SynthesisAnnals of human genetics2016
Exploring the Major Sources and Extent of Heterogeneity in a Genome-Wide Association Meta-Analysis.
Synthesis in Annals of human genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- A comprehensive compilation of data on the association between XRCC3 polymorphisms and thyroid cancer susceptibility.BMC endocrine disorders · 2025Pooled it
- The effect of pharmacist-led interventions on the appropriateness and clinical outcomes of anticoagulant therapy: a systematic review and meta-analysis.European heart journal. Quality of care & clinical outcomes · 2024Pooled it
- Famine Exposure during Early Life and Risk of Cancer in Adulthood: A Systematic Review and Meta-Analysis.The journal of nutrition, health & aging · 2023Pooled it
- Genome-Wide Association Study to Identify Genetic Variants Associated With Diabetic Maculopathy.Investigative ophthalmology & visual science · 2025Article
- MTCH2 in Metabolic Diseases, Neurodegenerative Diseases, Cancers, Embryonic Development and Reproduction.Drug design, development and therapy · 2024Review
- sPLINK: a hybrid federated tool as a robust alternative to meta-analysis in genome-wide association studies.Genome biology · 2022Article
- Reliability of genomic variants across different next-generation sequencing platforms and bioinformatic processing pipelines.BMC genomics · 2021Observational
- Genetic Studies of Metabolic Syndrome in Arab Populations: A Systematic Review and Meta-Analysis.Frontiers in genetics · 2021Review
- Obesity as a risk factor for malignant melanoma and non-melanoma skin cancer.Reviews in endocrine & metabolic disorders · 2016Review
- Efficacy and safety of full-thickness versus circular peroral endoscopic myotomy for treatment of achalasia: a systematic review and meta-analysis.Annals of gastroenterologyArticle
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Genome-wide association (GWA) meta-analysis has become a popular approach for discovering genetic variants responsible for complex diseases. The between-study heterogeneity effect is a severe issue that may complicate the interpretation of results. Aiming to improve the interpretation of meta-analysis results, we empirically explored the extent and source of heterogeneity effect. We analyzed a previously reported GWA meta-analysis of obesity, in which over 21,000 subjects from seven individual samples were meta-analyzed. We first evaluated the extent and distribution of heterogeneity across the entire genome. We then studied the effects of several potentially confounding factors, including age, ethnicity, gender composition, study type, and genotype imputation on heterogeneity with a random-effects meta-regression model. Of the total 4,325,550 SNPs being tested, heterogeneity was moderate to very large for 25.4% of the total SNPs. Heterogeneity was more severe in SNPs with stronger association signals. Ethnicity, average age, and genotype imputation accuracy had significant effects on the heterogeneity. Exploring the effects of ethnicity can provide clues to the potential ethnic-specific effects for two loci known to affect obesity, MC4R, and MTCH2. Our analysis can help to clarify understanding of the obesity mechanism and may provide guidance for an effective design of future GWA meta-analysis.
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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.