Introduction: Type 1 diabetes (T1D) is characterized by autoimmune-induced dysfunction and destruction of the pancreatic beta cells. Unfortunately, this process is poorly understood, and the current best treatment for type 1 diabetes is the administration of exogenous insulin. To better understand these mechanisms and to develop new therapies, there is an urgent need for biomarkers that can reliably predict disease stage.

Areas covered: Mass spectrometry (MS)-based proteomics and complementary techniques play an important role in understanding the autoimmune response, inflammation and beta-cell death. MS is also a leading technology for the identification of biomarkers. This, and the technical difficulties and new technologies that provide opportunities to characterize small amounts of sample in great depth and to analyze large sample cohorts will be discussed in this review.

Expert opinion: Understanding disease mechanisms and the discovery of disease-associated biomarkers are highly interconnected goals. Ideal biomarkers would be molecules specific to the different stages of the disease process that are released from beta cells to the bloodstream. However, such molecules are likely to be present in trace amounts in the blood due to the small number of pancreatic beta cells in the human body and the heterogeneity of the target organ and disease process.

简介：1 型糖尿病 (T1D) 的特点是自身免疫诱导的功能障碍和胰腺 β 细胞的破坏。不幸的是，人们对这一过程知之甚少，目前 1 型糖尿病的最佳治疗方法是施用外源性胰岛素。为了更好地了解这些机制并开发新疗法，迫切需要能够可靠预测疾病阶段的生物标志物。

涵盖领域：基于质谱 (MS) 的蛋白质组学和补充技术在理解自身免疫反应、炎症和 β 细胞死亡方面发挥着重要作用。 MS 也是识别生物标志物的领先技术。本综述将讨论这一点，以及为深入表征少量样本和分析大样本群体提供机会的技术困难和新技术。

专家意见：了解疾病机制和发现疾病相关生物标志物是高度相互关联的目标。理想的生物标志物是从β细胞释放到血液中的疾病过程不同阶段特有的分子。然而，由于人体内胰腺β细胞数量较少以及靶器官和疾病过程的异质性，此类分子很可能在血液中微量存在。