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Handbook of Experimental Pharmacology 2022Lipids are natural substances found in all living organisms and involved in many biological functions. Imbalances in the lipid metabolism are linked to various diseases... (Review)
Review
Lipids are natural substances found in all living organisms and involved in many biological functions. Imbalances in the lipid metabolism are linked to various diseases such as obesity, diabetes, or cardiovascular disease. Lipids comprise thousands of chemically distinct species making them a challenge to analyze because of their great structural diversity.Thanks to the technological improvements in the fields of chromatography, high-resolution mass spectrometry, and bioinformatics over the last years, it is now possible to perform global lipidomics analyses, allowing the concomitant detection, identification, and relative quantification of hundreds of lipid species. This review shall provide an insight into a general lipidomics workflow and its application in metabolic biomarker research.
Topics: Biomarkers; Humans; Lipid Metabolism; Lipidomics; Lipids; Mass Spectrometry
PubMed: 34409495
DOI: 10.1007/164_2021_517 -
Journal of Hepatology Apr 2023Biomarkers have the potential to accelerate drug development, as early indicators of improved clinical response, to improve patient safety, and for personalised... (Review)
Review
Biomarkers have the potential to accelerate drug development, as early indicators of improved clinical response, to improve patient safety, and for personalised medicine. However, few have been approved through the biomarker qualification pathways of the regulatory agencies. This paper outlines how biomarkers can accelerate drug development, and reviews the lessons learned by the EU IMI2-funded LITMUS consortium, which has had several interactions with regulatory agencies in both the US and EU regarding biomarker qualification in patients with non-alcoholic fatty liver disease and non-alcoholic steatohepatitis. Sharing knowledge of such interactions with the scientific community is of paramount importance to increase the chances of qualification of relevant biomarkers that may accelerate drug development, and thereby help patients, across disease indications. A qualified biomarker enables a decision to be made that all understand and support in a common framework.
Topics: Humans; Non-alcoholic Fatty Liver Disease; Biomarkers; Drug Development
PubMed: 36526000
DOI: 10.1016/j.jhep.2022.11.028 -
Osteoarthritis and Cartilage Mar 2018To summarise important findings from biomarker studies relevant to osteoarthritis (OA), published between April 2016 and March 2017; to consider these findings in the... (Review)
Review
OBJECTIVE
To summarise important findings from biomarker studies relevant to osteoarthritis (OA), published between April 2016 and March 2017; to consider these findings in the context of new discoveries and technologies, and clinical and scientific need in OA.
DESIGN
Studies were selected by PubMed search, conducted between 01/04/2016 and 01/03/2017. MeSH terms [biomarker] AND [OA] were used; the search was restricted to Human, English language and Full Text Available publications, which yielded 50 eligible publications. Any biomarker was considered, including non-proteins and other clinical measurements.
RESULTS
Three main areas are overviewed: 1) Studies examining highly validated biomarkers, in the FNIH OA Biomarkers Consortium and elsewhere, particularly their ongoing application and validation. Control reference intervals, work on predictive validity and other longitudinal studies examining prognostic value of biomarkers in large cohorts are reviewed. 2) Novel studies relating to biomarkers of inflammation are discussed, including complement, the performance of markers of so-called 'cold inflammation' and results from clinical trials including biomarkers. 3) Discovery studies, including whole blood RNA, proteomics and metabolomics are reviewed, with an emphasis on new technologies.
CONCLUSIONS
Discovery, characterisation and qualification of various biomarkers is ongoing; several novel protein and non-protein candidate biomarkers have been reported this year. Biomarkers provide us with an opportunity to better diagnose and stratify the disease, via established panels or new discovery approaches. Improving quality of sampling and testing, and measuring large numbers of markers simultaneously in large cohorts would seem likely to identify new clinically applicable biomarkers, which are still much needed in this disease.
Topics: Biomarkers; Humans; Osteoarthritis; Prognosis; Treatment Outcome
PubMed: 29107060
DOI: 10.1016/j.joca.2017.10.016 -
Circulating miR-150 and miR-342 in plasma are novel potential biomarkers for acute myeloid leukemia.Journal of Translational Medicine Feb 2013MicroRNAs (miRNAs) are small (19-22-nt) single-stranded noncoding RNA molecules whose deregulation of expression can contribute to human disease including the multistep...
BACKGROUND
MicroRNAs (miRNAs) are small (19-22-nt) single-stranded noncoding RNA molecules whose deregulation of expression can contribute to human disease including the multistep processes of carcinogenesis in human. Circulating miRNAs are emerging biomarkers in many diseases and cancers such as type 2 diabetes, pulmonary disease, colorectal cancer, and gastric cancer among others; however, defining a plasma miRNA signature in acute myeloblastic leukemia (AML) that could serve as a biomarker for diagnosis or in the follow-up has not been done yet.
METHODS
TaqMan miRNA microarray was performed to identify deregulated miRNAs in the plasma of AML patients. Quantitative real-time RT-PCR was used to validate the results. Receiver-operator characteristic (ROC) curve analysis was conducted to evaluate the diagnostic accuracy of the highly and significantly identified deregulated miRNA(s) as potential candidate biomarker(s).
RESULTS
The plasma expression level of let-7d, miR-150, miR-339, and miR-342 was down-regulated whilst that of let-7b, and miR-523 was up-regulated in the AML group at diagnosis compared to healthy controls. ROC curve analyses revealed an AUC (the areas under the ROC curve) of 0.835 (95% CI: 0.7119- 0.9581; P<0.0001) and 0.8125 (95% CI: 0.6796-0.9454; P=0.0005) for miR-150, and miR-342 respectively. Combined ROC analyses using these 2 miRNAs revealed an elevated AUC of 0.86 (95% CI: 0.7819-0.94; P<0.0001) indicating the additive effect in the diagnostic value of these 2 miRNAs. QRT-PCR results showed that the expression level of these two miRs in complete remission AML patients resembled that of healthy controls.
CONCLUSIONS
Our findings indicated that plasma miR-150 and miR-342 are novel important promising biomarkers in the diagnosis of AML. These novel and promising markers warrant validation in larger prospective studies.
Topics: Area Under Curve; Biomarkers, Tumor; Case-Control Studies; Gene Expression Profiling; Humans; Leukemia, Myeloid, Acute; MicroRNAs; Oligonucleotide Array Sequence Analysis; ROC Curve; Real-Time Polymerase Chain Reaction
PubMed: 23391324
DOI: 10.1186/1479-5876-11-31 -
The Cochrane Database of Systematic... Dec 2021The Revised Cardiac Risk Index (RCRI) is a widely acknowledged prognostic model to estimate preoperatively the probability of developing in-hospital major adverse... (Review)
Review
The comparative and added prognostic value of biomarkers to the Revised Cardiac Risk Index for preoperative prediction of major adverse cardiac events and all-cause mortality in patients who undergo noncardiac surgery.
BACKGROUND
The Revised Cardiac Risk Index (RCRI) is a widely acknowledged prognostic model to estimate preoperatively the probability of developing in-hospital major adverse cardiac events (MACE) in patients undergoing noncardiac surgery. However, the RCRI does not always make accurate predictions, so various studies have investigated whether biomarkers added to or compared with the RCRI could improve this.
OBJECTIVES
Primary: To investigate the added predictive value of biomarkers to the RCRI to preoperatively predict in-hospital MACE and other adverse outcomes in patients undergoing noncardiac surgery. Secondary: To investigate the prognostic value of biomarkers compared to the RCRI to preoperatively predict in-hospital MACE and other adverse outcomes in patients undergoing noncardiac surgery. Tertiary: To investigate the prognostic value of other prediction models compared to the RCRI to preoperatively predict in-hospital MACE and other adverse outcomes in patients undergoing noncardiac surgery.
SEARCH METHODS
We searched MEDLINE and Embase from 1 January 1999 (the year that the RCRI was published) until 25 June 2020. We also searched ISI Web of Science and SCOPUS for articles referring to the original RCRI development study in that period.
SELECTION CRITERIA
We included studies among adults who underwent noncardiac surgery, reporting on (external) validation of the RCRI and: - the addition of biomarker(s) to the RCRI; or - the comparison of the predictive accuracy of biomarker(s) to the RCRI; or - the comparison of the predictive accuracy of the RCRI to other models. Besides MACE, all other adverse outcomes were considered for inclusion.
DATA COLLECTION AND ANALYSIS
We developed a data extraction form based on the CHARMS checklist. Independent pairs of authors screened references, extracted data and assessed risk of bias and concerns regarding applicability according to PROBAST. For biomarkers and prediction models that were added or compared to the RCRI in ≥ 3 different articles, we described study characteristics and findings in further detail. We did not apply GRADE as no guidance is available for prognostic model reviews.
MAIN RESULTS
We screened 3960 records and included 107 articles. Over all objectives we rated risk of bias as high in ≥ 1 domain in 90% of included studies, particularly in the analysis domain. Statistical pooling or meta-analysis of reported results was impossible due to heterogeneity in various aspects: outcomes used, scale by which the biomarker was added/compared to the RCRI, prediction horizons and studied populations. Added predictive value of biomarkers to the RCRI Fifty-one studies reported on the added value of biomarkers to the RCRI. Sixty-nine different predictors were identified derived from blood (29%), imaging (33%) or other sources (38%). Addition of NT-proBNP, troponin or their combination improved the RCRI for predicting MACE (median delta c-statistics: 0.08, 0.14 and 0.12 for NT-proBNP, troponin and their combination, respectively). The median total net reclassification index (NRI) was 0.16 and 0.74 after addition of troponin and NT-proBNP to the RCRI, respectively. Calibration was not reported. To predict myocardial infarction, the median delta c-statistic when NT-proBNP was added to the RCRI was 0.09, and 0.06 for prediction of all-cause mortality and MACE combined. For BNP and copeptin, data were not sufficient to provide results on their added predictive performance, for any of the outcomes. Comparison of the predictive value of biomarkers to the RCRI Fifty-one studies assessed the predictive performance of biomarkers alone compared to the RCRI. We identified 60 unique predictors derived from blood (38%), imaging (30%) or other sources, such as the American Society of Anesthesiologists (ASA) classification (32%). Predictions were similar between the ASA classification and the RCRI for all studied outcomes. In studies different from those identified in objective 1, the median delta c-statistic was 0.15 and 0.12 in favour of BNP and NT-proBNP alone, respectively, when compared to the RCRI, for the prediction of MACE. For C-reactive protein, the predictive performance was similar to the RCRI. For other biomarkers and outcomes, data were insufficient to provide summary results. One study reported on calibration and none on reclassification. Comparison of the predictive value of other prognostic models to the RCRI Fifty-two articles compared the predictive ability of the RCRI to other prognostic models. Of these, 42% developed a new prediction model, 22% updated the RCRI, or another prediction model, and 37% validated an existing prediction model. None of the other prediction models showed better performance in predicting MACE than the RCRI. To predict myocardial infarction and cardiac arrest, ACS-NSQIP-MICA had a higher median delta c-statistic of 0.11 compared to the RCRI. To predict all-cause mortality, the median delta c-statistic was 0.15 higher in favour of ACS-NSQIP-SRS compared to the RCRI. Predictive performance was not better for CHADS, CHADS-VASc, RCHADS, Goldman index, Detsky index or VSG-CRI compared to the RCRI for any of the outcomes. Calibration and reclassification were reported in only one and three studies, respectively.
AUTHORS' CONCLUSIONS
Studies included in this review suggest that the predictive performance of the RCRI in predicting MACE is improved when NT-proBNP, troponin or their combination are added. Other studies indicate that BNP and NT-proBNP, when used in isolation, may even have a higher discriminative performance than the RCRI. There was insufficient evidence of a difference between the predictive accuracy of the RCRI and other prediction models in predicting MACE. However, ACS-NSQIP-MICA and ACS-NSQIP-SRS outperformed the RCRI in predicting myocardial infarction and cardiac arrest combined, and all-cause mortality, respectively. Nevertheless, the results cannot be interpreted as conclusive due to high risks of bias in a majority of papers, and pooling was impossible due to heterogeneity in outcomes, prediction horizons, biomarkers and studied populations. Future research on the added prognostic value of biomarkers to existing prediction models should focus on biomarkers with good predictive accuracy in other settings (e.g. diagnosis of myocardial infarction) and identification of biomarkers from omics data. They should be compared to novel biomarkers with so far insufficient evidence compared to established ones, including NT-proBNP or troponins. Adherence to recent guidance for prediction model studies (e.g. TRIPOD; PROBAST) and use of standardised outcome definitions in primary studies is highly recommended to facilitate systematic review and meta-analyses in the future.
Topics: Adult; Bias; Biomarkers; Heart Arrest; Humans; Myocardial Infarction; Peptide Fragments; Predictive Value of Tests; Prognosis; Risk Assessment
PubMed: 34931303
DOI: 10.1002/14651858.CD013139.pub2 -
Ophthalmic Research 2018Glaucoma is one of the leading causes of irreversible blindness worldwide. However, there are no biomarkers that accurately help clinicians perform an early diagnosis or... (Review)
Review
Glaucoma is one of the leading causes of irreversible blindness worldwide. However, there are no biomarkers that accurately help clinicians perform an early diagnosis or detect patients with a high risk of progression. Metabolomics is the study of all metabolites in an organism, and it has the potential to provide a biomarker. This review summarizes the findings of metabolomics in glaucoma patients and explains why this field is promising for new research. We identified published studies that focused on metabolomics and ophthalmology. After providing an overview of metabolomics in ophthalmology, we focused on human glaucoma studies. Five studies have been conducted in glaucoma patients and all compared patients to healthy controls. Using mass spectrometry, significant differences were found in blood plasma in the metabolic pathways that involve palmitoylcarnitine, sphingolipids, vitamin D-related compounds, and steroid precursors. For nuclear magnetic resonance spectroscopy, a high glutamine-glutamate/creatine ratio was found in the vitreous and lateral geniculate body; no differences were detected in the optic radiations, and a lower N-acetylaspartate/choline ratio was observed in the geniculocalcarine and striate areas. Metabolomics can move glaucoma care towards a personalized approach and provide new knowledge concerning the pathophysiology of glaucoma, which can lead to new therapeutic options.
Topics: Biomarkers; Early Diagnosis; Glaucoma; Humans; Metabolomics
PubMed: 28858875
DOI: 10.1159/000479158 -
Journal of Pharmacy & Pharmaceutical... 2022Periostin is a matricellular, nonstructural protein belonging to the fasciclin family and is encoded by the POSTN gene in humans. Periostin plays an important role in... (Review)
Review
Periostin is a matricellular, nonstructural protein belonging to the fasciclin family and is encoded by the POSTN gene in humans. Periostin plays an important role in maintaining a normal tissue matrix in the lungs. Despite the vital role as a structural mediator in tissue growth and repair, periostin is involved in the pathogenic mechanism during tissue remodeling and fibrosis. Periostin is a chemoattractant mediator, promotes eosinophil recruitment and adhesion on the airways sub-epithelial membrane of asthmatic patients. POSTN gene was identified as one of the highly expressed genes induced by interleukins IL-13, IL-5 and IL-4 - the key cytokines of Th2 immune responses in the bronchial tissues of asthmatic patients. This review highlights the potential role of periostin as a validated biomarker in respiratory disease progression and its candidacy to predict the response to treatments targeting Th-2 cytokines in bronchial asthma. In addition, its potential role in COPD, IPF, lung cancer and lung infection, is also speculated. Keywords Periostin, Asthma, Pneumonia, COPD, Idiopathic pulmonary fibrosis, Biomarker.
Topics: Biomarkers; Fibrosis; Humans; Lung Diseases
PubMed: 35379385
DOI: 10.18433/jpps32306 -
Experimental Biology and Medicine... Apr 2017Calprotectin is a heterodimer formed by two proteins, S100A8 and S100A9, which are mainly produced by activated monocytes and neutrophils in the circulation and in... (Review)
Review
Calprotectin is a heterodimer formed by two proteins, S100A8 and S100A9, which are mainly produced by activated monocytes and neutrophils in the circulation and in inflamed tissues. The implication of calprotectin in the inflammatory process has already been demonstrated, but its role in the pathogenesis, diagnosis, and monitoring of rheumatic diseases has gained great attention in recent years. Calprotectin, being stable at room temperature, is a candidate biomarker for the follow-up of disease activity in many autoimmune disorders, where it can predict response to treatment or disease relapse. There is evidence that a number of immunomodulators, including TNF-α inhibitors, may reduce calprotectin expression. S100A8 and S100A9 have a potential role as a target of treatment in murine models of autoimmune disorders, since the direct or indirect blockade of these proteins results in amelioration of the disease process. In this review, we will go over the biologic functions of calprotectin which might be involved in the etiology of rheumatic disorders. We will also report evidence of its potential use as a disease biomarker. Impact statement Calprotectin is an acute-phase protein produced by monocytes and neutrophils in the circulation and inflamed tissues. Calprotectin seems to be more sensitive than CRP, being able to detect minimal residual inflammation and is a candidate biomarker in inflammatory diseases. High serum levels are associated with some severe manifestations of rheumatic diseases, such as glomerulonephritis and lung fibrosis. Calprotectin levels in other fluids, such as saliva and synovial fluid, might be helpful in the diagnosis of rheumatic diseases. Of interest is also the potential role of calprotectin as a target of treatment.
Topics: Adaptive Immunity; Adult; Biomarkers; Humans; Leukocyte L1 Antigen Complex; Models, Molecular; Rheumatic Diseases
PubMed: 27895095
DOI: 10.1177/1535370216681551 -
Nature Reviews. Chemistry Dec 2022Biomarkers are crucial biological indicators in medical diagnostics and therapy. However, the process of biomarker discovery and validation is hindered by a lack of... (Review)
Review
Biomarkers are crucial biological indicators in medical diagnostics and therapy. However, the process of biomarker discovery and validation is hindered by a lack of standardized protocols for analytical studies, storage and sample collection. Wearable chemical sensors provide a real-time, non-invasive alternative to typical laboratory blood analysis, and are an effective tool for exploring novel biomarkers in alternative body fluids, such as sweat, saliva, tears and interstitial fluid. These devices may enable remote at-home personalized health monitoring and substantially reduce the healthcare costs. This Review introduces criteria, strategies and technologies involved in biomarker discovery using wearable chemical sensors. Electrochemical and optical detection techniques are discussed, along with the materials and system-level considerations for wearable chemical sensors. Lastly, this Review describes how the large sets of temporal data collected by wearable sensors, coupled with modern data analysis approaches, would open the door for discovering new biomarkers towards precision medicine.
Topics: Wearable Electronic Devices; Biosensing Techniques; Body Fluids; Sweat; Biomarkers
PubMed: 37117704
DOI: 10.1038/s41570-022-00439-w -
Critical Care (London, England) Aug 2018Sepsis remains a critical problem with high morbidity and mortality worldwide. One of the problems we have in critical care is the need to find a good biomarker of...
Sepsis remains a critical problem with high morbidity and mortality worldwide. One of the problems we have in critical care is the need to find a good biomarker of sepsis to determine the existence of bacterial infection and the severity of patients. This would enable us to start appropriate treatment at an earlier stage of the disease course. We propose that decreases in the plasma protein histidine-rich glycoprotein (HRG) is an excellent biomarker of sepsis compared with the current markers. Based on the novel pathophysiological roles of HRG in the cascade of events during sepsis, we also discuss the potential for supplemental therapy with purified HRG.
Topics: APACHE; Biomarkers; Enzyme-Linked Immunosorbent Assay; Humans; Proteins; Sepsis
PubMed: 30119699
DOI: 10.1186/s13054-018-2127-5