A personalized network framework reveals predictive axis of anti-TNF response across diseases.
anti-TNF antibodies
drug response
immune-mediated diseases
individual-level network analysis
inflammatory bowel disease
infliximab
pan-disease drug response diagnostics
precision medicine
rheumatoid arthritis
Journal
Cell reports. Medicine
ISSN: 2666-3791
Titre abrégé: Cell Rep Med
Pays: United States
ID NLM: 101766894
Informations de publication
Date de publication:
12 Dec 2023
12 Dec 2023
Historique:
received:
21
02
2023
revised:
20
08
2023
accepted:
31
10
2023
medline:
21
12
2023
pubmed:
21
12
2023
entrez:
20
12
2023
Statut:
aheadofprint
Résumé
Personalized treatment of complex diseases has been mostly predicated on biomarker identification of one drug-disease combination at a time. Here, we use a computational approach termed Disruption Networks to generate a data type, contextualized by cell-centered individual-level networks, that captures biology otherwise overlooked when performing standard statistics. This data type extends beyond the "feature level space", to the "relations space", by quantifying individual-level breaking or rewiring of cross-feature relations. Applying Disruption Networks to dissect high-dimensional blood data, we discover and validate that the RAC1-PAK1 axis is predictive of anti-TNF response in inflammatory bowel disease. Intermediate monocytes, which correlate with the inflammatory state, play a key role in the RAC1-PAK1 responses, supporting their modulation as a therapeutic target. This axis also predicts response in rheumatoid arthritis, validated in three public cohorts. Our findings support blood-based drug response diagnostics across immune-mediated diseases, implicating common mechanisms of non-response.
Identifiants
pubmed: 38118442
pii: S2666-3791(23)00494-9
doi: 10.1016/j.xcrm.2023.101300
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
101300Informations de copyright
Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of interests These authors disclose the following: Y.C. received consulting fees from AbbVie, Janssen, Takeda, Pfizer, and CytoReason; speaker fees from AbbVie, Janssen, and Takeda; and grants from AbbVie, Takeda and Janssen. S.S.S.-O. received grant fees from Takeda. S.S.S.-O., E.S., R.G., and Y.C. declare CytoReason equity. S.S.S.-O. declares CytoReason advisory fees. Y.C., N.Maimon, and A.K. are employees at CytoReason. S.G.V. declares CytoReason advisory fees. S.S.S.-O., Y.C., S.G.V., A.B., E.S., R.G., and N.Maimon, have a National Phase Patent: WO2022/264134 A1 (METHOD FOR DETERMINING SUITABILITY TO ANTI-TNF ALPHA THERAPY, published as of December 22, 2022). The grant support did not affect study design at any stage.