Profiling serum levels of glutathione reductase and interleukin‐10 in positive and negative‐PCR COVID‐19 outpatients: A comparative study from southwestern Iran

Abstract

Since the outbreak of COVID‐19 in China, it has rapidly spread across many other countries. We evaluated antioxidant defense systems and inflammatory status related to the SARS‐CoV2 infection in a population from southwestern Iran. Comorbidities and clinical symptoms of 104 subjects (comprising negative and positive‐PCR COVID‐19 outpatients) were assessed. Serum concentrations of glutathione reductase (GR) and interleukin‐10 (IL‐10) were measured using ELISA. In the positive‐PCR group, follow‐ups on clinical symptoms were carried out for 28 days at 7‐day intervals. In the positive‐PCR group, hypertension, diabetes, liver disease, chronic heart disease, and chronic kidney disease were the most common comorbidities. In the general category of symptoms, we found a significant difference between negative and positive‐PCR groups, except regarding runny noses. In the pulmonary category, there was a significant difference between the two groups except in terms of chest pain. We also determined a significant difference in neurologic symptoms, except for ear pain, between negative and positive‐PCR groups. We also found significantly lower levels of GR but higher levels of IL‐10 in the positive‐PCR group (p = 0.000 for both). In the positive‐PCR group, serum levels of IL‐10 (odds ratio = 0.914, p = 0.012) decreased the chances of neurological symptoms occurring over time. The antioxidant defense systems of positive‐PCR outpatients failed as demonstrated by a reduction in the serum levels of GR. We also indicated a dysregulation in the immune response against COVID‐19, characterized by changes in serum IL‐10 levels.

N-Acetyl Cysteine Restores the Diminished Activity of the Antioxidant Enzymatic System Caused by SARS-CoV-2 Infection: Preliminary Findings

“…This enzyme is essential for the GSH regeneration. A study in 104 subjects showed that the activity of GR was decreased in the SARS-CoV-2 infection [25]. Our results show a decrease in the activity of this enzyme and, although there was a tendency of the activity of GR to increase due to treatment with NAC, it did not show a statistical difference.…”

“…The temperature median was of 36 , the arterial pressure (78, 71-102 mmHg), the body temperature (36, 36.5-37.2 • C), total cholesterol (1363, 89-210 mg/dL), triglycerides (186.5, 80-726 mg/dL), high-density lipoprotein (26, 14-40 mg/dL), low-density lipoprotein (62, 40-110 mg/dL), leukocytes (8.8, 3.5-14.9 10 3 /µL), lymphocytes (8.3, 0.14-1.54 10 3 /µL), platelets median (253, 164-408 10 3 /µL), ferritin (435.4, 146-2592 ng/mL), D-dimer (605, 200-2100 µg/mL), CRP (143.15, 44.7-221 mg/L), IL-6 (16, 7.8-324 pg/mL), NR (8.4, 6-67), procalcitonin (0.23, 0.08-11.4 ng/mL). The sepsis score according to SOFA index was (0, 0-3), APACHE (5.5, 4-8), and SAPS (27,(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32). The patients with moderate and severe condition were 8, respectively (50/50%), and the number of days with mechanic ventilation was (13,, days in ICU were (17,, and death 2 (12%).…”

Reconstructed Genome-Scale Metabolic Model Characterizes Adaptive Metabolic Flux Changes in Peripheral Blood Mononuclear Cells in Severe COVID-19 Patients

“…There were 10 up-regulated enzymes responsible for the increased flux of related metabolic reactions, including pyruvate kinase M1/2 (PKM), cytidine/uridine monophosphate kinase 2 (CMPK2), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), SLC38A5, SLC16A1, SLC2A3, glutathione-disulfide reductase (GSR), myeloperoxidase (MPO), cytochrome P450 family 1 subfamily B member 1 (CYP1B1), and galactosidase beta 1 (GLB1). As a known metabolic marker in serum, GSR shows a significant negative correlation with increased IL-10 in COVID-19 patients [ 85 ]. In addition, MPO involved in steroid metabolism is considered as a neutrophil-derived infection marker to activate the production of cytokines and ROS in severe SARS-CoV-2 infection [ 86 ].…”

The predictive power of data: machine learning analysis for Covid-19 mortality based on personal, clinical, preclinical, and laboratory variables in a case–control study

“…Symptoms such as productive cough, dyspnea, and delirium are significantly associated with COVID-19 mortality, emphasizing the need for immediate monitoring and intervention [ 56 ]. Laboratory tests show altered hematologic and biochemical markers in deceased patients, underscoring the importance of routine laboratory monitoring in COVID-19 patients [ 57 , 58 ].…”