Discovery of Distinct Immune Phenotypes Using Machine Learning in Pulmonary Arterial Hypertension.

Autor:	Sweatt AJ; From the Division of Pulmonary and Critical Care Medicine (A.J.S., M.R.N., R.T.Z.), in the Department of Medicine, Stanford University, CA.; Vera Moulton Wall Center for Pulmonary Vascular Disease, Stanford University, CA (A.J.S., A.H., M.R.N., M.R., R.T.Z.)., Hedlin HK; Quantitative Sciences Unit (H.K.H., V.B.), in the Department of Medicine, Stanford University, CA., Balasubramanian V; Quantitative Sciences Unit (H.K.H., V.B.), in the Department of Medicine, Stanford University, CA., Hsi A; Vera Moulton Wall Center for Pulmonary Vascular Disease, Stanford University, CA (A.J.S., A.H., M.R.N., M.R., R.T.Z.)., Blum LK; Division of Immunology and Rheumatology (L.K.B., W.H.R.), in the Department of Medicine, Stanford University, CA., Robinson WH; Division of Immunology and Rheumatology (L.K.B., W.H.R.), in the Department of Medicine, Stanford University, CA., Haddad F; Division of Cardiovascular Medicine (F.H.), in the Department of Medicine, Stanford University, CA.; Stanford Cardiovascular Institute (F.H.), in the Department of Medicine, Stanford University, CA., Hickey PM; Department of Infection, Immunity, and Cardiovascular Disease, University of Sheffield, United Kingdom (P.M.H., A.L.)., Condliffe R; Sheffield Pulmonary Vascular Disease Unit, Royal Hallamshire Hospital, United Kingdom (R.C.)., Lawrie A; Department of Infection, Immunity, and Cardiovascular Disease, University of Sheffield, United Kingdom (P.M.H., A.L.)., Nicolls MR; From the Division of Pulmonary and Critical Care Medicine (A.J.S., M.R.N., R.T.Z.), in the Department of Medicine, Stanford University, CA.; Institute for Immunity, Transplantation, and Infection (M.R.N., P.K.), in the Department of Medicine, Stanford University, CA.; Vera Moulton Wall Center for Pulmonary Vascular Disease, Stanford University, CA (A.J.S., A.H., M.R.N., M.R., R.T.Z.)., Rabinovitch M; Vera Moulton Wall Center for Pulmonary Vascular Disease, Stanford University, CA (A.J.S., A.H., M.R.N., M.R., R.T.Z.).; Department of Pediatric Cardiology, Stanford University, CA (M.R.)., Khatri P; Institute for Immunity, Transplantation, and Infection (M.R.N., P.K.), in the Department of Medicine, Stanford University, CA.; Division of Biomedical Informatics Research (P.K.) in the Department of Medicine, Stanford University, CA., Zamanian RT; From the Division of Pulmonary and Critical Care Medicine (A.J.S., M.R.N., R.T.Z.), in the Department of Medicine, Stanford University, CA.; Vera Moulton Wall Center for Pulmonary Vascular Disease, Stanford University, CA (A.J.S., A.H., M.R.N., M.R., R.T.Z.).
Jazyk:	angličtina
Zdroj:	Circulation research [Circ Res] 2019 Mar 15; Vol. 124 (6), pp. 904-919.
DOI:	10.1161/CIRCRESAHA.118.313911
Abstrakt:	Rationale: Accumulating evidence implicates inflammation in pulmonary arterial hypertension (PAH) and therapies targeting immunity are under investigation, although it remains unknown if distinct immune phenotypes exist. Objective: Identify PAH immune phenotypes based on unsupervised analysis of blood proteomic profiles. Methods and Results: In a prospective observational study of group 1 PAH patients evaluated at Stanford University (discovery cohort; n=281) and University of Sheffield (validation cohort; n=104) between 2008 and 2014, we measured a circulating proteomic panel of 48 cytokines, chemokines, and factors using multiplex immunoassay. Unsupervised machine learning (consensus clustering) was applied in both cohorts independently to classify patients into proteomic immune clusters, without guidance from clinical features. To identify central proteins in each cluster, we performed partial correlation network analysis. Clinical characteristics and outcomes were subsequently compared across clusters. Four PAH clusters with distinct proteomic immune profiles were identified in the discovery cohort. Cluster 2 (n=109) had low cytokine levels similar to controls. Other clusters had unique sets of upregulated proteins central to immune networks-cluster 1 (n=58; TRAIL [tumor necrosis factor-related apoptosis-inducing ligand], CCL5 [C-C motif chemokine ligand 5], CCL7, CCL4, MIF [macrophage migration inhibitory factor]), cluster 3 (n=77; IL [interleukin]-12, IL-17, IL-10, IL-7, VEGF [vascular endothelial growth factor]), and cluster 4 (n=37; IL-8, IL-4, PDGF-β [platelet-derived growth factor beta], IL-6, CCL11). Demographics, PAH clinical subtypes, comorbidities, and medications were similar across clusters. Noninvasive and hemodynamic surrogates of clinical risk identified cluster 1 as high-risk and cluster 3 as low-risk groups. Five-year transplant-free survival rates were unfavorable for cluster 1 (47.6%; 95% CI, 35.4%-64.1%) and favorable for cluster 3 (82.4%; 95% CI, 72.0%-94.3%; across-cluster P<0.001). Findings were replicated in the validation cohort, where machine learning classified 4 immune clusters with comparable proteomic, clinical, and prognostic features. Conclusions: Blood cytokine profiles distinguish PAH immune phenotypes with differing clinical risk that are independent of World Health Organization group 1 subtypes. These phenotypes could inform mechanistic studies of disease pathobiology and provide a framework to examine patient responses to emerging therapies targeting immunity.
Databáze:	MEDLINE
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