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Pavoni-Ferreira, P. C., A. S. Petrilli, M. T. Alves, R. Jesus-Garcia Filho, and S. R. Toledo. "Angiogenic biomaker study in osteosarcoma." Journal of Clinical Oncology 27, no. 15_suppl (May 20, 2009): e21507-e21507. http://dx.doi.org/10.1200/jco.2009.27.15_suppl.e21507.
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e21507 Background: This study represents a prospective assessment of angiogenesis genes mRNA expression in tumors and blood from patients treated with pre- and post-operative Brazilian osteosarcoma protocol (GCBTO 2006) that introduce metronomic chemotherapy (anti-angiogenic) in order to try to increase survival of osteosarcoma patients. Methods: Tumor samples from 27 patients were analyzed before and after chemotherapy to determine VEGFA, VEGFR1, VEGFR2, PDGFC, SDF1 and TSP1 genes expression profile by Quantitative Real Time PCR. Also, blood samples of these patients were investigated pre- and post-chemotherapy and at the end of high-dose chemotherapy trying to evaluate potential for proangiogenic factors and antiangiogenic factor (TSP1) which could be used to monitor treatment activity. Results: Of all six genes studied pre- and post- chemotherapy, in tumor samples, only SDF1 and VEGFR2 were underexpressed. SDF1 gene has the lowest expression at all. In tumor samples, TSP1 and VEGFA expression was higher than SDF1, VEGFR2 and PDGFC expression in biopsies and surgeries (P=0.001). VEGFR1 expression was higher than VEGFR2 expression (P=0.001). PDGFC and VEGFR1 overexpression were associated with necrosis grade I and II (Huvos score) (P=0.005). VEGFA and TSP1 were overexpressed in 96% and 92% of surgery samples, respectively. In blood samples from biopsy, surgery and end of treatment there were no statistically significant changes in the marker genes expression. Conclusions: The study suggests an association between PDGFC and VEGFR1 overexpression and lower grade necrosis. TSP1 and VEGFA were the most expressed genes in all tumor samples but TSP1 was lower than VEGFA in biopsies and VEGFA was lower than TSP1 in surgery (P=0.001). Although VEGFR2 is the primary receptor of VEGF, VEGFR1 was the most expressed VEGF receptor. No significant financial relationships to disclose.
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Hashimoto, T., T. Hata, Y. Mori, J. Suzuki, Y. Kamata, K. Yoshimura, M. Kunou, et al. "P17-3 Evaluating event-related potential P50 suppression for diagnostic biomaker for psychiatric disorders." Clinical Neurophysiology 121 (October 2010): S203—S204. http://dx.doi.org/10.1016/s1388-2457(10)60836-x.
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Li, Chen, Hui Geng, Linhua Ji, Xiaojing Ma, Qichao Yin, and Hua Xiong. "ESM-1: A Novel Tumor Biomaker and its Research Advances." Anti-Cancer Agents in Medicinal Chemistry 19, no. 14 (December 16, 2019): 1687–94. http://dx.doi.org/10.2174/1871520619666190705151542.
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Background:Cancer kills nearly 9,000,000 people worldwide, and its mortality was reported up to 28% in the past decade. Few available tumor markers have been known to help early stage diagnosis. In this study, Endocan was taken as a novel tumor marker, which has been found in many cancers related to cancer cell proliferation, neoangiogenesis, etc.Methods:Studies on Endocan and its correlation with cancer were reviewed, and key points of meaningful studies on the structure, pathways and targeted agents of Endocan were drawn.Results:Endocan leads to tumorigenesis and promotes tumor cells proliferation via HGF/SF signal transmission pathway, suppresses tumor cells apoptosis via NF-κB signaling pathway and promotes angiogenesis within tumors via VEGF and HIF pathway. Medicine suppressing the expression of Endocan could prevent tumorigenesis and even improve survival rate of mice with tumor significantly.Conclusion:Endocan is capable of promoting prognosis of cancer patients. Moreover, Endocan is supposed to a potential target of tumor-targeted therapy.
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Nafi’u, S. A., K. Suleiman, M. K. Ahmad, and M. Zakariyya. "Effect of Paraquat Herbicide on Oxidative Stress Biomaker Enzyme Activities in C. Gariepinus." Dutse Journal of Pure and Applied Sciences 7, no. 3b (January 6, 2022): 48–59. http://dx.doi.org/10.4314/dujopas.v7i3b.6.
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Toxicity assessment was conducted for 96hr exposure duration using synthetic herbicide (paraquat dichloride 276g/L) on Claris gariepinus with mean weight range of 27.2 - 29.7g and mean length 10.95 -15.5cm. They were exposed to varying herbicide concentrations of 0.0, 3.45, 6.90, 10.35 and 13.5mg/L with 5-levels exposure concentrations in a Completely Randomized Design (CRD). Liver, gills and kidney tissues were analyzed for oxidative stress enzymes activities using Solarbio science assay kit (BC1170, 0170 and 0020). Four days lethal concentration (LC50) value for 96hr was found to be 7.298mg/L. The treated fish displayed erratic swimming with irregular opercular movement, loss of reflex, mucus secretion and increased air gulping with the increasing concentration of the herbicide compared with the control fish. Antioxidant biomarkers activities revealed that Glutathione S-transferase (GST), catalase (CAT) and superoxide dismutase (SOD) activities increased significantly (P<0.05) in the gills, liver and kidney tissues at higher concentrations compared with control. It can be deduced that alterations in the oxidative stress enzyme activities in the exposed fish to paraquat exert toxic effect on the liver, gills and kidney tissues. It is therefore recommended that appropriate authorities should develop strategies on minimizing the indiscriminate use of synthetic herbicides due to their impact on aquatic biota such as fish in order to reduce its potential risk to other non-target organisms.
Keywords: Clarias gariepinus, Lethal concentration, Oxidative Stress enzymes, Paraquat, Toxicity assessment
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Liu, Tianju, Andrew E. Rinke, Kevin Flaherty, and Sem Hin Phan. "Soluble B7H3 induction in pulmonary fibrosis is associated with disease severity." Journal of Immunology 204, no. 1_Supplement (May 1, 2020): 146.9. http://dx.doi.org/10.4049/jimmunol.204.supp.146.9.
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Abstract Idiopathic pulmonary fibrosis (IPF) is a progressive disease with limited therapeutic options. Both innate and adaptive immune mechanisms contribute to fibrogenesis. B7 family member B7H3, identified as important regulator of the immune system, has been implicated in cancer, graft-versus host disease, and allergy-related disease. Increased soluble B7H3 (sB7H3) was associated with enhanced lung fibrosis in mice receiving BLM-primed BM. Elevated sB7H3 in bronchoalveolar lavage fluid was associated with acute exacerbation IPF. To investigate whether induced sB7H3 could be used as a biomaker for IPF diagnosis and/or prognosis, plasma sB7H3 from control subjects and IPF patients was measured by ELISA. Its correlation with peripheral blood immune cells, lung function, and drug treatments were evaluated in this study. The results showed that the sB7H3 level was significantly elevated in IPF patients. This induction was associated with increased circulating B7H3+ cells, and significantly correlated with increased granulocytic myeloid-derived suppressive cells (G-MDSCs). This suggests a potential regulatory role of the induced B7H3 in the immune response in IPF. The plasma sB7H3 was negatively correlated with lung function measured as diffusing capacity of the lungs for carbon monoxide (DLCO), indicating the potential utility of plasma sB7H3 as an indicator of disease severity. The slightly elevated sB7H3 in the pirfenidone and/or nintedanib treated IPF patients were not significantly different relative to controls, which was in contrast to the significant elevation noted for the untreated patients. These findings suggest that sB7H3 may be a useful biomarker for clinical assessment of prognosis and response to drug treatment.
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B. Veena, B. Veena. "Bioinformatics Analysis of Mirna Data for Potential Biomarker Discovery." International Journal of Scientific Research 2, no. 8 (June 1, 2012): 45–47. http://dx.doi.org/10.15373/22778179/aug2013/16.
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McNamara, Aoife E., and Lorraine Brennan. "Potential of food intake biomarkers in nutrition research." Proceedings of the Nutrition Society 79, no. 4 (July 2, 2020): 487–97. http://dx.doi.org/10.1017/s0029665120007053.
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The influence of dietary habits on health/disease is well-established. Accurate dietary assessment is essential to understand metabolic pathways/processes involved in this relationship. In recent years, biomarker discovery has become a major area of interest for improving dietary assessment. Well-established nutrient intake biomarkers exist; however, there is growing interest in identifying and using biomarkers for more accurate and objective measurements of food intake. Metabolomics has emerged as a key tool used for biomarker discovery, employing techniques such as NMR spectroscopy, or MS. To date, a number of putatively identified biomarkers were discovered for foods including meat, cruciferous vegetables and legumes. However, many of the results are associations only and lack the desired validation including dose–response studies. Food intake biomarkers can be employed to classify individuals into consumers/non-consumers of specific foods, or into dietary patterns. Food intake biomarkers can also play a role in correcting self-reported measurement error, thus improving dietary intake estimates. Quantification of food intake was previously performed for citrus (proline betaine), chicken (guanidoacetate) and grape (tartaric acid) intake. However, this area still requires more investigation and expansion to a range of foods. The present review will assess the current literature of identified specific food intake biomarkers, their validation and the variety of biomarker uses. Addressing the utility of biomarkers and highlighting gaps in this area is important to advance the field in the context of nutrition research.
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K. Mohammed, Lona, and Sarhang S. Gul. "Diagnostic Potential of Salivary Biomarker Profiles in Epidemiological Survey of Periodontitis." Sulaimani dental journal 7, no. 2 (January 12, 2020): 36–44. http://dx.doi.org/10.17656/sdj.10114.
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Priya, Shalini, Alina Peluso, Mayanka Chandra Shekhar, Ioana Danciu, Jordan Miller, and Heidi A. Hanson. "Abstract 4191: Assessing performance of biomarker extraction from electronic health records: Data augmentation methods for a hierarchical self-attention network (HiSAN)." Cancer Research 83, no. 7_Supplement (April 4, 2023): 4191. http://dx.doi.org/10.1158/1538-7445.am2023-4191.
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Abstract Background: Extraction of HER2 status from electronic health records (EHR) may expedite clinical trials matching and be used for survivorship research. Deep learning (DL) algorithms have potential to extract this data; however, inherent class imbalance leads to reduced model performance. We compare state of the art strategies to handle class imbalance in models trained to extract HER2 status. This comparative analysis may be used as a guideline for HER2 extraction. Methods: 680,117 pathology reports collected from 2017-2021 by the National Cancer Institutes’ Surveillance, Epidemiology, and End-Results (SEER) program were used for this study. Pathology reports are manually labelled by cancer registrars as HER2 -, HER2+, or Unknown (class ratio 65%, 11%, 24% respectively). We compare six data augmentation (DA) methods: balanced frequency weighting, ROS while up-sampling HER2+ by 595%, RUS while down-sampling HER2- by 83%, SMOTE, ADASYN, and SMOTE-Tomek. As a comparison we consider the HiSAN model i.e., a DL architecture currently used by SEER for automatic classification of reports. Result: Applying DA strategies did not improve the performance of the HiSAN model (Table 1). Frequency based class-weighting (Acc=0.78), ROS (Acc=0.81), and RUS (Acc=0.80) perform worse than the baseline model, suggesting simple data augmentation methods do not boost performance for this task. Advanced oversampling with SMOTE (Acc=0.88) and ADASYN (Acc=0.88) perform better than simple approaches, but do not improve the predictive accuracy of the baseline HiSAN. Conclusion: Common DA methods do not improve the performance of the HiSAN biomaker method. While the overall accuracy of the baseline HiSAN model is quite high, other methods for improved accuracy should be explored. Table 1. Method Accuracy (Acc) Sensitivity Specificity Precision HiSAN (Baseline) 0.8898 0.7583 0.8944 0.8507 Frequency class weighting 0.7826 0.8033 0.8932 0.7040 Random Over Sampling (ROS) 0.8057 0.7672 0.8883 0.7130 Random Under Sampling (RUS) 0.8042 0.7883 0.8930 0.6902 Synthetic Minority Oversampling Technique (SMOTE) 0.8796 0.7341 0.8827 0.8340 Adaptive Synthetic Sampling (ADASYN) 0.8764 0.7467 0.8863 0.8142 SMOTE-Tomek 0.8823 0.7620 0.8956 0.8200 Citation Format: Shalini Priya, Alina Peluso, Mayanka Chandra Shekhar, Ioana Danciu, Jordan Miller, Heidi A. Hanson. Assessing performance of biomarker extraction from electronic health records: Data augmentation methods for a hierarchical self-attention network (HiSAN). [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4191.
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Ebadi, Maryam, and Vera C. Mazurak. "Potential Biomarkers of Fat Loss as a Feature of Cancer Cachexia." Mediators of Inflammation 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/820934.
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Fat loss is associated with shorter survival and reduced quality of life in cancer patients. Effective intervention for fat loss in cachexia requires identification of the condition using prognostic biomarkers for early detection and prevention of further depletion. No biomarkers of fat mass alterations have been defined for application to the neoplastic state. Several inflammatory cytokines have been implicated in mediating fat loss associated with cachexia; however, plasma levels may not relate to adipose atrophy. Zinc-α2-glycoprotein may be a local catabolic mediator within adipose tissue rather than serving as a plasma biomarker of fat loss. Plasma glycerol and leptin associate with adipose tissue atrophy and mass, respectively; however, no study has evaluated their potential as a prognostic biomarker of cachexia-associated fat loss. This review confirms the need for further studies to identify valid prognostic biomarkers to identify loss of fat based on changes in plasma levels of biomarkers.
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P, Gupta. "Role of Bioinformatics in Identifying Potential Biomarkers of Cervical Cancer." Open Access Journal of Microbiology & Biotechnology 8, no. 1 (January 2, 2023): 1–8. http://dx.doi.org/10.23880/oajmb-16000252.
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Cervical cancer is the one of the leading causes of death among women worldwide. The cancer evolves over a longer period of time and can be screened by different laboratory tests. In developed countries although the rate of incidence and mortality has been reduced, in developing countries the incidence rate still remains high. A large number of factors have been reported that promote the risk of cervical cancer. Some host factors play crucial role in the induction of the malignant transformation. These include micro RNAs that have known to act as oncogenes or tumor suppressor genes in tumors of cervical cancer. Certain high throughput technologies have generated data on miRNAs that are significant in the pathogenesis of cervical cancer. The data has been investigated extensively with the help of tools of bioinformatics for identification of potential biomarkers of cervical cancer. In the current article, we aim to discuss the properties of the tools of bioinformatics that have paved the research on cervical cancer. It is concluded that there is a need of development of large number and various types of tools of bioinformatics facilitating identification of potential biomarkers of cervical cancer for early diagnosis and better treatment regimen.
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Prentice, Ross L. "Criteria for Acceptable Dietary Intake Biomarkers." Cancer Epidemiology, Biomarkers & Prevention 31, no. 6 (June 1, 2022): 1151–53. http://dx.doi.org/10.1158/1055-9965.epi-22-0180.
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Abstract Dietary intake biomarkers that can be written as actual intake, plus ‘error’ that is independent of actual intake and confounding factors can substitute for actual intake in disease association analyses. Also, such biomarkers can be used to develop calibration equations using self-reported diet and participant measures, and biomarker-calibrated intakes can be calculated in larger cohorts for use in disease association analyses. Criteria for biomarkers, and for biomarker-calibrated intakes, arise by working back from properties needed for valid disease association analyses. Accordingly, arguments for a potential biomarker are strengthened if error components are small relative to actual intakes, and important sources of reduced sensitivity or specificity are not apparent. Feeding study biomarker development can then involve regression of actual intake on putative biomarkers, with regression R2 values playing a role in biomarker evaluation. In comparison, ‘predictive’ biomarker status, as argued in this issue by Freedman and colleagues for 24-hour urinary sucrose plus fructose as biomarker for total sugars, involves regression of potential biomarker on actual intake and other variables, with parameter stability across populations and limited within-person variability as criteria. The choice of criteria for biomarkers and for biomarker-calibrated intakes, is discussed here, in the context of total sugars intake. See related article by Freedman et al., p. 1227
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Gautam, Shailendra K., Parvez Khan, Gopalakrishnan Natarajan, Pranita Atri, Abhijit Aithal, Apar K. Ganti, Surinder K. Batra, Mohd W. Nasser, and Maneesh Jain. "Mucins as Potential Biomarkers for Early Detection of Cancer." Cancers 15, no. 6 (March 7, 2023): 1640. http://dx.doi.org/10.3390/cancers15061640.
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Early detection significantly correlates with improved survival in cancer patients. So far, a limited number of biomarkers have been validated to diagnose cancers at an early stage. Considering the leading cancer types that contribute to more than 50% of deaths in the USA, we discuss the ongoing endeavors toward early detection of lung, breast, ovarian, colon, prostate, liver, and pancreatic cancers to highlight the significance of mucin glycoproteins in cancer diagnosis. As mucin deregulation is one of the earliest events in most epithelial malignancies following oncogenic transformation, these high-molecular-weight glycoproteins are considered potential candidates for biomarker development. The diagnostic potential of mucins is mainly attributed to their deregulated expression, altered glycosylation, splicing, and ability to induce autoantibodies. Secretory and shed mucins are commonly detected in patients’ sera, body fluids, and tumor biopsies. For instance, CA125, also called MUC16, is one of the biomarkers implemented for the diagnosis of ovarian cancer and is currently being investigated for other malignancies. Similarly, MUC5AC, a secretory mucin, is a potential biomarker for pancreatic cancer. Moreover, anti-mucin autoantibodies and mucin-packaged exosomes have opened new avenues of biomarker development for early cancer diagnosis. In this review, we discuss the diagnostic potential of mucins in epithelial cancers and provide evidence and a rationale for developing a mucin-based biomarker panel for early cancer detection.
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Feng, Ziding, Jacob Kagan, Margaret Pepe, Mark Thornquist, Jo Ann Rinaudo, Jackie Dahlgren, Karl Krueger, et al. "The Early Detection Research Network's Specimen Reference Sets: Paving the Way for Rapid Evaluation of Potential Biomarkers." Clinical Chemistry 59, no. 1 (January 1, 2013): 68–74. http://dx.doi.org/10.1373/clinchem.2012.185140.
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BACKGROUND The mission of the National Cancer Institute's Early Detection Research Network (EDRN) is to identify and validate cancer biomarkers for clinical use. Since its inception, EDRN investigators have learned a great deal about the process of validating biomarkers for clinical use. Translational research requires a broad spectrum of research expertise, and coordinating collaborative activities can be challenging. The EDRN has developed a robust triage and validation system that serves the roles of both “facilitator” and “brake.” CONTENT The system consists of (a) establishing a reference set of specimens collected under PRoBE (Prospective Specimen Collection Retrospective Blinded Evaluation) design criteria; (b) using the reference set to prevalidate candidate biomarkers before committing to full-scale validation; (c) performing full-scale validation for those markers that pass prevalidation testing; and (d) ensuring that the reference set is sufficiently large in numbers and volumes of sample that it can also be used to study future candidate biomarkers. This system provides rigorous and efficient evaluation of candidate biomarkers and biomarker panels. Reference sets should also be constructed to enable high-quality biomarker-discovery research. SUMMARY We describe the process of establishing our system in the hope that it will serve as an example of how to validate biomarkers for clinical application. We also hope that this description of the biospecimen reference sets available from the EDRN will encourage the biomarker research community—from academia or industry—to use this resource to advance biomarkers into clinical use.
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Gromova, Mariya, Annegret Vaggelas, Gabriele Dallmann, and Diane Seimetz. "Biomarkers: Opportunities and Challenges for Drug Development in the Current Regulatory Landscape." Biomarker Insights 15 (January 2020): 117727192097465. http://dx.doi.org/10.1177/1177271920974652.
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Biomarkers are widely used at every stage of drug discovery and development. Utilisation of biomarkers has a potential to make drug discovery, development and approval processes more efficient. An overview of the current global regulatory landscape is presented in this article with particular emphasis on the validation and qualification of biomarkers, as well as legal framework for companion diagnostics. Furthermore, this article shows how the number of approved drugs with at least 1 biomarker used during development (biomarker acceptance) is affected by the recent advances in the biomarker regulations. More than half of analysed approvals were supported by biomarker data and there has been a slight increase in acceptance of biomarkers in recent years, even though the growth is not continuous. For certain pharmacotherapeutic groups, approvals with biomarkers are more common than without. Examples include immunosuppressants, immunostimulants, drugs used in diabetes, antithrombotic drugs, antineoplastic agents and antivirals. As a conclusion, potential benefits, challenges and opportunities of using biomarkers in drug discovery and development in the current regulatory landscape are summarised and discussed.
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Adki, Kaveri M., and Yogesh A. Kulkarni. "Potential Biomarkers in Diabetic Retinopathy." Current Diabetes Reviews 16, no. 9 (November 6, 2020): 971–83. http://dx.doi.org/10.2174/1573399816666200217092022.
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Background: Diabetic retinopathy is one of the important complications of diabetes. In major cases, diabetic retinopathy is unnoticed until the irreversible damage to eye occurs and leads to blurred vision and, eventually, blindness. Objective: The pathogenesis and diagnosis of diabetic retinopathy are very complex and not fully understood. Currently, well-established laser techniques and medications are available, but these treatment options have their own shortcomings on biological systems. Biomarkers can help to overcome this problem due to easy, fast and economical options for diagnosis of diabetic retinopathy. Methods: The search terms used were “Diabetic retinopathy”, “Biomarkers in diabetic retinopathy”, “Novel biomarkers in diabetic retinopathy” and “Potential biomarkers of diabetic retinopathy” by using different scientific resources and databases like EBSCO, ProQuest, PubMed and Scopus. Eligibility criteria included biomarkers involved in diabetic retinopathy in the detectable range. Exclusion criteria included the repetition and duplication of the biomarker in diabetic retinopathy. Results: Current review and literature study revealed that biomarkers of diabetic retinopathy can be categorized as inflammatory: tumor necrosis factor-α, monocyte chemoattractant protein-1, transforming growth factor- β; antioxidant: nicotinamide adenine dinucleotide phosphate oxidase; nucleic acid: poly ADP ribose polymerase- α, Apelin, Oncofetal; enzyme: ceruloplasmin, protein kinase C; and miscellaneous: erythropoietin. These biomarkers have a great potential in the progression of diabetic retinopathy hence can be used in the diagnosis and management of this debilitating disease. Conclusion: Above mentioned biomarkers play a key role in the pathogenesis of diabetic retinopathy; hence they can also be considered as potential targets for new drug development.
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Li, Yuanzhang, Robert Yolken, David N. Cowan, Michael R. Boivin, and David W. Niebuhr. "Potential Biomarkers Selection for Bipolar Disorder Identification." Research in Health Science 2, no. 3 (July 19, 2017): 262. http://dx.doi.org/10.22158/rhs.v2n3p262.
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<p><em>A biomarker is a measurable indicator of the severity or presence of some disease. A biomarker is anything that can be used as an indicator of a particular disease state or some other physiological state of an organism. The space Decomposition-Gradient-Regression (DGR) method has been developed (Li et al., 2012; Li et al., 2015) to select biomarkers for schizophrenia. This study performs the DGR approach on data for bipolar disorder patients, which contains 56 biomarkers and 8 infectious agent’s antibodies. Serum specimens were collected from 132 United States military service members </em><em>(118 males and 14 females) </em><em>with a diagnosis of bipolar disorder from 1992 to 2005 and their matched healthy controls.. Trefoil Factor3 (TFF3), Gliadin, prolactin (PRL), Apolipoprotein A-II (Apo A-II) and Immunoglobulin A (IGA) </em><em>were found to be significant predictors of Bipolar Disorder (BD) in males. Macrophage-Derived Chemokine (MDC), Alpha-1-Antitrypsin (AAT), Gliadin, Beta-2-Microglobulin (B2M) and Monocyte Chemotactic Protein 2 (MCP-2) might be used to identify </em><em>bipolar disorder</em><em> in females. A predictive biomarker panel for BD offers the potential to aid in the diagnosis, initiate treatment earlier and ideally alter the course of disease with reduced morbidity and functional impairment.</em></p>
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Mesarcova, L., J. Kottferova, L. Skurkova, L. Leskova, and N. Kmecova. "Analysis of cortisol in dog hair - a potential biomarker of chronic stress: a review." Veterinární Medicína 62, No. 7 (July 25, 2017): 363–76. http://dx.doi.org/10.17221/19/2017-vetmed.
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Cortisol, which is produced in the adrenal glands, is an endogenous glucocorticoid hormone that delivers its hormonal message to cells by acting on glucocorticoid receptors. It is one of the main stress hormones responsible for stress responses in animals and humans, and its overproduction is characteristic of certain diseases. While acute stress disorder can be evaluated by means of measuring the cortisol concentration in blood and urine, chronic stress disorder can be detected by monitoring the cortisol concentration in fur or hair. Hair collection is simple, inexpensive and non-invasive, and can be performed easily and rapidly; thus, it appears to be a suitable method for determining the level of stress in dogs from shelters, abused dogs or dogs involved in different types of animal interactions. Since it is a relatively new method, monitoring cortisol in hair or fur requires further research in order to definitively prove its efficacy, and possibly to determine reference range values for different breeds of dogs.
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Considine, Elizabeth C., Ali S. Khashan, and Louise C. Kenny. "Screening for Preterm Birth: Potential for a Metabolomics Biomarker Panel." Metabolites 9, no. 5 (May 7, 2019): 90. http://dx.doi.org/10.3390/metabo9050090.
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The aim of this preliminary study was to investigate the potential of maternal serum to provide metabolomic biomarker candidates for the prediction of spontaneous preterm birth (SPTB) in asymptomatic pregnant women at 15 and/or 20 weeks’ gestation. Metabolomics LC-MS datasets from serum samples at 15- and 20-weeks’ gestation from a cohort of approximately 50 cases (GA < 37 weeks) and 55 controls (GA > 41weeks) were analysed for candidate biomarkers predictive of SPTB. Lists of the top ranked candidate biomarkers from both multivariate and univariate analyses were produced. At the 20 weeks’ GA time-point these lists had high concordance with each other (85%). A subset of 4 of these features produce a biomarker panel that predicts SPTB with a partial Area Under the Curve (pAUC) of 12.2, a sensitivity of 87.8%, a specificity of 57.7% and a p-value of 0.0013 upon 10-fold cross validation using PanelomiX software. This biomarker panel contained mostly features from groups already associated in the literature with preterm birth and consisted of 4 features from the biological groups of “Bile Acids”, “Prostaglandins”, “Vitamin D and derivatives” and “Fatty Acids and Conjugates”.
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Santri, Ichtiarini Nurullita, Lalu Muhammad Irham, Gina Noor Djalilah, Dyah Aryani Perwitasari, Yuniar Wardani, Yohane Vincent Abero Phiri, and Wirawan Adikusuma. "Identification of Hub Genes and Potential Biomarkers for Childhood Asthma by Utilizing an Established Bioinformatic Analysis Approach." Biomedicines 10, no. 9 (September 16, 2022): 2311. http://dx.doi.org/10.3390/biomedicines10092311.
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Childhood asthma represents a heterogeneous disease resulting from the interaction between genetic factors and environmental exposures. Currently, finding reliable biomarkers is necessary for the clinical management of childhood asthma. However, only a few biomarkers are being used in clinical practice in the pediatric population. In the long run, new biomarkers for asthma in children are required and would help direct therapy approaches. This study aims to identify potential childhood asthma biomarkers using a genetic-driven biomarkers approach. Herein, childhood asthma-associated Single Nucleotide Polymorphisms (SNPs) were utilized from the GWAS database to drive and facilitate the biomarker of childhood asthma. We uncovered 466 childhood asthma-associated loci by extending to proximal SNPs based on r2 > 0.8 in Asian populations and utilizing HaploReg version 4.1 to determine 393 childhood asthma risk genes. Next, the functional roles of these genes were subsequently investigated using Gene Ontology (GO) term enrichment analysis, a Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and a protein–protein interaction (PPI) network. MCODE and CytoHubba are two Cytoscape plugins utilized to find biomarker genes from functional networks created using childhood asthma risk genes. Intriguingly, 10 hub genes (IL6, IL4, IL2, IL13, PTPRC, IL5, IL33, TBX21, IL2RA, and STAT6) were successfully identified and may have been identified to play a potential role in the pathogenesis of childhood asthma. Among 10 hub genes, we strongly suggest IL6 and IL4 as prospective childhood asthma biomarkers since both of these biomarkers achieved a high systemic score in Cytohubba’s MCC algorithm. In summary, this study offers a valuable genetic-driven biomarker approach to facilitate the potential biomarkers for asthma in children.
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Hariadi, Hariadi, Maia Thalia Giani, and Silvia Handika Anggraeni. "Potential Biomarkers as Early Detection of Diabetic Cardiomyopathy." Cardiovascular and Cardiometabolic Journal (CCJ) 2, no. 2 (September 30, 2021): 95. http://dx.doi.org/10.20473/ccj.v2i2.2021.95-109.
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Abstract: Diabetes mellitus (DM) is one of the most prevalent and burdensome among chronic disease worldwide. Its complications accelerate mortality rate within population. Diabetic cardiomyopathy (DCM) is one of diabetes macrovascular complications, which symptoms are frequently unforeseen. Advances in pathogenesis understanding DCM underlying mechanisms remain not fully perceived. Current diagnostic approach of DCM can hardly determine diabetic patients with asymptomatic cardiomyopathy. Previous studies suggested biomarkers might detect early stage DCM. There are numerous selective biomarkers representing several pathophysiological pathways, such as myocardial fibrosis, inflammatory response, cardiomyocyte apoptosis, and metabolic dysregulation in the development of diabetic heart anomaly It was also reported those biomarkers are useful for the prognostic assessment of the disease. However, not all biomarkers are cardiac specific and can be an auspicious diagnostic tool candidate. Recent studies show that there are certain biomarkers, such as microRNA, H-FABP, IGFBP7, and some other novel cardiac biomarkers were more specifically associated with the pathological mechanism of DCM. In this review, we aimed to discuss the role of several potential cardiac biomarkers as early detection in DCM that may predict future incident of DCM, and contribute to improving mortality prediction in patients with subclinical DCM.Keywords: Biomarker; Diabetic Cardiomyopathy
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Galen, Gaby van, Emil Olsen, and Natalia Siwinska. "Biomarkers of Kidney Disease in Horses: A Review of the Current Literature." Animals 12, no. 19 (October 5, 2022): 2678. http://dx.doi.org/10.3390/ani12192678.
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Creatinine only allows detection of kidney disease when 60 to 75% of the glomerular function is lost and is therefore not an ideal marker of disease. Additional biomarkers could be beneficial to assess kidney function and disease. The objectives are to describe new equine kidney biomarkers. This systematic review assesses the available literature, including the validation process and reference values, following which the authors suggest recommendations for clinical use. SDMA may have some potential as equine kidney biomarker, but there is currently a lack of evidence that SDMA offers any advantage compared to creatinine in detecting Acute Kidney Injury (AKI). Cystatin C and podocin show potential as biomarkers for kidney disease (including detecting AKI earlier than creatinine) and should be studied further. NGAL has potential as a biomarker of kidney disease (including detecting AKI earlier than creatinine), and potential as an inflammatory marker. Literature on MMP-9 does not allow for conclusive statements about its potential as a biomarker for kidney disease. The future may show that NAG has potential. For all biomarkers, at this stage, available scientific information is limited or too scarce to support clinical use, and only SDMA can be measured for clinical purposes. In conclusion, there are multiple new biomarkers with the potential to diagnose kidney problems. However, there are only a few studies available and more data is needed before these biomarkers can be applied and recommended in our daily practice.
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Leung, Jason Hongting, Benjamin Ng, and Wei-Wen Lim. "Interleukin-11: A Potential Biomarker and Molecular Therapeutic Target in Non-Small Cell Lung Cancer." Cells 11, no. 14 (July 21, 2022): 2257. http://dx.doi.org/10.3390/cells11142257.
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Non-small cell lung cancer (NSCLC) accounts for 85% of lung cancer and is a fast progressive disease when left untreated. Identification of potential biomarkers in NSCLC is an ongoing area of research that aims to detect, diagnose, and prognosticate patients early to optimize treatment. We review the role of interleukin-11 (IL11), a stromal-cell derived pleiotropic cytokine with profibrotic and cellular remodeling properties, as a potential biomarker in NSCLC. This review identifies the need for biomarkers in NSCLC, the potential sources of IL11, and summarizes the available information leveraging upon published literature, publicly available datasets, and online tools. We identify accumulating evidence suggesting IL11 to be a potential biomarker in NSCLC patients. Further in-depth studies into the pathophysiological effects of IL11 on stromal-tumor interaction in NSCLC are warranted and current available literature highlights the potential value of IL11 detection as a diagnostic and prognostic biomarker in NSCLC.
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Thorsen, Stine, Irina Gromova, Ib Christensen, Simon Fredriksson, Claus Andersen, Hans Nielsen, Jan Stenvang, and José Moreira. "Gel-Based Proteomics of Clinical Samples Identifies Potential Serological Biomarkers for Early Detection of Colorectal Cancer." International Journal of Molecular Sciences 20, no. 23 (December 2, 2019): 6082. http://dx.doi.org/10.3390/ijms20236082.
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The burden of colorectal cancer (CRC) is considerable—approximately 1.8 million people are diagnosed each year with CRC and of these about half will succumb to the disease. In the case of CRC, there is strong evidence that an early diagnosis leads to a better prognosis, with metastatic CRC having a 5-year survival that is only slightly greater than 10% compared with up to 90% for stage I CRC. Clearly, biomarkers for the early detection of CRC would have a major clinical impact. We implemented a coherent gel-based proteomics biomarker discovery platform for the identification of clinically useful biomarkers for the early detection of CRC. Potential protein biomarkers were identified by a 2D gel-based analysis of a cohort composed of 128 CRC and site-matched normal tissue biopsies. Potential biomarkers were prioritized and assays to quantitatively measure plasma expression of the candidate biomarkers were developed. Those biomarkers that fulfilled the preset criteria for technical validity were validated in a case-control set of plasma samples, including 70 patients with CRC, adenomas, or non-cancer diseases and healthy individuals in each group. We identified 63 consistently upregulated polypeptides (factor of four-fold or more) in our proteomics analysis. We selected 10 out of these 63 upregulated polypeptides, and established assays to measure the concentration of each one of the ten biomarkers in plasma samples. Biomarker levels were analyzed in plasma samples from healthy individuals, individuals with adenomas, CRC patients, and patients with non-cancer diseases and we identified one protein, tropomyosin 3 (Tpm3) that could discriminate CRC at a significant level (p = 0.0146). Our results suggest that at least one of the identified proteins, Tpm3, could be used as a biomarker in the early detection of CRC, and further studies should provide unequivocal evidence for the real-life clinical validity and usefulness of Tpm3.
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Hermann, Stefanie, Christian Grätz, Benedikt Kirchner, and Michael W. Pfaffl. "Extracellular vesicle-derived microRNA biomarkers: goals and pitfalls." Extracellular vesicles as biomarkers – in pathophysiology, physical education and home office? 2, no. 1 (September 2, 2020): 42–47. http://dx.doi.org/10.47184/tev.2020.01.04.
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Liquid biopsy-derived extracellular vesicles (EVs) are an auspicious source for transcriptomic biomarker studies. Here, we review the potential of EV microRNAs (miRNAs) biomarkers, exemplary outline commonly used methods to elucidate new biomarker signatures, and pivotally discuss their applicability at present. Keywords: extracellular vesicles, liquid biopsies, transcriptomic biomarkers, microRNAs
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Mathur, Deepali, Bikash Kumar Mishra, Soumyashree Rout, Francisco Jose Lopez-Iranzo, Gerardo Lopez-Rodas, Jayalakshmi Vallamkondu, Ramesh Kandimalla, and Bonaventura Casanova. "Potential Biomarkers Associated with Multiple Sclerosis Pathology." International Journal of Molecular Sciences 22, no. 19 (September 25, 2021): 10323. http://dx.doi.org/10.3390/ijms221910323.
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Multiple sclerosis (MS) is a complex disease of the central nervous system (CNS) that involves an intricate and aberrant interaction of immune cells leading to inflammation, demyelination, and neurodegeneration. Due to the heterogeneity of clinical subtypes, their diagnosis becomes challenging and the best treatment cannot be easily provided to patients. Biomarkers have been used to simplify the diagnosis and prognosis of MS, as well as to evaluate the results of clinical treatments. In recent years, research on biomarkers has advanced rapidly due to their ability to be easily and promptly measured, their specificity, and their reproducibility. Biomarkers are classified into several categories depending on whether they address personal or predictive susceptibility, diagnosis, prognosis, disease activity, or response to treatment in different clinical courses of MS. The identified members indicate a variety of pathological processes of MS, such as neuroaxonal damage, gliosis, demyelination, progression of disability, and remyelination, among others. The present review analyzes biomarkers in cerebrospinal fluid (CSF) and blood serum, the most promising imaging biomarkers used in clinical practice. Furthermore, it aims to shed light on the criteria and challenges that a biomarker must face to be considered as a standard in daily clinical practice.
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Neuhaus, Jochen, and Bo Yang. "Liquid Biopsy Potential Biomarkers in Prostate Cancer." Diagnostics 8, no. 4 (September 21, 2018): 68. http://dx.doi.org/10.3390/diagnostics8040068.
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Prostate cancer (PCa) is the second most common cancer in men worldwide with an incidence of 14.8% and a mortality of 6.6%. Shortcomings in comprehensive medical check-ups in low- and middle-income countries lead to delayed detection of PCa and are causative of high numbers of advanced PCa cases at first diagnosis. The performance of available biomarkers is still insufficient and limited applicability, including logistical and financial burdens, impedes comprehensive implementation into health care systems. There is broad agreement on the need of new biomarkers to improve (i) early detection of PCa, (ii) risk stratification, (iii) prognosis, and (iv) treatment monitoring. This review focuses on liquid biopsy tests distinguishing high-grade significant (Gleason score (GS) ≥ 7) from low-grade indolent PCa. Available biomarkers still lack performance in risk stratification of biopsy naïve patients. However, biomarkers with highly negative predictive values may help to reduce unnecessary biopsies. Risk calculators using integrative scoring systems clearly improve decision-making for invasive prostate biopsy. Emerging biomarkers have the potential to substitute PSA and improve the overall performance of risk calculators. Until then, PSA should be used and may be replaced whenever enough evidence has accumulated for better performance of a new biomarker.
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Morris, Adam D., Anthony W. Rowbottom, Francis L. Martin, Alexander Woywodt, and Ajay P. Dhaygude. "Biomarkers in ANCA-Associated Vasculitis: Potential Pitfalls and Future Prospects." Kidney360 2, no. 3 (January 19, 2021): 586–97. http://dx.doi.org/10.34067/kid.0006432020.
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Over the past 3 decades, significant advancements in the understanding of the pathophysiology of ANCA-associated vasculitis has led to the development of a multitude of potential candidate biomarkers. Accompanied by the advent of increasingly effective therapeutic strategies, the need for a dependable biomarker to help determine the extent of disease activity and risk of relapse is ever present. Implementation of such a biomarker would enable tailored therapy, optimizing disease control while helping to mitigate unnecessary exposure to therapy and potential treatment-related damage. Although far from perfect, ANCA serology and B-cell population are the two main staple biomarker tools widely used in practice to help supplement clinical assessment. Over recent years, the application and progress of more novel biomarker tools have arisen in both organ-limited and multisystem disease, including genomics, urinary proteins, degradation products of the alternative complement system, cytokines, metabolomics, and biospectroscopy. Validation studies and clinical translation of these tools are required, with serial assessment of disease activity and determination of therapy according to biomarker status correlated with patient outcomes.
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Beattie, Erin, Jeffery Edmiston, Patrudu Makena, Elizabeth Mason, Mike McEwan, and Krishna Prasad. "Review of recent lung biomarkers of potential harm/effect for tobacco research." F1000Research 10 (December 17, 2021): 1293. http://dx.doi.org/10.12688/f1000research.55411.1.
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Biomarkers of potential harm (BoPH) are indicators of biological perturbations which may contribute to the pathophysiology of disease. In this review, we critically assessed the published data on lung-related BoPH in human lung disease for potential use in evaluating the effects of tobacco and nicotine products. A Scopus literature search was conducted on lung disease biomarkers used in a clinical setting over the last 10 years. We identified 1171 papers which were further screened using commercial software (Sciome SWIFT-Active Screener) giving 68 publications that met our inclusion criteria (data on the association of the biomarker with cigarette smoking, the impact of smoking cessation on the biomarker, and differences between smokers and non-smokers), the majority of which investigated chronic obstructive pulmonary disease. Several physiological and biochemical measures were identified that are potentially relevant for evaluating the impact of tobacco products on lung health. Promising new candidates included blood biomarkers, such as surfactant protein D (SP-D), soluble receptor for advanced glycation end products (sRAGE), skin autofluorescence (SAF), and imaging techniques. These biomarkers may provide insights into lung disease development and progression; however, all require further research and validation to confirm their role in the context of tobacco and nicotine exposure, their time course of development and ability to measure or predict disease progression.
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Zainal, N. H. M., R. Abas, and S. F. Mohamad Asri. "Childhood Allergy Disease, Early Diagnosis, and the Potential of Salivary Protein Biomarkers." Mediators of Inflammation 2021 (October 8, 2021): 1–12. http://dx.doi.org/10.1155/2021/9198249.
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Allergic disease has risen to epidemic proportions since the last decade and is among the most common noncommunicable, chronic diseases in children and adolescents worldwide. Allergic disease usually occurs in early life; thus, early biomarkers of allergic susceptibility are required for preventive measures to high-risk infants which enable early interventions to decrease allergic severity. However, to date, there is no reliable general or specific allergy phenotype detection method that is easy and noninvasive for children. Most reported allergic phenotype detection methods are invasive, such as the skin prick test (SPT), oral food challenge (OFC), and blood test, and many involve not readily accessible biological samples, such as cord blood (CB), maternal blood, or newborn vernix. Saliva is a biological sample that has great potential as a biomarker measurement as it consists of an abundance of biomarkers, such as genetic material and proteins. It is easily accessible, noninvasive, collected via a painless procedure, and an easy bedside screening for real-time measurement of the ongoing human physiological system. All these advantages emphasise saliva as a very promising diagnostic candidate for the detection and monitoring of disease biomarkers, especially in children. Furthermore, protein biomarkers have the advantages as modifiable influencing factors rather than genetic and epigenetic factors that are mostly nonmodifiable factors for allergic disease susceptibility in childhood. Saliva has great potential to replace serum as a biological fluid biomarker in diagnosing clinical allergy. However, to date, saliva is not considered as an established medically acceptable biomarker. This review considers whether the saliva could be suitable biological samples for early detection of allergic risk. Such tools may be used as justification for targeted interventions in early childhood for disease prevention and assisting in reducing morbidity and mortality caused by childhood allergy.
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Wang, Li, and Jing Sun. "ASPN Is a Potential Biomarker and Associated with Immune Infiltration in Endometriosis." Genes 13, no. 8 (July 28, 2022): 1352. http://dx.doi.org/10.3390/genes13081352.
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Objective: Endometriosis is a benign gynecological disease characterized by distant metastasis. Previous studies have discovered abnormal numbers and function of immune cells in endometriotic lesions. We aimed to find potential biomarkers of endometriosis and to explore the relationship between ASPN and the immune microenvironment of endometriosis. Methods: We obtained the GSE141549 and GSE7305 datasets containing endometriosis and normal endometrial samples from the Gene Expression Omnibus database (GEO). In the GSE141549 dataset, differentially expressed genes (DEGs) were found. The Least Absolute Shrinkage and Selection Operator (Lasso) regression and generalized linear models (GLMs) were used to screen new biomarkers. The expression levels and diagnostic utility of biomarkers were assessed in GSE7305, and biomarker expression levels were further validated using qRT-PCR and western blot. We identified DEGs between high and low expression groups of key biomarkers. Enrichment analysis was carried out to discover the target gene’s biological function. We analyzed the relationship between key biomarker expression and patient clinical features. Finally, the immune cells that infiltrate endometriosis were assessed using the Microenvironment Cell Population-Counter (MCP-counter), and the correlation of biomarker expression with immune cell infiltration and immune checkpoints genes was studied. Results: There were a total of 38 DEGs discovered. Two machine learning techniques were used to identify 10 genes. Six biomarkers (SCG2, ASPN, SLIT2, GEM, EGR1, and FOS) had good diagnostic efficiency (AUC > 0.7) by internal and external validation. We excluded previously reported related genes (SLIT2, EGR1, and FOS). ASPN was the most significantly differentially expressed biomarker between normal and ectopic endometrial tissues, as verified by qPCR. The western blot assay revealed a significant upregulation of ASPN expression in endometriotic tissues. The investigation for DEGs in the ASPN high- and low-expression groups revealed that the DEGs were particularly enriched in extracellular matrix tissue, vascular smooth muscle contraction, cytokine interactions, the calcium signaling pathway, and the chemokine signaling pathway. High ASPN expression was related to r-AFS stage (p = 0.006), age (p = 0.03), and lesion location (p < 0.001). Univariate and multivariate logistic regression analysis showed that ASPN expression was an independent influencing factor in patients with endometriosis. Immune cell infiltration analysis revealed a significant increase in T-cell, B-cell, and fibroblast infiltration in endometriosis lesions; cytotoxic lymphocyte, NK-cell, and endothelial cell infiltration were reduced. Additionally, the percentage of T cells, B cells, fibroblasts, and endothelial cells was favorably connected with ASPN expression, while the percentage of cytotoxic lymphocytes and NK cells was negatively correlated. Immune checkpoint gene (CTLA4, LAG3, CD27, CD40, and ICOS) expression and ASPN expression were positively associated. Conclusions: Increased expression of ASPN is associated with immune infiltration in endometriosis, and ASPN can be used as a diagnostic biomarker as well as a potential immunotherapeutic target in endometriosis.
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Kovač, Valerija, and Vladka Čurin Šerbec. "Prion Proteins Without the Glycophosphatidylinositol Anchor: Potential Biomarkers in Neurodegenerative Diseases." Biomarker Insights 13 (January 1, 2018): 117727191875664. http://dx.doi.org/10.1177/1177271918756648.
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Prion protein (PrP) is a biomolecule that is involved in neuronal signaling, myelinization, and the development of neurodegenerative diseases. In the cell, PrP is shed by the ADAM10 protease. This process generates PrP molecules that lack glycophosphatidylinositol anchor, and these molecules incorporate into toxic aggregates and neutralize toxic oligomers. Due to this dual role, these molecules are important biomarkers for neurodegenerative diseases. In this review, we present shed PrP as a potential biomarker, with a focus on PrP226*, which may be the main biomarker for predicting neurodegenerative diseases in humans.
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Salas, Maribel, Maxine Gossell-Williams, Priyanka Yalamanchili, Sameer Dhingra, Marina A. Malikova, Omar Aimer, and Toluwalope Junaid. "The Use of Biomarkers in Pharmacovigilance: A Systematic Review of the Literature." Biomarker Insights 18 (January 2023): 117727192311645. http://dx.doi.org/10.1177/11772719231164528.
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Background: The use of biomarkers varies from disease etiognosis and diagnosis to signal detection, risk prediction, and management. Biomarker use has expanded in recent years, however, there are limited reviews on the use of biomarkers in pharmacovigilance and specifically in the monitoring and management of adverse drug reactions (ADRs). Objective: The objective of this manuscript is to identify the multiple uses of biomarkers in pharmacovigilance irrespective of the therapeutic area. Design: This is a systematic review of the literature. Data Sources and Methods: Embase and MEDLINE database searches were conducted for literature published between 2010-March 19, 2021. Scientific articles that described the potential use of biomarkers in pharmacovigilance in sufficient detail were reviewed. Papers that did not fulfill the United States Food and Drug Administration (US FDA) definition of a biomarker were excluded, which is based on the International Conference on Harmonisation (ICH)−E16 guidance. Results: Twenty-seven articles were identified for evaluation. Most articles involved predictive biomarkers (41%), followed by safety biomarkers (38%), pharmacodynamic/response biomarkers (14%), and diagnostic biomarkers (7%). Some articles described biomarkers that applied to multiple categories. Conclusion: Various categories of biomarkers including safety, predictive, pharmacodynamic/response, and diagnostic biomarkers are being investigated for potential use in pharmacovigilance. The most frequent potential uses of biomarkers in pharmacovigilance in the literature were the prediction of the severity of an ADR, mortality, response, safety, and toxicity. The safety biomarkers identified were used to evaluate patient safety during dose escalation, identify patients who may benefit from further biomarker testing during treatment, and monitor ADRs.
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Vrba, Lukas, and Bernard W. Futscher. "DNA methylation changes in biomarker loci occur early in cancer progression." F1000Research 8 (December 16, 2019): 2106. http://dx.doi.org/10.12688/f1000research.21584.1.
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Tumor-specific DNA methylation can be used for cancer diagnostics and monitoring. We have recently reported a set of DNA methylation biomarkers that can distinguish plasma samples from lung cancer patients versus healthy controls with high sensitivity and specificity. Furthermore, the DNA methylation signal from the biomarker loci detected in plasma samples correlated with tumor size and decreased after surgical resection of lung tumors. In order to determine the timing of DNA methylation of these loci during carcinogenesis and thus the potential of the biomarkers to detect early stages of the disease we analyzed the DNA methylation of the biomarker loci in five precancerous conditions using available data from the GEO database. We found that the DNA methylation of the biomarker loci is gained early in carcinogenesis since most of the precancerous conditions already have biomarker loci hypermethylated. Moreover, these DNA methylation biomarkers are able to distinguish between precancerous lesions with malignant potential and those that stay benign where data is available. Taken together, the biomarkers have the potential to detect the earliest cancer stages; the only limitation to detection of cancer from plasma samples or other liquid biopsies is the timing when tumors start to shed enough DNA into body fluids.
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Vrba, Lukas, and Bernard W. Futscher. "DNA methylation changes in biomarker loci occur early in cancer progression." F1000Research 8 (February 14, 2020): 2106. http://dx.doi.org/10.12688/f1000research.21584.2.
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Tumor-specific DNA methylation can be used for cancer diagnostics and monitoring. We have recently reported a set of DNA methylation biomarkers that can distinguish plasma samples from lung cancer patients versus healthy controls with high sensitivity and specificity. Furthermore, the DNA methylation signal from the biomarker loci detected in plasma samples correlated with tumor size and decreased after surgical resection of lung tumors. In order to determine the timing of DNA methylation of these loci during carcinogenesis and thus the potential of the biomarkers to detect early stages of the disease we analyzed the DNA methylation of the biomarker loci in five precancerous conditions using available data from the GEO database. We found that the DNA methylation of the biomarker loci is gained early in carcinogenesis since most of the precancerous conditions already have biomarker loci hypermethylated. Moreover, these DNA methylation biomarkers are able to distinguish between precancerous lesions with malignant potential and those that stay benign where data is available. Taken together, the biomarkers have the potential to detect the earliest cancer stages; the only limitation to detection of cancer from plasma samples or other liquid biopsies is the timing when tumors start to shed enough DNA into body fluids.
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Wallace, Robert G., Laura C. Twomey, Marc-Antoine Custaud, Niall Moyna, Philip M. Cummins, Marco Mangone, and Ronan P. Murphy. "Potential Diagnostic and Prognostic Biomarkers of Epigenetic Drift within the Cardiovascular Compartment." BioMed Research International 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/2465763.
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Biomarkers encompass a wide range of different measurable indicators, representing a tangible link to physiological changes occurring within the body. Accessibility, sensitivity, and specificity are significant factors in biomarker suitability. New biomarkers continue to be discovered, and questions over appropriate selection and assessment of their usefulness remain. If traditional markers of inflammation are not sufficiently robust in their specificity, then perhaps alternative means of detection may provide more information. Epigenetic drift (epigenetic modifications as they occur as a direct function with age), and its ancillary elements, including platelets, secreted microvesicles (MVs), and microRNA (miRNA), may hold enormous predictive potential. The majority of epigenetic drift observed in blood is independent of variations in blood cell composition, addressing concerns affecting traditional blood-based biomarker efficacy. MVs are found in plasma and other biological fluids in healthy individuals. Altered MV/miRNA profiles may also be found in individuals with various diseases. Platelets are also highly reflective of physiological and lifestyle changes, making them extremely sensitive biomarkers of human health. Platelets release increased levels of MVs in response to various stimuli and under a plethora of disease states, which demonstrate a functional effect on other cell types.
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Zhang, Zhen, Dai Zhang, Yaping Cui, Yongsheng Qiu, Changhong Miao, and Xihua Lu. "Identification of microRNA-451a as a Novel Circulating Biomarker for Colorectal Cancer Diagnosis." BioMed Research International 2020 (August 27, 2020): 1–18. http://dx.doi.org/10.1155/2020/5236236.
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Background. Colorectal cancer (CRC) is one of the leading causes of cancer death worldwide. Successful treatment of CRC relies on accurate early diagnosis, which is currently a challenge due to its complexity and personalized pathologies. Thus, novel molecular biomarkers are needed for early CRC detection. Methods. Gene and microRNA microarray profiling of CRC tissues and miRNA-seq data were analyzed. Candidate microRNA biomarkers were predicted using both CRC-specific network and miRNA-BD tool. Validation analyses were carried out to interrogate the identified candidate CRC biomarkers. Results. We identified miR-451a as a potential early CRC biomarker circulating in patient’s serum. The dysregulation of miR-451a was revealed both in primary tumors and in patients’ sera. Downstream analysis validated the tumor suppressor role of miR-451a and high sensitivity of miR-451a in CRC patients, further confirming its potential role as CRC circulation biomarker. Conclusion. The miR-451a is a potential circulating biomarker for early CRC diagnosis.
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Bieniaś, Beata, and Przemysław Sikora. "Potential Novel Biomarkers of Obstructive Nephropathy in Children with Hydronephrosis." Disease Markers 2018 (September 13, 2018): 1–9. http://dx.doi.org/10.1155/2018/1015726.
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Obstructive nephropathy (ON) secondary to the congenital hydronephrosis (HN) is one of the most common causes of chronic kidney disease in children. Neither currently used imaging techniques nor conventional laboratory parameters are sufficient to assess the onset and outcome of this condition; hence, there is a need to prove the usefulness of newly discovered biomarkers of kidney injury in this respect. The purpose of the study was to assess the urinary excretion of alpha-GST, pi-GST, NGAL, and KIM-1 and the serum level of NGAL in children with congenital unilateral hydronephrosis secondary to ureteropelvic junction obstruction. The results were evaluated in relation to severity of HN, the presence of ON, relative function of an obstructed kidney, and the presence of proteinuria. The study comprised 45 children with HN of different grades and 21 healthy controls. Urinary and serum concentrations of biomarkers were measured using specific ELISA kits. Urinary biomarker excretions were expressed as a biomarker/creatinine (Cr) ratio. Patients with the highest grades of HN showed significantly increased values of all measured biomarkers, whereas those with the lowest grades of HN displayed only significant elevation of urinary alpha-GST and the serum NGAL. Urinary NGAL positively correlated with percentage loss of relative function of an obstructed kidney in renal scintigraphy. In patients with proteinuria, significantly higher urinary alpha-GST excretion was revealed as compared to those without this symptom. The ROC curve analysis showed the best diagnostic profile for urinary alpha-GST/Cr and NGAL/Cr ratios in the detection of ON. In conclusion, the results of the study showed that urinary alpha-GST and NGAL are promising biomarkers of ON. Ambiguous results of the remaining biomarkers, i.e., urinary pi-GST and KIM-1, and serum NGAL level may be related to a relatively small study group. Their utility in an early diagnosis of ON should be reevaluated.
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Sims, Tasha Nicholle, Bo Gao, Robert Phillips, and Israel Lowy. "Potential predictive and prognostic biomarkers identified in baseline plasma samples from the VELOUR trial." Journal of Clinical Oncology 33, no. 3_suppl (January 20, 2015): 638. http://dx.doi.org/10.1200/jco.2015.33.3_suppl.638.
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638 Background: Biomarkers of resistance or susceptibility to vascular endothelial growth factor (VEGF) inhibition have not been validated. Ziv-aflibercept (ZALTRAP), a fusion protein that binds and neutralizes ligands of VEGFR1 and VEGFR2 (e.g., VEGFA, PLGF, and VEGFB), is approved for the treatment of metastatic colorectal cancer (mCRC) in combination with FOLFIRI in patients who have progressed after oxaliplatin therapy. We are currently analyzing plasma samples from VELOUR, the registration trial of FOLFIRI +/- ziv-aflibercept, in an effort to identify prognostic and predictive factors. Methods: VELOUR was a prospective, multicenter, multinational, randomized (1:1), double-blind, parallel-arm phase III study conducted in 1,226 patients. Retrospective analysis of circulating proteins from 553 baseline plasma samples was performed. Samples were analyzed for levels of 98 analytes using multiplex assays and ELISA. Biomarker values were dichotomized around the median value and analyzed with respect to overall survival (OS). Results: The biomarker study sub-population was similar to the overall VELOUR population. For OS, the hazard ratio (HR) was 0.809 in the plasma biomarker population vs. HR =0.817 in the overall VELOUR population. For PFS, the HR = 0.752 in the plasma biomarker population vs. HR = 0.758 in VELOUR. Patient demographics, including ECOG status, were similar between the groups. Several biomarkers were identified as potentially predictive or prognostic (or both) of OS, with a HR<0.7 (false discovery rate of 0.05 and interaction p < 0.10). No biomarker subset corresponded to worse OS with ziv-aflibercept treatment. Conclusions: Multiple potential prognostic and predictive biomarkers were identified in VELOUR and will be presented. These results are exploratory and require prospective studies for validation. Patient subsets with elevated expression of alternative angiogenic factors or increased pro-inflammatory markers may correlate with poor outcome overall, and in some cases are not improved by addition of ziv-aflibercept treatment. Further investigation of this dataset continues, including analysis of on-treatment plasma samples in a subset of patients.
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De Jesus, J. R., and Marco Arruda. "Human disease biomarkers: challenges, advances, and trends in their validation." Journal of Integrated OMICS 11, no. 2 (December 29, 2021): 16–28. http://dx.doi.org/10.5584/jiomics.v11i2.207.
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Biomarkers are important tools in the medical field, once they allow better prediction, characterization, and treatment of diseases. In this scenario, it is essential that biomarkers are highly accurate. Thus, biomarker validation is an essential part of ensuring the effectiveness of a biomarker. Validation of biomarkers is the process by which biomarkers are evaluated for accuracy and consistency, as well as their ability to inform the condition of health or disease. Although, there is no unique measure that can be used to determine the validity for all biomarkers, there are general criteria that all biomarkers must meet to be useful. In this work, we review the definition of biomarkers and discuss the validity components. We then critically discuss the main methods used to validate biomarkers and consider some examples of biomarkers of the diseases which most killer in the world (cardiovascular diseases, cancer, and viral infections), highlighting the potential biochemical pathways of these biomarkers in the biological system. In addition, we also comment on the omic strategies used in the biomarker discovery process and conclude with information about perspectives in biomarker validation through imaging techniques.
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Lineham, B., A. Altaie, P. Harwood, D. McGonagle, H. Pandit, and E. Jones. "A SYSTEMATIC REVIEW OF THE POTENTIAL VALUE OF SYNOVIAL FLUID BIOMARKERS TO PREDICT CLINICAL OUTCOMES IN CARTILAGE REPAIR TREATMENTS." Orthopaedic Proceedings 105-B, SUPP_8 (April 11, 2023): 144. http://dx.doi.org/10.1302/1358-992x.2023.8.144.
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Multiple biochemical biomarkers have been previously investigated for the diagnosis, prognosis and response to treatment of articular cartilage damage, including osteoarthritis (OA). Synovial fluid (SF) biomarker measurement is a potential method to predict treatment response and effectiveness. However, the significance of different biomarkers and their correlation to clinical outcomes remains unclear. This systematic review evaluated current SF biomarkers used in investigation of cartilage degeneration or regeneration in the knee joint and correlated these biomarkers with clinical outcomes following cartilage repair or regeneration interventions.PubMed, Institute of Science Index, Scopus, Cochrane Central Register of Controlled Trials, and Embase databases were searched. Studies evaluating SF biomarkers and clinical outcomes following cartilage repair intervention were included. Two researchers independently performed data extraction and QUADAS-2 analysis. Biomarker inclusion, change following intervention and correlation with clinical outcome was compared.9 studies were included. Study heterogeneity precluded meta-analysis. There was significant variation in sampling and analysis. 33 biomarkers were evaluated in addition to microRNA and catabolic/anabolic ratios. Five studies reported on correlation of biomarkers with six biomarkers significantly correlated with clinical outcomes following intervention. However, correlation was only demonstrated in isolated studies.This review demonstrates significant difficulties in drawing conclusions regarding the importance of SF biomarkers based on the available literature. Improved standardisation for collection and analysis of SF samples is required. Future publications should also focus on clinical outcome scores and seek to correlate biomarkers with progression to further understand the significance of identified markers in a clinical context.
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Zhang, Xueli, Hong Zhang, Chuanwen Fan, Camilla Hildesjö, Bairong Shen, and Xiao-Feng Sun. "Loss of CHGA Protein as a Potential Biomarker for Colon Cancer Diagnosis: A Study on Biomarker Discovery by Machine Learning and Confirmation by Immunohistochemistry in Colorectal Cancer Tissue Microarrays." Cancers 14, no. 11 (May 27, 2022): 2664. http://dx.doi.org/10.3390/cancers14112664.
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Background. The incidence of colorectal cancers has been constantly increasing. Although the mortality has slightly decreased, it is far from satisfaction. Precise early diagnosis for colorectal cancer has been a great challenge in order to improve patient survival. Patients and Methods. We started with searching for protein biomarkers based on our colorectal cancer biomarker database (CBD), finding differential expressed genes (GEGs) and non-DEGs from RNA sequencing (RNA-seq) data, and further predicted new biomarkers of protein–protein interaction (PPI) networks by machine learning (ML) methods. The best-selected biomarker was further verified by a receiver operating characteristic (ROC) test from microarray and RNA-seq data, biological network, and functional analysis, and immunohistochemistry in the tissue arrays from 198 specimens. Results. There were twelve proteins (MYO5A, CHGA, MAPK13, VDAC1, CCNA2, YWHAZ, CDK5, GNB3, CAMK2G, MAPK10, SDC2, and ADCY5) which were predicted by ML as colon cancer candidate diagnosis biomarkers. These predicted biomarkers showed close relationships with reported biomarkers of the PPI network and shared some pathways. An ROC test showed the CHGA protein with the best diagnostic accuracy (AUC = 0.9 in microarray data and 0.995 in RNA-seq data) among these candidate protein biomarkers. Furthermore, immunohistochemistry examination on our colon cancer tissue microarray samples further confirmed our bioinformatical prediction, indicating that CHGA may be used as a potential biomarker for early diagnosis of colon cancer patients. Conclusions. CHGA could be a potential candidate biomarker for diagnosing earlier colon cancer in the patients.
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Xu, Hong, Jinwei Xie, Shaoyun Zhang, Duan Wang, Zeyu Huang, and Zongke Zhou. "Potential Blood Biomarkers for Diagnosing Periprosthetic Joint Infection: A Single-Center, Retrospective Study." Antibiotics 11, no. 4 (April 11, 2022): 505. http://dx.doi.org/10.3390/antibiotics11040505.
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Background: Blood biomarkers are first-line tools for identifying periprosthetic joint infection (PJI). C-reactive protein (CRP) is currently recognized as the standard biomarker for PJI diagnosis. Other recently reported novel biomarkers, including plasma fibrinogen, platelet count, monocyte/lymphocyte ratio (MLR), neutrophil/lymphocyte ratio (NLR), and platelet count/lymphocyte ratio (PLR), have also shown promise in diagnosing PJI. This study aimed to evaluate whether these biomarkers were superior to CRP for identifying PJI. Methods: Patients who underwent revision hip or knee arthroplasty at our hospital from January 2008 to September 2020 were included consecutively and divided into infected and non-infected groups according to the 2013 International Consensus Meeting Criteria. Blood samples were collected preoperatively, and erythrocyte sedimentation rate (ESR), CRP, interleukin-6, fibrinogen, platelet count, MLR, NLR, and PLR were analyzed. The diagnostic values of the tested biomarkers and their combinations were compared with CRP based on the area under the receiver operating characteristic curve (AUC) using the z-test. Classification trees were constructed to explore more accurate combinations of the tested markers for identifying PJI. Results: A total of 543 patients were included, of whom 245 had PJI. Among the tested biomarkers, CRP with a cutoff of 7.39 mg/L showed the highest AUC, which gave a sensitivity of 79.1% and specificity of 86.0%. The AUCs of pairwise combinations of tested markers including CRP also were inferior to CRP itself, as were combinations derived from classification trees. Conclusions: Preoperative serum CRP with a low cutoff may be the best reliable blood biomarker for identifying PJI, and those traditional or novel available blood biomarkers could not further improve the diagnostic ability on the basis of CRP.
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Casey, David A. "Event-related Potentials and the Diagnosis of Alzheimer’s Disease— The COGNISION™ System." US Neurology 06, no. 02 (2010): 34. http://dx.doi.org/10.17925/usn.2010.06.02.34.
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Alzheimer’s disease is a major cause of cognitive decline among older people. Current diagnostic approaches rely primarily on cognitive symptoms. Recently proposed changes in the definition of the disease place more emphasis on the use of biomarkers (such as neuroimaging or cerebrospinal fluid markers) in the hope of allowing earlier and more definitive diagnosis for research and, eventually, clinical purposes. Event-related potentials (ERP) represent another promising biomarker approach. Alzheimer’s disease has been demonstrated to have a recognizable ERP signature. Recent advances in ERP technology may make the process painless, non-invasive and portable. These advantages suggest that ERP should be further considered as a potential biomarker for Alzheimer’s disease.
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Jung, Chan-Young, and Tae-Hyun Yoo. "Pathophysiologic Mechanisms and Potential Biomarkers in Diabetic Kidney Disease." Diabetes & Metabolism Journal 46, no. 2 (March 31, 2022): 181–97. http://dx.doi.org/10.4093/dmj.2021.0329.
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Although diabetic kidney disease (DKD) remains the leading cause of end-stage kidney disease eventually requiring chronic kidney replacement therapy, the prevalence of DKD has failed to decline over the past 30 years. In order to reduce disease prevalence, extensive research has been ongoing to improve prediction of DKD onset and progression. Although the most commonly used markers of DKD are albuminuria and estimated glomerular filtration rate, their limitations have encouraged researchers to search for novel biomarkers that could improve risk stratification. Considering that DKD is a complex disease process that involves several pathophysiologic mechanisms such as hyperglycemia induced inflammation, oxidative stress, tubular damage, eventually leading to kidney damage and fibrosis, many novel biomarkers that capture one specific mechanism of the disease have been developed. Moreover, the increasing use of high-throughput omic approaches to analyze biological samples that include proteomics, metabolomics, and transcriptomics has emerged as a strong tool in biomarker discovery. This review will first describe recent advances in the understanding of the pathophysiology of DKD, and second, describe the current clinical biomarkers for DKD, as well as the current status of multiple potential novel biomarkers with respect to protein biomarkers, proteomics, metabolomics, and transcriptomics.
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Li, Zhuoyuan, Hua Lin, Qi Zhang, Rong Shi, Huanyu Xu, Fan Yang, Xueyan Jiang, Luyao Wang, Ying Han, and Jiehui Jiang. "Individual Proportion Loss of Functional Connectivity Strength: A Novel Individual Functional Connectivity Biomarker for Subjective Cognitive Decline Populations." Biology 12, no. 4 (April 7, 2023): 564. http://dx.doi.org/10.3390/biology12040564.
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High individual variation in the subjective cognitive decline (SCD) population makes functional connectivity (FC) biomarkers unstable. This study proposed a novel individual FC index, named individual proportion loss of functional connectivity strength (IPLFCS), and explored potential biomarkers for SCD using this new index. We proposed an IPLFCS analysis framework and compared it with traditional FC in Chinese and Western cohorts. Post hoc tests were used to determine biomarkers. Pearson’s correlation analysis was used to investigate the correlation between neuropsychological scores or cortical amyloid deposits and IPLFCS biomarkers. Receiver operating characteristic curves were utilized to evaluate the ability of potential biomarkers to distinguish between groups. IPLFCS of the left middle temporal gyrus (LMTG) was identified as a potential biomarker. The IPLFC was correlated with the traditional FC (r = 0.956, p < 0.001; r = 0.946, p < 0.001) and cortical amyloid deposition (r = −0.245, p = 0.029; r = −0.185, p = 0.048) in both cohorts. Furthermore, the IPLFCS decreased across the Alzheimer’s disease (AD) continuum. Its diagnostic efficiency was superior to that of existing fMRI biomarkers. These findings suggest that IPLFCS of the LMTG could be a potential biomarker of SCD.
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Chai, Hwa Chia, and Kek Heng Chua. "The Potential Use of Volatile Biomarkers for Malaria Diagnosis." Diagnostics 11, no. 12 (November 30, 2021): 2244. http://dx.doi.org/10.3390/diagnostics11122244.
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Pathogens may change the odor and odor-related biting behavior of the vector and host to enhance pathogen transmission. In recent years, volatile biomarker investigations have emerged to identify odors that are differentially and specifically released by pathogens and plants, or the pathogen-infected or even cancer patients. Several studies have reported odors or volatile biomarkers specifically detected from the breath and skin of malaria-infected individuals. This review will discuss the potential use of these odors or volatile biomarkers for the diagnosis of malaria. This approach not only allows for the non-invasive mean of sample collection but also opens up the opportunity to develop a biosensor for malaria diagnosis in low-resource settings.
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Liu, Yan-Yan, Zhong-Xian Yang, Li-Min Ma, Xu-Qing Wen, Huan-Lin Ji, and Ke Li. "1H-NMR spectroscopy identifies potential biomarkers in serum metabolomic signatures for early stage esophageal squamous cell carcinoma." PeerJ 7 (November 29, 2019): e8151. http://dx.doi.org/10.7717/peerj.8151.
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Background Esophageal squamous cell carcinoma (ESCC) is one of the most prevalent types of upper gastrointestinal malignancies. Here, we used 1H nuclear magnetic resonance spectroscopy (1H-NMR) to identify potential serum biomarkers in patients with early stage ESCC. Methods Sixty-five serum samples from early stage ESCC patients (n = 25) and healthy controls (n = 40) were analysed using 1H-NMR spectroscopy. We distinguished between different metabolites through principal component analysis, partial least squares-discriminant analysis, and orthogonal partial least squares-discriminant analysis (OPLS-DA) using SIMCA-P+ version 14.0 software. Receiver operating characteristic (ROC) analysis was conducted to verify potential biomarkers. Results Using OPLS-DA, 31 altered serum metabolites were successfully identified between the groups. Based on the area under the ROC curve (AUROC), and the biomarker panel with AUROC of 0.969, six serum metabolites (α-glucose, choline, glutamine, glutamate, valine, and dihydrothymine) were selected as potential biomarkers for early stage ESCC. Dihydrothymine particularly was selected as a new feasible biomarker associated with tumor occurrence. Conclusions 1H-NMR spectroscopy may be a useful tumour detection approach in identifying useful metabolic ESCC biomarkers for early diagnosis and in the exploration of the molecular pathogenesis of ESCC.
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Fathi, Parinaz, Maria Karkanitsa, Adam Rupert, Emily Ricotta, Irini Sereti, and Kaitlyn Sadtler. "Identifying immune biomarkers associated with human trauma as potential therapeutic targets." Journal of Immunology 210, no. 1_Supplement (May 1, 2023): 229.19. http://dx.doi.org/10.4049/jimmunol.210.supp.229.19.
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Abstract Severe trauma can induce systemic immunosuppression, which makes understanding the biomarker profiles of trauma patients critical for therapeutic development and for predicting potential immune responses to treatments such as biomedical implants. Our goal was to establish a data set containing levels of a large array of biomarkers measured in blood from human trauma patients. Multiplex electrochemiluminescence assays were conducted to measure the levels of 59 biomarkers in 1000 blood samples collected from patients at the time of admission to trauma centers. Injury types were categorized as motor vehicle crashes (n=448), falls (n=221), gun wounds (n=78), stabbings (n=117), or other traumatic injuries. Patients ranged in age from 18 to 101, with a mean age of 42.7 for male patients (n= 725) and 49.8 for female patients (n= 272). There were no significant differences in biomarker expression levels between the different injury types. Differences in age distributions of male and female patients for each injury type were not found to be statistically significant, except in the case of falls, which had a higher average age for female patients compared to male patients. MIF, MIP-5, and YKL-40 had the highest expression, with concentrations of 554148 ± 62938 pg/mL, 17409 ± 919 pg/mL, and 98793 ± 10015 pg/mL (mean ± 95 % CI) respectively, at 1:100 dilution. Further experiments are currently being conducted to establish biomarker profiles for control uninjured human samples, and data comparing the profiles of trauma patients and uninjured controls will be presented. Overall, this work provides a resource for understanding immune responses to injury and potentially developing new therapeutics with these biomarker profiles in mind. This work was supported by the National Institute of Biomedical Imaging and Bioengineering
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Nafar, Mohsen, Shiva Samavat, Nooshin Dalili, Shiva Kalantari, Leonard Foster, Kyung-Mee Moon, and Somaye-Sadat Heidari. "Identification of Potential Predictive and Diagnostic Urinary Biomarkers for Acute Rejection in Renal Transplant Recipients: A Proteomics Study." OBM Transplantation 07, no. 03 (July 7, 2023): 1–33. http://dx.doi.org/10.21926/obm.transplant.2303191.
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Acute rejection (AR) is one of the main predictors of long-term survival of allograft. The development of noninvasive diagnostic biomarkers of AR is an unmet need for the timely detection. This study aimed to identify novel detective biomarkers of AR by analyzing the urine proteome profile of transplant patients. Forty-two transplant patients including 30 biopsy-proven AR patients (including antibody and T-cell mediated rejection) and 12 transplant patients with stable renal function (control group) were enrolled. Label-free quantification (LFQ) proteomics technique was performed on urine samples. Multivariate statistical analysis was applied for biomarker identification. The ELISA method validated EGF (epidermal growth factor) from the top 10 candidate biomarkers in an independent cohort. Gene ontology and possible pathways were also analyzed. LFQ analysis revealed 453 identified proteins differentially expressed between groups that mainly participated in complement and coagulation pathways and proteolysis. Ten proteins with the highest AUCs (Area under the ROC Curve) were identified as candidate diagnostic biomarkers. Candidate biomarkers were mainly associated with extracellular matrix (ECM) degradation and epithelial-to-mesenchymal transition (EMT). Reduction of urinary EGF measured by ELISA in an independent group confirmed proteomics results. We introduced a unique set of diagnostic urinary biomarkers for AR. Interactions of biomarkers and validation of EGF among biomarker panels revealed that ECM remodeling and EMT might be the consequence of immunological processes in AR. If validated as a panel, the mentioned biomarkers might shed light on the pathogenesis of chronic injury after AR and point out the potential treatment strategies.