Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomisation (STROBE-MR): explanation and elaboration.
Open accessAbstract
Mendelian randomisation (MR) studies allow a better understanding of the causal effects of modifiable exposures on health outcomes, but the published evidence is often hampered by inadequate reporting. Reporting guidelines help authors effectively communicate all critical information about what was done and what was found. STROBE-MR (strengthening the reporting of observational studies in epidemiology using mendelian randomisation) assists authors in reporting their MR research clearly and transparently. Adopting STROBE-MR should help readers, reviewers, and journal editors evaluate the quality of published MR studies. This article explains the 20 items of the STROBE-MR checklist, along with their meaning and rationale, using terms defined in a glossary. Examples of transparent reporting are used for each item to illustrate best practices.
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Written from the paper’s full text.
TL;DR
STROBE-MR is a 20-item reporting checklist for Mendelian randomisation (MR) studies, and this article explains each item and provides examples of transparent reporting. It aims to help authors, reviewers, and journal editors communicate and appraise MR studies more clearly.
Key findings
- STROBE-MR comprises 20 reporting items covering title/abstract, introduction, methods, results, discussion, and other information; it was developed by an expert group and revised after a July 2019 preprint and debate at the 4th International Mendelian Randomisation Conference.
- The paper states that empirical evidence indicates many MR reports do not clearly state or examine MR assumptions and report insufficient details on data sources, making quality and reliability difficult to evaluate.
- This explanation and elaboration document explains the rationale of each checklist item and uses published MR studies as examples of transparent reporting; the examples are not necessarily ideal but highlight the intended issue for each item.
- The authors encourage MR study authors, reviewers, and journal editors to use STROBE-MR to improve reporting.
Methods
- Guideline development: the initiative was established in 2018 following guidance for developing medical research reporting guidelines; an expert group met face-to-face in Bristol, UK, over two days in May 2019 to discuss empirical evidence and draft checklist items.
- The draft checklist was published as a preprint in July 2019, debated on the preprint platform, social media, and at the 4th International Mendelian Randomisation Conference, then revised.
- This article is an explanation and elaboration document complementing the STROBE-MR statement; it explains the 20 checklist items using a glossary and examples identified from published MR studies, with some examples edited by removing citations and unrelated sections.
Limitations
- The paper states that STROBE-MR is not intended as a formal tool for assessing methodological or reporting quality and should not be transformed into a quality scale; it is also not a formal guideline to design and conduct MR studies.
- The paper states that some items will not apply to MR studies that do not use an instrument for the exposure or do not report instrumental variable estimates, though the checklist still provides useful guidance.
- The paper states that the examples do not necessarily represent the ideal statement for each checklist item; evident from the text, this is a consensus/guideline explanation and elaboration without reported empirical validation of whether STROBE-MR improves reporting quality.
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Claims the paper makes
0 of 101 cited sources checked · 0 supported · 0 flagged
- Findingcitation
Many reports of Mendelian randomisation studies do not clearly state or examine the various assumptions of Mendelian randomisation methods.
“Empirical evidence22 23 24 indicates that many reports of MR studies do not clearly state or examine the various assumptions of MR methods”
Quote in the paperSubstantial claim0 of 3 sources checked - Findingcitation
Many reports of Mendelian randomisation studies report insufficient details on the data sources.
“and report insufficient details on the data sources”
Quote in the paperSubstantial claim0 of 3 sources checked - Findingreasoning
The quality of reporting of Mendelian randomisation studies has been inconsistent.
“As a result, the quality of reporting of these studies has been inconsistent.”
Quote in the paperSubstantial claim0 of 3 sources checked - Premisecitation
Associations reported in epidemiological studies can be produced by confounding.
“and can be produced by confounding (that is, by another factor that affects both the outcome and exposure)1 2 3”
Quote in the paperSubstantial claim0 of 3 sources checked - Interpretationreasoning
Genetic variants are generally not influenced by the outcome and therefore, by reverse causation.
“Similarly, genetic variants are generally not influenced by the outcome and therefore, by reverse causation.”
Quote in the paperSubstantial claim- Rests on an assumption: Genetic variation is essentially randomly inherited from parents to offspring at conception.
- Premisecitation
Published evidence from Mendelian randomisation studies is often hampered by inadequate reporting.
“but the published evidence is often hampered by inadequate reporting”
Quote in the paperSubstantial claim0 of 3 sources checked - Premisecitation
Ill health could be related to a reduction or cessation of alcohol consumption, introducing potential bias due to reverse causality, when interest is in studying the effect of alcohol consumption on subsequent health.
“In turn, ill health could be related to a reduction or cessation of alcohol consumption, introducing potential bias due to reverse causality, when interest is in studying the effect of alcohol consumption on subsequent health.4 5”
Quote in the paperSubstantial claim0 of 2 sources checked - Interpretationreasoning
Mendelian randomisation provides an opportunity to study the association between exposures and outcomes while reducing potential bias from confounding and reverse causation.
“MR thus provides an opportunity to study the association between exposures and outcomes while reducing potential bias from confounding and reverse causation.9”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [9] source
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- Rests on an assumption: Genetic variation is essentially randomly inherited from parents to offspring at conception.
- Premisecitation
Genetic variations can be used as instrumental variables to analyse the effect of modifiable exposures on diseases through Mendelian randomisation.
“These genetic variations can be used as instrumental variables to analyse the effect of modifiable exposures on diseases through a study method termed mendelian randomisation (MR).8”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [8] source
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- Interpretationreasoning
Many factors that confound the association between the exposure and outcome cannot affect the genetic variants.
“and consequently, many factors that confound the association between the exposure and outcome cannot affect the genetic variants.”
Quote in the paperSubstantial claim- Rests on an assumption: Genetic variation is essentially randomly inherited from parents to offspring at conception.
- Premisecitation
Associations reported in epidemiological studies can be produced by other forms of bias.
“or by other forms of bias.”
Quote in the paperSubstantial claim0 of 3 sources checked - Premisecitation
Associations reported in epidemiological studies are often not reliable estimates of causal effects.
“However, such associations reported in epidemiological studies are often not reliable estimates of causal effects”
Quote in the paperSubstantial claim0 of 3 sources checked - Interpretationreasoning
For Mendelian randomisation studies that do not use an instrument for the exposure or do not report instrumental variable estimates, some items of STROBE-MR will not apply.
“some items of STROBE-MR will not apply”
Quote in the paperSubstantial claim - Premisecitation
Most MR studies rely on three core IV assumptions (relevance, independence, and exclusion restriction) to carry out testing for causal effects of the exposure on the outcome.
“Most MR studies rely on three core IV assumptions (relevance, independence, and exclusion restriction; fig 1, box 3) to carry out testing for causal effects of the exposure on the outcome.16”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [16] source
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- The authors state this as an assumption: Relevance: genetic variant G is associated with the exposure of interest X.
- The authors state this as an assumption: Independence: genetic variant G shares no unmeasured cause with outcome Y.
- The authors state this as an assumption: Exclusion restriction: genetic variant G does not affect outcome Y except through its potential effect on the exposure of interest X.
- Premisecitation
Negative control outcomes or negative control populations can sometimes evaluate the reasonableness of the independence assumption.
“Negative control outcomes or negative control populations can sometimes evaluate the reasonableness of the assumption.66”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [66] source
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- The authors state this as an assumption: Independence: genetic variant G shares no unmeasured cause with outcome Y.
- Premisecitation
Little consensus exists around the reporting of Mendelian randomisation studies.
“Despite the growth in MR applications and methods and the increasing relevance of MR findings, little consensus exists around the reporting of MR studies.”
Quote in the paperSubstantial claim0 of 3 sources checked - Premisenone given
Most MR studies are designed to assess a specific hypothesis that has arisen from previous studies.
“While some authors have used MR to test the effect of exposures on many different outcomes without prior hypotheses,37 most MR studies are designed to assess a specific hypothesis that has arisen from previous studies.”
Quote in the paperNot a substantial claim - Interpretationcitation
The insufficient reporting of assumptions and data sources makes the quality and reliability of the results difficult to evaluate.
“which makes the quality and reliability of the results difficult to evaluate.”
Quote in the paperSubstantial claim - Interpretationreasoning
A large E value could help support that confounding by ancestry is unlikely to explain a non-null effect.
“A large E value could help support that confounding by ancestry is unlikely to explain a non-null effect.”
Quote in the paperNot a substantial claim - Premisecitation
Bidirectional MR can be used to orient the causal direction(s) of effect.
“Bidirectional MR can be used to orient the causal direction(s) of effect.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [102] source
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- Premisecitation
The use of negative control outcomes or negative control populations might also allow evaluation of the exclusion restriction assumption.
“The use of negative control outcomes or negative control populations might also allow evaluation of this assumption.70”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [70] source
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- The authors state this as an assumption: Exclusion restriction: genetic variant G does not affect outcome Y except through its potential effect on the exposure of interest X.
- Premisereasoning
Similarity of the two samples can be violated if genetic associations were estimated in pre-menopausal versus post-menopausal women, or in a population-based sample versus a high-risk sample.
“Similarity of the two samples can also be violated if, for example, genetic associations were estimated in pre-menopausal versus post-menopausal women, or in a population based sample versus a high risk sample.”
Quote in the paperNot a substantial claim - Interpretationreasoning
If the associations are similar in the two samples, heterogeneity in the associations of the SNPs with the exposure and the outcome is less likely to cause bias.
“If the associations are similar in the two samples, heterogeneity in the associations of the SNPs with the exposure and the outcome is less likely to cause bias.”
Quote in the paperSubstantial claim - Premisecitation
A funnel plot, in which causal effect estimates for variants are plotted against their precisions, can be used to perform a visual inspection for asymmetry, which might indicate horizontal pleiotropy.
“A funnel plot, in which causal effect estimates for variants are plotted against their precisions, can be used to perform a visual inspection for asymmetry, which might indicate horizontal pleiotropy.55”
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- Interpretationreasoning
The winner's curse bias in two-sample MR can be overcome by using entirely separate samples to select SNPs and estimate SNP-outcome associations.
“This bias can be overcome by using entirely separate samples to select SNPs and estimate SNP-outcome associations.”
Quote in the paperNot a substantial claim - Interpretationcitation
If the authors used the same or similar individuals to estimate the SNP-exposure and SNP-outcome associations, MR estimates could be biased by a form of the winner's curse.
“If the authors used the same or similar individuals to estimate the SNP-exposure and the SNP-outcome associations, MR estimates could be biased by a form of the winner’s curse,94 95 which occurs when the statistically strongest associations—usually using a P value threshold—are selected from the discovery sample.”
Quote in the paperNot a substantial claim0 of 2 sources checked - Premisecitation
Forest plots, which plot the causal estimate obtained from each genetic variant, allow for a visual inspection of heterogeneity around the overall causal estimate.
“Forest plots, which plot the causal estimate obtained from each genetic variant, allow for a visual inspection of heterogeneity around the overall causal estimate.84”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [84] source
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- Premisecitation
When many variants are included in the allele score, bias and coverage probabilities of the instrumental variable estimates are improved compared with estimates from the two stage least squares approach.
“When many variants are included in the score, bias and coverage probabilities of the instrumental variable estimates are improved compared with estimates from the two stage least squares approach.80”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [80] source
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- Premisecitation
Many of the traditional bias analytical techniques in epidemiology can be adapted for MR readily, including the calculations from formulas for understanding the magnitude and direction of confounding bias or for violations of the exclusion restriction.
“Many of the traditional bias analytical techniques in epidemiology can be adapted for MR readily, including the calculations from formulas for understanding the magnitude and direction of confounding bias59 67 68 69 75 or for violations of the exclusion restriction.59 76”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites 59 67 68 69 75
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- cites 59 76
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- The authors state this as an assumption: Relevance: genetic variant G is associated with the exposure of interest X.
- The authors state this as an assumption: Independence: genetic variant G shares no unmeasured cause with outcome Y.
- The authors state this as an assumption: Exclusion restriction: genetic variant G does not affect outcome Y except through its potential effect on the exposure of interest X.
- The authors state this as an assumption: The exposure has the same effects in everyone (homogeneity).
- Premisecitation
Cochran's Q and I2 statistics can be used to assess evidence of heterogeneity of causal effects estimated by each of the genetic variants.
“Cochran’s Q and I2 statistics can be used to assess evidence of heterogeneity of causal effects estimated by each of the genetic variants.100”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [100] source
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- Premisecitation
Another relatively straightforward joint test of all assumptions comes from comparing the effect estimate with that obtained by use of a more traditional confounding-adjustment approach.
“Another relatively straightforward joint test of all assumptions comes from comparing the effect estimate with that obtained by use of a more traditional confounding-adjustment approach.73”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [73] source
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- The authors state this as an assumption: Relevance: genetic variant G is associated with the exposure of interest X.
- The authors state this as an assumption: Independence: genetic variant G shares no unmeasured cause with outcome Y.
- The authors state this as an assumption: Exclusion restriction: genetic variant G does not affect outcome Y except through its potential effect on the exposure of interest X.
- The authors state this as an assumption: The exposure has the same effects in everyone (homogeneity).
- Premisenone given
When using multiple genetic variants as proposed instruments, it is possible to test whether heterogeneity exists across the separate effect estimates.
“When using multiple genetic variants as proposed instruments, it is possible to test whether heterogeneity exists across the separate effect estimates (see Test for difference, table 2).”
Quote in the paperNot a substantial claim- The authors state this as an assumption: Relevance: genetic variant G is associated with the exposure of interest X.
- The authors state this as an assumption: Independence: genetic variant G shares no unmeasured cause with outcome Y.
- The authors state this as an assumption: Exclusion restriction: genetic variant G does not affect outcome Y except through its potential effect on the exposure of interest X.
- Premisecitation
Additional approaches to test the exclusion restriction include weighted median and mode.
“Additional approaches to test the exclusion restriction include weighted median56 and mode.57”
Quote in the paperNot a substantial claim0 of 2 sources checked- The authors state this as an assumption: Exclusion restriction: genetic variant G does not affect outcome Y except through its potential effect on the exposure of interest X.
- Interpretationreasoning
Evidence of heterogeneity suggests that there is at least one proposed instrument for which at least one of the instrumental variable assumptions fails to hold.
“Evidence of heterogeneity suggests that there is at least one proposed instrument for which at least one of the instrumental variable assumptions fails to hold.”
Quote in the paperNot a substantial claim - Interpretationcitation
The fact that similar estimates are seen in this regard for a wide variety of non-overlapping sets of instruments constructed to match pharmaceutical agents for LDL cholesterol lowering adds robustness to the interpretation.
“The fact that similar estimates are seen in this regard for a wide variety of non-overlapping sets of instruments constructed to match pharmaceutical agents for LDL cholesterol lowering adds robustness to the interpretation.112”
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- Interpretationcitation
This difference seen between estimates relating to lifetime differences and shorter term cholesterol lowering is anticipated from the known cumulative effect of lipids on atherosclerotic coronary disease.
“This difference seen between estimates relating to lifetime differences and shorter term cholesterol lowering is anticipated from the known cumulative effect of lipids on atherosclerotic coronary disease.112”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [112] source
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- Premisecitation
A common reason why MR estimates do not have a straightforward causal interpretation is because it is unclear whether the gene-environment equivalence assumption is plausible.
“A common reason why MR estimates do not have a straightforward causal interpretation is because it is unclear whether the gene-environment equivalence assumption (table 2) is plausible”
Quote in the paperSubstantial claim - Premisereasoning
The often lifelong influence of genetic variants can be different from the environmental influences investigated in conventional epidemiological studies that are generally experienced at defined stages of later life.
“The often lifelong influence of genetic variants can be different from the environmental influences investigated in conventional epidemiological studies that are generally experienced at defined stages of later life.”
Quote in the paperSubstantial claim - Interpretationcitation
If the homogeneity assumption cannot be made, but the monotonicity assumption is plausible, then the causal estimate can be used to represent the local average treatment effect.
“If the homogeneity assumption cannot be made, but the monotonicity assumption is plausible, then the causal estimate can be used to represent the local average treatment effect.86”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [86] source
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- Interpretationnone given
If the MR estimate was derived from a population subgroup, it might not be generalisable beyond that subgroup.
“Further, if the MR estimate was derived from a population subgroup, it might not be generalisable beyond that subgroup.”
Quote in the paperNot a substantial claim - Premisereasoning
Instrumental variable estimates will also be more precise when estimated from larger datasets, because the standard error for the SNP effect estimates, used to calculate the instrumental variable estimate, will be smaller.
“Instrumental variable estimates will also be more precise when estimated from larger datasets, because the standard error for the SNP effect estimates, used to calculate the instrumental variable estimate, will be smaller.”
Quote in the paperNot a substantial claim - Interpretationcitation
If the exposure is a dichotomisation of a continuous risk factor, this poses a further threat to the violation of the exclusion restriction assumption.
“Also, if the exposure is a dichotomisation of a continuous risk factor, this poses a further threat to the violation of the exclusion restriction assumption.114”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [114] source
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- Interpretationcitation
In two sample MR studies with exposure samples containing only a small number of participants who have experienced the exposure, the causal effect estimate reflects the effects of the genetic liability to the exposure rather than the exposure itself.
“For example, when two sample MR studies are carried out in exposure samples that contain only a small number of participants who have experienced the exposure in question, it would be misleading to interpret the effects as being those of the exposure itself. Instead, the causal effect estimate should be interpreted as reflecting the effects of the genetic liability to the exposure.115 116”
Quote in the paperSubstantial claim0 of 2 sources checked - Premisecitation
It is possible to separate the effects of body mass index in childhood and adulthood on a variety of health outcomes using different instruments for the two exposure periods.
“For example, it is possible to separate the effects of body mass index in childhood and adulthood on a variety of health outcomes using different instruments for the two exposure periods.111”
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- Interpretationcitation
If the effect of an exposure on an outcome is cumulative over many years, MR can overestimate the effect when compared to short term interventions.
“Likewise, if the effect of an exposure on an outcome is cumulative over many years, MR can overestimate the effect when compared to short term interventions.60 119”
Quote in the paperNot a substantial claim0 of 2 sources checked - Interpretationreasoning
Differing effects over the life course do not lessen the potential use of MR estimates.
“Differing effects over the life course do not lessen the potential use of MR estimates.”
Quote in the paperNot a substantial claim - Interpretationnone given
If the homogeneity assumption is plausible, along with the other assumptions, then the causal estimate will represent the average causal effect of the exposure on the outcome in the studied population.
“If the homogeneity assumption is plausible, along with the other assumptions (box 2), then the causal estimate will represent the average causal effect of the exposure on the outcome in the studied population.”
Quote in the paperSubstantial claim - Interpretationreasoning
If the effect of the exposure on the outcome is time dependent, or only occurs during a critical period, MR estimates could be misleading if used to guide future interventions if they occur outside of this time frame.
“For example, if the effect of the exposure on the outcome is time dependent, or only occurs during a critical period, MR estimates could be misleading if used to guide future interventions if they occur outside of this time frame.”
Quote in the paperSubstantial claim
- May combine two claims. 38
- Classified as probably not a substantial claim. 103
- The quote only partly states this claim. 1
May combine two claims.
InterpretationreasoningThese features make genetic variants suitable candidates as instrumental variables, which can help estimate the causal effects of modifiable exposures on outcomes.
“These features make genetic variants suitable candidates as instrumental variables, which can help estimate the causal effects of modifiable exposures on outcomes.7”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [7] source
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- Rests on an assumption: Genetic variation is essentially randomly inherited from parents to offspring at conception.
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisenone givenMendelian randomisation is not limited to studies using genetic variants to generate instrumental variable estimates.
“MR is not limited to studies using genetic variants to generate instrumental variable estimates (box 1, table 1); however, these studies dominate the literature.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenMendelian randomisation studies allow a better understanding of the causal effects of modifiable exposures on health outcomes.
“Mendelian randomisation (MR) studies allow a better understanding of the causal effects of modifiable exposures on health outcomes”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe term "mendelian randomisation" was introduced in 1991 for investigations of bone marrow transplantation in the treatment of childhood malignancies.
“Indeed, the term “mendelian randomisation” was introduced in 1991 for investigations of bone marrow transplantation in the treatment of childhood malignancies.11 12”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [11] Gray, 1991, How to avoid bias when comparing bone marrow transplantation with chemotherapy, Bone Marrow Transplant
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- cites [12] Davey Smith G. Capitalising on Mendelian randomization to assess the effects of treatments. 2006. https://www.jameslindlibrary.org/articles/capitalising-on-mendelian-randomization-to-assess-the-effects-of-treatments/
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InterpretationreasoningHaving an HLA compatible sibling (as a matter of chance) could also serve as a genetic instrument for bone marrow transplantation, and so might be used to infer effects of transplantation on cancer outcomes.
“Having an HLA compatible sibling (as a matter of chance) could also serve as a genetic instrument for bone marrow transplantation, and so might be used to infer effects of transplantation on cancer outcomes.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim.
Interpretationnone givenSTROBE-MR assists authors in reporting their Mendelian randomisation research clearly and transparently.
“STROBE-MR (strengthening the reporting of observational studies in epidemiology using mendelian randomisation) assists authors in reporting their MR research clearly and transparently.”
Quote in the paperSubstantial claim- Rests on an assumption: Reporting guidelines help authors effectively communicate all critical information about what was done and what was found.
May combine two claims.
PremisecitationConcerns about violations of the independence assumption usually focus on confounding by ancestry (or population stratification), but it can also be violated by various forms of selection or collider bias, by dynastic effects, or by assortative mating.
“Concerns about violations of the independence assumption usually focus on confounding by ancestry (or population stratification). However, it can also be violated by various forms of selection or collider bias, by dynastic effects, or by assortative mating.62 63 64”
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- The authors state this as an assumption: Independence: genetic variant G shares no unmeasured cause with outcome Y.
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Premisenone givenStudy methods could evolve over time.
“Also, study methods could evolve over time.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
PremisereasoningReaders need information on the population(s) studied, setting, and locations to assess the context and generalisability of the study results.
“Readers need information on the population(s) studied, setting, and locations to assess the context and generalisability of the study results.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationcitationThe inclusion of variants in high linkage disequilibrium might not contribute additional information in estimating the causal effect, and could even lead to biased estimates of standard errors if this correlation structure is not accounted for.
“The inclusion of variants in high linkage disequilibrium might not contribute additional information in estimating the causal effect, and could even lead to biased estimates of standard errors if this correlation structure is not accounted for.47”
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Premisenone givenThe STROBE-MR guidelines are aimed at the currently large majority of Mendelian randomisation studies that are implemented within an instrumental variable framework.
“The STROBE-MR (strengthening the reporting of observational studies in epidemiology using mendelian randomisation) guidelines are aimed at the (currently) large majority of MR studies that are implemented within an instrumental variable framework.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisenone givenSources of data could be from meta-analyses of multiple samples.
“Furthermore, sources of data could be from meta-analyses of multiple samples.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationMR Egger regression relaxes the exclusion restriction assumption but imposes an InSIDE assumption that the size of the direct effects of the genetic variants on the outcome that do not operate through the exposure are independent of the size of the genetic variants' effects on the exposure.
“MR Egger regression relaxes the exclusion restriction assumption but imposes an InSIDE assumption that the size of the direct effects of the genetic variants on the outcome that do not operate through the exposure are independent of the size of the genetic variants’ effects on the exposure.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [55] source
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- The authors state this as an assumption: The size of the direct effects of the genetic variants on the outcome that do not operate through the exposure are independent of the size of the genetic variants’ effects on the exposure (InSIDE).
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
Premisenone givenArticulating the assumptions also motivates sensitivity analyses and other additional analyses used to assess the assumptions or the robustness of conclusions to their violations.
“Articulating the assumptions also motivates sensitivity analyses and other additional analyses used to assess the assumptions or the robustness of conclusions to their violations.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationPower calculations provide information about sample sizes needed to obtain appropriate power for desired precision of the effect estimate.
“Power calculations provide information about sample sizes needed to obtain appropriate power for desired precision of the effect estimate,43 44”
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Premisenone givenSome MR studies draw on multiple sources of data, such as different sources for the ascertainment of the association between the genetic variant and exposure and for the association between the genetic variant and outcome.
“Some MR studies draw on multiple sources of data (eg, different sources for the ascertainment of the association between the genetic variant and exposure, and for the association between the genetic variant and outcome).”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
PremisecitationInstrumental variable estimation to obtain effect estimates imposes a fourth assumption, typically effect homogeneity or monotonicity.
“When instrumental variable estimation is used to obtain effect estimates, a fourth assumption should then be stated: typically, an assumption of effect homogeneity53 or monotonicity.54”
Quote in the paperSubstantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.
Premisenone givenThe two sample MR approach assumes that the association between the genetic variants and the exposure is the same in the two samples, which might not hold if samples are selected from different subpopulations (eg, by sex, age, ethnicity).
“Additionally, the two sample MR approach assumes that the association between the genetic variants and the exposure is the same in the two samples, which might not hold if samples are selected from different subpopulations (eg, by sex, age, ethnicity).”
Quote in the paperNot a substantial claim- The authors state this as an assumption: The association between the genetic variants and the exposure is the same in the two samples (two sample MR).
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisenone givenIn a two sample MR study, one stage can use summary data and another stage can use individual level data.
“In a two sample MR study, one stage can use summary data and another stage can use individual level data.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
PremisecitationPresenting critical elements of study design early in the article allows readers to orient themselves on the study basics.
“As in STROBE,26 presenting critical elements of study design early in the article allows readers to orient themselves on the study basics.”
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Premisenone givenThe STROBE-MR reporting guidelines are meant to apply to studies that use properties of germline genetic variants to strengthen causal inference regarding possible effects of potentially modifiable exposures on outcomes.
“The STROBE-MR reporting guidelines are meant to apply to studies that use properties of germline genetic variants to strengthen causal inference regarding possible effects of potentially modifiable exposures on outcomes.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe STROBE guidelines for observational research were developed for the three main study designs in epidemiology: cohort, case-control, and cross sectional studies.
“The STROBE (strengthening the reporting of observational studies in epidemiology) guidelines for observational research25 26 were developed for the three main study designs in epidemiology (cohort, case-control, and cross sectional studies).”
Quote in the paperNot a substantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Premisenone givenMR can be used to test causal null hypotheses or estimate point, period, or lifetime effects.
“MR can be used to test causal null hypotheses or estimate point, period, or lifetime effects.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationEstimating effect sizes through the instrumental variable approach imposes a fourth assumption, usually homogeneity of effects of the exposure on the outcome.
“Estimating effect sizes through the instrumental variable approach imposes a fourth assumption, usually homogeneity of effects of the exposure on the outcome.16 58 59 60”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites [16] source
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- cites 58 59 60
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- The authors state this as an assumption: The exposure has the same effects in everyone (homogeneity).
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Premisenone givenOther aspects, such as temporal stability of association, population specificity, or biological plausability, could help understand the selected genetic variants' validity to be used as instrumental variables.
“Other aspects, such as temporal stability of association, population specificity, or biological plausability, could help understand the selected genetic variants’ validity to be used as instrumental variables.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningSome STROBE items are either too general or do not apply to Mendelian randomisation studies, while other items relevant to Mendelian randomisation studies are missing.
“Some STROBE items are either too general or do not apply to MR studies, while other items relevant to MR studies are missing.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
Premisenone givenWhen planning a study or interpreting the analysis results, information about the sample size is essential.
“When planning a study or interpreting the analysis results, information about the sample size is essential.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
InterpretationreasoningStatistical power is best ascertained by examination of the 95% confidence intervals of the estimates, since they require fewer assumptions than pre-experiment power calculations.
“Statistical power is best ascertained by examination of the 95% confidence intervals of the estimates, since they require fewer assumptions than pre-experiment power calculations.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductcitationThe STROBE-MR initiative was established in 2018, following guidance for the development of medical research reporting guidelines.
“Described in detail elsewhere,27 we established this initiative in 2018, following guidance for the development of medical research reporting guidelines.28”
Quote in the paperNot a substantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Premisenone givenWhen multiple variants are used in the analysis, these assumptions pertain to each of the variants.
“When multiple variants are used in the analysis, these assumptions pertain to each of the variants.”
Quote in the paperNot a substantial claim- The authors state this as an assumption: Relevance: genetic variant G is associated with the exposure of interest X.
- The authors state this as an assumption: Independence: genetic variant G shares no unmeasured cause with outcome Y.
- The authors state this as an assumption: Exclusion restriction: genetic variant G does not affect outcome Y except through its potential effect on the exposure of interest X.
Probably not a substantial claim: may not pass S2 (checkable).
PremisereasoningExplicitly stating the three core instrumental variable assumptions, ideally in the methods sections, can help readers to understand the underlying premises of the MR method, and to allow them to judge their validity.
“Explicitly stating the three core instrumental variable assumptions, ideally in the methods sections, can help readers to understand the underlying premises of the MR method, and to allow them to judge their validity.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
Premisenone givenFor two sample MR, this information will often require referring to supplementary material presented in previously published articles.
“For two sample MR, this information will often require referring to supplementary material presented in previously published articles.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Premisenone givenTwo sample Mendelian randomisation studies are most commonly conducted with summary level data, where the weights are derived from the first sample and then applied in the second sample to estimate the gene-outcome association.
“Two sample MR studies are most commonly conducted with summary level data, where the weights are derived from the first sample, which are then applied in the second sample to estimate the gene-outcome association.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationThe exclusion restriction is sometimes also referred to as an assumption of no horizontal pleiotropy, but it can be violated in several other ways, including by gene-exposure interaction, by having some form of time varying exposures, by measurement error in the exposure that is related to the instrument, or by a multi-component exposure.
“The exclusion restriction is sometimes also referred to as an assumption of no horizontal pleiotropy (box 3), but it can be violated in several other ways (eg, by gene-exposure interaction, by having some form of time varying exposures, by measurement error in the exposure that is related to the instrument or by a multi-component exposure).59”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [59] source
Not checked in the free run.
- The authors state this as an assumption: Exclusion restriction: genetic variant G does not affect outcome Y except through its potential effect on the exposure of interest X.
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisenone givenThe F statistic can also be approximated using summary level data.
“The F statistic can also be approximated using summary level data.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
InterpretationreasoningOther study designs, such as twin studies, also use the basic principles of mendelian genetics and so can be considered a form of Mendelian randomisation.
“Other study designs, such as twin studies, also use the basic principles of mendelian genetics and so can be considered a form of MR.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisereasoningThe independence assumption cannot be directly verified, but it can be partially assessed in many research settings.
“The independence assumption cannot be directly verified, but it can be partially assessed in many research settings.”
Quote in the paperNot a substantial claim- The authors state this as an assumption: Independence: genetic variant G shares no unmeasured cause with outcome Y.
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
PremisereasoningProviding a description of the ancestry of the participants will help understand potential sources of heterogeneity and generalisability of results.
“Providing a description of the ancestry of the participants will help understand potential sources of heterogeneity and generalisability of results.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Premisenone givenExposures such as environmental factors and therapies can change over time.
“Exposures such as environmental factors and therapies can change over time.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
Premisenone givenDetailed descriptions of the study participants and sampling frame help readers understand the applicability of the results.
“Detailed descriptions of the study participants and sampling frame help readers understand the applicability of the results.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationReporting the F statistic, if individual level data are available, provides several advantages for understanding the risk of weak instrument bias.
“Reporting the F statistic, if individual level data are available, provides several advantages for understanding the risk of weak instrument bias.65”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [65] source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationThe homogeneity assumption can also be replaced by imposing a monotonicity assumption that an increase in the number of risk alleles does not lower the likelihood of exposure for any individuals, typically leading to estimating an effect in a subgroup of the study population.
“The homogeneity assumption can also be replaced by imposing a monotonicity assumption that an increase in the number of risk alleles does not lower the likelihood of exposure for any individuals, typically leading to estimating an effect in a subgroup of the study population.61”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [61] source
Not checked in the free run.
- The authors state this as an assumption: An increase in the number of risk alleles does not lower the likelihood of exposure for any individuals (monotonicity).
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
PremisecitationReporting associations between measured covariates that might confound the variant-outcome association can also prove helpful, particularly if scaled by instrument strength or presented alongside a related bias analytical approach.
“Reporting associations between measured covariates that might confound the variant-outcome association can also prove helpful, particularly if scaled by instrument strength67 68 or presented alongside a related bias analytical approach.69”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites 67 68
Not checked in the free run.
- cites [69] source
Not checked in the free run.
- The authors state this as an assumption: Independence: genetic variant G shares no unmeasured cause with outcome Y.
Classified as probably not a substantial claim.
Premisenone givenMendelian randomisation only provides estimates intended to inform understanding of causal associations under specific assumptions.
“The word “causal” should be used carefully, because MR only provides estimates intended to inform our understanding of causal associations under specific assumptions.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based). May combine two claims.
Premisenone givenIn case-control studies, the choice of cases and controls is crucial to interpreting the results, and the method of their selection has major implications for study validity.
“In case-control studies, the choice of cases and controls is crucial to interpreting the results, and the method of their selection has major implications for study validity.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
PremisereasoningProviding information on the ascertainment of genotypes and their quality control will enable readers to assess the quality of the genetic variants used in the study.
“Providing information on the ascertainment of genotypes and their quality control will enable readers to assess the quality of the genetic variants used in the study.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
PremisereasoningKnowing when a study took place and over what period participants were recruited and followed up puts the study in historical context, which is essential for interpreting results.
“Knowing when a study took place and over what period participants were recruited and followed up puts the study in historical context, which is essential for interpreting results.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). The quote only partly states this claim.
PremisereasoningWhen homogeneity and monotonicity assumptions do not hold, the estimation is replaced by testing for a non-null effect.
“Instead, the estimation is replaced by testing for a non-null effect.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationnone givenAlthough the heterogeneity test is often interpreted as an assessment of the exclusion restriction, it is jointly testing the exclusion restriction, independence, and homogeneity assumptions.
“Although this test is often interpreted as an assessment of the exclusion restriction, it is jointly testing the exclusion restriction, independence, and homogeneity assumptions.”
Quote in the paperSubstantial claim- The authors state this as an assumption: Relevance: genetic variant G is associated with the exposure of interest X.
- The authors state this as an assumption: Independence: genetic variant G shares no unmeasured cause with outcome Y.
- The authors state this as an assumption: Exclusion restriction: genetic variant G does not affect outcome Y except through its potential effect on the exposure of interest X.
- The authors state this as an assumption: The exposure has the same effects in everyone (homogeneity).
Probably not a substantial claim: may not pass S3 (load-bearing).
Premisenone givenEvidence on the consistency of the genetic variant's association with the exposure or outcome helps to understand the degree of heterogeneity of effects.
“Evidence on the consistency of the genetic variant’s association with the exposure or outcome helps to understand the degree of heterogeneity of effects.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim. May combine two claims.
Premisenone givenMany assumptions underlying Mendelian randomisation cannot be verified, but there are methods available to attempt to falsify them.
“While many assumptions cannot be verified, there are methods available to attempt to falsify them.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
Interpretationnone givenIf the homogeneity and monotonicity assumptions do not hold, it might be preferable not to report the estimates and outline this situation.
“However, if the homogeneity and monotonicity assumptions do not hold, it might be preferable not to report the estimates and outline this situation.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
PremisereasoningReaders can assess group differences better if the descriptive statistics are provided for each category separately.
“Readers can assess group differences better if the descriptive statistics are provided for each category separately.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing). May combine two claims.
Premisenone givenDistributions of continuous variables are easily summarised by mean and standard deviation, or by median and percentile range in case of asymmetrical distribution.
“Distributions of continuous variables are easily summarised by mean and standard deviation, or by median and percentile range (eg, 25th and 75th percentiles) in case of asymmetrical distribution.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
Premisenone givenInformation on study participants helps readers understand the target population and assess the validity and generalisability of results.
“Information on study participants will help readers understand the target population and assess the validity and generalisability of results.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.
PremisereasoningA global exploration of the homogeneity assumption can examine any differences in variance of a continuous outcome across the genetic instrument; the extent of such differences provides evidence as to extent of violation of the homogeneity assumption.
“Furthermore, a global exploration of the homogeneity assumption can examine any differences in variance of a continuous outcome across the genetic instrument; the extent of such differences provides evidence as to extent of violation of the homogeneity assumption.”
Quote in the paperNot a substantial claim- The authors state this as an assumption: The exposure has the same effects in everyone (homogeneity).
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
Premisenone givenReporting on the association between the genetic variant and the outcome is useful because it can provide an initial indication about the possibility of a causal association between the exposure and outcome.
“Reporting on the association between the genetic variant and the outcome is useful because it can provide an initial indication about the possibility of a causal association between the exposure and outcome.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
Interpretationnone givenIf the results from all the approaches are largely consistent, authors can have more confidence in drawing robust conclusions regarding the presence and magnitude of a causal effect.
“If the results from all the approaches are largely consistent, author can have more confidence in drawing robust conclusions regarding the presence and magnitude of a causal effect.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisenone givenIndependent replication of MR findings in an independent dataset or with a different study design (eg, one sample v two sample MR) is typically advocated to assess the findings' robustness.
“Independent replication of MR findings in an independent dataset or with a different study design (eg, one sample v two sample MR) is typically advocated to assess the findings’ robustness.”
Quote in the paperNot a substantial claim- The authors state this as an assumption: Relevance: genetic variant G is associated with the exposure of interest X.
- The authors state this as an assumption: Independence: genetic variant G shares no unmeasured cause with outcome Y.
- The authors state this as an assumption: Exclusion restriction: genetic variant G does not affect outcome Y except through its potential effect on the exposure of interest X.
- The authors state this as an assumption: The exposure has the same effects in everyone (homogeneity).
Classified as probably not a substantial claim.
PremisereasoningReporting the association between the genetic variant and the exposure is required to evaluate the relevance assumption.
“Reporting the association between the genetic variant and the exposure is required to evaluate the relevance assumption (item 8b).”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisenone givenThe use of known biological effects of a SNP can also be leveraged to decrease the probability of violation of the exclusion restriction assumption.
“The use of known biological effects of a SNP can also be leveraged to decrease the probability of violation of this assumption.”
Quote in the paperNot a substantial claim- The authors state this as an assumption: Exclusion restriction: genetic variant G does not affect outcome Y except through its potential effect on the exposure of interest X.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe E value can be used to understand the degree to which unmeasured confounding might explain findings.
“The E value69 can be used to understand the degree to which unmeasured confounding might explain findings.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [69] source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.
Premisenone givenThe first three core assumptions pertain to any MR analysis with a single instrument; the additional assumptions are needed for instrumental variable estimation.
“The first three core assumptions pertain to any MR analysis with a single instrument; the additional assumptions are needed for instrumental variable estimation.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisenone givenComparing levels of exposure across the genotype distribution can indicate monotonicity and linearity of the genetic effect.
“Comparing levels of exposure across the genotype distribution can also indicate monotonicity and linearity of the genetic effect.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
Premisenone givenInformation on the distribution of the exposure, outcomes, and other variables helps judge the comparability of groups and generalisability of the findings.
“Information on the distribution of the exposure, outcomes, and other variables helps judge the comparability of groups and generalisability of the findings.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisenone givenAn allele score could be weighted or unweighted.
“An allele score could be weighted or unweighted.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.
Premisenone givenEach study design has different types of biases and could have different degrees of statistical power.
“Each study design has different types of biases and could have different degrees of statistical power.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
PremisecitationSimulations might also help understand the plausible size and direction of bias induced by assortative mating, dynastic effects, and time varying effects, if deemed relevant.
“Simulations might also help understand the plausible size and direction of bias induced by assortative mating,62 dynastic effects,9 63 and time varying effects,77 if deemed relevant.”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites [62] source
Not checked in the free run.
- cites 9 63
Not checked in the free run.
- cites [77] source
Not checked in the free run.
- The authors state this as an assumption: Relevance: genetic variant G is associated with the exposure of interest X.
- The authors state this as an assumption: Independence: genetic variant G shares no unmeasured cause with outcome Y.
- The authors state this as an assumption: Exclusion restriction: genetic variant G does not affect outcome Y except through its potential effect on the exposure of interest X.
- The authors state this as an assumption: The exposure has the same effects in everyone (homogeneity).
Classified as probably not a substantial claim. May combine two claims.
Interpretationnone givenIf the instrumental variable assumptions are not apparently falsified and are generally supported, or sensitivity analyses are robust to violation of the assumptions, then estimates from the MR analysis can be reported in a meaningful manner.
“If the instrumental variable assumptions are not apparently falsified and are generally supported, or sensitivity analyses are robust to violation of the assumptions (item 8b), then estimates from the MR analysis can be reported in a meaningful manner, preferably on an intuitive scale (eg, relative risk, risk difference).”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Premisenone givenExclusion restriction is relaxed in sensitivity analyses such as MR Egger regression.
“Exclusion restriction is relaxed in sensitivity analyses such as MR Egger regression.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenWider adoption of pre-registration methods should increase the accuracy, transparency, and robustness of MR studies.
“Wider adoption of these methods should increase the accuracy, transparency, and robustness of MR studies.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationMR Egger regression can be used to detect certain versions of pleiotropy and therefore provide evidence of certain violations of the exclusion restriction.
“For the exclusion restriction assumption, MR Egger regression55 can be used to detect certain versions of pleiotropy and therefore provide evidence of certain violations of the exclusion restriction.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [55] source
Not checked in the free run.
- The authors state this as an assumption: Exclusion restriction: genetic variant G does not affect outcome Y except through its potential effect on the exposure of interest X.
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
InterpretationreasoningPutting the MR results in context will help readers understand if the strengths and weaknesses of MR allow for results that support or contradict previous evidence.
“Putting the MR results in context will help readers understand if the strengths and weaknesses of MR allow for results that support or contradict previous evidence.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing). May combine two claims.
PremisereasoningInformation on study participants provides readers with the information needed to replicate the study and to assess whether the study is likely to show collider bias.
“It also provides readers with the information needed to replicate the study and to assess whether the study is likely to show collider bias.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisenone givenAny transformations made in the quantitative variables (that is, exposure, outcome, or relevant covariates) affect both interpretation of results and their comparability with other studies.
“Any transformations made in the quantitative variables (that is, exposure, outcome, or relevant covariates) should be explicitly mentioned, because they affect both interpretation of results and their comparability with other studies.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationPlots can be useful for examining potential violations of the instrumental variable assumptions, especially for the exclusion restriction assumption.
“Plots can be useful for examining potential violations of the instrumental variable assumptions, especially for the exclusion restriction assumption.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
Premisenone givenNumbers and percentages best describe categorical variables.
“Numbers and percentages best describe categorical variables.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Premisenone givenTwo-sample MR analyses assume that the SNP-exposure associations are similar in the two samples.
“Two sample MR analyses assume that the SNP-exposure associations are similar in the two samples.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based). May combine two claims.
Premisenone givenThe homogeneity assumption requires that the exposure has the same effects in everyone, which is not directly verifiable.
“The homogeneity assumption requires that the exposure has the same effects in everyone, which is not directly verifiable.”
Quote in the paperNot a substantial claim- The authors state this as an assumption: The exposure has the same effects in everyone (homogeneity).
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.
InterpretationreasoningA measure of absolute risk can provide an estimate of the excess amount of disease that can be attributed to the exposure over a particular period, which can then be used to estimate the absolute benefit of an intervention aimed at reducing levels of the exposure.
“A measure of absolute risk can provide an estimate of the excess amount of disease that can be attributed to the exposure over a particular period, which can then be used to estimate the absolute benefit of an intervention aimed at reducing levels of the exposure.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Premisenone givenIf the estimation is based on a meta-analysis, the number of included studies helps determine if tests for heterogeneity are properly powered to detect its presence.
“If the estimation is based on a meta-analysis, the number of included studies will also help determine if tests for heterogeneity are properly powered to detect its presence.”
Quote in the paperNot a substantial claimMay combine two claims.
Premisenone givenAssociations with measured covariates and effect estimates across subpopulations can be reported with one-sample MR studies, but generally not with two-sample MR studies.
“Associations with measured covariates (eg, age, sex, and race or ethnic origin) and effect estimates across subpopulations can be reported with one sample MR studies, but generally not with two sample MR studies”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Interpretationnone givenThe inclusion of multiple variants with missing data in the estimation of causal effects could decrease precision.
“The inclusion of multiple variants with missing data in the estimation of causal effects could decrease precision.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationWhen selection bias is a concern, researchers also frequently conduct simulations to understand the plausible size and direction of bias.
“When selection bias is a concern, researchers also frequently conduct simulations to understand the plausible size and direction of bias.64”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [64] source
Not checked in the free run.
- The authors state this as an assumption: Relevance: genetic variant G is associated with the exposure of interest X.
- The authors state this as an assumption: Independence: genetic variant G shares no unmeasured cause with outcome Y.
- The authors state this as an assumption: Exclusion restriction: genetic variant G does not affect outcome Y except through its potential effect on the exposure of interest X.
- The authors state this as an assumption: The exposure has the same effects in everyone (homogeneity).
Classified as probably not a substantial claim.
PremisecitationBecause several of the estimators using multiple genetic variants rely on different versions of relaxing or adapting the instrumental variable assumptions, a comparison of estimates obtained using each of these approaches can help understand the sensitivity of effect estimates to the non-overlapping assumptions of each.
“Because several of the estimators using multiple genetic variants rely on different versions of relaxing or adapting the instrumental variable assumptions (eg, MR Egger, median based, or modal based estimators), a comparison of estimates obtained using each of these approaches can help understand the sensitivity of effect estimates to the non-overlapping assumptions of each.74”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [74]
Not checked in the free run.
- The authors state this as an assumption: Relevance: genetic variant G is associated with the exposure of interest X.
- The authors state this as an assumption: Independence: genetic variant G shares no unmeasured cause with outcome Y.
- The authors state this as an assumption: Exclusion restriction: genetic variant G does not affect outcome Y except through its potential effect on the exposure of interest X.
- The authors state this as an assumption: The exposure has the same effects in everyone (homogeneity).
Classified as probably not a substantial claim.
Interpretationnone givenIn two-sample Mendelian randomisation, differences in the use of covariates between the genetic variant-exposure and genetic variant-outcome associations could lead to bias.
“For a two sample analysis, authors should state the covariates used to estimate the genetic variant-exposure and genetic variant-outcome associations to assess any differences in the use of covariates between the two associations, which could lead to bias.”
Quote in the paperSubstantial claimClassified as probably not a substantial claim. May combine two claims.
Interpretationnone givenSensitivity analyses can test the robustness of effect estimates to plausible violations of the underlying assumptions and help understand the plausible size or direction of bias.
“Sensitivity analyses can test the robustness of effect estimates to plausible violations of the underlying assumptions and help understand the plausible size or direction of bias.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
InterpretationreasoningIn some instances, the interpretation of estimates in terms of absolute risks or risk differences rather than relative risk differences might be more clinically meaningful, by taking into account the baseline risk.
“In some instances, the interpretation of estimates in terms of absolute risks or risk differences rather than relative risk differences might be more clinically meaningful, by taking into account the baseline risk.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationOne possibility for supporting the validity of the homogeneity assumption is to determine whether the effect estimate, or even the genetic variants' effects on the exposure, is the same across subpopulations.
“One possibility for supporting its validity is to determine whether the effect estimate, or even the genetic variants’ effects on the exposure, is the same across subpopulations.67 71”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites 67 71
Not checked in the free run.
- The authors state this as an assumption: The exposure has the same effects in everyone (homogeneity).
May combine two claims.
Premisenone givenThe MR Egger approach depends on an additional assumption and requires multiple independent variants.
“However, the approach depends on an additional assumption (described above) and requires multiple independent variants.”
Quote in the paperNot a substantial claim- The authors state this as an assumption: Exclusion restriction: genetic variant G does not affect outcome Y except through its potential effect on the exposure of interest X.
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
PremisereasoningA summary measure of follow-up time is important to understand the period over which events were recorded.
“A summary measure of follow-up time—such as mean, median, or total follow-up—is also important to understand the period over which events were recorded.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationcitationThe winner's curse bias is a linear function of the number of individuals included in both samples, so the consequences of a small amount of overlap may not be severe.
“The bias is a linear function of the number of individuals included in both samples, so the consequences of a small amount of overlap may not be severe.94”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [94] source
Not checked in the free run.
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing). May combine two claims.
PremisecitationAdditional plots might also aid in the visualisation of results, assessing assumption violation, and detecting potential influential or outlier points.
“Additional plots might also aid in the visualisation of results, assessing assumption violation, and detecting potential influential or outlier points.”
Quote in the paperNot a substantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
PremisecitationIn general, causal inference can be presented in a triangulation framework, evaluating the overall body of evidence from several different approaches.
“In general, causal inference can be presented in a triangulation framework, evaluating the overall body of evidence from several different approaches.103 104”
Quote in the paperNot a substantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Premisenone givenUsually MR studies are interpreted as a so-called lifetime effect of the exposure, but some settings (eg, MR studies in pregnant women to study prenatal exposures) lend themselves to studies of period effects.
“Usually MR studies are interpreted as a so-called lifetime effect of the exposure, but some settings (eg, MR studies in pregnant women to study prenatal exposures) lend themselves to studies of period effects.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
PremisereasoningBecause many interventions cannot be tested in randomised clinical trials, MR evidence might help to better understand the possible causal effect of the exposure on the outcome.
“Because many interventions cannot be tested in randomised clinical trials, MR evidence might help to better understand the possible causal effect of the exposure on the outcome (box 4).”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationThe long term effect of lowered low density lipoprotein (LDL) cholesterol can be estimated from early life onwards by MR and is double the effect estimate derived from randomised trials.
“Conversely, the long term effect of lowered low density lipoprotein (LDL) cholesterol can be estimated from early life onwards by MR and is double the effect estimate derived from randomised trials.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [112] source
Not checked in the free run.
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing). May combine two claims.
PremisecitationStructured discussions can help authors avoid over-interpreting results, and act as a guide for readers.
“Structured discussions can help authors avoid over-interpreting results, and act as a guide for readers.107 108”
Quote in the paperNot a substantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationFindings from a cohort of a specific age group collected in the past might not apply to people currently in the same age group.
“For example, findings from a cohort of a specific age group collected in the past might not apply to people currently in the same age group.118”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [118] source
Not checked in the free run.
Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing). May combine two claims.
InterpretationreasoningTime dependency of the effects of instruments is an important issue that should be considered when interpreting MR findings, and is well served by viewing this in the context of gene-environment equivalence.
“Time dependency of the effects of instruments is an important issue that should be considered when interpreting MR findings, and is well served by viewing this in the context of gene-environment equivalence.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationBiobanks or other repositories or databases used in their study have commercial interests that might influence research integrity.
“Authors should disclose funding sources for biobanks or other repositories or databases used in their study because these entities also have commercial interests that might influence research integrity.124 125”
Quote in the paperNot a substantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThis bias is of special concern when research is funded by an entity that has an interest in outcomes that are favourable to its own commercial, academic, or other interests.
“This bias is of special concern when research is funded by an entity that has an interest in outcomes that are favourable to its own commercial, academic, or other interests.123”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [123] source
Not checked in the free run.
Probably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningDescribing the source of funding allows readers to evaluate the work's credibility and trustworthiness in the light of any potential influence from funders.
“Describing the source of funding allows readers to evaluate the work’s credibility and trustworthiness in the light of any potential influence from funders.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningThis difference probably reflects MR providing an estimate of lifelong effects, whereas trials provide an effect estimate for period of randomisation, which lasts just a few years in cholesterol lowering randomised clinical trials.
“This difference probably reflects MR providing an estimate of lifelong effects, whereas trials provide an effect estimate for period of randomisation, which lasts just a few years in cholesterol lowering randomised clinical trials.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Premisenone givenThe biological mechanisms that allow genetic variants to be used as instrumental variables are often unknown.
“While the biological mechanisms that allow genetic variants to be used as instrumental variables are often unknown, the discussion should consider possibilities.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Premisenone givenMany of the instrumental variable assumptions are not empirically verifiable.
“Authors should address the plausibility of all the instrumental variable assumptions, which is especially important because many of the assumptions are not empirically verifiable.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Premisenone givenAn instrumental variable estimate's precision from a meta-analysis of multiple SNPs will usually be greater than that for a single SNP.
“For example, an instrumental variable estimate’s precision from a meta-analysis of multiple SNPs will usually be greater than that for a single SNP.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
InterpretationcitationCaution is especially warranted when interpreting effect estimates with a binary exposure.
“Caution is especially warranted when interpreting effect estimates with a binary exposure.114”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [114] source
Not checked in the free run.
Probably not a substantial claim: may not pass S4 (based).
Premisenone givenGenetic variants might not have a constant effect over the entire life course.
“For example, because genetic variants might not have a constant effect over the entire life course, authors should consider whether the effect estimate derived in the study would generalise to other exposure periods.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Premisenone givenOther sources of influence can include employers, political appointees, and government researchers.
“Other sources of influence can include employers, political appointees, and government researchers.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Premisenone given(Residual) genotype-phenotype confounders (such as population structure, genetic nurture, or assortative mating) could lead to a violation of the independence assumption.
“Authors could consider, for example, the possibility that (residual) genotype-phenotype confounders (such as population structure, genetic nurture, or assortative mating) could lead to a violation of the independence assumption.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe source of research funding can lead to bias or perceptions of bias in the design, conduct, or interpretation of research.
“The source of research funding can lead to bias or perceptions of bias in the design, conduct, or interpretation of research.121 122”
Quote in the paperNot a substantial claim0 of 2 sources checkedMay combine two claims.
InterpretationreasoningMR estimates are directly calculated only for the exposure range caused by differences in alleles. Applying MR results, therefore, might not generalise to a wider exposure range.
“Also, MR estimates are directly calculated only for the exposure range caused by differences in alleles. Applying MR results, therefore, might not generalise to a wider exposure range.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S4 (based).
Premisenone givenClinical and policy interventions might have different effect sizes compared with the genetic variants included in the MR study.
“Since clinical and policy interventions might have different effect sizes compared with the genetic variants included in the MR study, extrapolation of this evidence should be clearly described and cautious.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationWhen financial or ideological interests are not disclosed, public trust in the research enterprise is eroded.
“When such interests are not disclosed, public trust in the research enterprise is eroded.128”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [128] source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationAn important component of interpretation is defining the time period.
“Finally, an important component of interpretation is defining the time period.60”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [60] source
Not checked in the free run.
May combine two claims.
Premisenone givenVarious components of growth and development could be influenced by the variants, whilst their identification through genetic association studies is often from association with phenotype measured at one time point.
“Various components of growth and development could be influenced by the variants, whilst their identification through genetic association studies is often from association with phenotype measured at one time point.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationConsensus is building that data sharing is an inseparable part of the research process.
“Consensus is building that data sharing is “an inseparable part of the research process.”127”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [127] source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationFinancial connections between researchers and commercial or other entities and firmly held ideological or intellectual views can lead to bias in the design, conduct, or reporting of study results.
“Financial connections between researchers and commercial or other entities and firmly held ideological or intellectual views can lead to bias in the design, conduct, or reporting of study results.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [128] source
Not checked in the free run.
May combine two claims.
Premisenone givenEffects of genetic variants can influence outcomes from conception onwards and in a manner that can be variable and complex.
“Effects of genetic variants can influence outcomes from conception onwards and in a manner that can be variable and complex.”
Quote in the paperSubstantial claim
The paper relies on this without support.
Reporting guidelines help authors effectively communicate all critical information about what was done and what was found.
“Reporting guidelines help authors effectively communicate all critical information about what was done and what was found.”
The paper relies on this without support.
Genetic variation is essentially randomly inherited from parents to offspring at conception.
“Genetic variation is essentially randomly inherited from parents to offspring at conception”
The paper relies on this without support.
Mendelian randomisation studies have increased in popularity and have begun to inform understanding of disease causation.
“Given these advantages, MR studies have increased in popularity and have begun to inform understanding of disease causation.”
The authors state this as an assumption.
Relevance: genetic variant G is associated with the exposure of interest X.
“I. Relevance: genetic variant G is associated with the exposure of interest X”
The authors state this as an assumption.
Independence: genetic variant G shares no unmeasured cause with outcome Y.
“II. Independence: genetic variant G shares no unmeasured cause with outcome Y”
The authors state this as an assumption.
Exclusion restriction: genetic variant G does not affect outcome Y except through its potential effect on the exposure of interest X.
“III. Exclusion restriction: genetic variant G does not affect outcome Y except through its potential effect on the exposure of interest X.”
The authors state this as an assumption.
The exposure has the same effects in everyone (homogeneity).
“The homogeneity assumption requires that the exposure has the same effects in everyone, which is not directly verifiable.”
The authors state this as an assumption.
An increase in the number of risk alleles does not lower the likelihood of exposure for any individuals (monotonicity).
“The homogeneity assumption can also be replaced by imposing a monotonicity assumption that an increase in the number of risk alleles does not lower the likelihood of exposure for any individuals, typically leading to estimating an effect in a subgroup of the study population.61”
The authors state this as an assumption.
The size of the direct effects of the genetic variants on the outcome that do not operate through the exposure are independent of the size of the genetic variants’ effects on the exposure (InSIDE).
“MR Egger regression relaxes the exclusion restriction assumption but imposes an InSIDE assumption that the size of the direct effects of the genetic variants on the outcome that do not operate through the exposure are independent of the size of the genetic variants’ effects on the exposure.”
The authors state this as an assumption.
The association between the genetic variants and the exposure is the same in the two samples (two sample MR).
“Additionally, the two sample MR approach assumes that the association between the genetic variants and the exposure is the same in the two samples, which might not hold if samples are selected from different subpopulations (eg, by sex, age, ethnicity).”
The paper relies on this without support.
Original data are needed by readers or researchers who wish to evaluate or replicate analyses.
“Original data are needed by readers or researchers who wish to evaluate or replicate analyses.”
The paper relies on this without support.
Many funders and journals encourage or require data sharing, and provide guidance to authors about the content of any explicit data sharing statement required by their journal.
“Many funders and journals encourage or require data sharing, and provide guidance to authors about the content of any explicit data sharing statement required by their journal.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The comprehensive E&E document also benefited greatly from the consultation process used to develop the checklist.
“The comprehensive E&E document, 15 which is intended for use alongside the checklist, also benefited greatly from this consultation process.”
From Strengthening the Reporting of Observational Studies in Epidemiology Using Mendelian Randomization: The STROBE-MR Statement (2021) · cites this paper as [15]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Replicated odds ratio for rs4233949 falls outside its confidence interval
MinorThe replication-stage odds ratio is 1.04, but its stated 95% confidence interval runs from 1.05 to 1.05.
“| 2p16.2 | SPTBN1 | rs4233949 | −23.21 | G | 0.61 | 1.03 (1.02 to 1.05) | 6.9×10−5 | | 1.04 (1.05 to 1.05)”
“1.05 to 1.05”
Confidence interval for the BMI allele score association changes between examples
MinorThe two examples report the same −0.06% association with 25(OH)D concentrations and P=0.004, but give different lower confidence limits: −0.20% and −0.10%.
“The BMI allele score was also associated with 25(OH)D concentrations (per unit increase −0.06% [-0.20% to −0.02%], p=0.004).”
“The BMI allele score was also associated with 25(OH)D concentrations (per unit increase −0.06%, [−0.10% to −0.02%], p=0.004)”
Replicated odds ratio for rs7851693 falls outside its confidence interval
MinorThe replication-stage odds ratio is 1.05, but its stated 95% confidence interval runs from 1.06 to 1.06.
“| 9q34.11 | FUBP3 | rs7851693 | 0 | G | 0.35 | 1.03 (1.01 to 1.06) | 1.3×10−4 | | 1.05 (1.06 to 1.06)”
“1.06 to 1.06”
One SNP has more fracture cases than the stated combined total
MinorTable 8 lists 185 085 combined fracture cases for rs1286083, exceeding the table note's combined total of 185 057 cases by 28.
“| 14q32.12 | RPS6KA5 | rs1286083 | 0 | T | 0.82 | 1.04 (1.02 to 1.06) | 8.8×10−5 | | 1.05 (1.04 to 1.07) | 3.0×10−14 | | 1.05 (1.04 to 1.06) | 1.6×10−17 | 185 085 | 43.3 |”
“combined (185 057 cases; 377 201 controls).”
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The Role of Gallstones in Gallbladder Cancer in India: A Mendelian Randomization Study
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Self-citationGenomic atlas of the plasma metabolome prioritizes metabolites implicated in human diseases
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Self-citationGuidelines for performing Mendelian randomization investigations: update for summer 2023
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Self-citationBias correction for inverse variance weighting Mendelian randomization
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Understanding the assumptions underlying Mendelian randomization
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“In this study, we estimated the effect size through the instrumental variable method, so the study satisfies the fourth hypothesis: the effect of exposure on the outcome is homogeneous [30].”
MethodMaina, J. G., Balkhiyarova, Z., Nouwen, A., Pupko, I., Ulrich, A., Boissel, M., Bonnefond, A., Froguel, P., Khamis, A., Prokopenko, I., et al. (2023) · Diabetes Care · doi:10.2337/dc22-2373 · Cited by 151 · see citing works
“We used the Strengthening the Reporting of Observational Studies in Epidemiology Using MR (STROBE-MR) reporting guideline to facilitate readers’ evaluation of our results (15) (Supplementary Table 1).”
MethodHamilton, F., Thomas, M., Arnold, D., Palmer, T., Moran, E., Mentzer, A. J., Maskell, N. A., Baillie, J. K., Summers, C., Hingorani, A. D., et al. (2023) · PLoS Medicine · doi:10.1371/journal.pmed.1004174 · Cited by 141 · see citing works
“This study is reported in line with the STROBE-MR guidance, with the checklist available in the Supporting information (S1 STROBE Checklist) [42].”
MethodSelf-citationCross-talks between gut microbiota and tobacco smoking: a two-sample Mendelian randomization study
Fan, J., Zhou, Y., Meng, R., Tang, J., Zhu, J., Aldrich, M. C., Cox, N. J., Zhu, Y., Li, Y., & Zhou, D. (2023) · BMC Medicine · doi:10.1186/s12916-023-02863-1 · Cited by 121 · see citing works
“The usage and interpretation of our MR study adhere to the STROBE-MR (Strengthening the Reporting of Observational Studies in Epidemiology-Mendelian Randomization) checklist [44] (Additional file 1: Table S1) and the critical appraisal checklist proposed by Davies et al.”
MethodMendelian Randomization as a Tool for Cardiovascular Research
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Self-citationNavarese, E. P., Vine, D., Proctor, S., Grzelakowska, K., Berti, S., Kubica, J., & Raggi, P. (2023) · Arteriosclerosis, Thrombosis, and Vascular Biology · doi:10.1161/atvbaha.123.319297 · Cited by 107 · see citing works
A Mendelian randomization study investigating the causal role of inflammation on Parkinson’s disease
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“The present study was conducted following the STROBE-MR guidelines for transparent reporting of MR studies.(28)”
MethodInfluentialSun, X., Chen, B., Qi, Y., Wei, M., Chen, W., Wu, X., Wang, Q., Li, J., Lei, X., & Luo, G. (2024) · The Journal of Headache and Pain · doi:10.1186/s10194-024-01828-w · Cited by 104 · see citing works
“The STROBE-MR checklist is provided as Table S3 [36], and the study was carried out in accordance with the current guideline.”
MethodAssociation of Hypertensive Disorders of Pregnancy With Future Cardiovascular Disease
Rayes, B., Ardissino, M., Slob, E. A. W., Patel, K. H. K., Girling, J., & Ng, F. S. (2023) · JAMA Network Open · doi:10.1001/jamanetworkopen.2023.0034 · Cited by 102 · see citing works
Zhao, H., Rasheed, H., Nøst, T. H., Cho, Y., Liu, Y., Bhatta, L., Bhattacharya, A., Initiative, G. B. M.-A., Hemani, G., Smith, G. D., et al. (2022) · Cell Genomics · doi:10.1016/j.xgen.2022.100195 · Cited by 89 · see citing works
“org/).(55,56) To complement these guidelines, we list here some specific challenges of MR and provide some specific recommendations for multi-ancestry proteomewide MR in the era of global biobank meta-analysis.”
Berstein, F. M., McCartney, D. L., Lu, A. T., Tsilidis, K. K., Bouras, E., Haycock, P., Burrows, K., Phipps, A. I., Buchanan, D. D., Cheng, I. C., et al. (2022) · eLife · doi:10.7554/elife.75374 · Cited by 86 · see citing works
“This study has been reported according to the STROBE-MR guidelines ( Skrivankova et al., 2021 ; Supplementary file 2 ).”
Self-citationCausal effects of exposure to ambient air pollution on cancer risk: Insights from genetic evidence
Li, W., & Wang, W. (2023) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2023.168843 · Cited by 87 · see citing works
Circulating levels of micronutrients and risk of infections: a Mendelian randomization study
Flatby, H. M., Ravi, A., Damås, J. K., Solligård, E., & Rogne, T. (2023) · BMC Medicine · doi:10.1186/s12916-023-02780-3 · Cited by 87 · see citing works
“For the secondary analyses, we generally observed comparable effects as in the main analyses (Additional file 2: Table S11).”
MethodInfluentialHazelwood, E., Sanderson, E. C. M., Tan, V. Y., Ruth, K. S., Frayling, T. M., Dimou, N. L., Gunter, M. J., Dossus, L., Newton, C. L., Ryan, N. A. J., et al. (2022) · BMC Medicine · doi:10.1186/s12916-022-02322-3 · Cited by 78 · see citing works
“Additional file 3: Appendix S16.”
MethodSelf-citationRosoff, D. B., Mavromatis, L. A., Bell, A. S., Wagner, J., Jung, J., Marioni, R. E., Smith, G. D., Horvath, S., & Lohoff, F. W. (2023) · Nature Aging · doi:10.1038/s43587-023-00455-5 · Cited by 83 · see citing works
A Guide to Understanding Mendelian Randomization Studies
Nguyen, K., & Mitchell, B. D. (2024) · Arthritis Care & Research · doi:10.1002/acr.25400 · Cited by 79 · see citing works
Lovegrove, C. E., Howles, S., Furniss, D., & Holmes, M. V. (2024) · Journal of Bone and Mineral Research · doi:10.1093/jbmr/zjae136 · Cited by 80 · see citing works
“1,15,114 Akin to the original STROBE checklist, STROBE-MR recommends using a 20-point checklist (available at https://www.strobe-mr.org/) to enable readers, journal reviewers,and editors to evaluate the quality of an MR study.”
BackgroundMethodMediating Factors in the Association of Maternal Educational Level With Pregnancy Outcomes
Rogne, T., Gill, D., Liew, Z., Shi, X., Stensrud, V. H., Nilsen, T. I. L., & Burgess, S. (2024) · JAMA Network Open · doi:10.1001/jamanetworkopen.2023.51166 · Cited by 69 · see citing works
Alzheimer Disease and Epilepsy
Fang, Y., Si, X., Wang, J., Wang, Z., Chen, Y., Liu, Y., Yan, Y., Tian, J., Zhang, B., & Pu, J. (2023) · Neurology · doi:10.1212/wnl.0000000000207423 · Cited by 66 · see citing works
Park, S., Kim, S. G., Lee, S., Kim, Y., Cho, S., Kim, K., Kim, Y. C., Han, S. S., Lee, H., Lee, J. P., et al. (2023) · Journal of Cachexia Sarcopenia and Muscle · doi:10.1002/jcsm.13174 · Cited by 63 · see citing works
“The method allows balanced pleiotropic effects of the utilized variants.(19,24) Next, the weighted median method, which relaxes the MR assumptions for up to half of instruments, was used.”
MethodVitamin D and human health: evidence from Mendelian randomization studies
Fang, A., Zhao, Y., Yang, P., Zhang, X., & Giovannucci, E. L. (2024) · European Journal of Epidemiology · doi:10.1007/s10654-023-01075-4 · Cited by 64 · see citing works
“We additionally recorded whether the studies were reported according to the Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomization (STROBE-MR) guidelines [34, 35].”
Wang, S., Li, Z., Wang, X., Guo, S., Sun, Y., Li, G., Zhao, C., Yuan, W., Li, M., Li, X., et al. (2022) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2022.930000 · Cited by 67 · see citing works
“In recent years, Mendelian randomization (MR) studies have used genetic variants as instrument variables to mimic the RCT design, that is, genetic variants are randomly assigned to individuals before birth; this design can provide causal inferences about many disease outcomes (18, 19).”
BackgroundMulti-omic underpinnings of epigenetic aging and human longevity
Mavromatis, L. A., Rosoff, D. B., Bell, A. S., Jung, J., Wagner, J., & Lohoff, F. W. (2023) · Nature Communications · doi:10.1038/s41467-023-37729-w · Cited by 61 · see citing works
“All MR analyses in this study are reported according to the MR StrengtheningtheReportingofObservationalStudiesinEpidemiology (STROBE) guidelines (Supplementary Note 1) 82 .”
Power, G. M., Sanderson, E. C. M., Pagoni, P., Fraser, A., Morris, T., Prince, C., Frayling, T. M., Heron, J., Richardson, T. G., Richmond, R. C., et al. (2023) · European Journal of Epidemiology · doi:10.1007/s10654-023-01032-1 · Cited by 61 · see citing works
“These studies fulfil the criteria outlined in the STROBE-MR guidelines, and specifically to the criterion of whether effect estimates previously derived would generalise to other exposure periods [16, 17].”
Self-citationPrapiadou, S., Živković, L., Thorand, B., George, M. J., van der Laan, S. W., Malik, R., Herder, C., Köenig, W., Ueland, T., Kleveland, O., et al. (2023) · Circulation · doi:10.1161/circulationaha.123.064974 · Cited by 60 · see citing works
“19 The checklist is provided in the Extended Methods of the Supplemental Material.”
MethodZhang, L., Zi, L., Kuang, T., Wang, K., Qiu, Z., Wu, Z., Liu, L., Liu, R., Wang, P., & Wang, W. (2023) · Frontiers in Endocrinology · doi:10.3389/fendo.2023.1159148 · Cited by 59 · see citing works
Yang, Q., Borges, M. C., Sanderson, E. C. M., Magnus, M. C., Kilpi, F., Collings, P. J., Soares, A. G., West, J., Magnus, P. M., Wright, J., et al. (2022) · PLoS Medicine · doi:10.1371/journal.pmed.1004090 · Cited by 58 · see citing works
“This study is reported as per the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline, specific for MR (S1 STROBE Checklist) [39].”
MethodFang, S., Yarmolinsky, J., Gill, D., Bull, C. J., Perks, C. M., the PRACTICAL Consortium, Davey Smith, G., Gaunt, T. R., & Richardson, T. G. (2023) · PLOS Medicine · doi:10.1371/journal.pmed.1003988 · Cited by 55 · see citing works
Prognosis of Myocarditis Developing After mRNA COVID-19 Vaccination Compared With Viral Myocarditis
Lai, F. T. T., Chan, E. W. W., Huang, L., Cheung, C. L., Chui, C. S. L., Li, X., Wan, E. Y. F., Wong, C. K. H., Chan, E. W., Yiu, K. H., et al. (2022) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2022.09.049 · Cited by 53 · see citing works
“We adopted a retrospective cohort study design following the statement on Strengthening the Reporting of Observational Studies in Epidemiology.15 Routine health care records provided by the Hospital Authority of Hong Kong were linked with population-based vaccination records at the Department of Health to identify myo…”
MethodStandardizing the reporting of Mendelian randomization studies
Yeung, S. L. A., & Gill, D. (2023) · BMC Medicine · doi:10.1186/s12916-023-02894-8 · Cited by 54 · see citing works
“However, more checks on the STROBE-MR checklist do not necessarily mean the MR study is of better quality.”
BackgroundInfluentialLovegrove, C. E., Bešević, J., Wiberg, A., Lacey, B., Littlejohns, T. J., Allen, N. E., Goldsworthy, M. E., Kim, J., Hannan, F. M., Curhan, G. C., et al. (2023) · Journal of the American Society of Nephrology · doi:10.1681/asn.0000000000000238 · Cited by 55 · see citing works
Circulating Proteins Influencing Psychiatric Disease: A Mendelian Randomization Study
Lu, T., Forgetta, V., Greenwood, C. M. T., Zhou, S., & Richards, J. B. (2022) · Biological Psychiatry · doi:10.1016/j.biopsych.2022.08.015 · Cited by 53 · see citing works
Self-citationDietary Factors and Endometrial Cancer Risk: A Mendelian Randomization Study
Wang, X. M., Glubb, D. M., & O’Mara, T. A. (2023) · Nutrients · doi:10.3390/nu15030603 · Cited by 52 · see citing works
“This study referred to the Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomization (STROBE-MR) guidelines [32].”
MethodCirculating white blood cell traits and colorectal cancer risk: A Mendelian randomisation study
Constantinescu, A., Bull, C. J., Jones, N., Mitchell, R. E., Burrows, K., Dimou, N. L., Bezieau, S., Brenner, H., Buchanan, D. D., D’Amato, M., et al. (2023) · International Journal of Cancer · doi:10.1002/ijc.34691 · Cited by 50 · see citing works
“25 Here, units were interpreted as odds ratio (OR) for CRC per a normalised SD (1-SD) increase in WBC count.”
BackgroundSelf-citationLin, C., Sun, Z., Mei, Z., Zeng, H., Zhao, M., Hu, J., Xia, M., Huang, T., Wang, C., Gao, X., et al. (2022) · BMC Medicine · doi:10.1186/s12916-022-02612-w · Cited by 51 · see citing works
“This study followed the Strengthening the reporting of observational studies in epidemiology using Mendelian randomization (STROBE-MR, Additional file 2: STROBE-MR checklist) guideline [24].”
MethodDeng, Y., & Wong, M. C. S. (2023) · Arthritis & Rheumatology · doi:10.1002/art.42502 · Cited by 51 · see citing works
Mendelian randomization study on the causal effects of omega-3 fatty acids on rheumatoid arthritis
Zhu, G., Zhou, S. Y., Xu, Y., Gao, R., Li, H., Zhai, B., Liu, X., He, Y., Wang, X., Han, G., et al. (2022) · Clinical Rheumatology · doi:10.1007/s10067-022-06052-y · Cited by 50 · see citing works
“We followed PRISMA (The Preferred Reporting Items for Systematic reviews and Meta-Analyses) [20, 21] and STROBE-MR (Strengthening the reporting of observational studies in epidemiology using mendelian randomization) [22, 23] guidelines.”
MethodMendelian randomization for nephrologists
Dobrijevic, E. L. K., van Zwieten, A., Kiryluk, K., Grant, A. J., Wong, G., & Teixeira-Pinto, A. M. (2023) · Kidney International · doi:10.1016/j.kint.2023.09.016 · Cited by 49 · see citing works
Zhang, X., Sun, Y., Ye, S., Huang, Q., Zheng, R., Li, Z., Yu, F., Zhao, C., Zhang, M., Zhao, G., et al. (2024) · Journal of Clinical Sleep Medicine · doi:10.5664/jcsm.11326 · Cited by 51 · see citing works
A Causal Atlas on Comorbidities in Idiopathic Pulmonary Fibrosis
Zhu, J., Zhou, D., Wang, J., Yang, Y., Chen, D., He, F., & Li, Y. (2023) · CHEST Journal · doi:10.1016/j.chest.2023.02.038 · Cited by 47 · see citing works
Kong, L., Ye, C., Wang, Y., Hou, T., Zheng, J., Zhao, Z., Li, M., Xu, Y., Lu, J., Chen, Y., et al. (2023) · The Journals of Gerontology Series A · doi:10.1093/gerona/glad078 · Cited by 48 · see citing works
Bell, J. A., Richardson, T. G., Wang, Q., Sanderson, E. C. M., Palmer, T., Walker, V. M., O’Keeffe, L. M., Timpson, N. J., Cichońska, A., Julkunen, H., et al. (2022) · The Lancet Regional Health - Europe · doi:10.1016/j.lanepe.2022.100457 · Cited by 47 · see citing works
Self-citationZha, F., Cao, C., Hong, M., Hou, H., Zhang, Q., Tang, B. H., Hu, H., Han, Y. Y., Zan, Y., Wang, Y., et al. (2023) · Frontiers in Endocrinology · doi:10.3389/fendo.2023.1120277 · Cited by 47 · see citing works
Li, R., Guo, Q., Zhao, J., Kang, W., Lu, R., Long, Z., Huang, L., Chen, Y., Zhao, A., Wu, J., et al. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1148684 · Cited by 47 · see citing works
Ye, X., Liu, B., Bai, Y., Cao, Y., Lin, S.-R., Lyu, L., Meng, H., Dai, Y., Ye, D., Pan, W., et al. (2023) · Journal of Translational Medicine · doi:10.1186/s12967-023-04559-9 · Cited by 46 · see citing works
“Our study was reported according to the “STrengthening the Reporting of OBservational studies in Epidemiology using Mendelian Randomization (STROBE-MR)” checklist [22].”
MethodQin, P., Qin, T., Liang, L., Li, X., Jiang, B., Wang, X., Ma, J., Hu, F., Zhang, M., & Hu, D. (2024) · Cardiovascular Diabetology · doi:10.1186/s12933-023-02074-1 · Cited by 46 · see citing works
Lv, H., Zeng, N., Li, M., Sun, J., Wu, N., Xu, M., Chen, Q., Zhao, X., Chen, S., Liu, W., et al. (2024) · Health Data Science · doi:10.34133/hds.0087 · Cited by 46 · see citing works
“This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) [25] and STROBE Mendelian randomization reporting guidelines [26].”
MethodVandebergh, M., Degryse, N., Dubois, B., & Goris, A. (2022) · Journal of Neurology · doi:10.1007/s00415-022-11072-4 · Cited by 47 · see citing works
“To aid in conducting and critically evaluating MR studies, guidelines for performing, reporting and reviewing MR studies are now available [6, 11, 12].”
MethodWalker, V. M., Zheng, J., Gaunt, T. R., & Smith, G. D. (2022) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-122120-024910 · Cited by 43 · see citing works
Causal inference on neuroimaging data with Mendelian randomisation
Taschler, B., Smith, S. M., & Nichols, T. E. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119385 · Cited by 46 · see citing works
Zhu, J., Zhou, D., Nie, Y., Wang, J., Yang, Y., Chen, D., Yu, M., & Li, Y. (2023) · Journal of Cachexia Sarcopenia and Muscle · doi:10.1002/jcsm.13319 · Cited by 44 · see citing works
“The study adhered to the STROBE-MR (Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomization) guidelines in terms of reporting and analytical processes.(13) All data used in this study are publicly available, and ethical approval and informed consent”
MethodHaglund, A., Zuber, V., Abouzeid, M., Yang, Y., Ko, J. H., Wiemann, L., Otero‐Jimenez, M., Muhammed, L., Feleke, R., Nott, A., et al. (2025) · Nature Genetics · doi:10.1038/s41588-024-02050-9 · Cited by 43 · see citing works
Woolf, B. A. R., Zagkos, L., & Gill, D. (2022) · Genes · doi:10.3390/genes13091541 · Cited by 44 · see citing works
“Reporting based on the STROBE-MR guidelines are provided below [9].”
MethodSelf-citationAssociation between Liver MRI Proton Density Fat Fraction and Liver Disease Risk
Xia, T., Du, M., Li, H., Wang, Y., Zha, J., Wu, T., & Ju, S. (2023) · Radiology · doi:10.1148/radiol.231007 · Cited by 43 · see citing works
Xiong, Y., Tvedt, J., Åkerstedt, T., Cadar, D., & Wang, H. (2024) · Psychiatry Research · doi:10.1016/j.psychres.2024.115760 · Cited by 43 · see citing works
“We followed the STROBE-MR guideline to conduct the analysis (Skrivankova et al., 2021a, 2021b).”
MethodRelationship between periodontitis and psoriasis: A two‐sample Mendelian randomization study
Baurecht, H., Freuer, D., Welker, C., Tsoi, L. C., Elder, J. T., Ehmke, B., Leitzmann, M. F., Holtfreter, B., & Baumeister, S. (2022) · Journal Of Clinical Periodontology · doi:10.1111/jcpe.13620 · Cited by 40 · see citing works
“Reporting follows the STROBE-MR statement (Skrivankova et al., 2021).”
Duan, Q., Wang, H., Su, W., Gu, X., Shen, X., Jiang, Z., Ren, Y., Cao, B., Li, G., Wang, Y., et al. (2024) · BMC Medicine · doi:10.1186/s12916-024-03314-1 · Cited by 41 · see citing works
Yoshiji, S., Lu, T., Butler‐Laporte, G., Carrasco-Zanini, J., Su, C., Chen, Y., Liang, K. Y. H., Willett, J., Wang, S., Adra, D., et al. (2025) · Nature Genetics · doi:10.1038/s41588-024-02052-7 · Cited by 41 · see citing works
“Although MR relies on several key assumptions 6,7 , when these are met, it can be a powerful tool to describe causal relationships.”
Self-citationHan, X., Laíns, I., Li, J., Li, J., Chen, Y., Yu, B., Qi, Q., Boerwinkle, E., Kaplan, R. C., Thyagarajan, B., et al. (2023) · Cell Reports Medicine · doi:10.1016/j.xcrm.2023.101085 · Cited by 40 · see citing works
“, SNP-metabolite and SNP-AMDassociations are from two separate studies) to evaluate the potential causal relationships between metabolites and AMD.(22,23) In addition, other genetic approaches may reveal novel insights into the sharedgenetic components betweenmetabolites and AMD.”
BackgroundSelf-citationGibson, M., Lawlor, D. A., & Millard, L. A. C. (2023) · BMC Medicine · doi:10.1186/s12916-023-02832-8 · Cited by 38 · see citing works
Yan, L., Deng, Q., & Liu, Z. (2023) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2023.1296417 · Cited by 37 · see citing works
Diet-derived antioxidants and nonalcoholic fatty liver disease: a Mendelian randomization study
Chen, L., Fan, Z., Sun, X., Qiu, W., Mu, W., Chai, K., Cao, Y., Wang, G., & Lv, G. (2022) · Hepatology International · doi:10.1007/s12072-022-10443-3 · Cited by 36 · see citing works
Deng, Y., Huang, J., & Wong, M. C. S. (2022) · Hepatology Communications · doi:10.1002/hep4.1960 · Cited by 35 · see citing works
“Fifth, in a two- sample MR study, bias caused by the winner’s curse will occur when data on the exposures and outcome are derived from the same population.[10] Nevertheless, for a binary outcome involving cases and controls, unbiased results can be obtained even in a one- sample setting if the associations between SNP…”
BackgroundMethodLi, H., Pan, X., Zhang, S., Shen, X., Wan, L., Shang, W., Wen, Z., Huang, S., Chen, L., Zhang, X., et al. (2023) · Critical Care · doi:10.1186/s13054-023-04763-5 · Cited by 36 · see citing works
“This study is reported in line with the STROBE-MR guidance, with the checklist available in the Supporting information [23].”
Deciphering how early life adiposity influences breast cancer risk using Mendelian randomization
Vabistsevits, M., Smith, G. D., Sanderson, E. C. M., Richardson, T. G., Lloyd‐Lewis, B., & Richmond, R. C. (2022) · Communications Biology · doi:10.1038/s42003-022-03272-5 · Cited by 35 · see citing works
Self-citationDeng, Y., Huang, J., & Wong, M. C. S. (2022) · European Journal of Nutrition · doi:10.1007/s00394-022-03076-7 · Cited by 33 · see citing works
“This MR study was reported according to the strengthening of the reporting of observational studies in epidemiology using Mendelian randomization (STROBE-MR) guideline (Online Resource 1) [10].”
MethodGarcia-Argibay, M., Brikell, I., Thapar, A., Lichtenstein, P., Lundström, S., Demontis, D., & Larsson, H. (2024) · Biological Psychiatry · doi:10.1016/j.biopsych.2023.07.017 · Cited by 33 · see citing works
Causal Associations of PM2.5 and GDM: A Two-Sample Mendelian Randomization Study
Yang, Y., Ma, X., Pang, W., & Jiang, C. (2023) · Toxics · doi:10.3390/toxics11020171 · Cited by 33 · see citing works
Wang, K., Wang, S., Chen, Y., Lu, X., Wang, D., Zhang, Y., Pan, W., Zhou, C., & Zou, D. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1327503 · Cited by 32 · see citing works
Chen, S., Yang, L., Yang, Y., Shi, W., Stults‐Kolehmainen, M., Qiao, Y., Wang, C., & Ye, J. (2024) · PLoS ONE · doi:10.1371/journal.pone.0300074 · Cited by 31 · see citing works
“Our study complied with the standards of the Strengthening the Reporting of Observational Studies in Epidemiology using the Mendelian Randomization S1 Checklist [33].”
MethodVariation in ERAP2 has opposing effects on severe respiratory infection and autoimmune disease
Hamilton, F., Mentzer, A. J., Parks, T., Baillie, J. K., Smith, G. D., Ghazal, P., & Timpson, N. J. (2023) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2023.02.008 · Cited by 31 · see citing works
Self-citationYang, J., Liu, P., Wang, S., Jiang, T., Zhang, Y., & Liu, W. (2023) · European journal of medical research · doi:10.1186/s40001-023-01322-0 · Cited by 31 · see citing works
“…reported according to the Strengthening the reporting of observational studies in epidemiology using Mendelian randomization (STROBE-MR) guidelines [31], the causal relationship between sarcopenia-related traits and OA were explored using genetic variants for exposure as instrument variables (IV).”
BackgroundMethodA Guide for Understanding and Designing Mendelian Randomization Studies in the Musculoskeletal Field
Hartley, A. E., Power, G. M., Sanderson, E. C. M., & Smith, G. D. (2022) · JBMR Plus · doi:10.1002/jbm4.10675 · Cited by 31 · see citing works
“Guidelines for performing an MR study have been published,((57)) and the STROBE-MR consortium has developed a checklist for MR studies.((58,59)) These are important to follow when writing an MR article to ensure correct interpretation and reproducibility.”
MethodZhang, Y., Liu, S., Wang, Y., & Wang, Y. (2022) · Frontiers in Public Health · doi:10.3389/fpubh.2022.1000103 · Cited by 30 · see citing works
Garfield, V., Salzmann, A., Burgess, S., & Chaturvedi, N. (2023) · Diabetes · doi:10.2337/db22-0110 · Cited by 30 · see citing works
Jiang, D., Hou, J., Nan, H., Yue, A., Chu, M. K., Wang, Y., Wang, Y., & Wu, L. (2024) · Alzheimer s Research & Therapy · doi:10.1186/s13195-024-01586-6 · Cited by 30 · see citing works
“The reporting of this study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomisation (STROBE-MR) reporting guideline [15].”
MethodPapadimitriou, N., Bull, C. J., Jenab, M., Hughes, D. J., Bell, J. A., Sanderson, E. C. M., Timpson, N. J., Smith, G. D., Albanes, D., Campbell, P. T., et al. (2023) · BMC Medicine · doi:10.1186/s12916-022-02702-9 · Cited by 30 · see citing works
“Reporting guidelines for MR studies were followed (MR STROBE checklist outlined in Additional file 1: Table S6) [35, 36].”
MethodSelf-citationNolde, M., Alayash, Z., Reckelkamm, S. L., Kocher, T., Ehmke, B., Holtfreter, B., Baurecht, H., Georgakis, M. K., & Baumeister, S. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1160148 · Cited by 30 · see citing works
Thyroid Function and Metabolic Syndrome: A Two-Sample Bidirectional Mendelian Randomization Study
Pleić, N., Gunjača, I., Leko, M. B., & Zemunik, T. (2023) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgad371 · Cited by 31 · see citing works
Singh, S., Baars, D. P., Desai, R., Singh, D., & Pinto‐Sietsma, S. (2023) · Current Problems in Cardiology · doi:10.1016/j.cpcardiol.2023.102024 · Cited by 32 · see citing works
Li, M., Jiang, C., Lai, Y., Wang, Y., Zhao, M., Li, S., Peng, X., He, L., Guo, X., Li, S., et al. (2023) · Journal of the American Heart Association · doi:10.1161/jaha.123.029623 · Cited by 29 · see citing works
Assessing the causal effect of genetically predicted metabolites and metabolic pathways on stroke
Zhang, T., Cao, Y., Zhao, J., Yao, J., & Liu, G. (2023) · Journal of Translational Medicine · doi:10.1186/s12967-023-04677-4 · Cited by 29 · see citing works
“This study adheres to the reporting guidelines outlined in STROBE-MR (Additional File 1) [25].”
MethodMitochondrial DNA copy number and cancer risks: A comprehensive Mendelian randomization analysis
Cai, X., Liang, C., Zhang, M., Dong, Z., Weng, Y., & Yu, W. (2023) · International Journal of Cancer · doi:10.1002/ijc.34833 · Cited by 29 · see citing works
“31,32 The MR design was based on three fundamental assumptions: the relevance assumption, which suggests a significant association between genetic variants and mtDNA-CN; the independence assumption, which postulates no association between genetic variants and other variables that are related to…”
MethodLi, J., Wang, W., Yang, Z., Qiu, L., Ren, Y., Wang, D., Li, M., Li, W., Gao, F., & Zhang, J. (2024) · Lipids in Health and Disease · doi:10.1186/s12944-024-02042-y · Cited by 29 · see citing works
“The present study strictly adheres to the STROBE-MR guidelines [33].”
MethodWang, K., Wang, S., Qin, X., Chen, Y., Chen, Y., Wang, J., Zhang, Y., Guo, Q., Zhou, C., & Zou, D. (2024) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2024.1308742 · Cited by 29 · see citing works
Liu, D., Cao, M., Wang, H., Cao, W., Zheng, C., Li, J., & Wang, Y. (2024) · BMC Medicine · doi:10.1186/s12916-024-03352-9 · Cited by 30 · see citing works
“Summarized data derived from genome-wide association studies (GWAS) are widely reported to make two-sample MR studies easy and popular to implement [21, 22].”
BackgroundNolde, M., Holtfreter, B., Kocher, T., Alayash, Z., Reckelkamm, S. L., Ehmke, B., Baurecht, H., & Baumeister, S. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.918404 · Cited by 29 · see citing works
EVALUATING THE CAUSAL RELATIONSHIP BETWEEN EDUCATIONAL ATTAINMENT AND MENTAL HEALTH
Demange, P., Boomsma, D. I., van Bergen, E., & Nivard, M. G. (2023) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2023.08.044 · Cited by 28 · see citing works
Inoue, K., Naito, T., Fuji, R., Sonehara, K., Yamamoto, K., Baba, R., Kodama, T., Otagaki, Y., Okada, A., Itcho, K., et al. (2024) · Journal of the American Heart Association · doi:10.1161/jaha.123.034180 · Cited by 28 · see citing works
Gestational diabetes and future cardiovascular diseases: associations by sex-specific genetic data
Zhang, Y., Yu, S., Chen, Z., Liu, H., Li, H., Long, X., Ye, F., Luo, W., Dai, Y., Tu, S., et al. (2024) · European Heart Journal · doi:10.1093/eurheartj/ehae706 · Cited by 28 · see citing works
Ying, H., Wu, X., Jia, X., Yang, Q., Liu, H., Zhao, H., Chen, Z., Xu, M., Wang, T., Li, M., et al. (2025) · EBioMedicine · doi:10.1016/j.ebiom.2025.105596 · Cited by 28 · see citing works
“39,40 49 Directionality test using MR steiger fi ltering A drug that alters disease risk should in theory in fl uence both gene expression and protein levels.”
Iron status and the risk of sepsis and severe COVID-19: a two-sample Mendelian randomization study
Mohus, R. M., Flatby, H., Liyanarachi, K. V., DeWan, A. T., Solligård, E., Damås, J. K., Åsvold, B. O., Gustad, L. T., & Rogne, T. (2022) · Scientific Reports · doi:10.1038/s41598-022-20679-6 · Cited by 28 · see citing works
“6 MR studies according to STROBE-MR guidelines (36).”
Method
- Authors
- Skrivankova, V. W., Richmond, R. C., Woolf, B. A. R., Davies, N. M., Swanson, S. A., VanderWeele, T. J., Timpson, N. J., Higgins, J. P. T., Dimou, N., Langenberg, C., Loder, E. W., Golub, R. M., Egger, M., Davey Smith, G., & Richards, J. B.
- Affiliations
- University of Bern (CH)
- University of Bristol (GB)
- Norwegian University of Science and Technology (NO)
- Erasmus MC (NL)
- Harvard University (US)
- Centre international de recherche sur le cancer (FR)
- University of Cambridge (GB)
- Northwestern University (US)
- University of London (GB)
- Corresponding author
- Richards, J Brent
- ORCID
- Venue
- BMJ
- Publisher
- BMJ
- Published
- 2021-10-26
- Volume
- 375
- Pages
- n2233
- ISSN
- 1756-1833 (ISSN-L)
- PMC
- PMC8546498
- OpenAlex
- W3210406414
- Semantic Scholar
- 99c3b9a1837c0cd16d8ee30fe55332a366bfbbf6
- Cited by
- 1,648
- References
- 137
- Citations by year
- 2026: 217 · 2025: 484 · 2024: 599 · 2023: 252 · 2022: 91 · 2021: 4
- FWCI
- 140.35
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- BMJ (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (publishedVersion, cc-by)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion, cc-by)
- BORIS (University Library Bern) (submittedVersion, cc-by)
- Apollo (University of Cambridge) (submittedVersion, cc-by)
- Apollo
- Apollo (cc-by)
- Funders
- National Science Foundation (189498)
- World Health Organization
- Wellcome Trust (WT 217065/Z/19/Z, 217065/Z/19/Z, 202802/Z/16/Z, 217065, 202802)
- Public Health Agency of Canada
- University Hospitals Bristol NHS Foundation Trust
- Compute Canada
- NIHR Bristol Biomedical Research Centre (MC_UU_00011/1, BRC‐1215‐2001, NF-SI-0617-10145)
- Cancer Research UK (C18281/, 29019, C18281 / A19169, 10710, MC_UU_00011/1, 10118, 16563, A19169, 19169)
- National Institute for Health and Care Research (BRC-1215-2001, C18281/A19169, 217065/Z/19/Z, NF-SI-0617-10145, MC_UU_00011/1)
- Department of Health and Social Care
- King's College London
- European Commission (633784)
- University of Bristol (C18281/A19169, 217065/Z/19/Z, MC_UU_00011/1)
- Public Health Agency
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (189498, 10145)
- ZonMw (91617066)
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (91617066)
- Jewish General Hospital
- Norges Forskningsråd (189498, 295989)
- National Institutes of Health (217065/Z/19/Z)
- Canadian Institutes of Health Research (365825; 409511, 40951_1, 365825)
- Medical Research Council (MC_UU_00011/6, 217065/Z/19/Z, MR/M005070/1, 202802/Z/16/Z, 217065, WT 217065/Z/19/Z, MC_UU_00011/7, MC_UU_00011/5, MC_UU_00011/1, MC_UU_00011, MC_UU_00011/2)
- Economic and Social Research Council (+3 PhD Studentship Award, ES/P000630/1, 1+3 PhD Studentship, ES/N000498/1)
- National Cancer Institute (R01CA222147)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Keywords
- reporting guidelines, Mendelian randomization, observational studies, causal inference, reporting checklist, transparency in research reporting, study quality assessment
- MeSH terms
- Humans, Epidemiologic Research Design, Guidelines as Topic, Mendelian Randomization Analysis, Observational Studies as Topic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-10.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-10.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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