Our group has a manuscript just out in Diabetes in which we have investigated the role of type 1 interferon signalling in the pathogenesis of the autoimmune disease T1D. The work was led by Ricardo Ferreira and Hui Guo. Type 1 interferon (IFN) signalling is a evolutionarily conserved biological pathway that plays a major role in the defense against viral infections. Every mammal expresses IFN genes and birds, amphibians and fish also express functionally homologous molecules. However, a side effect of the IFN responses is that they can also cause bystander tissue damage and can also lead to the activation of an autoimmune response. In fact, in humans chronically activated IFN signalling has been recently implicated in the aetiology of several systemic autoimmune diseases such as systemic lupus erythematosus (SLE) or vasculitis. Importantly, in T1D, genetic evidence from genome-wide association studies has pointed to an important role of this biological pathway in this disease, including the identification of IFIH1, a major sensor of viral infections, as a susceptibility gene.
In this study, we were interested in investigating if T1D patients showed evidence of an exacerbated IFN response, by measuring the global transcriptional profile of blood cells by microarray. One major challenge was to integrate a large amount of transcriptional data into a quantitative metric of IFN responses. For that we identified a set of IFN-inducible genes based on timecourse data from stimulated cells, and applied a principal components (PC) analysis. Between the T1D low and high expression groups and between the control groups, clear batch effects were observed, which could not be removed by various normalisation methods. We were unable to use the standard PC correction as this also removed evidence for the IFN signature within batches. Instead, we projected the T1D cases and controls onto the first PC that explained over 60% of variation in the homogeneous group – SLE samples – to circumvent batch effects. This first PC was then defined as the quantitative measure of an underlying IFN signature.
In comparison with SLE patients, we found that established T1D patients cannot be clearly clustered according to the expression of this IFN signature. However, we were also able to characterise the IFN signature in a large prospective birth cohort of children at high risk of developing T1D (BABYDIET), with longitudinal expression measurements. Linear mixed models were fitted to allow for within-subject correlations. Interestingly, in this cohort, we found evidence for an increased expression of IFN-inducible genes before the development of T1D-specific autoantibodies which correlated temporally with parental reports of recent viral infection.
The relationship of IFN gene expression with future autoantibody detection was replicated in a completely independent study from a Finnish cohort, in a co-submitted manuscript (link?), which strongly supports the hypothesis that increased IFN signalling is a risk factor for the development of the first autoimmune events in T1D.
This study was only possible through collaboration with Ezio Bonifacio and Annette Ziegler who are responsible for the unique BABYDIET cohort of children at risk from type 1 diabetes, followed longitudinally from birth. We thank those children and their families for their participation in this study which continues to reveal information about the earliest events preceding type 1 diabetes.