Salivary biomarkers in COVID-19 patients.

The use of salivary biomarkers in diagnosis, treatment, and overall prognosis of coronavirus disease 2019 (COVID-19) has been developed recently. Salivary biomarkers are extremely promising as they are fast to obtain and involve noninvasive collection of specimens. Monitoring patients in real time is necessary in this pandemic. Saliva is another biofluid with major advantages at the molecular level. Methods that detect viral presence in the host secretions measure the current infection by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), whereas the detection of human antibodies against SARS-CoV-2 evaluates the past exposure to the virus. There is an urgent need to increase the active research for the detection of SARS-CoV-2 in saliva because diagnostics may provide a reliable and cost-effective method and is suitable for the fast and early detection of COVID-19 infection. Salivary biomarkers have a potential to be a vital guide in determining coronavirus disease. Many people still do not get results of COVID-19 tests due to imbalance between supply and demand at large testing centers. The use of saliva has various advantages compared to collection of nasopharyngeal swabs. New techniques should be developed for detecting salivary biomarkers that help in diagnosis of COVID-19.

Serum Procalcitonin as a Predictive Biomarker in COVID-19: A Retrospective Cohort Analysis.

INTRODUCTION:  Since the onset of COVID-19, physicians and scientists have been working to further understand biomarkers associated with the infection, so that patients who have contracted the virus can be treated. Although COVID-19 is a complex virus that affects patients differently, current research suggests that COVID-19 infections have been associated with increased procalcitonin, a biomarker traditionally indicative of bacterial infections. This paper aims to investigate the relationship between COVID-19 infection severity and procalcitonin levels in the hopes to aid the management of patients with COVID-19 infections. METHODS:  Patient data were obtained from the Renaissance School of Medicine at Stony Brook University. The data of the patients who had tested positive for COVID-19 and had an associated procalcitonin value (n=1046) was divided into age splits of 18-59, 59-74, and 74-90. Multiple factors were analyzed to determine the severity of each patient's infection. Patients were divided into low, medium, and high severity dependent on the patient's COVID-19 severity. A one-way analysis of variance (ANOVA) was done for each age split to compare procalcitonin values of the severity groups within the respective age split. Next, post hoc analysis was done for the severity groups in each age split to further compare the groups against each other.  Results: One-way ANOVA testing of the three age splits all had a resulting p<0.0001, displaying that the null hypothesis was rejected. In the post hoc analysis, however, the test failed to reject the null hypothesis when comparing the medium and high severity groups against each other in the 59-74 and 74-90 age splits. The null hypothesis was rejected in all pairwise comparisons in the 18-59 age split. We determined that a procalcitonin value of greater than 0.24 ng/mL would be characterized as a more severe COVID-19 infection when considering patient factors and comorbidities.  Conclusion: The analysis of the data concluded that elevated procalcitonin levels correlated with the severity of COVID-19 infections. This finding can be used to assist medical providers in the management of COVID-19 patients.

Orally delivered perilla (Perilla frutescens) leaf extract effectively inhibits SARS-CoV-2 infection in a Syrian hamster model

On analyzing the results of cell-based assays, we have previously shown that perilla (Perilla frutescens) leaf extract (PLE), a food supplement and orally deliverable traditional Chinese medicine approved by the Taiwan Food and Drug Administration, effectively inhibits SARS-CoV-2 by directly targeting virions. PLE was also found to modulate virus-induced cytokine expression levels. In this study, we explored the anti-SARS-CoV-2 activity of PLE in a hamster model by examining viral loads and virus-induced immunopathology in lung tissues. Experimental animals were intranasally challenged with different SARS-CoV-2 doses. Jugular blood samples and lung tissue specimens were obtained in the acute disease stage (3-4 post-infection days). As expected, SARS-CoV-2 induced lung inflammation and hemorrhagic effusions in the alveoli and perivascular areas;additionally, it increased the expression of several immune markers of lung injury - including lung Ki67-positive cells, Iba-1-positive macrophages, and myeloperoxidase-positive neutrophils. Virus-induced lung alterations were significantly attenuated by orally administered PLE. In addition, pretreatment of hamsters with PLE significantly reduced viral loads and immune marker expression. A purified active fraction of PLE was found to confer higher antiviral protection. Notably, PLE prevented SARS-CoV-2-induced increase in serum markers of liver and kidney function as well as the decrease in serum high-density lipoprotein and total cholesterol levels in a dose-dependent fashion. Differently from lung pathology, monitoring of serum biomarkers in Syrian hamsters may allow a more humane assessment of the novel drugs with potential anti-SARS-CoV-2 activity. Our results expand prior research by confirming that PLE may exert an in vivo therapeutic activity against SARS-CoV-2 by attenuating viral loads and lung tissue inflammation, which may pave the way for future clinical applications.

Early Warning of Infection in Patients Undergoing Hematopoietic Stem Cell Transplantation Using Heart Rate Variability and Serum Biomarkers.

Early warning of infection is critical to reduce the risk of deterioration and mortality, especially in neutropenic patients following hematopoietic stem cell transplantation (HCT). Given that heart rate variability (HRV) is a sensitive and early marker for infection, and that serum inflammatory biomarkers can have high specificity for infection, we hypothesized their combination may be useful for accurate early warning of infection. In this study, we developed and evaluated a composite predictive model using continuous HRV with daily serum biomarker measurements to provide risk stratification of future deterioration in HCT recipients. A total of 116 ambulatory outpatients about to undergo HCT consented to collection of prospective demographic, clinical (daily vital signs), HRV (continuous electrocardiography [ECG] monitoring, laboratory [daily serum samples frozen at -80 °C]), and infection outcome variables (defined as the time of escalation of antibiotics), all from 24 hours pre-HCT to the onset of infection or 14 days post-HCT. Indications for antibiotic escalation were adjudicated as "true infection" or not by 2 blinded HCT clinicians. A composite time series of 8 HRV metrics was created for each patient, and the probability of deterioration within the next 72 hours was estimated using logistic regression modeling of composite HRV and serum biomarkers using a rule-based naïve Bayes model if the HRV-based probability exceeded a median threshold. Thirty-five patients (30%) withdrew within <24 hours owing to intolerability of ECG monitoring, leaving 81 patients, of whom 48 (59%) had antibiotic escalation adjudicated as true infection. The combined HRV and biomarker (TNF-α, IL-6, and IL-7) predictive model began increasing at ~48 hours on average before the diagnosis of infection, could distinguish between high risk of impending infection (>90% incidence of subsequent infection within 72 hours), average risk (~50%), and low risk (<10%), with an area under the receiver operating characteristic curve of 0.87. However, given that prophylactic predictive ECG monitoring and daily serum collection proved challenging for many patients, further refinement in measurement is necessary for further study.

Impact of COVID-19 on Renal Function: A Multivariate Analysis of Biochemical and Immunological Markers in Patients.

Introduction There have been tremendous continuous efforts to understand the broad spectrum of disease and its sequelae since the start of the coronavirus disease 2019 (COVID-19) pandemic. Several studies have identified biomarkers that correlate with multiple organ failure in COVID-19 patients. The purpose of our study was to evaluate COVID-19-associated kidney injury. Methods This retrospective cross-sectional study was conducted at the Institute of Biochemistry, Madras Medical College, by reviewing the electronic records of 1,000 reverse transcription-polymerase chain reaction (RT-PCR)-confirmed COVID-19-positive patients admitted at the COVID-19 care center. Data were extracted from the case records of 1,000 RT-PCR-positive patients with different CT chest grades plus comorbid conditions such as type 2 diabetes mellitus (T2DM), systemic hypertension (SHT), coronary artery disease (CAD), chronic obstructive pulmonary disease (COPD), and cerebrovascular accident (CVA) as Group I (n = 500). Group II (n = 500) comprised of COVID-19-positive patients with no comorbid conditions. The data were recorded from all the patients at the time of admission, prior to starting treatment. Patients with comorbid and non-comorbid conditions were compared according to different CT grades. Results COVID-19 patients with different CT grades showed a significant relationship with creatinine, sodium, potassium, C-reactive protein (CRP), ferritin, total protein, and albumin with p-values of 0.04, 0.01, 0.02, 0.000, 0.00, 0.00, and 0.000, respectively, in Group I. In Group II, with various grades of CT changes, the neutrophil-lymphocyte ratio (NLR) and creatinine showed no significance. The sodium, potassium, CRP, ferritin, total protein, and albumin showed low significance with the chest CT grades. Conclusions Our study demonstrated that COVID-19 can cause mild to moderate renal impairment in COVID-19 patients. Multiple factors contributed to this, such as the higher angiotensin-converting enzyme 2 (ACE2) expression on kidney cells, microinflammation, increased blood clotting, and probable direct infection of the kidney. A high NLR, increased inflammatory markers, and altered renal function analytes such as urea, creatinine, sodium, potassium, total protein, and albumin also confirmed this.

Lung Function, Radiological Findings and Biomarkers of Fibrogenesis in a Cohort of COVID-19 Patients Six Months After Hospital Discharge.

INTRODUCTION: Impairment in pulmonary function tests and radiological abnormalities are a major concern in COVID-19 survivors. Our aim is to evaluate functional respiratory parameters, changes in chest CT, and correlation with peripheral blood biomarkers involved in lung fibrosis at two and six months after SARS-CoV-2 pneumonia. METHODS: COVID-FIBROTIC (clinicaltrials.gov NCT04409275) is a multicenter prospective observational cohort study aimed to evaluate discharged patients. Pulmonary function tests, circulating serum biomarkers, chest radiography and chest CT were performed at outpatient visits. RESULTS: In total, 313, aged 61.12 ± 12.26 years, out of 481 included patients were available. The proportion of patients with DLCO < 80% was 54.6% and 47% at 60 and 180 days. Associated factors with diffusion impairment at 6 months were female sex (OR: 2.97, 95%CI 1.74-5.06, p = 0.001), age (OR: 1.03, 95% CI: 1.01-1.05, p = 0.005), and peak RALE score (OR: 1.22, 95% CI 1.06-1.40, p = 0.005). Patients with altered lung diffusion showed higher levels of MMP-7 (11.54 ± 8.96 vs 6.71 ± 4.25, p = 0.001), and periostin (1.11 ± 0.07 vs 0.84 ± 0.40, p = 0.001). 226 patients underwent CT scan, of whom 149 (66%) had radiological sequelae of COVID-19. In severe patients, 68.35% had ground glass opacities and 38.46% had parenchymal bands. Early fibrotic changes were associated with higher levels of MMP7 (13.20 ± 9.20 vs 7.92 ± 6.32, p = 0.001), MMP1 (10.40 ± 8.21 vs 6.97 ± 8.89, p = 0.023), and periostin (1.36 ± 0.93 vs 0.87 ± 0.39, p = 0.001). CONCLUSION: Almost half of patients with moderate or severe COVID-19 pneumonia had impaired pulmonary diffusion six months after discharge. Severe patients showed fibrotic lesions in CT scan and elevated serum biomarkers involved in pulmonary fibrosis.

INTRODUCCIÓN: El deterioro de la función pulmonar en las pruebas correspondientes y las alteraciones radiológicas son las preocupaciones principales en los supervivientes de la COVID-19. Nuestro objetivo fue evaluar los parámetros de la función respiratoria, los cambios en la TC de tórax y la correlación con los biomarcadores en sangre periférica involucrados en la fibrosis pulmonar a los 2 y a los 6 meses tras la neumonía por SARS-CoV-2. MÉTODOS: El ensayo COVID-FIBROTIC (clinicaltrials.gov NCT04409275) es un estudio de cohortes multicéntrico, prospectivo y observacional cuyo objetivo fue evaluar los pacientes dados de alta. Se realizaron pruebas de función pulmonar, detección de biomarcadores en plasma circulante y radiografía y TC de tórax durante las visitas ambulatorias. RESULTADOS: En total 313 pacientes, de 61,12 ± 12,26 años, de los 481 incluidos estuvieron disponibles.La proporción de pacientes con DLCO < 80% fue del 54,6 y del 47% a los 60 y 180 días.Los factores que se asociaron a la alteración de la difusión a los 6 meses fueron el sexo femenino (OR: 2,97; IC del 95%: 1,74-5,06; p = 0,001), la edad (OR: 1,03; IC del 95%: 1,01-1,05; p = 0,005) y la puntuación RALE más alta (OR: 1,22; IC del 95%: 1,06-1,40; p = 0,005). Los pacientes con alteración de la difusión pulmonar mostraron niveles más altos de MMP-7 (11,54 ± 8,96 frente a 6,71 ± 4,25; p = 0,001) y periostina (1,11 ± 0.07 frente a 0,84 ± 0,40; p = 0,001). Se le realizó una TC a 226 pacientes de los cuales 149 (66%) presentaban secuelas radiológicas de la COVID-19. En los pacientes graves, el 68,35% mostraban opacidades en vidrio esmerilado y el 38,46%, bandas parenquimatosas. Los cambios fibróticos tempranos se asociaron a niveles más altos de MMP7 (13,20 ± 9,20 frente a 7,92 ± 6,32; p = 0,001), MMP1 (10,40 ± 8,21 frente a 6,97 ± 8,89; p = 0,023), y periostina (1,36 ± 0,93 frente a 0,87 ± 0,39; p = 0,001). CONCLUSIÓN: Casi la mitad de los pacientes con neumonía moderada o grave por COVID-19 presentaba alteración de la difusión pulmonar 6 meses después del alta. Los pacientes graves mostraban lesiones fibróticas en laTC y un aumento de los biomarcadores séricos relacionados con la fibrosis pulmonar.

Quench me if you can: Alpha-2-macroglobulin trypsin complexes enable serum biomarker analysis by MALDI mass spectrometry.

One of the main functions of alpha-2-macroglobulin (A2M) in human blood serum is the binding of all classes of protease. It is known that trypsin, after such interaction, possesses modified proteolytic activity. Trypsin first hydrolyzes two bonds in A2M's 'bait region', and the peptide 705VGFYESDVMGR715 is released from A2M. In this work, specifics of the A2M-trypsin interaction were used to determine A2M concentration directly in human blood serum using MALDI mass-spectrometry. Following exogenous addition of trypsin to human blood serum in vitro, the concentration of the VGFYESDVMGR peptide was measured, using its isotopically-labeled analogue (18O), and A2M concentration was calculated. The optimized mass spectrometric approach was verified using a standard method for A2M concentration determination (ELISA) and the relevant statistical analysis methods. It was also shown that trypsin's modified proteolytic activity in the presence of serum A2M can be used to analyze other serum proteins, including potential biomarkers of pathological processes. Thus, this work describes a promising approach to serum biomarker analysis that can be technically extended in several useful directions.

The Impact of COVID-19-Related Lockdown on Diet and Serum Markers in Healthy Adults.

Due to limited data about the impact of lockdown on health status, the present study aimed to investigate the impact of COVID-19-related lockdown on changes in dietary habits, physical activity and serum markers in healthy adults. A total of 38 asymptomatic adults aged from 23 to 59 with a normal BMI (22.5 kg/m2) participated in baseline and post-lockdown measurements that included dietary and physical activity assessment, anthropometric measurements and blood samples; and the lockdown survey which included dietary assessment and questionnaires about changes in lifestyle and physical activity. A decreased diet quality during lockdown was observed (Healthy Eating Index reduced from 64.59 to 61.08), which returned to near baseline post-lockdown. Energy intake decreased during lockdown (p = 0.002) and returned to baseline post-lockdown. Despite lower physical activity levels during lockdown (p = 0.035), we observed no significant changes in body composition. However, we observed a significant increase in serum glucose (p = 0.005), total cholesterol (p = 0.003), and low-density lipoprotein (LDL) (p = 0.049) post-lockdown. Increase in serum glucose levels was pronounced in subjects with higher increase in energy intake (p = 0.039), increased omega-6 fatty acids intake (p = 0.016), those who were exposed to several risky contacts (p = 0.018, compared to those with less risky contacts) and those who were not active in nature (p = 0.008, compared to those active in nature). Increased serum LDL was correlated to decreased monounsaturated fatty acids intake (p = 0.028). Within the limits of this preliminary report, changes in serum markers observed among healthy subjects point to a possible impact of COVID-19-related lockdown on adults' health to be confirmed in larger groups.

Value of clinical laboratory test for early prediction of mortality in patients with COVID-19: the BGM score.

BACKGROUND: COVID-19 causes high mortality and long hospitalization periods. The aim of this study was to search for new early prognostic strategies accessible to most health care centers. METHODS: Laboratory results, demographic and clinical data from 500 patients with positive SARS-CoV-2 infection were included in our study. The data set was split into training and test set prior to generating different multivariate models considering the occurrence of death as the response variable. A final computational method called the BGM score was obtained by combining the previous models and is available as an interactive web application. RESULTS: The logistic regression model comprising age, creatinine (CREA), D-dimer (DD), C-reactive protein (CRP), platelet count (PLT), and troponin I (TNI) showed a sensitivity of 47.3%, a specificity of 98.7%, a kappa of 0.56, and a balanced accuracy of 0.73. The CART classification tree yielded TNI, age, DD, and CRP as the most potent early predictors of mortality (sensitivity = 68.4%, specificity = 92.5%, kappa = 0.61, and balanced accuracy = 0.80). The artificial neural network including age, CREA, DD, CRP, PLT, and TNI yielded a sensitivity of 66.7%, a specificity of 92.3%, a kappa of 0.54, and a balanced accuracy of 0.79. Finally, the BGM score surpassed the prediction accuracy performance of the independent multivariate models, yielding a sensitivity of 73.7%, a specificity of 96.5%, a kappa of 0.74, and a balanced accuracy of 0.85. CONCLUSIONS: The BGM score may support clinicians in managing COVID-19 patients and providing focused interventions to those with an increased risk of mortality.

Reduction in Chronic Disease Risk and Burden in a 70-Individual Cohort Through Modification of Health Behaviors.

Introduction Health risk factors, including lifestyle risks and health literacy, are known to contribute to the chronic disease epidemic. According to the Centers for Disease Control and Prevention (CDC), chronic diseases account for 90% of healthcare costs, morbidity, and mortality. In the United States, healthcare providers attempt to modulate a limited set of risks. However, chronic diseases continue to proliferate despite expansion of wellness programs and drugs to manage and prevent chronic conditions. Pandemics, exemplified by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), show that people in good health suffer mortality rates at 10% the rate compared to those with pre-existing chronic conditions. Healthcare costs and morbidity rates often parallel mortality rates. New root-cause risk and health tools that accommodate low health literacy and are linked to personalized health improvement care plans are needed to reverse the chronic disease epidemic. Reported here is a study on 70 manufacturing employees in the Midwest US using a personalized and group approach to chronic disease reversal and prevention which may also find utility in pandemic severity and policy decisions. Methods Health, lifestyle, behavior, and motivation data were collected on 70 individuals at the beginning of a nine-month disease reversal and prevention program. The data were updated every two to six months over the period. Inputs included information from a novel health risk assessment, serum biomarkers specific for chronic disease, and traditional medical information. Using all these data we generated robust, personalized, and modifiable care plans that were implemented by the participant and guided by a care team including health coaches and medical providers. Periodic renewal of profile data and biomarkers facilitated adjustment of care plans to optimize the path toward health goals set mutually by the participant and the care team. Results Ninety percent of participants experienced a favorable reduction in chronic disease biomarkers. The reduction in serum biomarkers coincided with a reduction in disease and risk attributes based on medical chart data and before and after interviews. Hemoglobin A1C, for example, lowered in all but one participant concomitant with reported improved energy and reduced need for medications in the majority of participants. Markers of inflammation lowered across the population. Most importantly each individual reported improvement in their overall health. Conclusions This simple, inexpensive, root-cause based risk and health approach generates a "do no harm" action plan that guides a care team, including the participant, on a path to improved health. The data demonstrate that changes in a novel risk calculator score coincide with changes in sensitive biomarkers for chronic disease. When the risks of an individual are reduced, the biomarkers reflect that change with self-reported wellbeing also improved. This program and process may be of value to society plagued with escalating levels of chronic disease and merits further study and implementation.