Cancer Medicine (Jan 2023)

Genetic risk, metabolic syndrome, and gastrointestinal cancer risk: A prospective cohort study

  • Yaqian Liu,
  • Caiwang Yan,
  • Shuangshuang Yin,
  • Tianpei Wang,
  • Meng Zhu,
  • Li Liu,
  • Guangfu Jin

DOI
https://doi.org/10.1002/cam4.4923
Journal volume & issue
Vol. 12, no. 1
pp. 597 – 605

Abstract

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Abstract Background Gastrointestinal (GI) cancer risk has been associated with metabolic syndrome (MetS), a surrogate indicator for unhealthy lifestyles, and a number of genetic loci, but the combined effect of MetS and genetic variants on GI cancer risk is uncertain. Methods We included 430,036 participants with available MetS and genotype data from UK Biobank. During the follow‐up time, 5494 incident GI cancer cases, including esophageal cancer, gastric cancer, and colorectal cancer, were identified. We created a GI polygenic risk score (GI‐PRS) for overall GI cancer derived from three site‐specific cancer PRSs. Cox proportional hazards regression was used to estimate the associations of MetS and GI‐PRS with the risk of GI cancer. Results MetS was significantly associated with 28% increment in GI cancer risk (hazard ratio [HR]MetS vs. non‐MetS: 1.28, 95% confidence interval [CI]: 1.21–1.35, p < 0.0001), whereas a high GI‐PRS (top quintile) was associated with 2.28‐fold increase in risk (HRhigh vs. low: 2.28, 95% CI: 2.09–2.49, p < 0.0001). Compared with participants without MetS and at low genetic risk (bottom quintile of GI‐PRS), those with MetS and at high genetic risk had 2.75‐fold increase in GI cancer risk (HR: 2.75, 95% CI: 2.43–3.12, p < 0.0001). Additionally, MetS in comparison with no MetS had 1.49‰, 2.75‰, and 3.37‰ absolute risk increases in 5 years among participants at low, intermediate (quintiles 2–4 of GI‐PRS) and high genetic risk, respectively, representing the number of subjects diagnosed as MetS causing a new GI cancer case in 5 years were 669, 364, and 296, respectively. Conclusions Metabolic and genetic factors may jointly contribute to GI cancer risk and may serve as predictors by quantitative measurements to identify high‐risk populations of GI cancer for precise prevention.

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