ReviewAnnual review of biomedical data science2022
Phenotypic Causal Inference Using Genome-Wide Association Study Data: Mendelian Randomization and Beyond.
Review in Annual review of biomedical data science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
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.
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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
29 citing papers in PubMed.
- Inferring multi-organ genetic connections using imaging and clinical data through Mendelian randomization.Nature biomedical engineering · 2026Article
- Poor sleep is robustly correlated with accelerated aging but the evidence for causation is mixed.medRxiv : the preprint server for health sciences · 2026Article
- Article
- LYPLAL1 rare loss-of-function variants in humans and deletion in human hepatoma cells protect against MASLD.Journal of lipid research · 2026Article
- Identifying prioritization of potential targets for idiopathic pulmonary fibrosis: Proteome-wide Mendelian randomization and colocalization analyses.Clinics (Sao Paulo, Brazil) · 2026Article
- Leveraging large-scale biobanks for therapeutic target discovery.HGG advances · 2026Article
- Identification of potential therapeutic targets for idiopathic pulmonary fibrosis: an integrated multiomics analysis.Frontiers in immunology · 2026Article
- RNA variation as the driver of genomic efficiency and phenotypic complexity.International journal of biological sciences · 2026Review
- Epstein-Barr virus-related antibody traits and idiopathic pulmonary fibrosis: a bidirectional Mendelian randomization study.Archives of medical science : AMS · 2026Article
- MICA protein as a plasma biomarker for dermatomyositis with malignancy: a proteome-wide Mendelian randomization and ELISA study.Clinical rheumatology · 2026Article
- Deciphering the Causal Links Among Metabolomics, Ageing Phenotypes, and Pathological Scars: A Two-Sample Mendelian Randomization Study.Clinical, cosmetic and investigational dermatology · 2026Article
- The causal association between psychiatric disorders and gynecological cancer: a bidirectional Mendelian randomization study.Discover oncology · 2025Article
- A Multi-omics Exploration Revealing SLIT2 as a Prime Therapeutic Target for Peripheral Facial Paralysis: Integrating Single-Cell Transcriptomics and Plasma Proteome Data.Cellular and molecular neurobiology · 2025Article
- Understanding the risk of diabetic retinopathy from glucagon-like peptide-1 receptor agonists: a Mendelian randomization study and systematic review of European populations.Diabetology & metabolic syndrome · 2025Article
- Obsessive-compulsive symptoms in individuals with a history of eating disorders.Journal of affective disorders · 2025Observational
- The Causal Relationships and Therapeutic Targets of Plasma Proteins in Ankylosing Spondylitis.Biomedicines · 2025Article
- Integrated Single-Cell RNA Sequencing and Proteome-Wide Mendelian Randomization Identifies Therapeutic Targets for Psoriasis and Associated Complications.Psoriasis (Auckland, N.Z.) · 2025Article
- Article
- A Two-Sample Mendelian Randomization Study of Basophil Count and Risk of Gestational Diabetes Mellitus.International journal of women's health · 2025Article
- Exploring Potential Drug Targets in Multiple Cardiovascular Diseases: A Study Based on Proteome-Wide Mendelian Randomization and Colocalization Analysis.Cardiovascular therapeutics · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
statistics for genome-wide association studies (GWAS) are increasingly available for downstream analyses. Meanwhile, the popularity of causal inference methods has grown as we look to gather robust evidence for novel medical and public health interventions. This has led to the development of methods that use GWAS summary statistics for causal inference. Here, we describe these methods in order of their escalating complexity, from genetic associations to extensions of Mendelian randomization that consider thousands of phenotypes simultaneously. We also cover the assumptions and limitations of these approaches before considering the challenges faced by researchers performing causal inference using GWAS data. GWAS summary statistics constitute an important data source for causal inference research that offers a counterpoint to nongenetic methods when triangulating evidence. Continued efforts to address the challenges in using GWAS data for causal inference will allow the full impact of these approaches to be realized.
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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.