MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.
Curr Diab Rep. 2020 Oct 8;20(11):60. doi: 10.1007/s11892-020-01340-w.
Proteins are the central layer of information transfer from genome to phenome and represent the largest class of drug targets. We review recent advances in high-throughput technologies that provide comprehensive, scalable profiling of the plasma proteome with the potential to improve prediction and mechanistic understanding of type 2 diabetes (T2D).
Technological and analytical advancements have enabled identification of novel protein biomarkers and signatures that help to address challenges of existing approaches to predict and screen for T2D. Genetic studies have so far revealed putative causal roles for only few of the proteins that have been linked to T2D, but ongoing large-scale genetic studies of the plasma proteome will help to address this and increase our understanding of aetiological pathways and mechanisms leading to diabetes. Studies of the human plasma proteome have started to elucidate its potential for T2D prediction and biomarker discovery. Future studies integrating genomic and proteomic data will provide opportunities to prioritise drug targets and identify pathways linking genetic predisposition to T2D development.
蛋白质是从基因组到表现型的信息传递的核心层，代表了最大的一类药物靶点。我们综述了高通量技术的最新进展，这些技术为血浆蛋白质组的全面、可扩展分析提供了可能，从而提高了对 2 型糖尿病（T2D）的预测和机制理解。
技术和分析上的进步使得能够识别新型的蛋白质生物标志物和特征，这有助于解决现有方法在预测和筛选 T2D 方面的挑战。遗传研究迄今为止仅揭示了少数与 T2D 相关的蛋白质的可能因果作用，但正在进行的大规模血浆蛋白质组遗传研究将有助于解决这一问题，并提高我们对导致糖尿病的病因途径和机制的理解。对人类血浆蛋白质组的研究已经开始阐明其在 T2D 预测和生物标志物发现方面的潜力。未来整合基因组和蛋白质组数据的研究将提供机会来确定药物靶点，并确定将遗传易感性与 T2D 发展联系起来的途径。
