Li Jiaoyuan, Chang Jiang, Zhu Ying, Yang Yang, Gong Yajie, Ke Juntao, Lou Jiao, Zhong Rong, Gong Jing, Xia Xiaoping, Miao Xiaoping
Department of Epidemiology and Biostatistics, School of Public Health.
Key Laboratory of Environment and Health, Ministry of Education and Ministry of Environmental Protection, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
Zhonghua Liu Xing Bing Xue Za Zhi. 2015 Oct;36(10):1053-7.
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.
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.
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).
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.
了解全基因组关联研究（GWAS）所识别的多个基因位点与结直肠癌（CRC）风险之间的关联，以及这些遗传因素与传统风险因素是否有助于预测中国汉族人群的结直肠癌风险。
最初开展一项病例对照研究（1066例CRC病例和3880例对照），以评估21个最近发现的单核苷酸多态性（SNP）与CRC风险之间的关联。计算遗传风险评分（GRS）和加权遗传风险评分（wGRS）以评估所选位点的联合效应。建立了结合遗传和非遗传因素的多个模型，并采用受试者工作特征曲线分析来比较不同预测模型的判别能力。
有7个SNP与CRC易感性显著相关。随着GRS或wGRS升高，CRC风险也增加（GRS的趋势P=0.0026，wGRS的趋势P<0.0001）。GRS和wGRS最高四分位数与最低四分位数的OR分别为1.33（95%CI：1.12-1.58，P=0.0010）和1.76（95%CI：1.45-2.14，P<0.0001）。纳入wGRS和包括性别、年龄、吸烟和饮酒在内的传统风险因素的模型是预测该人群CRC风险的最佳模型，曲线下面积为0.593（95%CI：0.573-0.613）。
GWAS所识别的多个基因位点共同影响CRC风险。遗传因素与传统非遗传因素的结合提高了结直肠癌风险预测模型的性能。
