State Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology, Institute of Genetics, School of Life Sciences, Fudan University, Handan Rd, Shanghai 200433, China.
BMC Med Genet. 2012 Dec 10;13:118. doi: 10.1186/1471-2350-13-118.
Lung cancer is a complex polygenic disease. Although recent genome-wide association (GWA) studies have identified multiple susceptibility loci for lung cancer, most of these variants have not been validated in a Chinese population. In this study, we investigated whether a genetic risk score combining multiple.
Five single-nucleotide polymorphisms (SNPs) identified in previous GWA or large cohort studies were genotyped in 5068 Chinese case-control subjects. The genetic risk score (GRS) based on these SNPs was estimated by two approaches: a simple risk alleles count (cGRS) and a weighted (wGRS) method. The area under the receiver operating characteristic (ROC) curve (AUC) in combination with the bootstrap resampling method was used to assess the predictive performance of the genetic risk score for lung cancer.
Four independent SNPs (rs2736100, rs402710, rs4488809 and rs4083914), were found to be associated with a risk of lung cancer. The wGRS based on these four SNPs was a better predictor than cGRS. Using a liability threshold model, we estimated that these four SNPs accounted for only 4.02% of genetic variance in lung cancer. Smoking history contributed significantly to lung cancer (P < 0.001) risk [AUC = 0.619 (0.603-0.634)], and incorporated with wGRS gave an AUC value of 0.639 (0.621-0.652) after adjustment for over-fitting. This model shows promise for assessing lung cancer risk in a Chinese population.
Our results indicate that although genetic variants related to lung cancer only added moderate discriminatory accuracy, it still improved the predictive ability of the assessment model in Chinese population.
肺癌是一种复杂的多基因疾病。尽管最近的全基因组关联（GWA）研究已经确定了多个肺癌易感位点，但这些变体中的大多数尚未在中国人群中得到验证。在这项研究中，我们研究了是否可以通过结合多个遗传风险评分来预测肺癌的风险。
对 5068 例中国病例对照研究对象进行了先前 GWA 或大型队列研究中确定的 5 个单核苷酸多态性（SNP）的基因分型。基于这些 SNP 的遗传风险评分（GRS）通过两种方法进行估计：简单风险等位基因计数（cGRS）和加权（wGRS）方法。使用接收者操作特性（ROC）曲线下的面积（AUC）结合引导重采样方法来评估遗传风险评分对肺癌的预测性能。
发现 4 个独立的 SNP（rs2736100、rs402710、rs4488809 和 rs4083914）与肺癌风险相关。基于这四个 SNP 的 wGRS 是一个更好的预测因子。使用倾向得分模型，我们估计这四个 SNP 仅占肺癌遗传变异的 4.02%。吸烟史对肺癌（P<0.001）风险有显著影响[AUC=0.619（0.603-0.634）]，与 wGRS 结合后，在调整过度拟合后 AUC 值为 0.639（0.621-0.652）。该模型有望在中国人群中评估肺癌风险。
我们的研究结果表明，尽管与肺癌相关的遗传变异仅增加了适度的判别准确性，但它仍然提高了评估模型在中国人中的预测能力。
