Performance of the Use of Genetic Information to Assess the Risk of Colorectal Cancer in the Basque Population.

Abstract

Simple SummaryThe risk of developing colorectal cancer (CRC) is partially associated with genetics. Different studies have provided valuable genetic information to understand the biology behind CRC and to build models of genetic risk. However, the study of the applicability of such genetic information within the Basque population is limited. Thus, our objectives were to find out if the genetic variants associated with CRC in other populations are the same in the Basque population and to assess the performance of the use of genetic information to calculate the risk of developing CRC. We found that the available genetic information can be applied to the Basque population, although local genetic variation can affect its use. Our findings will help to refine the use of CRC genetic risk calculation in the Basque population, and we expect that our findings could be useful for other populations.Although the genetic contribution to colorectal cancer (CRC) has been studied in various populations, studies on the applicability of available genetic information in the Basque population are scarce. In total, 835 CRC cases and 940 controls from the Basque population were genotyped and genome-wide association studies were carried out. Mendelian Randomization analyses were used to discover the effect of modifiable risk factors and microbiota on CRC. In total, 25 polygenic risk score models were evaluated to assess their performance in CRC risk calculation. Moreover, 492 inflammatory bowel disease cases were used to assess whether that genetic information would not confuse both conditions. Five suggestive (p < 5 × 10−6) loci were associated with CRC risk, where genes previously associated with CRC were located (e.g., ABCA12, ATIC or ERBB4). Moreover, the analyses of CRC locations detected additional genes consistent with the biology of CRC. The possible contribution of cholesterol, BMI, Firmicutes and Cyanobacteria to CRC risk was detected by Mendelian Randomization. Finally, although polygenic risk score models showed variable performance, the best model performed correctly regardless of the location and did not misclassify inflammatory bowel disease cases. Our results are consistent with CRC biology and genetic risk models and could be applied to assess CRC risk in the Basque population.