Analysis of Glycan Markers in Neuronal Diseases
Glycan Markers: Paving the Path to Neuronal Disease Insights
Neuronal diseases are characterized by the deterioration of neuronal function and the death of cells, leading to symptoms that significantly affect patients' daily activities. Significant associations have been uncovered between alterations in glycan structures and a variety of neurological conditions, including Alzheimer's disease (AD), multiple sclerosis, Parkinson's disease, amyotrophic lateral sclerosis (ALS), and Huntington's disease. Therefore, CD BioGlyco provides
Glycoinformatics-assisted Neuronal Diseases Glycomics Analysis Service for performing a quick and thorough analysis of those neuronal diseases. Our neuronal diseases glycomics analysis includes the
Characterization of Neurological Glycans and analysis of glycan markers in neuronal diseases.
Glycan identification and quantitation
To fully grasp the roles of glycans and glycoproteins, it is crucial to delineate the entire spectrum of oligosaccharides present within a sample. Our research team meticulously analyzes and compares the various glycan structures while conducting relative quantitation of the oligosaccharides. This process employs a diverse array of analytical techniques, including:
- High-performance/ultra-performance liquid chromatography (HPLC/UPLC)
- Capillary electrophoresis (CE)
- Mass spectrometry (MS): LC-MS; Matrix-assisted laser desorption ionization-time of flight MS (MALDI-TOF MS)
- Lectin-based technologies: Either individually or in combination, these analytical methods are used to identify the structures of glycans and measure the abundance of different oligosaccharides.
Glycoinformatics-assisted biomarker discovery
After glycan identification and quantitation, a vast amount of glycan data is obtained. We utilize various glycoinformatics tools, including databases and software, to interpret glycomics data and analyze glycan structures from different glyco-analysis methods. These glycoinformatics tools are used for the analysis and discovery of glycan biomarkers.
- Identification and analysis of glycan structures: We use software to identify glycan peaks in MS data and analyze their structures, aiding in the determination of the presence and characteristics of different glycans. These tools process and interpret data from various MS analysis methods, helping understand glycan variations across different biological samples.
- Data alignment and normalization: When analyzing multiple samples, the software can align chromatographic profiles to ensure that LC-MS data from different samples are compared consistently. This step is crucial for improving the accuracy of data analysis.
- Providing uncertainty measurements: Some alignment techniques use Bayesian models to estimate variability in retention times and provide measures of uncertainty, which enhances the reliability of the results.
- Biomarker Discovery: We use glycoinformatics tools like Glycolyzer to identify significant glycan signals in raw MS data, which can be used to discover potential biomarkers for neuronal diseases.
By assessing variations in glycan abundance across distinct cohorts, we identify glycans as potential biomarkers in neuronal diseases. Through using these technologies, we have advanced the relative quantification of the glycome from easily accessible biofluids like plasma to identify glycan biomarkers for neuronal diseases.
Publication Data
Technology: Glycan release, MALDI-TOF MS
Journal: Biomolecules
Published: 2023
IF: 4.8
Results: In this study, authors investigated the glycoprotein glycome of cerebrospinal fluid (CSF) from a cohort of 262 subjects to enhance AD diagnosis and differential diagnosis through glycan analytics. The study included meticulous methods for the isolation and purification of N- and O-glycans, which included permethylation and analysis through MS. In this study, glycan samples were analyzed using MALDI-TOF-MS with an Ultraflex III mass spectrometer. To process the data, FlexAnalysis 3.4 software was used for baseline correction and peak picking. For glycan structure annotation, GlycoPeakfinder was employed, and the assignment of glycan structures was done using GlycoWorkbench version 2.1. Key findings include the profiling of free-glycans, N-glycans, and O-glycans, with two free-glycans showing promising biomarker potential for AD based on receiver operating characteristic (ROC) curves. The study highlights the need for further multi-center investigations that consider various influencing factors such as gender, pre-existing conditions, lifestyle, and genetic predispositions to validate the biomarker potential of free-glycans.
Advantages
- We possess various analytical methods like HPLC/UPLC, CE, MS, and lectin-based technologies, that guarantee precise detection and measurement of glycans, delivering a thorough comprehension of their involvement in neuronal disorders.
- Our research team uses diverse glycoinformatics tools for the interpretation and analysis of the extensive glycan data obtained from analyses.
- Our researchers have a lot of advanced knowledge, that helps with interpreting MS data, aligning and normalizing data, and discovering biomarkers.
Applications
- By analyzing the glycan profiles of neuronal tissues or fluids from patients with various neurological diseases, we identify specific glycan signatures that are associated with disease pathogenesis. These glycan markers can serve as biomarkers for early detection, disease progression monitoring, and outcome prediction.
- The analysis of glycan biomarkers can be applied to the development and research of diagnostic assays that are more sensitive and specific than traditional methods, enabling earlier and more accurate diagnosis of diseases.
- The analysis of glycan markers can serve as potential targets for drug development. By understanding the change of glycan in neuronal diseases, drugs can be designed that interfere with these modifications or their downstream effects.
Frequently Asked Questions
- What other diseases can we conduct computer-aided glycomics analysis on?
- What glycoinformatics-assisted tools do we use?
- Databases and bioinformatics tools are used for interpreting glycomics data into glycan structural information, including GlycoWorkbench, UniCarb-DB, GlycoDigest for MS, and GlycoBase for HPLC/UPLC. We also incorporate guidance on leveraging glycan structural information to query UniCarbKB for glycan-protein correlations and SugarBind for glycan-pathogen interactions.
At CD BioGlyco, our researchers provide
Glycoinformatics-assisted Glycomics Analysis that is centered on investigating glycan markers and their alterations in neurological disorders. Through our strategy, we uncover how changes in glycan structures and functions are associated with neuronal diseases. By analyzing these glycan markers, we assist clients in understanding their role in neuronal cell dysfunction and death. Please contact us for more information about
Glycoinformatics-assisted Disease Glycomics Analysis Service, if you would like to develop and research new diagnostic tools and therapeutic strategies for these conditions.
Reference
- Krüger, L., et al. The cerebrospinal fluid free-glycans Hex1 and HexNAc1Hex1Neu5Ac1 as potential biomarkers of Alzheimer's disease. Biomolecules. 2024, 14(5): 512.
For research use only. Not intended for any diagnostic use.
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