Data-independent acquisition mass spectrometry in severe rheumatic heart disease (RHD) identifies a proteomic signature showing ongoing inflammation and effectively classifying RHD cases.
Adiponectin
Biomarker
Complement component C7
Fibulin-1
Inflammatory response
Rheumatic heart disease
Journal
Clinical proteomics
ISSN: 1542-6416
Titre abrégé: Clin Proteomics
Pays: England
ID NLM: 101184586
Informations de publication
Date de publication:
22 Mar 2022
22 Mar 2022
Historique:
received:
24
09
2021
accepted:
28
02
2022
entrez:
23
3
2022
pubmed:
24
3
2022
medline:
24
3
2022
Statut:
epublish
Résumé
Rheumatic heart disease (RHD) remains a major source of morbidity and mortality in developing countries. A deeper insight into the pathogenetic mechanisms underlying RHD could provide opportunities for drug repurposing, guide recommendations for secondary penicillin prophylaxis, and/or inform development of near-patient diagnostics. We performed quantitative proteomics using Sequential Windowed Acquisition of All Theoretical Fragment Ion Mass Spectrometry (SWATH-MS) to screen protein expression in 215 African patients with severe RHD, and 230 controls. We applied a machine learning (ML) approach to feature selection among the 366 proteins quantifiable in at least 40% of samples, using the Boruta wrapper algorithm. The case-control differences and contribution to Area Under the Receiver Operating Curve (AUC) for each of the 56 proteins identified by the Boruta algorithm were calculated by Logistic Regression adjusted for age, sex and BMI. Biological pathways and functions enriched for proteins were identified using ClueGo pathway analyses. Adiponectin, complement component C7 and fibulin-1, a component of heart valve matrix, were significantly higher in cases when compared with controls. Ficolin-3, a protein with calcium-independent lectin activity that activates the complement pathway, was lower in cases than controls. The top six biomarkers from the Boruta analyses conferred an AUC of 0.90 indicating excellent discriminatory capacity between RHD cases and controls. These results support the presence of an ongoing inflammatory response in RHD, at a time when severe valve disease has developed, and distant from previous episodes of acute rheumatic fever. This biomarker signature could have potential utility in recognizing different degrees of ongoing inflammation in RHD patients, which may, in turn, be related to prognostic severity.
Sections du résumé
BACKGROUND
BACKGROUND
Rheumatic heart disease (RHD) remains a major source of morbidity and mortality in developing countries. A deeper insight into the pathogenetic mechanisms underlying RHD could provide opportunities for drug repurposing, guide recommendations for secondary penicillin prophylaxis, and/or inform development of near-patient diagnostics.
METHODS
METHODS
We performed quantitative proteomics using Sequential Windowed Acquisition of All Theoretical Fragment Ion Mass Spectrometry (SWATH-MS) to screen protein expression in 215 African patients with severe RHD, and 230 controls. We applied a machine learning (ML) approach to feature selection among the 366 proteins quantifiable in at least 40% of samples, using the Boruta wrapper algorithm. The case-control differences and contribution to Area Under the Receiver Operating Curve (AUC) for each of the 56 proteins identified by the Boruta algorithm were calculated by Logistic Regression adjusted for age, sex and BMI. Biological pathways and functions enriched for proteins were identified using ClueGo pathway analyses.
RESULTS
RESULTS
Adiponectin, complement component C7 and fibulin-1, a component of heart valve matrix, were significantly higher in cases when compared with controls. Ficolin-3, a protein with calcium-independent lectin activity that activates the complement pathway, was lower in cases than controls. The top six biomarkers from the Boruta analyses conferred an AUC of 0.90 indicating excellent discriminatory capacity between RHD cases and controls.
CONCLUSIONS
CONCLUSIONS
These results support the presence of an ongoing inflammatory response in RHD, at a time when severe valve disease has developed, and distant from previous episodes of acute rheumatic fever. This biomarker signature could have potential utility in recognizing different degrees of ongoing inflammation in RHD patients, which may, in turn, be related to prognostic severity.
Identifiants
pubmed: 35317720
doi: 10.1186/s12014-022-09345-1
pii: 10.1186/s12014-022-09345-1
pmc: PMC8939134
doi:
Types de publication
Journal Article
Langues
eng
Pagination
7Subventions
Organisme : British Heart Foundation
ID : RG/F/21/110050
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 099313/B/12/A
Pays : United Kingdom
Organisme : Wellcome Trust
Pays : United Kingdom
Informations de copyright
© 2022. The Author(s).
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