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S01.3 RNA-SEQ in peripheral blood immune cells identifies modular networks predictive and protective for progression from ana positivity to classifiable systemic autoimmune disease
  1. L Carter,
  2. A Psarras,
  3. Z Wigston,
  4. MY Md Yusof and
  5. E Vital
  1. University of Leeds ~ UK

Abstract

ANA-positivity represents a complex ‘At-Risk’ state for development of connective tissue disease (CTD). While ANA may become positive years in advance of clinical CTD, they are also positive in up to 25% of the population, of whom only a small fraction ultimately develop symptoms. Complex immune disturbances iare evident even among ANA-positive individuals who do not ultimately progress to overt disease [1]. In a prospective observational cohort of ANA positive individuals ‘At-Risk’ for CTD we have shown that a validated blood IFN-Score was predictive of progression to classifiable SLE [2]. However, the wider transcriptional fingerprint of the ‘At-Risk’ state and other factors modifying risk of progression are not known. We hypothesise that diverse immune processes, both independent and interacting with IFN pathway activation, could modulate risk of progression.

Purpose To investigate how peripheral blood immune cell transcriptional signatures derived by RNA Seq associate with progression or non-progression from At-Risk ANA positivity to clinically apparent CTD.

Methods Peripheral blood mononuclear cells (PBMCs) were isolated at baseline from ANA-positive At-Risk individuals demonstrating ≤1 clinical criterion for classifiable CTD, symptom duration <12 months and naive of glucocorticoid or immunosuppressive therapy. Progression was prospectively adjudicated at 12 months and defined as accrual of clinical/immunological criteria sufficient to meet classification for SLE (SLICC 2012) or other relevant CTDs. Bulk RNASeq was performed on PMBCs from 16 Progressors and 19 non-Progressors. Weighted gene co-expression network analysis (WCGNA) was performed using WCGNA package and gene ontology (GO) enrichment was envaluated using ClusterProfiler, in R Bioconductor. The top 20% genes ranked by connectivity were defined as hub genes. Major cell subsets were quantified in parallel by multiparameter flow cytometry.

Results 29 modules were identified by WCGNA. Eigengenes for 3 modules were significantly associated with progression status. A single, 152 gene module showed strong positive correlation with progression (R=0.55, p<0.001). Hub genes were significantly enriched for type I IFN-siganlling pathway and included established interferon stimulated genes such as IFI44 and IRF7.

Two further modules had a negative, ie protective, association with progression; a smaller 37 gene module, correlated negatively with both blood interferon score (R=-0.46, p=0.005) and with progression (R=-0.43, p=0.01). A larger 252 gene module was also negatively related to progression (R=-0.43, p=0.009) and demonstrated significant pathway enrichment for regulation of cell morphogenesis and actin cyctoskeleton organisation.

Conclusions We identify novel modular transcriptomic signatures implicated in SLE disease initiation. We show (i) IFN-pathway activation is the single strongest transcriptomic risk marker of progression from the ‘At Risk state’ and (ii) we identify 2 novel protective signatures in peripheral blood immune cells for which further functionally characterization is ongoing.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

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