Multiplexed measurement of candidate blood protein biomarkers of heart failure

Abstract

Aims There is a critical need for better biomarkers so that heart failure can be diagnosed at an earlier stage and with greater accuracy. The purpose of this study was to design a robust mass spectrometry (MS)-based assay for the simultaneous measurement of a panel of 35 candidate protein biomarkers of heart failure, in blood. The overall aim was to evaluate the potential clinical utility of this biomarker panel for prediction of heart failure in a cohort of 500 patients. Methods and results Multiple reaction monitoring (MRM) MS assays were designed with Skyline and Spectrum Mill PeptideSelector software and developed using nanoflow reverse phase C18 chromatographic Chip Cube-based separation, coupled to a 6460 triple quadrupole mass spectrometer. Optimized MRM assays were applied, in a sample-blinded manner, to serum samples from a cohort of 500 patients with heart failure and non-heart failure (non-HF) controls who had cardiovascular risk factors. Both heart failure with reduced ejection fraction (HFrEF) patients and heart failure with preserved ejection fraction (HFpEF) patients were included in the study. Peptides for the Apolipoprotein AI (APOA1) protein were the most significantly differentially expressed between non-HF and heart failure patients (P = 0.013 and P = 0.046). Four proteins were significantly differentially expressed between non-HF and the specific subtypes of HF (HFrEF and HFpEF); Leucine-rich-alpha-2glycoprotein (LRG1, P < 0.001), zinc-alpha-2-glycoprotein (P = 0.005), serum paraoxanse/arylesterase (P = 0.013), and APOA1 (P = 0.038). A statistical model found that combined measurements of the candidate biomarkers in addition to BNP were capable of correctly predicting heart failure with 83.17% accuracy and an area under the curve (AUC) of 0.90. This was a notable improvement on predictive capacity of BNP measurements alone, which achieved 77.1% accuracy and an AUC of 0.86 (P = 0.005). The protein peptides for LRG1, which contributed most significantly to model performance, were significantly associated with future new onset HF in the non-HF cohort [Peptide 1: odds ratio (OR) 2.345 95% confidence interval (CI) (1.456-3.775) P = 0.000; peptide 2: OR 2.264 95% CI (1.422-3.605), P = 0.001]. Conclusions This study has highlighted a number of promising candidate biomarkers for (i) diagnosis of heart failure and subtypes of heart failure and (ii) prediction of future new onset heart failure in patients with cardiovascular risk factors. Furthermore, this study demonstrates that multiplexed measurement of a combined biomarker signature that includes BNP is a more accurate predictor of heart failure than BNP alone.

Screening of Lipid Metabolism-Related Gene Diagnostic Signature for Patients With Dilated Cardiomyopathy

“…The up-regulated genes include Apolipoprotein A1 (APOA1), a main protein in high-density lipoprotein (HDL) (20), but many of the other genes related to lipid metabolism have rarely been reported. Another study also found that APOA1 was significantly differentially expressed between non-heart failure and heart failure patients, and could be a candidate blood protein biomarker of heart failure (21). The present study identified numerous DELs associated with DCM, which could be potential targets for subsequent research.…”

LRG1: an emerging player in disease pathogenesis

“…Notably, female study participants showed higher LRG1 levels than males [ 113 , 114 ] which supports other findings suggesting there are sex differences in the biology of LRG1. Other studies reported a positive correlation between circulating or coronary sinus LRG1 levels and the incidence of heart failure [ 115 – 118 ] and idiopathic pulmonary arterial hypertension [ 119 ]. In contrast, in patients with statin-treated familial hypercholesteremia, detectable serum levels of LRG1 were observed only in the absence of coronary artery disease [ 120 ].…”

Research Progress on Leucine-Rich Alpha-2 Glycoprotein 1: A Review

“…LRG1 might be a potential serum biomarker for early onset myocardial infarction, while a combined biomarker signature that included BNP (plasma brain natriuretic peptide) would be a more accurate predictor of heart failure than BNP alone (Xuan et al, 2019). TLRG1 was the most prominent biomarker, among others, to predict the pathological progress of heart failure (Tonry et al, 2021). LRG1 was selected to distinguish persistent atrial fibrillation patients and control subjects (Cao et al, 2020).…”

“…Due to their great potential in the prediction of cardiovascular diseases, particular methods and mechanisms had yet to be investigated. Uncovering potential lncRNAs and mRNAs, including LRG1 was essential biomarkers from acute myocardial infarction aggravated to heart failure (Tonry et al, 2021;Wang et al, 2021). In terms of mechanism research, overexpressed miR-494 bound with LRG1 inactivated Wnt signaling pathway might promote fibroblasts and vascular endothelial cells proliferation in myocardial infarction (Su et al, 2019).…”