Guidelines for performing Mendelian randomization investigations: update for summer 2023

Burgess, Stephen; Smith, George Davey; Davies, Neil M; Dudbridge, Frank; Glymour, M. Maria; Hartwig, Fernando Pires; Kutalik, Zoltán; Holmes, Michael V; Minelli, Cosetta; Morrison, Jean; Pan, Wei; Relton, Caroline L; Τheodoratou, Evropi

doi:10.12688/wellcomeopenres.15555.3

Cited by 317 publications

(233 citation statements)

References 165 publications

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“…Guidelines for reporting and interpreting MR studies have been developed by expert consensus, and the Strengthening the Reporting of Observational Studies in Epidemiology initiative provides MRspecific guidance for authors (STROBE-MR). 7,31 In general, authors are…”

Section: Reporting and Interpreting Mr Resultsmentioning

confidence: 99%

“…Because most genetic association studies to date have been performed in individuals genetically similar to European reference populations, most MR studies have focused on this population. 7 While non-European populations remain underrepresented in MR, a recent multiancestry MR study 8 investigated the role of diabetes and circulating lipids as risk factors for ischemic stroke, finding similar effects among populations of African and European ancestry. Efforts to increase the representativeness and generalizability of MR findings to diverse populations are critically needed and ongoing.…”

Section: Weak Instrumentsmentioning

confidence: 99%

“…ing of Observational Studies in Epidemiology initiative provides MRspecific guidance for authors (STROBE-MR). 7,31 In general, authors are encouraged to explicitly consider the underlying assumptions of MR, provide justification for the instruments they select, and cautiously interpret findings. A helpful framework for reporting MR findings is to separate the reporting of results from subsequent inferences regarding potential causality.…”

Section: Selection and Survival Biasmentioning

confidence: 99%

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Mendelian Randomization as a Tool for Cardiovascular Research

Levin,

Burgess

2024

JAMA Cardiol

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ImportanceMendelian randomization (MR) is a statistical approach that has become increasingly popular in the field of cardiovascular disease research. It offers a way to infer potentially causal relationships between risk factors and outcomes using observational data, which is particularly important in cases where randomized clinical trials are not feasible or ethical. With the growing availability of large genetic data sets, MR has become a powerful and accessible tool for studying the risk factors for cardiovascular disease.ObservationsMR uses genetic variation associated with modifiable exposures or risk factors to mitigate biases that affect traditional observational study designs. The approach uses genetic variants that are randomly assigned at conception as proxies for exposure to a risk factor, mimicking a randomized clinical trial. By comparing the outcomes of individuals with different genetic variants, researchers may draw causal inferences about the effects of specific risk factors on cardiovascular disease, provided assumptions are met that address (1) the association between each genetic variant and risk factor and (2) the association of the genetic variants with confounders and (3) that the association between each genetic variant and the outcome only occurs through the risk factor. Like other observational designs, MR has limitations, which include weak instruments that are not strongly associated with the exposure of interest, linkage disequilibrium where genetic instruments influence the outcome via correlated rather than direct effects, overestimated genetic associations, and selection and survival biases. In addition, many genetic databases and MR studies primarily include populations genetically similar to European reference populations; improved diversity of participants in these databases and studies is critically needed.Conclusions and RelevanceThis review provides an overview of MR methodology, including assumptions, strengths, and limitations. Several important applications of MR in cardiovascular disease research are highlighted, including the identification of drug targets, evaluation of potential cardiovascular risk factors, as well as emerging methodology. Overall, while MR alone can never prove a causal relationship beyond reasonable doubt, MR offers a rigorous approach for investigating possible causal relationships in observational data and has the potential to transform our understanding of the etiology and treatment of cardiovascular disease.

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Section: Reporting and Interpreting Mr Resultsmentioning

confidence: 99%

Section: Weak Instrumentsmentioning

confidence: 99%

Section: Selection and Survival Biasmentioning

confidence: 99%

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Mendelian Randomization as a Tool for Cardiovascular Research

Levin,

Burgess

2024

JAMA Cardiol

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“…In addition, while family data are able to correct for biases due to AM-induced LD, it cannot account for biases due to other violations of the exclusion restriction such as horizontal pleiotropy. Care should be taken to critically evaluate whether each SNP included is reliable (Burgess et al 2019, Skrivankova 2021).…”

Section: Discussionmentioning

confidence: 99%

A General Approach to Adjusting Genetic Studies for Assortative Mating

Bilghese,

Manansala,

Jaishankar

et al. 2023

Preprint

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The effects of assortative mating (AM) on estimates from genetic studies has been receiving increasing attention in recent years. We extend existing AM theory to more general models of sorting and conclude that correct theory-based AM adjustments require knowledge of complicated, unknown historical sorting patterns. We propose a simple, general purpose approach using polygenic indexes (PGIs). Our approach can estimate the fraction of genetic variance and genetic correlation that is driven by AM. Our approach is less effective when applied to Mendelian randomization (MR) studies for two reasons: AM can induce a form of selection bias in MR studies that remains after our adjustment; and, in the MR context, the adjustment is particularly sensitive to PGI estimation error. Using data from the UK Biobank, we find that AM inflates genetic correlation estimates between health traits and education by 14% on average. Our results suggest caution in interpreting genetic correlations or MR estimates for traits subject to AM.

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“…Leverage Plot were employed to determine if any individual SNPs were detected as outliers or influential points in the MR analysis (33). To assess the validity and robustness of our results, we conducted several sensitivity analyses, including the MR-Egger, weighted median, simple mode, and weighted mode methods.…”

Section: Two-sample Mr Analysismentioning

confidence: 99%

Genetically predicted smoking behaviors on Graves’ disease: A two-sample mendelian randomization

Akbarzadeh,

Pourganji,

Tabashiri

et al. 2023

Preprint

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Background/AimThe potential link between smoking and the susceptibility to Graves’ disease (GD) has been scrutinized in observational studies, yielding inconsistent results. We conducted a Mendelian randomization (MR) analysis to ascertain the causal relationship between smoking behaviors and the risk of GD.MethodThe data on smoking behaviors, including smoking initiation and lifetime smoking, were obtained from the published GWAS of individuals of European descent who participated in the GSCAN consortium. The genetic variants associated with Graves’ disease were identified using a GWAS of 458,620 participants of European descent from the UK Biobank.ResultsOur results show that smoking initiation was associated with GD [OR= 1.50, 95% CI (1.03,2.18), SE□=□0.199, Pbeta□=□0.031; Cochran’s Q=36.62, p=0.999, I2=0.0%; MR–Eggerintercept= 0.003, p= 0.879], and lifetime smoking [OR□=□3.42, 95% CI (1.56, 7.50), SE□=□0.39, Pbeta<0.01; Cochran’s Q=62.68, p=0.99, I2=0.0%; Eggerintercept=0.012, p=0.49]. All other MR methods, as well as sensitivity analysis results, were consistent in terms of betas and significance levels.ConclusionOur findings lend support to a causal relationship between smoking behaviors and the risk of Graves’ disease. These observations raise important questions about the role of smoking in the progression of GD. So, further investigation is clinically necessary to clarify the links between smoking and GD, which could inform health policy decisions aimed at reducing the risk of GD.

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Guidelines for performing Mendelian randomization investigations: update for summer 2023

Cited by 317 publications

References 165 publications

Mendelian Randomization as a Tool for Cardiovascular Research

Mendelian Randomization as a Tool for Cardiovascular Research

A General Approach to Adjusting Genetic Studies for Assortative Mating

Genetically predicted smoking behaviors on Graves’ disease: A two-sample mendelian randomization

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