Identification of type 2 diabetes subgroups through topological analysis of patient similarity.
Identification of type 2 diabetes subgroups through topological analysis of patient similarity.
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DOI：
10.1126/scitranslmed.aaa9364
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发表时间：
2015-10-28
影响因子：
17.1
通讯作者：
Dudley JT
中科院分区：
文献类型：
--
作者：
Li L;Cheng WY;Glicksberg BS;Gottesman O;Tamler R;Chen R;Bottinger EP;Dudley JT
2 型糖尿病 (T2D) 是一种异质性复杂疾病，仅影响超过 2900 万美国人，其患病率在未来几十年内呈稳步上升趋势。因此，临床迫切需要改善T2D及其并发症的早期预防和临床管理。临床医生了解到，诊断为 T2D 的患者具有多种表型，并且对糖尿病相关并发症具有易感性。我们根据 11,210 名个体的高维电子病历 (EMR) 和基因型数据，使用精准医学方法来描述 T2D 患者群体的复杂性。我们从基于拓扑的患者-患者网络中成功识别出 T2D 的三个不同亚组。 1型的特点是T2D并发症糖尿病肾病和糖尿病视网膜病变； 2 亚型富含癌症恶性肿瘤和心血管疾病；亚型 3 与心血管疾病、神经系统疾病、过敏和 HIV 感染的相关性最强。我们对新出现的 T2D 亚型进行了遗传关联分析，以确定亚型特异性遗传标记，并鉴定了 1279、1227 和 1338 个单核苷酸多态性 (SNP)，分别映射到亚型 1、2 和 3 特有的 425、322 和 437 个独特基因。通过评估每个亚型的人类疾病-SNP 关联，每个亚型在基因水平上丰富的表型和生物学功能与我们通过 EMR 确定的疾病合并症和临床差异相匹配。我们的方法展示了在 T2D 中应用精准医学范例的实用性，以及将该方法扩展到其他复杂、多因素疾病研究的前景。
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, multi-factorial diseases.