Serum Protein Changes in Pediatric Sepsis Patients Identified With an Aptamer-Based Multiplexed Proteomic Approach
Nicholas J Shubin1, Krupa Navalkar2, Dayle Sampson2
1Seattle Children's Research Institute, Seattle, WA.
Insights
Pediatric sepsis diagnosis is challenging. A novel proteomic approach identified 111 serum protein changes, distinguishing sepsis from non-infectious inflammation, potentially improving early detection and treatment.
Area of Science:
- Biochemistry and Molecular Biology
- Pediatric Critical Care Medicine
- Proteomics and Biomarker Discovery
Background:
- Sepsis is a life-threatening condition in children, characterized by organ dysfunction due to a dysregulated host response to infection.
- Early and accurate diagnosis of pediatric sepsis is difficult, often leading to delayed treatment and increased mortality.
- Current diagnostic criteria for pediatric sepsis have limitations in sensitivity and specificity.
Purpose of the Study:
- To investigate novel serum protein changes in pediatric sepsis using an aptamer-based multiplexed proteomics approach.
- To identify specific protein expression patterns that can differentiate between pediatric sepsis and infection-negative systemic inflammation.
- To enhance the diagnostic accuracy of sepsis in children beyond existing clinical criteria.
Main Methods:
- Retrospective observational cohort study involving pediatric patients in Intensive Care Units.
- Aptamer-based proteomic platform used to measure 1,305 proteins in serum samples from sepsis and control groups.
- Statistical analysis, including linear modeling and Boruta, employed to identify differentially expressed proteins and correlate them with clinical sepsis traits.
Main Results:
- A total of 111 proteins were significantly differentially expressed between pediatric sepsis patients and infection-negative controls.
- 55 of the differentially expressed proteins had been previously associated with sepsis.
- Weighted gene correlation network analysis identified 76 proteins highly correlated with clinical sepsis traits, with 27 being novel findings in sepsis research.
Conclusions:
- The identified serum protein changes, detected via aptamer-based multiplexed proteomics, show promise in distinguishing pediatric sepsis from non-infectious systemic inflammation.
- This proteomic signature could potentially improve the sensitivity and specificity of sepsis diagnosis in pediatric populations.
- Further validation is warranted to integrate these findings into clinical diagnostic tools for early sepsis detection.
Objectives:
Sepsis, a life-threatening organ dysfunction caused by a dysregulated host response to infection, is a leading cause of death and disability among children worldwide. Identifying sepsis in pediatric patients is difficult and can lead to treatment delay. Our objective was to assess the host proteomic response to infection utilizing an aptamer-based multiplexed proteomics approach to identify novel serum protein changes that might help distinguish between pediatric sepsis and infection-negative systemic inflammation and hence can potentially improve sensitivity and specificity of the diagnosis of sepsis over current clinical criteria approaches.
Design:
Retrospective, observational cohort study.
Setting:
PICU and cardiac ICU, Seattle Children's Hospital, Seattle, WA.
Patients:
A cohort of 40 children with clinically overt sepsis and 30 children immediately postcardiopulmonary bypass surgery (infection-negative systemic inflammation control subjects) was recruited. Children with sepsis had a confirmed or suspected infection, two or more systemic inflammatory response syndrome criteria, and at least cardiovascular and/or pulmonary organ dysfunction.
Interventions:
None.
Measurements And Main Results:
Serum samples from 35 of the sepsis and 28 of the bypass surgery subjects were available for screening with an aptamer-based proteomic platform that measures 1,305 proteins to search for large-scale serum protein expression pattern changes in sepsis. A total of 111 proteins were significantly differentially expressed between the sepsis and control groups, using the linear models for microarray data (linear modeling) and Boruta (decision trees) R packages, with 55 being previously identified in sepsis patients. Weighted gene correlation network analysis helped identify 76 proteins that correlated highly with clinical sepsis traits, 27 of which had not been previously reported in sepsis.
Conclusions:
The serum protein changes identified with the aptamer-based multiplexed proteomics approach used in this study can be useful to distinguish between sepsis and noninfectious systemic inflammation.
