Longitudinal expression profiling of CD4+ and CD8+ cells in patients with active to quiescent giant cell arteritis

• Main Authors: Elisabeth De Smit, Samuel W. Lukowski, Lisa Anderson, Anne Senabouth, Kaisar Dauyey, Sharon Song, Bruce Wyse, Lawrie Wheeler, Christine Y. Chen, Khoa Cao, Amy Wong Ten Yuen, Neil Shuey, Linda Clarke, Isabel Lopez Sanchez, Sandy S. C. Hung, Alice Pébay, David A. Mackey, Matthew A. Brown, Alex W. Hewitt, Joseph E. Powell
• Format: Article
• Language: English
• Published: BMC 2018-07-01
• Series: BMC Medical Genomics
• Subjects: Giant cell arteritis; Disease biomarkers; RNA sequencing; Expression profiling; Transcriptome; CD4 & CD8 T lymphocytes
• Online Access: http://link.springer.com/article/10.1186/s12920-018-0376-4

Abstract Background Giant cell arteritis (GCA) is the most common form of vasculitis affecting elderly people. It is one of the few true ophthalmic emergencies but symptoms and signs are variable thereby making it a challenging disease to diagnose. A temporal artery biopsy is the gold standard to confirm GCA, but there are currently no specific biochemical markers to aid diagnosis. We aimed to identify a less invasive method to confirm the diagnosis of GCA, as well as to ascertain clinically relevant predictive biomarkers by studying the transcriptome of purified peripheral CD4+ and CD8+ T lymphocytes in patients with GCA. Methods We recruited 16 patients with histological evidence of GCA at the Royal Victorian Eye and Ear Hospital, Melbourne, Australia, and aimed to collect blood samples at six time points: acute phase, 2–3 weeks, 6–8 weeks, 3 months, 6 months and 12 months after clinical diagnosis. CD4+ and CD8+ T-cells were positively selected at each time point through magnetic-assisted cell sorting. RNA was extracted from all 195 collected samples for subsequent RNA sequencing. The expression profiles of patients were compared to those of 16 age-matched controls. Results Over the 12-month study period, polynomial modelling analyses identified 179 and 4 statistically significant transcripts with altered expression profiles (FDR < 0.05) between cases and controls in CD4+ and CD8+ populations, respectively. In CD8+ cells, two transcripts remained differentially expressed after 12 months; SGTB, associated with neuronal apoptosis, and FCGR3A, associatied with Takayasu arteritis. We detected genes that correlate with both symptoms and biochemical markers used for predicting long-term prognosis. 15 genes were shared across 3 phenotypes in CD4 and 16 across CD8 cells. In CD8, IL32 was common to 5 phenotypes including Polymyalgia Rheumatica, bilateral blindness and death within 12 months. Conclusions This is the first longitudinal gene expression study undertaken to identify robust transcriptomic biomarkers of GCA. Our results show cell type-specific transcript expression profiles, novel gene-phenotype associations, and uncover important biological pathways for this disease. In the acute phase, the gene-phenotype relationships we have identified could provide insight to potential disease severity and as such guide in initiating appropriate patient management.