Investigation of coordination and order in transcription regulation of innate and adaptive immunity genes in type 1 diabetes

Abstract

Background: Type 1 diabetes (T1D) is an autoimmune disease and extensive evidence has indicated a critical role of both the innate and the adaptive arms of immune system in disease development. To date most clinical trials of immunomodulation therapies failed to show efficacy. A number of gene expression studies of T1D have been carried out. However, a systems analysis of the expression variations of the innate and adaptive immunity gene sets, or their co-expression network structures in cohorts at different disease states or of different disease risks, is not available till now. Methods: We utilized data from a large gene expression study that included transcription profiles of control peripheral blood mononuclear cells (PBMC) exposed to plasma of 148 human subjects from four cohorts that included unrelated healthy controls (uHC), recent onset T1D patients (RO-T1D), and healthy siblings of probands that possess high (HRS, High Risk Sibling) or low (LRS, Low Risk Sibling) risk HLA haplotypes. Both weighted and non-weighted co-expression networks were constructed in each cohort separately, and edge weight distribution and the activation of known protein complexes were examined. The co-expression networks of the innate and adaptive immunity genes were further examined in more detail through a number of network measures that included network density, Shannon entropy, h-index, and the scaling exponent γ of degree distribution. Pathway analysis was carried out using CoGA, a tool for detecting significant network structural changes of a gene set. Results: Weighted network edge distribution revealed a globally weakened co-expression network induced by the RO-T1D cohort as compared to that by the uHC, suggesting a broad spectrum loss of transcriptional coordination. The two healthy T1D family cohorts (HRS and LRS) induced more active but heterogeneous transcription coordination globally, and among both the innate and the adaptive immunity genes, than the uHC. This finding is consistent with our previous report of these cohorts sharing a heightened innate inflammatory state. The spike-in of IL-1RA to RO-T1D sera improved co-expression network strength of both the innate and the adaptive immunity genes, and enabled a global order recovery in transcription regulation that resulted in significantly increased number of activated protein complexes. Many of the top pathways that showed significant difference in co-expression network structures and order between RO-T1D and uHC have strong links to T1D. Conclusions: Network level analysis of the innate and adaptive immunity genes, and the whole genome, revealed striking cohort-dependent differences in co-expression network structural measures, suggesting their potential in cohort classification and disease-relevant pathway identification. The results demonstrated the advantages of systems analysis in defining molecular signatures as well as in predicting targets in future research.