Literature DB >> 21432888

Bias in causal estimates from Mendelian randomization studies with weak instruments.

Stephen Burgess1, Simon G Thompson.   

Abstract

Mendelian randomization studies using genetic instrumental variables (IVs) are now being commonly used to estimate the causal association of a phenotype on an outcome. Even when the necessary underlying assumptions are valid, estimates from analyses using IVs are biased in finite samples. The source and nature of this bias appear poorly understood in the epidemiological field. We explain why the bias is in the direction of the confounded observational association, with magnitude relating to the statistical strength of association between the instrument and phenotype. We comment on the size of the bias, from simulated data, showing that when multiple instruments are used, although the variance of the IV estimator decreases, the bias increases. We discuss ways to analyse Mendelian randomization studies to alleviate the problem of weak instrument bias.
Copyright © 2011 John Wiley & Sons, Ltd.

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Year:  2011        PMID: 21432888     DOI: 10.1002/sim.4197

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  60 in total

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2.  Plasma sRAGE Acts as a Genetically Regulated Causal Intermediate in Sepsis-associated Acute Respiratory Distress Syndrome.

Authors:  Tiffanie K Jones; Rui Feng; V Eric Kerchberger; John P Reilly; Brian J Anderson; Michael G S Shashaty; Fan Wang; Thomas G Dunn; Thomas R Riley; Jason Abbott; Caroline A G Ittner; David C Christiani; Carmen Mikacenic; Mark M Wurfel; Lorraine B Ware; Carolyn S Calfee; Michael A Matthay; Jason D Christie; Nuala J Meyer
Journal:  Am J Respir Crit Care Med       Date:  2020-01-01       Impact factor: 21.405

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

Authors:  Sonja A Swanson; Henning Tiemeier; M Arfan Ikram; Miguel A Hernán
Journal:  Epidemiology       Date:  2017-09       Impact factor: 4.822

4.  Elevated Platelet Count Appears to Be Causally Associated with Increased Risk of Lung Cancer: A Mendelian Randomization Analysis.

Authors:  Ying Zhu; Yongyue Wei; Ruyang Zhang; Xuesi Dong; Sipeng Shen; Yang Zhao; Jianling Bai; Demetrius Albanes; Neil E Caporaso; Maria Teresa Landi; Bin Zhu; Stephen J Chanock; Fangyi Gu; Stephen Lam; Ming-Sound Tsao; Frances A Shepherd; Adonina Tardon; Ana Fernández-Somoano; Guillermo Fernandez-Tardon; Chu Chen; Matthew J Barnett; Jennifer Doherty; Stig E Bojesen; Mattias Johansson; Paul Brennan; James D McKay; Robert Carreras-Torres; Thomas Muley; Angela Risch; Heunz-Erich Wichmann; Heike Bickeboeller; Albert Rosenberger; Gad Rennert; Walid Saliba; Susanne M Arnold; John K Field; Michael P A Davies; Michael W Marcus; Xifeng Wu; Yuanqing Ye; Loic Le Marchand; Lynne R Wilkens; Olle Melander; Jonas Manjer; Hans Brunnström; Rayjean J Hung; Geoffrey Liu; Yonathan Brhane; Linda Kachuri; Angeline S Andrew; Eric J Duell; Lambertus A Kiemeney; Erik Hfm van der Heijden; Aage Haugen; Shanbeh Zienolddiny; Vidar Skaug; Kjell Grankvist; Mikael Johansson; Penella J Woll; Angela Cox; Fiona Taylor; Dawn M Teare; Philip Lazarus; Matthew B Schabath; Melinda C Aldrich; Richard S Houlston; John McLaughlin; Victoria L Stevens; Hongbing Shen; Zhibin Hu; Juncheng Dai; Christopher I Amos; Younghun Han; Dakai Zhu; Gary E Goodman; Feng Chen; David C Christiani
Journal:  Cancer Epidemiol Biomarkers Prev       Date:  2019-01-30       Impact factor: 4.254

5.  Arsenic metabolism efficiency has a causal role in arsenic toxicity: Mendelian randomization and gene-environment interaction.

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Journal:  Int J Epidemiol       Date:  2013-12       Impact factor: 7.196

6.  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

7.  Association Between Telomere Length and Risk of Cancer and Non-Neoplastic Diseases: A Mendelian Randomization Study.

Authors:  Philip C Haycock; Stephen Burgess; Aayah Nounu; Jie Zheng; George N Okoli; Jack Bowden; Kaitlin Hazel Wade; Nicholas J Timpson; David M Evans; Peter Willeit; Abraham Aviv; Tom R Gaunt; Gibran Hemani; Massimo Mangino; Hayley Patricia Ellis; Kathreena M Kurian; Karen A Pooley; Rosalind A Eeles; Jeffrey E Lee; Shenying Fang; Wei V Chen; Matthew H Law; Lisa M Bowdler; Mark M Iles; Qiong Yang; Bradford B Worrall; Hugh Stephen Markus; Rayjean J Hung; Chris I Amos; Amanda B Spurdle; Deborah J Thompson; Tracy A O'Mara; Brian Wolpin; Laufey Amundadottir; Rachael Stolzenberg-Solomon; Antonia Trichopoulou; N Charlotte Onland-Moret; Eiliv Lund; Eric J Duell; Federico Canzian; Gianluca Severi; Kim Overvad; Marc J Gunter; Rosario Tumino; Ulrika Svenson; Andre van Rij; Annette F Baas; Matthew J Bown; Nilesh J Samani; Femke N G van t'Hof; Gerard Tromp; Gregory T Jones; Helena Kuivaniemi; James R Elmore; Mattias Johansson; James Mckay; Ghislaine Scelo; Robert Carreras-Torres; Valerie Gaborieau; Paul Brennan; Paige M Bracci; Rachel E Neale; Sara H Olson; Steven Gallinger; Donghui Li; Gloria M Petersen; Harvey A Risch; Alison P Klein; Jiali Han; Christian C Abnet; Neal D Freedman; Philip R Taylor; John M Maris; Katja K Aben; Lambertus A Kiemeney; Sita H Vermeulen; John K Wiencke; Kyle M Walsh; Margaret Wrensch; Terri Rice; Clare Turnbull; Kevin Litchfield; Lavinia Paternoster; Marie Standl; Gonçalo R Abecasis; John Paul SanGiovanni; Yong Li; Vladan Mijatovic; Yadav Sapkota; Siew-Kee Low; Krina T Zondervan; Grant W Montgomery; Dale R Nyholt; David A van Heel; Karen Hunt; Dan E Arking; Foram N Ashar; Nona Sotoodehnia; Daniel Woo; Jonathan Rosand; Mary E Comeau; W Mark Brown; Edwin K Silverman; John E Hokanson; Michael H Cho; Jennie Hui; Manuel A Ferreira; Philip J Thompson; Alanna C Morrison; Janine F Felix; Nicholas L Smith; Angela M Christiano; Lynn Petukhova; Regina C Betz; Xing Fan; Xuejun Zhang; Caihong Zhu; Carl D Langefeld; Susan D Thompson; Feijie Wang; Xu Lin; David A Schwartz; Tasha Fingerlin; Jerome I Rotter; Mary Frances Cotch; Richard A Jensen; Matthias Munz; Henrik Dommisch; Arne S Schaefer; Fang Han; Hanna M Ollila; Ryan P Hillary; Omar Albagha; Stuart H Ralston; Chenjie Zeng; Wei Zheng; Xiao-Ou Shu; Andre Reis; Steffen Uebe; Ulrike Hüffmeier; Yoshiya Kawamura; Takeshi Otowa; Tsukasa Sasaki; Martin Lloyd Hibberd; Sonia Davila; Gang Xie; Katherine Siminovitch; Jin-Xin Bei; Yi-Xin Zeng; Asta Försti; Bowang Chen; Stefano Landi; Andre Franke; Annegret Fischer; David Ellinghaus; Carlos Flores; Imre Noth; Shwu-Fan Ma; Jia Nee Foo; Jianjun Liu; Jong-Won Kim; David G Cox; Olivier Delattre; Olivier Mirabeau; Christine F Skibola; Clara S Tang; Merce Garcia-Barcelo; Kai-Ping Chang; Wen-Hui Su; Yu-Sun Chang; Nicholas G Martin; Scott Gordon; Tracey D Wade; Chaeyoung Lee; Michiaki Kubo; Pei-Chieng Cha; Yusuke Nakamura; Daniel Levy; Masayuki Kimura; Shih-Jen Hwang; Steven Hunt; Tim Spector; Nicole Soranzo; Ani W Manichaikul; R Graham Barr; Bratati Kahali; Elizabeth Speliotes; Laura M Yerges-Armstrong; Ching-Yu Cheng; Jost B Jonas; Tien Yin Wong; Isabella Fogh; Kuang Lin; John F Powell; Kenneth Rice; Caroline L Relton; Richard M Martin; George Davey Smith
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9.  On the use of kernel machines for Mendelian randomization.

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10.  Assessing the linear and non-linear association of HbA1c with cardiovascular disease: a Mendelian randomisation study.

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