critical to develop statistical methods that can be flexible to capture the underlying interaction mechanism without assuming a specific model assumption. In this study, we develop a mixed kernel function which combines both linear and Gaussian kernels with different weights to capture the linear or nonlinear interaction of two genes. Instead of optimizing the weight function, we propose a grid search strategy and use a Cauchy transformation of the P-values obtained under different weights to aggregate the P-values. We further extend the two-gene interaction model to a high-dimensional setup using a de-biased LASSO algorithm. Extensive simulation studies are conducted to verify the performance of the proposed method. Application to two case studies further demonstrates the utility of the model. Our method provides a flexible and computationally efficient tool for disentangling complex gene-gene interactions associated with complex traits.
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Affiliation(s)
- Yan Liu
- Division of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, PR China
| | - Yuzhao Gao
- School of Statistics, Shanxi University of Finance and Economics, Taiyuan, PR China
| | - Ruiling Fang
- Division of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, PR China
| | - Hongyan Cao
- Division of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, PR China
| | - Jian Sa
- Division of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, PR China
| | - Jianrong Wang
- Department of Computational Mathematics, Science and Engineering, Michigan State University, East Lansing, MI, USA
| | - Hongqi Liu
- Division of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, PR China
| | - Tong Wang
- Division of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, PR China
| | - Yuehua Cui
- Department of Statistics and Probability, Michigan State University, East Lansing, MI, USA
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6
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Thompson A, King K, Morris AP, Pirmohamed M. Assessing the impact of alcohol consumption on the genetic contribution to mean corpuscular volume. Hum Mol Genet 2021; 30:2040-2051. [PMID: 34104963 PMCID: PMC8522631 DOI: 10.1093/hmg/ddab147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 04/08/2021] [Accepted: 05/25/2021] [Indexed: 11/13/2022] Open
Abstract
The relationship between the genetic loci that influence mean corpuscular volume (MCV) and those associated with excess alcohol drinking are unknown. We used white British participants from the UK Biobank (n = 362 595) to assess the association between alcohol consumption and MCV, and whether this was modulated by genetic factors. Multivariable regression was applied to identify predictors of MCV. GWAS, with and without stratification for alcohol consumption, determined how genetic variants influence MCV. SNPs in ADH1B, ADH1C and ALDH1B were used to construct a genetic score to test the assumption that acetaldehyde formation is an important determinant of MCV. Additional investigations using mendelian randomisation and phenome-wide association analysis were conducted. Increasing alcohol consumption by 40 g/week resulted in a 0.30% (95% CI: 0.30 to 0.31%) increase in MCV (P < 1.0x10-320). Unstratified (irrespective of alcohol intake) GWAS identified 212 loci associated with MCV, of which 108 were novel. There was no heterogeneity of allelic effects by drinking status. No association was found between MCV and the genetic score generated from alcohol metabolising genes. Mendelian randomisation demonstrated a causal effect for alcohol on MCV. Seventy-one SNP-outcome pairs reached statistical significance in phenome-wide association analysis, with evidence of shared genetic architecture for MCV and thyroid dysfunction, and mineral metabolism disorders. MCV increases linearly with alcohol intake in a causal manner. Many genetic loci influence MCV, with new loci identified in this analysis that provide novel biological insights. However, there was no interaction between alcohol consumption and the allelic variants associated with MCV.
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Affiliation(s)
- Andrew Thompson
- Wolfson Centre for Personalised Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.,MRC Centre for Drug Safety Science, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.,Liverpool Centre for Alcohol Research, University of Liverpool, Liverpool, UK
| | - Katharine King
- Wolfson Centre for Personalised Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.,MRC Centre for Drug Safety Science, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.,Division of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, The University of Manchester, Manchester, UK.,Department of Biostatistics, University of Liverpool, Liverpool, UK
| | - Munir Pirmohamed
- Wolfson Centre for Personalised Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.,MRC Centre for Drug Safety Science, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, UK.,Liverpool Centre for Alcohol Research, University of Liverpool, Liverpool, UK.,Liverpool University Hospital, Liverpool, UK.,Liverpool Health Partners, Liverpool, UK
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7
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Mamluk L, Jones T, Ijaz S, Edwards HB, Savović J, Leach V, Moore THM, von Hinke S, Lewis SJ, Donovan JL, Lawlor DA, Davey Smith G, Fraser A, Zuccolo L. Evidence of detrimental effects of prenatal alcohol exposure on offspring birthweight and neurodevelopment from a systematic review of quasi-experimental studies. Int J Epidemiol 2021; 49:1972-1995. [PMID: 31993631 PMCID: PMC7825937 DOI: 10.1093/ije/dyz272] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Revised: 11/25/2019] [Accepted: 01/08/2020] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Systematic reviews of prenatal alcohol exposure effects generally only include conventional observational studies. However, estimates from such studies are prone to confounding and other biases. OBJECTIVES To systematically review the evidence on the effects of prenatal alcohol exposure from randomized controlled trials (RCTs) and observational designs using alternative analytical approaches to improve causal inference. SEARCH STRATEGY Medline, Embase, Web of Science, PsychINFO from inception to 21 June 2018. Manual searches of reference lists of retrieved papers. SELECTION CRITERIA RCTs of interventions to stop/reduce drinking in pregnancy and observational studies using alternative analytical methods (quasi-experimental studies e.g. Mendelian randomization and natural experiments, negative control comparisons) to determine the causal effects of prenatal alcohol exposure on pregnancy and longer-term offspring outcomes in human studies. DATA COLLECTION AND ANALYSIS One reviewer extracted data and another checked extracted data. Risk of bias was assessed using customized risk of bias tools. A narrative synthesis of findings was carried out and a meta-analysis for one outcome. MAIN RESULTS Twenty-three studies were included, representing five types of study design, including 1 RCT, 9 Mendelian randomization and 7 natural experiment studies, and reporting on over 30 outcomes. One study design-outcome combination included enough independent results to meta-analyse. Based on evidence from several studies, we found a likely causal detrimental role of prenatal alcohol exposure on cognitive outcomes, and weaker evidence for a role in low birthweight. CONCLUSION None of the included studies was judged to be at low risk of bias in all domains, results should therefore be interpreted with caution. SYSTEMATIC REVIEW REGISTRATION This study is registered with PROSPERO, registration number CRD42015015941.
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Affiliation(s)
- Loubaba Mamluk
- MRC Integrative Epidemiology Unit, Department of Population Health Sciences, University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR ARC West, University Hospitals Bristol NHS Foundation Trust, Bristol, UK
| | - Timothy Jones
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR ARC West, University Hospitals Bristol NHS Foundation Trust, Bristol, UK
| | - Sharea Ijaz
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR ARC West, University Hospitals Bristol NHS Foundation Trust, Bristol, UK
| | - Hannah B Edwards
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR ARC West, University Hospitals Bristol NHS Foundation Trust, Bristol, UK
| | - Jelena Savović
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR ARC West, University Hospitals Bristol NHS Foundation Trust, Bristol, UK
| | - Verity Leach
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR ARC West, University Hospitals Bristol NHS Foundation Trust, Bristol, UK
| | - Theresa H M Moore
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR ARC West, University Hospitals Bristol NHS Foundation Trust, Bristol, UK
| | - Stephanie von Hinke
- Department of Economics, School of Economics, Finance and Management, University of Bristol, Bristol, UK
| | - Sarah J Lewis
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Jenny L Donovan
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR ARC West, University Hospitals Bristol NHS Foundation Trust, Bristol, UK
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit, Department of Population Health Sciences, University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR ARC West, University Hospitals Bristol NHS Foundation Trust, Bristol, UK
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust, University of Bristol, Bristol, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, Department of Population Health Sciences, University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust, University of Bristol, Bristol, UK
| | - Abigail Fraser
- MRC Integrative Epidemiology Unit, Department of Population Health Sciences, University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust, University of Bristol, Bristol, UK
| | - Luisa Zuccolo
- MRC Integrative Epidemiology Unit, Department of Population Health Sciences, University of Bristol, Bristol, UK
- Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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8
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Lawson DJ, Davies NM, Haworth S, Ashraf B, Howe L, Crawford A, Hemani G, Davey Smith G, Timpson NJ. Is population structure in the genetic biobank era irrelevant, a challenge, or an opportunity? Hum Genet 2020; 139:23-41. [PMID: 31030318 PMCID: PMC6942007 DOI: 10.1007/s00439-019-02014-8] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2018] [Accepted: 04/12/2019] [Indexed: 12/11/2022]
Abstract
Replicable genetic association signals have consistently been found through genome-wide association studies in recent years. The recent dramatic expansion of study sizes improves power of estimation of effect sizes, genomic prediction, causal inference, and polygenic selection, but it simultaneously increases susceptibility of these methods to bias due to subtle population structure. Standard methods using genetic principal components to correct for structure might not always be appropriate and we use a simulation study to illustrate when correction might be ineffective for avoiding biases. New methods such as trans-ethnic modeling and chromosome painting allow for a richer understanding of the relationship between traits and population structure. We illustrate the arguments using real examples (stroke and educational attainment) and provide a more nuanced understanding of population structure, which is set to be revisited as a critical aspect of future analyses in genetic epidemiology. We also make simple recommendations for how problems can be avoided in the future. Our results have particular importance for the implementation of GWAS meta-analysis, for prediction of traits, and for causal inference.
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Affiliation(s)
- Daniel John Lawson
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
| | - Neil Martin Davies
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Simon Haworth
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Bilal Ashraf
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Laurence Howe
- Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, Gower Street, London, WC1E 6BT, UK
| | - Andrew Crawford
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Gibran Hemani
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Nicholas John Timpson
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
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9
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Liver enzymes in alcohol consumers with or without binge drinking. Alcohol 2019; 78:13-19. [PMID: 30890357 DOI: 10.1016/j.alcohol.2019.03.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Revised: 02/28/2019] [Accepted: 03/04/2019] [Indexed: 02/06/2023]
Abstract
BACKGROUND While alcohol use is linked with a wide variety of health problems, the question of whether differences in drinking patterns could yield different outcomes has remained unclear. PATIENTS AND METHODS We measured liver enzymes (ALT, GGT) from alcohol consumers with or without binge drinking from a population-based sample in Finland, where binge-type drinking is common. Data on alcohol use, diet, body weight, lifestyle (smoking, coffee consumption, physical activity), and health status were collected from 19225 subjects (9492 men, 9733 women), aged 25-74 years. The participants were subsequently classified to subgroups, both according to the frequencies of binge drinking and the amounts of regular alcohol intake (low-, medium-, and high-risk drinking). RESULTS The quantity of regular alcohol use was roughly linearly related with GGT and ALT activities. ANOVA analyses of the trends according to the frequency of binge drinking showed a significant GGT increase in both men (p < 0.0005) and women (p < 0.0005), and a significant increase of ALT in men (p < 0.0005). In those with low-risk overall consumption, markedly higher GGT (p < 0.0005) and ALT (p < 0.0005) occurred in those with binge drinking more than once a month, compared with those with no such occasions. Binge drinking occurring ≤1/month also resulted in higher GGT (p < 0.0005) and ALT (p < 0.05) activities. CONCLUSIONS These results emphasize possible adverse consequences of binge drinking on hepatic function even in those with low-risk overall consumption. The pattern of drinking should be more systematically implicated in clinical recommendations for drinking reduction.
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Carter AR, Borges MC, Benn M, Tybjærg-Hansen A, Davey Smith G, Nordestgaard BG, Lawlor DA. Combined Association of Body Mass Index and Alcohol Consumption With Biomarkers for Liver Injury and Incidence of Liver Disease: A Mendelian Randomization Study. JAMA Netw Open 2019; 2:e190305. [PMID: 30848805 PMCID: PMC6484655 DOI: 10.1001/jamanetworkopen.2019.0305] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
IMPORTANCE Individually, higher body mass index (BMI) and alcohol consumption increase the risk of liver disease. Evidence of a joint association is mixed; however, previous studies have not used causal inference methods robust to confounding and reverse causation. Understanding any true effect is key to developing effective interventions to reduce liver disease. OBJECTIVE To investigate the joint association of BMI and alcohol consumption with liver injury biomarkers and incident liver disease using factorial mendelian randomization (MR). DESIGN, SETTING, AND PARTICIPANTS A population-based cohort study (Copenhagen General Population Study) recruited a random sample of Copenhagen, Denmark, residents aged 20 years or older of white, Danish descent (N = 98 643) between November 25, 2003, and July 1, 2014. Data were also obtained from ongoing links to national registers, and then analyzed from September 30, 2016, to April 23, 2018. EXPOSURES High and low BMI and alcohol consumption categories from baseline-measured or self-reported observational data and genetic variants predicting BMI and alcohol consumption. MAIN OUTCOMES AND MEASURES Plasma biomarkers of liver injury (alanine aminotransferase [ALT] and γ-glutamyltransferase [GGT]) and incident cases of liver disease from hospital records were the outcomes. RESULTS Of the 98 643 individuals recruited, 91 552 (54 299 [45.2%] women; mean [SD] age, 58 [13.05] years) with no baseline liver disease were included in main analyses. Individuals had a mean (SD) BMI of 26.2 (4.3) and consumed a mean (SD) of 10.6 (10.2) U/wk of alcohol. In factorial MR analyses, considering the high BMI/high alcohol group as the reference, mean circulating ALT and GGT levels were lowest in the low BMI/low alcohol group (ALT: -2.32%; 95% CI, -4.29% to -0.35%, and GGT: -3.56%; 95% CI, -5.88% to -1.24%). Individuals with low BMI/high alcohol use and high BMI/low alcohol use also had lower mean circulating ALT levels (low BMI/high alcohol use: -1.31%; 95% CI, -1.88% to -0.73%, and high BMI/low alcohol use: -0.81%; 95% CI, -2.86% to 1.22%) and GGT levels (low BMI/high alcohol use: -0.91%; 95% CI, -1.60% to -0.22%, and high BMI/low alcohol use: -1.13%; 95% CI, -3.55% to 1.30%) compared with the high BMI/high alcohol use reference group. These patterns were similar in multivariable factorial analyses. For incident liver disease (N = 580), factorial MR results were less conclusive (odds ratio of liver disease vs high BMI/high alcohol group: 1.01; 95% CI, 0.84 to 1.18, for the low BMI/high alcohol group, 1.22; 95% CI, 0.56 to 1.88 for the high BMI/low alcohol group, and 0.99 (95% CI, 0.41 to 1.56 for the low BMI/low alcohol group). CONCLUSIONS AND RELEVANCE Interventions to reduce both BMI and alcohol consumption might reduce population levels of biomarkers of liver injury more than interventions aimed at either BMI or alcohol use alone. However, it is not clear whether this intervention will directly translate to a reduced risk of liver disease.
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Affiliation(s)
- Alice R. Carter
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Science, Bristol Medical School, University of Bristol, United Kingdom
| | - Maria-Carolina Borges
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Science, Bristol Medical School, University of Bristol, United Kingdom
| | - Marianne Benn
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen, Denmark
- The Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen, Denmark
- Copenhagen University Hospital, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Anne Tybjærg-Hansen
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen, Denmark
- The Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen, Denmark
- Copenhagen University Hospital, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Science, Bristol Medical School, University of Bristol, United Kingdom
| | - Børge G. Nordestgaard
- The Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen, Denmark
- Copenhagen University Hospital, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen, Denmark
| | - Debbie A. Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Science, Bristol Medical School, University of Bristol, United Kingdom
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Yang M, Zhang Y, Ren J. ALDH2 Polymorphism and Ethanol Consumption: A Genetic-Environmental Interaction in Carcinogenesis. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019; 1193:229-236. [DOI: 10.1007/978-981-13-6260-6_14] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
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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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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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Xu L, Jiang CQ, Cheng KK, Au Yeung SLR, Zhang WS, Lam TH, Schooling CM. Alcohol Use and Gamma-Glutamyltransferase Using a Mendelian Randomization Design in the Guangzhou Biobank Cohort Study. PLoS One 2015; 10:e0137790. [PMID: 26356841 PMCID: PMC4565586 DOI: 10.1371/journal.pone.0137790] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2015] [Accepted: 08/21/2015] [Indexed: 12/11/2022] Open
Abstract
Background Observational studies and small intervention studies suggest alcohol raises gamma-glutamyltransferase (GGT). We used Mendelian randomization to assess the causal effect of alcohol use on GGT in older Chinese people. Methods An instrumental variable (IV) analysis in 2,321 men and 2,757 women aged 50+ years from phase 3 of the Guangzhou Biobank Cohort Study with ALDH2 (rs671) genotyped, alcohol use and GGT available was used to assess the causal effect of alcohol use on GGT. Rs671 was used as an IV and F-statistics was used to test for weak instrument hypothesis. An F-statistic of ≥10 indicates the IV is not weak. Results In men, the F-statistic for rs671 on alcohol use was 70. Using IV analysis alcohol use increased GGT by 10.60 U/L per alcohol unit (10 gram ethanol) per day (95% confidence interval (CI) 6.58 to 14.62). The estimate was lower in observational multivariate regression: 3.48 U/L GGT per alcohol unit per day (95% CI 2.84 to 4.11) adjusted for age, education, physical activity and smoking. In women, rs671 was not associated with alcohol or GGT and the F-statistic was 7 precluding IV analysis. Conclusion In Mendelian randomization, we found confirmative evidence that alcohol use increases GGT among Southern Chinese men. Moreover, we found that the ALDH2 variant rs671 was not associated with GGT among Southern Chinese women who generally consume very low levels of alcohol. Taken together our findings strongly suggest that alcohol increases GGT, although we cannot rule out the possibility that other unknown factors may cause a different relation between alcohol and GGT in other populations.
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Affiliation(s)
- Lin Xu
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | | | - Kar Keung Cheng
- Public Health, Epidemiology and Biostatistics, University of Birmingham, Birmingham, UK
| | - Shiu Lun Ryan Au Yeung
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | | | - Tai Hing Lam
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
- * E-mail:
| | - Catherine Mary Schooling
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
- School of Urban Public Health, Hunter College and CUNY School of Public Health, New York, New York, United States of America
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