Evidence map›Paper›PMID 42665836›Full record

ArticleGenome biology2026

Protein-protein interaction network architecture of human polygenic traits reveals domain-spanning connectivity and evolutionary pressures.

Ehsan Tamandeh, Kiran Kunwar, Jessica Bigge, Adrian Serohijos, Johannes Schumacher, Carlo Maj, Pouria Dasmeh

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Article in Genome biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Ehsan TamandehCenter for Human Genetics, Marburg University, Marburg, Germany.
Kiran KunwarCenter for Human Genetics, Marburg University, Marburg, Germany.
Jessica BiggeCenter for Human Genetics, Marburg University, Marburg, Germany.
Adrian SerohijosDepartment of Biochemistry, Faculty of Medicine, University of Montreal, Montreal, Canada.
Johannes SchumacherCenter for Human Genetics, Marburg University, Marburg, Germany.
Carlo MajCenter for Human Genetics, Marburg University, Marburg, Germany. Carlo.maj@uni-marburg.de.
Pouria DasmehCenter for Human Genetics, Marburg University, Marburg, Germany. Dasmeh@staff.uni-marburg.de.ORCID https://orcid.org/0000-0002-4527-5302

Funding

Deutsche Forschungsgemeinschaft 534238115
6 · The paper itself

Abstract

backgroundHuman polygenic phenotypes arise from the combined effects of many genes that interact within molecular networks. Yet, we know little about how the structure of these networks constrains or facilitates the evolution of complex traits. Here, we systematically examine the relationship between protein-protein interaction (PPI) network architecture and evolutionary signatures across 4,756 human polygenic phenotypes.

resultsWe show that genes associated with polygenic phenotypes exhibit significantly higher connectivity within the global PPI network compared to matched random gene sets. Highly connected genes are enriched for immune-related biological processes, whereas genes with fewer interactions are preferentially associated with neurogenesis-related functions. Importantly, among trait-associated genes, greater network connectivity is associated with weaker selective constraint, indicating that evolutionary pressure varies according to network embedding.

conclusionsTogether, these findings provide a systems-level framework linking molecular interaction architecture to the evolution of human polygenic traits. To support this effort, we also develop an online portal enabling researchers to generate and explore hypotheses by identifying genes that are both highly associated and highly connected across thousands of polygenic phenotypes.

Indexed as

Evolution, MolecularMultifactorial InheritanceProtein Interaction MapsHumansPhenotype

Identifiers

PMID42665836
PMCPMC13523357

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