Dataset Information

A new multiplexed plasma biomarker panel developed using targeted proteomics and machine learning has diagnostic and prognostic potential in children with hypertrophic cardiomyopathy

ABSTRACT: Background Hypertrophic cardiomyopathy (HCM) is defined clinically by pathological left ventricular hypertrophy (LVH). We have previously developed a plasma proteomics biomarker panel that correlates with clinical markers of disease severity and sudden cardiac death (SCD) risk in adult patients with HCM. The aim of this study was to validate the adult biomarkers and perform new discovery proteomics in childhood-onset HCM. Methods Fifty-nine protein biomarkers were identified from an exploratory plasma proteomics screen in children with HCM and augmented into our existing multiplexed targeted liquid chromatography-tandem/mass spectrometry-based assay. The association of these biomarkers with clinical phenotypes and outcomes was prospectively tested in plasma collected from 148 children with HCM and 50 healthy controls. Machine learning techniques were used to develop novel paediatric plasma proteomic biomarker panels.Results Four previously validated adult HCM markers (Aldolase Fructose-Bisphosphate A, Complement C3a, Talin-1 and Thrombospondin 1) and three new markers (Glycogen Phosphorylase B, Lipoprotein A and Profilin 1) were elevated in paediatric HCM. Using supervised machine learning applied to training (n=137) and validation cohorts (n=61), this 7-biomarker panel differentiated HCM from healthy controls with an area under the curve of 1.0 in the training dataset (sensitivity 100% [95% confidence interval: 95–100]; specificity 100% [96–100]) and 0.82 in the validation dataset (sensitivity 75% [59–86]; specificity 88% [75–94]). Reduced circulating levels of 4 other peptides (Apolipoprotein L1-, Complement 5b-, Immunoglobulin Heavy Constant Epsilon- and Serum Amyloid A4-peptide) found in children with high SCD risk provided complete separation from the low and intermediate risk groups, and predicted mortality and adverse cardiovascular outcomes (hazard ratio 1.53 [1.2 –2.0], p = 0.001). ConclusionIn children, a 7-biomarker proteomics panel can distinguish HCM from controls with high sensitivity and specificity, and a second 4-biomarker panel identifies those at high risk of adverse outcomes, including sudden cardiac death.

INSTRUMENT(S): Q-Tof Ultima

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Cell, Blood Plasma

DISEASE(S): Cardiovascular System Disease

SUBMITTER: Gabriella Captur

LAB HEAD: Professor Kevin

PROVIDER: PXD045304 | Pride | 2024-07-03

REPOSITORIES: Pride

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Novel Multiplexed Plasma Biomarker Panel Has Diagnostic and Prognostic Potential in Children With Hypertrophic Cardiomyopathy.

Captur Gabriella G Doykov Ivan I Chung Sheng-Chia SC Field Ella E Barnes Annabelle A Zhang Enpei E Heenan Imogen I Norrish Gabrielle G Moon James C JC Elliott Perry M PM Heywood Wendy E WE Mills Kevin K Kaski Juan Pablo JP

Circulation. Genomic and precision medicine 20240607 3

<h4>Background</h4>Hypertrophic cardiomyopathy (HCM) is defined clinically by pathological left ventricular hypertrophy. We have previously developed a plasma proteomics biomarker panel that correlates with clinical markers of disease severity and sudden cardiac death risk in adult patients with HCM. The aim of this study was to investigate the utility of adult biomarkers and perform new discoveries in proteomics for childhood-onset HCM.<h4>Methods</h4>Fifty-nine protein biomarkers were identifi ...[more]

PMID: 38847081

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Project description:Rationale There is a need for new and better biomarkers for hypertrophic cardiomyopathy (HCM) which correlate more closely with disease progression as determined by clinical imaging and biohumoral information. We have used a combination of heart tissue and plasma proteomics to identify potential biomarkers for HCM and developed them into an exploratory targeted proteomic assay. Objective To identify informative staging biomarkers for HCM and develop them into a blood test. The test using 10 µl of plasma, was developed into a 10 min liquid chromatography-tandem/mass spectrometry (LC-MS/MS) assay to analyze multiple candidate biomarkers and evaluate their association with clinical phenotypes in patients with HCM. Methods and Results Myocardial tissue and plasma samples from patients with HCM and healthy volunteers (controls) were screened using a combined gel- and nano-LC quadrupole time of flight MS approach. Twenty-six potential biomarkers were identified from the proteomics screens and developed into a multiplexed targeted proteomic assay. Their association with clinical phenotypes was tested in plasma samples collected from 207 prospectively recruited participants: 110 patients with HCM (50.1 ± 15.0 years, 70% male; 48 [44%] with identified genetic mutations) and 97 controls (49.6 ± 13.4 years, 58% male), randomly split into training (80 HCM, 67 controls) and validation datasets (30 HCM, 30 controls). Six markers (Aldolase Fructose-Bisphosphate A, Complement C3, Glutathione S-Transferase Omega 1, Ras Suppressor Protein 1, Talin 1, and Thrombospondin 1) were significantly increased (P<0.006) in the plasma of HCM patients compared to controls in the training dataset. These markers correlated with left ventricular (LV) wall thickness, LV mass and % myocardial scar on cardiovascular magnetic resonance imaging. Using supervized machine learning (ML) this panel differentiated HCM from controls (area under the curve: 0.89 in the training dataset, sensitivity 96%, 95% confidence interval [CI] 77–93; specificity 87%, 95%CI 77–94; and 0.87 in the validation dataset, sensitivity 97%, 95%CI 83–100; specificity 77%, 95%CI 58–90). Four of the biomarkers as well as the composite ML score of the plasma proteome correlated with the presence of nonsustained ventricular tachycardia and the estimated 5-year risk of sudden cardiac death. Conclusion By developing a high-throughput, multiplex, and targeted proteomic plasma assay we identified 6 biomarkers that correlate with the presence of disease and with clinical risk score for sudden cardiac death.

Project description:Background: How prenatal smoke exposure affects DNA methylation leading to atopic disorders remains to be addressed. Epigenetic biomarkers informative of prenatal smoke exposure and atopic disorders are wanting. Since most children suffering from atopic dermatitis (AD) continue to develop asthma later in life, we explored whether prenatal smoke exposure e induces DNA methylation and searched for predictive epigenetic biomarkers for smoke related atopic disorders. Methods: Methylation differences associated with smoke exposure were screened by Illumina methylation panel for children from the Taiwan birth panel study cohort initially. Information about development of atopic dermatitis (AD) and risk factors were collected. Cord blood cotinine levels were measured to represent prenatal smoke exposure. CpG loci that demonstrated a statistically significant difference in methylation were validated by methylation-dependent fragment separation (MDFS). Differential methylation in three genes (TSLP, GSTT1, and CYB5R3) was identified through the screen and their functions were investigated. Results: Among these, only thymic stromal lymphopoietin (TSLP) gene displayed significant difference in promoter methylation percentage after being validated by MDFS (p=0.029). TSLP gene was further investigated in a larger sample of 92 children from the cohort. Methylation status of the TSLP 5′-CpG island (CGI) was found to be significantly associated with prenatal smoke exposure (OR=3.59, 95%CI=1.49-8.64; cotinine level 0.10 ng/ml, sensitivity= 77%; specificity = 61%) and with AD (OR=4.77, 95%CI=1.47-15.53). The degree of TSLP 5′CGI methylation inversely correlated with TSLP protein expression levels (per unit: β=－6.69 ng/ml; 95% CIs, －12.80~－0.59; p=0.032). Conclusions: The effect of prenatal tobacco smoke exposure on the risk for AD may be mediated through DNA methylation. Cord blood methylated TSLP 5′CGI may be a potential epigenetic biomarker for environmentally-related atopic disorders. The buffy coat and plasma samples were separated and stored at −80°C. DNA (100 ng-500 ng) was extracted from cord white blood cells. Microarrays have been performed to investigate fourteen samples, which were classified as two groups according to cotinine exposure dosage (7 versus 7 : high exposure verses low exposure).

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