ArticlePLoS genetics2021
Causal inference for heritable phenotypic risk factors using heterogeneous genetic instruments.
Article in PLoS genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 3 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
63 citing papers in PubMed, 3 syntheses or guidelines pooled it, 97 citations in OpenAlex.
- Shared Genetic Risk Factors for Multiple Sclerosis/Psoriasis Suggest Involvement of Interleukin-17 and Janus Kinase-Signal Transducers and Activators of Transcription Signaling.Annals of neurology · 2023Pooled it
- Shared genetic risk factors and causal association between psoriasis and coronary artery disease.Nature communications · 2022Pooled it
- Telomere Length and Hearing Loss: A Two-Sample Mendelian Randomization.International journal of environmental research and public health · 2022Pooled it
- Inferring multi-organ genetic connections using imaging and clinical data through Mendelian randomization.Nature biomedical engineering · 2026Article
- TL-HDMR: a transfer learning framework for advancing equitable causal inference reveals metabolic signatures of stroke across multiple ancestries.Briefings in bioinformatics · 2026Article
- A flexible framework for robust and efficient Mendelian randomization with debiasing.Briefings in bioinformatics · 2026Article
- A Mendelian randomization-based drug repurposing pipeline: application to lipid traits and coronary artery disease.medRxiv : the preprint server for health sciences · 2026Article
- Simulated sample splitting approach to address biases due to instrument selection and participant overlap in two-sample Mendelian Randomization studies.PLoS genetics · 2026Article
- Estimating causal effects of C-reactive protein on disease and health outcomes using multivariable Mendelian randomization adjusting for heritable confounding.International journal of epidemiology · 2026Article
- Methods for Prioritizing Causal Genes in Molecular Studies of Human Disease: The State of the Art.Genetic epidemiology · 2026Review
- MRBEE-TL: improving causal effect estimation in multi-ancestry multivariable Mendelian randomization with transfer learning.Genome biology · 2026Article
- Mind the gap: Characterizing bias due to population mismatch in two-sample Mendelian randomization.American journal of human genetics · 2026Article
- Exploring the Relationship Between Caffeine Consumption, Caffeine Metabolism, and Sleep Behaviours: A Mendelian Randomisation Study.Journal of sleep research · 2026Article
- Extending the Use of Mendelian Randomisation With Non-Inherited Variants to Assess Socially Transmitted Parental Exposures Under Assortative Mating.Genetic epidemiology · 2026Article
- Improving estimation efficiencies for family-based GWAS by integrating large external data.medRxiv : the preprint server for health sciences · 2025Article
- Analysis of spermidine's effect on coronary heart disease risk using bidirectional Mendelian randomization and LC-MS/MS.Hereditas · 2025Article
- Integrative Mendelian randomization for detecting exposure-by-group interactions using group-specific and combined summary statistics.PLoS genetics · 2025Article
- RMR-ICP: robust Mendelian randomization method accounting for idiosyncratic and correlated pleiotropy with applications to stroke outcomes.Briefings in bioinformatics · 2025Article
- Improving causal effect estimation in multi-ancestry multivariable Mendelian randomization with transfer learning.bioRxiv : the preprint server for biology · 2025Article
- Mind the gap: characterizing bias due to population mismatch in two-sample Mendelian randomization.medRxiv : the preprint server for health sciences · 2025Article
3 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 5 institutions in 2 countries.
Funding
Abstract
Over a decade of genome-wide association studies (GWAS) have led to the finding of extreme polygenicity of complex traits. The phenomenon that "all genes affect every complex trait" complicates Mendelian Randomization (MR) studies, where natural genetic variations are used as instruments to infer the causal effect of heritable risk factors. We reexamine the assumptions of existing MR methods and show how they need to be clarified to allow for pervasive horizontal pleiotropy and heterogeneous effect sizes. We propose a comprehensive framework GRAPPLE to analyze the causal effect of target risk factors with heterogeneous genetic instruments and identify possible pleiotropic patterns from data. By using GWAS summary statistics, GRAPPLE can efficiently use both strong and weak genetic instruments, detect the existence of multiple pleiotropic pathways, determine the causal direction and perform multivariable MR to adjust for confounding risk factors. With GRAPPLE, we analyze the effect of blood lipids, body mass index, and systolic blood pressure on 25 disease outcomes, gaining new information on their causal relationships and potential pleiotropic pathways involved.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.