Interplay between Genome, Metabolome and Microbiome in Colorectal Cancer

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. 120 individuals were...

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Bibliographic Details
Published in:Cancers 2021-12, Vol.13 (24), p.6216
Main Authors: Garcia-Etxebarria, Koldo, Clos-Garcia, Marc, Telleria, Oiana, Nafría, Beatriz, Alonso, Cristina, Iruarrizaga-Lejarreta, Marta, Franke, Andre, Crespo, Anais, Iglesias, Agueda, Cubiella, Joaquín, Bujanda, Luis, Falcón-Pérez, Juan Manuel
Format: Article
Language:English
Subjects:
Adenoma
Age
Biobanks
Biomarkers
Cholesterol
Colorectal cancer
Colorectal carcinoma
Epistasis
Feces
Genetic diversity
Genomes
High density lipoprotein
Lipid metabolism
Metabolism
Metabolites
Microbiomes
Microbiota
Prediction models
Quality control
Risk factors
Software
Tumors
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Summary: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. 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. We detected genetic variants that were associated to components of metabolome or microbiome and adenoma or CRC risk (e.g., in , and genes). In addition, we found interactions between genes of cholesterol metabolism, and HDL cholesterol levels affected adenoma ( = 0.0448) and CRC ( = 0.0148) risk. The combination of the three omic layers to build risk prediction models reached high AUC values (>0.91). 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.
ISSN:2072-6694
2072-6694
DOI:10.3390/cancers13246216