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

Abstract

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.

Host Genetics and Microbiota Interactions in Colorectal Cancer: Shared or Independent Risk?

“…Although it is an indirect method, it gives information to determine if there are shared genetic mechanisms to CRC risk and the abundance of a given phylum. Although the results were weak, the genetic variants associated with the abundance of Firmicutes and Cyanobacteria phyla were also associated with the genetic risk of CRC, specifically with the genetic risk of left colon cancer [55]. It must pointed out that in the study in question, the genetic variants involved in total cholesterol levels were determined to be a risk factor in left colon cancer [55].…”

“…The study of the genetic variants of the host that affect the abundance of bacterial taxa has been a valuable asset to get genetic signatures related to microbiota composition [54]. Based on those genetic signatures of microbiota composition, it has been analyzed the contribution of various phyla to CRC risk using Mendelian Randomization analyses [55]. Although it is an indirect method, it gives information to determine if there are shared genetic mechanisms to CRC risk and the abundance of a given phylum.…”

Optimization of Multi-Ancestry Polygenic Risk Score Disease Prediction Models

“…We generated novel genome-wide summary statistics for 30 medically-related traits, leveraging trans-ancestry genome-wide association study (GWAS) meta-analysis of diverse cohort data, including the UK Biobank (Table 1) 14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40 , 41,42,43,44,45,46, 47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,79 . The following traits were selected: age-related macular degeneration, Alzheimer’s disease, asthma, atrial fibrillation, bipolar disorder, body mass index (BMI), bowel cancer, breast cancer, cardiovascular disease, celiac disease, coronary artery disease, Crohn’s disease, hypertension, ischemic stroke, melanoma, multiple sclerosis, osteoporosis, Parkinson’s disease, primary open angle glaucoma, prostate cancer, psoriasis, rheumatoid arthritis, schizophrenia, systemic lupus erythematosus, total cholesterol, triglycerides, type 1 diabetes, type 2 diabetes, ulcerative colitis, venous thromboembolic disease.…”

“…We generated novel genome-wide summary statistics for 30 medically-related traits, leveraging trans-ancestry genome-wide association study (GWAS) meta-analysis of diverse cohort data, including the UK Biobank (Table 1) 14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42, 43,44,45,46, 47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,79 . For the purpose of PRS training, the three continuous traits, BMI, total cholesterol and triglycerides, were converted into binary outcomes, obesity, hypercholesterolemia, and hypertriglyceridemia, respectively.…”

Clinical, Pathological, and Molecular Characteristics in Colorectal Cancer

“…In addition, an original study analyzed the contribution of the genetic component to CRC risk in the Basque population with a specific genetic history [ 7 ], while another assessed the importance of routine immunohistochemistry screening for MMR status in CRC patients in the identification of Lynch syndrome patients [ 8 ].…”