A necessary component to advancing a precision medicine paradigm for complex acute traits such as sepsis, acute respiratory distress syndrome (ARDS), acute kidney injury (AKI), primary graft dysfunction (PGD) post- lung transplant, and delirium includes broad profiling of human body fluids in affected and unaffected individuals. Our group has identified numerous protein markers with significant associations with each of these acute disorders, and is poised to integrate clinical data from 3 large cohorts with genomic, meta-genomic, and proteomic data for both discovery and validation work. However, the bottleneck for our discovery work is at the level of protein quantification step, as each putative biomarker is assessed in duplicate in single validated ELISAs. A high-throughput multiplex detection system that utilizes small volumes of human subject biosamples would dramatically increase laboratory productivity and speed the discovery and validation of potentially endotype-defining markers as well as allowing us to simulate rapid determination of potential enrichment factors for target population identification. In this application, we propose the acquisition of one Meso Scale Discovery (MSD) MESO Quickplex SQ 120 multiarray electrochemiluminescent platform for shared use among 3 ?Major User? core faculty engaged in human translational studies, in addition to a core of researchers performing translational work. The 3 core faculty each direct molecular cohort studies totaling over 3000 subjects enrolled, and with carefully timed biospecimens (plasma, urine, bronchoalveolar lavage) collected in acute-care hospital settings. Sepsis, trauma, and lung transplantation each trigger a cascade of innate inflammation, vascular activation, and damage-associated molecular pathogen signaling, with both shared and distinct pattern expression that can be mined to enhance our understanding of shared and distinct pathway contributions to organ failure following severe insults. As inpatient cohort studies, each of our studies is limited by timing and safety concerns to collecting the minimum amount of blood that permits approved research while not exposing critically ill subjects to excessive risk, and thus there is an imperative to maximize the value of each plasma, urine, and bronchoalveolar lavage sample. With MSD multiplexed technology, we can rapidly and efficiently assay our identified candidate proteins to assess their predictive and prognostic utility for ARDS, AKI, or PGD risk, stated aims in our funded work. This platform will also allow endotype discovery work with expanded panels of markers that, combined with clinical and physiologic data, will permit latent class analysis and classification and regression analysis, with the potential to identify and then test for replication in related cohorts. Finally, this platform allows the scaling up of Mendelian randomization and mediation analyses with candidate intermediate markers in the plasma, urine, and lung lavage fluid, in an attempt to identify markers with causal contributions towards these syndromes.

Public Health Relevance

Sepsis, severe injury, and lung transplantation precipitate thousands of intensive care unit admissions and contribute to significant organ injury, failure, and even death. Our goal is to use protein analysis in the blood, urine, and lung fluid of these critically ill patients to identify new biologic subgroups, or endotypes, that may respond to specific, precision therapies. A multiplexed immunoassay platform that analyzes multiple proteins on small volume biosamples in an efficient, high throughput manner would make a significant contribution toward this molecular phenotyping that may facilitate new breakthroughs.

Agency
National Institute of Health (NIH)
Institute
Office of The Director, National Institutes of Health (OD)
Type
Biomedical Research Support Shared Instrumentation Grants (S10)
Project #
1S10OD025172-01
Application #
9493967
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Klosek, Malgorzata
Project Start
2018-07-15
Project End
2019-07-14
Budget Start
2018-07-15
Budget End
2019-07-14
Support Year
1
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of Pennsylvania
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
042250712
City
Philadelphia
State
PA
Country
United States
Zip Code
19104