SynthesisHuman genetics2014
On individual genome-wide association studies and their meta-analysis.
Synthesis in Human genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 6 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 6 syntheses or guidelines pooled it.
- Meta-regression of genome-wide association studies to estimate age-varying genetic effects.European journal of epidemiology · 2024Pooled it
- Risk of type 2 diabetes and KCNJ11 gene polymorphisms: a nested case-control study and meta-analysis.Scientific reports · 2022Pooled it
- Four pleiotropic loci associated with fat mass and lean mass.International journal of obesity (2005) · 2020Pooled it
- Association of 3q13.32 variants with hip trochanter and intertrochanter bone mineral density identified by a genome-wide association study.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2016Pooled it
- Exploring the Major Sources and Extent of Heterogeneity in a Genome-Wide Association Meta-Analysis.Annals of human genetics · 2016Pooled it
- Multistage genome-wide association meta-analyses identified two new loci for bone mineral density.Human molecular genetics · 2014Pooled it
- Article
- Article
- Identifying novel associations in GWAS by hierarchical Bayesian latent variable detection of differentially misclassified phenotypes.BMC bioinformatics · 2020Article
- Identification of novel functional CpG-SNPs associated with type 2 diabetes and coronary artery disease.Molecular genetics and genomics : MGG · 2020Article
- Identifying Pleiotropic SNPs Associated With Femoral Neck and Heel Bone Mineral Density.Frontiers in genetics · 2020Article
- Identifying Multi-Omics Causers and Causal Pathways for Complex Traits.Frontiers in genetics · 2019Article
- Gene-based GWAS analysis for consecutive studies of GEFOS.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2018Article
- Improved detection of genetic loci in estimated glomerular filtration rate and type 2 diabetes using a pleiotropic cFDR method.Molecular genetics and genomics : MGG · 2018Article
- Article
- Identification of novel genetic loci for osteoporosis and/or rheumatoid arthritis using cFDR approach.PloS one · 2017Article
- Genetics of structural connectivity and information processing in the brain.Brain structure & function · 2016Article
- Genome-wide Association Studies for Osteoporosis: A 2013 Update.Journal of bone metabolism · 2014Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Individual genome-wide association (GWA) studies and their meta-analyses represent two approaches for identifying genetic loci associated with complex diseases/traits. Inconsistent findings and non-replicability between individual GWA studies and meta-analyses are commonly observed, hence posing the critical question as to how to interpret their respective results properly. In this study, we performed a series of simulation studies to investigate and compare the statistical properties of the two approaches. Our results show that (1) as expected, meta-analysis of larger sample size is more powerful than individual GWA studies under the ideal setting of population homogeneity among individual studies; (2) under the realistic setting of heterogeneity among individual studies, detection of heterogeneity is usually difficult and meta-analysis (even with the random-effects model) may introduce elevated false positive and/or negative rates; (3) despite relatively small sample size, well-designed individual GWA study has the capacity to identify novel loci for complex traits; (4) replicability between meta-analysis and independent individual studies or between independent meta-analyses is limited, and thus inconsistent findings are not unexpected.
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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.