Contemporary Use of Transcriptomics to Facilitate Precision Medicine in Systemic Lupus Erythematosus (SLE)
Open Access DepositedSLE is one presentation of autoimmunity, loss of self-tolerance, that can result in injury to the normal function in many organ systems, including, blood, skin, joints, heart, lungs, and kidneys. Despite deeply characterizing the molecules, signaling pathways, and cells involved in this breakdown, there still exists a gap between the scientific base of knowledge surrounding lupus and clinical care and development of new treatments. Management of SLE is challenged by significant inter-individual variability (heterogeneity) of both patient experience (symptoms), organ damage, and molecular underpinnings of disease. Developments in means to treat lupus have been challenging because of the unpredictable nature of the disease that confounds many aspects of care. In this dissertation, I present a method of lupus patient subsetting based upon important transcriptomic (RNA-level) features and how they were prioritized. I also present an example of the discovery process of lupus biomarkers, in this case, genes causative of primary immunodeficiency that operate orthogonally in autoimmunity, and ultimately how they confirm but do not expand upon patient stratification. The patient subsetting approach begins to bridge the gap between the molecules involved in disease propagation and clinical application, and I demonstrate how discriminative, explainable machine learning can be utilized to reproducibly assign lupus patients to the subsets described, as well as how machine learning can be used throughout biomarker identification. Finally, I present a novel use of correlation of transcripts that demarcate immune cells to delineate possible changes in functional or differentiation states of cells across disease conditions, and, suggest future directions for lupus research and development. All of the questions addressed in this dissertation are centered on detailed transcriptomic analysis and work to expand methods currently available to provide prognostic and molecular insight into an individual lupus patient’s disease.
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