• BMB Reports
• /
• v.53 no.1
• /
• pp.10-19
• /
• 2020

Alzheimer's disease (AD) is a chronic neurodegenerative disease characterized by the accumulation of amyloid plaques and neurofibrillary tangles in the brain. The AD pathophysiology entails chronic inflammation involving innate immune cells including microglia, astrocytes, and other peripheral blood cells. Inflammatory mediators such as cytokines and complements are also linked to AD pathogenesis. Despite increasing evidence supporting the association between abnormal inflammation and AD, no well-established inflammatory biomarkers are currently available for AD. Since many reports have shown that abnormal inflammation precedes the outbreak of the disease, non-invasive and readily available peripheral inflammatory biomarkers should be considered as possible biomarkers for early diagnosis of AD. In this minireview, we introduce the peripheral biomarker candidates related to abnormal inflammation in AD and discuss their possible molecular mechanisms. Furthermore, we also summarize the current state of inflammatory biomarker research in clinical practice and molecular diagnostics. We believe this review will provide new insights into biomarker candidates for the early diagnosis of AD with systemic relevance to inflammation during AD pathogenesis.

• Genomics & Informatics
• /
• v.14 no.1
• /
• pp.2-11
• /
• 2016

The advances in mass spectrometry-based proteomics technologies have enabled the generation of global proteome data from tissue or body fluid samples collected from a broad spectrum of human diseases. Comparative proteomic analysis of global proteome data identifies and prioritizes the proteins showing altered abundances, called differentially expressed proteins (DEPs), in disease samples, compared to control samples. Protein biomarker candidates that can serve as indicators of disease states are then selected as key molecules among these proteins. Recently, it has been addressed that cellular pathways can provide better indications of disease states than individual molecules and also network analysis of the DEPs enables effective identification of cellular pathways altered in disease conditions and key molecules representing the altered cellular pathways. Accordingly, a number of network-based approaches to identify disease-related pathways and representative molecules of such pathways have been developed. In this review, we summarize analytical platforms for network-based protein biomarker discovery and key components in the platforms.

• Journal of Korea Multimedia Society
• /
• v.23 no.8
• /
• pp.940-952
• /
• 2020

The Alzheimer's disease (AD) is a neurodegenerative disease commonly found in the elderly individuals. It is one of the most common forms of dementia; patients with AD suffer from a degradation of cognitive abilities over time. To correctly diagnose AD, compuated-aided system equipped with automatic classification algorithm is of great importance. In this paper, we propose a novel deep learning based classification algorithm that takes advantage of MRI biomarker images including brain areas of hippocampus and cerebrospinal fluid for the purpose of improving the AD classification performance. In particular, we develop a new approach that effectively applies MRI biomarker patch images as input to 3D Deep Convolution Neural Network. To integrate multiple classification results from multiple biomarker patch images, we proposed the effective confidence score fusion that combine classification scores generated from soft-max layer. Experimental results show that AD classification performance can be considerably enhanced by using our proposed approach. Compared to the conventional AD classification approach relying on entire MRI input, our proposed method can improve AD classification performance of up to 10.57% thanks to using biomarker patch images. Moreover, the proposed method can attain better or comparable AD classification performances, compared to state-of-the-art methods.

• BMB Reports
• /
• v.45 no.6
• /
• pp.323-330
• /
• 2012

The glycome consists of all glycans (or carbohydrates) within a biological system, and modulates a wide range of important biological activities, from protein folding to cellular communications. The mining of the glycome for disease markers represents a new paradigm for biomarker discovery; however, this effort is severely complicated by the vast complexity and structural diversity of glycans. This review summarizes recent developments in analytical technology and methodology as applied to the fields of glycomics and glycoproteomics. Mass spectrometric strategies for glycan compositional profiling are described, as are potential refinements which allow structure-specific profiling. Analytical methods that can discern protein glycosylation at a specific site of modification are also discussed in detail. Biomarker discovery applications are shown at each level of analysis, highlighting the key role that glycoscience can play in helping scientists understand disease biology.

• Tuberculosis and Respiratory Diseases
• /
• v.83 no.3
• /
• pp.185-194
• /
• 2020

Blood eosinophil counts have emerged as a chronic obstructive pulmonary disease (COPD) biomarker that predict the effects of inhaled corticosteroids (ICS) in clinical practice. Post-hoc and prospective analysis of randomized control trials have shown that higher blood eosinophil counts at the start of the study predict a greater response to ICS. COPD patients with frequent exacerbations (2 or more moderate exacerbations/yr) or a history of hospitalization have a greater response to ICS. Ex-smokers also appear to have a greater ICS response. Blood eosinophil counts can be combined with clinical information such as exacerbation history and smoking status to enable a precision medicine approach to the use of ICS. Higher blood eosinophil counts are associated with increased eosinophilic lung inflammation, and other biological features that may contribute to the increased ICS response observed. Emerging data indicates that lower blood eosinophil counts are associated with an increased risk of bacterial infection, suggesting complex relationships between eosinophils, ICS response, and the airway microbiome.

• Journal of Veterinary Clinics
• /
• v.35 no.2
• /
• pp.35-38
• /
• 2018

Recently assessment of suppression of tumorigenicity 2 (ST2) level has become a useful cardiac biomarker in human medicine. This study compared serum ST2 levels and N-terminal pro-B-type natriuretic peptide (NT-proBNP) levels between healthy dogs and dogs with chronic mitral valve disease. Twenty client-owned dogs were investigated. Dogs were divided into normal, asymptomatic, and symptomatic groups. Serum samples were used to measure levels of NT-proBNP and ST2. Samples for NT-proBNP were sent to IDEXX laboratory for analysis while ST2 levels were measured by using a canine interleukin 33 receptor ELISA kit. There was a significant difference in NT-proBNP levels between asymptomatic and symptomatic groups (P < 0.01), and between normal and symptomatic groups (P < 0.01). In contrast, ST2 levels were not relatively different between asymptomatic and symptomatic groups (P > 0.05). There was no significant difference was observed among all groups in ST2 study. The usefulness of measuring NT-proBNP level as a cardiac biomarker in dogs with chronic mitral valve disease was confirmed, but usefulness of the ST2 level was not observed. Further investigations are needed to evaluate the potential usefulness of ST2 level as a cardiac biomarker in canines.

• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.4
• /
• pp.1667-1670
• /
• 2014

Background: Calprotectin in feces seems to be a more sensitive marker for gastrointestinal (GI) cancers than fecal occult blood, but its specificity may be too low for screening average risk populations. This study aims at evaluating the diagnostic value of fecal calprotectin as a screening biomarker for GI malignancies. Materials and Methods: In a case-control study, 100 patients with GI malignancies (50 patients with colorectal cancer and 50 patients with gastric cancer) and 50 controls were recruited in Tabriz Imam Reza and Sina hospitals during a 24-month period. One to two weeks after the last endoscopy/colonoscopy, fecal specimens were collected by the patients and examined by ELISA method for quantitative measurement of calprotectin content. The results were compared between the three groups. Results: The mean fecal calprotectin level was $109.1{\pm}105.3$ (2.3-454.3, median:74), $241.1{\pm}205.2$ (3.4-610.0, median:19.3) and $45.9{\pm}55.1{\mu}g/g$ (1.3-257.1, median:19.3) in gastric cancer, colorectal cancer and control group, respectively, the differences being significant (p<0.001) and remaining after adjustment for age. The optimal cut-off point for fecal calprotectin was ${\geq}75.8{\mu}g/g$ for distinguishing colorectal cancer from normal cases (sensitivity and specificity of 80% and 84%, respectively). This value was ${\geq}41.9{\mu}g/g$ for distinguishing gastric cancer from normal cases (sensitivity and specificity of 62%). Conclusions: Our results revealed that fecal calprotectin might be a useful and non-invasive biomarker for distinguishing colorectal cancer from non-malignant GI conditions. However, due to low sensitivity and specificity, this biomarker may not help physicians distinguishing gastric cancer cases from healthy subjects.

• Journal of Life Science
• /
• v.30 no.12
• /
• pp.1118-1127
• /
• 2020

Alzheimer's disease causes progressive neuronal loss that leads to cognitive disturbances. It is not currently curable, and there is no way to stop its progression. However, since medical treatment for Alzheimer's disease is most effective in the early stages, early detection can provide the best chance for symptom management. Biomarkers for the diagnosis of Alzheimer's disease include amyloid β (Aβ) deposition, pathologic tau, and neurodegeneration. Aβ deposition and phosphorylated tau can be detected by cerebrospinal fluid (CSF) analysis or positron emission tomography (PET). However, CSF sampling is quite invasive, and PET analysis needs specialized and expensive equipment. During the last decades, blood-based biomarker analysis has been studied to develop fast and minimally invasive biomarker analysis method. And one of the remarkable findings is the involvement of platelets as a primary source of Aβ in plasma. Aβ can be transported across the blood - brain barrier, creating an equilibrium of Aβ levels between the brain and blood under normal condition. Interestingly, a number of clinical studies have unequivocally demonstrated that plasma Aβ42/Aβ40 ratios are reduced in mild cognitive impairment and Alzheimer's disease. Together, these recent findings may lead to the development of a fast and minimally invasive early diagnostic approach to Alzheimer's disease. In this review, we summarize recent advances in the biomarkers of Alzheimer's disease, especially the involvement of platelets as a source of peripheral Aβ production and its potential as a blood-based biomarker.

• Biomedical Science Letters
• /
• v.21 no.1
• /
• pp.1-8
• /
• 2015

Alzheimer's disease is a common form of dementia occurring among the elderly population and can be identified by symptoms such as cognition impairments, memory loss and neuronal dysfunction. Alzheimer's disease was found to be caused by the deposition of $\beta$-amyloid plaques and neurofibrillary tangles. In addition, mutation in the APP (Amyloid precursor protein), Presenilin 1 (PSEN1) and Presenilin 2 (PSEN2) genes were also found to contribute to Alzheimer's disease. Since the potential conformational diagnosis of Alzheimer's disease requires histopathological tests on brain through autopsy, potential early diagnosis still remains challenging. In recent years, several researches have proposed the use of biomarkers for early diagnosis. In cerebrospinal fluid (CSF), $\beta$-amyloid(1-42), phosphorylated-tau and total tau were suggested to be effective biomarkers for Alzheimer's disease diagnosis. However, a single biomarker might not be sufficient for potential diagnosis of Alzheimer's disease. Thus, the use of RNA interference (RNAi) through microRNAs (miRNAs) has been proposed by several researchers for simultaneous analysis of several biomarkers using microarray technology. These miRNA based biomarkers can be analysed from both blood and CSF, but miRNAs from blood are advantageous over CSF as they are non-invasive and simple for collection. Moreover, the RNAi based therapeutics by siRNA (short interference RNA) or shRNA (short hairpin RNA) have also been proposed to be effective in the treatment of Alzheimer's disease. This review describes the promising application of RNAi technology in therapeutics and as a biomarker for both Alzheimer's disease diagnosis and treatment.

• Korean Journal of Veterinary Service
• /
• v.41 no.2
• /
• pp.79-83
• /
• 2018

This study compared serum concentrations of suppression of tumorigenicity 2 (ST2) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) between healthy and heartworm- infected dogs. Eighteen heartworm-infected dogs and five healthy dogs were included in the study. Dogs were diagnosed and categorized by history, clinical signs, and blood assay, thoracic radiography, echocardiography, and commercial ELISA kit results. Serum samples were sent to the IDEXX reference laboratory for NT-proBNP measurement. ST2 was examined by using a canine interleukin 33 receptor ELISA kit with the quantitative sandwich ELISA method. The severely infected group showed significant elevation of NT-proBNP concentration over those of the control (P=0.03) and mildly infected (P=0.04) group. There were no significant difference in ST2 concentrations among the three groups. The usefulness of NT-proBNP as a cardiac biomarker in dogs with severe heartworm disease was confirmed by the results of this study. Further investigations to assess ST2 as a cardiac biomarker are warranted.