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）的特征是自身免疫性功能障碍和胰腺β细胞破坏。不幸的是，对这一过程了解甚少，目前治疗1型糖尿病的最佳方法是外源胰岛素的给药。为了更好地理解这些机制并开发新的疗法，迫切需要能够可靠地预测疾病阶段的生物标志物。

涵盖的领域：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细胞死亡方面起着重要作用。MS还是识别生物标志物的领先技术。本文将讨论这一点以及技术难点和新技术，这些技术和新技术将提供机会来深度表征少量样品并分析大量样品。

专家意见：了解疾病机制和发现与疾病相关的生物标记是高度相关的目标。理想的生物标志物应是特定于疾病过程不同阶段的分子，这些分子将从β细胞释放到血液中。然而，由于人体中胰腺β细胞的数量少以及靶器官和疾病过程的异质性，此类分子可能以微量存在于血液中。