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      Appraising the causal role of smoking in multiple diseases: A systematic review and meta-analysis of Mendelian randomization studies

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          Summary

          Background

          The causal association between cigarette smoking and several diseases remains equivocal. The purpose of this study was to appraise the causal role of smoking in a wide range of diseases by summarizing the evidence from Mendelian randomization (MR) studies.

          Methods

          MR studies on genetic liability to smoking initiation or lifetime smoking (composite of smoking initiation, heaviness, duration, and cessation) in relation to circulatory system, digestive system, nervous system, musculoskeletal system, endocrine, metabolic, and eye diseases, and neoplasms published until February 15, 2022, were identified in PubMed. De novo MR analyses were performed using summary statistics data from genome-wide association studies. Meta-analysis was applied to combine study-specific estimates.

          Findings

          Meta-analyses of findings of 29 published MR studies and 123 de novo MR analyses of 57 distinct primary outcomes showed that genetic liability to smoking (smoking initiation or lifetime smoking) was associated with increased risk of 13 circulatory system diseases, several digestive system diseases (including diverticular, gallstone, gastroesophageal reflux, and Crohn's disease, acute pancreatitis, and periodontitis), epilepsy, certain musculoskeletal system diseases (including fracture, osteoarthritis, and rheumatoid arthritis), endocrine (polycystic ovary syndrome), metabolic (type 2 diabetes) and eye diseases (including age-related macular degeneration and senile cataract) as well as cancers of the lung, head and neck, esophagus, pancreas, bladder, kidney, cervix, and ovaries, and myeloid leukemia. Smoking liability was associated with decreased risk of Parkinson's disease and prostate cancer.

          Interpretation

          This study found robust evidence that cigarette smoking causes a wide range of diseases.

          Funding

          This work was supported by research grants from the Swedish Cancer Society (Cancerfonden), the Swedish Heart Lung Foundation (Hjärt-Lungfonden, 20210351), the Swedish Research Council for Health, Working Life and Welfare (Forte, 2018-00123), and the Swedish Research Council (Vetenskapsrådet, 2019-00977). Stephen Burgess is supported by Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (204623/Z/16/Z) and the National Institute for Health Research Cambridge Biomedical Research Centre (BRC-1215-20014). The views expressed are those of the authors and not necessarily those of the National Institute for Health Research or the Department of Health and Social Care.

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          Most cited references72

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          The MR-Base platform supports systematic causal inference across the human phenome

          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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            ‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease?*

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              Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use

              Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders1. They are heritable 2,3 and etiologically related 4,5 behaviors that have been resistant to gene discovery efforts 6–11 . In sample sizes up to 1.2 million individuals, we discovered 566 genetic variants in 406 loci associated with multiple stages of tobacco use (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci evidencing pleiotropic association. Smoking phenotypes were positively genetically correlated with many health conditions, whereas alcohol use was negatively correlated with these conditions, such that increased genetic risk for alcohol use is associated with lower disease risk. We report evidence for the involvement of many systems in tobacco and alcohol use, including genes involved in nicotinic, dopaminergic, and glutamatergic neurotransmission. The results provide a solid starting point to evaluate the effects of these loci in model organisms and more precise substance use measures.
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                Author and article information

                Contributors
                Journal
                eBioMedicine
                EBioMedicine
                eBioMedicine
                Elsevier
                2352-3964
                08 July 2022
                August 2022
                08 July 2022
                : 82
                : 104154
                Affiliations
                [a ]Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
                [b ]Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
                [c ]Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
                [d ]MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
                Author notes
                [* ]Corresponding author at: Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden. susanna.larsson@ 123456surgsci.uu.se
                Article
                S2352-3964(22)00335-8 104154
                10.1016/j.ebiom.2022.104154
                9278068
                35816897
                dca7ebd0-d766-49cf-9365-058cd7236ca8
                © 2022 The Author(s)

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 17 March 2022
                : 17 June 2022
                : 24 June 2022
                Categories
                Articles

                cancer,cardiovascular disease,chronic diseases,lifestyle factors,mendelian randomization,smoking

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