A composite immune signature parallels disease progression across T1D subjects

At diagnosis, most people with type 1 diabetes (T1D) produce measurable levels of endogenous insulin, but the rate at which insulin secretion declines is heterogeneous. To explain this heterogeneity, we sought to identify a composite signature predictive of insulin secretion, using a collaborative assay evaluation and analysis pipeline that incorporated multiple cellular and serum measures reflecting beta cell health and immune system activity. The ability to predict decline in insulin secretion would be useful for patient stratification for clinical trial enrollment or therapeutic selection. Analytes from 12 qualified assays were measured in shared samples from subjects newly diagnosed with T1D. We developed a computational tool to identify a composite panel associated with decline in insulin secretion over 2 years after diagnosis. The tool employs multiple filtering steps to reduce data dimensionality, incorporates error-estimation techniques including cross-validation and sensitivity analysis, and is flexible to assay type, clinical outcome and disease setting. Using this novel analytical tool, we identified a panel of immune markers that, in combination, are highly associated with loss of insulin secretion. The methods used here represent a novel process for identifying combined immune signatures that predict outcomes relevant for complex and heterogeneous diseases like T1D

Association of the CpG Methylation Pattern of the Proximal Insulin Gene Promoter with Type 1 Diabetes

The insulin (INS) region is the second most important locus associated with Type 1 Diabetes (T1D). The study of the DNA methylation pattern of the 7 CpGs proximal to the TSS in the INS gene promoter revealed that T1D patients have a lower level of methylation of CpG -19, -135 and -234 (p = 2.10−16) and a higher methylation of CpG -180 than controls, while methylation was comparable for CpG -69, -102, -206. The magnitude of the hypomethylation relative to a control population was 8–15% of the corresponding levels in controls and was correlated in CpGs -19 and -135 (r = 0.77) and CpG -135 and -234 (r = 0.65). 70/485 (14%) of T1D patients had a simultaneous decrease in methylation of CpG -19, -135, -234 versus none in 317 controls. CpG methylation did not correlate with glycated hemoglobin or with T1D duration. The methylation of CpG -69, -102, -180, -206, but not CpG -19, -135, -234 was strongly influenced by the cis-genotype at rs689, a SNP known to show a strong association with T1D. We hypothesize that part of this genetic association could in fact be mediated at the statistical and functional level by the underlying changes in neighboring CpG methylation. Our observation of a CpG-specific, locus-specific methylation pattern, although it can provide an epigenetic biomarker of a multifactorial disease, does not indicate whether the reported epigenetic pattern preexists or follows the establishment of T1D. To explore the effect of chronic hyperglycemia on CpG methylation, we studied non obese patients with type 2 diabetes (T2D) who were found to have decreased CpG-19 methylation versus age-matched controls, similar to T1D (p = 2.10−6) but increased CpG-234 methylation (p = 5.10−8), the opposite of T1D. The causality and natural history of the different epigenetic changes associated with T1D or T2D remain to be determined

Type 1 diabetes: translating mechanistic observations into effective clinical outcomes

Type 1 diabetes remains an important health problem, particularly in Western countries where the incidence has been increasing in younger children(1). In 1986, Eisenbarth described Type 1 diabetes as a chronic autoimmune disease. Work over the past 3 ½ decades has identified many of the genetic, immunologic, and environmental factors that are involved in the disease and have led to hypotheses concerning its pathogenesis. Based on these findings, clinical trials have been conducted to test these hypotheses but have had mixed results. In this review, we discuss the findings that have led to current concepts of the disease mechanisms, how this understanding has prompted clinical studies, and the results of these studies. The findings from preclinical and clinical studies support the original proposed model for how type 1 diabetes develops, but have also suggested that this disease is more complex than originally thought and will require broader treatment approaches