University of Leicester
2020CHANDCSPhD.pdf (6.52 MB)

Plasma Proteomics for Biomarker Discovery to Predict Progression of Initially Asymptomatic Moderate- Severe Aortic Stenosis

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posted on 2020-07-15, 09:17 authored by Daniel C. S. Chan
The optimal timing of aortic valve replacement in asymptomatic moderate-severe aortic stenosis (AS) is challenging. Robust markers predicting symptom onset or aortic valve related events in these patients are urgently needed. Plasma proteomics offers an opportunity to identify novel biomarkers in these patients. Two sample preparation workflows for mass spectrometry were developed and compared – a) Immunodepletion + Protein prefractionation on a reversed phased C18 column and b) extracellular vesicle pulldown followed by calcium silicate hydrate pulldown. The extracellular vesicle and calcium silicate hydrate pulldown method was more reproducible with >1500 protein identifications. This method was used for biomarker discovery in 92 propensity-matched event vs noevent samples, using one dimensional liquid-chromatography-linked tandem mass spectrometry with ion mobility specific collision energies for proteomic analysis. Samples were recruitment plasma samples from the PRIMID-AS study, a prospective observational multicentre study of asymptomatic moderate-severe AS patients with extensive phenotyping with electrocardiography, echocardiography, bicycle exercise testing and multiparametric cardiac magnetic resonance testing with T1 mapping, late gadolinium enhancement and stress first pass perfusion imaging. The primary endpoint was valve replacement for spontaneous AS-related symptoms or cardiovascular death or unplanned cardiovascular hospitalisation. 49 proteins were found to be differentially expressed, which may represent novel associated pathways such as fatty acid oxidation, inflammation, cell death/apoptosis/autophagy, arrhythmogenesis, neural remodelling and lysosomal survival. Of these, 17 were selected for verification using 18Oisotope-labelled-pooled internal standards as the reference. Apolipoprotein D (APOD) emerged as a strong predictor of the primary endpoint, independent to exercise testing, sex, peak velocity, mean gradient and N-terminal-pro-brain natriuretic peptide. Addition of APOD to baseline characteristics resulted in a net reclassification improvement of 50-78%, particularly in moderate AS. Important correlates of APOD were tetranectin and body mass index. This biomarker could be used to optimally time aortic valve replacement in this group of patients.



Leong Ng

Date of award


Author affiliation

Cardiovascular Sciences

Awarding institution

University of Leicester

Qualification level

  • Doctoral

Qualification name

  • PhD



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