Network analysis reveals rare disease signatures across multiple levels of biological organization

Pisanu Buphamalai, Tomislav Kokotovic, Vanja Nagy and Jörg Menche ()
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Pisanu Buphamalai: CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences
Tomislav Kokotovic: CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences
Vanja Nagy: CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences
Jörg Menche: CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences

Nature Communications, 2021, vol. 12, issue 1, 1-15

Abstract: Abstract Rare genetic diseases are typically caused by a single gene defect. Despite this clear causal relationship between genotype and phenotype, identifying the pathobiological mechanisms at various levels of biological organization remains a practical and conceptual challenge. Here, we introduce a network approach for evaluating the impact of rare gene defects across biological scales. We construct a multiplex network consisting of over 20 million gene relationships that are organized into 46 network layers spanning six major biological scales between genotype and phenotype. A comprehensive analysis of 3,771 rare diseases reveals distinct phenotypic modules within individual layers. These modules can be exploited to mechanistically dissect the impact of gene defects and accurately predict rare disease gene candidates. Our results show that the disease module formalism can be applied to rare diseases and generalized beyond physical interaction networks. These findings open up new venues to apply network-based tools for cross-scale data integration.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-26674-1

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DOI: 10.1038/s41467-021-26674-1

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