A Critical Analysis of the Biomolecular Variation of Immune Cells Across Time and Stressful Environmental Exposures Using Multiomic Methods
Open Access
- Author:
- Apsley, Abner
- Graduate Program:
- Molecular, Cellular, and Integrative Biosciences
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- February 20, 2025
- Committee Members:
- Melissa Rolls, Program Head/Chair
David Almeida, Outside Unit Member
Yogasudha Veturi, Major Field Member
Idan Shalev, Chair & Dissertation Advisor
Molly Hall, Outside Field Member - Keywords:
- genomics
multiomics
multiomic integration
stress
early-life adversity
immune system
immune cells
epigenomics
DNA methylation
transcriptomics
metabolomics
NMR
RNA-seq - Abstract:
- Systems biology aims to both generate molecular parts lists for each -omic category of biomolecules and mathematically model how these molecular parts interact. Although much attention has been given to the development of molecular parts lists, these lists are often conceptualized as static. However, biomolecular profiles are highly dynamic entities that vary with respect to both time and environmental exposures. Biomolecular variations across time and environmental exposures, specifically in circulating immune cells and blood, have significant academic and biomedical relevance. Therefore, to achieve the lofty goals of systems biology, time- and environment-dependent molecular parts lists must be generated. The present work aims to contribute to the development of time- and environment-dependent molecular parts lists by documenting and analyzing the epigenome, transcriptome, and metabolome of circulating immune cells and blood. Specifically, DNA methylation and gene expression were documented for human peripheral blood mononuclear cells and the metabolome was documented for circulating plasma. The Shalev Lab’s “Stress Study” (NCT03637751) was used to perform the present work. The unique within-person, between-group experimental design of this study enabled the documentation and analysis of multiple -omic parts lists across various temporal scenarios. In addition, the effects of stressful environmental exposures (early-life adversity and acute psychosocial stress) were analyzed across -omic measurements. Furthermore, the interaction between early-life adversity and acute stress was analyzed for its effects on the epigenome, transcriptome, and metabolome. Major findings included the documentation of individual DNA methylation sites, gene expression levels, and metabolite concentrations across time, early-life adversity, and acute stress. The within-person stability of each -omic category was assessed both comprehensively and on an individual feature-level. In general, the stability of all -omes decreased as temporal distance between measurements increased. Furthermore, on a systems-wide level, acute stress tended to increase the stability of all -omic measurements when compared to no-stress scenarios. Early-life adversity exposure moderated the effects of acute stress on individual -omic measurements. Baseline differences across the epigenome, transcriptome, and metabolome were observed when comparing control and early-life adversity individuals. Overall, findings support the importance of considering both temporal and environmental effects when generating -omic parts lists.