Interplay between Genome, Metabolome and Microbiome in Colorectal Cancer

SIMPLE SUMMARY: The development of colorectal cancer (CRC) is influenced by the environment, genetics and microbiota. Microbiome and metabolome analyses allowed for the finding of factors and markers associated with adenoma and CRC risk, but the interaction of host genomics with those omic layers remains unclear. Thus, our aim is to add host genome information to find new factors and markers associated with adenoma and CRC risk or to propose biological mechanisms involved in the risk. We found interactions between different omic layers that could be biologically relevant, and the three layers gave complementary information to predict adenoma and CRC risk. Our findings will help to find new markers for adenoma and CRC risk and to analyze biological mechanisms involved in adenoma and CRC development. ABSTRACT: Background: Colorectal cancer (CRC), a major health concern, is developed depending on environmental, genetic and microbial factors. The microbiome and metabolome have been analyzed to study their role in CRC. However, the interplay of host genetics with those layers in CRC remains unclear. Methods: 120 individuals were sequenced and association analyses were carried out for adenoma and CRC risk, and for selected components of the microbiome and metabolome. The epistasis between genes located in cholesterol pathways was analyzed; modifiable risk factors were studied using Mendelian randomization; and the three omic layers were used to integrate their data and to build risk prediction models. Results: We detected genetic variants that were associated to components of metabolome or microbiome and adenoma or CRC risk (e.g., in LINC01605, PROKR2 and CCSER1 genes). In addition, we found interactions between genes of cholesterol metabolism, and HDL cholesterol levels affected adenoma (p = 0.0448) and CRC (p = 0.0148) risk. The combination of the three omic layers to build risk prediction models reached high AUC values (>0.91). Conclusions: The use of the three omic layers allowed for the finding of biological mechanisms related to the development of adenoma and CRC, and each layer provided complementary information to build risk prediction models.