Seroconversion stages COVID19 into distinct pathophysiological states

Regulation of kynurenine metabolism by blood donor genetics and biology impacts red cell hemolysis in vitro and in vivo

ABSTRACT

In the field of transfusion medicine, the clinical relevance of the metabolic markers of the red blood cell (RBC) storage lesion is incompletely understood. Here, we performed metabolomics of RBC units from 643 donors enrolled in the Recipient Epidemiology and Donor Evaluation Study, REDS RBC Omics. These units were tested on storage days 10, 23, and 42 for a total of 1929 samples and also characterized for end-of-storage hemolytic propensity after oxidative and osmotic insults. Our results indicate that the metabolic markers of the storage lesion poorly correlated with hemolytic propensity. In contrast, kynurenine was not affected by storage duration and was identified as the top predictor of osmotic fragility. RBC kynurenine levels were affected by donor age and body mass index and were reproducible within the same donor across multiple donations from 2 to 12 months apart. To delve into the genetic underpinnings of kynurenine levels in stored RBCs, we thus tested kynurenine levels in stored RBCs on day 42 from 13 091 donors from the REDS RBC Omics study, a population that was also genotyped for 879 000 single nucleotide polymorphisms. Through a metabolite quantitative trait loci analysis, we identified polymorphisms in SLC7A5, ATXN2, and a series of rate-limiting enzymes (eg, kynurenine monooxygenase, indoleamine 2,3-dioxygenase, and tryptophan dioxygenase) in the kynurenine pathway as critical factors affecting RBC kynurenine levels. By interrogating a donor-recipient linkage vein-to-vein database, we then report that SLC7A5 polymorphisms are also associated with changes in hemoglobin and bilirubin levels, suggestive of in vivo hemolysis in 4470 individuals who were critically ill and receiving single-unit transfusions.

Investigating the Potential Shared Molecular Mechanisms between COVID-19 and Alzheimer's Disease via Transcriptomic Analysis

SARS-CoV-2 caused the COVID-19 pandemic. COVID-19 may elevate the risk of cognitive impairment and even cause dementia in infected individuals; it may accelerate cognitive decline in elderly patients with dementia, possibly in Alzheimer's disease (AD) patients. However, the mechanisms underlying the interplay between AD and COVID-19 are still unclear. To investigate the underlying mechanisms and associations between AD progression and SARS-CoV-2 infection, we conducted a series of bioinformatics research into SARS-CoV-2-infected cells, COVID-19 patients, AD patients, and SARS-CoV-2-infected AD patients. We identified the common differentially expressed genes (DEGs) in COVID-19 patients, AD patients, and SARS-CoV-2-infected cells, and these DEGs are enriched in certain pathways, such as immune responses and cytokine storms. We constructed the gene interaction network with the signaling transduction module in the center and identified IRF7, STAT1, STAT2, and OAS1 as the hub genes. We also checked the correlations between several key transcription factors and the SARS-CoV-2 and COVID-19 pathway-related genes. We observed that ACE2 expression is positively correlated with IRF7 expression in AD and coronavirus infections, and interestingly, IRF7 is significantly upregulated in response to different RNA virus infections. Further snRNA-seq analysis indicates that NRGN neurons or endothelial cells may be responsible for the increase in ACE2 and IRF7 expression after SARS-CoV-2 infection. The positive correlation between ACE2 and IRF7 expressions is confirmed in the hippocampal formation (HF) of SARS-CoV-2-infected AD patients. Our findings could contribute to the investigation of the molecular mechanisms underlying the interplay between AD and COVID-19 and to the development of effective therapeutic strategies for AD patients with COVID-19.

Serum Albumin as Prognostic Marker for Older Adults in Hospital and Community Settings

Serum albumin, known for its multifaceted role in health, is hypothesized to serve as a prognostic marker for older adults, both in hospital and community settings. Nine studies were included in the review, revealing consistent associations between low serum albumin levels and increased mortality risk in hospitalized older individuals. In community settings, low serum albumin levels were linked to higher mortality rates compared to those with normal levels. The synthesis of evidence underscores the potential of serum albumin as a prognostic marker for older adults, offering valuable insights for risk stratification and targeted interventions. While robust evidence supports its utility in hospital settings, further research is warranted in community settings to address current limitations and enhance the applicability of serum albumin as a prognostic tool. This review merges existing knowledge of the prognostic significance of serum albumin in older adults across hospital and community settings. The findings emphasize the importance of serum albumin as a potential prognostic marker, urging continued research efforts to refine its application in diverse healthcare contexts and improve outcomes for the aging population.

Elevated A-to-I RNA editing in COVID-19 infected individuals

Given the current status of coronavirus disease 2019 (COVID-19) as a global pandemic, it is of high priority to gain a deeper understanding of the disease's development and how the virus impacts its host. Adenosine (A)-to-Inosine (I) RNA editing is a post-transcriptional modification, catalyzed by the ADAR family of enzymes, that can be considered part of the inherent cellular defense mechanism as it affects the innate immune response in a complex manner. It was previously reported that various viruses could interact with the host's ADAR enzymes, resulting in epigenetic changes both to the virus and the host. Here, we analyze RNA-seq of nasopharyngeal swab specimens as well as whole-blood samples of COVID-19 infected individuals and show a significant elevation in the global RNA editing activity in COVID-19 compared to healthy controls. We also detect specific coding sites that exhibit higher editing activity. We further show that the increment in editing activity during the disease is temporary and returns to baseline shortly after the symptomatic period. These significant epigenetic changes may contribute to the immune system response and affect adverse outcomes seen in post-viral cases.

Multiple COVID reinfections in a vaccinated psoriatic patient receiving adalimumab

Currently, psoriasis patients are advised to follow their standard therapeutic regimen, and are advised to be vaccinated against Covid-19. However, the data about the antibody responses, induced by the various kinds of SARS-CoV-2 vaccines in psoriasis patients who require systemic immunosuppressive treatment is scant. In this case report, we describe antibody responses induced by COVID-19 vaccine, in a 26-year-old male patient with psoriasis being treated with anti-TNF biotherapy, adalimumab biosimilar every two weeks. The patient was vaccinated against COVID-19, according to the national protocol. He experienced three episodes of symptomatic COVID-19. His first and second exposures did not result in antibody production. After the third episode of COVID-19, The SARS-CoV-2 anti-spike antibody (IgG) was more than 100 Ru/mL (ELISA; ≥8 Ru/mL is considered positive), and SARS-CoV-2 neutralizing antibody (total) was more than 40 micg/mL (ELISA; ≥2.5 micg/mL is considered positive). This is the first case with weak antibody response to vaccination and multiple episodes of COVID infection in a psoriatic patient with adalimumab biosimilar. However, we cannot assume causality due to the treatment.

The Renin-Angiotensin System in COVID-19: Can Long COVID Be Predicted?

(1) Background: Co-morbidities such as hypertension and cardiovascular disease are major risk factors for severe COVID-19. The renin-angiotensin system (RAS) is critically involved in their pathophysiology and is counter-balanced by both angiotensin-converting enzyme 2 (ACE2), the functional receptor of SARS-CoV-2, and the kallikrein-kinin system (KKS). Considerable research interest with respect to COVID-19 treatment is currently being directed towards the components of these systems. In earlier studies, we noticed significantly reduced carboxypeptidase N (CPN, KKS member) activity and excessive angiotensin-converting enzyme (ACE, RAS member) activity in the sera of both hospitalized COVID-19 patients and a subgroup of convalescent patients. The data had been obtained using labeled bradykinin (BK) as a reporter peptide, which is a target of both CPN and ACE. The data were supplemented with mass-spectrometry-based serum proteomic analysis. Here, we hypothesize that the degree of BK serum degradation could be indicative of Long COVID. (2) Review and Discussion: The recent literature is briefly reviewed. The fact that the levels of the BK serum degradation products did not reach normal concentrations in almost half of the patients during convalescences could have been partially due to a dysregulated RAS. (3) Conclusions: Standard tests for routine patient care in Long COVID come often back normal. We suggest that the measurement of selected members of the RAS such as ACE and angiotensin II or the use of our BK degradation assay could identify Long COVID candidates. Clinical studies are required to test this hypothesis.

Multidimensional definition of the interferonopathy of Down syndrome and its response to JAK inhibition

Individuals with Down syndrome (DS) display chronic hyperactivation of interferon signaling. However, the clinical impacts of interferon hyperactivity in DS are ill-defined. Here, we describe a multiomics investigation of interferon signaling in hundreds of individuals with DS. Using interferon scores derived from the whole blood transcriptome, we defined the proteomic, immune, metabolic, and clinical features associated with interferon hyperactivity in DS. Interferon hyperactivity associates with a distinct proinflammatory phenotype and dysregulation of major growth signaling and morphogenic pathways. Individuals with the highest interferon activity display the strongest remodeling of the peripheral immune system, including increased cytotoxic T cells, B cell depletion, and monocyte activation. Interferon hyperactivity accompanies key metabolic changes, most prominently dysregulated tryptophan catabolism. High interferon signaling stratifies a subpopulation with elevated rates of congenital heart disease and autoimmunity. Last, a longitudinal case study demonstrated that JAK inhibition normalizes interferon signatures with therapeutic benefit in DS. Together, these results justify the testing of immune-modulatory therapies in DS.

Red Blood Cell Omics and Machine Learning in Transfusion Medicine: Singularity Is Near

Background

Blood transfusion is a life-saving intervention for millions of recipients worldwide. Over the last 15 years, the advent of high-throughput, affordable omics technologies - including genomics, proteomics, lipidomics, and metabolomics - has allowed transfusion medicine to revisit the biology of blood donors, stored blood products, and transfusion recipients.

Summary

Omics approaches have shed light on the genetic and non-genetic factors (environmental or other exposures) impacting the quality of stored blood products and efficacy of transfusion events, based on the current Food and Drug Administration guidelines (e.g., hemolysis and post-transfusion recovery for stored red blood cells). As a treasure trove of data accumulates, the implementation of machine learning approaches promises to revolutionize the field of transfusion medicine, not only by advancing basic science. Indeed, computational strategies have already been used to perform high-content screenings of red blood cell morphology in microfluidic devices, generate in silico models of erythrocyte membrane to predict deformability and bending rigidity, or design systems biology maps of the red blood cell metabolome to drive the development of novel storage additives.

Key Message

In the near future, high-throughput testing of donor genomes via precision transfusion medicine arrays and metabolomics of all donated products will be able to inform the development and implementation of machine learning strategies that match, from vein to vein, donors, optimal processing strategies (additives, shelf life), and recipients, realizing the promise of personalized transfusion medicine.

Multiplatform analyses reveal distinct drivers of systemic pathogenesis in adult versus pediatric severe acute COVID-19

The pathogenesis of multi-organ dysfunction associated with severe acute SARS-CoV-2 infection remains poorly understood. Endothelial damage and microvascular thrombosis have been identified as drivers of COVID-19 severity, yet the mechanisms underlying these processes remain elusive. Here we show alterations in fluid shear stress-responsive pathways in critically ill COVID-19 adults as compared to non-COVID critically ill adults using a multiomics approach. Mechanistic in-vitro studies, using microvasculature-on-chip devices, reveal that plasma from critically ill COVID-19 adults induces fibrinogen-dependent red blood cell aggregation that mechanically damages the microvascular glycocalyx. This mechanism appears unique to COVID-19, as plasma from non-COVID sepsis patients demonstrates greater red blood cell membrane stiffness but induces less significant alterations in overall blood rheology. Multiomics analyses in pediatric patients with acute COVID-19 or the post-infectious multi-inflammatory syndrome in children (MIS-C) demonstrate little overlap in plasma cytokine and metabolite changes compared to adult COVID-19 patients. Instead, pediatric acute COVID-19 and MIS-C patients show alterations strongly associated with cytokine upregulation. These findings link high fibrinogen and red blood cell aggregation with endotheliopathy in adult COVID-19 patients and highlight differences in the key mediators of pathogenesis between adult and pediatric populations.

A two-gene marker for the two-tiered innate immune response in COVID-19 patients

For coronavirus disease 2019 (COVID-19), a pandemic disease characterized by strong immune dysregulation in severe patients, convenient and efficient monitoring of the host immune response is critical. Human hosts respond to viral and bacterial infections in different ways, the former is characterized by the activation of interferon stimulated genes (ISGs) such as IFI27, while the latter is characterized by the activation of anti-bacterial associated genes (ABGs) such as S100A12. This two-tiered innate immune response has not been examined in COVID-19. In this study, the activation patterns of this two-tiered innate immune response represented by IFI27 and S100A12 were explored based on 1421 samples from 17 transcriptome datasets derived from the blood of COVID-19 patients and relevant controls. It was found that IFI27 activation occurred in most of the symptomatic patients and displayed no correlation with disease severity, while S100A12 activation was more restricted to patients under severe and critical conditions with a stepwise activation pattern. In addition, most of the S100A12 activation was accompanied by IFI27 activation. Furthermore, the activation of IFI27 was most pronounced within the first week of symptom onset, but generally waned after 2-3 weeks. On the other hand, the activation of S100A12 displayed no apparent correlation with disease duration and could last for several months in certain patients. These features of the two-tiered innate immune response can further our understanding on the disease mechanism of COVID-19 and may have implications to the clinical triage. Development of a convenient two-gene protocol for the routine serial monitoring of this two-tiered immune response will be a valuable addition to the existing laboratory tests.

A Counterintuitive Neutrophil-Mediated Pattern in COVID-19 Patients Revealed through Transcriptomics Analysis

The COVID-19 pandemic has persisted for almost three years. However, the mechanisms linked to the SARS-CoV-2 effect on tissues and disease severity have not been fully elucidated. Since the onset of the pandemic, a plethora of high-throughput data related to the host transcriptional response to SARS-CoV-2 infections has been generated. To this end, the aim of this study was to assess the effect of SARS-CoV-2 infections on circulating and organ tissue immune responses. We profited from the publicly accessible gene expression data of the blood and soft tissues by employing an integrated computational methodology, including bioinformatics, machine learning, and natural language processing in the relevant transcriptomics data. COVID-19 pathophysiology and severity have mainly been associated with macrophage-elicited responses and a characteristic "cytokine storm". Our counterintuitive findings suggested that the COVID-19 pathogenesis could also be mediated through neutrophil abundance and an exacerbated suppression of the immune system, leading eventually to uncontrolled viral dissemination and host cytotoxicity. The findings of this study elucidated new physiological functions of neutrophils, as well as tentative pathways to be explored in asymptomatic-, ethnicity- and locality-, or staging-associated studies.

Multi-omics identify falling LRRC15 as a COVID-19 severity marker and persistent pro-thrombotic signals in convalescence

Patients with end-stage kidney disease (ESKD) are at high risk of severe COVID-19. Here, we perform longitudinal blood sampling of ESKD haemodialysis patients with COVID-19, collecting samples pre-infection, serially during infection, and after clinical recovery. Using plasma proteomics, and RNA-sequencing and flow cytometry of immune cells, we identify transcriptomic and proteomic signatures of COVID-19 severity, and find distinct temporal molecular profiles in patients with severe disease. Supervised learning reveals that the plasma proteome is a superior indicator of clinical severity than the PBMC transcriptome. We show that a decreasing trajectory of plasma LRRC15, a proposed co-receptor for SARS-CoV-2, is associated with a more severe clinical course. We observe that two months after the acute infection, patients still display dysregulated gene expression related to vascular, platelet and coagulation pathways, including PF4 (platelet factor 4), which may explain the prolonged thrombotic risk following COVID-19.

Dynamics of humoral immune response in SARS-CoV-2 infected individuals with different clinical stages

Background

The COVID-19 pandemic remains a global health problem. As in other viral infections, the humoral immune response against SARS-CoV-2 is thought to be crucial for controlling the infection. However, the dynamic of B cells in the clinical spectrum of this disease is still controversial. This study aimed to characterize B cell subsets and neutralizing responses in COVID-19 patients according to disease severity through a one-month follow-up.

Methods

A cohort of 71 individuals with SARS-CoV-2 infection confirmed by RT-PCR were recruited and classified into four groups: i) asymptomatic; ii) symptomatic outpatients; iii) hospitalized in ward, and iv) intensive care unit patients (ICU). Samples were taken at days 0 (inclusion to the study), 7 and 30. B cell subsets and neutralizing antibodies were assessed using multiparametric flow cytometry and plaque reduction neutralization, respectively.

Results

Older age, male gender and body mass index over 25 were common factors among hospitalized and ICU patients, compared to those with milder clinical presentations. In addition, those requiring hospitalization had more comorbidities. A significant increase in the frequencies of CD19+ cells at day 0 was observed in hospitalized and ICU patients compared to asymptomatic and symptomatic groups. Likewise, the frequency of plasmablasts was significantly increased at the first sample in the ICU group compared to the asymptomatic group, but then waned over time. The frequency of naïve B cells decreased at days 7 and 30 compared to day 0 in hospitalized and ICU patients. The neutralizing antibody titers were higher as the severity of COVID-19 increased; in asymptomatic individuals, it was strongly correlated with the percentage of IgM+ switched memory B cells, and a moderate correlation was found with plasmablasts.

Conclusion

The humoral immune response is variable among SARS-CoV-2 infected people depending on the severity and time of clinical evolution. In severe COVID-19 patients, a higher plasmablast frequency and neutralizing antibody response were observed, suggesting that, despite having a robust humoral immunity, this response could be late, having a low impact on disease outcome.

Signatures of Mitochondrial Dysfunction and Impaired Fatty Acid Metabolism in Plasma of Patients with Post-Acute Sequelae of COVID-19 (PASC)

Exercise intolerance is a major manifestation of post-acute sequelae of severe acute respiratory syndrome coronavirus infection (PASC, or "long-COVID"). Exercise intolerance in PASC is associated with higher arterial blood lactate accumulation and lower fatty acid oxidation rates during graded exercise tests to volitional exertion, suggesting altered metabolism and mitochondrial dysfunction. It remains unclear whether the profound disturbances in metabolism that have been identified in plasma from patients suffering from acute coronavirus disease 2019 (COVID-19) are also present in PASC. To bridge this gap, individuals with a history of previous acute COVID-19 infection that did not require hospitalization were enrolled at National Jewish Health (Denver, CO, USA) and were grouped into those that developed PASC (n = 29) and those that fully recovered (n = 16). Plasma samples from the two groups were analyzed via mass spectrometry-based untargeted metabolomics and compared against plasma metabolic profiles of healthy control individuals (n = 30). Observational demographic and clinical data were retrospectively abstracted from the medical record. Compared to plasma of healthy controls or individuals who recovered from COVID-19, PASC plasma exhibited significantly higher free- and carnitine-conjugated mono-, poly-, and highly unsaturated fatty acids, accompanied by markedly lower levels of mono-, di- and tricarboxylates (pyruvate, lactate, citrate, succinate, and malate), polyamines (spermine) and taurine. Plasma from individuals who fully recovered from COVID-19 exhibited an intermediary metabolic phenotype, with milder disturbances in fatty acid metabolism and higher levels of spermine and taurine. Of note, depletion of tryptophan-a hallmark of disease severity in COVID-19-is not normalized in PASC patients, despite normalization of kynurenine levels-a tryptophan metabolite that predicts mortality in hospitalized COVID-19 patients. In conclusion, PASC plasma metabolites are indicative of altered fatty acid metabolism and dysfunctional mitochondria-dependent lipid catabolism. These metabolic profiles obtained at rest are consistent with previously reported mitochondrial dysfunction during exercise, and may pave the way for therapeutic intervention focused on restoring mitochondrial fat-burning capacity.

Early Prediction of COVID-19 Patient Survival by Targeted Plasma Multi-Omics and Machine Learning

The recent surge of coronavirus disease 2019 (COVID-19) hospitalizations severely challenges healthcare systems around the globe and has increased the demand for reliable tests predictive of disease severity and mortality. Using multiplexed targeted mass spectrometry assays on a robust triple quadrupole MS setup which is available in many clinical laboratories, we determined the precise concentrations of hundreds of proteins and metabolites in plasma from hospitalized COVID-19 patients. We observed a clear distinction between COVID-19 patients and controls and, strikingly, a significant difference between survivors and nonsurvivors. With increasing length of hospitalization, the survivors' samples showed a trend toward normal concentrations, indicating a potential sensitive readout of treatment success. Building a machine learning multi-omic model that considers the concentrations of 10 proteins and five metabolites, we could predict patient survival with 92% accuracy (area under the receiver operating characteristic curve: 0.97) on the day of hospitalization. Hence, our standardized assays represent a unique opportunity for the early stratification of hospitalized COVID-19 patients.

Mapping the Serum Proteome of COVID-19 Patients; Guidance for Severity Assessment

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), whose outbreak in 2019 led to an ongoing pandemic with devastating consequences for the global economy and human health. According to the World Health Organization, COVID-19 has affected more than 481 million people worldwide, with 6 million confirmed deaths. The joint efforts of the scientific community have undoubtedly increased the pace of production of COVID-19 vaccines, but there is still so much uncharted ground to cover regarding the mechanisms of SARS-CoV-2 infection, replication and host response. These issues can be approached by proteomics with unprecedented capacity paving the way for the development of more efficient strategies for patient care. In this study, we present a deep proteome analysis that has been performed on a cohort of 72 COVID-19 patients aiming to identify serum proteins assessing the dynamics of the disease at different age ranges. A panel of 53 proteins that participate in several functions such as acute-phase response and inflammation, blood coagulation, cell adhesion, complement cascade, endocytosis, immune response, oxidative stress and tissue injury, have been correlated with patient severity, suggesting a molecular basis for their clinical stratification. Eighteen protein candidates were further validated by targeted proteomics in an independent cohort of 84 patients including a group of individuals that had satisfactorily resolved SARS-CoV-2 infection. Remarkably, all protein alterations were normalized 100 days after leaving the hospital, which further supports the reliability of the selected proteins as hallmarks of COVID-19 progression and grading. The optimized protein panel may prove its value for optimal severity assessment as well as in the follow up of COVID-19 patients.

Proteomics of Human Biological Fluids for Biomarker Discoveries: Technical Advances and Recent Applications

INTRODUCTION

Biological fluids are routine samples for diagnostic testing and monitoring. Blood samples are typically measured because of their moderate collection invasiveness and high information content on health and disease. Several body fluids, such as cerebrospinal fluid (CSF), are also studied and suited to specific pathologies. Over the last two decades proteomics has quested to identify protein biomarkers but with limited success. Recent technologies and refined pipelines have accelerated the profiling of human biological fluids.

AREAS COVERED

We review proteomic technologies for the identification of biomarkers. Those are based on antibodies/aptamers arrays or mass spectrometry (MS), but new ones are emerging. Advances in scalability and throughput have allowed to better design studies and cope with the limited sample size that had until now prevailed due to technological constraints. With these enablers, plasma/serum, CSF, saliva, tears, urine, and milk proteomes have been further profiled; we provide a non-exhaustive picture of some recent highlights (mainly covering literature from last five years in the Scopus database) using MS-based proteomics.

EXPERT OPINION

While proteomics has been in the shadow of genomics for years, proteomic tools and methodologies have reached a certain maturity. They are better suited to discover innovative and robust biofluid biomarkers.

Specialized interferon action in COVID-19

The impacts of interferon (IFN) signaling on COVID-19 pathology are multiple, with both protective and harmful effects being documented. We report here a multiomics investigation of systemic IFN signaling in hospitalized COVID-19 patients, defining the multiomics biosignatures associated with varying levels of 12 different type I, II, and III IFNs. The antiviral transcriptional response in circulating immune cells is strongly associated with a specific subset of IFNs, most prominently IFNA2 and IFNG. In contrast, proteomics signatures indicative of endothelial damage and platelet activation associate with high levels of IFNB1 and IFNA6. Seroconversion and time since hospitalization associate with a significant decrease in a specific subset of IFNs. Additionally, differential IFN subtype production is linked to distinct constellations of circulating myeloid and lymphoid immune cell types. Each IFN has a unique metabolic signature, with IFNG being the most associated with activation of the kynurenine pathway. IFNs also show differential relationships with clinical markers of poor prognosis and disease severity. For example, whereas IFNG has the strongest association with C-reactive protein and other immune markers of poor prognosis, IFNB1 associates with increased neutrophil to lymphocyte ratio, a marker of late severe disease. Altogether, these results reveal specialized IFN action in COVID-19, with potential diagnostic and therapeutic implications.

Reprogramming of red blood cell metabolism in Zika virus–infected donors

BACKGROUND

Diseases caused by arthropod-borne viruses remain a burden to global health; in particular, Zika virus (ZIKV) has been reported in 87 countries and territories. In healthy blood donors, ZIKV RNA can be detected in red blood cells (RBCs) months after infection, clearance of detectable nucleic acid in plasma, and seroconversion. However, little information is available on the impact of ZIKV infection to metabolism.

STUDY DESIGN AND METHODS

We applied mass spectrometry-based metabolomics and lipidomics approaches to investigate the impact of ZIKV infection on RBCs over the course of infection. ZIKV-infected blood donors (n = 25) were identified through molecular and serologic methods, which included nucleic acid amplification testing and real-time polymerase chain reaction (PCR) for detection of ZIKV RNA and enzyme-linked immunosorbent assay (ELISA) for detection of flavivirus-specific IgM and IgG.

RESULTS

In ZIKV RNA-positive donors, we observed lower glucose and lactate levels, and higher levels of ribose phosphate, suggestive of the activation of the pentose phosphate pathway. The top pathways altered in RBCs from ZIKV-IgM-positive donors include amino acid metabolism and biosynthesis, fatty acid metabolism and biosynthesis, linoleic acid and arachidonate metabolism and glutathione metabolism. RBCs from ZIKV-infected donors had increased levels of early glycolytic metabolites, and higher levels of metabolites of the pentose phosphate pathway. Alterations in acyl-carnitine and fatty acid metabolism are consistent with impaired membrane lipid homeostasis in RBCs from ZIKV IgM positive donors.

CONCLUSION

RBC from healthy blood donors who had been infected by ZIKV are characterized by long-lasting metabolic alterations even months after infection has resolved.

Immune mechanisms associated with sex-based differences in severe COVID-19 clinical outcomes

Background

Although biological males and females are equally likely to become infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), evidence has mounted that males experience higher severity and fatality compared to females.

Main

The objective of this review is to examine the existing literature on biological mechanisms underlying sex-based differences that could contribute to SARS-CoV-2 infection clinical outcomes. Sex-based differences in immunologic response and hormonal expression help explain the differences in coronavirus disease 2019 (COVID-19) outcomes observed in biological males and females. X inactivation facilitates a robust immune response to COVID-19 in females, who demonstrate a more profound antibody response and faster recovery when compared to males. Low testosterone levels also help explain the dysregulated inflammatory response and poor outcomes observed in some males with COVID-19. Gender differences in health expression and behaviors further compound these observed differences.

Conclusion

Understanding the biology of sex-based differences in COVID-19 severity and mortality could help inform preventative measures, treatment decisions, and development of personalized, sex-specific therapies.

Although most COVID-19 patients develop only mild disease, some mount a pronounced inflammatory response that results in severe pneumonia, respiratory failure, and death.

Male sex is a known risk factor for severe outcomes in COVID-19.

Biological sex-based differences in COVID-19 severity and mortality are influenced by genetic and hormonal differences at the cellular and immunologic level.

Biological sex-based differences are further complicated by environmental factors, namely social and cultural norms, that define gender roles which impact risk of infection and severe outcomes.

Understanding sex-based differences in COVID-19 outcomes will help inform clinical decision algorithms and treatment strategies to optimize the care of COVID-19 patients.

COVIDomics: The Proteomic and Metabolomic Signatures of COVID-19

Omics-based technologies have been largely adopted during this unprecedented global COVID-19 pandemic, allowing the scientific community to perform research on a large scale to understand the pathobiology of the SARS-CoV-2 infection and its replication into human cells. The application of omics techniques has been addressed to every level of application, from the detection of mutations, methods of diagnosis or monitoring, drug target discovery, and vaccine generation, to the basic definition of the pathophysiological processes and the biochemical mechanisms behind the infection and spread of SARS-CoV-2. Thus, the term COVIDomics wants to include those efforts provided by omics-scale investigations with application to the current COVID-19 research. This review summarizes the diverse pieces of knowledge acquired with the application of COVIDomics techniques, with the main focus on proteomics and metabolomics studies, in order to capture a common signature in terms of proteins, metabolites, and pathways dysregulated in COVID-19 disease. Exploring the multiomics perspective and the concurrent data integration may provide new suitable therapeutic solutions to combat the COVID-19 pandemic.

Compositional Data Analysis using Kernels in mass cytometry data

MOTIVATION

Cell-type abundance data arising from mass cytometry experiments are compositional in nature. Classical association tests do not apply to the compositional data due to their non-Euclidean nature. Existing methods for analysis of cell type abundance data suffer from several limitations for high-dimensional mass cytometry data, especially when the sample size is small.

RESULTS

We proposed a new multivariate statistical learning methodology, Compositional Data Analysis using Kernels (CODAK), based on the kernel distance covariance (KDC) framework to test the association of the cell type compositions with important predictors (categorical or continuous) such as disease status. CODAK scales well for high-dimensional data and provides satisfactory performance for small sample sizes (n < 25). We conducted simulation studies to compare the performance of the method with existing methods of analyzing cell type abundance data from mass cytometry studies. The method is also applied to a high-dimensional dataset containing different subgroups of populations including Systemic Lupus Erythematosus (SLE) patients and healthy control subjects.

AVAILABILITY AND IMPLEMENTATION

CODAK is implemented using R. The codes and the data used in this manuscript are available on the web at http://github.com/GhoshLab/CODAK/.

CONTACT

prudra@okstate.edu.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics Advances online.

The Impact of Age and BMI on the VWF/ADAMTS13 Axis and Simultaneous Thrombin and Plasmin Generation in Hospitalized COVID-19 Patients

Aging and obesity independently contribute toward an endothelial dysfunction that results in an imbalanced VWF to ADAMTS13 ratio. In addition, plasma thrombin and plasmin generation are elevated and reduced, respectively, with increasing age and also with increasing body mass index (BMI). The severity risk of Corona Virus Disease 2019 (COVID-19) increases in adults older than 65 and in individuals with certain pre-existing health conditions, including obesity (>30 kg/m²). The present cross-sectional study focused on an analysis of the VWF/ADAMTS13 axis, including measurements of von Willebrand factor (VWF) antigen (VWF:AG), VWF collagen binding activity (VWF:CBA), Factor VIII antigen, ADAMTS13 antigen, and ADAMTS13 activity, in addition to thrombin and plasmin generation potential, in a demographically diverse population of COVID-19 negative (−) (n = 288) and COVID-19 positive (+) (n = 543) patient plasmas collected at the time of hospital presentation. Data were analyzed as a whole, and then after dividing patients by age (<65 and ≥65) and independently by BMI [<18.5, 18.5–24.9, 25–29.9, >30 (kg/m²)]. These analyses suggest that VWF parameters (i.e., the VWF/ADAMTS13 activity ratio) and thrombin and plasmin generation differed in COVID-19 (+), as compared to COVID-19 (−) patient plasma. Further, age (≥65) more than BMI contributed to aberrant plasma indicators of endothelial coagulopathy. Based on these findings, evaluating both the VWF/ADAMTS13 axis, along with thrombin and plasmin generation, could provide insight into the extent of endothelial dysfunction as well as the plasmatic imbalance in coagulation and fibrinolysis potential, particularly for at-risk patient populations.

Association of cardiometabolic microRNAs with COVID-19 severity and mortality

AIMS

Coronavirus disease 2019 (COVID-19) can lead to multiorgan damage. MicroRNAs (miRNAs) in blood reflect cell activation and tissue injury. We aimed to determine the association of circulating miRNAs with COVID-19 severity and 28 day intensive care unit (ICU) mortality.

METHODS AND RESULTS

We performed RNA-Seq in plasma of healthy controls (n = 11), non-severe (n = 18), and severe (n = 18) COVID-19 patients and selected 14 miRNAs according to cell- and tissue origin for measurement by reverse transcription quantitative polymerase chain reaction (RT-qPCR) in a separate cohort of mild (n = 6), moderate (n = 39), and severe (n = 16) patients. Candidates were then measured by RT-qPCR in longitudinal samples of ICU COVID-19 patients (n = 240 samples from n = 65 patients). A total of 60 miRNAs, including platelet-, endothelial-, hepatocyte-, and cardiomyocyte-derived miRNAs, were differentially expressed depending on severity, with increased miR-133a and reduced miR-122 also being associated with 28 day mortality. We leveraged mass spectrometry-based proteomics data for corresponding protein trajectories. Myocyte-derived (myomiR) miR-133a was inversely associated with neutrophil counts and positively with proteins related to neutrophil degranulation, such as myeloperoxidase. In contrast, levels of hepatocyte-derived miR-122 correlated to liver parameters and to liver-derived positive (inverse association) and negative acute phase proteins (positive association). Finally, we compared miRNAs to established markers of COVID-19 severity and outcome, i.e. SARS-CoV-2 RNAemia, age, BMI, D-dimer, and troponin. Whilst RNAemia, age and troponin were better predictors of mortality, miR-133a and miR-122 showed superior classification performance for severity. In binary and triplet combinations, miRNAs improved classification performance of established markers for severity and mortality.

CONCLUSION

Circulating miRNAs of different tissue origin, including several known cardiometabolic biomarkers, rise with COVID-19 severity. MyomiR miR-133a and liver-derived miR-122 also relate to 28 day mortality. MiR-133a reflects inflammation-induced myocyte damage, whilst miR-122 reflects the hepatic acute phase response.

Multiomics integration-based molecular characterizations of COVID-19

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), rapidly became a global health challenge, leading to unprecedented social and economic consequences. The mechanisms behind the pathogenesis of SARS-CoV-2 are both unique and complex. Omics-scale studies are emerging rapidly and offer a tremendous potential to unravel the puzzle of SARS-CoV-2 pathobiology, as well as moving forward with diagnostics, potential drug targets, risk stratification, therapeutic responses, vaccine development and therapeutic innovation. This review summarizes various aspects of understanding multiomics integration-based molecular characterizations of COVID-19, which to date include the integration of transcriptomics, proteomics, genomics, lipidomics, immunomics and metabolomics to explore virus targets and developing suitable therapeutic solutions through systems biology tools. Furthermore, this review also covers an abridgment of omics investigations related to disease pathogenesis and virulence, the role of host genetic variation and a broad array of immune and inflammatory phenotypes contributing to understanding COVID-19 traits. Insights into this review, which combines existing strategies and multiomics integration profiling, may help further advance our knowledge of COVID-19.

Immunopathology and Immunosenescence, the Immunological Key Words of Severe COVID-19. Is There a Role for Stem Cell Transplantation?

The outcomes of Coronavirus disease-2019 (COVID-19) vary depending on the age, health status and sex of an individual, ranging from asymptomatic to lethal. From an immunologic viewpoint, the final severe lung damage observed in COVID-19 should be caused by cytokine storm, driven mainly by interleukin-6 and other pro-inflammatory cytokines. However, which immunopathogenic status precedes this "cytokine storm" and why the male older population is more severely affected, are currently unanswered questions. The aging of the immune system, i.e., immunosenescence, closely associated with a low-grade inflammatory status called "inflammageing," should play a key role. The remodeling of both innate and adaptive immune response observed with aging can partly explain the age gradient in severity and mortality of COVID-19. This review discusses how aging impacts the immune response to the virus, focusing on possible strategies to rejuvenate the immune system with stem cell-based therapies. Indeed, due to immunomodulatory and anti-inflammatory properties, multipotent mesenchymal stem cells (MSCs) are a worth-considering option against COVID-19 adverse outcomes.

Biological and Clinical Factors Contributing to the Metabolic Heterogeneity of Hospitalized Patients with and without COVID-19

The Corona Virus Disease 2019 (COVID-19) pandemic represents an ongoing worldwide challenge. The present large study sought to understand independent and overlapping metabolic features of samples from acutely ill patients (n = 831) that tested positive (n = 543) or negative (n = 288) for COVID-19. High-throughput metabolomics analyses were complemented with antigen and enzymatic activity assays on plasma from acutely ill patients collected while in the emergency department, at admission, or during hospitalization. Lipidomics analyses were also performed on COVID-19-positive or -negative subjects with the lowest and highest body mass index (n = 60/group). Significant changes in amino acid and fatty acid/acylcarnitine metabolism emerged as highly relevant markers of disease severity, progression, and prognosis as a function of biological and clinical variables in these patients. Further, machine learning models were trained by entering all metabolomics and clinical data from half of the COVID-19 patient cohort and then tested on the other half, yielding ~78% prediction accuracy. Finally, the extensive amount of information accumulated in this large, prospective, observational study provides a foundation for mechanistic follow-up studies and data sharing opportunities, which will advance our understanding of the characteristics of the plasma metabolism in COVID-19 and other acute critical illnesses.

The COVIDome Explorer researcher portal

COVID-19 pathology involves dysregulation of diverse molecular, cellular, and physiological processes. To expedite integrated and collaborative COVID-19 research, we completed multi-omics analysis of hospitalized COVID-19 patients, including matched analysis of the whole-blood transcriptome, plasma proteomics with two complementary platforms, cytokine profiling, plasma and red blood cell metabolomics, deep immune cell phenotyping by mass cytometry, and clinical data annotation. We refer to this multidimensional dataset as the COVIDome. We then created the COVIDome Explorer, an online researcher portal where the data can be analyzed and visualized in real time. We illustrate herein the use of the COVIDome dataset through a multi-omics analysis of biosignatures associated with C-reactive protein (CRP), an established marker of poor prognosis in COVID-19, revealing associations between CRP levels and damage-associated molecular patterns, depletion of protective serpins, and mitochondrial metabolism dysregulation. We expect that the COVIDome Explorer will rapidly accelerate data sharing, hypothesis testing, and discoveries worldwide.

A serum proteome signature to predict mortality in severe COVID-19 patients

Here, we recorded serum proteome profiles of 33 severe COVID-19 patients admitted to respiratory and intensive care units because of respiratory failure. We received, for most patients, blood samples just after admission and at two more later time points. With the aim to predict treatment outcome, we focused on serum proteins different in abundance between the group of survivors and non-survivors. We observed that a small panel of about a dozen proteins were significantly different in abundance between these two groups. The four structurally and functionally related type-3 cystatins AHSG, FETUB, histidine-rich glycoprotein, and KNG1 were all more abundant in the survivors. The family of inter-α-trypsin inhibitors, ITIH1, ITIH2, ITIH3, and ITIH4, were all found to be differentially abundant in between survivors and non-survivors, whereby ITIH1 and ITIH2 were more abundant in the survivor group and ITIH3 and ITIH4 more abundant in the non-survivors. ITIH1/ITIH2 and ITIH3/ITIH4 also showed opposite trends in protein abundance during disease progression. We defined an optimal panel of nine proteins for mortality risk assessment. The prediction power of this mortality risk panel was evaluated against two recent COVID-19 serum proteomics studies on independent cohorts measured in other laboratories in different countries and observed to perform very well in predicting mortality also in these cohorts. This panel may not be unique for COVID-19 as some of the proteins in the panel have previously been annotated as mortality markers in aging and in other diseases caused by different pathogens, including bacteria.

American College of Rheumatology Guidance for COVID-19 Vaccination in Patients With Rheumatic and Musculoskeletal Diseases: Version 1

OBJECTIVE

To provide guidance to rheumatology providers on the use of coronavirus disease 2019 (COVID-19) vaccines for patients with rheumatic and musculoskeletal diseases (RMDs).

METHODS

A task force was assembled that included 9 rheumatologists/immunologists, 2 infectious disease specialists, and 2 public health physicians. After agreeing on scoping questions, an evidence report was created that summarized the published literature and publicly available data regarding COVID-19 vaccine efficacy and safety, as well as literature for other vaccines in RMD patients. Task force members rated their agreement with draft consensus statements on a 9-point numerical scoring system, using a modified Delphi process and the RAND/University of California Los Angeles Appropriateness Method, with refinement and iteration over 2 sessions. Consensus was determined based on the distribution of ratings.

RESULTS

Despite a paucity of direct evidence, 74 draft guidance statements were developed by the task force and agreed upon with consensus to provide guidance for use of the COVID-19 vaccines in RMD patients and to offer recommendations regarding the use and timing of immunomodulatory therapies around the time of vaccination.

CONCLUSION

These guidance statements, made in the context of limited clinical data, are intended to provide direction to rheumatology health care providers on how to best use COVID-19 vaccines and to facilitate implementation of vaccination strategies for RMD patients.

SARS-CoV-2 RNAemia and proteomic trajectories inform prognostication in COVID-19 patients admitted to intensive care

Prognostic characteristics inform risk stratification in intensive care unit (ICU) patients with coronavirus disease 2019 (COVID-19). We obtained blood samples (n = 474) from hospitalized COVID-19 patients (n = 123), non-COVID-19 ICU sepsis patients (n = 25) and healthy controls (n = 30). Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA was detected in plasma or serum (RNAemia) of COVID-19 ICU patients when neutralizing antibody response was low. RNAemia is associated with higher 28-day ICU mortality (hazard ratio [HR], 1.84 [95% CI, 1.22-2.77] adjusted for age and sex). RNAemia is comparable in performance to the best protein predictors. Mannose binding lectin 2 and pentraxin-3 (PTX3), two activators of the complement pathway of the innate immune system, are positively associated with mortality. Machine learning identified 'Age, RNAemia' and 'Age, PTX3' as the best binary signatures associated with 28-day ICU mortality. In longitudinal comparisons, COVID-19 ICU patients have a distinct proteomic trajectory associated with mortality, with recovery of many liver-derived proteins indicating survival. Finally, proteins of the complement system and galectin-3-binding protein (LGALS3BP) are identified as interaction partners of SARS-CoV-2 spike glycoprotein. LGALS3BP overexpression inhibits spike-pseudoparticle uptake and spike-induced cell-cell fusion in vitro.

Delayed, transient and self-resolving neutropenia following COVID-19 pneumonia

A novel coronaravirus, identified as SARS-CoV-2, spread throughout the world in 2020. The COVID-19 pandemic has led to many discoveries and clinical manifestations. A young patient is presented with new, self-resolving neutropenia presenting weeks after a prolonged hospital stay for COVID-19 pneumonia. Workup included analysis for underlying infection, nutritional abnormalities, malignancy, medication and toxin exposure, all of which were negative. From 2020 to the present, few reports have described neutropenia associated with a recent COVID-19 infection. In particular, no reports have described a delayed presentation of neutropenia. The authors would like to propose that the significant inflammatory response associated with COVID-19 is likely what led to this patient's postviral neutropenia. Furthermore, in young healthy patients, bone marrow biopsy may be deferred and a watchful-waiting approach may be taken to assess for neutropenia resolution.

Biological and Clinical Factors contributing to the Metabolic Heterogeneity of Hospitalized Patients with and without COVID-19

The Corona Virus Disease 2019 (COVID-19) pandemic represents an ongoing worldwide challenge. Exploratory studies evaluating the impact of COVID-19 infection on the plasma metabolome have been performed, often with small numbers of patients, and with or without relevant control data; however, determining the impact of biological and clinical variables remains critical to understanding potential markers of disease severity and progression. The present large study, including relevant controls, sought to understand independent and overlapping metabolic features of samples from acutely ill patients (n = 831), testing positive (n = 543) or negative (n = 288) for COVID-19. High-throughput metabolomics analyses were complemented with antigen and enzymatic activity assays on 831 plasma samples from acutely ill patients while in the emergency department, at admission, and during hospitalization. We then performed additional lipidomics analyses of the 60 subjects with the lowest and highest body mass index, either COVID-19 positive or negative. Omics data were correlated to detailed data on patient characteristics and clinical laboratory assays measuring coagulation, hematology and chemistry analytes. Significant changes in arginine/proline/citrulline, tryptophan/indole/kynurenine, fatty acid and acyl-carnitine metabolism emerged as highly relevant markers of disease severity, progression and prognosis as a function of biological and clinical variables in these patients. Further, machine learning models were trained by entering all metabolomics and clinical data from half of the COVID-19 patient cohort and then tested on the other half yielding ~ 78% prediction accuracy. Finally, the extensive amount of information accumulated in this large, prospective, observational study provides a foundation for follow-up mechanistic studies and data sharing opportunities, which will advance our understanding of the characteristics of the plasma metabolism in COVID-19 and other acute critical illnesses.

Comparative immune profiling of acute respiratory distress syndrome patients with or without SARS-CoV-2 infection

Acute respiratory distress syndrome (ARDS) is the main complication of coronavirus disease 2019 (COVID-19), requiring admission to the intensive care unit (ICU). Despite extensive immune profiling of COVID-19 patients, to what extent COVID-19-associated ARDS differs from other causes of ARDS remains unknown. To address this question, here, we build 3 cohorts of patients categorized in COVID-19⁻ARDS⁺, COVID-19⁺ARDS⁺, and COVID-19⁺ARDS⁻, and compare, by high-dimensional mass cytometry, their immune landscape. A cell signature associating S100A9/calprotectin-producing CD169⁺ monocytes, plasmablasts, and Th1 cells is found in COVID-19⁺ARDS⁺, unlike COVID-19⁻ARDS⁺ patients. Moreover, this signature is essentially shared with COVID-19⁺ARDS⁻ patients, suggesting that severe COVID-19 patients, whether or not they experience ARDS, display similar immune profiles. We show an increase in CD14⁺HLA-DR^low and CD14^lowCD16⁺ monocytes correlating to the occurrence of adverse events during the ICU stay. We demonstrate that COVID-19-associated ARDS displays a specific immune profile and may benefit from personalized therapy in addition to standard ARDS management.

Machine-learning analysis of CyTOF data segregates COVID-19⁺ and COVID-19⁻ ARDS

CD169⁺S100A9⁺ monocytes differentiate COVID-19 ARDS from other ARDS

Monocyte compartment alterations correlate with other immune subset modifications

CD14⁺HLA-DR^low and CD14^loCD16⁺ monocytes are markers of adverse COVID-19 evolution

The COVIDome Explorer Researcher Portal

COVID-19 pathology involves dysregulation of diverse molecular, cellular, and physiological processes. In order to expedite integrated and collaborative COVID-19 research, we completed multi-omics analysis of hospitalized COVID-19 patients including matched analysis of the whole blood transcriptome, plasma proteomics with two complementary platforms, cytokine profiling, plasma and red blood cell metabolomics, deep immune cell phenotyping by mass cytometry, and clinical data annotation. We refer to this multidimensional dataset as the COVIDome. We then created the COVIDome Explorer, an online researcher portal where the data can be analyzed and visualized in real time. We illustrate here the use of the COVIDome dataset through a multi-omics analysis of biosignatures associated with C-reactive protein (CRP), an established marker of poor prognosis in COVID-19, revealing associations between CRP levels and damage-associated molecular patterns, depletion of protective serpins, and mitochondrial metabolism dysregulation. We expect that the COVIDome Explorer will rapidly accelerate data sharing, hypothesis testing, and discoveries worldwide.