Enhancing Insights into Pulmonary Vascular Disease through a Precision Medicine Approach. A Joint NHLBI–Cardiovascular Medical Research and Education Fund Workshop Report

Newman, John H.; Rich, Stuart; Abman, Steven H.; Alexander, John H.; Barnard, John; Beck, Gerald J.; Benza, Raymond L.; Bull, Todd; Chan, Stephen Y.; Chun, Hyung J.; Doogan, Declan; Dupuis, Jocelyn; Erzurum, Serpil C.; Frantz, Robert P.; Geraci, Mark W.; Gillies, Hunter; Gladwin, Mark T.; Gray, Michael P.; Hemnes, Anna R.; Herbst, Roy S.; Hernandez, Adrian F.; Hill, Nicholas S.; Horn, Evelyn M.; Hunter, Kendall S.; Jing, Zhi‐Cheng; Johns, Roger A.; Kaul, Sanjay; Kawut, Steven M.; Lahm, Tim; Leopold, Jane A.; Lewis, Greg; Mathai, Stephen C.; McLaughlin, Vallerie V.; Michelakis, Evangelos D.; Nathan, Steven D.; Nichols, William C.; Page, Grier P.; Rabinovitch, Marlene; Rich, Jonathan D.; Rischard, Franz; Rounds, Sharon; Shah, Sanjiv J.; Tapson, Victor F.; Lowy, Naomi; Stockbridge, Norman; Weinmann, Gail G.; Xiao, Lei

doi:10.1164/rccm.201701-0150ws

Cited by 74 publications

(77 citation statements)

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“…In 2014, the Redefining Pulmonary Hypertension through Pulmonary Vascular Disease Phenomics (PVDOMICS) initiative was launched in the USA, with the aim of supporting clinical research with a molecular-based classification of pulmonary vascular disease. Over the next few years, the PVDOMICS consortium plan to integrate existing genomic data with patient transcriptomic, proteomic, metabolomic, coagulomic and cell biomic profiles, which can be influenced by environmental and genetic factors 116,117 . In combination with improvements in tissue functioning and imaging, these studies will help to precisely categorize features of PAH and pulmonary vascular disease, providing a foundation to facilitate the development of precision medicine and personalised therapeutic interventions.…”

Section: P Ag E | 18mentioning

confidence: 99%

Molecular genetic framework underlying pulmonary arterial hypertension

et al. 2019

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| Pulmonary arterial hypertension (PAH) is a rare, progressive disorder typified by occlusion of the pulmonary arterioles owing to endothelial dysfunction and uncontrolled proliferation of pulmonary artery smooth muscle cells and fibroblasts. Vascular occlusion can lead to increased pressure in the pulmonary arteries, often resulting in right ventricular failure with shortness of breath and syncope. Since the identification of BMPR2, which encodes a receptor in the transforming growth factor-β superfamily, the development of highthroughput sequencing approaches to identify novel causal genes has substantially advanced our understanding of the molecular genetics of PAH. In the past 6 years, additional pathways involved in PAH susceptibility have been described through the identification of deleterious genetic variants in potassium channels (KCNK3 and ABCC8) and transcription factors (TBX4 and SOX17), among others. Although familial PAH most often has an autosomal dominant pattern of inheritance, cases of incomplete penetrance and evidence of genetic heterogeneity support a model of PAH as a Mendelian disorder with complex disease features. In this Review, we outline the latest advances in the detection of rare and common genetic variants underlying PAH susceptibility and disease progression. These findings have clinical implications on lung vascular function and can help to identify mechanistic pathways amenable to pharmacological intervention. P ag e | 2

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Section: P Ag E | 18mentioning

confidence: 99%

Molecular genetic framework underlying pulmonary arterial hypertension

et al. 2019

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“…We utilized unsupervised consensus clustering to sort PAH patients into clusters based on proteomic immune profiles (online supplement p. [4][5]. This resampling-based analysis framework guides any clustering algorithm to achieve more robust data partitioning.…”

Section: Immune Cluster Identification: Unsupervised Machine Learningmentioning

confidence: 99%

“…Identification of PAH endophenotypes may translate to patient classification schemes that sit closer to underlying pathobiology, assist in clinical trial cohort selection, and pave a road to precision medicine. [3][4][5] An expanding body of knowledge indicates that inflammation and autoimmunity underlie PAH pathogenesis. Pre-clinical work suggests that aberrant reparative immunity and loss of self-tolerance result in exuberant inflammation, which appears to perpetuate vascular injury and remodeling.…”

Section: Introductionmentioning

confidence: 99%

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

Sweatt

Hedlin

Balasubramanian

et al. 2019

Circulation Research

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155

116

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In December 2018, the average time from submission to first decision for all original research papers submitted to Circulation Research was 14.99 days. ABSTRACTRationale: Accumulating evidence implicates inflammation in pulmonary arterial hypertension (PAH) and therapies targeting immunity are under investigation, though 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 2008-2014, 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, CCL5, CCL7, CCL4, MIF), cluster 3 (n=77)(IL-12, IL-17, IL-10, IL-7, VEGF), and cluster 4 (n=37)(IL-8, IL-4, PDGF-, IL-6, CCL11). Demographics, PAH etiologies, comorbidities, and medications were similar across clusters. Non-invasive 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%, CI 35.4-64.1%) and favorable for cluster 3 (82.4%, CI 72.0-94.3%)(across-cluster p<0.001). Findings were replicated in the validation cohort, where machine learning classified four 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. Nonstandard Abbreviations and Acronyms: CI confidence interval 95% EC pulmonary artery endothelial cell IQR interquartile range 25-75% K cluster number in unsupervised consensus clustering MFI median fluorescence intensity mPAP mean pulmonary arterial pressure NT-proBNP N-terminal pro b-type natriuretic peptide PAH pulmonary arterial hypertension PVDOMICS Pulmonary Vascular Disease Phenomics Program PVR pulmonary vascular resistance REVEAL Registry to Evaluate Early and Long-term PAH Disease Management SMC pulmonary artery smooth muscle cell SQL structured query language TAPSE tricuspid annular pla...

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“…In 2014, a new pulmonary vascular disease research initiative termed PVDOMICS was launched by the NHLBI Division of Lung Diseases. 3 PVDOMICS is a collaborative, multidisciplinary effort across 7 medical centers in the US. Cleveland Clinic is the data-coordinating center and the 6 clinical sites are Brigham and Women's Hospital, Columbia University/Cornell University, Johns Hopkins University, Mayo Clinic, University of Arizona, and Vanderbilt University.…”

Section: Update On the Nih-nhlbi Pvdomics Projectmentioning

confidence: 99%

The Road Toward Precision in PH: Personal Omics, Phenomics, and Wearables—Oh My!

Elinoff

Solomon

2018

Advances in Pulmonary Hypertension

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The keynote address of the 2018 Pulmonary Hypertension Association (PHA) Scientific Sessions given by Dr Roham Zamanian, “From Clinical Classification to Precision-Phenotyping: Envisioning Precision Medicine in Pulmonary Hypertension,” was the perfect prelude to the final session of the symposium. In this session the speakers tackled the timely question: “Omics and Wearables in Pulmonary Hypertension: Are We There Yet?” Dr Michael Snyder of Stanford University described how longitudinal, integrative personal omics profiling that incorporate whole genome sequencing, multidimensional omics measurements, and data from wearables can be applied to: 1) determine what it means to be healthy; 2) potentially predict transitions from health to disease prior to symptom development; and 3) better monitor and treat chronic disease. Dr Anna Hemnes of Vanderbilt University shared promising preliminary data from the ongoing multicenter, collaborative PVDOMICS initiative (Redefining Pulmonary Hypertension through Pulmonary Vascular Disease Phenomics), funded by the National Heart, Lung and Blood Institute (NHLBI) and PHA. Finally, Dr Raymond Benza of the Allegheny Health Network shared intriguing pilot data on the safety and utility of an implantable hemodynamic monitoring device, the CardioMEMS™ HF system, in patients with advanced pulmonary arterial hypertension (PAH).

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Enhancing Insights into Pulmonary Vascular Disease through a Precision Medicine Approach. A Joint NHLBI–Cardiovascular Medical Research and Education Fund Workshop Report

Cited by 74 publications

References 50 publications

Molecular genetic framework underlying pulmonary arterial hypertension

Molecular genetic framework underlying pulmonary arterial hypertension

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

The Road Toward Precision in PH: Personal Omics, Phenomics, and Wearables—Oh My!

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