Background/Purpose: Clinically isolated aortitis (CIA) is an inflammatory aortopathy of unknown pathogenesis associated with progressive aortic complications and no validated biomarkers or targeted therapies. While giant cell arteritis (GCA) represents a well-characterized granulomatous large-vessel vasculitis and thoracic aortic aneurysm (TAA) an inflammatory disease driven by lipid accumulation and vascular remodeling, the molecular and immune landscape distinguishing CIA from these conditions remains poorly defined. We aimed to elucidate the pathogenic mechanisms of CIA through comparative single-cell and spatial transcriptomic analyses of CIA, GCA, and TAA.

Methods: Single-cell RNA sequencing and spatial transcriptomics were performed on surgically resected aortic tissue from 6 CIA, 3 GCA, 1 TAA, and 2 healthy controls (Fig 1). 

Results: We identified seven major cell populations: myeloid cells, B cells, T cells, plasma cells, mast cells, endothelial cells, and smooth muscle cells (Fig 1). Compared with TAA and healthy controls, both CIA and GCA demonstrated marked expansion of T-cell and plasma-cell compartments. CIA was distinguished by disproportionate plasma-cell expansion, enrichment of CXCL13+ CD4 T cells, activated macrophages, proliferating myeloid cells, and expansion of lymphatic and valvular endothelial cells. Both vasculitides contained naïve and memory B cells, whereas controls were composed almost exclusively of naïve B cells (Fig 1). To define disease-specific immune programs, we generated pathway-based gene signature scores encompassing macrophage activation, complement activation, extracellular matrix (ECM)/fibrosis remodeling, foam cell-lipid handling, plasma-cell activation, and interferon (IFN) responses. While all three diseases shared a core arterial injury program characterized by macrophage/complement activation and ECM remodeling, their dominant immune architectures diverged substantially. TAA was defined by lipid-handling foam-cell macrophages with minimal adaptive immune involvement. GCA exhibited the most destructive phenotype, combining prominent SPP1+/TREM2+ macrophage activation with a strong IFN response. In contrast, CIA occupied a distinct intermediate state characterized by endothelial CCL21 expression, robust plasma-cell activation, and tissue remodeling. Spatial transcriptomics localized CCL21+ endothelial niches to adventitial-intimal border regions enriched for B-cell and plasma-cell signatures, supporting active endothelial-lymphoid crosstalk and tertiary lymphoid organization within CIA lesions.

Conclusion: CIA represents a pathogenically distinct aortopathy characterized by tertiary lymphoid structure formation, local humoral immune activation, and lymphoid neogenesis, distinguishing it from the IFN-high granulomatous inflammation of GCA and the lipid-driven innate immune response of TAA. These findings provide the first high-resolution molecular framework for CIA pathogenesis, identify CCL21-mediated endothelial-lymphoid crosstalk as a potential therapeutic target, and suggest that B-cell/plasma-cell-directed strategies may represent a rational precision-medicine approach for this disease.

Figure 1. Single-cell transcriptomic landscape of human aortic tissue across inflammatory and aneurysmal conditions. Single-cell RNA sequencing and spatial transcriptomics were performed on 12 surgically resected thoracic aortic specimens: 6 clinically induced aortitis (CIA), 3 giant cell arteritis (GCA), 1 thoracic aortic aneurysm (TAA), and 2 healthy controls. A total of 70,619 cells were analyzed. Differential gene expression, subcluster analysis, pathway scoring, and spatial co-localization analyses were performed. (A) Uniform Manifold Approximation and Projection (UMAP) embedding of aortic cells from healthy controls, TAA, CIA, and GCA patients, colored by condition. Each point represents a single cell. (B) Stacked bar plot depicting the proportional composition of cell clusters within each condition, illustrating shifts in cellular abundance across disease states. (C-F) UMAP plots of major aortic cell populations identified by unsupervised clustering, shown separately for (C) myeloid cells (MC), (D) B cells, (E) T cells, and (F) endothelial cells (EC), with subclusters indicated by color.

ACR Meeting Abstracts - https://acrabstracts.org/abstract/a-single-cell-and-spatial-transcriptomic-atlas-of-the-inflamed-aorta-decoding-the-pathogenesis-of-clinically-isolated-aortitis/