PLoS ONE (Jan 2018)

Prediction model for pancreatic cancer risk in the general Japanese population.

  • Masahiro Nakatochi,
  • Yingsong Lin,
  • Hidemi Ito,
  • Kazuo Hara,
  • Fumie Kinoshita,
  • Yumiko Kobayashi,
  • Hiroshi Ishii,
  • Masato Ozaka,
  • Takashi Sasaki,
  • Naoki Sasahira,
  • Manabu Morimoto,
  • Satoshi Kobayashi,
  • Makoto Ueno,
  • Shinichi Ohkawa,
  • Naoto Egawa,
  • Sawako Kuruma,
  • Mitsuru Mori,
  • Haruhisa Nakao,
  • Chaochen Wang,
  • Takeshi Nishiyama,
  • Takahisa Kawaguchi,
  • Meiko Takahashi,
  • Fumihiko Matsuda,
  • Shogo Kikuchi,
  • Keitaro Matsuo

DOI
https://doi.org/10.1371/journal.pone.0203386
Journal volume & issue
Vol. 13, no. 9
p. e0203386

Abstract

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Genome-wide association studies (GWASs) have identified many single nucleotide polymorphisms (SNPs) that are significantly associated with pancreatic cancer susceptibility. We sought to replicate the associations of 61 GWAS-identified SNPs at 42 loci with pancreatic cancer in Japanese and to develop a risk model for the identification of individuals at high risk for pancreatic cancer development in the general Japanese population. The model was based on data including directly determined or imputed SNP genotypes for 664 pancreatic cancer case and 664 age- and sex-matched control subjects. Stepwise logistic regression uncovered five GWAS-identified SNPs at five loci that also showed significant associations in our case-control cohort. These five SNPs were included in the risk model and also applied to calculation of the polygenic risk score (PRS). The area under the curve determined with the leave-one-out cross-validation method was 0.63 (95% confidence interval, 0.60-0.66) or 0.61 (0.58-0.64) for versions of the model that did or did not include cigarette smoking and family history of pancreatic cancer in addition to the five SNPs, respectively. Individuals in the lowest and highest quintiles for the PRS had odds ratios of 0.62 (0.42-0.91) and 1.98 (1.42-2.76), respectively, for pancreatic cancer development compared with those in the middle quintile. We have thus developed a risk model for pancreatic cancer that showed moderately good discriminatory ability with regard to differentiation of pancreatic cancer patients from control individuals. Our findings suggest the potential utility of a risk model that incorporates replicated GWAS-identified SNPs and established demographic or environmental factors for the identification of individuals at increased risk for pancreatic cancer development.