Sci Transl Med:II型糖尿病的3个不同亚组

    西奈山医学院研究人员用精密医学方法来梳理1万1000名糖尿病患者的电子病历中的临床数据和基因组数据，研究人员确定了II型糖尿病中的3个不同的亚组。这些发现可能会带来对每个疾病亚型的临床及基因生物标记物的发现，它们或能对糖尿病患者更精确的诊断和治疗策略提供指导。在美国，II型糖尿病(T2D)是一个主要的致死原因，有2900万人受其困扰;T2D的患病人数估计在未来几十年中还会增加。T2D是一种复杂的代谢性疾病，它能引起从截肢、失明至肾脏疾病和心脏病等一系列并发症。为了更好地理解这种疾病的复杂性，Li Li和同事用了一种结合了电子病历临床数据的精密医学方法;这些临床数据包括了1万1210名患者的实验室化验结果和用药史及基因型数据。应用计算分析，他们基于患者临床特征的相似性构建了患者网络。这些网络将T2D患者分成3个不同的集群。亚型-1患者是年龄最小及最肥胖的，他们更容易被诊断罹患肾脏疾病和失明。亚型-2中的人有着最高的罹患癌症和心脏病的风险。亚型-3中的成员最常罹患心脏病、精神疾病、过敏和HIV感染。对患者基因型进行独立分析揭示了在这3个亚型中的每一个亚型中的基因变异体，它们能与其相应亚组的临床特征匹配，从而提出了存在基础基因因子的可能性。研究人员说，他们的对患者临床及基因特征的数据驱动分析可帮助阐明T2D以外的其它复杂疾病。

    原文链接：Identification of type 2 diabetes subgroups through topological analysis of patient similarity

    原文摘要：Type 2 diabetes (T2D) is a heterogeneous complex disease affecting more than 29 million Americans alone with a rising prevalence trending toward steady increases in the coming decades. Thus, there is a pressing clinical need to improve early prevention and clinical management of T2D and its complications. Clinicians have understood that patients who carry the T2D diagnosis have a variety of phenotypes and susceptibilities to diabetes-related complications. We used a precision medicine approach to characterize the complexity of T2D patient populations based on high-dimensional electronic medical records (EMRs) and genotype data from 11,210 individuals. We successfully identified three distinct subgroups of T2D from topology-based patient-patient networks. Subtype 1 was characterized by T2D complications diabetic nephropathy and diabetic retinopathy; subtype 2 was enriched for cancer malignancy and cardiovascular diseases; and subtype 3 was associated most strongly with cardiovascular diseases, neurological diseases, allergies, and HIV infections. We performed a genetic association analysis of the emergent T2D subtypes to identify subtype-specific genetic markers and identified 1279, 1227, and 1338 single-nucleotide polymorphisms (SNPs) that mapped to 425, 322, and 437 unique genes specific to subtypes 1, 2, and 3, respectively. By assessing the human disease–SNP association for each subtype, the enriched phenotypes and biological functions at the gene level for each subtype matched with the disease comorbidities and clinical differences that we identified through EMRs. Our approach demonstrates the utility of applying the precision medicine paradigm in T2D and the promise of extending the approach to the study of other complex, multifactorial diseases.