A road map for efficient and reliable human genome epidemiology

Ioannidis, John P. A.; Gwinn, Marta; Little, Julian; Higgins, Julian P T; Bernstein, Jonine L.; Boffetta, Paolo; Bondy, Melissa L.; Bray, Molly S.; Brenchley, Paul; Buffler, Patricia A.; Casas, Juan P.; Chokkalingam, Anand P.; Danesh, John; Smith, George Davey; Dolan, Siobhan M.; Duncan, Ross; Gruis, Nelleke A.; Hartge, Patricia; Hashibe, Mia; Hunter, David J.; Järvelin, Marjo‐Riitta; Malmer, Beatrice; Maraganore, Demetrius M.; Newton-Bishop, Julia; O’Brien, Thomas R.; Petersen, Gloria M.; Riboli, Elio; Salanti, Georgia; Seminara, Daniela; Smeeth, Liam; Taioli, Emanuela; Timpson, Nic; Uitterlinden, André G.; Víneis, Paolo; Wareham, Nick; Winn, Deborah M.; Zimmern, Ron; Khoury, Muin J.

doi:10.1038/ng0106-3

Cited by 220 publications

(122 citation statements)

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“…11,12 As many of the key elements in STROBE apply to these designs, authors who report such studies may nevertheless find our recommendations useful. For authors of observational studies that specifically address diagnostic tests, tumor markers and genetic associations, STARD, 13 REMARK, 14 and STREGA 15 recommendations may be particularly useful.…”

Section: How To Use This Papermentioning

confidence: 99%

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Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration

et al. 2007

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Much medical research is observational. The reporting of observational studies is often of insufficient quality. Poor reporting hampers the assessment of the strengths and weaknesses of a study and the generalizability of its results. Taking into account empirical evidence and theoretical considerations, a group of methodologists, researchers, and editors developed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) recommendations to improve the quality of reporting of observational studies.The STROBE Statement consists of a checklist of 22 items, which relate to the title, abstract, introduction, methods, results and discussion sections of articles. Eighteen items are common to cohort studies, case-control studies and cross-sectional studies and four are specific to each of the three study designs. The STROBE Statement provides guidance to authors about how to improve the reporting of observational studies and facilitates critical appraisal and interpretation of studies by reviewers, journal editors and readers.This explanatory and elaboration document is intended to enhance the use, understanding, and dissemination of the STROBE Statement. The meaning and rationale for each checklist item are presented. For each item, one or several published examples and, where possible, references to relevant empirical studies and methodological literature are provided. Examples of useful flow diagrams are also included. The STROBE Statement, this document, and the associated web site (http://www.strobe-statement.org) should be helpful resources to improve reporting of observational research. (Epidemiology 2007;18: 805-835) R ational health care practices require knowledge about the etiology and pathogenesis, diagnosis, prognosis and treatment of diseases. Randomized trials provide valuable evidence about treatments and other interventions. However, much of clinical or public health knowledge comes from observational research. 1 About nine of ten research papers published in clinical speciality journals describe observational research. 2,3 The STROBE StatementReporting of observational research is often not detailed and clear enough to assess the strengths and weaknesses of the investigation. 4,5 To improve the reporting of observational research, we developed a checklist of items that should be addressed: the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement (Table 1). Items relate to title, abstract, introduction, methods, results and discussion sections of articles. The STROBE Statement has recently been published in several journals. 6 Our aim is to ensure clear presentation of what was planned, done, and found in an observational study. We stress that the recommendations are not prescriptions for setting up or conducting studies, nor do they dictate methodology or mandate a uniform presentation.STROBE provides general reporting recommendations for descriptive observational studies and studies that investigate 805associations between expos...

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Section: How To Use This Papermentioning

confidence: 99%

“…"10 years' use of HRT ͓hormone replacement therapy͔ is estimated to result in five (95% CI 3-7) additional breast cancers per 1000 users of oestrogen-only preparations and 19 [15][16][17][18][19][20][21][22][23] additional cancers per 1000 users of oestrogen-progestagen combinations." 163 …”

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confidence: 99%

Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration

et al. 2007

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“…18,19,20 Systematic databases, such as the HuGE Navigator, 10 are available that can help create comprehensive lists of previously proposed loci and synopses of the genetic association literature may also be helpful to keep track of the evidence. 11,12,21 The thresholds at which past candidate loci should be claimed to be robustly replicated in GWAS platforms can be debated. Some may argue that similar stringent thresholds such as those proposed for newly discovered variants may be needed, eg Po10 À7 or even Alzheimer's disease 0 1 Statin-induced myopathy 0 1…”

Section: Discussionmentioning

confidence: 99%

Replication of past candidate loci for common diseases and phenotypes in 100 genome-wide association studies

2010

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Genome-wide association studies (GWASs) have created a paradigm shift in discovering genetic associations for common diseases and phenotypes, but it is unclear whether the thousands of candidate genetic association studies performed in the pre-GWAS era had found any reliable associations for common diseases and phenotypes. We aimed to systematically evaluate whether loci proposed to harbor candidate associations before the advent of GWASs are replicated in GWASs. The GWAS data published through August, 2008 and included in the NHGRI catalog were screened and variants in candidate loci were selected on the basis of statistical significance (Po0.05) to create a list of independent, non-redundant associations. Altogether, 159 articles on GWASs were evaluated, 100 of which addressed past proposed candidate loci. A total of 291 independent, nominally significant (Po0.05) candidate gene associations were assembled after keeping only the SNP with lowest P-value for each locus and each phenotype; 108 of those had Po10 À3 for association and 41 had Po10 À7 . A total of 22 of these 41 candidate gene associations pertained to binary phenotypes with a median odds ratio¼2.91 (IQR: 1.82-4.6) and median minor allele frequency¼0.17 (IQR: 0.12-0.29) in Caucasians; for comparison, 60 new associations of binary outcomes with Po10 À7 discovered in the same GWASs had much smaller effects (median odds ratio 1.30, IQR: 1.18-1.58) and modestly larger minor allele frequencies (median 0.27, IQR: 0.15-0.43). Overall, few of the numerous genetic associations proposed in the candidate gene era have been replicated in GWASs, but those that have been conclusively replicated have large genetic effects that should not be discarded.

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“…The systematic review of such studies, especially meta-analyses across multiple studies, has been recommended to minimize false-positive associations and as a tool to assess the credibility of the findings. 2 Genome-wide association studies (GWAS) have recently emerged as a powerful tool to find many novel genetic associations that the traditional candidate gene approach has failed to discover. 3 In the field of cancer, genetic association studies are among the most active and well-funded research areas and have produced hundreds of genetic associations, especially in the GWAS era.…”

Section: Introductionmentioning

confidence: 99%

Cancer GAMAdb: database of cancer genetic associations from meta-analyses and genome-wide association studies

Schully

McCallum

et al. 2011

Eur J Hum Genet

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In the field of cancer, genetic association studies are among the most active and well-funded research areas, and have produced hundreds of genetic associations, especially in the genome-wide association studies (GWAS) era. Knowledge synthesis of these discoveries is the first critical step in translating the rapidly emerging data from cancer genetic association research into potential applications for clinical practice. To facilitate the effort of translational research on cancer genetics, we have developed a continually updated database named Cancer Genome-wide Association and Meta Analyses database that contains key descriptive characteristics of each genetic association extracted from published GWAS and meta-analyses relevant to cancer risk. Here we describe the design and development of this tool with the aim of aiding the cancer research community to quickly obtain the current updated status in cancer genetic association studies.

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A road map for efficient and reliable human genome epidemiology

Cited by 220 publications

References 22 publications

Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration

Strengthening the Reporting of Observational Studies in Epidemiology (STROBE): Explanation and Elaboration

Replication of past candidate loci for common diseases and phenotypes in 100 genome-wide association studies

Cancer GAMAdb: database of cancer genetic associations from meta-analyses and genome-wide association studies

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