175 Epigenomics (2015) 7(2), 175–186 ISSN 1750-1911 part of Research Article 10.2217/EPI.14.77 © 2015 Future Medicine Ltd Aims: We applied artificial neural networks (ANNs) to understand the connections among polymorphisms of genes involved in folate metabolism, clinico-pathological features and promoter methylation levels of MLH1, APC, CDKN2A INK4A , MGMT and RASSF1A in 83 sporadic colorectal cancer (CRC) tissues, and to link dietary and lifestyle factors with gene promoter methylation. Materials & Methods: Promoter methylation was assessed by means of methylation-sensitive high-resolution melting and genotyping by PCR-RFLP technique. Data were analyzed with the Auto Contractive Map, a special kind of ANN able to define the strength of the association of each variable with all the others and to visually show the map of the main connections. Results: We observed a strong connection between the low methylation levels of the five CRC genes and the MTR 2756AA genotype. Several other connections were revealed, including those between dietary and lifestyle factors and the methylation levels of CRC genes. Conclusion: ANNs revealed the complexity of the interconnections among factors linked to DNA methylation in CRC. Keywords: APC฀•฀artiicial฀neural฀networks฀•฀CDKN2A฀•฀colorectal฀cancer฀ •฀DNA฀methylation฀•฀folate฀•฀MGMT, MLH1,฀polymorphisms฀•฀RASSF1A Colorectal cancer (CRC) evolves through a stepwise accumulation of mutations and epi- genetic modifications that transform normal colonic cells into cancer [1,2] . Among epi- genetic mechanisms, DNA methylation has gained particular interest in cancer studies because it was linked to the silencing of tumor suppressor genes and DNA repair genes [3] . Several genes are frequently hypermethylated in sporadic CRC, including MLH1, APC, CDKN2A, MGMT and RASSF1A [4–14] . Common polymorphisms of folate meta- bolic genes have been largely investigated as CRC genetic risk factors, mainly because folate metabolism (one-carbon metabolism) in required for DNA synthesis and meth- ylation (Figure 1), but literature data in this field are conflicting and often insufficient to clarify their contribution to DNA methyla- tion and CRC risk [3] . This is likely due to the complexity of this metabolic pathway (Figure 1), and to the fact that traditional statistical algorithms are often unsuitable to dissect the relationship between high num- ber of variables due to the nonlinearity and complexity of their interactions [3] . In addi- tion to genetic factors, dietary habits and lifestyles, such as drinking and smoking, are among the environmental factors suspected to impair DNA methylation [15–17] . In the present pilot study we applied Arti- ficial Neural Networks (ANNs) to identify genetic and dietary/lifestyle factors linked to MLH1, APC, CDKN2A INK4A , MGMT and RASSF1A promoter methylation in sporadic CRC. ANNs aim to understand natural pro- cesses and recreate those processes using auto- mated models, and have been used success- fully in gastroenterology and cancer studies to understand nonlinear relationships among variables [18–20] . Particularly, we applied the Auto Contractive Map-Auto-CM algorithm (Auto-CM), which is a peculiar ANN able to define the strength of the associations of Application of artificial neural networks to link genetic and environmental factors to DNA methylation in colorectal cancer Fabio Coppedè* ,1,2,3 , Enzo Grossi 4,5 , Angela Lopomo 1,6 , Roberto Spisni 7 , Massimo Buscema 5,8 & Lucia Migliore 1,2,3 1 Department฀of฀Translational฀Research฀&฀ New฀Technologies฀in฀Medicine฀&฀Surgery,฀ Division฀of฀Medical฀Genetics,฀University฀ of฀Pisa,฀Medical฀School,฀Via฀Roma฀55,฀ 56126฀Pisa,฀Italy 2 Istituto฀Toscano฀Tumori฀(ITT),฀ Florence,฀Italy 3 Interdepartmental฀Research฀Center฀ Nutrafood฀‘Nutraceuticals฀&฀Food฀for฀ Health’,฀Pisa,฀Italy 4 Bracco฀Foundation,฀Milan,฀Italy 5 Semeion฀Research฀Center,฀Rome,฀Italy 6 Doctoral฀School฀in฀Genetics,฀Oncology฀ &฀Clinical฀Medicine,฀University฀of฀Siena,฀ Siena,฀Italy 7 Department฀of฀Surgery,฀Medical,฀ Molecular฀&฀Critical฀Area฀Pathology,฀ University฀of฀Pisa,฀Pisa,฀Italy 8 Department฀of฀Mathematical฀ &฀Statistical฀Sciences,฀University฀of฀ Colorado฀at฀Denver,฀CO,฀USA *Author฀for฀correspondence:฀ Tel.:฀+39฀050฀221฀8544 fabio.coppede@med.unipi.it For reprint orders, please contact: reprints@futuremedicine.com