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Host-Response Subphenotypes Offer Prognostic Enrichment in Patients With or at Risk for Acute Respiratory Distress Syndrome*

Kitsios, Georgios D. MD, PhD1,2; Yang, Libing MDc1; Manatakis, Dimitris V. PhD3; Nouraie, Mehdi MD, PhD1; Evankovich, John MD1; Bain, William MD1; Dunlap, Daniel G. MD1; Shah, Faraaz MD, MPH1; Barbash, Ian J. MD, MS1; Rapport, Sarah F. BS, MPH1; Zhang, Yingze PhD1; DeSensi, Rebecca S. BA1; Weathington, Nathaniel M. MD, PhD1; Chen, Bill B. PhD1; Ray, Prabir PhD1; Mallampalli, Rama K. MD1,4; Benos, Panayiotis V. PhD3; Lee, Janet S. MD1; Morris, Alison MD, MS1,2,5; McVerry, Bryan J. MD1,2

doi: 10.1097/CCM.0000000000004018
Clinical Investigations
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Objectives: Classification of patients with acute respiratory distress syndrome into hyper- and hypoinflammatory subphenotypes using plasma biomarkers may facilitate more effective targeted therapy. We examined whether established subphenotypes are present not only in patients with acute respiratory distress syndrome but also in patients at risk for acute respiratory distress syndrome (ARFA) and then assessed the prognostic information of baseline subphenotyping on the evolution of host-response biomarkers and clinical outcomes.

Design: Prospective, observational cohort study.

Setting: Medical ICU at a tertiary academic medical center.

Patients: Mechanically ventilated patients with acute respiratory distress syndrome or ARFA.

Interventions: None.

Measurements and Main Results: We performed longitudinal measurements of 10 plasma biomarkers of host injury and inflammation. We applied unsupervised latent class analysis methods utilizing baseline clinical and biomarker variables and demonstrated that two-class models (hyper- vs hypoinflammatory subphenotypes) offered improved fit compared with one-class models in both patients with acute respiratory distress syndrome and ARFA. Baseline assignment to the hyperinflammatory subphenotype (39/104 [38%] acute respiratory distress syndrome and 30/108 [28%] ARFA patients) was associated with higher severity of illness by Sequential Organ Failure Assessment scores and incidence of acute kidney injury in patients with acute respiratory distress syndrome, as well as higher 30-day mortality and longer duration of mechanical ventilation in ARFA patients (p < 0.0001). Hyperinflammatory patients exhibited persistent elevation of biomarkers of innate immunity for up to 2 weeks postintubation.

Conclusions: Our results suggest that two distinct subphenotypes are present not only in patients with established acute respiratory distress syndrome but also in patients at risk for its development. Hyperinflammatory classification at baseline is associated with higher severity of illness, worse clinical outcomes, and trajectories of persistently elevated biomarkers of host injury and inflammation during acute critical illness compared with hypoinflammatory patients. Our findings provide strong rationale for examining treatment effect modifications by subphenotypes in randomized clinical trials to inform precision therapeutic approaches in critical care.

1Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and University of Pittsburgh Medical Center, Pittsburgh, PA.

2Center for Medicine and the Microbiome, University of Pittsburgh School of Medicine, Pittsburgh, PA.

3Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA.

4Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, PA.

5Department of Immunology, University of Pittsburgh School of Medicine, Pittsburgh, PA.

*See also p.1806.

Drs. Kitsios, Morris, and McVerry involved in conception and design. Dr. Kitsios, Ms. Yang, and Drs. Manatakis, Evankovich, Bain, Dunlap, Shah, and Barbash, Ms. Rapport, Drs. Zhang and Nouraie, Ms. DeSensi, and Drs. Weathington, Benos, Lee, Morris, and McVerry involved in acquisition, analysis, or interpretation of data. Drs. Kitsios, Evankovich, Bain, Dunlap, Shah, and Barbash, Ms. Rapport, and Drs. Weathington, Lee, Morris, and McVerry involved in clinical cohort phenotyping. Drs. Kitsios, Yang, Manatakis, Evankovich, Bain, Dunlap, Shah, and Barbash, Ms. Rapport, Drs. Zhang and Nouraie, Ms. DeSensi, and Drs. Weathington, Chen, Ray, Mallampalli, Benos, Lee, Morris, and McVerry involved in drafting of work and/or revising for important intellectual content. Dr. Kitsios, Ms. Yang, and Drs. Manatakis, Evankovich, Bain, Dunlap, Shah, and Barbash, Ms. Rapport, Drs. Zhang and Nouraie, Ms. DeSensi, and Drs. Weathington, Chen, Ray, Mallampalli, Benos, Lee, Morris, and McVerry involved in final approval of version to be published, and agreement to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Supported, in part, by grants from National Institutes of Health (NIH) (K23 HL139987 [to Dr. Kitsios]; U01 HL098962 [to Dr. Morris]; P01 HL114453 [to Drs. Ray, Mallampalli, and McVerry]; R01 HL097376 [to Drs. Mallampalli and McVerry]; R01 HL116472 [to Dr. Chen]; K24 HL123342 [to Dr. Morris]; U01 HL137159 [to Drs. Manatakis and Benos]; R01 LM012087 [to Drs. Manatakis and Benos]; R01 HL142084 [to Dr. Lee]; R01 HL136143 [to Dr. Lee]; F32 HL137258 [to Dr. Evankovich]; F32 HL142172 [to Dr. Bain]; K08 HS025455 [to Dr. Barbash]; K23 GM122069 [to Dr. Shah]; R35 HL139860 [to Dr. Chen]; and R01 HL133184 [to Dr. Chen]).

Dr. Kitsios receives research funding from Karius. Drs. Kitsios, Nouraie, Evankovich, Bain, Shah, Barbash, Zhang, Weathington, Chen, Ray, Mallampalli, Benos, Lee, Morris, and McVerry received support for article research from the NIH. Drs. Chen and Mallampalli are consultants for Koutif Pharmaceuticals, and they received funding from Koutif Pharmaceuticals (consulting). Dr. Morris’s institution received funding from Gilead. Dr. McVerry received funding from Vapotherm (consulting) and Bayer Pharmaceuticals (research support). The remaining authors have disclosed that they do not have any potential conflicts of interest

Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s website (http://journals.lww.com/ccmjournal).

All de-identified datasets as well as the statistical code in R used for analyses for this study are provided in https://github.com/MicrobiomeALIR.

For information regarding this article, E-mail: kitsiosg@upmc.edu

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