Gene Expression Scoring of Immune Activity Levels for Precision Use of Hydrocortisone in Vasodilatory Shock.


Journal

Shock (Augusta, Ga.)
ISSN: 1540-0514
Titre abrégé: Shock
Pays: United States
ID NLM: 9421564

Informations de publication

Date de publication:
01 03 2022
Historique:
pubmed: 27 1 2022
medline: 22 3 2022
entrez: 26 1 2022
Statut: ppublish

Résumé

Among patients with vasodilatory shock, gene expression scores may identify different immune states. We aimed to test whether such scores are robust in identifying patients' immune state and predicting response to hydrocortisone treatment in vasodilatory shock. We selected genes to generate continuous scores to define previously established subclasses of sepsis. We used these scores to identify a patient's immune state. We evaluated the potential for these states to assess the differential effect of hydrocortisone in two randomized clinical trials of hydrocortisone versus placebo in vasodilatory shock. We initially identified genes associated with immune-adaptive, immune-innate, immune-coagulant functions. From these genes, 15 were most relevant to generate expression scores related to each of the functions. These scores were used to identify patients as immune-adaptive prevalent (IA-P) and immune-innate prevalent (IN-P). In IA-P patients, hydrocortisone therapy increased 28-day mortality in both trials (43.3% vs 14.7%, P = 0.028) and (57.1% vs 0.0%, P = 0.99). In IN-P patients, this effect was numerically reversed. Gene expression scores identified the immune state of vasodilatory shock patients, one of which (IA-P) identified those who may be harmed by hydrocortisone. Gene expression scores may help advance the field of personalized medicine.

Identifiants

pubmed: 35081076
doi: 10.1097/SHK.0000000000001910
pii: 00024382-202203000-00009
pmc: PMC8868213
doi:

Substances chimiques

Anti-Inflammatory Agents 0
Hydrocortisone WI4X0X7BPJ

Types de publication

Journal Article Randomized Controlled Trial

Langues

eng

Sous-ensembles de citation

IM

Pagination

384-391

Informations de copyright

Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the Shock Society.

Déclaration de conflit d'intérêts

ROD, LY, RK, EVA, LB, JO, LTF, and DAR are employees of Endpoint Health, Inc. BL and Hl are employees of HypaHub, Inc. ASN reported receiving personal fees from Dräger unrelated to the submitted work and consulting fees from Endpoint Health. RB has no conflict of interest.

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Auteurs

Lijing Yao (L)

Department of Clinical Data Science, Endpoint Health Inc, Palo Alto, California.

Diego Ariel Rey (DA)

Department of Clinical Data Science, Endpoint Health Inc, Palo Alto, California.

Lucas Bulgarelli (L)

Department of Clinical Data Science, Endpoint Health Inc, Palo Alto, California.

Rachel Kast (R)

Department of Clinical Data Science, Endpoint Health Inc, Palo Alto, California.

Jeff Osborn (J)

Department of Clinical Data Science, Endpoint Health Inc, Palo Alto, California.

Emily Van Ark (E)

Department of Clinical Data Science, Endpoint Health Inc, Palo Alto, California.

Li Tai Fang (LT)

Department of Clinical Data Science, Endpoint Health Inc, Palo Alto, California.

Bayo Lau (B)

Bioinformatics Department, HypaHub Inc, San Jose, California, USA.

Hugo Lam (H)

Bioinformatics Department, HypaHub Inc, San Jose, California, USA.

Leonardo Maestri Teixeira (LM)

Department of Clinical Data Science, Endpoint Health Inc, Palo Alto, California.

Ary Serpa Neto (AS)

Department of Critical Care Medicine, Hospital Israelita Albert Einstein, São Paulo, Brazil.
Australian and New Zealand Intensive Care Research Centre (ANZIC-RC), School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
Department of Critical Care, Melbourne Medical School, University of Melbourne, Austin Hospital, Melbourne, Australia.
Data Analytics Research and Evaluation (DARE) Centre, Austin Hospital, Melbourne, Australia.

Rinaldo Bellomo (R)

Australian and New Zealand Intensive Care Research Centre (ANZIC-RC), School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia.
Department of Critical Care, Melbourne Medical School, University of Melbourne, Austin Hospital, Melbourne, Australia.
Data Analytics Research and Evaluation (DARE) Centre, Austin Hospital, Melbourne, Australia.
Department of Intensive Care, Austin Hospital, Melbourne, Australia.
Department of Intensive Care, Royal Melbourne Hospital, Melbourne, Australia.

Rodrigo Octávio Deliberato (RO)

Department of Clinical Data Science, Endpoint Health Inc, Palo Alto, California.

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