Literature DB >> 30894442

Effect of age at puberty on risk of multiple sclerosis: A mendelian randomization study.

Adil Harroud1, John A Morris1, Vincenzo Forgetta1, Ruth Mitchell1, George Davey Smith1, Stephen J Sawcer1, J Brent Richards2.   

Abstract

OBJECTIVE: To investigate the potential for a causal effect of age at puberty on multiple sclerosis (MS) susceptibility using a mendelian randomization (MR) approach.
METHODS: We used 372 genetic variants strongly associated with age at menarche in a genome-wide association study (GWAS) involving 329,245 women. The genetic architecture of pubertal timing across both sexes is highly correlated (genetic correlation [r g] = 0.75, p = 1.2 × 10-79), allowing these variants to provide reliable insight into pubertal timing in males as well. The effect of pubertal timing on risk of MS was measured with summary statistics from a GWAS of 14,802 cases with MS and 26,703 controls from the International Multiple Sclerosis Genetics Consortium. Multivariable MR controlling for effects of body mass index (BMI) using genetic data from additional consortia investigated whether pubertal effects on MS were dependent on weight status.
RESULTS: A 1-year increase in genetically predicted age at puberty decreased odds of MS by 8% (odds ratio [OR] 0.92, 95% confidence interval [CI] 0.86-0.99, p = 0.03). However, multivariable MR analysis showed that after accounting for effects on adult BMI, the association of age at puberty with MS susceptibility attenuated (OR 0.96, 95% CI 0.88-1.04, p = 0.36). Similar results were obtained when childhood BMI was incorporated. Sensitivity analyses provided no evidence of major bias from genetic pleiotropy.
CONCLUSIONS: We found support for an association between higher age at puberty and decreased risk of MS with a magnitude comparable to that reported in observational studies. This effect appears to be largely mediated by the strong association between age at puberty and obesity. A large causal effect of pubertal timing independent of BMI is unlikely.
© 2019 American Academy of Neurology.

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Year:  2019        PMID: 30894442      PMCID: PMC6550505          DOI: 10.1212/WNL.0000000000007325

Source DB:  PubMed          Journal:  Neurology        ISSN: 0028-3878            Impact factor:   9.910


  45 in total

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Authors:  George Davey Smith; Shah Ebrahim
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2.  Puberty in females enhances the risk of an outcome of multiple sclerosis in children and the development of central nervous system autoimmunity in mice.

Authors:  Jeeyoon Jennifer Ahn; Julia O'Mahony; Marina Moshkova; Heather E Hanwell; Hargurinder Singh; Monan Angela Zhang; Ruth Ann Marrie; Amit Bar-Or; Dessa A Sadovnick; Shannon E Dunn; Brenda L Banwell
Journal:  Mult Scler       Date:  2014-12-22       Impact factor: 6.312

3.  Body size and risk of MS in two cohorts of US women.

Authors:  Kassandra L Munger; Tanuja Chitnis; Alberto Ascherio
Journal:  Neurology       Date:  2009-11-10       Impact factor: 9.910

4.  Genetic Regulation of Puberty Timing in Humans.

Authors:  Felix R Day; John R B Perry; Ken K Ong
Journal:  Neuroendocrinology       Date:  2015-05-07       Impact factor: 4.914

5.  Re: "Multivariable Mendelian randomization: the use of pleiotropic genetic variants to estimate causal effects".

Authors:  Stephen Burgess; Frank Dudbridge; Simon G Thompson
Journal:  Am J Epidemiol       Date:  2015-02-05       Impact factor: 4.897

6.  Mendelian randomization analysis with multiple genetic variants using summarized data.

Authors:  Stephen Burgess; Adam Butterworth; Simon G Thompson
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7.  Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression.

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8.  Environmental exposures and the risk of multiple sclerosis investigated in a Norwegian case-control study.

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10.  Bias due to participant overlap in two-sample Mendelian randomization.

Authors:  Stephen Burgess; Neil M Davies; Simon G Thompson
Journal:  Genet Epidemiol       Date:  2016-09-14       Impact factor: 2.135

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  10 in total

1.  Strengthening the reporting of observational studies in epidemiology using mendelian randomisation (STROBE-MR): explanation and elaboration.

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Journal:  BMJ       Date:  2021-10-26

Review 2.  Towards a global view of multiple sclerosis genetics.

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Review 3.  Environmental risk factors in multiple sclerosis: bridging Mendelian randomization and observational studies.

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4.  Mendelian randomization provides no evidence for a causal role in the bidirectional relationship between depression and multiple sclerosis.

Authors:  Adil Harroud; Ruth Ann Marrie; Kathryn C Fitzgerald; Amber Salter; Yi Lu; Mitulkumar Patel; Kaarina Kowalec
Journal:  Mult Scler       Date:  2021-02-16       Impact factor: 6.312

Review 5.  Multiple Sclerosis: Melatonin, Orexin, and Ceramide Interact with Platelet Activation Coagulation Factors and Gut-Microbiome-Derived Butyrate in the Circadian Dysregulation of Mitochondria in Glia and Immune Cells.

Authors:  George Anderson; Moses Rodriguez; Russel J Reiter
Journal:  Int J Mol Sci       Date:  2019-11-05       Impact factor: 5.923

6.  Smoking and multiple sclerosis risk: a Mendelian randomization study.

Authors:  Marijne Vandebergh; An Goris
Journal:  J Neurol       Date:  2020-06-11       Impact factor: 4.849

7.  Little evidence for an effect of smoking on multiple sclerosis risk: A Mendelian Randomization study.

Authors:  Ruth E Mitchell; Kirsty Bates; Robyn E Wootton; Adil Harroud; J Brent Richards; George Davey Smith; Marcus R Munafò
Journal:  PLoS Biol       Date:  2020-11-30       Impact factor: 8.029

8.  Effects of Vitamin D and Body Mass Index on Disease Risk and Relapse Hazard in Multiple Sclerosis: A Mendelian Randomization Study.

Authors:  Marijne Vandebergh; Bénédicte Dubois; An Goris
Journal:  Neurol Neuroimmunol Neuroinflamm       Date:  2022-04-07

Review 9.  Predicting Multiple Sclerosis: Challenges and Opportunities.

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Journal:  Front Neurol       Date:  2022-02-08       Impact factor: 4.086

10.  Serum Uric Acid Level and Multiple Sclerosis: A Mendelian Randomization Study.

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  10 in total

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