ArticleInternational journal of epidemiology2023
Design and quality control of large-scale two-sample Mendelian randomization studies.
Article in International journal of epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Integrative Single-Cell Transcriptomic, Mendelian Randomization and In Silico Perturbation Analyses Prioritize MUC20 as a Candidate Gene Associated with Osteoporosis and Metabolic Dysfunction-Associated Steatotic Liver Disease in the Liver-Bone Axis.International journal of molecular sciences · 2026Article
- Postpartum Psychosis: could genetic vulnerability to insomnia or short sleep duration be protective?Translational psychiatry · 2026Article
- Mendelian Randomization Uncovers Potential Repurposable Medications for Neuropsychiatric Disorders.Current neuropharmacology · 2026Article
- Causal effects of circulating inflammatory proteins on colorectal cancer: a Mendelian randomization and Spatial transcriptomic study.Discover oncology · 2025Article
- Examining socioeconomic differences in sepsis risk and mediation by modifiable factors: a Mendelian randomization study.BMC infectious diseases · 2025Article
- Exploring the causal association between congenital heart disease and stroke based on two-sample Mendelian randomization.Cardiovascular diagnosis and therapy · 2025Article
- MRanalysis: a comprehensive online platform for integrated, multimethod Mendelian randomization and associated post-GWAS analyses.GigaScience · 2025Article
- Causal association of smoking and laryngeal cancer: A Mendelian randomization study.Tobacco induced diseases · 2025Article
- MRSamePopTest: introducing a simple falsification test for the two-sample mendelian randomisation 'same population' assumption.BMC research notes · 2024Article
- Causal relationship between sarcopenia and rotator cuff tears: a Mendelian randomization study.Frontiers in endocrinology · 2024Article
- GCPBayes pipeline: a tool for exploring pleiotropy at the gene level.NAR genomics and bioinformatics · 2023Article
- The association between genetically elevated polyunsaturated fatty acids and risk of cancer.EBioMedicine · 2023Article
Corrections and comments
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Authors and funding
29 authors.
Funding
Abstract
Background: Mendelian randomization (MR) studies are susceptible to metadata errors (e.g. incorrect specification of the effect allele column) and other analytical issues that can introduce substantial bias into analyses. We developed a quality control (QC) pipeline for the Fatty Acids in Cancer Mendelian Randomization Collaboration (FAMRC) that can be used to identify and correct for such errors. Methods: We collated summary association statistics from fatty acid and cancer genome-wide association studies (GWAS) and subjected the collated data to a comprehensive QC pipeline. We identified metadata errors through comparison of study-specific statistics to external reference data sets (the National Human Genome Research Institute-European Bioinformatics Institute GWAS catalogue and 1000 genome super populations) and other analytical issues through comparison of reported to expected genetic effect sizes. Comparisons were based on three sets of genetic variants: (i) GWAS hits for fatty acids, (ii) GWAS hits for cancer and (iii) a 1000 genomes reference set. Results: We collated summary data from 6 fatty acid and 54 cancer GWAS. Metadata errors and analytical issues with the potential to introduce substantial bias were identified in seven studies (11.6%). After resolving metadata errors and analytical issues, we created a data set of 219 842 genetic associations with 90 cancer types, generated in analyses of 566 665 cancer cases and 1 622 374 controls. Conclusions: In this large MR collaboration, 11.6% of included studies were affected by a substantial metadata error or analytical issue. By increasing the integrity of collated summary data prior to their analysis, our protocol can be used to increase the reliability of downstream MR analyses. Our pipeline is available to other researchers via the CheckSumStats package (https://github.com/MRCIEU/CheckSumStats).
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