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Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables
Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital.ORCID iD: 0000-0002-6513-2384
Lund University Diabetes Centre, Department of Clinical Sciences, Lund University, Skåne University Hospital.ORCID iD: 0000-0002-7655-3731
Department of Primary Health Care, Vaasa Central Hospital, Finland.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Public Health and Caring Sciences, Family Medicine and Preventive Medicine. (Cardiovascular disease and diabetes)ORCID iD: 0000-0002-6060-6229
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2018 (English)In: The Lancet Diabetes and Endocrinology, ISSN 2213-8587, E-ISSN 2213-8595, Vol. 6, no 5, p. 361-369Article in journal (Refereed) Published
Abstract [en]

 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, 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.

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.

Place, publisher, year, edition, pages
2018. Vol. 6, no 5, p. 361-369
National Category
Endocrinology and Diabetes
Research subject
Endocrinology and Diabetology
Identifiers
URN: urn:nbn:se:uu:diva-328355DOI: 10.1016/S2213-8587(18)30051-2ISI: 000430631600013OAI: oai:DiVA.org:uu-328355DiVA, id: diva2:1135251
Projects
Diabetes Mellitus at the Time for Diagnosis, Studies on Prognostic Factors
Funder
EXODIAB - Excellence of Diabetes Research in Sweden, 2009-1039Swedish Research Council, 521-2010-3490Swedish Research Council, 2010-5983Linnaeus research environment CADICS, 349-2006-237
Note

Tredjeförfattarskapet delas av tredje och fjärde författaren.

Available from: 2017-08-22 Created: 2017-08-22 Last updated: 2018-07-20Bibliographically approved
In thesis
1. Diabetes Mellitus at the Time for Diagnosis: Studies on Prognostic Factors
Open this publication in new window or tab >>Diabetes Mellitus at the Time for Diagnosis: Studies on Prognostic Factors
2017 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The aim for this thesis was to identify prognostic factors for chronic diabetes complications that exist at the time of diabetes diagnosis.

Low level of education (<12 years) and low income (<60% of median) was found to increase the risk to have high (>70 mmol/mol) HbA1c at the time of diagnosis with 34 % and 35 %, respectively.

Prevalence of diabetic retinopathy (DR) was 12% in a cohort of patients newly diagnosed with diabetes. Diabetic macular edema was present in 11% of patients with type 2 diabetes (T2D) and 13% of those with Latent Autoimmune Diabetes in Adults (LADA). Low beta cell function and low level of education increased the risk for DR with 110% and 43%, respectively. For every unit of increase in body mass index, the risk for DR was reduced by 3%.

The cellular immunology of LADA patients was a mixture of that observed in both type 1 (T1D) and T2D patients. Compared to patients with T1D, LADA patients had more B-regulatory lymphocytes and antigen presenting cells capable of producing interleukine-35. This indicates a higher anti-inflammatory capacity in LADA patients compared to type T1D patients.

By imputing age, body mass index, HbA1c at diagnosis, beta cell function and insulin resistance in a cluster analysis, five distinct diabetes clusters were identified. The four clusters representing T2D patients differed in incidence of DR, nephropathy and non-alcoholic fatty liver disease. This was replicated with similar results in three geographically separate populations.

By studying socioeconomic background and factors present at the time of diagnosis we can better predict prognosis for chronic diabetes complications. These findings may facilitate better-targeted diabetes screening programs and more individually tailored treatment regimes.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2017. p. 87
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 1361
Keywords
New-onset Diabetes Mellitus, socioeconomic position, epidemiology, diabetes complications, diabetic retinopathy, cellular immunology, diabetes classification, type 2 diabetes, latent autoimmune diabetes in adults (LADA), type 1 diabetes
National Category
General Practice
Research subject
Family Medicine; Endocrinology and Diabetology
Identifiers
urn:nbn:se:uu:diva-328382 (URN)978-91-513-0047-4 (ISBN)
Public defence
2017-10-13, Auditorium Minus, Gustavianum, Akademigatan 3, Uppsala, 13:00 (Swedish)
Opponent
Supervisors
Funder
EXODIAB - Excellence of Diabetes Research in Sweden, 2009-1039
Available from: 2017-09-21 Created: 2017-08-22 Last updated: 2018-01-13

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