Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables

被引：1525

作者：

Ahlqvist, Emma ^{[1
]}

Storm, Petter ^{[1
]}

Karajamaki, Annemari ^{[2
,3
]}

Martinell, Mats ^{[4
]}

Dorkhan, Mozhgan ^{[1
]}

Carlsson, Annelie ^{[1
]}

Vikman, Petter ^{[1
]}

Prasad, Rashmi B. ^{[1
]}

Aly, Dina Mansour

Almgren, Peter ^{[1
]}

Wessman, Ylva ^{[1
]}

Shaat, Nael ^{[1
]}

Spegel, Peter ^{[1
,5
]}

Mulder, Hindrik ^{[1
]}

Lindholm, Eero ^{[1
]}

Melander, Olle ^{[1
]}

Hansson, Ola ^{[1
]}

Malmqvist, Ulf ^{[6
]}

Lernmark, Ake ^{[1
]}

Lahti, Kaj ^{[2
,3
]}

Forsen, Tom ^{[7
]}

Tuomi, Tiinamaija ^{[7
,8
,9
]}

Rosengren, Anders H. ^{[1
,10
]}

Groop, Leif ^{[1
,9
]}

机构：

[1] Lund Univ, Skane Univ Hosp, Diabet Ctr, Dept Clin Sci, Malmo, Sweden

[2] Vaasa Cent Hosp, Dept Primary Hlth Care, Vaasa, Finland

[3] Vaasa Hlth Care Ctr, Diabet Ctr, Vaasa, Finland

[4] Uppsala Univ, Dept Publ Hlth & Caring Sci, Uppsala, Sweden

[5] Lund Univ, Dept Chem, Ctr Anal & Synth, Lund, Sweden

[6] Lund Univ Hosp, Clin Res & Trial Ctr, Lund, Sweden

[7] Folkhalsan Res Ctr, Helsinki, Finland

[8] Univ Helsinki, Cent Hosp, Abdominal Ctr, Res Program Diabet & Obes,Endocrinol, Helsinki, Finland

[9] Univ Helsinki, Finnish Inst Mol Med, Helsinki, Finland

[10] Univ Gothenburg, Wallenberg Ctr Mol & Translat Med, Dept Neurosci & Physiol, Gothenburg, Sweden

来源：

LANCET DIABETES & ENDOCRINOLOGY | 2018年 / 6卷 / 05期

基金：

欧洲研究理事会; 芬兰科学院; 瑞典研究理事会;

关键词：

INSULIN; RISK; COMPLICATIONS; DEFINITION; MECHANISMS; MUTATIONS; VARIANTS; ASSAY; GENE;

D O I：

10.1016/S2213-8587(18)30051-2

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

Background Diabetes is presently classified into two main forms, type 1 and type 2 diabetes, but type 2 diabetes in particular is highly heterogeneous. A refined classification could provide a powerful tool to individualise treatment regimens and identify individuals with increased risk of complications at diagnosis. Methods We did data-driven cluster analysis (k-means and hierarchical clustering) in patients with newly diagnosed diabetes (n=8980) from the Swedish All New Diabetics in Scania cohort. Clusters were based on six variables (glutamate decarboxylase antibodies, age at diagnosis, BMI, HbA(1c), and homoeostatic model assessment 2 estimates of beta-cell function and insulin resistance), and were related to prospective data from patient records on development of complications and prescription of medication. Replication was done in three independent cohorts: the Scania Diabetes Registry (n=1466), All New Diabetics in Uppsala (n=844), and Diabetes Registry Vaasa (n=3485). Cox regression and logistic regression were used to compare time to medication, time to reaching the treatment goal, and risk of diabetic complications and genetic associations. Findings We identified five replicable clusters of patients with diabetes, which had significantly different patient characteristics and risk of diabetic complications. In particular, individuals in cluster 3 (most resistant to insulin) had significantly higher risk of diabetic kidney disease than individuals in clusters 4 and 5, but had been prescribed similar diabetes treatment. Cluster 2 (insulin deficient) had the highest risk of retinopathy. In support of the clustering, genetic associations in the clusters differed from those seen in traditional type 2 diabetes. Interpretation We stratified patients into five subgroups with differing disease progression and risk of diabetic complications. This new substratification might eventually help to tailor and target early treatment to patients who would benefit most, thereby representing a first step towards precision medicine in diabetes.

引用

页码：361 / 369

页数：9

共 27 条

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