Abstract
Byline: Taariq M Salie, Univ of Cape Town, Cape Town, South Africa; Jing Yang, Univ of Manchester, Manchester, United Kingdom; Carlos R Medina, Univ of Manchester, Manchester, United Kingdom; Nophar Geifman, Div of Informatics, Imaging & Data Sciences, Univ of Manchester, Manchester, United Kingdom; Liesl J Zuhlke, Paediatrics, Univ of Cape Town, Institute of Child Health, Red Cross Children's Hosp, Cape Town, South Africa; Simon Frain, Div of Cardiovascular Sciences, Univ of Manchester, Manchester, United Kingdom; Anthony Whetton, Univ of Manchester, Manchester, United Kingdom; Bernard Keavney, Univ of Manchester, Manchester; Mark E Engel, Univ of Cape Town, OBSERVATORY; Introduction: 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: We conducted a proteomic study in 215 African patients with severe RHD and 230 controls, using the SWATH-MS technique. 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 AUC of the ROC 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: Adiponectin, complement component C7 and fibulin-1, a component of heart valve matrix, were each 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 6 biomarkers from the Boruta analyses conferred an AUC of 0.90 indicating excellent discriminatory capacity between RHD cases and controls. 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.