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- Gaulton, Kyle J, et al.
(författare)
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Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci.
- 2015
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Ingår i: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 47:12, s. 1415-1415
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Tidskriftsartikel (refereegranskat)abstract
- We performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry. We identified 49 distinct association signals at these loci, including five mapping in or near KCNQ1. 'Credible sets' of the variants most likely to drive each distinct signal mapped predominantly to noncoding sequence, implying that association with T2D is mediated through gene regulation. Credible set variants were enriched for overlap with FOXA2 chromatin immunoprecipitation binding sites in human islet and liver cells, including at MTNR1B, where fine mapping implicated rs10830963 as driving T2D association. We confirmed that the T2D risk allele for this SNP increases FOXA2-bound enhancer activity in islet- and liver-derived cells. We observed allele-specific differences in NEUROD1 binding in islet-derived cells, consistent with evidence that the T2D risk allele increases islet MTNR1B expression. Our study demonstrates how integration of genetic and genomic information can define molecular mechanisms through which variants underlying association signals exert their effects on disease.
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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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- Lindh, Magnus, 1960, et al.
(författare)
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Clinical Effectiveness of Liraglutide vs Sitagliptin on Glycemic Control and Body Weight in Patients with Type 2 Diabetes: A Retrospective Assessment in Sweden
- 2016
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Ingår i: Diabetes Therapy. - : Springer Science and Business Media LLC. - 1869-6953 .- 1869-6961. ; 7:2, s. 321-333
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: The aim of the present study was to use real-world data from Swedish primary-care and national registries to understand clinical outcomes in patients with Type 2 diabetes (T2D) treated with liraglutide in clinical practice, and to compare with data from those treated with sitagliptin. Methods: This was a non-interventional, retrospective study conducted between February 2014 and September 2014 using T2D patient data from Swedish primary-care centers and national healthcare registries. The primary objective was to assess the effectiveness of liraglutide in control of glycemia and body weight in clinical practice (stage 1). The secondary objective was to compare the clinical effectiveness of liraglutide with sitagliptin on glycemic control and body weight in clinical practice in a propensity-score-matched population (stage 2). Results: In stage 1 (n = 402), 39.4% of patients treated with liraglutide achieved >= 1.0% (10.9 mmol/mol) reduction in glycated hemoglobin (HbA1c) after 180 days of treatment and 54.9% achieved the target HbA1c of <7.0% (53.0 mmol/mol). Moreover, compared with baseline, 22.5% of patients treated with liraglutide achieved both >= 1.0% reduction in HbA1c and >= 3.0% reduction in body weight. In stage 2, a significantly greater proportion of patients receiving liraglutide (n = 180) than sitagliptin (n = 208) achieved >= 1.0% reduction in HbA1c [52.9% vs 33.5%, respectively (P = 0.0002)]. Mean body-weight loss was also significantly greater in patients receiving liraglutide vs sitagliptin [-3.5 vs -1.3 kg, respectively (P < 0.0001)]. Conclusion: This study provides real-world evidence from Sweden corroborating previous clinical trials that demonstrate greater efficacy of liraglutide over sitagliptin on glycemic control and body-weight reduction in patients with T2D.
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