Details

Autor(en) / Beteiligte

• THEODORATOU, Evropi
• MONTAZERI, Zahra
• ZGAGA, Lina
• LANDRY, Denise
• BENSON, Helen E
• READ, Stephanie H
• RUDAN, Igor
• TENESA, Albert
• DUNLOP, Malcolm G
• CAMPBELL, Harry
• LITTLE, Julian
• HAWKEN, Steven
• CDLALLUM, Genevieve
• GONG, Jacintha
• TAIT, Valerie
• KIRAC, Iva
• TAZARI, Mahmood
• FARRINGTON, Susan M
• DEMARSH, Alex

Titel

Systematic Meta-Analyses and Field Synopsis of Genetic Association Studies in Colorectal Cancer

Ist Teil von

• JNCI : Journal of the National Cancer Institute, 2012-10, Vol.104 (19), p.1433-1457

Ort / Verlag

Cary, NC: Oxford University Press

Erscheinungsjahr

2012

Link zum Volltext

Quelle

Oxford Journals 2020 Medicine

Beschreibungen/Notizen

• Colorectal cancer is a major global public health problem, with approximately 950,000 patients newly diagnosed each year. We report the first comprehensive field synopsis and creation of a parallel publicly available and regularly updated database (CRCgene) that catalogs all genetic association studies on colorectal cancer (http://www.chs.med.ed.ac.uk/CRCgene/). We performed two independent systematic reviews, reviewing 10 145 titles, then collated and extracted data from 635 publications reporting on 445 polymorphisms in 110 different genes. We carried out meta-analyses to derive summary effect estimates for 92 polymorphisms in 64 different genes. For assessing the credibility of associations, we applied the Venice criteria and the Bayesian False Discovery Probability (BFDP) test. We consider 16 independent variants at 13 loci (MUTYH, MTHFR, SMAD7, and common variants tagging the loci 8q24, 8q23.3, 11q23.1, 14q22.2, 1q41, 20p12.3, 20q13.33, 3q26.2, 16q22.1, and 19q13.1) to have the most highly credible associations with colorectal cancer, with all variants except those in MUTYH and 19q13.1 reaching genome-wide statistical significance in at least one meta-analysis model. We identified less-credible (higher heterogeneity, lower statistical power, BFDP >0.2) associations with 23 more variants at 22 loci. The meta-analyses of a further 20 variants for which associations have previously been reported found no evidence to support these as true associations. The CRCgene database provides the context for genetic association data to be interpreted appropriately and helps inform future research direction.