Microvascular and proteomic signatures overlap in COVID-19 and bacterial sepsis: the MICROCODE study

Association between the lactate-albumin ratio and microcirculation changes in Pediatric Septic patients

A lactate/albumin ratio (LAR) greater than 0.5 measured early in the course of pediatric critical illness is associated with greater mortality. Whether the elevated LAR can be explained by microcirculation disorders in children with sepsis is not known. In this longitudinal retrospective study (January 2021-January 2024), serum albumin and lactate were measured on admission to the pediatric intensive care unit (PICU), with sublingual video microscopy performed simultaneously to measure microcirculation. A total of 178 children were included, 37% of whom had septic shock measured with the Phoenix Sepsis Score. Patients with remote sepsis had greater odds of an elevated LAR (aOR 6.87: 95% CI 1.98-23.73; p < 0.01). Children with an elevated LAR had more microvascular blood flow abnormalities (aOR 1.31 95% CI 1.08-1.58; p < 0.01), lower 4-6-micron capillary density (aOR 1.03 95% CI 1.01-1.05; p < 0.01) and greater odds of dying (aOR 3.55 95% CI 1.21-10.38; p = 0.02) compared to those with a low LAR. We found no association between LAR and endothelial glycocalyx degradation. A normal LAR is associated with less risk of microcirculatory injury (aOR 0.77 95% CI 0.65-0.93; p < 0.01). In children with sepsis, an elevated LAR is associated with microcirculation abnormalities (microvascular density and flow). The lactate/albumin ratio is a potentially useful biomarker for microcirculatory injury in sepsis.

Interleukin-6 drives endothelial glycocalyx damage in COVID-19 and bacterial sepsis

Damage of the endothelial glycocalyx (eGC) plays a central role in the development of vascular hyperpermeability and organ damage during systemic inflammation. However, the specific signalling pathways for eGC damage remain poorly defined. Aim of this study was to combine sublingual video-microscopy, plasma proteomics and live cell imaging to uncover further pathways of eGC damage in patients with coronavirus disease 2019 (COVID-19) or bacterial sepsis. This secondary analysis of the prospective multicenter MICROCODE study included 22 patients with COVID-19 and 43 patients with bacterial sepsis admitted to intermediate or intensive care units and 10 healthy controls. Interleukin-6 (IL-6) was strongly associated with damaged eGC and correlated both with eGC dimensions (rs=0.36, p = 0.0015) and circulating eGC biomarkers. In vitro, IL-6 reduced eGC height and coverage, which was inhibited by blocking IL-6 signalling with the anti-IL-6 receptor antibody tocilizumab or the Janus kinase inhibitor tofacitinib. Exposure of endothelial cells to 5% serum from COVID-19 or sepsis patients resulted in a significant decrease in eGC height, which was attenuated by co-incubation with tocilizumab. In an external COVID-19 cohort of 219 patients from Massachusetts General Hospital, a previously identified proteomic eGC signature correlated with IL-6 (rs=-0.58, p < 0.0001) and predicted the combined endpoint of 28-day mortality and/or intubation (ROC-AUC: 0.86 [95% CI: 0.81-0.91], p < 0.001). The data suggest that IL-6 may significantly drive eGC damage in COVID-19 and bacterial sepsis. Our findings provide valuable insights into pathomechanisms of vascular dysfunction during systemic inflammation and highlight the need for further in vivo studies.

A reduced proteomic signature in critically ill Covid-19 patients determined with plasma antibody micro-array and machine learning

BACKGROUND

COVID-19 is a complex, multi-system disease with varying severity and symptoms. Identifying changes in critically ill COVID-19 patients' proteomes enables a better understanding of markers associated with susceptibility, symptoms, and treatment. We performed plasma antibody microarray and machine learning analyses to identify novel proteins of COVID-19.

METHODS

A case-control study comparing the concentration of 2000 plasma proteins in age- and sex-matched COVID-19 inpatients, non-COVID-19 sepsis controls, and healthy control subjects. Machine learning was used to identify a unique proteome signature in COVID-19 patients. Protein expression was correlated with clinically relevant variables and analyzed for temporal changes over hospitalization days 1, 3, 7, and 10. Expert-curated protein expression information was analyzed with Natural language processing (NLP) to determine organ- and cell-specific expression.

RESULTS

Machine learning identified a 28-protein model that accurately differentiated COVID-19 patients from ICU non-COVID-19 patients (accuracy = 0.89, AUC = 1.00, F1 = 0.89) and healthy controls (accuracy = 0.89, AUC = 1.00, F1 = 0.88). An optimal nine-protein model (PF4V1, NUCB1, CrkL, SerpinD1, Fen1, GATA-4, ProSAAS, PARK7, and NET1) maintained high classification ability. Specific proteins correlated with hemoglobin, coagulation factors, hypertension, and high-flow nasal cannula intervention (P < 0.01). Time-course analysis of the 28 leading proteins demonstrated no significant temporal changes within the COVID-19 cohort. NLP analysis identified multi-system expression of the key proteins, with the digestive and nervous systems being the leading systems.

CONCLUSIONS

The plasma proteome of critically ill COVID-19 patients was distinguishable from that of non-COVID-19 sepsis controls and healthy control subjects. The leading 28 proteins and their subset of 9 proteins yielded accurate classification models and are expressed in multiple organ systems. The identified COVID-19 proteomic signature helps elucidate COVID-19 pathophysiology and may guide future COVID-19 treatment development.

The modes of angiogenesis: an updated perspective

Following the process of vasculogenesis during development, angiogenesis generates new vascular structures through a variety of different mechanisms or modes. These different modes of angiogenesis involve, for example, increasing microvasculature density by sprouting of endothelial cells, splitting of vessels to increase vascular surface area by intussusceptive angiogenesis, fusion of capillaries to increase blood flow by coalescent angiogenesis, and the recruitment of non-endothelial cells by vasculogenic mimicry. The recent reporting on coalescent angiogenesis as a new mode of vessel formation warrants a brief overview of angiogenesis mechanisms to provide a more complete picture. The journal Angiogenesis is devoted to the delineation of the different modes and mechanisms that collectively dictate blood vessel formation, inhibition, and function in health and disease.

Bedside Hyperspectral Imaging and Organ Dysfunction Severity in Critically Ill COVID-19 Patients-A Prospective, Monocentric Observational Study

Hyperspectral imaging (HSI) is a non-invasive technology that provides information on biochemical tissue properties, including skin oxygenation and perfusion quality. Microcirculatory alterations are associated with organ dysfunction in septic COVID-19 patients. This prospective observational study investigated associations between skin HSI and organ dysfunction severity in critically ill COVID-19 patients. During the first seven days in the ICU, palmar HSI measurements were carried out with the TIVITA® tissue system. We report data from 52 critically ill COVID-19 patients, of whom 40 required extracorporeal membrane oxygenation (ECMO). HSI parameters for superficial tissue oxygenation (StO2) and oxygenation and perfusion quality (NPI) were persistently decreased. Hemoglobin tissue content (THI) increased, and tissue water content (TWI) was persistently elevated. Regression analysis showed strong indications for an association of NPI and weaker indications for associations of StO2, THI, and TWI with sequential organ failure assessment (SOFA) scoring. StO2 and NPI demonstrated negative associations with vasopressor support and lactate levels as well as positive associations with arterial oxygen saturation. These results suggest that skin HSI provides clinically relevant information, opening new perspectives for microcirculatory monitoring in critical care.

Analysis of Urinary Glycosaminoglycans to Predict Outcome in COVID-19 and Community-Acquired Pneumonia-A Proof-of-Concept Study

Although coronavirus disease 2019 (COVID-19) is considered a systemic disease associated with vascular inflammation and eventual destruction of the protective endothelial glycocalyx (eGC), biomarkers of eGC damage are not yet available in the clinic. The most prominent components of eGC are sulphated glycosaminoglycans (sGAGs) attached to core proteoglycans. We hypothesised that the amount of sGAG fragments shed in urine (as a surrogate for systemic eGC damage) would correlate with disease severity and outcome. Total urinary sGAG concentration was measured using an in-house optimised 1,9-dimethylmethylene blue (DMMB) assay, which is highly accurate and insensitive to interferences. The median urinary sGAG concentration was significantly higher in 67 hospitalised patients with COVID-19 compared to 72 hospitalised patients with community-acquired pneumonia (CAP). In both groups, urinary sGAG concentrations predicted a combined endpoint (including intubation and death) with an area under the receiver operator characteristic curve of 0.72 (95% CI 0.55-0.88, p = 0.01) and 0.70 (95% CI 0.57-0.83, p = 0.007), respectively. In conclusion, the inexpensive and easy-to-perform DMMB assay provides a surrogate parameter for eGC damage that may be useful for risk stratification of patients with COVID-19 and CAP.

Pathological angiogenesis: mechanisms and therapeutic strategies

In multicellular organisms, angiogenesis, the formation of new blood vessels from pre-existing ones, is an essential process for growth and development. Different mechanisms such as vasculogenesis, sprouting, intussusceptive, and coalescent angiogenesis, as well as vessel co-option, vasculogenic mimicry and lymphangiogenesis, underlie the formation of new vasculature. In many pathological conditions, such as cancer, atherosclerosis, arthritis, psoriasis, endometriosis, obesity and SARS-CoV-2(COVID-19), developmental angiogenic processes are recapitulated, but are often done so without the normal feedback mechanisms that regulate the ordinary spatial and temporal patterns of blood vessel formation. Thus, pathological angiogenesis presents new challenges yet new opportunities for the design of vascular-directed therapies. Here, we provide an overview of recent insights into blood vessel development and highlight novel therapeutic strategies that promote or inhibit the process of angiogenesis to stabilize, reverse, or even halt disease progression. In our review, we will also explore several additional aspects (the angiogenic switch, hypoxia, angiocrine signals, endothelial plasticity, vessel normalization, and endothelial cell anergy) that operate in parallel to canonical angiogenesis mechanisms and speculate how these processes may also be targeted with anti-angiogenic or vascular-directed therapies.

Personalizing Care for Critically Ill Adults Using Omics: A Concise Review of Potential Clinical Applications

Current guidelines for critically ill patients use broad recommendations to promote uniform protocols for the management of conditions such as acute kidney injury, acute respiratory distress syndrome, and sepsis. Although these guidelines have enabled the substantial improvement of care, mortality for critical illness remains high. Further outcome improvement may require personalizing care for critically ill patients, which involves tailoring management strategies for different patients. However, the current understanding of disease heterogeneity is limited. For critically ill patients, genomics, transcriptomics, proteomics, and metabolomics have illuminated such heterogeneity and unveiled novel biomarkers, giving clinicians new means of diagnosis, prognosis, and monitoring. With further engineering and economic development, omics would then be more accessible and affordable for frontline clinicians. As the knowledge of pathophysiological pathways mature, targeted treatments can then be developed, validated, replicated, and translated into clinical practice.

Combining Deep Phenotyping of Serum Proteomics and Clinical Data via Machine Learning for COVID-19 Biomarker Discovery

The persistence of long-term coronavirus-induced disease 2019 (COVID-19) sequelae demands better insights into its natural history. Therefore, it is crucial to discover the biomarkers of disease outcome to improve clinical practice. In this study, 160 COVID-19 patients were enrolled, of whom 80 had a "non-severe" and 80 had a "severe" outcome. Sera were analyzed by proximity extension assay (PEA) to assess 274 unique proteins associated with inflammation, cardiometabolic, and neurologic diseases. The main clinical and hematochemical data associated with disease outcome were grouped with serological data to form a dataset for the supervised machine learning techniques. We identified nine proteins (i.e., CD200R1, MCP1, MCP3, IL6, LTBP2, MATN3, TRANCE, α2-MRAP, and KIT) that contributed to the correct classification of COVID-19 disease severity when combined with relative neutrophil and lymphocyte counts. By analyzing PEA, clinical and hematochemical data with statistical methods that were able to handle many variables in the presence of a relatively small sample size, we identified nine potential serum biomarkers of a "severe" outcome. Most of these were confirmed by literature data. Importantly, we found three biomarkers associated with central nervous system pathologies and protective factors, which were downregulated in the most severe cases.

Publication trends of research on COVID-19 and host immune response: A bibliometric analysis

Introduction

As the first bibliometric analysis of COVID-19 and immune responses, this study will provide a comprehensive overview of the latest research advances. We attempt to summarize the scientific productivity and cooperation across countries and institutions using the bibliometric methodology. Meanwhile, using clustering analysis of keywords, we revealed the evolution of research hotspots and predicted future research focuses, thereby providing valuable information for the follow-up studies.

Methods

We selected publications on COVID-19 and immune response using our pre-designed search strategy. Web of Science was applied to screen the eligible publications for subsequent bibliometric analyses. GraphPad Prism 8.0, VOSviewer, and CiteSpace were applied to analyze the research trends and compared the contributions of countries, authors, institutions, and journals to the global publications in this field.

Results

We identified 2,200 publications on COVID-19 and immune response published between December 1, 2019, and April 25, 2022, with a total of 3,154 citations. The United States (611), China (353), and Germany (209) ranked the top three in terms of the number of publications, accounting for 53.3% of the total articles. Among the top 15 institutions publishing articles in this area, four were from France, four were from the United States, and three were from China. The journal Frontiers in Immunology published the most articles (178) related to COVID-19 and immune response. Alessandro Sette (31 publications) from the United States were the most productive and influential scholar in this field, whose publications with the most citation frequency (3,633). Furthermore, the development and evaluation of vaccines might become a hotspot in relevant scope.

Conclusions

The United States makes the most indispensable contribution in this field in terms of publication numbers, total citations, and H-index. Although publications from China also take the lead regarding quality and quantity, their international cooperation and preclinical research need to be further strengthened. Regarding the citation frequency and the total number of published articles, the latest research progress might be tracked in the top-ranking journals in this field. By analyzing the chronological order of the appearance of retrieved keywords, we speculated that vaccine-related research might be the novel focus in this field.