Colorectal Cancer Predicted by Merging Risk Factors

A team of Spanish cancer researchers has devised a method for predicting risk of developing colorectal cancer (CRC) that combines life style choices, family background, and genetic data.

Investigators at IDIBELL-Bellvitge Biomedical Research Institute set out to elaborate a model to stratify the risk of CRC by merging environmental information and single nucleotide polymorphisms (SNPs) data. To achieve this end, they conducted a case-control study that included 1336 CRC cases and 2744 controls. Subjects were interviewed on lifestyle factors, family, and medical history. In addition, 21 CRC susceptibility SNPs were genotyped.

Results revealed that the environmental risk model, which included alcohol consumption, obesity, physical activity, red meat and vegetable consumption, and nonsteroidal anti-inflammatory drug use, contributed to CRC with an average OR (odds ratio) factor of 1.36. Family history of CRC contributed an OR of 2.25, and each additional SNP contributed an OR of 1.07. The risk of subjects with more than 25 risk alleles (fifth quintile) was 82% higher than subjects with less than 19 alleles (first quintile). Thus, environmental factors had more weight than the genetic score, which should be considered to encourage patients to achieve a healthier lifestyle.

The investigators did stress that this study only included 21 risk SNPs, while more than 60 have already been identified. More studies will be needed to determine the generalizability, usefulness of information, and the cost-effectiveness of applying individual genotyping in a CRC screening program.

"A risk model is a mathematical tool that allows us to predict who is most likely to suffer from a particular disease, in this case colon cancer," said senior author Dr. Victor Moreno, professor of medicine and health sciences head at IDIBELL-Bellvitge Biomedical Research Institute. "Today, screening for colon cancer in patients with no family history is based solely on age. If we include information about lifestyle and genetics, we could classify the population into groups of greater or lesser risk, which would allow us to offer a more personalized follow-up."

The study was published in the February 24, 2017, online edition of the journal Scientific Reports.