Inflammatory Response in COVID-19 Depending on the Severity of the Disease and the Vaccination Status.

The aim of this study was to analyze the serum concentration of interleukin-6 (IL-6), C-reactive protein (CRP), D-dimer, lactate dehydrogenase (LDH), ferritin, and procalcitonin in COVID-19 patients with different forms of the disease. We performed a prospective cohort study on 137 COVID-19 consecutive patients, divided into four groups according to the severity of the disease as follows: 30 patients in the mild form group, 49 in the moderate form group, 28 in the severe form group, and 30 in the critical form group. The tested parameters were correlated with COVID-19 severity. Significant differences were registered between the form of COVID-19 depending on the vaccination status, between LDH concentrations depending on the virus variant, and in IL-6, CRP, and ferritin concentrations and vaccination status depending on the gender. ROC analysis revealed that D-dimer best predicted COVID-19 severe forms and LDH predicted the virus variant. Our findings confirmed the interdependence relationships observed between inflammation markers in relation to the clinical severity of COVID-19, with all the tested biomarkers increasing in severe and critical COVID-19. IL-6, CRP, ferritin, LDH, and D-dimer were increased in all COVID-19 forms. These inflammatory markers were lower in Omicron-infected patients. The unvaccinated patients developed more severe forms compared to the vaccinated ones, and a higher proportion of them needed hospitalization. D-dimer could predict a severe form of COVID-19, while LDH could predict the virus variant.

The Importance of Serum Homocysteine as a Biomarker in Diabetic and Obese COVID-19 Patients.

Homocysteine is a possible risk marker in hematological complications of COVID-19 infection. This study aimed to elucidate the significance of homocysteine as a biomarker for COVID-19 infection, and the relation of homocysteine with COVID-19 severity in obese people and diabetic patients.  The study groups were 1- COVID-19 patients + Diabetic + Obese (CDO), 2- COVID-19 patients + Diabetic (CD), 3- COVID-19 patients + Obese (CO), 4- Healthy Group (HG). Serum levels of homocysteine, IL-6, D-dimer, vitamin B12, and folate were measured by a fully automated biochemistry device Cobas 6000 analyzer series. The mean serum concentration of homocysteine in the COD, CD, CO and H groups were 32.0114, 23.604, 19.4154, and 9.3206 umol/l respectively. The mean concentration of homocysteine levels between every two groups was statistically significant differences (P<0.05) except for the CD and the CO group (P=0.957). In the CDO group, the males have higher mean concentrations than females (P<0.05). The means of homocysteine concentrations in the CDO group among different age groups were different (P <0.001). The serum homocysteine level in the CDO group has a strong positive correlation (R=0.748) with D-dimer and a strong negative correlation (R= - 0.788) with serum folate, while its correlation with serum vitamin B12 is moderate negative (-0.499) and its correlation with serum IL-6 is weakly positive (R=0.376). The AUC value for homocysteine in predicting COVID-19 in the CDO group was 0.843, while 0.714 for the CD group, and 0.728 for the CO group. The serum homocysteine concentration test for all study groups was compared to the serum IL-6 test and the sensitivity was equal to 95% and its specificity was 67.5%. Serum homocysteine has potential predictive power in COVID-19 patients, and the severity of COVID-19 infection and the type of comorbidity is associated with higher sensitivity and specificity of homocysteine serological tests.

Biomarker-guided duration of antibiotic treatment in children hospitalised with confirmed or suspected bacterial infection: statistical analysis plan for the BATCH trial and PRECISE sub-study.

INTRODUCTION: The BATCH trial is a multi-centre randomised controlled trial to compare procalcitonin-guided management of severe bacterial infection in children with current management. PRECISE is a mechanistic sub-study embedded into the BATCH trial. This paper describes the statistical analysis plan for the BATCH trial and PRECISE sub-study. METHODS: The BATCH trial will assess the effectiveness of an additional procalcitonin test in children (aged 72 h to 18 years) hospitalised with suspected or confirmed bacterial infection to guide antimicrobial prescribing decisions. Participants will be enrolled in the trial from randomisation until day 28 follow-up. The co-primary outcomes are duration of intravenous antibiotic use and a composite safety outcome. Target sample size is 1942 patients, based on detecting a 1-day reduction in intravenous antibiotic use (90% power, two-sided) and on a non-inferiority margin of 5% risk difference in the composite safety outcome (90% power, one-sided), while allowing for up to 10% loss to follow-up. RESULTS: Baseline characteristics will be summarised overall, by trial arm, and by whether patients were recruited before or after the pause in recruitment due to the COVID-19 pandemic. In the primary analysis, duration of intravenous antibiotic use will be tested for superiority using Cox regression, and the composite safety outcome will be tested for non-inferiority using logistic regression. The intervention will be judged successful if it reduces the duration of intravenous antibiotic use without compromising safety. Secondary analyses will include sensitivity analyses, pre-specified subgroup analyses, and analysis of secondary outcomes. Two sub-studies, including PRECISE, involve additional pre-specified subgroup analyses. All analyses will be adjusted for the balancing factors used in the randomisation, namely centre and patient age. CONCLUSION: We describe the statistical analysis plan for the BATCH trial and PRECISE sub-study, including definitions of clinical outcomes, reporting guidelines, statistical principles, and analysis methods. The trial uses a design with co-primary superiority and non-inferiority endpoints. The analysis plan has been written prior to the completion of follow-up. TRIAL REGISTRATION: BATCH: ISRCTN11369832, registered 20 September 2017, doi.org/10.1186/ISRCTN11369832. PRECISE: ISRCTN14945050, registered 17 December 2020, doi.org/10.1186/ISRCTN14945050.

Evaluation of laboratory parameters in 1587 COVID-19 patients admitted to metropolitan hospital area of Bologna, Italy.

Since the outbreak of the 2019 pandemic coronavirus disease (COVID-19), great attention has been given to identifying the main clinical features of the disease. Identification of laboratory parameters able to classify patients based on their risk is mandatory to improve their clinical management. We retrospectively evaluated twenty-six laboratory tests measured in COVID-19 positive patients admitted to the hospital in March and April 2020 to find any correlation between their changes and the risk of death. We divided them into surviving and non-surviving patients. A total of 1587 patients were recruited, 854 males with median age of 71 (IQR 56-81) and 733 females with median age of 77 (IQR 61-87). On admission, death was found to be positively correlated with age (p=0.001), but not with sex (p=0.640) or with hospitalization in days (p=0.827). Brain natriuretic peptide (BNP), creatinine, C-reactive protein (CRP), INR, leukocyte count, lymphocyte count, neutrophil count, and procalcitonin (PCT) demonstrated a statistically significant difference between the two groups (p<0.001), suggesting their role as markers of disease severity; only lymphocyte count resulted as an independent risk factor for death.

Intradermal skin test with mRNA vaccines as a surrogate marker of T cell immunity in immunocompromised patients.

OBJECTIVES: Intradermal skin test (IDT) with mRNA vaccines may represent a simple, reliable, and affordable tool to measure T cell response in immunocompromised patients who failed to mount serological responses following vaccination with mRNA covid-19 vaccines. METHODS: We compared anti-SARS-CoV-2 antibodies and cellular responses in vaccinated immunocompromised patients (n = 58), healthy seronegative naive controls (NC, n = 8), and healthy seropositive vaccinated controls (VC, n = 32) by Luminex, spike-induced IFN-γ Elispot and an IDT. A skin biopsy 24 h after IDT and single-cell RNAseq was performed in three vaccinated volunteers. RESULTS: Twenty-five percent of seronegative NC had a positive Elispot (2/8) and IDT (1/4), compared to 95% (20/21) and 93% (28/30) in seropositive VC, respectively. Single-cell RNAseq data in the skin of VC showed a predominant mixed population of effector helper and cytotoxic T cells. The TCR repertoire revealed 18/1064 clonotypes with known specificities against SARS-CoV-2, among which six were spike-specific. Seronegative immunocompromised patients with positive Elispot and IDT were in 83% (5/6) treated with B cell-depleting reagents, while those with negative IDT were all transplant recipients. CONCLUSIONS: Our results indicate that delayed local reaction to IDT reflects vaccine-induced T-cell immunity opening new perspectives to monitor seronegative patients and elderly populations with waning immunity.

Small molecule metabolites: discovery of biomarkers and therapeutic targets.

Metabolic abnormalities lead to the dysfunction of metabolic pathways and metabolite accumulation or deficiency which is well-recognized hallmarks of diseases. Metabolite signatures that have close proximity to subject's phenotypic informative dimension, are useful for predicting diagnosis and prognosis of diseases as well as monitoring treatments. The lack of early biomarkers could lead to poor diagnosis and serious outcomes. Therefore, noninvasive diagnosis and monitoring methods with high specificity and selectivity are desperately needed. Small molecule metabolites-based metabolomics has become a specialized tool for metabolic biomarker and pathway analysis, for revealing possible mechanisms of human various diseases and deciphering therapeutic potentials. It could help identify functional biomarkers related to phenotypic variation and delineate biochemical pathways changes as early indicators of pathological dysfunction and damage prior to disease development. Recently, scientists have established a large number of metabolic profiles to reveal the underlying mechanisms and metabolic networks for therapeutic target exploration in biomedicine. This review summarized the metabolic analysis on the potential value of small-molecule candidate metabolites as biomarkers with clinical events, which may lead to better diagnosis, prognosis, drug screening and treatment. We also discuss challenges that need to be addressed to fuel the next wave of breakthroughs.

A novel scale based on biomarkers associated with COVID-19 severity can predict the need for hospitalization and intensive care, as well as enhanced probabilities for mortality.

Prognostic scales may help to optimize the use of hospital resources, which may be of prime interest in the context of a fast spreading pandemics. Nonetheless, such tools are underdeveloped in the context of COVID-19. In the present article we asked whether accurate prognostic scales could be developed to optimize the use of hospital resources. We retrospectively studied 467 files of hospitalized patients after COVID-19. The odds ratios for 16 different biomarkers were calculated, those that were significantly associated were screened by a Pearson's correlation, and such index was used to establish the mathematical function for each marker. The scales to predict the need for hospitalization, intensive-care requirement and mortality had enhanced sensitivities (0.91 CI 0.87-0.94; 0.96 CI 0.94-0.98; 0.96 CI 0.94-0.98; all with p < 0.0001) and specificities (0.74 CI 0.62-0.83; 0.92 CI 0.87-0.96 and 0.91 CI 0.86-0.94; all with p < 0.0001). Interestingly, when a different population was assayed, these parameters did not change considerably. These results show a novel approach to establish the mathematical function of a marker in the development of highly sensitive prognostic tools, which in this case, may aid in the optimization of hospital resources. An online version of the three algorithms can be found at: http://benepachuca.no-ip.org/covid/index.php.

Myocarditis and autoimmunity.

INTRODUCTION: Autoimmune myocarditis may develop due to heterogeneous causes. Myocarditis is often caused by viral infections, but it can also be caused by systemic autoimmune diseases. Immune checkpoint inhibitors and virus vaccines induce immune activation, and they can cause the development of myocarditis, as well as several immune-related adverse events. The development of myocarditis is dependent on the genetic factors of the host, and the major histocompatibility complex (MHC) may be an important determinant of the type and severity of the disease. However, non-MHC immunoregulatory genes may also play a role in determining susceptibility. AREA COVERED: This review summarizes the current knowledge of the etiology, pathogenesis, diagnosis, and treatment of autoimmune myocarditis with a particular focus on viral infection, autoimmunity, and biomarkers of myocarditis. EXPERT OPINION: An endomyocardial biopsy may not be the gold standard for the diagnosis of myocarditis. Cardiac magnetic resonance imaging is useful in diagnosing autoimmune myocarditis. Recently identified biomarkers of inflammation and myocyte injury are promising for the diagnosis of myocarditis when measured simultaneously. Future treatments should focus on the appropriate diagnosis of the etiologic agent, as well as on the specific stage of the evolution of immune and inflammatory processes.

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-ß1 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.

Machine learning and integrative analysis identify the common pathogenesis of azoospermia complicated with COVID-19.

Background: Although more recent evidence has indicated COVID-19 is prone to azoospermia, the common molecular mechanism of its occurrence remains to be elucidated. The aim of the present study is to further investigate the mechanism of this complication. Methods: To discover the common differentially expressed genes (DEGs) and pathways of azoospermia and COVID-19, integrated weighted co-expression network (WGCNA), multiple machine learning analyses, and single-cell RNA-sequencing (scRNA-seq) were performed. Results: Therefore, we screened two key network modules in the obstructive azoospermia (OA) and non-obstructive azoospermia (NOA) samples. The differentially expressed genes were mainly related to the immune system and infectious virus diseases. We then used multiple machine learning methods to detect biomarkers that differentiated OA from NOA. Enrichment analysis showed that azoospermia patients and COVID-19 patients shared a common IL-17 signaling pathway. In addition, GLO1, GPR135, DYNLL2, and EPB41L3 were identified as significant hub genes in these two diseases. Screening of two different molecular subtypes revealed that azoospermia-related genes were associated with clinicopathological characteristics of age, hospital-free-days, ventilator-free-days, charlson score, and d-dimer of patients with COVID-19 (P < 0.05). Finally, we used the Xsum method to predict potential drugs and single-cell sequencing data to further characterize whether azoospermia-related genes could validate the biological patterns of impaired spermatogenesis in cryptozoospermia patients. Conclusion: Our study performs a comprehensive and integrated bioinformatics analysis of azoospermia and COVID-19. These hub genes and common pathways may provide new insights for further mechanism research.

Free Light Chains κ and λ as New Biomarkers of Selected Diseases.

Diagnostic and prognostic markers are necessary to help in patient diagnosis and the prediction of future clinical events or disease progression. As promising biomarkers of selected diseases, the free light chains (FLCs) κ and λ were considered. Measurements of FLCs are currently used in routine diagnostics of, for example, multiple myeloma, and the usefulness of FLCs as biomarkers of monoclonal gammopathies is well understood. Therefore, this review focuses on the studies concerning FLCs as new potential biomarkers of other disorders in which an inflammatory background has been observed. We performed a bibliometric review of studies indexed in MEDLINE to assess the clinical significance of FLCs. Altered levels of FLCs were observed both in diseases strongly connected with inflammation such as viral infections, tick-borne diseases or rheumatic disorders, and disorders that are moderately associated with immune system reactions, e.g., multiple sclerosis, diabetes, cardiovascular disorders and cancers. Increased concentrations of FLCs appear to be a useful prognostic marker in patients with multiple sclerosis or tick-borne encephalitis. Intensive synthesis of FLCs may also reflect the production of specific antibodies against pathogens such as SARS-CoV-2. Moreover, abnormal FLC concentrations might predict the development of diabetic kidney disease in patients with type 2 diabetes. Markedly elevated levels are also associated with increased risk of hospitalization and death in patients with cardiovascular disorders. Additionally, FLCs have been found to be increased in rheumatic diseases and have been related to disease activity. Furthermore, it has been suggested that inhibition of FLCs would reduce the progression of tumorigenesis in breast cancer or colitis-associated colon carcinogenesis. In conclusion, abnormal levels of κ and λ FLCs, as well as the ratio of κ:λ, are usually the result of disturbances in the synthesis of immunoglobulins as an effect of overactive inflammatory reactions. Therefore, it seems that κ and λ FLCs may be significant diagnostic and prognostic biomarkers of selected diseases. Moreover, the inhibition of FLCs appears to be a promising therapeutical target for the treatment of various disorders where inflammation plays an important role in the development or progression of the disease.

COVID-19 Biomarkers Comparison: Children, Adults and Elders.

Background and Objectives: this study aimed to research links between C-reactive protein (CRP), lactate dehydrogenase (LDH), creatinekinase (CK), 25-OH vitamin D (25-OHD), ferritin (FER), high-density lipoprotein cholesterol (HDL)cholesterol and clinical severity in patients from the western part of Romania, and compare their potential use as biomarkers for intensive care units (ICU) admission and death in children, adults and elders. Materials and Methods: this study is a retrospective cohort study, performed on patients positively diagnosed with COVID-19. Available CRP, LDH, CK 25-OH vitamin D, ferritin, HDL cholesterol and clinical severity were recorded. The following were assessed: median group differences, association, correlation and receiver operating characteristic. Results: 381 children, 614 adults and 381 elders were studied between 1 March 2021 and 1 March 2022. Most children and adults presented mild symptomatology (53.28%, 35.02%, respectively), while most elders presented severe symptomatology (30.04%). ICU admission was 3.67% for children, 13.19% for adults and 46.09% for elders, while mortality was 0.79% for children, 8.63% for adults and 25.1% for elders. With the exception of CK, all other biomarkers showed some significant associations with clinical severity, ICU admission and death. Conclusions: CRP, LDH, 25-OH vitamin D, ferritin and HDL are important biomarkers for COVID-19 positive patients, especially in the pediatric population, while CK was mostly within normal ranges.

Serum KL-6 levels predict clinical outcomes and are associated with MUC1 polymorphism in Japanese patients with COVID-19.

BACKGROUND: Krebs von den Lungen-6 (KL-6) is a known biomarker for diagnosis and monitoring of interstitial lung diseases. However, the role of serum KL-6 and the mucin 1 (MUC1) variant (rs4072037) in COVID-19 outcomes remains to be elucidated. We aimed to evaluate the relationships among serum KL-6 levels, critical outcomes and the MUC1 variant in Japanese patients with COVID-19. METHODS: This is a secondary analysis of a multicentre retrospective study using data from the Japan COVID-19 Task Force collected from February 2020 to November 2021, including 2226 patients with COVID-19 whose serum KL-6 levels were measured. An optimal serum KL-6 level cut-off to predict critical outcomes was determined and used for multivariable logistic regression analysis. Furthermore, the relationship among the allele dosage of the MUC1 variant, calculated from single nucleotide polymorphism typing data of genome-wide association studies using the imputation method, serum KL-6 levels and COVID-19 critical outcomes was evaluated. RESULTS: Serum KL-6 levels were significantly higher in patients with COVID-19 with critical outcomes (511±442 U/mL) than those without (279±204 U/mL) (p<0.001). Serum KL-6 levels ≥304 U/mL independently predicted critical outcomes (adjusted OR (aOR) 3.47, 95% CI 2.44 to 4.95). Moreover, multivariable logistic regression analysis with age and sex indicated that the MUC1 variant was independently associated with increased serum KL-6 levels (aOR 0.24, 95% CI 0.28 to 0.32) but not significantly associated with critical outcomes (aOR 1.11, 95% CI 0.80 to 1.54). CONCLUSION: Serum KL-6 levels predicted critical outcomes in Japanese patients with COVID-19 and were associated with the MUC1 variant. Therefore, serum KL-6 level is a potentially useful biomarker of critical COVID-19 outcomes.

Evaluation of the relationship between TAFI level and prognosis in COVID-19 patients.

OBJECTIVE: Serum thrombin-activated fibrinolysis inhibitor (TAFI) levels were measured in coronavirus disease 2019 (COVID-19) patients requiring intensive care, clinical hospitalization, and outpatient follow-up. The relationships between serum TAFI levels and prognosis were determined. PATIENTS AND METHODS: Ninety patients who had positive COVID-19 PCR test results were randomly selected and included in the study. Subgroups were formed according to the clinical characteristics of the patients as follows: mild, moderate, and severe. Venous blood samples were taken from all patients, and serum C-reactive protein (CRP), lactate dehydrogenase (LDH), fibrinogen, D-dimer, ferritin, and TAFI levels were measured. The results were evaluated by comparing each group. RESULTS: The one-way ANOVA test to determine differences between subgroups resulted in p-values lower than 0.05 for all biochemical analytes (CRP, LDH, fibrinogen, D-dimer, ferritin, and TAFI). Regarding serum TAFI levels, there were significant differences in the severe group (853.04 ± 338.58 ng/mL) compared to the mild group (548.33 ± 264.17 ng/mL). ROC curve analysis to predict mortality revealed that TAFI levels were able to detect 85% of deaths. In addition, ROC analysis revealed that serum TAFI levels could detect 86% of intubated cases. CONCLUSIONS: The disease progression is more severe in patients with high TAFI levels, and high TAFI levels are associated with mortality and intubation rates. Further studies are needed to determine serum TAFI levels as a biomarker of prognosis in COVID-19 patients.

The Impact of Serum Levels of Reactive Oxygen and Nitrogen Species on the Disease Severity of COVID-19.

Elucidation of the redox pathways in severe coronavirus disease 2019 (COVID-19) might aid in the treatment and management of the disease. However, the roles of individual reactive oxygen species (ROS) and individual reactive nitrogen species (RNS) in COVID-19 severity have not been studied to date. The main objective of this research was to assess the levels of individual ROS and RNS in the sera of COVID-19 patients. The roles of individual ROS and RNS in COVID-19 severity and their usefulness as potential disease severity biomarkers were also clarified for the first time. The current case-control study enrolled 110 COVID-19-positive patients and 50 healthy controls of both genders. The serum levels of three individual RNS (nitric oxide (NO•), nitrogen dioxide (ONO-), and peroxynitrite (ONOO-)) and four ROS (superoxide anion (O2•-), hydroxyl radical (•OH), singlet oxygen (1O2), and hydrogen peroxide (H2O2)) were measured. All subjects underwent thorough clinical and routine laboratory evaluations. The main biochemical markers for disease severity were measured and correlated with the ROS and RNS levels, and they included tumor necrosis factor-alpha (TNF-alpha), interleukin-6 (IL-6), the neutrophil-to-lymphocyte ratio (NLR), and angiotensin-converting enzyme 2 (ACE2). The results indicated that the serum levels of individual ROS and RNS were significantly higher in COVID-19 patients than in healthy subjects. The correlations between the serum levels of ROS and RNS and the biochemical markers ranged from moderate to very strongly positive. Moreover, significantly elevated serum levels of ROS and RNS were observed in intensive care unit (ICU) patients compared with non-ICU patients. Thus, ROS and RNS concentrations in serum can be used as biomarkers to track the prognosis of COVID-19. This investigation demonstrated that oxidative and nitrative stress play a role in the etiology of COVID-19 and contribute to disease severity; thus, ROS and RNS are probable innovative targets in COVID-19 therapeutics.

Serum cystatin C and inflammatory factors related to COVID-19 consequences.

BACKGROUND: Besides impaired respiratory function and immune system, COVID-19 can affect renal function from elevated blood urea nitrogen (BUN) or serum creatinine (sCr) levels to acute kidney injury (AKI) and renal failure. This study aims to investigate the relationship between Cystatin C and other inflammatory factors with the consequences of COVID-19. METHODS: A total of 125 patients with confirmed Covid-19 pneumonia were recruited in this cross-sectional study from March 2021 to May 2022 at Firoozgar educational hospital in Tehran, Iran. Lymphopenia was an absolute lymphocyte count of less than 1.5 × 109/L. AKI was identified as elevated serum Cr concentration or reduced urine output. Pulmonary consequences were evaluated. Mortality was recorded in the hospital one and three months after discharge. The effect of baseline biochemical and inflammatory factors on odds of death was examined. SPSS, version 26, was used for all analyses. P-vale less than 0.05 was considered significant. RESULTS: The highest amount of co-morbidities was attributed to COPD (31%; n = 39), dyslipidemia and hypertension (27%; n = 34 for each) and diabetes (25%; n = 31). The mean baseline cystatin C level was 1.42 ± 0.93 mg/L, baseline creatinine was 1.38 ± 0.86 mg/L, and baseline NLR was 6.17 ± 4.50. Baseline cystatin C level had a direct and highly significant linear relationship with baseline creatinine level of patients (P < 0.001; r: 0.926). ). The average score of the severity of lung involvement was 31.42 ± 10.80. There is a direct and highly significant linear relationship between baseline cystatin C level and lung involvement severity score (r = 0.890, P < 0.001). Cystatin C has a higher diagnostic power in predicting the severity of lung involvement (B = 3.88 ± 1.74, p = 0.026). The mean baseline cystatin C level in patients with AKI was 2.41 ± 1.43 mg/L and significantly higher than patients without AKI (P > 0.001). 34.4% (n = 43) of patients expired in the hospital, and the mean baseline cystatin C level of this group of patients was 1.58 ± 0.90 mg/L which was significantly higher than other patients (1.35 ± 0.94 mg/L, P = 0.002). CONCLUSION: cystatin C and other inflammatory factors such as ferritin, LDH and CRP can help the physician predict the consequences of COVID-19. Timely diagnosis of these factors can help reduce the complications of COVID-19 and better treat this disease. More studies on the consequences of COVID-19 and knowing the related factors will help treat the disease as well as possible.

Serum butyrylcholinesterase as a marker of COVID-19 mortality: Results of the monocentric prospective observational study.

The COVID-19 pandemic represents an excessive burden on health care systems worldwide and the number of patients who require special care in the clinical setting is often hard to predict. Consequently, there is an unmet need for a reliable biomarker that could predict clinical outcomes of high-risk patients. Lower serum butyrylcholinesterase (BChE) activity was recently linked with poor outcomes of COVID-19 patients. In line with this, our monocentric observational study on hospitalized COVID-19 patients focused on changes in serum BChE activity in relation to disease progression. Blood samples from 148 adult patients of both sexes were collected during their hospital stay at the Clinics of Infectiology and Clinics of Anesthesiology and Intensive Care, Trnava University Hospital in alignment with routine blood tests. Sera were analyzed using modified Ellman's method. Patient data with information about the health status, comorbidities and other blood parameters were collected in pseudonymized form. Our results show a lower serum BChE activity together with progressive decline of BChE activity in non-survivors, while higher stable values were present in discharged or transferred patients requiring further care. Lower BChE activity was associated with higher age and lower BMI. Moreover, we observed a negative correlation of serum BChE activity with the routinely used inflammatory markers, C-reactive protein and interleukin-6. Serum BChE activity mirrored clinical outcomes of COVID-19 patients and thus serves as a novel prognostic marker in high-risk patients.

Impact of COVID-19 and vaccination on first and second trimester screening results.

COVID-19 has been shown to affect pregnant women. Since pregnant women are at risk of this infection, vaccination against COVID-19 has been suggested as an imperative way to diminish rate of COVID-19 in this population. In the current observational study, we have collected data of first and second trimester screening (FTS and STS) from pregnant women who were infected with SARS-CoV-2 and/or vaccinated against COVID-19 during their pregnancy, and compared this data with a group of control pregnant women. The cohort included 4612 and 2426 women referred for FTS and STS, respectively. There was no significant difference in median values of Pregnancy-associated plasma protein A (PAPP-A) and human chorionic gonadotropin-beta subunit (ßHCG) between infected women and controls. Moreover, these levels were not different between "Infected + vaccinated" and "Only vaccinated" groups. However, median values of PAPP-A and ßHCG were higher in "Infected + vaccinated" and "Only vaccinated" groups compared with "Infected" and "Control" groups (P < 0.001). Median values of unconjugated Estriol (uE3) and ßHCG markers were not different between "Only vaccinated" and "Control" groups, yet both markers were elevated in "Infected" and "Infected + vaccinated" groups compared with other groups. AFP values were higher in "Infected" group (P = 0.012). However, multiple of the median (MoM) and risk of open spina bifida (OSB) were not affected. Finally, median of calculated risk of trisomy 18 was lower in "Infected" and "Vaccinated" groups compared with controls (P = 0.007). Moreover, AstraZeneca and Sinopharm vaccines were associated with elevation of the calculated risk values of trisomy 21 and trisomy 18 (P < 0.001). While Sinopharm did not affect nuchal translucency (NT) and NT MoM (P = 0.13), AstraZeneca and Barakat increased and decreased these values, respectively (P values = 0.0027 and 0.015, respectively). Taken together, COVID-19 during pregnancy might be associated with some adverse obstetric outcomes. Besides, vaccination against this infection might affect the results of STS or FTS.

Integrative proteomic profiling of lung tissues and blood in acute respiratory distress syndrome.

Introduction: Acute respiratory distress syndrome and acute lung injury (ARDS/ALI) still lack a recognized diagnostic test and pharmacologic treatments that target the underlying pathology. Methods: To explore the sensitive non-invasive biomarkers associated with pathological changes in the lung of direct ARDS/ALI, we performed an integrative proteomic analysis of lung and blood samples from lipopolysaccharide (LPS)-induced ARDS mice and COVID-19-related ARDS patients. The common differentially expressed proteins (DEPs) were identified based on combined proteomic analysis of serum and lung samples in direct ARDS mice model. The clinical value of the common DEPs was validated in lung and plasma proteomics in cases of COVID-19-related ARDS. Results: We identified 368 DEPs in serum and 504 in lung samples from LPS-induced ARDS mice. Gene ontology (GO) classification and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that these DEPs in lung tissues were primarily enriched in pathways, including IL-17 and B cell receptor signaling pathways, and the response to stimuli. In contrast, DEPs in the serum were mostly involved in metabolic pathways and cellular processes. Through network analysis of protein-protein interactions (PPI), we identified diverse clusters of DEPs in the lung and serum samples. We further identified 50 commonly upregulated and 10 commonly downregulated DEPs in the lung and serum samples. Internal validation with a parallel-reacted monitor (PRM) and external validation in the Gene Expression Omnibus (GEO) datasets further showed these confirmed DEPs. We then validated these proteins in the proteomics of patients with ARDS and identified six proteins (HP, LTA4H, S100A9, SAA1, SAA2, and SERPINA3) with good clinical diagnostic and prognostic value. Discussion: These proteins can be viewed as sensitive and non-invasive biomarkers associated with lung pathological changes in the blood and could potentially serve as targets for the early detection and treatment of direct ARDS especially in hyperinflammatory subphenotype.