Poster Session A
Sunday, 19 April, 2015 - 19:00Systematic Meta-analyses and Field Synopsis of Genetic Association Studies in Colorectal Adenomas
1. School of Epidemiology, Public Health and Preventive Medicine, University of Ottawa, Ottawa, Canada; 2. Centre for Population Health Sciences, University of Edinburgh, Edinburgh, United Kingdom; 3. Colon Cancer Genetics Group and Academic Coloproctology, Institute of Genetics and Molecular Medicine, University of Edinburgh and MRC Human Genetics Unit Western General Hospital Edinburgh, United Kingdom
Background: Colorectal cancer (CRC) constitutes a major global public health challenge. Most CRCs develop from preneoplastic asymptomatic lesions known as colorectal adenoma (CRA). We have previously summarized the associations between common genetic variants and CRC in a field synopsis of genetic association and GWAS, but the genetic basis of CRA is less well documented. We now present the first synthesis of all published genetic association data for CRAs and the results of meta-analyses to summarise risk estimates.
Methods: Using Medline and the HuGENet phenopedia™, we identified and synthesized all published genetic association data for CRAs. We conducted meta-analyses of the identified studies and data from two GWAS to summarise risk estimates. We applied the Venice criteria and Bayesian False Discovery Probability (BFDP) to assess the levels of the credibility of associations.
Results: 9750 titles and abstracts were initially screened, and 1750 publications were identified for full text screening of which 130 articles met the inclusion criteria. Data were extracted for 181 SNPs in 74 genes. The variant at 8q24.21 (rs6983267) was considered as “highly credible” and MTHFR (C677T), NAT1, NQO1 (Pro187Ser), and TP53 (Arg72Pro) as “less credible”.
Conclusion: The identification of genetic variants with influence on CRA risk may provide new insights into the fundamental biological mechanisms involved in early CRC development and help to inform future research. Further, CRA risk-associated SNP variants may also show utility in contributing to future risk scores for accurate population risk stratification which could be of potential value in improving CRC screening modalities.