Systematic meta-analyses and field synopsis of genetic association studies in colorectal adenomas
A partir d'une revue systématique de la littérature (130 études portant sur 181 polymorphismes de 74 gènes), cette méta-analyse évalue les niveaux de crédibilité des associations entre des polymorphismes génétiques et le risque d'adénomes colorectaux
Background: Low penetrance genetic variants, primarily single nucleotide polymorphisms, have substantial influence on colorectal cancer (CRC) susceptibility. Most CRCs develop from colorectal adenomas (CRA). Here we report the first comprehensive field synopsis that catalogues all genetic association studies on CRA, with a parallel online database [http://www.chs.med.ed.ac.uk/CRAgene/].
Methods : We performed a systematic review, reviewing 9750 titles, and then extracted data from 130 publications reporting on 181 polymorphisms in 74 genes. We conducted meta-analyses to derive summary effect estimates for 37 polymorphisms in 26 genes. We applied the Venice criteria and Bayesian False Discovery Probability (BFDP) to assess the levels of the credibility of associations.
Results: We considered the association with the rs6983267 variant at 8q24 as ‘highly credible’, reaching genome-wide statistical significance in at least one meta-analysis model. We identified ‘less credible’ associations (higher heterogeneity, lower statistical power, BFDP > 0.02) with a further four variants of four independent genes: MTHFR c.677C>T p.A222V (rs1801133), TP53 c.215C>G p.R72P (rs1042522), NQO1 c.559C>T p.P187S (rs1800566), and NAT1 alleles imputed as fast acetylator genotypes. For the remaining 32 variants of 22 genes for which positive associations with CRA risk have been previously reported, the meta-analyses revealed no credible evidence to support these as true associations.
Conclusions: The limited number of credible associations between low penetrance genetic variants and CRA reflects the lower volume of evidence and associated lack of statistical power to detect associations of the magnitude typically observed for genetic variants and chronic diseases. The CRA gene database provides context for CRA genetic association data and will help inform future research directions.
International Journal of Epidemiology , résumé, 2015