A colorectal cancer prediction model using traditional and genetic risk scores in Koreans

Keum Ji Jung, Daeyoun Won, Christina Jeon, Soriul Kim, Tae Il Kim, Sun Ha Jee, Terri H. Beaty

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Genome-wide association studies have identified numerous single nucleotide polymorphisms (SNPs) as associated with colorectal cancer (CRC) risk in populations of European descent. However, their utility for predicting risk to CRC in Asians remains unknown. A case-cohort study (random sub-cohort N=1,685) from the Korean Cancer Prevention Study-II (KCPS-II) (N=145,842) was used. Twenty-three SNPs identified in previous 47 studies were genotyped on the KCPS-II sub-cohort members. A genetic risk score (GRS) was calculated by summing the number of risk alleles over all SNPs. Prediction models with or without GRS were evaluated in terms of the area under the receiver operating characteristic curve (AUROC) and the continuous net reclassification index (NRI). Results: Seven of 23 SNPs showed significant association with CRC and rectal cancer in Koreans, but not with colon cancer alone. AUROCs (95% CI) for traditional risk score (TRS) alone and TRS plus GRS were 0.73 (0.69-0.78) and 0.74 (0.70-0.78) for CRC, and 0.71 (0.65-0.77) and 0.74 (0.68-0.79) for rectal cancer, respectively. The NRI (95% CI) for a prediction model with GRS compared to the model with TRS alone was 0.17 (-0.05-0.37) for CRC and 0.41 (0.10-0.68) for rectal cancer alone. Conclusion: Our results indicate genetic variants may be useful for predicting risk to CRC in the Koreans, especially risk for rectal cancer alone. Moreover, this study suggests effective prediction models for colon and rectal cancer should be developed separately.

Original languageEnglish (US)
Article number49
JournalBMC genetics
Volume16
Issue number1
DOIs
StatePublished - May 9 2015

Keywords

  • Colorectal cancer
  • Gene-traditional risk score
  • Single nucleotide polymorphisms

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

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