Dataset Information

A neutrophil activation signature predicts critical illness and mortality in COVID-19.

ABSTRACT: Pathologic immune hyperactivation is emerging as a key feature of critical illness in COVID-19, but the mechanisms involved remain poorly understood. We carried out proteomic profiling of plasma from cross-sectional and longitudinal cohorts of hospitalized patients with COVID-19 and analyzed clinical data from our health system database of more than 3300 patients. Using a machine learning algorithm, we identified a prominent signature of neutrophil activation, including resistin, lipocalin-2, hepatocyte growth factor, interleukin-8, and granulocyte colony-stimulating factor, which were the strongest predictors of critical illness. Evidence of neutrophil activation was present on the first day of hospitalization in patients who would only later require transfer to the intensive care unit, thus preceding the onset of critical illness and predicting increased mortality. In the health system database, early elevations in developing and mature neutrophil counts also predicted higher mortality rates. Altogether, these data suggest a central role for neutrophil activation in the pathogenesis of severe COVID-19 and identify molecular markers that distinguish patients at risk of future clinical decompensation.

SUBMITTER: Meizlish ML

PROVIDER: S-EPMC7908851 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:ObjectiveTo investigate the clinical outcomes of patients with rheumatoid arthritis (RA) with COVID-19.MethodsThis retrospective study consisted of 361 patients with RA+ and 45,954 patients with RA- (March 2020 to August 2022) who tested positive for SARS-CoV-2 by polymerase-chain-reaction in the Montefiore Health System, which serves a large low-income, minority-predominant population in the Bronx and was an epicenter of the initial pandemic and subsequent surges. Primary outcomes were hospitalization, critical illness, and all-cause mortality associated with SARS-CoV-2 infection. Comparisons were made with and without adjustment for covariates, as well as with 1083 matched controls of patients with RA- and COVID-19.ResultsPatients with RA+ and COVID-19 were older (62.2 ± 23.5 vs. 45.5 ± 26.3; P < 0.001), were more likely females (83.1% vs. 55.8%; P < 0.001), were Black (35.5% vs. 30.3%; P < 0.05), and had higher rates of comorbidities (P < 0.05), hospitalization (52.4% vs. 32.5%; P < 0.005), critical illness (10.5% vs. 6.9%; P < 0.05), and mortality (11.1% vs. 6.2%; P < 0.01) compared with patients with RA- and COVID-19. Patients with RA+ with COVID-19 had higher odds of critical illness (adjusted odds ratio [aOR] = 1.46, 95% confidence interval [CI]: 1.09-1.93; P = 0.008) but no differences in hospitalization (aOR = 1.18 [95% CI: 0.93-1.49]; P = 0.16) and mortality (aOR = 1.34 [95% CI: 0.92-1.89]; P = 0.10) after adjusting for covariates. Odds ratio analysis identified age, hospitalization status, female sex, chronic kidney disease, chronic obstructive pulmonary disease, and Black race to be significant risk factors for COVID-19-related mortality. Pre-COVID-19 steroid and biologic therapy to treat RA were not significantly associated with worse outcomes (P > 0.05). Outcomes were not different between patients with RA+ and propensity-matched RA- controls (P > 0.05).ConclusionOur findings suggest that risk factors for adverse COVID-19 outcomes were not attributed to RA per se but rather age and preexisting medical conditions of patients with RA.

Project description:Background: Increasing clinical evidence suggests that people with severe mental illness (SMI), including schizophrenia spectrum disorders, bipolar disorder (BD), and major depressive disorder (MDD), are at higher risk of dying from COVID-19. Several systematic reviews examining the association between psychiatric disorders and COVID-19-related mortality have recently been published. Although these reviews have been conducted thoroughly, certain methodological limitations may hinder the accuracy of their research findings. Methods: A systematic literature search, using the PubMed, Embase, Web of Science, and Scopus databases (from inception to July 23, 2021), was conducted for observational studies assessing the risk of death associated with COVID-19 infection in adult patients with pre-existing schizophrenia spectrum disorders, BD, or MDD. Methodological quality of the included studies was assessed using the Newcastle-Ottawa Scale (NOS). Results: Of 1,446 records screened, 13 articles investigating the rates of death in patients with pre-existing SMI were included in this systematic review. Quality assessment scores of the included studies ranged from moderate to high. Most results seem to indicate that patients with SMI, particularly patients with schizophrenia spectrum disorders, are at significantly higher risk of COVID-19-related mortality, as compared to patients without SMI. However, the extent of the variation in COVID-19-related mortality rates between studies including people with schizophrenia spectrum disorders was large because of a low level of precision of the estimated mortality outcome(s) in certain studies. Most studies on MDD and BD did not include specific information on the mood state or disease severity of patients. Due to a lack of data, it remains unknown to what extent patients with BD are at increased risk of COVID-19-related mortality. A variety of factors are likely to contribute to the increased mortality risk of COVID-19 in these patients. These include male sex, older age, somatic comorbidities (particularly cardiovascular diseases), as well as disease-specific characteristics. Conclusion: Methodological limitations hamper the accuracy of COVID-19-related mortality estimates for the main categories of SMIs. Nevertheless, evidence suggests that SMI is associated with excess COVID-19 mortality. Policy makers therefore must consider these vulnerable individuals as a high-risk group that should be given particular attention. This means that targeted interventions to maximize vaccination uptake among these patients are required to address the higher burden of COVID-19 infection in this already disadvantaged group.

Dataset Information

A neutrophil activation signature predicts critical illness and mortality in COVID-19.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets