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Article ; Online: Biomarkers of biological age as predictors of COVID-19 disease severity.

Lauc, Gordan / Sinclair, David

Aging

2020 Volume 12, Issue 8, Page(s) 6490–6491

MeSH term(s)	Age Factors ; Aging ; Betacoronavirus ; Biomarkers ; COVID-19 ; COVID-19 Testing ; Clinical Laboratory Techniques ; Coronavirus Infections/diagnosis ; Coronavirus Infections/physiopathology ; Disease Progression ; Humans ; Pandemics ; Pneumonia, Viral/diagnosis ; Pneumonia, Viral/physiopathology ; SARS-CoV-2
Chemical Substances	Biomarkers
Keywords	covid19
Language	English
Publishing date	2020-04-08
Publishing country	United States
Document type	Journal Article
ISSN	1945-4589
ISSN (online)	1945-4589
DOI	10.18632/aging.103052
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Biomarkers of biological age as predictors of COVID-19 disease severity

Lauc, Gordan / Sinclair, David

Aging (Albany NY)

Keywords	covid19
Publisher	WHO
Document type	Article
Note	WHO #Covidence: #46959
Database	COVID19

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Article: Biomarkers Predicting Poor Prognosis in Covid-19 Patients: A Survival Analysis.

Idrissi, Amjad / Lekfif, Asmae / Amrani, Abdessamad / Yacoubi, Abdelkader / Yahyaoui, Abir / Belmahi, Sabrina / Nassiri, Oumaima / Elmezgueldi, Imane / Sebbar, El-Houcine / Choukri, Mohammed

Cureus

2023 Volume 15, Issue 1, Page(s) e33921

Abstract: ... Knowledge and monitoring of predictive biomarkers of poor prognosis in patients with Covid-19 could be ... in several countries, the importance of identifying predictors of severity is of paramount importance. The objective ... concerned the biological parameters carried out on the admission of the patients, in addition to age and sex ...

Abstract	Introduction With the spread of the Covid-19 pandemic and its overwhelming impact on health systems in several countries, the importance of identifying predictors of severity is of paramount importance. The objective of this study is to determine the relationship between death and the biological parameters of patients with Covid-19. Materials and methods This is an analytical retrospective cohort study conducted on 326 patients admitted to the Mohammed VI University Hospital in Oujda, Morocco. The statistical analysis concerned the biological parameters carried out on the admission of the patients, in addition to age and sex. The comparison between the two surviving and non-surviving groups was made by a simple analysis than a multivariate analysis by logistic regression. Next, a survival analysis was performed by the Kaplan-Meier method and then by Cox regression. Results A total of 326 patients were included in the study, including 108 fatal cases. The mean age was 64.66 ± 15.51 and the sex ratio was 1.08:1 (M:F). Age, procalcitonin, liver enzymes, and coagulation factors were significantly higher in patients who died of Covid-19 and are therefore considered to be the main prognostic factors identified in this study. Conclusion Knowledge and monitoring of predictive biomarkers of poor prognosis in patients with Covid-19 could be of great help in the identification of patients at risk and in the implementation of an effective diagnostic and therapeutic strategy to predict severe disease forms.
Language	English
Publishing date	2023-01-18
Publishing country	United States
Document type	Journal Article
ZDB-ID	2747273-5
ISSN	2168-8184
ISSN	2168-8184
DOI	10.7759/cureus.33921
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: The adverse inflammatory response of tobacco smoking in COVID-19 patients: biomarkers from proteomics and metabolomics.

Cui, Tenglong / Miao, Gan / Jin, Xiaoting / Yu, Haiyi / Zhang, Ze / Xu, Liting / Wu, Yili / Qu, Guangbo / Liu, Guoliang / Zheng, Yuxin / Jiang, Guibin

Journal of breath research

2022 Volume 16, Issue 4

Abstract: ... pathways, which can be biomarkers to reflect and predict adverse outcomes in smoking COVID-19 patients ... patients. Our study provides novel evidence and corresponding biomarkers as potential predictors of severe ... disease progression in smoking COVID-19 patients, which is of great significance for preventing further deterioration ...

Abstract	Whether tobacco smoking affects the occurrence and development of coronavirus disease 2019 (COVID-19) is still a controversial issue, and potential biomarkers to predict the adverse outcomes of smoking in the progression of COVID-19 patients have not yet been elucidated. To further uncover their linkage and explore the effective biomarkers, three proteomics and metabolomics databases (i.e. smoking status, COVID-19 status, and basic information of population) from human serum proteomic and metabolomic levels were established by literature search. Bioinformatics analysis was then performed to analyze the interactions of proteins or metabolites among the above three databases and their biological effects. Potential confounding factors (age, body mass index (BMI), and gender) were controlled to improve the reliability. The obtained data indicated that smoking may increase the relative risk of conversion from non-severe to severe COVID-19 patients by inducing the dysfunctional immune response. Seven interacting proteins (C8A, LBP, FCN2, CRP, SAA1, SAA2, and VTN) were found to promote the deterioration of COVID-19 by stimulating the complement pathway and macrophage phagocytosis as well as inhibiting the associated negative regulatory pathways, which can be biomarkers to reflect and predict adverse outcomes in smoking COVID-19 patients. Three crucial pathways related to immunity and inflammation, including tryptophan, arginine, and glycerophospholipid metabolism, were considered to affect the effect of smoking on the adverse outcomes of COVID-19 patients. Our study provides novel evidence and corresponding biomarkers as potential predictors of severe disease progression in smoking COVID-19 patients, which is of great significance for preventing further deterioration in these patients.
MeSH term(s)	Biomarkers/metabolism ; Breath Tests ; COVID-19 ; Humans ; Metabolomics ; Proteomics ; Reproducibility of Results ; Smoking/adverse effects ; Tobacco Smoking
Chemical Substances	Biomarkers
Language	English
Publishing date	2022-07-11
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2381007-5
ISSN	1752-7163 ; 1752-7155
ISSN (online)	1752-7163
ISSN	1752-7155
DOI	10.1088/1752-7163/ac7d6b
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Characterization by Quantitative Serum Proteomics of Immune-Related Prognostic Biomarkers for COVID-19 Symptomatology.

Villar, Margarita / Urra, José Miguel / Rodríguez-Del-Río, Francisco J / Artigas-Jerónimo, Sara / Jiménez-Collados, Natalia / Ferreras-Colino, Elisa / Contreras, Marinela / de Mera, Isabel G Fernández / Estrada-Peña, Agustín / Gortázar, Christian / de la Fuente, José

Frontiers in immunology

2021 Volume 12, Page(s) 730710

Abstract: ... with COVID-19 disease symptomatology from asymptomatic to severe cases. The analysis was then focused ... disease progression and severity. The identification of prognostic biomarkers and physiological processes associated ... to translational medicine, results corroborated the predictive value of selected immune-related biomarkers for disease ...

Abstract	The COVID-19 pandemic caused by SARS-CoV-2 challenges the understanding of factors affecting disease progression and severity. The identification of prognostic biomarkers and physiological processes associated with disease symptoms is relevant for the development of new diagnostic and therapeutic interventions to contribute to the control of this pandemic. To address this challenge, in this study, we used a quantitative proteomics together with multiple data analysis algorithms to characterize serum protein profiles in five cohorts from healthy to SARS-CoV-2-infected recovered (hospital discharge), nonsevere (hospitalized), and severe [at the intensive care unit (ICU)] cases with increasing systemic inflammation in comparison with healthy individuals sampled prior to the COVID-19 pandemic. The results showed significantly dysregulated proteins and associated biological processes and disorders associated to COVID-19. These results corroborated previous findings in COVID-19 studies and highlighted how the representation of dysregulated serum proteins and associated BPs increases with COVID-19 disease symptomatology from asymptomatic to severe cases. The analysis was then focused on novel disease processes and biomarkers that were correlated with disease symptomatology. To contribute to translational medicine, results corroborated the predictive value of selected immune-related biomarkers for disease recovery [Selenoprotein P (SELENOP) and Serum paraoxonase/arylesterase 1 (PON1)], severity [Carboxypeptidase B2 (CBP2)], and symptomatology [Pregnancy zone protein (PZP)] using protein-specific ELISA tests. Our results contributed to the characterization of SARS-CoV-2-host molecular interactions with potential contributions to the monitoring and control of this pandemic by using immune-related biomarkers associated with disease symptomatology.
MeSH term(s)	Adult ; Aged ; Aged, 80 and over ; Aryldialkylphosphatase/blood ; Biomarkers/blood ; COVID-19/blood ; COVID-19/immunology ; Carboxypeptidase B2/blood ; Female ; Humans ; Interleukin-1/blood ; Interleukin-4/blood ; Male ; Middle Aged ; Pregnancy Proteins/blood ; Prognosis ; Proteome/analysis ; Proteomics ; Retrospective Studies ; SARS-CoV-2 ; Selenoprotein P/blood
Chemical Substances	Biomarkers ; IL4 protein, human ; Interleukin-1 ; PZP protein, human ; Pregnancy Proteins ; Proteome ; SELENOP protein, human ; Selenoprotein P ; Interleukin-4 (207137-56-2) ; Aryldialkylphosphatase (EC 3.1.8.1) ; PON1 protein, human (EC 3.1.8.1) ; Carboxypeptidase B2 (EC 3.4.17.20)
Language	English
Publishing date	2021-09-08
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2606827-8
ISSN	1664-3224 ; 1664-3224
ISSN (online)	1664-3224
ISSN	1664-3224
DOI	10.3389/fimmu.2021.730710
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Novel biomarkers for the prediction of COVID-19 progression a retrospective, multi-center cohort study

Yalan Yu (8879618) / Tao Liu (10785) / Liang Shao (427875) / Xinyi Li (1778476) / Colin K. He (9626779) / Muhammad Jamal (275930) / Yi Luo (143206) / Yingying Wang (124944) / Yanan Liu (114059) / Yufeng Shang (9626782) / Yunbao Pan (286272) / Xinghuan Wang (533787) / Fuling Zhou (286273)

2020

Abstract: ... for disease progression were determined by MedCalc Version 19.2.0. Age (95%CI, 1.017 to 1.048; P < 0.001), serum ... novel promising ones for predicting disease progression in COVID-19. ... A pandemic designated as Coronavirus Disease 2019 (COVID-19), caused ...

Abstract	A pandemic designated as Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading worldwide. Up to date, there is no efficient biomarker for the timely prediction of the disease progression in patients. To analyze the inflammatory profiles of COVID-19 patients and demonstrate their implications for the illness progression of COVID-19. Retrospective analysis of 3,265 confirmed COVID-19 cases hospitalized between 10 January 2020, and 26 March 2020 in three medical centers in Wuhan, China. Patients were diagnosed as COVID-19 and hospitalized in Leishenshan Hospital, Zhongnan Hospital of Wuhan University and The Seventh Hospital of Wuhan, China. Univariable and multivariable logistic regression models were used to determine the possible risk factors for disease progression. Moreover, cutoff values, the sensitivity and specificity of inflammatory parameters for disease progression were determined by MedCalc Version 19.2.0. Age (95%CI, 1.017 to 1.048; P < 0.001), serum amyloid A protein (SAA) (95%CI, 1.216 to 1.396; P < 0.001) and erythrocyte sedimentation rate (ESR) (95%CI, 1.006 to 1.045; P < 0.001) were likely the risk factors for the disease progression. The Area under the curve (AUC) of SAA for the progression of COVID-19 was 0.923, with the best predictive cutoff value of SAA of 12.4 mg/L, with a sensitivity of 83.9% and a specificity of 97.67%. SAA-containing parameters are novel promising ones for predicting disease progression in COVID-19.
Keywords	Medicine ; Microbiology ; Cancer ; Virology ; Biological Sciences not elsewhere classified ; Mathematical Sciences not elsewhere classified ; Chemical Sciences not elsewhere classified ; COVID-19 ; serum amyloid A protein ; disease progression ; risk factor ; predictor ; biomarker ; covid19
Publishing date	2020-11-11T08:50:03Z
Publishing country	us
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Serum Cystatin C and Coronavirus Disease 2019: A Potential Inflammatory Biomarker in Predicting Critical Illness and Mortality for Adult Patients.

Chen, Dan / Sun, Wenwu / Li, Jia / Wei, Bohua / Liu, Wei / Wang, Xiaopin / Song, Fan / Chen, Liangkai / Yang, Junhui / Yu, Li

Mediators of inflammation

2020 Volume 2020, Page(s) 3764515

Abstract: ... disease 2019 (COVID-19) and investigating the potential prognostic value of serum cystatin C in adult ... patients with COVID-19. 481 patients with COVID-19 were consecutively included in this study from January 2 ... 2020, and followed up to April 15, 2020. All clinical and laboratory data of COVID-19 patients ...

Abstract	This study aimed at determining the relationship between baseline cystatin C levels and coronavirus disease 2019 (COVID-19) and investigating the potential prognostic value of serum cystatin C in adult patients with COVID-19. 481 patients with COVID-19 were consecutively included in this study from January 2, 2020, and followed up to April 15, 2020. All clinical and laboratory data of COVID-19 patients with definite outcomes were reviewed. For every measure, COVID-19 patients were grouped into quartiles according to the baseline levels of serum cystatin C. The highest cystatin C level was significantly related to more severe inflammatory conditions, worse organ dysfunction, and worse outcomes among patients with COVID-19 (
MeSH term(s)	Adult ; Aged ; Betacoronavirus ; Biomarkers/blood ; COVID-19 ; China/epidemiology ; Cohort Studies ; Comorbidity ; Coronavirus Infections/blood ; Coronavirus Infections/epidemiology ; Coronavirus Infections/mortality ; Critical Illness ; Cystatin C/blood ; Female ; Humans ; Inflammation Mediators/blood ; Kaplan-Meier Estimate ; Logistic Models ; Male ; Middle Aged ; Models, Biological ; Nonlinear Dynamics ; Pandemics ; Pneumonia, Viral/blood ; Pneumonia, Viral/epidemiology ; Pneumonia, Viral/mortality ; Prognosis ; Retrospective Studies ; Risk Factors ; SARS-CoV-2
Chemical Substances	Biomarkers ; CST3 protein, human ; Cystatin C ; Inflammation Mediators
Keywords	covid19
Language	English
Publishing date	2020-10-08
Publishing country	United States
Document type	Journal Article
ZDB-ID	1137605-3
ISSN	1466-1861 ; 0962-9351
ISSN (online)	1466-1861
ISSN	0962-9351
DOI	10.1155/2020/3764515
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Article ; Online: Cognitive impairment in long-COVID and its association with persistent dysregulation in inflammatory markers.

Damiano, Rodolfo Furlan / Rocca, Cristiana Castanho de Almeida / Serafim, Antonio de Pádua / Loftis, Jennifer M / Talib, Leda Leme / Pan, Pedro Mário / Cunha-Neto, Edecio / Kalil, Jorge / de Castro, Gabriela Salim / Seelaender, Marilia / Guedes, Bruno F / Nagahashi Marie, Suely K / de Souza, Heraldo Possolo / Nitrini, Ricardo / Miguel, Euripedes Constantino / Busatto, Geraldo / Forlenza, Orestes V

Frontiers in immunology

2023 Volume 14, Page(s) 1174020

Abstract: ... impacted, compared to their pre-COVID-19 status. Multivariate analysis found sex, age, ethnicity, education ... factors on the long-term cognitive outcome of patients who survived moderate and severe forms of COVID-19.: Methods ... and disease severity markers.: Results: Concerning the subjective assessment of cognitive ...

Abstract	Objective: To analyze the potential impact of sociodemographic, clinical and biological factors on the long-term cognitive outcome of patients who survived moderate and severe forms of COVID-19. Methods: We assessed 710 adult participants (Mean age = 55 ± 14; 48.3% were female) 6 to 11 months after hospital discharge with a complete cognitive battery, as well as a psychiatric, clinical and laboratory evaluation. A large set of inferential statistical methods was used to predict potential variables associated with any long-term cognitive impairment, with a focus on a panel of 28 cytokines and other blood inflammatory and disease severity markers. Results: Concerning the subjective assessment of cognitive performance, 36.1% reported a slightly poorer overall cognitive performance, and 14.6% reported being severely impacted, compared to their pre-COVID-19 status. Multivariate analysis found sex, age, ethnicity, education, comorbidity, frailty and physical activity associated with general cognition. A bivariate analysis found that G-CSF, IFN-alfa2, IL13, IL15, IL1.RA, EL1.alfa, IL45, IL5, IL6, IL7, TNF-Beta, VEGF, Follow-up C-Reactive Protein, and Follow-up D-Dimer were significantly (p<.05) associated with general cognition. However, a LASSO regression that included all follow-up variables, inflammatory markers and cytokines did not support these findings. Conclusion: Though we identified several sociodemographic characteristics that might protect against cognitive impairment following SARS-CoV-2 infection, our data do not support a prominent role for clinical status (both during acute and long-stage of COVID-19) or inflammatory background (also during acute and long-stage of COVID-19) to explain the cognitive deficits that can follow COVID-19 infection.
MeSH term(s)	Adult ; Humans ; Female ; Middle Aged ; Aged ; Male ; COVID-19 ; SARS-CoV-2 ; Post-Acute COVID-19 Syndrome ; Cognitive Dysfunction/epidemiology ; Cytokines
Chemical Substances	Cytokines
Language	English
Publishing date	2023-05-23
Publishing country	Switzerland
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S. ; Research Support, Non-U.S. Gov't
ZDB-ID	2606827-8
ISSN	1664-3224 ; 1664-3224
ISSN (online)	1664-3224
ISSN	1664-3224
DOI	10.3389/fimmu.2023.1174020
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Flower lose, a cell fitness marker, predicts COVID-19 prognosis.

Yekelchyk, Michail / Madan, Esha / Wilhelm, Jochen / Short, Kirsty R / Palma, António M / Liao, Linbu / Camacho, Denise / Nkadori, Everlyne / Winters, Michael T / Rice, Emily S / Rolim, Inês / Cruz-Duarte, Raquel / Pelham, Christopher J / Nagane, Masaki / Gupta, Kartik / Chaudhary, Sahil / Braun, Thomas / Pillappa, Raghavendra / Parker, Mark S /

Menter, Thomas / Matter, Matthias / Haslbauer, Jasmin Dionne / Tolnay, Markus / Galior, Kornelia D / Matkwoskyj, Kristina A / McGregor, Stephanie M / Muller, Laura K / Rakha, Emad A / Lopez-Beltran, Antonio / Drapkin, Ronny / Ackermann, Maximilian / Fisher, Paul B / Grossman, Steven R / Godwin, Andrew K / Kulasinghe, Arutha / Martinez, Ivan / Marsh, Clay B / Tang, Benjamin / Wicha, Max S / Won, Kyoung Jae / Tzankov, Alexandar / Moreno, Eduardo / Gogna, Rajan

EMBO molecular medicine

2021 Volume 13, Issue 11, Page(s) e13714

Abstract: ... 67-0.92). The cell fitness marker, hFwe-Lose, accurately predicts outcomes in COVID-19 patients ... conventional methods in predicting outcomes (e.g., death and hospitalization) in COVID-19 patients ... in the early phase of COVID-19 illness, hFwe-Lose expression accurately predicts subsequent hospitalization or ...

Abstract	Risk stratification of COVID-19 patients is essential for pandemic management. Changes in the cell fitness marker, hFwe-Lose, can precede the host immune response to infection, potentially making such a biomarker an earlier triage tool. Here, we evaluate whether hFwe-Lose gene expression can outperform conventional methods in predicting outcomes (e.g., death and hospitalization) in COVID-19 patients. We performed a post-mortem examination of infected lung tissue in deceased COVID-19 patients to determine hFwe-Lose's biological role in acute lung injury. We then performed an observational study (n = 283) to evaluate whether hFwe-Lose expression (in nasopharyngeal samples) could accurately predict hospitalization or death in COVID-19 patients. In COVID-19 patients with acute lung injury, hFwe-Lose is highly expressed in the lower respiratory tract and is co-localized to areas of cell death. In patients presenting in the early phase of COVID-19 illness, hFwe-Lose expression accurately predicts subsequent hospitalization or death with positive predictive values of 87.8-100% and a negative predictive value of 64.1-93.2%. hFwe-Lose outperforms conventional inflammatory biomarkers and patient age and comorbidities, with an area under the receiver operating characteristic curve (AUROC) 0.93-0.97 in predicting hospitalization/death. Specifically, this is significantly higher than the prognostic value of combining biomarkers (serum ferritin, D-dimer, C-reactive protein, and neutrophil-lymphocyte ratio), patient age and comorbidities (AUROC of 0.67-0.92). The cell fitness marker, hFwe-Lose, accurately predicts outcomes in COVID-19 patients. This finding demonstrates how tissue fitness pathways dictate the response to infection and disease and their utility in managing the current COVID-19 pandemic.
MeSH term(s)	Biomarkers ; COVID-19 ; Flowers ; Humans ; Pandemics ; ROC Curve ; Retrospective Studies ; SARS-CoV-2 ; Severity of Illness Index
Chemical Substances	Biomarkers
Language	English
Publishing date	2021-10-18
Publishing country	England
Document type	Journal Article ; Observational Study ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2467145-9
ISSN	1757-4684 ; 1757-4676
ISSN (online)	1757-4684
ISSN	1757-4676
DOI	10.15252/emmm.202013714
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