Meta-analysis can be a powerful way to reveal otherwise hidden or unclear associations, when done with care. In line with recent trends in biomedical literature (1), PLOS ONE has seen a consistent increase in submissions reporting meta-analyses of genetic association studies over the last few years. These submissions report analyses of potential associations between candidate gene variants (usually single nucleotide polymorphisms, or SNPs) and specific disease risks and outcomes in human populations, based on a search of the literature to identify published reports studying the association and statistical analyses that synthesize the results of the identified studies.

However, researchers in the community, among them members of our editorial board, have raised concerns about some of these meta-analyses, including the risk of false positives due to publication bias, incomplete searches of the literature, redundancy, and an insufficient assessment of the power and quality of the included studies. As noted a decade ago, “Meta-analysis is not a replacement for adequately powered genetic association studies” (2).  Many of these studies focus on a single gene variant, and many do not include data from relevant genome-wide association  studies (GWAS), some of which have failed to replicate previously reported associations between candidate genes and diseases.

While many meta-analyses of genetic association studies are still clinically relevant, especially those studying rare conditions where GWAS data are not available, and well-conducted meta-analyses can provide useful and valid clinical evidence, we strongly feel that meta-analyses of genetic association studies considered by PLOS ONE must have the rationale clearly explained and that authors must report their studies according to high standards.

In order to address these concerns and after consultation with PLOS ONE editorial board members, we are introducing a new process to handle meta-analyses of genetic association studies. Authors will now be asked to provide the following information:

1. The rationale for conducting the meta-analysis;
2. The contribution that the meta-analysis makes to knowledge in light of previously published related reports, including other meta-analyses and systematic reviews;
3. Whether GWASs relevant to the meta-analysis have been published and whether these were included in the analysis;
4. Full methodological details for the meta-analysis, including completion of a checklist that has been developed with reference to several published guidelines (3, 4, 5) and in consultation with members of the PLOS ONE editorial board.

The information supplied by the authors will be evaluated by the in-house editorial team as part of the checks undertaken on new submissions. Meta-analyses replicating studies in the literature without adequate justification will be rejected. For those manuscripts that proceed to review, PLOS ONE Academic Editors will be consulted on the adequacy of the methodological aspects of the study and the quality of the reporting in the manuscript.

This process underscores our commitment to maintaining high standards of quality and reporting in publications at PLOS ONE. We are grateful for the input we have received from our editorial board that led to this new process, and wish to thank the PLOS ONE Academic Editors who provided advice and guidance.

If you have any questions or feedback, or if you are an author who would like additional information about our requirements for meta-analyses of genetic association studies, please contact us at plosone@plos.org.

Posted on behalf of the in-house editors at PLOS ONE:

Associate Editors Gina Alvino, Meghan Byrne, Christna Chap, Michelle Dohm, Matt Hodgkinson, Alejandra Clark and Nicola Stead and; Senior Editors Eric Martens and Iratxe Puebla; and Editorial Director Damian Pattinson

1. Ioannidis JPA, Chang CQ, Lam TK, Schully SD, Khoury MJ (2013) The Geometric Increase in Meta-Analyses from China in the Genomic Era. PLOS ONE 8(6): e65602. doi:10.1371/journal.pone.0065602
2. Marcus R. Munafò and Jonathan Flint (2004) Meta-analysis of genetic association studies. Trends Genet. 20(9):439-44 doi:10.1016/j.tig.2004.06.014
3. Sagoo GS, Little J, Higgins JPT (2009) Systematic Reviews of Genetic Association Studies. PLOS Med 6(3): e1000028. doi:10.1371/journal.pmed.1000028
4. Minelli C, Thompson JR, Abrams KR, Thakkinstian A, Attia J: The quality of meta-analyses of genetic association studies: a review with recommendations. Am J Epidemiol. 2009 Dec 1;170(11):1333-43. doi: 10.1093/aje/kwp350
5. Little J, Higgins JP, Ioannidis JP, Moher D, Gagnon F, et al. (2009) STrengthening the REporting of Genetic Association Studies (STREGA)- An Extension of the STROBE Statement. PLOS Med 6(2): e1000022. doi:10.1371/journal.pmed.1000022

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