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Combinations of single nucleotide polymorphisms identified in genome‐wide association studies determine risk for colorectal cancer
Author(s) -
Xin Junyi,
Du Mulong,
Gu Dongying,
Ge Yuqiu,
Li Shuwei,
Chu Haiyan,
Meng Yixuan,
Shen Hongbing,
Zhang Zhengdong,
Wang Meilin
Publication year - 2019
Publication title -
international journal of cancer
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.475
H-Index - 234
eISSN - 1097-0215
pISSN - 0020-7136
DOI - 10.1002/ijc.32267
Subject(s) - single nucleotide polymorphism , genome wide association study , colorectal cancer , genetic association , oncology , medicine , population stratification , biology , genetics , population , cancer , genotype , gene , environmental health
Genome‐wide association studies (GWASs) have identified single nucleotide polymorphisms (SNPs) associated with colorectal cancer (CRC) risk, but whether these SNPs have additive effects on the risk of CRC remains unclear. We performed a systematic analysis of GWAS‐identified SNPs using GWAS datasets from China (2,248 patients and 3,173 controls) and Europe (4,461 patients and 4,140 controls). We analyzed 58 independent variants from DNA samples from Chinese populations and found 19 SNPs that were significantly associated with CRC risk. We identified two genetic risk scores (GRSs) based on 58 and 19 SNPs, which were significantly associated with an increased risk of CRC. A decision curve analysis showed higher predictive power for the 58 SNPs. Using all the 58 SNPs to assess 5‐year absolute risk (AR), we found that, at a cutoff of 0.4% (two times the median AR) and 0.6% (three times the median AR), approximately 32.76 and 16.45% of Chinese individuals were grouped as high risk for developing CRC, respectively. Risk stratification analysis further indicated that the population in the top 30% risk group accounted for 46.71% of the CRC cases. In addition, the 58 SNPs could explain approximately 1.13% of the phenotypic variance in Chinese populations. Similar findings were found in European populations. Combinations of SNPs identified in GWASs may therefore be useful for identifying individuals at high risk for CRC.