Prediction of new potential associations between LncRNAs and environmental factors based on KATZ measure

Abstract

The associations between genetic and environmental factors (EFs) are significant to understand the development and progression of many complex human diseases. There have been many research studies concerning genetic factors (protein-coding genes, microRNAs) and EFs but limited research addressing the associations between long noncoding RNAs (lncRNAs) and EFs. LncRNAs of more than 200 nucleotides are an important class of non coding transcripts and are effective in the organization of gene expressions and, therefore, on the formation of diseases. Environmental factors can alter the expression patterns of some lncRNAs, so a thorough understanding of the associations between lncRNAs and environmental factors will contribute to the understanding of the mechanisms of many complex diseases at the molecular level. In this study, we have developed a model based on the KATZ measure to find potential new associations between lncRNAs and EFs by using the DLREFD database, which contains proven associations between lncRNAs and EFs. The KATZ measure and Gaussian interaction profile kernel similarity were used to predict new potential associations between lncRNAs and EFs. The AUC results obtained by global leave-one-out cross-validation and 2-fold and 5-fold cross-validations were 0.855, 0.827, 0.838, respectively. These results show that our model can predict new potential associations between lncRNAs and EFs with high reliability. Also, the results obtained in case studies demonstrate the effectiveness of our model.