Phosphate and IL-10 concentration as predictors of long-covid in hemodialysis patients: A Brazilian study

Liquid saliva-based Raman spectroscopy device with on-board machine learning detects COVID-19 infection in real-time

With greater population density, the likelihood of viral outbreaks achieving pandemic status is increasing. However, current viral screening techniques use specific reagents, and as viruses mutate, test accuracy decreases. Here, we present the first real-time, reagent-free, portable analysis platform for viral detection in liquid saliva, using COVID-19 as a proof-of-concept. We show that vibrational molecular spectroscopy and machine learning (ML) detect biomolecular changes consistent with the presence of viral infection. Saliva samples were collected from 470 individuals, including 65 that were infected with COVID-19 (28 from hospitalized patients and 37 from a walk-in testing clinic) and 251 that had a negative polymerase chain reaction (PCR) test. A further 154 were collected from healthy volunteers. Saliva measurements were achieved in 6 minutes or less and led to machine learning models predicting COVID-19 infection with sensitivity and specificity reaching 90%, depending on volunteer symptoms and disease severity. Machine learning models were based on linear support vector machines (SVM). This platform could be deployed to manage future pandemics using the same hardware but using a tunable machine learning model that could be rapidly updated as new viral strains emerge.

Immune activation and immune-associated neurotoxicity in Long-COVID: A systematic review and meta-analysis of 103 studies comprising 58 cytokines/chemokines/growth factors

BACKGROUND

Multiple studies have shown that Long COVID (LC) disease is associated with heightened immune activation, as evidenced by elevated levels of inflammatory mediators. However, there is no comprehensive meta-analysis focusing on activation of the immune inflammatory response system (IRS) and the compensatory immunoregulatory system (CIRS) along with other immune phenotypes in LC patients.

OBJECTIVES

This meta-analysis is designed to explore the IRS and CIRS profiles in LC patients, the individual cytokines, chemokines, growth factors, along with C-reactive protein (CRP) and immune-associated neurotoxicity.

METHODS

To gather relevant studies for our research, we conducted a thorough search using databases such as PubMed, Google Scholar, and SciFinder, covering all available literature up to July 5th, 2024.

RESULTS

The current meta-analysis encompassed 103 studies that examined multiple immune profiles, C-reactive protein, and 58 cytokines/chemokines/growth factors in 5502 LC patients versus 5962 normal controls (NC). LC patients showed significant increases in IRS/CIRS ratio (standardized mean difference (SMD: 0.156, confidence interval (CI): 0.062;0.250), IRS (SMD: 0.338, CI: 0.236;0.440), M1 macrophage (SMD: 0.371, CI: 0.263;0.480), T helper (Th)1 (SMD: 0.316, CI: 0.185;0.446), Th17 (SMD: 0.439, CI: 0.302;0.577) and immune-associated neurotoxicity (SMD: 0.384, CI: 0.271;0.497). In addition, CRP and 21 different cytokines displayed significantly elevated levels in LC patients compared to NC.

CONCLUSION

LC disease is characterized by IRS activation and increased immune-associated neurotoxicity.

IL-6 and IL-17 as potential links between pre-existing hypertension and long-term COVID sequelae in patients undergoing hemodialysis: a multicenter cross-sectional study

Long COVID, characterized by persistent symptoms following acute infection, poses a significant health challenge, particularly for patients with pre-existing chronic conditions such as hypertension. We hypothesized that an increase in the production of interleukins (IL)-6 and IL-17 could serve as a potential mechanism linking pre-existing uncontrolled blood pressure (BP) to the occurrence of long-term COVID sequelae in patients undergoing hemodialysis (HD). This cross-sectional study examined serum IL-6 and IL-17 levels in 80 patients undergoing HD, considering preinfection BP, the presence of long-term COVID sequelae, and the time interval after acute COVID-19 infection, which was either 5 or 10 months. Controlled BP was defined as a 3-month average pre-dialysis BP < 140/90 mmHg and post-dialysis < 130/80 mmHg. The findings suggest that the prevalence of long-term COVID sequelae was significantly higher in patients with uncontrolled BP than in the BP-controlled group. Both IL-6 and IL-17 concentrations were also significantly higher in patients with uncontrolled BP compared with the BP-controlled group. The patients with long-term COVID sequelae had higher IL-6 and IL-17 values than the fully recovered patients at both time points, but their concentrations decreased significantly over time. Further research and prospective studies are warranted to validate these findings.

Maintained imbalance of triglycerides, apolipoproteins, energy metabolites and cytokines in long-term COVID-19 syndrome patients

Background

Deep metabolomic, proteomic and immunologic phenotyping of patients suffering from an infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have matched a wide diversity of clinical symptoms with potential biomarkers for coronavirus disease 2019 (COVID-19). Several studies have described the role of small as well as complex molecules such as metabolites, cytokines, chemokines and lipoproteins during infection and in recovered patients. In fact, after an acute SARS-CoV-2 viral infection almost 10-20% of patients experience persistent symptoms post 12 weeks of recovery defined as long-term COVID-19 syndrome (LTCS) or long post-acute COVID-19 syndrome (PACS). Emerging evidence revealed that a dysregulated immune system and persisting inflammation could be one of the key drivers of LTCS. However, how these biomolecules altogether govern pathophysiology is largely underexplored. Thus, a clear understanding of how these parameters within an integrated fashion could predict the disease course would help to stratify LTCS patients from acute COVID-19 or recovered patients. This could even allow to elucidation of a potential mechanistic role of these biomolecules during the disease course.

Methods

This study comprised subjects with acute COVID-19 (n=7; longitudinal), LTCS (n=33), Recov (n=12), and no history of positive testing (n=73). ¹H-NMR-based metabolomics with IVDr standard operating procedures verified and phenotyped all blood samples by quantifying 38 metabolites and 112 lipoprotein properties. Univariate and multivariate statistics identified NMR-based and cytokine changes.

Results

Here, we report on an integrated analysis of serum/plasma by NMR spectroscopy and flow cytometry-based cytokines/chemokines quantification in LTCS patients. We identified that in LTCS patients lactate and pyruvate were significantly different from either healthy controls (HC) or acute COVID-19 patients. Subsequently, correlation analysis in LTCS group only among cytokines and amino acids revealed that histidine and glutamine were uniquely attributed mainly with pro-inflammatory cytokines. Of note, triglycerides and several lipoproteins (apolipoproteins Apo-A1 and A2) in LTCS patients demonstrate COVID-19-like alterations compared with HC. Interestingly, LTCS and acute COVID-19 samples were distinguished mostly by their phenylalanine, 3-hydroxybutyrate (3-HB) and glucose concentrations, illustrating an imbalanced energy metabolism. Most of the cytokines and chemokines were present at low levels in LTCS patients compared with HC except for IL-18 chemokine, which tended to be higher in LTCS patients.

Conclusion

The identification of these persisting plasma metabolites, lipoprotein and inflammation alterations will help to better stratify LTCS patients from other diseases and could help to predict ongoing severity of LTCS patients.

Inflammatory and vascular biomarkers in post-COVID-19 syndrome: A systematic review and meta-analysis of over 20 biomarkers

Severe acute respiratory syndrome coronavirus 2 may inflict a post-viral condition known as post-COVID-19 syndrome (PCS) or long-COVID. Studies measuring levels of inflammatory and vascular biomarkers in blood, serum, or plasma of COVID-19 survivors with PCS versus non-PCS controls have produced mixed findings. Our review sought to meta-analyse those studies. A systematic literature search was performed across five databases until 25 June 2022, with an updated search on 1 November 2022. Data analyses were performed with Review Manager and R Studio statistical software. Twenty-four biomarkers from 23 studies were meta-analysed. Higher levels of C-reactive protein (Standardized mean difference (SMD) = 0.20; 95% CI: 0.02-0.39), D-dimer (SMD = 0.27; 95% CI: 0.09-0.46), lactate dehydrogenase (SMD = 0.30; 95% CI: 0.05-0.54), and leukocytes (SMD = 0.34; 95% CI: 0.02-0.66) were found in COVID-19 survivors with PCS than in those without PCS. After sensitivity analyses, lymphocytes (SMD = 0.30; 95% CI: 0.12-0.48) and interleukin-6 (SMD = 0.30; 95% CI: 0.12-0.49) were also significantly higher in PCS than non-PCS cases. No significant differences were noted in the remaining biomarkers investigated (e.g., ferritin, platelets, troponin, and fibrinogen). Subgroup analyses suggested the biomarker changes were mainly driven by PCS cases diagnosed via manifestation of organ abnormalities rather than symptomatic persistence, as well as PCS cases with duration of <6 than ≥6 months. In conclusion, our review pinpointed certain inflammatory and vascular biomarkers associated with PCS, which may shed light on potential new approaches to understanding, diagnosing, and treating PCS.