基于常见遗传变异和传统风险因素的中国南方汉族人群结直肠癌风险预测模型研究

目的 基于结直肠癌全基因组关联研究(GWAS)发现的易感位点,联合传统风险因素建立中国南方汉族人群结直肠癌风险预测模型。方法 对1 066例结直肠癌患者和3 880例健康对照的21个GWAS候选位点进行基因分型,分析其与结直肠癌易感性之间的关联。通过遗传风险评分(GRS)和加权遗传风险评分(wGRS)计算显著候选位点的联合效应。以不同方式组合遗传风险评分和传统风险因素,构建结直肠癌风险预测模型,并绘制受试者工作特征曲线评价模型优劣性。结果 7个候选位点与结直肠癌易感性显著相关。随着风险评分的升高,人群患结直肠癌的风险也随之升高(GRS:P=0.002 6,wGRS:P<0.000 1),相比于四分位分组中最低一组,GRS和wGRS最高的一组OR值分别为1.33(95%CI:1.12~1.58,P=0.001 0)和1.76(95%CI:1.45~2.14,P<0.000 1)。联合传统风险因素和wGRS的模型为最优模型,其曲线下面积为0.593(95%CI:0.573~0.613)。结论 结直肠癌易感位点间存在显著的联合作用。相比于传统风险因素模型,传统风险因素结合加权遗传风险评分模型能更好预测结直肠癌的患病风险。

Risk prediction of colorectal cancer with common genetic variants and conventional non-genetic factors in a Chinese Han population

Objective 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. Methods 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. Results 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). Conclusion 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.