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Multiomic, mass spectrometry-based analysis of dried blood for deep phenotyping of sepsis

基于多组学、质谱分析的干燥血液用于脓毒症的深层表型分析

基本信息

批准号：
10431072
负责人：
Matthew Wolf Foster
金额：
$ 20.13万
依托单位：
DUKE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-04-01 至 2024-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10431072
关键词：
Address Adoption Affect Ambulatory Care Facilities Antibiotics Bioethics Biological Assay Biology Blood Blood specimen C-reactive protein COVID-19 Cause of Death Cells Cessation of life Clinical Clinical Data Clinical Management Code Collection Coupled Critical Illness Data Data Set Development Devices Disease Electronic Health Record Erythrocytes Exhibits Functional disorder Future Generations Goals Hospitals IV Fluid Immune response Immune signaling In Vitro Infection Intensive Care Units Laboratories Life Liquid Chromatography Long-Term Effects Mass Spectrum Analysis Metabolism Methodology Methods Morbidity - disease rate Multiomic Data Organ Outcome Pathway Analysis Pathway interactions Patient Care Patients Persons Phase Phenotype Phosphorylation Pilot Projects Plasma Post-Translational Protein Processing Preparation Procedures Proteins Proteome Proteomics Pythons Quality Control Recovery Reporting Role Sampling Sepsis Shipping Signal Pathway Signal Transduction Standardization Techniques Tissues Translations Universities Validation Viremia Whole Blood Work base biobank cell type cohort cost data repository demographics glycosylation high throughput screening metabolome metabolomics mortality multidisciplinary multiple omics novel post-COVID-19 procalcitonin protein metabolite protein profiling septic patients severe COVID-19 stability testing standard of care tandem mass spectrometry translational scientist

项目摘要

Sepsis, which is characterized by life threatening organ dysfunction caused by an uncontrolled host response to infection, is the leading cause of death in hospitals and is responsible for >250,000 deaths per year in the U.S. at the cost of over $20 billion in patient care. Sepsis has a mortality rate nearing 50% at 2 years, which has profound implications for patients recovering from severe COVID-19, a form of viral sepsis. Because sepsis is a multi-organ disease, the quantification of circulating proteins and metabolites is central to the profiling of sepsis and of its long-term effects, and some such assays (lactate, procalcitonin) have become the standard of care. To date, the majority of studies, and particularly the large number in COVID-19 sepsis, have profiled plasma and serum, which, compared to whole blood is fraught with variability and belies the important roles of the erythrocyte and other cell-types. To this end, biorepositories at Duke University, which are banking samples from COVID- 19 sepsis patients in the intensive care unit (ICU) and in a post-COVID outpatient clinic, have been utilizing volumetric absorptive microsampling (VAMS) on Neoteryx Mitra tips to collect and store whole blood specimens for future ‘omic analyses. The overarching goals of this application are to develop and validate multiomic methods for mass spectrometry-based quantification of proteins and metabolites from Mitra tips that comprehensively profile sepsis pathobiology. In the R21 phase, we will develop and validate mass spectrometry-based methods for the non-targeted quantification of proteins and post-translational modifications (phosphorylation, glycosylation) in whole blood, and for targeted quantification of numerous metabolite classes. We will develop reference materials and standard operating procedures for inter-laboratory translation of these approaches. In the R33 phase, we will analyze proteins, PTMs and metabolites from over 600 patient timepoints from biorepositories containing longitudinal samples in critically ill sepsis and post-COVID-19 cohorts, and we will integrate these data with well-curated clinical datasets. Completion of these aims will establish the utility of blood sampling by VAMS for future sepsis studies and will create a highly curated clinical and deep multiomic dataset for future hypothesis generation.

败血症，其特点是危及生命的器官功能障碍引起的不受控制的宿主反应