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- Ahlqvist, Emma, et al.
(author)
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Novel subgroups of adult-onset diabetes and their association with outcomes : a data-driven cluster analysis of six variables
- 2018
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In: The Lancet Diabetes and Endocrinology. - 2213-8587 .- 2213-8595. ; 6:5, s. 361-369
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Journal article (peer-reviewed)abstract
- BackgroundDiabetes 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.MethodsWe 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, HbA1c, and homoeostatic model assessment 2 estimates of β-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.FindingsWe 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.InterpretationWe 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.
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| 2. |
- Hjort, Rebecka, et al.
(author)
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Overweight, obesity and the risk of LADA : results from a Swedish case–control study and the Norwegian HUNT Study
- 2018
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In: Diabetologia. - : Springer Science and Business Media LLC. - 0012-186X .- 1432-0428. ; 61:6, s. 1333-1343
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Journal article (peer-reviewed)abstract
- Aims/hypothesis: Excessive weight is a risk factor for type 2 diabetes, but its role in the promotion of autoimmune diabetes is not clear. We investigated the risk of latent autoimmune diabetes in adults (LADA) in relation to overweight/obesity in two large population-based studies. Methods: Analyses were based on incident cases of LADA (n = 425) and type 2 diabetes (n = 1420), and 1704 randomly selected control participants from a Swedish case–control study and prospective data from the Norwegian HUNT Study including 147 people with LADA and 1,012,957 person-years of follow-up (1984–2008). We present adjusted ORs and HRs with 95% CI. Results: In the Swedish data, obesity was associated with an increased risk of LADA (OR 2.93, 95% CI 2.17, 3.97), which was even stronger for type 2 diabetes (OR 18.88, 95% CI 14.29, 24.94). The association was stronger in LADA with low GAD antibody (GADA;
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