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Liu Y, Zhu L, Guo L, Zhao J, Li J, Li W, Li Z, Chen S, Zheng J, Zhao Y. Causal relationship between endometrial cancer and risk of breast cancer: A 2-sample Mendelian randomization study. Medicine (Baltimore) 2024; 103:e38732. [PMID: 38941373 DOI: 10.1097/md.0000000000038732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/30/2024] Open
Abstract
Several studies have confirmed the important role of endometrial cancer (EC) in the development and progression of breast cancer (BC), and this study will explore the causal relationship between EC and BC by 2-sample Mendelian randomization analysis. Pooled data from published genome-wide association studies were used to assess the association between EC and BC risk in women using 5 methods, namely, inverse variance weighting (IVW), MR-Egger, weighted median (WME), simple multimaximetry (SM) and weighted multimaximetry (WM) with the EC-associated genetic loci as the instrumental variables (IV) and sensitivity analyses were used to assess the robustness of the results. The statistical results showed a causal association between EC and BC (IVW: OR = 1.07, 95% CI = 1.01-1.32, P = .02; MR-Egger: OR = 1.21, 95% CI = 0.71-1.51, P = .11; weighted median: OR = 1.05, 95% CI = 0.97-1.31, P = .19; simple plurality method: OR = 0.98, 95% CI = 0.81-1.15, P = .78; weighted plurality method: OR = 0.98, 95% CI = 0.81-1.14, P = .75), and the results of the sensitivity analyses showed that there was no significant heterogeneity or multiplicity, and the results were stable. EC is associated with an increased risk of developing BC. The results of this MR analysis can be used as a guideline for screening for BC in women with EC and to help raise awareness of screening for early detection and treatment.
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Affiliation(s)
- Ye Liu
- Affiliated Hospital of North China University of Science and Technology, Breast Disease Treatment Center, Tangshan, Hebei, China
| | - Lichao Zhu
- Affiliated Hospital of North China University of Science and Technology, Breast Disease Treatment Center, Tangshan, Hebei, China
| | - Lei Guo
- Affiliated Hospital of North China University of Science and Technology, Breast Disease Treatment Center, Tangshan, Hebei, China
| | - Jianhai Zhao
- Affiliated Hospital of North China University of Science and Technology, Breast Disease Treatment Center, Tangshan, Hebei, China
| | - Jiang Li
- Tangshan Maternal and Child Health Centre, General Surgery, Tangshan, Hebei, China
| | - Wenying Li
- Affiliated Hospital of North China University of Science and Technology, Breast Disease Treatment Center, Tangshan, Hebei, China
| | - Ziyun Li
- Affiliated Hospital of North China University of Science and Technology, Breast Disease Treatment Center, Tangshan, Hebei, China
| | - Shuai Chen
- Affiliated Hospital of North China University of Science and Technology, General Surgery, Hebei, China
| | - Jiapeng Zheng
- Affiliated Hospital of North China University of Science and Technology, General Surgery, Hebei, China
| | - Yating Zhao
- Affiliated Hospital of North China University of Science and Technology, Breast Disease Treatment Center, Tangshan, Hebei, China
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Rosoff DB, Hamandi AM, Bell AS, Mavromatis LA, Park LM, Jung J, Wagner J, Lohoff FW. Major Psychiatric Disorders, Substance Use Behaviors, and Longevity. JAMA Psychiatry 2024:2820199. [PMID: 38888899 PMCID: PMC11195603 DOI: 10.1001/jamapsychiatry.2024.1429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 04/04/2024] [Indexed: 06/20/2024]
Abstract
Importance Observational studies suggest that major psychiatric disorders and substance use behaviors reduce longevity, making it difficult to disentangle their relationships with aging-related outcomes. Objective To evaluate the associations between the genetic liabilities for major psychiatric disorders, substance use behaviors (smoking and alcohol consumption), and longevity. Design, Settings, and Participants This 2-sample mendelian randomization (MR) study assessed associations between psychiatric disorders, substance use behaviors, and longevity using single-variable and multivariable models. Multiomics analyses were performed elucidating transcriptomic underpinnings of the MR associations and identifying potential proteomic therapeutic targets. This study sourced summary-level genome-wide association study (GWAS) data, gene expression, and proteomic data from cohorts of European ancestry. Analyses were performed from May 2022 to November 2023. Exposures Genetic susceptibility for major depression (n = 500 199), bipolar disorder (n = 413 466), schizophrenia (n = 127 906), problematic alcohol use (n = 435 563), weekly alcohol consumption (n = 666 978), and lifetime smoking index (n = 462 690). Main Outcomes and Measures The main outcome encompassed aspects of health span, lifespan, and exceptional longevity. Additional outcomes were epigenetic age acceleration (EAA) clocks. Results Findings from multivariable MR models simultaneously assessing psychiatric disorders and substance use behaviorsm suggest a negative association between smoking and longevity in cohorts of European ancestry (n = 709 709; 431 503 [60.8%] female; β, -0.33; 95% CI, -0.38 to -0.28; P = 4.59 × 10-34) and with increased EAA (n = 34 449; 18 017 [52.3%] female; eg, PhenoAge: β, 1.76; 95% CI, 0.72 to 2.79; P = 8.83 × 10-4). Transcriptomic imputation and colocalization identified 249 genes associated with smoking, including 36 novel genes not captured by the original smoking GWAS. Enriched pathways included chromatin remodeling and telomere assembly and maintenance. The transcriptome-wide signature of smoking was inversely associated with longevity, and estimates of individual smoking-associated genes, eg, XRCC3 and PRMT6, aligned with the smoking-longevity MR analyses, suggesting underlying transcriptomic mediators. Cis-instrument MR prioritized brain proteins associated with smoking behavior, including LY6H (β, 0.02; 95% CI, 0.01 to 0.03; P = 2.37 × 10-6) and RIT2 (β, 0.02; 95% CI, 0.01 to 0.03; P = 1.05 × 10-5), which had favorable adverse-effect profiles across 367 traits evaluated in phenome-wide MR. Conclusions The findings suggest that the genetic liability of smoking, but not of psychiatric disorders, is associated with longevity. Transcriptomic associations offer insights into smoking-related pathways, and identified proteomic targets may inform therapeutic development for smoking cessation strategies.
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Affiliation(s)
- Daniel B. Rosoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland
- Radcliffe Department of Medicine, NIH-Oxford-Cambridge Scholars Program, University of Oxford, United Kingdom
| | - Ali M. Hamandi
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland
| | - Andrew S. Bell
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland
| | - Lucas A. Mavromatis
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland
| | - Lauren M. Park
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland
| | - Jeesun Jung
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland
| | - Josephin Wagner
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland
| | - Falk W. Lohoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, Maryland
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Bann D, Wright L, Hughes A, Chaturvedi N. Socioeconomic inequalities in cardiovascular disease: a causal perspective. Nat Rev Cardiol 2024; 21:238-249. [PMID: 37821646 DOI: 10.1038/s41569-023-00941-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/13/2023] [Indexed: 10/13/2023]
Abstract
Socioeconomic inequalities in cardiovascular disease (CVD) persist in high-income countries despite marked overall declines in CVD-related morbidity and mortality. After decades of research, the field has struggled to unequivocally answer a crucial question: is the association between low socioeconomic position (SEP) and the development of CVD causal? We review relevant evidence from various study designs and disciplinary perspectives. Traditional observational, family-based and Mendelian randomization studies support the widely accepted view that low SEP causally influences CVD. However, results from quasi-experimental and experimental studies are both limited and equivocal. While more experimental and quasi-experimental studies are needed to aid causal understanding and inform policy, high-quality descriptive studies are also required to document inequalities, investigate their contextual dependence and consider SEP throughout the lifespan; no simple hierarchy of evidence exists for an exposure as complex as SEP. The COVID-19 pandemic illustrates the context-dependent nature of CVD inequalities, with the generation of potentially new causal pathways linking SEP and CVD. The linked goals of understanding the causal nature of SEP and CVD associations, their contextual dependence, and their remediation by policy interventions necessitate a detailed understanding of society, its change over time and the phenotypes of CVD. Interdisciplinary research is therefore key to advancing both causal understanding and policy translation.
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Affiliation(s)
- David Bann
- Centre for Longitudinal Studies, Social Research Institute, IOE, UCL's Faculty of Education and Society, University College London, London, UK.
| | - Liam Wright
- Centre for Longitudinal Studies, Social Research Institute, IOE, UCL's Faculty of Education and Society, University College London, London, UK
| | - Alun Hughes
- MRC Unit for Lifelong Health & Ageing at UCL, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Science, University College London, London, UK
| | - Nish Chaturvedi
- MRC Unit for Lifelong Health & Ageing at UCL, Department of Population Science and Experimental Medicine, Institute of Cardiovascular Science, Faculty of Population Health Science, University College London, London, UK
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Park JK, Petrazzini BO, Bafna S, Duffy Á, Forrest IS, Vy HM, Marquez-Luna C, Verbanck M, Narula J, Rosenson RS, Jordan DM, Rocheleau G, Do R. Muesli Intake May Protect Against Coronary Artery Disease: Mendelian Randomization on 13 Dietary Traits. JACC. ADVANCES 2024; 3:100888. [PMID: 38737007 PMCID: PMC11087059 DOI: 10.1016/j.jacadv.2024.100888] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 12/12/2023] [Indexed: 05/14/2024]
Abstract
BACKGROUND Diet is a key modifiable risk factor of coronary artery disease (CAD). However, the causal effects of specific dietary traits on CAD risk remain unclear. With the expansion of dietary data in population biobanks, Mendelian randomization (MR) could help enable the efficient estimation of causality in diet-disease associations. OBJECTIVES The primary goal was to test causality for 13 common dietary traits on CAD risk using a systematic 2-sample MR framework. A secondary goal was to identify plasma metabolites mediating diet-CAD associations suspected to be causal. METHODS Cross-sectional genetic and dietary data on up to 420,531 UK Biobank and 184,305 CARDIoGRAMplusC4D individuals of European ancestry were used in 2-sample MR. The primary analysis used fixed effect inverse-variance weighted regression, while sensitivity analyses used weighted median estimation, MR-Egger regression, and MR-Pleiotropy Residual Sum and Outlier. RESULTS Genetic variants serving as proxies for muesli intake were negatively associated with CAD risk (OR: 0.74; 95% CI: 0.65-0.84; P = 5.385 × 10-4). Sensitivity analyses using weighted median estimation supported this with a significant association in the same direction. Additionally, we identified higher plasma acetate levels as a potential mediator (OR: 0.03; 95% CI: 0.01-0.12; P = 1.15 × 10-4). CONCLUSIONS Muesli, a mixture of oats, seeds, nuts, dried fruit, and milk, may causally reduce CAD risk. Circulating levels of acetate, a gut microbiota-derived short-chain fatty acid, could be mediating its cardioprotective effects. These findings highlight the role of gut flora in cardiovascular health and help prioritize randomized trials on dietary interventions for CAD.
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Affiliation(s)
- Joshua K. Park
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Medical Scientist Training Program, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Ben Omega Petrazzini
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Shantanu Bafna
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Áine Duffy
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Iain S. Forrest
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Medical Scientist Training Program, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Ha My Vy
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Carla Marquez-Luna
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | | | - Jagat Narula
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Cardiovascular Imaging Program, Zena and Michael A. Wiener Cardiovascular Institute, Mount Sinai Heart, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Robert S. Rosenson
- Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Metabolism and Lipids Unit, Zena and Michael A. Wiener Cardiovascular Institute, Mount Sinai Heart, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Daniel M. Jordan
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Ghislain Rocheleau
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Ron Do
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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5
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Papadimitriou N, Qu C, Harrison TA, Bever AM, Martin RM, Tsilidis KK, Newcomb PA, Thibodeau SN, Newton CC, Um CY, Obón-Santacana M, Moreno V, Brenner H, Mandic M, Chang-Claude J, Hoffmeister M, Pellatt AJ, Schoen RE, Harlid S, Ogino S, Ugai T, Buchanan DD, Lynch BM, Gruber SB, Cao Y, Hsu L, Huyghe JR, Lin Y, Steinfelder RS, Sun W, Van Guelpen B, Zaidi SH, Toland AE, Berndt SI, Huang WY, Aglago EK, Drew DA, French AJ, Georgeson P, Giannakis M, Hullar M, Nowak JA, Thomas CE, Le Marchand L, Cheng I, Gallinger S, Jenkins MA, Gunter MJ, Campbell PT, Peters U, Song M, Phipps AI, Murphy N. Body size and risk of colorectal cancer molecular defined subtypes and pathways: Mendelian randomization analyses. EBioMedicine 2024; 101:105010. [PMID: 38350331 PMCID: PMC10874711 DOI: 10.1016/j.ebiom.2024.105010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 01/25/2024] [Accepted: 01/30/2024] [Indexed: 02/15/2024] Open
Abstract
BACKGROUND Obesity has been positively associated with most molecular subtypes of colorectal cancer (CRC); however, the magnitude and the causality of these associations is uncertain. METHODS We used Mendelian randomization (MR) to examine potential causal relationships between body size traits (body mass index [BMI], waist circumference, and body fat percentage) with risks of Jass classification types and individual subtypes of CRC (microsatellite instability [MSI] status, CpG island methylator phenotype [CIMP] status, BRAF and KRAS mutations). Summary data on tumour markers were obtained from two genetic consortia (CCFR, GECCO). FINDINGS A 1-standard deviation (SD:5.1 kg/m2) increment in BMI levels was found to increase risks of Jass type 1MSI-high,CIMP-high,BRAF-mutated,KRAS-wildtype (odds ratio [OR]: 2.14, 95% confidence interval [CI]: 1.46, 3.13; p-value = 9 × 10-5) and Jass type 2non-MSI-high,CIMP-high,BRAF-mutated,KRAS-wildtype CRC (OR: 2.20, 95% CI: 1.26, 3.86; p-value = 0.005). The magnitude of these associations was stronger compared with Jass type 4non-MSI-high,CIMP-low/negative,BRAF-wildtype,KRAS-wildtype CRC (p-differences: 0.03 and 0.04, respectively). A 1-SD (SD:13.4 cm) increment in waist circumference increased risk of Jass type 3non-MSI-high,CIMP-low/negative,BRAF-wildtype,KRAS-mutated (OR 1.73, 95% CI: 1.34, 2.25; p-value = 9 × 10-5) that was stronger compared with Jass type 4 CRC (p-difference: 0.03). A higher body fat percentage (SD:8.5%) increased risk of Jass type 1 CRC (OR: 2.59, 95% CI: 1.49, 4.48; p-value = 0.001), which was greater than Jass type 4 CRC (p-difference: 0.03). INTERPRETATION Body size was more strongly linked to the serrated (Jass types 1 and 2) and alternate (Jass type 3) pathways of colorectal carcinogenesis in comparison to the traditional pathway (Jass type 4). FUNDING Cancer Research UK, National Institute for Health Research, Medical Research Council, National Institutes of Health, National Cancer Institute, American Institute for Cancer Research, Brigham and Women's Hospital, Prevent Cancer Foundation, Victorian Cancer Agency, Swedish Research Council, Swedish Cancer Society, Region Västerbotten, Knut and Alice Wallenberg Foundation, Lion's Cancer Research Foundation, Insamlingsstiftelsen, Umeå University. Full funding details are provided in acknowledgements.
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Affiliation(s)
- Nikos Papadimitriou
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France.
| | - Conghui Qu
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Tabitha A Harrison
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Alaina M Bever
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School, Boston, MA, USA
| | - Richard M Martin
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; Bristol Medical School, Department of Population Health Sciences, University of Bristol, Bristol, UK; National Institute for Health Research (NIHR) Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol, Bristol, UK
| | - Konstantinos K Tsilidis
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Polly A Newcomb
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA; School of Public Health, University of Washington, Seattle, WA, USA
| | - Stephen N Thibodeau
- Division of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Christina C Newton
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | - Caroline Y Um
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | - Mireia Obón-Santacana
- Unit of Biomarkers and Suceptibility (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L'Hospitalet del Llobregat, Barcelona 08908, Spain; ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona 08908, Spain; Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid 28029, Spain
| | - Victor Moreno
- Unit of Biomarkers and Suceptibility (UBS), Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology (ICO), L'Hospitalet del Llobregat, Barcelona 08908, Spain; ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona 08908, Spain; Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid 28029, Spain; Department of Clinical Sciences, Faculty of Medicine and Health Sciences and Universitat de Barcelona Institute of Complex Systems (UBICS), University of Barcelona (UB), L'Hospitalet de Llobregat, Barcelona 08908, Spain
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany; Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany; German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Marko Mandic
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany; Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany; University Medical Centre Hamburg-Eppendorf, University Cancer Centre Hamburg (UCCH), Hamburg, Germany
| | - Michael Hoffmeister
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Andrew J Pellatt
- Division of Cancer Medicine, MD Anderson Cancer Center, Houston, TX, USA
| | - Robert E Schoen
- Department of Medicine and Epidemiology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Sophia Harlid
- Department of Radiation Sciences, Oncology Unit, Umeå University, Umeå, Sweden
| | - Shuji Ogino
- Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Cancer Immunology Program, Dana-Farber Harvard Cancer Center, Boston, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Tomotaka Ugai
- Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Daniel D Buchanan
- Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria 3010, Australia; University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Victoria 3010, Australia; Genetic Medicine and Family Cancer Clinic, The Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Brigid M Lynch
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia
| | - Stephen B Gruber
- Department of Medical Oncology & Therapeutics Research, City of Hope National Medical Center, Duarte, CA, USA
| | - Yin Cao
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, MO, USA; Alvin J. Siteman Cancer Center at Barnes-Jewish Hospital and Washington University School of Medicine, St. Louis, MO, USA; Division of Gastroenterology, Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA
| | - Li Hsu
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA; Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Jeroen R Huyghe
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Yi Lin
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Robert S Steinfelder
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Wei Sun
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Bethany Van Guelpen
- Department of Radiation Sciences, Oncology Unit, Umeå University, Umeå, Sweden; Wallenberg Centre for Molecular Medicine, Umeå University, Umeå, Sweden
| | - Syed H Zaidi
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
| | - Amanda E Toland
- Departments of Cancer Biology and Genetics and Internal Medicine, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA
| | - Sonja I Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Wen-Yi Huang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Elom K Aglago
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - David A Drew
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Amy J French
- Division of Laboratory Genetics, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Peter Georgeson
- Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria 3010, Australia; University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, Victoria 3010, Australia
| | - Marios Giannakis
- Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Meredith Hullar
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Johnathan A Nowak
- Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Claire E Thomas
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | | | - Iona Cheng
- Department of Epidemiology and Biostatistics, University of California-San Francisco, San Francisco, CA, USA
| | - Steven Gallinger
- Lunenfeld Tanenbaum Research Institute, Mount Sinai Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Mark A Jenkins
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia
| | - Marc J Gunter
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Peter T Campbell
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Ulrike Peters
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA; Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Mingyang Song
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Amanda I Phipps
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA; Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Neil Murphy
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France
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6
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Papadimitriou N, Kazmi N, Dimou N, Tsilidis KK, Martin RM, Lewis SJ, Lynch BM, Hoffmeister M, Kweon S, Li L, Milne RL, Sakoda LC, Schoen RE, Phipps AI, Figueiredo JC, Peters U, Dixon‐Suen SC, Gunter MJ, Murphy N. Leisure time television watching, computer use and risks of breast, colorectal and prostate cancer: A Mendelian randomisation analysis. Cancer Med 2023; 13:e6732. [PMID: 38155458 PMCID: PMC10807615 DOI: 10.1002/cam4.6732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 10/05/2023] [Accepted: 11/07/2023] [Indexed: 12/30/2023] Open
Abstract
BACKGROUND Sedentary behaviours have been associated with increased risks of some common cancers in epidemiological studies; however, it is unclear if these associations are causal. METHODS We used univariable and multivariable two-sample Mendelian randomisation (MR) to examine potential causal relationships between sedentary behaviours and risks of breast, colorectal and prostate cancer. Genetic variants associated with self-reported leisure television watching and computer use were identified from a recent genome-wide association study (GWAS). Data related to cancer risk were obtained from cancer GWAS consortia. A series of sensitivity analyses were applied to examine the robustness of the results to the presence of confounding. RESULTS A 1-standard deviation (SD: 1.5 h/day) increment in hours of television watching increased risk of breast cancer (OR per 1-SD: 1.15, 95% confidence interval [CI]: 1.05-1.26) and colorectal cancer (OR per 1-SD: 1.32, 95% CI: 1.16-1.49) while there was little evidence of an association for prostate cancer risk (OR per 1-SD: 0.94, 95% CI: 0.84-1.06). After adjusting for years of education, the effect estimates for television watching were attenuated (breast cancer, OR per 1-SD: 1.08, 95% CI: 0.92-1.27; colorectal cancer, OR per 1-SD: 1.08, 95% CI: 0.90-1.31). Post hoc analyses showed that years of education might have a possible confounding and mediating role in the association between television watching with breast and colorectal cancer. Consistent results were observed for each cancer site according to sex (colorectal cancer), anatomical subsites and cancer subtypes. There was little evidence of associations between genetically predicted computer use and cancer risk. CONCLUSIONS Our univariable analysis identified some positive associations between hours of television watching and risks of breast and colorectal cancer. However, further adjustment for additional lifestyle factors especially years of education attenuated these results. Future studies using objective measures of exposure can provide new insights into the possible role of sedentary behaviour in cancer development.
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Affiliation(s)
- Nikos Papadimitriou
- Nutrition and Metabolism BranchInternational Agency for Research on CancerLyonFrance
| | - Nabila Kazmi
- MRC Integrative Epidemiology Unit (IEU)Population Health Sciences, Bristol Medical School, University of BristolBristolUK
| | - Niki Dimou
- Nutrition and Metabolism BranchInternational Agency for Research on CancerLyonFrance
| | - Konstantinos K. Tsilidis
- Department of Hygiene and EpidemiologyUniversity of Ioannina School of MedicineIoanninaGreece
- Department of Epidemiology and BiostatisticsSchool of Public Health, Imperial College LondonLondonUK
| | - Richard M. Martin
- MRC Integrative Epidemiology Unit (IEU)Population Health Sciences, Bristol Medical School, University of BristolBristolUK
- Department of Population Health SciencesBristol Medical School, University of BristolBristolUK
- National Institute for Health Research (NIHR) Bristol Biomedical Research CentreUniversity Hospitals Bristol, Weston NHS Foundation Trust, University of BristolBristolUK
| | - Sarah J. Lewis
- Department of Population Health SciencesBristol Medical School, University of BristolBristolUK
| | - Brigid M. Lynch
- Cancer Epidemiology DivisionCancer Council VictoriaMelbourneVictoriaAustralia
- Centre for Epidemiology and BiostatisticsMelbourne School of Population and Global Health, The University of MelbourneMelbourneVictoriaAustralia
- Physical Activity LaboratoryBaker Heart and Diabetes InstituteMelbourneVictoriaAustralia
| | - Michael Hoffmeister
- Division of Clinical Epidemiology and Aging ResearchGerman Cancer Research Center (DKFZ)HeidelbergGermany
| | - Sun‐Seog Kweon
- Department of Preventive MedicineChonnam National University Medical SchoolGwangjuKorea
- Jeonnam Regional Cancer CenterChonnam National University Hwasun HospitalGwangjuKorea
| | - Li Li
- Department of Family MedicineUniversity of VirginiaCharlottesvilleVirginiaUSA
| | - Roger L. Milne
- Cancer Epidemiology DivisionCancer Council VictoriaMelbourneVictoriaAustralia
- Centre for Epidemiology and BiostatisticsMelbourne School of Population and Global Health, The University of MelbourneMelbourneVictoriaAustralia
- Precision MedicineSchool of Clinical Sciences at Monash Health, Monash UniversityClaytonVictoriaAustralia
| | - Lori C. Sakoda
- Division of ResearchKaiser Permanente Northern CaliforniaOaklandCaliforniaUSA
- Public Health Sciences DivisionFred Hutchinson Cancer CenterSeattleWashingtonUSA
| | - Robert E. Schoen
- Department of Medicine and EpidemiologyUniversity of Pittsburgh Medical CenterPittsburghPennsylvaniaUSA
| | - Amanda I. Phipps
- Public Health Sciences DivisionFred Hutchinson Cancer CenterSeattleWashingtonUSA
- Department of EpidemiologyUniversity of WashingtonSeattleWashingtonUSA
| | - Jane C. Figueiredo
- Department of MedicineSamuel Oschin Comprehensive Cancer Institute, Cedars‐Sinai Medical CenterLos AngelesCaliforniaUSA
- Department of Preventive MedicineKeck School of Medicine, University of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Ulrike Peters
- Public Health Sciences DivisionFred Hutchinson Cancer CenterSeattleWashingtonUSA
- Department of EpidemiologyUniversity of WashingtonSeattleWashingtonUSA
| | - Suzanne C. Dixon‐Suen
- Cancer Epidemiology DivisionCancer Council VictoriaMelbourneVictoriaAustralia
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin UniversityGeelongVictoriaAustralia
| | - Marc J. Gunter
- Nutrition and Metabolism BranchInternational Agency for Research on CancerLyonFrance
- Department of Epidemiology and BiostatisticsSchool of Public Health, Imperial College LondonLondonUK
| | - Neil Murphy
- Nutrition and Metabolism BranchInternational Agency for Research on CancerLyonFrance
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7
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Davies NM, Dickson M, Davey Smith G, Windmeijer F, van den Berg GJ. The causal effects of education on adult health, mortality and income: evidence from Mendelian randomization and the raising of the school leaving age. Int J Epidemiol 2023; 52:1878-1886. [PMID: 37463867 PMCID: PMC10749779 DOI: 10.1093/ije/dyad104] [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: 09/05/2022] [Accepted: 07/04/2023] [Indexed: 07/20/2023] Open
Abstract
BACKGROUND On average, educated people are healthier, wealthier and have higher life expectancy than those with less education. Numerous studies have attempted to determine whether education causes differences in later health outcomes or whether another factor ultimately causes differences in education and subsequent outcomes. Previous studies have used a range of natural experiments to provide causal evidence. Here we compare two natural experiments: a policy reform, raising the school leaving age in the UK in 1972; and Mendelian randomization. METHODS We used data from 334 974 participants of the UK Biobank, sampled between 2006 and 2010. We estimated the effect of an additional year of education on 25 outcomes, including mortality, measures of morbidity and health, ageing and income, using multivariable adjustment, the policy reform and Mendelian randomization. We used a range of sensitivity analyses and specification tests to assess the plausibility of each method's assumptions. RESULTS The three different estimates of the effects of educational attainment were largely consistent in direction for diabetes, stroke and heart attack, mortality, smoking, income, grip strength, height, body mass index (BMI), intelligence, alcohol consumption and sedentary behaviour. However, there was evidence that education reduced rates of moderate exercise and increased alcohol consumption. Our sensitivity analyses suggest that confounding by genotypic or phenotypic confounders or specific forms of pleiotropy are unlikely to explain our results. CONCLUSIONS Previous studies have suggested that the differences in outcomes associated with education may be due to confounding. However, the two independent sources of exogenous variation we exploit largely imply consistent causal effects of education on outcomes later in life.
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Affiliation(s)
- Neil M Davies
- Division of Psychiatry, University College London, London, UK
- Department of Statistical Sciences, University College London, London, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Tronheim, Norway
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Matt Dickson
- Institute for Policy Research, University of Bath, Bath, UK
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Frank Windmeijer
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Department of Statistics and Nuffield College, University of Oxford, Oxford, UK
| | - Gerard J van den Berg
- Department of Economics, University of Groningen, Groningen, The Netherlands
- Department of Epidemiology, University Medical Center Groningen, Groningen, The Netherlands
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8
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Hujoel PP. Confounding by Smoking May Drive Spurious Associations Between Intermittent Fasting and Mortality. J Acad Nutr Diet 2023; 123:1406-1407. [PMID: 37244592 DOI: 10.1016/j.jand.2023.05.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 02/24/2023] [Accepted: 05/22/2023] [Indexed: 05/29/2023]
Affiliation(s)
- Philippe P Hujoel
- Department of Epidemiology, School of Public Health, and Department of Oral Health Sciences, School of Dentistry, University of Washington, Seattle, WA
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9
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Hujoel P. Yet another cautionary tale? Br Dent J 2023; 234:782. [PMID: 37291285 DOI: 10.1038/s41415-023-5951-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 05/03/2023] [Indexed: 06/10/2023]
Affiliation(s)
- P Hujoel
- University of Washington, Seattle, USA.
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10
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Adebisi YA. Decolonizing Epidemiological Research: A Critical Perspective. Avicenna J Med 2023; 13:68-76. [PMID: 37435557 PMCID: PMC10332938 DOI: 10.1055/s-0043-1769088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/13/2023] Open
Abstract
Decolonizing epidemiological research is a crucial endeavor. Historically, colonial and imperialistic ideologies have pervaded epidemiology, leading to an emphasis on Western perspectives and the neglect of indigenous and other marginalized communities' needs and experiences. To effectively address health disparities and promote justice and equality, acknowledging and addressing these power imbalances are imperative. In this article, I highlight the need of decolonizing epidemiological research and make recommendations. These include increasing the representation of researchers from underrepresented communities, ensuring that epidemiological research is contextually relevant and responsive to the experiences of these communities, and collaborating with policymakers and advocacy groups to inform policies and practices that benefit all populations. Moreover, I underscore the importance of recognizing and valuing the knowledge and skills of marginalized populations, and integrating traditional knowledge-the distinct, culturally specific understanding unique to a particular group-into research efforts. I also emphasize the need of capacity building and equitable research collaborations and authorship as well as epidemiological journal editorship. Decolonizing epidemiology research is a continual process that requires continuing discourse, collaboration, and education.
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Papadimitriou N, Kazmi N, Dimou N, Tsilidis KK, Martin RM, Lewis SJ, Lynch BM, Hoffmeister M, Kweon SS, Li L, Milne RL, Sakoda LC, Schoen RE, Phipps AI, Figueiredo JC, Peters U, Dixon-Suen SC, Gunter MJ, Murphy N. Leisure time sedentary behaviour and risks of breast, colorectal, and prostate cancer: A Mendelian randomization analysis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.03.01.23286492. [PMID: 36993622 PMCID: PMC10055454 DOI: 10.1101/2023.03.01.23286492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Sedentary behaviours have been associated with increased risks of some common cancers in epidemiological studies; however, it is unclear if these associations are causal. We examined potential causal associations between self-reported leisure television watching and computer use and risks of breast, colorectal, and prostate cancer using a two-sample Mendelian randomization framework. Genetic variants were identified from a recent genome-wide association study (GWAS). Cancer data were obtained from cancer GWAS consortia. Additional sensitivity analyses were applied to examine the robustness of the results. A 1-standard deviation increment in hours of television watching increased risk of breast (OR: 1.15, 95% confidence interval [CI]: 1.05,1.26) and colorectal cancer (OR: 1.32, 95%CI: 1.16,1.49) with little evidence of an association for prostate cancer risk. In multivariable models adjusted for years of education, the effect estimates for television watching were attenuated (breast cancer, OR: 1.08, 95%CI: 0.92,1.27; colorectal cancer, OR: 1.08, 95%CI: 0.90,1.31). Post-hoc analyses showed that years of education might have a possible confounding and mediating role in the association between television watching with breast and colorectal cancer. Consistent results were observed by sex (colorectal cancer), anatomical subsites, and cancer subtypes. There was little evidence of associations between computer use and cancer risk. We found evidence of positive associations between hours of television watching and risks of breast and colorectal cancer. However, these findings should be interpreted cautiously given the complex role of education. Future studies using objective measures of exposure can provide new insights into the possible role of sedentary behaviour in cancer development. Novelty and impact Evidence from observational studies that examined associations between sedentary behaviours and common cancers is mixed and causality is uncertain. In our Mendelian randomization analyses, higher levels of leisure television watching were found to increase the risks of breast and colorectal cancer, suggesting that the that the promotion of lowering sedentary behaviour time could be an effective strategy in the primary prevention of these commonly diagnosed cancers. Article category Cancer Epidemiology.
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12
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Gleadhill C, Lee H, Kamper SJ, Cashin A, Hansford H, Traeger AC, Viana Da Silva P, Nolan E, Davidson SRE, Wilczynska M, Robson E, Williams CM. Mixed messages: most spinal pain and osteoarthritis observational research is unclear or misaligned. J Clin Epidemiol 2023; 155:39-47. [PMID: 36736708 DOI: 10.1016/j.jclinepi.2023.01.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 12/17/2022] [Accepted: 01/19/2023] [Indexed: 02/05/2023]
Abstract
OBJECTIVES We assessed authors' language and methods to determine alignment between reported aims, methods, intent, and interpretations in observational studies in spinal pain or osteoarthritis. STUDY DESIGN AND SETTING We searched five databases for observational studies that included people with spinal pain or osteoarthritis published in the last 5 years. We randomized 100 eligible studies, and classified study intent (aims and methods) and interpretations as causal, non-causal, unclear, or misaligned. RESULTS Overall, 38% of studies were aligned regarding their intent and interpretation (either causally (22%) or non-causally (16%)). 29% of studies' aims and 29% of study methods were unclear. Intent was misaligned in 16% of studies (where aim differed to method) and 23% of studies had misaligned interpretations (where there were multiple conflicting claims). The most common kind of aim was non-causal (38%), and the most common type of method (39%), intent (38%), and interpretations (35%) was causal. CONCLUSIONS Misalignment and mixed messages are common in observational research of spinal pain and osteoarthritis. More than 6 in 10 observational studies may be uninterpretable, because study intent and interpretations do not align. While causal methods and intent are most common in observational research, authors commonly shroud causal intent in non-causal terminology.
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Affiliation(s)
- Connor Gleadhill
- School of Medicine and Public Health, University of Newcastle, Callaghan, NSW, 2308, Australia; Hunter New England Population Health, Hunter New England Local Health District, Wallsend, NSW, 2287, Australia.
| | - Hopin Lee
- Centre for Statistics in Medicine, Rehabilitation Research in Oxford, Nuffield Department of Orthopaedics Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Steven J Kamper
- School of Health Sciences, University of Sydney, PO Box M179, Camperdown, NSW, 2050, Australia; Allied Health Department, Nepean Blue Mountains Local Health District, Nepean Hospital, Penrith, NSW, 2750, Australia
| | - Aidan Cashin
- Centre for Pain IMPACT, Neuroscience Research Australia, Sydney, Australia; School of Health Sciences, Faculty of Medicine & Health, University of New South Wales, Sydney, Australia
| | - Harrison Hansford
- Centre for Pain IMPACT, Neuroscience Research Australia, Sydney, Australia; School of Health Sciences, Faculty of Medicine & Health, University of New South Wales, Sydney, Australia
| | - Adrian C Traeger
- Faculty of Medicine and Health, Institute for Musculoskeletal Health, Sydney School of Public Health, The University of Sydney, King George V Building, Camperdown, NSW, 2050, Australia
| | - Priscilla Viana Da Silva
- School of Medicine and Public Health, University of Newcastle, Callaghan, NSW, 2308, Australia; Hunter New England Population Health, Hunter New England Local Health District, Wallsend, NSW, 2287, Australia
| | - Erin Nolan
- School of Medicine and Public Health, University of Newcastle, Callaghan, NSW, 2308, Australia; Hunter Medical Research Institute, New Lambton Heights, NSW, 2305, Australia
| | - Simon R E Davidson
- School of Medicine and Public Health, University of Newcastle, Callaghan, NSW, 2308, Australia; Hunter New England Population Health, Hunter New England Local Health District, Wallsend, NSW, 2287, Australia
| | - Magdalena Wilczynska
- School of Medicine and Public Health, University of Newcastle, Callaghan, NSW, 2308, Australia; Hunter New England Population Health, Hunter New England Local Health District, Wallsend, NSW, 2287, Australia
| | - Emma Robson
- School of Medicine and Public Health, University of Newcastle, Callaghan, NSW, 2308, Australia; Hunter New England Population Health, Hunter New England Local Health District, Wallsend, NSW, 2287, Australia
| | - Christopher M Williams
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, NSW, 2287, Australia; School of Health Sciences, University of Sydney, PO Box M179, Camperdown, NSW, 2050, Australia; Research and Knowledge Translation Directorate, Mid North Coast Local Health District, Port Macquarie, Australia
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13
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Abstract
A Nutrition Society member-led meeting was held online on 18th January 2021 to discuss the role of observational studies in developing public health policy and dietary guidelines. In addition, participants debated media reporting of observational studies and the implications for public perception and trust in science. Speakers outlined the benefits of observational studies and how they fit within the suite of research tools available for estimating dietary intakes and determining their impact on health and disease risk. However, there are clear limitations, such as conscious and unconscious bias, measurement error, confounding and representativeness of populations. Researchers can overcome some of these issues with careful design, awareness of inter-individual variation, open and transparent reporting of findings, and hypothesis-driven statistical analysis to avoid multiple testing errors. Although there is evidence that data provided by nutritional epidemiology can be misleading, strong and thoughtful methodology including pre-registration, risk of bias assessment, awareness of confounders, and evidence grading can minimise potential bias, particularly when conducting systematic reviews. Translation of relative risk into population health impact is important and feeds into the need for responsible lay communication of results via mass media, especially regarding assumptions about cause and effect. Although use of mass media can bring benefits to academia, responsible dissemination is essential and starts with the press release. In conclusion, nutritional epidemiology is an important tool for exploring the risk/benefits of dietary patterns and contributing to health improvement via dietary guidelines, evidence-based policy and responsible lay communication provided its limitations are fully understood.
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Havdahl A, Wootton RE, Leppert B, Riglin L, Ask H, Tesli M, Bugge Askeland R, Hannigan LJ, Corfield E, Øyen AS, Andreassen OA, Tilling K, Davey Smith G, Thapar A, Reichborn-Kjennerud T, Stergiakouli E. Associations Between Pregnancy-Related Predisposing Factors for Offspring Neurodevelopmental Conditions and Parental Genetic Liability to Attention-Deficit/Hyperactivity Disorder, Autism, and Schizophrenia: The Norwegian Mother, Father and Child Cohort Study (MoBa). JAMA Psychiatry 2022; 79:799-810. [PMID: 35793100 PMCID: PMC9260642 DOI: 10.1001/jamapsychiatry.2022.1728] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 05/10/2022] [Indexed: 02/02/2023]
Abstract
Importance Several maternal exposures during pregnancy are considered predisposing factors for offspring neurodevelopmental conditions. However, many of these exposures may be noncausal and biased by maternal genetic liability. Objective To assess whether pregnancy-related predisposing factors for offspring neurodevelopmental conditions are associated with maternal genetic liability for attention-deficit/hyperactivity disorder (ADHD), autism, and schizophrenia and to compare associations for maternal genetic liability with those for paternal genetic liability, which could indicate that paternal exposures are not suitable negative controls for maternal exposures. Design, Setting, and Participants The Norwegian Mother, Father and Child Cohort Study (MoBa) is a population-based pregnancy cohort that recruited parents from June 1999 to December 2008. Polygenic scores (PGS) for ADHD, autism, and schizophrenia were derived in mothers and fathers. The associations between maternal PGS and 37 pregnancy-related measures were estimated, and these results were compared with those from paternal PGS predicting paternal measures during the mother's pregnancy. Analysis took place between March 2021 and March 2022. Exposures PGS for ADHD, autism, and schizophrenia, calculated (using discovery effect size estimates and threshold of P < .05) from the largest available genome-wide association studies. Main Outcomes and Measures Self-reported pregnancy-related measures capturing lifestyle behaviors, metabolism, infectious and autoimmune diseases, other physical health conditions, and medication use. Results Data were available for up to 14 539 mothers (mean [SD] age, 30.00 [4.45] years) and 14 897 fathers (mean [SD] age, 32.46 [5.13] years) of European ancestry. Modest but robust associations were observed between specific pregnancy-related measures and maternal PGS, including ADHD PGS with asthma (odds ratio [OR], 1.15 [95% CI, 1.06-1.25]), smoking (OR, 1.26 [95% CI, 1.19-1.33]), prepregnancy body mass index (β, 0.25 [95% CI, 0.18-0.31]), pregnancy weight gain (β, 0.20 [95% CI, 0.10-0.30]), taking folate (OR, 0.92 [95% CI, 0.88-0.96]), and not taking supplements (OR, 1.09 [95% CI, 1.04-1.14]). Schizophrenia PGS was associated with coffee consumption (OR, 1.09 [95% CI, 1.05-1.12]), smoking (OR, 1.12 [95% CI, 1.06-1.19]), prepregnancy body mass index (β, -0.18 [95% CI, -0.25 to -0.11]), and pregnancy weight gain (β, 0.17 [95% CI, 0.07-0.27]). All 3 PGSs associated with symptoms of depression/anxiety (ADHD: OR, 1.15 [95% CI, 1.09-1.22]; autism: OR, 1.13 [95% CI, 1.06-1.19]; schizophrenia: OR, 1.13 [95% CI, 1.07-1.20]). Associations were largely consistent for maternal and paternal PGS, except ADHD PGS and smoking (fathers: OR, 1.13 [95% CI, 1.09-1.17]). Conclusions and Relevance In this study, genetic liability to neurodevelopmental conditions that is passed from mothers to children was associated with several pregnancy-related factors and may therefore confound associations between these pregnancy-related factors and offspring neurodevelopment that have previously been thought to be causal. It is crucial that future study designs account for genetic confounding to obtain valid causal inferences so that accurate advice can be given to pregnant individuals.
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Affiliation(s)
- Alexandra Havdahl
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- PROMENTA, Department of Psychology, University of Oslo, Oslo, Norway
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - Robyn E. Wootton
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Beate Leppert
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Lucy Riglin
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
- Wolfson Centre for Young People’s Mental Health, Cardiff University, Cardiff, United Kingdom
| | - Helga Ask
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
| | - Martin Tesli
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Ragna Bugge Askeland
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - Laurie J. Hannigan
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - Elizabeth Corfield
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
| | - Anne-Siri Øyen
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
| | - Ole A. Andreassen
- NORMENT, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Kate Tilling
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - George Davey Smith
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Anita Thapar
- Division of Psychological Medicine and Clinical Neurosciences, MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
- Wolfson Centre for Young People’s Mental Health, Cardiff University, Cardiff, United Kingdom
| | - Ted Reichborn-Kjennerud
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Evie Stergiakouli
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
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Zhang M, Wang Y, Wang Y, Bai Y, Gu D. Association Between Systemic Lupus Erythematosus and Cancer Morbidity and Mortality: Findings From Cohort Studies. Front Oncol 2022; 12:860794. [PMID: 35600353 PMCID: PMC9115099 DOI: 10.3389/fonc.2022.860794] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Accepted: 03/28/2022] [Indexed: 01/08/2023] Open
Abstract
Background Observational studies suggested that systemic lupus erythematosus (SLE) might be associated with increased cancer incidence and cancer-related death, however, the results are inconsistent. We aim to comprehensively estimate the causal relationships between SLE and cancer morbidity and mortality using a meta-analysis of cohort studies and Mendelian randomization. Methods A systematic search was conducted using PubMed to identify cohort studies published before January 21, 2021. Meta-analysis was performed to calculate relative risk (RR) and corresponding 95% confidence intervals (CI). In addition, we further evaluated the potentially causal relationships identified by cohort studies using two-sample Mendelian randomization. Results A total of 48 cohort studies involving 247,575 patients were included. We performed 31 main meta-analysis to assess the cancer risk and three meta-analyses to evaluate cancer mortality in SLE patients. Through meta-analyses, we observed an increased risk of overall cancer (RR=1.62, 95%CI, 1.47-1.79, P<0.001) and cancer-related death (RR=1.52, 95%CI, 1.36-1.70, P<0.001) in patients with SLE. Subgroup analysis by site-specific cancer showed that SLE was a risk factor for 17 site-specific cancers, including six digestive cancers (esophagus, colon, anus, hepatobiliary, liver, pancreatic), five hematologic cancers (lymphoma, Hodgkin's lymphoma, non-Hodgkin lymphoma, leukemia, multiple myeloma), as well as cancer in lung, larynx, cervical, vagina/vulva, renal, bladder, skin, and thyroid. In addition, further mendelian randomization analysis verified a weakly association between genetically predisposed SLE and lymphoma risk (odds ratio=1.0004, P=0.0035). Conclusions Findings from our study suggest an important role of SLE in carcinogenesis, especially for lymphoma. Systematic Review Registration https://www.crd.york.ac.uk/PROSPERO/, CRD42021243635.
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Affiliation(s)
- Min Zhang
- School of Public Health and Management, Chongqing Medical University, Chongqing, China
| | - Yizhou Wang
- Department of Pathology, The Third Hospital of Mianyang, Sichuan Mental Health Center, Mianyang, China
| | - Yutong Wang
- Department of Epidemiology and Medicine, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Ye Bai
- School of Public Health and Management, Chongqing Medical University, Chongqing, China
| | - Dongqing Gu
- Department of Infectious Diseases, First Affiliated Hospital, Army Medical University, Chongqing, China
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Wang Q, Wang R, Chen C, Feng Y, Ye Z, Zhan M, Wen H, Guo K. Educational attainment and endometrial cancer: A Mendelian randomization study. Front Genet 2022; 13:993731. [PMID: 36523765 PMCID: PMC9744760 DOI: 10.3389/fgene.2022.993731] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 11/04/2022] [Indexed: 12/03/2022] Open
Abstract
Background: Low educational attainment has been reported as a risk factor for many diseases. However, conclusion on the association between educational attainment and endometrial cancer (EC) are inconsistent in previous observational studies. This study aims to explore the potential causal association between educational attainment and EC. Methods: A Mendelian Randomization analysis was performed using publicly summary-level data sets of genome-wide association studies (GWAS). A total of 306 single-nucleotide polymorphisms (SNPs) were extracted as instrumental variables for the exposure of educational attainment from the Social Science Genetic Association Consortium GWAS summary data of 1,131,881 participants of European ancestry. SNPs of EC were obtained from the Endometrial Cancer Association Consortium, the Epidemiology of Endometrial Cancer Consortium and the UK Biobank involving 121,885 people. We conducted inverse variance weighted (IVW) to estimate the causal effect as our primary outcome. And we perform several sensitivity analyses, including MR-Egger regression, weighted median method, MR-PRESSO (Mendelian Randomization Pleiotropy Residual Sum and Outlier) global test, and leave-one-out sensitivity analysis, to evaluate the effect of pleiotropism on the causal estimates. Results: Genetic predisposition towards 4.2 years of additional educational attainment was associated with 38% lower risk of EC. (odds ratio 0.72, 95% confidence interval 0.62 to 0.83; p = 1.65*10-5). The consistent results of sensitivity analyses indicated our causal estimates were reliable. Genetic predisposition towards longer educational attainment was associated with lower risk of obesity, high waist-to-hip ratio (WHR), and diabetes. Conclusion: This study indicated that low educational attainment was a causal risk factor for EC, especially for EC with endometrioid histology. Low educational attainment might lead to EC through the mediator of obesity, high WHR, and diabetes.
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Affiliation(s)
- Qixia Wang
- Department of Obstetrics and Gynecology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China.,Nanshan School, Guangzhou Medical University, Guangzhou, China
| | - Runchen Wang
- Department of Obstetrics and Gynecology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China.,Nanshan School, Guangzhou Medical University, Guangzhou, China
| | - Chao Chen
- Department of Obstetrics and Gynecology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China.,Nanshan School, Guangzhou Medical University, Guangzhou, China
| | - Yi Feng
- Department of Obstetrics and Gynecology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China.,Nanshan School, Guangzhou Medical University, Guangzhou, China
| | - Zhiming Ye
- Department of Obstetrics and Gynecology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China.,Nanshan School, Guangzhou Medical University, Guangzhou, China
| | - Miaorong Zhan
- Department of Obstetrics and Gynecology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China.,Third Clinical School, Guangzhou Medical University, Guangzhou, China
| | - Hao Wen
- Department of Obstetrics and Gynecology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China.,First Clinical School, Guangzhou Medical University, Guangzhou, China
| | - Kaimin Guo
- Department of Obstetrics and Gynecology, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, China
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Rosoff DB, Yoo J, Lohoff FW. Smoking is significantly associated with increased risk of COVID-19 and other respiratory infections. Commun Biol 2021; 4:1230. [PMID: 34711921 PMCID: PMC8553923 DOI: 10.1038/s42003-021-02685-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Accepted: 09/01/2021] [Indexed: 12/11/2022] Open
Abstract
Observational studies suggest smoking, cannabis use, alcohol consumption, and substance use disorders (SUDs) may impact risk for respiratory infections, including coronavirus 2019 (COVID-2019). However, causal inference is challenging due to comorbid substance use. Using summary-level European ancestry data (>1.7 million participants), we performed single-variable and multivariable Mendelian randomization (MR) to evaluate relationships between substance use behaviors, COVID-19 and other respiratory infections. Genetic liability for smoking demonstrated the strongest associations with COVID-19 infection risk, including the risk for very severe respiratory confirmed COVID-19 (odds ratio (OR) = 2.69, 95% CI, 1.42, 5.10, P-value = 0.002), and COVID-19 infections requiring hospitalization (OR = 3.49, 95% CI, 2.23, 5.44, P-value = 3.74 × 10-8); these associations generally remained robust in models accounting for other substance use and cardiometabolic risk factors. Smoking was also strongly associated with increased risk of other respiratory infections, including asthma-related pneumonia/sepsis (OR = 3.64, 95% CI, 2.16, 6.11, P-value = 1.07 × 10-6), chronic lower respiratory diseases (OR = 2.29, 95% CI, 1.80, 2.91, P-value = 1.69 × 10-11), and bacterial pneumonia (OR = 2.14, 95% CI, 1.42, 3.24, P-value = 2.84 × 10-4). We provide strong genetic evidence showing smoking increases the risk for COVID-19 and other respiratory infections even after accounting for other substance use behaviors and cardiometabolic diseases, which suggests that prevention programs aimed at reducing smoking may be important for the COVID-19 pandemic and have substantial public health benefits.
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Affiliation(s)
- Daniel B Rosoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
- NIH-Oxford-Cambridge Scholars Program; Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Joyce Yoo
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Falk W Lohoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA.
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18
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Herpesvirus infections and Alzheimer's disease: a Mendelian randomization study. ALZHEIMERS RESEARCH & THERAPY 2021; 13:158. [PMID: 34560893 PMCID: PMC8464096 DOI: 10.1186/s13195-021-00905-5] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Accepted: 09/15/2021] [Indexed: 12/14/2022]
Abstract
Background Observational studies have suggested that herpesvirus infection increased the risk of Alzheimer’s disease (AD), but it is unclear whether the association is causal. The aim of the present study is to evaluate the causal relationship between four herpesvirus infections and AD. Methods We performed a two-sample Mendelian randomization analysis to investigate association of four active herpesvirus infections with AD using summary statistics from genome-wide association studies. The four herpesvirus infections (i.e., chickenpox, shingles, cold sores, mononucleosis) are caused by varicella-zoster virus, herpes simplex virus type 1, and Epstein-Barr virus (EBV), respectively. A large summary statistics data from International Genomics of Alzheimer’s Project was used in primary analysis, including 21,982 AD cases and 41,944 controls. Validation was further performed using family history of AD data from UK Biobank (27,696 cases of maternal AD, 14,338 cases of paternal AD and 272,244 controls). Results We found evidence of a significant association between mononucleosis (caused by EBV) and risk of AD after false discovery rates (FDR) correction (odds ratio [OR] = 1.634, 95% confidence interval [CI] = 1.092–2.446, P = 0.017, FDR-corrected P = 0.034). It has been verified in validation analysis that mononucleosis is also associated with family history of AD (OR [95% CI] = 1.392 [1.061, 1.826], P = 0.017). Genetically predicted shingles were associated with AD risk (OR [95% CI] = 0.867 [0.784, 0.958], P = 0.005, FDR-corrected P = 0.020), while genetically predicted chickenpox was suggestively associated with increased family history of AD (OR [95% CI] = 1.147 [1.007, 1.307], P = 0.039). Conclusions Our findings provided evidence supporting a positive relationship between mononucleosis and AD, indicating a causal link between EBV infection and AD. Further elucidations of this association and underlying mechanisms are likely to identify feasible interventions to promote AD prevention. Supplementary Information The online version contains supplementary material available at 10.1186/s13195-021-00905-5.
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19
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Zhu X. Mendelian randomization and pleiotropy analysis. QUANTITATIVE BIOLOGY 2021; 9:122-132. [PMID: 34386270 PMCID: PMC8356909 DOI: 10.1007/s40484-020-0216-3] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Revised: 05/16/2020] [Accepted: 05/21/2020] [Indexed: 10/23/2022]
Abstract
BACKGROUND Mendelian randomization (MR) analysis has become popular in inferring and estimating the causality of an exposure on an outcome due to the success of genome wide association studies. Many statistical approaches have been developed and each of these methods require specific assumptions. RESULTS In this article, we review the pros and cons of these methods. We use an example of high-density lipoprotein cholesterol on coronary artery disease to illuminate the challenges in Mendelian randomization investigation. CONCLUSION The current available MR approaches allow us to study causality among risk factors and outcomes. However, novel approaches are desirable for overcoming multiple source confounding of risk factors and an outcome in MR analysis.
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Affiliation(s)
- Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
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20
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Leppert B, Riglin L, Wootton RE, Dardani C, Thapar A, Staley JR, Tilling K, Davey Smith G, Thapar A, Stergiakouli E. The Effect of Attention Deficit/Hyperactivity Disorder on Physical Health Outcomes: A 2-Sample Mendelian Randomization Study. Am J Epidemiol 2021; 190:1047-1055. [PMID: 33324987 PMCID: PMC8168225 DOI: 10.1093/aje/kwaa273] [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] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Revised: 12/10/2020] [Accepted: 12/10/2020] [Indexed: 12/25/2022] Open
Abstract
Attention-deficit/hyperactivity disorder (ADHD) is associated with a broad range of physical health problems. Using different research designs to test whether ADHD has a causal role in these associations is important because comorbid health problems increase the serious social and economic impacts of ADHD. We used 2-sample Mendelian randomization (MR) to infer causal relationships between ADHD and previously implicated physical health conditions. Different MR methods were used to test the robustness and plausibility of our findings. Consistent findings underwent bidirectional and multivariable MR. We found evidence of ADHD having a causal effect on childhood obesity (odds ratio = 1.29, 95% confidence interval: 1.02, 1.63) and coronary artery disease (odds ratio = 1.11, 95% confidence interval: 1.03, 1.19) with consistent results across MR approaches. There was additional MR evidence for a bidirectional relationship between ADHD and childhood obesity. The relationship with coronary artery disease attenuated when controlling for childhood obesity. There was little evidence for inferring a causal effect on other cardiometabolic, autoimmune, allergic, and neurological diseases. Our findings strengthen the argument for effective treatment of children with ADHD, and suggest that clinicians who manage ADHD need to be aware of the risk of childhood obesity to reduce future risks of coronary artery disease.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Evie Stergiakouli
- Correspondence to Dr Evie Stergiakouli, MRC Integrated Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK (e-mail: )
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21
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Khim K, Andermann A. Challenges and opportunities in addressing social determinants of child health in Cambodia: perspectives and experience of frontline providers in two health districts. CANADIAN JOURNAL OF PUBLIC HEALTH = REVUE CANADIENNE DE SANTE PUBLIQUE 2021; 112:317-330. [PMID: 33471345 PMCID: PMC7816155 DOI: 10.17269/s41997-020-00442-y] [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] [Subscribe] [Scholar Register] [Received: 12/01/2019] [Accepted: 10/25/2020] [Indexed: 12/04/2022]
Abstract
OBJECTIVES Other forces related to socio-economic and cultural factors, besides biomedical and behavioural fields, also influence health but receive little attention in health research. This study aims to illuminate social determinants of health and to identify challenges and opportunities in addressing social determinants of child health (SDCH) in rural Cambodia. METHODS This is a qualitative study based on interviews of frontline primary health care providers, health officials, local authorities and community volunteers in two health districts in Cambodia. The data were supplemented by secondary data on different aspects of the districts and Cambodia. RESULTS Poverty, lack of basic commodities and adverse social conditions remained problems for population health. While access to health services was considered adequate, households and communities had several major risk exposures. Challenges in addressing SDCH were the high prevalence of social and household adverse conditions, and the lack of training of providers, of information about social services, of effective coordination and of trust in public services. Opportunities were present, including social services being existent albeit poor functioning, the traditional practice of social inquiry, existing frontline providers being open to further information and training, existing subnational coordination bodies at district and provincial levels, and use of evidence in planning and resource allocation. CONCLUSION Addressing SDCH requires broad and coordinated efforts of stakeholders from multiple sectors. Among the prerequisites are to leverage the existing structures and mechanisms, training primary health care providers and providing them with adequate information about local resources and available supports. Improving social care services and infrastructures requires strong coordination, planning and adequate resource allocation.
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Affiliation(s)
- Keovathanak Khim
- Public Health Department, University of Health Sciences, 73, Monivong Blvd., Khan Daun Penh, Phnom Penh, Cambodia.
- Department of Family Medicine, McGill University, Montreal, Quebec, Canada.
| | - Anne Andermann
- Department of Family Medicine, McGill University, Montreal, Quebec, Canada
- School of Population and Global Health, McGill University, Montreal, Quebec, Canada
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22
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Rosoff DB, Yoo J, Lohoff FW. A genetically-informed study disentangling the relationships between tobacco smoking, cannabis use, alcohol consumption, substance use disorders and respiratory infections, including COVID-19. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.02.11.21251581. [PMID: 33594380 PMCID: PMC7885939 DOI: 10.1101/2021.02.11.21251581] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Background Observational studies suggest smoking, cannabis use, alcohol consumption, cannabis use, and substance use disorders (SUDs) may play a role in the susceptibility for respiratory infections and disease, including coronavirus 2019 (COVID-2019). However, causal inference is challenging due to comorbid substance use. Methods Using genome-wide association study data of European ancestry (data from >1.7 million individuals), we performed single-variable and multivariable Mendelian randomization to evaluate relationships between smoking, cannabis use, alcohol consumption, SUDs, and respiratory infections. Results Genetically predicted lifetime smoking was found to be associated with increased risk for hospitalized COVID-19 (odds ratio (OR)=4.039, 95% CI 2.335-6.985, P-value=5.93×10-7) and very severe hospitalized COVID-19 (OR=3.091, 95% CI, 1.883-5.092, P-value=8.40×10-6). Genetically predicted lifetime smoking was also associated with increased risk pneumoniae (OR=1.589, 95% CI, 1.214-2.078, P-value=7.33×10-4), lower respiratory infections (OR=2.303, 95% CI, 1.713-3.097, P-value=3.40×10-8), and several others. Genetically predicted cannabis use disorder (CUD) was associated with increased bronchitis risk (OR=1.078, 95% CI, 1.020-1.128, P-value=0.007). Conclusions We provide strong genetic evidence showing smoking increases the risk for respiratory infections and diseases even after accounting for other substance use and abuse. Additionally, we provide find CUD may increase the risk for bronchitis, which taken together, may guide future research SUDs and respiratory outcomes.
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Affiliation(s)
- Daniel B. Rosoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
- NIH-Oxford-Cambridge Scholars Program; Nuffield Department of Population Health, University of Oxford, UK
| | - Joyce Yoo
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Falk W. Lohoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
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23
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Mentis AFA, Dardiotis E, Efthymiou V, Chrousos GP. Non-genetic risk and protective factors and biomarkers for neurological disorders: a meta-umbrella systematic review of umbrella reviews. BMC Med 2021; 19:6. [PMID: 33435977 PMCID: PMC7805241 DOI: 10.1186/s12916-020-01873-7] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2020] [Accepted: 11/26/2020] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND The etiologies of chronic neurological diseases, which heavily contribute to global disease burden, remain far from elucidated. Despite available umbrella reviews on single contributing factors or diseases, no study has systematically captured non-purely genetic risk and/or protective factors for chronic neurological diseases. METHODS We performed a systematic analysis of umbrella reviews (meta-umbrella) published until September 20th, 2018, using broad search terms in MEDLINE, SCOPUS, Web of Science, Cochrane Database of Systematic Reviews, Cumulative Index to Nursing and Allied Health Literature, ProQuest Dissertations & Theses, JBI Database of Systematic Reviews and Implementation Reports, DARE, and PROSPERO. The PRISMA guidelines were followed for this study. Reference lists of the identified umbrella reviews were also screened, and the methodological details were assessed using the AMSTAR tool. For each non-purely genetic factor association, random effects summary effect size, 95% confidence and prediction intervals, and significance and heterogeneity levels facilitated the assessment of the credibility of the epidemiological evidence identified. RESULTS We identified 2797 potentially relevant reviews, and 14 umbrella reviews (203 unique meta-analyses) were eligible. The median number of primary studies per meta-analysis was 7 (interquartile range (IQR) 7) and that of participants was 8873 (IQR 36,394). The search yielded 115 distinctly named non-genetic risk and protective factors with a significant association, with various strengths of evidence. Mediterranean diet was associated with lower risk of dementia, Alzheimer disease (AD), cognitive impairment, stroke, and neurodegenerative diseases in general. In Parkinson disease (PD) and AD/dementia, coffee consumption, and physical activity were protective factors. Low serum uric acid levels were associated with increased risk of PD. Smoking was associated with elevated risk of multiple sclerosis and dementia but lower risk of PD, while hypertension was associated with lower risk of PD but higher risk of dementia. Chronic occupational exposure to lead was associated with higher risk of amyotrophic lateral sclerosis. Late-life depression was associated with higher risk of AD and any form of dementia. CONCLUSIONS We identified several non-genetic risk and protective factors for various neurological diseases relevant to preventive clinical neurology, health policy, and lifestyle counseling. Our findings could offer new perspectives in secondary research (meta-research).
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Affiliation(s)
- Alexios-Fotios A Mentis
- Public Health Laboratories, Hellenic Pasteur Institute, Athens, Greece; and, Department of Neurology, University Hospital of Larissa, University of Thessaly, Larissa, Greece.
| | - Efthimios Dardiotis
- Department of Neurology, University Hospital of Larissa, University of Thessaly, Larissa, Greece
| | - Vasiliki Efthymiou
- University Research Institute of Maternal and Child Health and Precision Medicine, National and Kapodistrian University of Athens, Athens, Greece
| | - George P Chrousos
- University Research Institute of Maternal and Child Health and Precision Medicine, and UNESCO Chair on Adolescent Health Care, National and Kapodistrian University of Athens, Athens, Greece
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24
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Rosoff DB, Clarke TK, Adams MJ, McIntosh AM, Davey Smith G, Jung J, Lohoff FW. Educational attainment impacts drinking behaviors and risk for alcohol dependence: results from a two-sample Mendelian randomization study with ~780,000 participants. Mol Psychiatry 2021; 26:1119-1132. [PMID: 31649322 PMCID: PMC7182503 DOI: 10.1038/s41380-019-0535-9] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Revised: 09/05/2019] [Accepted: 09/20/2019] [Indexed: 01/01/2023]
Abstract
Observational studies suggest that lower educational attainment (EA) may be associated with risky alcohol use behaviors; however, these findings may be biased by confounding and reverse causality. We performed two-sample Mendelian randomization (MR) using summary statistics from recent genome-wide association studies (GWAS) with >780,000 participants to assess the causal effects of EA on alcohol use behaviors and alcohol dependence (AD). Fifty-three independent genome-wide significant SNPs previously associated with EA were tested for association with alcohol use behaviors. We show that while genetic instruments associated with increased EA are not associated with total amount of weekly drinks, they are associated with reduced frequency of binge drinking ≥6 drinks (ßIVW = -0.198, 95% CI, -0.297 to -0.099, PIVW = 9.14 × 10-5), reduced total drinks consumed per drinking day (ßIVW = -0.207, 95% CI, -0.293 to -0.120, PIVW = 2.87 × 10-6), as well as lower weekly distilled spirits intake (ßIVW = -0.148, 95% CI, -0.188 to -0.107, PIVW = 6.24 × 10-13). Conversely, genetic instruments for increased EA were associated with increased alcohol intake frequency (ßIVW = 0.331, 95% CI, 0.267-0.396, PIVW = 4.62 × 10-24), and increased weekly white wine (ßIVW = 0.199, 95% CI, 0.159-0.238, PIVW = 7.96 × 10-23) and red wine intake (ßIVW = 0.204, 95% CI, 0.161-0.248, PIVW = 6.67 × 10-20). Genetic instruments associated with increased EA reduced AD risk: an additional 3.61 years schooling reduced the risk by ~50% (ORIVW = 0.508, 95% CI, 0.315-0.819, PIVW = 5.52 × 10-3). Consistency of results across complementary MR methods accommodating different assumptions about genetic pleiotropy strengthened causal inference. Our findings suggest EA may have important effects on alcohol consumption patterns and may provide potential mechanisms explaining reported associations between EA and adverse health outcomes.
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Affiliation(s)
- Daniel B. Rosoff
- grid.94365.3d0000 0001 2297 5165Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD USA
| | - Toni-Kim Clarke
- grid.4305.20000 0004 1936 7988Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Mark J. Adams
- grid.4305.20000 0004 1936 7988Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Andrew M. McIntosh
- grid.4305.20000 0004 1936 7988Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - George Davey Smith
- grid.5337.20000 0004 1936 7603MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Jeesun Jung
- grid.94365.3d0000 0001 2297 5165Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD USA
| | - Falk W. Lohoff
- grid.94365.3d0000 0001 2297 5165Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD USA
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25
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Abstract
The models used to estimate disease transmission, susceptibility and severity determine what epidemiology can (and cannot tell) us about COVID-19. These include: 'model organisms' chosen for their phylogenetic/aetiological similarities; multivariable statistical models to estimate the strength/direction of (potentially causal) relationships between variables (through 'causal inference'), and the (past/future) value of unmeasured variables (through 'classification/prediction'); and a range of modelling techniques to predict beyond the available data (through 'extrapolation'), compare different hypothetical scenarios (through 'simulation'), and estimate key features of dynamic processes (through 'projection'). Each of these models: address different questions using different techniques; involve assumptions that require careful assessment; and are vulnerable to generic and specific biases that can undermine the validity and interpretation of their findings. It is therefore necessary that the models used: can actually address the questions posed; and have been competently applied. In this regard, it is important to stress that extrapolation, simulation and projection cannot offer accurate predictions of future events when the underlying mechanisms (and the contexts involved) are poorly understood and subject to change. Given the importance of understanding such mechanisms/contexts, and the limited opportunity for experimentation during outbreaks of novel diseases, the use of multivariable statistical models to estimate the strength/direction of potentially causal relationships between two variables (and the biases incurred through their misapplication/misinterpretation) warrant particular attention. Such models must be carefully designed to address: 'selection-collider bias', 'unadjusted confounding bias' and 'inferential mediator adjustment bias' - all of which can introduce effects capable of enhancing, masking or reversing the estimated (true) causal relationship between the two variables examined.1 Selection-collider bias occurs when these two variables independently cause a third (the 'collider'), and when this collider determines/reflects the basis for selection in the analysis. It is likely to affect all incompletely representative samples, although its effects will be most pronounced wherever selection is constrained (e.g. analyses focusing on infected/hospitalised individuals). Unadjusted confounding bias disrupts the estimated (true) causal relationship between two variables when: these share one (or more) common cause(s); and when the effects of these causes have not been adjusted for in the analyses (e.g. whenever confounders are unknown/unmeasured). Inferentially similar biases can occur when: one (or more) variable(s) (or 'mediators') fall on the causal path between the two variables examined (i.e. when such mediators are caused by one of the variables and are causes of the other); and when these mediators are adjusted for in the analysis. Such adjustment is commonplace when: mediators are mistaken for confounders; prediction models are mistakenly repurposed for causal inference; or mediator adjustment is used to estimate direct and indirect causal relationships (in a mistaken attempt at 'mediation analysis'). These three biases are central to ongoing and unresolved epistemological tensions within epidemiology. All have substantive implications for our understanding of COVID-19, and the future application of artificial intelligence to 'data-driven' modelling of similar phenomena. Nonetheless, competently applied and carefully interpreted, multivariable statistical models may yet provide sufficient insight into mechanisms and contexts to permit more accurate projections of future disease outbreaks.
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Affiliation(s)
- George T H Ellison
- Centre for Data Innovation, Faculty of Science and Technology, University of Central Lancashire, Preston, UK
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26
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Rosoff DB, Kaminsky ZA, McIntosh AM, Davey Smith G, Lohoff FW. Educational attainment reduces the risk of suicide attempt among individuals with and without psychiatric disorders independent of cognition: a bidirectional and multivariable Mendelian randomization study with more than 815,000 participants. Transl Psychiatry 2020; 10:388. [PMID: 33168806 PMCID: PMC7653915 DOI: 10.1038/s41398-020-01047-2] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Revised: 09/22/2020] [Accepted: 10/05/2020] [Indexed: 12/16/2022] Open
Abstract
Rates of suicidal behavior are increasing in the United States and identifying causal risk factors continues to be a public health priority. Observational literature has shown that educational attainment (EA) and cognitive performance (CP) influence suicide attempt risk; however, the causal nature of these relationships is unknown. Using summary statistics from genome-wide association studies (GWAS) of EA, CP, and suicide attempt risk with > 815,000 combined white participants of European ancestry, we performed multivariable Mendelian randomization (MR) to disentangle the effects of EA and CP on attempted suicide. In single-variable MR (SVMR), EA and CP appeared to reduce suicide attempt risk (EA odds ratio (OR) per standard deviation (SD) increase in EA (4.2 years), 0.524, 95% CI, 0.412-0.666, P = 1.07 × 10-7; CP OR per SD increase in standardized score, 0.714, 95% CI, 0.577-0.885, P = 0.002). Conversely, bidirectional analyses found no effect of a suicide attempt on EA or CP. Using various multivariable MR (MVMR) models, EA seems to be the predominant risk factor for suicide attempt risk with the independent effect (OR, 0.342, 95% CI, 0.206-0.568, P = 1.61 × 10-4), while CP had no effect (OR, 1.182, 95% CI, 0.842-1.659, P = 0.333). In additional MVMR analyses accounting simultaneously for potential behavioral and psychiatric mediators (tobacco smoking; alcohol consumption; and self-reported nerves, tension, anxiety, or depression), the effect of EA was little changed (OR, 0.541, 95% CI, 0.421-0.696, P = 3.33 × 10-6). Consistency of results across complementary MR methods accommodating different assumptions about genetic pleiotropy strengthened causal inference. Our results show that even after accounting for psychiatric disorders and behavioral mediators, EA, but not CP, may causally influence suicide attempt risk among white individuals of European ancestry, which could have important implications for health policy and programs aimed at reducing the increasing rates of suicide. Future work is necessary to examine the EA-suicide relationship populations of different ethnicities.
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Affiliation(s)
- Daniel B Rosoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Zachary A Kaminsky
- Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada
| | - Andrew M McIntosh
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | | | - Falk W Lohoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA.
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Leppert B, Millard LAC, Riglin L, Davey Smith G, Thapar A, Tilling K, Walton E, Stergiakouli E. A cross-disorder PRS-pheWAS of 5 major psychiatric disorders in UK Biobank. PLoS Genet 2020; 16:e1008185. [PMID: 32392212 PMCID: PMC7274459 DOI: 10.1371/journal.pgen.1008185] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Revised: 06/05/2020] [Accepted: 02/11/2020] [Indexed: 12/14/2022] Open
Abstract
Psychiatric disorders are highly heritable and associated with a wide variety of social adversity and physical health problems. Using genetic liability (rather than phenotypic measures of disease) as a proxy for psychiatric disease risk can be a useful alternative for research questions that would traditionally require large cohort studies with long-term follow up. Here we conducted a hypothesis-free phenome-wide association study in about 330,000 participants from the UK Biobank to examine associations of polygenic risk scores (PRS) for five psychiatric disorders (major depression (MDD), bipolar disorder (BP), schizophrenia (SCZ), attention-deficit/ hyperactivity disorder (ADHD) and autism spectrum disorder (ASD)) with 23,004 outcomes in UK Biobank, using the open-source PHESANT software package. There was evidence after multiple testing (p<2.55x10-06) for associations of PRSs with 294 outcomes, most of them attributed to associations of PRSMDD (n = 167) and PRSSCZ (n = 157) with mental health factors. Among others, we found strong evidence of association of higher PRSADHD with 1.1 months younger age at first sexual intercourse [95% confidence interval [CI]: -1.25,-0.92] and a history of physical maltreatment; PRSASD with 0.01% lower erythrocyte distribution width [95%CI: -0.013,-0.007]; PRSSCZ with 0.95 lower odds of playing computer games [95%CI:0.95,0.96]; PRSMDD with a 0.12 points higher neuroticism score [95%CI:0.111,0.135] and PRSBP with 1.03 higher odds of having a university degree [95%CI:1.02,1.03]. We were able to show that genetic liabilities for five major psychiatric disorders associate with long-term aspects of adult life, including socio-demographic factors, mental and physical health. This is evident even in individuals from the general population who do not necessarily present with a psychiatric disorder diagnosis. Psychiatric disorders are associated with a wide range of adverse health, social and economic problems. Our study investigated the association of genetic risk for five common psychiatric disorders with socio- demographics, lifestyle and health of about 330,000 participants in the UK Biobank using a systematic, hypothesis-free approach. We found that genetic risk for attention deficit/hyperactivity disorder (ADHD) and bipolar disorder were most strongly associated with lifestyle factors, such as time of first sexual intercourse and educational attainment. Genetic risks for autism spectrum disorder and schizophrenia were associated with altered blood cell counts and decreased risk of playing computer games, respectively. Increased genetic risk for depression was associated with other mental health outcomes such as neuroticism and irritability. In general, our results suggest that genetic risk for psychiatric disorders associates with a range of health and lifestyle traits that were measured in adulthood, in individuals from the general population who do not necessarily present with a psychiatric disorder diagnosis. However, it is important to note that these associations are not necessary causal but can also represent genetic correlation or be influenced by other factors, such as socio-economic factors and selection into the cohort. The findings should inform future research using causally informative designs.
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Affiliation(s)
- Beate Leppert
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- * E-mail: (BL); (ES)
| | - Louise A. C. Millard
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- Intelligent Systems Laboratory, University of Bristol, Bristol, United Kingdom
| | - Lucy Riglin
- Division of Psychological Medicine and Clinical Neurosciences; MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Anita Thapar
- Division of Psychological Medicine and Clinical Neurosciences; MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
| | - Kate Tilling
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Esther Walton
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, United Kingdom
- Department of Psychology, University of Bath, Bath, United Kingdom
| | - Evie Stergiakouli
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- * E-mail: (BL); (ES)
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With friends like these…: Peer delinquency influences across age cohorts on smoking, alcohol and illegal substance use. Eur Psychiatry 2020; 26:6-12. [DOI: 10.1016/j.eurpsy.2010.09.002] [Citation(s) in RCA: 53] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/05/2010] [Revised: 09/14/2010] [Accepted: 09/15/2010] [Indexed: 11/20/2022] Open
Abstract
AbstractBackgroundDiscussions and debate about youth smoking, alcohol use, and illegal substance use (collectively referred to as youth substance use) continue to receive wide attention among researchers, policymakers, and the general public. Previous research has suggested that peer delinquency is a particularly strong correlate of youth substance use. The current study focuses on the influence of delinquent peers on substance use, and how peer delinquency influences change across age cohorts of youth.MethodThe current study examines multiple correlates for youth substance use in a sample of 8,256 youth (mean age 14), with the goal of identifying the influence of delinquent peers across age cohorts while controlling for other correlates. Data was collected from the Ohio version of the Youth Risk Behavior Surveillance System (YRBSS) developed by the Centers for Disease Control.ResultsResults from multiple regression analyses identified peer delinquency as the strongest correlate of youth substance use even when other relevant factors related to family, neighborhood, and media use were controlled. Correlations between peer delinquency and substance use behavior increased across age cohorts and for individuals who first used in middle teen years (13–16) irrespective of current age.Interpretation.Age appears to be a moderating factor regarding the correlation between peer delinquency and youth substance abuse. Primary and secondary prevention and intervention strategies that focus on peers are potentially more likely to reduce youth substance use and improve peer relationships than those focused on other areas such as schools or media.
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Davey Smith G, Phillips AN. Correlation without a cause: an epidemiological odyssey. Int J Epidemiol 2020; 49:4-14. [DOI: 10.1093/ije/dyaa016] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Accepted: 02/04/2020] [Indexed: 12/12/2022] Open
Abstract
Background
In the 1980s debate intensified over whether there was a protective effect of high-density lipoprotein cholesterol (HDL-C) or an adverse effect of triglycerides on coronary heart disease (CHD) risk. In a 1991 paper reprinted in the IJE we suggested that the high degree of correlation between the two, together with plausible levels of measurement error, made it unlikely that conventional epidemiological approaches could contribute to causal understanding. The consensus that HDL-C was protective, popularly reified in the notion of ‘good cholesterol’, strengthened over subsequent years. Reviewing the biostatistical and epidemiological literature from before and after 1991 we suggest that within the observational epidemiology pantheon only Mendelian randomization studies—that began to appear at the same time as the initial negative randomized controlled trials—made a meaningful contribution. It is sobering to realize that many issues that appear suitable targets for epidemiological investigation are simply refractory to conventional approaches. The discipline should surely revisit this and other high-profile cases of consequential epidemiological failure—such as that with respect to vitamin E supplementation and CHD risk—rather than pass them over in silence.
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Affiliation(s)
- George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
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Kazmi N, Haycock P, Tsilidis K, Lynch BM, Truong T, Martin RM, Lewis SJ. Appraising causal relationships of dietary, nutritional and physical-activity exposures with overall and aggressive prostate cancer: two-sample Mendelian-randomization study based on 79 148 prostate-cancer cases and 61 106 controls. Int J Epidemiol 2020; 49:587-596. [PMID: 31802111 DOI: 10.1093/ije/dyz235] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Accepted: 11/05/2019] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Prostate cancer is the second most common male cancer worldwide, but there is substantial geographical variation, suggesting a potential role for modifiable risk factors in prostate carcinogenesis. METHODS We identified previously reported prostate cancer risk factors from the World Cancer Research Fund (WCRF)'s systematic appraisal of the global evidence (2018). We assessed whether each identified risk factor was causally associated with risk of overall (79 148 cases and 61 106 controls) or aggressive (15 167 cases and 58 308 controls) prostate cancer using Mendelian randomization (MR) based on genome-wide association-study summary statistics from the PRACTICAL and GAME-ON/ELLIPSE consortia. We assessed evidence for replication in UK Biobank (7844 prostate-cancer cases and 204 001 controls). RESULTS WCRF identified 57 potential risk factors, of which 22 could be instrumented for MR analyses using single nucleotide polymorphisms. For overall prostate cancer, we identified evidence compatible with causality for the following risk factors (odds ratio [OR] per standard deviation increase; 95% confidence interval): accelerometer-measured physical activity, OR = 0.49 (0.33-0.72; P = 0.0003); serum iron, OR = 0.92 (0.86-0.98; P = 0.007); body mass index (BMI), OR = 0.90 (0.84-0.97; P = 0.003); and monounsaturated fat, OR = 1.11 (1.02-1.20; P = 0.02). Findings in our replication analyses in UK Biobank were compatible with our main analyses (albeit with wide confidence intervals). In MR analysis, height was positively associated with aggressive-prostate-cancer risk: OR = 1.07 (1.01-1.15; P = 0.03). CONCLUSIONS The results for physical activity, serum iron, BMI, monounsaturated fat and height are compatible with causality for prostate cancer. The results suggest that interventions aimed at increasing physical activity may reduce prostate-cancer risk, although interventions to change other risk factors may have negative consequences on other diseases.
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Affiliation(s)
- Nabila Kazmi
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Philip Haycock
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Konstantinos Tsilidis
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Brigid M Lynch
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia
- Physical-Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, Australia
| | - Therese Truong
- Université Paris-Saclay, Université Paris-Sud, CESP (Center for Research in Epidemiology and Population Health), INSERM, Team Cancer and Environment, Villejuif, France
| | - Richard M Martin
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research (NIHR) Bristol Biomedical Research Centre, University Hospitals NHS Trust and University of Bristol, Bristol, UK
| | - Sarah J Lewis
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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Howey R, Shin SY, Relton C, Davey Smith G, Cordell HJ. Bayesian network analysis incorporating genetic anchors complements conventional Mendelian randomization approaches for exploratory analysis of causal relationships in complex data. PLoS Genet 2020; 16:e1008198. [PMID: 32119656 PMCID: PMC7067488 DOI: 10.1371/journal.pgen.1008198] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2019] [Revised: 03/12/2020] [Accepted: 01/21/2020] [Indexed: 12/26/2022] Open
Abstract
Mendelian randomization (MR) implemented through instrumental variables analysis is an increasingly popular causal inference tool used in genetic epidemiology. But it can have limitations for evaluating simultaneous causal relationships in complex data sets that include, for example, multiple genetic predictors and multiple potential risk factors associated with the same genetic variant. Here we use real and simulated data to investigate Bayesian network analysis (BN) with the incorporation of directed arcs, representing genetic anchors, as an alternative approach. A Bayesian network describes the conditional dependencies/independencies of variables using a graphical model (a directed acyclic graph) with an accompanying joint probability. In real data, we found BN could be used to infer simultaneous causal relationships that confirmed the individual causal relationships suggested by bi-directional MR, while allowing for the existence of potential horizontal pleiotropy (that would violate MR assumptions). In simulated data, BN with two directional anchors (mimicking genetic instruments) had greater power for a fixed type 1 error than bi-directional MR, while BN with a single directional anchor performed better than or as well as bi-directional MR. Both BN and MR could be adversely affected by violations of their underlying assumptions (such as genetic confounding due to unmeasured horizontal pleiotropy). BN with no directional anchor generated inference that was no better than by chance, emphasizing the importance of directional anchors in BN (as in MR). Under highly pleiotropic simulated scenarios, BN outperformed both MR (and its recent extensions) and two recently-proposed alternative approaches: a multi-SNP mediation intersection-union test (SMUT) and a latent causal variable (LCV) test. We conclude that BN incorporating genetic anchors is a useful complementary method to conventional MR for exploring causal relationships in complex data sets such as those generated from modern "omics" technologies.
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Affiliation(s)
- Richard Howey
- Institute of Genetic Medicine, Newcastle University, Newcastle, United Kingdom
| | - So-Youn Shin
- Institute of Genetic Medicine, Newcastle University, Newcastle, United Kingdom
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, University of Bristol, Bristol, United Kingdom
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, University of Bristol, Bristol, United Kingdom
| | - Heather J. Cordell
- Institute of Genetic Medicine, Newcastle University, Newcastle, United Kingdom
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Davey Smith G, Holmes MV, Davies NM, Ebrahim S. Mendel's laws, Mendelian randomization and causal inference in observational data: substantive and nomenclatural issues. Eur J Epidemiol 2020; 35:99-111. [PMID: 32207040 PMCID: PMC7125255 DOI: 10.1007/s10654-020-00622-7] [Citation(s) in RCA: 112] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Accepted: 03/09/2020] [Indexed: 12/16/2022]
Abstract
We respond to criticisms of Mendelian randomization (MR) by Mukamal, Stampfer and Rimm (MSR). MSR consider that MR is receiving too much attention and should be renamed. We explain how MR links to Mendel's laws, the origin of the name and our lack of concern regarding nomenclature. We address MSR's substantive points regarding MR of alcohol and cardiovascular disease, an issue on which they dispute the MR findings. We demonstrate that their strictures with respect to population stratification, confounding, weak instrument bias, pleiotropy and confounding have been addressed, and summarise how the field has advanced in relation to the issues they raise. We agree with MSR that "the hard problem of conducting high-quality, reproducible epidemiology" should be addressed by epidemiologists. However we see more evidence of confrontation of this issue within MR, as opposed to conventional observational epidemiology, within which the same methods that have demonstrably failed in the past are simply rolled out into new areas, leaving their previous failures unexamined.
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Affiliation(s)
- George Davey Smith
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
| | - Michael V Holmes
- Medical Research Council Population Health Research Unit (MRC PHRU), Department of Population Health, University of Oxford, Nuffield, Oxford, UK
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Neil M Davies
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Shah Ebrahim
- London School of Hygiene and Tropical Medicine, London, UK
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Bedford J, Farrar J, Ihekweazu C, Kang G, Koopmans M, Nkengasong J. A new twenty-first century science for effective epidemic response. Nature 2019; 575:130-136. [PMID: 31695207 PMCID: PMC7095334 DOI: 10.1038/s41586-019-1717-y] [Citation(s) in RCA: 128] [Impact Index Per Article: 25.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Accepted: 09/24/2019] [Indexed: 12/20/2022]
Abstract
With rapidly changing ecology, urbanization, climate change, increased travel and fragile public health systems, epidemics will become more frequent, more complex and harder to prevent and contain. Here we argue that our concept of epidemics must evolve from crisis response during discrete outbreaks to an integrated cycle of preparation, response and recovery. This is an opportunity to combine knowledge and skills from all over the world-especially at-risk and affected communities. Many disciplines need to be integrated, including not only epidemiology but also social sciences, research and development, diplomacy, logistics and crisis management. This requires a new approach to training tomorrow's leaders in epidemic prevention and response.
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Affiliation(s)
| | | | | | - Gagandeep Kang
- Translational Health Science and Technology Institute, Faridabad, India
| | - Marion Koopmans
- Department of Viroscience, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - John Nkengasong
- Africa Centres for Disease Control and Prevention, African Union, Addis Ababa, Ethiopia
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Davey Smith G. Post-Modern Epidemiology: When Methods Meet Matter. Am J Epidemiol 2019; 188:1410-1419. [PMID: 30877306 PMCID: PMC6670067 DOI: 10.1093/aje/kwz064] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Revised: 02/26/2019] [Accepted: 02/26/2019] [Indexed: 12/17/2022] Open
Abstract
In the last third of the 20th century, etiological epidemiology within academia in high-income countries shifted its primary concern from attempting to tackle the apparent epidemic of noncommunicable diseases to an increasing focus on developing statistical and causal inference methodologies. This move was mutually constitutive with the failure of applied epidemiology to make major progress, with many of the advances in understanding the causes of noncommunicable diseases coming from outside the discipline, while ironically revealing the infectious origins of several major conditions. Conversely, there were many examples of epidemiologic studies promoting ineffective interventions and little evident attempt to account for such failure. Major advances in concrete understanding of disease etiology have been driven by a willingness to learn about and incorporate into epidemiology developments in biology and cognate data science disciplines. If fundamental epidemiologic principles regarding the rooting of disease risk within populations are retained, recent methodological developments combined with increased biological understanding and data sciences capability should herald a fruitful post-Modern Epidemiology world.
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Affiliation(s)
- George Davey Smith
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, United Kingdom
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Leppert B, Havdahl A, Riglin L, Jones HJ, Zheng J, Davey Smith G, Tilling K, Thapar A, Reichborn-Kjennerud T, Stergiakouli E. Association of Maternal Neurodevelopmental Risk Alleles With Early-Life Exposures. JAMA Psychiatry 2019; 76:834-842. [PMID: 31042271 PMCID: PMC6495368 DOI: 10.1001/jamapsychiatry.2019.0774] [Citation(s) in RCA: 71] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2018] [Accepted: 02/14/2019] [Indexed: 12/27/2022]
Abstract
Importance Early-life exposures, such as prenatal maternal lifestyle, illnesses, nutritional deficiencies, toxin levels, and adverse birth events, have long been considered potential risk factors for neurodevelopmental disorders in offspring. However, maternal genetic factors could be confounding the association between early-life exposures and neurodevelopmental outcomes in offspring, which makes inferring a causal relationship problematic. Objective To test whether maternal polygenic risk scores (PRSs) for neurodevelopmental disorders were associated with early-life exposures previously linked to the disorders. Design, Setting, and Participants In this UK population-based cohort study, 7921 mothers with genotype data from the Avon Longitudinal Study of Parents and Children (ALSPAC) underwent testing for association of maternal PRS for attention-deficit/hyperactivity disorder (ADHD PRS), autism spectrum disorder (ASD PRS), and schizophrenia (SCZ PRS) with 32 early-life exposures. ALSPAC data collection began September 6, 1990, and is ongoing. Data were analyzed for the current study from April 1 to September 1, 2018. Exposures Maternal ADHD PRS, ASD PRS, and SCZ PRS were calculated using discovery effect size estimates from the largest available genome-wide association study and a significance threshold of P < .05. Main Outcomes and Measures Outcomes measured included questionnaire data on maternal lifestyle and behavior (eg, smoking, alcohol consumption, body mass index, and maternal age), maternal use of nutritional supplements and medications in pregnancy (eg, acetaminophen, iron, zinc, folic acid, and vitamins), maternal illnesses (eg, diabetes, hypertension, rheumatism, psoriasis, and depression), and perinatal factors (eg, birth weight, preterm birth, and cesarean delivery). Results Maternal PRSs were available from 7921 mothers (mean [SD] age, 28.5 [4.8] years). The ADHD PRS was associated with multiple prenatal factors, including infections (odds ratio [OR], 1.11; 95% CI, 1.04-1.18), use of acetaminophen during late pregnancy (OR, 1.11; 95% CI, 1.04-1.18), lower blood levels of mercury (β coefficient, -0.06; 95% CI, -0.11 to -0.02), and higher blood levels of cadmium (β coefficient, 0.07; 95% CI, 0.05-0.09). Little evidence of associations between ASD PRS or SCZ PRS and prenatal factors or of association between any of the PRSs and adverse birth events was found. Sensitivity analyses revealed consistent results. Conclusions and Relevance These findings suggest that maternal risk alleles for neurodevelopmental disorders, primarily ADHD, are associated with some pregnancy-related exposures. These findings highlight the need to carefully account for potential genetic confounding and triangulate evidence from different approaches when assessing the effects of prenatal exposures on neurodevelopmental disorders in offspring.
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Affiliation(s)
- Beate Leppert
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Alexandra Havdahl
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- Nic Waals Institute, Lovisenberg Diaconal Hospital, Oslo, Norway
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
| | - Lucy Riglin
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
| | - Hannah J. Jones
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- National Institute for Health Research Biomedical Research Centre, University Hospitals Bristol NHS (National Health Service) Foundation Trust and the University of Bristol, Bristol, United Kingdom
| | - Jie Zheng
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - George Davey Smith
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Kate Tilling
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Anita Thapar
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
| | - Ted Reichborn-Kjennerud
- Department of Mental Disorders, Norwegian Institute of Public Health, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Evie Stergiakouli
- MRC (Medical Research Council) Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
- School of Oral and Dental Sciences, University of Bristol, Bristol, United Kingdom
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Harper S. A Future for Observational Epidemiology: Clarity, Credibility, Transparency. Am J Epidemiol 2019; 188:840-845. [PMID: 30877294 DOI: 10.1093/aje/kwy280] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Revised: 12/17/2018] [Accepted: 12/18/2018] [Indexed: 12/12/2022] Open
Abstract
Observational studies are ambiguous, difficult, and necessary for epidemiology. Presently, there are concerns that the evidence produced by most observational studies in epidemiology is not credible and contributes to research waste. I argue that observational epidemiology could be improved by focusing greater attention on 1) defining questions that make clear whether the inferential goal is descriptive or causal; 2) greater utilization of quantitative bias analysis and alternative research designs that aim to decrease the strength of assumptions needed to estimate causal effects; and 3) promoting, experimenting with, and perhaps institutionalizing both reproducible research standards and replication studies to evaluate the fragility of study findings in epidemiology. Greater clarity, credibility, and transparency in observational epidemiology will help to provide reliable evidence that can serve as a basis for making decisions about clinical or population-health interventions.
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Affiliation(s)
- Sam Harper
- Department of Epidemiology, Biostatistics & Occupational Health, McGill University, Montreal, Quebec
- Institute for Health and Social Policy, McGill University, Montreal, Quebec
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Yarmolinsky J, Berryman K, Langdon R, Bonilla C, Davey Smith G, Martin RM, Lewis SJ. Mendelian randomization does not support serum calcium in prostate cancer risk. Cancer Causes Control 2018; 29:1073-1080. [PMID: 30306355 PMCID: PMC6245088 DOI: 10.1007/s10552-018-1081-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Accepted: 09/11/2018] [Indexed: 12/29/2022]
Abstract
PURPOSE Observational studies suggest that dietary and serum calcium are risk factors for prostate cancer. However, such studies suffer from residual confounding (due to unmeasured or imprecisely measured confounders), undermining causal inference. Mendelian randomization uses randomly assigned (hence unconfounded and pre-disease onset) germline genetic variation to proxy for phenotypes and strengthen causal inference in observational studies. We tested the hypothesis that serum calcium is associated with an increased risk of overall and advanced prostate cancer. METHODS A genetic instrument was constructed using five single-nucleotide polymorphisms robustly associated with serum calcium in a genome-wide association study (n ≤ 61,079). This instrument was then used to test the effect of a 0.5 mg/dL increase (1 standard deviation, SD) in serum calcium on risk of prostate cancer in 72,729 men in the PRACTICAL (Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome) Consortium (44,825 cases, 27,904 controls) and risk of advanced prostate cancer in 33,498 men (6,263 cases, 27,235 controls). RESULTS We found weak evidence for a protective effect of serum calcium on prostate cancer risk (odds ratio [OR] per 0.5 mg/dL increase in calcium: 0.83, 95% CI 0.63-1.08; p = 0.12). We did not find strong evidence for an effect of serum calcium on advanced prostate cancer (OR per 0.5 mg/dL increase in calcium: 0.98, 95% CI 0.57-1.70; p = 0.93). CONCLUSIONS Our Mendelian randomization analysis does not support the hypothesis that serum calcium increases risk of overall or advanced prostate cancer.
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Affiliation(s)
- James Yarmolinsky
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Katie Berryman
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Ryan Langdon
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Carolina Bonilla
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Department of Preventive Medicine, School of Medicine, University of São Paulo, São Paulo, Brazil
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research (NIHR) Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
| | - Richard M Martin
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research (NIHR) Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
| | - Sarah J Lewis
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
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Fluharty ME, Sallis H, Munafò MR. Investigating possible causal effects of externalizing behaviors on tobacco initiation: A Mendelian randomization analysis. Drug Alcohol Depend 2018; 191:338-342. [PMID: 30173087 PMCID: PMC6152577 DOI: 10.1016/j.drugalcdep.2018.07.015] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/25/2018] [Revised: 07/07/2018] [Accepted: 07/12/2018] [Indexed: 12/19/2022]
Abstract
Observational studies suggest childhood externalizing disorders are associated with increased smoking and earlier initiation. However, causality cannot be inferred from observational data alone. The current study uses two-sample MR to examine the causal relationship between externalizing behaviors and tobacco use. Single nucleotide polymorphisms (SNPs) associated with aggression were obtained from the Early Life Epidemiology Consortium (mean age 8), ADHD from the Integrative Psychiatric Research and Psychiatric Genomics Consortiums (age range 6-18), and tobacco initiation and age of onset from the Tobacco and Genetics Consortium. SNPs were combined using the inverse variance weighted approach, weighted median approach, and MR-Egger regression. There was no clear evidence of an effect of aggression on tobacco initiation or age of onset for childhood aggression (initiation: β -0.002, 95% CI -0.005, 0.001, P = 0.286; age: β -0.001 95% CI -0.002, 0.000, P = 0.310) or adolescent aggression (initiation: β -0.001, 95% CI -0.006, 0.003, P = 0.610; age: β 0.000, 95% CI 0.000, 0.001, P = 0.183)]. However, there was some evidence of an association of ADHD on tobacco initiation (OR 1.23, 95% CI 1.10, 1.35, P = 0.016), although no clear evidence of an effect of ADHD on age of onset (OR = 1.022, 95% CI 0.992, 1.052, P = 0.215). Our results provide some evidence that genetic risk of childhood ADHD is causally related to increased risk of tobacco initiation; however, the causal estimate is relatively small. We found no clear evidence that genetic risk of childhood aggression is causally related to the risk of tobacco initiation or age of onset.
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Affiliation(s)
- Meg E Fluharty
- MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, United Kingdom; UK Centre for Tobacco and Alcohol Studies, School of Experimental Psychology, University of Bristol, United Kingdom.
| | - Hannah Sallis
- MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, United Kingdom; UK Centre for Tobacco and Alcohol Studies, School of Experimental Psychology, University of Bristol, United Kingdom; Centre of Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, United Kingdom
| | - Marcus R Munafò
- MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, United Kingdom; UK Centre for Tobacco and Alcohol Studies, School of Experimental Psychology, University of Bristol, United Kingdom
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40
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Yarmolinsky J, Wade KH, Richmond RC, Langdon RJ, Bull CJ, Tilling KM, Relton CL, Lewis SJ, Davey Smith G, Martin RM. Causal Inference in Cancer Epidemiology: What Is the Role of Mendelian Randomization? Cancer Epidemiol Biomarkers Prev 2018; 27:995-1010. [PMID: 29941659 PMCID: PMC6522350 DOI: 10.1158/1055-9965.epi-17-1177] [Citation(s) in RCA: 92] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2017] [Revised: 02/15/2018] [Accepted: 06/05/2018] [Indexed: 02/07/2023] Open
Abstract
Observational epidemiologic studies are prone to confounding, measurement error, and reverse causation, undermining robust causal inference. Mendelian randomization (MR) uses genetic variants to proxy modifiable exposures to generate more reliable estimates of the causal effects of these exposures on diseases and their outcomes. MR has seen widespread adoption within cardio-metabolic epidemiology, but also holds much promise for identifying possible interventions for cancer prevention and treatment. However, some methodologic challenges in the implementation of MR are particularly pertinent when applying this method to cancer etiology and prognosis, including reverse causation arising from disease latency and selection bias in studies of cancer progression. These issues must be carefully considered to ensure appropriate design, analysis, and interpretation of such studies. In this review, we provide an overview of the key principles and assumptions of MR, focusing on applications of this method to the study of cancer etiology and prognosis. We summarize recent studies in the cancer literature that have adopted a MR framework to highlight strengths of this approach compared with conventional epidemiological studies. Finally, limitations of MR and recent methodologic developments to address them are discussed, along with the translational opportunities they present to inform public health and clinical interventions in cancer. Cancer Epidemiol Biomarkers Prev; 27(9); 995-1010. ©2018 AACR.
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Affiliation(s)
- James Yarmolinsky
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Kaitlin H Wade
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Rebecca C Richmond
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Ryan J Langdon
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Caroline J Bull
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Kate M Tilling
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Caroline L Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Sarah J Lewis
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Richard M Martin
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
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41
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Ebrahim S, Davey Smith G. Who needs editors? The epidemiology of publications in the IJE. Int J Epidemiol 2018; 47:1020-1022. [DOI: 10.1093/ije/dyy143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Accepted: 06/21/2018] [Indexed: 11/12/2022] Open
Affiliation(s)
- Shah Ebrahim
- London School of Hygiene and Tropical Medicine, London, UK
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42
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Hemani G, Bowden J, Davey Smith G. Evaluating the potential role of pleiotropy in Mendelian randomization studies. Hum Mol Genet 2018; 27:R195-R208. [PMID: 29771313 PMCID: PMC6061876 DOI: 10.1093/hmg/ddy163] [Citation(s) in RCA: 701] [Impact Index Per Article: 116.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Revised: 04/26/2018] [Accepted: 04/30/2018] [Indexed: 02/06/2023] Open
Abstract
Pleiotropy, the phenomenon of a single genetic variant influencing multiple traits, is likely widespread in the human genome. If pleiotropy arises because the single nucleotide polymorphism (SNP) influences one trait, which in turn influences another ('vertical pleiotropy'), then Mendelian randomization (MR) can be used to estimate the causal influence between the traits. Of prime focus among the many limitations to MR is the unprovable assumption that apparent pleiotropic associations are mediated by the exposure (i.e. reflect vertical pleiotropy), and do not arise due to SNPs influencing the two traits through independent pathways ('horizontal pleiotropy'). The burgeoning treasure trove of genetic associations yielded through genome wide association studies makes for a tantalizing prospect of phenome-wide causal inference. Recent years have seen substantial attention devoted to the problem of horizontal pleiotropy, and in this review we outline how newly developed methods can be used together to improve the reliability of MR.
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Affiliation(s)
- Gibran Hemani
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol
| | - Jack Bowden
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol
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43
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Hemani G, Zheng J, Elsworth B, Wade KH, Haberland V, Baird D, Laurin C, Burgess S, Bowden J, Langdon R, Tan VY, Yarmolinsky J, Shihab HA, Timpson NJ, Evans DM, Relton C, Martin RM, Davey Smith G, Gaunt TR, Haycock PC. The MR-Base platform supports systematic causal inference across the human phenome. eLife 2018. [PMID: 29846171 DOI: 10.7554/elife.34408s] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/07/2023] Open
Abstract
Results from genome-wide association studies (GWAS) can be used to infer causal relationships between phenotypes, using a strategy known as 2-sample Mendelian randomization (2SMR) and bypassing the need for individual-level data. However, 2SMR methods are evolving rapidly and GWAS results are often insufficiently curated, undermining efficient implementation of the approach. We therefore developed MR-Base (<ext-link ext-link-type="uri" xlink:href="http://www.mrbase.org">http://www.mrbase.org</ext-link>): a platform that integrates a curated database of complete GWAS results (no restrictions according to statistical significance) with an application programming interface, web app and R packages that automate 2SMR. The software includes several sensitivity analyses for assessing the impact of horizontal pleiotropy and other violations of assumptions. The database currently comprises 11 billion single nucleotide polymorphism-trait associations from 1673 GWAS and is updated on a regular basis. Integrating data with software ensures more rigorous application of hypothesis-driven analyses and allows millions of potential causal relationships to be efficiently evaluated in phenome-wide association studies.
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Affiliation(s)
- Gibran Hemani
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Jie Zheng
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Benjamin Elsworth
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Kaitlin H Wade
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Valeriia Haberland
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Denis Baird
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Charles Laurin
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Stephen Burgess
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Jack Bowden
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Ryan Langdon
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Vanessa Y Tan
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - James Yarmolinsky
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Hashem A Shihab
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Nicholas J Timpson
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - David M Evans
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.,University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Australia
| | - Caroline Relton
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Richard M Martin
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - George Davey Smith
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Tom R Gaunt
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Philip C Haycock
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
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44
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Hemani G, Zheng J, Elsworth B, Wade KH, Haberland V, Baird D, Laurin C, Burgess S, Bowden J, Langdon R, Tan VY, Yarmolinsky J, Shihab HA, Timpson NJ, Evans DM, Relton C, Martin RM, Davey Smith G, Gaunt TR, Haycock PC. The MR-Base platform supports systematic causal inference across the human phenome. eLife 2018; 7:e34408. [PMID: 29846171 PMCID: PMC5976434 DOI: 10.7554/elife.34408] [Citation(s) in RCA: 3222] [Impact Index Per Article: 537.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2018] [Accepted: 03/28/2018] [Indexed: 12/21/2022] Open
Abstract
Results from genome-wide association studies (GWAS) can be used to infer causal relationships between phenotypes, using a strategy known as 2-sample Mendelian randomization (2SMR) and bypassing the need for individual-level data. However, 2SMR methods are evolving rapidly and GWAS results are often insufficiently curated, undermining efficient implementation of the approach. We therefore developed MR-Base (http://www.mrbase.org): a platform that integrates a curated database of complete GWAS results (no restrictions according to statistical significance) with an application programming interface, web app and R packages that automate 2SMR. The software includes several sensitivity analyses for assessing the impact of horizontal pleiotropy and other violations of assumptions. The database currently comprises 11 billion single nucleotide polymorphism-trait associations from 1673 GWAS and is updated on a regular basis. Integrating data with software ensures more rigorous application of hypothesis-driven analyses and allows millions of potential causal relationships to be efficiently evaluated in phenome-wide association studies.
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Affiliation(s)
- Gibran Hemani
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Jie Zheng
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Benjamin Elsworth
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Kaitlin H Wade
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Valeriia Haberland
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Denis Baird
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Charles Laurin
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Stephen Burgess
- Department of Public Health and Primary CareUniversity of CambridgeCambridgeUnited Kingdom
| | - Jack Bowden
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Ryan Langdon
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Vanessa Y Tan
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - James Yarmolinsky
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Hashem A Shihab
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Nicholas J Timpson
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - David M Evans
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
- University of Queensland Diamantina InstituteTranslational Research InstituteBrisbaneAustralia
| | - Caroline Relton
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Richard M Martin
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - George Davey Smith
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Tom R Gaunt
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
| | - Philip C Haycock
- Medical Research Council (MRC) Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUnited Kingdom
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45
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Ebrahim S, Ferrie JE, Davey Smith G. The future of epidemiology: methods or matter? Int J Epidemiol 2018; 45:1699-1716. [PMID: 28375510 DOI: 10.1093/ije/dyx032] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Affiliation(s)
- Shah Ebrahim
- London School of Hygiene and Tropical Medicine, London WC1E 7HT
| | - Jane E Ferrie
- School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN
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46
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Krieger N, Davey Smith G. Response: FACEing reality: productive tensions between our epidemiological questions, methods and mission. Int J Epidemiol 2018; 45:1852-1865. [PMID: 28130315 DOI: 10.1093/ije/dyw330] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/16/2017] [Indexed: 12/20/2022] Open
Affiliation(s)
- Nancy Krieger
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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47
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Krieger N, Davey Smith G. The tale wagged by the DAG: broadening the scope of causal inference and explanation for epidemiology. Int J Epidemiol 2018; 45:1787-1808. [PMID: 27694566 DOI: 10.1093/ije/dyw114] [Citation(s) in RCA: 78] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/13/2016] [Indexed: 12/31/2022] Open
Abstract
'Causal inference', in 21st century epidemiology, has notably come to stand for a specific approach, one focused primarily on counterfactual and potential outcome reasoning and using particular representations, such as directed acyclic graphs (DAGs) and Bayesian causal nets. In this essay, we suggest that in epidemiology no one causal approach should drive the questions asked or delimit what counts as useful evidence. Robust causal inference instead comprises a complex narrative, created by scientists appraising, from diverse perspectives, different strands of evidence produced by myriad methods. DAGs can of course be useful, but should not alone wag the causal tale. To make our case, we first address key conceptual issues, after which we offer several concrete examples illustrating how the newly favoured methods, despite their strengths, can also: (i) limit who and what may be deemed a 'cause', thereby narrowing the scope of the field; and (ii) lead to erroneous causal inference, especially if key biological and social assumptions about parameters are poorly conceived, thereby potentially causing harm. As an alternative, we propose that the field of epidemiology consider judicious use of the broad and flexible framework of 'inference to the best explanation', an approach perhaps best developed by Peter Lipton, a philosopher of science who frequently employed epidemiologically relevant examples. This stance requires not only that we be open to being pluralists about both causation and evidence but also that we rise to the challenge of forging explanations that, in Lipton's words, aspire to 'scope, precision, mechanism, unification and simplicity'.
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Affiliation(s)
- Nancy Krieger
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - George Davey Smith
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
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48
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49
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Elsworth B, Dawe K, Vincent EE, Langdon R, Lynch BM, Martin RM, Relton C, Higgins JPT, Gaunt TR. MELODI: Mining Enriched Literature Objects to Derive Intermediates. Int J Epidemiol 2018; 47:4803214. [PMID: 29342271 PMCID: PMC5913624 DOI: 10.1093/ije/dyx251] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Revised: 11/02/2017] [Accepted: 01/03/2018] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND The scientific literature contains a wealth of information from different fields on potential disease mechanisms. However, identifying and prioritizing mechanisms for further analytical evaluation presents enormous challenges in terms of the quantity and diversity of published research. The application of data mining approaches to the literature offers the potential to identify and prioritize mechanisms for more focused and detailed analysis. METHODS Here we present MELODI, a literature mining platform that can identify mechanistic pathways between any two biomedical concepts. RESULTS Two case studies demonstrate the potential uses of MELODI and how it can generate hypotheses for further investigation. First, an analysis of ETS-related gene ERG and prostate cancer derives the intermediate transcription factor SP1, recently confirmed to be physically interacting with ERG. Second, examining the relationship between a new potential risk factor for pancreatic cancer identifies possible mechanistic insights which can be studied in vitro. CONCLUSIONS We have demonstrated the possible applications of MELODI, including two case studies. MELODI has been implemented as a Python/Django web application, and is freely available to use at [www.melodi.biocompute.org.uk].
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Affiliation(s)
- Benjamin Elsworth
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Karen Dawe
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Emma E Vincent
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Ryan Langdon
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Brigid M Lynch
- Cancer Epidemiology and Intelligence Division, Cancer Council Victoria, Melbourne, VIC, Australia
- Centre for Epidemiology and Biostatistics, University of Melbourne, Melbourne, VIC, Australia
- Physical Activity Laboratory, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Richard M Martin
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | | | - Tom R Gaunt
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
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50
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Gage SH, Jones HJ, Burgess S, Bowden J, Davey Smith G, Zammit S, Munafò MR. Assessing causality in associations between cannabis use and schizophrenia risk: a two-sample Mendelian randomization study. Psychol Med 2017; 47:971-980. [PMID: 27928975 PMCID: PMC5341491 DOI: 10.1017/s0033291716003172] [Citation(s) in RCA: 140] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2016] [Revised: 11/08/2016] [Accepted: 11/09/2016] [Indexed: 01/17/2023]
Abstract
BACKGROUND Observational associations between cannabis and schizophrenia are well documented, but ascertaining causation is more challenging. We used Mendelian randomization (MR), utilizing publicly available data as a method for ascertaining causation from observational data. METHOD We performed bi-directional two-sample MR using summary-level genome-wide data from the International Cannabis Consortium (ICC) and the Psychiatric Genomics Consortium (PGC2). Single nucleotide polymorphisms (SNPs) associated with cannabis initiation (p < 10-5) and schizophrenia (p < 5 × 10-8) were combined using an inverse-variance-weighted fixed-effects approach. We also used height and education genome-wide association study data, representing negative and positive control analyses. RESULTS There was some evidence consistent with a causal effect of cannabis initiation on risk of schizophrenia [odds ratio (OR) 1.04 per doubling odds of cannabis initiation, 95% confidence interval (CI) 1.01-1.07, p = 0.019]. There was strong evidence consistent with a causal effect of schizophrenia risk on likelihood of cannabis initiation (OR 1.10 per doubling of the odds of schizophrenia, 95% CI 1.05-1.14, p = 2.64 × 10-5). Findings were as predicted for the negative control (height: OR 1.00, 95% CI 0.99-1.01, p = 0.90) but weaker than predicted for the positive control (years in education: OR 0.99, 95% CI 0.97-1.00, p = 0.066) analyses. CONCLUSIONS Our results provide some that cannabis initiation increases the risk of schizophrenia, although the size of the causal estimate is small. We find stronger evidence that schizophrenia risk predicts cannabis initiation, possibly as genetic instruments for schizophrenia are stronger than for cannabis initiation.
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Affiliation(s)
- S. H. Gage
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- UK Centre for Tobacco and Alcohol Studies, School of Experimental Psychology, University of Bristol, Bristol, UK
| | - H. J. Jones
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - S. Burgess
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - J. Bowden
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- School of Social and Community Medicine, University of Bristol, Bristol, UK
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - G. Davey Smith
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - S. Zammit
- School of Social and Community Medicine, University of Bristol, Bristol, UK
- MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, UK
| | - M. R. Munafò
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- UK Centre for Tobacco and Alcohol Studies, School of Experimental Psychology, University of Bristol, Bristol, UK
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