SynthesisGenetic epidemiology2010
Meta-analysis of genome-wide association studies: no efficiency gain in using individual participant data.
Synthesis in Genetic epidemiology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 89 papers, 24 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
89 citing papers in PubMed, 24 syntheses or guidelines pooled it.
- Pan-UK Biobank genome-wide association analyses enhance discovery and resolution of ancestry-enriched effects.Nature genetics · 2025Pooled it
- Genome-wide association analysis using multiple Atlantic salmon populations.Genetics, selection, evolution : GSE · 2025Pooled it
- Meta-analysis of Diurnal Transcriptomics in Mouse Liver Reveals Low Repeatability of Rhythm Analyses.Journal of biological rhythms · 2023Pooled it
- Demonstrating paths for unlocking the value of cloud genomics through cross cohort analysis.Nature communications · 2023Pooled it
- Powerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies.Nature genetics · 2023Pooled it
- Circulating ceramides and sphingomyelins and the risk of incident cardiovascular disease among people with diabetes: the strong heart study.Cardiovascular diabetology · 2022Pooled it
- TwinEQTL: ultrafast and powerful association analysis for eQTL and GWAS in twin studies.Genetics · 2022Pooled it
- Incorporating European GWAS findings improve polygenic risk prediction accuracy of breast cancer among East Asians.Genetic epidemiology · 2021Pooled it
- Non-del(5q) myelodysplastic syndromes-associated loci detected by SNP-array genome-wide association meta-analysis.Blood advances · 2019Pooled it
- Meta-analysis of genome-wide association studies provides insights into genetic control of tomato flavor.Nature communications · 2019Pooled it
- Associations of circulating very-long-chain saturated fatty acids and incident type 2 diabetes: a pooled analysis of prospective cohort studies.The American journal of clinical nutrition · 2019Pooled it
- Traumatic stress and accelerated DNA methylation age: A meta-analysis.Psychoneuroendocrinology · 2018Pooled it
- Improved score statistics for meta-analysis in single-variant and gene-level association studies.Genetic epidemiology · 2018Pooled it
- Meta-analysis of sequence-based association studies across three cattle breeds reveals 25 QTL for fat and protein percentages in milk at nucleotide resolution.BMC genomics · 2017Pooled it
- Meta-analysis of quantitative pleiotropic traits for next-generation sequencing with multivariate functional linear models.European journal of human genetics : EJHG · 2017Pooled it
- Meta-Analysis for Penalized Regression Methods with Multi-Cohort Genome-Wide Association Studies.Human heredity · 2016Pooled it
- An empirical comparison of meta-analysis and mega-analysis of individual participant data for identifying gene-environment interactions.Genetic epidemiology · 2014Pooled it
- On individual genome-wide association studies and their meta-analysis.Human genetics · 2014Pooled it
- Meta-analysis of gene-level associations for rare variants based on single-variant statistics.American journal of human genetics · 2013Pooled it
- A mega-analysis of genome-wide association studies for major depressive disorder.Molecular psychiatry · 2013Pooled it
29 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
To identify genetic variants with modest effects on complex human diseases, a growing number of networks or consortia are created for sharing data from multiple genome-wide association studies on the same disease or related disorders. A central question in this enterprise is whether to obtain summary results or individual participant data from relevant studies. We show theoretically and numerically that meta-analysis of summary results is statistically as efficient as joint analysis of individual participant data (provided that both analyses are performed properly under the same modeling assumptions). We illustrate this equivalence with case-control data from the Finland-United States Investigation of NIDDM Genetics (FUSION) study. Collating only summary results will increase the number and representativeness of available studies, simplify data collection and analysis, reduce resource utilization, and accelerate discovery.
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What OpenQuestion holds
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.