The Power of Meta-Analysis in Genome-Wide Association Studies

Panagiotou, Orestis A.; Willer, Cristen J.; Hirschhorn, Joel N.; Ioannidis, John P. A.

doi:10.1146/annurev-genom-091212-153520

Cited by 116 publications

(94 citation statements)

References 104 publications

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“…This has transformed the reliability of genetic research, with fewer but more robust genetic signals now being identified [59]. The successful transformation has required international collaboration, the combination of data in large consortia, and the adoption of rigorous replication practices in meta-analysis within consortia [60, 61]. …”

Section: Empirical Evidence For Publication and Other Reporting Biasementioning

confidence: 99%

Publication and other reporting biases in cognitive sciences: detection, prevalence, and prevention

Ioannidis

Munafò

Fusar‐Poli

et al. 2014

Trends in Cognitive Sciences

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430

373

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Recent systematic reviews and empirical evaluations of the cognitive sciences literature suggest that publication and other reporting biases are prevalent across diverse domains of cognitive science. This review summarizes the various forms of publication and reporting biases and other questionable research practices, and overviews the available methods for probing into their existence. We discuss the available empirical evidence for the presence of such biases across the neuroimaging, animal, other pre-clinical, psychological, clinical trials, and genetics literature in the cognitive sciences. We also highlight emerging solutions (from study design to data analyses and reporting) to prevent bias and improve the fidelity in the field of cognitive science research.

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Section: Empirical Evidence For Publication and Other Reporting Biasementioning

confidence: 99%

Publication and other reporting biases in cognitive sciences: detection, prevalence, and prevention

Ioannidis

Munafò

Fusar‐Poli

et al. 2014

Trends in Cognitive Sciences

Self Cite

430

373

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“…These consortia-based genetic association studies aggregate GWAS data from individual studies in order to address the need to increase sample size and improve power to detect significant associations. Consortia-based genetic association studies often use meta-analyses and report summary data submitted across studies or analyze raw data from multiple GWASs (Panagiotou et al, 2013). …”

Section: Genetic Association Studiesmentioning

confidence: 99%

The genetic epidemiology of substance use disorder: A review

Prom‐Wormley

Ebejer

Dick

et al. 2017

Drug and Alcohol Dependence

128

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Background Substance use disorder (SUD) remains a significant public health issue. A greater understanding of how genes and environment interact to regulate phenotypes comprising SUD will facilitate directed treatments and prevention. Methods The literature studying the neurobiological correlates of SUD with a focus on the genetic and environmental influences underlying these mechanisms was reviewed. Results from twin/family, human genetic association, gene-environment interaction, epigenetic literature, phenome-wide association studies are summarized for alcohol, nicotine, cannabinoids, cocaine, and opioids. Results There are substantial genetic influences on SUD that are expected to influence multiple neurotransmission pathways, and these influences are particularly important within the dopaminergic system. Genetic influences involved in other aspects of SUD etiology including drug processing and metabolism are also identified. Studies of gene-environment interaction emphasize the importance of environmental context in SUD. Epigenetic studies indicate drug-specific changes in gene expression as well as differences in gene expression related to the use of multiple substances. Further, gene expression is expected to differ by stage of SUD such as substance initiation versus chronic substance use. While a substantial literature has developed for alcohol and nicotine use disorders, there is comparatively less information for other commonly abused substances. Conclusions A better understanding of genetically-mediated mechanisms involved in the neurobiology of SUD provides increased opportunity to develop behavioral and biologically based treatment and prevention of SUD.

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“…This kind of relationship was previously described for height, lipid levels and blood pressure as examples, showing a linear or more rapid increase in “hits” above the inflection point. (4) The likely explanation is that the genetic contributions to these traits are predominantly polygenic, with each associated SNP making a small additive contribution to risk. Below the inflection point, samples are underpowered to reliably detect even the strongest (individually small) common SNP effects; above the inflection point, numerous weaker effects are detected in a more or less linear fashion.…”

mentioning

confidence: 99%