The Future of Biomarkers

Vincent, Jean‐Louis; Bogossian, Elisa Gouvêa; Menozzi, Marco

doi:10.1016/j.ccc.2019.08.014

Cited by 25 publications

(15 citation statements)

References 46 publications

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“…Biomarker dosage can be useful as an indicator of biological processes, whether natural, pathological, or in response to a therapeutic intervention [2]. One of the main advantages is that they can be readily detected with potentially high sensitivity and specificity [3]. Understanding the dynamics of biomarkers promises to aid in the diagnosis, management, and prognosis of brain injuries.…”

Section: Introductionmentioning

confidence: 99%

Inflammatory markers assessment in an animal model of intracranial hypertension: a randomized trial

Santo

Faria

Solla

et al. 2021

ICMx

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Background Intracranial hypertension (ICH) is a common final pathway of most neurosurgical pathologies and leads to poor prognosis if not detected and treated properly. Inflammatory markers have been assessed in clinical scenarios of neurological injuries, in which systemic and brain tissue aggressions may introduce bias. There is a lack of studies under controlled settings to isolate the ICH effect on inflammation. This study aims to evaluate the effects of ICH on the serum concentration of cytokines as biomarkers of neuroinflammation in an experimental model which isolates ICH from potential confounding variables. Methods An established model of ICH using an intracerebral pediatric bladder catheter and a multisensor intraparenchymal catheter was used in adult pigs (Sus domesticus). The animals were randomly allocated to 2 groups based on the catheter balloon volume used to simulate the ICP increase (4 ml or 7 ml). Cytokines were measured in 4 timepoints during the experiment: (1) 15 min before balloon insufflation; (2) 5 min after insufflation; (3) 125 min after insufflation; (4) 60 min after deflation. The following cytokines were measured IL-1α; IL-1β; IL–1ra; IL-2; IL-4; IL-6; IL-8; IL-10; IL-12; IL-18; TNFα. Generalized estimating equations were modeled to compare the ICP and cytokines values between the groups along the experiment. The study sample size was powered to detect interactions between the groups and the study moments with an effect size (f) of at least 0.3. The ARRIVE checklist was followed. Results A total of 20 animals were studied (10 in each group, 4 ml or 7 ml balloon volume insufflation). The animal model was successful in increasing the ICP along the moments of the experiment (p < 0,001) and in creating an ICP gradient between the groups (p = 0,004). The interaction term (moment × group) was also significant (p < 0,001). There was a significant association between ICP elevation and most cytokines variation. The cytokines IL-1α, IL-1β, IL1-ra, IL-6, IL-12, and IL-18 increased, whereas IL-2, IL-4, and TNF-α decreased. IL-10 did not vary significantly in response to the ICP elevation. Conclusion The serum concentration of cytokines varied in response to intracranial hypertension. The study demonstrated the specific changes in each cytokine after intracranial hypertension and provides key information to guide neuroinflammation clinical research. The proposed experiment was successful as an animal model to the study of neuroinflammation biomarkers

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Section: Introductionmentioning

confidence: 99%

Inflammatory markers assessment in an animal model of intracranial hypertension: a randomized trial

Santo

Faria

Solla

et al. 2021

ICMx

View full text Add to dashboard Cite

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“…Biomarkers commonly used as part of routine clinical practice can complement clinical examination and contribute to the management of various diseases. The advance of the new sequencing approach and access to some huge genetic and epigenetic databases including TCGA and GEO, are providing potential biomarkers options and the focus is shifting to a combination of several or more biomarkers, rather than a single marker that researchers have concentrated on in the past ( Conway and Wong, 2020 ; Vincent et al, 2020 ; Bian et al, 2022 ). In this study, we conducted an integrative analysis of gene expression and DNA methylation data, and identified the DMGs and DEGs between PD patients and healthy controls.…”

Section: Discussionmentioning

confidence: 99%

Integrative analysis of DNA methylation and gene expression data for the diagnosis and underlying mechanism of Parkinson’s disease

Ding

Liang²,

Guo³

et al. 2022

Front. Aging Neurosci.

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BackgroundParkinson’s disease (PD) is the second most common progressive neurodegenerative disorder and the leading cause of disability in the daily activities. In the management of PD, accurate and specific biomarkers in blood for the early diagnosis of PD are urgently needed. DNA methylation is one of the main epigenetic mechanisms and associated with the gene expression and disease initiation of PD. We aimed to construct a methylation signature for the diagnosis of PD patients, and explore the potential value of DNA methylation in therapeutic options.Materials and methodsWhole blood DNA methylation and gene expression data of PD patients as well as healthy controls were extracted from Gene Expression Omnibus database. Next, differentially expressed genes (DEGs) and differentially methylated genes (DMGs) between PD patients and healthy controls were identified. Least absolute shrinkage and selection operator cox regression analysis was carried out to construct a diagnostic signature based on the overlapped genes. And, the receiver operating characteristic (ROC) curves were drawn and the area under the curve (AUC) was used to assess the diagnostic performance of the signature in both the training and testing datasets. Finally, gene ontology and gene set enrichment analysis were subsequently carried out to explore the underlying mechanisms.ResultsWe obtained a total of 9,596 DMGs, 1,058 DEGs, and 237 overlapped genes in the whole blood between PD patients and healthy controls. Eight methylation-driven genes (HIST1H4L, CDC42EP3, KIT, GNLY, SLC22A1, GCM1, INO80B, and ARHGAP26) were identified to construct the gene expression signature. The AUCs in predicting PD patients were 0.84 and 0.76 in training dataset and testing dataset, respectively. Additionally, eight methylation-altered CpGs were also identified to construct the CpGs signature which showed a similarly robust diagnostic capability, with AUCs of 0.8 and 0.73 in training dataset and testing dataset, respectively.ConclusionWe conducted an integrated analysis of the gene expression and DNA methylation data, and constructed a methylation-driven genes signature and a methylation-altered CpGs signature to distinguish the patients with PD from healthy controls. Both of them had a robust prediction power and provide a new insight into personalized diagnostic and therapeutic strategies for PD.

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“…Aunque han sido múltiples los BM estudiados en los SUH y su utilidad de forma individual o combinada entre ellos o con otras variables (lo que se conoce como la sinergia de los BM), hoy en día se recomienda la utilización conjunta de los conocidos como BM de diagnóstico de infección bacteriana, bacteriemia y sepsis (a la cabeza la procalcitonina) y aquellos que consiguen el mejor rendimiento pronóstico (entre otros lactato y suPAR) [ 11 , 12 ].…”

Section: Introductionunclassified

Prognostic power of soluble urokinase plasminogen activator receptor (suPAR) for short-term mortality in patients seen in Emergency Departments due to infections

Díaz¹,

González²,

Torres³

et al. 2021

Rev Esp Quimioter

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Objectives. To analyse and compare 30-day mortality prognostic power of several biomarkers (C-reactive protein, procalcitonin, lactate and suPAR) in patients seen in emergency departments (ED) due to infections. Secondly, if these could improve the accuracy of systemic inflammatory response syndrome (SIRS) and quick Sepsis-related Organ Failure Assessment (qSOFA). Methods. A prospective, observational and analytical study was carried out on patients who were treated in an ED of one of the eight participating hospitals. An assessment was made of 32 independent variables that could influence mortality at 30 days. They covered epidemiological, comorbidity, functional, clinical and analytical factors. Results. The study included 347 consecutive patients, 54 (15.6%) of whom died within 30 days of visiting the ED. SUPAR has got the best biomarker area under the curve (AUC)-ROC to predict mortality at 30 days of 0.836 (95% CI: 0.765-0.907; P <.001) with a cut-off > 10 ng/mL who had a sensitivity of 70% and a specificity of 86%. The score qSOFA ≥ 2 had AUC-ROC of 0.707 (95% CI: 0.621-0.793; P < .001) with sensitivity of 53% and a specificity of 89%. The mixed model (suPAR > 10 ng/mL plus qSOFA ≥ 2) has improved the AUC-ROC to 0.853 [95% CI: 0.790-0.916; P < .001] with the best prognostic performance: sensitivity of 39% and a specificity of 97% with a negative predictive value of 90%. Conclusions. suPAR showed better performance for 30-day mortality prognostic power from several biomarkers in the patients seen in ED due to infections. Score qSOFA has better performance that SRIS and the mixed model (qSOFA ≥ 2 plus suPAR > 10 ng/mL) increased the ability of qSOFA.

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The Future of Biomarkers

Cited by 25 publications

References 46 publications

Inflammatory markers assessment in an animal model of intracranial hypertension: a randomized trial

Inflammatory markers assessment in an animal model of intracranial hypertension: a randomized trial

Integrative analysis of DNA methylation and gene expression data for the diagnosis and underlying mechanism of Parkinson’s disease

Prognostic power of soluble urokinase plasminogen activator receptor (suPAR) for short-term mortality in patients seen in Emergency Departments due to infections

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