The concentrations of essential/toxic elements in serum of COVID-19 patients are not directly related to the severity of the disease

BackgroundIn recent months, the current COVID-19 pandemic has generated thousands of studies directly or indirectly related with this disease and/or the coronavirus SARS-CoV-2 causing the infection. On August 22, 2022, the database PUBMED included 287,639 publications containing the term COVID-19. However, in spite of the importance of trace elements in human health, including the immune system, data on the levels of metals/metalloids in COVID-19 patients is very limited.MethodsThe concentrations of As, Cd, Cr, Cu, Hg, Fe, Mg, Mn, Pb, Se, V and Zn were determined by inductively coupled plasma-mass spectrometry (ICP-MS) in 126 serum samples of individuals infected with SARS-CoV-2, as well as in 88 samples of non-infected individuals. Participants were divided into four groups: i) individuals COVID-19 positive (COVID-19 +) with an asymptomatic infection course; ii) individuals suffering mild COVID-19; iii) individuals suffering severe COVID-19, and iv) individuals COVID-19 negative (COVID-19-) (control group). The occurrence of the analyzed metals/metalloids was evaluated along with the biochemical profile, including blood cell counts, lipids, proteins and crucial enzymes.ResultsSerum levels of Mg, V, Cr, Cu, Cd, and Pb were higher in COVID-19 positive patients than those in the control group. Although no significant differences were observed between the different groups of patients, the concentrations of Cd, Pb, V and Zn showed a tendency to be higher in individuals with severe COVID-19 than in those showing mild symptoms or being asymptomatic. Arsenic and Hg were rarely detected, regardless if the subjects were infected by SARS-CoV-2, or not. The current results did not show significant differences in the levels of the rest of analyzed elements according to the severity of the disease (asymptomatic, mild and severe).ConclusionsIn spite of the results here obtained, we highlight the need to reduce the exposure to Cd, Pb and V to minimize the potential adverse health outcomes after COVID-19 infection. On the other hand, although a protective role of essential elements was not found, Mg and Cu concentrations were higher in severe COVID-19 patients than in non-infected individuals.     

基于脂质组学技术研究急性缺血性脑卒中临床诊断标志物

目的:急性缺血性脑卒中(Acute ischemic stroke, AIS)是由于血流减少导致的脑功能突然丧失。由于AIS发病机制是异质性和多因素的,我们建立全面的脂质组学方法来阐明AIS进程相关的脂质变化和复杂的脂质代谢网络。方法:选取26例AIS患者血液标本和27例健康志愿者血清作为研究对象,进行总脂抽提,通过基于LC-MS策略的非靶向脂质组学方法进行规模性、整体性的脂质组学分析。结果:对AIS患者和健康志愿者血浆进行大规模脂质定性定量分析,通过Progenesis~? QI软件分析Xevo~? G2-XS QTOF质谱系统MSE采集的子离子数据,精确定量到1054个脂质特征差异,准确定性得到368个脂质分子,多变量统计分析中差异脂质组成能将AIS患者和健康志愿者区分开来,通路富集分析图显示差异脂质主要参与甘油磷脂代谢的紊乱。结论:AIS患者血浆脂质组成与健康志愿者存在显著差异,差异表达的脂质可能与AIS发生有关。这些发现有助于开发新的诊断标志物和AIS治疗靶点。     

Dissecting lipid metabolism alterations in SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the COVID-19 pandemic that has infected over a hundred million people globally. There have been more than two million deaths recorded worldwide, with no end in sight until a widespread vaccination will be achieved. Current research has centred on different aspects of the virus interaction with cell surface receptors, but more needs to be done to further understand its mechanism of action in order to develop a targeted therapy and a method to control the spread of the virus. Lipids play a crucial role throughout the viral life cycle, and viruses are known to exploit lipid signalling and synthesis to affect host cell lipidome. Emerging studies using untargeted metabolomic and lipidomic approaches are providing new insight into the host response to COVID-19 infection. Indeed, metabolomic and lipidomic approaches have identified numerous circulating lipids that directly correlate to the severity of the disease, making lipid metabolism a potential therapeutic target. Circulating lipids play a key function in the pathogenesis of the virus and exert an inflammatory response. A better knowledge of lipid metabolism in the host-pathogen interaction will provide valuable insights into viral pathogenesis and to the development of novel therapeutic targets.     

MicroRNA-425-5p modulates osteoporosis by targeting annexin A2

The disease (COVID-19) novel coronavirus pandemic has so far infected millions resulting in the death of over a million people as of Oct 2020. More than 90% of those infected with COVID-19 show mild or no symptoms but the rest of the infected cases show severe symptoms resulting in significant mortality. Age has emerged as a major factor to predict the severity of the disease and mortality rates are significantly higher in elderly patients. Besides, patients with underlying conditions like Type 2 diabetes, cardiovascular diseases, hypertension, and cancer have an increased risk of severe disease and death due to COVID-19 infection. Obesity has emerged as a novel risk factor for hospitalization and death due to COVID-19. Several independent studies have observed that people with obesity are at a greater risk of severe disease and death due to COVID-19. Here we review the published data related to obesity and overweight to assess the possible risk and outcome in Covid-19 patients based on their body weight. Besides, we explore how the obese host provides a unique microenvironment for disease pathogenesis, resulting in increased severity of the disease and poor outcome.

     

Proteomics of extracellular vesicles in plasma reveals the characteristics and residual traces of COVID-19 patients without underlying diseases after 3 months of recovery

More and more patients suffered from Coronavirus disease 2019 (COVID-19) have got recovery gradually due to suitable intervention. Increasing data mainly studies the clinical characteristics of recovered COVID-19 patients, and their molecular changes especially proteome changes also play the same important role in understanding of biological characteristics of recovered COVID-19 patients as clinical characteristics do. In our study, we reported the whole lung-ground glass-CT value-average of mild/severe recovered patients 3 months after discharge without underlying diseases was significantly lower than that of healthy subjects. Then we isolated the extracellular vesicles (EVs) of plasma from 19 healthy subjects and 67 recovered COVID-19 patients. Mass Spectrometry was used to catalogue the proteins of these EVs compared to a defined group of controls. Identified 174 proteins were differentially expressed in the EVs of COVID-19 patients compared with healthy subjects, which involved in lipid metabolic process, response to cellular, and response to stress oxygen-containing compound. Besides, we identified several protein of plasma EVs in recovered patients associated with coagulation activity, inflammatory reaction, immune response, and low organ function. In addition, proteins correlating with clinical index such as alkaline phosphatase (ALP) and alanine aminotransferase (ALT) were also detected. Moreover, we also identified many unique or characteristic associations found in the recovered COVID-19 patients, which especially involved the kidney, serum electrolyte levels, and inflammation functions. This finding suggests that monitoring the situation of recovered patients might be useful, especially the indexes of coagulation, inflammation, immunity, and organ function, which can prevent bleeding, reinfection and organ dysfunction.Subject terms: Proteomics, Proteomics     

Shorter leukocyte telomere length is associated with severity of COVID-19 infection.

The infection by COVID-19 is a serious global public health problem. An efficient way to improve this disease's clinical management would be to characterize patients at higher risk of progressing to critically severe infection using prognostic biomarkers. The telomere length could be used for this purpose. Telomeres are responsible for controlling the number of maximum cell divisions. The telomere length is a biomarker of aging and several diseases. We aimed to compare leukocyte telomere length (LTL) between patients without COVID-19 and patients with different clinical severity of the infection. Were included 53 patients who underwent SARS-CoV-2 PCR divided in four groups. The first group was composed by patients with a negative diagnosis for COVID-19 (n = 12). The other three groups consisted of patients with a confirmed diagnosis of COVID-19 divided according to the severity of the disease: mild (n = 15), moderate (n = 17) and severe (n = 9). The LTL was determined by Q-PCR. The severe group had the shortest LTL, followed by the moderate group. The negative and mild groups showed no differences. There is an increase of patients with hypertension (p = 0.0099) and diabetes (p = 0.0067) in moderate and severe groups. Severe group was composed by older patients in comparison with the other three groups (p = 0.0083). Regarding sex, there was no significant difference between groups (p = 0.6279). In an ordinal regression model, only LTL and diabetes were significantly associated with disease severity. Shorter telomere length was significantly associated with the severity of COVID-19 infection, which can be useful as a biomarker or to better understand the SARS-CoV-2 pathophysiology.     

Low serum calcium: a new,important indicator of COVID-19 patients from mild/moderate to severe/critical

Background: Coronavirus disease 2019 (COVID-19) virus is still spreading, finding out the initial hits of viral infection is important to minimize the mild/moderate population, prevent disease aggravation and organs dysfunction.Objective: We investigated COVID-19 patients with different serum calcium levels.Design: We checked the serum calcium level of the patients based on days after symptom onset as well as the severity of COVID-19. We also checked multiorgan injuries and immune cytokines level in their blood.Results: Both mild/moderate and severe critical cases we observed showed low calcium level in the early stage of viral infection, while the severe/critical cases showed significant lower calcium level than mild/moderate cases in the early stage. We also found that low calcium level related to severe/critical multiorgan injuries especially in the mild/moderate population. Proinflammatory cytokine IL-6 also correlated to calcium change in both mild/moderate and severe/critical cases.Conclusions: Our finding indicates that calcium balance is a primal hit of COVID-19 and a biomarker of clinical severity at the beginning of symptom onset. Calcium is closely associated with virus-associated multiple organ injuries and the increase in inflammatory cytokines. Our results provide a new, important indicator of COVID-19 patients from mild/moderate to severe/critical: serum calcium.     

Cytokine storm intervention in the early stages of COVID-19 pneumonia

Clinical intervention in patients with corona virus disease 2019 (COVID-19) has demonstrated a strong upregulation of cytokine production in patients who are critically ill with SARS-CoV2-induced pneumonia. In a retrospective study of 41 patients with COVID-19, most patients with SARS-CoV-2 infection developed mild symptoms, whereas some patients later developed aggravated disease symptoms, and eventually passed away because of multiple organ dysfunction syndrome (MODS), as a consequence of a severe cytokine storm. Guidelines for the diagnosis and treatment of SARS-CoV-2 infected pneumonia were first published January 30^th, 2020; these guidelines recommended for the first time that cytokine monitoring should be applied in severely ill patients to reduce pneumonia related mortality. The cytokine storm observed in COVID-19 illness is also an important component of mortality in other viral diseases, including SARS, MERS and influenza. In view of the severe morbidity and mortality of COVID-19 pneumonia, we review the current understanding of treatment of human coronavirus infections from the perspective of a dysregulated cytokine and immune response.     

Osteopontin as a biomarker for COVID-19 severity and multisystem inflammatory syndrome in children: A pilot study

This study sought to evaluate the candidacy of plasma osteopontin (OPN) as a biomarker of COVID-19 severity and multisystem inflammatory condition in children (MIS-C) in children. A retrospective analysis of 26 children (0–21 years of age) admitted to Children’s Healthcare of Atlanta with a diagnosis of COVID-19 between March 17 and May 26, 2020 was undertaken. The patients were classified into three categories based on COVID-19 severity levels: asymptomatic or minimally symptomatic (control population, admitted for other non-COVID-19 conditions), mild/moderate, and severe COVID-19. A fourth category of children met the Centers for Disease Control and Prevention''s case definition for MIS-C. Residual blood samples were analyzed for OPN, a marker of inflammation using commercial ELISA kits (R&D), and results were correlated with clinical data. This study demonstrates that OPN levels are significantly elevated in children hospitalized with moderate and severe COVID-19 and MIS-C compared to OPN levels in mild/asymptomatic children. Further, OPN differentiated among clinical levels of severity in COVID-19, while other inflammatory markers including maximum erythrocyte sedimentation rate, C-reactive protein and ferritin, minimum lymphocyte and platelet counts, soluble interleukin-2R, and interleukin-6 did not. We conclude OPN is a potential biomarker of COVID-19 severity and MIS-C in children that may have future clinical utility. The specificity and positive predictive value of this marker for COVID-19 and MIS-C are areas for future larger prospective research studies.     

Metabolomic analyses of COVID-19 patients unravel stage-dependent and prognostic biomarkers

The circulating metabolome provides a snapshot of the physiological state of the organism responding to pathogenic challenges. Here we report alterations in the plasma metabolome reflecting the clinical presentation of COVID-19 patients with mild (ambulatory) diseases, moderate disease (radiologically confirmed pneumonitis, hospitalization and oxygen therapy), and critical disease (in intensive care). This analysis revealed major disease- and stage-associated shifts in the metabolome, meaning that at least 77 metabolites including amino acids, lipids, polyamines and sugars, as well as their derivatives, were altered in critical COVID-19 patient’s plasma as compared to mild COVID-19 patients. Among a uniformly moderate cohort of patients who received tocilizumab, only 10 metabolites were different among individuals with a favorable evolution as compared to those who required transfer into the intensive care unit. The elevation of one single metabolite, anthranilic acid, had a poor prognostic value, correlating with the maintenance of high interleukin-10 and -18 levels. Given that products of the kynurenine pathway including anthranilic acid have immunosuppressive properties, we speculate on the therapeutic utility to inhibit the rate-limiting enzymes of this pathway including indoleamine 2,3-dioxygenase and tryptophan 2,3-dioxygenase.Subject terms: Metabolomics, Viral infection     

Unbiased lipidomic profiling reveals metabolomic changes during the onset and antipsychotics treatment of schizophrenia disease

Introduction

Schizophrenia (SCH) is one of the most common psychiatric disorders, which involves impairments in motivation and cognition. The pathological mechanisms underlying SCH are still unknown, and no effective therapies can prevent or treat perfectly the cognitive impairments and deficit symptoms caused by SCH.

Objectives

We aimed to find the lipid expression change in plasma that underlie SCH onset and antipsychotics treatment.

Methods

We performed a data independent acquisition-based untargeted lipidomic approach on a quadrupole-time of flight liquid chromatography coupled to mass spectrometry platform. The plasma lipidomic profiles of SCH patients (n?=?20) pre- and post-antipsychotics treatment were acquired as well as healthy controls (n?=?29). Grouped or paired t-test were used to analyze the data.

Results

Over 1000 features were detected by our lipidomic analysis, of which 445 lipids belonging to 17 lipid species were reliably identified by tandem mass spectrometry. After statistical analysis, 47 lipids belonging to 9 lipid species were found to be dysregulated between naive SCH patients and healthy controls, and 50 lipids belonging to 9 lipid species were found to be dysregulated after antipsychotics treatment. These findings include several new SCH-relevant lipid species such as sphingomyelin, acylcarnitine and ceramide. Four types of lipid expression regulative patterns can be concluded from the above mentioned findings, revealing information about mechanism, side-effect and potential target of antipsychotics.

Conclusions

The work presented here have revealed several new lipid species which are significantly dysregulated in SCH disease development or antipsychotics treatment. These lipids provide new evidence for the pathological studies of SCH and new antipsychotics development, or can be considered as potentially candidate biomarkers for further validation.

     

Prolonged humoral and cellular immunity in COVID-19-recovered patients

By the beginning of 2021, the battle against coronavirus disease 2019 (COVID-19) remains ongoing. Investigating the adaptive immune response against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes COVID-19, in patients who have recovered from this disease could contribute to our understanding of the natural host immune response. We enrolled 38 participants in this study. 7 healthy participants and 31 COVID-19 patients who had recovered from COVID-19 and categorized them into 3 groups according to their previous clinical presentations: 10 moderate, 9 mild, and 12 asymptomatic. Flow cytometry analysis of peripheral lymphocyte counts in recovered patients showed significantly increased levels of CD4⁺ T cells in patients with a history of mild and moderate COVID-19 symptoms compared with those healthy individuals (p < 0.05 and p < 0.0001 respectively). whereas no significant difference was observed in the CD8⁺ T cell percentage in COVID-19-recovered patients compared with healthy individuals. Our study demonstrated that antibodies against the SARS-CoV-2 spike protein (anti-S) IgG antibody production could be observed in all recovered COVID-19 patients, regardless of whether they were asymptomatic (p < 0.05)or presented with mild (p < 0.0001) or moderate symptoms (p < 0.01). Anti-S IgG antibodies could be detected in participants up to 90 days post-infection. In conclusion, the lymphocyte levels in recovered patients were associated with the clinical presentation of the disease, and further analysis is required to investigate relationships between different clinical presentations and lymphocyte activation and function.     

Data-driven multi-scale mathematical modeling of SARS-CoV-2 infection reveals heterogeneity among COVID-19 patients

Patients with coronavirus disease 2019 (COVID-19) often exhibit diverse disease progressions associated with various infectious ability, symptoms, and clinical treatments. To systematically and thoroughly understand the heterogeneous progression of COVID-19, we developed a multi-scale computational model to quantitatively understand the heterogeneous progression of COVID-19 patients infected with severe acute respiratory syndrome (SARS)-like coronavirus (SARS-CoV-2). The model consists of intracellular viral dynamics, multicellular infection process, and immune responses, and was formulated using a combination of differential equations and stochastic modeling. By integrating multi-source clinical data with model analysis, we quantified individual heterogeneity using two indexes, i.e., the ratio of infected cells and incubation period. Specifically, our simulations revealed that increasing the host antiviral state or virus induced type I interferon (IFN) production rate can prolong the incubation period and postpone the transition from asymptomatic to symptomatic outcomes. We further identified the threshold dynamics of T cell exhaustion in the transition between mild-moderate and severe symptoms, and that patients with severe symptoms exhibited a lack of naïve T cells at a late stage. In addition, we quantified the efficacy of treating COVID-19 patients and investigated the effects of various therapeutic strategies. Simulations results suggested that single antiviral therapy is sufficient for moderate patients, while combination therapies and prevention of T cell exhaustion are needed for severe patients. These results highlight the critical roles of IFN and T cell responses in regulating the stage transition during COVID-19 progression. Our study reveals a quantitative relationship underpinning the heterogeneity of transition stage during COVID-19 progression and can provide a potential guidance for personalized therapy in COVID-19 patients.     

新型冠状病毒肺炎患者血清SAA、ESR、CRP检测结果分析

目的:分析新型冠状病毒肺炎(COVID-19)患者血清淀粉样蛋白A(SAA)、血沉ESR(ESR)、C-反应蛋白CRP(CRP)的临床价值。方法:以我院2020年1月至2020年2月确诊的COVID-19患者51例为实验组:其中重症患者21例,轻症患者30例,选取非感染患者30例为对照组。分析新型冠状病毒肺炎(COVID-19)患者血清SAA、ESR、CRP水平以及临床价值。结果:实验组SAA、ESR、CRP水平高于对照组(P0.05);重症组SAA、ESR、CRP水平高于轻症组(P0.05),由ROC曲线得知SAA、ESR、CRP预测COVID-19的AUC小于三者联合预测的AUC。结论:COVID-19的SAA、ESR、CRP水平会升高,三者联合预测为疾病评估、预测疾病发展的提供依据,值得临床进一步推广应用。     

Plasma proteomic and metabolomic characterization of COVID-19 survivors 6 months after discharge

Coronavirus disease 2019 (COVID-19) has gained prominence as a global pandemic. Studies have suggested that systemic alterations persist in a considerable proportion of COVID-19 patients after hospital discharge. We used proteomic and metabolomic approaches to analyze plasma samples obtained from 30 healthy subjects and 54 COVID-19 survivors 6 months after discharge from the hospital, including 30 non-severe and 24 severe patients. Through this analysis, we identified 1019 proteins and 1091 metabolites. The differentially expressed proteins and metabolites were then subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Among the patients evaluated, 41% of COVID-19 survivors reported at least one clinical symptom and 26.5% showed lung imaging abnormalities at 6 months after discharge. Plasma proteomics and metabolomics analysis showed that COVID-19 survivors differed from healthy control subjects in terms of the extracellular matrix, immune response, and hemostasis pathways. COVID-19 survivors also exhibited abnormal lipid metabolism, disordered immune response, and changes in pulmonary fibrosis-related proteins. COVID-19 survivors show persistent proteomic and metabolomic abnormalities 6 months after discharge from the hospital. Hence, the recovery period for COVID-19 survivors may be longer.Subject terms: Viral infection, Predictive markers     

The influence of citrate, EDTA, and heparin anticoagulants to human plasma LC–MS lipidomic profiling

Lipid profiling of human plasma by liquid chromatography-electrospray ionization coupled to mass spectrometry (LC–ESI-MS) is being used to identify biomarkers of health, disease, and treatment efficacy. However, there is no consensus on the choice of anticoagulant to perform and compare lipidomic measurements. This study assessed the effect of the anticoagulants citrate, EDTA, and heparin, on eight synthetic and 80 plasma lipids, and compared lipidomic data among anticoagulants. Lipid extraction was affected distinctively by the anticoagulant of choice likely due to the different physico-chemical properties among anticoagulants. Peak areas of seventy endogenous lipids showed significant differences between citrate–heparin and EDTA–heparin comparisons similar to those observed for synthetic lipids. Only ten endogenous lipid species showed comparable peak areas among the three anticoagulants. Correction by a structurally related internal standard only partly eliminated differences among anticoagulants (ANOVA, P value <0.001). However, comparisons among anticoagulants were possible for most endogenous lipids after correction of peak areas by the sum of areas of its lipid class. Our observations indicate that the choice of anticoagulant distinctively impact the peak response of most lipid species by LC–ESI-MS. Lipidomic data from plasma obtained with different anticoagulants should address differences in matrix effects and extraction procedures since ion strength, plasma pH, and different physicochemical properties among anticoagulants influence lipid extraction and LC–ESI-MS analysis.     

Revealing serum lipidomic characteristics and potential lipid biomarkers in patients with POEMS syndrome

POEMS syndrome is a rare plasma cell dyscrasia with distinct lipid metabolism abnormalities at disease onset. However, the serum lipidomic characteristics in patients with POEMS syndrome were not investigated. The study performed an untargeted lipidome screening by liquid chromatography-tandem mass spectrometry (LS-MS/MS) in the pre- and post-treatment serum of 24 patients with POEMS syndrome, together with the serum of 24 paired healthy controls. Patients with POEMS syndrome had a distinct serum lipid composition compared with healthy controls, and a 3-lipid model had a predictive accuracy of 93.5% in distinguishing patients and healthy controls consisting of fatty acyl 17-oxo-20Z-hexacosenoic acid, phosphatidylcholine(16:0/18:1(9Z)) and sterol lipid 5b-pregnanediol. Four lipids including 17-oxo-20Z-hexacosenoic acid (r = 0.423, P = .040) were correlated with risk stratification, and 2 lipids including Cer(d18:0/13:0) were inversely related to serum vascular endothelial growth factor level (r=−0.465, P = .022). Eleven lipids were related to disease activity, including arachidonic acid which was inversely related and lysoPC(20:4) which was positively related. The study indicated a distinct lipid characteristic profile of patients with POEMS syndrome different from healthy controls and identified several lipids that may serve as potential diagnostic markers and monitors of therapeutic efficacy, as well as indicating potential metabolism pathways involved in the pathological process.     

Systems level analysis of lipidome

Lipids, once thought to be mainly for energy-storage and structural purpose, have now gained immense recognition as a class of critical metabolites with versatile functions. The diversity and complexity of the cellular lipids are the main challenge for the comprehensive analysis of a lipidome. Lipidomics, which aims at mapping all of the lipids in a cell, is expanded rapidly in recent years, mainly attributed to recent advances in mass spectrometry (MS). MS-based lipidomic approaches developed recently allow the quick profiling of hundreds of lipids in a crude lipid extract. With the aid of latest computational tools/software (chemometrics), aberrant lipid metabolites or important signaling lipid(s) could be easily identified using unbiased lipid profiling approaches. Further tandem MS (MS/MS)-based lipidomic approaches, known as targeted approaches and able to convey structural information, hold the promise for high-throughput lipidome analysis. In this review, I discussed the basic strategy for systems level analysis of lipidome in biomedical study.