Single-cell multi-omics analysis of COVID-19 patients with pre-existing autoimmune diseases shows aberrant immune responses to infection.

In COVID-19, hyperinflammatory and dysregulated immune responses contribute to severity. Patients with pre-existing autoimmune conditions can therefore be at increased risk of severe COVID-19 and/or associated sequelae, yet SARS-CoV-2 infection in this group has been little studied. Here, we performed single-cell analysis of peripheral blood mononuclear cells from patients with three major autoimmune diseases (rheumatoid arthritis, psoriasis, or multiple sclerosis) during SARS-CoV-2 infection. We observed compositional differences between the autoimmune disease groups coupled with altered patterns of gene expression, transcription factor activity, and cell-cell communication that substantially shape the immune response under SARS-CoV-2 infection. While enrichment of HLA-DRlow CD14+ monocytes was observed in all three autoimmune disease groups, type-I interferon signaling as well as inflammatory T cell and monocyte responses varied widely between the three groups of patients. Our results reveal disturbed immune responses to SARS-CoV-2 in patients with pre-existing autoimmunity, highlighting important considerations for disease treatment and follow-up.

Use of Biomarkers to Improve 28-Day Mortality Stratification in Patients with Sepsis and SOFA ≤ 6.

Early diagnosis and appropriate treatments are crucial to reducing mortality risk in septic patients. Low SOFA scores and current biomarkers may not adequately discern patients that could develop severe organ dysfunction or have an elevated mortality risk. The aim of this prospective observational study was to evaluate the predictive value of the biomarkers mid-regional pro-adrenomedullin (MR-proADM), procalcitonin (PCT), C-reactive protein (CRP), and lactate for 28-day mortality in patients with sepsis, and patients with a SOFA score ≤6. 284 were included, with a 28-day all-cause mortality of 8.45% (n = 24). Non-survivors were older (p = 0.003), required mechanical ventilation (p = 0.04), were ventilated for longer (p = 0.02), and had higher APACHE II (p = 0.015) and SOFA (p = 0.027) scores. Lactate showed the highest predictive ability for all-cause 28-day mortality, with an area under the receiver-operating characteristic curve (AUROC) of 0.67 (0.55-0.79). The AUROC for all-cause 28-day mortality in patients with community-acquired infection was 0.69 (0.57-0.84) for SOFA and 0.70 (0.58-0.82) for MR-proADM. A 2.1 nmol/L cut-off point for this biomarker in this subgroup of patients discerned, with 100% sensibility, survivors from non-survivors at 28 days. In patients with community-acquired sepsis and initial SOFA score ≤ 6, MR-proADM could help identify patients at risk of 28-day mortality.

Characterization of a proteomic profile associated with organ dysfunction and mortality of sepsis and septic shock.

INTRODUCTION: The search for new biomarkers that allow an early diagnosis in sepsis and predict its evolution has become a necessity in medicine. The objective of this study is to identify, through omics techniques, potential protein biomarkers that are expressed in patients with sepsis and their relationship with organ dysfunction and mortality. METHODS: Prospective, observational and single-center study that included adult patients (≥ 18 years) who were admitted to a tertiary hospital and who met the criteria for sepsis. A mass spectrometry-based approach was used to analyze the plasma proteins in the enrolled subjects. Subsequently, using recursive feature elimination classification and cross-validation with a vector classifier, an association of these proteins with mortality and organ dysfunction was established. The protein-protein interaction network was analyzed with String software. RESULTS: 141 patients were enrolled in this study. Mass spectrometry identified 177 proteins. Of all of them, and by recursive feature elimination, nine proteins (GPX3, APOB, ORM1, SERPINF1, LYZ, C8A, CD14, APOC3 and C1QC) were associated with organ dysfunction (SOFA > 6) with an accuracy of 0.82 ± 0.06, precision of 0.85 ± 0.093, sensitivity 0.81 ± 0.10, specificity 0.84 ± 0.10 and AUC 0.82 ± 0.06. Twenty-two proteins (CLU, LUM, APOL1, SAA1, CLEBC3B, C8A, ITIH4, KNG1, AGT, C7, SAA2, APOH, HRG, AFM, APOE, APOC1, C1S, SERPINC1, IGFALS, KLKB1, CFB and BTD) were associated with mortality with an accuracy of 0.86 ± 0.05, a precision of 0.91 ± 0.05, a sensitivity of 0.91 ± 0.05, a specificity of 0.72 ± 0.17, and an area under the curve (AUC) of 0.81 ± 0.08 with a confidence interval of 95%. CONCLUSION: In sepsis there are proteomic patterns associated with organ dysfunction and mortality.

Epigenetic and transcriptomic reprogramming in monocytes of severe COVID-19 patients reflects alterations in myeloid differentiation and the influence of inflammatory cytokines.

BACKGROUND: COVID-19 manifests with a wide spectrum of clinical phenotypes, ranging from asymptomatic and mild to severe and critical. Severe and critical COVID-19 patients are characterized by marked changes in the myeloid compartment, especially monocytes. However, little is known about the epigenetic alterations that occur in these cells during hyperinflammatory responses in severe COVID-19 patients. METHODS: In this study, we obtained the DNA methylome and transcriptome of peripheral blood monocytes from severe COVID-19 patients. DNA samples extracted from CD14 + CD15- monocytes of 48 severe COVID-19 patients and 11 healthy controls were hybridized on MethylationEPIC BeadChip arrays. In parallel, single-cell transcriptomics of 10 severe COVID-19 patients were generated. CellPhoneDB was used to infer changes in the crosstalk between monocytes and other immune cell types. RESULTS: We observed DNA methylation changes in CpG sites associated with interferon-related genes and genes associated with antigen presentation, concordant with gene expression changes. These changes significantly overlapped with those occurring in bacterial sepsis, although specific DNA methylation alterations in genes specific to viral infection were also identified. We also found these alterations to comprise some of the DNA methylation changes occurring during myeloid differentiation and under the influence of inflammatory cytokines. A progression of DNA methylation alterations in relation to the Sequential Organ Failure Assessment (SOFA) score was found to be related to interferon-related genes and T-helper 1 cell cytokine production. CellPhoneDB analysis of the single-cell transcriptomes of other immune cell types suggested the existence of altered crosstalk between monocytes and other cell types like NK cells and regulatory T cells. CONCLUSION: Our findings show the occurrence of an epigenetic and transcriptional reprogramming of peripheral blood monocytes, which could be associated with the release of aberrant immature monocytes, increased systemic levels of pro-inflammatory cytokines, and changes in immune cell crosstalk in these patients.

Precision medicine in sepsis and septic shock: From omics to clinical tools.

Sepsis is a heterogeneous disease with variable clinical course and several clinical phenotypes. As it is associated with an increased risk of death, patients with this condition are candidates for receipt of a very well-structured and protocolized treatment. All patients should receive the fundamental pillars of sepsis management, which are infection control, initial resuscitation, and multiorgan support. However, specific subgroups of patients may benefit from a personalized approach with interventions targeted towards specific pathophysiological mechanisms. Herein, we will review the framework for identifying subpopulations of patients with sepsis, septic shock, and multiorgan dysfunction who may benefit from specific therapies. Some of these approaches are still in the early stages of research, while others are already in routine use in clinical practice, but together will help in the effective generation and safe implementation of precision medicine in sepsis.

Label-Free Plasmonic Biosensor for Rapid, Quantitative, and Highly Sensitive COVID-19 Serology: Implementation and Clinical Validation.

Serological tests are essential for the control and management of COVID-19 pandemic (diagnostics and surveillance, and epidemiological and immunity studies). We introduce a direct serological biosensor assay employing proprietary technology based on plasmonics, which offers rapid (<15 min) identification and quantification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in clinical samples, without signal amplification. The portable plasmonic device employs a custom-designed multiantigen (RBD peptide and N protein) sensor biochip and reaches detection limits in the low ng mL-1 range employing polyclonal antibodies. It has also been implemented employing the WHO-approved anti-SARS-CoV-2 immunoglobulin standard. A clinical validation with COVID-19 positive and negative samples (n = 120) demonstrates its excellent diagnostic sensitivity (99%) and specificity (100%). This positions our biosensor as an accurate and easy-to-use diagnostics tool for rapid and reliable COVID-19 serology to be employed both at laboratory and decentralized settings for the disease management and for the evaluation of immunological status during vaccination or treatment.

JAK2-STAT Epigenetically Regulates Tolerized Genes in Monocytes in the First Encounter With Gram-Negative Bacterial Endotoxins in Sepsis.

Microbial challenges, such as widespread bacterial infection in sepsis, induce endotoxin tolerance, a state of hyporesponsiveness to subsequent infections. The participation of DNA methylation in this process is poorly known. In this study, we perform integrated analysis of DNA methylation and transcriptional changes following in vitro exposure to gram-negative bacterial lipopolysaccharide, together with analysis of ex vivo monocytes from septic patients. We identify TET2-mediated demethylation and transcriptional activation of inflammation-related genes that is specific to toll-like receptor stimulation. Changes also involve phosphorylation of STAT1, STAT3 and STAT5, elements of the JAK2 pathway. JAK2 pathway inhibition impairs the activation of tolerized genes on the first encounter with lipopolysaccharide. We then confirm the implication of the JAK2-STAT pathway in the aberrant DNA methylome of patients with sepsis caused by gram-negative bacteria. Finally, JAK2 inhibition in monocytes partially recapitulates the expression changes produced in the immunosuppressive cellular state acquired by monocytes from gram-negative sepsis, as described by single cell-RNA-sequencing. Our study evidences both the crucial role the JAK2-STAT pathway in epigenetic regulation and initial response of the tolerized genes to gram-negative bacterial endotoxins and provides a pharmacological target to prevent exacerbated responses.

Inflammatory cytokines and organ dysfunction associate with the aberrant DNA methylome of monocytes in sepsis.

BACKGROUND: Sepsis, a life-threatening organ dysfunction caused by a dysregulated systemic immune response to infection, associates with reduced responsiveness to subsequent infections. How such tolerance is acquired is not well understood but is known to involve epigenetic and transcriptional dysregulation. METHODS: Bead arrays were used to compare global DNA methylation changes in patients with sepsis, non-infectious systemic inflammatory response syndrome, and healthy controls. Bioinformatic analyses were performed to dissect functional reprogramming and signaling pathways related to the acquisition of these specific DNA methylation alterations. Finally, in vitro experiments using human monocytes were performed to test the induction of similar DNA methylation reprogramming. RESULTS: Here, we focused on DNA methylation changes associated with sepsis, given their potential role in stabilizing altered phenotypes. Tolerized monocytes from patients with sepsis display changes in their DNA methylomes with respect to those from healthy controls, affecting critical monocyte-related genes. DNA methylation profiles correlate with IL-10 and IL-6 levels, significantly increased in monocytes in sepsis, as well as with the Sequential Organ Failure Assessment score; the observed changes associate with TFs and pathways downstream to toll-like receptors and inflammatory cytokines. In fact, in vitro stimulation of toll-like receptors in monocytes results in similar gains and losses of methylation together with the acquisition of tolerance. CONCLUSION: We have identified a DNA methylation signature associated with sepsis that is downstream to the response of monocytes to inflammatory signals associated with the acquisition of a tolerized phenotype and organic dysfunction.

Machine learning in critical care: state-of-the-art and a sepsis case study.

BACKGROUND: Like other scientific fields, such as cosmology, high-energy physics, or even the life sciences, medicine and healthcare face the challenge of an extremely quick transformation into data-driven sciences. This challenge entails the daunting task of extracting usable knowledge from these data using algorithmic methods. In the medical context this may for instance realized through the design of medical decision support systems for diagnosis, prognosis and patient management. The intensive care unit (ICU), and by extension the whole area of critical care, is becoming one of the most data-driven clinical environments. RESULTS: The increasing availability of complex and heterogeneous data at the point of patient attention in critical care environments makes the development of fresh approaches to data analysis almost compulsory. Computational Intelligence (CI) and Machine Learning (ML) methods can provide such approaches and have already shown their usefulness in addressing problems in this context. The current study has a dual goal: it is first a review of the state-of-the-art on the use and application of such methods in the field of critical care. Such review is presented from the viewpoint of the different subfields of critical care, but also from the viewpoint of the different available ML and CI techniques. The second goal is presenting a collection of results that illustrate the breath of possibilities opened by ML and CI methods using a single problem, the investigation of septic shock at the ICU. CONCLUSION: We have presented a structured state-of-the-art that illustrates the broad-ranging ways in which ML and CI methods can make a difference in problems affecting the manifold areas of critical care. The potential of ML and CI has been illustrated in detail through an example concerning the sepsis pathology. The new definitions of sepsis and the relevance of using the systemic inflammatory response syndrome (SIRS) in its diagnosis have been considered. Conditional independence models have been used to address this problem, showing that SIRS depends on both organ dysfunction measured through the Sequential Organ Failure (SOFA) score and the ICU outcome, thus concluding that SIRS should still be considered in the study of the pathophysiology of Sepsis. Current assessment of the risk of dead at the ICU lacks specificity. ML and CI techniques are shown to improve the assessment using both indicators already in place and other clinical variables that are routinely measured. Kernel methods in particular are shown to provide the best performance balance while being amenable to representation through graphical models, which increases their interpretability and, with it, their likelihood to be accepted in medical practice.