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      HMG-CoA reductase is a potential therapeutic target for migraine: a mendelian randomization study

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          Abstract

          Statins are thought to have positive effects on migraine but existing data are inconclusive. We aimed to evaluate the causal effect of such drugs on migraines using Mendelian randomization. We used four types of genetic instruments as proxies for HMG-CoA reductase inhibition. We included the expression quantitative trait loci of the HMG-CoA reductase gene and genetic variation within or near the HMG-CoA reductase gene region. Variants were associated with low-density lipoprotein cholesterol, apolipoprotein B, and total cholesterol. Genome-wide association study summary data for the three lipids were obtained from the UK Biobank. Comparable data for migraine were obtained from the International Headache Genetic Consortium and the FinnGen Consortium. Inverse variance weighting method was used for the primary analysis. Additional analyses included pleiotropic robust methods, colocalization, and meta-analysis. Genetically determined high expression of HMG-CoA reductase was associated with an increased risk of migraines (OR = 1.55, 95% CI 1.30–1.84, P = 6.87 × 10 −7). Similarly, three genetically determined HMG-CoA reductase-mediated lipids were associated with an increased risk of migraine. These conclusions were consistent across meta-analyses. We found no evidence of bias caused by pleiotropy or genetic confounding factors. These findings support the hypothesis that statins can be used to treat migraine.

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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

                Contributors
                dongge@jlu.edu.cn
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                27 May 2024
                27 May 2024
                2024
                : 14
                : 12094
                Affiliations
                [1 ]Department of Neurology and Neuroscience Center, The First Hospital of Jilin University, ( https://ror.org/034haf133) Xinmin Street #1, Changchun, 130021 China
                [2 ]Department of Ophthalmology, The Second Hospital of Jilin University, ( https://ror.org/00js3aw79) Changchun, China
                [3 ]GRID grid.7737.4, ISNI 0000 0004 0410 2071, Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, , University of Helsinki, ; Helsinki, Finland
                [4 ]University of Helsinki, ( https://ror.org/040af2s02) Helsinki, Finland
                [5 ]Sutter Health, ( https://ror.org/0060avh92) Sacramento, CA USA
                [6 ]Department of Neuroscience, Karolinska Institutet, ( https://ror.org/056d84691) Stockholm, Sweden
                [7 ]Neurology Private Practice, Laeknasetrid, Reykjavík, Iceland
                [8 ]GRID grid.10419.3d, ISNI 0000000089452978, Department of Neurology, , Leiden University Medical Centre, ; Leiden, The Netherlands
                [9 ]GRID grid.10419.3d, ISNI 0000000089452978, Department of Human Genetics, , Leiden University Medical Centre, ; Leiden, The Netherlands
                [10 ]Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo University Hospital, ( https://ror.org/00j9c2840) Oslo, Norway
                [11 ]K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, ( https://ror.org/05xg72x27) Trondheim, Norway
                [12 ]Department of Neurology, Oslo University Hospital, ( https://ror.org/00j9c2840) Oslo, Norway
                [13 ]Max Planck Institute of Psychiatry, ( https://ror.org/04dq56617) Munich, Germany
                [14 ]GRID grid.5841.8, ISNI 0000 0004 1937 0247, Department of Genetics, Spain Centre for Biomedical Network Research on Rare Diseases, , University of Barcelona, ; Barcelona, Spain
                [15 ]GRID grid.420283.f, ISNI 0000 0004 0626 0858, 23&Me Inc., ; Mountain View, CA USA
                [16 ]Institute of Human Genetics, University Medical Center Hamburg-Eppendorf, ( https://ror.org/01zgy1s35) Hamburg, Germany
                [17 ]Department of Epidemiology, Erasmus University Medical Centre, ( https://ror.org/018906e22) Rotterdam, The Netherlands
                [18 ]School of Biomedical Sciences, Faculty of Health, Centre for Genomics and Personalised Health, Centre for Data Science, Queensland University of Technology, ( https://ror.org/03pnv4752) Brisbane, QLD Australia
                [19 ]Department of Medicine, Division of Preventive Medicine, Brigham and Women’s Hospital, ( https://ror.org/04b6nzv94) Boston, MA USA
                [20 ]GRID grid.38142.3c, ISNI 000000041936754X, Harvard Medical School, ; Boston, MA USA
                [21 ]Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Neuroscience Campus Amsterdam, VU University, ( https://ror.org/01x2d9f70) Amsterdam, The Netherlands
                [22 ]GRID grid.12380.38, ISNI 0000 0004 1754 9227, Netherlands Twin Register, Department of Biological Psychology, , Vrije Universiteit, ; Amsterdam, The Netherlands
                [23 ]Research and Communication Unit for Musculoskeletal Health, Department of Research, Innovation and Education, Division of Clinical Neuroscience, Akershus University Hospital and University of Oslo, ( https://ror.org/0331wat71) Oslo, Norway
                [24 ]Department of General Practice, Institute of Health and Society, University of Oslo, ( https://ror.org/01xtthb56) Oslo, Norway
                [25 ]Department of Neurology, Akershus University Hospital, ( https://ror.org/0331wat71) Lørenskog, Norway
                [26 ]Pediatric Neurology Research Group, Vall d’Hebron Research Institute, ( https://ror.org/01d5vx451) Barcelona, Spain
                [27 ]University of Bristol/Medical Research Council Integrative Epidemiology Unit, University of Bristol, ( https://ror.org/0524sp257) Bristol, UK
                [28 ]GRID grid.421812.c, ISNI 0000 0004 0618 6889, deCODE Genetics/Amgen Inc., ; Reykjavík, Iceland
                [29 ]GRID grid.4973.9, ISNI 0000 0004 0646 7373, Danish Headache Center, Department of Neurology, , Copenhagen University Hospital, ; Copenhagen, Denmark
                [30 ]Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, ( https://ror.org/01xtthb56) Oslo, Norway
                [31 ]Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, ( https://ror.org/049v75w11) Bethesda, MD USA
                [32 ]Centre for Genomics and Personalised Health, Queensland University of Technology, ( https://ror.org/03pnv4752) Brisbane, QLD Australia
                [33 ]Department of Epidemiology, Erasmus University Medical Center, ( https://ror.org/018906e22) Rotterdam, The Netherlands
                [34 ]GRID grid.428673.c, ISNI 0000 0004 0409 6302, Folkhälsan Research Center, ; Helsinki, Finland
                [35 ]Landspitali University Hospital, ( https://ror.org/011k7k191) Reykjavík, Iceland
                [36 ]GRID grid.7445.2, ISNI 0000 0001 2113 8111, Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, , Imperial College London, ; London, UK
                [37 ]Center for Life Course Health Research, Faculty of Medicine, University of Oulu, ( https://ror.org/03yj89h83) Oulu, Finland
                [38 ]Unit of Primary Health Care, Oulu University Hospital, OYS, ( https://ror.org/045ney286) Oulu, Finland
                [39 ]Department of Life Sciences, College of Health and Life Sciences, Brunel University London, ( https://ror.org/00dn4t376) London, UK
                [40 ]GRID grid.411095.8, ISNI 0000 0004 0477 2585, Institute for Stroke and Dementia Research, , University Hospital, LMU Munich, ; Munich, Germany
                [41 ]Munich Cluster for Systems Neurology, ( https://ror.org/025z3z560) Munich, Germany
                [42 ]Department of Mathematics and Statistics, University of Helsinki, ( https://ror.org/040af2s02) Helsinki, Finland
                [43 ]Department of Public Health, University of Helsinki, ( https://ror.org/040af2s02) Helsinki, Finland
                [44 ]Department of Neurology, Helsinki University Central Hospital, ( https://ror.org/040af2s02) Helsinki, Finland
                [45 ]Psychiatric and Neurodevelopmental Genetics Unit, Department of Medicine, Massachusetts General Hospital, ( https://ror.org/002pd6e78) Boston, MA USA
                [46 ]Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, ( https://ror.org/056d84691) Stockholm, Sweden
                [47 ]GRID grid.410552.7, ISNI 0000 0004 0628 215X, Centre for Population Health Research, University of Turku, , Turku University Hospital, ; Turku, Finland
                [48 ]Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, ( https://ror.org/05vghhr25) Turku, Finland
                [49 ]Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, ( https://ror.org/05dbzj528) Turku, Finland
                [50 ]GSK Inc., Cambridge, MA USA
                [51 ]GRID grid.411083.f, ISNI 0000 0001 0675 8654, Headache Unit, Neurology Department, , Vall d’Hebron University Hospital, ; Barcelona, Spain
                [52 ]Research and Communication Unit for Musculoskeletal Health, Department of Research, Innovation and Education, Division of Clinical Neuroscience, Oslo University Hospital, ( https://ror.org/00j9c2840) Oslo, Norway
                [53 ]Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, ( https://ror.org/033003e23) Tampere, Finland
                [54 ]Novo Nordic Foundation Center for Protein Research, Copenhagen University, ( https://ror.org/035b05819) Copenhagen, Denmark
                [55 ]Department of Neurology, Klinikum Passau, ( https://ror.org/05d1vf827) Passau, Germany
                [56 ]GRID grid.10392.39, ISNI 0000 0001 2190 1447, Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, , University of Tuebingen, ; Tübingen, Germany
                [57 ]Institute of Public Health, Charité – Universitätsmedizin, ( https://ror.org/001w7jn25) Berlin, Germany
                [58 ]Estonian Biobank Registry, the Estonian Genome Center, University of Tartu, ( https://ror.org/03z77qz90) Tartu, Estonia
                [59 ]Analytical and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, ( https://ror.org/002pd6e78) Boston, MA USA
                [60 ]Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, ( https://ror.org/05a0ya142) Cambridge, MA USA
                [61 ]GRID grid.66859.34, ISNI 0000 0004 0546 1623, Stanley Center for Psychiatric Research, , Broad Institute of MIT and Harvard, ; Cambridge, MA USA
                Article
                61628
                10.1038/s41598-024-61628-9
                11130224
                38802400
                044f985f-1717-44fb-8b02-2ecd32c02ebb
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 21 November 2023
                : 7 May 2024
                Funding
                Funded by: National Natural Science Foundation of China
                Award ID: Grant No. 31872772
                Award Recipient :
                Funded by: Natural Science Foundation of Jilin Province of China
                Award ID: Grant No. 20200201606JC
                Award Recipient :
                Categories
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                Custom metadata
                © Springer Nature Limited 2024

                Uncategorized
                statins,hmg-coa reductase,migraine,mendelian randomization,neuroscience,neurogenesis
                Uncategorized
                statins, hmg-coa reductase, migraine, mendelian randomization, neuroscience, neurogenesis

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