Quantitative measurement of T1D risk through molecular signature analysis

描述（由申请人提供）：成功延缓或预防1型糖尿病（T1D）将在很大程度上取决于区分那些将发展为T1D的个体与那些具有高风险主要组织相容性复合体等位基因和/或胰岛细胞自身抗体（AA）滴度的个体。为了实现这一目标，我们开发并应用了一种灵敏的生物测定方法，在控制良好的“报告者”外周血单核细胞（PBMC）群体中测量血清或血浆对诱导转录物水平的影响。通过这种方法，我们定义了一个近期发病（RO） T1D特征，其中包括由白细胞介素-1调节的基因，白细胞介素-1是一种在体外诱导胰腺细胞凋亡并共同刺激t细胞的细胞因子。这种反应是通过阻断培养物中的IL-1受体来调节的，与不相关的健康对照、长期T1D患者或患有其他疾病的患者的样品诱导的反应不同。到目前为止，我们已经检查了9例T1D进展者的纵向样本；在所有病例中，RO T1D特征在发病前都很明显。重要的是，这种特征在3/3的案例中被检测到，这些案例在AA开发之前就有样品。我们的数据支持这样的假设，即与胰腺细胞自身免疫相关的稀释细胞因子环境足以诱导独特的t1d特异性转录谱；这一特征反映了主动自身免疫，是疾病特异性的，可以改善AA以外的疾病预测。为了响应项目公告“对PAR-11-350的响应：使用选定的1型糖尿病临床研究（DP3）的生物样本进行研究”，我们提出了这项合作的多中心研究，将仔细研究以下目标，以完善这种机械信息生物标志物，并定义其预测潜力和效用：1)将该特征定义为T1D分期的定量早期生物标志物。2)明确t1d特征的疾病特异性。

DESCRIPTION (provided by applicant): Successfully delaying or preventing type 1 diabetes (T1D) will depend heavily on distinguishing those individuals that will progress to T1D among those individuals possessing high risk major histocompatibility complex alleles and/or titers for islet cell auto-antibodies (AA). Towards this goal, we have developed and applied a sensitive bioassay that measures the effect of serum or plasma on induced transcript levels in a well- controlled "reporter" peripheral blood mononuclear cell (PBMC) population. With this approach we have defined a recent onset (RO) T1D signature that includes genes regulated by interleukin-1, a cytokine that induces pancreatic ¿-cell apoptosis in vitro and co-stimulates T-cells. This response is modulated by blocking IL-1 receptor in cultures and is distinct from that induced by samples of unrelated healthy controls, long- standing T1D patients, or patients possessing other diseases. So far, we have examined longitudinal samples of 9 progressors to T1D; in all cases the RO T1D signature was evident prior to onset. Importantly, this signature was detected in 3/3 cases where samples were available prior to AA development. Our data support the hypothesis that the dilute cytokine milieu associated with autoimmunity towards the pancreatic ¿-cells is sufficient to induce a unique T1D-specific transcriptional profile; this signature reflects active autoimmunity, is disease specific, and may improve disease prediction beyond AA. In response to Program Announcement " Response to PAR-11-350: Research Using Biosamples From Selected Type 1 Diabetes Clinical Studies (DP3)" we propose this collaborative, multicenter study where the following aims will be perused to refine this mechanistically informative biomarker and define its predictive potential and utility: 1) Define the signature as a quantitative early biomarker for staging T1D progression. 2) Define disease-specificity of the T1D-signature.