Discovery of New Risk Markers for Ischemic Stroke Using a Novel Targeted Proteomics Chip

Visceral Fat and Novel Biomarkers of Cardiovascular Disease in Patients With Addison's Disease: A Case-Control Study

CONTEXT

Patients with Addison's disease (AD) have increased cardiovascular mortality.

OBJECTIVE

To study visceral fat and conventional and exploratory cardiovascular risk factors in patients with AD.

DESIGN

A cross-sectional, single-center, case-control study.

SUBJECTS

Patients (n = 76; n = 51 women) with AD and 76 healthy control subjects were matched for sex, age, body mass index (BMI), and smoking habits.

MAIN OUTCOME MEASURES

The primary outcome variable was visceral abdominal adipose tissue (VAT) measured using computed tomography. Secondary outcome variables were prevalence of metabolic syndrome (MetS) and 92 biomarkers of cardiovascular disease.

RESULTS

The mean ± standard deviation age of all subjects was 53 ± 14 years; mean BMI, 25 ± 4 kg/m2; and mean duration of AD, 17 ± 12 years. The median (range) daily hydrocortisone dose was 30 mg (10 to 50 mg). Median (interquartile range) 24-hour urinary free cortisol excretion was increased in patients vs controls [359 nmol (193 to 601 nmol) vs 175 nmol (140 to 244 nmol); P < 0.001]. VAT did not differ between groups. After correction for multiple testing, 17 of the 92 studied biomarkers differed significantly between patients and control subjects. Inflammatory, proinflammatory, and proatherogenic risk biomarkers were increased in patients [fold change (FC), >1] and vasodilatory protective marker was decreased (FC, <1). Twenty-six patients (34%) vs 12 control subjects (16%) fulfilled the criteria for MetS (P = 0.01).

CONCLUSION

Despite higher cortisol exposure, VAT was not increased in patients with AD. The prevalence of MetS was increased and several biomarkers of cardiovascular disease were adversely affected in patients with AD.

The potential mechanism for Hydroxysafflor yellow A attenuating blood-brain barrier dysfunction via tight junction signaling pathways excavated by an integrated serial affinity chromatography and shotgun proteomics analysis approach

Our previous studies elucidated that hydroxysafflor yellow A (HSYA) exerted anti-inflammatory effects against ischemia stroke by inhibiting TLR4 pathway-mediated signaling transduction. However, only several targets were verified in that limited work. The integrated method of serial affinity chromatography (SAC) and shotgun proteomics analysis (SPA) might be an alternative approach for exploring a potential therapeutic role. SAC was induced to extract specific binding proteins in the brain tissue of 2 h of ischemia stroke mice via HSYA affinity matrices. SPA was conducted by nanoLC-MS/MS, while the identified proteins were mapped on to Gene Ontology and KEGG pathway components analysis. The protection of HSYA for blood-brain barrier in mice with ischemia stroke was assessed with the leakage of Evans Blue. The expression of tight junction proteins of blood-brain barrier: occludin, claudin-5, and ZO-1 were detected with ischemia boundary positive areas staining. The regulation of nonmuscle myosin heavy chain IIA (NMMHC IIA), TLR4-mediated PI3K/AKT/JNK1/2/14-3-3ε/NF-κB p65 signaling pathway were evaluated using western blot analysis. A total of 35 proteins with molecular eights ranging from 27,841.22 to 234,122.79 KD were identified. Gene Ontology annotation and KEGG pathways analysis of the identified proteins were conducted with tight junction and PI3K/AKT signaling pathways. HSYA could significantly reduce the leakage of Evans Blue in mice with ischemia stroke, while attenuating the expression of occludin, claudin-5, and ZO-1. Western blot demonstrated that regulation of NMMHC IIA, TLR4-mediated PI3K/AKT/JNK1/2/14-3-3ε/NF-κB p65 signaling pathway played an essential role in the protective effect of HSYA. The integrated method of SAC and SPA provides the promising explanations for exploring the mechanism underlying blood-brain barrier dysfunction via the tight junction pathway. HSYA could attenuate blood-brain barrier dysfunction in anti-inflammatory patterns in ischemia stroke mice via the tight junction pathway.

Circulating proteins as predictors of incident heart failure in the elderly

AIMS

To identify novel risk markers for incident heart failure using proteomic profiling of 80 proteins previously associated with cardiovascular pathology.

METHODS AND RESULTS

Proteomic profiling (proximity extension assay) was performed in two community-based prospective cohorts of elderly individuals without heart failure at baseline: the Prospective Investigation of the Vasculature in Uppsala Seniors [PIVUS, n = 901, median age 70.2 (interquartile range 70.0-70.3) years, 80 events]; and the Uppsala Longitudinal Study of Adult Men [ULSAM, n = 685, median age 77.8 (interquartile range 76.9-78.1) years, 90 events]. Twenty-nine proteins were associated with incident heart failure in the discovery cohort PIVUS after adjustment for age and sex, and correction for multiple testing. Eighteen associations replicated in ULSAM. In pooled analysis of both cohorts, higher levels of nine proteins were associated with incident heart failure after adjustment for established risk factors: growth differentiation factor 15 (GDF-15), T-cell immunoglobulin and mucin domain 1 (TIM-1), tumour necrosis factor-related apoptosis-inducing ligand receptor 2 (TRAIL-R2), spondin-1 (SPON1), matrix metalloproteinase-12 (MMP-12), follistatin (FS), urokinase-type plasminogen activator surface receptor (U-PAR), osteoprotegerin (OPG), and suppression of tumorigenicity 2 (ST2). Of these, GDF-15, U-PAR, MMP-12, TRAIL-R2, SPON1 and FS were associated with worsened echocardiographic left ventricular systolic function at baseline, while only TIM-1 was positively associated with worsened diastolic function (P < 0.02 for all).

CONCLUSION

Proteomic profiling identified several novel associations between proteins involved in apoptosis, inflammation, matrix remodelling, and fibrinolysis with incident heart failure in elderly individuals. Our results encourage additional studies investigating the underlying mechanisms and the clinical utility of our findings.

Tracking and predicting disease progression in progressive supranuclear palsy: CSF and blood biomarkers

Progressive supranuclear palsy (PSP) is a rare and progressive neurodegenerative condition characterised pathologically by neuronal cell loss due to abnormal tau deposits. Clinically, the condition manifests as parkinsonism with the addition of progressive balance, speech, swallowing, eye movement and cognitive impairment, ultimately leading to death. Measuring change over time in neurodegenerative conditions is central to defining the effects of therapeutic intervention and disease biology. The current gold standard for measuring clinical disease progression in PSP is the PSP Rating Scale score. However, such scales may be affected by intrarater and inter-rater variability. In addition, their use in clinical trials may be hindered by differences in the time interval between pathological disease progression/response to therapeutics and change in clinical state. Therefore, the need for reliable disease progression biomarkers to complement clinical rating scales is clear. Here we discuss the benefits of using biomarkers to predict and track disease progression in both clinical and research settings. Through reviewing the literature to date on the role of cerebrospinal fluid (CSF) and blood biomarkers, we highlight data that reveals the ability of CSF and plasma neurofilament light chain (NF-L) to predict and track clinical disease progression in PSP. We also discuss the need for large-scale longitudinal studies to identify novel biomarkers.

Effect of food intake on 92 neurological biomarkers in plasma

OBJECTIVE

This study evaluates the effect of food intake on 92 neurological biomarkers in plasma. Moreover, it investigated if any of the biomarkers were correlated with body mass index.

MATERIALS AND METHODS

Twenty-two healthy subjects (11 male and 11 female aged 25.9 ± 4.2 years) were investigated. A total of 92 biomarkers were measured before a standardized meal as well as 30 and 120 min afterward with the Proseek Multiplex Neurology I kit.

RESULTS

The levels for 13 biomarkers decreased significantly (p < .001) 30 min after food intake. The levels for four biomarkers remained significantly decreased (p < .001) 120 min after food intake. One biomarker increased significantly (p < .001) 30 min after food intake. The changes were between 1% and 12%, with an average difference of about 5%. Only one biomarker showed a difference over 10% due to food intake. The biggest difference was observed for Plexin-B3 120 min after food intake (12%). Of all the 92 neurological biomarkers, only one was correlated with BMI, Kynureninase r = .46, p < .05.

CONCLUSIONS

This study shows that food intake has a very modest effect on 92 different neurological biomarkers. Timing of blood sampling in relation to food intake, therefore, appears not to be a major concern. Only Kynureninase was correlated with BMI. Further studies are warranted in older healthy subjects and in patients with various neurological diseases to determine whether the findings are reproducible in such populations.

Emerging Affinity-Based Proteomic Technologies for Large-Scale Plasma Profiling in Cardiovascular Disease

Plasma biomarkers that reflect molecular states of the cardiovascular system are central for clinical decision making. Routinely used plasma biomarkers include troponins, natriuretic peptides, and lipoprotein particles, yet interrogate only a modest subset of pathways relevant to cardiovascular disease. Systematic profiling of a larger portion of circulating plasma proteins (the plasma proteome) will provide opportunities for unbiased discovery of novel markers to improve diagnostic or predictive accuracy. In addition, proteomic profiling may inform pathophysiological understanding and point to novel therapeutic targets. Obstacles for comprehensive proteomic profiling include the immense size and structural heterogeneity of the proteome, and the broad range of abundance levels, as well. Proteome-wide, untargeted profiling can be performed in tissues and cells with tandem mass spectrometry. However, applications to plasma are limited by the need for complex preanalytical sample preparation stages limiting sample throughput. Multiplexing of targeted methods based on capture and detection of specific proteins are therefore receiving increasing attention in plasma proteomics. Immunoaffinity assays are the workhorse for measuring individual proteins but have been limited for proteomic applications by long development times, cross-reactivity preventing multiplexing, specificity issues, and incomplete sensitivity to detect proteins in the lower range of the abundance spectrum (below picograms per milliliter). Emerging technologies to address these issues include nucleotide-labeled immunoassays and aptamer reagents that can be automated for efficient multiplexing of thousands of proteins at high sample throughput, coupling of affinity capture methods to mass spectrometry for improved specificity, and ultrasensitive detection systems to measure low-abundance proteins. In addition, proteomics can now be integrated with modern genomics tools to comprehensively relate proteomic profiles to genetic variants, which may both influence binding of affinity reagents and serve to validate the target specificity of affinity assays. The application of deep quantitative proteomic profiling to large cohorts has thus become increasingly feasible with emerging affinity methods. The aims of this article are to provide the broad readership of Circulation with a timely overview of emerging methods for affinity proteomics and recent progress in cardiovascular medicine based on such methods.

Effect of food intake on 92 biomarkers for cardiovascular disease

Objective

The present study evaluates the effect of food intake on 92 biomarkers for cardiovascular disease (CVD).

Methods

Twenty two healthy subjects (11 male and 11 female aged 25.9±4.2 years) were investigated. A total of 92 biomarkers were measured before a standardized meal as well as 30 and 120 minutes afterwards with the Proseek Multiplex CVD III kit.

Results

The levels for eight biomarkers decreased significantly (P<0.05) 30 minutes after food intake. The levels for seven biomarkers remained significantly decreased 120 minutes after food intake. Nine biomarker decreased significantly at 120 minutes after food intake. The changes were between 4–30%, most commonly around 5%. Only six biomarkers showed a difference of 10% or more due to food intake. The biggest differences were observed for Insulin-like growth factor-binding protein 1 (30%); Azurocidin, Cystatin-B, and Myeloperoxidase (13%); Monocyte chemotactic protein 1 (11%); and Myeloblastin (10%), all 120 minutes after food intake.

Conclusions

This study shows that food intake affects several different CVD biomarkers, but the effect is predominantly modest. Timing of blood sampling in relation to food intake, therefore, appears not to be a major concern. Further studies are warranted in older healthy subjects and in patients with various cardiac diseases to determine whether the findings are reproducible.

Correlation of imaging and histopathology of thrombi in acute ischemic stroke with etiology and outcome: a systematic review

BACKGROUND AND PURPOSE

Studying the imaging and histopathologic characteristics of thrombi in ischemic stroke could provide insights into stroke etiology and ideal treatment strategies. We conducted a systematic review of imaging and histologic characteristics of thrombi in acute ischemic stroke.

MATERIALS AND METHODS

We identified all studies published between January 2005 and December 2015 that reported findings related to histologic and/or imaging characteristics of thrombi in acute ischemic stroke secondary to large vessel occlusion. The five outcomes examined in this study were (1) association between histologic composition of thrombi and stroke etiology; (2) association between histologic composition of thrombi and angiographic outcomes; (3) association between thrombi imaging and histologic characteristics; (4) association between thrombi imaging characteristics and angiographic outcomes; and (5) association between imaging characteristics of thrombi and stroke etiology. A meta-analysis was performed using a random effects model.

RESULTS

There was no significant difference in the proportion of red blood cell (RBC)-rich thrombi between cardioembolic and large artery atherosclerosis etiologies (OR 1.62, 95% CI 0.1 to 28.0, p=0.63). Patients with a hyperdense artery sign had a higher odds of having RBC-rich thrombi than those without a hyperdense artery sign (OR 9.0, 95% CI 2.6 to 31.2, p<0.01). Patients with a good angiographic outcome had a mean thrombus Hounsfield unit (HU) of 55.1±3.1 compared with a mean HU of 48.4±1.9 for patients with a poor angiographic outcome (mean standard difference 6.5, 95% CI 2.7 to 10.2, p<0.001). There was no association between imaging characteristics and stroke etiology (OR 1.13, 95% CI 0.32 to 4.00, p=0.85).

CONCLUSIONS

The hyperdense artery sign is associated with RBC-rich thrombi and improved recanalization rates. However, there was no association between the histopathological characteristics of thrombi and stroke etiology and angiographic outcomes.

Proteomics Research in Cardiovascular Medicine and Biomarker Discovery

Proteomics is a systems physiology discipline to address the large-scale characterization of protein species within a biological system, be it a cell, a tissue, a body biofluid, an organism, or a cohort population. Building on advances from chemical analytical platforms (e.g., mass spectrometry and other technologies), proteomics approaches have contributed powerful applications in cardiovascular biomedicine, most notably in: 1) the discovery of circulating protein biomarkers of heart diseases from plasma samples; and 2) the identification of disease mechanisms and potential therapeutic targets in cardiovascular tissues, in both preclinical models and translational studies. Contemporary proteomics investigations offer powerful means to simultaneously examine tens of thousands of proteins in various samples, and understand their molecular phenotypes in health and disease. This concise review introduces study design considerations, example applications and use cases, as well as interpretation and analysis of proteomics data in cardiovascular biomedicine.

Associations Between Macrophage Colony-Stimulating Factor and Monocyte Chemotactic Protein 1 in Plasma and First-Time Coronary Events: A Nested Case-Control Study

BACKGROUND

Myeloid cells play a central role in atherosclerosis. We investigated the associations between the plasma levels of growth factors and chemokines that regulate myeloid cell homeostasis and function and the risk of first-time acute coronary events in middle-aged persons.

METHODS AND RESULTS

We measured baseline plasma levels of macrophage colony-stimulating factor; monocyte chemotactic protein 1; C-C motif chemokine ligands 3, 4, and 20; C-X-C motif chemokine ligands 1, 6, and 16; and C-X3-C motif chemokine ligand 1 in 292 participants who had a coronary event during follow-up and 366 controls matched for age, sex, and time of inclusion who remained event free. Study participants were recruited from the Malmö Diet and Cancer Study population cohort and had no previous history of coronary artery disease. We found a strong independent negative association between macrophage colony-stimulating factor and incident coronary events in a forward stepwise Cox proportional hazards model including all biomarkers alongside the classic Framingham risk factors (age, sex, smoking, total cholesterol, high-density lipoprotein cholesterol, systolic blood pressure), diabetes mellitus, and medication. Conversely, monocyte chemotactic protein 1 had the strongest independent positive association with the outcome. The addition of macrophage colony-stimulating factor and monocyte chemotactic protein 1 significantly improved the predictive ability of a model including traditional risk factors alone (C statistic 0.81 [95% CI 0.78-0.84] versus 0.67 [95% CI 0.63-0.71]; net reclassification index 0.52 [0.42-0.62]; P<0.001). The combined model led to a 54% net downclassification of participants who did not have a coronary event during follow-up and was particularly effective in the intermediate-risk group.

CONCLUSIONS

High levels of macrophage colony-stimulating factor and low levels of monocyte chemotactic protein 1 in plasma characterize middle-aged persons at low risk to develop clinically manifested coronary artery disease.

Proteomics in stroke research: potentials of the nascent proteomics

Among omics, the proteomics assumes a unique role in that it offers the effectors or actuators of a biological condition. This brief review attempts to summarize the development in a relatively new but important subdiscipline of proteomics, the so-called nascent proteomics, and its potential applications in stroke research. First, we will discuss a few examples of proteomics-led discoveries in stroke research, and challenges or unmet demands when using commonly practiced proteomics approaches. Then we will introduce nascent proteomics and its studying tools, followed by discussions on its potentials in stroke research.

Plasma growth differentiation factor 15 predicts first-ever stroke in hypertensive patients

Growth differentiation factor 15 (GDF-15) is a relatively new biomarker that predicts adverse stroke outcomes. However, the association of GDF-15 with first-ever stroke in hypertensive patients has not yet been evaluated. The objective of this study was to evaluate the clinical implications of plasma GDF-15 on the development of first-ever stroke in patients with hypertension.In total, 254 patients with hypertension without a history of stroke were included from March 2010 to August 2010 and followed up until June 2013. The baseline circulating GDF-15 was determined by enzyme-linked immunosorbent assays.During a follow-up of 3.0 ± 0.6 years, 22 (8.7%) first-ever strokes were identified, including 12 ischemic strokes and 10 intracerebral hemorrhages (ICH). According to tertiles of GDF-15, survival free of first-ever stroke was lower in the highest tertile of GDF-15 (log-rank P = 0.001). By backward stepwise Cox-regression analysis, adjusted for age, gender, diabetes mellitus, hyperlipidemia, hypertension stage, body mass index, cigarette smoking, anti-hypertensive drugs, and uric acid, every 100 pg/mL-increase in plasma of GDF-15 predicted an 11% greater risk of first-ever stroke (hazard ratios [HR]: 1.11, 95% confidence interval [CI]: 1.03-1.20, P = 0.010) and an 18% increase in ischemic stroke risk (HR: 1.18, 95% CI: 1.07-1.30, P = 0.001). Receiver operating characteristic analysis indicated that GDF-15 had reasonable accuracy to predict first-ever stroke (area under curve = 0.73, 95% CI: 0.62-0.83, P < 0.001).This study identifies that GDF-15 is an independent predictor of first-ever stroke, especially for ischemic stroke in the patients with hypertension.

Update on ultrasensitive technologies to facilitate research on blood biomarkers for central nervous system disorders

Most research on fluid biomarkers for central nervous system (CNS) disorders has so far been performed using cerebrospinal fluid (CSF) as the biomarker source. CSF has the advantage of being closer to the brain than serum or plasma with a relative enrichment of CNS-specific proteins that are present at very low concentrations in the blood and thus difficult to reliably quantify using standard immunochemical technologies. Recent technical breakthroughs in the field of ultrasensitive assays have started to change this. Here, we review the most established ultrasensitive quantitative technologies that are currently available to general biomarker laboratories and discuss their use in research on biomarkers for CNS disorders.

Association of soluble tumor necrosis factor receptors 1 and 2 with nephropathy, cardiovascular events, and total mortality in type 2 diabetes

AIMS/HYPOTHESIS

Soluble tumor necrosis factor receptors 1 and 2 (sTNFR1 and sTNFR2) contribute to experimental diabetic kidney disease, a condition with substantially increased cardiovascular risk when present in patients. Therefore, we aimed to explore the levels of sTNFRs, and their association with prevalent kidney disease, incident cardiovascular disease, and risk of mortality independently of baseline kidney function and microalbuminuria in a cohort of patients with type 2 diabetes. In pre-defined secondary analyses we also investigated whether the sTNFRs predict adverse outcome in the absence of diabetic kidney disease.

METHODS

The CARDIPP study, a cohort study of 607 diabetes patients [mean age 61 years, 44 % women, 45 cardiovascular events (fatal/non-fatal myocardial infarction or stroke) and 44 deaths during follow-up (mean 7.6 years)] was used.

RESULTS

Higher sTNFR1 and sTNFR2 were associated with higher odds of prevalent kidney disease [odd ratio (OR) per standard deviation (SD) increase 1.60, 95 % confidence interval (CI) 1.32-1.93, p < 0.001 and OR 1.54, 95 % CI 1.21-1.97, p = 0.001, respectively]. In Cox regression models adjusting for age, sex, glomerular filtration rate and urinary albumin/creatinine ratio, higher sTNFR1 and sTNFR2 predicted incident cardiovascular events [hazard ratio (HR) per SD increase, 1.66, 95 % CI 1.29-2.174, p < 0.001 and HR 1.47, 95 % CI 1.13-1.91, p = 0.004, respectively]. Results were similar in separate models with adjustments for inflammatory markers, HbA1c, or established cardiovascular risk factors, or when participants with diabetic kidney disease at baseline were excluded (p < 0.01 for all). Both sTNFRs were associated with mortality.

CONCLUSIONS/INTERPRETATIONS

Higher circulating sTNFR1 and sTNFR2 are associated with diabetic kidney disease, and predicts incident cardiovascular disease and mortality independently of microalbuminuria and kidney function, even in those without kidney disease. Our findings support the clinical utility of sTNFRs as prognostic markers in type 2 diabetes.