Interferons are the key cytokines acting on pancreatic islets in type 1 diabetes
The pro-inflammatory cytokines IFNa, IFN?, IL-1ß and TNFa may contribute to innate and adaptive immune responses during islet inflammation (insulitis) in type 1 diabetes (T1D). We used deep RNA-sequencing analysis to characterize the response of human pancreatic beta cells to each cytokine individually and compared the signatures obtained with those present in islets of individuals affected by T1D. IFNa and IFN? had a much greater impact on the beta cell transcriptome when compared to IL-1ß and TNFa. The IFN-induced gene signatures have a strong correlation with those observed in beta cells from T1D patients, and the level of expression of specific IFN-stimulated genes is positively correlated with proteins present in islets of these individuals, regulating beta cell responses to “danger signals” such as viral infections. These data suggest that IFNa and IFN? are the central cytokines at the islet level in T1D, contributing to the triggering and amplification of autoimmunity. Overall design: The raw RNA-seq data of EndoC-BH1 cells treated with IFNa, IL-1B, and TNFa [ 2 x 150-bp paired-end with a sequencing depth > 200 million reads (Eurofins Genomics, Germany)] were first subjected to a quality check using fastp to remove low quality reads and adaptor trimming. The passing reads were then subjected to quality control (QC) using FastQC (Babraham Bioinformatics, Cambridge, UK). For comparison purposes, these five paired RNA-seq replicates were re-analyzed as described below. Gene expression was quantified using Salmon v1.457 with additional parameters “-seqBias -gcBias -validateMappings” and expressed in TPM (transcripts per million). GENCODE v36 was used as the reference genome and indexed with default k-mer values. The genes differentially expressed after exposure to cytokines were identified by DESeq2 v1.30.158. For each gene, a log2 fold change value was obtained based on the comparison performed (cytokine-treated condition versus non-treated condition). Each gene comparison has an associated Wald test statistic, p-value, and an adjusted p-value (Benjamini-Hochberg correction). Genes presenting an adjusted p-value < 0.05 were considered significantly differentially expressed.