Li Li, Cheng Wei-Yi, Glicksberg Benjamin S, Gottesman Omri, Tamler Ronald, Chen Rong, Bottinger Erwin P, Dudley Joel T
Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 700 Lexington Ave., New York, NY 10065, USA.
Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA.
Sci Transl Med. 2015 Oct 28;7(311):311ra174. doi: 10.1126/scitranslmed.aaa9364.
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.
2型糖尿病（T2D）是一种异质性复杂疾病，仅在美国就影响着超过2900万人，且患病率呈上升趋势，在未来几十年可能会持续稳步增长。因此，迫切需要改善T2D及其并发症的早期预防和临床管理。临床医生已经认识到，患有T2D诊断的患者具有多种表型和对糖尿病相关并发症的易感性。我们采用精准医学方法，基于11210名个体的高维电子病历（EMR）和基因型数据，对T2D患者群体的复杂性进行了表征。我们成功地从基于拓扑结构的患者-患者网络中识别出T2D的三个不同亚组。亚组1的特征是T2D并发症糖尿病肾病和糖尿病视网膜病变；亚组2富含癌症恶性肿瘤和心血管疾病；亚组3与心血管疾病、神经系统疾病、过敏和HIV感染关联最为密切。我们对新出现的T2D亚组进行了遗传关联分析，以识别亚组特异性遗传标记，并分别鉴定出1279、1227和1338个单核苷酸多态性（SNP），这些SNP分别映射到亚组1、2和3特有的425、322和437个独特基因。通过评估每个亚组的人类疾病-SNP关联，每个亚组在基因水平上富集的表型和生物学功能与我们通过EMR识别出的疾病共病和临床差异相匹配。我们的方法证明了在T2D中应用精准医学范式的实用性，以及将该方法扩展到其他复杂多因素疾病研究的前景。
