Evaluation and comparison of eighteen SARS-CoV-2 antibody assays from seven different companies to assess its diagnostic role in SARS-CoV-2 infections.

The diagnostic performance of reverse transcriptase polymerase chain reaction (RT-PCR) decreases during the late acute stage of the corona virus disease (COVID-19) infection; hence, serological assays can be used for disease diagnosis in patients non-protected through vaccinations at this stage. The objective of this study was to assess the diagnostic accuracy of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody tests in current/past infections, determine proper testing time, and check the accuracy of cutoff values. In this study, 18 Ig (immunoglobulin) G, IgM, IgA, and total antibody serological assays were performed using 839 samples. Positive sera (n=132) were collected during the first 5 months after the patients were symptomatic and tested positive for the SARS-CoV-2 RT-PCR test; they were grouped as 0-10, 10-15, >15 days according to the symptom onset. Negative sera (N=707) were obtained from patients with lupus before the pandemic. The performance of IgG and total antibody assays was better than those of IgA, IgM, and IgA-IgM for all post-symptom groups except for 0-10 days, which showed lower Ig assay sensitivity. During 10-15 and >15 days, >70% sensitivity to IgA, IgM, IgM-IgA assays and lower sensitivity were noted, respectively. The sensitivities of IgG and total antibody assays for group C were slightly lower than that of group B. There were no significant differences, but there were higher correlations between the methods or antigenic structures. Receiving operating characteristics (ROC) analysis revealed better cutoff values. For the diagnosis of late acute/past SARS-CoV-2 infection, serological tests can be performed on unvaccinated patients showing symptoms for ≥10 days. SARS-CoV-2 IgG and total antibodies were better diagnostic markers than IgM, IgA, and IgM+IgA, which were restricted to group B.

Association of serum ADMA, SDMA and L-NMMA concentrations with disease progression in COVID-19 patients.

Introduction: This study determines and compares the concentrations of arginine and methylated arginine products ((asymmetric dimethylarginine (ADMA), symmetric dimethylarginine (SDMA), n-monomethyl-1-arginine (L-NMMA) and homoarginine (HA)) for assessment of their association with disease severity in serum samples of COVID-19 patients. Materials and methods: Serum arginine and methylated arginine products of 57 mild-moderate and 29 severe (N = 86) COVID-19 patients and 21 controls were determined by tandem mass spectrometry. Moreover, the concentrations of some of the routine clinical laboratory parameters -neutrophil lymphocyte ratio (NLR), C-reactive protein, ferritin, D-dimer, and fibrinogen measured during COVID-19 follow-up were also taken into consideration and compared with the concentrations of arginine and methylated arginine products. Results: Serum ADMA, SDMA and L-NMMA were found to be significantly higher in severe COVID-19 patients, than in both mild-moderate patients and the control group (P < 0.001 for each). In addition, multiple logistic regression analysis indicated L-NMMA (cut-off =120 nmol/L OR = 34, 95% confidence interval (CI) = 3.5-302.0, P= 0.002), CRP (cut-off = 32 mg/L, OR = 37, 95% CI = 4.8-287.0, P < 0.001), and NLR (cut-off = 7, OR = 22, 95% CI = 1.4-335.0, P = 0.020) as independent risk factors for identification of severe patients. Conclusions: The concentration of methylated arginine metabolites are significantly altered in COVID-19 disease. The results of this study indicate a significant correlation between the severity of COVID-19 disease and concentrations of CRP, NLR and L-NMMA.

Zinc protoporphyrin levels in COVID-19 are indicative of iron deficiency and potential predictor of disease severity.

BACKGROUND: Coronavirus disease (COVID-19) has a severe impact on all aspects of patient care. Among the numerous biomarkers of potential validity for diagnostic and clinical management of COVID-19 are biomarkers at the interface of iron metabolism and inflammation. METHODS: The follow-up study included 54 hospitalized patients with laboratory-confirmed COVID-19 with a moderate and severe/critical form of the disease. Iron deficiency specific biomarkers such as iron, ferritin, transferrin receptor, hepcidin, and zinc protoporphyrin (ZnPP) as well as relevant markers of inflammation were evaluated twice: in the first five days when the patient was admitted to the hospital and during five to 15 days; and their validity to diagnose iron deficiency was further assessed. The regression and Receiver Operating Characteristics (ROC) analyses were performed to evaluate the prognosis and determine the probability for predicting the severity of the disease in the first five days of COVID-19. RESULTS: Based on hemoglobin values, anemia was observed in 21 of 54 patients. Of all iron deficiency anemia-related markers, only ZnPP was significantly elevated (P<0.001) in the anemic group. When patients were grouped according to the severity of disease, slight differences in hemoglobin or other anemia-related parameters could be observed. However, the levels of ZnPP were significantly increased in the severely ill group of patients. The ratio of ZnPP to lymphocyte count (ZnPP/L) had a discrimination power stronger than the neutrophil to lymphocyte count ratio (N/L) to determine disease severity. Additionally, only two markers were independently associated with the severity of COVID-19 in logistic regression analysis; D-dimer (OR (5.606)(95% CI 1.019-30.867)) and ZnPP/L ratio (OR (74.313) (95% CI 1.081-5108.103)). CONCLUSIONS: For the first time ZnPP in COVID-19 patients were reported in this study. Among all iron-related markers tested, ZnPP was the only one that was associated with anemia as based on hemoglobin. The increase in ZnPP might indicate that the underlying cause of anemia in COVID-19 patients is not only due to the inflammation but also of nutritional origin. Additionally, the ZnPP/L ratio might be a valid prognostic marker for the severity of COVID-19.

Kynurenine pathway in Coronavirus disease (COVID-19): Potential role in prognosis.

BACKGROUND: It is known that inflammatory responses play an important role in the pathophysiology of COVID-19. AIMS: In this study, we aimed to examine the role of kynurenine (KYN) metabolism on the severity of COVID-19 disease AQ5. MATERIALS & METHODS: Seventy COVID-19 patients of varying severity and 30 controls were included in the study. In addition to the classical laboratory parameters, KYN, tryptophan (TRP), kynurenic acid (KYNA), 3 hydroxykynurenine (3OHKYN), quinolinic acid (QA), and picolinic acid (PA) were measured with mass spectrometry. RESULTS: TRP, KYN, KYN:TRP ratio, KYNA, 3OHKYN, PA, and QA results were found to be significantly different in COVID-19 patients (p < 0.001 for all). The KYN:TRP ratio and PA of severe COVID-19 patients was statistically higher than that of mild-moderate COVID-19 patients (p < 0.001 for all). When results were examined, statistically significant correlations with KYN:TRP ratio, IL-6, ferritin, and procalcitonin were only found in COVID-19 patients. ROC analysis indicated that highest AUC values were obtained by KYN:TRP ratio and PA (0.751 vs 0.742). In determining the severity of COVID-19 disease, the odd ratios (and confidence intervals) of KYN:TRP ratio and PA levels that were adjusted according to age, gender, and comorbidity were determined to be 1.44 (1.1-1.87, p = 0.008) and 1.06 (1.02-1.11, p = 0.006), respectively. DISCUSSION & CONCLUSION: According to the results of this study, KYN metabolites play a role in the pathophysiology of COVID-19, especially KYN:TRP ratio and PA could be markers for identification of severe COVID-19 cases.

A cross-sectional overview of SARS-CoV-2 genome variations in Turkey

We assessed SARS-CoV-2 genome diversity and probable impact on epidemiology, immune response and clinical disease in Turkey.Complete genomes and partial Spike (S) sequences were accessed from the Global Initiative on Sharing Avian Influenza Data (GISAID) database. The genomes were analysed for variations and recombinations using appropriate softwares.Four hundred ten complete genomes and 206 S region sequences were included. Overall, 1,200 distinct nucleotide variations were noted. Mean variation count was 14.2 per genome and increased significantly during the course of the pandemic. The most frequent variations were identified as A23403G (D614G;92.9,%), C14408T (P323L, 92.2%), C3037T (89.8%), C241T (83.4%) and GGG28881AAC (RG203KR, 62.6%). The A23403G mutation was the most frequent variation in the S region sequences (99%). Most genomes (98.3%) belonged in the SARS-CoV-2 haplogroup A. No evidence for recombination was identified in genomes representing sub-haplogroup branches. The variants B.1.1.7, B.1.351 and P.1 were detected, with a statistically-significant time-associated increase in B.1.1.7 prevalence.We described prominent SARS-CoV-2 variations as well as comparisons with global virus diversity. Continuing a molecular surveillance in agreement with local disease epidemiology appears to be crucial, as vaccination and mitigation efforts are ongoing. (English) [ABSTRACT FROM AUTHOR] Türkiye kaynaklı SARS-CoV-2 genomik dizi çeşitliliğinin ve epidemiyoloji, bağışık yanıt ve hastalık seyri üzerine muhtemel etkili varyasyonların incelenmesi.“Global Initiative on Sharing Avian Influenza Data” (GISAID) veri tabanında yer alan tüm genom ve “Spike” (S) bölgesine ait verilere ulaşılarak uygun yazılımlar yardımıyla varyasyon ve muhtemel rekombinasyonlar araştırıldı.Toplam 410 tam genom ve 206 S bölgesi dizisi incelendi, 1200 farklı nükleotid düzeyinde varyasyon saptandı. Genom başına toplam varyasyon ortalaması 14.2 olarak hesaplandı ve salgının ilerleyişi süresince istatistiksel olarak anlamlı artış izlendi. En sık saptanan varyasyonlar A23403G (D614G;92.9,%), C14408T (P323L, 92.2%), C3037T (89.8%), C241T (83.4%) ve GGG28881AAC (RG203KR, 62.6%) olarak sıralandı. S bölgesi dizilerinde de A23403G, en yaygın varyasyon (%99) şeklinde izlendi. Íncelenen genomların sıklıkla (%98.3) SARS-CoV-2 A haplogrubuna ait olduğu görüldü. Alt haplogrupları temsil eden genomlarda yapılan incelemelerde rekombinasyon bulgusu saptanmadı. Çalışma grubunda B.1.1.7, B.1.351 ve P.1 varyantları tespit edildi. B.1.1.7 prevalansında izlenen zamanla ilişkili artış, istatistiksel olarak anlamlı bulundu.Çalışmada ülkemiz kaynaklı SARS-CoV-2 genomlarında belli başlı varyasyonlar belirlenmiş ve küresel virüs çeşitliliği ışığında değerlendirilmiştir. Kontrol ve aşılama çalışmaları ile eşzamanlı olarak önemli varyantların tanımlanabilmesi için, bölgesel epidemiyoloji ile uyumlu moleküler sürveyans çalışmaları sürdürülmelidir. (Turkish) [ABSTRACT FROM AUTHOR] Copyright of Turkish Journal of Biochemistry / Turk Biyokimya Dergisi is the property of De Gruyter and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A new haematocytometric index: Predicting severity and mortality risk value in COVID-19 patients.

INTRODUCTION: Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 virus, is a major public health concern spanning from healthy carriers to patients with life-threatening conditions. Although most of COVID-19 patients have mild-to-moderate clinical symptoms, some patients have severe pneumonia leading to death. Therefore, the early prediction of disease prognosis and severity is crucial in COVID-19 patients. The main objective of this study is to evaluate the haemocytometric parameters and identify severity score associated with SARS-CoV-2 infection. METHODS: Clinical and laboratory records were retrospectively reviewed from 97 cases of COVID-19 admitted to hospitals in Istanbul, Turkey. The patient groups were subdivided into three major groups: Group 1 (Non-critical): 59 patients, Group 2 (Critical-Survivors): 23 patients and Group 3 (Critical-Non-survivors):15 patients. These data was tested for correlation, including with derived haemocytometric parameters. The blood analyses were performed the Sysmex XN-series automated hematology analyser using standard laboratory protocols. All statistical testing was undertaken using Analyse-it software. RESULTS: 97 patients with COVID-19 disease and 935 sequential complete blood count (CBC-Diff) measurements (days 0-30) were included in the final analyses. Multivariate analysis demonstrated that red cell distribution width (RDW) (>13.7), neutrophil to lymphocyte ratio (NLR) (4.4), Hemoglobin (Hgb) (<11.4 gr/dL) and monocyte to neutrophil ratio (MNR) (0.084) had the highest area under curve (AUC) values, respectively in discrimination critical patients than non-critical patients. In determining Group 3, MNR (<0.095), NLR (>5.2), Plateletcount (PLT) (>142 x103/L) and RDW (>14) were important haemocytometric parameters, and the mortality risk value created by their combination had the highest AUC value (AUC = 0.911, 95% CI, 0886-0.931). Trend analysis of CBC-Diff parameters over 30 days of hospitalization, NLR on day 2, MNR on day 4, RDW on day 6 and PLT on day 7 of admission were found to be the best time related parameters in discrimination non-critical (mild-moderate) patient group from critical (severe and non-survivor) patient group. CONCLUSION: NLR is a strong predictor for the prognosis for severe COVID-19 patients when the cut-off chosen was 4.4, the combined mortality risk factor COVID-19 disease generated from RDW-CV, NLR, MNR and PLT is best as a mortality haematocytometric index.

The molecular footprints of COVID-19

COVID-19 is the third spread of animal coronavirus over the past two decades, resulting in a major epidemic in humans after SARS and MERS. COVID-19 is responsible of the biggest biological earthquake in the world. In the global fight against COVID-19 some serious mistakes have been done like, the countries' misguided attempts to protect their economies, lack of international co-operation. These mistakes that the people had done in previous deadly outbreaks. The result has been a greater economic devastation and the collapse of national and international trust for all. In this constantly changing environment, if we have a better understanding of the hostvirus interactions than we can be more prepared to the future deadly outbreaks. When encountered with a disease which the causative is unknown, the reaction time and the precautions that should be taken matters a great deal. In this review we aimed to reveal the molecular footprints of COVID-19 scientifically and to get an understanding of the pandemia. This review might be a highlight to the possible outbreaks.