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      Smoking and heart failure: a Mendelian randomization and mediation analysis

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          Abstract

          Aims

          We performed a Mendelian randomization (MR) study to elucidate the associations of ever smoking, lifelong smoking duration, and smoking cessation with heart failure (HF) risk.

          Methods and results

          We extracted genetic variants associated with smoking initiation, age at initiation of regular smoking, cigarettes per day, and smoking cessation from the genome‐wide association study and Sequencing Consortium of Alcohol and Nicotine use (1.2 million individuals), as well as a composite lifetime smoking index from the UK Biobank (462 690 individuals). The associations between smoking phenotypes and HF were explored in the Heart Failure Molecular Epidemiology for Therapeutic Targets Consortium (47 309 cases; 930 014 controls) employing inverse variance‐weighted meta‐analysis and multivariable MR. The mediation effects of coronary artery disease and atrial fibrillation on smoking–HF risk were explored using mediation analysis. The odds ratios (ORs) for HF were 1.28 [95% confidence interval (CI), 1.22–1.36; P = 1.5 × 10 −18] for ever regular smokers compared with never smokers and 1.25 (95% CI, 1.09–1.44; P = 1.6 × 10 −3) for current smokers vs. former smokers. Genetic liability to smoking more cigarettes per day (OR, 1.37; 95% CI, 1.20–1.58; P = 6.4 × 10 −6) and a higher composite lifetime smoking index (OR, 1.49; 95% CI, 1.31–1.70; P = 2.5 × 10 −9) were associated with a higher risk of HF. The results were robust and consistent in all sensitivity analyses and multivariable MR after adjusting for HF risk factors, and their associations were independent of coronary artery disease and atrial fibrillation.

          Conclusions

          Genetic liability to ever smoking and a higher lifetime smoking burden are associated with a higher risk of HF.

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          Most cited references43

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          Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression

          Background: The number of Mendelian randomization analyses including large numbers of genetic variants is rapidly increasing. This is due to the proliferation of genome-wide association studies, and the desire to obtain more precise estimates of causal effects. However, some genetic variants may not be valid instrumental variables, in particular due to them having more than one proximal phenotypic correlate (pleiotropy). Methods: We view Mendelian randomization with multiple instruments as a meta-analysis, and show that bias caused by pleiotropy can be regarded as analogous to small study bias. Causal estimates using each instrument can be displayed visually by a funnel plot to assess potential asymmetry. Egger regression, a tool to detect small study bias in meta-analysis, can be adapted to test for bias from pleiotropy, and the slope coefficient from Egger regression provides an estimate of the causal effect. Under the assumption that the association of each genetic variant with the exposure is independent of the pleiotropic effect of the variant (not via the exposure), Egger’s test gives a valid test of the null causal hypothesis and a consistent causal effect estimate even when all the genetic variants are invalid instrumental variables. Results: We illustrate the use of this approach by re-analysing two published Mendelian randomization studies of the causal effect of height on lung function, and the causal effect of blood pressure on coronary artery disease risk. The conservative nature of this approach is illustrated with these examples. Conclusions: An adaption of Egger regression (which we call MR-Egger) can detect some violations of the standard instrumental variable assumptions, and provide an effect estimate which is not subject to these violations. The approach provides a sensitivity analysis for the robustness of the findings from a Mendelian randomization investigation.
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            Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases

            Horizontal pleiotropy occurs when the variant has an effect on disease outside of its effect on the exposure in Mendelian randomization (MR). Violation of the ‘no horizontal pleiotropy’ assumption can cause severe bias in MR. We developed the Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) test to identify horizontal pleiotropic outliers in multi-instrument summary-level MR testing. We showed using simulations that MR-PRESSO is best suited when horizontal pleiotropy occurs in <50% of instruments. Next, we applied MR-PRESSO, along with several other MR tests to complex traits and diseases, and found that horizontal pleiotropy: (i) was detectable in over 48% of significant causal relationships in MR; (ii) introduced distortions in the causal estimates in MR that ranged on average from −131% to 201%; (iii) induced false positive causal relationships in up to 10% of relationships; and (iv) can be corrected in some but not all instances.
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              Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010

              Non-fatal health outcomes from diseases and injuries are a crucial consideration in the promotion and monitoring of individual and population health. The Global Burden of Disease (GBD) studies done in 1990 and 2000 have been the only studies to quantify non-fatal health outcomes across an exhaustive set of disorders at the global and regional level. Neither effort quantified uncertainty in prevalence or years lived with disability (YLDs). Of the 291 diseases and injuries in the GBD cause list, 289 cause disability. For 1160 sequelae of the 289 diseases and injuries, we undertook a systematic analysis of prevalence, incidence, remission, duration, and excess mortality. Sources included published studies, case notification, population-based cancer registries, other disease registries, antenatal clinic serosurveillance, hospital discharge data, ambulatory care data, household surveys, other surveys, and cohort studies. For most sequelae, we used a Bayesian meta-regression method, DisMod-MR, designed to address key limitations in descriptive epidemiological data, including missing data, inconsistency, and large methodological variation between data sources. For some disorders, we used natural history models, geospatial models, back-calculation models (models calculating incidence from population mortality rates and case fatality), or registration completeness models (models adjusting for incomplete registration with health-system access and other covariates). Disability weights for 220 unique health states were used to capture the severity of health loss. YLDs by cause at age, sex, country, and year levels were adjusted for comorbidity with simulation methods. We included uncertainty estimates at all stages of the analysis. Global prevalence for all ages combined in 2010 across the 1160 sequelae ranged from fewer than one case per 1 million people to 350,000 cases per 1 million people. Prevalence and severity of health loss were weakly correlated (correlation coefficient -0·37). In 2010, there were 777 million YLDs from all causes, up from 583 million in 1990. The main contributors to global YLDs were mental and behavioural disorders, musculoskeletal disorders, and diabetes or endocrine diseases. The leading specific causes of YLDs were much the same in 2010 as they were in 1990: low back pain, major depressive disorder, iron-deficiency anaemia, neck pain, chronic obstructive pulmonary disease, anxiety disorders, migraine, diabetes, and falls. Age-specific prevalence of YLDs increased with age in all regions and has decreased slightly from 1990 to 2010. Regional patterns of the leading causes of YLDs were more similar compared with years of life lost due to premature mortality. Neglected tropical diseases, HIV/AIDS, tuberculosis, malaria, and anaemia were important causes of YLDs in sub-Saharan Africa. Rates of YLDs per 100,000 people have remained largely constant over time but rise steadily with age. Population growth and ageing have increased YLD numbers and crude rates over the past two decades. Prevalences of the most common causes of YLDs, such as mental and behavioural disorders and musculoskeletal disorders, have not decreased. Health systems will need to address the needs of the rising numbers of individuals with a range of disorders that largely cause disability but not mortality. Quantification of the burden of non-fatal health outcomes will be crucial to understand how well health systems are responding to these challenges. Effective and affordable strategies to deal with this rising burden are an urgent priority for health systems in most parts of the world. Bill & Melinda Gates Foundation. Copyright © 2012 Elsevier Ltd. All rights reserved.
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                Author and article information

                Contributors
                1191066@zju.edu.cn
                Journal
                ESC Heart Fail
                ESC Heart Fail
                10.1002/(ISSN)2055-5822
                EHF2
                ESC Heart Failure
                John Wiley and Sons Inc. (Hoboken )
                2055-5822
                03 March 2021
                June 2021
                : 8
                : 3 ( doiID: 10.1002/ehf2.v8.3 )
                : 1954-1965
                Affiliations
                [ 1 ] Department of Cardiology, The First Affiliated Hospital, School of Medicine Zhejiang University Hangzhou Zhejiang 310003 China
                [ 2 ] Huzhou Maternal and Child Health Care Hospital Huzhou Zhejiang China
                [ 3 ] Institute for Stroke and Dementia Research (ISD) University Hospital, Ludwig Maximilian University of Munich (LMU) Munich Germany
                [ 4 ] The First Affiliated Hospital, School of Medicine Zhejiang University Hangzhou Zhejiang China
                Author notes
                [*] [* ]Correspondence to: Liangrong Zheng, Department of Cardiology, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310003, China. Tel: 86‐0571‐87236502; Fax: 86‐0571‐87236502. Email: 1191066@ 123456zju.edu.cn
                Article
                EHF213248 ESCHF-20-00759
                10.1002/ehf2.13248
                8120408
                33656795
                83f9905e-177b-48a0-a7dc-a04fad51a47f
                © 2021 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 15 January 2021
                : 10 August 2020
                : 26 January 2021
                Page count
                Figures: 3, Tables: 2, Pages: 12, Words: 3824
                Funding
                Funded by: Deutscher Akademischer Austauschdienst , open-funder-registry 10.13039/501100001655;
                Funded by: Alexander S. Onassis Public Benefit Foundation , open-funder-registry 10.13039/501100005302;
                Funded by: Medical Science Research Foundation of Zhejiang Province
                Award ID: 2018ZD017
                Funded by: Natural Science Foundation of Zhejiang Province , open-funder-registry 10.13039/501100004731;
                Award ID: Y17H020020
                Award ID: LY15H020002
                Award ID: LZ16H020001
                Funded by: National Natural Science Foundation of China , open-funder-registry 10.13039/501100001809;
                Award ID: 81873484
                Award ID: 81800231
                Award ID: 30900612
                Funded by: National Basic Research Program of China (973 Program) , open-funder-registry 10.13039/501100012166;
                Award ID: 2016YFC1301003
                Categories
                Original Research Article
                Original Research Articles
                Custom metadata
                2.0
                June 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.2 mode:remove_FC converted:14.05.2021

                heart failure,mendelian randomization,mediation analysis,smoking

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