https://gatech.zoom.us/j/98694357299?pwd=MnYxbDRtamw2Tzhrd05RTG9tdiszZz09&from

Committee

• Dr. Wilbur Lam (Ph.D. Advisor, Biomedical Engineering, GT & Emory)

• Dr. Anant Madabhushi (Biomedical Engineering, GT & Emory)

• Dr. Paynabar Kamran (Industrial & Systems Engineering, GT)

• Dr. Eva Dyer (Electrical and Computer Engineering, GT)

• Dr. David Myers (Biomedical Engineering, GT & Emory)

Unraveling Hidden Heterogeneity: Quantitative Characterization of Cellular Heterogeneity

in Multicolor Flow Cytometry Data for Enhanced Insights

Varying health outcomes present a significant challenge in medicine. At the biological and microscopic level of human health, cells are the smallest functional with diverse functions, undergoing dynamic changes over time and exhibiting unique variations among individuals.

Understanding this intra- and inter-individual cellular diversity, and its impact on health is crucial for the implementation of personalized medicine. Multicolor flow cytometry is the most established single-cell technology, providing multi-parametric information about each cell's protein profiles. It has facilitated the discovery of cellular subpopulations and biomarkers for health and disease. However, current analyses of multicolor flow cytometry data fail to fully

capture multifaceted representations of cellular heterogeneity. The focus on population averages and frequencies neglects the amount, shape, and direction of cellular heterogeneity, which may collectively indicate various forms of cellular heterogeneity with biological and clinical significance. Yet, the lack of quantitative definitions for these aspects hinders objective analyses of their contribution to health. This research proposes and evaluates quantitative metrics to capture previously under-appreciated aspects of cellular heterogeneity in multicolor flow cytometry data. It first examines the biological significance of cellular heterogeneity in healthy platelets, elucidating its translation into functional diversity at the population-level in hemostasis and thrombosis. Subsequently, it investigates the clinical relevance of cellular heterogeneity in peripheral blood mononuclear cells (PBMCs) to understand the role of immune cell heterogeneity in the manifestations of long COVID. By providing a new quantitative lens to uncover hidden aspects of cellular heterogeneity, the proposed methods offer a more holistic understanding of cellular variability. Serving as biomarkers to establish the reference of homeostatic forms of cellular heterogeneity, the proposed metrics can be used to diagnose and monitor diseases and guide the design of tailored therapies. Ultimately, these metrics reveal “hidden heterogeneity”, which will help better resolve and manage inter-individual differences in disease manifestations and therapy responses, advancing personalized medicine.