Background Autophagy, a lysosome-mediated catabolic process that allows cells to degrade unwanted cytoplasmic constituents and to recycle nutrients, is also involved in innate and adaptive immune responses. It is induced by different stress signals including cytokines such as interferons (IFN). In systemic lupus erythematosus (SLE), a pivotal role for IFN is supported by gene expression studies. A dysregulation of autophagy has been recently reported in SLE patients and hydroxychloroquine (HCQ), its main treatment, is an inhibitor of autophagy.
Objectives The aim of this study was to evaluate autophagy pathways and identify autophagy-related (A-R) biomarkers in SLE patients.
Methods After identification of A-R transcripts (PubMed, KEGG), candidate A-R transcripts were selected through a data-driven approach. Publicly available datasets related to “human/blood/SLE” gene expression profiles and restrained to types of platforms (illumina or affymetrix) as well as tissue (whole blood (WB) or PBMC) were retrieved from GEO database. Candidate A-R transcripts corresponded to those with a significant differential expression between SLE patients (n=157) and matched healthy controls (adjusted p-value <0.05) in the LUPUCE cohort dataset. Fold change (FC) analyses across multiple SLE datasets and interferon inducibility (interferome database) of these candidates allowed the selection of a final panel. Finally, the relative expression of this panel of A-R transcripts (ΔΔCT) was determined by RT-qPCR on WB samples from SLE patients (n=32) and their controls (n=14). Results were correlated with clinical (SLEDAI score) and biological (including IFN modular transcriptional signatures) characteristics as well as treatments of SLE patients (Brown-Mood test).
Results Overall, 97 A-R transcripts were identified through the literature search and 12 SLE datasets from GEO database (WB n=8, PBMC n=4). Among SLE patients from the LUPUCE cohort study, 16 genes (corresponding to 23 A-R Transcripts) were differentially expressed, of which 9 with a significant FC (>1.3): 8 overexpressed (RGS19, MAP1LC3B, ATG7, RAB24, APP, TGM2, TNFSF10/TRAIL and STAT1) and 1 underexpressed (CASP8). The expression levels of a panel of 5 of these candidates (TRAIL, STAT1, CASP8, WIPI1, ATG7) were determined by PCR and only TRAIL and STAT1 exhibited significant overexpression in SLE patients compared to controls (p=0.0105 and 0.0001 respectively). For TRAIL, expression was significantly lower in patients with completely inactive disease (SLEDAI=0) compared to other SLE patients with moderate to important disease activity (p=0.0338). For these 2 genes, no clinical of biological differences were observed between high expressers (> mean ΔCT ± 2SD) and other SLE patients, except that high STAT1 and TRAIL expressers had significantly higher modular transcriptional type I and II IFN signatures, and a trend for being less treated by HCQ was observed for high STAT1 expressers (p=0.075).
Conclusions An exploratory transcriptome data-driven approach identified autophagy-related transcripts as candidate biomarkers in SLE, and suggests that autophagy is induced by type I IFN via the JAK1-STAT1 pathway and may present a potential therapeutic target in this disease.
Disclosure of Interest None declared
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