Variability of Primary Sjögren's Syndrome Is Driven by Interferon-α and Interferon-α Blood Levels Are Associated With the Class II HLA-DQ Locus

Abstract

Objective: Primary Sjögren's syndrome (SS) is the second most frequent systemic autoimmune disease, affecting 0.1% of the general population. To characterize the molecular and clinical variabilities among patients with primary SS, we integrated transcriptomic, proteomic, cellular, and genetic data with clinical phenotypes in a cohort of 351 patients with primary SS.

Methods: We analyzed blood transcriptomes and genotypes of 351 patients with primary SS who were participants in a multicenter prospective clinical cohort. We replicated the transcriptome analysis in 3 independent cohorts (n = 462 patients). We determined circulating interferon-α (IFNα) and IFNγ protein concentrations using digital single molecular arrays (Simoa).

Results: Transcriptome analysis of the prospective cohort showed a strong IFN gene signature in more than half of the patients; this finding was replicated in the 3 independent cohorts. Because gene expression analysis did not discriminate between type I IFN and type II IFN, we used Simoa to demonstrate that the IFN transcriptomic signature was driven by circulating IFNα and not by IFNγ protein levels. IFNα protein levels, detectable in 75% of patients, were significantly associated with clinical and immunologic features of primary SS disease activity at enrollment and with increased frequency of systemic complications over the 5-year follow-up. Genetic analysis revealed a significant association between IFNα protein levels, a major histocompatibility (MHC) class II haplotype, and anti-SSA antibody. Additional cellular analysis revealed that an MHC class II HLA-DQ locus acts through up-regulation of HLA class II molecules on conventional dendritic cells.

Conclusion: We identified the predominance of IFNα as a driver of primary SS variability, with IFNα demonstrating an association with HLA gene polymorphisms.

Figure 1

Unsupervised transcriptomic analysis enables robust stratification of patients with primary Sjögren's syndrome (SS) in 4 different cohorts. A, Expression of marker genes across the 4 clusters of patients from the Assessment of Systemic Signs and Evolution in Sjögren's Syndrome (ASSESS) cohort, normalized by row, and annotation of the identified gene modules based on hierarchical clustering. B, Expression of 6 genes identified as marker genes across the patients from the ASSESS cohort. Values are shown as box plots, where the line inside the box represents the median, the box represents the interquartile range, and the whiskers represent the 10th and 90th percentiles. C, Expression of marker genes across the 3 clusters of patients identified in the Norwegian cohort and annotation of the identified gene modules based on hierarchical clustering. D, Expression of marker genes across the 4 clusters of patients identified in the cohort from Lessard et al (7) and annotation of the identified gene modules based on hierarchical clustering. E, Expression of marker genes across the 4 clusters of patients identified in the cohort from James et al (8) and annotation of the identified gene modules based on hierarchical clustering. F, Intersection between the sets of marker genes identified in the 4 different primary SS cohorts. G, Association between erythroid (ER) transcriptomic score and EULAR Sjögren's Syndrome Disease Activity Index (ESSDAI) score, anti‐SSA status, and anti‐SSB status. ISG = interferon‐stimulated gene.

Figure 2

Quantification of interferon‐α (IFNα) and IFNγ protein serum concentrations by digital enzyme‐linked immunosorbent assay reveals the pivotal role of IFNα in patients with primary Sjögren's syndrome (SS). A, IFNα (left) and IFNγ (right) serum titers across clusters. B, Description of the linear model used to describe gene expression (top) and Venn diagram showing the number of genes transcriptionally controlled by IFNα, IFNγ, or both (bottom). C, IFNα (top) and IFNγ (bottom) concentrations based on anti‐SSA (left) and anti‐SSB (right) status. D, Correlations between IFNα and rheumatoid factor (RF) concentrations (top) and between IFNγ and RF concentrations (bottom). Dashed lines are based on the linear regression between the 2 variables. E, IFNα (top) and IFNγ (bottom) concentrations based on presence versus absence of an active biologic domain according to components of the EULAR Sjögren's Syndrome Disease Activity Index (ESSDAI). F, Concentrations of IFNα (left) and IFNγ (right) according to focus score of inflammatory infiltrates in the salivary glands of patients with primary SS. For box plots, the line inside the box represents the median, the box represents the interquartile range, and the whiskers extend to the most extreme data point that is no more than 1.5 times the interquartile range from the box. Color figure can be viewed in the online issue, which is available at http://onlinelibrary.wiley.com/doi/10.1002/art.42265/abstract.

Figure 3

Genome‐wide association study reveals a genetic determinant in patient stratification and interferon‐α (IFNα) blood concentration in patients with primary Sjögren's syndrome. A, Genome‐wide association between single‐nucleotide polymorphisms (SNPs) and IFNα concentration. Dashed line corresponds to the threshold for a suggested genome‐wide association, and solid line corresponds to a significant genome‐wide association. B, LocusZoom plot of the HLA region. C, IFNα concentration according to the rs9273012 SNP status. D, IFNα gene expression in whole blood from 1,000 healthy donors from the Milieu Intérieur cohort, under conditions of no stimulation versus stimulation with lipopolysaccharide (LPS) versus stimulation with poly(I‐C). E, P values indicating possible statistical significance of associations between the rs9273012 SNP and the 166 immunophenotypes measured in the Milieu Intérieur study from Patin et al (30). The top horizontal line represents the threshold after Bonferroni correction for multiple testing at P = 0.05. F, Mass cytometry analysis of data from Mingueneau et al (9). Panels show the 3 dendritic cell (DC) populations defined using unsupervised analysis (top left) and HLA–DR expression in the 3 DC populations (bottom left), as well as mean fluorescence intensity (MFI) results for HLA–DR (top right) and CD40 (bottom right) in the 3 DC populations based on anti‐SSA status. For box plots, the line inside the box represents the median, the box represents the interquartile range, and the whiskers extend to the most extreme data point that is no more than 1.5 times the interquartile range from the box. moDCs = monocyte‐derived DCs; cDCs = conventional DCs; pDCs = plasmacytoid DCs; Neg = negative; Pos = positive. Color figure can be viewed in the online issue, which is available at http://onlinelibrary.wiley.com/doi/10.1002/art.42265/abstract.