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Chinese Journal of Epidemiology ; (12): 1053-1057, 2015.
Article Dans Chinois | WPRIM | ID: wpr-248712

Résumé

<p><b>OBJECTIVE</b>To understand the association between multiple genetic loci identified by genome-wide association studies (GWASs) and colorectal cancer (CRC) risk, and whether these genetic factors, along with traditional risk factors, could contribute to the colorectal cancer risk prediction in a Chinese Han population.</p><p><b>METHODS</b>A case-control study (1 066 CRC cases and 3 880 controls) was initially conducted to assess the association between 21 recently discovered single-nucleotide polymorphisms (SNPs) and CRC risk. Genetic risk score (GRS) and weighted genetic risk score (wGRS) were calculated to evaluate the joint effects of selected loci. Multiple models combining genetic and non-genetic factors were established and receiver operating characteristic curve analysis was used to compare the discriminatory power of different predictive models.</p><p><b>RESULTS</b>There were 7 SNPs significantly associated with CRC susceptibility. As the GRS or wGRS increased, the risk of CRC also increased (trend P=0.002 6 for GRS, trend P<0.000 1 for wGRS). The ORs for highest versus lowest quartile of GRS and wGRS were 1.33 (95% CI: 1.12-1.58, P=0.001 0) and 1.76 (95% CI: 1.45-2.14, P<0.000 1) , respectively. The model incorporating wGRS and traditional risk factors, including sex, age, smoking and drinking, was the best one to predict CRC risk in this population, with an area under curve of 0.593 (95% CI: 0.573-0.613).</p><p><b>CONCLUSION</b>Multiple genetic loci identified by GWASs jointly influenced the CRC risk. The combination of genetic factors and conventional non-genetic factors improved the performance of risk predictive model for colorectal cancer.</p>


Sujets)
Humains , Asiatiques , Études cas-témoins , Chine , Épidémiologie , Tumeurs colorectales , Épidémiologie , Génétique , Ethnies , Locus génétiques , Prédisposition génétique à une maladie , Variation génétique , Étude d'association pangénomique , Polymorphisme de nucléotide simple , Courbe ROC , Facteurs de risque
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