180. Deconvolution of transcriptomic data reveals immune cell landscape of inflammatory infiltrates in giant cell arteritis

Background: Giant cell arteritis (GCA) is the most common form of vasculitis in people over 50 years old and can lead to serious ischaemic complications, such as permanent visual loss. It is characterized by inflammation in medium- and large-sized vessels, but the molecular events leading to different phenotypes remains largely unexplained. Current treatment choices are very limited and high glucocorticoid doses are required at disease onset, despite carrying a substantial risk of side effects. Better understanding of the molecular mechanisms underlying GCA is needed to discover alternative treatment options and to improve molecular stratification of GCA management. Our study aims to integrate bulk and single-cell transcriptomes generated from temporal artery biopsies to reveal cell-type-specific expression profiles associated with distinct histological patterns of arterial inflammation in GCA.

Methods: Patients from the UK GCA Consortium (UKGCA; n=41) and Newcastle and North Tyneside registry (NNT; n=9) were selected for the study. All UKGCA cases had a positive histological diagnosis as part of routine clinical care. RNA was extracted from formalin-fixed paraffin embedded temporal artery biopsies from UKGCA participants and subjected to next-generation sequencing, while cells from all (5 positive and 4 negative) NNT biopsies were dissociated from fresh tissue and subjected to single-cell RNA-sequencing, using 10x Genomics. Various clinical and histological variables, identified in a serial section, were recorded for each patient. Deconvolution analysis was performed using the MuSIC software (https://github.com/xuranw/MuSiC) to infer sample-specific cell-type proportions and to enable cell-type-specific differential expression analysis. All statistical testing for clinical and histological features was performed using the non-parametric Mann-Whitney-Wilcoxon test to avoid making parametric assumptions. False Discovery Rate was used to account for multiple testing.

Results: Transcripts differentially expressed in patients with specific histological features were identified. Those showing the strongest associations were: the presence of giant cells (1571 transcripts; FDR-corrected p-value <0.01) and the extent of inflammation in the intima, media and adventitia (3301, 2637 and 5359 transcripts respectively; all FDR-corrected p-values <0.01). The deconvoluted data for cell-type-specific differences revealed the myofibroblast population to have the strongest association with transcriptomic profiles which confirms the importance of vascular remodelling. Additional analyses to assess the influence of confounding factors on gene expression, in particular sex, age and duration of steroid treatment were also conducted, resulting in no clear evidence for a confounding effect from patients’ age (UKGCA: 59-92; NNT: 64-84) or steroid treatment duration (UKGCA: 0-16 days; NNT: 4-13 days). Gender was found to be a likely source of confounding and secondary to inclusion of the sex chromosomes in the analysis pipeline.

Conclusions: Our findings reveal a previously unreported landscape of cell population abundance levels in GCA biopsies and their associations with different inflammatory phenotypes. We also aim to provide novel insights into cell-type-specific expression profiles of both, transcripts already known to be involved in GCA pathogenesis, as well as novel molecular signatures that might have potential for therapeutic targeting. Although no clear confounding influence of unavoidable prednisolone exposure prior to biopsy was found, such effects will be further investigated in an expanded patient cohort. Ultimately, we aim to identify novel therapeutically amenable candidate genes and pathways involved in the inflammatory response.

Disclosures: AWM has received research grant and educational funding or undertaken consultancy for the following pharmaceutical companies in the last 5 years: AstraZeneca, Kiniska Pharmaceuticals, Regeneron, Roche/Chugai, Sanofi and Vifor.