MultiCens: Multilayer network centrality measures to uncover molecular mediators of tissue-tissue communication

• Main Authors: Kumar, T. (Author), Mitra, S. (Author), Narayanan, M. (Author), Ravindran, B. (Author), Sethuraman, R. (Author)
• Format: Article
• Language: English
• Published: NLM (Medline) 2023
• Subjects: Alzheimer disease; Alzheimer Disease; brain; Brain; gene regulatory network; Gene Regulatory Networks; genetics; human; Humans
• Online Access: View Fulltext in Publisher; View in Scopus
• ISBN: 15537358 (ISSN)
• DOI: 10.1371/journal.pcbi.1011022

With the evolution of multicellularity, communication among cells in different tissues and organs became pivotal to life. Molecular basis of such communication has long been studied, but genome-wide screens for genes and other biomolecules mediating tissue-tissue signaling are lacking. To systematically identify inter-tissue mediators, we present a novel computational approach MultiCens (Multilayer/Multi-tissue network Centrality measures). Unlike single-layer network methods, MultiCens can distinguish within- vs. across-layer connectivity to quantify the "influence" of any gene in a tissue on a query set of genes of interest in another tissue. MultiCens enjoys theoretical guarantees on convergence and decomposability, and performs well on synthetic benchmarks. On human multi-tissue datasets, MultiCens predicts known and novel genes linked to hormones. MultiCens further reveals shifts in gene network architecture among four brain regions in Alzheimer's disease. MultiCens-prioritized hypotheses from these two diverse applications, and potential future ones like "Multi-tissue-expanded Gene Ontology" analysis, can enable whole-body yet molecular-level systems investigations in humans. Copyright: © 2023 Kumar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.