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- Rasouli, B., et al.
(författare)
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Coffee consumption, genetic susceptibility and risk of latent autoimmune diabetes in adults : A population-based case-control study
- 2018
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Ingår i: Diabetes & Metabolism. - : Elsevier BV. - 1262-3636 .- 1878-1780. ; 44:4, s. 354-360
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Tidskriftsartikel (refereegranskat)abstract
- Aim: Coffee consumption is inversely related to risk of type 2 diabetes (T2D). In contrast, an increased risk of latent autoimmune diabetes in adults (LADA) has been reported in heavy coffee consumers, primarily in a subgroup with stronger autoimmune characteristics. Our study aimed to investigate whether coffee consumption interacts with HLA genotypes in relation to risk of LADA. Methods: This population-based study comprised incident cases of LADA (n = 484) and T2D (n = 1609), and also 885 healthy controls. Information on coffee consumption was collected by food frequency questionnaire. Odds ratios (ORs) with 95% CIs of diabetes were calculated and adjusted for age, gender, BMI, education level, smoking and alcohol intake. Potential interactions between coffee consumption and high-risk HLA genotypes were calculated by attributable proportion (AP) due to interaction. Results: Coffee intake was positively associated with LADA in carriers of high-risk HLA genotypes (OR: 1.14 per cup/day, 95% CI: 1.02–1.28), whereas no association was observed in non-carriers (OR: 1.04, 95% CI: 0.93–1.17). Subjects with both heavy coffee consumption (≥ 4 cups/day) and high-risk HLA genotypes had an OR of 5.74 (95% CI: 3.34–9.88) with an estimated AP of 0.36 (95% CI: 0.01–0.71; P = 0.04370). Conclusion: Our findings suggest that coffee consumption interacts with HLA to promote LADA.
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- Ahlqvist, E., et al.
(författare)
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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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Ingår i: Lancet Diabetes & Endocrinology. - : Elsevier BV. - 2213-8587. ; 6:5, s. 361-369
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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- Rasouli, B., et al.
(författare)
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Serious life events and the risk of latent autoimmune diabetes in adults (LADA) and Type 2 diabetes
- 2017
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Ingår i: Diabetic Medicine. - : Wiley. - 0742-3071 .- 1464-5491. ; 34:9, s. 1259-1263
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Tidskriftsartikel (refereegranskat)abstract
- Aim: It has been suggested that experiencing serious life events may promote Type 1 diabetes in children. Studies in adults are lacking, as are studies on the interaction of life events with genetic factors. We aimed to investigate life events and the risk of latent autoimmune diabetes in adults (LADA) and Type 2 diabetes while taking into account HLA genotype. Methods: Analysis was based on 425 incident cases of LADA, 1417 incident cases of Type 2 diabetes and 1702 population-based controls recruited in Sweden between 2010 and 2016. Self-reported information on life events including conflicts, divorce, illness/accidents, death and financial problems experienced during the 5 years preceding diagnosis/index year was used. Odds ratios (ORs) and 95% confidence intervals (95% CI) were calculated by logistic regression and adjusted for age, sex, BMI, family history of diabetes, smoking, physical activity and education. Results: Overall there was no association between experience of any life event and either LADA (OR 0.86, 95% CI 0.68-1.08) or Type 2 diabetes (OR 1.00, 95% CI 0.83-1.21). The results were similar for individual events as well as in separate analysis of men and women. Similar results were seen in more autoimmune LADA (glutamic acid decarboxylase antibodies > median) [OR (any life event) 0.88, 95% CI 0.64-1.21] and in LADA carriers of the high-risk HLADR4-DQ8 genotype (OR 0.89, 95% CI 0.61-1.29). Conclusions: Our findings indicate that experience of a serious life event, including the death of a family member, divorce or financial problems, is not associated with an increased risk of LADA, overall or in genetically susceptible individuals.
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