Methods: To address the first purpose, we will briefly review the technology of metabolomics, describing what it is, how it works, and why it offers a powerful real-time picture of the physiological processes occurring in a given individual,7 including the real-time production of metabolites and activation of metabolic pathways associated with chronic stress. Important clinical examples wherein metabolomics has been shown to provide unique and variable prognostic and diagnostic data will be presented, focusing on nursing assessment, diagnosis, and intervention. This will be followed by an exemplar of chronic stress exposure in pregnant African American women enrolled in our NIN-funded study (R01NR014800) investigating risk factors for preterm birth. In this study, African American women enroll during their first trimester of pregnancy and are followed through delivery. During their 1st and 3rd trimesters, participants complete demographic and health questionnaires, as well as questionnaires related to acute and chronic stress exposure including: perceived stress; lifetime stressful life events; childhood stressors; and exposure to racism and discrimination. Participants also provided a blood sample for measurement of dexamethasone suppression, a biological indicator of chronic stress exposure, following standard techniques published previously.3,8 Serum samples are then analyzed for metabolites using a Thermo Scientific Orbitrab Fusion Mass Spectrometer with dual ionization/dual liquid chromatography.3 Three technical replicates are run for each sample along with pooled reference samples. Metabolic features are extracted after preliminary statistical analyses and feature selection. Medical record review after delivery is conducted to gather empirical evidence of birth outcomes. Big data mummichug software is used for pathway enrichment analysis9 to identify associations between metabolites and metabolic pathways with self-report and biological indicators of chronic stress exposure. Metabolite features from untargeted LC-MS are then ranked by their Pearson correlation with DexIC50 levels. Pathways with p<0.05 and more than 3 significant metabolites are considered significant. Strategies for utilizing this knowledge for future nursing assessment, diagnosis and intervention will be discussed.
Results: Currently, 486 women are enrolled in the prenatal study and metabolomics analyses have been conducted on samples from the first 320 women. Findings indicate that the metabolomic pathways related to chronic stress with p<0.05 and more than 3 significant metabolites: include: anti-oxidant pathways10 including those related to vitamin C; metabolomic pathways related to the metabolism of tryptophan, the precursor to serotonin;11 and pathways related to mitochondrial enzymes and energy production.12 A discussion of how nursing assessment, diagnosis, and intervention strategies can be leveraged from the knowledge generated regarding these metabolites and metabolic pathways will follow, and symposium attendees will gain a better understanding of how this emerging technology can be leveraged by both nurse researchers and nurse clinicians.
Conclusion: Until a better understanding of the underlying biology by which chronic stress exposure contributes to adverse birth outcomes is achieved, an unacceptably high number of the world’s most vulnerable women and infants will continue to be at risk. Applying a metabolomic approach to expose the metabolites and metabolic pathways associated with chronic stress during pregnancy provides increasing opportunities for targeted nursing assessment, diagnosis, and intervention. By gaining exposure to cutting-edge technologies such as metabolomics, nurse scientists can better lead and/or participate in innovative interdisciplinary research initiatives in the future and can better provide a precision nursing approach to patient care: the very essence of nursing science.