MultiCens: Multilayer network centrality measures to uncover molecular mediators of tissue-tissue communication.
PLoS Comput Biol
; 19(4): e1011022, 2023 04.
Article
em En
| MEDLINE
| ID: mdl-37093889
ABSTRACT
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.
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MEDLINE
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Encéfalo
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Doença de Alzheimer
Limite:
Humans
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article