Network-Based Disease Gene Prioritization by Hitting Time Analysis

Many methods have been published to prioritize genes using network theory. By using protein-protein interaction (PPI) data, it is possible to use mathematical features to rank and prioritize genes products in the network. Taking into account that genes related to the same diseases tend to connect, in the network structure, the prioritization methods search for candidate genes in the neighborhood of other genes already known to be related to a specific phenotype. Unfortunately, some existing algorithms can not deal well with highly connected genes, and some of them end up being related by chance to the disease being studied. We propose a pure method, with no need of adjustments, based on the hitting time of a random walk in PPI networks. This method captures information of the whole network and can equally prioritize genes regardless of its degree. We tested the efficiency of our method prioritizing candidate genes for Attention-Deficit/Hyperactivity Disorder (ADHD). The proposed method was able to give a good rank to genes that have genetic association with ADHD and was able to prioritize a large proportion of genes prioritized by other random-walk-based methods.