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Hwang LD, Evans DM. A Note on Modelling Bidirectional Feedback Loops in Mendelian Randomization Studies. Behav Genet 2024; 54:367-373. [PMID: 38822217 PMCID: PMC11196367 DOI: 10.1007/s10519-024-10183-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Accepted: 05/05/2024] [Indexed: 06/02/2024]
Abstract
Structural equation models (SEMs) involving feedback loops may offer advantages over standard instrumental variables estimators in terms of modelling causal effects in the presence of bidirectional relationships. In the following note, we show that in the case of a single "exposure" and "outcome" variable, modelling relationships using a SEM with a simple bidirectional linear feedback loop offers no advantage over traditional instrumental variables estimators in terms of consistency (i.e. both approaches yield consistent estimates of the causal effect, provided that causal estimates are obtained in both directions). In the case of finite samples, traditional IV estimators and SEM exhibited similar power across many of the conditions we examined, although which method performed best depended on the residual correlation between variables and the strength of the instruments. In particular, the power of SEM was insensitive to the residual correlation between variables, whereas the power of the Wald estimator/2SLS improved (deteriorated) relative to SEM as the magnitude of the residual correlation increased (decreased) assuming a positive causal effect of the exposure on the outcome. The power of SEM improved relative to the Wald estimator/2SLS as the instruments explained more residual variance in the "outcome" variable.
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Affiliation(s)
- Liang-Dar Hwang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
| | - David M Evans
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia.
- The Frazer Institute, The University of Queensland, Woolloongabba, QLD, 4102, Australia.
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
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2
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Noce D, Foco L, Orth-Höller D, König E, Barbieri G, Pietzner M, Ghasemi-Semeskandeh D, Coassin S, Fuchsberger C, Gögele M, Del Greco M F, De Grandi A, Summerer M, Wheeler E, Langenberg C, Lass-Flörl C, Pramstaller PP, Kronenberg F, Würzner R, Pattaro C. Genetic determinants of complement activation in the general population. Cell Rep 2024; 43:113611. [PMID: 38159276 DOI: 10.1016/j.celrep.2023.113611] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 09/08/2023] [Accepted: 12/07/2023] [Indexed: 01/03/2024] Open
Abstract
Complement is a fundamental innate immune response component. Its alterations are associated with severe systemic diseases. To illuminate the complement's genetic underpinnings, we conduct genome-wide association studies of the functional activity of the classical (CP), lectin (LP), and alternative (AP) complement pathways in the Cooperative Health Research in South Tyrol study (n = 4,990). We identify seven loci, encompassing 13 independent, pathway-specific variants located in or near complement genes (CFHR4, C7, C2, MBL2) and non-complement genes (PDE3A, TNXB, ABO), explaining up to 74% of complement pathways' genetic heritability and implicating long-range haplotypes associated with LP at MBL2. Two-sample Mendelian randomization analyses, supported by transcriptome- and proteome-wide colocalization, confirm known causal pathways, establish within-complement feedback loops, and implicate causality of ABO on LP and of CFHR2 and C7 on AP. LP causally influences collectin-11 and KAAG1 levels and the risk of mouth ulcers. These results build a comprehensive resource to investigate the role of complement in human health.
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Affiliation(s)
- Damia Noce
- Institute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Via Volta 21, 39100 Bolzano, Italy; Institute of Hygiene & Medical Microbiology, Department of Hygiene, Microbiology and Public Health, Medical University of Innsbruck, Schöpfstr. 41, 6020 Innsbruck, Austria
| | - Luisa Foco
- Institute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Via Volta 21, 39100 Bolzano, Italy
| | - Dorothea Orth-Höller
- Institute of Hygiene & Medical Microbiology, Department of Hygiene, Microbiology and Public Health, Medical University of Innsbruck, Schöpfstr. 41, 6020 Innsbruck, Austria; MB-LAB - Clinical Microbiology Laboratory, Franz-Fischer-Str. 7b, 6020 Innsbruck, Austria
| | - Eva König
- Institute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Via Volta 21, 39100 Bolzano, Italy
| | - Giulia Barbieri
- Institute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Via Volta 21, 39100 Bolzano, Italy; Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Maik Pietzner
- Computational Medicine, Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, Berlin, Germany; MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Dariush Ghasemi-Semeskandeh
- Institute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Via Volta 21, 39100 Bolzano, Italy; Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Stefan Coassin
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstr. 41, 6020 Innsbruck, Austria
| | - Christian Fuchsberger
- Institute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Via Volta 21, 39100 Bolzano, Italy
| | - Martin Gögele
- Institute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Via Volta 21, 39100 Bolzano, Italy
| | - Fabiola Del Greco M
- Institute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Via Volta 21, 39100 Bolzano, Italy
| | - Alessandro De Grandi
- Institute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Via Volta 21, 39100 Bolzano, Italy
| | - Monika Summerer
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstr. 41, 6020 Innsbruck, Austria
| | - Eleanor Wheeler
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Claudia Langenberg
- Computational Medicine, Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Cornelia Lass-Flörl
- Institute of Hygiene & Medical Microbiology, Department of Hygiene, Microbiology and Public Health, Medical University of Innsbruck, Schöpfstr. 41, 6020 Innsbruck, Austria
| | - Peter Paul Pramstaller
- Institute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Via Volta 21, 39100 Bolzano, Italy
| | - Florian Kronenberg
- Institute of Genetic Epidemiology, Medical University of Innsbruck, Schöpfstr. 41, 6020 Innsbruck, Austria.
| | - Reinhard Würzner
- Institute of Hygiene & Medical Microbiology, Department of Hygiene, Microbiology and Public Health, Medical University of Innsbruck, Schöpfstr. 41, 6020 Innsbruck, Austria.
| | - Cristian Pattaro
- Institute for Biomedicine (affiliated to the University of Lübeck), Eurac Research, Via Volta 21, 39100 Bolzano, Italy.
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de La Harpe R, Schoeler T, Thorball CW, Thomas A, Kutalik Z, Vaucher J. Cannabis use and atherosclerotic cardiovascular disease: a Mendelian randomization study. BMC Cardiovasc Disord 2023; 23:611. [PMID: 38093188 PMCID: PMC10717446 DOI: 10.1186/s12872-023-03641-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 11/29/2023] [Indexed: 12/17/2023] Open
Abstract
BACKGROUND Association between cannabis use and development of atherosclerotic cardiovascular disease (ASCVD) is inconsistent and challenging to interpret, given existing study limitations. METHODS Sixty five independent single-nucleotide polymorphisms (SNPs), obtained from a genome-wide association study on lifetime cannabis use, were employed as genetic instruments to estimate the effects of genetically indexed cannabis use on risk of coronary artery disease (CAD) and acute ischemic stroke (IS) using a two-sample Mendelian randomization (MR) approach. Summary statistics on CAD (CARDIoGRAMplusC4D; 60,801 cases and 123,504 controls) and IS (MEGASTROKE; 34,217 cases and 406,111 controls) were obtained separately. A comprehensive review of the observational literature on cannabis use and CAD or IS was also performed and contrasted with MR results. RESULTS There was no causal effect of cannabis use on the risk of CAD (odds ratio (OR) per ever-users vs. never-users 0.93; 95% confidence interval (CI), 0.83 to 1.03) or IS (OR 1.05; 95%CI, 0.93 to 1.19). Sensitivity analyses yielded similar results, and no heterogeneity and directional pleiotropy was observed. Our meta-analysis of observational studies showed no significant association between ever use of cannabis with risk of CAD (k = 6 studies; ORpooled = 1.23, 95%CI 0.78 to 1.69), nor with IS (k = 6 studies; ORpooled = 1.22, 95%CI 0.95 to 1.50). CONCLUSION Using a genetic approach approximating a clinical trial does not provide evidence consistent with a causal effect of genetic predisposition to cannabis use on CAD or IS development. Further studies are needed to replicate our findinds, an to investigate more precisely the risk of ASCVD in relation to the quantity, type, route of administration, or the age at exposure to cannabis.
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Affiliation(s)
- Roxane de La Harpe
- Department of Medicine, Division of Internal Medicine, University Hospital of Lausanne, Rue du Bugnon 46, 1011, Lausanne, Switzerland.
| | - Tabea Schoeler
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Christian W Thorball
- Precision Medicine Unit, Biomedical Data Science Center, Lausanne University Hospital of Lausanne, Chemin des Roches 1a/1b, 1010, Lausanne, Switzerland
| | - Aurélien Thomas
- Faculty Unit of Toxicology, CURML, Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland
| | - Zoltán Kutalik
- Swiss Institute of Bioinformatics, 1015, Lausanne, Switzerland
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Centre universitaire de médecine et santé publique, Lausanne, Switzerland
| | - Julien Vaucher
- Department of Medicine, Division of Internal Medicine, University Hospital of Lausanne, Rue du Bugnon 46, 1011, Lausanne, Switzerland
- HFR Freiburg Kantonspital, Lausanne, Switzerland
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Howell AE, Relton C, Martin RM, Zheng J, Kurian KM. Role of DNA methylation in the relationship between glioma risk factors and glioma incidence: a two-step Mendelian randomization study. Sci Rep 2023; 13:6590. [PMID: 37085538 PMCID: PMC10121678 DOI: 10.1038/s41598-023-33621-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 04/15/2023] [Indexed: 04/23/2023] Open
Abstract
Genetic evidence suggests glioma risk is altered by leukocyte telomere length, allergic disease (asthma, hay fever or eczema), alcohol consumption, childhood obesity, low-density lipoprotein cholesterol (LDLc) and triglyceride levels. DNA methylation (DNAm) variation influences many of these glioma-related traits and is an established feature of glioma. Yet the causal relationship between DNAm variation with both glioma incidence and glioma risk factors is unknown. We applied a two-step Mendelian randomization (MR) approach and several sensitivity analyses (including colocalization and Steiger filtering) to assess the association of DNAm with glioma risk factors and glioma incidence. We used data from a recently published catalogue of germline genetic variants robustly associated with DNAm variation in blood (32,851 participants) and data from a genome-wide association study of glioma risk (12,488 cases and 18,169 controls, sub-divided into 6191 glioblastoma cases and 6305 non-glioblastoma cases). MR evidence indicated that DNAm at 3 CpG sites (cg01561092, cg05926943, cg01584448) in one genomic region (HEATR3) had a putative association with glioma and glioblastoma risk (False discovery rate [FDR] < 0.05). Steiger filtering provided evidence against reverse causation. Colocalization presented evidence against genetic confounding and suggested that differential DNAm at the 3 CpG sites and glioma were driven by the same genetic variant. MR provided little evidence to suggest that DNAm acts as a mediator on the causal pathway between risk factors previously examined and glioma onset. To our knowledge, this is the first study to use MR to appraise the causal link of DNAm with glioma risk factors and glioma onset. Subsequent analyses are required to improve the robustness of our results and rule out horizontal pleiotropy.
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Affiliation(s)
- Amy E Howell
- Brain Tumour Research Centre, Institute of Clinical Neurosciences, University of Bristol, Bristol, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Richard M Martin
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- National Institute for Health Research (NIHR) Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, Bristol, UK
| | - Jie Zheng
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Kathreena M Kurian
- Brain Tumour Research Centre, Institute of Clinical Neurosciences, University of Bristol, Bristol, UK.
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Yuan R, Liu K, Cai Y, He F, Xiao X, Zou J. Body shape and risk of glaucoma: A Mendelian randomization. Front Med (Lausanne) 2022; 9:999974. [PMID: 36213644 PMCID: PMC9538570 DOI: 10.3389/fmed.2022.999974] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 08/29/2022] [Indexed: 12/04/2022] Open
Abstract
Background Body size (BS) is one of the risk factors for the development of many clinical diseases, but the relationship between BS and glaucoma is controversial. Herein, we try to use Mendelian randomization (MR) method to study BS causal association with glaucoma risk from the genetic level. Methods The Body Size was determined through anthropometric traits (ATs), such as body mass index (BMI), waist-to-hip ratio adjusted by body mass index (WHRadjBMI), waist-to-hip ratio (WHR), and waist circumference (WC). Association of single nucleotide polymorphisms (SNPs) with each AT and glaucoma were determined individually from the aggregated data of the Genetic Investigation of Anthropometric Traits (GIANT) consortium and the FinnGen study summary data (8,591 cases with glaucoma and 210,201 controls). To explore the role of BS and glaucoma, a two-sample MR analysis was performed on genome-wide association study (GWAS) data. Besides, three MR methods [inverse variance weighted (IVW), Weighted median, and MR-Egger regression] were used to get the whole causal estimate for multiple instrumental SNPs. Results BMI (OR = 1.20; 95% CI = 1.02-1.41; P = 0.03) and WC (OR = 1.32; 95% CI =1.04-1.69; P = 0.03) were associated with a risk of glaucoma. Besides, genetically predicted WHRadjBMI (OR = 1.10; 95% CI = 0.88-1.35; P = 0.43) and WHR (OR = 1.22; 95% CI = 0.93-1,572; P = 0.14) were not associated with glaucoma. No heterogeneity and directional pleiotropy were detected. Conclusion The data of this study revealed that increased BMI and WC are potential risk factors for glaucoma, and WHRadjBMI and WHR are not associated with the occurrence of glaucoma.
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Affiliation(s)
- Ruolan Yuan
- Eye Center of Xiangya Hospital, Hunan Key Laboratory of Ophthalmology, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Kangcheng Liu
- Jiangxi Clinical Research Center for Ophthalmic Disease, Jiangxi Research Institute of Ophthalmology and Visual Science, Affiliated Eye Hospital of Nanchang University, Nanchang, China
| | - Yingjun Cai
- Eye Center of Xiangya Hospital, Hunan Key Laboratory of Ophthalmology, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
| | - Fei He
- The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Xiaoxiong Xiao
- Eye Center of Xiangya Hospital, Hunan Key Laboratory of Ophthalmology, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
- Department of Thoracic Surgery, Xiangya Hospital, Central South University, Changsha, China
| | - Jing Zou
- Eye Center of Xiangya Hospital, Hunan Key Laboratory of Ophthalmology, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, China
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Li Y, Liu X, Tu R, Hou J, Zhuang G. Mendelian Randomization Analysis of the Association of SOCS3 Methylation with Abdominal Obesity. Nutrients 2022; 14:nu14183824. [PMID: 36145200 PMCID: PMC9503364 DOI: 10.3390/nu14183824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Revised: 09/06/2022] [Accepted: 09/13/2022] [Indexed: 11/16/2022] Open
Abstract
This study was conducted to evaluate the potential causality association of SOCS3 methylation with abdominal obesity using Mendelian randomization. A case-control study, including 1064 participants, was carried out on Chinese subjects aged 18 to 79. MethylTargetTM was used to detect the methylation level for each CpG site of SOCS3, and SNPscan® was applied to measure the single-nucleotide polymorphism (SNP) genotyping. The logistic regression was used to assess the relationship of SOCS3 methylation level and SNP genotyping with abdominal obesity. Three types of Mendelian randomization methods were implemented to examine the potential causality between SOCS3 methylation and obesity based on the SNP of SOCS3 as instrumental variables. SOCS3 methylation levels were inversely associated with abdominal obesity in five CpG sites (effect estimates ranged from 0.786 (Chr17:76356054) to 0.851 (Chr17:76356084)), and demonstrated positively association in 18 CpG sites (effect estimates ranged from 1.243 (Chr17:76354990) to 1.325 (Chr17:76355061)). The causal relationship between SOCS3 methylation and abdominal obesity was found using the maximum-likelihood method and Mendelian randomization method of penalized inverse variance weighted (MR-IVW), and the β values (95% CI) were 5.342 (0.215, 10.469) and 4.911 (0.259, 9.564), respectively. The causality was found between the SOCS3 methylation level and abdominal obesity in the Chinese population.
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Affiliation(s)
- Yuqian Li
- Departmentof Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Centre, Xi’an 710061, China
- Department of Clinical Pharmacology, School of Pharmaceutical Science, Zhengzhou University, Zhengzhou 450052, China
| | - Xiaotian Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Zhengzhou University, Zhengzhou 450052, China
| | - Runqi Tu
- Department of Epidemiology and Biostatistics, School of Public Health, Zhengzhou University, Zhengzhou 450052, China
| | - Jian Hou
- Department of Epidemiology and Biostatistics, School of Public Health, Zhengzhou University, Zhengzhou 450052, China
| | - Guihua Zhuang
- Departmentof Epidemiology and Biostatistics, School of Public Health, Xi’an Jiaotong University Health Science Centre, Xi’an 710061, China
- Correspondence: ; Tel.: +86-29-826-551-03
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Jin A, Wang M, Chen W, Yan H, Xiang X, Pan Y. Differential Effects of Genetically Determined Cholesterol Efflux Capacity on Coronary Artery Disease and Ischemic Stroke. Front Cardiovasc Med 2022; 9:891148. [PMID: 35859596 PMCID: PMC9289203 DOI: 10.3389/fcvm.2022.891148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Accepted: 06/14/2022] [Indexed: 12/02/2022] Open
Abstract
Background Observational studies indicated that cholesterol efflux capacity (CEC) of high-density lipoprotein (HDL) is inversely associated with cardiovascular events, independently of the HDL cholesterol concentration. The aim of the study is to examine the casual relevance of CEC for coronary artery disease (CAD) and myocardial infarction (MI), and compare it with that for ischemic stroke and its subtypes using a Mendelian randomization approach. Methods We performed a 2-sample Mendelian randomization to estimate the casual relationship of CEC with the risk of CAD, MI, and ischemic stroke. A CEC-related genetic variant (rs141622900) and other five genetic variants were used as the instrumental variables. Association of genetic variants with CAD were estimated in a GWAS involving 60,801 CAD cases and 123,504 controls. They were then compared with the associations of these variants with ischemic stroke and its subtypes (large vessel, small vessel, and cardioembolic) involving 40,585 ischemic stroke cases and 406,111 controls. Results Using the SNP of rs141622900 as the instrument, a 1-SD increase in CEC was associated with 45% lower risk for CAD (odds ratio [OR] 0.55, 95% confidence interval [CI] 0.44–0.69, p < 0.001) and 33% lower risk for MI (odds ratio [OR] 0.67, 95% CI 0.52–0.87, p = 0.002). By contrast, the causal effect of CEC was much weaker for ischemic stroke (odds ratio [OR] 0.79, 95% CI 0.64–0.97, p = 0.02; p for heterogeneity = 0.03) and, in particular, for cardioembolic stroke (p for heterogeneity = 0.006) when compared with that for CAD. Results using five genetic variants as the instrument also indicated consistently weaker effects on ischemic stroke than on CAD. Conclusion Genetic predicted higher CEC may be associated with decreased risk of CAD. However, the casual association of CEC with ischemic stroke and specific subtypes would need to be validated in further Mendelian randomization studies.
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Affiliation(s)
- Aoming Jin
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Mengxing Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Weiqi Chen
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Hongyi Yan
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xianglong Xiang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yuesong Pan
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- *Correspondence: Yuesong Pan
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Kim H, Kim K, Han B. Exploration of errors in variance caused by using the first-order approximation in Mendelian randomization. Genomics Inform 2022; 20:e9. [PMID: 35399008 PMCID: PMC9002003 DOI: 10.5808/gi.21060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 01/23/2022] [Indexed: 11/20/2022] Open
Abstract
Mendelian randomization (MR) uses genetic variation as a natural experiment to investigate the causal effects of modifiable risk factors (exposures) on outcomes. Two-sample Mendelian randomization (2SMR) is widely used to measure causal effects between exposures and outcomes via genome-wide association studies. 2SMR can increase statistical power by utilizing summary statistics from large consortia such as the UK Biobank. However, the first-order term approximation of standard error is commonly used when applying 2SMR. This approximation can underestimate the variance of causal effects in MR, which can lead to an increased false-positive rate. An alternative is to use the second-order approximation of the standard error, which can considerably correct for the deviation of the first-order approximation. In this study, we simulated MR to show the degree to which the first-order approximation underestimates the variance. We show that depending on the specific situation, the first-order approximation can underestimate the variance almost by half when compared to the true variance, whereas the second-order approximation is robust and accurate.
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Affiliation(s)
- Hakin Kim
- Interdisciplinary Program of Bioengineering, Seoul National University College of Engineering, Seoul 08826, Korea
| | - Kunhee Kim
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul 03080, Korea.,Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.,UTHealth Graduate School of Biomedical Sciences, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Buhm Han
- Interdisciplinary Program of Bioengineering, Seoul National University College of Engineering, Seoul 08826, Korea.,Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul 03080, Korea
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Bond TA, Richmond RC, Karhunen V, Cuellar-Partida G, Borges MC, Zuber V, Couto Alves A, Mason D, Yang TC, Gunter MJ, Dehghan A, Tzoulaki I, Sebert S, Evans DM, Lewin AM, O'Reilly PF, Lawlor DA, Järvelin MR. Exploring the causal effect of maternal pregnancy adiposity on offspring adiposity: Mendelian randomisation using polygenic risk scores. BMC Med 2022; 20:34. [PMID: 35101027 PMCID: PMC8805234 DOI: 10.1186/s12916-021-02216-w] [Citation(s) in RCA: 8] [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: 08/02/2021] [Accepted: 12/13/2021] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Greater maternal adiposity before or during pregnancy is associated with greater offspring adiposity throughout childhood, but the extent to which this is due to causal intrauterine or periconceptional mechanisms remains unclear. Here, we use Mendelian randomisation (MR) with polygenic risk scores (PRS) to investigate whether associations between maternal pre-/early pregnancy body mass index (BMI) and offspring adiposity from birth to adolescence are causal. METHODS We undertook confounder adjusted multivariable (MV) regression and MR using mother-offspring pairs from two UK cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC) and Born in Bradford (BiB). In ALSPAC and BiB, the outcomes were birthweight (BW; N = 9339) and BMI at age 1 and 4 years (N = 8659 to 7575). In ALSPAC only we investigated BMI at 10 and 15 years (N = 4476 to 4112) and dual-energy X-ray absorptiometry (DXA) determined fat mass index (FMI) from age 10-18 years (N = 2659 to 3855). We compared MR results from several PRS, calculated from maternal non-transmitted alleles at between 29 and 80,939 single nucleotide polymorphisms (SNPs). RESULTS MV and MR consistently showed a positive association between maternal BMI and BW, supporting a moderate causal effect. For adiposity at most older ages, although MV estimates indicated a strong positive association, MR estimates did not support a causal effect. For the PRS with few SNPs, MR estimates were statistically consistent with the null, but had wide confidence intervals so were often also statistically consistent with the MV estimates. In contrast, the largest PRS yielded MR estimates with narrower confidence intervals, providing strong evidence that the true causal effect on adolescent adiposity is smaller than the MV estimates (Pdifference = 0.001 for 15-year BMI). This suggests that the MV estimates are affected by residual confounding, therefore do not provide an accurate indication of the causal effect size. CONCLUSIONS Our results suggest that higher maternal pre-/early-pregnancy BMI is not a key driver of higher adiposity in the next generation. Thus, they support interventions that target the whole population for reducing overweight and obesity, rather than a specific focus on women of reproductive age.
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Affiliation(s)
- Tom A Bond
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK.
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK.
- The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, Australia.
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Rebecca C Richmond
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Ville Karhunen
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Center for Life-course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Research Unit of Mathematical Sciences, University of Oulu, Oulu, Finland
| | - Gabriel Cuellar-Partida
- The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, Australia
- 23andMe, Inc., Sunnyvale, CA, USA
| | - Maria Carolina Borges
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Verena Zuber
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- MRC Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Alexessander Couto Alves
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
| | - Dan Mason
- Born in Bradford, Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Tiffany C Yang
- Born in Bradford, Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Marc J Gunter
- Section of Nutrition and Metabolism, IARC, Lyon, France
| | - Abbas Dehghan
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Ioanna Tzoulaki
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
| | - Sylvain Sebert
- Center for Life-course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - David M Evans
- The University of Queensland Diamantina Institute, The University of Queensland, Brisbane, Australia
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Australia
| | - Alex M Lewin
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
| | - Paul F O'Reilly
- Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Marjo-Riitta Järvelin
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Center for Life-course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK
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10
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Abstract
Mendelian randomization (MR) is a method of studying the causal effects of modifiable exposures (i.e., potential risk factors) on health, social, and economic outcomes using genetic variants associated with the specific exposures of interest. MR provides a more robust understanding of the influence of these exposures on outcomes because germline genetic variants are randomly inherited from parents to offspring and, as a result, should not be related to potential confounding factors that influence exposure-outcome associations. The genetic variant can therefore be used as a tool to link the proposed risk factor and outcome, and to estimate this effect with less confounding and bias than conventional epidemiological approaches. We describe the scope of MR, highlighting the range of applications being made possible as genetic data sets and resources become larger and more freely available. We outline the MR approach in detail, covering concepts, assumptions, and estimation methods. We cover some common misconceptions, provide strategies for overcoming violation of assumptions, and discuss future prospects for extending the clinical applicability, methodological innovations, robustness, and generalizability of MR findings.
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Affiliation(s)
- Rebecca C Richmond
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, United Kingdom
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, United Kingdom
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Bristol BS1 3NU, United Kingdom
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11
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Hazewinkel AD, Richmond RC, Wade KH, Dixon P. Mendelian randomization analysis of the causal impact of body mass index and waist-hip ratio on rates of hospital admission. ECONOMICS AND HUMAN BIOLOGY 2022; 44:101088. [PMID: 34894623 PMCID: PMC8784824 DOI: 10.1016/j.ehb.2021.101088] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 10/27/2021] [Accepted: 11/21/2021] [Indexed: 05/31/2023]
Abstract
We analyze how measures of adiposity - body mass index (BMI) and waist hip ratio (WHR) - causally influence rates of hospital admission. Conventional analyses of this relationship are susceptible to omitted variable bias from variables that jointly influence both hospital admission and adipose status. We implement a novel quasi-Poisson instrumental variable model in a Mendelian randomization framework, identifying causal effects from random perturbations to germline genetic variation. We estimate the individual and joint effects of BMI, WHR, and WHR adjusted for BMI. We also implement multivariable instrumental variable methods in which the causal effect of one exposure is estimated conditionally on the causal effect of another exposure. Data on 310,471 participants and over 550,000 inpatient admissions in the UK Biobank were used to perform one-sample and two-sample Mendelian randomization analyses. The results supported a causal role of adiposity on hospital admissions, with consistency across all estimates and sensitivity analyses. Point estimates were generally larger than estimates from comparable observational specifications. We observed an attenuation of the BMI effect when adjusting for WHR in the multivariable Mendelian randomization analyses, suggesting that an adverse fat distribution, rather than a higher BMI itself, may drive the relationship between adiposity and risk of hospital admission.
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Affiliation(s)
- Audinga-Dea Hazewinkel
- Population Health Sciences, Bristol Medical School, University of Bristol, UK; MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, UK.
| | - Rebecca C Richmond
- Population Health Sciences, Bristol Medical School, University of Bristol, UK; MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, UK
| | - Kaitlin H Wade
- Population Health Sciences, Bristol Medical School, University of Bristol, UK; MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, UK
| | - Padraig Dixon
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, UK; Nuffield Department of Primary Care Health Sciences, University of Oxford, UK
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12
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Chen PS, Tang LY, Chang HH. Roles of C-reactive protein polymorphisms and life event changes on cognitive function in bipolar patients receiving valproate. Int J Immunopathol Pharmacol 2022; 36:3946320221084835. [PMID: 35377256 PMCID: PMC8984865 DOI: 10.1177/03946320221084835] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Introduction Patients with bipolar disorder (BD) exhibit an inflamed condition that is
associated with metabolic disturbance and cognitive impairment. Whether
inflammation, represented by C-reactive protein (CRP), is causally
associated with BD and influences treatment outcome has not been
established. Methods We examined whether CRP is a causal factor for the risk of BD in drug-naïve,
depressed BD patients and investigated whether polymorphisms in
CRP and life event changes influence cognitive function
in BD patients receiving valproate (VPA) treatment. Results Our results showed that BD patients had significantly higher CRP levels and
worse cognitive function than the controls, while the frequencies of
CRP single nucleotide polymorphisms in BD patients and
in controls were not different. In addition, the life event scale score was
higher for BD patients than for controls. Furthermore, the genotypes of
CRP polymorphisms and the interactions between
polymorphisms of CRP and life event scale score had a
significant influence on cognitive performance in BD patients after 12 weeks
of VPA treatment. Conclusion Our study demonstrated the clinical utility of the application of functional
genetics in clarifying the interactions among CRP, life event stress, and BD
and suggested the important roles of CRP gene–environment
interactions in developing treatment strategies for BD.
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Affiliation(s)
- Po See Chen
- Department of Psychiatry, National Cheng Kung University Hospital, College of Medicine, 38026National Cheng Kung University, Tainan, Taiwan.,Institute of Behavioral Medicine, College of Medicine, 38026National Cheng Kung University, Tainan, Taiwan
| | - Li-Yi Tang
- Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, 38026National Cheng Kung University, Tainan, Taiwan
| | - Hui Hua Chang
- Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, 38026National Cheng Kung University, Tainan, Taiwan.,School of Pharmacy, College of Medicine, 38026National Cheng Kung University, Tainan, Taiwan.,Department of Pharmacy, National Cheng Kung University Hospital, College of Medicine, 38026National Cheng Kung University, Tainan, Taiwan.,Department of Pharmacy, National Cheng Kung University Hospital, Dou-Liou Branch, Yunlin, Taiwan
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13
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Estimating the influence of body mass index (BMI) on mortality using offspring BMI as an instrumental variable. Int J Obes (Lond) 2022; 46:77-84. [PMID: 34497352 PMCID: PMC7612209 DOI: 10.1038/s41366-021-00962-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 08/12/2021] [Accepted: 08/27/2021] [Indexed: 02/07/2023]
Abstract
OBJECTIVE High body mass index (BMI) is an important predictor of mortality but estimating underlying causality is hampered by confounding and pre-existing disease. Here, we use information from the offspring to approximate parental BMIs, with an aim to avoid biased estimation of mortality risk caused by reverse causality. METHODS The analyses were based on information on 9674 offspring-mother and 9096 offspring-father pairs obtained from the 1958 British birth cohort. Parental BMI-mortality associations were analysed using conventional methods and using offspring BMI as a proxy, or instrument, for their parents' BMI. RESULTS In the conventional analysis, associations between parental BMI and all-cause mortality were U-shaped (Pcurvature < 0.001), while offspring BMI had linear associations with parental mortality (Ptrend < 0.001, Pcurvature > 0.46). Curvature was particularly pronounced for mortality from respiratory diseases and from lung cancer. Instrumental variable analyses suggested a positive association between BMI and mortality from all causes [mothers: HR per SD of BMI 1.43 (95% CI 1.21-1.69), fathers: HR 1.17 (1.00-1.36)] and from coronary heart disease [mothers: HR 1.65 (1.15-2.36), fathers: HR 1.51 (1.17-1.97)]. These were larger than HR from the equivalent conventional analyses, despite some attenuation by adjustment for social indicators and smoking. CONCLUSIONS Analyses using offspring BMI as a proxy for parental BMI suggest that the apparent adverse consequences of low BMI are considerably overestimated and adverse consequences of overweight are underestimated in conventional epidemiological studies.
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14
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Abstract
Making drug development more efficient by identifying promising drug targets can contribute to resource savings. Identifying promising drug targets using human genetic approaches can remove barriers related to translation. In addition, genetic information can be used to identify potentially causal relationships between a drug target and disease. Mendelian randomization (MR) is a class of approaches used to identify causal associations between pairs of genetically predicted traits using data from human genetic studies. MR can be used to prioritize candidate drug targets by predicting disease outcomes and adverse events that could result from the manipulation of a drug target. The theory behind MR is reviewed, including a discussion of MR assumptions, different MR analytical methods, tests for violations of assumptions, and MR methods that can be robust to some violations of MR assumptions. A protocol to perform two-sample MR (2SMR) with summary genome-wide association study (GWAS) results is described. An example of 2SMR examining the causal relationship between low-density lipoprotein (LDL) and coronary artery disease (CAD) is provided as an illustration of the protocol.
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Affiliation(s)
- Daniel S Evans
- California Pacific Medical Center Research Institute, San Francisco, CA, USA.
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA.
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15
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Jones HJ, Borges MC, Carnegie R, Mongan D, Rogers PJ, Lewis SJ, Thompson AD, Zammit S. Associations between plasma fatty acid concentrations and schizophrenia: a two-sample Mendelian randomisation study. Lancet Psychiatry 2021; 8:1062-1070. [PMID: 34735824 DOI: 10.1016/s2215-0366(21)00286-8] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 06/21/2021] [Accepted: 07/22/2021] [Indexed: 12/30/2022]
Abstract
BACKGROUND Although studies suggest that concentrations of omega-3 and omega-6 fatty acids are lower in individuals with schizophrenia, evidence for beneficial effects of fatty acid supplementation is scarce. Therefore, in this study, we aimed to determine whether omega-3 and omega-6 fatty acid concentrations are causally related to schizophrenia. METHODS We did a two-sample Mendelian randomisation study, using deidentified summary-level data that were publicly available. Exposure-outcome relationships were evaluated using the inverse variance weighted two-sample Mendelian randomisation method using results from genome-wide association studies (GWASs) of fatty acid concentrations and schizophrenia. GWAS results were available for European (fatty acids) and European and Asian (schizophrenia) ancestry samples. Overall age and gender information were not calculable from the summary-level GWAS results. Weighted median, weighted mode, and Mendelian randomisation Egger regression methods were used as sensitivity analyses. To address underlying mechanisms, further analyses were done using single instruments within the FADS gene cluster and ELOVL2 gene locus. FADS gene cluster and ELOVL2 gene causal effects on schizophrenia were calculated by dividing the single nucleotide polymorphism (SNP)-schizophrenia effect estimate by the SNP-fatty acid effect estimate with standard errors derived using the first term from a delta method expansion for the ratio estimate. Multivariable Mendelian randomisation was used to estimate direct effects of omega-3 fatty acids on schizophrenia, independent of omega-6 fatty acids, lipoproteins (ie, HDL and LDL), and triglycerides. FINDINGS Mendelian randomisation analyses indicated that long-chain omega-3 and long-chain omega-6 fatty acid concentrations were associated with a lower risk of schizophrenia (eg, inverse variance weighted odds ratio [OR] 0·83 [95% CI 0·75-0·92] for docosahexaenoic acid). By contrast, there was weak evidence that short-chain omega-3 and short-chain omega-6 fatty acids were associated with an increased risk of schizophrenia (eg, inverse variance weighted OR 1·07 [95% CI 0·98-1·18] for α-linolenic acid). Effects were consistent across the sensitivity analyses and the FADS single-SNP analyses, suggesting that long-chain omega-3 and long-chain omega-6 fatty acid concentrations were associated with lower risk of schizophrenia (eg, OR 0·74 [95% CI 0·58-0·96] for docosahexaenoic acid) whereas short-chain omega-3 and short-chain omega-6 fatty acid concentrations were associated with an increased risk of schizophrenia (eg, OR 1·08 [95% CI 1·02-1·15] for α-linolenic acid). By contrast, estimates from the ELOVL2 single-SNP analyses were more imprecise and compatible with both risk-increasing and protective effects for each of the fatty acid measures. Multivariable Mendelian randomisation indicated that the protective effect of docosahexaenoic acid on schizophrenia persisted after conditioning on other lipids, although evidence was slightly weaker (multivariable inverse variance weighted OR 0·84 [95% CI 0·71-1·01]). INTERPRETATION Our results are compatible with the protective effects of long-chain omega-3 and long-chain omega-6 fatty acids on schizophrenia, suggesting that people with schizophrenia might have difficulty converting short-chain polyunsaturated fatty acids to long-chain polyunsaturated fatty acids. Further studies are required to determine whether long-chain polyunsaturated fatty acid supplementation or diet enrichment might help prevent onset of schizophrenia. FUNDING National Institute for Health Research Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol.
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Affiliation(s)
- Hannah J Jones
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol, Bristol, UK.
| | - Maria Carolina Borges
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Rebecca Carnegie
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - David Mongan
- Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland
| | - Peter J Rogers
- Nutrition and Behaviour Unit, School of Psychological Science, University of Bristol, Bristol, UK; National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol, Bristol, UK
| | - Sarah J Lewis
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; Bristol Dental School, University of Bristol, Bristol, UK
| | - Andrew D Thompson
- Division of Mental Health and Wellbeing, University of Warwick, Coventry, UK; Orygen, Centre of Youth Mental Health, Melbourne, Australia
| | - Stanley Zammit
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol, Bristol, UK; MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff University, Cardiff, UK
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16
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Blond K, Carslake D, Gjærde LK, Vistisen D, Sørensen TIA, Smith GD, Baker JL. Instrumental variable analysis using offspring BMI in childhood as an indicator of parental BMI in relation to mortality. Sci Rep 2021; 11:22408. [PMID: 34789785 PMCID: PMC8599489 DOI: 10.1038/s41598-021-01352-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 10/19/2021] [Indexed: 01/11/2023] Open
Abstract
Childhood BMI shows associations with adult mortality, but these may be influenced by effects of ill health in childhood on BMI and later mortality. To avoid this, we used offspring childhood BMI as an instrumental variable (IV) for own BMI in relation to mortality and compared it with conventional associations of own childhood BMI and own mortality. We included 36,097 parent-offspring pairs with measured heights and weights from the Copenhagen School Health Records Register and register-based information on death. Hazard ratios (HR) were estimated using adjusted Cox regression models. For all-cause mortality, per zBMI at age 7 the conventional HR = 1.07 (95%CI: 1.04-1.09) in women and 1.02 (95%CI: 0.92-1.14) in men, whereas the IV HR = 1.23 (95%CI: 1.15-1.32) in women and 1.05 (95%CI: 0.94-1.17) in men. Per zBMI at age 13, the conventional HR = 1.11 (95%CI: 1.08-1.15) in women and 1.03 (95%CI: 0.99-1.06) in men, whereas the IV HR = 1.30 (95%CI: 1.19-1.42) in women and 1.15 (95%CI: 1.04-1.29) in men. Only conventional models showed indications of J-shaped associations. Our IV analyses suggest that there is a causal relationship between BMI and mortality that is positive at both high and low BMI values.
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Affiliation(s)
- Kim Blond
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, The Capital Region, Copenhagen, Denmark
| | - David Carslake
- Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Line Klingen Gjærde
- Children's Hospital Copenhagen and Juliane Marie Centre, Rigshospitalet, The Capital Region, Copenhagen, Denmark
| | | | - Thorkild I A Sørensen
- Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Department of Public Health, Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - George Davey Smith
- Medical Research Council (MRC) Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Jennifer L Baker
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, The Capital Region, Copenhagen, Denmark.
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17
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Baumeister S, Nolde M, Alayash Z, Leitzmann M, Baurecht H, Meisinger C. Cannabis use does not impact on type 2 diabetes: A two-sample Mendelian randomization study. Addict Biol 2021; 26:e13020. [PMID: 33580533 DOI: 10.1111/adb.13020] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 01/18/2021] [Accepted: 01/20/2021] [Indexed: 12/17/2022]
Abstract
Cannabis has effects on the insulin/glucose metabolism. As the use of cannabis and the prevalence of type 2 diabetes increase worldwide, it is important to examine the effect of cannabis on the risk of diabetes. We conducted a Mendelian randomization (MR) study by using 19 single-nucleotide polymorphisms (SNPs) as instrumental variables for lifetime cannabis use and 14 SNPs to instrument cannabis use disorder and linking these to type 2 diabetes risk using genome-wide association study data (lifetime cannabis use [N = 184,765]; cannabis use disorder [2387 cases/48,985 controls], type 2 diabetes [74,124 cases/824,006 controls]). The MR analysis suggested no effect of lifetime cannabis use (inverse-variance weighted odds ratio [95% confidence interval] = 1.00 [0.93-1.09], P value = 0.935) and cannabis use disorder (OR = 1.03 [0.99-1.08]) on type 2 diabetes. Sensitivity analysis to assess potential pleiotropy led to no substantive change in the estimates. This study adds to the evidence base that cannabis use does not play a causal role in type 2 diabetes.
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Affiliation(s)
- Sebastian‐Edgar Baumeister
- Chair of Epidemiology LMU München, UNIKA‐T Augsburg Augsburg Germany
- Independent Research Group Clinical Epidemiology Helmholtz Zentrum München, German Research Center for Environmental Health Munich Germany
- Institute of Health Services Research in Dentistry University of Münster Münster Germany
| | - Michael Nolde
- Chair of Epidemiology LMU München, UNIKA‐T Augsburg Augsburg Germany
- Independent Research Group Clinical Epidemiology Helmholtz Zentrum München, German Research Center for Environmental Health Munich Germany
| | - Zoheir Alayash
- Chair of Epidemiology LMU München, UNIKA‐T Augsburg Augsburg Germany
| | - Michael Leitzmann
- Department of Epidemiology and Preventive Medicine University of Regensburg Regensburg Germany
| | - Hansjörg Baurecht
- Department of Epidemiology and Preventive Medicine University of Regensburg Regensburg Germany
| | - Christa Meisinger
- Chair of Epidemiology LMU München, UNIKA‐T Augsburg Augsburg Germany
- Independent Research Group Clinical Epidemiology Helmholtz Zentrum München, German Research Center for Environmental Health Munich Germany
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18
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Kim K, Kim S, Myung W, Shim I, Lee H, Kim B, Cho SK, Yoon J, Kim DK, Won HH. Shared Genetic Background between Parkinson's Disease and Schizophrenia: A Two-Sample Mendelian Randomization Study. Brain Sci 2021; 11:1042. [PMID: 34439661 PMCID: PMC8393703 DOI: 10.3390/brainsci11081042] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2021] [Revised: 07/27/2021] [Accepted: 07/30/2021] [Indexed: 12/25/2022] Open
Abstract
Background and objectives: Parkinson's disease (PD) and schizophrenia often share symptomatology. Psychotic symptoms are prevalent in patients with PD, and similar motor symptoms with extrapyramidal signs are frequently observed in antipsychotic-naïve patients with schizophrenia as well as premorbid families. However, few studies have examined the relationship between PD and schizophrenia. We performed this study to evaluate whether genetic variants which increase PD risk influence the risk of developing schizophrenia, and vice versa. Materials and Methods: Two-sample Mendelian randomization (TSMR) with summary statistics from large-scale genome-wide association studies (GWAS) was applied. Summary statistics were extracted for these instruments from GWAS of PD and schizophrenia; Results: We found an increase in the risk of schizophrenia per one-standard deviation (SD) increase in the genetically-predicted PD risk (inverse-variance weighted method, odds ratio = 1.10; 95% confidence interval, 1.05-1.15; p = 3.49 × 10-5). The association was consistent in sensitivity analyses, including multiple TSMR methods, analysis after removing outlier variants with potential pleiotropic effects, and analysis after applying multiple GWAS subthresholds. No relationships were evident between PD and smoking or other psychiatric disorders, including attention deficit hyperactivity disorder, autism spectrum disorder, bipolar affective disorder, major depressive disorder, Alzheimer's disease, or alcohol dependence. However, we did not find a reverse relationship; genetic variants increasing schizophrenia risk did not alter the risk of PD; Conclusions: Overall, our findings suggest that increased genetic risk of PD can be associated with increased risk of schizophrenia. This association supports the intrinsic nature of the psychotic symptom in PD rather than medication or environmental effects. Future studies for possible comorbidities and shared genetic structure between the two diseases are warranted.
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Affiliation(s)
- Kiwon Kim
- Department of Psychiatry, Kangdong Sacred Heart Hospital, College of Medicine, Hallym University, Sungan-ro, Kangdong-gu, Seoul 05355, Korea;
| | - Soyeon Kim
- Samsung Medical Center, Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Seoul 06351, Korea; (S.K.); (I.S.); (B.K.)
| | - Woojae Myung
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam 13620, Korea;
| | - Injeong Shim
- Samsung Medical Center, Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Seoul 06351, Korea; (S.K.); (I.S.); (B.K.)
| | - Hyewon Lee
- Department of Health Administration and Management, College of Medical Sciences, Soonchunhyang University, Asan 31538, Korea;
- Department of Software Convergence, Graduate School, Soonchunhyang University, Asan 31538, Korea
| | - Beomsu Kim
- Samsung Medical Center, Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Seoul 06351, Korea; (S.K.); (I.S.); (B.K.)
| | - Sung Kweon Cho
- Department of Pharmacology, School of Medicine, Ajou University, Worldcup-ro, Yeongtong-gu, Suwon 16499, Korea;
| | - Joohyun Yoon
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam 13620, Korea;
| | - Doh Kwan Kim
- Samsung Medical Center, Department of Psychiatry, School of Medicine, Sungkyunkwan University, Seoul 06351, Korea;
| | - Hong-Hee Won
- Samsung Medical Center, Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Seoul 06351, Korea; (S.K.); (I.S.); (B.K.)
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19
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Allman PH, Aban I, Long DM, Bridges SL, Srinivasasainagendra V, MacKenzie T, Cutter G, Tiwari HK. A novel Mendelian randomization method with binary risk factor and outcome. Genet Epidemiol 2021; 45:549-560. [PMID: 33998053 DOI: 10.1002/gepi.22387] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Revised: 03/17/2021] [Accepted: 04/28/2021] [Indexed: 11/07/2022]
Abstract
BACKGROUND Mendelian randomization (MR) applies instrumental variable (IV) methods to observational data using a genetic variant as an IV. Several Monte-Carlo studies investigate the performance of MR methods with binary outcomes, but few consider them in conjunction with binary risk factors. OBJECTIVE To develop a novel MR estimator for scenarios with a binary risk factor and outcome; and compare to existing MR estimators via simulations and real data analysis. METHODS A bivariate Bernoulli distribution is adapted to the IV setting. Empirical bias and asymptotic coverage probabilities are estimated via simulations. The proposed method is compared to the Wald method, two-stage predictor substitution (2SPS), two-stage residual inclusion (2SRI), and the generalized method of moments (GMM). An analysis is performed using existing data from the CLEAR study to estimate the potential causal effect of smoking on rheumatoid arthritis risk in African Americans. RESULTS Bias was low for the proposed method and comparable to 2SPS. The Wald method was often biased towards the null. Coverage was adequate for the proposed method, 2SPS, and 2SRI. Coverage for the Wald and GMM methods was poor in several scenarios. The causal effect of ever smoking on rheumatoid arthritis risk was not statistically significant using a variety of genetic instruments. CONCLUSIONS Simulations suggest the proposed MR method is sound with binary risk factors and outcomes, and comparable to 2SPS and 2SRI in terms of bias. The proposed method also provides more natural framework for hypothesis testing compared to 2SPS or 2SRI, which require ad-hoc variance adjustments.
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Affiliation(s)
- Philip H Allman
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Inmaculada Aban
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Dustin M Long
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - S Louis Bridges
- Department of Medicine, Hospital for Special Surgery and Weill Cornell Medicine Center, New York, New York, USA
| | | | - Todd MacKenzie
- Department of Biomedical Data Science, Dartmouth College, Hanover, New Hampshire, USA
| | - Gary Cutter
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Hemant K Tiwari
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, Alabama, USA
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20
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Lin L, Zhang R, Huang H, Zhu Y, Li Y, Dong X, Shen S, Wei L, Chen X, Christiani DC, Wei Y, Chen F. Mendelian Randomization With Refined Instrumental Variables From Genetic Score Improves Accuracy and Reduces Bias. Front Genet 2021; 12:618829. [PMID: 33868364 PMCID: PMC8044958 DOI: 10.3389/fgene.2021.618829] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2020] [Accepted: 02/01/2021] [Indexed: 11/15/2022] Open
Abstract
Mendelian randomization (MR) can estimate the causal effect for a risk factor on a complex disease using genetic variants as instrument variables (IVs). A variety of generalized MR methods have been proposed to integrate results arising from multiple IVs in order to increase power. One of the methods constructs the genetic score (GS) by a linear combination of the multiple IVs using the multiple regression model, which was applied in medical researches broadly. However, GS-based MR requires individual-level data, which greatly limit its application in clinical research. We propose an alternative method called Mendelian Randomization with Refined Instrumental Variable from Genetic Score (MR-RIVER) to construct a genetic IV by integrating multiple genetic variants based on summarized results, rather than individual data. Compared with inverse-variance weighted (IVW) and generalized summary-data-based Mendelian randomization (GSMR), MR-RIVER maintained the type I error, while possessing more statistical power than the competing methods. MR-RIVER also presented smaller biases and mean squared errors, compared to the IVW and GSMR. We further applied the proposed method to estimate the effects of blood metabolites on educational attainment, by integrating results from several publicly available resources. MR-RIVER provided robust results under different LD prune criteria and identified three metabolites associated with years of schooling and additional 15 metabolites with indirect mediation effects through butyrylcarnitine. MR-RIVER, which extends score-based MR to summarized results in lieu of individual data and incorporates multiple correlated IVs, provided a more accurate and powerful means for the discovery of novel risk factors.
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Affiliation(s)
- Lijuan Lin
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Ruyang Zhang
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,China International Cooperation Center for Environment and Human Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
| | - Hui Huang
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Ying Zhu
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yi Li
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, United States
| | - Xuesi Dong
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Department of Epidemiology and Biostatistics, School of Public Health, Southeast University, Nanjing, China
| | - Sipeng Shen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Liangmin Wei
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Xin Chen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - David C Christiani
- China International Cooperation Center for Environment and Human Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, United States.,Division of Pulmonary and Critical Care Medicine, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States
| | - Yongyue Wei
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,China International Cooperation Center for Environment and Human Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
| | - Feng Chen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,China International Cooperation Center for Environment and Human Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
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21
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Thomas DG, Wei Y, Tall AR. Lipid and metabolic syndrome traits in coronary artery disease: a Mendelian randomization study. J Lipid Res 2021; 62:100044. [PMID: 32907989 PMCID: PMC7933489 DOI: 10.1194/jlr.p120001000] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 08/20/2020] [Indexed: 01/14/2023] Open
Abstract
Mendelian randomization (MR) of lipid traits in CAD has provided evidence for causal associations of LDL-C and TGs in CAD, but many lipid trait genetic variants have pleiotropic effects on other cardiovascular risk factors that may bias MR associations. The goal of this study was to evaluate pleiotropic effects of lipid trait genetic variants and to account for these effects in MR of lipid traits in CAD. We performed multivariable MR using inverse variance-weighted and MR-Egger methods in large (n ≥ 300,000) GWAS datasets. We found that 30% of lipid trait genetic variants have effects on metabolic syndrome traits, including BMI, T2D, and systolic blood pressure (SBP). Nonetheless, in multivariable MR analysis, LDL-C, HDL-C, TGs, BMI, T2D, and SBP are independently associated with CAD, and each of these associations is robust to adjustment for directional pleiotropy. MR at loci linked to direct effects on HDL-C and TGs suggests locus- and mechanism-specific causal effects of these factors on CAD.
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Affiliation(s)
- David G Thomas
- Department of Medicine, New York Presbyterian Hospital/Weill Cornell Medicine, New York, NY, USA
| | - Ying Wei
- Department of Biostatistics, Columbia University, New York, NY, USA
| | - Alan R Tall
- Division of Molecular Medicine, Department of Medicine, Columbia University, New York, NY, USA.
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22
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Wang K, Ding L, Yang C, Hao X, Wang C. Exploring the Relationship Between Psychiatric Traits and the Risk of Mouth Ulcers Using Bi-Directional Mendelian Randomization. Front Genet 2020; 11:608630. [PMID: 33424931 PMCID: PMC7793678 DOI: 10.3389/fgene.2020.608630] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Accepted: 11/09/2020] [Indexed: 12/26/2022] Open
Abstract
Background Although the association between mouth ulcers and psychiatric traits has been reported by observational studies, their causal relationship remains unclear. Mendelian randomization (MR), powered by large-scale genome-wide association studies (GWAS), provides an opportunity to clarify the causality between mouth ulcers and psychiatric traits. Methods We collected summary statistics of mouth ulcers (sample size n = 461,106) and 10 psychiatric traits from the largest publicly available GWAS on Europeans, including anxiety disorder (n = 83,566), attention deficit/hyperactivity disorder (n = 53,293), autism spectrum disorder (n = 46,350), bipolar disorder (n = 51,710), insomnia (n = 1,331,010), major depressive disorder (n = 480,359), mood instability (n = 363,705), neuroticism (n = 168,105), schizophrenia (n = 105,318), and subjective wellbeing (n = 388,538). We applied three two-sample bi-directional MR analysis methods, namely the Inverse Variance Weighted (IVW) method, the MR pleiotropy residual sum and outlier (MR-PRESSO) method, and the weighted median method, to assess the causal relationship between each psychiatric trait and mouth ulcers. Results We found significant effects of autism spectrum disorder, insomnia, major depressive disorder, and subjective wellbeing on mouth ulcers, with the corresponding odds ratio (OR) from the IVW method being 1.160 [95% confidence interval (CI): 1.066–1.261, P = 5.39 × 10–4], 1.092 (1.062–1.122, P = 3.37 × 10–10), 1.234 (1.134–1.342, P = 1.03 × 10–6), and 0.703 (0.571–0.865, P = 8.97 × 10–4), respectively. We also observed suggestive evidence for mood instability to cause mouth ulcers [IVW, OR = 1.662 (1.059–2.609), P = 0.027]. These results were robust to weak instrument bias and heterogeneity. We found no evidence on causal effects between other psychiatric traits and mouth ulcers, in either direction. Conclusion Our findings suggest a protective effect of subjective wellbeing and risk effects of autism spectrum disorder, insomnia, major depressive disorder, and mood instability on mouth ulcers. These results clarify the causal relationship between psychiatric traits and the development of mouth ulcers.
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Affiliation(s)
- Kai Wang
- Key Laboratory for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lin Ding
- Key Laboratory for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Can Yang
- Department of Mathematics, The Hong Kong University of Science and Technology, Hong Kong, China
| | - Xingjie Hao
- Key Laboratory for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Chaolong Wang
- Key Laboratory for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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23
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Sex-Specific Genetically Predicted Iron Status in relation to 12 Vascular Diseases: A Mendelian Randomization Study in the UK Biobank. BIOMED RESEARCH INTERNATIONAL 2020; 2020:6246041. [PMID: 33195696 PMCID: PMC7641690 DOI: 10.1155/2020/6246041] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 09/30/2020] [Accepted: 10/14/2020] [Indexed: 11/17/2022]
Abstract
Background Iron overload has been implicated in the pathogenesis of varicose veins (VVs). However, the association of serum iron status with other vascular diseases (VDs) is not well understood, which might be a potential target for VD prevention. This study was aimed at investigating the causal associations between iron status and VDs using the Mendelian randomization (MR) method. Methods A two-sample MR was designed to investigate whether iron status was associated with VDs, based on iron data from a published genome-wide association study meta-analysis of 48,972 subjects of European descent and VD data obtained from the UK Biobank, including 361,194 British subjects (167,020 males and 194,174 females). We further explored whether there was sex difference in the associations between genetically predicted iron status and VDs. Results The results demonstrated that iron status had a significant causal effect on VVs of lower extremities (P < 0.001) and a potential effect on coronary atherosclerosis (P < 0.05 for serum iron, ferritin, and transferrin saturation, respectively), but not on other VDs. Furthermore, higher iron status exerted a detrimental effect on VVs of lower extremities in both genders (P < 0.05) and a protective effect on male patients with coronary atherosclerosis (P < 0.05 for serum iron, ferritin, and transferrin saturation, respectively). Conclusions This MR study provides robust evidence that higher iron status increases the risk of VVs of lower extremities, whereas it reduces the incidence of coronary atherosclerosis in the male population, which indicates that iron has divergent effects on vascular pathology.
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Abstract
The International Statistical Genetics Workshop (commonly referred to as the "Boulder Workshop") has been held annually in Boulder, Colorado almost every year since 1990. A staple feature of each workshop has been the presence of a "question box" (either a physical box or an online virtual one) where workshop participants are given the opportunity of asking questions to the faculty. In this manuscript, we have compiled a list of ten "classic" questions that have appeared in one form or another across multiple workshops and our attempts at answering them.
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25
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Investigating causal relationships between Body Mass Index and risk of atopic dermatitis: a Mendelian randomization analysis. Sci Rep 2020; 10:15279. [PMID: 32943721 PMCID: PMC7498603 DOI: 10.1038/s41598-020-72301-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2019] [Accepted: 08/24/2020] [Indexed: 01/07/2023] Open
Abstract
Population studies suggest that atopic dermatitis (AD) is associated with an increased risk of obesity, however a causal relationship between these two conditions remains to be established. We therefore use Mendelian randomization (MR) to evaluate whether obesity and AD are causally interlinked. We used summary statistics extracted from genome wide association studies of Body Mass Index (BMI) and AD. MR analysis was performed in both directions to establish the direction of causality between BMI and AD. We find that genetically determined increase in adiposity is associated with increased risk of AD (odds ratio of AD 1.08 [95% CI 1.01 to 1.14; p = 0.015] per unit increase in BMI). Conversely, genetically determined increased risk of AD is not associated with a higher BMI (change in BMI attributable to AD based on genetic information: 0.00; 95% CI − 0.02 to 0.02; p = 0.862). There was no evidence for confounding of these genetic analyses by horizontal pleiotropy. Our results indicate that the association of AD with obesity is likely to reflect a causal role for adiposity in the development of AD. Our findings enhance understanding of the etiology of AD, and the basis for experimental studies to evaluate the mechanistic pathways by which adiposity promotes AD.
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26
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Jones HJ, Martin D, Lewis SJ, Davey Smith G, O'Donovan MC, Owen MJ, Walters JTR, Zammit S. A Mendelian randomization study of the causal association between anxiety phenotypes and schizophrenia. Am J Med Genet B Neuropsychiatr Genet 2020; 183:360-369. [PMID: 32578352 DOI: 10.1002/ajmg.b.32808] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Revised: 05/19/2020] [Accepted: 05/28/2020] [Indexed: 12/31/2022]
Abstract
Schizophrenia shows a genetic correlation with both anxiety disorder and neuroticism, a trait strongly associated with anxiety. However, genetic correlations do not discern causality from genetic confounding. We therefore aimed to investigate whether anxiety-related phenotypes lie on the causal pathway to schizophrenia using Mendelian randomization (MR). Four MR methods, each with different assumptions regarding instrument validity, were used to investigate casual associations of anxiety and neuroticism related phenotypes on schizophrenia, and vice versa: inverse variance weighted (IVW), weighted median, weighted mode, and, when appropriate, MR Egger regression. MR provided evidence of a causal effect of neuroticism on schizophrenia (IVW odds ratio [OR]: 1.33, 95% confidence interval [CI]: 1.12-1.59), but only weak evidence of a causal effect of anxiety on schizophrenia (IVW OR: 1.10, 95% CI: 1.01-1.19). There was also evidence of a causal association from schizophrenia liability to anxiety disorder (IVW OR: 1.28, 95% CI: 1.18-1.39) and worry (IVW beta: 0.05, 95% CI: 0.03-0.07), but effect estimates from schizophrenia to neuroticism were inconsistent in the main analysis. The evidence of neuroticism increasing schizophrenia risk provided by our results supports future efforts to evaluate neuroticism- or anxiety-based therapies to prevent onset of psychotic disorders.
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Affiliation(s)
- Hannah J Jones
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.,National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust, University of Bristol, Bristol, UK
| | - David Martin
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Sarah J Lewis
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,Bristol Dental School, University of Bristol, Bristol, UK
| | | | - Michael C O'Donovan
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
| | - Michael J Owen
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
| | - James T R Walters
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
| | - Stanley Zammit
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.,MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University School of Medicine, Cardiff, UK
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27
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Slob EAW, Burgess S. A comparison of robust Mendelian randomization methods using summary data. Genet Epidemiol 2020; 44:313-329. [PMID: 32249995 PMCID: PMC7317850 DOI: 10.1002/gepi.22295] [Citation(s) in RCA: 341] [Impact Index Per Article: 68.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2019] [Revised: 08/22/2019] [Accepted: 03/11/2020] [Indexed: 01/20/2023]
Abstract
The number of Mendelian randomization (MR) analyses including large numbers of genetic variants is rapidly increasing. This is due to the proliferation of genome-wide association studies, and the desire to obtain more precise estimates of causal effects. Since it is unlikely that all genetic variants will be valid instrumental variables, several robust methods have been proposed. We compare nine robust methods for MR based on summary data that can be implemented using standard statistical software. Methods were compared in three ways: by reviewing their theoretical properties, in an extensive simulation study, and in an empirical example. In the simulation study, the best method, judged by mean squared error was the contamination mixture method. This method had well-controlled Type 1 error rates with up to 50% invalid instruments across a range of scenarios. Other methods performed well according to different metrics. Outlier-robust methods had the narrowest confidence intervals in the empirical example. With isolated exceptions, all methods performed badly when over 50% of the variants were invalid instruments. Our recommendation for investigators is to perform a variety of robust methods that operate in different ways and rely on different assumptions for valid inferences to assess the reliability of MR analyses.
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Affiliation(s)
- Eric A. W. Slob
- Erasmus School of EconomicsErasmus University RotterdamRotterdamThe Netherlands
- Erasmus University Rotterdam Institute for Behavior and BiologyRotterdamThe Netherlands
| | - Stephen Burgess
- Department of Public Health and Primary CareUniversity of CambridgeCambridgeUK
- MRC Biostatistics UnitUniversity of CambridgeCambridgeUK
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28
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Zheng Y, Huang T, Wang T, Mei Z, Sun Z, Zhang T, Ellervik C, Chai JF, Sim X, van Dam RM, Tai ES, Koh WP, Dorajoo R, Saw SM, Sabanayagam C, Wong TY, Gupta P, Rossing P, Ahluwalia TS, Vinding RK, Bisgaard H, Bønnelykke K, Wang Y, Graff M, Voortman T, van Rooij FJA, Hofman A, van Heemst D, Noordam R, Estampador AC, Varga TV, Enzenbach C, Scholz M, Thiery J, Burkhardt R, Orho-Melander M, Schulz CA, Ericson U, Sonestedt E, Kubo M, Akiyama M, Zhou A, Kilpeläinen TO, Hansen T, Kleber ME, Delgado G, McCarthy M, Lemaitre RN, Felix JF, Jaddoe VWV, Wu Y, Mohlke KL, Lehtimäki T, Wang CA, Pennell CE, Schunkert H, Kessler T, Zeng L, Willenborg C, Peters A, Lieb W, Grote V, Rzehak P, Koletzko B, Erdmann J, Munz M, Wu T, He M, Yu C, Lecoeur C, Froguel P, Corella D, Moreno LA, Lai CQ, Pitkänen N, Boreham CA, Ridker PM, Rosendaal FR, de Mutsert R, Power C, Paternoster L, Sørensen TIA, Tjønneland A, Overvad K, Djousse L, Rivadeneira F, Lee NR, Raitakari OT, Kähönen M, Viikari J, Langhendries JP, Escribano J, Verduci E, Dedoussis G, König I, Balkau B, Coltell O, Dallongeville J, Meirhaeghe A, Amouyel P, Gottrand F, Pahkala K, Niinikoski H, Hyppönen E, März W, Mackey DA, Gruszfeld D, Tucker KL, Fumeron F, Estruch R, Ordovas JM, Arnett DK, Mook-Kanamori DO, Mozaffarian D, Psaty BM, North KE, Chasman DI, Qi L. Mendelian randomization analysis does not support causal associations of birth weight with hypertension risk and blood pressure in adulthood. Eur J Epidemiol 2020; 35:685-697. [PMID: 32383070 DOI: 10.1007/s10654-020-00638-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Accepted: 04/21/2020] [Indexed: 12/22/2022]
Abstract
Epidemiology studies suggested that low birthweight was associated with a higher risk of hypertension in later life. However, little is known about the causality of such associations. In our study, we evaluated the causal association of low birthweight with adulthood hypertension following a standard analytic protocol using the study-level data of 183,433 participants from 60 studies (CHARGE-BIG consortium), as well as that with blood pressure using publicly available summary-level genome-wide association data from EGG consortium of 153,781 participants, ICBP consortium and UK Biobank cohort together of 757,601 participants. We used seven SNPs as the instrumental variable in the study-level analysis and 47 SNPs in the summary-level analysis. In the study-level analyses, decreased birthweight was associated with a higher risk of hypertension in adults (the odds ratio per 1 standard deviation (SD) lower birthweight, 1.22; 95% CI 1.16 to 1.28), while no association was found between genetically instrumented birthweight and hypertension risk (instrumental odds ratio for causal effect per 1 SD lower birthweight, 0.97; 95% CI 0.68 to 1.41). Such results were consistent with that from the summary-level analyses, where the genetically determined low birthweight was not associated with blood pressure measurements either. One SD lower genetically determined birthweight was not associated with systolic blood pressure (β = - 0.76, 95% CI - 2.45 to 1.08 mmHg), 0.06 mmHg lower diastolic blood pressure (β = - 0.06, 95% CI - 0.93 to 0.87 mmHg), or pulse pressure (β = - 0.65, 95% CI - 1.38 to 0.69 mmHg, all p > 0.05). Our findings suggest that the inverse association of birthweight with hypertension risk from observational studies was not supported by large Mendelian randomization analyses.
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Affiliation(s)
- Yan Zheng
- Department of Cardiology Zhongshan Hospital, State Key Laboratory of Genetic Engineering School of Life Sciences, Human Phenome Institue, Fudan University, 2005 Songhu Road, Shanghai, 200438, China. .,Key Laboratory of Public Health Safety of Ministry of Education, School of Public Health, Fudan University, Shanghai, China.
| | - Tao Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Tiange Wang
- Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, 1440 Canal St, Suite 1724, New Orleans, LA, 70112, USA
| | - Zhendong Mei
- Department of Cardiology Zhongshan Hospital, State Key Laboratory of Genetic Engineering School of Life Sciences, Human Phenome Institue, Fudan University, 2005 Songhu Road, Shanghai, 200438, China
| | - Zhonghan Sun
- Department of Cardiology Zhongshan Hospital, State Key Laboratory of Genetic Engineering School of Life Sciences, Human Phenome Institue, Fudan University, 2005 Songhu Road, Shanghai, 200438, China
| | - Tao Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.,Department of Biostatistics, School of Public Health, Shandong University, Jinan, 250012, China
| | - Christina Ellervik
- University of Copenhagen, Copenhagen, Denmark.,Harvard Medical School, Boston, USA.,Department of Production, Research and Innovation, Region Zealand, Denmark.,Boston Children's Hospital, Boston, USA
| | - Jin-Fang Chai
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, 117549, Singapore
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, 117549, Singapore
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, 117549, Singapore
| | - E-Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, 117549, Singapore.,Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Woon-Puay Koh
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, 117549, Singapore.,Health Services and Systems Research, Duke-NUS Medical School, Singapore, Singapore
| | - Rajkumar Dorajoo
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
| | - Seang-Mei Saw
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, 117549, Singapore.,Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore.,Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Charumathi Sabanayagam
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore.,Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Tien Yin Wong
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore.,Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Preeti Gupta
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | | | - Tarunveer S Ahluwalia
- Steno Diabetes Center Copenhagen (SDCC), Niels Steensens Vej 2, 2820, Gentofte, Denmark.,COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Rebecca K Vinding
- COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Hans Bisgaard
- COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Klaus Bønnelykke
- COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Yujie Wang
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, 27514, USA
| | - Mariaelisa Graff
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, 27514, USA
| | - Trudy Voortman
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Frank J A van Rooij
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Albert Hofman
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.,Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA
| | - Diana van Heemst
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Raymond Noordam
- Section of Gerontology and Geriatrics, Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Angela C Estampador
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Skåne University Hospital Malmö, Lund University, 21741, Malmö, Sweden
| | - Tibor V Varga
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Skåne University Hospital Malmö, Lund University, 21741, Malmö, Sweden
| | - Cornelia Enzenbach
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany.,Institute for Laboratory Medicine, University of Leipzig, Leipzig, Germany
| | - Markus Scholz
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany.,Institute for Laboratory Medicine, University of Leipzig, Leipzig, Germany.,LIFE Research Center for Civilisation Diseases, University of Leipzig, Leipzig, Germany
| | - Joachim Thiery
- Institute for Laboratory Medicine, University of Leipzig, Leipzig, Germany.,LIFE Research Center for Civilisation Diseases, University of Leipzig, Leipzig, Germany
| | - Ralph Burkhardt
- Institute for Laboratory Medicine, University of Leipzig, Leipzig, Germany.,LIFE Research Center for Civilisation Diseases, University of Leipzig, Leipzig, Germany.,Institute of Clinical Chemistry and Laboratory Medicine, University Hospital Regensburg, Regensburg, Germany
| | | | | | - Ulrika Ericson
- Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | - Emily Sonestedt
- Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | - Michiaki Kubo
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama City, Japan
| | - Masato Akiyama
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama City, Japan
| | - Ang Zhou
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, University of South Australia, Adelaide, Australia.,South Australian Health and Medical Research Institute Adelaide, Adelaide, Australia
| | - Tuomas O Kilpeläinen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, 2200N, Copenhagen, Denmark
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, 2200N, Copenhagen, Denmark
| | - Marcus E Kleber
- Vth Department of Medicine, Mannheim Medical Faculty, Heidelberg University, Mannheim, Germany.,Institute of Nutrition, Friedrich Schiller University Jena, Jena, Germany.,Competence Cluster of Nutrition and Cardiovascular Health (nutriCARD) Halle-Jena-Leipzig, Copenhagen, Germany
| | - Graciela Delgado
- Vth Department of Medicine, Mannheim Medical Faculty, Heidelberg University, Mannheim, Germany
| | - Mark McCarthy
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, University of Oxford, Old Road, Headington, Oxford, OX3 7LJ, UK
| | - Rozenn N Lemaitre
- Department of Medicine, Cardiovascular Health Research Unit, University of Washington, Seattle, WA, 98101, USA
| | - Janine F Felix
- The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.,Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.,Department of Pediatrics, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
| | - Vincent W V Jaddoe
- The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.,Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.,Department of Pediatrics, Erasmus MC, University Medical Center, Rotterdam, The Netherlands
| | - Ying Wu
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, 33520, Tampere, Finland.,Department of Clinical Chemistry, University of Tampere School of Medicine, 33014, Tampere, Finland
| | - Carol A Wang
- School of Medicine and Public Health, Faculty of Medicine and Health, The University of Newcastle, Callaghan, NSW, 2308, Australia
| | - Craig E Pennell
- School of Medicine and Public Health, Faculty of Medicine and Health, The University of Newcastle, Callaghan, NSW, 2308, Australia
| | - Heribert Schunkert
- Deutsches Herzzentrum München, Technische Universität München, Munich, Germany
| | - Thorsten Kessler
- Deutsches Herzzentrum München, Technische Universität München, Munich, Germany
| | - Lingyao Zeng
- Deutsches Herzzentrum München, Technische Universität München, Munich, Germany
| | - Christina Willenborg
- Department of Clinical Chemistry, University of Tampere School of Medicine, 33014, Tampere, Finland
| | - Annette Peters
- Institute of Epidemiology and PopGen Biobank, Kiel University, Kiel, Germany
| | - Wolfgang Lieb
- Institute of Epidemiology and PopGen Biobank, Kiel University, Kiel, Germany
| | - Veit Grote
- Division of Metabolic and Nutritional Medicine, Dr. Von Hauner Children's Hospital, Klinikum Der Universitaet Muenchen, Munich, Germany
| | - Peter Rzehak
- Division of Metabolic and Nutritional Medicine, Dr. Von Hauner Children's Hospital, Klinikum Der Universitaet Muenchen, Munich, Germany
| | - Berthold Koletzko
- Division of Metabolic and Nutritional Medicine, Dr. Von Hauner Children's Hospital, Klinikum Der Universitaet Muenchen, Munich, Germany
| | - Jeanette Erdmann
- Institute for Cardiogenetics, University of Lübeck, 23562, Lübeck, Germany
| | - Matthias Munz
- Institute for Cardiogenetics, University of Lübeck, 23562, Lübeck, Germany.,Charité - University Medicine Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute for Dental and Craniofacial Sciences, Department of Periodontology and Synoptic Dentistry, 14197 Berlin, Germany
| | - Tangchun Wu
- MOE Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan, 430030, Hubei, China
| | - Meian He
- MOE Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan, 430030, Hubei, China
| | - Caizheng Yu
- MOE Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan, 430030, Hubei, China
| | - Cécile Lecoeur
- University of Lille Nord de France, CNRS UMR8199, Lille, France.,Institut Pasteur de Lille, Lille, France
| | - Philippe Froguel
- University of Lille Nord de France, CNRS UMR8199, Lille, France.,Institut Pasteur de Lille, Lille, France
| | - Dolores Corella
- Department of Preventive Medicine and Public Health, University of Valencia, 46022, Valencia, Spain.,CIBER Fisiopatología de La Obesidad y Nutrición, Instituto de Salud Carlos III, 28029, Madrid, Spain
| | - Luis A Moreno
- CIBER Fisiopatología de La Obesidad y Nutrición, Instituto de Salud Carlos III, 28029, Madrid, Spain.,Growth Exercise, Nutrition and Development (GENUD) Research Group, Facultad de Ciencias de La Salud, Universidad de Zaragoza, Zaragoza, Spain
| | - Chao-Qiang Lai
- USDA ARS, Human Nutrition Research Center on Aging at Tufts University, Boston, MA, 02111, USA
| | - Niina Pitkänen
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, 20520, Turku, Finland
| | - Colin A Boreham
- UCD Institute for Sport & Health, University College Dublin, Dublin, Ireland
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham & Women's Hospital, Boston, MA, 02215, USA
| | - Frits R Rosendaal
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Renée de Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Chris Power
- Population, Policy and Practice, UCL Institute of Child Health, London, UK
| | - Lavinia Paternoster
- MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, BS82BN, UK
| | - Thorkild I A Sørensen
- Vth Department of Medicine, Mannheim Medical Faculty, Heidelberg University, Mannheim, Germany.,MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, BS82BN, UK.,Department of Public Health, Section of Epidemiology, Faculty of Health and Medical Sciences, University of Copenhagen, 1353K, Copenhagen, Denmark
| | - Anne Tjønneland
- Danish Cancer Society Research Center, 2100, Copenhagen, Denmark
| | - Kim Overvad
- Department of Public Health, Section for Epidemiology, Aarhus University, 8000, Aarhus C, Denmark.,Aalborg University Hospital, 9000, Aalborg, Denmark
| | - Luc Djousse
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Fernando Rivadeneira
- The Generation R Study Group, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.,Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.,Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Nanette R Lee
- USC-Office of Population Studies Foundation, Inc., University of San Carlos, 6000, Cebu City, Philippines.,Department of Anthropology, Sociology, and History, University of San Carlos, 6000, Cebu City, Philippines
| | - Olli T Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, 20520, Turku, Finland.,Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, 20521, Turku, Finland.,Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, 33521, Tampere, Finland.,Department of Clinical Physiology, Faculty of Medicine and Health Technology, Tampere University, 33014, Tampere, Finland
| | - Jorma Viikari
- Division of Medicine, Turku University Hospital, 20521, Turku, Finland.,Department of Medicine, University of Turku, 20520, Turku, Finland
| | | | - Joaquin Escribano
- Paediatrics Research Unit, Universitat Rovira I Virgili, IISPV, Reus, Spain
| | - Elvira Verduci
- Department of Pediatrics, San Paolo Hospital, University of Milan, Milan, Italy
| | - George Dedoussis
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, Athens, Greece
| | - Inke König
- Institut für Medizinische Biometrie Und Statistik, Universität Zu Lübeck, Lübeck, Germany
| | - Beverley Balkau
- INSERM, Centre for Research in Epidemiology and Population Health, U1018, 94807, Villejuif, France.,University Versailles Saint-Quentin-en-Yvelines, UMRS 1018, 78035, Versailles, France.,University Paris Sud 11, UMRS 1018, 94807, Villejuif, France
| | - Oscar Coltell
- CIBER Fisiopatología de La Obesidad y Nutrición, Instituto de Salud Carlos III, 28029, Madrid, Spain.,Department of Computer Languages and Systems, University Jaume I, 12071, Castellon, Spain
| | | | - Aline Meirhaeghe
- INSERM U1167, Institut Pasteur de Lille, Univ. Lille, Lille, France
| | - Philippe Amouyel
- INSERM U1167, Institut Pasteur de Lille, Univ. Lille, Lille, France
| | - Frédéric Gottrand
- INSERM U1286, Hôpital Jeanne de Flandre, CHU Lille, Univ. Lille, Lille, France
| | - Katja Pahkala
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, 20520, Turku, Finland.,Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland.,Department of Physical Activity and Health, Paavo Nurmi Centre, Sports and Exercise Medicine Unit, Turku, Finland
| | - Harri Niinikoski
- Department of Pediatrics, Turku University Hospital, Turku, Finland.,Department of Physiology, University of Turku, Turku, Finland
| | - Elina Hyppönen
- Population, Policy and Practice, UCL Institute of Child Health, London, UK.,Australian Centre for Precision Health, University of South Australia Cancer Research Institute, University of South Australia, Adelaide, Australia.,South Australian Health and Medical Research Institute Adelaide, Adelaide, Australia
| | - Winfried März
- Vth Department of Medicine, Mannheim Medical Faculty, Heidelberg University, Mannheim, Germany.,Synlab Academy, Synlab Holding Deutschland GmbH, Mannheim, Germany.,Clinical Institute of Medical and Chemical Laboratory Diagnostics Medical, University of Graz, Graz, Austria
| | - David A Mackey
- Centre For Ophthalmology and Visual Science, Lions Eye Institute, University of Western Australia, Crawley, Australia
| | - Dariusz Gruszfeld
- Department of Neonatology and Neonatal Intensive Care, The Children's Memorial Health Institute, Al. Dzieci Polskich 20, 04-730, Warsaw, Poland
| | - Katherine L Tucker
- Biomedical and Nutritional Sciences, University of Massachusetts Lowell, Lowell, MA, USA
| | - Frédéric Fumeron
- INSERM, UMR_S 1138, Centre de Recherche Des Cordeliers, 75006, Paris, France.,Université de Paris, Centre de Recherche Des Cordeliers UMR-S 1138, 75006, Paris, France.,Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1138, Centre de Recherche Des Cordeliers, 75006, Paris, France
| | - Ramon Estruch
- CIBER Fisiopatología de La Obesidad y Nutrición, Instituto de Salud Carlos III, 28029, Madrid, Spain.,Department of Internal Medicine, Hospital Clinic, IDIBAPS, 08036, Barcelona, Spain
| | - Jose M Ordovas
- USDA ARS, Human Nutrition Research Center on Aging at Tufts University, Boston, MA, 02111, USA.,IMDEA Food Institute, CEI UAM + CSIC, Madrid, Spain
| | - Donna K Arnett
- College of Public Health, University of Kentucky, Lexington, KY, UK
| | - Dennis O Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.,Department of Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands
| | - Dariush Mozaffarian
- Friedman School of Nutrition Science & Policy, Tufts University, Boston, MA, 02111, USA
| | - Bruce M Psaty
- Department of Medicine, Cardiovascular Health Research Unit, University of Washington, Seattle, WA, 98101, USA.,Department of Epidemiology, University of Washington, Seattle, WA, 98101, USA.,Department of Health Sciences, University of Washington, Seattle, WA, 98101, USA.,Kaiser Permanent Washington Health Research Institute, Seattle, WA, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, 27514, USA.,Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, 27514, USA
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham & Women's Hospital, Boston, MA, 02215, USA.,Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, USA
| | - Lu Qi
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, 1440 Canal St, Suite 1724, New Orleans, LA, 70112, USA.
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29
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Jamieson E, Korologou-Linden R, Wootton RE, Guyatt AL, Battram T, Burrows K, Gaunt TR, Tobin MD, Munafò M, Davey Smith G, Tilling K, Relton C, Richardson TG, Richmond RC. Smoking, DNA Methylation, and Lung Function: a Mendelian Randomization Analysis to Investigate Causal Pathways. Am J Hum Genet 2020; 106:315-326. [PMID: 32084330 PMCID: PMC7058834 DOI: 10.1016/j.ajhg.2020.01.015] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Accepted: 01/21/2020] [Indexed: 12/18/2022] Open
Abstract
Whether smoking-associated DNA methylation has a causal effect on lung function has not been thoroughly evaluated. We first investigated the causal effects of 474 smoking-associated CpGs on forced expiratory volume in 1 s (FEV1) in UK Biobank (n = 321,047) by using two-sample Mendelian randomization (MR) and then replicated this investigation in the SpiroMeta Consortium (n = 79,055). Second, we used two-step MR to investigate whether DNA methylation mediates the effect of smoking on FEV1. Lastly, we evaluated the presence of horizontal pleiotropy and assessed whether there is any evidence for shared causal genetic variants between lung function, DNA methylation, and gene expression by using a multiple-trait colocalization ("moloc") framework. We found evidence of a possible causal effect for DNA methylation on FEV1 at 18 CpGs (p < 1.2 × 10-4). Replication analysis supported a causal effect at three CpGs (cg21201401 [LIME1 and ZGPAT], cg19758448 [PGAP3], and cg12616487 [EML3 and AHNAK] [p < 0.0028]). DNA methylation did not clearly mediate the effect of smoking on FEV1, although DNA methylation at some sites might influence lung function via effects on smoking. By using "moloc", we found evidence of shared causal variants between lung function, gene expression, and DNA methylation. These findings highlight potential therapeutic targets for improving lung function and possibly smoking cessation, although larger, tissue-specific datasets are required to confirm these results.
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Affiliation(s)
- Emily Jamieson
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Roxanna Korologou-Linden
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Robyn E Wootton
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; School of Psychological Science, University of Bristol, 12a Priory Road, Bristol BS8 1TU, UK; National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals Bristol National Health Service Foundation Trust and University of Bristol, Bristol, UK
| | - Anna L Guyatt
- Department of Health Sciences, University of Leicester, University Road, Leicester LE1 7RH, UK
| | - Thomas Battram
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Kimberley Burrows
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Tom R Gaunt
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals Bristol National Health Service Foundation Trust and University of Bristol, Bristol, UK
| | - Martin D Tobin
- Department of Health Sciences, University of Leicester, University Road, Leicester LE1 7RH, UK
| | - Marcus Munafò
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; School of Psychological Science, University of Bristol, 12a Priory Road, Bristol BS8 1TU, UK; National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals Bristol National Health Service Foundation Trust and University of Bristol, Bristol, UK
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals Bristol National Health Service Foundation Trust and University of Bristol, Bristol, UK
| | - Kate Tilling
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Caroline Relton
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Tom G Richardson
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Rebecca C Richmond
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
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30
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Qian Y, Ye D, Huang H, Wu DJH, Zhuang Y, Jiang X, Mao Y. Coffee Consumption and Risk of Stroke: A Mendelian Randomization Study. Ann Neurol 2020; 87:525-532. [PMID: 32034791 DOI: 10.1002/ana.25693] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Revised: 01/22/2020] [Accepted: 02/02/2020] [Indexed: 12/11/2022]
Abstract
OBJECTIVE Observational epidemiological studies have reported a relationship between coffee intake and risk of stroke. However, evidence for this association is inconsistent, and it remains uncertain whether the association is causal or due to confounding or reverse causality. To clarify this relationship, we adopted a Mendelian randomization (MR) approach to evaluate the effects of coffee consumption on the risk of stroke and its subtypes. METHODS A meta-analysis of genome-wide association studies (GWASs) including 91,462 coffee consumers was used to identify instruments for coffee consumption. Summary-level data for stroke, intracerebral hemorrhage, ischemic stroke (IS), and IS subtypes were obtained from GWAS meta-analyses conducted by the MEGASTROKE consortium. MR analyses were performed using the inverse-variance-weighted, weighted-median, MR-PRESSO (Pleiotropy RESidual Sum and Outlier) test and MR-Egger regression. Sensitivity analyses were further performed using alternative instruments to test the robustness of our findings. RESULTS Genetically predicted coffee consumption (high vs infrequent/no) was not associated with risk of stroke. Similarly, among coffee consumers, MR analysis did not indicate causal associations between coffee consumption (cups/day) and risk of stroke. However, in the subgroup analysis, we found weak suggestive evidence for a potential protective effect of coffee consumption on risk of small vessel (SV)-IS, although the association did not reach statistical significance after correction for multiple comparisons. INTERPRETATION This study suggests that coffee consumption is not causally associated with risk of stroke or its subtypes. Further studies are warranted to elucidate the possible association between coffee intake and risk of SV-IS, as well as its potential underlying mechanisms. ANN NEUROL 2020;87:525-532.
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Affiliation(s)
- Yu Qian
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
| | - Ding Ye
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
| | - Huijun Huang
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
| | - David J H Wu
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China.,University of Minnesota Medical School, Minneapolis, MN
| | - Yaxuan Zhuang
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
| | - Xia Jiang
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard University T. H. Chan School of Public Health, Boston, MA.,Cardiovascular Epidemiology Unit, Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden
| | - Yingying Mao
- School of Public Health, Zhejiang Chinese Medical University, Hangzhou, China
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31
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Burgess S, Foley CN, Allara E, Staley JR, Howson JMM. A robust and efficient method for Mendelian randomization with hundreds of genetic variants. Nat Commun 2020; 11:376. [PMID: 31953392 PMCID: PMC6969055 DOI: 10.1038/s41467-019-14156-4] [Citation(s) in RCA: 335] [Impact Index Per Article: 67.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2019] [Accepted: 12/17/2019] [Indexed: 12/17/2022] Open
Abstract
Mendelian randomization (MR) is an epidemiological technique that uses genetic variants to distinguish correlation from causation in observational data. The reliability of a MR investigation depends on the validity of the genetic variants as instrumental variables (IVs). We develop the contamination mixture method, a method for MR with two modalities. First, it identifies groups of genetic variants with similar causal estimates, which may represent distinct mechanisms by which the risk factor influences the outcome. Second, it performs MR robustly and efficiently in the presence of invalid IVs. Compared to other robust methods, it has the lowest mean squared error across a range of realistic scenarios. The method identifies 11 variants associated with increased high-density lipoprotein-cholesterol, decreased triglyceride levels, and decreased coronary heart disease risk that have the same directions of associations with various blood cell traits, suggesting a shared mechanism linking lipids and coronary heart disease risk mediated via platelet aggregation.
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Affiliation(s)
- Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
| | | | - Elias Allara
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - James R Staley
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Joanna M M Howson
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK
- Novo Nordisk Research Centre Oxford, Innovation Building - Old Road Campus, Roosevelt Drive, Oxford, UK
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32
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Lin J, Wang Y, Wang Y, Pan Y. Inflammatory biomarkers and risk of ischemic stroke and subtypes: A 2-sample Mendelian randomization study. Neurol Res 2020; 42:118-125. [PMID: 31900081 DOI: 10.1080/01616412.2019.1710404] [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] [Indexed: 12/12/2022]
Abstract
Objective: Chronic inflammation is considered as playing an important role in the pathophysiology of atherosclerosis, but the exact contributing inflammatory pathway on stroke is not clear. We aimed to examine the causal association of inflammatory biomarkers, such as interleukin-1 receptor antagonist (IL-1Ra), soluble interleukin-6 receptor (sIL-6R) and C-reactive protein (CRP), with the risk of ischemic stroke and its subtypes.Methods: Two-sample mendelian randomization analyses were performed using IL-1Ra, sIL-6R and CRP related genetic variants as instrumental variables. Summary-level data on ischemic stroke and its subtypes were obtained from the largest GWAS meta-analysis on stroke to date - the Multiancestry Genome-wide Association Study of Stroke (MEGASTROKE) consortium. Associations of IL-1Ra with stroke or its subtypes were estimated using inverse-variance weighted (IVW) method with SNPs rs6743376 and rs1542176 as instruments. Wald ratio method with SNP rs2228145 as the instrument was used for sIL-6R and IVW, MR-Egger, simple and weighted median approaches with 4- or 18-SNPs instruments were used for CRP.Results: Genetically elevated ln(IL-1Ra), ln(sIL-6R) and ln(CRP) levels were not causally associated with ischemic stroke (OR = 1.00, 95% CI: 0.97-1.04, p = 0.80; OR = 0.93, 95% CI: 0.87-0.99, p = 0.03; OR = 1.01, 95% CI: 0.94-1.09, p = 0.78). No significant association was observed between ln(IL-1Ra), ln(sIL-6R) and ln(CRP) level and ischemic stroke subtypes.Conclusions: Our study did not find convincing evidence to support that inflammatory biomarkers like IL-1Ra, sIL-6R and CRP are causally associated with the risk of ischemic stroke or its subtypes.
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Affiliation(s)
- Jinxi Lin
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yilong Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yongjun Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yuesong Pan
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.,China National Clinical Research Center for Neurological Diseases, Beijing, China
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33
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Wang T, Ren C, Ni J, Ding H, Qi Q, Yan C, Deng B, Dai J, Li G, Ding Y, Jin G. Genetic Association of Plasma Homocysteine Levels with Gastric Cancer Risk: A Two-Sample Mendelian Randomization Study. Cancer Epidemiol Biomarkers Prev 2019; 29:487-492. [PMID: 31748259 DOI: 10.1158/1055-9965.epi-19-0724] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2019] [Revised: 09/19/2019] [Accepted: 11/15/2019] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND The association of plasma homocysteine level (PHL) with gastric cancer risk was reported in observational studies. However, the causality is challenging due to confounding factors and the lack of evidence from well-designed cohort studies. Herein, we performed a two-sample Mendelian randomization (MR) analysis to investigate whether PHL is causally related to gastric cancer risk. METHODS We performed the MR analysis based on the results from genome-wide association studies consisting of 2,631 patients with gastric cancer and 4,373 controls. An externally weighted genetic risk score (wGRS) was constructed with 15 SNPs with well-established associations with PHL. We utilized logistic regression model to estimate associations of PHL-related SNPs and wGRS with gastric cancer risk in total population and in strata by sex, age, and study site, in addition to a series of sensitivity analyses. RESULTS High genetically predicted PHL was associated with an increased gastric cancer risk (per SD increase in the wGRS: OR = 1.07; 95% confidence interval, 1.01-1.12; P = 0.011), which was consistent in sensitivity analyses. Subgroup analyses provided evidence of a stronger association with gastric cancer risk in women than in men. MR-Egger and weighted median regression suggested that potentially unknown pleiotropic effects were not biasing the association between PHL and gastric cancer risk. CONCLUSIONS These results revealed that genetically predicted high PHL was associated with an increased gastric cancer risk, suggesting that high PHL may have a causal role in the etiology of gastric cancer. IMPACT These findings provide causal inference for PHL on gastric cancer risk, suggesting a causal role of high PHL in the etiology of gastric cancer.
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Affiliation(s)
- Tianpei Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Chuanli Ren
- Clinical Medical Testing Laboratory, Northern Jiangsu People's Hospital and Clinical Medical College of Yangzhou University, Yangzhou, China
| | - Jing Ni
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Hui Ding
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Qi Qi
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Caiwang Yan
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Bin Deng
- Department of Gastroenterology, The Affiliated Hospital of Yangzhou University, Yangzhou, China
| | - Juncheng Dai
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Gang Li
- Department of General Surgery, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
| | - Yanbing Ding
- Department of Gastroenterology, The Affiliated Hospital of Yangzhou University, Yangzhou, China
| | - Guangfu Jin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China. .,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
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Zhou Y, Sun X, Zhou M. Body Shape and Alzheimer's Disease: A Mendelian Randomization Analysis. Front Neurosci 2019; 13:1084. [PMID: 31649504 PMCID: PMC6795688 DOI: 10.3389/fnins.2019.01084] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2019] [Accepted: 09/25/2019] [Indexed: 01/27/2023] Open
Abstract
Obesity has been reported to be related to memory impairment and decline in cognitive function, possibly further leading to the development of Alzheimer’s disease (AD). However, observational studies revealed both negative and positive associations between body shape (BS) and AD, thereby making it difficult to confirm causality due to residual confounds and reverse causation. Thus, using genome-wide association study summary data, two-sample Mendelian randomization (MR) analyses were applied to identify whether there exists a causal association between BS and AD. BS was measured using anthropometric traits (ATs) in this study, including body mass index (BMI), waist-to-hip ratio (WHR), waist-to-hip ratio adjusted by body mass index (WHRadjBMI), and waist circumference (WC). The associations of single nucleotide polymorphisms (SNP) with each AT and AD were obtained separately from aggregated data from the Genetic Investigation of Anthropometric Traits (GIANT) consortium and International Genomics of Alzheimer’s Project (IGAP) summary data (17,008 cases with AD and 37,154 controls). An inverse-variance weighted method was applied to obtain the overall causal estimate for multiple instrumental SNPs. The odds ratio (OR) [95% confidence interval (CI)] for AD risk per 1-SD difference in BMI was 1.04 (0.88, 1.23), in WHR was 1.01 (0.77, 1.33), in WHRadjBMI was 1.12 (0.89, 1.41), and in WC was 1.02 (0.82, 1.27). Furthermore, simulation analyses of survivor bias indicated the overall causal effect of BMI on risk of AD was not biased. In conclusion, the evidence from MR analyses showed no casual effect of BS on AD risk, which is inconsistent with the results from previous observational studies. The biological mechanism underlying the findings warrants further study.
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Affiliation(s)
- Yuchang Zhou
- Department of Biostatistics, School of Public Health, Shandong University, Jinan, China
| | - Xiubin Sun
- Department of Biostatistics, School of Public Health, Shandong University, Jinan, China
| | - Maigeng Zhou
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
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Battram T, Richmond RC, Baglietto L, Haycock PC, Perduca V, Bojesen SE, Gaunt TR, Hemani G, Guida F, Carreras-Torres R, Hung R, Amos CI, Freeman JR, Sandanger TM, Nøst TH, Nordestgaard BG, Teschendorff AE, Polidoro S, Vineis P, Severi G, Hodge AM, Giles GG, Grankvist K, Johansson MB, Johansson M, Davey Smith G, Relton CL. Appraising the causal relevance of DNA methylation for risk of lung cancer. Int J Epidemiol 2019; 48:1493-1504. [PMID: 31549173 PMCID: PMC6857764 DOI: 10.1093/ije/dyz190] [Citation(s) in RCA: 48] [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] [Accepted: 09/02/2019] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND DNA methylation changes in peripheral blood have recently been identified in relation to lung cancer risk. Some of these changes have been suggested to mediate part of the effect of smoking on lung cancer. However, limitations with conventional mediation analyses mean that the causal nature of these methylation changes has yet to be fully elucidated. METHODS We first performed a meta-analysis of four epigenome-wide association studies (EWAS) of lung cancer (918 cases, 918 controls). Next, we conducted a two-sample Mendelian randomization analysis, using genetic instruments for methylation at CpG sites identified in the EWAS meta-analysis, and 29 863 cases and 55 586 controls from the TRICL-ILCCO lung cancer consortium, to appraise the possible causal role of methylation at these sites on lung cancer. RESULTS Sixteen CpG sites were identified from the EWAS meta-analysis [false discovery rate (FDR) < 0.05], for 14 of which we could identify genetic instruments. Mendelian randomization provided little evidence that DNA methylation in peripheral blood at the 14 CpG sites plays a causal role in lung cancer development (FDR > 0.05), including for cg05575921-AHRR where methylation is strongly associated with both smoke exposure and lung cancer risk. CONCLUSIONS The results contrast with previous observational and mediation analysis, which have made strong claims regarding the causal role of DNA methylation. Thus, previous suggestions of a mediating role of methylation at sites identified in peripheral blood, such as cg05575921-AHRR, could be unfounded. However, this study does not preclude the possibility that differential DNA methylation at other sites is causally involved in lung cancer development, especially within lung tissue.
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Affiliation(s)
- Thomas Battram
- MRC Integrative Epidemiology Unit
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Rebecca C Richmond
- MRC Integrative Epidemiology Unit
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Laura Baglietto
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Philip C Haycock
- MRC Integrative Epidemiology Unit
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Vittorio Perduca
- Laboratoire de Mathématiques Appliquées, Université Paris Descartes, Paris, France
| | - Stig E Bojesen
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Copenhagen City Heart Study, Frederiksberg Hospital, Copenhagen University Hospital, Copenhagen, Denmark
| | - Tom R Gaunt
- MRC Integrative Epidemiology Unit
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Gibran Hemani
- MRC Integrative Epidemiology Unit
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Florence Guida
- Genetic Epidemiology Division, International Agency for Research on Cancer, Lyon, France
| | - Robert Carreras-Torres
- Genetic Epidemiology Division, International Agency for Research on Cancer, Lyon, France
| | - Rayjean Hung
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada
| | - Christopher I Amos
- Biomedical Data Science, Geisel School of Medicine, Dartmouth College, Hanover, NH, USA
| | - Joshua R Freeman
- Department of Biostatistics and Epidemiology, University of Massachusetts, Amherst, MA, USA
| | - Torkjel M Sandanger
- Department of Community Medicine,Arctic University of Norway, Tromso, Norway
| | - Therese H Nøst
- Department of Community Medicine,Arctic University of Norway, Tromso, Norway
| | - Børge G Nordestgaard
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Copenhagen City Heart Study, Frederiksberg Hospital, Copenhagen University Hospital, Copenhagen, Denmark
| | - Andrew E Teschendorff
- Department of Women's Cancer, Institute for Women's Health, University College London, London, UK
- UCL Cancer Institute, University College London, London, UK
- Chinese Academy of Sciences (CAS) Key Laboratory of Computational Biology, CAS–Max Planck Gesellschaft (MPG) Partner Institute for Computational Biology, Shanghai, China
| | - Silvia Polidoro
- Molecular and Genetic Epidemiology Unit, Italian Institute for Genomic Medicine (IIGM), Turin, Italy
| | - Paolo Vineis
- Molecular and Genetic Epidemiology Unit, Italian Institute for Genomic Medicine (IIGM), Turin, Italy
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Gianluca Severi
- CESP (Inserm U1018), Facultés de Médicine Université Paris-Sud, UVSQ, Université Paris-Saclay, Gustave Roussy, 94805, Villejuif, France
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population & Global Health, University of Melbourne, Melbourne, VIC, Australia
| | - Allison M Hodge
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population & Global Health, University of Melbourne, Melbourne, VIC, Australia
| | - Graham G Giles
- Cancer Epidemiology & Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population & Global Health, University of Melbourne, Melbourne, VIC, Australia
| | | | | | - Mattias Johansson
- Genetic Epidemiology Division, International Agency for Research on Cancer, Lyon, France
| | - George Davey Smith
- MRC Integrative Epidemiology Unit
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Caroline L Relton
- MRC Integrative Epidemiology Unit
- Population Health Sciences, University of Bristol, Bristol, UK
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Censin JC, Peters SAE, Bovijn J, Ferreira T, Pulit SL, Mägi R, Mahajan A, Holmes MV, Lindgren CM. Causal relationships between obesity and the leading causes of death in women and men. PLoS Genet 2019; 15:e1008405. [PMID: 31647808 PMCID: PMC6812754 DOI: 10.1371/journal.pgen.1008405] [Citation(s) in RCA: 92] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Accepted: 09/09/2019] [Indexed: 12/25/2022] Open
Abstract
Obesity traits are causally implicated with risk of cardiometabolic diseases. It remains unclear whether there are similar causal effects of obesity traits on other non-communicable diseases. Also, it is largely unexplored whether there are any sex-specific differences in the causal effects of obesity traits on cardiometabolic diseases and other leading causes of death. We constructed sex-specific genetic risk scores (GRS) for three obesity traits; body mass index (BMI), waist-hip ratio (WHR), and WHR adjusted for BMI, including 565, 324, and 337 genetic variants, respectively. These GRSs were then used as instrumental variables to assess associations between the obesity traits and leading causes of mortality in the UK Biobank using Mendelian randomization. We also investigated associations with potential mediators, including smoking, glycemic and blood pressure traits. Sex-differences were subsequently assessed by Cochran's Q-test (Phet). A Mendelian randomization analysis of 228,466 women and 195,041 men showed that obesity causes coronary artery disease, stroke (particularly ischemic), chronic obstructive pulmonary disease, lung cancer, type 2 and 1 diabetes mellitus, non-alcoholic fatty liver disease, chronic liver disease, and acute and chronic renal failure. Higher BMI led to higher risk of type 2 diabetes in women than in men (Phet = 1.4×10-5). Waist-hip-ratio led to a higher risk of chronic obstructive pulmonary disease (Phet = 3.7×10-6) and higher risk of chronic renal failure (Phet = 1.0×10-4) in men than women. Obesity traits have an etiological role in the majority of the leading global causes of death. Sex differences exist in the effects of obesity traits on risk of type 2 diabetes, chronic obstructive pulmonary disease, and renal failure, which may have downstream implications for public health.
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Affiliation(s)
- Jenny C. Censin
- Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Sanne A. E. Peters
- The George Institute for Global Health, University of Oxford, Oxford, United Kingdom
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jonas Bovijn
- Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Teresa Ferreira
- Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
| | - Sara L. Pulit
- Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
- Department of Genetics, Center for Molecular Medicine, University Medical Center Utrecht, Utrecht, The Netherlands
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America
| | - Reedik Mägi
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Michael V. Holmes
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Oxford, United Kingdom
- Medical Research Council Population Health Research Unit at the University of Oxford, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, Big Data Institute Building, Roosevelt Drive, University of Oxford, Oxford, United Kingdom
| | - Cecilia M. Lindgren
- Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America
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Dong J, Gharahkhani P, Chow WH, Gammon MD, Liu G, Caldas C, Wu AH, Ye W, Onstad L, Anderson LA, Bernstein L, Pharoah PD, Risch HA, Corley DA, Fitzgerald RC, Iyer PG, Reid BJ, Lagergren J, Shaheen NJ, Vaughan TL, MacGregor S, Love S, Palles C, Tomlinson I, Gockel I, May A, Gerges C, Anders M, Böhmer AC, Becker J, Kreuser N, Thieme R, Noder T, Venerito M, Veits L, Schmidt T, Schmidt C, Izbicki JR, Hölscher AH, Lang H, Lorenz D, Schumacher B, Mayershofer R, Vashist Y, Ott K, Vieth M, Weismüller J, Nöthen MM, Moebus S, Knapp M, Peters WHM, Neuhaus H, Rösch T, Ell C, Jankowski J, Schumacher J, Neale RE, Whiteman DC, Thrift AP. No Association Between Vitamin D Status and Risk of Barrett's Esophagus or Esophageal Adenocarcinoma: A Mendelian Randomization Study. Clin Gastroenterol Hepatol 2019; 17:2227-2235.e1. [PMID: 30716477 PMCID: PMC6675666 DOI: 10.1016/j.cgh.2019.01.041] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Revised: 01/23/2019] [Accepted: 01/24/2019] [Indexed: 02/07/2023]
Abstract
BACKGROUND & AIMS Epidemiology studies of circulating concentrations of 25 hydroxy vitamin D (25(OH)D) and risk of esophageal adenocarcinoma (EAC) have produced conflicting results. We conducted a Mendelian randomization study to determine the associations between circulating concentrations of 25(OH)D and risks of EAC and its precursor, Barrett's esophagus (BE). METHODS We conducted a Mendelian randomization study using a 2-sample (summary data) approach. Six single-nucleotide polymorphisms (SNPs; rs3755967, rs10741657, rs12785878, rs10745742, rs8018720, and rs17216707) associated with circulating concentrations of 25(OH)D were used as instrumental variables. We collected data from 6167 patients with BE, 4112 patients with EAC, and 17,159 individuals without BE or EAC (controls) participating in the Barrett's and Esophageal Adenocarcinoma Consortium, as well as studies from Bonn, Germany, and Cambridge and Oxford, United Kingdom. Analyses were performed separately for BE and EAC. RESULTS Overall, we found no evidence for an association between genetically estimated 25(OH)D concentration and risk of BE or EAC. The odds ratio per 20 nmol/L increase in genetically estimated 25(OH)D concentration for BE risk estimated by combining the individual SNP association using inverse variance weighting was 1.21 (95% CI, 0.77-1.92; P = .41). The odds ratio for EAC risk, estimated by combining the individual SNP association using inverse variance weighting, was 0.68 (95% CI, 0.39-1.19; P = .18). CONCLUSIONS In a Mendelian randomization study, we found that low genetically estimated 25(OH)D concentrations were not associated with risk of BE or EAC.
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Affiliation(s)
- Jing Dong
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas
| | - Puya Gharahkhani
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Wong-Ho Chow
- Department of Epidemiology, MD Anderson Cancer Center, Houston, Texas
| | - Marilie D Gammon
- Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina
| | - Geoffrey Liu
- Pharmacogenomic Epidemiology, Ontario Cancer Institute, Toronto, Ontario, Canada
| | - Carlos Caldas
- Cancer Research UK, Cambridge Institute, Cambridge, United Kingdom
| | - Anna H Wu
- Department of Preventive Medicine, University of Southern California, Norris Comprehensive Cancer Center, Los Angeles, California
| | - Weimin Ye
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Lynn Onstad
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Lesley A Anderson
- Centre for Public Health, Queen's University Belfast, Belfast, Northern Ireland
| | - Leslie Bernstein
- Department of Population Sciences, Beckman Research Institute and City of Hope Comprehensive Cancer Center, Duarte, California
| | - Paul D Pharoah
- Department of Oncology, University of Cambridge, Cambridge, United Kingdom; Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Harvey A Risch
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, Connecticut
| | - Douglas A Corley
- Division of Research, Kaiser Permanente Northern California, Oakland, California; San Francisco Medical Center, Kaiser Permanente Northern California, San Francisco, California
| | - Rebecca C Fitzgerald
- Medical Research Council Cancer Unit, Hutchison-Medical Research Council Research Centre, University of Cambridge, Cambridge, United Kingdom
| | - Prasad G Iyer
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota
| | - Brian J Reid
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Jesper Lagergren
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden; School of Cancer and Pharmaceutical Sciences, King's College London, London, United Kingdom
| | - Nicholas J Shaheen
- Division of Gastroenterology and Hepatology, School of Medicine, University of North Carolina, Chapel Hill, North Carolina
| | - Thomas L Vaughan
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Stuart MacGregor
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Sharon Love
- Oxford Clinical Trials Research Unit, Centre for Statistics in Medicine, Oxford, United Kingdom
| | - Claire Palles
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Ian Tomlinson
- Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Ines Gockel
- Department of Visceral, Transplant, Thoracic and Vascular Surgery, University Hospital of Leipzig, Leipzig, Germany
| | - Andrea May
- Department of Medicine II, Sana Klinikum, Offenbach, Germany
| | - Christian Gerges
- Department of Internal Medicine II, Evangelisches Krankenhaus, Düsseldorf, Germany
| | - Mario Anders
- Department of Interdisciplinary Endoscopy, University Hospital Hamburg-Eppendorf, Hamburg, Germany; Department of Gastroenterology and Interdisciplinary Endoscopy, Vivantes Wenckebach-Klinikum, Berlin, Germany
| | - Anne C Böhmer
- Institute of Human Genetics, University of Bonn, Bonn, Germany; Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany
| | - Jessica Becker
- Department of Gastroenterology, Hepatology and Infectious Diseases, Otto-von-Guericke University Hospital, Magdeburg, Germany; Institute of Pathology, Klinikum Bayreuth, Bayreuth, Germany
| | - Nicole Kreuser
- Department of Visceral, Transplant, Thoracic and Vascular Surgery, University Hospital of Leipzig, Leipzig, Germany
| | - Rene Thieme
- Department of Visceral, Transplant, Thoracic and Vascular Surgery, University Hospital of Leipzig, Leipzig, Germany
| | - Tania Noder
- Department of Interdisciplinary Endoscopy, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Marino Venerito
- Department of Gastroenterology, Hepatology and Infectious Diseases, Otto-von-Guericke University Hospital, Magdeburg, Germany
| | - Lothar Veits
- Institute of Pathology, Klinikum Bayreuth, Bayreuth, Germany
| | - Thomas Schmidt
- Department of General, Visceral and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany
| | - Claudia Schmidt
- Department of General, Visceral and Cancer Surgery, University of Cologne, Cologne, Germany
| | - Jakob R Izbicki
- Department of General, Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, University of Hamburg, Hamburg, Germany
| | - Arnulf H Hölscher
- Department of General, Visceral and Cancer Surgery, University of Cologne, Cologne, Germany
| | - Hauke Lang
- Department of General, Visceral and Transplant Surgery, University Medical Center, University of Mainz, Mainz, Germany
| | - Dietmar Lorenz
- Department of General, Visceral and Thoracic Surgery, Klinikum Darmstadt, Darmstadt, Germany
| | - Brigitte Schumacher
- Department of Internal Medicine and Gastroenterology, Elisabeth Hospital, Essen, Germany
| | | | - Yogesh Vashist
- Department of General, Visceral and Thoracic Surgery, University Medical Center Hamburg-Eppendorf, University of Hamburg, Hamburg, Germany; Kantonsspital Aarau, Aarau, Switzerland
| | - Katja Ott
- Department of General, Visceral and Transplantation Surgery, University of Heidelberg, Heidelberg, Germany; Department of General, Visceral and Thorax Surgery, RoMed Klinikum Rosenheim, Rosenheim, Germany
| | - Michael Vieth
- Institute of Pathology, Klinikum Bayreuth, Bayreuth, Germany
| | | | - Markus M Nöthen
- Institute of Human Genetics, University of Bonn, Bonn, Germany; Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany
| | - Susanne Moebus
- Centre of Urban Epidemiology, Institute of Medical Informatics, Biometry and Epidemiology, University of Essen, Essen, Germany
| | - Michael Knapp
- Institute for Medical Biometry, Informatics, and Epidemiology, University of Bonn, Bonn, Germany
| | - Wilbert H M Peters
- Department of Gastroenterology, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands
| | - Horst Neuhaus
- Institute of Human Genetics, University of Bonn, Bonn, Germany
| | - Thomas Rösch
- Department of Internal Medicine II, Evangelisches Krankenhaus, Düsseldorf, Germany
| | - Christian Ell
- Department of Medicine II, Sana Klinikum, Offenbach, Germany
| | | | - Johannes Schumacher
- Institute of Human Genetics, University of Bonn, Bonn, Germany; Department of Genomics, Life and Brain Center, University of Bonn, Bonn, Germany
| | - Rachel E Neale
- Cancer Aetiology and Prevention, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - David C Whiteman
- Cancer Control, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Aaron P Thrift
- Dan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas; Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, Texas.
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Pazoki R, Evangelou E, Mosen-Ansorena D, Pinto RC, Karaman I, Blakeley P, Gill D, Zuber V, Elliott P, Tzoulaki I, Dehghan A. GWAS for urinary sodium and potassium excretion highlights pathways shared with cardiovascular traits. Nat Commun 2019; 10:3653. [PMID: 31409800 PMCID: PMC6692500 DOI: 10.1038/s41467-019-11451-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2018] [Accepted: 06/27/2019] [Indexed: 01/04/2023] Open
Abstract
Urinary sodium and potassium excretion are associated with blood pressure (BP) and cardiovascular disease (CVD). The exact biological link between these traits is yet to be elucidated. Here, we identify 50 loci for sodium and 13 for potassium excretion in a large-scale genome-wide association study (GWAS) on urinary sodium and potassium excretion using data from 446,237 individuals of European descent from the UK Biobank study. We extensively interrogate the results using multiple analyses such as Mendelian randomization, functional assessment, co localization, genetic risk score, and pathway analyses. We identify a shared genetic component between urinary sodium and potassium expression and cardiovascular traits. Ingenuity pathway analysis shows that urinary sodium and potassium excretion loci are over-represented in behavioural response to stimuli. Our study highlights pathways that are shared between urinary sodium and potassium excretion and cardiovascular traits.
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Affiliation(s)
- Raha Pazoki
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary's campus, Norfolk Place, London, W2 1PG, UK
| | - Evangelos Evangelou
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary's campus, Norfolk Place, London, W2 1PG, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, 45110, Ioannina, Greece
| | - David Mosen-Ansorena
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary's campus, Norfolk Place, London, W2 1PG, UK
| | - Rui Climaco Pinto
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary's campus, Norfolk Place, London, W2 1PG, UK
- Dementia Research Institute at Imperial College London, London, W2 1PG, UK
| | - Ibrahim Karaman
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary's campus, Norfolk Place, London, W2 1PG, UK
- Dementia Research Institute at Imperial College London, London, W2 1PG, UK
| | - Paul Blakeley
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary's campus, Norfolk Place, London, W2 1PG, UK
- NIHR Imperial Biomedical Research Centre, ITMAT Data Science Group, Imperial College London, London, W2 1PG, UK
| | - Dipender Gill
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary's campus, Norfolk Place, London, W2 1PG, UK
- Department of Stroke Medicine, Imperial College London, London, W2 1PG, UK
| | - Verena Zuber
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary's campus, Norfolk Place, London, W2 1PG, UK
| | - Paul Elliott
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary's campus, Norfolk Place, London, W2 1PG, UK
- Dementia Research Institute at Imperial College London, London, W2 1PG, UK
- Imperial College NIHR Biomedical Research Centre, London, W2 1NY, UK
- Health Data Research UK-London, London, NW1 2BE, UK
| | - Ioanna Tzoulaki
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary's campus, Norfolk Place, London, W2 1PG, UK.
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, 45110, Ioannina, Greece.
- Dementia Research Institute at Imperial College London, London, W2 1PG, UK.
| | - Abbas Dehghan
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary's campus, Norfolk Place, London, W2 1PG, UK.
- Dementia Research Institute at Imperial College London, London, W2 1PG, UK.
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Gill D, Brewer CF, Monori G, Trégouët D, Franceschini N, Giambartolomei C, Tzoulaki I, Dehghan A. Effects of Genetically Determined Iron Status on Risk of Venous Thromboembolism and Carotid Atherosclerotic Disease: A Mendelian Randomization Study. J Am Heart Assoc 2019; 8:e012994. [PMID: 31310728 PMCID: PMC6761644 DOI: 10.1161/jaha.119.012994] [Citation(s) in RCA: 48] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Accepted: 05/21/2019] [Indexed: 12/16/2022]
Abstract
Background Systemic iron status has been implicated in atherosclerosis and thrombosis. The aim of this study was to investigate the effect of genetically determined iron status on carotid intima-media thickness, carotid plaque, and venous thromboembolism using Mendelian randomization. Methods and Results Genetic instrumental variables for iron status were selected from a genome-wide meta-analysis of 48 972 subjects. Genetic association estimates for carotid intima-media thickness and carotid plaque were obtained using data from 71 128 and 48 434 participants, respectively, and estimates for venous thromboembolism were obtained using data from a study incorporating 7507 cases and 52 632 controls. Conventional 2-sample summary data Mendelian randomization was performed for the main analysis. Higher genetically determined iron status was associated with increased risk of venous thromboembolism. Odds ratios per SD increase in biomarker levels were 1.37 (95% CI 1.14-1.66) for serum iron, 1.25 (1.09-1.43) for transferrin saturation, 1.92 (1.28-2.88) for ferritin, and 0.76 (0.63-0.92) for serum transferrin (with higher transferrin levels representing lower iron status). In contrast, higher iron status was associated with lower risk of carotid plaque. Corresponding odds ratios were 0.85 (0.73-0.99) for serum iron and 0.89 (0.80-1.00) for transferrin saturation, with concordant trends for serum transferrin and ferritin that did not reach statistical significance. There was no Mendelian randomization evidence of an effect of iron status on carotid intima-media thickness. Conclusions These findings support previous work to suggest that higher genetically determined iron status is protective against some forms of atherosclerotic disease but increases the risk of thrombosis related to stasis of blood.
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Affiliation(s)
- Dipender Gill
- Department of Epidemiology and BiostatisticsSchool of Public HealthImperial College LondonLondonUnited Kingdom
| | | | - Grace Monori
- Department of Epidemiology and BiostatisticsSchool of Public HealthImperial College LondonLondonUnited Kingdom
| | | | - Nora Franceschini
- Department of EpidemiologyUNC Gillings Global School of Public HealthChapel HillNC
| | - Claudia Giambartolomei
- Department of Pathology and Laboratory MedicineUniversity of California, Los AngelesLos AngelesCA
| | | | - Ioanna Tzoulaki
- Department of Epidemiology and BiostatisticsSchool of Public HealthImperial College LondonLondonUnited Kingdom
- MRC‐PHE Centre for EnvironmentSchool of Public HealthImperial College LondonLondonUnited Kingdom
- Department of Hygiene and EpidemiologyUniversity of Ioannina Medical SchoolIoanninaGreece
| | - Abbas Dehghan
- Department of Epidemiology and BiostatisticsSchool of Public HealthImperial College LondonLondonUnited Kingdom
- MRC‐PHE Centre for EnvironmentSchool of Public HealthImperial College LondonLondonUnited Kingdom
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40
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Carslake D, Fraser A, May MT, Palmer T, Silventoinen K, Tynelius P, Lawlor DA, Davey Smith G. Associations of mortality with own blood pressure using son's blood pressure as an instrumental variable. Sci Rep 2019; 9:8986. [PMID: 31222129 PMCID: PMC6586810 DOI: 10.1038/s41598-019-45391-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2019] [Accepted: 05/28/2019] [Indexed: 11/09/2022] Open
Abstract
High systolic blood pressure (SBP) causes cardiovascular disease (CVD) and is associated with mortality from other causes, but conventional multivariably-adjusted results may be confounded. Here we used a son’s SBP (>1 million Swedish men) as an instrumental variable for parental SBP and examined associations with parents’ cause-specific mortality, avoiding reverse causation. The hazard ratio for CVD mortality per SD (10.80 mmHg) of SBP was 1.49 (95% CI: 1.43, 1.56); SBP was positively associated with coronary heart disease and stroke. SBP was also associated positively with all-cause, diabetes and kidney cancer mortality, and negatively with external causes. Negative associations with respiratory-related mortality were probably confounded by smoking. Hazard ratios for other causes were imprecise or null. Diastolic blood pressure gave similar results to SBP. CVD hazard ratios were intermediate between those from conventional multivariable studies and Mendelian randomization and stronger than those from clinical trials, approximately consistent with an effect of exposure duration on effect sizes. Plots of parental mortality against offspring SBP were approximately linear, supporting calls for lower SBP targets. Results suggest that conventional multivariable analyses of mortality and SBP are not substantially confounded by reverse causation and confirm positive effects of SBP on all-cause, CVD and diabetes mortality.
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Affiliation(s)
- David Carslake
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK. .,Population Health Sciences, Bristol Medical School, Bristol, UK.
| | - Abigail Fraser
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, Bristol, UK
| | - Margaret T May
- Population Health Sciences, Bristol Medical School, Bristol, UK
| | - Tom Palmer
- Department of Mathematics and Statistics, University of Lancaster, Lancaster, UK
| | - Karri Silventoinen
- Population Research Unit, Department of Social Research, University of Helsinki, Helsinki, Finland
| | - Per Tynelius
- Department of Public Health Sciences, Karolinska Institute, Stockholm, Sweden
| | - Debbie A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, Bristol, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, Bristol, UK
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41
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Bowden J, Del Greco M F, Minelli C, Zhao Q, Lawlor DA, Sheehan NA, Thompson J, Davey Smith G. Improving the accuracy of two-sample summary-data Mendelian randomization: moving beyond the NOME assumption. Int J Epidemiol 2019; 48:728-742. [PMID: 30561657 PMCID: PMC6659376 DOI: 10.1093/ije/dyy258] [Citation(s) in RCA: 505] [Impact Index Per Article: 84.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/09/2018] [Indexed: 01/25/2023] Open
Abstract
BACKGROUND Two-sample summary-data Mendelian randomization (MR) incorporating multiple genetic variants within a meta-analysis framework is a popular technique for assessing causality in epidemiology. If all genetic variants satisfy the instrumental variable (IV) and necessary modelling assumptions, then their individual ratio estimates of causal effect should be homogeneous. Observed heterogeneity signals that one or more of these assumptions could have been violated. METHODS Causal estimation and heterogeneity assessment in MR require an approximation for the variance, or equivalently the inverse-variance weight, of each ratio estimate. We show that the most popular 'first-order' weights can lead to an inflation in the chances of detecting heterogeneity when in fact it is not present. Conversely, ostensibly more accurate 'second-order' weights can dramatically increase the chances of failing to detect heterogeneity when it is truly present. We derive modified weights to mitigate both of these adverse effects. RESULTS Using Monte Carlo simulations, we show that the modified weights outperform first- and second-order weights in terms of heterogeneity quantification. Modified weights are also shown to remove the phenomenon of regression dilution bias in MR estimates obtained from weak instruments, unlike those obtained using first- and second-order weights. However, with small numbers of weak instruments, this comes at the cost of a reduction in estimate precision and power to detect a causal effect compared with first-order weighting. Moreover, first-order weights always furnish unbiased estimates and preserve the type I error rate under the causal null. We illustrate the utility of the new method using data from a recent two-sample summary-data MR analysis to assess the causal role of systolic blood pressure on coronary heart disease risk. CONCLUSIONS We propose the use of modified weights within two-sample summary-data MR studies for accurately quantifying heterogeneity and detecting outliers in the presence of weak instruments. Modified weights also have an important role to play in terms of causal estimation (in tandem with first-order weights) but further research is required to understand their strengths and weaknesses in specific settings.
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Affiliation(s)
- Jack Bowden
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, University of Bristol, Bristol, UK
| | | | - Cosetta Minelli
- Population Health and Occupational Disease, NHLI, Imperial College, London, UK
| | - Qingyuan Zhao
- Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA
| | - Debbie A Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Nuala A Sheehan
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - John Thompson
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, University of Bristol, Bristol, UK
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42
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Pagoni P, Dimou NL, Murphy N, Stergiakouli E. Using Mendelian randomisation to assess causality in observational studies. EVIDENCE-BASED MENTAL HEALTH 2019; 22:67-71. [PMID: 30979719 PMCID: PMC10270458 DOI: 10.1136/ebmental-2019-300085] [Citation(s) in RCA: 74] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Revised: 03/25/2019] [Accepted: 03/26/2019] [Indexed: 12/15/2022]
Abstract
OBJECTIVE Mendelian randomisation (MR) is a technique that aims to assess causal effects of exposures on disease outcomes. The paper aims to present the main assumptions that underlie MR, the statistical methods used to estimate causal effects and how to account for potential violations of the key assumptions. METHODS We discuss the key assumptions that should be satisfied in an MR setting. We list the statistical methodologies used in two-sample MR when summary data are available to estimate causal effects (ie, Wald ratio estimator, inverse-variance weighted and maximum likelihood method) and identify/adjust for potential violations of MR assumptions (ie, MR-Egger regression and weighted Median approach). We also present statistical methods and graphical tools used to evaluate the presence of heterogeneity. RESULTS We use as an illustrative example of a published two-sample MR study, investigating the causal association of body mass index with three psychiatric disorders (ie, bipolar disorder, schizophrenia and major depressive disorder). We highlight the importance of assessing the results of all available methods rather than each method alone. We also demonstrate the impact of heterogeneity in the estimation of the causal effects. CONCLUSIONS MR is a useful tool to assess causality of risk factors in medical research. Assessment of the key assumptions underlying MR is crucial for a valid interpretation of the results.
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Affiliation(s)
- Panagiota Pagoni
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Niki L Dimou
- International Agency for Research on Cancer, Lyon, France
| | - Neil Murphy
- International Agency for Research on Cancer, Lyon, France
| | - Evie Stergiakouli
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, University of Bristol, Bristol, UK
- School of Oral and Dental Sciences, University of Bristol, Bristol, UK
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43
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Qian F, Wang S, Mitchell J, McGuffog L, Barrowdale D, Leslie G, Oosterwijk JC, Chung WK, Evans DG, Engel C, Kast K, Aalfs CM, Adank MA, Adlard J, Agnarsson BA, Aittomäki K, Alducci E, Andrulis IL, Arun BK, Ausems MGEM, Azzollini J, Barouk-Simonet E, Barwell J, Belotti M, Benitez J, Berger A, Borg A, Bradbury AR, Brunet J, Buys SS, Caldes T, Caligo MA, Campbell I, Caputo SM, Chiquette J, Claes KBM, Margriet Collée J, Couch FJ, Coupier I, Daly MB, Davidson R, Diez O, Domchek SM, Donaldson A, Dorfling CM, Eeles R, Feliubadaló L, Foretova L, Fowler J, Friedman E, Frost D, Ganz PA, Garber J, Garcia-Barberan V, Glendon G, Godwin AK, Gómez Garcia EB, Gronwald J, Hahnen E, Hamann U, Henderson A, Hendricks CB, Hopper JL, Hulick PJ, Imyanitov EN, Isaacs C, Izatt L, Izquierdo Á, Jakubowska A, Kaczmarek K, Kang E, Karlan BY, Kets CM, Kim SW, Kim Z, Kwong A, Laitman Y, Lasset C, Hyuk Lee M, Won Lee J, Lee J, Lester J, Lesueur F, Loud JT, Lubinski J, Mebirouk N, Meijers-Heijboer HEJ, Meindl A, Miller A, Montagna M, Mooij TM, Morrison PJ, Mouret-Fourme E, Nathanson KL, Neuhausen SL, Nevanlinna H, Niederacher D, Nielsen FC, Nussbaum RL, Offit K, Olah E, Ong KR, Ottini L, Park SK, Peterlongo P, Pfeiler G, Phelan CM, Poppe B, Pradhan N, Radice P, Ramus SJ, Rantala J, Robson M, Rodriguez GC, Schmutzler RK, Hutten Selkirk CG, Shah PD, Simard J, Singer CF, Sokolowska J, Stoppa-Lyonnet D, Sutter C, Yen Tan Y, Teixeira RM, Teo SH, Terry MB, Thomassen M, Tischkowitz M, Toland AE, Tucker KM, Tung N, van Asperen CJ, van Engelen K, van Rensburg EJ, Wang-Gohrke S, Wappenschmidt B, Weitzel JN, Yannoukakos D, Greene MH, Rookus MA, Easton DF, Chenevix-Trench G, Antoniou AC, Goldgar DE, Olopade OI, Rebbeck TR, Huo D. Height and Body Mass Index as Modifiers of Breast Cancer Risk in BRCA1/2 Mutation Carriers: A Mendelian Randomization Study. J Natl Cancer Inst 2019; 111:350-364. [PMID: 30312457 PMCID: PMC6449171 DOI: 10.1093/jnci/djy132] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2017] [Revised: 06/03/2018] [Accepted: 06/29/2018] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND BRCA1/2 mutations confer high lifetime risk of breast cancer, although other factors may modify this risk. Whether height or body mass index (BMI) modifies breast cancer risk in BRCA1/2 mutation carriers remains unclear. METHODS We used Mendelian randomization approaches to evaluate the association of height and BMI on breast cancer risk, using data from the Consortium of Investigators of Modifiers of BRCA1/2 with 14 676 BRCA1 and 7912 BRCA2 mutation carriers, including 11 451 cases of breast cancer. We created a height genetic score using 586 height-associated variants and a BMI genetic score using 93 BMI-associated variants. We examined both observed and genetically determined height and BMI with breast cancer risk using weighted Cox models. All statistical tests were two-sided. RESULTS Observed height was positively associated with breast cancer risk (HR = 1.09 per 10 cm increase, 95% confidence interval [CI] = 1.0 to 1.17; P = 1.17). Height genetic score was positively associated with breast cancer, although this was not statistically significant (per 10 cm increase in genetically predicted height, HR = 1.04, 95% CI = 0.93 to 1.17; P = .47). Observed BMI was inversely associated with breast cancer risk (per 5 kg/m2 increase, HR = 0.94, 95% CI = 0.90 to 0.98; P = .007). BMI genetic score was also inversely associated with breast cancer risk (per 5 kg/m2 increase in genetically predicted BMI, HR = 0.87, 95% CI = 0.76 to 0.98; P = .02). BMI was primarily associated with premenopausal breast cancer. CONCLUSION Height is associated with overall breast cancer and BMI is associated with premenopausal breast cancer in BRCA1/2 mutation carriers. Incorporating height and BMI, particularly genetic score, into risk assessment may improve cancer management.
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Affiliation(s)
- Frank Qian
- Department of Medicine, The University of Chicago, Chicago, IL
| | - Shengfeng Wang
- Center for Clinical Cancer Genetics, The University of Chicago, Chicago, IL
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Jonathan Mitchell
- Division of Gastroenterology, Department of Hepatology and Nutrition, Children's Hospital of Philadelphia, Philadelphia, PA
| | - Lesley McGuffog
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Daniel Barrowdale
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Goska Leslie
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Jan C Oosterwijk
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Wendy K Chung
- Departments of Pediatrics and Medicine, Columbia University, New York, NY
| | - D Gareth Evans
- Division of Evolution and Genomic Sciences, Genomic Medicine, Manchester Academic Health Sciences Centre, University of Manchester, Central Manchester University Hospitals, NHS Foundation Trust, Manchester, UK
| | - Christoph Engel
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
- LIFE - Leipzig Research Centre for Civilization Diseases, University of Leipzig, Leipzig, Germany
| | - Karin Kast
- Department of Gynecology and Obstetrics, Technical University of Dresden, Dresden, Germany
- Department of Clinical Genetics and GROW, School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Cora M Aalfs
- Department of Clinical Genetics, Academic Medical Center, Amsterdam, the Netherlands
- Center for Medical Genetics, NorthShore University HealthSystem, Evanston, IL
- The University of Chicago Pritzker School of Medicine, Chicago, IL
| | - Muriel A Adank
- Family Cancer Clinic, Netherlands Cancer Institute, Antoni van Leeuwenhoek Hospital, Amsterdam, the Netherlands
| | - Julian Adlard
- Yorkshire Regional Genetics Service, Chapel Allerton Hospital, Leeds, UK
- Department of Clinical Genetics and GROW, School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Bjarni A Agnarsson
- Department of Pathology, National Institute of Oncology, Budapest, Hungary
- School of Medicine, University of Iceland, Reykjavik, Iceland
| | - Kristiina Aittomäki
- Department of Clinical Genetics, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
| | - Elisa Alducci
- Immunology and Molecular Oncology Unit, Veneto Institute of Oncology IOV - IRCCS, Padua, Italy
- Department of Clinical Genetics and GROW, School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Irene L Andrulis
- Fred A. Litwin Center for Cancer Genetics, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Banu K Arun
- Department of Breast Medical Oncology, University of Texas MD Anderson Cancer Center, Houston, TX
| | | | - Jacopo Azzollini
- Unit of Medical Genetics, Department of Medical Oncology and Hematology, Fondazione IRCCS (Istituto Di Ricovero e Cura a Carattere Scientifico) Istituto Nazionale dei Tumori (INT), Milan, Italy
| | - Emmanuelle Barouk-Simonet
- Oncogénétique, Institut Bergonié, Bordeaux, France
- Department of Pathology and Laboratory Medicine, Kansas University Medical Center, Kansas City, KS
| | - Julian Barwell
- Leicestershire Clinical Genetics Service, University Hospitals of Leicester NHS Trust, Leicester, UK
- Genetic Counseling Unit, Hereditary Cancer Program, IDIBGI (Institut d'Investigació Biomèdica de Girona), Catalan Institute of Oncology, CIBERONC, Girona, Spain
| | | | - Javier Benitez
- Schools of Medicine and Public Health, Division of Cancer Prevention & Control Research, Jonsson Comprehensive Cancer Center, University of California Los Angeles, CA
| | - Andreas Berger
- Department of Oncology, Lund University and Skåne University Hospital, Lund, Sweden
| | - Ake Borg
- Cancer Risk and Prevention Clinic, Dana-Farber Cancer Institute, Boston, MA
- Institute of Genetic Medicine, Centre for Life, Newcastle Upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, UK
| | - Angela R Bradbury
- Department of Medicine, Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | - Joan Brunet
- Service de Génétique, Institut Curie, Paris, France
- Human Cancer Genetics Program, Spanish National Cancer Research Centre, Madrid, Spain
- Centro de Investigación en Red de Enfermedades Raras (CIBERER), Valencia, Spain, Department of Obstetrics and Gynecology, Medical University of Vienna, Vienna, Austria
| | - Saundra S Buys
- Department of Medicine, Huntsman Cancer Institute at the University of Utah, Salt Lake City, UT
| | - Trinidad Caldes
- Molecular Oncology Laboratory, Hospital Clinico San Carlos, IdISSC, CIBERONC, Madrid, Spain
| | - Maria A Caligo
- Section of Genetic Oncology, Department of Laboratory Medicine, University and University Hospital of Pisa, Pisa, Italy
| | - Ian Campbell
- Peter MacCallum Cancer Center, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Sandrine M Caputo
- Leicestershire Clinical Genetics Service, University Hospitals of Leicester NHS Trust, Leicester, UK
- Service de Génétique, Institut Curie, Paris, France
| | - Jocelyne Chiquette
- Unité de recherche en santé des populations, Centre des maladies du sein Deschênes-Fabia, Hôpital du Saint-Sacrement, Québec, QC, Canada
| | | | - J Margriet Collée
- Department of Clinical Genetics, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Fergus J Couch
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN
| | - Isabelle Coupier
- Unité d'Oncogénétique, CHU Arnaud de Villeneuve, Montpellier, France
| | - Mary B Daly
- Department of Clinical Genetics, Fox Chase Cancer Center, Philadelphia, PA
| | - Rosemarie Davidson
- Department of Clinical Genetics, South Glasgow University Hospitals, Glasgow, UK
| | - Orland Diez
- N.N. Petrov Institute of Oncology, St. Petersburg, Russia
| | - Susan M Domchek
- Department of Medicine, Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | - Alan Donaldson
- Oncogenetics Group, Clinical and Molecular Genetics Area, Vall d'Hebron Institute of Oncology (VHIO), University Hospital, Vall d'Hebron, Barcelona, Spain (OD); Clinical Genetics Department, St Michael's Hospital, Bristol, UK
| | - Cecilia M Dorfling
- Department of Genetics, University of Pretoria, Arcadia, South Africa
- City of Hope Clinical Cancer Genetics Community Research Network, Duarte, CA
| | - Ros Eeles
- Ocogenetics Team, The Institute of Cancer Research and Royal Marsden NHS Foundation Trust, London, UK
| | - Lidia Feliubadaló
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Lenka Foretova
- Molecular Diagnostic Unit, Hereditary Cancer Program, ICO-IDIBELL (Catalan Institute of Oncology, Bellvitge Biomedical Research Institute), CIBERONC, Barcelona, Spain
- Department of Cancer Epidemiology and Genetics, Masaryk Memorial Cancer Institute, Brno, Czech Republic
| | - Jeffrey Fowler
- The Ohio State University, Columbus Cancer Council, Columbus, OH
| | - Eitan Friedman
- The Susanne Levy Gertner Oncogenetics Unit, Chaim Sheba Medical Center, Ramat Gan, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Ramat Aviv, Israel
| | - Debra Frost
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Patricia A Ganz
- Schools of Medicine and Public Health, Division of Cancer Prevention & Control Research, Jonsson Comprehensive Cancer Center, University of California Los Angeles, CA
| | - Judy Garber
- Cancer Risk and Prevention Clinic, Dana-Farber Cancer Institute, Boston, MA
| | - Vanesa Garcia-Barberan
- Molecular Oncology Laboratory, Hospital Clinico San Carlos, IdISSC, CIBERONC, Madrid, Spain
| | - Gord Glendon
- Fred A. Litwin Center for Cancer Genetics, Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, ON, Canada
| | - Andrew K Godwin
- Department of Pathology and Laboratory Medicine, Kansas University Medical Center, Kansas City, KS
| | - Encarna B Gómez Garcia
- Department of Clinical Genetics and GROW, School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Jacek Gronwald
- Department of Clinical Genetics and GROW, School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Eric Hahnen
- Centers for Hereditary Breast and Ovarian Cancer, Integrated Oncology and Molecular Medicine, University Hospital of Cologne, Cologne, Germany Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Alex Henderson
- Institute of Genetic Medicine, Centre for Life, Newcastle Upon Tyne Hospitals NHS Trust, Newcastle upon Tyne, UK
| | - Carolyn B Hendricks
- City of Hope Clinical Cancer Genetics Community Research Network, Duarte, CA
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Peter J Hulick
- Center for Medical Genetics, NorthShore University HealthSystem, Evanston, IL
- The University of Chicago Pritzker School of Medicine, Chicago, IL
| | | | - Claudine Isaacs
- Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC (CI)
| | - Louise Izatt
- Clinical Genetics, Guy’s and St Thomas’ NHS Foundation Trust, London, UK
| | - Ángel Izquierdo
- Genetic Counseling Unit, Hereditary Cancer Program, IDIBGI (Institut d'Investigació Biomèdica de Girona), Catalan Institute of Oncology, CIBERONC, Girona, Spain
| | - Anna Jakubowska
- Department of Clinical Genetics and GROW, School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Katarzyna Kaczmarek
- Department of Clinical Genetics and GROW, School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Eunyoung Kang
- Department of Surgery, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Beth Y Karlan
- Women's Cancer Program at the Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Carolien M Kets
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Sung-Won Kim
- Department of Surgery, Daerim Saint Mary's Hospital, Seoul, Korea
| | - Zisun Kim
- Department of Surgery, Soonchunhyang University Hospital Bucheon, Bucheon, Korea
| | - Ava Kwong
- Hong Kong Hereditary Breast Cancer Family Registry, Happy Valley, Hong Kong
- Department of Surgery, The University of Hong Kong, Pok Fu Lam, Hong Kong
- Department of Surgery, Hong Kong Sanatorium and Hospital, Happy Valley, Hong Kong
| | - Yael Laitman
- The Susanne Levy Gertner Oncogenetics Unit, Chaim Sheba Medical Center, Ramat Gan, Israel
| | - Christine Lasset
- Unité de Prévention et d’Epidémiologie Génétique, Centre Léon Bérard, Lyon, France
| | - Min Hyuk Lee
- Department of Surgery, Soonchunhyang University College of Medicine and Soonchunhyang University Hospital, Seoul, Korea
| | - Jong Won Lee
- Department of Surgery, Ulsan University College of Medicine and Asan Medical Center, Seoul, Korea
| | - Jihyoun Lee
- Department of Clinical Genetics and GROW, School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, the Netherlands
- Women's Cancer Program at the Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA
- Department of Surgery, Soonchunhyang University College of Medicine and Soonchunhyang University Hospital, Seoul, Korea
| | - Jenny Lester
- Department of Clinical Genetics and GROW, School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Fabienne Lesueur
- Genetic Epidemiology of Cancer team, Institut Curie, Paris, France
- U900, INSERM, Paris, France
- PSL University, Paris, France
- Mines ParisTech, Fontainebleau, France
| | - Jennifer T Loud
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD
| | - Jan Lubinski
- Department of Clinical Genetics and GROW, School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, the Netherlands
| | - Noura Mebirouk
- Genetic Epidemiology of Cancer team, Institut Curie, Paris, France
- U900, INSERM, Paris, France
- PSL University, Paris, France
- Mines ParisTech, Fontainebleau, France
| | | | - Alfons Meindl
- Division of Gynaecology and Obstetrics, Technische Universität München, Munich, Germany
- NRG Oncology, Statistics and Data Management Center, Roswell Park Cancer Institute, Buffalo, NY
| | - Austin Miller
- Division of Gynaecology and Obstetrics, Technische Universität München, Munich, Germany
| | - Marco Montagna
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Thea M Mooij
- Department of Epidemiology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Patrick J Morrison
- Centre for Cancer Research and Cell Biology, Queens University Belfast, Belfast, UK
| | | | | | - Susan L Neuhausen
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, CA
| | - Heli Nevanlinna
- Department of Obstetrics and Gynecology, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
| | - Dieter Niederacher
- Department of Gynecology and Obstetrics, University Hospital Düsseldorf, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Finn C Nielsen
- Center for Genomic Medicine, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Robert L Nussbaum
- Cancer Genetics and Prevention Program, University of California San Francisco, San Francisco, CA
| | - Kenneth Offit
- Clinical Genetics Research Laboratory, Department of Cancer Biology and Genetics, Memorial Sloan-Kettering Cancer Center, New York, NY
- Clinical Genetics Service, Department of Medicine, Memorial Sloan-Kettering Cancer Center, New York, NY
| | - Edith Olah
- Department of Molecular Genetics, National Institute of Oncology, Budapest, Hungary
| | - Kai-Ren Ong
- West Midlands Regional Genetics Service, Birmingham Women’s Hospital Healthcare NHS Trust, Birmingham, UK
| | - Laura Ottini
- Department of Molecular Medicine, University La Sapienza, Rome, Italy
| | - Sue K Park
- Departments of Preventive Medicine and Biomedical Sciences, and Cancer Research Institute, Seoul National University, Seoul, Korea
| | - Paolo Peterlongo
- IFOM, The FIRC (Italian Foundation for Cancer Research) Institute of Molecular Oncology, Milan, Italy
| | - Georg Pfeiler
- Department of Urology, Medical University of Vienna, Vienna, Austria
| | | | - Bruce Poppe
- Centre for Medical Genetics, Ghent University, Ghent, Belgium
| | - Nisha Pradhan
- Clinical Genetics Research Laboratory, Department of Cancer Biology and Genetics, Memorial Sloan-Kettering Cancer Center, New York, NY
| | - Paolo Radice
- Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of Research, Fondazione IRCCS (Istituto Di Ricovero e Cura a Carattere Scientifico) Istituto Nazionale dei Tumori (INT), Milan, Italy
| | - Susan J Ramus
- School of Women's and Children's Health, University of New South Wales Sydney, New South Wales, Australia
- The Kinghorn Cancer Centre, Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | | | - Mark Robson
- Clinical Genetics Service, Department of Medicine, Memorial Sloan-Kettering Cancer Center, New York, NY
| | - Gustavo C Rodriguez
- Division of Gynecologic Oncology, NorthShore University HealthSystem, University of Chicago, Evanston, IL
| | - Rita K Schmutzler
- Centers for Hereditary Breast and Ovarian Cancer, Integrated Oncology and Molecular Medicine, University Hospital of Cologne, Cologne, Germany Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Payal D Shah
- Department of Medicine, Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | - Jacques Simard
- Laboratoire de génétique médicale, Nancy Université, Centre Hospitalier Régional et Universitaire, Vandoeuvre-les-Nancy, France
| | - Christian F Singer
- Department of Obstetrics and Gynecology and Comprehensive Cancer Center, Medical University of Vienna, Vienna, Austria
| | - Johanna Sokolowska
- Genomics Center, Centre Hospitalier Universitaire de Québec Research Center, Laval University, Québec City, QC, Canada
| | - Dominique Stoppa-Lyonnet
- Department of Tumour Biology, Institut Curie, INSERM U830, Paris, France
- Université Paris Descartes, Paris, France
| | - Christian Sutter
- Institute of Human Genetics, University Hospital Heidelberg, Heidelberg, Germany
| | - Yen Yen Tan
- Centro de Investigación en Red de Enfermedades Raras (CIBERER), Valencia, Spain, Department of Obstetrics and Gynecology, Medical University of Vienna, Vienna, Austria
| | - R Manuel Teixeira
- Department of Genetics, Portuguese Oncology Institute, Porto, Portugal
- Biomedical Sciences Institute (ICBAS), University of Porto, Porto, Portugal
| | - Soo H Teo
- Cancer Research Malaysia, Subang Jaya, Selangor, Malaysia
- Breast Cancer Research Unit, Cancer Research Institute, University Malaya Medical Centre, Kuala Lumpur, Malaysia
| | - Mary Beth Terry
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY
| | - Mads Thomassen
- Department of Clinical Genetics, Odense University Hospital, Odense C, Denmark
| | - Marc Tischkowitz
- Program in Cancer Genetics, Departments of Human Genetics and Oncology, McGill University, Montréal, QC, Canada
- Department of Medical Genetics, Addenbrooke's Hospital, Cambridge, UK
| | - Amanda E Toland
- Department of Cancer Biology and Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH
| | - Katherine M Tucker
- School of Medicine, University of New South Wales, Sydney, New South Wales, Australia
- Hereditary Cancer Centre, Prince of Wales Hospital, Sydney, New South Wales, Australia
| | - Nadine Tung
- Department of Medical Oncology, Beth Israel Deaconess Medical Center, Boston, MA
| | - Christi J van Asperen
- Department of Clinical Genetics, Leiden University Medical Center, Leiden, the Netherlands
| | - Klaartje van Engelen
- Department of Clinical Genetics, Academic Medical Center, Amsterdam, the Netherlands
| | | | - Shan Wang-Gohrke
- Department of Gynaecology and Obstetrics, University of Ulm, Ulm, Germany
| | - Barbara Wappenschmidt
- Centers for Hereditary Breast and Ovarian Cancer, Integrated Oncology and Molecular Medicine, University Hospital of Cologne, Cologne, Germany Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | | | - Drakoulis Yannoukakos
- Molecular Diagnostics Laboratory, INRASTES, National Centre for Scientific Research ‘Demokritos’, Athens, Greece
| | - GEMO Study Collaborators
- Department of Tumour Biology, Institut Curie, INSERM U830, Paris, France
- Université Paris Descartes, Paris, France
| | - HEBON
- The Hereditary Breast and Ovarian Cancer Research Group Netherlands
- Coordinating Center, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - EMBRACE
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Mark H Greene
- Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD
| | - Matti A Rookus
- Department of Epidemiology, Netherlands Cancer Institute, Amsterdam, the Netherlands
| | - Douglas F Easton
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Georgia Chenevix-Trench
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Antonis C Antoniou
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - David E Goldgar
- Department of Dermatology, Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, UT
| | | | - Timothy R Rebbeck
- Harvard T.H. Chan School of Public Health, Boston, MA
- Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA
| | - Dezheng Huo
- Department of Medicine, The University of Chicago, Chicago, IL
- Department of Public Health Sciences, The University of Chicago, Chicago, IL (DH)
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Walton E, Relton CL, Caramaschi D. Using Openly Accessible Resources to Strengthen Causal Inference in Epigenetic Epidemiology of Neurodevelopment and Mental Health. Genes (Basel) 2019; 10:E193. [PMID: 30832291 PMCID: PMC6470715 DOI: 10.3390/genes10030193] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Accepted: 01/25/2019] [Indexed: 12/18/2022] Open
Abstract
The recent focus on the role of epigenetic mechanisms in mental health has led to several studies examining the association of epigenetic processes with psychiatric conditions and neurodevelopmental traits. Some studies suggest that epigenetic changes might be causal in the development of the psychiatric condition under investigation. However, other scenarios are possible, e.g., statistical confounding or reverse causation, making it particularly challenging to derive conclusions on causality. In the present review, we examine the evidence from human population studies for a possible role of epigenetic mechanisms in neurodevelopment and mental health and discuss methodological approaches on how to strengthen causal inference, including the need for replication, (quasi-)experimental approaches and Mendelian randomization. We signpost openly accessible resources (e.g., "MR-Base" "EWAS catalog" as well as tissue-specific methylation and gene expression databases) to aid the application of these approaches.
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Affiliation(s)
- Esther Walton
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, BS8 2BN Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, BS8 2BN Bristol, UK.
- Department of Psychology, University of Bath, BA2 7AY Bath, UK.
| | - Caroline L Relton
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, BS8 2BN Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, BS8 2BN Bristol, UK.
| | - Doretta Caramaschi
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, BS8 2BN Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, BS8 2BN Bristol, UK.
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Gong J, Wang F, Xiao B, Panjwani N, Lin F, Keenan K, Avolio J, Esmaeili M, Zhang L, He G, Soave D, Mastromatteo S, Baskurt Z, Kim S, O’Neal WK, Polineni D, Blackman SM, Corvol H, Cutting GR, Drumm M, Knowles MR, Rommens JM, Sun L, Strug LJ. Genetic association and transcriptome integration identify contributing genes and tissues at cystic fibrosis modifier loci. PLoS Genet 2019; 15:e1008007. [PMID: 30807572 PMCID: PMC6407791 DOI: 10.1371/journal.pgen.1008007] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Revised: 03/08/2019] [Accepted: 02/06/2019] [Indexed: 01/09/2023] Open
Abstract
Cystic Fibrosis (CF) exhibits morbidity in several organs, including progressive lung disease in all patients and intestinal obstruction at birth (meconium ileus) in ~15%. Individuals with the same causal CFTR mutations show variable disease presentation which is partly attributed to modifier genes. With >6,500 participants from the International CF Gene Modifier Consortium, genome-wide association investigation identified a new modifier locus for meconium ileus encompassing ATP12A on chromosome 13 (min p = 3.83x10(-10)); replicated loci encompassing SLC6A14 on chromosome X and SLC26A9 on chromosome 1, (min p<2.2x10(-16), 2.81x10(-11), respectively); and replicated a suggestive locus on chromosome 7 near PRSS1 (min p = 2.55x10(-7)). PRSS1 is exclusively expressed in the exocrine pancreas and was previously associated with non-CF pancreatitis with functional characterization demonstrating impact on PRSS1 gene expression. We thus asked whether the other meconium ileus modifier loci impact gene expression and in which organ. We developed and applied a colocalization framework called the Simple Sum (SS) that integrates regulatory and genetic association information, and also contrasts colocalization evidence across tissues or genes. The associated modifier loci colocalized with expression quantitative trait loci (eQTLs) for ATP12A (p = 3.35x10(-8)), SLC6A14 (p = 1.12x10(-10)) and SLC26A9 (p = 4.48x10(-5)) in the pancreas, even though meconium ileus manifests in the intestine. The meconium ileus susceptibility locus on chromosome X appeared shifted in location from a previously identified locus for CF lung disease severity. Using the SS we integrated the lung disease association locus with eQTLs from nasal epithelia of 63 CF participants and demonstrated evidence of colocalization with airway-specific regulation of SLC6A14 (p = 2.3x10(-4)). Cystic Fibrosis is realizing the promise of personalized medicine, and identification of the contributing organ and understanding of tissue specificity for a gene modifier is essential for the next phase of personalizing therapeutic strategies.
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Affiliation(s)
- Jiafen Gong
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada
| | - Fan Wang
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada
| | - Bowei Xiao
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada
| | - Naim Panjwani
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada
| | - Fan Lin
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada
| | - Katherine Keenan
- Program in Physiology and Experimental Medicine, The Hospital for Sick Children, Toronto, ON, Canada
| | - Julie Avolio
- Program in Translational Medicine, The Hospital for Sick Children, Toronto, ON, Canada
| | - Mohsen Esmaeili
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada
| | - Lin Zhang
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada
| | - Gengming He
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada
- Biostatistics Division, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - David Soave
- Wilfrid Laurier University, Department of Mathematics, Waterloo, Ontario, Canada
- Ontario Institute for Cancer Research, Department of Computational Biology, Toronto, Ontario, Canada
| | - Scott Mastromatteo
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada
| | - Zeynep Baskurt
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada
| | - Sangook Kim
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada
- Biostatistics Division, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Wanda K. O’Neal
- Marsico Lung Institute and Cystic Fibrosis Pulmonary Research and Treatment Center, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Deepika Polineni
- Marsico Lung Institute and Cystic Fibrosis Pulmonary Research and Treatment Center, University of North Carolina, Chapel Hill, North Carolina, United States of America
- Department of Internal Medicine, University of Kansas Medical Centre, Kansas City, Kansas, United States of America
| | - Scott M. Blackman
- Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Harriet Corvol
- Assistance Publique-Hôpitaux de Paris (AP-HP), Hôspital Trousseau, Pediatric Pulmonary Department; Institut National de la Santé et la Recherche Médicale (INSERM) U938, Paris, France
- Sorbonne Universités, Université Pierre et Marie (UPMC) Paris, Paris, France
| | - Garry R. Cutting
- Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Mitchell Drumm
- Department of Pediatrics, Case Western Reserve University, Cleveland, Ohio, United States of America
- Department of Genetics, Case Western Reserve University, Cleveland, Ohio, United States of America
| | - Michael R. Knowles
- Marsico Lung Institute and Cystic Fibrosis Pulmonary Research and Treatment Center, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Johanna M. Rommens
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Lei Sun
- Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada
- Biostatistics Division, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Lisa J. Strug
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, ON, Canada
- Department of Statistical Sciences, University of Toronto, Toronto, ON, Canada
- Biostatistics Division, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
- The Centre for Applied Genomics, The Hospital for Sick Children, Toronto, ON, Canada
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Williams DM, Hägg S, Pedersen NL. Circulating antioxidants and Alzheimer disease prevention: a Mendelian randomization study. Am J Clin Nutr 2019; 109:90-98. [PMID: 30596810 PMCID: PMC6358036 DOI: 10.1093/ajcn/nqy225] [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] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Revised: 06/26/2018] [Accepted: 08/07/2018] [Indexed: 12/15/2022] Open
Abstract
Background Higher circulating antioxidant concentrations are associated with a lower risk of late-onset Alzheimer disease (AD) in observational studies, suggesting that diet-sourced antioxidants may be modifiable targets for reducing disease risk. However, observational evidence is prone to substantial biases that limit causal inference, including residual confounding and reverse causation. Objectives In order to infer whether long-term circulating antioxidant exposure plays a role in AD etiology, we tested the hypothesis that AD risk would be lower in individuals with lifelong, genetically predicted increases in concentrations of 4 circulating antioxidants that are modifiable by diet. Methods Two-sample Mendelian randomization analyses were conducted. First, published genetic association studies were used to identify single-nucleotide polymorphisms (SNPs) that determine variation in circulating ascorbate (vitamin C), β-carotene, retinol (vitamin A), and urate. Second, for each set of SNP data, statistics for genotype associations with AD risk were extracted from data of a genome-wide association study of late-onset AD cases and controls (n = 17,008 and 37,154, respectively). Ratio-of-coefficients and inverse-variance-weighted meta-analyses were the primary methods used to assess the 4 sets of SNP-exposure and SNP-AD associations. Additional analyses assessed the potential impact of bias from pleiotropy on estimates. Results The models suggested that genetically determined differences in circulating ascorbate, retinol, and urate are not associated with differences in AD risk. All estimates were close to the null, with all ORs for AD ≥1 per unit increase in antioxidant exposure (ranging from 1.00 for ascorbate to 1.05 for retinol). There was little evidence to imply that pleiotropy had biased results. Conclusions Our findings suggest that higher exposure to ascorbate, β-carotene, retinol, or urate does not lower the risk of AD. Replication Mendelian randomization studies could assess this further, providing larger AD case-control samples and, ideally, using additional variants to instrument each exposure.
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Affiliation(s)
- Dylan M Williams
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
- Department of Psychology, University of Southern California, Los Angeles, CA
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47
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Teumer A, Gambaro G, Corre T, Bochud M, Vollenweider P, Guessous I, Kleber ME, Delgado GE, Pilz S, März W, Barnes CLK, Joshi PK, Wilson JF, de Borst MH, Navis G, van der Harst P, Heerspink HJL, Homuth G, Endlich K, Nauck M, Köttgen A, Pattaro C, Ferraro PM. Negative effect of vitamin D on kidney function: a Mendelian randomization study. Nephrol Dial Transplant 2018; 33:2139-2145. [PMID: 29718335 PMCID: PMC6275146 DOI: 10.1093/ndt/gfy074] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2017] [Accepted: 02/23/2018] [Indexed: 01/08/2023] Open
Abstract
Background The kidney plays a central role in the regulation of vitamin D metabolism. It is not clear, however, whether vitamin D influences kidney function. Previous studies have reported conflicting results, which may have been influenced by reverse causation and residual confounding. We conducted a Mendelian randomization (MR) study to obtain unconfounded estimates of the association between genetically instrumented vitamin D metabolites and estimated glomerular filtration rate (eGFR) as well as the urinary albumin:creatinine ratio (UACR). Methods We performed a two-sample MR study based on three single nucleotide variants associated with 25(OH)D levels: rs2282679, rs10741657 and rs12785878, related to the genes GC, CYP2R1 and DHCR7, respectively. Estimates of the allele-dependent effects on serum 25(OH)D and eGFR/UACR were obtained from summary statistics of published genome-wide association meta-analyses. Additionally, we performed a one-sample MR analysis for both 25(OH)D and 1,25(OH)2 D using individual-level data from six cohorts. Results The combined MR estimate supported a negative causal effect of log transformed 25(OH)D on log transformed eGFR (β = -0.013, P = 0.003). The analysis of individual-level data confirmed the main findings and also revealed a significant association of 1,25(OH)2 D on eGFR (β = -0.094, P = 0.008). These results show that a 10% increase in serum 25(OH)D levels causes a 0.3% decrease in eGFR. There was no effect of 25(OH)D on UACR (β = 0.032, P = 0.265). Conclusion Our study suggests that circulating vitamin D metabolite levels are negatively associated with eGFR. Further studies are needed to elucidate the underlying mechanisms.
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Affiliation(s)
- Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Giovanni Gambaro
- Divisione di Nefrologia, Fondazione Policlinico Universitario A. Gemelli, Università Cattolica del Sacro Cuore, Rome, Italy
| | - Tanguy Corre
- Institute of Social and Preventive Medicine, Lausanne, Switzerland
- Department of computational biology, University of Lausanne, Lausanne, Switzerland
| | - Murielle Bochud
- Institute of Social and Preventive Medicine, Lausanne, Switzerland
| | | | - Idris Guessous
- Division of Primary Care Medicine, University Hospital of Geneva, Geneva, Switzerland
| | - Marcus E Kleber
- Vth Department of Medicine (Nephrology, Hypertensiology, Endocrinology, Diabetology, Rheumatology), Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Graciela E Delgado
- Vth Department of Medicine (Nephrology, Hypertensiology, Endocrinology, Diabetology, Rheumatology), Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Stefan Pilz
- Department of Internal Medicine, Division of Endocrinology and Diabetology, Medical University of Graz, Graz, Austria
| | - Winfried März
- Synlab Academy, Synlab Holding Deutschland GmbH, Mannheim, Germany
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University Graz, Graz, Austria
| | - Catriona L K Barnes
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, Scotland
| | - Peter K Joshi
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, Scotland
| | - James F Wilson
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, Scotland
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, Scotland
| | - Martin H de Borst
- Department of Internal Medicine, Division of Nephrology, Groningen, The Netherlands
| | - Gerjan Navis
- Department of Internal Medicine, Division of Nephrology, Groningen, The Netherlands
| | - Pim van der Harst
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Hiddo J L Heerspink
- Department of Clinical Pharmacy and Pharmacology, Groningen, The Netherlands
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Karlhans Endlich
- Institute of Anatomy and Cell Biology, University Medicine Greifswald, Greifswald, Germany
| | - Matthias Nauck
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | | | - Pietro Manuel Ferraro
- Divisione di Nefrologia, Fondazione Policlinico Universitario A. Gemelli, Università Cattolica del Sacro Cuore, Rome, Italy
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Wade KH, Carslake D, Sattar N, Davey Smith G, Timpson NJ. BMI and Mortality in UK Biobank: Revised Estimates Using Mendelian Randomization. Obesity (Silver Spring) 2018; 26:1796-1806. [PMID: 30358150 PMCID: PMC6334168 DOI: 10.1002/oby.22313] [Citation(s) in RCA: 54] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2018] [Revised: 07/27/2018] [Accepted: 08/15/2018] [Indexed: 01/07/2023]
Abstract
OBJECTIVE The aim of this study was to obtain estimates of the causal relationship between BMI and mortality. METHODS Mendelian randomization (MR) with BMI-associated genotypic variation was used to test the causal effect of BMI on all-cause and cause-specific mortality in UK Biobank participants of White British ancestry. RESULTS MR analyses supported a causal association between higher BMI and greater risk of all-cause mortality (hazard ratio [HR] per 1 kg/m2 : 1.03; 95% CI: 0.99-1.07) and mortality from cardiovascular diseases (HR: 1.10; 95% CI: 1.01-1.19), specifically coronary heart disease (HR: 1.12; 95% CI: 1.00-1.25) and those excluding coronary heart disease/stroke/aortic aneurysm (HR: 1.24; 95% CI: 1.03-1.48), stomach cancer (HR: 1.18; 95% CI: 0.87-1.62), and esophageal cancer (HR: 1.22; 95% CI: 0.98-1.53), and a decreased risk of lung cancer mortality (HR: 0.96; 95% CI: 0.85-1.08). Sex stratification supported the causal role of higher BMI increasing bladder cancer mortality risk (males) but decreasing respiratory disease mortality risk (males). The J-shaped observational association between BMI and mortality was visible with MR analyses, but the BMI at which mortality was minimized was lower and the association was flatter over a larger BMI range. CONCLUSIONS Results support a causal role of higher BMI in increasing the risk of all-cause mortality and mortality from several specific causes.
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Affiliation(s)
- Kaitlin H. Wade
- MRC Integrative Epidemiology UnitUniversity of BristolBristolUK
- Population Health Sciences, Bristol Medical School, Faculty of Health SciencesUniversity of BristolBristolUK
| | - David Carslake
- MRC Integrative Epidemiology UnitUniversity of BristolBristolUK
- Population Health Sciences, Bristol Medical School, Faculty of Health SciencesUniversity of BristolBristolUK
| | - Naveed Sattar
- Institute of Cardiovascular and Medical Sciences, British Heart Foundation Glasgow Cardiovascular Research CentreUniversity of GlasgowGlasgowUK
| | - George Davey Smith
- MRC Integrative Epidemiology UnitUniversity of BristolBristolUK
- Population Health Sciences, Bristol Medical School, Faculty of Health SciencesUniversity of BristolBristolUK
| | - Nicholas J. Timpson
- MRC Integrative Epidemiology UnitUniversity of BristolBristolUK
- Population Health Sciences, Bristol Medical School, Faculty of Health SciencesUniversity of BristolBristolUK
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Kobylecki CJ, Afzal S, Nordestgaard BG. Genetically high plasma vitamin C and urate: a Mendelian randomization study in 106 147 individuals from the general population. Rheumatology (Oxford) 2018; 57:1769-1776. [PMID: 29939348 DOI: 10.1093/rheumatology/key171] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2017] [Indexed: 11/13/2022] Open
Abstract
Objective Gout is the most common form of inflammatory arthritis and is caused by hyperuricaemia. Some studies have found a reduction in plasma urate with vitamin C supplementation. We tested the hypothesis that high plasma vitamin C is causally associated with low plasma urate and low risk of hyperuricaemia, using a Mendelian randomization approach. Methods We measured plasma urate and genotyped for the SLC23A1 rs33972313 vitamin C variant in 106 147 individuals from the Copenhagen General Population Study, of which 24 099 had hyperuricaemia. We measured plasma vitamin C in 9234 individuals and genotyped for the SLC2A9 rs7442295 urate variant in 102 345 individuals. Results Each 10 µmol/l higher plasma vitamin C was associated with a -2.3(95%CI: -0.69 to -3.9) µmol/l lower plasma urate after multivariable adjustments. The SLC23A1 rs33972313 GG genotype was associated with a 9% (5.6%, 11.9%) higher plasma vitamin C compared with AA and AG combined but was not associated with plasma urate (P = 0.31). Likewise, for each 10 µmol/l higher plasma vitamin C the odds ratios for hyperuricaemia were 0.92 (0.86, 0.98) observationally after multivariable adjustments, but 1.01 (0.84, 1.23) genetically. Conclusion High plasma vitamin C was associated with low plasma urate and with low risk of hyperuricaemia. However, the SLC23A1 genetic variant causing lifelong high plasma vitamin C was not associated with plasma urate levels or with risk of hyperuricaemia. Thus, our data do not support a causal relationship between high plasma vitamin C and low plasma urate.
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Affiliation(s)
- Camilla J Kobylecki
- Department of Clinical Biochemistry and the Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark.,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | - Shoaib Afzal
- Department of Clinical Biochemistry and the Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark.,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | - Børge G Nordestgaard
- Department of Clinical Biochemistry and the Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark.,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
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50
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Lund-Nielsen J, Vedel-Krogh S, Kobylecki CJ, Brynskov J, Afzal S, Nordestgaard BG. Vitamin D and Inflammatory Bowel Disease: Mendelian Randomization Analyses in the Copenhagen Studies and UK Biobank. J Clin Endocrinol Metab 2018; 103:3267-3277. [PMID: 29947775 DOI: 10.1210/jc.2018-00250] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2018] [Accepted: 06/21/2018] [Indexed: 12/14/2022]
Abstract
CONTEXT Vitamin D may be a modifiable risk factor for inflammatory bowel disease (IBD). OBJECTIVES We tested the hypothesis that plasma 25-hydroxyvitamin D levels are causally associated with risk of Crohn disease (CD) and ulcerative colitis (UC). DESIGN, SETTING, PATIENTS, AND INTERVENTIONS We used a Mendelian randomization design to study 120,013 individuals from the Copenhagen City Heart Study, the Copenhagen General Population Study, and a Copenhagen-based cohort of patients with IBD. Of these, 35,558 individuals had plasma 25-hydroxyvitamin D measurements available, and 115,110 were genotyped for rs7944926 and rs11234027 in DHCR7 and rs10741657 and rs12794714 in CYP2R1, all variants associated with plasma 25-hydroxyvitamin D levels. We identified 653 cases of CD and 1265 cases of UC, of which 58 and 113, respectively, had 25-hydroxyvitamin D measurements available. We also included genetic data from 408,455 individuals from the UK Biobank, including 1707 CD cases and 3147 UC cases. MAIN OUTCOME MEASURE Hazard ratios for higher plasma 25-hydroxyvitamin D levels. RESULTS The multivariable-adjusted hazard ratios for 10 nmol/L higher 25-hydroxyvitamin D level were 1.04 (95% CI: 0.93 to 1.16) for CD and 1.13 (95% CI: 1.06 to 1.21) for UC. A combined 25-hydroxyvitamin D allele score was associated with a 1.4-nmol/L increase in plasma 25-hydroxyvitamin D level and hazard ratios of 0.98 (95% CI: 0.94 to 1.03) for CD and 1.01 (95% CI: 0.97 to 1.05) for UC. Combining genetic data from the Copenhagen studies and the UK Biobank, genetically determined vitamin D did not appear to influence the risk of CD or UC. CONCLUSIONS Our results do not support a major role for vitamin D deficiency in the development of IBD.
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Affiliation(s)
- Josephine Lund-Nielsen
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Herlev, Denmark
- The Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Herlev, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Signe Vedel-Krogh
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Herlev, Denmark
- The Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Herlev, Denmark
| | - Camilla Jannie Kobylecki
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Herlev, Denmark
- The Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Herlev, Denmark
| | - Jørn Brynskov
- Department of Gastroenterology, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Herlev, Denmark
| | - Shoaib Afzal
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Herlev, Denmark
- The Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Herlev, Denmark
| | - Børge G Nordestgaard
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Herlev, Denmark
- The Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Copenhagen, Herlev, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Copenhagen City Heart Study, Frederiksberg Hospital, Copenhagen University Hospital, Copenhagen, Denmark
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