A practical guide for nephrologist peer reviewers: understanding and appraising Mendelian randomization studies

Identifying risk factors for disease onset and progression has been a core focus in nephrology research. Mendelian Randomization (MR) has emerged as a powerful genetic epidemiological approach, utilizing genome-wide association studies (GWAS) to establish causal relationships between modifiable risk...

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Vydáno v:Renal failure Ročník 47; číslo 1; s. 2445763
Hlavní autoři: Qing, Jianbo, Li, Yafeng, Soliman, Karim M., Cheungpasitporn, Wisit
Médium: Journal Article
Jazyk:angličtina
Vydáno: England Taylor & Francis 01.12.2025
Taylor & Francis Group
Témata:
causal inference
genetic epidemiology
Genome-Wide Association Study
Humans
kidney diseases
Kidney Diseases - genetics
Medical Education and Training
Mendelian Randomization
Mendelian Randomization Analysis - methods
Mendelian Randomization Analysis - standards
Nephrology
peer review
Peer Review, Research - standards
Risk Factors
nephrology
Mendelian Randomization
causal inference
peer review
kidney diseases
genetic epidemiology
ISSN:0886-022X, 1525-6049, 1525-6049
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Abstract Identifying risk factors for disease onset and progression has been a core focus in nephrology research. Mendelian Randomization (MR) has emerged as a powerful genetic epidemiological approach, utilizing genome-wide association studies (GWAS) to establish causal relationships between modifiable risk factors and kidney disease outcomes. MR uses genetic variants as instrumental variables to infer causal relationships between exposures and disease outcomes. This method leverages the natural randomization of genetic variants to balance confounders, akin to matched cohorts in observational research. The rapid increase in MR studies on kidney disease poses challenges for journals and peer reviewers, especially clinicians unfamiliar with the methodology. High-quality MR studies use strong, well-validated genetic instruments with clear biological relevance, thoroughly testing for pleiotropy and confounding factors using methods like MR-Egger. Sensitivity analyses, such as MR-PRESSO, should ensure findings remain consistent across various assumptions. Effect sizes with confidence intervals should be reported and discussed within established biological mechanisms. Additionally, limitations must be transparently addressed, with recommendations for replication in future studies, to strengthen findings. This article guides readers in understanding MR application in nephrology and identifying high-quality MR studies, helping peers avoid pitfalls while seizing new opportunities in advancing kidney disease research.
AbstractList Identifying risk factors for disease onset and progression has been a core focus in nephrology research. Mendelian Randomization (MR) has emerged as a powerful genetic epidemiological approach, utilizing genome-wide association studies (GWAS) to establish causal relationships between modifiable risk factors and kidney disease outcomes. MR uses genetic variants as instrumental variables to infer causal relationships between exposures and disease outcomes. This method leverages the natural randomization of genetic variants to balance confounders, akin to matched cohorts in observational research. The rapid increase in MR studies on kidney disease poses challenges for journals and peer reviewers, especially clinicians unfamiliar with the methodology. High-quality MR studies use strong, well-validated genetic instruments with clear biological relevance, thoroughly testing for pleiotropy and confounding factors using methods like MR-Egger. Sensitivity analyses, such as MR-PRESSO, should ensure findings remain consistent across various assumptions. Effect sizes with confidence intervals should be reported and discussed within established biological mechanisms. Additionally, limitations must be transparently addressed, with recommendations for replication in future studies, to strengthen findings. This article guides readers in understanding MR application in nephrology and identifying high-quality MR studies, helping peers avoid pitfalls while seizing new opportunities in advancing kidney disease research.
Identifying risk factors for disease onset and progression has been a core focus in nephrology research. Mendelian Randomization (MR) has emerged as a powerful genetic epidemiological approach, utilizing genome-wide association studies (GWAS) to establish causal relationships between modifiable risk factors and kidney disease outcomes. MR uses genetic variants as instrumental variables to infer causal relationships between exposures and disease outcomes. This method leverages the natural randomization of genetic variants to balance confounders, akin to matched cohorts in observational research. The rapid increase in MR studies on kidney disease poses challenges for journals and peer reviewers, especially clinicians unfamiliar with the methodology. High-quality MR studies use strong, well-validated genetic instruments with clear biological relevance, thoroughly testing for pleiotropy and confounding factors using methods like MR-Egger. Sensitivity analyses, such as MR-PRESSO, should ensure findings remain consistent across various assumptions. Effect sizes with confidence intervals should be reported and discussed within established biological mechanisms. Additionally, limitations must be transparently addressed, with recommendations for replication in future studies, to strengthen findings. This article guides readers in understanding MR application in nephrology and identifying high-quality MR studies, helping peers avoid pitfalls while seizing new opportunities in advancing kidney disease research.Identifying risk factors for disease onset and progression has been a core focus in nephrology research. Mendelian Randomization (MR) has emerged as a powerful genetic epidemiological approach, utilizing genome-wide association studies (GWAS) to establish causal relationships between modifiable risk factors and kidney disease outcomes. MR uses genetic variants as instrumental variables to infer causal relationships between exposures and disease outcomes. This method leverages the natural randomization of genetic variants to balance confounders, akin to matched cohorts in observational research. The rapid increase in MR studies on kidney disease poses challenges for journals and peer reviewers, especially clinicians unfamiliar with the methodology. High-quality MR studies use strong, well-validated genetic instruments with clear biological relevance, thoroughly testing for pleiotropy and confounding factors using methods like MR-Egger. Sensitivity analyses, such as MR-PRESSO, should ensure findings remain consistent across various assumptions. Effect sizes with confidence intervals should be reported and discussed within established biological mechanisms. Additionally, limitations must be transparently addressed, with recommendations for replication in future studies, to strengthen findings. This article guides readers in understanding MR application in nephrology and identifying high-quality MR studies, helping peers avoid pitfalls while seizing new opportunities in advancing kidney disease research.
Author Li, Yafeng
Cheungpasitporn, Wisit
Soliman, Karim M.
Qing, Jianbo
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Issue 1
Keywords nephrology
Mendelian Randomization
causal inference
peer review
kidney diseases
genetic epidemiology
Language English
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Snippet Identifying risk factors for disease onset and progression has been a core focus in nephrology research. Mendelian Randomization (MR) has emerged as a powerful...
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SubjectTerms causal inference
genetic epidemiology
Genome-Wide Association Study
Humans
kidney diseases
Kidney Diseases - genetics
Medical Education and Training
Mendelian Randomization
Mendelian Randomization Analysis - methods
Mendelian Randomization Analysis - standards
Nephrology
peer review
Peer Review, Research - standards
Risk Factors
Title A practical guide for nephrologist peer reviewers: understanding and appraising Mendelian randomization studies
URI https://www.ncbi.nlm.nih.gov/pubmed/39806780
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https://pubmed.ncbi.nlm.nih.gov/PMC11734392
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