Proteomics is the complete evaluation of the function and structure of proteins to understand an organism’s nature. Mass spectrometry is an essential tool that is used for profiling proteins in the cell. However, biomarker discovery remains the major challenge of proteomics because of their complexity and dynamicity. Therefore, combining the proteomics approach with genomics and bioinformatics will provide an understanding of the information of biological systems and their disease alteration. However, most studies have investigated a small part of the proteins in the blood. This review highlights the types of proteomics, the available proteomic techniques, and their applications in different research fields.
Objectives Critical illness in COVID-19 is attributed to an exaggerated host immune response. Since neutrophils are the major component of innate immunity, we hypothesize that the quantum of activated neutrophils in the blood may predict adverse outcome. Design In a retrospective study of 300 Omani adult patients with confirmed COVID-19, we analyzed the impact of neutrophil activation (NEUT-RI), interleukin-6 (IL-6) and the established clinical risk factors of age, diabetes, obesity and hypertension on the clinical outcome. Results Significant predictors of the need for mechanical ventilation were NEUT-RI (OR = 1.22, p < 0.001), diabetes (OR = 2.56, p = 0.00846) and obesity (OR 6.55, p < 0.001). For death, the significant predictors were NEUT-RI (OR = 1.14, p = 0.00432), diabetes (OR = 4.11, p = 0.00185) and age (OR = 1.04, p = 0.00896). The optimal cut-off value for NEUT-RI to predict mechanical ventilation and death was 52 FI (sensitivity 44%, specificity 88%, AUC 0.67 and 44%, 86%, AUC 0.64 respectively). Conclusion This finding supports an aberrant neutrophil response in COVID-19, likely due to uncontained viral replication, tissue hypoxia and exacerbated inflammation, introduces a novel biomarker for rapid monitoring, and opens new avenues for therapeutic strategies.
A subset of human follicular helper T cells (TFH) cells expresses CD57 for which no distinct function has been identified. We show that CD57+ TFH cells are universally PD-1hi, but compared to their CD57− PD-1hi counterparts, express little IL-21 or IL-10 among others. Instead, CD57 expression on TFH cells marks cytotoxicity transcriptional signatures that translate into only a weak cytotoxic phenotype. Similarly, circulating PD-1+ CD57+ CD4+ T cells make less cytokine than their CD57− PD-1+ counterparts, but have a prominent cytotoxic phenotype. By analysis of responses to STAT3-dependent cytokines and cells from patients with gain- or loss-of-function STAT3 mutations, we show that CD4+ T cell cytotoxicity is STAT3-dependent. TFH formation also requires STAT3, but paradoxically, once formed, PD-1hi cells become unresponsive to STAT3. These findings suggest that changes in blood and germinal center cytotoxicity might be affected by changes in STAT3 signaling, or modulation of PD-1 by therapy.
Background : Identifying immune cells involved in COVID-19 disease progression and predictors of poor outcomes is important to manage patients adequately. Methods : A prospective observational cohort study enrolled 53 mild non-hospitalized and 48 hospitalized confirmed COVID-19 patients to a tertiary hospital in Oman. Results : Hospitalized patients were older (58 years vs 36 years, p <0.001) and had more comorbid conditions like diabetes (65 % Vs 21% p <0.001). Hospitalized patients had significantly higher inflammatory markers ( p <0.001); C-reactive protein (CRP) (114 vs 4 mg/L), Interleukin-6 (IL-6) (33 vs 3.71pg/ml), lactate dehydrogenase (LDH) (417 vs 214 U/L), ferritin (760 vs 196 ng/mL), fibrinogen (6 vs 3 g/L), D-dimer (1.0 vs 0.3 mcg/mL), disseminated intravascular coagulopathy (DIC) score (2 vs 0) and neutrophil/lymphocyte ratio (4 vs 1.1), ( p <0.001). In multivariate regression analysis, statistically significant independent early predictors of ICU admission or death were higher levels of IL-6 (OR 1.03, p =0.03), frequency of large inflammatory monocytes (CD14+CD16+) (OR 1.117, p =0.010) and frequency of circulating naïve CD4+ T cells (CD27+CD28+CD45RA+CCR7+) (OR 0.476, p =0.03). Conclusion : IL-6, frequency of large inflammatory monocytes, and circulating naïve CD4 T cells can be used as independent immunological predictors of poor outcomes in COVID-19 patients to prioritize critical care and resources.
The specific IgG reference range within a healthy adult Omani population was comparable to those reported in other populations.
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