A personalized network framework reveals predictive axis of anti-TNF response across diseases

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 captu...

Full description

Saved in:

Bibliographic Details
Published in:	Cell reports. Medicine Vol. 5; no. 1; p. 101300
Main Authors:	Gerassy-Vainberg, Shiran, Starosvetsky, Elina, Gaujoux, Renaud, Blatt, Alexandra, Maimon, Naama, Gorelik, Yuri, Pressman, Sigal, Alpert, Ayelet, Bar-Yoseph, Haggai, Dubovik, Tania, Perets, Benny, Katz, Adir, Milman, Neta, Segev, Meital, Chowers, Yehuda, Shen-Orr, Shai S
Format:	Journal Article
Language:	English
Published:	United States Elsevier 16-01-2024
Subjects:	Arthritis, Rheumatoid - drug therapy Humans Inflammatory Bowel Diseases - drug therapy Infliximab - therapeutic use Tumor Necrosis Factor Inhibitors - therapeutic use Tumor Necrosis Factor-alpha drug response anti-TNF antibodies immune-mediated diseases infliximab precision medicine individual-level network analysis pan-disease drug response diagnostics rheumatoid arthritis inflammatory bowel disease
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Description
Summary:	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.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Israeli IBD Research Network (IIRN) These authors contributed equally Lead contact
ISSN:	2666-3791 2666-3791
DOI:	10.1016/j.xcrm.2023.101300