The power of meta-analysis in genome-wide association studies.

paper Cited Public

Authors: Panagiotou, Orestis A; Willer, Cristen J; Hirschhorn, Joel N; Ioannidis, John P A
Year: 2013
Journal: Annual review of genomics and human genetics
PMID: 23724904
DOI: 10.1146/annurev-genom-091212-153520
PMCID: PMC4040957

#	Section	Preview
0	INTRODUCTION	The advent of genome-wide association (GWA) studies has led to the discovery of hundreds of…
1	INTRODUCTION	Over the last years, GWA studies have made major contributions to the efforts of gene mapping (2,…
2	INTRODUCTION	As a statistical method which allows the quantitative synthesis of results from different studies in…
3	INTRODUCTION	GWA meta-analysis has been made feasible due to technical advances in imputation of missing…
4	INTRODUCTION	In this review, we demonstrate the power of meta-analysis in GWA studies by summarizing the…
5	PART 1: EMPIRICAL APPRAISAL OF PUBLISHED GWA META-ANALYSES — 1.1. METHODS	We searched the publicly available database “A Catalog of Published Genome-Wide Association…
6	PART 1: EMPIRICAL APPRAISAL OF PUBLISHED GWA META-ANALYSES — 1.1. METHODS	We identified GWA studies with a sample size ≥10,000 in the discovery stage. We used this…
7	PART 1: EMPIRICAL APPRAISAL OF PUBLISHED GWA META-ANALYSES — 1.1. METHODS	From each eligible GWA report and the corresponding meta-analyses, we extracted the following…
8	PART 1: EMPIRICAL APPRAISAL OF PUBLISHED GWA META-ANALYSES — 1.1. METHODS	Additionally, from each eligible GWA meta-analysis we extracted the independent SNPs discovered and…
9	PART 1: EMPIRICAL APPRAISAL OF PUBLISHED GWA META-ANALYSES — 1.2. RESULTS	As of June 15, 2012, the catalog included a total of 1,271 published GWA reports. Of those, 88…
10	PART 1: EMPIRICAL APPRAISAL OF PUBLISHED GWA META-ANALYSES — 1.2. RESULTS	As shown in Supplementary Table 1, for all but 2 meta-analyses the respective individual studies…
11	PART 1: EMPIRICAL APPRAISAL OF PUBLISHED GWA META-ANALYSES — 1.2. RESULTS	while additional models had been used in a total of 16 meta-analyses pertaining to random-effects…
12	PART 1: EMPIRICAL APPRAISAL OF PUBLISHED GWA META-ANALYSES — 1.2. RESULTS	the Mantel-Haenszel effect-size based method. The median number of SNPs discovered, i.e. passing the…
13	PART 1: EMPIRICAL APPRAISAL OF PUBLISHED GWA META-ANALYSES — 1.2. RESULTS	Supplementary Table 2 shows the SNP quality control criteria used in the eligible 88 GWA reports. In…
14	PART 1: EMPIRICAL APPRAISAL OF PUBLISHED GWA META-ANALYSES — 1.2. RESULTS	used 97%, 4 used 98%, and 2 used 99%. The P-value used to denote deviation from HWE varied from…
15	PART 1: EMPIRICAL APPRAISAL OF PUBLISHED GWA META-ANALYSES — 1.2. RESULTS	Supplementary Table 3 shows the selected genome-wide significance thresholds, the methods of…
16	PART 1: EMPIRICAL APPRAISAL OF PUBLISHED GWA META-ANALYSES — 1.2. RESULTS	observed differences in results are compatible with chance. I2 measures the percentage of…
17	PART 1: EMPIRICAL APPRAISAL OF PUBLISHED GWA META-ANALYSES — 1.2. RESULTS	Replication efforts had been performed for the results of 104 meta-analyses, showing that the…
18	PART 1: EMPIRICAL APPRAISAL OF PUBLISHED GWA META-ANALYSES — 1.2. RESULTS	As shown in Supplementary Table 4, the results of only 27 (19%) meta-analyses used populations of…
19	PART 1: EMPIRICAL APPRAISAL OF PUBLISHED GWA META-ANALYSES — 1.2. RESULTS	and internal carotid intima media thickness and plaque); from using different definitions of the…

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Four Genome-Wide Association Studies Identify New Extreme Longevity Variants.	Sebastiani P et al.	—	2017	→
GWAR: robust analysis and meta-analysis of genome-wide association studies.	Dimou NL et al.	—	2017	→
The Genetic Architecture of Gene Expression in Peripheral Blood.	Lloyd-Jones LR et al.	—	2017	→
The genetic epidemiology of substance use disorder: A review.	Prom-Wormley EC et al.	—	2017	→
Trends in published meta-analyses in cancer research, 2008-2013.	Qadir XV et al.	—	2017	→
Exposure-wide epidemiology: revisiting Bradford Hill.	Ioannidis JP	—	2016	→
Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function.	Pattaro C et al.	—	2016	→
Genome-wide association studies and resting heart rate.	Kilpeläinen TO	—	2016	→
Genome-wide association studies in pediatric chronic kidney disease.	Gupta J et al.	—	2016	→
Identification of IDUA and WNT16 Phosphorylation-Related Non-Synonymous Polymorphisms for Bone Mineral Density in Meta-Analyses of Genome-Wide Association Studies.	Niu T et al.	—	2016	→
Multivariate Analysis of Anthropometric Traits Using Summary Statistics of Genome-Wide Association Studies from GIANT Consortium.	Park H et al.	—	2016	→
Neuronal networks in mental diseases and neuropathic pain: Beyond brain derived neurotrophic factor and collapsin response mediator proteins.	Quach TT et al.	—	2016	→
The Mass Production of Redundant, Misleading, and Conflicted Systematic Reviews and Meta-analyses.	Ioannidis JP	—	2016	→
A genome-wide pleiotropy scan for prostate cancer risk.	Panagiotou OA et al.	—	2015	→
A review of study designs and statistical methods for genomic epidemiology studies using next generation sequencing.	Wang Q et al.	—	2015	→
A systematic appraisal of field synopses in genetic epidemiology: a HuGE review.	Belbasis L et al.	—	2015	→
Design and Implementation of the International Genetics and Translational Research in Transplantation Network.	International Genetics & Translational Research in Transplantation Network (iGeneTRAiN)	—	2015	→
Genetics and brain morphology.	Strike LT et al.	—	2015	→
Genome-wide association meta-analysis identifies novel variants associated with fasting plasma glucose in East Asians.	Hwang JY et al.	—	2015	→
Identification of a novel FGFRL1 MicroRNA target site polymorphism for bone mineral density in meta-analyses of genome-wide association studies.	Niu T et al.	—	2015	→
Models to explore genetics of human aging.	Karasik D et al.	—	2015	→
Replication of ZNF804A gene variant associations with risk of heroin addiction.	Hancock DB et al.	—	2015	→
Statistical and Computational Methods for Genetic Diseases: An Overview.	Camastra F et al.	—	2015	→
The catalase C-262T gene polymorphism and cancer risk: a systematic review and meta-analysis.	Shen Y et al.	—	2015	→
The dawning age of genetic testing for sports injuries.	Goodlin GT et al.	—	2015	→
Diverse convergent evidence in the genetic analysis of complex disease: coordinating omic, informatic, and experimental evidence to better identify and validate risk factors.	Ciesielski TH et al.	—	2014	→
GACT: a Genome build and Allele definition Conversion Tool for SNP imputation and meta-analysis in genetic association studies.	Sulovari A et al.	—	2014	→
Genetic studies of major depressive disorder: why are there no genome-wide association study findings and what can we do about it?	Levinson DF et al.	—	2014	→
How to make more published research true.	Ioannidis JP	—	2014	→
Molecular basis and genetic predisposition to intracranial aneurysm.	Tromp G et al.	—	2014	→
Publication and other reporting biases in cognitive sciences: detection, prevalence, and prevention.	Ioannidis JP et al.	—	2014	→
Research: increasing value, reducing waste - Authors' reply.	Glasziou P et al.	—	2014	→
SecureMA: protecting participant privacy in genetic association meta-analysis.	Xie W et al.	—	2014	→
Using previously genotyped controls in genome-wide association studies (GWAS): application to the Stroke Genetics Network (SiGN).	Mitchell BD et al.	—	2014	→
Meta-analysis methods for genome-wide association studies and beyond.	Evangelou E et al.	—	2013	→
To replicate or not to replicate: the case of pharmacogenetic studies: Have pharmacogenomics failed, or do they just need larger-scale evidence and more replication?	Ioannidis JP	—	2013	→