Plasma biomarkers for systemic inflammation in COVID-19 survivors

A blood-based mRNA signature distinguishes people with Long COVID from recovered individuals

Introduction

Long COVID is a debilitating condition that lasts for more than three months post-infection by SARS-CoV-2. On average, one in ten individuals infected with SARS CoV- 2 develops Long COVID worldwide. A knowledge gap exists in our understanding of the mechanisms, genetic risk factors, and biomarkers that could be associated with Long COVID.

Methods

In this pilot study we used RNA-Seq to quantify the transcriptomes of peripheral blood mononuclear cells isolated from COVID-recovered individuals, seven with and seven without Long COVID symptoms (age- and sex-matched individuals), on average 6 months after infection.

Results

Seventy genes were identified as significantly up- or down-regulated in Long COVID samples, and the vast majority were downregulated. The most significantly up- or downregulated genes fell into two main categories, either associated with cell survival or with inflammation. This included genes such as ICOS (FDR p = 0.024) and S1PR1 (FDR p = 0.019) that were both up-regulated, indicating that a pro-inflammatory state is sustained in Long COVID PBMCs compared with COVID recovered PBMCs. Functional enrichment analysis identified that immune-related functions were expectedly predominant among the up- or down-regulated genes. The most frequently downregulated genes in significantly altered functional categories were two leukocyte immunoglobulin like receptors LILRB1 (FDR p = 0.005) and LILRB2 (FDR p = 0.027). PCA analysis demonstrated that LILRB1 and LILRB2 expression discriminated all of the Long COVID samples from COVID recovered samples.

Discussion

Downregulation of these inhibitory receptors similarly indicates a sustained pro-inflammatory state in Long COVID PBMCs. LILRB1 and LILRB2 should be validated as prospective biomarkers of Long COVID in larger cohorts, over time and against clinically overlapping conditions.

Immune activation and immune-associated neurotoxicity in Long-COVID: A systematic review and meta-analysis of 103 studies comprising 58 cytokines/chemokines/growth factors

BACKGROUND

Multiple studies have shown that Long COVID (LC) disease is associated with heightened immune activation, as evidenced by elevated levels of inflammatory mediators. However, there is no comprehensive meta-analysis focusing on activation of the immune inflammatory response system (IRS) and the compensatory immunoregulatory system (CIRS) along with other immune phenotypes in LC patients.

OBJECTIVES

This meta-analysis is designed to explore the IRS and CIRS profiles in LC patients, the individual cytokines, chemokines, growth factors, along with C-reactive protein (CRP) and immune-associated neurotoxicity.

METHODS

To gather relevant studies for our research, we conducted a thorough search using databases such as PubMed, Google Scholar, and SciFinder, covering all available literature up to July 5th, 2024.

RESULTS

The current meta-analysis encompassed 103 studies that examined multiple immune profiles, C-reactive protein, and 58 cytokines/chemokines/growth factors in 5502 LC patients versus 5962 normal controls (NC). LC patients showed significant increases in IRS/CIRS ratio (standardized mean difference (SMD: 0.156, confidence interval (CI): 0.062;0.250), IRS (SMD: 0.338, CI: 0.236;0.440), M1 macrophage (SMD: 0.371, CI: 0.263;0.480), T helper (Th)1 (SMD: 0.316, CI: 0.185;0.446), Th17 (SMD: 0.439, CI: 0.302;0.577) and immune-associated neurotoxicity (SMD: 0.384, CI: 0.271;0.497). In addition, CRP and 21 different cytokines displayed significantly elevated levels in LC patients compared to NC.

CONCLUSION

LC disease is characterized by IRS activation and increased immune-associated neurotoxicity.

Methods and clinical biomarker discovery for targeted proteomics using Olink technology

PURPOSE

This paper is to offer insights for designing research utilizing Olink technology to identify biomarkers and potential therapeutic targets for disease treatment.

EXPERIMENTAL DESIGN

We discusses the application of Olink technology in oncology, cardiovascular, respiratory and immune-related diseases, and Outlines the advantages and limitations of Olink technology.

RESULTS

Olink technology simplifies the search for therapeutic targets, advances proteomics research, reveals the pathogenesis of diseases, and ultimately helps patients develop precision treatments.

CONCLUSIONS

Although proteomics technology has been rapidly developed in recent years, each method has its own disadvantages, so in the future research, more methods should be selected for combined application to verify each other.

Blood Biomarkers of Long COVID: A Systematic Review

BACKGROUND

Long coronavirus disease (COVID; LC) affects millions of people worldwide. The exact mechanisms which result in a broad, undulating and detrimental symptom profile remain unknown. Blood biomarkers associated with LC have been described; however, consensus on these remains elusive, in part due to a lack of continuity between studies on a universally accepted definition of LC. This systematic review aimed to consolidate current knowledge of blood biomarkers associated with the prevalence of LC on the basis of the World Health Organisation (WHO) clinical definition of this condition.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Observational, cross-sectional, and randomised control studies published in the English language that studied blood biomarkers associated with the WHO definition of LC. All studies included participants who were ≥ 18 years old and group sizes ≥ 10 participants, and were compared against a control group without any known co-morbidities.

METHODS

A systematic literature search was conducted according to Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines and prospectively registered on Prospero (ID: CRD42022373121). The Cochrane, Embase, PubMed and Web of Science databases were searched from inception to January 2024. Search results were gathered using Rayyan software and data extracted using Microsoft Excel. The reporting recommendations for tumour markers prognostic studies (REMARK) questionnaire was used to assess the quality of the included studies.

RESULTS

A total of 45 observational and one interventional study comprising 4415 participants were included in this review which identified 525 blood biomarkers thought to be associated with LC. Three blood biomarker subtypes were associated with the development of LC: (1) immunological and inflammatory dysfunction, (2) endothelial/vascular dysfunction and (3) metabolic and clotting abnormalities.

DISCUSSION AND CONCLUSIONS

Our data are consistent with previous findings; however, no single biomarker was sufficiently associated with LC prevalence and instead a profile of biomarkers across various physiological systems may be more clinically useful. In all, 196 studies were excluded due to a lack of an adequately healthy comparator group and/or failure to meet the WHO LC definition. This demonstrates a need for further research incorporating a universal LC definition across all disease severity groups and symptom profiles, and longitudinal data reflecting the relapsing and remitting nature of this condition. Further investigation into blood biomarkers of LC, including clear reporting of healthy comparator groups and the investigation of acute and chronic biomarker changes, within the context of medical practice, may support the development of curative/restorative approaches.

sMR and PTX3 levels associate with COVID-19 outcome and survival but not with Long COVID

Biomarkers for monitoring COVID-19 disease course are lacking. Study aim was to identify biomarkers associated with disease severity, survival, long-term outcome, and Long COVID. As excessive macrophages activation is a hallmark of COVID-19 and complement activation is key in this, we selected the following proteins involved in these processes: PTX3, C1q, C1-INH, C1s/C1-INH, and sMR. EDTA-plasma concentrations were measured in 215 patients and 47 controls using ELISA. PTX3, sMR, C1-INH, and C1s/C1-INH levels were associated with disease severity. PTX3 and sMR were also associated with survival and long-term immune recovery. Lastly, sMR levels associate with ICU admittance. sMR (AUC 0.85) and PTX3 (AUC 0.78) are good markers for disease severity, especially when used in combination (AUC 0.88). No association between biomarker levels and Long COVID was observed. sMR has not previously been associated with COVID-19 disease severity, ICU admittance or survival and may serve as marker for disease course.

Proteomic profiling identifies biomarkers of COVID-19 severity

SARS-CoV-2 infection remains a major public health concern, particularly for the aged and those individuals with co-morbidities at risk for developing severe COVID-19. Understanding the pathogenesis and biomarkers associated with responses to SARS-CoV-2 infection remain critical components in developing effective therapeutic approaches, especially in cases of severe and long-COVID-19. In this study blood plasma protein expression was compared in subjects with mild, moderate, and severe COVID-19 disease. Evaluation of an inflammatory protein panel confirms upregulation of proteins including TNFβ, IL-6, IL-8, IL-12, already associated with severe cytokine storm and progression to severe COVID-19. Importantly, we identify several proteins not yet associated with COVID-19 disease, including mesothelin (MSLN), that are expressed at significantly higher levels in severe COVID-19 subjects. In addition, we find a subset of markers associated with T-cell and dendritic cell responses to viral infection that are significantly higher in mild cases and decrease in expression as severity of COVID-19 increases, suggesting that an immediate and effective activation of T-cells is critical in modulating disease progression. Together, our findings identify new targets for further investigation as therapeutic approaches for the treatment of SARS-CoV-2 infection and prevention of complications of severe COVID-19.

Disrupted epithelial permeability as a predictor of severe COVID-19 development

BACKGROUND

An impaired epithelial barrier integrity in the gastrointestinal tract is important to the pathogenesis of many inflammatory diseases. Accordingly, we assessed the potential of biomarkers of epithelial barrier dysfunction as predictive of severe COVID-19.

METHODS

Levels of bacterial DNA and zonulin family peptides (ZFP) as markers of bacterial translocation and intestinal permeability and a total of 180 immune and inflammatory proteins were analyzed from the sera of 328 COVID-19 patients and 49 healthy controls.

RESULTS

Significantly high levels of circulating bacterial DNA were detected in severe COVID-19 cases. In mild COVID-19 cases, serum bacterial DNA levels were significantly lower than in healthy controls suggesting epithelial barrier tightness as a predictor of a mild disease course. COVID-19 patients were characterized by significantly elevated levels of circulating ZFP. We identified 36 proteins as potential early biomarkers of COVID-19, and six of them (AREG, AXIN1, CLEC4C, CXCL10, CXCL11, and TRANCE) correlated strongly with bacterial translocation and can be used to predict and discriminate severe cases from healthy controls and mild cases (area under the curve (AUC): 1 and 0.88, respectively). Proteomic analysis of the serum of 21 patients with moderate disease at admission which progressed to severe disease revealed 10 proteins associated with disease progression and mortality (AUC: 0.88), including CLEC7A, EIF4EBP1, TRANCE, CXCL10, HGF, KRT19, LAMP3, CKAP4, CXADR, and ITGB6.

CONCLUSION

Our results demonstrate that biomarkers of intact or defective epithelial barriers are associated with disease severity and can provide early information on the prediction at the time of hospital admission.

Epidemiology, clinical presentation, pathophysiology, and management of long COVID: an update

The increasing number of coronavirus disease 2019 (COVID-19) infections have highlighted the long-term consequences of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection called long COVID. Although the concept and definition of long COVID are described differently across countries and institutions, there is general agreement that it affects multiple systems, including the immune, respiratory, cardiovascular, gastrointestinal, neuropsychological, musculoskeletal, and other systems. This review aims to provide a synthesis of published epidemiology, symptoms, and risk factors of long COVID. We also summarize potential pathophysiological mechanisms and biomarkers for precise prevention, early diagnosis, and accurate treatment of long COVID. Furthermore, we suggest evidence-based guidelines for the comprehensive evaluation and management of long COVID, involving treatment, health systems, health finance, public attitudes, and international cooperation, which is proposed to improve the treatment strategies, preventive measures, and public health policy making of long COVID.

Usefulness of the Veterans Health Administration COVID-19 (VACO) Index for Predicting Short-Term Mortality among Patients of the COLOS Study

Advanced age is known to be a predictor with COVID-19 severity. Understanding of other disease progression factors may shorten the time from patient admission to applied treatment. The Veterans Health Administration COVID-19 (VACO index) was assumed to additionally anticipate clinical results of patients hospitalized with a proven infection caused by the SARS-CoV-2 virus.

METHODS

The medical records of 2183 hospitalized patients were retrospectively analyzed. Patients were divided into four risk-of-death categories: low risk, medium risk, high-risk, and extreme risk depending on their VACO index calculation.

RESULTS

Significant differences in the mortality at the hospital after three months of discharge and six months after discharge were noticed. For the patients in the extreme-risk group, mortality reached 37.42%, 62.81%, and 78.44% for in-hospital, three months of discharge, and six months of discharge, respectively. The mortality marked as high risk reached 20.38%, 37.19%, and 58.77%. Moreover, the secondary outcomes analysis acknowledged that patients classified as extreme risk were more likely to suffer from cardiogenic shock, myocardial infarction, myocardial injury, stroke, pneumonia, acute kidney injury, and acute liver dysfunction. Patients at moderate risk were more often admitted to ICU when compared to other patients.

CONCLUSIONS

The usage of the VACO index, combined with an appropriate well-defined medical interview and past medical history, tends to be a helpful instrument in order to predict short-term mortality and disease progression based on previous medical records.

Demonstration of the impact of COVID-19 on metabolic associated fatty liver disease by bioinformatics and system biology approach

BACKGROUND

Severe coronavirus disease 2019 (COVID-19) has caused a great threat to human health. Metabolic associated fatty liver disease (MAFLD) is a liver disease with a high prevalence rate. Previous studies indicated that MAFLD led to increased mortality and severe case rates of COVID-19 patients, but its mechanism remains unclear.

METHODS

This study analyzed the transcriptional profiles of COVID-19 and MAFLD patients and their respective healthy controls from the perspectives of bioinformatics and systems biology to explore the underlying molecular mechanisms between the 2 diseases. Specifically, gene expression profiles of COVID-19 and MAFLD patients were acquired from the gene expression omnibus datasets and screened shared differentially expressed genes (DEGs). Gene ontology and pathway function enrichment analysis were performed for common DEGs to reveal the regulatory relationship between the 2 diseases. Besides, the hub genes were extracted by constructing a protein-protein interaction network of shared DEGs. Based on these hub genes, we conducted regulatory network analysis of microRNA/transcription factors-genes and gene - disease relationship and predicted potential drugs for the treatment of COVID-19 and MAFLD.

RESULTS

A total of 3734 and 589 DEGs were screened from the transcriptome data of MAFLD (GSE183229) and COVID-19 (GSE196822), respectively, and 80 common DEGs were identified between COVID-19 and MAFLD. Functional enrichment analysis revealed that the shared DEGs were involved in inflammatory reaction, immune response and metabolic regulation. In addition, 10 hub genes including SERPINE1, IL1RN, THBS1, TNFAIP6, GADD45B, TNFRSF12A, PLA2G7, PTGES, PTX3 and GADD45G were identified. From the interaction network analysis, 41 transcription factors and 151 micro-RNAs were found to be the regulatory signals. Some mental, Inflammatory, liver diseases were found to be most related with the hub genes. Importantly, parthenolide, luteolin, apigenin and MS-275 have shown possibility as therapeutic agents against COVID-19 and MAFLD.

CONCLUSION

This study reveals the potential common pathogenesis between MAFLD and COVID-19, providing novel clues for future research and treatment of MAFLD and severe acute respiratory syndrome coronavirus 2 infection.

Plasma proteome of Long-COVID patients indicates HIF-mediated vasculo-proliferative disease with impact on brain and heart function

AIMS

Long-COVID occurs after SARS-CoV-2 infection and results in diverse, prolonged symptoms. The present study aimed to unveil potential mechanisms, and to inform prognosis and treatment.

METHODS

Plasma proteome from Long-COVID outpatients was analyzed in comparison to matched acutely ill COVID-19 (mild and severe) inpatients and healthy control subjects. The expression of 3072 protein biomarkers was determined with proximity extension assays and then deconvoluted with multiple bioinformatics tools into both cell types and signaling mechanisms, as well as organ specificity.

RESULTS

Compared to age- and sex-matched acutely ill COVID-19 inpatients and healthy control subjects, Long-COVID outpatients showed natural killer cell redistribution with a dominant resting phenotype, as opposed to active, and neutrophils that formed extracellular traps. This potential resetting of cell phenotypes was reflected in prospective vascular events mediated by both angiopoietin-1 (ANGPT1) and vascular-endothelial growth factor-A (VEGFA). Several markers (ANGPT1, VEGFA, CCR7, CD56, citrullinated histone 3, elastase) were validated by serological methods in additional patient cohorts. Signaling of transforming growth factor-β1 with probable connections to elevated EP/p300 suggested vascular inflammation and tumor necrosis factor-α driven pathways. In addition, a vascular proliferative state associated with hypoxia inducible factor 1 pathway suggested progression from acute COVID-19 to Long-COVID. The vasculo-proliferative process predicted in Long-COVID might contribute to changes in the organ-specific proteome reflective of neurologic and cardiometabolic dysfunction.

CONCLUSIONS

Taken together, our findings point to a vasculo-proliferative process in Long-COVID that is likely initiated either prior hypoxia (localized or systemic) and/or stimulatory factors (i.e., cytokines, chemokines, growth factors, angiotensin, etc). Analyses of the plasma proteome, used as a surrogate for cellular signaling, unveiled potential organ-specific prognostic biomarkers and therapeutic targets.

Plasma proteome dynamics of COVID-19 severity learnt by a graph convolutional network of multi-scale topology

Efforts to understand the molecular mechanisms of COVID-19 have led to the identification of ACE2 as the main receptor for the SARS-CoV-2 spike protein on cell surfaces. However, there are still important questions about the role of other proteins in disease progression. To address these questions, we modelled the plasma proteome of 384 COVID-19 patients using protein level measurements taken at three different times and incorporating comprehensive clinical evaluation data collected 28 d after hospitalisation. Our analysis can accurately assess the severity of the illness using a metric based on WHO scores. By using topological vectorisation, we identified proteins that vary most in expression based on disease severity, and then utilised these findings to construct a graph convolutional network. This dynamic model allows us to learn the molecular interactions between these proteins, providing a tool to determine the severity of a COVID-19 infection at an early stage and identify potential pharmacological treatments by studying the dynamic interactions between the most relevant proteins.

Acute and postacute COVID-19 outcomes for patients with rheumatoid arthritis: lessons learned and emerging directions 3 years into the pandemic

PURPOSE OF REVIEW

To summarize the findings of studies investigating patients with rheumatoid arthritis (RA) and risk of acute and postacute COVID-19 outcomes 3 years into the pandemic.

RECENT FINDINGS

Most studies early in the pandemic included all patients with systemic autoimmune rheumatic diseases (SARDs), not only those with RA, due to limited sample size. Many of these studies found that patients with SARDs were at higher risk of COVID-19 infection and severe outcomes, including hospitalization, hyperinflammation, mechanical ventilation, and death. Studies performed later were able to focus on RA and found similar associations, while also identifying RA-specific factors such as immunosuppressive medications, disease activity/severity, and interstitial lung disease as risk factors for severe COVID-19. After COVID-19 vaccination, the risks for COVID-19 infection and severity were reduced for patients with RA, but a gap between the general population persisted, and some patients with RA are susceptible to breakthrough infection after vaccination. Preexposure prophylaxis, effective treatments, and changes in viral variants have also contributed to improved COVID-19 outcomes throughout the pandemic. Emerging data suggest that patients with RA may be at risk for postacute sequelae of COVID-19 (PASC).

SUMMARY

Although COVID-19 outcomes have improved over the pandemic for patients with RA, some experience poor acute and postacute outcomes after COVID-19. Clinicians and patients should remain vigilant about risk mitigation for infection and consider early treatment for RA patients with COVID-19. Future studies are needed to investigate clinical outcomes and mechanisms of PASC among patients with RA.

Cellular and molecular biomarkers of long COVID: a scoping review

BACKGROUND

Long-COVID (LC) encompasses diverse symptoms lasting months after the initial SARS-CoV-2 infection. Symptoms can be debilitating and affect the quality of life of individuals with LC and their families. Although the symptoms of LC are well described, the aetiology of LC remains unclear, and consequently, patients may be underdiagnosed. Identification of LC specific biomarkers is therefore paramount for the diagnosis and clinical management of the syndrome. This scoping review describes the molecular and cellular biomarkers that have been identified to date with potential use for diagnosis or prediction of LC.

METHODS

This review was conducted using the Joanna Briggs Institute (JBI) Methodology for Scoping Reviews. A search was executed in the MEDLINE and EMBASE databases, as well as in the grey literature for original studies, published until October 5th, 2022, reporting biomarkers identified in participants with LC symptoms (from all ages, ethnicities, and sex), with a previous infection of SARS-CoV-2. Non-English studies, cross-sectional studies, studies without a control group, and pre-prints were excluded. Two reviewers independently evaluated the studies, extracted population data and associated biomarkers.

FINDINGS

23 cohort studies were identified, involving 2163 LC patients [median age 51.8 years, predominantly female sex (61.10%), white (75%), and non-vaccinated (99%)]. A total of 239 candidate biomarkers were identified, consisting mainly of immune cells, immunoglobulins, cytokines, and other plasma proteins. 19 of the 239 candidate biomarkers identified were evaluated by the authors, by means of receiver operating characteristic (ROC) curves.

INTERPRETATION

Diverse cellular and molecular biomarkers for LC have been proposed. Validation of candidate biomarkers in independent samples should be prioritized. Modest reported performance (particularly in larger studies) suggests LC may encompass many distinct aetiologies, which should be explored e.g., by stratifying by symptom clusters and/or sex.

FUNDING

Dr. Tebbutt has received funding from the Canadian Institutes of Health Research (177747) to conduct this work. The funding source was not involved in this scoping review, or in the decision to submit this manuscript for publication.

Biomarkers in long COVID-19: A systematic review

Purpose

Long COVID, also known as post-acute sequelae of COVID-19, refers to the constellation of long-term symptoms experienced by people suffering persistent symptoms for one or more months after SARS-CoV-2 infection. Blood biomarkers can be altered in long COVID patients; however, biomarkers associated with long COVID symptoms and their roles in disease progression remain undetermined. This study aims to systematically evaluate blood biomarkers that may act as indicators or therapeutic targets for long COVID.

Methods

A systematic literature review in PubMed, Embase, and CINAHL was performed on 18 August 2022. The search keywords long COVID-19 symptoms and biomarkers were used to filter out the eligible studies, which were then carefully evaluated.

Results

Identified from 28 studies and representing six biological classifications, 113 biomarkers were significantly associated with long COVID: (1) Cytokine/Chemokine (38, 33.6%); (2) Biochemical markers (24, 21.2%); (3) Vascular markers (20, 17.7%); (4) Neurological markers (6, 5.3%); (5) Acute phase protein (5, 4.4%); and (6) Others (20, 17.7%). Compared with healthy control or recovered patients without long COVID symptoms, 79 biomarkers were increased, 29 were decreased, and 5 required further determination in the long COVID patients. Of these, up-regulated Interleukin 6, C-reactive protein, and tumor necrosis factor alpha might serve as the potential diagnostic biomarkers for long COVID. Moreover, long COVID patients with neurological symptoms exhibited higher levels of neurofilament light chain and glial fibrillary acidic protein whereas those with pulmonary symptoms exhibited a higher level of transforming growth factor beta.

Conclusion

Long COVID patients present elevated inflammatory biomarkers after initial infection. Our study found significant associations between specific biomarkers and long COVID symptoms. Further investigations are warranted to identify a core set of blood biomarkers that can be used to diagnose and manage long COVID patients in clinical practice.

Plasma proteome responses in zebrafish following λ-carrageenan-Induced inflammation are mediated by PMN leukocytes and correlate highly with their human counterparts

Regulation of inflammation is a critical process for maintaining physiological homeostasis. The λ-carrageenan (λ-CGN) is a mucopolysaccharide extracted from the cell wall of red algae (Chondrus crispus) capable of inducing acute intestinal inflammation, which is translated into the production of acute phase reactants secreted into the blood circulation. However, the associated mechanisms in vertebrates are not well understood. Here, we investigated the crucial factors behind the inflammatory milieu of λ-CGN-mediated inflammation administered at 0, 1.75, and 3.5% (v/w) by i.p. injection into the peritoneal cavity of adult zebrafish (ZF) (Danio rerio). We found that polymorphonuclear leukocytes (neutrophils) and lymphocytes infiltrating the ZF peritoneal cavity had short-term persistence. Nevertheless, they generate a strong pattern of inflammation that affects systemically and is enough to produce edema in the cavity. Consistent with these findings, cell infiltration, which causes notable tissue changes, resulted in the overexpression of several acute inflammatory markers at the protein level. Using reversed-phase high-performance liquid chromatography followed by a hybrid linear ion-trap mass spectrometry shotgun proteomic approach, we identified 2938 plasma proteins among the animals injected with PBS and 3.5% λ-CGN. First, the bioinformatic analysis revealed the composition of the plasma proteome. Interestingly, 72 commonly expressed proteins were recorded among the treated and control groups, but, surprisingly, 2830 novel proteins were differentially expressed exclusively in the λ-CGN-induced group. Furthermore, from the commonly expressed proteins, compared to the control group 62 proteins got a significant (p < 0.05) upregulation in the λ-CGN-treated group, while the remaining ten proteins were downregulated. Next, we obtained the major protein-protein interaction networks between hub protein clusters in the blood plasma of the λ-CGN induced group. Moreover, to understand the molecular underpinnings of these effects based on the unveiled protein sets, we performed a bioinformatic structural similarity analysis and generated overlapping 3D reconstructions between ZF and humans during acute inflammation. Biological pathway analysis pointed to the activation and abundance of diverse classical immune and acute phase reactants, several catalytic enzymes, and varied proteins supporting the immune response. Together, this information can be used for testing and finding novel pharmacological targets to treat human intestinal inflammatory diseases.

Plasma biomarkers for systemic inflammation in COVID-19 survivors

BACKGROUND

While the majority of COVID-19 patients fully recover from the infection and become asymptomatic, a significant proportion of COVID-19 survivors experience a broad spectrum of symptoms lasting weeks to months post-infection, a phenomenon termed "post-acute sequelae of COVID-19 (PASC)." The aim of this study is to determine whether inflammatory proteins are dysregulated and can serve as potential biomarkers for systemic inflammation in COVID-19 survivors.

METHODS

We determined the levels of inflammatory proteins in plasma from 22 coronavirus disease 2019 (COVID-19) long haulers (COV-LH), 22 COVID-19 asymptomatic survivors (COV-AS), and 22 healthy subjects (HS) using an Olink proteomics assay and assessed the results by a beads-based multiplex immunoassay.

RESULTS

Compared to HS, we found that COVID-19 survivors still exhibited systemic inflammation, as evidenced by significant changes in the levels of multiple inflammatory proteins in plasma from both COV-LH and COV-AS. CXCL10 was the only protein that significantly upregulated in COV-LH compared with COV-AS and HS.

CONCLUSIONS

Our results indicate that several inflammatory proteins remain aberrantly dysregulated in COVID-19 survivors and CXCL10 might serve as a potential biomarker to typify COV-LH. Further characterization of these signature inflammatory molecules might improve the understanding of the long-term impacts of COVID-19 and provide new targets for the diagnosis and treatment of COVID-19 survivors with PASC.