Global Transcriptomic Profiling Identifies Differential Gene Expression Signatures Between Inflammatory and Noninflammatory Aortic Aneurysms

Abstract

Objective To identify hallmark genes and biomolecular processes in aortitis using high‐throughput gene expression profiling, and to provide a range of potentially new drug targets (genes) and therapeutics from a pharmacogenomic network analysis. Methods Bulk RNA sequencing was performed on surgically resected ascending aortic tissues from inflammatory aneurysms (giant cell arteritis [GCA] with or without polymyalgia rheumatica, n = 8; clinically isolated aortitis [CIA], n = 17) and noninflammatory aneurysms (n = 25) undergoing surgical aortic repair. Differentially expressed genes (DEGs) between the 2 patient groups were identified while controlling for clinical covariates. A protein–protein interaction model, drug–gene target information, and the DEGs were used to construct a pharmacogenomic network for identifying promising drug targets and potentially new treatment strategies in aortitis. Results Overall, tissue gene expression patterns were the most associated with disease state than with any other clinical characteristic. We identified 159 and 93 genes that were significantly up‐regulated and down‐regulated, respectively, in inflammatory aortic aneurysms compared to noninflammatory aortic aneurysms. We found that the up‐regulated genes were enriched in immune‐related functions, whereas the down‐regulated genes were enriched in neuronal processes. Notably, gene expression profiles of inflammatory aortic aneurysms from patients with GCA were no different than those from patients with CIA. Finally, our pharmacogenomic network analysis identified genes that could potentially be targeted by immunosuppressive drugs currently approved for other inflammatory diseases. Conclusion We performed the first global transcriptomics analysis in inflammatory aortic aneurysms from surgically resected aortic tissues. We identified signature genes and biomolecular processes, while finding that CIA may be a limited presentation of GCA. Moreover, our computational network analysis revealed potential novel strategies for pharmacologic interventions and suggests future biomarker discovery directions for the precise diagnosis and treatment of aortitis.

Stem-like CD4 + T cells in perivascular tertiary lymphoid structures sustain autoimmune vasculitis

“…Underlying disease processes did not affect expression patterns of the 22 TLS-associated gene transcripts (Fig. 2E) ( 21 ). Expression of CXCL13 and CCL19 , but not of CCL21 , was up-regulated in aortitis and closely associated with the size of the mononuclear cell aggregates (Fig.…”

“…The tissues were treated with buffer PKD and proteinase K and placed in a QIAcube for RNA purification (extraction) as previously described ( 21 ). Libraries were prepared using a TruSeq RNA Exome Capture kit (Illumina) following the manufacturer’s protocol as previously described ( 21 ). The raw reads were preprocessed using the nf-core RNA-seq pipeline (version 3.3), aligned to the human reference genome GRCh38.…”

“…Bulk RNA-seq data analysis RNA was extracted from formalin-fixed paraffin-embedded block sections. The tissues were treated with buffer PKD and proteinase K and placed in a QIAcube for RNA purification (extraction) as previously described (21). Libraries were prepared using a TruSeq RNA Exome Capture kit (Illumina) following the manufacturer's protocol as previously described (21).…”

Vascular disease persistence in giant cell arteritis: are stromal cells neglected?

“…Furthermore, studies employing transcriptomic analyses of GCA and non-inflamed aortic tissues revealed an enrichment of interferon (I, II and III) signatures and JAK/STAT signalling in GCA 88 89. Pharmacogenomic network analysis also identified IFN-γ and CXCL10 to be druggable candidate genes 89. It is however noteworthy that disease duration prior to surgery is not specified for this cohort and the representative GCA-aortic cohort was relatively small 89…”

“…These studies potentially suggest a role for Th-1 cytokines in disease chronicity, yet the exact mechanisms by which T-cell subsets exert their effector functions and their synergistic partners remain elusive. Furthermore, studies employing transcriptomic analyses of GCA and non-inflamed aortic tissues revealed an enrichment of interferon (I, II and III) signatures and JAK/STAT signalling in GCA 88 89. Pharmacogenomic network analysis also identified IFN-γ and CXCL10 to be druggable candidate genes 89.…”