Metabolic disturbances and inflammatory dysfunction predict severity of coronavirus disease 2019 (COVID-19): a retrospective study

Nie, Shuke; Zhao, Xueqing; Zhao, Kang; Zhang, Zhaohui; Zhang, Zhentao; Zhang, Zhan

doi:10.1101/2020.03.24.20042283

Cited by 77 publications

(111 citation statements)

References 17 publications

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“…Based on the GS study, we note that the serum levels of APOA1 are correlated with those of HDL cholesterol ( Figure S3). Although decreased APOA1 levels have been observed in systemic inflammatory response (Kumaraswamy et al, 2012;Sirniö et al, 2017) , including in COVID-19 (Nie et al, 2020) , a potential explanation of the downregulation we observe here would also be provided, if naturally lower APOA1, and hence a different metabolic condition of the individual, were associated with a higher risk of severe SARS-CoV-2 disease progression.…”

Section: Tissue Injury and Dysregulation Of Modulators Of Inflammationmentioning

confidence: 64%

Clinical classifiers of COVID-19 infection from novel ultra-high-throughput proteomics

Messner

Demichev

Wendisch

et al. 2020

Preprint

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The COVID-19 pandemic is an unprecedented global challenge. Highly variable in its presentation, spread and clinical outcome, novel point-of-care diagnostic classifiers are urgently required. Here, we describe a set of COVID-19 clinical classifiers discovered using a newly designed low-cost high-throughput mass spectrometry-based platform. Introducing a new sample preparation pipeline coupled with short-gradient high-flow liquid chromatography and mass spectrometry, our methodology facilitates clinical implementation and increases sample throughput and quantification precision. Providing a rapid assessment of serum or plasma samples at scale, we report 27 biomarkers that distinguish mild and severe forms of COVID-19, of which some may have potential as therapeutic targets. These proteins highlight the role of complement factors, the coagulation system, inflammation modulators as well as pro-inflammatory signalling upstream and downstream of Interleukin 6. Application of novel methodologies hence transforms proteomics from a research tool into a rapid-response, clinically actionable technology adaptable to infectious outbreaks. Highlights-A completely redesigned clinical proteomics platform increases throughput and precision while reducing costs.-27 biomarkers are differentially expressed between WHO severity grades for COVID-19.-The study highlights potential therapeutic targets that include complement factors, the coagulation system, inflammation modulators as well as pro-inflammatory signalling both upstream and downstream of interleukin 6.

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Section: Tissue Injury and Dysregulation Of Modulators Of Inflammationmentioning

confidence: 64%

Clinical classifiers of COVID-19 infection from novel ultra-high-throughput proteomics

Messner

Demichev

Wendisch

et al. 2020

Preprint

View full text Add to dashboard Cite

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“…Some previous studies have revealed that serum ApoA1 is associated with the outcome of patients with sepsis, acute respiratory distress syndrome induced by pneumonia, and critical ill [16][17][18][19]. A recent research observed that low level ApoA1 was associated with the severity of COVID-19, with an AUROC of 0.728 in predicting its severity [20]. Our study con rmed its role in distinguishing the severe cases, however, the predictability of ApoA1 in our study was even higher than the former, with an AUROC as high as 0.896 (95% CI:0.834-0.941), and recognized as a risk factor for the severity of COVID-19.…”

Section: Discussionmentioning

confidence: 97%

Low serum level of apolipoprotein A1 is an indicator of severity in patients with coronavirus disease 2019

Yang

Zhu

Fan

et al. 2020

Preprint

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Background: Recently, dyslipidemia was observed in the patients of coronavirus disease 2019 (COVID-19), especially in the severe cases. This study aimed to explore the predictive value of blood lipid for the severity of COVID-19.Methods: All patients with COVID-19 who admitted to HwaMei Hospital, University of Chinese Academy of Sciences from January 23 to April 20, 2020 were included in this retrospective study. General clinical characteristics and laboratory data (including blood lipid parameters) were obtained, and their predictive values for the severity were analyzed.Results: 142 consecutive patients with COVID-19 were included. There were 125 cases in the non-severe group and 17 cases in the severe group. Total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A1 (ApoA1) at baseline were significantly lower in the severe group. ApoA1 and interleukin-6 (IL-6) were recognized as independent risk factors for the severity of COVID-19. ApoA1 had the highest area under the receiver operator characteristic curve (AUROC) among all the single markers (AUROC: 0.896, 95% CI: 0.834-0.941). Moreover, the risk model established upon ApoA1 and IL-6 enhanced the predictability (AUROC: 0.977, 95% CI: 0.932-0.995). On the other hand, ApoA1 in the severe group elevated during the treatment, there was no significant difference between the severe and non-severe groups in the recovery stage of disease.Conclusion: The profile of blood lipid in the severe patients with COVID-19 is quite different from that in the non-severe cases. Serum ApoA1 could severe as a good marker to reflect the severity of COVID-19.

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“…At present, the most di culty challenge in treating patients and saving lives is the extreme shortage of medical resources, especially critical care resources. Therefore, the differentiation of patients with severe and nonsevere COVID-19 is key to providing treatment at different levels as needed [18][20] [21] . The rational allocation of medical resources is an important means of improving diagnosis and treatment e ciency and reducing patient mortality.…”

Section: Discussionmentioning

confidence: 99%

“…According to the Novel Coronavirus Pneumonia Diagnosis and Treatment Plan (Trial Version 6) issued by the National Health Commission of the People' s Republic of China and the study conducted by Li et al, the progressive declination of peripheral blood lymphocytes in adult COVID-19 patients is an early warning of progression from mild to severe disease [17] [18] . In addition, clinical studies conducted by Lippi and Zhang et al found that hemoglobin (HGB) levels declined in COVID-19 patients with progression to severe disease [19][20] [21] . However, there is insu cient evidence supporting the direct use of Lym% and HGB to guide the diagnosis and treatment of COVID-19 [18] [21] .…”

Section: Introductionmentioning

confidence: 99%

“…In addition, clinical studies conducted by Lippi and Zhang et al found that hemoglobin (HGB) levels declined in COVID-19 patients with progression to severe disease [19][20] [21] . However, there is insu cient evidence supporting the direct use of Lym% and HGB to guide the diagnosis and treatment of COVID-19 [18] [21] . We hypothesize that a joint parameter obtained through the integration of Lym% and HGB can predict severe COVID-19, potentially improving the diagnosis and treatment e ciency in patients with severe disease.…”

Section: Introductionmentioning

confidence: 99%

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A preliminary study on the joint parameter Lym% and HGB for the prediction of severe and nonsevere COVID-19

Zhang

Ye³

et al. 2020

Preprint

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Objectives The aim of this study was to identify the parameters in routine blood tests that can be used to evaluate the severity of coronavirus disease 2019 (COVID-19) and thus assist in clinically predicting the extent of progression. Methods This study retrospectively analyzed the epidemiological, clinical symptom and laboratory examination data of 159 COVID-19 patients. The percentage of lymphocytes (Lym%) and hemoglobin (HGB) were integrated into a joint parameter, Lym%&HGB, by binary logistic regression. Results Both Lym% and HGB gradually decreased with disease progression whereas the joint parameter Lym%&HGB increased gradually with disease progression. When using Lym%, HGB, and Lym%&HGB to predict COVID-19 severity, the area under the receiver operating characteristic (ROC) curve (AUC) was 0.89, 0.79, and 0.92, respectively. The dynamic change curves showed that Lym% and HGB continued to decline while Lym%&HGB continued to increase with disease progression in patients with severe COVID. The change in Lym%&HGB was more prominent than the changes in Lym% and HBG. Conclusions The joint parameter Lym%&HGB can serve as a good tool to differentiate severe and nonsevere COVID-19, and it has a higher sensitivity and specificity than either Lym% or HGB alone.

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Metabolic disturbances and inflammatory dysfunction predict severity of coronavirus disease 2019 (COVID-19): a retrospective study

Cited by 77 publications

References 17 publications

Clinical classifiers of COVID-19 infection from novel ultra-high-throughput proteomics

Clinical classifiers of COVID-19 infection from novel ultra-high-throughput proteomics

Low serum level of apolipoprotein A1 is an indicator of severity in patients with coronavirus disease 2019

A preliminary study on the joint parameter Lym% and HGB for the prediction of severe and nonsevere COVID-19

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