ArticlePLoS genetics2012
Interpreting meta-analyses of genome-wide association studies.
Article in PLoS genetics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 115 papers, 29 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
115 citing papers in PubMed, 29 syntheses or guidelines pooled it.
- Intrinsic Factors Influencing Simvastatin and Simvastatin Acid Pharmacokinetics: Age-Related Studies in Thai Adults and Cross-Population Comparisons.Clinical and translational science · 2026Pooled it
- Genome-Wide Association Study Points to Novel Locus for Gilles de la Tourette Syndrome.Biological psychiatry · 2024Pooled it
- GenomeMUSter mouse genetic variation service enables multitrait, multipopulation data integration and analysis.Genome research · 2024Pooled it
- Genome-wide association study meta-analysis of blood pressure traits and hypertension in sub-Saharan African populations: an AWI-Gen study.Nature communications · 2023Pooled it
- Mouse phenome database: curated data repository with interactive multi-population and multi-trait analyses.Mammalian genome : official journal of the International Mammalian Genome Society · 2023Pooled it
- GWAS meta-analysis of over 29,000 people with epilepsy identifies 26 risk loci and subtype-specific genetic architecture.Nature genetics · 2023Pooled it
- Cross-trait analyses identify shared genetics between migraine, headache, and glycemic traits, and a causal relationship with fasting proinsulin.Human genetics · 2023Pooled it
- PheWAS and cross-disorder analysis reveal genetic architecture, pleiotropic loci and phenotypic correlations across 11 autoimmune disorders.Frontiers in immunology · 2023Pooled it
- Genetic Overlap Analysis Identifies a Shared Etiology between Migraine and Headache with Type 2 Diabetes.Genes · 2022Pooled it
- Cross-ancestry genome-wide meta-analysis of 61,047 cases and 947,237 controls identifies new susceptibility loci contributing to lung cancer.Nature genetics · 2022Pooled it
- Genetic characterization of outbred Sprague Dawley rats and utility for genome-wide association studies.PLoS genetics · 2022Pooled it
- Genetic overlap analysis of endometriosis and asthma identifies shared loci implicating sex hormones and thyroid signalling pathways.Human reproduction (Oxford, England) · 2022Pooled it
- Reviewing and assessing existing meta-analysis models and tools.Briefings in bioinformatics · 2021Pooled it
- Investigating Shared Genetic Basis Across Tourette Syndrome and Comorbid Neurodevelopmental Disorders Along the Impulsivity-Compulsivity Spectrum.Biological psychiatry · 2021Pooled it
- Association of theAnnals of the rheumatic diseases · 2020Pooled it
- Meta-Analysis Based on Nonconvex Regularization.Scientific reports · 2020Pooled it
- International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci.Nature communications · 2019Pooled it
- Meta-analysis of GWA studies provides new insights on the genetic architecture of skin pigmentation in recently admixed populations.BMC genetics · 2019Pooled it
- A Genome-Wide Association Study of Skin and Iris Pigmentation among Individuals of South Asian Ancestry.Genome biology and evolution · 2019Pooled it
- DNA Methylation Signatures of Depressive Symptoms in Middle-aged and Elderly Persons: Meta-analysis of Multiethnic Epigenome-wide Studies.JAMA psychiatry · 2018Pooled it
55 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
2 authors.
Funding
Abstract
Meta-analysis is an increasingly popular tool for combining multiple genome-wide association studies in a single analysis to identify associations with small effect sizes. The effect sizes between studies in a meta-analysis may differ and these differences, or heterogeneity, can be caused by many factors. If heterogeneity is observed in the results of a meta-analysis, interpreting the cause of heterogeneity is important because the correct interpretation can lead to a better understanding of the disease and a more effective design of a replication study. However, interpreting heterogeneous results is difficult. The standard approach of examining the association p-values of the studies does not effectively predict if the effect exists in each study. In this paper, we propose a framework facilitating the interpretation of the results of a meta-analysis. Our framework is based on a new statistic representing the posterior probability that the effect exists in each study, which is estimated utilizing cross-study information. Simulations and application to the real data show that our framework can effectively segregate the studies predicted to have an effect, the studies predicted to not have an effect, and the ambiguous studies that are underpowered. In addition to helping interpretation, the new framework also allows us to develop a new association testing procedure taking into account the existence of effect.
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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.