ArticleNature communications2021
Graphical analysis for phenome-wide causal discovery in genotyped population-scale biobanks.
Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.
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Who cites it
13 citing papers in PubMed, 2 syntheses or guidelines pooled it, 24 citations in OpenAlex.
- Causal inference in the diagnosis and prognosis of ovarian cancer: current state and future directions.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025Pooled it
- Pooled it
- Causal inference for multiple risk factors and diseases from genomics data.Nature communications · 2026Article
- Methods for Prioritizing Causal Genes in Molecular Studies of Human Disease: The State of the Art.Genetic epidemiology · 2026Review
- The link between red blood cell distribution width and 3-month prognosis in acute ischemic stroke patients: a secondary analysis of a cohort study.BMC neurology · 2025Article
- Association between red blood cell distribution width and encephalitis based on the pediatric intensive care unit database: a cross-sectional study.Frontiers in neurology · 2025Article
- A novel constraint-based structure learning algorithm using marginal causal prior knowledge.Scientific reports · 2024Article
- MRSL: a causal network pruning algorithm based on GWAS summary data.Briefings in bioinformatics · 2024Article
- Correlation between diabetic retinopathy and diabetic nephropathy: a two-sample Mendelian randomization study.Frontiers in endocrinology · 2023Article
- Association of red cell distribution width with the risk of 3-month readmission in patients with heart failure: A retrospective cohort study.Frontiers in cardiovascular medicine · 2023Article
- A review of causal discovery methods for molecular network analysis.Molecular genetics & genomic medicine · 2022Review
- Genetic estimates of correlation and causality between blood-based biomarkers and psychiatric disorders.Science advances · 2022Article
- Confirmation of the superior performance of the causal Graphical Analysis Using Genetics (cGAUGE) pipeline in comparison to various competing alternatives.Wellcome open research · 2022Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
Causal inference via Mendelian randomization requires making strong assumptions about horizontal pleiotropy, where genetic instruments are connected to the outcome not only through the exposure. Here, we present causal Graphical Analysis Using Genetics (cGAUGE), a pipeline that overcomes these limitations using instrument filters with provable properties. This is achievable by identifying conditional independencies while examining multiple traits. cGAUGE also uses ExSep (Exposure-based Separation), a novel test for the existence of causal pathways that does not require selecting instruments. In simulated data we illustrate how cGAUGE can reduce the empirical false discovery rate by up to 30%, while retaining the majority of true discoveries. On 96 complex traits from 337,198 subjects from the UK Biobank, our results cover expected causal links and many new ones that were previously suggested by correlation-based observational studies. Notably, we identify multiple risk factors for cardiovascular disease, including red blood cell distribution width.
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