Plasma proteomic analysis reveals altered protein abundances in cardiovascular disease

Prediction of Clinically Significant Prostate Cancer by a Specific Collagen-related Transcriptome, Proteome, and Urinome Signature

BACKGROUND AND OBJECTIVE

While collagen density has been associated with poor outcomes in various cancers, its role in prostate cancer (PCa) remains elusive. Our aim was to analyze collagen-related transcriptomic, proteomic, and urinome alterations in the context of detection of clinically significant PCa (csPCa, International Society of Urological Pathology [ISUP] grade group ≥2).

METHODS

Comprehensive analyses for PCa transcriptome (n = 1393), proteome (n = 104), and urinome (n = 923) data sets focused on 55 collagen-related genes. Investigation of the cellular source of collagen-related transcripts via single-cell RNA sequencing was conducted. Statistical evaluations, clustering, and machine learning models were used for data analysis to identify csPCa signatures.

KEY FINDINGS AND LIMITATIONS

Differential expression of 30 of 55 collagen-related genes and 34 proteins was confirmed in csPCa in comparison to benign prostate tissue or ISUP 1 cancer. A collagen-high cancer cluster exhibited distinct cellular and molecular characteristics, including fibroblast and endothelial cell infiltration, intense extracellular matrix turnover, and enhanced growth factor and inflammatory signaling. Robust collagen-based machine learning models were established to identify csPCa. The models outcompeted prostate-specific antigen (PSA) and age, showing comparable performance to multiparametric magnetic resonance imaging (mpMRI) in predicting csPCa. Of note, the urinome-based collagen model identified four of five csPCa cases among patients with Prostate Imaging-Reporting and Data System (PI-IRADS) 3 lesions, for which the presence of csPCa is considered equivocal. The retrospective character of the study is a limitation.

CONCLUSIONS AND CLINICAL IMPLICATIONS

Collagen-related transcriptome, proteome, and urinome signatures exhibited superior accuracy in detecting csPCa in comparison to PSA and age. The collagen signatures, especially in cases of ambiguous lesions on mpMRI, successfully identified csPCa and could potentially reduce unnecessary biopsies. The urinome-based collagen signature represents a promising liquid biopsy tool that requires prospective evaluation to improve the potential of this collagen-based approach to enhance diagnostic precision in PCa for risk stratification and guiding personalized interventions.

PATIENT SUMMARY

In our study, collagen-related alterations in tissue, and urine were able to predict the presence of clinically significant prostate cancer at primary diagnosis.

Multimodal Analytical Tools to Enhance Mechanistic Understanding of Aortic Valve Calcification

This review focuses on technologies at the core of calcific aortic valve disease (CAVD) and drug target research advancement, including transcriptomics, proteomics, and molecular imaging. We examine how bulk RNA sequencing and single-cell RNA sequencing have engendered organismal genomes and transcriptomes, promoting the analysis of tissue gene expression profiles and cell subpopulations, respectively. We bring into focus how the field is also largely influenced by increasingly accessible proteome profiling techniques. In unison, global transcriptional and protein expression analyses allow for increased understanding of cellular behavior and pathogenic pathways under pathologic stimuli including stress, inflammation, low-density lipoprotein accumulation, increased calcium and phosphate levels, and vascular injury. We also look at how direct investigation of protein signatures paves the way for identification of targetable pathways for pharmacologic intervention. Here, we note that imaging techniques, once a clinical diagnostic tool for late-stage CAVD, have since been refined to address a clinical need to identify microcalcifications using positron emission tomography/computed tomography and even detect in vivo cellular events indicative of early stage CAVD and map the expression of identified proteins in animal models. Together, these techniques generate a holistic approach to CAVD investigation, with the potential to identify additional novel regulatory pathways.

Integrated untargeted and targeted proteomics to unveil plasma prognostic markers for patients with acute paraquat poisoning: A pilot study

Paraquat (PQ) is a widely used but strongly toxic herbicide, which can induce multiple organ failure. The overall survival rate of the poisoned patients was only 54.4% due to lack of specific antidotes. Besides, the definite pathogenic mechanism of PQ is still not fully understood. In this pilot study, untargeted and targeted proteomics were integrated to explore the expression characteristics of plasma protein in PQ poisoned patients, and identify the differentially expressed proteins between survivors and non-survivors. A total of 494 plasma proteins were detected, and of which 47 were upregulated and 44 were downregulated in PQ poisoned patients compared to healthy controls. Among them, five differential plasma proteins (S100A9, S100A8, MB, ACTB and RAB11FIP3) were further validated by multiple reaction monitoring (MRM)-based targeted proteomic approach, and three of them (S100A9, S100A8 and ACTB) were confirmed to be correlated with PQ poisoning. Meanwhile, 84 dysregulated plasma proteins were identified in non-survivors compared with survivors. Moreover, targeted proteomic and ROC analysis suggested that ACTB had a good performance in predicting the prognosis of PQ poisoned patients. These findings highlighted the value of label-free and mass spectrometry-based proteomics in screening prognostic biomarkers of PQ poisoning and studying the mechanism of PQ toxicity.

Searching for Atherosclerosis Biomarkers by Proteomics: A Focus on Lesion Pathogenesis and Vulnerability

Plaque rupture and thrombosis are the most important clinical complications in the pathogenesis of stroke, coronary arteries, and peripheral vascular diseases. The identification of early biomarkers of plaque presence and susceptibility to ulceration could be of primary importance in preventing such life-threatening events. With the improvement of proteomic tools, large-scale technologies have been proven valuable in attempting to unravel pathways of atherosclerotic degeneration and identifying new circulating markers to be utilized either as early diagnostic traits or as targets for new drug therapies. To address these issues, different matrices of human origin, such as vascular cells, arterial tissues, plasma, and urine, have been investigated. Besides, proteomics was also applied to experimental atherosclerosis in order to unveil significant insights into the mechanisms influencing atherogenesis. This narrative review provides an overview of the last twenty years of omics applications to the study of atherogenesis and lesion vulnerability, with particular emphasis on lipoproteomics and vascular tissue proteomics. Major issues of tissue analyses, such as plaque complexity, sampling, availability, choice of proper controls, and lipoproteins purification, will be raised, and future directions will be addressed.

Dietary Mg Supplementation Decreases Oxidative Stress, Inflammation, and Vascular Dysfunction in an Experimental Model of Metabolic Syndrome with Renal Failure

BACKGROUND

Metabolic syndrome (MetS) and chronic kidney disease (CKD) are commonly associated with cardiovascular disease (CVD) and in these patients Mg concentration is usually decreased. This study evaluated whether a dietary Mg supplementation might attenuate vascular dysfunction through the modulation of oxidative stress and inflammation in concurrent MetS and CKD.

METHODS

A rat model of MetS (Zucker strain) with CKD (5/6 nephrectomy, Nx) was used. Nephrectomized animals were fed a normal 0.1%Mg (MetS+Nx+Mg0.1%) or a supplemented 0.6%Mg (MetS+Nx+Mg0.6%) diet; Sham-operated rats with MetS receiving 0.1%Mg were used as controls.

RESULTS

As compared to controls, the MetS+Nx-Mg0.1% group showed a significant increase in oxidative stress and inflammation biomarkers (lipid peroxidation and aortic interleukin-1b and -6 expression) and Endothelin-1 levels, a decrease in nitric oxide and a worsening in uremia and MetS associated pathology as hypertension, and abnormal glucose and lipid profile. Moreover, proteomic evaluation revealed changes mainly related to lipid metabolism and CVD markers. By contrast, in the MetS+Nx+Mg0.6% group, these parameters remained largely similar to controls.

CONCLUSION

In concurrent MetS and CKD, dietary Mg supplementation reduced inflammation and oxidative stress and improved vascular function.

Identification of common sequence motifs shared exclusively among selectively packed exosomal pathogenic microRNAs during rickettsial infections

We previously reported that microRNA (miR)23a and miR30b are selectively sorted into rickettsia-infected, endothelial cell-derived exosomes ( R -ECExos). Yet, the mechanism remains unknown. The number of cases of spotted fever rickettsioses has been increasing in recent years, and infections with these bacteria cause life-threatening diseases by targeting brain and lung tissues. Therefore, the aim of the present study is to continue to dissect the molecular mechanism underlying R -ECExos-induced barrier dysfunction of normal recipient microvascular endothelial cells (MECs), depending on their exosomal RNA cargos. Rickettsiae are transmitted to human hosts by the bite of an infected tick into the skin. In the present study we demonstrate that treatment with R -ECExos, which were derived from spotted fever group R parkeri infected human dermal MECs, induced disruptions of the paracellular adherens junctional protein VE-cadherin and breached the paracellular barrier function in recipient pulmonary MECs (PMECs) in an exosomal RNA-dependent manner. Similarly, we did not detect different levels of miRs in parent dermal MECs following rickettsial infections. However, we demonstrated that the microvasculopathy-relevant miR23a-27a-24 cluster and miR30b are selectively enriched in R -ECExos. Bioinformatic analysis revealed that common sequence motifs are shared exclusively among the exosomal, selectively-enriched miR23a cluster and miR30b at different levels. Taken together, these data warrant further functional identification and characterization of a single, bipartition, or tripartition among ACA, UCA, and CAG motifs that guide recognition of microvasculopathy-relevant miR23a-27a-24 and miR30b, and subsequently results in their selective enrichments in R -ECExos.

Association between infections and functional somatic disorders: a cross-sectional population-based cohort study

OBJECTIVES

It has been suggested that infections can trigger functional somatic disorders (FSD). However, current evidence is limited by inconsistent findings in smaller studies conducted in clinical settings within selected populations and short follow-up times. We aimed to test the hypothesis that former infections are associated with FSD using data from nationwide registries and a large population-based cohort study, the Danish Study of Functional Disorders study.

DESIGN

FSD cases were identified in a cross-sectional population-based cohort and linked retrospectively to former hospital contacts with infections identified in the Danish National Patient Registry. The associations between FSD and former infections within 17 years were analysed using logistic regressions to calculate ORs and 95% CIs adjusted for age, sex and subjective social status.

SETTING

A population-based cohort in Denmark examined between 2011 and 2015.

PARTICIPANTS

A total of 9656 men and women aged 18-76 years.

MAIN OUTCOME MEASURES

FSD measured by various delimitations, including bodily distress syndrome (BDS), irritable bowel (IB), chronic fatigue (CF), chronic widespread pain (CWP), and multiple chemical sensitivity (MCS).

RESULTS

Overall, infections were associated with increased risk of all delimitations of FSD. The associations were more pronounced for multisystemic FSD. The number of prior infections increased the risk in a dose-response manner (p<0.0001). Bacterial but not viral infections were significantly associated with BDS (OR 1.69 (95% CI 1.46 to 1.96)), IB (OR 1.41 (95% CI 1.06 to 1.88)), CWP (OR 1.47 (95% CI 1.13 to 1.90)) and CF (OR 1.62 (95% CI 1.34 to 1.96)), but not MCS.

CONCLUSION

Former infections leading to hospital contacts were associated with a higher risk of having FSD. These associations were more pronounced for bacterial than viral infections, and more infections increased the risk in a dose-response manner. These results tend to support the idea that severe infections could play a role in FSD.

Cardioprotection by selective SGLT-2 inhibitors in a non-diabetic mouse model of myocardial ischemia/reperfusion injury: a class or a drug effect?

Major clinical trials with sodium glucose co-transporter-2 inhibitors (SGLT-2i) exhibit protective effects against heart failure events, whereas inconsistencies regarding the cardiovascular death outcomes are observed. Therefore, we aimed to compare the selective SGLT-2i empagliflozin (EMPA), dapagliflozin (DAPA) and ertugliflozin (ERTU) in terms of infarct size (IS) reduction and to reveal the cardioprotective mechanism in healthy non-diabetic mice. C57BL/6 mice randomly received vehicle, EMPA (10 mg/kg/day) and DAPA or ERTU orally at the stoichiometrically equivalent dose (SED) for 7 days. 24 h-glucose urinary excretion was determined to verify SGLT-2 inhibition. IS of the region at risk was measured after 30 min ischemia (I), and 120 min reperfusion (R). In a second series, the ischemic myocardium was collected (10th min of R) for shotgun proteomics and evaluation of the cardioprotective signaling. In a third series, we evaluated the oxidative phosphorylation capacity (OXPHOS) and the mitochondrial fatty acid oxidation capacity by measuring the respiratory rates. Finally, Stattic, the STAT-3 inhibitor and wortmannin were administered in both EMPA and DAPA groups to establish causal relationships in the mechanism of protection. EMPA, DAPA and ERTU at the SED led to similar SGLT-2 inhibition as inferred by the significant increase in glucose excretion. EMPA and DAPA but not ERTU reduced IS. EMPA preserved mitochondrial functionality in complex I&II linked oxidative phosphorylation. EMPA and DAPA treatment led to NF-kB, RISK, STAT-3 activation and the downstream apoptosis reduction coinciding with IS reduction. Stattic and wortmannin attenuated the cardioprotection afforded by EMPA and DAPA. Among several upstream mediators, fibroblast growth factor-2 (FGF-2) and caveolin-3 were increased by EMPA and DAPA treatment. ERTU reduced IS only when given at the double dose of the SED (20 mg/kg/day). Short-term EMPA and DAPA, but not ERTU administration at the SED reduce IS in healthy non-diabetic mice. Cardioprotection is not correlated to SGLT-2 inhibition, is STAT-3 and PI3K dependent and associated with increased FGF-2 and Cav-3 expression.

The Implant Proteome—The Right Surgical Glue to Fix Titanium Implants In Situ

Titanium implants are frequently applied to the bone in orthopedic and trauma surgery. Although these biomaterials are characterized by excellent implant survivorship and clinical outcomes, there are almost no data available on the initial protein layer binding to the implant surface in situ. This study aims to investigate the composition of the initial protein layer on endoprosthetic surfaces as a key initiating step in osseointegration. In patients qualified for total hip arthroplasty, the implants are inserted into the femoral canal, fixed and subsequently explanted after 2 and 5 min. The proteins adsorbed to the surface (the implant proteome) are analyzed by liquid chromatography–tandem mass spectrometry (LC-MS/MS). A statistical analysis of the proteins’ alteration with longer incubation times reveals a slight change in their abundance according to the Vroman effect. The pathways involved in the extracellular matrix organization of bone, sterile inflammation and the beginning of an immunogenic response governed by neutrophils are significantly enriched based on the analysis of the implant proteome. Those are generally not changed with longer incubation times. In summary, proteins relevant for osseointegration are already adsorbed within 2 min in situ. A deeper understanding of the in situ protein–implant interactions in patients may contribute to optimizing implant surfaces in orthopedic and trauma surgery.

Evaluating the detection ability of a range of epistasis detection methods on simulated data for pure and impure epistatic models

Background

Numerous approaches have been proposed for the detection of epistatic interactions within GWAS datasets in order to better understand the drivers of disease and genetics.

Methods

A selection of state-of-the-art approaches were assessed. These included the statistical tests, fast-epistasis, BOOST, logistic regression and wtest; swarm intelligence methods, namely AntEpiSeeker, epiACO and CINOEDV; and data mining approaches, including MDR, GSS, SNPRuler and MPI3SNP. Data were simulated to provide randomly generated models with no individual main effects at different heritabilities (pure epistasis) as well as models based on penetrance tables with some main effects (impure epistasis). Detection of both two and three locus interactions were assessed across a total of 1,560 simulated datasets. The different methods were also applied to a section of the UK biobank cohort for Atrial Fibrillation.

Results

For pure, two locus interactions, PLINK’s implementation of BOOST recovered the highest number of correct interactions, with 53.9% and significantly better performing than the other methods (p = 4.52e − 36). For impure two locus interactions, MDR exhibited the best performance, recovering 62.2% of the most significant impure epistatic interactions (p = 6.31e − 90 for all but one test). The assessment of three locus interaction prediction revealed that wtest recovered the highest number (17.2%) of pure epistatic interactions(p = 8.49e − 14). wtest also recovered the highest number of three locus impure epistatic interactions (p = 6.76e − 48) while AntEpiSeeker ranked as the most significant the highest number of such interactions (40.5%). Finally, when applied to a real dataset for Atrial Fibrillation, most notably finding an interaction between SYNE2 and DTNB.

Quantitative proteomics reveal three potential biomarkers for risk assessment of acute myocardial infarction

Acute myocardial infarction (AMI) is the one of the main cause of death worldwide. Exosomes carry important information about intercellular communication and could be diagnostic marker for many diseases. Here, we aimed to find potential key proteins for the early diagnosis of AMI. A label free proteomics strategy was used to identify the differentially expressed proteins (DEPs) of AMI patients’ plasma exosome. By bioinformatics analysis and enzyme-linked immunosorbent assay to validate the candidate proteins. Compared to healthy control plasma exosome, we totally identified 72 differentially expressed proteins (DEPs) in AMI patients. Also, we found that complement and coagulation cascades was activated by KEGG analysis and GSEA. PLG, C8B and F2 were selected as candidate molecules for further study, and then validated another 40 plasma samples using enzyme-linked immunosorbent assay. Finally, we found that the expression levels of these three proteins (PLG, C8B and F2) were significantly higher than those of healthy controls (P < 0.05). ROC analysis revealed that PLG, C8B and F2 had potential value for AMI early diagnosis. In conclusion, our study identified three potential biomarkers for AMI diagnosis. But there remains a need to further study the mechanism of the biomarkers.

Co-expression gene network analysis reveals novel regulatory pathways involved in porto-sinusoidal vascular disease

BACKGROUND & AIMS

Porto-sinusoidal vascular disease (PSVD) is a rare vascular liver disease of unknown etiology that causes portal hypertension. It usually affects young individuals and shortens live expectancy. The deregulated pathways involved in PSVD development are unknown and therefore we lack curative treatments. The purpose of this study was to integrate transcriptomic and clinical data by comprehensive network-based modeling in order to uncover altered biological processes in patients with PSVD.

METHODS

We obtained liver tissue samples from 20 consecutive patients with PSVD and 21 sex- and age-matched patients with cirrhosis and 13 histologically normal livers (HNL) (initial cohort) and performed transcriptomic analysis. Microarray data were analyzed using weighted gene correlation network analysis to identify clusters of highly correlated genes differently expressed in patients with PSVD. We next evaluated the molecular pathways enriched in patients with PSVD and the core-related genes from the most significantly enriched pathways in patients with PSVD. Our main findings were validated using RNA sequencing in a different cohort of PSVD, cirrhosis and HNL (n = 8 for each group).

RESULTS

Patients with PSVD have a distinctive genetic profile enriched mainly in canonical pathways involving hemostasis and coagulation but also lipid metabolism and oxidative phosphorylation. Serpin family (SERPINC1), the apolipoproteins (APOA, APOB, APOC), ATP synthases (ATP5G1, ATP5B), fibrinogen genes (FGB, FGA) and alpha-2-macroglobulin were identified as highly connective genes that may have an important role in PSVD pathogenesis.

CONCLUSION

PSVD has a unique transcriptomic profile and we have identified deregulation of pathways involved in vascular homeostasis as the main pathogenic event of disease development.

LAY SUMMARY

Porto-sinusoidal vascular disease is a rare but life-shortening disease that affects mainly young people. Knowledge of the disrupted pathways involved in its development will help to identify novel therapeutic targets and new treatments. Using a systems biology approach, we identify that pathways regulating endothelial function and tone may act as drivers of porto-sinusoidal vascular disease.

Apolipoprotein Signature of HDL and LDL from Atherosclerotic Patients in Relation with Carotid Plaque Typology: A Preliminary Report

In the past years, it has become increasingly clear that the protein cargo of the different lipoprotein classes is largely responsible for carrying out their various functions, also in relation to pathological conditions, including atherosclerosis. Accordingly, detailed information about their apolipoprotein composition and structure may contribute to the revelation of their role in atherogenesis and the understanding of the mechanisms that lead to atherosclerotic degeneration and toward vulnerable plaque formation. With this aim, shotgun proteomics was applied to identify the apolipoprotein signatures of both high-density and low-density lipoproteins (HDL and LDL) plasma fractions purified from healthy volunteers and atherosclerotic patients with different plaque typologies who underwent carotid endarterectomy. By this approach, two proteins with potential implications in inflammatory, immune, and hemostatic pathways, namely, integrin beta-2 (P05107) and secretoglobin family 3A member 2 (Q96PL1), have been confirmed to belong to the HDL proteome. Similarly, the list of LDL-associated proteins has been enriched with 21 proteins involved in complement and coagulation cascades and the acute-phase response, which potentially double the protein species of LDL cargo. Moreover, differential expression analysis has shown protein signatures specific for patients with “hard” or “soft” plaques.

Role of extracellular vesicle derived biomarkers in drug metabolism and disposition

Extracellular vesicles (EVs) are small, non-replicating, lipid encapsulated particles that contain a myriad of protein and nucleic acid cargo derived from their tissue of origin. The potential role of EV derived biomarkers to the study of drug metabolism and disposition (DMD) has gained attention in recent years. The key trait that makes EVs an attractive biomarker source is their capacity to provide comparable insights to solid organ biopsy through an appreciably less invasive collection procedure. Blood-derived EVs exist as a heterogenous milieu of biologically distinct particles originating from different sources through different biogenesis pathways. Furthermore, blood (plasma and serum) contains an array of vesicular and non-vesicular contaminants such as apoptotic bodies, plasma proteins and lipoproteins that are routinely co-isolated with EVs albeit to a different extent depending on the isolation technique. The following mini-review summarises current studies reporting DMD biomarkers and addresses elements of EV isolation and quantification relevant to the application of EV derived DMD biomarkers. Evidence based best practice guidance aligned to Minimum Information for the Study of Extracellular Vesicles (MISEV) and EV Track reporting standards are summarised in the context of DMD studies. Significance Statement Extracellular vesicle (EV) derived protein and nucleic acid cargo represent a potentially game changing source of novel DMD biomarkers with the capacity to define within- and between- individual variability in drug exposure irrespective of aetiology. However, robust translation of EV-derived biomarkers requires the generation of transparent reproducible evidence. This review outlines the critical elements of data generation and reporting relevant to achieving this evidence in a drug metabolism and disposition context.

Anti-PD-1 elicits regression of undifferentiated pleomorphic sarcomas with UV-mutation signatures

Undifferentiated pleomorphic sarcoma (UPS), an aggressive soft-tissue sarcoma of adults, has been characterized by low tumor mutational burden (TMB) and high copy number alterations. Clinical trials of programmed death-1 (PD-1) blockade in UPS have reported widely varying efficacy. We describe two patients with recurrent scalp UPS that experienced clinical benefit from PD-1 blockade. These tumors had high TMB with a UV-induced mutational pattern. Analysis of additional head and neck UPS cases identified five out of seven tumors with high TMB and an ultraviolet (UV) mutational signature. Head and neck UPS tumors also had increased programmed death-ligand 1 (PD-L1) expression and CD8+ T cell infiltration as compared with UPS tumors arising from other sites. In summary, we found that UPS tumors of the head and neck, but not elsewhere, have a PD-L1+, T-cell-inflamed tumor microenvironment and high TMB, suggesting that these tumors represent a distinct genetic subgroup of UPS for which immune checkpoint inhibitor therapy might be effective.

Mining the Biomarker Potential of the Urine Peptidome: From Amino Acids Properties to Proteases

Native biofluid peptides offer important information about diseases, holding promise as biomarkers. Particularly, the non-invasive nature of urine sampling, and its high peptide concentration, make urine peptidomics a useful strategy to study the pathogenesis of renal conditions. Moreover, the high number of detectable peptides as well as their specificity set the ground for the expansion of urine peptidomics to the identification of surrogate biomarkers for extra-renal diseases. Peptidomics further allows the prediction of proteases (degradomics), frequently dysregulated in disease, providing a complimentary source of information on disease pathogenesis and biomarkers. Then, what does urine peptidomics tell us so far? In this paper, we appraise the value of urine peptidomics in biomarker research through a comprehensive analysis of all datasets available to date. We have mined > 50 papers, addressing > 30 different conditions, comprising > 4700 unique peptides. Bioinformatic tools were used to reanalyze peptide profiles aiming at identifying disease fingerprints, to uncover hidden disease-specific peptides physicochemical properties and to predict the most active proteases associated with their generation. The molecular patterns found in this study may be further validated in the future as disease biomarker not only for kidney diseases but also for extra-renal conditions, as a step forward towards the implementation of a paradigm of predictive, preventive and personalized (3P) medicine.

Quantitative proteomic analysis to identify differentially expressed proteins in patients with epilepsy

There is a great need for biomarkers in epilepsy, particularly markers of epileptogenesis. A first seizure will lead to epilepsy in 20-45 % of cases, but biomarkers that can identify these individuals are missing. The purpose of this study was to identify potential biomarkers of epilepsy/epileptogenesis in a cohort of adults with new-onset seizures, using quantitative proteomic analysis. Plasma was collected from 55 adults with new-onset seizures and sufficient follow-up to identify epilepsy. After a follow up period of two years, 63.6 % of the cohort had a diagnosis of epilepsy, whereas 36.4 % of patients only had a single seizure. Plasma proteins were extracted and labelled with tandem mass tags, then analyzed using mass spectrometry approach. Proteins that were up- or downregulated by ≥20 % and with a p-value of <0.05 were considered as differentially expressed and were also annotated to their processes and pathways. Several proteins were differentially expressed in the epilepsy group compared to controls. A total of 1075 proteins were detected, out of which 41 proteins were found to be significantly dysregulated in epilepsy patients. Many of these have been identified in experimental studies of epilepogenesis. We report plasma proteome profiling in new-onset epilepsy in a pilot study with 55 individuals. The identified proteins could be involved in pathways associated with epileptogenesis. The results should be seen as hypothesis-generating and targeted, confirmatory studies are needed.

Proteomic Profiling of Leukocytes Reveals Dysregulation of Adhesion and Integrin Proteins in Chronic Kidney Disease-Related Atherosclerosis

A progressive loss of functional nephrons defines chronic kidney disease (CKD). Complications related to cardiovascular disease (CVD) are the principal causes of mortality in CKD; however, the acceleration of CVD in CKD remains unresolved. Our study used a complementary proteomic approach to assess mild and advanced CKD patients with different atherosclerosis stages and two groups of patients with different classical CVD progression but without renal dysfunction. We utilized a label-free approach based on LC-MS/MS and functional bioinformatic analyses to profile CKD and CVD leukocyte proteins. We revealed dysregulation of proteins involved in different phases of leukocytes' diapedesis process that is very pronounced in CKD's advanced stage. We also showed an upregulation of apoptosis-related proteins in CKD as compared to CVD. The differential abundance of selected proteins was validated by multiple reaction monitoring, ELISA, Western blotting, and at the mRNA level by ddPCR. An increased rate of apoptosis was then functionally confirmed on the cellular level. Hence, we suggest that the disturbances in leukocyte extravasation proteins may alter cell integrity and trigger cell death, as demonstrated by flow cytometry and microscopy analyses. Our proteomics data set has been deposited to the ProteomeXchange Consortium via the PRIDE repository with the data set identifier PXD018596.

Platelet biomarkers for a descending cognitive function: A proteomic approach

Memory loss is the most common clinical sign in Alzheimer's disease (AD); thus, searching for peripheral biomarkers to predict cognitive decline is promising for early diagnosis of AD. As platelets share similarities to neuron biology, it may serve as a peripheral matrix for biomarkers of neurological disorders. Here, we conducted a comprehensive and in-depth platelet proteomic analysis using TMT-LC-MS/MS in the populations with mild cognitive impairment (MCI, MMSE = 18-23), severe cognitive impairments (AD, MMSE = 2-17), and the age-/sex-matched normal cognition controls (MMSE = 29-30). A total of 360 differential proteins were detected in MCI and AD patients compared with the controls. These differential proteins were involved in multiple KEGG pathways, including AD, AMP-activated protein kinase (AMPK) pathway, telomerase RNA localization, platelet activation, and complement activation. By correlation analysis with MMSE score, three positively correlated pathways and two negatively correlated pathways were identified to be closely related to cognitive decline in MCI and AD patients. Partial least squares discriminant analysis (PLS-DA) showed that changes of nine proteins, including PHB, UQCRH, CD63, GP1BA, FINC, RAP1A, ITPR1/2, and ADAM10 could effectively distinguish the cognitively impaired patients from the controls. Further machine learning analysis revealed that a combination of four decreased platelet proteins, that is, PHB, UQCRH, GP1BA, and FINC, was most promising for predicting cognitive decline in MCI and AD patients. Taken together, our data provide a set of platelet biomarkers for predicting cognitive decline which may be applied for the early screening of AD.

Identification of Breast Cancer Subtype-Specific Biomarkers by Integrating Copy Number Alterations and Gene Expression Profiles

Background and Objectives: Breast cancer is a heterogeneous disease categorized into four subtypes. Previous studies have shown that copy number alterations of several genes are implicated with the development and progression of many cancers. This study evaluates the effects of DNA copy number alterations on gene expression levels in different breast cancer subtypes. Materials and Methods: We performed a computational analysis integrating copy number alterations and gene expression profiles in 1024 breast cancer samples grouped into four molecular subtypes: luminal A, luminal B, HER2, and basal. Results: Our analyses identified several genes correlated in all subtypes such as KIAA1967 and MCPH1. In addition, several subtype-specific genes that showed a significant correlation between copy number and gene expression profiles were detected: SMARCB1, AZIN1, MTDH in luminal A, PPP2R5E, APEX1, GCN5 in luminal B, TNFAIP1, PCYT2, DIABLO in HER2, and FAM175B, SENP5, SCAF1 in basal subtype. Conclusions: This study showed that computational analyses integrating copy number and gene expression can contribute to unveil the molecular mechanisms of cancer and identify new subtype-specific biomarkers.

Chronic Empagliflozin Treatment Reduces Myocardial Infarct Size in Nondiabetic Mice Through STAT-3-Mediated Protection on Microvascular Endothelial Cells and Reduction of Oxidative Stress

Aims: Empagliflozin (EMPA) demonstrates cardioprotective effects on diabetic myocardium but its infarct-sparing effects in normoglycemia remain unspecified. We investigated the acute and chronic effect of EMPA on infarct size after ischemia-reperfusion (I/R) injury and the mechanisms of cardioprotection in nondiabetic mice. Results: Chronic oral administration of EMPA (6 weeks) reduced myocardial infarct size after 30 min/2 h I/R (26.5% ± 3.9% vs 45.8% ± 3.3% in the control group, p < 0.01). Body weight, blood pressure, glucose levels, and cardiac function remained unchanged between groups. Acute administration of EMPA 24 or 4 h before I/R did not affect infarct size. Chronic EMPA treatment led to a significant reduction of oxidative stress biomarkers. STAT-3 (signal transducer and activator of transcription 3) was activated by Y(705) phosphorylation at the 10th minute of R, but it remained unchanged at 2 h of R and in the acute administration protocols. Proteomic analysis was employed to investigate signaling intermediates and revealed that chronic EMPA treatment regulates several pathways at reperfusion, including oxidative stress and integrin-related proteins that were further evaluated. Superoxide dismutase and vascular endothelial growth factor were increased throughout reperfusion. EMPA pretreatment (24 h) increased the viability of human microvascular endothelial cells in normoxia and on 3 h hypoxia/1 h reoxygenation and reduced reactive oxygen species production. In EMPA-treated murine hearts, CD31-/VEGFR2-positive endothelial cells and the pSTAT-3(Y705) signal derived from endothelial cells were boosted at early reperfusion. Innovation: Chronic EMPA administration reduces infarct size in healthy mice via the STAT-3 pathway and increases the survival of endothelial cells. Conclusion: Chronic but not acute administration of EMPA reduces infarct size through STAT-3 activation independently of diabetes mellitus.

Pathological cardiac remodeling seen by the eyes of proteomics

Cardiac remodeling involves cellular and structural changes that occur as consequence of multifactorial events to maintain the homeostasis. The progression of pathological cardiac remodeling involves a transition from adaptive to maladaptive changes that eventually leads to impairment of ventricular function and heart failure. In this scenario, proteins are key elements that orchestrate molecular events as increased expression of fetal genes, neurohormonal and second messengers' activation, contractile dysfunction, rearrangement of the extracellular matrix and alterations in heart geometry. Mass spectrometry based-proteomics has emerged as a sound method to study protein dysregulation and identification of cardiac diseases biomarkers in plasma. In this review, we summarize the main findings related to large-scale proteome modulation of cardiac cells and extracellular matrix occurred during pathological cardiac remodeling. We describe the recent proteomic progresses in the selection of protein targets and introduce the renin-angiotensin system as an interesting target for the treatment of pathological cardiac remodeling.

Plasma Proteome Profiling of Coronary Artery Disease Patients: Downregulation of Transthyretin-An Important Event

Coronary artery disease (CAD) is a prevalent chronic inflammatory cardiac disorder. An early diagnosis is likely to help in the prevention and proper management of this disease. As the study of proteomics provides the potential markers for detection of a disease, in the present investigation, attempt has been made to identify disease-associated differential proteins involved in CAD pathogenesis. For this study, a total of 200 selected CAD patients were considered, who were recruited for percutaneous coronary intervention (PCI) treatment. The proteomic analysis was performed using two-dimensional gel electrophoresis (2-DE) and MALDI-TOF MS/MS. Samples were also subjected to Western blot analysis, enzyme-linked immunosorbent assay (ELISA), peripheral blood mononuclear cells isolation immunofluorescence (IF) analysis, analytical screening by fluorescence-activated cell sorting (FACS), and in silico analysis. The representative data were shown as mean ± SD of at least three experiments. A total of 19 proteins were identified. Among them, the most abundant five proteins (serotransferrin, talin-1, alpha-2HS glycoprotein, transthyretin (TTR), fibrinogen-α chain) were found to have altered level in CAD. Serotransferrin, talin-1, alpha-2HS glycoprotein, and transthyretin (TTR) were found to have lower level, whereas fibrinogen-α chain was found to have higher level in CAD plasma compared to healthy, confirmed by Western blot analysis. TTR, an important acute phase transport protein, was validated low level in 200 CAD patients who confirmed to undergo PCI treatment. Further, in silico and in vitro studies of TTR indicated a downexpression of CAD in plasma as compared to the plasma of healthy individuals. Lower level of plasma TTR was determined to be an important risk marker in the atherosclerotic-approved CAD patients. We suggest that the TTR lower level predicts disease severity and hence may serve as an important marker tool for CAD screening. However, further large-scale studies are required to determine the clinical significance of TTR.

Genome Wide Epistasis Study of On-Statin Cardiovascular Events with Iterative Feature Reduction and Selection

Predicting risk for major adverse cardiovascular events (MACE) is an evidence-based practice that incorporates lifestyle, history, and other risk factors. Statins reduce risk for MACE by decreasing lipids, but it is difficult to stratify risk following initiation of a statin. Genetic risk determinants for on-statin MACE are low-effect size and impossible to generalize. Our objective was to determine high-level epistatic risk factors for on-statin MACE with GWAS-scale data. Controlled-access data for 5890 subjects taking a statin collected from Vanderbilt University Medical Center's BioVU were obtained from dbGaP. We used Random Forest Iterative Feature Reduction and Selection (RF-IFRS) to select highly informative genetic and environmental features from a GWAS-scale dataset of patients taking statin medications. Variant-pairs were distilled into overlapping networks and assembled into individual decision trees to provide an interpretable set of variants and associated risk. 1718 cases who suffered MACE and 4172 controls were obtained from dbGaP. Pathway analysis showed that variants in genes related to vasculogenesis (FDR = 0.024), angiogenesis (FDR = 0.019), and carotid artery disease (FDR = 0.034) were related to risk for on-statin MACE. We identified six gene-variant networks that predicted odds of on-statin MACE. The most elevated risk was found in a small subset of patients carrying variants in COL4A2, TMEM178B, SZT2, and TBXAS1 (OR = 4.53, p < 0.001). The RF-IFRS method is a viable method for interpreting complex "black-box" findings from machine-learning. In this study, it identified epistatic networks that could be applied to risk estimation for on-statin MACE. Further study will seek to replicate these findings in other populations.

Exploratory analysis of large-scale lipidome in large cohorts: are we any closer of finding lipid-based markers suitable for CVD risk stratification and management?

Cardiovascular diseases (CVD) remain the biggest cause of deaths worldwide and a major socio-economic impact to society. In this work, we conducted an unbiased exploratory analysis of the large-scale lipidome in human plasma samples from patients with fatal and non-fatal CVD from large cohorts. The exploratory analysis included data from 10,349 individuals from 20 countries in Asia, Australasia, Europe and North America (ADVANCE cohort), and thus representative of the worldwide population. Through the analysis of hazard ratios (HR), we found 306 lipids relevant in CV Death and 294 lipids relevant in CV Events of which 262 lipids were common to fatal and non-fatal events followed over time (3, 5 and 8 years). Our exploratory analysis reveals that, over time, the plasma lipid signature found in non-fatal CVD events is similar to that preceding CVD death. Among the common lipid signature, we found that sphingolipids (HexCer, SM, Cer and other glycosphingolipids) and phospholipids (PC and PE) were strongly associated with CVD events outcome, while polyunsaturated plasmenyl PC and PE lipids were inversely associated with CV outcome. The restricted panel of specific lipids has the potential to improve CVD risk stratification and management, and significantly reduce the time involved in the analysis and data treatment in low-resolution MS instruments making plasma lipidomics a cost-efficient approach for clinical scenario. In our view, once standardized clinical, analytical and data reporting guidelines are implemented worldwide, lipid-based discriminators can be routinely applied in the CVD risk stratification and improve the performance of current clinical, biochemical and imaging diagnostic tools assisting the decision-making process particularly in patients with multiple co-morbidities.

Big Data Approaches in Heart Failure Research

PURPOSE OF REVIEW

The goal of this review is to summarize the state of big data analyses in the study of heart failure (HF). We discuss the use of big data in the HF space, focusing on "omics" and clinical data. We address some limitations of this data, as well as their future potential.

RECENT FINDINGS

Omics are providing insight into plasmal and myocardial molecular profiles in HF patients. The introduction of single cell and spatial technologies is a major advance that will reshape our understanding of cell heterogeneity and function as well as tissue architecture. Clinical data analysis focuses on HF phenotyping and prognostic modeling. Big data approaches are increasingly common in HF research. The use of methods designed for big data, such as machine learning, may help elucidate the biology underlying HF. However, important challenges remain in the translation of this knowledge into improvements in clinical care.

Molecular Changes in Tissue Proteome during Prostate Cancer Development: Proof-of-Principle Investigation

(1) Background: Prostate cancer (PCa) is characterized by high heterogeneity. The aim of this study was to investigate molecular alterations underlying PCa development based on proteomics data. (2) Methods: Liquid chromatography coupled to tandem mass spectrometry was conducted for 22 fresh-frozen tissue specimens from patients with benign prostatic hyperplasia (BPH, n = 5) and PCa (n = 17). Mann Whitney test was used to define significant differences between the two groups. Association of protein abundance with PCa progression was evaluated using Spearman correlation, followed by verification through investigating the Prostate Cancer Transcriptome Atlas. Functional enrichment and interactome analysis were carried out using Metascape and String. (3) Results: Proteomics analysis identified 1433 proteins, including 145 proteins as differentially abundant between patients with PCa and BPH. In silico analysis revealed alterations in several pathways and hallmarks implicated in metabolism and signalling, represented by 67 proteins. Among the latter, 21 proteins were correlated with PCa progression at both the protein and mRNA levels. Interactome analysis of these 21 proteins predicted interactions between Myc proto-oncogene (MYC) targets, protein processing in the endoplasmic reticulum, and oxidative phosphorylation, with MYC targets having a central role. (4) Conclusions: Tissue proteomics allowed for characterization of proteins and pathways consistently affected during PCa development. Further validation of these findings is required.

Proteomic analysis detects deregulated reverse cholesterol transport in human subjects with ST-segment elevation myocardial infarction

Reverse cholesterol transport (RCT) plays a critical role in removing cholesterol from the arterial wall. However, very few reports directly relate chronic inflammation and RCT with atherosclerosis. The present study was undertaken to investigate clinical implications of significantly altered circulating proteins in subjects with ST-segment elevation myocardial infarction (STEMI) in the manifestation of atherosclerotic events. Using a case-control design, more than 2500 proteins in both STEMI and healthy control subjects were identified by Orbitrap mass spectrometer. Quantitative proteomics study revealed downregulation of 26 proteins while expression of 38 proteins increased significantly in STEMI subjects compared to healthy controls. Pathway enrichment analyses indicated that most of the identified proteins were related to chronic inflammation, atherosclerosis, and RCT. Altered proteins such as AZGP1, ABCA5, Calicin, PGLYRP2, HAVCR2 and C17ORF57 were further validated by Western blotting analysis of human plasma. Pathophysiological significance was studied using macrophage derived foam cell for their critical role in RCT which indicated the imbalance of RCT via the interaction of AZGP1 with CD36. In summary, this study revealed a unique relationship of some novel proteins apparently responsible for impaired RCT and chronic inflammation leading to atherothrombosis and myocardial infarction. SIGNIFICANCE: In the present study we identified ≥2500 unique circulating proteins in healthy control and clinically diagnosed STEMI subjects among which 423 proteins were found to be common in both the groups. We further show 64 proteins significantly different between healthy control and STEMI subjects. Proteomic analyses reveal a panel of proteins associated with atherosclerosis and STEMI. One of the proteins, AZGP1, an adipokine, is likely to act as the missing link between chronic inflammation and cholesterol transport. Deregulation of reverse cholesterol transport might be orchestrated by AZGP1, CD36, ABCA5, and PPARɣ in STEMI subjects. The present study employs shotgun and quantitative proteomics followed by in vitro validations demonstrating a biochemical basis for reverse cholesterol transport in the local milieu of the luminal wall of the artery which are critical for plaque build-up and atherosclerosis.

Blood Viscoelasticity Measurement Using Interface Variations in Coflowing Streams under Pulsatile Blood Flows

Blood flows in microcirculation are determined by the mechanical properties of blood samples, which have been used to screen the status or progress of diseases. To achieve this, it is necessary to measure the viscoelasticity of blood samples under a pulsatile blood condition. In this study, viscoelasticity measurement is demonstrated by quantifying interface variations in coflowing streams. To demonstrate the present method, a T-shaped microfluidic device is designed to have two inlets (a, b), one outlet (a), two guiding channels (blood sample channel, reference fluid channel), and one coflowing channel. Two syringe pumps are employed to infuse a blood sample at a sinusoidal flow rate. The reference fluid is supplied at a constant flow rate. Using a discrete fluidic circuit model, a first-order linear differential equation for the interface is derived by including two approximate factors (F₁ = 1.094, F₂ = 1.1087). The viscosity and compliance are derived analytically as viscoelasticity. The experimental results showed that compliance is influenced substantially by the period. The hematocrit and diluent contributed to the varying viscosity and compliance. The viscoelasticity varied substantially for red blood cells fixed with higher concentrations of glutaraldehyde solution. The experimental results showed that the present method has the ability to monitor the viscoelasticity of blood samples under a sinusoidal flow-rate pattern.

Systems biology identifies cytosolic PLA2 as a target in vascular calcification treatment

Although cardiovascular disease (CVD) is the leading cause of morbimortality worldwide, promising new drug candidates are lacking. We compared the arterial high-resolution proteome of patients with advanced versus early-stage CVD to predict, from a library of small bioactive molecules, drug candidates able to reverse this disease signature. Of the approximately 4000 identified proteins, 100 proteins were upregulated and 52 were downregulated in advanced-stage CVD. Arachidonyl trifluoromethyl ketone (AACOCF3), a cytosolic phospholipase A2 (cPLA2) inhibitor was predicted as the top drug able to reverse the advanced-stage CVD signature. Vascular cPLA2 expression was increased in patients with advanced-stage CVD. Treatment with AACOCF3 significantly reduced vascular calcification in a cholecalciferol-overload mouse model and inhibited osteoinductive signaling in vivo and in vitro in human aortic smooth muscle cells. In conclusion, using a systems biology approach, we have identified a potentially new compound that prevented typical vascular calcification in CVD in vivo. Apart from the clear effect of this approach in CVD, such strategy should also be able to generate novel drug candidates in other complex diseases.

Intrasurgical Protein Layer on Titanium Arthroplasty Explants: From the Big Twelve to the Implant Proteome

PURPOSE

Aseptic loosening in total joint replacement due to insufficient osteointegration is an unsolved problem in orthopaedics. The purpose of the study is to obtain a picture of the initial protein adsorption layer on femoral endoprosthetic surfaces as the key to the initiation of osseointegration.

EXPERIMENTAL DESIGN

The paper describes the first study of femoral stem explants from patients for proteome analysis of the primary protein layer. After 2 min in situ, the stems are explanted and frozen in liquid nitrogen. Proteins are eluted under reducing conditions and analyzed by LC-MS/MS.

RESULTS

After exclusion of proteins identified by a single peptide, the implant proteome is found to consist of 2802 unique proteins. Of these, 77% are of intracellular origin, 9% are derived from the plasma proteome, 8% from the bone proteome, and four proteins with highest specificity score could be assigned to the bone marrow proteome (transcriptome). The most abundant protein in the adsorbed total protein layer is hemoglobin (8-11%) followed by serum albumin (3.6-6%).

CONCLUSIONS

A detailed knowledge of the initial protein film deposited onto the implants, as demonstrated here for the first time, may help to understand and predict the response of the osseous microenvironment to implant surfaces.

Proteomics based identification of KDM5 histone demethylases associated with cardiovascular disease

Background

The increased prevalence of cardiovascular disease (CVD) indicates a demand for novel therapeutic approaches. Proteome analysis of vascular tissues from animal models and humans with CVD could lead to the identification of novel druggable targets.

Methods

LC-MS/MS analysis of thoracic aortas from three mouse models of non-diabetic and diabetic (streptozotocin (STZ)-induced) atherosclerosis followed by bioinformatics/pathway analysis was performed. Selected findings were confirmed by proteomics analysis of human vessels from patients with CVD as well as in vitro studies (migration, proliferation, angiogenesis assays) using endothelial (HUVEC) cells.

Findings

Comparative tissue proteomics of low density lipoprotein receptor deficient (Ldlr−/−) and diabetic Ldlr−/− (Ldlr−/−STZ) with wild type (WT) animals led to the identification of 284 differentially expressed proteins in both models. Among them, 177 proteins were also differentially expressed in diabetic apolipoprotein E deficient (ApoE−/−STZ) mice, suggesting expression changes associated with atherosclerosis independent of the model used. These proteins recapitulated the hallmarks of atherosclerosis. Comparison of these findings with differentially expressed proteins in human vessels with CVD enabled shortlisting of six commonly dysregulated proteins. Among them, lysine-specific demethylase 5D (KDM5D) exhibited pronounced overexpression accompanied by a reduction in the protein levels of its substrate, the trimethylated lysine 4 of histone H3 (H3K4me3), in patients with CVD. Functional interference studies applying a KDM5 inhibitor on HUVEC reduced cell proliferation, migration and tube-forming ability in vitro.

Interpretation

This high-throughput proteomics strategy identified KDM5 histone demethylases being potentially involved in CVD, possibly by affecting H3K4 methylation.

Fund

[SysVasc, HEALTH-2013 603288], [ERA-CVD PROACT: ANR-17-ECVD-0006, 01KL1805], [FRM, DEQ20170336759].