Delis, A. | bioRxiv Science

bioRxiv2020

Drug repurposing through a bioinformatics pipeline applied on IPF and other fibrotic diseases

Subject Fibrotic diseases cover a spectrum of systemic and organ-specific maladies that affect a large portion of the population, currently without cure. The shared characteristic these diseases feature is their uncontrollable fibrogenesis deemed responsible for the accumulated damage in the susceptible tissues. Idiopathic Pulmonary Fibrosis (IPF), an interstitial lung disease, is one of the most common and studied fibrotic diseases and still remains an active research target.Objective We highlight unique and common (i) genes, (ii) biological pathways and (iii) candidate repurposed drugs among nine fibrotic diseases. We bibliographically explore the resulting candidate substances for potential anti-fibrotic mode of action and focus on diseases that appear to be more similar to IPF so as to jointly examine potential treatments.Methodology We identify key genes for the 9 fibrotic diseases by analyzing transcriptomics datasets. We construct gene-to-gene networks for each disease and examine these networks to explore functional communities of biological pathways. We also use the most significant genes as input in Drug Repurposing (DR) tools and re-rank the resulting candidates according to their structural properties and functional relationship to each investigated disease.Results We identify 7 biological pathways involved in all 9 fibrotic diseases as well as pathways unique to some of these diseases. Based on our DR results, we suggest captopril and ibuprofen that both appear to slow the progression of fibrotic diseases according to existing bibliography. We also recommend nafcillin and memantine, which haven’t been studied against fibrosis yet, for further wet-lab experimentation. We also observe a group of cardiomyopathy-related pathways that are exclusively highlighted for Oral Submucous Fibrosis (OSF). We suggest digoxin to be tested against OSF, since we observe cardiomyopathy-related pathways implicated in OSF and there is bibliographic evidence that digoxin may potentially clear myocardial fibrosis. Finally, we establish that IPF shares several involved genes, biological pathways and candidate inhibiting-drugs with Dupuytren’s Disease, IgG4-related Disease, SSc and Cystic Fibrosis. We propose that treatments for these fibrotic diseases should be jointly pursued.Competing Interest StatementThe authors have declared no competing interest.View Full Text

bioinformatics↗

bioRxiv2020

PathWalks: Identifying pathway communities using a disease-related map of integrated information

Understanding disease underlying biological mechanisms and respective interactions remains an elusive, time consuming and costly task. The realization of computational methodologies that can propose pathway/mechanism communities and reveal respective relationships can be of great value as it can help expedite the process of identifying how perturbations in a single pathway can affect other pathways. Random walks is a stochastic approach that can be used for both efficient discovery of strong connections and identification of communities formed in networks. The approach has grown in popularity as it efficiently exposes key network components and reveals strong interactions among genes, proteins, metabolites, pathways and drugs. Using random walks in biology, we need to overcome two key challenges: 1) construct disease-specific biological networks by integrating information from available data sources as they become available, and 2) provide guidance to the walker so as it can follow plausible trajectories that comply with inherent biological constraints. In this work, we present a methodology called PathWalks, where a random walker crosses a pathway-to-pathway network under the guidance of a disease-related map. The latter is a gene network that we construct by integrating multi-source information regarding a specific disease. The most frequent trajectories highlight communities of pathways that are expected to be strongly related to the disease under study. We present maps for Alzheimers Disease and Idiopathic Pulmonary Fibrosis and we use them as case-studies for identifying pathway communities through the application of PathWalks. In the case of Alzheimers Disease, the most visited pathways are the "Alzheimers disease" and the "Calcium signaling" pathways which have indeed the strongest association with Alzheimers Disease. Interestingly however, in the top-20 visited pathways we identify the "Kaposi sarcoma-associated herpesvirus infection" (HHV-8) and the "Human papillomavirus infection" (HPV) pathways suggesting that viruses may be involved in the development and progression of Alzheimers. Similarly, most of the highlighted pathways in Idiopathic Pulmonary Fibrosis are backed by the bibliography. We establish that "MAPK signaling" and "Cytokine-cytokine receptor interaction" pathways are the most visited. However, the "NOD receptor signaling" pathway is also in the top-40 edges. In Idiopathic Pulmonary Fibrosis samples, increased NOD receptor signaling has been associated with augmented concentrations of certain strains of Streptococcus. Additional experimental evidence is required however to further explore and ascertain the above indications.

bioinformatics↗