Dataset Information

Data independent acquisition mass spectrometry in severe Rheumatic Heart Disease (RHD) identifies a proteomic signature showing ongoing inflammation and effectively classifying RHD cases.

ABSTRACT: 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. A machine learning (ML) approach was applied 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. 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 six biomarkers from the Boruta analyses conferred an AUC of 0.90 indicating excellent discriminatory capacity between RHD cases and controls.

INSTRUMENT(S): TripleTOF 6600

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Cell, Blood Plasma

DISEASE(S): Thanatophoric Dysplasia,Type 2 Diabetes Mellitus,Swine Influenza,Cardiovascular System Disease,Wounds And Injuries,Stage Iv Colorectal Cancer,Chronic Bronchitis,Sjogren's Syndrome,Trypanosomiasis

SUBMITTER: jing yang

LAB HEAD: Mark Engel

PROVIDER: PXD030598 | Pride | 2022-04-04

REPOSITORIES: Pride

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Publications

Data-independent acquisition mass spectrometry in severe rheumatic heart disease (RHD) identifies a proteomic signature showing ongoing inflammation and effectively classifying RHD cases.

Salie M Taariq MT Yang Jing J Ramírez Medina Carlos R CR Zühlke Liesl J LJ Chishala Chishala C Ntsekhe Mpiko M Gitura Bernard B Ogendo Stephen S Okello Emmy E Lwabi Peter P Musuku John J Mtaja Agnes A Hugo-Hamman Christopher C El-Sayed Ahmed A Damasceno Albertino A Mocumbi Ana A Bode-Thomas Fidelia F Yilgwan Christopher C Amusa Ganiyu A GA Nkereuwem Esin E Shaboodien Gasnat G Da Silva Rachael R Lee Dave Chi Hoo DCH Frain Simon S Geifman Nophar N Whetton Anthony D AD Keavney Bernard B Engel Mark E ME

Clinical proteomics 20220322 1

<h4>Background</h4>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.<h4>Methods</h4>We performed quantitative proteomics using Sequential Windowed Acquisition of All Theoretical Fragment Ion Mass Spectrometry (SWATH ...[more]

PMID: 35317720

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Dataset Information

Data independent acquisition mass spectrometry in severe Rheumatic Heart Disease (RHD) identifies a proteomic signature showing ongoing inflammation and effectively classifying RHD cases.

Publications

Data-independent acquisition mass spectrometry in severe rheumatic heart disease (RHD) identifies a proteomic signature showing ongoing inflammation and effectively classifying RHD cases.

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