For personalized healthcare, the purpose of this study was to examine the key genes and metabolites in the one-carbon metabolism (OCM) pathway and their interactions as predictors of colorectal cancer (CRC) in multi-ethnic families. In this proof-of-concept study, we included a total of 30 participants, 15 CRC cases and 15 matched family/friends representing major ethnic groups in southern California. Analytics based on supervised machine learning were applied, with the target variable being specified as cancer, including the ensemble method and generalized regression (GR) prediction. Elastic Net with Akaike’s Information Criterion with correction (AICc) and Leave-One-Out cross validation GR methods were used to validate the results for enhanced optimality, prediction, and reproducibility. The results revealed that despite some family members sharing genetic heritage, the CRC group had greater combined gene polymorphism-mutations than the family controls (p < 0.1) for five genes including MTHFR C677T, MTHFR A1298C, MTR A2756G, MTRR A66G, and DHFR 19bp. Blood metabolites including homocysteine (7 µmol/L), methyl-folate (40 nmol/L) with total gene mutations (≥4); age (51 years) and vegetable intake (2 cups), and interactions of gene mutations and methylmalonic acid (MMA) (400 nmol/L) were significant predictors (all p < 0.0001) using the AICc. The results were validated by a 3% misclassification rate, AICc of 26, and >99% area under the receiver operating characteristic curve. These results point to the important roles of blood metabolites as potential markers in the prevention of CRC. Future intervention studies can be designed to target the ways to mitigate the enzyme-metabolite deficiencies in the OCM pathway to prevent cancer.
- Colorectal cancer
- Diverse ethnic groups
- Generalized regression with validation
- Metabolites and genes
- One carbon metabolism pathways
ASJC Scopus subject areas
- Medicine (miscellaneous)