Mendelian randomization

In the paper

“Triangulation of evidence from multiple methodologies — using different methodologies that are subject to different sources and directions of potential bias — can help to identify bias in MR studies.6,7,155 Alignment of results across these different methodologies can improve confidence in an initial causal interpretation.”

What the sources say

• Supported

  Split into 2 atoms — 2 confirmed, 0 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

  cites [6] Munafò, M. R., Higgins, J. P. & Davey Smith, G. Triangulating evidence through the inclusion of genetically informed designs. Cold Spring Harb. Perspect. Med. 11, a040659 (2021). source
• Not checked yetcites [7] Lawlor, D. A., Tilling, K. & Davey Smith, G. Triangulation in aetiological epidemiology. Int. J. Epidemiol. 45, 1866–1886 (2017).
• Partly supported

  Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

  cites [155] Davies, N. M. et al. Multivariable two-sample Mendelian randomization estimates of the effects of intelligence and education on health. eLife 8, e43990 (2019). sourceExperimental — accuracy not yet measured

In the paper

“MR can be applied using any genetic variation that satisfies the requirements of an IV,5 although it is most often implemented using single nucleotide polymorphisms (SNPs).”

What the sources say

• Not checked yetcites [5] Zuccolo, L. & Holmes, M. V. Commentary: Mendelian randomization-inspired causal inference in the absence of genetic data. Int. J. Epidemiol. 46, 962–965 (2017).

In the paper

“Using genetic variants in this way, MR avoids bias from unobserved confounding of the exposure and outcome.”

In the paper

“Genetic variants typically only explain a small proportion of the variation in the relevant phenotype; as a result, low statistical power and imprecise effect estimates are common in MR studies and well-powered studies usually require large datasets.”

In the paper

“MR was first proposed using the family data where the difference in alleles between siblings is random, however data limitations mean most MR is conducted using data on unrelated individuals.22”

What the sources say

• Not checked yetcites [22] Swanson, S. A., Tiemeier, H., Ikram, M. A. & Hernán, M. A. Nature as a trialist? Deconstructing the analogy between Mendelian randomization and randomized trials. Epidemiology 28, 653–659 (2017). source

In the paper

“IV analysis was first proposed a century ago and is an approach to causal inference that uses an IV, or “instrument” — which is related to the exposure but not the outcome of interest other than through its association with the exposure — to make causal effect estimates in the presence of unobserved confounding of the exposure and the outcome.”

What the sources say

• Not checked yetcites [2] Angrist, J. D., Imbens, G. W. & Rubin, D. B. Identification of causal effects using instrumental variables. J. Am. Stat. Assoc. 91, 444–455 (1996). source
• Not checked yetcites [3] Hernán, M. A. & Robins, J. M. Causal Inference: What If (Chapman & Hall/CRC, 2020).
• Not checked yetcites [4] Greenland, S. An introduction to instrumental variables for epidemiologists. Int. J. Epidemiol. 29, 722–729 (2000). source

In the paper

“In RCTs, randomly assigned treatment therefore evaluates the effect of treatment on the outcome, whereas in MR, a genetic variant is treated as a naturally occurring form of randomization.”

In the paper

“MR is especially appealing because it relies on different assumptions to conventional observational studies and therefore circumvents some of their common biases.8”

What the sources say

• Not checked yetcites [8] Richmond, R. C. & Davey Smith, G. Mendelian randomization: concepts and scope. Cold Spring Harb. Perspect. Med. https://doi.org/10.1101/cshperspect.a040501 (2022). source

In the paper

“Causal effect estimates from MR can be evaluated within a triangulation of evidence framework, which involves interpreting findings alongside results from complementary approaches that rely on different assumptions.”

What the sources say

• Not checked yetcites [6] Munafò, M. R., Higgins, J. P. & Davey Smith, G. Triangulating evidence through the inclusion of genetically informed designs. Cold Spring Harb. Perspect. Med. 11, a040659 (2021). source
• Not checked yetcites [7] Lawlor, D. A., Tilling, K. & Davey Smith, G. Triangulation in aetiological epidemiology. Int. J. Epidemiol. 45, 1866–1886 (2017).
• Not checked yetcites [8] Richmond, R. C. & Davey Smith, G. Mendelian randomization: concepts and scope. Cold Spring Harb. Perspect. Med. https://doi.org/10.1101/cshperspect.a040501 (2022). source

In the paper

“MR studies — especially two-sample studies using previously published summary-level genetic association data — provide a rapid and affordable approach to evaluating causal questions.”

In the paper

“The first three of these conditions are commonly referred to as the conditions for a valid instrumental variable and are required for any IV analysis to test whether the exposure has a causal effect on the outcome.”

In the paper

“The rationale of MR studies parallels that of RCTs in which randomization influences the treatment received by participants, is not associated with any confounders of the treatment and outcome and has no other plausible mechanism to influence health outcomes other than through treatment (see Fig. 1).”

In the paper

“The above example highlights an important difference between RCTs and MR: RCTs estimate the effect of a particular intervention or treatment over the timeframe of the study, whereas MR estimates the lifetime effects.21”

What the sources say

• Not checked yetcites [21] Morris, T. T., Heron, J., Sanderson, E., Davey Smith, G. & Tilling, K. Interpretation of Mendelian randomization using one measure of an exposure that varies over time. Preprint at medRxiv https://doi.org/10.1101/2021.11.18.21266515 (2021). source

In the paper

“Two methods, MR GxE and MR GENIUS, have extended and formalised these concepts and enable the estimation of causal effects in more general settings.”

What the sources say

• Not checked yetcites [76] Spiller, W., Slichter, D., Bowden, J. & Davey Smith, G. Detecting and correcting for bias in Mendelian randomization analyses using gene-by-environment interactions. Int. J. Epidemiol. 48, 702–712 (2019). source
• Not checked yetcites [77] Tchetgen Tchetgen, E. J., Sun, B. & Walter, S. The GENIUS approach to robust Mendelian randomization inference. Stat. Sci. 36, 443–464 (2019).
• Not checked yetcites [78] Burgess, S., Dudbridge, F. & Thompson, S. G. Combining information on multiple instrumental variables in Mendelian randomization: comparison of allele score and summarized data methods. Stat. Med. 35, 1880–1906 (2016). source

In the paper

“An alternative approach is to split the allele scores for each exposure into high and low values and compare outcomes across the resulting four groups by dividing participants up based on their score for each exposure, mimicking a 2x2 factorial randomised trial.”

In the paper

“The bias in this situation is equivalent to that caused by pleiotropy (see Fig. 3) and although it is unlikely that this pattern will arise at many independent genetic locations in MR studies with multiple IVs, it should be a consideration in single-IV studies.”

In the paper

“Although this involves an implicit assumption of directionality in its interpretation, the test is not dependent on this assumption and indeed a single pleiotropic variant would satisfy the statistical definition of a shared causal variants (Fig 6b).”

In the paper

“As with individual level data analysis, IV conditions need to be assessed for any summary-data MR.”

In the paper

“A number of different methods are available to correct for horizontal pleiotropy — a violation of the third IV condition — under different assumptions about the causal structure of that pleiotropy.”

In the paper

“Although the second and third IV conditions cannot be proven to be true, they can sometimes be disproven.”

In the paper

“Therefore, a few methods should be selected based on the most plausible assumptions for the application in question and used alongside an IVW MR estimation to perform a sensitivity analysis; this can determine how robust MR results are to the assumption that genetic variants have no pleiotropic effects on the outcome under different alternative specifications.”

In the paper

“None of the methods described above are truly robust to all types of pleiotropy and each imposes different assumptions on the nature of the pleiotropy and how the pleiotropic effects are accounted for.”

In the paper

“Results from bidirectional MR studies should be interpreted with caution. Evidence of an effect in both directions could indicate a true bidirectional relationship between the exposures or be a product of bias from horizontal pleiotropic effects in the variants, misspecification of the primary phenotype, or a violation of the second IV condition owing to confounding of genetic variants and outcome”

In the paper

“Traditionally, summary-data MR is visualized as a scatter plot plotting associations of the variant and exposure against associations of the variant and outcome (Fig 4a, b); however, this can limit the identification of outliers.”

In the paper

“Standard MR only provides a single effect estimate, which may not be informative if the effect of the exposure varies in a non-linear way — for example, a dose-response curve.”

In the paper

“Weighted scores provide increased instrument strength and power, although there are cases in which the unweighted approach is preferred — for example, if the definition of the exposure in the discovery dataset differs from the exposure variable in the estimation data.”

What the sources say

• Not checked yetcites [26] Davies, N. M. et al. The many weak instruments problem and Mendelian randomization. Stat. Med. 34, 454–468 (2015). source

In the paper

“Furthermore, many methods have less statistical power than conventional MR, leading to very wide confidence intervals.”

In the paper

“The inclusion of these additional terms decreases the statistical power for detecting an effect and should be limited to a single interaction.”

In the paper

“Non-linear MR has supported this, although it has also suggested that the J-shape could be caused by the relationship between BMI and mortality risk differing for ever-smokers [G] and never-smokers.109”

What the sources say

• Not checked yetcites [109] North, T.-L. et al. Using genetic instruments to estimate interactions in Mendelian randomization studies. Epidemiology 30, e33–e35 (2019). source

In the paper

“In bidirectional MR, two MR analyses are conducted on the same pair of phenotypes by reversing the exposure and the outcome. This method can be used to establish the direction of effect between two variables.”

In the paper

“Multiple, correlated exposures can be included in a multivariable MR; however, including multiple exposures can reduce power and potentially instrument strength and thus the benefit of adding extra exposures must be considered carefully.”

In the paper

“Ever larger GWAS have now provided evidence that hundreds of genetic variants may be associated with many human phenotypes.”

In the paper

“Multivariable MR is an extension of standard MR that includes multiple exposures, predicted by a set of genetic variants used as instruments.”

In the paper

“If many SNPs that each only have a small effect on the exposure are being used, combining them into a single score can increase the power of the analysis and reduce the risk of bias from many weak instruments.27”

What the sources say

• Not checked yetcites [27] Hernán, M. A. & Robins, J. M. Instruments for causal inference: an epidemiologist’s dream? Epidemiology 17, 360–372 (2006). source

In the paper

“This correlation between genetic variants and the outcome can potentially affect most (or all) of the genetic variants used as instruments; it is therefore not easy to correct for with current MR methods as most assume that the majority of genetic variants satisfy all of the IV conditions.61”

What the sources say

• Not checked yetcites [61] Davey Smith, G. & Hemani, G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Hum. Mol. Genet. 23, R89–R98 (2014). source

In the paper

“Pre-registration of study protocols has not been widely adopted in observational epidemiology, although it could in principle be applied and help protect against bias, such as publication bias against null results or findings that do not fit with the anticipated conclusion.161,162”

What the sources say

• Not checked yetcites [161] Brumpton, B. et al. Avoiding dynastic, assortative mating, and population stratification biases in Mendelian randomization through within-family analyses. Nat. Commun. 11, 3519 (2020). source
• Not checked yetcites [162] Morris, T. T., Davies, N. M., Hemani, G. & Davey Smith, G. Population phenomena inflate genetic associations of complex social traits. Sci. Adv. 6, eaay0328 (2020). source

In the paper

“In addition to physiological consequences, body weight has social consequences such increasing exposure to stigma and discrimination and these MR analyses include the consequences of all such mechanisms for hospitalization costs.”

In the paper

“Within-family MR requires data from either pairs of siblings or mother–father–child trios and allows for estimation of causal effects using MR after family-level structure has been taken into account.164,167”

What the sources say

• Not checked yetcites [164] Davies, N. M. et al. Within family Mendelian randomization studies. Hum. Mol. Genet. 28, R170–R179 (2019). source
• Not checked yetcites [167] Taylor, A. E. et al. Exploring the association of genetic factors with participation in the Avon Longitudinal Study of Parents and Children. Int. J. Epidemiol. 47, 1207–1216 (2018). source

In the paper

“Thus, available evidence from MR methods that facilitate estimation in the presence of unobserved confounding — assuming no selection bias — do not support the conclusion that the consumption of a moderate amount of alcohol may lower vascular disease risk and identify alcohol consumption as a factor linked to increased likelihood of ischemic stroke”

In the paper

“Open research can increase the robustness of data through allowing greater scrutiny of data and increased error detection by researchers and the wider research community.”

In the paper

“Within MR, using methods that make different assumptions (such as those regarding pleiotropy) and are therefore subject to different sources and directions of potential bias can support this approach, although the least plausible assumption may be shared by many methods, reducing the potential independent insight to be gained from comparing studies.”

In the paper

“Alternatively, Bayesian frameworks for colocalization analysis consider GWAS summary statistics for both traits across multiple SNPs in the region around the IV and assess either the evidence that each variant is jointly causal115 or consider shared causal variants as one of five competing hypotheses.116”

What the sources say

• Not checked yetcites [115] Giambartolomei, C. et al. Bayesian test for colocalisation between pairs of genetic association studies using summary statistics. PLoS Genet. 10, e1004383 (2014). source
• Not checked yetcites [116] Wallace, C. Eliciting priors and relaxing the single causal variant assumption in colocalisation analyses. PLoS Genet. 16, e1008720 (2020). source

In the paper

“However, population stratification, dynastic effects and assortative mating all induce bias by creating an artefactual relation at the population level between the genetic variants and the outcome, violating the second IV condition.65,163–166”

What the sources say

• Not checked yetcites [65] Sargan, J. D. The estimation of economic relationships using instrumental variables. Econometrica 26, 393–415 (1958). source
• Not checked yetcites [163] Minică, C. C., Boomsma, D. I., Dolan, C. V., de Geus, E. & Neale, M. C. Empirical comparisons of multiple Mendelian randomization approaches in the presence of assortative mating. Int. J. Epidemiol. 49, 1185–1193 (2020). source
• Not checked yetcites [164] Davies, N. M. et al. Within family Mendelian randomization studies. Hum. Mol. Genet. 28, R170–R179 (2019). source
• Not checked yetcites [165] Minică, C. C., Dolan, C. V., Boomsma, D. I., de Geus, E. & Neale, M. C. Extending causality tests with genetic instruments: an integration of Mendelian randomization with the classical twin design. Behav. Genet. 48, 337–349 (2018). source
• Not checked yetcites [166] Howe, L. J. et al. Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects. Nat. Genet. (in the press).

In the paper

“However, it must be noted that MR studies are themselves not free from issues of bias or lack of power; evidence from MR studies for the presence or absence of an effect should be compared with results from studies with other potential sources of bias.”

In the paper

“Using genetic variants associated with higher BMI as instruments in an individual-level MR study to estimate the effect of BMI on hospitalization costs,147 the authors found that higher BMI increased hospital costs with little evidence for non-linearity in this effect.”

What the sources say

• Not checked yetcites [147] Holmes, M. V. Human genetics and drug development. N. Engl. J. Med. 380, 1076–1079 (2019). source

In the paper

“This suggests that for children that are overweight, losing weight in their adulthood can still effectively lower risk of T2D and CAD and in this case a metabolically unhealthy childhood can potentially be offset by healthy lifestyle approaches adopted in adulthood.”

In the paper

“Study participation has shown to be heritable and is influenced by a number of different traits, and large studies such as the UK Biobank have been shown to have high levels of selection in those who participate.31,170–172”

What the sources say

• Not checked yetcites [31] Davey Smith, G. Epigenesis for epidemiologists: does evo-devo have implications for population health research and practice? Int. J. Epidemiol. 41, 236–247 (2012). source
• Not checked yetcites [170] Smit, R. A., Trompet, S., Dekkers, O. M., Jukema, J. W. & le Cessie, S. Survival bias in Mendelian randomization studies: a threat to causal inference. Epidemiology 30, 813 (2019). source
• Not checked yetcites [171] Schooling, C. M. et al. Use of multivariable Mendelian randomization to address biases due to competing risk before recruitment. Front. Genet. 11, 610852 (2020). source
• Not checked yetcites [172] Vansteelandt, S., Dukes, O. & Martinussen, T. Survivor bias in Mendelian randomization analysis. Biostatistics 19, 426–443 (2017). source

In the paper

“Gene expression and protein are often instrumented with a single genetic variant and so colocalization can be particularly useful in MR studies of these exposures;42 in these settings colocalization can be used to attempt to falsify the second IV condition.”

What the sources say

• Not checked yetcites [42] Bound, J., Jaeger, D. A. & Baker, R. M. Problems with instrumental variables estimation when the correlation between the instruments and the endogenous explanatory variable is weak. J. Am. Stat. Assoc. 90, 443–450 (1995).

In the paper

“Indeed, where data already exists, MR studies are relatively cheap to conduct — particularly compared to a large RCT — and can provide additional evidence that can be used to direct which studies are worth follow up with RCTs.”

In the paper

“An example is the J-shaped association between alcohol consumption and cardiovascular disease; there is now consensus that this apparent protective effect of moderate levels of consumption is artefactual, as discussed above.130”

What the sources say

• Not checked yetcites [130] Goldstein, J. L. & Brown, M. S. A century of cholesterol and coronaries: from plaques to genes to statins. Cell 161, 161–172 (2015). source

In the paper

“In the context of epidemiological research, one area of concern is that findings may be replicated in settings with nearly identical sources of bias. Data with such replication provide little independent confirmation of the initial result and thus even highly consistent replicated findings may not reflect true causal effects.”

In the paper

“For example, although MR studies have shown that smoking causes lung cancer186, this is not useful therapeutically following the onset of the disease as smoking cessation is not a useful treatment once lung cancer has developed.”

What the sources say

• Not checked yetcites [186] Davey Smith, G., Paternoster, L. & Relton, C. When will Mendelian randomization become relevant for clinical practice and public health? JAMA 317, 589–591 (2017). source

In the paper

“Although the increasing size of GWAS datasets appears to be positive for MR studies, it can also introduce problems; smaller and smaller effect sizes are being identified as significant in GWAS and it is increasingly likely that such variants affect the trait of interest through an upstream phenotype that might in turn influence the outcomes under investigation.”

In the paper

“When initially presented, it was concluded that “[MR] offers a more robust approach to understanding the effect of some modifiable exposures on health outcomes than does much conventional observational epidemiology”1 and that where possible, RCTs should follow to establish the effects of interventions. This conclusion remains unchanged, although moving towards formal triangulation of all pertinent”

What the sources say

• Not checked yetcites [1] Davey Smith, G. & Ebrahim, S. ‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease? Int. J. Epidemiol. 32, 1–22 (2003). source

In the paper

“The situation with MR is now moving towards the one seen in the meta-analysis literature, with the mass production of redundant, misleading, and conflicted publications.183”

What the sources say

• Not checked yetcites [183] Zhou, W. et al. Causal relationships between body mass index, smoking and lung cancer: univariable and multivariable Mendelian randomization. Int. J. Cancer 148, 1077–1086 (2021). source

In the paper

“These are relatively easy to conduct — perhaps too easy — and they can contain clear errors as discussed and demonstrated elsewhere.81”

What the sources say

• Not checked yetcites [81] Bowden, J. et al. Improving the visualization, interpretation and analysis of two-sample summary data Mendelian randomization via the radial plot and radial regression. Int. J. Epidemiol. 47, 1264–1278 (2018). source

In the paper

“For example, as the GWAS of CRP and vitamin D increased in size, multiple variants that primarily influence adiposity were identified — with adiposity being a confounder of the observational association of these exposures with health outcomes.”

In the paper

“Finally, MR uses genetic variants that are fixed across the life course to estimate the lifetime effects of the exposure of interest. This introduces a potential limitation in the form of canalization, which refers to a natural tendency for the suppression of phenotypic variation among individuals despite contrasting genotypes.”

In the paper

“Papers reporting two-sample MR have grown rapidly over recent years and now constitute a large majority of published studies.8,81”

What the sources say

• Not checked yetcites [8] Richmond, R. C. & Davey Smith, G. Mendelian randomization: concepts and scope. Cold Spring Harb. Perspect. Med. https://doi.org/10.1101/cshperspect.a040501 (2022). source
• Not checked yetcites [81] Bowden, J. et al. Improving the visualization, interpretation and analysis of two-sample summary data Mendelian randomization via the radial plot and radial regression. Int. J. Epidemiol. 47, 1264–1278 (2018). source

In the paper

“This means that although MR has been a powerful tool for confirming or discovering factors that cause disease, it does not often identify therapeutic targets.185”

What the sources say

• Not checked yetcites [185] Kim, Y.-I. Role of folate in colon cancer development and progression. J. Nutr. 133, 3731S–3739S (2003). source

In the paper

“For example, the onset and progression of Crohn’s disease are associated with different genetic variants, indicating that different risk factors play a role in onset and development.187”

What the sources say

• Not checked yetcites [187] Ye, T., Shao, J. & Kang, H. Debiased inverse-variance weighted estimator in two-sample summary-data Mendelian randomization. Ann. Stat. 49, 2079–2100 (2021).

In the paper

“This can influence the generalizability of MR findings and exacerbate existing inequity in medical research.”

In the paper

“As most contemporary MR studies rely on available GWAS data, they unfortunately suffer from considerable bias with respect to representativeness of populations according to geography and ancestry.184”

What the sources say

• Not checked yetcites [184] Lee, J. C. et al. Genome-wide association study identifies distinct genetic contributions to prognosis and susceptibility in Crohn’s disease. Nat. Genet. 49, 262–268 (2017). source

In the paper

“All forms of selection biases could bias MR estimates and so careful assessment of the potential for selection into the sample or samples used in an MR study is important.65”

What the sources say

• Not checked yetcites [65] Sargan, J. D. The estimation of economic relationships using instrumental variables. Econometrica 26, 393–415 (1958). source

In the paper

“In addition, most studies recruit survivors of the original birth cohorts. This means all participants must have survived in order to observe whether they get the outcome of interest. Selection of participants on surviving their genetic make-up and the outcome of interest or a competing risk of the outcome effectively applies covariable adjustment on survival into the estimates.173–175”

What the sources say

• Not checked yetcites [173] Hernán, M. A. Invited commentary: selection bias without colliders. Am. J. Epidemiol. 185, 1048–1050 (2017). source
• Not checked yetcites [174] Mahmoud, O., Dudbridge, F., Davey Smith, G., Munafo, M. & Tilling, K. Slope-Hunter: a robust method for index-event bias correction in genome-wide association studies of subsequent traits. Nat. Commun. (in the press).
• Not checked yetcites [175] Waddington, C. H. Canalization of development and the inheritance of acquired characters. Nature 150, 563–565 (1942). source

In the paper

“The resulting bias can be accounted for through multivariable MR if the upstream factor is known; however, in many cases it is not and thus bias will remain undetected.”

In the paper

“This form of selection bias is likely to be particularly problematic for studies of harmful exposures on disease outcomes that occur in later life and will be least evident in studies where the exposure does not affect survival to recruitment.176”

What the sources say

• Not checked yetcites [176] Debat, V. & David, P. Mapping phenotypes: canalization, plasticity and developmental stability. Trends Ecol. Evol. 16, 555–561 (2001). source

In the paper

“Importantly, case-only study designs may be severely compromised by collider bias[[G] 56,64, which must be taken into account in data analysis185.”

What the sources say

• Not checked yetcites [56] Hernán, M. A., Hernández-Díaz, S. & Robins, J. M. A structural approach to selection bias. Epidemiology 15, 615–625 (2004). source
• Not checked yetcites [64] Hughes, R. A., Davies, N. M., Davey Smith, G. & Tilling, K. Selection bias when estimating average treatment effects using one-sample instrumental variable analysis. Epidemiology 30, 350–357 (2019). source
• Not checked yetcites [185] Kim, Y.-I. Role of folate in colon cancer development and progression. J. Nutr. 133, 3731S–3739S (2003). source