Effectiveness of Updated 2023-2024 (Monovalent XBB.1.5) COVID-19 Vaccination Against SARS-CoV-2 Omicron XBB and BA.2.86/JN.1 Lineage Hospitalization and a Comparison of Clinical Severity-IVY Network, 26 Hospitals, October 18, 2023-March 9, 2024.

BACKGROUND: Assessing variant-specific COVID-19 vaccine effectiveness (VE) and severity can inform public health risk assessments and decisions about vaccine composition. BA.2.86 and its descendants, including JN.1 (referred to collectively as "JN lineages"), emerged in late 2023 and exhibited substantial divergence from co-circulating XBB lineages. METHODS: We analyzed patients hospitalized with COVID-19-like illness at 26 hospitals in 20 U.S. states admitted October 18, 2023-March 9, 2024. Using a test-negative, case-control design, we estimated effectiveness of an updated 2023-2024 (Monovalent XBB.1.5) COVID-19 vaccine dose against sequence-confirmed XBB and JN lineage hospitalization using logistic regression. Odds of severe outcomes, including intensive care unit (ICU) admission and invasive mechanical ventilation (IMV) or death, were compared for JN versus XBB lineage hospitalizations using logistic regression. RESULTS: 585 case-patients with XBB lineages, 397 case-patients with JN lineages, and 4,580 control-patients were included. VE in the first 7-89 days after receipt of an updated dose was 54.2% (95% CI = 36.1%-67.1%) against XBB lineage hospitalization and 32.7% (95% CI = 1.9%-53.8%) against JN lineage hospitalization. Odds of ICU admission (adjusted odds ratio [aOR] 0.80; 95% CI = 0.46-1.38) and IMV or death (aOR 0.69; 95% CI = 0.34-1.40) were not significantly different among JN compared to XBB lineage hospitalizations. CONCLUSIONS: Updated 2023-2024 COVID-19 vaccination provided protection against both XBB and JN lineage hospitalization, but protection against the latter may be attenuated by immune escape. Clinical severity of JN lineage hospitalizations was not higher relative to XBB.

Association between asthma and COVID-19 severity during Omicron epidemic: a retrospective cohort study using real-world data.

BACKGROUND: The available evidence presented inconsistencies and inconclusive findings regarding the associations between co-existing asthma and mortality among COVID-19 patients. The objective of the current study is to investigate the relationship between asthma and severe outcomes after SARS-CoV-2 Omicron infection in an infection-naïve population. METHODS: A retrospective cohort study using propensity score matching was conducted. The COVID-19 patients requiring hospitalisation in Hong Kong from January 1, 2022, to November 13, 2022, an Omicron-predominated period, were identified. Severe clinical outcomes were defined as ICU admission and inpatient death after the first positive PCR results as well as a composite outcome of both. RESULTS: Of the 74,396 hospitalised COVID-19 patients admitted, 1,290 asthma patients and 18,641 non-asthma patients were included in the matched cohort. The rates of death and the composite outcome were 15·3% and 17·2%, respectively, among the non-asthma patients,12·2% and 13·6%, respectively, among the asthma patients, with adjusted hazard ratios equal to 0·775 (95% CI: 0·660-0·909) and 0·770 (95% CI: 0·662-0·895), respectively. The negative association was more apparent in the elderly and female groups. Asthma remained a factor that lowered the risk of disease severity even though the patients were not fully vaccinated with at least two doses. CONCLUSIONS: We used real-world data to demonstrate that asthma was not a risk factor for COVID-19 severity of the infections of Omicron variant, even though the patients were not fully vaccinated.

T cell-mediated Immune response and correlates of inflammation and their relationship with COVID-19 clinical severity: not an intuitive guess.

BACKGROUND: Predictors of the outcome of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection remain to be fully determined. We evaluated selected viral characteristics and immunological responses that might predict and/or correlate to the clinical outcome of COVID-19. METHODS: For individuals developing divergent clinical outcomes, the magnitude and breadth of T cell-mediated responses were measured within 36 h of symptom onset. Peripheral Blood Mononuclear Cells (PBMCs) were subjected to in vitro stimulation with SARS-CoV-2-based peptides. In addition, SARS-CoV-2 sequences were generated by metagenome, and HLA typing was performed using Luminex technology. FINDINGS: CD4+ T cell activation was negatively correlated with SARS-CoV-2 basal viral load in patients with severe COVID-19 (p = 0·043). The overall cellular immune response, as inferred by the IFN-γ signal, was higher at baseline for patients who progressed to mild disease compared to patients who progressed to severe disease (p = 0·0044). Subjects with milder disease developed higher T cell responses for MHC class I and II-restricted peptides (p = 0·033). INTERPRETATION: Mounting specific cellular immune responses in the first days after symptom onset, as inferred by IFN-γ magnitude in the ELISPOT assay, may efficiently favor a positive outcome. In contrast, progression to severe COVID-19 was accompanied by stronger cellular immune responses, higher CD4 + T cell activation, and a higher number of in silico predicted high-affinity class I HLA alleles.

The relation between proteinuria and the severity of COVID-19.

BACKGROUND: The association between proteinuria, which is also an indicator of chronic kidney disease (CKD), and coronavirus disease 2019 (COVID-19) severity is unclear. METHODS: We selected 342 hospitalized patients with COVID-19 diagnosed via polymerase chain reaction testing between February 2020 and October 2022 and who had at least one urinalysis 14-365 days before admission. RESULTS: Proteinuria before admission was associated neither with oxygen administration nor developing pneumonia in multivariate analysis (odds ratio [OR] 1.03; 95% confidence interval (CI) 0.44-2.40, p = 0.95 and OR 1.01; 95% CI 0.47-2.17, p = 0.98, respectively). Proteinuria on admission was associated both with oxygen administration and developing pneumonia in multivariate analysis (OR 3.29; 95% CI 1.37-7.88, p < 0.01 and OR 3.81; 95% CI 1.68-8.62, p < 0.01, respectively). The percentage of patients with proteinuria on admission was significantly higher than those before admission (37.4% vs. 17.8%; p < 0.01). In the subgroup analysis, proteinuria on admission among patients with eGFR ≥ 60 mL/min/1.73 m2 was associated with both oxygen administration and developing pneumonia (OR 4.86; 95% CI 1.22-19.38, p = 0.03, OR 3.65; 95% CI 1.06-12.58, p = 0.04, respectively). In contrast, proteinuria on admission among patients with eGFR < 60 mL/min/1.73 m2 was associated with developing pneumonia (OR 6.45; 95%CI 1.78-23.35, p = 0.01), not with oxygen administration (OR 3.28; 95% CI 0.92-11.72, p = 0.07). CONCLUSIONS: Although underlying proteinuria before admission was not associated with COVID-19 severity, proteinuria on admission was associated with oxygen demand and developing pneumonia.

Inflammasome-Related Genetic Polymorphisms as Severity Biomarkers of COVID-19.

The most critical forms of coronavirus disease 2019 (COVID-19) are associated with excessive activation of the inflammasome. Despite the COVID-19 impact on public health, we still do not fully understand the mechanisms by which the inflammatory response influences disease prognosis. Accordingly, we aimed to elucidate the role of polymorphisms in the key genes of the formation and signaling of the inflammasome as biomarkers of COVID-19 severity. For this purpose, a large and well-defined cohort of 377 COVID-19 patients with mild (n = 72), moderate (n = 84), severe (n = 100), and critical (n = 121) infections were included. A total of 24 polymorphisms located in inflammasome-related genes (NLRP3, NLRC4, NLRP1, CARD8, CASP1, IL1B, IL18, NFKB1, ATG16L1, and MIF) were genotyped in all of the patients and in the 192 healthy controls (HCs) (who were without COVID-19 at the time of and before the study) by RT-qPCR. Our results showed that patients with mild, moderate, severe, and critical COVID-19 presented similar allelic and genotypic distribution in all the variants studied. No statistically significant differences in the haplotypic distribution of NLRP3, NLRC4, NLRP1, CARD8, CASP1, IL1B, and ATG16L1 were observed between COVID-19 patients, who were stratified by disease severity. Each stratified group of patients presented a similar genetic distribution to the HCs. In conclusion, our results suggest that the inflammasome polymorphisms studied are not associated with the worsening of COVID-19.

Preexisting Autoimmunity Is Associated With Increased Severity of Coronavirus Disease 2019: A Retrospective Cohort Study Using Data From the National COVID Cohort Collaborative (N3C).

BACKGROUND: Identifying individuals with a higher risk of developing severe coronavirus disease 2019 (COVID-19) outcomes will inform targeted and more intensive clinical monitoring and management. To date, there is mixed evidence regarding the impact of preexisting autoimmune disease (AID) diagnosis and/or immunosuppressant (IS) exposure on developing severe COVID-19 outcomes. METHODS: A retrospective cohort of adults diagnosed with COVID-19 was created in the National COVID Cohort Collaborative enclave. Two outcomes, life-threatening disease and hospitalization, were evaluated by using logistic regression models with and without adjustment for demographics and comorbidities. RESULTS: Of the 2 453 799 adults diagnosed with COVID-19, 191 520 (7.81%) had a preexisting AID diagnosis and 278 095 (11.33%) had a preexisting IS exposure. Logistic regression models adjusted for demographics and comorbidities demonstrated that individuals with a preexisting AID (odds ratio [OR], 1.13; 95% confidence interval [CI]: 1.09-1.17; P < .001), IS exposure (OR, 1.27; 95% CI: 1.24-1.30; P < .001), or both (OR, 1.35; 95% CI: 1.29-1.40; P < .001) were more likely to have a life-threatening disease. These results were consistent when hospitalization was evaluated. A sensitivity analysis evaluating specific IS revealed that tumor necrosis factor inhibitors were protective against life-threatening disease (OR, 0.80; 95% CI: .66-.96; P = .017) and hospitalization (OR, 0.80; 95% CI: .73-.89; P < .001). CONCLUSIONS: Patients with preexisting AID, IS exposure, or both are more likely to have a life-threatening disease or hospitalization. These patients may thus require tailored monitoring and preventative measures to minimize negative consequences of COVID-19.

Preoperative SARS-CoV-2 infection increases risk of early postoperative cardiovascular complications following noncardiac surgery.

As the coronavirus disease 2019 (COVID-19) pandemic progresses to an endemic phase, a greater number of patients with a history of COVID-19 will undergo surgery. Major adverse cardiovascular and cerebrovascular events (MACE) are the primary contributors to postoperative morbidity and mortality; however, studies assessing the relationship between a previous severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and postoperative MACE outcomes are limited. Here, we analyzed retrospective data from 457,804 patients within the N3C Data Enclave, the largest national, multi-institutional data set on COVID-19 in the United States. However, 7.4% of patients had a history of COVID-19 before surgery. When comorbidities, age, race, and risk of surgery were controlled, patients with preoperative COVID-19 had an increased risk for 30-day postoperative MACE. MACE risk was influenced by an interplay between COVID-19 disease severity and time between surgery and infection; in those with mild disease, MACE risk was not increased even among those undergoing surgery within 4 wk following infection. In those with moderate disease, risk for postoperative MACE was mitigated 8 wk after infection, whereas patients with severe disease continued to have elevated postoperative MACE risk even after waiting for 8 wk. Being fully vaccinated decreased the risk for postoperative MACE in both patients with no history of COVID-19 and in those with breakthrough COVID-19 infection. Together, our results suggest that a thorough assessment of the severity, vaccination status, and timing of SARS-CoV-2 infection must be a mandatory part of perioperative stratification.NEW & NOTEWORTHY With an increasing proportion of patients undergoing surgery with a prior history of COVID-19, it is crucial to understand the impact of SARS-CoV-2 infection on postoperative cardiovascular/cerebrovascular risk. Our work assesses a large, national, multi-institutional cohort of patients to highlight that COVID-19 infection increases risk for postoperative major adverse cardiovascular and cerebrovascular events (MACE). MACE risk is influenced by an interplay between disease severity and time between infection and surgery, and full vaccination reduces the risk for 30-day postoperative MACE. These results highlight the importance of stratifying time-to-surgery guidelines based on disease severity.

Cross-sectional analysis reveals autoantibody signatures associated with COVID-19 severity.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is associated with increased levels of autoantibodies targeting immunological proteins such as cytokines and chemokines. Reports further indicate that COVID-19 patients may develop a broad spectrum of autoimmune diseases due to reasons not fully understood. Even so, the landscape of autoantibodies induced by SARS-CoV-2 infection remains uncharted territory. To gain more insight, we carried out a comprehensive assessment of autoantibodies known to be linked to diverse autoimmune diseases observed in COVID-19 patients in a cohort of 231 individuals, of which 161 were COVID-19 patients (72 with mild, 61 moderate, and 28 with severe disease) and 70 were healthy controls. Dysregulated IgG and IgA autoantibody signatures, characterized mainly by elevated concentrations, occurred predominantly in patients with moderate or severe COVID-19 infection. Autoantibody levels often accompanied anti-SARS-CoV-2 antibody concentrations while stratifying COVID-19 severity as indicated by random forest and principal component analyses. Furthermore, while young versus elderly COVID-19 patients showed only slight differences in autoantibody levels, elderly patients with severe disease presented higher IgG autoantibody concentrations than young individuals with severe COVID-19. This work maps the intersection of COVID-19 and autoimmunity by demonstrating the dysregulation of multiple autoantibodies triggered during SARS-CoV-2 infection. Thus, this cross-sectional study suggests that SARS-CoV-2 infection induces autoantibody signatures associated with COVID-19 severity and several autoantibodies that can be used as biomarkers of COVID-19 severity, indicating autoantibodies as potential therapeutical targets for these patients.

Integrative systems immunology uncovers molecular networks of the cell cycle that stratify COVID-19 severity.

Several perturbations in the number of peripheral blood leukocytes, such as neutrophilia and lymphopenia associated with Coronavirus disease 2019 (COVID-19) severity, point to systemic molecular cell cycle alterations during severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. However, the landscape of cell cycle alterations in COVID-19 remains primarily unexplored. Here, we performed an integrative systems immunology analysis of publicly available proteome and transcriptome data to characterize global changes in the cell cycle signature of COVID-19 patients. We found significantly enriched cell cycle-associated gene co-expression modules and an interconnected network of cell cycle-associated differentially expressed proteins (DEPs) and genes (DEGs) by integrating the molecular data of 1469 individuals (981 SARS-CoV-2 infected patients and 488 controls [either healthy controls or individuals with other respiratory illnesses]). Among these DEPs and DEGs are several cyclins, cell division cycles, cyclin-dependent kinases, and mini-chromosome maintenance proteins. COVID-19 patients partially shared the expression pattern of some cell cycle-associated genes with other respiratory illnesses but exhibited some specific differential features. Notably, the cell cycle signature predominated in the patients' blood leukocytes (B, T, and natural killer cells) and was associated with COVID-19 severity and disease trajectories. These results provide a unique global understanding of distinct alterations in cell cycle-associated molecules in COVID-19 patients, suggesting new putative pathways for therapeutic intervention.

Severe and fatal COVID-19 is characterised by increased circulating glucagon like peptide 1 and procalcitonin modulated by type 2 diabetes.

AIMS: Endotoxemia commonly occurs in severe and fatal COVID-19, suggesting that concomitant bacterial stimuli may amplify the innate immune response induced by SARS-CoV-2. We previously demonstrated that the endogenous glucagon like peptide 1 (GLP-1) system in conjunction with increased procalcitonin (PCT) is hyperactivated in patients with severe Gram-negative sepsis and modulated by type 2 diabetes (T2D). We aimed to determine the association of COVID-19 severity with endogenous GLP-1 activation upregulated by increased specific pro-inflammatory innate immune response in patients with and without T2D. MATERIALS AND METHODS: Plasma levels of total GLP-1, IL-6, and PCT were estimated on admission and during hospitalisation in 61 patients (17 with T2D) with non-severe and severe COVID-19. RESULTS: COVID-19 patients demonstrated ten-fold increase of IL-6 levels regardless of disease severity. Increased admission GLP-1 levels (p = 0.03) accompanied by two-fold increased PCT were found in severe as compared with non-severe patients. Moreover, GLP-1 and PCT levels were significantly increased in non-survived as compared with survived patients at admission (p = 0.01 and p = 0.001, respectively) and at 5 to 6 days of hospitalisation (p = 0.05). Both non-diabetic and T2D patients demonstrated a positive correlation between GLP-1 and PCT response (r = 0.33, p = 0.03, and r = 0.54, p = 0.03, respectively), but the intensity of this joint pro-inflammatory/GLP-1 response was modulated by T2D. In addition, hypoxaemia down-regulated GLP-1 response only in T2D patients with bilateral lung damage. CONCLUSIONS: The persistent joint increase of endogenous GLP-1 and PCT in severe and fatal COVID-19 suggests a role of concomitant bacterial infection in disease exacerbation. Early elevation of endogenous GLP-1 may serve as a new biomarker of COVID-19 severity and fatal outcome.

Depression, worry, and loneliness are associated with subsequent risk of hospitalization for COVID-19: a prospective study.

BACKGROUND: Pre-pandemic psychological distress is associated with increased susceptibility to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, but associations with the coronavirus disease 2019 (COVID-19) severity are not established. The authors examined the associations between distress prior to SARS-CoV-2 infection and subsequent risk of hospitalization. METHODS: Between April 2020 (baseline) and April 2021, we followed 54 781 participants from three ongoing cohorts: Nurses' Health Study II (NHSII), Nurses' Health Study 3 (NHS3), and the Growing Up Today Study (GUTS) who reported no current or prior SARS-CoV-2 infection at baseline. Chronic depression was assessed during 2010-2019. Depression, anxiety, worry about COVID-19, perceived stress, and loneliness were measured at baseline. SARS-CoV-2 infection and hospitalization due to COVID-19 was self-reported. Relative risks (RRs) were calculated by Poisson regression. RESULTS: 3663 participants reported a positive SARS-CoV-2 test (mean age = 55.0 years, standard deviation = 13.8) during follow-up. Among these participants, chronic depression prior to the pandemic [RR = 1.72; 95% confidence interval (CI) 1.20-2.46], and probable depression (RR = 1.81, 95% CI 1.08-3.03), being very worried about COVID-19 (RR = 1.79; 95% CI 1.12-2.86), and loneliness (RR = 1.81, 95% CI 1.02-3.20) reported at baseline were each associated with subsequent COVID-19 hospitalization, adjusting for demographic factors and healthcare worker status. Anxiety and perceived stress were not associated with hospitalization. Depression, worry about COVID-19, and loneliness were as strongly associated with hospitalization as were high cholesterol and hypertension, established risk factors for COVID-19 severity. CONCLUSIONS: Psychological distress may be a risk factor for hospitalization in patients with SARS-CoV-2 infection. Assessment of psychological distress may identify patients at greater risk of hospitalization. Future work should examine whether addressing distress improves physical health outcomes.

A method for comparing multiple imputation techniques: A case study on the U.S. national COVID cohort collaborative.

Healthcare datasets obtained from Electronic Health Records have proven to be extremely useful for assessing associations between patients' predictors and outcomes of interest. However, these datasets often suffer from missing values in a high proportion of cases, whose removal may introduce severe bias. Several multiple imputation algorithms have been proposed to attempt to recover the missing information under an assumed missingness mechanism. Each algorithm presents strengths and weaknesses, and there is currently no consensus on which multiple imputation algorithm works best in a given scenario. Furthermore, the selection of each algorithm's parameters and data-related modeling choices are also both crucial and challenging. In this paper we propose a novel framework to numerically evaluate strategies for handling missing data in the context of statistical analysis, with a particular focus on multiple imputation techniques. We demonstrate the feasibility of our approach on a large cohort of type-2 diabetes patients provided by the National COVID Cohort Collaborative (N3C) Enclave, where we explored the influence of various patient characteristics on outcomes related to COVID-19. Our analysis included classic multiple imputation techniques as well as simple complete-case Inverse Probability Weighted models. Extensive experiments show that our approach can effectively highlight the most promising and performant missing-data handling strategy for our case study. Moreover, our methodology allowed a better understanding of the behavior of the different models and of how it changed as we modified their parameters. Our method is general and can be applied to different research fields and on datasets containing heterogeneous types.

Increased Pro Th1 And Th17 Transcriptional Activity In Patients With Severe COVID-19.

Background: COVID-19 is known to disrupt immune response and induce hyperinflammation that could potentially induce fatal outcome of the disease. Until now, it is known that interplay among cytokines is rather important for clinical presentation and outcome of COVID-19. The aim of this study was to determine transcriptional activity and functional phenotype of T cells and the relationship between pro- and anti-inflammatory cytokines and clinical parameters of COVID-19 severity. Methods: All recruited patients met criteria for COVID-19 are were divided in four groups according to disease severity. Serum levels of IL-12, IFN-γ, IL-17 and IL-23 were measured, and flow cytometry analysis of T cells from peripheral blood was performed. Results: Significant elevation of IL-12, IFN-γ, IL-17 and IL-23 in stage IV of the disease has been revealed. Further, strong intercorrelation between IL-12, IFN-γ, IL-17 and IL-23 was also found in stage IV of the disease, marking augmented Th1 and Th17 response. Analyses of T cells subsets indicate a noticeable phenotype change. CD4+, but not CD8+ T cells expressed increased transcriptional activity through increased expression of Tbet and RORγT, accompanied with increased percentage of IFN-γ and IL-17 producing T cells. Conclusion: Our results pose a novel hypothesis of the underlying mechanism behind deteriorating immune response in severe cases of COVID-19.

Shared genetic architecture between type 2 diabetes and COVID-19 severity.

PURPOSE: Patients with type 2 diabetes (T2D) have demonstrated a higher risk for developing more severe cases of COVID-19, but the complex genetic mechanism between them is still unknown. The aim of the present study was to untangle this relationship using genetically based approaches. METHODS: By leveraging large-scale genome-wide association study (GWAS) summary statistics of T2D and COVID-19 severity, linkage disequilibrium score regression and Mendelian randomization (MR) analyses were utilized to quantify the genetic correlations and causal relationships between the two traits. Gene-based association and enrichment analysis were further applied to identify putative functional pathways shared between T2D and COVID-19 severity. RESULTS: Significant, moderate genetic correlations were detected between T2D and COVID-19 hospitalization (rg = 0.156, SE = 0.057, p = 0.005) or severe disease (rg = 0.155, SE = 0.057, p = 0.006). MR analysis did not support evidence for a causal effect of T2D on COVID-19 hospitalization (OR 1.030, 95% CI 0.979, 1.084, p = 0.259) or severe disease (OR 0.999, 95% CI 0.934, 1.069, p = 0.982). Genes having pgene < 0.05 for both T2D and COVID-19 severe were significantly enriched for biological pathways, such as response to type I interferon, glutathione derivative metabolic process and glutathione derivative biosynthetic process. CONCLUSIONS: Our findings further confirm the comorbidity of T2D and COVID-19 severity, but a non-causal impact of T2D on severe COVID-19. Shared genetically modulated molecular mechanisms underlying the co-occurrence of the two disorders are crucial for identifying therapeutic targets.

Effects of sulfasalazine in axial spondyloarthritis on COVID-19 outcomes: real-life data from a single center.

INTRODUCTION: Compared to biological agents, little is known about the impact of sulfasalazine therapy on COVID-19 outcomes in patients with Axial Spondyloarthritis (AxSpA). Therefore, we aimed to evaluate the COVID-19 severity in AxSpAs receiving sulfasalazine and biologic-agent. MATERIALS AND METHODS: A total of 219 SARS-CoV-2 positive AxSpA patients were retrospectively analyzed. COVID-19 pneumonia, hospitalization rate, and length of stay were used to determine COVID-19 severity. AxSpA patients were mainly grouped and compared as sulfasalazine and non-sulfasalazine. Afterward, we excluded no-treatment patients to reveal the drug's effects more clearly and regrouped AxSpA patients as sulfasalazine-monotherapy (34.3%), biologic-monotherapy (33.7%), and sulfasalazine + biologic (7.3%). RESULTS: Fifty-nine percent of the patients were male and the mean age was 45.0 years. Peripheral arthritis was 35% and uveitis 15%. In total, 41.5% of them have received sulfasalazine and 41.0% biologic agents, and the remaining patients with no AxSpA-specific treatment. In the first comparison, the sulfasalazine group had a higher age, more frequent COVID-19 pneumonia, hospitalization, and longer hospitalization than a non-sulfasalazine group. In the pairwise comparison of 3 treatment groups, the demographic and clinical features, the hospitalization rate and the length of hospital stay were similar but the sulfasalazine-monotherapy group had a higher frequency of COVID-19 pneumonia than the biologic-monotherapy group (23% vs. 7%, p = 0.008). CONCLUSION: Our results imply sulfasalazine may be related to more severe COVID-19 in AxSpA patients. These patients should be followed more carefully in the presence of COVID-19, regardless of reasons such as age, comorbidity, and extra-axial disease, and consideration of discontinuing sulfasalazine maybe even thought.

COVID-19 Severity Prediction from Chest X-ray Images Using an Anatomy-Aware Deep Learning Model.

The COVID-19 pandemic has been adversely affecting the patient management systems in hospitals around the world. Radiological imaging, especially chest x-ray and lung Computed Tomography (CT) scans, plays a vital role in the severity analysis of hospitalized COVID-19 patients. However, with an increasing number of patients and a lack of skilled radiologists, automated assessment of COVID-19 severity using medical image analysis has become increasingly important. Chest x-ray (CXR) imaging plays a significant role in assessing the severity of pneumonia, especially in low-resource hospitals, and is the most frequently used diagnostic imaging in the world. Previous methods that automatically predict the severity of COVID-19 pneumonia mainly focus on feature pooling from pre-trained CXR models without explicitly considering the underlying human anatomical attributes. This paper proposes an anatomy-aware (AA) deep learning model that learns the generic features from x-ray images considering the underlying anatomical information. Utilizing a pre-trained model and lung segmentation masks, the model generates a feature vector including disease-level features and lung involvement scores. We have used four different open-source datasets, along with an in-house annotated test set for training and evaluation of the proposed method. The proposed method improves the geographical extent score by 11% in terms of mean squared error (MSE) while preserving the benchmark result in lung opacity score. The results demonstrate the effectiveness of the proposed AA model in COVID-19 severity prediction from chest X-ray images. The algorithm can be used in low-resource setting hospitals for COVID-19 severity prediction, especially where there is a lack of skilled radiologists.

Genetic Predisposition to Elevated Levels of Circulating ADAM17 Is Associated with the Risk of Severe COVID-19.

High levels of ADAM17 activity have emerged as an important mediator in severe COVID-19. This study aims to characterize eventual causal relationships between ADAM17 and COVID-19. Using Mendelian randomization analyses, we examined the causal effects of circulating ADAM17 on COVID-19 outcomes using summary statistics from large, genome-wide association studies of ADAM17 (up to 35,559 individuals) from the Icelandic Cancer Project and deCODE genetics, as well as critically ill COVID-19 patients (cases: 13,769; controls: 1,072,442), hospitalized COVID-19 patients (cases: 32,519; controls: 2,062,805) and reported SARS-CoV-2 infections (cases: 122,616; controls: 2,475,240) from the COVID-19 Host Genetics Initiative. The Mendelian randomization (MR) analyses demonstrated that a 1 standard deviation increase in genetically determined circulating ADAM17 (extracellular domain) was associated with an increased risk of developing critical ill COVID-19 (odds ratio [OR] = 1.26, 95% confidence interval [CI]:1.03-1.55). The multivariable MR analysis suggested a direct causal role of circulating ADAM17 (extracellular domain) in the risk of developing critical COVID-19 (OR = 1.09; 95% CI:1.01-1.17) when accounting for body mass index. No causal effect for the cytoplasmic domain of ADAM17 on COVID-19 was observed. Our results suggest that an increased genetic susceptibility to elevated levels of circulating ADAM17 (extracellular domain) is associated with a higher risk of suffering from severe COVID-19, strengthening the idea that the timely selective inhibition of ADAM17 could be a potential therapeutic target worthy of investigation.

Nucleotide, Phospholipid, and Kynurenine Metabolites Are Robustly Associated with COVID-19 Severity and Time of Plasma Sample Collection in a Prospective Cohort Study.

Understanding the molecular underpinnings of disease severity and progression in human studies is necessary to develop metabolism-related preventative strategies for severe COVID-19. Metabolites and metabolic pathways that predispose individuals to severe disease are not well understood. In this study, we generated comprehensive plasma metabolomic profiles in >550 patients from the Longitudinal EMR and Omics COVID-19 Cohort. Samples were collected before (n = 441), during (n = 86), and after (n = 82) COVID-19 diagnosis, representing 555 distinct patients, most of which had single timepoints. Regression models adjusted for demographics, risk factors, and comorbidities, were used to determine metabolites associated with predisposition to and/or persistent effects of COVID-19 severity, and metabolite changes that were transient/lingering over the disease course. Sphingolipids/phospholipids were negatively associated with severity and exhibited lingering elevations after disease, while modified nucleotides were positively associated with severity and had lingering decreases after disease. Cytidine and uridine metabolites, which were positively and negatively associated with COVID-19 severity, respectively, were acutely elevated, reflecting the particular importance of pyrimidine metabolism in active COVID-19. This is the first large metabolomics study using COVID-19 plasma samples before, during, and/or after disease. Our results lay the groundwork for identifying putative biomarkers and preventive strategies for severe COVID-19.

The independent prediction study of the effect of heart-type fatty acid binding protein on the severity and long-term cardiac function in Covid-19 patients.

The study was conducted to assess the predictive ability of the heart-type fatty acid binding protein (HFABP) on the severity and long-term cardiac function of Covid-19 infected persons. In the case of negative HsTn-T, we determined whether HFABP was related to the severity of Covid-19 or it was the long-term impact of cardiac function. Chi-square test and t-test were used to evaluate whether HFABP level was an independent predictor of myocardial injury and whether it was related to the severity of Covid-19 and the long-term impact of cardiac function. Among the 20 patients in each of the two groups (mild and severe), 27.5% of all had elevated HFABP. Two were HFABP positive in the mild group, and nine were HFABP positive in the severe group, with a significant difference between the two groups (P=0.013). The mean serum level of HFABP in the mild group was 3.96 ±1.80, compared with 6.70±3.77 in the severe group, with a significant difference between the two groups (P=0.003). In addition, after two years of follow-up, there was a statistically significant difference in the changes of cardiac function between the HFABP-positive group and the HFABP-negative group (P=0.037). These data indicate that among HsTn-T-negative Covid-19 patients, HFABP is a more sensitive and independent predictor of myocardial damage, and it is useful for distinguishing mild and severe Covid-19. The level of HFABP has a significant effect on the long-term changes of heart function in Covid-19 patients.

What is the role of proton pump inhibitors consumption on the clinical presentation and severity of COVID-19 infection?

OBJECTIVE: Proton pump inhibitors (PPI) are among the most prescribed drugs worldwide; therefore, assessing their effect on COVID-19 infection symptoms and severity is of great importance. This study was designed to evaluate the role of previous PPI consumption on the clinical presentation and severity of COVID-19. PATIENTS AND METHODS: All adult COVID-19 patients were eligible in this observational cross-sectional study. The patients' demographic and clinical data, history of PPI consumption, and comorbid disease were recorded. Charlson comorbidity index (CCI) and quick COVID-19 severity index (qCSI) score were calculated for each patient. IBM SPSS version 25 was used for statistical analysis. RESULTS: Totally 670 patients completed the study (PPI users=121). The average severity (qCSI) score of PPI user patients with comorbidity score of zero was significantly higher than non-users (P-value=0.001). Mortality rate was 6.6% and 3.8% in PPI-users and non-users respectively (P-value=0.117). PPI users were significantly more symptomatic compared to non-users (P-value=0.001). CONCLUSION: We found that PPI users were meaningfully more symptomatic and had a higher severity (qCSI) score. Rational prescription of PPIs should be considered by physicians during and after the pandemic.