PLS-SEM mediation analysis of gene-expression data for the evaluation of a drug effect

Abstract

Gene expression analysis can unveil the genes associated with the molecular action of a drug. However, it is not always clear how the differentially expressed genes restore the phenotype and whether, globally, the drug has an effect on the disease. We propose a method that exploits gene-expression data and network biology information to build a mediation analysis model for the evaluation of the effect of treatment on the disease at molecular level. First, differentially expressed genes (DEGs) associated to the drug and the disease are discovered. Then, based on a pathway analysis, shortest paths between drug DEGs and disease DEGs are obtained. This allows discovering the mediator genes that connect drug genes to disease genes. The expression values of the three sets of genes are used to conduct a mediation analysis that evaluates the effect of the drug on the disease. The effect could be direct, indirect by mediators, or both. The latent variables and mediation model are constructed by using the PLS-SEM. The procedure is applied to a real example concerning the effect of abacavir on HIV samples. The proposed pipeline can offer an additional tool for the understanding of the etiology of a disease and unveiling the mechanisms of action of a drug at gene level.