TY - JOUR
T1 - Strengthening the reporting of genetic association studies (STREGA)-an extension of the strengthening the reporting of observational studies in epidemiology (STROBE) statement
AU - Little, Julian
AU - Higgins, Julian P.T.
AU - Ioannidis, John P.A.
AU - Moher, David
AU - Gagnon, France
AU - von Elm, Erik
AU - Khoury, Muin J.
AU - Cohen, Barbara
AU - Davey-Smith, George
AU - Grimshaw, Jeremy
AU - Scheet, Paul
AU - Gwinn, Marta
AU - Williamson, Robin E.
AU - Zou, Guang Yong
AU - Hutchings, Kim
AU - Johnson, Candice Y.
AU - Tait, Valerie
AU - Wiens, Miriam
AU - Golding, Jean
AU - van Duijn, Cornelia
AU - McLaughlin, John
AU - Paterson, Andrew
AU - Wells, George
AU - Fortier, Isabel
AU - Freedman, Matthew
AU - Zecevic, Maja
AU - King, Richard
AU - Infante-Rivard, Claire
AU - Stewart, Alex F.
AU - Birkett, Nick
N1 - Funding Information:
The authors thank Kyle Vogan and Allen Wilcox for their participation in the workshop and for their comments; Michele Cargill (Affymetrix Inc) and Aaron del Duca (DNA Genotek) for their participation in the workshop as observers; and the Public Population Project in Genomics (P 3 G), hosted by the University of Montreal and supported by Genome Canada and Genome Quebec. This article was made possible by the input and discussion by the P 3 G International Working Group on Epidemiology and Biostatistics—discussion held in Montreal, May 2007. The authors also thank the reviewers for their very thoughtful feedback, and Silvia Visentin, Rob Moriarity, Morgan Macneill, and Valery L'Heureux for administrative support. The authors were unable to contact Barbara Cohen to confirm her involvement in the latest version of this article.
Funding Information:
Grant support: by the Institutes of Genetics and of Nutrition, Metabolism and Diabetes, Canadian Institutes of Health Research; Genome Canada; Biotechnology, Genomics and Population Health Branch, Public Health Agency of Canada; Affymetrix; DNA Genotek; TrialStat!; and GeneSens. The funders had no role in the decision to submit the article or in its preparation.
PY - 2009/6
Y1 - 2009/6
N2 - Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence, the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association (STREGA) studies initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed, but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.
AB - Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence, the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association (STREGA) studies initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modeling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed, but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.
KW - Epidemiology
KW - Gene-disease associations
KW - Gene-environment interaction
KW - Genetics
KW - Genome-wide association
KW - Meta-analysis
KW - Reporting recommendations
KW - Systematic review
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U2 - 10.1016/j.jclinepi.2008.12.004
DO - 10.1016/j.jclinepi.2008.12.004
M3 - Article
C2 - 19217256
AN - SCOPUS:67349252770
SN - 0895-4356
VL - 62
SP - 597-608.e4
JO - Journal of clinical epidemiology
JF - Journal of clinical epidemiology
IS - 6
ER -