Proteomic Discovery and Validation of the Confounding Effect of Heparin Administration on the Analysis of Candidate Cardiovascular Biomarkers

Myocardial proteome changes in aortic stenosis rats subjected to long-term aerobic exercise

The effects of exercise training (ET) on the heart of aortic stenosis (AS) rats are controversial and the mechanisms involved in alterations induced by ET have been poorly clarified. In this study, we analyzed the myocardial proteome to identify proteins modulated by moderate-intensity aerobic ET in rats with chronic supravalvular AS. Wistar rats were divided into four groups: sedentary control (C-Sed), exercised control (C-Ex), sedentary aortic stenosis (AS-Sed), and exercised AS (AS-Ex). ET consisted of five treadmill running sessions per week for 16 weeks. Statistical analysis was performed by ANOVA or Kruskal-Wallis and Goodman tests. Results were discussed at a significance level of 5%. At the end of the experiment, AS-Ex rats had higher functional capacity, lower blood lactate concentration, and better cardiac structural and left ventricular (LV) functional parameters than the AS-Sed. Myocardial proteome analysis showed that AS-Sed had higher relative protein abundance related to the glycolytic pathway, oxidative stress, and inflammation, and lower relative protein abundance related to beta-oxidation than C-Sed. AS-Ex had higher abundance of one protein related to mitochondrial biogenesis and lower relative protein abundance associated with oxidative stress and inflammation than AS-Sed. Proteomic data were validated for proteins related to lipid and glycolytic metabolism. Chronic pressure overload changes the abundance of myocardial proteins that are mainly involved in lipid and glycolytic energy metabolism in rats. Moderate-intensity aerobic training attenuates changes in proteins related to oxidative stress and inflammation and increases the COX4I1 protein, related to mitochondrial biogenesis. Protein changes are combined with improved functional capacity, cardiac remodeling, and LV function in AS rats.

A Mass Spectrometry-Based Proteome Study of Twin Pairs Discordant for Incident Acute Myocardial Infarction within Three Years after Blood Sampling Suggests Novel Biomarkers

Acute myocardial infarction (AMI) is a major cause of mortality and morbidity worldwide, yet biomarkers for AMI in the short- or medium-term are lacking. We apply the discordant twin pair design, reducing genetic and environmental confounding, by linking nationwide registry data on AMI diagnoses to a survey of 12,349 twins, thereby identifying 39 twin pairs (48-79 years) discordant for their first-ever AMI within three years after blood sampling. Mass spectrometry of blood plasma identified 715 proteins. Among 363 proteins with a call rate > 50%, imputation and stratified Cox regression analysis revealed seven significant proteins (FDR < 0.05): FGD6, MCAM, and PIK3CB reflected an increased level in AMI twins relative to their non-AMI co-twins (HR > 1), while LBP, IGHV3-15, C1RL, and APOC4 reflected a decreased level in AMI twins relative to their non-AMI co-twins (HR < 1). Additional 50 proteins were nominally significant (p < 0.05), and bioinformatics analyses of all 57 proteins revealed biology within hemostasis, coagulation cascades, the immune system, and the extracellular matrix. A protein-protein-interaction network revealed Fibronectin 1 as a central hub. Finally, technical validation confirmed MCAM, LBP, C1RL, and APOC3. We put forward novel biomarkers for incident AMI, a part of the proteome field where markers are surprisingly rare and where additional studies are highly needed.

Differential gene expression patterns in ST-elevation Myocardial Infarction and Non-ST-elevation Myocardial Infarction

The ST-elevation Myocardial Infarction (STEMI) and Non-ST-elevation Myocardial Infarction (NSTEMI) might occur because of coronary artery stenosis. The gene biomarkers apply to the clinical diagnosis and therapeutic decisions in Myocardial Infarction. The aim of this study was to introduce, enrich and estimate timely the blood gene profiles based on the high-throughput data for the molecular distinction of STEMI and NSTEMI. The text mining data (50 genes) annotated with DisGeNET data (144 genes) were merged with the GEO gene expression data (5 datasets) using R software. Then, the STEMI and NSTEMI networks were primarily created using the STRING server, and improved using the Cytoscape software. The high-score genes were enriched using the KEGG signaling pathways and Gene Ontology (GO). Furthermore, the genes were categorized to determine the NSTEMI and STEMI gene profiles. The time cut-off points were identified statistically by monitoring the gene profiles up to 30 days after Myocardial Infarction (MI). The gene heatmaps were clearly created for the STEMI (high-fold genes 69, low-fold genes 45) and NSTEMI (high-fold genes 68, low-fold genes 36). The STEMI and NSTEMI networks suggested the high-score gene profiles. Furthermore, the gene enrichment suggested the different biological conditions for STEMI and NSTEMI. The time cut-off points for the NSTEMI (4 genes) and STEMI (13 genes) gene profiles were established up to three days after Myocardial Infarction. The study showed the different pathophysiologic conditions for STEMI and NSTEMI. Furthermore, the high-score gene profiles are suggested to measure up to 3 days after MI to distinguish the STEMI and NSTEMI.

Identification of Highly Sensitive Pleural Effusion Protein Biomarkers for Malignant Pleural Mesothelioma by Affinity-Based Quantitative Proteomics

Malignant pleural mesothelioma (MPM) is an asbestos-associated, highly aggressive cancer characterized by late-stage diagnosis and poor prognosis. Gold standards for diagnosis are pleural biopsy and cytology of pleural effusion (PE), both of which are limited by low sensitivity and markedly inter-observer variations. Therefore, the assessment of PE biomarkers is considered a viable and objective diagnostic tool for MPM diagnosis. We applied a novel affinity-enrichment mass spectrometry-based proteomics method for explorative analysis of pleural effusions from a prospective cohort of 84 patients referred for thoracoscopy due to clinical suspicion of MPM. Protein biomarkers with a high capability to discriminate MPM from non-MPM patients were identified, and a Random Forest algorithm was applied for building classification models. Immunohistology of pleural biopsies confirmed MPM in 40 patients and ruled out MPM in 44 patients. Proteomic analysis of pleural effusions identified panels of proteins with excellent diagnostic properties (90-100% sensitivities, 89-98% specificities, and AUC 0.97-0.99) depending on the specific protein combination. Diagnostic proteins associated with cancer growth included galactin-3 binding protein, testican-2, haptoglobin, Beta ig-h3, and protein AMBP. Moreover, we also confirmed previously reported diagnostic accuracies of the MPM markers fibulin-3 and mesothelin measured by two complementary mass spectrometry-based methods. In conclusion, a novel affinity-enrichment mass spectrometry-based proteomics identified panels of proteins in pleural effusion with extraordinary diagnostic accuracies, which are described here for the first time as biomarkers for MPM.

Elucidation of Cellular Contributions to Heparin-Induced Thrombocytopenia Using Omic Approaches

Heparin-induced thrombocytopenia (HIT) is an unpredictable, complex, immune-mediated adverse drug reaction associated with a high mortality. Despite decades of research into HIT, fundamental knowledge gaps persist regarding HIT likely due to the complex and unusual nature of the HIT immune response. Such knowledge gaps include the identity of a HIT immunogen, the intrinsic roles of various cell types and their interactions, and the molecular basis that distinguishes pathogenic and non-pathogenic PF4/heparin antibodies. While a key feature of HIT, thrombocytopenia, implicates platelets as a seminal cell fragment in HIT pathogenesis, strong evidence exists for critical roles of multiple cell types. The rise in omic technologies over the last decade has resulted in a number of agnostic, whole system approaches for biological research that may be especially informative for complex phenotypes. Applying multi-omics techniques to HIT has the potential to bring new insights into HIT pathophysiology and identify biomarkers with clinical utility. In this review, we review the clinical, immunological, and molecular features of HIT with emphasis on key cell types and their roles. We then address the applicability of several omic techniques underutilized in HIT, which have the potential to fill knowledge gaps related to HIT biology.

Recent Developments in Clinical Plasma Proteomics—Applied to Cardiovascular Research

The human plasma proteome mirrors the physiological state of the cardiovascular system, a fact that has been used to analyze plasma biomarkers in routine analysis for the diagnosis and monitoring of cardiovascular diseases for decades. These biomarkers address, however, only a very limited subset of cardiovascular diseases, such as acute myocardial infarct or acute deep vein thrombosis, and clinical plasma biomarkers for the diagnosis and stratification cardiovascular diseases that are growing in incidence, such as heart failure and abdominal aortic aneurysm, do not exist and are urgently needed. The discovery of novel biomarkers in plasma has been hindered by the complexity of the human plasma proteome that again transforms into an extreme analytical complexity when it comes to the discovery of novel plasma biomarkers. This complexity is, however, addressed by recent achievements in technologies for analyzing the human plasma proteome, thereby facilitating the possibility for novel biomarker discoveries. The aims of this article is to provide an overview of the recent achievements in technologies for proteomic analysis of the human plasma proteome and their applications in cardiovascular medicine.

Determining Plasma Protein Variation Parameters as a Prerequisite for Biomarker Studies-A TMT-Based LC-MSMS Proteome Investigation

Specific plasma proteins serve as valuable markers for various diseases and are in many cases routinely measured in clinical laboratories by fully automated systems. For safe diagnostics and monitoring using these markers, it is important to ensure an analytical quality in line with clinical needs. For this purpose, information on the analytical and the biological variation of the measured plasma protein, also in the context of the discovery and validation of novel, disease protein biomarkers, is important, particularly in relation to for sample size calculations in clinical studies. Nevertheless, information on the biological variation of the majority of medium-to-high abundant plasma proteins is largely absent. In this study, we hypothesized that it is possible to generate data on inter-individual biological variation in combination with analytical variation of several hundred abundant plasma proteins, by applying LC-MS/MS in combination with relative quantification using isobaric tagging (10-plex TMT-labeling) to plasma samples. Using this analytical proteomic approach, we analyzed 42 plasma samples prepared in doublets, and estimated the technical, inter-individual biological, and total variation of 265 of the most abundant proteins present in human plasma thereby creating the prerequisites for power analysis and sample size determination in future clinical proteomics studies. Our results demonstrated that only five samples per group may provide sufficient statistical power for most of the analyzed proteins if relative changes in abundances >1.5-fold are expected. Seventeen of the measured proteins are present in the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Biological Variation Database, and demonstrated remarkably similar biological CV’s to the corresponding CV’s listed in the EFLM database suggesting that the generated proteomic determined variation knowledge is useful for large-scale determination of plasma protein variations.

Confounders in Identification and Analysis of Inflammatory Biomarkers in Cardiovascular Diseases

Proinflammatory biomarkers have been increasingly used in epidemiologic and intervention studies over the past decades to evaluate and identify an association of systemic inflammation with cardiovascular diseases. Although there is a strong correlation between the elevated level of inflammatory biomarkers and the pathology of various cardiovascular diseases, the mechanisms of the underlying cause are unclear. Identification of pro-inflammatory biomarkers such as cytokines, chemokines, acute phase proteins, and other soluble immune factors can help in the early diagnosis of disease. The presence of certain confounding factors such as variations in age, sex, socio-economic status, body mass index, medication and other substance use, and medical illness, as well as inconsistencies in methodological practices such as sample collection, assaying, and data cleaning and transformation, may contribute to variations in results. The purpose of the review is to identify and summarize the effect of demographic factors, epidemiological factors, medication use, and analytical and pre-analytical factors with a panel of inflammatory biomarkers CRP, IL-1b, IL-6, TNFa, and the soluble TNF receptors on the concentration of these inflammatory biomarkers in serum.

Basement membrane proteins in various arterial beds from individuals with and without type 2 diabetes mellitus: a proteome study

BACKGROUND

Basement membrane (BM) accumulation is a hallmark of micro-vessel disease in diabetes mellitus (DM). We previously reported marked upregulation of BM components in internal thoracic arteries (ITAs) from type 2 DM (T2DM) patients by mass spectrometry. Here, we first sought to determine if BM accumulation is a common feature of different arteries in T2DM, and second, to identify other effects of T2DM on the arterial proteome.

METHODS

Human arterial samples collected during heart and vascular surgery from well-characterized patients and stored in the Odense Artery Biobank were analysed by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). We included ascending thoracic aortas (ATA) (n = 10 (type 2 DM, T2DM) and n = 10 (non-DM)); laser capture micro-dissected plaque- and media compartments from carotid plaques (n = 10 (T2DM) and n = 9 (non-DM)); and media- and adventitia compartments from ITAs (n = 9 (T2DM) and n = 7 (non-DM)).

RESULTS

We first extended our previous finding of BM accumulation in arteries from T2DM patients, as 7 of 12 pre-defined BM proteins were significantly upregulated in bulk ATAs consisting of > 90% media. Although less pronounced, BM components tended to be upregulated in the media of ITAs from T2DM patients, but not in the neighbouring adventitia. Overall, we did not detect effects on BM proteins in carotid plaques or in the plaque-associated media. Instead, complement factors, an RNA-binding protein and fibrinogens appeared to be regulated in these tissues from T2DM patients.

CONCLUSION

Our results suggest that accumulation of BM proteins is a general phenomenon in the medial layer of non-atherosclerotic arteries in patients with T2DM. Moreover, we identify additional T2DM-associated effects on the arterial proteome, which requires validation in future studies.

Midkine and chronic kidney disease-associated multisystem organ dysfunctions

Chronic kidney disease (CKD) is a progressive multisystem condition with yet undefined mechanistic drivers and multiple implicated soluble factors. If identified, these factors could be targeted for therapeutic intervention for a disease that currently lacks specific treatment. There is increasing preclinical evidence that the heparin/endothelial glycocalyx-binding molecule midkine (MK) has a pathological role in multiple CKD-related, organ-specific disease processes, including CKD progression, hypertension, vascular and cardiac disease, bone disease and CKD-related cancers. Concurrent with this are studies documenting increases in circulating and urine MK proportional to glomerular filtration rate (GFR) loss in CKD patients and evidence that administering soluble MK reverses the protective effects of MK deficiency in experimental kidney disease. This review summarizes the growing body of evidence supporting MK's potential role in driving CKD-related multisystem disease, including MK's relationship with the endothelial glycocalyx, the deranged MK levels and glycocalyx profile in CKD patients and a proposed model of MK organ interplay in CKD disease processes and highlights the importance of ongoing research into MK's potential as a therapeutic target.

Does diabetes modify the effect of heparin on plasma proteins? - A proteomic search for plasma protein biomarkers for diabetes-related endothelial dysfunction

AIM

Heparin administration affects the concentrations of many plasma proteins through their displacement from the endothelial glycocalyx. A differentiated protein response in diabetes will therefore, at least partly, reflect glycocalyx changes. This study aims at identifying biomarkers of endothelial dysfunction in diabetes by statistical exploration of plasma proteome data for interactions between diabetes status and heparin treatment.

METHODS

Diabetes-by-heparin interactions in relation to protein levels were inspected by regression modelling in plasma proteome data from 497 patients admitted for acute angiography. Analyses were conducted separately for all 273 proteins and as set-based analyses of 44 heparin-relevant proteins identified by gene ontology analysis and 42 heparin-influenced proteins previously reported.

RESULTS

Seventy-five patients had diabetes and 361 received heparin before hospitalization. The proteome-wide analysis displayed no proteins with diabetes-heparin interaction to pass correction for multiple testing. The overall set-based analyses revealed significant association for both protein sets (p-values<2*10^-4), while constraining on opposite directions of effect in diabetics and none-diabetics was insignificant (p-values = 0.11 and 0.17).

CONCLUSIONS

Our plasma proteome-wide interaction approach supports that diabetes influences heparin effects on protein levels, however the direction of effects and individual proteins could not be definitively pinpointed, likely reflecting a complex protein-basis for glycocalyx dysfunction in diabetes.

PYRIN inflammasome activation abrogates IL1Ra expression providing a new mechanism underlying FMF pathogenesis

OBJECTIVE

Aberrant PYRIN inflammasome activity triggers FMF pathogenesis but the exact mechanism remains elusive and an obstacle to efficient treatment. Herein, we sought to identify PYRIN inflammasome specific mechanisms to improve FMF treatment and diagnostics in the future.

METHODS

PYRIN-specific protein secretion was assessed by proteome analysis in U937 derived macrophages, and specific findings were confirmed in PYRIN inflammasome activated monocytes from healthy blood donors (HD) and FMF patients, stratified by MEFV genotype categories corresponding to a suspected increasing FMF disease severity.

RESULTS

Proteome data revealed differential secretion pattern of IL1Rα from PYRIN and NLRP3 activated U937 derived macrophages, which was verified by ELISA and qPCR. Moreover, PYRIN activation significantly reduced IL1RN mRNA expression (p<0.001) and IL1Rα secretion (p<0.01) in healthy donor- and FMF monocytes, respectively. Independent of MEFV genotype, unstimulated FMF monocytes from colchicine treated patients secreted lower amounts of IL1Rα as compared to healthy donors (p<0.05) and displayed decreased ratios of IL1Rα/IL1β (p<0.05), suggesting a reduced anti-inflammatory capacity.

CONCLUSION

Our data show an inherent lack of IL-1 receptor antagonist expression specific to PYRIN inflammasome activation, providing a new mechanism underlying FMF pathogenesis. The reduced IL1Rα levels in FMF monocytes suggest a diminished anti-inflammatory capacity potentially leaving FMF patient monocytes more sensitive to pro-inflammatory stimuli, regardless of being in colchicine therapy. Thus, considering the potential clinical consequence of reduced monocyte IL1Rα secretion in FMF patients, we suggest further investigations into IL1Rα dynamics and its potential implications for FMF treatment in the future.

Rapid responses of adipocytes to iron overload increase serum TG level by decreasing adiponectin

Iron overload is tightly connected with metabolic disorders. Excess iron in the adipose and its roles in dyslipidemia are of interest to be identified. In acute iron overload mice receiving intraperitoneal injection of 100 mg/kg/day dextran-iron for 5 days, the epididymis adipose showed a remarkable increase in iron. Serum triglyceride and low-density lipoprotein cholesterol (LDL-C) levels were increased and high-density lipoprotein cholesterol (HDL-C) level was decreased, while serum alkaline phosphatase, aspartate aminotransferase, glucose, and insulin were not affected. The serum-cytokine-microarray showed that adipocytokines, including adiponectin, leptin, and resistin were significantly decreased. Other serum cytokines, including pro-insulin cytokines, inflammatory cytokines, chemokines, and growth factors were not changed, except that ghrelin and chemokine RANTES were increased. Iron overload decreased expressions of adiponectin and leptin both in vivo and in vitro. Intraperitoneal injection of recombinant leptin at 1 μg/g in acute iron overload mice had no significant effects on serum levels of TC, TG, HDL-C, and LDL-C, while intraperitoneal injection of recombinant adiponectin at 3 μg/g partially restored serum TG level through improving activities of lipoprotein lipase and hepatic lipase, but abnormal serum LDL-C and HDL-C were not redressed, suggesting other mechanisms also existed. In conclusion, the adipose responds to iron overload at an early stage to interfere with lipid metabolism by secreting adipocytokines, which may further affect glucose metabolism, inflammation, and other iron overload-induced effects on the body.

Study of three novel biomarkers, MR-proADM, midkine, and stromelysin2, and peripheral atherosclerosis in a Chinese Han population: A case-control study

Midregional pro-adrenomedullin (MR-proADM), midkine, and stromelysin2 (ST2) are novel cardiac biomarkers associated with heart failure and atherosclerotic diseases like stable ischemic disease and acute coronary syndrome. The potential association between these three biomarkers and peripheral artery disease (PAD) remains unclear. The aim of this study was to assess the correlation between these three biomarkers and their association with PAD in the Chinese Han population. This study included 224 patients suspected of having coronary artery disease (CAD). All subjects underwent coronary angiography and carotid and subclavian ultrasound assessment for detection of coronary and peripheral atherosclerosis and were divided into two groups according to whether they had PAD or not. Pearson’s correlation coefficient r was calculated, and multivariable logistic regression analysis was conducted to represent the associations of these biomarkers and PAD. The study included 133 patients with PAD and 91 non-PAD controls and these two groups had similar values for age, ST2, hematocrit, hemoglobin, red blood cell counts, creatinine and CAD ratio, smoking, and type 2 diabetes (all p > 0.05). Compared with non-PAD controls, patients with PAD had lower levels of MR-proADM and midkine and higher levels of TC, LDL-C, and fasting blood sugar (FBS) (all p < 0.05). MR-proADM was positively and ST2 negatively correlated with midkine (all p < 0.05). Compared with females, male patients had higher values of MR-proADM ( p < 0.05) and similar levels of ST2 and midkine (all p > 0.05). Multivariable regression analysis identified FBS as a risk predictor (OR: 1.163, 95% CI: 1.108–1.401, p = 0.014) and MR-proADM as a protective factor (OR: 0.720, 95% CI: 0.529–0.920, p = 0.037) of PAD. Three novel biomarkers, MR-proADM, midkine, and ST2, are internally related, and MR-proADM is gender-specific and a protective factor of peripheral atherosclerosis in the Chinese Han population studied. Clinical Trial: ChiCTR-DDD-17013908

Affinity Capture Enrichment versus Affinity Depletion: A Comparison of Strategies for Increasing Coverage of Low-Abundant Human Plasma Proteins

In the present study, we evaluated four small molecule affinity-based probes based on agarose-immobilized benzamidine (ABA), O-Phospho-L-Tyrosine (pTYR), 8-Amino-hexyl-cAMP (cAMP), or 8-Amino-hexyl-ATP (ATP) for their ability to remove high-abundant proteins such as serum albumin from plasma samples thereby enabling the detection of medium-to-low abundant proteins in plasma samples by mass spectrometry-based proteomics. We compared their performance with the most commonly used immunodepletion method, the Multi Affinity Removal System Human 14 (MARS14) targeting the top 14 most abundant plasma proteins and also the ProteoMiner protein equalization method by label-free quantitative liquid chromatography tandem mass spectrometry (LC-MSMS) analysis. The affinity-based probes demonstrated a high reproducibility for low-abundant plasma proteins, down to picomol per mL levels, compared to the Multi Affinity Removal System (MARS) 14 and the Proteominer methods, and also demonstrated superior removal of the majority of the high-abundant plasma proteins. The ABA-based affinity probe and the Proteominer protein equalization method performed better compared to all other methods in terms of the number of analyzed proteins. All the tested methods were highly reproducible for both high-abundant plasma proteins and low-abundant proteins as measured by correlation analyses of six replicate experiments. In conclusion, our results demonstrated that small-molecule based affinity-based probes are excellent alternatives to the commonly used immune-depletion methods for proteomic biomarker discovery studies in plasma. Data are available via ProteomeXchange with identifier PXD020727.

STEMI, Cardiogenic Shock, and Mortality in Patients Admitted for Acute Angiography: Associations and Predictions from Plasma Proteome Data

AIM

Acute myocardial infarction (AMI) remains a major cause of mortality and morbidity, and cardiogenic shock (CS) a major cause of hospital mortality after AMI. Especially for ST elevation myocardial infarction (STEMI) patients, fast intervention is essential.Few proteins have proven clinically applicable for AMI. Most proposed biomarkers are based on a priori hypothesis-driven studies of single proteins, not enabling identification of novel candidates. For clinical use, the ability to predict AMI is important; however, studies of proteins in prediction models are surprisingly scarce.Consequently, we applied proteome data for identifying proteins associated with definitive STEMI, CS, and all-cause mortality after admission, and examined the ability of the proteins to predict these outcomes.

METHODS AND RESULTS

Proteome-wide data of 497 patients with suspected STEMI were investigated; 381 patients were diagnosed with STEMI, 35 with CS, and 51 died during the first year. Data analysis was conducted by logistic and Cox regression modeling for association analysis, and by multivariable LASSO regression models for prediction modeling.Association studies identified 4 and 29 proteins associated with definitive STEMI or mortality, respectively. Prediction models for CS and mortality (holding two and five proteins, respectively) improved the prediction ability as compared with protein-free prediction models; AUC of 0.92 and 0.89, respectively.

CONCLUSION

The association analyses propose individual proteins as putative protein biomarkers for definitive STEMI and survival after suspected STEMI, while the prediction models put forward sets of proteins with putative predicting ability of CS and survival. These proteins may be verified as biomarkers of potential clinical relevance.

Immunoelectron microscopy and mass spectrometry for classification of amyloid deposits

Amyloidosis is a shared name for several rare, complex and serious diseases caused by extra-cellular deposits of different misfolded proteins. Accurate characterization of the amyloid protein is essential for patient care. Immunoelectron microscopy (IEM) and laser microdissection followed by tandem mass spectrometry (LMD-MS) are new gold standards for molecular subtyping. Both methods perform superiorly to immunohistochemistry, but their complementarities, strengths and weaknesses across amyloid subtypes and organ biopsy origin remain undefined. Therefore, we performed a retrospective study of 106 Congo Red positive biopsies from different involved organs; heart, kidney, lung, gut mucosa, skin and bone marrow. IEM, performed with gold-labelled antibodies against kappa light chains, lambda light chains, transthyretin and amyloid A, identified specific staining of amyloid fibrils in 91.6%; in six biopsies amyloid fibrils were not identified, and in two, the fibril subtype could not be established. LMD-MS identified amyloid protein signature in 98.1%, but in nine the amyloid protein could not be clearly identified. MS identified protein subtype in 89.6%. Corresponding specificities ranged at organ level from 94-100%. Concordance was 89.6-100% for different amyloid subtypes. Importantly, combined use of both methods increased the diagnostic classification to 100%. Some variety in performances at organ level was observed.

Heparin Administration, but Not Myocardial Ischemia or Necrosis, Leads to Midkine Elevation

Midkine (MK) is a heparin-binding growth factor, whose role as a biomarker of coronary artery disease, myocardial ischaemia and necrosis has not been well measured. This study quantified serial MK levels in patients undergoing coronary angiography (CA) and identified factors associated with MK. In this single-centre, parallel cohort study, forty patients undergoing CA had arterial samples collected prior, 10 and 20 min after heparin administration. Four groups were examined: 1-stable coronary artery disease (CAD) without percutaneous coronary intervention (PCI); 2-stable CAD for elective PCI; 3-non-ST elevation myocardial infarction (NSTEMI) with or without PCI; 4-ST elevation myocardial infarction (STEMI) with primary PCI. Groups 1, 2 and 4 were heparin naïve, allowing assessment of the effects of myocardial necrosis between baseline levels; group 3 had received low-molecular-weight heparin. MK levels were analysed by ELISA. Median MK at baseline did not differ between groups, demonstrating that myocardial ischaemia or necrosis does not affect MK levels. Heparin administration had an immediate effect on median MK at 10 min, showing an average 500-fold increase that is dose-dependent (R² = 0.35, p = 0.001). Median MK levels remained elevated at 20 min following heparin administration. Multivariate analysis showed that the estimated glomerular filtration rate (eGFR) was the only predictor of elevated baseline MK (p = 0.02). Baseline MK did not correlate with high-sensitivity troponin-I (HsTnI) taken just before CA (p = 0.97), or peak HsTnI during admission (p = 0.74). MK is not a reliable marker of myocardial ischaemia or necrosis. MK increased significantly in all patients following heparin administration in a dose-dependent manner.

Data Imputation in Merged Isobaric Labeling-Based Relative Quantification Datasets

The data-dependent acquisition in mass spectrometry-based proteomics combined with quantitative analysis using isobaric labeling (iTRAQ and TMT) inevitably introduces missing values in proteomic experiments where a number of LC-runs are combined, especially in the growing field of shotgun clinical proteomics, where the protein profiles from the proteomics analysis of several hundred patient samples are compared and correlated to clinical traits such as a specific disease or disease treatment in order to link specific outcomes to one or more proteins. In the context of clinical research it is evident that missing values in such datasets reduce the power of the downstream statistical analysis therefore may hampers the linking of the expression of disease traits to the expression of specific proteins that may be useful for prognostic, diagnostic, or predictive purposes. In our study, we tested three data imputation approaches initially developed for microarray data for the imputation of missing values in datasets that are generated by several runs of shotgun proteomic experiments and where the data were relative protein abundances based on isobaric tags (iTRAQ and TMT). Our conclusion is that imputation methods based on k Nearest Neighbors successfully impute missing values in datasets with up to 50% missing values.

Plasma CCN2 is independently related to subsequent need for abdominal aorta aneurysm repair

The objective of this study was to determine if plasma CCN2 is associated with abdominal aorta aneurysm (AAA), and future need for AAA repair, and further to assess the potential clinical value of CCN2 in predicting disease outcome. CCN2 was quantified in plasma samples obtained from a cohort of 679 men aged 65-74 at initial ultrasound screening for AAA in the Viborg Vascular (VIVA) screening trial. Plasma CCN2 was correlated with need for future surgical repair in the whole study population (HR = 1.457 (1.081-1.962), p = .013) and in the AAA group alone (HR = 1.431 (1.064-1.926), p = .018), yet the predictive value (CCN2 > 0 and <0 of 0.52 and 0.55, respectively) disqualified its use in clinically relevant AAA repair prediction. In conclusion, CCN2 is independently related to subsequent need for AAA repair, but has negligible predictive power for clinical use.