Mathematical modeling of folate metabolism: predicted effects of genetic polymorphisms on mechanisms and biomarkers relevant to carcinogenesis.

Publication Type:

Journal Article


Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, Volume 17, Issue 7, p.1822-31 (2008)


2008, DNA Methylation, DNA, Neoplasm, folic acid, Genotype, Humans, Models, Theoretical, Neoplasms, Polymorphism, Genetic, Public Health Sciences Division, Reproducibility of Results, Tumor Markers, Biological


Low-folate status and genetic polymorphisms in folate metabolism have been linked to several cancers. Possible biological mechanisms for this association include effects on purine and thymidine synthesis, DNA methylation, or homocysteine concentrations. The influence of genetic variation in folate metabolism on these putative mechanisms or biomarkers of cancer risk has been largely unexplored. We used a mathematical model that simulates folate metabolism biochemistry to predict (a) the effects of polymorphisms with defined effects on enzyme function (MTHFR and TS) and (b) the effects of potential, as-of-yet-unidentified polymorphisms in a comprehensive set of folate-metabolizing enzymes on biomarkers and mechanisms related to cancer risk. The model suggests that there is substantial robustness in the pathway. Our predictions were consistent with measured effects of known polymorphisms in MTHFR and TS on biomarkers. Polymorphisms that alter enzyme function of FTD, FTS, and MTCH are expected to affect purine synthesis, FTS more so under a low-folate status. In addition, MTCH polymorphisms are predicted to influence thymidine synthesis. Polymorphisms in methyltransferases should affect both methylation rates and thymidylate synthesis. Combinations of polymorphisms in MTHFR, TS, and SHMT are expected to affect nucleotide synthesis in a nonlinear fashion. These investigations provide information on effects of genetic polymorphisms on biomarkers, including those that cannot be measured well, and highlight robustness and sensitivity in this complex biological system with regard to genetic variability. Although the proportional changes in biomarkers of risk with individual polymorphisms are frequently small, they may be quite relevant if present over an individual's lifetime.