The study of serum hsCRP, ferritin, IL-6 and plasma D-dimer in COVID-19: a retrospective study

COVID-19 with high-sensitivity CRP associated with worse dynamic clinical parameters and outcomes

Objective

This study aimed to evaluate the relationship between high-sensitivity C-reactive protein (hsCRP) in hospitalized COVID-19 patients and their clinical outcomes, including trajectory of hsCRP changes during hospitalization.

Method and results

Patients with positive COVID-19 tests between 2021 and 2023 were admitted to two hospitals. Among 184 adult patients, approximately half (47.3%) had elevated hsCRP levels upon admission, which defined as exceeding the laboratory-specific upper limit of test (> 5.0 mg/L). Clinical outcomes included critical illness, acute kidney injury, thrombotic events, intensive care unit (ICU) requirement, and death during hospitalization. Elevated hsCRP levels had a higher risk of ICU requirement than those with normal, 39.1% versus 16.5%; adjusted odds ratio (aOR), 2.3 [95% CI, 1.05-5.01]; p = 0.036. Patients with extremely high (≥2 times) hsCRP levels had aOR, 2.65 [95% CI, 1.09-6.45]; p < 0.001. On the fifth day hospitalization, patients with high hsCRP levels associated with acute kidney injury (aOR, 4.13 [95% CI, 1.30-13.08]; p = 0.016), ICU requirement (aOR, 2.67 [95%CI, 1.02-6.99]; p = 0.044), or death (aOR, 4.24 [95% CI, 1.38-12.99]; p = 0.011). The likelihood of worse clinical outcomes increased as hsCRP levels rose; patients with elevated hsCRP had lower overall survival rate than those with normal (p = 0.02). The subset of high hsCRP patients with high viral load also had a shorter half-life compared to those with normal hsCRP level (p = 0.003).

Conclusion

Elevated hsCRP levels were found to be a significant predictor of ICU requirement, acute kidney injury, or death within 5 days after hospitalization in COVID-19 patients. This emphasized the importance of providing more intensive care management to patients with elevated hsCRP.

Integrative Molecular Structure Elucidation and Construction of an Extended Metabolic Pathway Associated with an Ancient Innate Immune Response in COVID-19 Patients

We present compelling evidence for the existence of an extended innate viperin-dependent pathway, which provides crucial evidence for an adaptive response to viral agents, such as SARS-CoV-2. We show the in vivo biosynthesis of a family of novel endogenous cytosine metabolites with potential antiviral activities. Two-dimensional nuclear magnetic resonance (NMR) spectroscopy revealed a characteristic spin-system motif, indicating the presence of an extended panel of urinary metabolites during the acute viral replication phase. Mass spectrometry additionally enabled the characterization and quantification of the most abundant serum metabolites, showing the potential diagnostic value of the compounds for viral infections. In total, we unveiled ten nucleoside (cytosine- and uracil-based) analogue structures, eight of which were previously unknown in humans allowing us to propose a new extended viperin pathway for the innate production of antiviral compounds. The molecular structures of the nucleoside analogues and their correlation with an array of serum cytokines, including IFN-α2, IFN-γ, and IL-10, suggest an association with the viperin enzyme contributing to an ancient endogenous innate immune defense mechanism against viral infection.

MBOAT7 expression is associated with disease progression in COVID-19 patients

BACKGROUND AND AIM

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in late 2019 caused a pandemic of acute respiratory disease, named coronavirus disease 2019 (COVID-19). COVID-19 became one of the most challenging health emergencies, hence the necessity to find different prognostic factors for disease progression, and severity. Membrane bound O-acyltransferase domain containing 7 (MBOAT7) demonstrates anti-inflammatory effects through acting as a fine-tune regulator of the amount of cellular free arachidonic acid. We aimed in this study to evaluate MBOAT7 expression in COVID-19 patients and to correlate it with disease severity and outcomes.

METHODS

This case-control study included 56 patients with confirmed SARS-CoV-2 diagnosis and 28 control subjects. Patients were further classified into moderate (n = 28) and severe (n = 28) cases. MBOAT7, tumor necrosis factor-α (TNF-α), and interleukin-1ß (IL-1ß) mRNA levels were evaluated in peripheral blood mononuclear cells (PBMC) samples isolated from patients and control subjects by real time quantitative polymerase chain reaction (RT-qPCR). In addition, circulating MBOAT7 protein levels were assayed by enzyme-linked immunosorbent assay (ELISA).

RESULTS

Significant lower levels of circulating MBOAT7 mRNA and protein were observed in COVID-19 patients compared to control subjects with severe COVID-19 cases showing significant lower levels compared to moderate cases. Moreover, severe cases showed a significant upregulation of TNF-α and IL-1ß mRNA. MBOAT7 mRNA and protein levels were significantly correlated with inflammatory markers (TNF-α, IL-1ß, C-reactive protein (CRP), and ferritin), liver enzymes, severity, and oxygen saturation levels.

CONCLUSION

COVID-19 is associated with downregulation of MBAOT7, which correlates with disease severity.

Integrative Plasma Metabolic and Lipidomic Modelling of SARS-CoV-2 Infection in Relation to Clinical Severity and Early Mortality Prediction

An integrative multi-modal metabolic phenotyping model was developed to assess the systemic plasma sequelae of SARS-CoV-2 (rRT-PCR positive) induced COVID-19 disease in patients with different respiratory severity levels. Plasma samples from 306 unvaccinated COVID-19 patients were collected in 2020 and classified into four levels of severity ranging from mild symptoms to severe ventilated cases. These samples were investigated using a combination of quantitative Nuclear Magnetic Resonance (NMR) spectroscopy and Mass Spectrometry (MS) platforms to give broad lipoprotein, lipidomic and amino acid, tryptophan-kynurenine pathway, and biogenic amine pathway coverage. All platforms revealed highly significant differences in metabolite patterns between patients and controls (n = 89) that had been collected prior to the COVID-19 pandemic. The total number of significant metabolites increased with severity with 344 out of the 1034 quantitative variables being common to all severity classes. Metabolic signatures showed a continuum of changes across the respiratory severity levels with the most significant and extensive changes being in the most severely affected patients. Even mildly affected respiratory patients showed multiple highly significant abnormal biochemical signatures reflecting serious metabolic deficiencies of the type observed in Post-acute COVID-19 syndrome patients. The most severe respiratory patients had a high mortality (56.1%) and we found that we could predict mortality in this patient sub-group with high accuracy in some cases up to 61 days prior to death, based on a separate metabolic model, which highlighted a different set of metabolites to those defining the basic disease. Specifically, hexosylceramides (HCER 16:0, HCER 20:0, HCER 24:1, HCER 26:0, HCER 26:1) were markedly elevated in the non-surviving patient group (Cliff's delta 0.91-0.95) and two phosphoethanolamines (PE.O 18:0/18:1, Cliff's delta = -0.98 and PE.P 16:0/18:1, Cliff's delta = -0.93) were markedly lower in the non-survivors. These results indicate that patient morbidity to mortality trajectories is determined relatively soon after infection, opening the opportunity to select more intensive therapeutic interventions to these "high risk" patients in the early disease stages.

Plasma Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9) as a Possible Biomarker for Severe COVID-19

Proprotein convertase subtilisin/kexin type 9 (PCSK9) reduces low density lipoprotein (LDL) uptake, leading to increased plasma levels of LDL. In addition, PCSK9 has been implicated in inflammation independently of the effects on cholesterol metabolism. The current analysis showed that our 156 patients with systemic inflammatory response syndrome (SIRS) or sepsis had higher plasma PCSK9 levels in contrast with the 68 healthy controls. COVID-19 sepsis patients had increased plasma PCSK9 levels in comparison to sepsis patients not infected by SARS-CoV-2. For further analysis, patients were divided in two groups based on COVID-19. In both sub-cohorts, plasma PCSK9 levels did not correlate with C-reactive protein, leukocyte count, and procalcitonin. Plasma PCSK9 levels of both patient groups did not significantly differ among SIRS/sepsis patients with and without dialysis and patients with and without ventilation. Furthermore, vasopressor therapy was not significantly associated with altered plasma PCSK9 levels. In the non-COVID-19 SIRS/sepsis group, patients with Gram-negative and Gram-positive infections had similar plasma PCSK9 levels as patients without a detectable pathogen in their blood. In conclusion, the current study suggests PCSK9 as a possible biomarker for COVID-19, but this needs to be validated in larger cohorts.

Prognostic models in COVID-19 infection that predict severity: a systematic review

Current evidence on COVID-19 prognostic models is inconsistent and clinical applicability remains controversial. We performed a systematic review to summarize and critically appraise the available studies that have developed, assessed and/or validated prognostic models of COVID-19 predicting health outcomes. We searched six bibliographic databases to identify published articles that investigated univariable and multivariable prognostic models predicting adverse outcomes in adult COVID-19 patients, including intensive care unit (ICU) admission, intubation, high-flow nasal therapy (HFNT), extracorporeal membrane oxygenation (ECMO) and mortality. We identified and assessed 314 eligible articles from more than 40 countries, with 152 of these studies presenting mortality, 66 progression to severe or critical illness, 35 mortality and ICU admission combined, 17 ICU admission only, while the remaining 44 studies reported prediction models for mechanical ventilation (MV) or a combination of multiple outcomes. The sample size of included studies varied from 11 to 7,704,171 participants, with a mean age ranging from 18 to 93 years. There were 353 prognostic models investigated, with area under the curve (AUC) ranging from 0.44 to 0.99. A great proportion of studies (61.5%, 193 out of 314) performed internal or external validation or replication. In 312 (99.4%) studies, prognostic models were reported to be at high risk of bias due to uncertainties and challenges surrounding methodological rigor, sampling, handling of missing data, failure to deal with overfitting and heterogeneous definitions of COVID-19 and severity outcomes. While several clinical prognostic models for COVID-19 have been described in the literature, they are limited in generalizability and/or applicability due to deficiencies in addressing fundamental statistical and methodological concerns. Future large, multi-centric and well-designed prognostic prospective studies are needed to clarify remaining uncertainties.