Biomarkers for cardiovascular disease: challenges and future directions

Enhanced CRISPR/Cas-Based Immunoassay through Magnetic Proximity Extension and Detection

Clustered regularly interspaced short palindromic repeats (CRISPR)/Cas-associated systems have recently emerged as a focal point for developing next-generation molecular diagnosis, particularly for nucleic acid detection. However, the detection of proteins is equally critical across diverse applications in biology, medicine, and the food industry, especially for diagnosing and prognosing diseases like cancer, Alzheimer's and cardiovascular conditions. Despite recent efforts to adapt CRISPR/Cas systems for protein detection with immunoassays, these methods typically achieved sensitivity only in the femtomolar to picomolar range, underscoring the need for enhanced detection capabilities. To address this, we developed CRISPR-AMPED, an innovative CRISPR/Cas-based immunoassay enhanced by magnetic proximity extension and detection. This approach combines proximity extension assay (PEA) with magnetic beads that converts protein into DNA barcodes for quantification with effective washing steps to minimize non-specific binding and hybridization, therefore reducing background noise and increasing detection sensitivity. The resulting DNA barcodes are then detected through isothermal nucleic acid amplification testing (NAAT) using recombinase polymerase amplification (RPA) coupled with the CRISPR/Cas12a system, replacing the traditional PCR. This integration eliminates the need for thermocycling and bulky equipment, reduces amplification time, and provides simultaneous target and signal amplification, thereby significantly boosting detection sensitivity. CRISPR-AMPED achieves attomolar level sensitivity, surpassing ELISA by over three orders of magnitude and outperforming existing CRISPR/Cas-based detection systems. Additionally, our smartphone-based detection device demonstrates potential for point-of-care applications, and the digital format extends dynamic range and enhances quantitation precision. We believe CRISPR-AMPED represents a significant advancement in the field of protein detection.

Evaluating Biomarkers as Tools for Early Detection and Prognosis of Heart Failure: A Comprehensive Review

There is a high prevalence of heart failure (HF) worldwide, which has significant consequences for healthcare costs, patient death and quality of life. Therefore, there has been much focus on finding and using biomarkers for early diagnosis, prognostication and therapy of HF. This overview of the research presents a thorough examination of the current state of HF biomarkers and their many uses. Their function in diagnosing HF, gauging its severity and monitoring its response to therapy are all discussed. Particularly promising in HF diagnosis and risk stratification are the cardiac-specific biomarkers, B-type natriuretic peptide and N-terminal pro-B-type natriuretic peptide. Markers of oxidative stress, extracellular matrix, renal function, inflammation and cardiac peptides have shown promise in evaluating HF severity and prognosis. MicroRNAs and insulin-like growth factor are two emerging biomarkers that have shown potential in helping with HF diagnosis and prognosis.

Epigenetic Regulation and its Effects on Aging and Cardiovascular Disease

Cardiovascular disease (CVD), specifically coronary atherosclerosis, is regulated by an interplay between genetic and lifestyle factors. Most recently, a factor getting much attention is the role epigenetics play in atherosclerosis; particularly the development of coronary artery disease. Furthermore, it is important to understand the intricate interaction between the environment and each individual genetic material and how this interaction affects gene expression and consequently influences the development of atherosclerosis. Our main goal is to discuss epigenetic regulations; particularly, the factors contributing to coronary atherosclerosis and their role in aging and longevity. We reviewed the current literature and provided a simplified yet structured and reasonable appraisal of this topic. This role has also been recently linked to longevity and aging. Epigenetic regulations (modifications) whether through histone modifications or DNA or RNA methylation have been shown to be regulated by environmental factors such as social stress, smoking, chemical contaminants, and diet. These sensitive interactions are further aggravated by racial health disparities that ultimately impact cardiovascular disease outcomes through epigenetic interactions. Certainly, limiting our exposure to such causative events at younger ages seems our "golden opportunity" to tackle the incidence of coronary atherosclerosis and probably the answer to longevity.

Microfluidic integrated capacitive biosensor for C-reactive protein label-free and real-time detection

A microfluidic chip has been integrated with a capacitive biosensor based on mass-producible three-dimensional (3D) interdigital electrode arrays. To achieve the monitoring of biosensor preparation and cardiac- and periodontitis-related biomarkers, all the processes were detected in a continuously on-site way. Fabrication steps for the microfluidic chip-bonded 3D interdigital capacitor biosensor include gold thiol modification, the activation of EDC/sulfo-NHS, and the bioconjugation of antibodies. Fluorescent characterization and X-ray photoelectron spectroscopy analysis were applied to assess the successful immobilization of the C-reactive protein (CRP) antibody. The experimental results indicate the good specificity and high sensitivity of the microfluidic integrated 3D capacitive biosensor. The limit of detection of the 3D capacitive biosensor for CRP label-free detection was about 1 pg mL^-1. This 3D capacitive biosensor with integrated microfluidics is mass-producible and has achieved the on-site continuous detection of cardiac- and periodontitis-related biomarkers with high performance.

It's in Our Blood: A Glimpse of Personalized Medicine

Recent advances in protein profiling technology has facilitated simultaneous measurement of thousands of proteins in large population studies, exposing the depth and complexity of the plasma and serum proteomes. This revealed that proteins in circulation were organized into regulatory modules under genetic control and closely associated with current and future common diseases. Unlike networks in solid tissues, serum protein networks comprise members synthesized across different tissues of the body. Genetic analysis reveals that this cross-tissue regulation of the serum proteome participates in systemic homeostasis and mirrors the global disease state of individuals. Here, we discuss how application of this information in routine clinical evaluations may transform the future practice of medicine.

Diagnostic value of plasma tryptophan and symmetric dimethylarginine levels for acute kidney injury among tacrolimus-treated kidney transplant patients by targeted metabolomics analysis

Few literatures have evaluated the exact role of metabolomics in the identification process of potential biomarkers for acute kidney injury among the patients receiving renal transplantation. On top of this, the success of metabolomics in biomarker translation seems to lie in the robust quantitative method. As such, a single-center retrospective observational study was conducted enrolling 42 patients underwent renal transplantation with/without acute kidney injury, as well as 24 healthy volunteers, in Shanghai Changzheng Hospital. Plasma amino acid metabolic patterns for the participants were investigated by targeted UHPLC-MS/MS metabolic profiling. The most significant changes of the explored metabolites were related to the disturbance of tryptophan metabolism and arginine metabolism. Abnormal circulating tryptophan and symmetric dimethylarginine were identified to be potential biomarkers of acute kidney injury, combination of which showed a higher area under receiver-operator curve value (AUC = 0.901), improved sensitivity (0.889) and specificity (0.831) compared with creatinine only. Overall, these results revealed that targeted metabolomics analysis would be a potent and promising strategy for identification and pre-validation of biomarkers of acute kidney injury in renal transplantation patients.

Relation of multi-marker panel to incident chronic kidney disease and rapid kidney function decline in African Americans: the Jackson Heart Study

Background

Few investigations have evaluated the incremental usefulness of multiple biomarkers representing varying physiological pathways for predicting risk of renal outcomes in African Americans.

Design, setting, participants, and measurements

We related a multi-marker panel to incident chronic kidney disease (CKD) and rapid kidney function decline (RKFD) in 2813 Jackson Heart Study participants without prevalent CKD at exam 1 (2000–2004) and with complete assays at exam 1 for 9 biomarkers: adiponectin, aldosterone, B-natriuretic peptide [BNP], cortisol, high sensitivity C-reactive protein (hsCRP), endothelin, homocysteine, plasma renin activity and mass. Incident CKD was defined as estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m² at exam 3 while RKFD was defined as eGFR ≥30% loss between exams 1 and 3 (8.2 median years). We employed multiple logistic regression model to describe association between the panel and incident CKD and RKFD and used backward elimination strategy to estimate the most parsimonious biomarker model while controlling for conventional risk factors.

Results

The multi-marker panel predicted the risk for both incident CKD (odds ratios [OR], 2.72; 95% confidence intervals [CI], 1.63, 4.56; P = 0.001) and RKFD (2.61; 95% CI, 1.67, 4.08; P < 0.001). Per standard deviation increase in log biomarker concentrations were significantly (multivariable adjusted odds ratios, [95% confidence interval], p-value) associated with incident CKD: plasma adiponectin (1.24 [1.07, 1.44], p = 0.005) and leptin (1.3 [1.06, 1.61], p = 0.011), and with RKFD: plasma adiponectin (1.22 [1.06, 1.40], p = 0.006); hsCRP (1.17 [1.01, 1.36], p = 0.031) and aldosterone (0.85 [0.74, 0.96], p = 0.012). Moderate levels (3rd quartile) of aldosterone were inversely associated with incident CKD (0.54 [0.35, 0.82], p = 0.004) while leptin was associated with RKFD (1.64 [1.10, 2.44], p = 0.015). Biomarkers improved CKD risk prediction (P = 0.003) but not RKFD risk prediction (P = 0.10).

Conclusion

In this community-based sample of African Americans, a multi-marker panel added only moderate predictive improvement compared to conventional risk factors.

Electronic supplementary material

The online version of this article (10.1186/s12882-018-1026-y) contains supplementary material, which is available to authorized users.

Pentraxin 3 and atherosclerosis among type 2 diabetic patients

Type 2 diabetes is contemporarily a major social and epidemiological problem and among others is a strong risk factor for cardiovascular diseases. Pentraxin 3, a potential early biomarker of atherosclerosis, is an acute-phase reactant produced by the peripheral tissues where the inflammation takes place. In this study we examined a group of patients with type 2 diabetes with and without cardiovascular complications compared to persons with normal glucose tolerance (patients with cardiovascular complications and healthy volunteers). Plasma pentraxin 3 concentration as well as some basic biochemical blood analysis were performed. Moreover, transcranial and carotid Doppler ultrasound examination as well as transthoracic echocardiography were performed. It turned out that there was an association of plasma pentraxin 3 concentration and carotid atherosclerosis found in the control group of patients with cardiovascular complications but with normal glucose tolerance. In the group of patients with type 2 diabetes and cardiovascular complications we have found an association of plasma pentraxin 3 concentration with diastolic left ventricular dysfunction. Additionally, in the group of patients with type 2 diabetes without cardiovascular disease plasma pentraxin 3 concentration was associated with elevated urinary albumin creatinine ratio. Further studies, on a larger group of patients, are required to confirm these observations.

The Longer, the Better? An Empirical Study of the Extent and Mechanisms of Attenuating Biomarker Associations in Cardiovascular Patient Cohorts

BACKGROUND

Identifying novel risk markers in cardiovascular patients remains a research priority. Longer follow-up generally is considered favorable in such studies, but associations of interest may become attenuated with increasing follow-up. This issue has not been adequately addressed in the context of patient cohorts. The current study analyzed the extent and mechanisms of attenuating associations in a cardiovascular patient cohort.

METHODS

The associations of numerous biomarkers with all-cause mortality were estimated by multiple Cox regression in the Langzeiterfolge der KARdiOLogischen Anschlussheilbehandlung (KAROLA) prospective cohort study of 1204 patients who had participated in an inpatient rehabilitation program after an acute coronary syndrome (ACS) or coronary bypass operation. Hazard ratios were estimated based on the entire follow-up period (13 years), and after truncation at previous follow-up times (3, 4.5, 6, 8, 10 years).

RESULTS

For the majority of markers, a clear and sometimes very pronounced attenuation of the hazard ratios could be observed with increasing follow-up duration. Differential attrition generally was not a sufficient explanation for this phenomenon, whereas further analyses suggested a role for reverse causality for some of the markers. Power analyses showed that the relationship of follow-up duration and statistical power can be counterintuitive in the presence of realistic amounts of attenuation.

CONCLUSIONS

The attenuation of estimates of association in patient cohorts is a much more substantial and complex issue than currently appreciated. This has important implications for the design and interpretation of prognostic, as well as etiologic, studies which may be particularly relevant in the case of patient cohorts defined by an initial acute event.

Platelet extracellular vesicles as biomarkers for arterial thrombosis

Arterial thrombosis is a major and global cause of human death and disability. Considering the socioeconomic costs of arterial thrombosis, identification of biomarkers to predict and detect arterial thrombosis at an early stage is an important public health goal. Platelet extracellular vesicles (PEV) are a new candidate biomarker of arterial thrombosis. PEV can be measured in biorepositories, thereby offering the possibility to validate PEV in multicenter clinical trials. PEV analysis has been hitherto hampered by lack of standardized methodology, but substantial technological improvements of PEV detection techniques have been achieved recently. However, before PEV emerge from research tools to clinical applications, a number of issues should be clarified. To facilitate validation of PEV as biomarkers of thrombosis, we discuss (i) whether PEV are useful as biomarkers of thrombosis, (ii) why previous conclusions on PEV concentrations, composition and functions require re-evaluation, and (iii) which questions have to be answered before PEV become clinically useful.

Reassessing lipid metabolism and its potentialities in the prediction of cardiovascular risk

There are numerous particles, enzymes, and mechanisms in the lipid metabolism that are involved in the genesis of cardiovascular disease (CVD). Given its prevalence in populations and its impact on mortality, it is relevant to review the lipid metabolism as it may potentially provide subsidies to better prediction. This article reviews the importance of traditional cardiovascular risk factors and comments on the potential of novel lipid biomarkers involved in the physiopathology of CVD. The Framingham cohorts proved the role of traditional risk factors (physical inactivity, smoking, blood pressure, total cholesterol, LDL-C, HDL-C, plasma glucose) in the prediction of cardiovascular events. However, a significant number of individuals that suffer from a cardiovascular event has few or none of these factors. Such finding indicates the need for new biomarkers able to identify plaques that are more susceptible to rupture. Some of bloodstream biomarkers related to lipid metabolism are modified LDL particles, apolipoprotein AI (apo AI), apolipoprotein B, lipoprotein (a) [Lp (a)], cholesteryl ester transfer protein (CETP), subtypes of LDL and HDL particles, and lipoprotein-associated phospholipase A2 (Lp-PLA2). These factors participate in the atherosclerotic process, and are abnormal in individuals at high risk, or in those who suffered from a cardiovascular event. Lp (a) determination is already employed in clinical practice and should be included as a reference parameter for CVD monitoring. Furthermore, there are expectations for wider use of apo B, non-HDL cholesterol and total cholesterol / HDL-C determination to improve cardiovascular risk assessment.

Polymorphism in microRNA-196a2 contributes to the risk of cardiovascular disease in type 2 diabetes patients

AIMS

To investigate the effect of the microRNA-196a2 gene polymorphism (rs11614913) on risk of cardiovascular disease in type 2 diabetes patients.

METHODS

We examined 920 patients with diabetes and 834 healthy controls. All subjects were genotyped for the miRNA-196a2 SNP by polymerase chain reaction (PCR) and restriction analysis.

RESULTS

The genotype distribution among controls and patients was in Hardy-Weinberg equilibrium (p=0.227 and 0.308, respectively). The frequency of the T allele was lower in patients than in controls (p=0.044). The odds ratio 0.66 (95% CI 0.54-0.79) suggests an association of the T allele with decreased risk of T2DM. For the main purpose of the study, T2DM patients were stratified into patients with CVD and those without it. The T allele and TT genotype were significantly more frequent in patients with CVD compared to those without CVD (p=0.013, p<0.001, respectively). The odds ratio for the T allele in the CVD+subgroup vs. CVD- was 1.76 (1.35-2.30), p<0.0001, mostly due to the overrepresentation of TT homozygotes. The highest risk of development of CVD was observed in the additive model for TT homozygotes (OR 3.33, 95% CI 2.05-5.42, p<0.0001).

CONCLUSION

Our findings suggest that miRNA-196a2 T/C polymorphism (rs11614913) is associated with an increased risk of CVD in type 2 diabetes patients. This provides further insights on pathogenesis of cardiovascular disease in type 2 diabetes patients.

Hard, harder, hardest: principal stratification, statistical identifiability, and the inherent difficulty of finding surrogate endpoints

In many areas of clinical investigation there is great interest in identifying and validating surrogate endpoints, biomarkers that can be measured a relatively short time after a treatment has been administered and that can reliably predict the effect of treatment on the clinical outcome of interest. However, despite dramatic advances in the ability to measure biomarkers, the recent history of clinical research is littered with failed surrogates. In this paper, we present a statistical perspective on why identifying surrogate endpoints is so difficult. We view the problem from the framework of causal inference, with a particular focus on the technique of principal stratification (PS), an approach which is appealing because the resulting estimands are not biased by unmeasured confounding. In many settings, PS estimands are not statistically identifiable and their degree of non-identifiability can be thought of as representing the statistical difficulty of assessing the surrogate value of a biomarker. In this work, we examine the identifiability issue and present key simplifying assumptions and enhanced study designs that enable the partial or full identification of PS estimands. We also present example situations where these assumptions and designs may or may not be feasible, providing insight into the problem characteristics which make the statistical evaluation of surrogate endpoints so challenging.

Towards the identification of blood biomarkers for acute stroke in humans: a comprehensive systematic review

AIMS

Identification of biomarkers for stroke will aid our understanding of its aetiology, provide diagnostic and prognostic indicators for patient selection and stratification, and play a significant role in developing personalized medicine. We undertook the largest systematic review conducted to date in an attempt to characterize diagnostic and prognostic biomarkers in acute ischaemic and haemorrhagic stroke and those likely to predict complications following thrombolysis.

METHODS

A comprehensive literature search was carried out to identify diagnostic and prognostic stroke blood biomarkers. Mean differences (MDs) and 95% confidence intervals (CIs) were calculated for each biomarker.

RESULTS

We identified a total of 141 relevant studies, interrogating 136 different biomarkers. Three biomarkers (C-reactive protein, P-selectin and homocysteine) significantly differentiated between ischaemic stroke and healthy control subjects. Furthermore, glial fibrillary acidic protein levels were significantly different between haemorrhagic stroke and ischaemic stroke patients (MD 224.58 ng l⁻¹; 95% CI 25.84, 423.32; P= 0.03), high levels of admission glucose were a strong predictor of poor prognosis after ischaemic stroke and symptomatic intracerebral haemorrhage post-thrombolysis, glutamate was found to be an indicator of progressive (unstable) stroke (MD 172.65 µmol l⁻¹, 95% CI 130.54, 214.75; P= 0.00001), D-dimer predicted in-hospital death (MD 0.67 µg ml⁻¹, 95% CI 0.35, 1.00; P= 0.0001), and high fibrinogen levels were associated with poor outcome at 3 months (MD 47.90 mg l⁻¹, 95% CI 14.88, 80.93; P= 0.004) following ischaemic stroke.

CONCLUSIONS

Few biomarkers currently investigated have meaningful clinical value. Admission glucose may be a strong marker of poor prognosis following acute thrombolytic treatment. However, molecules released in the bloodstream before, during or after stroke may have potential to be translated into sensitive blood-based tests.

Polymorphisms of miRNAs genes are associated with the risk and prognosis of coronary artery disease

BACKGROUND

MicroRNAs (miRNAs) are small, single-stranded, non-protein-coding RNAs of about 22 nucleotides. miRNA molecules have been identified that plays key roles in a broad range of physiologic and pathologic processes. Polymorphisms in the corresponding sequence space are likely to make a significant contribution to phenotypic variation.

METHODS AND RESULTS

To assess the variations of rs11614913 T → C in hsa-mir-196a2 and rs3746444 A → G in hsa-mir-499 in the complex etiology of coronary artery disease (CAD), 956 CAD patients diagnosed by coronary arterial angiography and 620 controls were enrolled. Among the patients, 785 (785/956) had complete follow-ups for 42 months. The variant genotypes CC/CT of hsa-mir-196a2 rs11614913 T → C were not associated with a significantly increased risk of CAD (adjusted OR = 1.02, 95% CI = 0.76-1.38), compared with wide genotype TT, but CC and CC/CT genotypes were associated with 34 and 35% increased risks of serious prognosis of CAD (adjusted HR = 1.34, 95% CI = 1.02-1.75 for CC; adjusted HR = 1.35, 95% CI = 1.03-1.75 for CC/CT). In the variant of hsa-mir-499 rs3746444A → G, GG was associated with the 223% increased risk of CAD (adjusted OR = 3.23, 95% CI = 1.56-6.67). Cox regression analysis showed that age, smoking status, numbers of pathological changes in coronary arteries, rs11614913 T → C, and diabetes mellitus were associated with serious prognosis of CAD.

CONCLUSION

Our findings strongly implicate the functional miRNAs polymorphisms of hsa-mir-196a2 and hsa-mir-499 genes may modulate the occurrence or prognosis in Chinese CAD.

Biomarkers and cardiovascular risk assessment for primary prevention: an update

BACKGROUND

Interest in cardiovascular biomarkers in primary prevention has increased dramatically in the past decade. This increase has been fueled by an improved understanding of cardiovascular pathophysiology, as well as novel technologies for biomarker identification.

CONTENT

In this review we provide a brief overview of recent concepts in the evaluation of screening biomarkers, because biomarkers may behave differently when used for screening as opposed to diagnosis or disease staging. The following specific biomarker examples are then discussed, with a focus on data from primary prevention studies: high-sensitivity C-reactive protein, B-type natriuretic peptide, lipoprotein-associated phospholipase A2, and high-sensitivity troponin T. The article concludes by addressing novel platforms for biomarker discovery, reviewing recent examples from the field of metabolomics.

SUMMARY

An ongoing challenge is to develop screening strategies that can identify individuals at risk for cardiovascular events well before symptoms appear. For this purpose, the measurement of soluble biomarkers could be an important adjunct to traditional cardiovascular risk assessment. Recent studies highlight both the strengths and limitations of "novel" circulating biomarkers, and suggest that substantial work is still needed to identify biomarkers that are sufficiently accurate and cost-effective for routine use in primary prevention.

Artificial antibodies for troponin T by its imprinting on the surface of multiwalled carbon nanotubes: its use as sensory surfaces

A novel artificial antibody for troponin T (TnT) was synthesized by molecular imprint (MI) on the surface of multiwalled carbon nanotubes (MWCNT). This was done by attaching TnT to the MWCNT surface, and filling the vacant spaces by polymerizing under mild conditions acrylamide (monomer) in N,N'-methylenebisacrylamide (cross-linker) and ammonium persulphate (initiator). After removing the template, the obtained biomaterial was able to rebind TnT and discriminate it among other interfering species. Stereochemical recognition of TnT was confirmed by the non-rebinding ability displayed by non-imprinted (NI) materials, obtained by imprinting without a template. SEM and FTIR analysis confirmed the surface modification of the MWCNT. The ability of this biomaterial to rebind TnT was confirmed by including it as electroactive compound in a PVC/plasticizer mixture coating a wire of silver, gold or titanium. Anionic slopes of 50 mV decade(-1) were obtained for the gold wire coated with MI-based membranes dipped in HEPES buffer of pH 7. The limit of detection was 0.16 μg mL(-1). Neither the NI-MWCNT nor the MWCNT showed the ability to recognize the template. Good selectivity was observed against creatinine, sucrose, fructose, myoglobin, sodium glutamate, thiamine and urea. The sensor was tested successfully on serum samples. It is expected that this work opens new horizons on the design of new artificial antibodies for complex protein structures.

Genetic and environmental regulation of inflammatory CVD biomarkers Lp-PLA2 and IgM anti-PC

OBJECTIVE

We set out to investigate the relative contribution of genetic and environmental effect on two inflammatory CVD biomarkers; lipoprotein-associated phospholipase A(2) (Lp-PLA(2)) and anti-phosphorylcholine IgM (anti-PC). Their relationships and possible co-regulation with other established CVD biomarkers are also examined.

METHODS

Lp-PLA(2) activity (N=1600) and anti-PC (N=2036) levels were measured in elderly Swedish twins. Correlation analyses and heritability estimation were conducted by structural equation modeling.

RESULTS

We attribute 0.37 of the variance of Lp-PLA(2) and 0.40 of anti-PC variance to genetic variance. In addition, a bivariate heritability of 0.33, 0.35 and 0.36 could be detected for levels of Lp-PLA(2) together with ApoB, total cholesterol and LDL, respectively. Anti-PC was only weakly related to other biomarkers of CVD, which may suggest a more independent role of anti-PC as a biomarker.

CONCLUSIONS

In this large sample, Lp-PLA(2) activity has lower heritability and higher environmental regulation than previously reported. Anti-PC levels are partly influenced by dominance genetics and appear to be regulated independently of more established CVD biomarkers.

Biomarkers and their consequences for the biomedical profession: a social science perspective

Although biomarkers are not altogether new, they are gaining a new life in our postgenomic present. This article takes this as a good reason to explore biomarkers in depth and to speculate about the consequences that biomarkers might engender in clinical practices. First, the article ventures into an endeavor of ordering the dynamic field of biomarkers, suggesting a possible classification of biomarkers, and then argues that we are currently witnessing a 'biomarkerization' of health and disease - defined as an ongoing future-oriented process that seeks to solve biomedical as well as public health problems through investments into biomarker research at the present time. Subsequently, this article reflects on some possible consequences of this phenomenon. It argues that while the movement of candidate biomarkers into the clinic is arduous, biomarkers might develop a life of their own once they arrive in the clinic. This article outlines the direction of two such possible consequences. It suggests that biomarkers might be involved in a change of the actors that order and categorize diseases, as well as trigger transformations in our understanding of what counts as disease in the first place. Hence, this article seeks to shed light on the paradox that while biomarkers are designed to add more evidence into clinical practice, they might actually increase uncertainty and ambiguity.

Evaluation of midkine and anterior gradient 2 in a multimarker panel for the detection of ovarian cancer

The aims of this study were: to characterise and compare plasma concentrations of midkine (MDK) in normal healthy women with concentrations observed in women with ovarian cancer; and to establish and compare the performance of MDK with that of anterior gradient 2 protein (AGR2) and CA125 in the development of multi-analyte classification algorithms for ovarian cancer. Median plasma concentrations of immunoreactive MDK, AGR2 and CA125 were significantly greater in the case cohort (909 pg/ml, 765 pg/ml and 502 U/ml, respectively n = 46) than in the control cohort (383 pg/ml, 188 pg/ml and 13 U/ml, respectively n = 61) (p < 0.001). The area under the receiver operator characteristic curve (AUC) for MDK and AGR2 was not significantly different (0.734 ± 0.046 and 0.784 ± 0.049, respectively, mean ± SE) but were both significantly less than the AUC for CA125 (0.934 ± 0.030, p < 0.003). When subjected to stochastic gradient boosted logistic regression modelling, the AUC of the multi-analyte panel (MDK, AGR2 and CA125, 0.988 ± 0.010) was significantly greater than that of CA125 alone (0.934 ± 0.030, p = 0.035). The sensitivity and specificity of the multi-analyte algorithm were 95.2 and 97.7%, respectively. Within the study cohort, CA125 displayed a sensitivity and specificity of 87.0 and 94.6%, respectively. The data obtained in this study confirm that both MDK and AGR2 individually display utility as biomarkers for ovarian cancer and that in a multi-analyte panel significantly improve the diagnostic utility of CA125 in symptomatic women.

An immunoassay method for quantitative detection of proteins using single antibodies

A new immunoassay method called specific analyte labeling and recapture assay (SALRA) to quantitatively measure protein abundance was developed, and the assay conditions were optimized. The key features of this method include labeling the antigen bound to the capture antibody, eluting the labeled antigen, and recapturing it by the same capture antibody on the detection plate. The reporter molecules on the labeled antigen provide a convenient and reliable means for signal detection. We demonstrated that the dose-response curve of SALRA was comparable to that of sandwich enzyme-linked immunosorbent assay (ELISA) and better than that of the antigen direct labeling method. In addition, multiple proteins can be measured simultaneously by SALRA. Using the SALRA method, the detection limit for most of the cytokines tested was approximately 0.01ng/ml. Further SALRA tests on interleukin 6 (IL-6) showed the linear dose-response was 3.3 to 0.01ng/ml, the accuracy of the test was 71 to 91%, the intraassay variation was 3.6 to 7.4%, and the interassay variation was 3.8 to 10.0%. The applications of SALRA include quantitatively measuring proteins for which there are no ELISA tools available and providing a new platform for protein microarrays.

Myeloperoxidase and C-reactive protein have combined utility for long-term prediction of cardiovascular mortality after coronary angiography

OBJECTIVES

We evaluated the relative and combined value of oxidative stress biomarkers for predicting cardiovascular mortality in patients undergoing selective coronary angiography.

BACKGROUND

Oxidative stress participates in all stages of cardiovascular disease, from lipoprotein modification to plaque rupture, and biomarkers of oxidative stress predict development of coronary artery disease (CAD). Oxidative stress biomarkers merit investigation for the value they may offer for long-term cardiovascular risk prediction.

METHODS

Myeloperoxidase (MPO), nitrotyrosine, oxidized low-density lipoprotein, and antioxidant capacity were measured in a prospective cohort of 885 selective coronary angiography patients followed up for >13 years for cardiovascular mortality.

RESULTS

MPO independently predicted CAD, and top tertile MPO levels predicted a 2.4-fold risk of cardiovascular mortality (95% confidence interval [CI]: 1.47 to 2.98), compared with patients with lowest tertile MPO levels. MPO also improved risk model discrimination and patient risk category classification. Elevations in multiple oxidative stress biomarkers predicted increased mortality risk; however, the strongest risk prediction was achieved by assessing MPO and C-reactive protein (CRP) together. Patients with either MPO or CRP elevated had 5.3-fold higher cardiovascular mortality risk (95% CI: 1.86 to 14.9), and patients with high levels of both MPO and CRP had a 4.3-fold risk compared with patients with only elevated marker (95% CI: 2.26 to 8.31). These results remained significant with adjustment for cardiovascular risk factors and baseline disease burden.

CONCLUSIONS

MPO accurately predicted cardiovascular mortality risk in coronary angiography patients. Considering MPO and CRP together may improve long-term risk assessment and CAD patient outcomes.

Biomarkers in systemic sclerosis

Systemic sclerosis is an autoimmune inflammatory disorder of unknown etiologycharacterized b y pronounced fibroproliferative alterations in the microvasculature, and frequent cellular and humoral immunity abnormalities, culminating in a severe and often progressive fibrotic process. Numerous biomarkers reflecting the three main pathogenetic mechanisms in systemic sclerosis have been described; however, aside from several disease-specific autoantibodies, other biomarkers have not been thoroughly validated and require further study. Thus, there is an unmet need for validated biomarkers for diagnosis, disease classification, and evaluation of organ involvement and therapeutic response in systemic sclerosis.

Phase II biomarker trial of a multimarker diagnostic for ovarian cancer

Purpose

The primary hypothesis to be tested in this study was that the diagnostic performance (as assessed by the area under the receiver operator characteristic curve, AUC) of a multianalyte panel to correctly identify women with ovarian cancer was significantly greater than that for CA-125 alone.

Methods

A retrospective, case–control study (phase II biomarker trial) was conducted that involved 362 plasma samples obtained from women with ovarian cancer (n = 150) and healthy controls (n = 212). A multivariate classification model was developed that incorporated five biomarkers of ovarian cancer, CA-125; C-reactive protein (CRP); serum amyloid A (SAA); interleukin 6 (IL-6); and interleukin 8 (IL-8) from a modelling cohort (n = 179). The performance of the model was evaluated using an independent validation cohort (n = 183) and compared with of CA-125 alone.

Results

The AUC for the biomarker panel was significantly greater than the AUC for CA-125 alone for a validation cohort (p < 0.01) and an early stage disease cohort (i.e. Stages I and II; p < 0.01). At a threshold of 0.3, the sensitivity and specificity of the multianalyte panel were 94.1 and 91.3%, respectively, for the validation cohort and 92.3 and 91.3%, respectively for an early stage disease cohort.

Conclusions

The use of a panel of plasma biomarkers for the identification of women with ovarian cancer delivers a significant increase in diagnostic performance when compared to the performance of CA-125 alone.