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Searching for the causal effects of body mass index in over 300 000 participants in UK Biobank, using Mendelian randomization

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  • Louise A C Millard
  • Neil M Davies
  • Kate Tilling
  • Tom R Gaunt
  • George Davey Smith

Abstract

Mendelian randomization (MR) has been used to estimate the causal effect of body mass index (BMI) on particular traits thought to be affected by BMI. However, BMI may also be a modifiable, causal risk factor for outcomes where there is no prior reason to suggest that a causal effect exists. We performed a MR phenome-wide association study (MR-pheWAS) to search for the causal effects of BMI in UK Biobank (n = 334 968), using the PHESANT open-source phenome scan tool. A subset of identified associations were followed up with a formal two-stage instrumental variable analysis in UK Biobank, to estimate the causal effect of BMI on these phenotypes. Of the 22 922 tests performed, our MR-pheWAS identified 587 associations below a stringent P value threshold corresponding to a 5% estimated false discovery rate. These included many previously identified causal effects, for instance, an adverse effect of higher BMI on risk of diabetes and hypertension. We also identified several novel effects, including protective effects of higher BMI on a set of psychosocial traits, identified initially in our preliminary MR-pheWAS in circa 115,000 UK Biobank participants and replicated in a different subset of circa 223,000 UK Biobank participants. Our comprehensive MR-pheWAS identified potential causal effects of BMI on a large and diverse set of phenotypes. This included both previously identified causal effects, and novel effects such as a protective effect of higher BMI on feelings of nervousness.Author summary: Mendelian randomization uses genetic variants associated with an exposure to investigate causality. For example, there are several genetic variants that have been robustly associated with body mass index, and these can be used to test whether body mass index causally affects other traits. Usually, Mendelian randomization studies focus on particular outcomes, for instance, estimating the causal effect of body mass index on blood pressure. However, a trait (such as body mass index) may be a modifiable, causal risk factor for outcomes where there is no prior reason to suggest that a causal effect exists. We recently published a novel tool called PHESANT, that allows comprehensive phenome scans to be performed, allowing researchers to search for the causal effects of a trait of interest across over 22,000 traits in UK Biobank. In this work we used PHESANT to search for the causal effects of body mass index. We identified previously established effects, for example, adverse effects of higher body mass index on risk of diabetes and hypertension. We also identified novel effects, such as a protective effect of higher body mass index on feelings of nervousness, and these need replicating in an independent sample and using other study designs.

Suggested Citation

  • Louise A C Millard & Neil M Davies & Kate Tilling & Tom R Gaunt & George Davey Smith, 2019. "Searching for the causal effects of body mass index in over 300 000 participants in UK Biobank, using Mendelian randomization," PLOS Genetics, Public Library of Science, vol. 15(2), pages 1-20, February.
  • Handle: RePEc:plo:pgen00:1007951
    DOI: 10.1371/journal.pgen.1007951
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    References listed on IDEAS

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    1. Børge G Nordestgaard & Tom M Palmer & Marianne Benn & Jeppe Zacho & Anne Tybjærg-Hansen & George Davey Smith & Nicholas J Timpson, 2012. "The Effect of Elevated Body Mass Index on Ischemic Heart Disease Risk: Causal Estimates from a Mendelian Randomisation Approach," PLOS Medicine, Public Library of Science, vol. 9(5), pages 1-13, May.
    2. Alastair J Noyce & Demis A Kia & Gibran Hemani & Aude Nicolas & T Ryan Price & Eduardo De Pablo-Fernandez & Philip C Haycock & Patrick A Lewis & Thomas Foltynie & George Davey Smith & International Pa, 2017. "Estimating the causal influence of body mass index on risk of Parkinson disease: A Mendelian randomisation study," PLOS Medicine, Public Library of Science, vol. 14(6), pages 1-19, June.
    3. Rebecca C Richmond & George Davey Smith & Andy R Ness & Marcel den Hoed & George McMahon & Nicholas J Timpson, 2014. "Assessing Causality in the Association between Child Adiposity and Physical Activity Levels: A Mendelian Randomization Analysis," PLOS Medicine, Public Library of Science, vol. 11(3), pages 1-16, March.
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    Cited by:

    1. Massaro, Alessandro & Giardinelli, Vito O. M. & Cosoli, Gabriele & Magaletti, Nicola & Leogrande, Angelo, 2022. "The Prediction of Hypertension Risk," MPRA Paper 113242, University Library of Munich, Germany.
    2. Jie Huang & Jennifer E. Huffman & Yunfeng Huang & Ítalo Valle & Themistocles L. Assimes & Sridharan Raghavan & Benjamin F. Voight & Chang Liu & Albert-László Barabási & Rose D. L. Huang & Qin Hui & Xu, 2022. "Genomics and phenomics of body mass index reveals a complex disease network," Nature Communications, Nature, vol. 13(1), pages 1-10, December.

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