Blood-based protein profiling identifies serum protein c-KIT as a novel biomarker for hypertrophic cardiomyopathy

Protein Biomarkers of Adverse Clinical Features and Events in Sarcomeric Hypertrophic Cardiomyopathy

BACKGROUND

Hypertrophic cardiomyopathy (HCM) is a heterogeneous condition that can lead to atrial fibrillation, heart failure, and sudden cardiac death in many individuals but mild clinical impact in others. The mechanisms underlying this phenotypic heterogeneity are not well defined. The aim of this study was to use plasma proteomic profiling to help illuminate biomarkers that reflect or inform the heterogeneity observed in HCM.

METHODS

The Olink antibody-based proteomic platform was used to measure plasma proteins in patients with genotype positive (sarcomeric) HCM participating in the HCM Registry. We assessed associations between plasma protein levels with clinical features, cardiac magnetic resonance imaging metrics, and the development of atrial fibrillation.

RESULTS

We measured 275 proteins in 701 patients with sarcomeric HCM. There were associations between late gadolinium enhancement with proteins reflecting neurohormonal activation (NT-proBNP [N-terminal pro-B-type natriuretic peptide] and ACE2 [angiotensin-converting enzyme 2]). Metrics of left ventricular remodeling had novel associations with proteins involved in vascular development and homeostasis (vascular endothelial growth factor-D and TM [thrombomodulin]). Assessing clinical features, the European Society of Cardiology sudden cardiac death risk score was inversely associated with SCF (stem cell factor). Incident atrial fibrillation was associated with mediators of inflammation and fibrosis (MMP2 [matrix metalloproteinase 2] and SPON1 [spondin 1]).

CONCLUSIONS

Proteomic profiling of sarcomeric HCM identified biomarkers associated with adverse imaging and clinical phenotypes. These circulating proteins are part of both established pathways, including neurohormonal activation and fibrosis, and less familiar pathways, including endothelial function and inflammatory proteins less well characterized in HCM. These findings highlight the value of plasma profiling to identify biomarkers of risk and to gain further insights into the pathophysiology of HCM.

Preclinical Serological Signatures are Associated With Complicated Crohn's Disease Phenotype at Diagnosis

BACKGROUND

At diagnosis, up to one-third of patients with Crohn's disease (CD) have a complicated phenotype with stricturing (B2) or penetrating (B3) behavior or require early surgery. We evaluated protein biomarkers and antimicrobial antibodies in serum archived years before CD diagnosis to assess whether complicated diagnoses were associated with a specific serological signature.

METHODS

Prediagnosis serum was obtained from 201 patients with CD and 201 healthy controls. Samples were evaluated with a comprehensive panel of 1129 proteomic markers (SomaLogic) and antimicrobial antibodies. CD diagnosis and complications were defined by the International Classification of Diseases-Ninth Revision and Current Procedural Terminology codes. Cox regression models were utilized to assess the association between markers and the subsequent risk of being diagnosed with complicated CD. In addition, biological pathway and network analyses were performed.

RESULTS

Forty-seven CD subjects (24%) had a B2 (n = 36) or B3 (n = 9) phenotype or CD-related surgery (n = 2) at diagnosis. Subjects presenting with complicated CD at diagnosis had higher levels of antimicrobial antibodies six years before diagnosis as compared with those diagnosed with noncomplicated CD. Twenty-two protein biomarkers (reflecting inflammatory, fibrosis, and tissue protection markers) were found to be associated with complicated CD. Pathway analysis of the altered protein biomarkers identified higher activation of the innate immune system and complement or coagulation cascades up to six years before diagnosis in complicated CD.

CONCLUSIONS

Proteins and antimicrobial antibodies associated with dysregulated innate immunity, excessive adaptive response to microbial antigens, and fibrosis precede and predict a complicated phenotype at the time of diagnosis in CD patients.

Blood-based biomarkers for the prediction of hypertrophic cardiomyopathy prognosis: a systematic review and meta-analysis

AIMS

Hypertrophic cardiomyopathy (HCM) is the most prevalent monogenic heart disease. HCM is an important cause of sudden cardiac death and may also lead to outflow tract obstruction and heart failure. Disease severity is highly variable and risk stratification remains limited. Therefore, we aimed to review current knowledge of prognostic blood-based biomarkers in HCM.

METHODS AND RESULTS

A systematic literature search was performed on PubMed, Embase, and the Cochrane library to identify studies assessing plasma or serum biomarkers for outcomes involving malignant ventricular arrhythmia, outflow tract obstruction, and heart failure. Risk of bias was assessed using the QUIPS tool. Meta-analyses were performed using the random effects method. A total of 26 unique cohort studies assessing 42 biomarkers were identified. Overall risk of bias was moderate. Thirty-two biomarkers were significantly associated to an HCM outcome in at least one study (nine biomarkers in at least two studies). In pooled analyses, cardiovascular mortality was predicted by N-terminal prohormone of brain natriuretic peptide (hazard ratio [HR] 5.38 per log[pg/mL], 95% confidence interval [CI] 2.07-14.03, P < 0.001, I2  = 0%) and high-sensitivity C-reactive protein (HR 1.30 per μg/mL, 95% CI 1.00-1.68, P = 0.05, I2  = 78%), all-cause mortality by low-density lipoprotein cholesterol (HR 0.63 per μmol/mL, 95% CI 0.49-0.80, P < 0.001, I2  = 0%), and a combined congestive heart failure, malignant ventricular arrhythmia, and stroke outcome by high-sensitivity cardiac troponin T (pooled HR 4.19 for ≥0.014 ng/mL, 95% CI 2.22-7.88, P < 0.001, I2  = 0%). Quality of evidence was low-moderate.

CONCLUSIONS

Several blood-based biomarkers were identified as predictors of HCM outcomes. Additional studies are required to validate their prognostic utility within current risk stratification models.

Dihydromyricetin ameliorates osteogenic differentiation of human aortic valve interstitial cells by targeting c-KIT/interleukin-6 signaling pathway

Aims: Calcific aortic valve disease (CAVD) is a chronic cardiovascular disease with high morbidity that lacks effective pharmacotherapeutics. As a natural flavonoid extracted from Ampelopsis grossedentata, dihydromyricetin (DHM) has been shown to be effective in protecting against atherosclerosis; yet, the therapeutic role of DHM in CAVD remains poorly understood. Herein, we aimed to clarify the therapeutic implications of DHM in CAVD and the underlying molecular mechanisms in human valvular interstitial cells (hVICs).

Methods and Results: The protein levels of two known osteogenesis-specific genes (alkaline phosphatase, ALP; runt-related transcription factor 2, Runx2) and calcified nodule formation in hVICs were detected by Western blot and Alizarin Red staining, respectively. The results showed that DHM markedly ameliorated osteogenic induction medium (OM)–induced osteogenic differentiation of hVICs, as evidenced by downregulation of ALP and Runx2 expression and decreased calcium deposition. The SwissTargetPrediction database was used to identify the potential AVC-associated direct protein target of DHM. Protein–protein interaction (PPI) analysis revealed that c-KIT, a tyrosine-protein kinase, can act as a credible protein target of DHM, as evidenced by molecular docking. Mechanistically, DHM-mediated inhibition of c-KIT phosphorylation drove interleukin-6 (IL-6) downregulation in CAVD, thereby ameliorating OM-induced osteogenic differentiation of hVICs and aortic valve calcification progression.

Conclusion: DHM ameliorates osteogenic differentiation of hVICs by blocking the phosphorylation of c-KIT, thus reducing IL-6 expression in CAVD. DHM could be a viable therapeutic supplement to impede CAVD.

Comprehensive Proteomics Profiling Identifies Patients With Late Gadolinium Enhancement on Cardiac Magnetic Resonance Imaging in the Hypertrophic Cardiomyopathy Population

Introduction

In hypertrophic cardiomyopathy (HCM), late gadolinium enhancement (LGE) on cardiac magnetic resonance imaging (CMR) represents myocardial fibrosis and is associated with sudden cardiac death. However, CMR requires particular expertise and is expensive and time-consuming. Therefore, it is important to specify patients with a high pre-test probability of having LGE as the utility of CMR is higher in such cases. The objective was to determine whether plasma proteomics profiling can distinguish patients with and without LGE on CMR in the HCM population.

Materials and Methods

We performed a multicenter case-control (LGE vs. no LGE) study of 147 patients with HCM. We performed plasma proteomics profiling of 4,979 proteins. Using the 17 most discriminant proteins, we performed logistic regression analysis with elastic net regularization to develop a discrimination model with data from one institution (the training set; n = 111) and tested the discriminative ability in independent samples from the other institution (the test set; n = 36). We calculated the area under the receiver-operating-characteristic curve (AUC), sensitivity, and specificity.

Results

Overall, 82 of the 147 patients (56%) had LGE on CMR. The AUC of the 17-protein model was 0.83 (95% confidence interval [CI], 0.75–0.90) in the training set and 0.71 in the independent test set for validation (95% CI, 0.54–0.88). The sensitivity of the training model was 0.72 (95% CI, 0.61–0.83) and the specificity was 0.78 (95% CI, 0.66–0.90). The sensitivity was 0.71 (95% CI, 0.49–0.92) and the specificity was 0.74 (95% CI, 0.54–0.93) in the test set. Based on the discrimination model derived from the training set, patients in the test set who had high probability of having LGE had a significantly higher odds of having LGE compared to those who had low probability (odds ratio 29.6; 95% CI, 1.6–948.5; p = 0.03).

Conclusions

In this multi-center case-control study of patients with HCM, comprehensive proteomics profiling of 4,979 proteins demonstrated a high discriminative ability to distinguish patients with and without LGE. By identifying patients with a high pretest probability of having LGE, the present study serves as the first step to establishing a panel of circulating protein biomarkers to better inform clinical decisions regarding CMR utilization.

Mass-Spectrometry-Based Functional Proteomic and Phosphoproteomic Technologies and Their Application for Analyzing Ex Vivo and In Vitro Models of Hypertrophic Cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is an autosomal dominant disease thought to be principally caused by mutations in sarcomeric proteins. Despite extensive genetic analysis, there are no comprehensive molecular frameworks for how single mutations in contractile proteins result in the diverse assortment of cellular, phenotypic, and pathobiological cascades seen in HCM. Molecular profiling and system biology approaches are powerful tools for elucidating, quantifying, and interpreting dynamic signaling pathways and differential macromolecule expression profiles for a wide range of sample types, including cardiomyopathy. Cutting-edge approaches combine high-performance analytical instrumentation (e.g., mass spectrometry) with computational methods (e.g., bioinformatics) to study the comparative activity of biochemical pathways based on relative abundances of functionally linked proteins of interest. Cardiac research is poised to benefit enormously from the application of this toolkit to cardiac tissue models, which recapitulate key aspects of pathogenesis. In this review, we evaluate state-of-the-art mass-spectrometry-based proteomic and phosphoproteomic technologies and their application to in vitro and ex vivo models of HCM for global mapping of macromolecular alterations driving disease progression, emphasizing their potential for defining the components of basic biological systems, the fundamental mechanistic basis of HCM pathogenesis, and treating the ensuing varied clinical outcomes seen among affected patient cohorts.

Intestinal Organoids in Colitis Research: Focusing on Variability and Cryopreservation

In recent years, stem cell-derived organoids have become a cell culture standard that is widely used for studying various scientific issues that were previously investigated through animal experiments and using common tumor cell lines. After their initial hype, concerns regarding their standardization have been raised. Here, we aim to provide some insights into our experience in standardizing murine colonic epithelial organoids, which we use as a replacement method for research on inflammatory bowel disease. Considering good scientific practice, we examined various factors that might challenge the design and outcome of experiments using these organoids. First, to analyze the impact of antibiotics/antimycotics, we performed kinetic experiments using ZellShield® and measured the gene expression levels of the tight junction markers Ocln, Zo-1, and Cldn4, the proliferation marker Ki67, and the proinflammatory cytokine Tnfα. Because we found no differences between cultivations with and without ZellShield®, we then performed infection experiments using the probiotic Escherichia coli Nissle 1917 as an already established model setup to analyze the impact of technical, interexperimental, and biologic replicates. We demonstrate that interexperimental differences pose the greatest challenge for reproducibility and explain our strategies for addressing these differences. Additionally, we conducted infection experiments using freshly isolated and cryopreserved/thawed organoids and found that cryopreservation influenced the experimental outcome during early passages. Formerly cryopreserved colonoids exhibited a premature appearance and a higher proinflammatory response to bacterial stimulation. Therefore, we recommend analyzing the growth characteristics and reliability of cryopreserved organoids before to their use in experiments together with conducting several independent experiments under standardized conditions. Taken together, our findings demonstrate that organoid culture, if standardized, constitutes a good tool for reducing the need for animal experiments and might further improve our understanding of, for example, the role of epithelial cells in inflammatory bowel disease development.

Towards Building a Quantitative Proteomics Toolbox in Precision Medicine: A Mini-Review

Precision medicine as a framework for disease diagnosis, treatment, and prevention at the molecular level has entered clinical practice. From the start, genetics has been an indispensable tool to understand and stratify the biology of chronic and complex diseases in precision medicine. However, with the advances in biomedical and omics technologies, quantitative proteomics is emerging as a powerful technology complementing genetics. Quantitative proteomics provide insight about the dynamic behaviour of proteins as they represent intermediate phenotypes. They provide direct biological insights into physiological patterns, while genetics accounting for baseline characteristics. Additionally, it opens a wide range of applications in clinical diagnostics, treatment stratification, and drug discovery. In this mini-review, we discuss the current status of quantitative proteomics in precision medicine including the available technologies and common methods to analyze quantitative proteomics data. Furthermore, we highlight the current challenges to put quantitative proteomics into clinical settings and provide a perspective to integrate proteomics data with genomics data for future applications in precision medicine.