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      Exploring the Relationship Between Schizophrenia and Cardiovascular Disease: A Genetic Correlation and Multivariable Mendelian Randomization Study

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          Abstract

          Individuals with schizophrenia have a reduced life-expectancy compared to the general population, largely due to an increased risk of cardiovascular disease (CVD). Clinical and epidemiological studies have been unable to unravel the nature of this relationship. We obtained summary-data of genome-wide-association studies of schizophrenia ( N = 130 644), heart failure ( N = 977 323), coronary artery disease ( N = 332 477), systolic and diastolic blood pressure ( N = 757 601), heart rate variability ( N = 46 952), QT interval ( N = 103 331), early repolarization and dilated cardiomyopathy ECG patterns ( N = 63 700). We computed genetic correlations and conducted bi-directional Mendelian randomization (MR) to assess causality. With multivariable MR, we investigated whether causal effects were mediated by smoking, body mass index, physical activity, lipid levels, or type 2 diabetes. Genetic correlations between schizophrenia and CVD were close to zero (−0.02–0.04). There was evidence that liability to schizophrenia causally increases heart failure risk. This effect remained consistent with multivariable MR. There was also evidence that liability to schizophrenia increases early repolarization pattern, largely mediated by BMI and lipids. Finally, there was evidence that liability to schizophrenia increases heart rate variability, a direction of effect contrasting clinical studies. There was weak evidence that higher systolic blood pressure increases schizophrenia risk. Our finding that liability to schizophrenia increases heart failure is consistent with the notion that schizophrenia involves a systemic dysregulation of the body with detrimental effects on the heart. To decrease cardiovascular mortality among individuals with schizophrenia, priority should lie with optimal treatment in early stages of psychosis.

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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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            Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator

            ABSTRACT Developments in genome‐wide association studies and the increasing availability of summary genetic association data have made application of Mendelian randomization relatively straightforward. However, obtaining reliable results from a Mendelian randomization investigation remains problematic, as the conventional inverse‐variance weighted method only gives consistent estimates if all of the genetic variants in the analysis are valid instrumental variables. We present a novel weighted median estimator for combining data on multiple genetic variants into a single causal estimate. This estimator is consistent even when up to 50% of the information comes from invalid instrumental variables. In a simulation analysis, it is shown to have better finite‐sample Type 1 error rates than the inverse‐variance weighted method, and is complementary to the recently proposed MR‐Egger (Mendelian randomization‐Egger) regression method. In analyses of the causal effects of low‐density lipoprotein cholesterol and high‐density lipoprotein cholesterol on coronary artery disease risk, the inverse‐variance weighted method suggests a causal effect of both lipid fractions, whereas the weighted median and MR‐Egger regression methods suggest a null effect of high‐density lipoprotein cholesterol that corresponds with the experimental evidence. Both median‐based and MR‐Egger regression methods should be considered as sensitivity analyses for Mendelian randomization investigations with multiple genetic variants.
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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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                Author and article information

                Journal
                Schizophr Bull
                Schizophr Bull
                schbul
                Schizophrenia Bulletin
                Oxford University Press (US )
                0586-7614
                1745-1701
                March 2022
                03 November 2021
                03 November 2021
                : 48
                : 2
                : 463-473
                Affiliations
                [1 ] Department of Psychiatry, Amsterdam UMC, University of Amsterdam , Amsterdam, The Netherlands
                [2 ] Integrative Epidemiology Unit, University of Bristol , Bristol, UK
                [3 ] Population Health Sciences, Bristol Medical School, University of Bristol , Bristol, UK
                [4 ] Nic Waals institute, Lovisenberg Diaconal Hospital , Oslo, Norway
                [5 ] Cardiovascular Genetics Center, Montreal Heart Institute, Faculty of Medicine, Université de Montréal , Montreal, QC, Canada
                [6 ] Department of Experimental Cardiology, Heart Center, Amsterdam Cardiovascular Sciences, University of Amsterdam, Amsterdam UMC , Amsterdam, The Netherlands
                [7 ] Tobacco and Alcohol Research Group, School of Psychological Science, University of Bristol , Bristol, UK
                Author notes
                To whom correspondence should be addressed; Meibergdreef 5, 1105 AZ, Amsterdam, The Netherlands; tel: +31(0)20-8913600, e-mail: j.l.treur@ 123456amsterdamumc.nl
                Author information
                https://orcid.org/0000-0001-5188-5775
                https://orcid.org/0000-0003-3961-3202
                https://orcid.org/0000-0002-1472-0258
                Article
                sbab132
                10.1093/schbul/sbab132
                8886584
                34730178
                50feba9b-094d-41ca-8f8b-621b0f0aff67
                © The Author(s) 2021. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                Page count
                Pages: 11
                Funding
                Funded by: Foundation Volksbond Rotterdam;
                Funded by: ZonMw grant;
                Award ID: 849200011
                Funded by: Dutch Heart Foundation Netherlands Cardiovascular Research Initiative;
                Award ID: PREDICT2 2018–30
                Funded by: University of Bristol, DOI 10.13039/501100000883;
                Award ID: MC_UU_00011/7
                Funded by: National Institute for Health Research, DOI 10.13039/501100000272;
                Funded by: University Hospitals Bristol NHS Foundation Trust, DOI 10.13039/100012141;
                Funded by: University of Bristol, DOI 10.13039/501100000883;
                Categories
                Regular Articles
                AcademicSubjects/MED00810

                Neurology
                coronary artery disease,heart rate variability,qt interval,early repolarization,dilated cardiomyopathy,causality

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