Epigenetics of Diabetes: A bioinformatic approach.

The adaptability of epigenetics offers a compelling research avenue, notably in the context of Type 2 Diabetes Mellitus (T2DM) biomarkers and provides a nuanced approach to managing biological systems for diagnosis. However, challenges such as DNA degradation during methylation studies are prominent, especially with cell-free DNA (cfDNA) which is present in small quantities in plasma, calling for innovative solutions. To tackle these challenges, four methodological approaches have been identified: firstly, selecting an appropriate DNA extraction method and enhancing DNA yield through amplification; secondly, adapting bisulfite modification techniques to minimize DNA degradation; thirdly, utilizing tools capable of working with minimal DNA quantities; and lastly, employing bisulfite-free methylation techniques. A particularly promising approach is the use of Methylated CpG Tandem Amplification and Sequencing (MCTA-Seq) combined with fragmentation analysis. MCTA-Seq, especially when targeting the CGCGCGG motif sequence associated with T2DM, is an underexplored area. In addressing the dearth of the exploration, our in-silico analysis identified 66 genes with the CGCGCGG motif sequence that contribute to the pathophysiology of T2DM. Further analysis revealed five potential target genes for T2DM screening: EP300, SRC, PPARG, CREBBP, and NCOR2. The method can also be integrated into fragment analysis, notable for its ability to differentiate between long and short DNA segments effectively. Such a distinction is a valuable asset in future diagnostic methodologies, particularly relevant in the analysis of cfDNA, where high precision and sensitivity are essential. However, it is crucial to validate these genes with clinical studies to confirm their relevance and effectiveness in T2DM diagnosis.