Nonstationary Gaussian Process Discriminant Analysis With Variable Selection for High-Dimensional Functional Data

High-dimensional classification and feature selection tasks are ubiquitous with the recent advancement in data acquisition technology. In several application areas such as biology, genomics, and proteomics, the data are often functional in their nature and exhibit a degree of roughness and nonstationarity. These structures pose additional challenges to commonly used methods that rely mainly on a two-stage approach performing variable selection and classification separately. We propose in this work a novel Gaussian process discriminant analysis (GPDA) that combines these steps in a unified framework. Our model is a two-layer nonstationary Gaussian process coupled with an Ising prior to identify differentially-distributed locations. Scalable inference is achieved via developing a variational scheme that exploits advances in the use of sparse inverse covariance matrices. We demonstrate the performance of our methodology on simulated datasets and two proteomics datasets: breast cancer and SARS-CoV-2. Our approach distinguishes itself by offering explainability as well as uncertainty quantification in addition to low computational cost, which are crucial to increase trust and social acceptance of data-driven tools. Supplementary materials for this article are available online.

Function and interaction of coronavirus ion channel proteins

Objective: COVID-19 has emerged as a significant global health crisis causing devastating effects on world population accounting for over 6 million deaths worldwide. Although acute RTI is the prevalent cause of morbidity, kidney outcomes centered on a spectrum of AKI have evolved over the course of the pandemic. Especially the emerging variants have posed a daunting challenge to the scientific communities, prompting an urging requirement for global contributions in understanding the viral dynamics. In addition to canonical genes, several subgroup- specific accessory genes are located between the S and E genes of coronaviruses regarding which little is known. Previous studies have shown that accessory proteins (aps) in viruses function as viroporins that regulate viral infection, propagation and egress [1]. In this study we attempted to characterize the function of aps of coronavirus variants as ion channels. Furthermore, we also probed the interaction of ap4 with the host system. Method(s): Serial passaging (selection pressure), growth kinetics, confocal imaging, genome sequence analysis and proteomics were performed in Huh-7, MRC5 cells and/or human monocyte derived macrophages. Potassium uptake assay was performed in a Saccharo myces cerevisiae strain, which lacks the potassium transporters trk1 and trk2. Ion conductivity experiments were performed in Xenopus laevis oocytes using Two Electrode Voltage Clamp (TEVC) method. Result(s): Serial passaging demonstrated the acquisition of several frameshift mutations in ORF4 resulting in C-terminally truncated protein versions (ap4 and ap4a) and indicate a strong selection pressure against retaining a complete ORF4 in vitro. Growth kinetics in primary cells illustrated a reduction of viral titers when the full-length ap4 was expressed compared to the C-terminally truncated protein ap4a. Confocal imaging showed that ap4 and ap4a are not exclusively located in a single cellular compartment. Potassium uptake assay in yeast and TEVC analyses in Xenopus oocytes showed that ap4 and ap4a act as a weak K+ selective ion channel. In addition, accessory proteins of other virus variants also elicited microampere range of currents. Conclusion(s): Our study provides the first evidence that ap4 and other accessory proteins of coronavirus variants act as viroporins. Future studies are aimed at demonstrating the role of ap4 during the viral life cycle by modulating ion homeostasis of host cell in vivo (interacting proteins obtained from proteomic studies) and thereby serve as a tool for potential drug target.

New Sample Prep Products and Accessories for 2023

[...]instrument-based sample preparation technologies are presented. [...]attention is turned to other sample preparation accessories and supporting technologies. First is the Swift HLB-DPX tips. First is the Thermo Scientific AccelerOme sample preparation platform automating sample preparation for liquid chroma-tography-mass spectrometry (LC-MS) proteomics.

Inflammatory biomarkers: Breast cancer survival and possible role in COVID-19 associated comorbidity

It is known that inflammatory cytokines exacerbate the persistence and severity of various disease states. Breast cancer is the most frequently detected cancer among women worldwide and our recent studies suggest that the inflammatory state of breast (BrCa) cancer, a byproduct of elevated cytokine expression, induces epigenetic modifications leading to increased recurrence. Ongoing NCI clinical trial data (ClinicalTrials.gov, CCC19, NCT04354701) indicates that among patients with cancer and COVID-19, the mortality is high, and the most prevalent malignancies are of breast [21%] and prostate [16%] origin. Due to the risk of cytokine storm during SARS-CoV-2 infection, it is crucial to identify potential mechanisms of hyperinflammation in BrCa patients. In this study, we have evaluated the level of copy number alteration (CNA) of different inflammatory cytokines including IL-8, IL-1b, IL6, IL-8, GM-CSF, TNF-alpha and many others using cBioportal platform which includes over sixty-nine thousand tumor samples (n>69,000 from 213 different studies) from over 33 different cancers. We found that IL-8 has the highest level of amplification in different breast cancers subtypes. Besides, we also analyzed serum samples from BrCa patients, both recurrent and non-recurrent, by different proteomics methods to identify serum cytokines involved in prognosis and recurrence. Comparative data analysis between non-recurrent BrCa against recurrent BrCa patients identified several proteins with very high significance, mostly proteins associated with epigenetic pathways including HDAC9 (P = 0.0035), HDAC5 (P = 0.013), and HDAC7 (P = 0.020). Besides, we identified differential expression of several pro-inflammatory cytokines and immune regulators (IL-8, IL-4, IL-18, IL-12p70) that were present only in recurrent BrCa patient serum. Our data indicate that inflammatory processes contribute to epigenetic modifications that ultimately play a critical role in breast cancer recurrence. In terms of COVID-19 associated co-morbidity, the already dysregulated inflammatory state of BrCa patients may increase their susceptibility to cytokine-storm, leading to increased severity of COVID-related complications and increased mortality rate. Specifically, we hypothesize that the identified elevated level of IL-8 in BrCa patients may lead to a higher basal level of inflammation and contribute to the risk of attaining cytokine-storm during SARS-CoV-2 infection, making it a valuable target for future studies.

Serum proteomics hint at an early T-cell response and modulation of SARS-CoV-2-related pathogenic pathways in COVID-19-ARDS treated with Ruxolitinib.

Background: Acute respiratory distress syndrome (ARDS) in corona virus disease 19 (COVID-19) is triggered by hyperinflammation, thus providing a rationale for immunosuppressive treatments. The Janus kinase inhibitor Ruxolitinib (Ruxo) has shown efficacy in severe and critical COVID-19. In this study, we hypothesized that Ruxo's mode of action in this condition is reflected by changes in the peripheral blood proteome. Methods: This study included 11 COVID-19 patients, who were treated at our center's Intensive Care Unit (ICU). All patients received standard-of-care treatment and n = 8 patients with ARDS received Ruxo in addition. Blood samples were collected before (day 0) and on days 1, 6, and 10 of Ruxo treatment or, respectively, ICU admission. Serum proteomes were analyzed by mass spectrometry (MS) and cytometric bead array. Results: Linear modeling of MS data yielded 27 significantly differentially regulated proteins on day 1, 69 on day 6 and 72 on day 10. Only five factors (IGLV10-54, PSMB1, PGLYRP1, APOA5, WARS1) were regulated both concordantly and significantly over time. Overrepresentation analysis revealed biological processes involving T-cells only on day 1, while a humoral immune response and complement activation were detected at day 6 and day 10. Pathway enrichment analysis identified the NRF2-pathway early under Ruxo treatment and Network map of SARS-CoV-2 signaling and Statin inhibition of cholesterol production at later time points. Conclusion: Our results indicate that the mechanism of action of Ruxo in COVID-19-ARDS can be related to both known effects of this drug as a modulator of T-cells and the SARS-CoV-2-infection.

Neuro-PASC is characterized by enhanced CD4+ and diminished CD8+ T cell responses to SARS-CoV-2 Nucleocapsid protein.

Introduction: Many people with long COVID symptoms suffer from debilitating neurologic post-acute sequelae of SARS-CoV-2 infection (Neuro-PASC). Although symptoms of Neuro-PASC are widely documented, it is still unclear whether PASC symptoms impact virus-specific immune responses. Therefore, we examined T cell and antibody responses to SARS-CoV-2 Nucleocapsid protein to identify activation signatures distinguishing Neuro-PASC patients from healthy COVID convalescents. Results: We report that Neuro-PASC patients exhibit distinct immunological signatures composed of elevated CD4+ T cell responses and diminished CD8+ memory T cell activation toward the C-terminal region of SARS-CoV-2 Nucleocapsid protein when examined both functionally and using TCR sequencing. CD8+ T cell production of IL-6 correlated with increased plasma IL-6 levels as well as heightened severity of neurologic symptoms, including pain. Elevated plasma immunoregulatory and reduced pro-inflammatory and antiviral response signatures were evident in Neuro-PASC patients compared with COVID convalescent controls without lasting symptoms, correlating with worse neurocognitive dysfunction. Discussion: We conclude that these data provide new insight into the impact of virus-specific cellular immunity on the pathogenesis of long COVID and pave the way for the rational design of predictive biomarkers and therapeutic interventions.

Fast proteomics with dia-PASEF and analytical flow-rate chromatography.

Increased throughput in proteomic experiments can improve accessibility of proteomic platforms, reduce costs, and facilitate new approaches in systems biology and biomedical research. Here we propose combination of analytical flow rate chromatography with ion mobility separation of peptide ions, data-independent acquisition, and data analysis with the DIA-NN software suite, to achieve high-quality proteomic experiments from limited sample amounts, at a throughput of up to 400 samples per day. For instance, when benchmarking our workflow using a 500-µL/min flow rate and 3-min chromatographic gradients, we report the quantification of 5211 proteins from 2 µg of a mammalian cell-line standard at high quantitative accuracy and precision. We further used this platform to analyze blood plasma samples from a cohort of COVID-19 inpatients, using a 3-min chromatographic gradient and alternating column regeneration on a dual pump system. The method delivered a comprehensive view of the COVID-19 plasma proteome, allowing classification of the patients according to disease severity and revealing plasma biomarker candidates.

Identification of core therapeutic targets for Monkeypox virus and repurposing potential of drugs against them: An in silico approach.

Monkeypox virus (mpox virus) outbreak has rapidly spread to 82 non-endemic countries. Although it primarily causes skin lesions, secondary complications and high mortality (1-10%) in vulnerable populations have made it an emerging threat. Since there is no specific vaccine/antiviral, it is desirable to repurpose existing drugs against mpox virus. With little knowledge about the lifecycle of mpox virus, identifying potential inhibitors is a challenge. Nevertheless, the available genomes of mpox virus in public databases represent a goldmine of untapped possibilities to identify druggable targets for the structure-based identification of inhibitors. Leveraging this resource, we combined genomics and subtractive proteomics to identify highly druggable core proteins of mpox virus. This was followed by virtual screening to identify inhibitors with affinities for multiple targets. 125 publicly available genomes of mpox virus were mined to identify 69 highly conserved proteins. These proteins were then curated manually. These curated proteins were funnelled through a subtractive proteomics pipeline to identify 4 highly druggable, non-host homologous targets namely; A20R, I7L, Top1B and VETFS. High-throughput virtual screening of 5893 highly curated approved/investigational drugs led to the identification of common as well as unique potential inhibitors with high binding affinities. The common inhibitors, i.e., batefenterol, burixafor and eluxadoline were further validated by molecular dynamics simulation to identify their best potential binding modes. The affinity of these inhibitors suggests their repurposing potential. This work can encourage further experimental validation for possible therapeutic management of mpox.

The promise and challenge of spatial omics in dissecting tumour microenvironment and the role of AI.

Growing evidence supports the critical role of tumour microenvironment (TME) in tumour progression, metastases, and treatment response. However, the in-situ interplay among various TME components, particularly between immune and tumour cells, are largely unknown, hindering our understanding of how tumour progresses and responds to treatment. While mainstream single-cell omics techniques allow deep, single-cell phenotyping, they lack crucial spatial information for in-situ cell-cell interaction analysis. On the other hand, tissue-based approaches such as hematoxylin and eosin and chromogenic immunohistochemistry staining can preserve the spatial information of TME components but are limited by their low-content staining. High-content spatial profiling technologies, termed spatial omics, have greatly advanced in the past decades to overcome these limitations. These technologies continue to emerge to include more molecular features (RNAs and/or proteins) and to enhance spatial resolution, opening new opportunities for discovering novel biological knowledge, biomarkers, and therapeutic targets. These advancements also spur the need for novel computational methods to mine useful TME insights from the increasing data complexity confounded by high molecular features and spatial resolution. In this review, we present state-of-the-art spatial omics technologies, their applications, major strengths, and limitations as well as the role of artificial intelligence (AI) in TME studies.

Neurodegeneration: 2021 update.

This article reviews a collection of manuscripts in the field of neurodegenerative disease chosen from what are considered by the author to be among the 10 most important and potentially impactful topics or research trends of 2020 relevant to the field of experimental and diagnostic neuropathology. A deliberate effort was made to provide balance among disease categories covered. The result is a varied selection that includes not just individual papers but also research topics and trends. The association of COVID-19 with longer-term neurological symptoms has launched a research trend fueled by speculation that the SARS-CoV-2 might trigger neurodegenerative changes. The onslaught of transcriptomic studies has begun to give way to proteomics, with three transformative studies published examining glial contributions to Alzheimer disease, cerebral atherosclerosis in cognitive decline, and the complex sequence of post-translational modifications of the tau protein. Plasma biomarkers for Alzheimer disease have continued to make rapid advances, especially around highly sensitive assays capable of detecting different forms of abnormal hyperphosphorylated tau in peripheral blood. Two studies using cryo-electron microscopy showed the power of the approach by continuing to elucidate the diversity of filamentous tau inclusions, and a third study gave the first glimpse of α-synuclein aggregates at near atomic resolution. Another study continued to delineate how different α-synuclein conformers ("strains") target specific brain regions and lead to neurodegeneration. In Huntington's disease, we saw compelling molecular data showing how cells adapt to endoplasmic reticulum stress through the unfolded protein response. Finally, the role of astrocytes in chronic traumatic encephalopathy has emerged as a critical area of interest.

No Substrate Left behind-Mining of Shotgun Proteomics Datasets Rescues Evidence of Proteolysis by SARS-CoV-2 3CLpro Main Protease.

Proteolytic processing is the most ubiquitous post-translational modification and regulator of protein function. To identify protease substrates, and hence the function of proteases, terminomics workflows have been developed to enrich and detect proteolytically generated protein termini from mass spectrometry data. The mining of shotgun proteomics datasets for such 'neo'-termini, to increase the understanding of proteolytic processing, is an underutilized opportunity. However, to date, this approach has been hindered by the lack of software with sufficient speed to make searching for the relatively low numbers of protease-generated semi-tryptic peptides present in non-enriched samples viable. We reanalyzed published shotgun proteomics datasets for evidence of proteolytic processing in COVID-19 using the recently upgraded MSFragger/FragPipe software, which searches data with a speed that is an order of magnitude greater than many equivalent tools. The number of protein termini identified was higher than expected and constituted around half the number of termini detected by two different N-terminomics methods. We identified neo-N- and C-termini generated during SARS-CoV-2 infection that were indicative of proteolysis and were mediated by both viral and host proteases-a number of which had been recently validated by in vitro assays. Thus, re-analyzing existing shotgun proteomics data is a valuable adjunct for terminomics research that can be readily tapped (for example, in the next pandemic where data would be scarce) to increase the understanding of protease function and virus-host interactions, or other diverse biological processes.

Identification of potential biomarkers to predict organ morbidity in COVID-19: A repository based proteomics perspective.

SARS-CoV-2 causes substantial extrapulmonary manifestations in addition to pulmonary disease. Some of the major organs affected are cardiovascular, hematological and thrombotic, renal, neurological, and digestive systems. These types of muti-organ dysfunctions make it difficult and challenging for clinicians to manage and treat COVID-19 patients. The article focuses to identify potential protein biomarkers that can flag various organ systems affected in COVID-19. Publicly reposited high throughput proteomic data from human serum (HS), HEK293T/17 (HEK) and Vero E6 (VE) kidney cell culture were downloaded from ProteomeXchange consortium. The raw data was analyzed in Proteome Discoverer 2.4 to delineate the complete list of proteins in the three studies. These proteins were analyzed in Ingenuity Pathway Analysis (IPA) to associate them to various organ diseases. The shortlisted proteins were analyzed in MetaboAnalyst 5.0 to shortlist potential biomarker proteins. These were then assessed for disease-gene association in DisGeNET and validated by Protein-protein interactome (PPI) and functional enrichment studies (GO_BP, KEGG and Reactome pathways) in STRING. Protein profiling resulted in shortlisting 20 proteins in 7 organ systems. Of these 15 proteins showed at least 1.25-fold changes with a sensitivity and specificity of 70%. Association analysis further shortlisted 10 proteins with a potential association with 4 organ diseases. Validation studies established possible interacting networks and pathways affected, confirmingh the ability of 6 of these proteins to flag 4 different organ systems affected in COVID-19 disease. This study helps to establish a platform to seek protein signatures in different clinical phenotypes of COVID-19. The potential biomarker candidates that can flag organ systems involved are: (a) Vitamin K-dependent protein S and Antithrombin-III for hematological disorders; (b) Voltage-dependent anion-selective channel protein 1 for neurological disorders; (c) Filamin-A for cardiovascular disorder and, (d) Peptidyl-prolyl cis-trans isomerase A and Peptidyl-prolyl cis-trans isomerase FKBP1A for digestive disorders.

Proteogenomic Features of the Highly Polymorphic Histidine-rich Glycoprotein Arose Late in Evolution.

Histidine-rich glycoprotein (HRG) is a liver-produced protein circulating in human serum at high concentrations of around 125 µg/ml. HRG belongs to the family of type-3 cystatins and has been implicated in a plethora of biological processes, albeit that its precise function is still not well understood. Human HRG is a highly polymorphic protein, with at least five variants with minor allele frequencies of more than 10%, variable in populations from different parts of the world. Considering these five mutations we can theoretically expect 35 = 243 possible genetic HRG variants in the population. Here, we purified HRG from serum of 44 individual donors and investigated by proteomics the occurrence of different allotypes, each being either homozygote or heterozygote for each of the five mutation sites. We observed that some mutational combinations in HRG were highly favored, while others were apparently missing, although they ought to be present based on the independent assembly of these five mutation sites. To further explore this behavior, we extracted data from the 1000 genome project (n ∼ 2500 genomes) and assessed the frequency of different HRG mutants in this larger dataset, observing a prevailing agreement with our proteomics data. From all the proteogenomic data we conclude that the five different mutation sites in HRG are not occurring independently, but several mutations at different sites are fully mutually exclusive, whereas others are highly intwined. Specific mutations do also affect HRG glycosylation. As the levels of HRG have been suggested as a protein biomarker in a variety of biological processes (e.g., aging, COVID-19 severity, severity of bacterial infections), we here conclude that the highly polymorphic nature of the protein needs to be considered in such proteomics evaluations, as these mutations may affect HRG's abundance, structure, posttranslational modifications, and function.

Integrative proteomic profiling of lung tissues and blood in acute respiratory distress syndrome.

Introduction: Acute respiratory distress syndrome and acute lung injury (ARDS/ALI) still lack a recognized diagnostic test and pharmacologic treatments that target the underlying pathology. Methods: To explore the sensitive non-invasive biomarkers associated with pathological changes in the lung of direct ARDS/ALI, we performed an integrative proteomic analysis of lung and blood samples from lipopolysaccharide (LPS)-induced ARDS mice and COVID-19-related ARDS patients. The common differentially expressed proteins (DEPs) were identified based on combined proteomic analysis of serum and lung samples in direct ARDS mice model. The clinical value of the common DEPs was validated in lung and plasma proteomics in cases of COVID-19-related ARDS. Results: We identified 368 DEPs in serum and 504 in lung samples from LPS-induced ARDS mice. Gene ontology (GO) classification and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that these DEPs in lung tissues were primarily enriched in pathways, including IL-17 and B cell receptor signaling pathways, and the response to stimuli. In contrast, DEPs in the serum were mostly involved in metabolic pathways and cellular processes. Through network analysis of protein-protein interactions (PPI), we identified diverse clusters of DEPs in the lung and serum samples. We further identified 50 commonly upregulated and 10 commonly downregulated DEPs in the lung and serum samples. Internal validation with a parallel-reacted monitor (PRM) and external validation in the Gene Expression Omnibus (GEO) datasets further showed these confirmed DEPs. We then validated these proteins in the proteomics of patients with ARDS and identified six proteins (HP, LTA4H, S100A9, SAA1, SAA2, and SERPINA3) with good clinical diagnostic and prognostic value. Discussion: These proteins can be viewed as sensitive and non-invasive biomarkers associated with lung pathological changes in the blood and could potentially serve as targets for the early detection and treatment of direct ARDS especially in hyperinflammatory subphenotype.

Proteomics and cytokine analyses distinguish myalgic encephalomyelitis/chronic fatigue syndrome cases from controls.

BACKGROUND: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex, heterogenous disease characterized by unexplained persistent fatigue and other features including cognitive impairment, myalgias, post-exertional malaise, and immune system dysfunction. Cytokines are present in plasma and encapsulated in extracellular vesicles (EVs), but there have been only a few reports of EV characteristics and cargo in ME/CFS. Several small studies have previously described plasma proteins or protein pathways that are associated with ME/CFS. METHODS: We prepared extracellular vesicles (EVs) from frozen plasma samples from a cohort of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) cases and controls with prior published plasma cytokine and plasma proteomics data. The cytokine content of the plasma-derived extracellular vesicles was determined by a multiplex assay and differences between patients and controls were assessed. We then performed multi-omic statistical analyses that considered not only this new data, but extensive clinical data describing the health of the subjects. RESULTS: ME/CFS cases exhibited greater size and concentration of EVs in plasma. Assays of cytokine content in EVs revealed IL2 was significantly higher in cases. We observed numerous correlations among EV cytokines, among plasma cytokines, and among plasma proteins from mass spectrometry proteomics. Significant correlations between clinical data and protein levels suggest roles of particular proteins and pathways in the disease. For example, higher levels of the pro-inflammatory cytokines Granulocyte-Monocyte Colony-Stimulating Factor (CSF2) and Tumor Necrosis Factor (TNFα) were correlated with greater physical and fatigue symptoms in ME/CFS cases. Higher serine protease SERPINA5, which is involved in hemostasis, was correlated with higher SF-36 general health scores in ME/CFS. Machine learning classifiers were able to identify a list of 20 proteins that could discriminate between cases and controls, with XGBoost providing the best classification with 86.1% accuracy and a cross-validated AUROC value of 0.947. Random Forest distinguished cases from controls with 79.1% accuracy and an AUROC value of 0.891 using only 7 proteins. CONCLUSIONS: These findings add to the substantial number of objective differences in biomolecules that have been identified in individuals with ME/CFS. The observed correlations of proteins important in immune responses and hemostasis with clinical data further implicates a disturbance of these functions in ME/CFS.

Proteomics research of SARS-CoV-2 and COVID-19 disease

Currently, coronavirus disease 2019 (COVID-19) is still spreading in a global scale, exerting a massive health and socioeconomic crisis. Deep insights into the molecular functions of the viral proteins and the pathogenesis of this infectious disease are urgently needed. In this review, we comprehensively describe the proteome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and summarize their protein interaction map with host cells. In the protein interaction network between the virus and the host, a total of 787 host prey proteins that appeared in at least two studies or were verified by co-immunoprecipitation experiments. Together with 29 viral proteins, a network of 1762 proximal interactions were observed. We also review the proteomics results of COVID-19 patients and proved that SARS-CoV-2 hijacked the host's translation system, post-translation modification system, and energy supply system via viral proteins, resulting in various immune disorders, multiple cardiomyopathies, and cholesterol metabolism diseases. © 2022 the author(s), published by De Gruyter, Berlin/Boston.

Changes in the proteomics of exhaled breath condensate under the influence of inhaled hydrogen in patients with post-COVID syndrome.

Aim. To study the effect of inhalation therapy with an active hydrogen (AH) on the protein composition of exhaled breath condensate (EBC) in patients with post-COVID syndrome (PCS). Material and methods. This randomized controlled parallel prospective study included 60 patients after coronavirus disease 2019 (COVID-19) with PCS during the recovery period and clinical manifestations of chronic fatigue syndrome who received standard therapy according to the protocol for managing patients with chronic fatigue syndrome (CFS). The patients were divided into 2 groups: group 1 (main) - 30 people who received standard therapy and AH inhalations (SUISONIA, Japan) for 10 days, and group 2 (control) - 30 medical workers who received only standard therapy. Patients in both groups were comparable in sex and mean age. All participants in the study were sampled with EBC on days 1 and 10. Samples were subjected to tryptic digestion and high-performance liquid chromatography combined with tandem mass spectrometry analysis using a nanoflow chromatograph (Dionex 3000) in tandem with a high-resolution time-of-flight mass spectrometer (timsTOF Pro). Results. A total of 478 proteins and 1350 peptides were identified using high resolution mass spectrometry. The number of proteins in samples after AH therapy, on average, is 12% more than before treatment. An analysis of the distribution of proteins in different groups of patients showed that only half of these proteins (112) are common for all groups of samples and are detected in EBC before, after, and regardless of hydrogen therapy. In addition to the qualitative difference in the EBC protein compositions in different groups, quantitative changes in the concentration of 36 proteins (mainly structural and protective) were also revealed, which together made it possible to reliably distinguish between subgroups before and after treatment. It is worth noting that among these proteins there are participants of blood coagulation (alpha-1-antitrypsin), chemokine- and cytokine-mediated inflammation, and a number of signaling pathways (cytoplasmic actin 2), response to oxidative stress (thioredoxin), glycolysis (glyceraldehyde-3- phosphate dehydrogenase), etc. Conclusion. The use of hydrogen therapy can contribute to the switching of a number of physiological processes, which may affect the success of recovery in PCS patients. In particular, the obtained results indicate the activation of aerobic synthesis of adenosine triphosphate in mitochondria by hydrogen therapy, which correlates well with the decrease in the blood lactate level detected by laboratory studies. At the same time, this therapy can inhibit pro-inflammatory activity, negatively affecting the coagulation and signaling pathways of integrins and apoptosis, and, in addition, activate protective pathways, tricarboxylic acid cycle, FAS signaling, and purine metabolism, which may be essential for effective recovery after COVID-19.Copyright © 2023 Vserossiiskoe Obshchestvo Kardiologov. All rights reserved.

Covid-19 Vaccination Impacts Functional Immune Responses and Plasma Proteome in Plwh

Background: The impact of COVID-19 infection or COVID-19 vaccination on the immune system of people living with HIV (PLWH) is unclear. We therefore studied the effects of COVID-19 infection or vaccination on functional immune responses and systemic inflammation in PLWH. Method(s): Between 2019 and 2021, 1985 virally suppressed, asymptomatic PLWH were included in the Netherlands in the 2000HIV study (NCT039948350): 1514 participants enrolled after the start of the COVID-19 pandemic were separated into a discovery and validation cohort. PBMCs were incubated with different stimuli for 24 hours: cytokine levels were measured in supernatants. ~3000 targeted plasma proteins were measured with Olink Explore panel. Past COVID-19 infection was proven when a positive PCR was reported or when serology on samples from inclusion proved positive. Compared were unvaccinated PLWH with and without past COVID-19 infection, and PLWH with or without anti-COVID-19 vaccination excluding those with past COVID-19 infection. Result(s): 471 out of 1514 participants were vaccinated (median days since vaccination: 33, IQR 16-66) and 242 had a past COVID-19 infection (median days since +PCR: 137, IQR 56-206). Alcohol, smoking, drug use, BMI, age, latest CD4 count and proportion with viral blips were comparable between groups. Systemic inflammation as assessed by targeted proteomics showed 89 upregulated and 43 downregulated proteins in the vaccinated participants. In contrast, individuals with a past COVID-19 infection display lower levels of 138 plasma proteins compared to the uninfected group (see figure). 'Innate immune system' and 'cell death' were upregulated in pathway analysis in vaccinated PLWH, but downregulated in COVID-19 infected participants. The increased systemic inflammation of the COVID-19 vaccinated group was accompanied by lower TNF-alpha and IL-1beta production capacity upon restimulation with a range of microbial stimuli, while production of IL-1Ra was increased. In COVID-19 infected PLWH only a reduced production of TNF-alpha to S. pneumonia was significant. Vaccinated PLWH also showed upregulation of platelet aggregation pathways. Conclusion(s): COVID-19 vaccination in PLWH leads to an increased systemic inflammation, but less effective cytokine production capacity of its immune cells upon microbial stimulation. This pattern is different from that of COVID-19 infection that leads to a decreased inflammatory profile and only minimal effects on cytokine production capacity. (Figure Presented).

BASELINE AND TEMPORAL DIFFERENCES IN PROTEOMICS FOLLOWING SARS-CoV-2 INFECTION IN PWH

Background: COVID-19 may be more severe in persons with HIV (PWH). However, underlying biological mechanisms associated with the development of COVID-19 and its clinical severity among antiretroviral therapy (ART) treated PWH are largely unknown. Therefore, we wished to evaluate temporal changes in plasma proteins following SARS-CoV-2 infection and identify pre-infection proteomic markers associated with future COVID-19. Method(s): We analyzed the data of clinical, antibody-confirmed COVID-19 ARTtreated PWH from the global Randomized Trial to Prevent Vascular Events in HIV (REPRIEVE). Individuals were matched on geographic region, age, and sample timing to antibody-negative controls. For cases and controls, pre-COVID-19 pandemic specimens were obtained prior to January 2020 to assess temporal changes and baseline differences in protein expression in relationship to COVID-19 severity, using mixed effects models adjusted for false-discovery rate. Result(s): We compared 257 unique plasma proteins (Olink Proteomics) in 94 COVID-19 antibody-confirmed clinical cases and 113 matched antibody-negative controls, excluding COVID-19 vaccinated participants (median age 50 years, 73% male). 40% of cases were characterized as mild;60% moderate to severe. Median time from COVID-19 infection to follow-up sampling was 4 months. Temporal changes in protein expression differed based on COVID-19 disease severity. Among moderate to severe cases vs. controls, NOS3 increased, whereas ANG, CASP-8, CD5, GZMH, GZMB, ITGB2, and KLRD1 decreased. Higher baseline circulating concentrations of granzymes A, B and H (GZMA, GZMB and GZMH) were associated with the future development of moderate-severe COVID-19 in PWH and were related to immune function, including CD4, CD8 and the CD4/ CD8 ratio. Conclusion(s): We identified temporal changes in novel proteins in closely linked inflammatory, immune, and fibrotic pathways which may relate to COVID-19-related morbidity among ART-treated PWH. Further, we identified key granzyme proteins, serine proteases expressed by cytotoxic T lymphocytes and NK cells in response to foreign antigens, associated with future COVID-19 in PWH. Our results provide unique insights into the biological susceptibility and responses to COVID-19 infection in PWH. (Figure Presented).

Uncovering a neurological protein signature for severe COVID-19.

Coronavirus disease of 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has sparked a global pandemic with severe complications and high morbidity rate. Neurological symptoms in COVID-19 patients, and neurological sequelae post COVID-19 recovery have been extensively reported. Yet, neurological molecular signature and signaling pathways that are affected in the central nervous system (CNS) of COVID-19 severe patients remain still unknown and need to be identified. Plasma samples from 49 severe COVID-19 patients, 50 mild COVID-19 patients, and 40 healthy controls were subjected to Olink proteomics analysis of 184 CNS-enriched proteins. By using a multi-approach bioinformatics analysis, we identified a 34-neurological protein signature for COVID-19 severity and unveiled dysregulated neurological pathways in severe cases. Here, we identified a new neurological protein signature for severe COVID-19 that was validated in different independent cohorts using blood and postmortem brain samples and shown to correlate with neurological diseases and pharmacological drugs. This protein signature could potentially aid the development of prognostic and diagnostic tools for neurological complications in post-COVID-19 convalescent patients with long term neurological sequelae.