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Identifying early pulmonary arterial hypertension biomarkers in systemic sclerosis: Machine learning on proteomics from the DETECT cohort

Yasmina Bauer, Simon de Bernard, Peter Hickey, Karri Ballard, Jeremy Cruz, Peter Cornelisse, Harbajan Chadha-Boreham, Oliver Distler, Daniel Rosenberg, Martin Doelberg, Sebastien Roux, Oliver Nayler, Allan Lawrie
European Respiratory Journal 2020; DOI: 10.1183/13993003.02591-2020
Yasmina Bauer
1Galapagos GmbH, Basel, Switzerland
2Idorsia Pharmaceuticals Ltd, Allschwil, Switzerland
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Simon de Bernard
3AltraBio, Lyon, France
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Peter Hickey
4Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Medical School, Sheffield, UK
5Sheffield Pulmonary Vascular Disease Unit, Royal Hallamshire Hospital, Sheffield, UK
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Karri Ballard
6Myriad RBM, Austin, USA
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Jeremy Cruz
6Myriad RBM, Austin, USA
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Peter Cornelisse
2Idorsia Pharmaceuticals Ltd, Allschwil, Switzerland
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Harbajan Chadha-Boreham
7Actelion Pharmaceuticals Ltd, Allschwil, Switzerland
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Oliver Distler
8University Hospital Zurich, Department of Rheumatology, Zurich, Switzerland
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Daniel Rosenberg
7Actelion Pharmaceuticals Ltd, Allschwil, Switzerland
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Martin Doelberg
7Actelion Pharmaceuticals Ltd, Allschwil, Switzerland
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Sebastien Roux
2Idorsia Pharmaceuticals Ltd, Allschwil, Switzerland
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Oliver Nayler
2Idorsia Pharmaceuticals Ltd, Allschwil, Switzerland
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Allan Lawrie
4Department of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Medical School, Sheffield, UK
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  • ORCID record for Allan Lawrie
  • For correspondence: a.lawrie@sheffield.ac.uk
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Abstract

Pulmonary arterial hypertension (PAH) is a devastating complication of Systemic Sclerosis (SSc). Screening for PAH in SSc has increased detection, allowed early treatment for PAH, and improved patient outcomes. Blood-based biomarkers that reliably identify SSc patients at risk of PAH, or with early disease, would significantly improve screening, potentially leading to improved survival, and provide novel mechanistic insights into early disease. The main objective of this study was to identify a proteomic biomarker signature that could discriminate SSc patients with, and without PAH using a Machine Learning approach, and to validate the findings in an external cohort.

Serum samples from patients with SSc and PAH (n=77) and SSc without PH (non-PH, n=80) were randomly selected from the clinical DETECT study and underwent proteomic screening using the MYRIAD RBM discovery platform consisting of 313 proteins. Samples from an independent validation cohort (SSc-PAH, n=22 and non-PH, n=22) were obtained from University of Sheffield, UK. Random Forest (RF) analysis identified a novel panel of eight proteins, comprising Collagen IV, Endostatin, IGFBP-2, IGFBP-7, MMP-2, Neuropilin-1, NT-proBNP and RAGE, that discriminated PAH from non-PH in SSc patients in the DETECT discovery cohort (average area under the ROC values (ROC-AUC) of 0.741, 65.1% sensitivity / 69.0% specificity) was reproduced in the Sheffield cohort (81.1% accuracy, 77.3% sensitivity / 86.5% specificity). This novel 8-protein biomarker panel has the potential to improve early detection of PAH in SSc patients and may provide novel insights into the pathogenesis of PAH in the context of SSc.

Footnotes

This manuscript has recently been accepted for publication in the European Respiratory Journal. It is published here in its accepted form prior to copyediting and typesetting by our production team. After these production processes are complete and the authors have approved the resulting proofs, the article will move to the latest issue of the ERJ online. Please open or download the PDF to view this article.

Conflict of interest: Dr. Bauer has nothing to disclose.

Conflict of interest: Dr. de Bernard reports grant from Idorsia, during the conduct of the study;.

Conflict of interest: Dr. Hickey has nothing to disclose.

Conflict of interest: Dr. Ballard has nothing to disclose.

Conflict of interest: Dr. Cruz has nothing to disclose.

Conflict of interest: Mr. Cornelisse has nothing to disclose.

Conflict of interest: Dr. Harbajan has nothing to disclose.

Conflict of interest: Dr. Distler reports personal fees from Amgen, personal fees from Abbvie, personal fees from Acceleron Pharma, personal fees from AnaMar, personal fees from Actelion, personal fees from Alexion, personal fees from Arxx Therapeutics, personal fees from Baecon Discovery, personal fees from Blade Therapeutics, grants and personal fees from Bayer, grants and personal fees from Boehringer Ingelheim, personal fees from Catenion, personal fees from Competitive Drug Development International Ltd, personal fees from Corbuspharma, personal fees from CSL Behring, personal fees from ChemomAb, personal fees from Horizon Pharmaceuticals, personal fees from Ergonex, personal fees from Galapagos NV, personal fees from Glenmark Pharmaceuticals, personal fees from GSK, personal fees from Inventiva, personal fees from Italfarmaco, personal fees from iQone, personal fees from iQvia, personal fees from Kymera, personal fees from Lilly, personal fees from Medac, personal fees from Medscape, grants and personal fees from Mitsubishi Tanabe Pharma, personal fees from MSD, personal fees from Novartis, personal fees from Pfizer, personal fees from Roche, personal fees from Sanofi, personal fees from Target Bio Science, personal fees from UCB, outside the submitted work; In addition, Dr. Distler has a patent mir-29 for the treatment of systemic sclerosis issued to US8247389, EP2331143.

Conflict of interest: Dr. Rosenberg reports other from Actelion, Janssen, Johnson and Johnson, during the conduct of the study; other from Johnson and Johnson, outside the submitted work;.

Conflict of interest: Dr. Doelberg reports other from Actelion Pharmaceuticals Ltd, outside the submitted work;.

Conflict of interest: Dr. roux has nothing to disclose.

Conflict of interest: Dr. Nayler reports other from Idorsia Pharmaceuticals Ltd, outside the submitted work;.

Conflict of interest: Dr. Lawrie reports grants from British Heart Foundation, grants from Medical Research Council, grants, personal fees and other from Actelion Pharmaceuticals, grants and personal fees from GlaxoSmithKline, outside the submitted work;.

  • Received July 6, 2020.
  • Accepted November 17, 2020.
  • Copyright ©ERS 2020
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Identifying early pulmonary arterial hypertension biomarkers in systemic sclerosis: Machine learning on proteomics from the DETECT cohort
Yasmina Bauer, Simon de Bernard, Peter Hickey, Karri Ballard, Jeremy Cruz, Peter Cornelisse, Harbajan Chadha-Boreham, Oliver Distler, Daniel Rosenberg, Martin Doelberg, Sebastien Roux, Oliver Nayler, Allan Lawrie
European Respiratory Journal Jan 2020, 2002591; DOI: 10.1183/13993003.02591-2020

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Identifying early pulmonary arterial hypertension biomarkers in systemic sclerosis: Machine learning on proteomics from the DETECT cohort
Yasmina Bauer, Simon de Bernard, Peter Hickey, Karri Ballard, Jeremy Cruz, Peter Cornelisse, Harbajan Chadha-Boreham, Oliver Distler, Daniel Rosenberg, Martin Doelberg, Sebastien Roux, Oliver Nayler, Allan Lawrie
European Respiratory Journal Jan 2020, 2002591; DOI: 10.1183/13993003.02591-2020
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