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. 2015 Oct 28;7(311):311ra174.
doi: 10.1126/scitranslmed.aaa9364.

Identification of Type 2 Diabetes Subgroups Through Topological Analysis of Patient Similarity

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Free PMC article

Identification of Type 2 Diabetes Subgroups Through Topological Analysis of Patient Similarity

Li Li et al. Sci Transl Med. .
Free PMC article

Abstract

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.

Conflict of interest statement

Competing interests: The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1. Patient and genotype networks
(A) Patient-patient network for topology patterns on 11,210 Biobank patients. Each node represents a single or a group of patients with the significant similarity based on their clinical features. Edge connected with nodes indicates the nodes have shared patients. Red color represents the enrichment for patients with T2D diagnosis, and blue color represents the non-enrichment for patients with T2D diagnosis. (B) Patient-patient network for topology patterns on 2551 T2D patients. Each node represents a single or a group of patients with the significant similarity based on their clinical features. Edge connected with nodes indicates the nodes have shared patients. Red color represents the enrichment for patients with females, and blue color represents the enrichment for males.
Fig. 2
Fig. 2. Genotype-phenotype network for three subtypes in T2D
The network consists of the significant association between phenotypes and genetic variants at gene level specific to three T2D subtypes (subtype 1 in blue, subtype 2 in orange, and subtype 3 in pink). Phenotypes (oval) and genes (triangle) are connected by gray lines (P value). Oval nodes in dark green indicate the shared phenotypes across subtypes. The edge width reflects the significance of the P value for enrichment. The size of the node reflects the amount of associated genes or phenotypes. This network was visualized using Cytoscape 3.2.0.

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