Exploring the sepsis-delirium connection through glycoproteomics

通过糖蛋白质组学探索脓毒症与谵妄之间的联系

• 批准号: 10677027
• 负责人: Steven Matthew Patrie
• 金额: $ 19.92万
• 依托单位: NORTHWESTERN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-05 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10677027
• 关键词: Acute-Phase Proteins; Age; Algorithms; Amino Acids; Anabolism; Biological Markers; Blood; Blood Screening; Brain; Chemicals; Chemistry; Clinical; Clinical Data; Collection; Communities; Complex; Critical Illness; DNA; Data; Data Set; Delirium; Detection; Development; Diagnosis; Dimensions; Disease; Disease Progression; Environment; Enzymatic Biochemistry; Evaluation; Event; Functional disorder; Gene Expression; Glycopeptides; Glycoproteins; Goals; Health; Heterogeneity; Hospitals; Human; Immune response; Immunosuppression; Impaired cognition; Infection; Inflammatory Response; Informatics; Investigation; Knowledge; Life; Mass Spectrum Analysis; Measures; Memory; Meta-Analysis; Methods; Molecular; Monitor; Organ; Parents; Pathway Analysis; Pathway interactions; Patients; Persons; Phase; Phenotype; Physiology; Plasma; Polysaccharides; Procedures; Protein Glycosylation; Proteins; Proteome; Proteomics; RNA; Reaction; Regional Anatomy; Regulation; Reporting; Reproducibility; Research; Resolution; Resources; Sampling; Science; Sepsis; Septic Shock; Serum; Severities; Shapes; Signal Transduction; Site; Staging; Symptoms; Technology; Testing; Time; United States; Work; brain health; data mining; data streams; endothelial dysfunction; experience; global health; glycoproteomics; glycosylation; human subject; individual patient; informatics tool; innovation; insight; knowledgebase; molecular marker; next generation; novel; programs; rapid detection; septic patients; temporal measurement; tool

ABSTRACT Our proposal seeks to create and apply new glycoproteomics procedures that permit unbiased discovery of alterations in protein glycosylation. This includes the creation of algorithms that assemble glycoproteoform networks from multi-dimensional mass spectrometry (MS) datasets, the prediction of underlying glycan information directly from intact glycoprotein MS spectral information, and statistical scoring with unique glycoproteoform informatics tools. An innovative aspect of the proposed technologies is that they are intended to permit evaluation of glycoproteins and prediction of glycan level information when glycosylation occurs at more than one amino acid residue, a well-recognized bottleneck in the top-down mass spectrometry field. Our aims also include the application of the algorithms to enable unsupervised "discovery" of glycoproteoforms biomarkers in biofluids. We will use these new tools to monitor the blood-plasma/serum of patients that derive from the DECODE-Sepsis and BRAIN-ICU programs with the intent to discover glycoproteoforms that correlate with specific endotypes or clinical symptoms across the spectrum of sepsis disorders, including prediction of long- term cognitive dysfunction. In particular, we seek to establish unique datasets that can be used to inform upon sepsis that is tied to different anatomical regions or tied to complex mechanisms involved in both sepsis (endothelial dysfunction and inflammatory responses) and sepsis-adjacent (i.e. immunosuppression) events. Sepsis is life-threatening, leading to organ dysfunction due to a dysregulated host response to infection and is an important global health problem that kills 11 million people each year and disables millions more. In the United States, the CDC reports that 87% of sepsis or the infection causing sepsis starts outside the hospital. These metrics highlight the urgent need for resources that can rapidly detect and stratify stages and mechanisms associated with individual patients. Our targeted informatics workflow will be able to compile large volumes of patient data to provide meaningful insight into the non-template driven regulation of glycosylation caused by specific gene expression, providing both novel sub-phenotype and endotype knowledge that is absent in classic non-glycoproteomics discovery. If our project aims are successful, we will not only have developed innovative tools for glycomics and glycoproteomics, but also established clinical proteomics procedures for the discovery and development of glycoprotein-based biomarkers.

摘要