GNExT uncovers pharmacological targets from genome-wide association studies through network medicine integration

Arend, L., Woller, F., Rehor, B., Emmert, D., Frasnelli, J., Fuchsberger, C., Blumenthal, D. B. et List, M. (2026, September 23-25). GNExT uncovers pharmacological targets from genome-wide association studies through network medicine integration. Dans RExPO26, Berlin, Germany DOI 10.58647/REXPO26000172.v1.

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Résumé

Abstract

As GWAS datasets continue to grow, associations for complex traits are identified at an unprecedented rate. The challenge has shifted from discovery to interpretation, as most platforms report variant-level statistics without linking them to the molecular mechanisms underlying phenotypes. Systems biomedicine closes this gap by embedding genetic signals into molecular interaction networks, revealing coherent modules that can illuminate disease biology and highlight drug targets or repurposing candidates.
We present GNExT (GWAS Network Exploration Tool), a web platform addressing the growing need within the GWAS community for improved accessibility, interpretability, and downstream (re)use of GWAS data. While current solutions such as PheWeb represent important advances in this direction, GNExT extends this paradigm by integrating GWAS findings with gene-mapping approaches, as well as systems and network biology and pharmacology frameworks. Its standardized and scalable Nextflow pipeline enables researchers to seamlessly deploy and host their own datasets while retaining full data control.
We demonstrate GNExT's utility through a GWAS meta-analysis of human olfactory identification and on European-ancestry Pan-UK Biobank data, distilling 7160 traits and over 2 TB of data into a large-scale resource. For Alzheimer's disease, GNExT successfully identified 12 significant genes (e.g., APOE) and a disease module of 22 genes, revealing critical links between dementia and lipid metabolism. This systems-level view further unlocks potential therapeutic targets, identifying repurposing candidates like Metformin and Chlorzoxazone alongside multi-target tyrosine kinase inhibitors such as Nintedanib and Sunitinib.
Hence, GNExT addresses the critical challenge of biological interpretation in large-scale genetic studies by transforming fragmented association signals into coherent mechanistic networks and generating actionable therapeutic hypotheses, and, through its publicly available and easily deployable framework, empowers any researcher to apply GNExT to their own GWAS data with minimal technical overhead.

Type de document:	Document issu d'une conférence ou d'un atelier
Mots-clés libres:	GWAS Drug repurposing Network pharmacology Gene-mapping
Date de dépôt:	21 oct. 2026 15:24
Dernière modification:	21 oct. 2026 15:24
Version du document déposé:	Version officielle de l'éditeur
URI:	https://depot-e.uqtr.ca/id/eprint/13246

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