Challenges in undertaking nonlinear Mendelian randomization
Mendelian randomization (MR) is a widely used method that exploits the unique properties of germline genetic variation to strengthen causal inference in relationships between exposures and outcomes. Nonlinear MR allows estimation of the shape of these relationships. In a previous paper, the authors...
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| Vydané v: | Obesity (Silver Spring, Md.) Ročník 31; číslo 12; s. 2887 - 2890 |
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| Hlavní autori: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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United States
Blackwell Publishing Ltd
01.12.2023
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| ISSN: | 1930-7381, 1930-739X, 1930-739X |
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| Abstract | Mendelian randomization (MR) is a widely used method that exploits the unique properties of germline genetic variation to strengthen causal inference in relationships between exposures and outcomes. Nonlinear MR allows estimation of the shape of these relationships. In a previous paper, the authors applied linear and nonlinear MR to estimate the effect of BMI on mortality in UK Biobank, providing evidence for a J‐shaped association. However, it is now clear that there are problems with widely used nonlinear MR methods, which draws attention to the likely erroneous nature of the conclusions regarding the shapes of several explored relationships. Here, the authors explore the utility and likely biases of these nonlinear MR methods with the use of a negative control design. Although there remains good evidence for a causal effect of higher BMI increasing the risk of mortality, the pattern of this association across different levels of BMI requires further characterization. |
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| AbstractList | Mendelian randomization (MR) is a widely used method that exploits the unique properties of germline genetic variation to strengthen causal inference in relationships between exposures and outcomes. Nonlinear MR allows estimation of the shape of these relationships. In a previous paper, the authors applied linear and nonlinear MR to estimate the effect of BMI on mortality in UK Biobank, providing evidence for a J-shaped association. However, it is now clear that there are problems with widely used nonlinear MR methods, which draws attention to the likely erroneous nature of the conclusions regarding the shapes of several explored relationships. Here, the authors explore the utility and likely biases of these nonlinear MR methods with the use of a negative control design. Although there remains good evidence for a causal effect of higher BMI increasing the risk of mortality, the pattern of this association across different levels of BMI requires further characterization. Mendelian randomization (MR) is a widely used method that exploits the unique properties of germline genetic variation to strengthen causal inference in relationships between exposures and outcomes. Nonlinear MR allows estimation of the shape of these relationships. In a previous paper, the authors applied linear and nonlinear MR to estimate the effect of BMI on mortality in UK Biobank, providing evidence for a J-shaped association. However, it is now clear that there are problems with widely used nonlinear MR methods, which draws attention to the likely erroneous nature of the conclusions regarding the shapes of several explored relationships. Here, the authors explore the utility and likely biases of these nonlinear MR methods with the use of a negative control design. Although there remains good evidence for a causal effect of higher BMI increasing the risk of mortality, the pattern of this association across different levels of BMI requires further characterization.Mendelian randomization (MR) is a widely used method that exploits the unique properties of germline genetic variation to strengthen causal inference in relationships between exposures and outcomes. Nonlinear MR allows estimation of the shape of these relationships. In a previous paper, the authors applied linear and nonlinear MR to estimate the effect of BMI on mortality in UK Biobank, providing evidence for a J-shaped association. However, it is now clear that there are problems with widely used nonlinear MR methods, which draws attention to the likely erroneous nature of the conclusions regarding the shapes of several explored relationships. Here, the authors explore the utility and likely biases of these nonlinear MR methods with the use of a negative control design. Although there remains good evidence for a causal effect of higher BMI increasing the risk of mortality, the pattern of this association across different levels of BMI requires further characterization. |
| Author | Hamilton, Fergus W. Sattar, Naveed Timpson, Nicholas J. Wade, Kaitlin H. Carslake, David Davey Smith, George |
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| Cites_doi | 10.1016/S2213-8587(22)00344-8 10.1016/S2213-8587(22)00345-X 10.1101/2023.08.21.23293658 10.1002/gepi.22041 10.1101/cshperspect.a040501 10.1136/bmj.k1767 10.1136/bmj.l1042 10.1016/S2213-8587(21)00263-1 10.1002/oby.22313 10.1016/S2213‐8587(23)00198‐5 |
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| References_xml | – volume: 12 start-page: a040501 year: 2022 article-title: Mendelian randomization: concepts and scope publication-title: Cold Spring Harb Perspect Med – volume: 9 start-page: 837 year: 2021 end-page: 846 article-title: Estimating dose‐respons relationships for vitamin D with coronary heart disease, stroke, and all‐cause mortality: observational and Mendelian randomisation analyses publication-title: Lancet Diabetes Endocrinol – volume: 26 start-page: 1796 year: 2018 end-page: 1806 article-title: BMI and mortality in UK Biobank: revised estimates using Mendelian randomization publication-title: Obesity (Silver Spring) – year: 2023 publication-title: Non‐linear Mendelian randomization: evaluation of biases using negative controls with a focus on BMI and vitamin D. medRxiv – volume: 11 start-page: 14 year: 2023 article-title: Mendelian randomisation and vitamin D: the importance of model assumptions publication-title: Lancet Diabetes Endocrinol – volume: 11 start-page: 15 year: 2023 end-page: 16 article-title: Mendelian randomisation and vitamin D: the importance of model assumptions–Authors' reply publication-title: Lancet Diabetes Endocrinol. – volume: 41 start-page: 341 year: 2017 end-page: 352 article-title: Semiparametric methods for estimation of a nonlinear exposure‐outcome relationship using instrumental variables with application to Mendelian randomization publication-title: Genet Epidemiol – volume: 364 year: 2019 article-title: Body mass index and all cause mortality in HUNT and UK Biobank studies: linear and non‐linear Mendelian randomisation analyses publication-title: BMJ – volume: 11 year: 2023 article-title: Expression of Concern—Estimating dose‐response relationships for vitamin D with coronary heart disease, stroke, and all‐cause mortality: observational and Mendelian randomisation analyses publication-title: Lancet Diabetes Endocrinol. – volume: 361 year: 2018 article-title: Role of obesity in smoking behaviour: Mendelian randomisation study in UK Biobank publication-title: BMJ – ident: e_1_2_3_7_1 doi: 10.1016/S2213-8587(22)00344-8 – ident: e_1_2_3_8_1 doi: 10.1016/S2213-8587(22)00345-X – ident: e_1_2_3_11_1 doi: 10.1101/2023.08.21.23293658 – ident: e_1_2_3_3_1 doi: 10.1002/gepi.22041 – ident: e_1_2_3_2_1 doi: 10.1101/cshperspect.a040501 – ident: e_1_2_3_6_1 doi: 10.1136/bmj.k1767 – ident: e_1_2_3_5_1 doi: 10.1136/bmj.l1042 – ident: e_1_2_3_9_1 doi: 10.1016/S2213-8587(21)00263-1 – ident: e_1_2_3_4_1 doi: 10.1002/oby.22313 – ident: e_1_2_3_10_1 doi: 10.1016/S2213‐8587(23)00198‐5 |
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| Title | Challenges in undertaking nonlinear Mendelian randomization |
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