Literature DB >> 28590373

Nature as a Trialist?: Deconstructing the Analogy Between Mendelian Randomization and Randomized Trials.

Sonja A Swanson1, Henning Tiemeier, M Arfan Ikram, Miguel A Hernán.   

Abstract

Mendelian randomization (MR) studies are often described as naturally occurring randomized trials in which genetic factors are randomly assigned by nature. Conceptualizing MR studies as randomized trials has profound implications for their design, conduct, reporting, and interpretation. For example, analytic practices that are discouraged in randomized trials should also be discouraged in MR studies. Here, we deconstruct the oft-made analogy between MR and randomized trials. We describe four key threats to the analogy between MR studies and randomized trials: (1) exchangeability is not guaranteed; (2) time zero (and therefore the time for setting eligibility criteria) is unclear; (3) the treatment assignment is often measured with error; and (4) adherence is poorly defined. By precisely defining the causal effects being estimated, we underscore that MR estimates are often vaguely analogous to per-protocol effects in randomized trials, and that current MR methods for estimating analogues of per-protocol effects could be biased in practice. We conclude that the analogy between randomized trials and MR studies provides further perspective on both the strengths and the limitations of MR studies as currently implemented, as well as future directions for MR methodology development and application. In particular, the analogy highlights potential future directions for some MR studies to produce more interpretable and informative numerical estimates.

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Year:  2017        PMID: 28590373      PMCID: PMC5552969          DOI: 10.1097/EDE.0000000000000699

Source DB:  PubMed          Journal:  Epidemiology        ISSN: 1044-3983            Impact factor:   4.822


  38 in total

Review 1.  Mendelian randomization studies: a review of the approaches used and the quality of reporting.

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2.  Instruments for causal inference: an epidemiologist's dream?

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3.  Credible Mendelian randomization studies: approaches for evaluating the instrumental variable assumptions.

Authors:  M Maria Glymour; Eric J Tchetgen Tchetgen; James M Robins
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4.  Apolipoprotein E isoforms, serum cholesterol, and cancer.

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Review 5.  Does water kill? A call for less casual causal inferences.

Authors:  Miguel A Hernán
Journal:  Ann Epidemiol       Date:  2016-08-31       Impact factor: 3.797

6.  FTO Obesity Variant Circuitry and Adipocyte Browning in Humans.

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Journal:  N Engl J Med       Date:  2015-08-19       Impact factor: 91.245

7.  Examining overweight and obesity as risk factors for common mental disorders using fat mass and obesity-associated (FTO) genotype-instrumented analysis: The Whitehall II Study, 1985-2004.

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Journal:  Am J Epidemiol       Date:  2011-01-19       Impact factor: 4.897

8.  Smoking is associated with, but does not cause, depressed mood in pregnancy--a mendelian randomization study.

Authors:  Sarah J Lewis; Ricardo Araya; George Davey Smith; Rachel Freathy; David Gunnell; Tom Palmer; Marcus Munafò
Journal:  PLoS One       Date:  2011-07-19       Impact factor: 3.240

9.  Bounding the per-protocol effect in randomized trials: an application to colorectal cancer screening.

Authors:  Sonja A Swanson; Øyvind Holme; Magnus Løberg; Mette Kalager; Michael Bretthauer; Geir Hoff; Eline Aas; Miguel A Hernán
Journal:  Trials       Date:  2015-11-30       Impact factor: 2.279

10.  Mendelian randomization: where are we now and where are we going?

Authors:  Stephen Burgess; Nicholas J Timpson; Shah Ebrahim; George Davey Smith
Journal:  Int J Epidemiol       Date:  2015-04       Impact factor: 7.196

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  34 in total

1.  Mendelian Randomization and mediation analysis of leukocyte telomere length and risk of lung and head and neck cancers.

Authors:  Linda Kachuri; Olli Saarela; Stig Egil Bojesen; George Davey Smith; Geoffrey Liu; Maria Teresa Landi; Neil E Caporaso; David C Christiani; Mattias Johansson; Salvatore Panico; Kim Overvad; Antonia Trichopoulou; Paolo Vineis; Ghislaine Scelo; David Zaridze; Xifeng Wu; Demetrius Albanes; Brenda Diergaarde; Pagona Lagiou; Gary J Macfarlane; Melinda C Aldrich; Adonina Tardón; Gad Rennert; Andrew F Olshan; Mark C Weissler; Chu Chen; Gary E Goodman; Jennifer A Doherty; Andrew R Ness; Heike Bickeböller; H-Erich Wichmann; Angela Risch; John K Field; M Dawn Teare; Lambertus A Kiemeney; Erik H F M van der Heijden; June C Carroll; Aage Haugen; Shanbeh Zienolddiny; Vidar Skaug; Victor Wünsch-Filho; Eloiza H Tajara; Raquel Ayoub Moysés; Fabio Daumas Nunes; Stephen Lam; Jose Eluf-Neto; Martin Lacko; Wilbert H M Peters; Loïc Le Marchand; Eric J Duell; Angeline S Andrew; Silvia Franceschi; Matthew B Schabath; Jonas Manjer; Susanne Arnold; Philip Lazarus; Anush Mukeriya; Beata Swiatkowska; Vladimir Janout; Ivana Holcatova; Jelena Stojsic; Dana Mates; Jolanta Lissowska; Stefania Boccia; Corina Lesseur; Xuchen Zong; James D McKay; Paul Brennan; Christopher I Amos; Rayjean J Hung
Journal:  Int J Epidemiol       Date:  2019-06-01       Impact factor: 7.196

2.  Emulating a target trial of statin use and risk of dementia using cohort data.

Authors:  Ellen C Caniglia; L Paloma Rojas-Saunero; Saima Hilal; Silvan Licher; Roger Logan; Bruno Stricker; M Arfan Ikram; Sonja A Swanson
Journal:  Neurology       Date:  2020-08-04       Impact factor: 9.910

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

Authors:  Veronika W Skrivankova; Rebecca C Richmond; Benjamin A R Woolf; Neil M Davies; Sonja A Swanson; Tyler J VanderWeele; Nicholas J Timpson; Julian P T Higgins; Niki Dimou; Claudia Langenberg; Elizabeth W Loder; Robert M Golub; Matthias Egger; George Davey Smith; J Brent Richards
Journal:  BMJ       Date:  2021-10-26

Review 4.  Understanding the assumptions underlying Mendelian randomization.

Authors:  Christiaan de Leeuw; Jeanne Savage; Ioan Gabriel Bucur; Tom Heskes; Danielle Posthuma
Journal:  Eur J Hum Genet       Date:  2022-01-26       Impact factor: 5.351

5.  Mendelian Randomization With Repeated Measures of a Time-varying Exposure: An Application of Structural Mean Models.

Authors:  Joy Shi; Sonja A Swanson; Peter Kraft; Bernard Rosner; Immaculata De Vivo; Miguel A Hernán
Journal:  Epidemiology       Date:  2022-01-01       Impact factor: 4.860

6.  Association of mTORC1‑dependent circulating protein levels with cataract formation: a mendelian randomization study.

Authors:  Yingjun Cai; Kangcheng Liu; Pengfei Wu; Ruolan Yuan; Fei He; Jing Zou
Journal:  BMC Genomics       Date:  2022-10-21       Impact factor: 4.547

7.  Selection Bias When Estimating Average Treatment Effects Using One-sample Instrumental Variable Analysis.

Authors:  Rachael A Hughes; Neil M Davies; George Davey Smith; Kate Tilling
Journal:  Epidemiology       Date:  2019-05       Impact factor: 4.822

Review 8.  Causal Inference in Cancer Epidemiology: What Is the Role of Mendelian Randomization?

Authors:  James Yarmolinsky; Kaitlin H Wade; Rebecca C Richmond; Ryan J Langdon; Caroline J Bull; Kate M Tilling; Caroline L Relton; Sarah J Lewis; George Davey Smith; Richard M Martin
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2018-06-25       Impact factor: 4.254

Review 9.  What indeed can be tested with an instrumental variable?

Authors:  Stephen Burgess
Journal:  Eur J Epidemiol       Date:  2018-08       Impact factor: 8.082

Review 10.  Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development.

Authors:  Michael V Holmes; Tom G Richardson; Brian A Ference; Neil M Davies; George Davey Smith
Journal:  Nat Rev Cardiol       Date:  2021-03-11       Impact factor: 32.419

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