Abstract Autoimmune diseases like systemic lupus erythematosus (SLE) affect the health of multiple organ systems including the central nervous system, skin, joints, and kidneys. The heterogeneity of clinical profiles observed with SLE reflects a complex dysregulation of cellular processes, including metabolism, apoptotic clearance, and inflammation. Diagnosis and treatment of SLE is thus challenging, and few new treatments have been approved over the past 60 years. In this study, we aimed to characterize the spatial immune and metabolic profiles of SLE at single cell resolution. To do so, we profiled a cohort of human FFPE SLE tissues with an ultrahigh-plex panel of >50 oligo-conjugated antibodies representing immune, apoptotic, metabolic and stress markers. Whole-slide, spatial phenotyping was performed using the PhenoCycler ®-Fusion system, followed by deep bioinformatic analyses to determine the cellular phenotypes, spatial neighborhoods, and metabolic determinants of SLE. By combining immune cell lineage information with expression of key proteins involved in glycolysis, amino acid metabolism, lipid metabolism, hypoxia, oxidative stress, and apoptosis, we elucidated the functional dysregulation in key immune subsystems that may contribute to development of autoimmunity and inflammation associated with SLE. Spatial phenotyping also revealed a high degree of inter- and intra-sample heterogeneity, confirming the complexity of the SLE clinical profile. Collectively, our data amount to new insights into metabolic reprogramming of immune cells in autoimmune diseases and may aid in the identification of novel therapeutic biomarkers within the tissue microenvironment of SLE patients.