Proteomic changes associated with racial background and sepsis survival outcomes

Establishing Quality Control Metrics for Large-Scale Plasma Proteomic Sample Preparation

Large-scale plasma proteomics studies have been transformed due to the multiplexing and automation of sample preparation workflows. However, these workflows can suffer from reproducibility issues, a lack of standardized quality control (QC) metrics, and the assessment of variation before liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. The incorporation of robust QC metrics in sample preparation workflows ensures better reproducibility, lower assay variation, and better-informed decisions for troubleshooting. Our laboratory conducted a plasma proteomics study of a cohort of patient samples (N = 808) using tandem mass tag (TMT) 16-plex batches (N = 58). The proteomic workflow consisted of protein depletion, protein digestion, TMT labeling, and fractionation. Five QC sample types (QCstd, QCdig, QCpool, QCTMT, and QCBSA) were created to measure the performance of sample preparation prior to the final LC-MS/MS analysis. We measured <10% CV for individual sample preparation steps in the proteomic workflow based on data from various QC sample steps. The establishment of robust measures for QC of sample preparation steps allowed for greater confidence in prepared samples for subsequent LC-MS/MS analysis. This study also provides recommendations for standardized QC metrics that can assist with future large-scale cohort sample preparation workflows.

A Prospective Cohort Protocol for the Remnant Investigation in Sepsis Study

BACKGROUND

Sepsis is a common and deadly syndrome, accounting for more than 11 million deaths annually. To mature a deeper understanding of the host and pathogen mechanisms contributing to poor outcomes in sepsis, and thereby possibly inform new therapeutic targets, sophisticated, and expensive biorepositories are typically required. We propose that remnant biospecimens are an alternative for mechanistic sepsis research, although the viability and scientific value of such remnants are unknown.

METHODS AND RESULTS

The Remnant Biospecimen Investigation in Sepsis study is a prospective cohort study of 225 adults (age ≥ 18 yr) presenting to the emergency department with community sepsis, defined as sepsis-3 criteria within 6 hours of arrival. The primary objective was to determine the scientific value of a remnant biospecimen repository in sepsis linked to clinical phenotyping in the electronic health record. We will study candidate multiomic readouts of sepsis biology, governed by a conceptual model, and determine the precision, accuracy, integrity, and comparability of proteins, small molecules, lipids, and pathogen sequencing in remnant biospecimens compared with paired biospecimens obtained according to research protocols. Paired biospecimens will include plasma from sodium-heparin, EDTA, sodium fluoride, and citrate tubes.

CONCLUSIONS

The study has received approval from the University of Pittsburgh Human Research Protection Office (Study 21120013). Recruitment began on October 25, 2022, with planned release of primary results anticipated in 2024. Results will be made available to the public, the funders, critical care societies, laboratory medicine scientists, and other researchers.

PATHWAYS ASSOCIATED WITH POSITIVE SEPSIS SURVIVAL OUTCOMES IN AFRICAN AMERICAN/BLACK AND NON-HISPANIC WHITE PATIENTS WITH URINARY TRACT INFECTION

ABSTRACT

Urinary tract infections (UTIs) are a common cause of sepsis worldwide. Annually, more than 60,000 US deaths can be attributed to sepsis secondary to UTIs, and African American/Black adults have higher incidence and case-fatality rates than non-Hispanic White adults. Molecular-level factors that may help partially explain differences in sepsis survival outcomes between African American/Black and Non-Hispanic White adults are not clear. In this study, patient samples (N = 166) from the Protocolized Care for Early Septic Shock cohort were analyzed using discovery-based plasma proteomics. Patients had sepsis secondary to UTIs and were stratified according to self-identified racial background and sepsis survival outcomes. Proteomics results suggest patient heterogeneity across mechanisms driving survival from sepsis secondary to UTIs. Differentially expressed proteins (n = 122, false discovery rate-adjusted P < 0.05) in Non-Hispanic White sepsis survivors were primarily in immune system pathways, while differentially expressed proteins (n = 47, false discovery rate-adjusted P < 0.05) in African American/Black patients were mostly in metabolic pathways. However, in all patients, regardless of racial background, there were 16 differentially expressed proteins in sepsis survivors involved in translation initiation and shutdown pathways. These pathways are potential targets for prognostic intervention. Overall, this study provides information about molecular factors that may help explain disparities in sepsis survival outcomes among African American/Black and Non-Hispanic White patients with primary UTIs.

Evaluating cPILOT Data toward Quality Control Implementation

Multiplexing enables the monitoring of hundreds to thousands of proteins in quantitative proteomics analyses and increases sample throughput. In most mass-spectrometry-based proteomics workflows, multiplexing is achieved by labeling biological samples with heavy isotopes via precursor isotopic labeling or isobaric tagging. Enhanced multiplexing strategies, such as combined precursor isotopic labeling and isobaric tagging (cPILOT), combine multiple technologies to afford an even higher sample throughput. Critical to enhanced multiplexing analyses is ensuring that analytical performance is optimal and that missingness of sample channels is minimized. Automation of sample preparation steps and use of quality control (QC) metrics can be incorporated into multiplexing analyses and reduce the likelihood of missing information, thus maximizing the amount of usable quantitative data. Here, we implemented QC metrics previously developed in our laboratory to evaluate a 36-plex cPILOT experiment that encompassed 144 mouse samples of various tissue types, time points, genotypes, and biological replicates. The evaluation focuses on the use of a sample pool generated from all samples in the experiment to monitor the daily instrument performance and to provide a means for data normalization across sample batches. Our results show that tracking QC metrics enabled the quantification of ∼7000 proteins in each sample batch, of which ∼70% had minimal missing values across up to 36 sample channels. Implementation of QC metrics for future cPILOT studies as well as other enhanced multiplexing strategies will help yield high-quality data sets.

Personalizing Care for Critically Ill Adults Using Omics: A Concise Review of Potential Clinical Applications

Current guidelines for critically ill patients use broad recommendations to promote uniform protocols for the management of conditions such as acute kidney injury, acute respiratory distress syndrome, and sepsis. Although these guidelines have enabled the substantial improvement of care, mortality for critical illness remains high. Further outcome improvement may require personalizing care for critically ill patients, which involves tailoring management strategies for different patients. However, the current understanding of disease heterogeneity is limited. For critically ill patients, genomics, transcriptomics, proteomics, and metabolomics have illuminated such heterogeneity and unveiled novel biomarkers, giving clinicians new means of diagnosis, prognosis, and monitoring. With further engineering and economic development, omics would then be more accessible and affordable for frontline clinicians. As the knowledge of pathophysiological pathways mature, targeted treatments can then be developed, validated, replicated, and translated into clinical practice.