Predicting Common Pathway Signatures Between DNA Methylation and Post Translational Modification in Type II Diabetes & Parkinson’s Disease Using Heterogeneous Data Integration

The complex diseases, namely, Type 2 Diabetes Mellitus (T2DM) and Parkinson’s Disease (PD), are extensively studied due to their prevalence in a large population group. Between these two diseases, T2DM is denoted as the zero index disease in a patient, which may lead to PD in a more advanced clinical stage. Both of these diseases may occur due to abrupt DNA methylation of genes. Likewise, both diseases may occur in a patient due to protein misfolding. Our study proposes a novel framework for building two disease-specific heterogeneous networks by integrating different tissue-based transcriptomics, epigenetics, epistasis, and PPI-based topological information. We predict the missing links between the DNA methylation and Post-Translational Modification (PTMs) associated with protein aggregation. Next, we have predicted the common signature of the prevalence of linked patterns in both diseases, further validated by relevant biological evidence.