Multiple biomarker panel to screen for severe aortic stenosis: results from the CASABLANCA study

Large-Scale Proteomics Identifies Novel Biomarkers and Circulating Risk Factors for Aortic Stenosis

BACKGROUND

Limited data exist regarding risk factors for aortic stenosis (AS). The plasma proteome is a promising phenotype for discovery of novel biomarkers and potentially causative mechanisms.

OBJECTIVES

The aim of this study was to discover novel biomarkers with potentially causal associations with AS.

METHODS

We measured 4,877 plasma proteins (SomaScan aptamer-affinity assay) among ARIC (Atherosclerosis Risk In Communities) study participants in mid-life (visit 3 [V3]; n = 11,430; age 60 ± 6 years) and in late-life (V5; n = 4,899; age 76 ± 5 years). We identified proteins cross-sectionally associated with aortic valve (AV) peak velocity (AVmax) and dimensionless index by echocardiography at V5 and with incident AV-related hospitalization after V3 with the use of multivariable linear and Cox proportional hazard regression. We assessed associations of candidate proteins with changes in AVmax over 6 years and with AV calcification with the use of cardiac computed tomography, replicated analysis in an independent sample, performed Mendelian randomization, and evaluated gene expression in explanted human AV tissue.

RESULTS

Fifty-two proteins cross-sectionally were associated with AVmax and dimensionless index at V5 and with risk of incident AV-related hospitalization after V3. Among 3,413 participants in the Cardiovascular Health Study, 6 of those proteins were significantly associated with adjudicated moderate or severe AS, including matrix metalloproteinase 12 (MMP12), complement C1q tumor necrosis factor-related protein 1 (C1QTNF1), and growth differentiation factor-15. MMP12 was also associated with greater increase in AVmax over 6 years, greater degree of AV calcification, and greater expression in calcific compared with normal or fibrotic AV tissue. C1QTNF1 had consistent potential causal effects on both AS and AVmax according to Mendelian randomization analysis.

CONCLUSIONS

These findings identify MMP12 as a potential novel circulating biomarker of AS risk and C1QTNF1 as a new putative target to prevent AS progression.

Plasma N-terminal pro-B-type natriuretic peptide in the detection of aortic valve stenosis

BACKGROUND

Systolic murmur suggestive of aortic valve origin is a common accidental finding, particularly in the elderly. Usually, it is due to aortic stenosis (AS) or aortic sclerosis (ASc). Currently, echocardiography is used to differentiate AS from ASc. Plasma N-terminal (NT)-prohormone BNP (NT-proBNP) is known to correlate with the severity of AS. We assessed whether NT-proBNP separates AS from ASc.

METHODS

The study population consisted of three groups: AS (n = 87, age 77 ± 7 years), ASc (n = 76, age 72 ± 10 years), and healthy controls (n = 101, age 55 ± 10 years). All subjects underwent transthoracic echocardiography and measurement of plasma NT-proBNP. Patients with diseases known to increase NT-proBNP were excluded.

RESULTS

The crude plasma NT-proBNP (median; IQR) in AS patients (413; 165-1055 ng/l) was significantly higher compared to ASc patients (96; 53-237 ng/l, p < 0.001) and healthy controls (50; 29-76 ng/l, p < 0.001). After adjusting for the confounding factors (age, coronary artery disease, renal function and diastolic blood pressure), plasma NT-proBNP remained significantly higher in AS patients as compared to ASc (p < 0.002) and controls (p < 0.0001). In the receiver-operating characteristic curve for NT-proBNP to identify AS from ASc and controls, the area under the curve was 0.878 with optimal cutoff of 115 ng/l. In addition, using 115 ng/l to separate AS from ASc yielded sensitivity of 0.885, and negative predictive value of 0.808.

CONCLUSIONS

NT-proBNP was sensitive to identify AS and useful to rule out AS in patients with systolic murmur in the left ventricular outflow tract provided the patient does not have coexisting disease known to impact NT-proBNP.

Pathophysiology, emerging techniques for the assessment and novel treatment of aortic stenosis

Our perspectives on aortic stenosis (AS) are changing. Evolving from the traditional thought of a passive degenerative disease, developing a greater understanding of the condition's mechanistic underpinning has shifted the paradigm to an active disease process. This advancement from the 'wear and tear' model is a result of the growing economic and health burden of AS, particularly within industrialised countries, prompting further research. The pathophysiology of calcific AS (CAS) is complex, yet can be characterised similarly to that of atherosclerosis. Progressive remodelling involves lipid-protein complexes, with lipoprotein(a) being of particular interest for diagnostics and potential future treatment options.There is an unmet clinical need for asymptomatic patient management; no pharmacotherapies are proven to slow progression and intervention timing varies. Novel approaches are developing to address this through: (1) screening with circulating biomarkers; (2) development of drugs to slow disease progression and (3) early valve intervention guided by medical imaging. Existing biomarkers (troponin and brain natriuretic peptide) are non-specific, but cost-effective predictors of ventricular dysfunction. In addition, their integration with cardiovascular MRI can provide accurate risk stratification, aiding aortic valve replacement decision making. Currently, invasive intervention is the only treatment for AS. In comparison, the development of lipoprotein(a) lowering therapies could provide an alternative; slowing progression of CAS, preventing left ventricular dysfunction and reducing reliance on surgical intervention.The landscape of AS management is rapidly evolving. This review outlines current understanding of the pathophysiology of AS, its management and future perspectives for the condition's assessment and treatment.

Models and Techniques to Study Aortic Valve Calcification in Vitro, ex Vivo and in Vivo. An Overview

Aortic valve stenosis secondary to aortic valve calcification is the most common valve disease in the Western world. Calcification is a result of pathological proliferation and osteogenic differentiation of resident valve interstitial cells. To develop non-surgical treatments, the molecular and cellular mechanisms of pathological calcification must be revealed. In the current overview, we present methods for evaluation of calcification in different ex vivo, in vitro and in vivo situations including imaging in patients. The latter include echocardiography, scanning with computed tomography and magnetic resonance imaging. Particular emphasis is on translational studies of calcific aortic valve stenosis with a special focus on cell culture using human primary cell cultures. Such models are widely used and suitable for screening of drugs against calcification. Animal models are presented, but there is no animal model that faithfully mimics human calcific aortic valve disease. A model of experimentally induced calcification in whole porcine aortic valve leaflets ex vivo is also included. Finally, miscellaneous methods and aspects of aortic valve calcification, such as, for instance, biomarkers are presented.

Biomarkers Associated with Mortality in Aortic Stenosis: A Systematic Review and Meta-Analysis

The optimal timing of aortic valve replacement (AVR) remains controversial. Several biomarkers reflect the underlying pathophysiological processes in aortic stenosis (AS) and may be of use as mortality predictors. The aim of this systematic review and meta-analysis is to evaluate the blood biomarkers utilised in AS and assess whether they associate with mortality. PubMed and Embase were searched for studies reporting baseline biomarker level and mortality outcomes in patients with AS. A total of 83 studies met the inclusion criteria and were systematically reviewed. Of these, 21 reporting brain natriuretic peptide (BNP), N-terminal pro B-type natriuretic peptide (NT-proBNP), Troponin and Galectin-3 were meta-analysed. Pooled analysis demonstrated that all-cause mortality was significantly associated with elevated baseline levels of BNP (HR 2.59; 95% CI 1.95–3.44; p < 0.00001), NT-proBNP (HR 1.73; 95% CI 1.45–2.06; p = 0.00001), Troponin (HR 1.65; 95% CI 1.31–2.07; p < 0.0001) and Galectin-3 (HR 1.82; 95% CI 1.27–2.61; p < 0.001) compared to lower baseline biomarker levels. Elevated levels of baseline BNP, NT-proBNP, Troponin and Galectin-3 were associated with increased all-cause mortality in a population of patients with AS. Therefore, a change in biomarker level could be considered to refine optimal timing of intervention. The results of this meta-analysis highlight the importance of biomarkers in risk stratification of AS, regardless of symptom status.

Optimizing Timing of Valve Intervention in Patients With Asymptomatic Severe Valvular Heart Disease

The management of valvular heart disease has changed dramatically over the past decade with advances in cardiac imaging, the use of novel biomarkers, and the development of transcatheter valve repair and replacement technology. International society guidelines have kept pace to provide recommendations for diagnosis, follow-up, and timing of intervention. The most challenging patient cohort for clinicians are patients with asymptomatic severe disease in whom the optimal timing of intervention can be ill-defined. It is a fine balance between the risks of early intervention on asymptomatic patients and improving patient outcomes by preventing long-term cardiac complications. The key in optimal patient management is gathering the necessary information on patient risk and combining that with the risk, efficacy, and durability of valve interventions to arrive at the appropriate timing for intervention. This group of patients will be the focus of this review as we delve into the natural history, recommended follow-up, and indications for intervention in patients with degenerative aortic and mitral valve disease.

Gaining Efficiency in Clinical Trials With Cardiac Biomarkers: JACC Review Topic of the Week

The momentum of cardiovascular drug development has slowed dramatically. Use of validated cardiac biomarkers in clinical trials could accelerate development of much-needed therapies, but biomarkers have been used less for cardiovascular drug development than in therapeutic areas such as oncology. Moreover, there are inconsistences in biomarker use in clinical trials, such as sample type, collection times, analytical methods, and storage for future research. With these needs in mind, participants in a Cardiac Safety Research Consortium Think Tank proposed the development of international guidance in this area, together with improved quality assurance and analytical methods, to determine what biomarkers can reliably show. Participants recommended the development of systematic methods for sample collection, and the archiving of samples in all cardiovascular clinical trials (including creation of a biobank or repository). The academic and regulatory communities also agreed to work together to ensure that published information is fully and clearly expressed.

Urea level is an independent predictor of mortality in patients with severe aortic valve stenosis

Introduction

Severe aortic stenosis (AS) is the most common valvular heart disease in the western world. Various factors are related to severe AS prognosis, including chronic kidney disease. The aim of this study was to evaluate the prognostic value of urea level in patients with severe AS.

Methods

We prospectively enrolled 142 patients (79.1±9.4 years, 88 women) with severe AS (mean valve area 0.67± 0.17 cm²). Clinical assessment, blood tests and echocardiography were performed at enrollment and follow up. The patient population was divided into low and high urea level groups, according to the median urea level at enrollment (72 patients, mean urea 35.5±6.2 mg/dL and 70 patients, mean urea 61.1±17.8 mg/dL, respectively). Hundred and twelve patients (79%) underwent aortic valve intervention. The primary endpoint was all-cause and cardiovascular mortality.

Outcomes

During follow-up of 37±19.5 months, 56 (37.1%) patients died, 39 due to cardiovascular causes. In univariate analysis, age, urea level, creatinine, New York Heart Association (NYHA) class and aortic valve intervention were associated with all-cause mortality. However, in multivariate analysis only aortic valve intervention and blood urea were independent predictors of all-cause mortality (HR 0.494; 95% CI 0.226–0.918, P = 0.026 and HR 1.015; 95% CI 1.003–1.029, P = 0.046 respectively). Urea level, NYHA class and age were also significant predictors of cardiovascular mortality. Whereas, in multivariate analysis, only urea level predicted cardiovascular mortality in these patients (HR 1.017; CI 1.003–1.031 P = 0.019).

Conclusions

Blood urea, a generally readily available and routinely determined marker of renal function, is an independent prognostic factor in patients with severe AS.