Biomarker InsightsPub Date : 2020-10-19eCollection Date: 2020-01-01DOI: 10.1177/1177271920965522
Lise A Matzke, Peter H Watson
{"title":"Biobanking for Cancer Biomarker Research: Issues and Solutions.","authors":"Lise A Matzke, Peter H Watson","doi":"10.1177/1177271920965522","DOIUrl":"10.1177/1177271920965522","url":null,"abstract":"Biomarkers are critical tools that underpin precision medicine. However there has been slow progress and frequent failure of biomarker development. The root causes are multifactorial. Here, we focus on the need for fast, efficient, and reliable access to quality biospecimens as a critical area that impacts biomarker development. We discuss the past history of biobanking and the evolution of biobanking processes relevant to the specific area of cancer biomarker development as an example, and describe some solutions that can improve this area, thus potentially accelerating biomarker research.","PeriodicalId":47060,"journal":{"name":"Biomarker Insights","volume":"15 ","pages":"1177271920965522"},"PeriodicalIF":3.8,"publicationDate":"2020-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1177271920965522","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38709151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Biomarker InsightsPub Date : 2020-10-12eCollection Date: 2020-01-01DOI: 10.1177/1177271920964108
David Bradley
{"title":"Clusterin as a Potential Biomarker of Obesity-Related Alzheimer's Disease Risk.","authors":"David Bradley","doi":"10.1177/1177271920964108","DOIUrl":"https://doi.org/10.1177/1177271920964108","url":null,"abstract":"<p><p>Over 35% of the adult US population is obese. In turn, excess adiposity increases the risk of multiple complications including type 2 diabetes (T2D), insulin resistance, and cardiovascular disease; yet, obesity also independently heightens risk of Alzheimer's Disease (AD), even after adjusting for other important confounding risk factors including blood pressure, sociodemographics, cholesterol levels, smoking status, and Apolipoprotein E (ApoE) genotype. Among patients over the age of 65 with dementia, 37% have coexisting diabetes, and an estimated 7.3% of cases of AD are directly attributable to midlife obesity. Clusterin, also known as apolipoprotein J (ApoJ), is a multifunctional glycoprotein that acts as a molecular chaperone, assisting folding of secreted proteins. Clusterin has been implicated in several physiological and pathological states, including AD, metabolic disease, and cardiovascular disease. Despite long-standing interest in elucidating clusterin's relationship with amyloid beta (Aβ) aggregation/clearance and toxicity, significant knowledge gaps still exist. Altered clusterin expression and protein levels have been linked with cognitive and memory function, disrupted central nervous system lipid flux, as well as pathogenic brain structure; and its role in cardiometabolic disease suggests that it may be a link between insulin resistance, dyslipidemia, and AD. Here, we briefly highlight clusterin's relevance to AD by presenting existing evidence linking clusterin to AD and cardiometabolic disease, and discussing its potential utility as a biomarker for AD in the presence of obesity-related metabolic disease.</p>","PeriodicalId":47060,"journal":{"name":"Biomarker Insights","volume":"15 ","pages":"1177271920964108"},"PeriodicalIF":3.8,"publicationDate":"2020-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1177271920964108","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38629754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Unraveling Pathophysiological Mechanisms of Parkinson's Disease: Contribution of CSF Biomarkers.","authors":"Lucia Farotti, Federico Paolini Paoletti, Simone Simoni, Lucilla Parnetti","doi":"10.1177/1177271920964077","DOIUrl":"https://doi.org/10.1177/1177271920964077","url":null,"abstract":"<p><p>Diagnosis of Parkinson's disease (PD) relies on clinical history and physical examination, but misdiagnosis is common in early stages. Identification of biomarkers for PD may allow for early and more precise diagnosis and provide information about prognosis. Developments in analytical chemistry allow for the detection of a large number of molecules in cerebrospinal fluid (CSF), which are known to be associated with the pathogenesis of PD. Given the pathophysiology of PD, CSF α-synuclein species have the strongest rationale for use, also providing encouraging preliminary results in terms of early diagnosis. In the field of classical Alzheimer's disease (AD) biomarkers, low CSF Aβ<sub>42</sub> levels have shown a robust prognostic value in terms of development of cognitive impairment. Other CSF biomarkers including lysosomal enzymes, neurofilament light chain, markers of neuroinflammation and oxidative stress, although promising, have not proved to be reliable for diagnostic and prognostic purposes yet. Overall, the implementation of CSF biomarkers may give a substantial contribution to the optimal use of disease-modifying drugs.</p>","PeriodicalId":47060,"journal":{"name":"Biomarker Insights","volume":"15 ","pages":"1177271920964077"},"PeriodicalIF":3.8,"publicationDate":"2020-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1177271920964077","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38629753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Biomarker InsightsPub Date : 2020-09-16eCollection Date: 2020-01-01DOI: 10.1177/1177271920958704
Deborah Jo Levine, David J Ross, Edward Sako
{"title":"Single Center \"Snapshot\" Experience With Donor-Derived Cell-Free DNA After Lung Transplantation.","authors":"Deborah Jo Levine, David J Ross, Edward Sako","doi":"10.1177/1177271920958704","DOIUrl":"10.1177/1177271920958704","url":null,"abstract":"","PeriodicalId":47060,"journal":{"name":"Biomarker Insights","volume":"15 ","pages":"1177271920958704"},"PeriodicalIF":3.8,"publicationDate":"2020-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/69/06/10.1177_1177271920958704.PMC7498978.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38424744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Biomarker InsightsPub Date : 2020-09-09eCollection Date: 2020-01-01DOI: 10.1177/1177271920954828
Ignacio I Álvarez-Rodríguez, Eduardo Castaño-Tostado, David G García-Gutiérrez, Rosalía Reynoso-Camacho, Juana E Elton-Puente, Alicia Barajas-Pozos, Iza F Pérez-Ramírez
{"title":"Non-Targeted Metabolomic Analysis Reveals Serum Phospholipid Alterations in Patients with Early Stages of Diabetic Foot Ulcer.","authors":"Ignacio I Álvarez-Rodríguez, Eduardo Castaño-Tostado, David G García-Gutiérrez, Rosalía Reynoso-Camacho, Juana E Elton-Puente, Alicia Barajas-Pozos, Iza F Pérez-Ramírez","doi":"10.1177/1177271920954828","DOIUrl":"https://doi.org/10.1177/1177271920954828","url":null,"abstract":"<p><p>Diabetic foot ulcer (DFU) is a common complication of type 2 diabetes mellitus (T2DM) characterized by ulcer formation, which can lead to the amputation of lower extremities. However, the metabolic alterations related to this complication are not completely elucidated. Therefore, we carried out a metabolomic analysis of serum samples obtained from T2DM adult patients diagnosed with diabetic foot ulcer in a cross-sectional, observational, and comparative study. Eighty-four volunteers were classified into the following groups: without T2DM (control group, n = 30) and with T2DM and different stages of diabetic foot ulcer according to Wagner-Meggitt classification system: DFU G0 (n = 11), DFU G1 (n = 14), DFU G2 (n = 16), and DFU G3 (n = 13). The non-target metabolomic profile followed by chemometric analysis revealed that lysophosphatidylethanolamine (16:1) could be proposed as key metabolite related to the onset of diabetic foot ulcer; however, this phospholipid was not affected by diabetic foot ulcer progression. Therefore, further studies are necessary to validate these phospholipids as biomarker candidates for the early diagnosis of diabetic foot ulcer in T2DM patients.</p>","PeriodicalId":47060,"journal":{"name":"Biomarker Insights","volume":"15 ","pages":"1177271920954828"},"PeriodicalIF":3.8,"publicationDate":"2020-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1177271920954828","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38496160","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Biomarker InsightsPub Date : 2020-08-21eCollection Date: 2020-01-01DOI: 10.1177/1177271920950319
Elena Camporesi, Johanna Nilsson, Ann Brinkmalm, Bruno Becker, Nicholas J Ashton, Kaj Blennow, Henrik Zetterberg
{"title":"Fluid Biomarkers for Synaptic Dysfunction and Loss.","authors":"Elena Camporesi, Johanna Nilsson, Ann Brinkmalm, Bruno Becker, Nicholas J Ashton, Kaj Blennow, Henrik Zetterberg","doi":"10.1177/1177271920950319","DOIUrl":"10.1177/1177271920950319","url":null,"abstract":"Synapses are the site for brain communication where information is transmitted between neurons and stored for memory formation. Synaptic degeneration is a global and early pathogenic event in neurodegenerative disorders with reduced levels of pre- and postsynaptic proteins being recognized as a core feature of Alzheimer’s disease (AD) pathophysiology. Together with AD, other neurodegenerative and neurodevelopmental disorders show altered synaptic homeostasis as an important pathogenic event, and due to that, they are commonly referred to as synaptopathies. The exact mechanisms of synapse dysfunction in the different diseases are not well understood and their study would help understanding the pathogenic role of synaptic degeneration, as well as differences and commonalities among them and highlight candidate synaptic biomarkers for specific disorders. The assessment of synaptic proteins in cerebrospinal fluid (CSF), which can reflect synaptic dysfunction in patients with cognitive disorders, is a keen area of interest. Substantial research efforts are now directed toward the investigation of CSF synaptic pathology to improve the diagnosis of neurodegenerative disorders at an early stage as well as to monitor clinical progression. In this review, we will first summarize the pathological events that lead to synapse loss and then discuss the available data on established (eg, neurogranin, SNAP-25, synaptotagmin-1, GAP-43, and α-syn) and emerging (eg, synaptic vesicle glycoprotein 2A and neuronal pentraxins) CSF biomarkers for synapse dysfunction, while highlighting possible utilities, disease specificity, and technical challenges for their detection.","PeriodicalId":47060,"journal":{"name":"Biomarker Insights","volume":"15 ","pages":"1177271920950319"},"PeriodicalIF":3.8,"publicationDate":"2020-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1177271920950319","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38368135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Biomarker InsightsPub Date : 2020-08-04eCollection Date: 2020-01-01DOI: 10.1177/1177271920946715
Stuart G Baker, Barnett S Kramer
{"title":"Simple Methods for Evaluating 4 Types of Biomarkers: Surrogate Endpoint, Prognostic, Predictive, and Cancer Screening.","authors":"Stuart G Baker, Barnett S Kramer","doi":"10.1177/1177271920946715","DOIUrl":"https://doi.org/10.1177/1177271920946715","url":null,"abstract":"<p><p>We review simple methods for evaluating 4 types of biomarkers. First, we discuss the evaluation of surrogate endpoint biomarkers (to shorten a randomized trial) using 2 statistical and 3 biological criteria. Second, we discuss the evaluation of prognostic biomarkers (to predict the risk of disease) by comparing data collection costs with the anticipated net benefit of risk prediction. Third, we discuss the evaluation of predictive markers (to search for a promising subgroup in a randomized trial) using a multivariate subpopulation treatment effect pattern plot involving a risk difference or responders-only benefit function. Fourth, we discuss the evaluation of cancer screening biomarkers (to predict cancer in asymptomatic persons) using methodology to substantially reduce the sample size with stored specimens.</p>","PeriodicalId":47060,"journal":{"name":"Biomarker Insights","volume":"15 ","pages":"1177271920946715"},"PeriodicalIF":3.8,"publicationDate":"2020-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1177271920946715","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38294326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Interleukin-31 and Chronic Pruritus of Unknown Origin.","authors":"Kanin Salao, Kittisak Sawanyawisuth, Kengkart Winaikosol, Charoen Choonhakarn, Suteeraporn Chaowattanapanit","doi":"10.1177/1177271920940712","DOIUrl":"https://doi.org/10.1177/1177271920940712","url":null,"abstract":"<p><p>Chronic pruritus of unknown origin (CPUO) is a refractory condition. The expression of Interleukin-31 (IL-31), a major pruritogenic cytokine, in CPUO patients has not been investigated. This study aimed to investigate the potential association of IL-31 with CPUO. This was a cross-sectional, analytical study. Patients diagnosed with CPUO and healthy subjects were included at a ratio of 1:2. Serum IL-31 levels were measured in both groups and compared. There were 10 CPUO and 20 healthy subjects who participated in this study. The median IL-31 level in the CPUO group was significantly higher than in the healthy group (127.3 vs 34.4 pg/mL; <i>P</i> < .001). The presence of CPUO was independently associated with IL-31 levels with a coefficient of 89.678 (<i>P</i> < .001). The serum IL-31 cutoff point for CPUO was 56.8 pg/mL, with an area under the receiver operating characteristic curve (ROC) of 100%. Chronic pruritus of unknown origin was significantly and independently associated with higher IL-31 levels. Further clinical trials of IL-31-related treatment may be justified in CPUO patients.</p>","PeriodicalId":47060,"journal":{"name":"Biomarker Insights","volume":"15 ","pages":"1177271920940712"},"PeriodicalIF":3.8,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1177271920940712","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38171845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Biomarker InsightsPub Date : 2020-06-08eCollection Date: 2020-01-01DOI: 10.1177/1177271920929705
Vaibhav Gandhi, Mara H O'Brien, Sumit Yadav
{"title":"High-Quality and High-Yield RNA Extraction Method From Whole Human Saliva.","authors":"Vaibhav Gandhi, Mara H O'Brien, Sumit Yadav","doi":"10.1177/1177271920929705","DOIUrl":"https://doi.org/10.1177/1177271920929705","url":null,"abstract":"<p><strong>Background: </strong>Human saliva has been identified as a novel, practical, and noninvasive source of biomarkers and genetic materials. However, it is equally challenging due to the availability of an abundance of impurities in the form of microbes and other proteinaceous compounds. The objective of this study was to develop a robust, reproducible, and economic method of extracting high-yield and high-quality RNA from whole human saliva.</p><p><strong>Methods: </strong>The modified TRIzol protocol was developed to extract RNA from saliva (n = 14), followed by complementary DNA synthesis and reverse transcription quantitative polymerase chain reaction analyses for the genes encoding <i>IL1B, ALPL, RUNX2</i>, and <i>ACTB.</i> To compare our protocol with the spin column-based method, we used Qiagen Salivary Protect Micro-RNA spin columns (n = 6). To evaluate and compare the yields and quality of extracted RNAs from both methods, we used (1) Experion Bioanalyzer, (2) QuantiFluor RNA dye, and (3) NanoDrop 2000 Spectrometer.</p><p><strong>Results: </strong>With the modified TRIzol lysis protocol, a high yield of total RNA, on average 12.34 μg, from saliva was extracted compared with on average 0.2 μg with a spin column-based method. The average RQI (RNA quality index) with the TRIzol method was 7.86, which is also comparable with that of the spin column-based method (RQI = 7.58). QuantiFluor dye used for RNA quantification showed a 16-fold higher yield of RNA concentration using our TRIzol protocol.</p><p><strong>Conclusions: </strong>Our modified TRIzol protocol is a reproducible method to extract RNA from whole human saliva which can be used for gene expression analysis. This method allows also ensures the quality of RNA required for specific applications such as RNA sequencing.</p>","PeriodicalId":47060,"journal":{"name":"Biomarker Insights","volume":"15 ","pages":"1177271920929705"},"PeriodicalIF":3.8,"publicationDate":"2020-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1177271920929705","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38059630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Biomarker InsightsPub Date : 2020-06-05eCollection Date: 2020-01-01DOI: 10.1177/1177271920928923
Luisa Veiga, Miguel Brito, Carina Silva, José Silva-Nunes
{"title":"Glucose Homeostasis in Obese Women Is Not Associated to Unacylated Ghrelin Plasma Levels.","authors":"Luisa Veiga, Miguel Brito, Carina Silva, José Silva-Nunes","doi":"10.1177/1177271920928923","DOIUrl":"https://doi.org/10.1177/1177271920928923","url":null,"abstract":"<p><strong>Introduction: </strong>Unacylated ghrelin (UAG) is the major form of circulating ghrelin. Initially considered as a nonfunctional peptide, soon after, UAG has been associated to an insulin sensitizing action and to a negative action on energy balance. The aim of this study was to analyze the association between the serum levels of UAG and glucose metabolism parameters in obese women, independently from eventual influence of anthropometrics.</p><p><strong>Methods: </strong>One hundred lean and 254 obese Caucasian women were studied. Each woman was characterized for anthropometrics, fasting glucose, insulin, HbA1c, and UAG. In addition, obese women were subjected to a classic oral glucose tolerance test (oGTT) to assess glucose and insulin at 120 minutes. Insulin resistance was assessed by the homeostasis model assessment (HOMA-IR). Obese women were classified in 3 glycemic status subgroups (normoglycemia, prediabetes, and diabetes) according to HbA1c and to fasting and oGTT glucose values.</p><p><strong>Results: </strong>In comparison with the lean group, significantly lower levels of UAG were observed in obese women. However, no significant difference was observed through obesity classes I to III. UAG levels were not significantly different among glycemic status subgroups and did not show any association with glucose, insulin, HOMA-IR, or HbA1c.</p><p><strong>Conclusions: </strong>Although anthropometry can influence the level of the unacylated form of ghrelin, UAG plasma levels do not associate to glucose homeostasis parameters.</p>","PeriodicalId":47060,"journal":{"name":"Biomarker Insights","volume":"15 ","pages":"1177271920928923"},"PeriodicalIF":3.8,"publicationDate":"2020-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/1177271920928923","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"38059629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}