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Träfflista för sökning "WFRF:(Tuomi Tiinamaija) ;pers:(Almgren Peter)"

Sökning: WFRF:(Tuomi Tiinamaija) > Almgren Peter

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1.
  • van Zuydam, NR, et al. (författare)
  • A Genome-Wide Association Study of Diabetic Kidney Disease in Subjects With Type 2 Diabetes
  • 2018
  • Ingår i: Diabetes. - : American Diabetes Association. - 1939-327X .- 0012-1797. ; 67:7, s. 1414-1427
  • Tidskriftsartikel (refereegranskat)abstract
    • Identification of sequence variants robustly associated with predisposition to diabetic kidney disease (DKD) has the potential to provide insights into the pathophysiological mechanisms responsible. We conducted a genome-wide association study (GWAS) of DKD in type 2 diabetes (T2D) using eight complementary dichotomous and quantitative DKD phenotypes: the principal dichotomous analysis involved 5,717 T2D subjects, 3,345 with DKD. Promising association signals were evaluated in up to 26,827 subjects with T2D (12,710 with DKD). A combined T1D+T2D GWAS was performed using complementary data available for subjects with T1D, which, with replication samples, involved up to 40,340 subjects with diabetes (18,582 with DKD). Analysis of specific DKD phenotypes identified a novel signal near GABRR1 (rs9942471, P = 4.5 × 10−8) associated with microalbuminuria in European T2D case subjects. However, no replication of this signal was observed in Asian subjects with T2D or in the equivalent T1D analysis. There was only limited support, in this substantially enlarged analysis, for association at previously reported DKD signals, except for those at UMOD and PRKAG2, both associated with estimated glomerular filtration rate. We conclude that, despite challenges in addressing phenotypic heterogeneity, access to increased sample sizes will continue to provide more robust inference regarding risk variant discovery for DKD.
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2.
  • Ahlqvist, Emma, et al. (författare)
  • Novel subgroups of adult-onset diabetes and their association with outcomes : a data-driven cluster analysis of six variables
  • 2018
  • Ingår i: The Lancet Diabetes and Endocrinology. - 2213-8587 .- 2213-8595. ; 6:5, s. 361-369
  • Tidskriftsartikel (refereegranskat)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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4.
  • Almgren, Peter, et al. (författare)
  • Heritability and familiality of type 2 diabetes and related quantitative traits in the Botnia Study.
  • 2011
  • Ingår i: Diabetologia. - : Springer Science and Business Media LLC. - 1432-0428 .- 0012-186X. ; 54, s. 2811-2819
  • Tidskriftsartikel (refereegranskat)abstract
    • AIMS/HYPOTHESIS: To study the heritability and familiality of type 2 diabetes and related quantitative traits in families from the Botnia Study in Finland. METHODS: Heritability estimates for type 2 diabetes adjusted for sex, age and BMI are provided for different age groups of type 2 diabetes and for 34 clinical and metabolic traits in 5,810 individuals from 942 families using a variance component model (SOLAR). In addition, family means of these traits and their distribution across families are calculated. RESULTS: The strongest heritability for type 2 diabetes was seen in patients with age at onset 35-60 years (h (2) = 0.69). However, including patients with onset up to 75 years dropped the h (2) estimates to 0.31. Among quantitative traits, the highest h (2) estimates in all individuals and in non-diabetic individuals were seen for lean body mass (h (2) = 0.53-0.65), HDL-cholesterol (0.52-0.61) and suppression of NEFA during OGTT (0.63-0.76) followed by measures of insulin secretion (insulinogenic index [IG(30)] = 0.41-0.50) and insulin action (insulin sensitivity index [ISI] = 0.37-0.40). In contrast, physical activity showed rather low heritability (0.16-0.18), whereas smoking showed strong heritability (0.57-0.59). Family means of these traits differed two- to fivefold between families belonging to the lowest and highest quartile of the trait (p < 0.00001). CONCLUSIONS/INTERPRETATION: To detect stronger genetic effects in type 2 diabetes, it seems reasonable to restrict inclusion of patients to those with age at onset 35-60 years. Sequencing of families with extreme quantitative traits could be an important next step in the dissection of the genetics of type 2 diabetes.
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5.
  • Alyass, Akram, et al. (författare)
  • Modelling of OGTT curve identifies 1 h plasma glucose level as a strong predictor of incident type 2 diabetes: results from two prospective cohorts
  • 2015
  • Ingår i: Diabetologia. - : Springer Science and Business Media LLC. - 1432-0428 .- 0012-186X. ; 58:1, s. 87-97
  • Tidskriftsartikel (refereegranskat)abstract
    • Aims/hypothesis The relevance of the OGTT in predicting type 2 diabetes is unclear. We assessed the performance of 14 OGTT glucose traits in type 2 diabetes prediction. Methods We studied 2,603 and 2,386 Europeans from the Botnia study and Malmo Prevention Project (MPP) cohorts with baseline OGTT data. Over a follow-up period of 4.94 years and 23.5 years, 155 (5.95%) and 467 (19.57%) participants, respectively, developed type 2 diabetes. The main outcome was incident type 2 diabetes. Results One-hour plasma glucose (1h-PG) was a fair/good predictor of incident type 2 diabetes in the Botnia study and MPP (AUC for receiver operating characteristic [AUC(ROC)] 0.80 [0.77, 0.84] and 0.70 [0.68, 0.73]). 1h-PG alone outperformed the prediction model of multiple clinical risk factors (age, sex, BMI, family history of type 2 diabetes) in the Botnia study and MPP (AUC(ROC) 0.75 [0.72, 0.79] and 0.67 [0.64, 0.70]). The same clinical risk factors added to 1h-PG modestly increased prediction for incident type 2 diabetes (Botnia, AUC(ROC) 0.83 [0.80, 0.86]; MPP, AUC(ROC) 0.74 [0.72, 0.77]). 1h-PG also outperformed HbA(1c) in predicting type 2 diabetes in the Botnia cohort. A 1h-PG value of 8.9 mmol/l and 8.4 mmol/l was the optimal cut-point for initial screening and selection of high-risk individuals in the Botnia study and MPP, respectively, and represented 30% and 37% of all participants in these cohorts. High-risk individuals had a substantially increased risk of incident type 2 diabetes (OR 8.0 [5.5, 11.6] and 3.8 [3.1, 4.7]) and captured 75% and 62% of all incident type 2 diabetes in the Botnia study and MPP. Conclusions/interpretation1h-PG is a valuable prediction tool for identifying adults at risk for future type 2 diabetes.
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6.
  • Bacos, Karl, et al. (författare)
  • Blood-based biomarkers of age-associated epigenetic changes in human islets associate with insulin secretion and diabetes
  • 2016
  • Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7
  • Tidskriftsartikel (refereegranskat)abstract
    • Aging associates with impaired pancreatic islet function and increased type 2 diabetes (T2D) risk. Here we examine whether age-related epigenetic changes affect human islet function and if blood-based epigenetic biomarkers reflect these changes and associate with future T2D. We analyse DNA methylation genome-wide in islets from 87 non-diabetic donors, aged 26-74 years. Aging associates with increased DNA methylation of 241 sites. These sites cover loci previously associated with T2D, for example, KLF14. Blood-based epigenetic biomarkers reflect age-related methylation changes in 83 genes identified in human islets (for example, KLF14, FHL2, ZNF518B and FAM123C) and some associate with insulin secretion and T2D. DNA methylation correlates with islet expression of multiple genes, including FHL2, ZNF518B, GNPNAT1 and HLTF. Silencing these genes in β-cells alter insulin secretion. Together, we demonstrate that blood-based epigenetic biomarkers reflect age-related DNA methylation changes in human islets, and associate with insulin secretion in vivo and T2D.
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7.
  • Cervin, Camilla, et al. (författare)
  • An investigation of serum concentration of apoM as a potential MODY3 marker using a novel ELISA.
  • 2010
  • Ingår i: Journal of Internal Medicine. - : Wiley. - 1365-2796 .- 0954-6820. ; 267, s. 316-321
  • Tidskriftsartikel (refereegranskat)abstract
    • Abstract. Cervin C, Axler O, Holmkvist J, Almgren P, Rantala E, Tuomi T, Groop L, Dahlbäck B, Karlsson E (Lund University, Malmö, Sweden, Steno Diabetes Center, Gentofte, Denmark, University of Helsinki; and Folkhälsan Research Centre, Helsinki, Finland). An investigation of serum concentration of apoM as a potential MODY3 marker using a novel ELISA. J Intern Med 2009; doi: 10.1111/j.1365-2796.2009.02145.x.Objective. To investigate the fitness of serum apolipoprotein M (apoM) concentration as a marker for maturity-onset diabetes of the young 3 (MODY3). Study design and subjects. This study consisted of two parts. A family study included 71 carriers of the P291fsinsC mutation in hepatocyte nuclear factor-1alpha (HNF-1alpha) from the Finnish Botnia study, 53 of whom were diabetic, and 75 matched family controls. A second, case-control study included 24 MODY3 patients, 17 healthy MODY3 mutation carriers, 11 MODY1 patients, 18 type 2 diabetes patients and 19 healthy control individuals. Subjects in the case-control study were recruited from the Botnia study or the Clinic of Endocrinology, Malmö University Hospital. Serum apoM levels were measured using a novel ELISA based on two monoclonal apoM antibodies. Results. In the family study, mean serum apoM was 10% lower in female carriers of the P291fsinsC mutation compared to the family controls (P = 0.0058), a difference which remained significant after adjustment for diabetes status. There was no observed difference between groups for men. In the case-control study, no significant difference in apoM concentration was observed between MODY3 and type 2 diabetes patients, neither before nor after adjustment for total cholesterol. Conclusions. Female carriers of the P291fsinsC mutation in HNF-1alpha displayed slightly lower apoM serum levels. This difference is too small for apoM to be reliably employed as a biomarker for HNF-1alpha mutation status.
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8.
  • Dayeh, Tasnim, et al. (författare)
  • DNA methylation of loci within ABCG1 and PHOSPHO1 in blood DNA is associated with future type 2 diabetes risk
  • 2016
  • Ingår i: Epigenetics. - : Informa UK Limited. - 1559-2294 .- 1559-2308. ; 11:7, s. 482-488
  • Tidskriftsartikel (refereegranskat)abstract
    • Identification of subjects with a high risk of developing type 2 diabetes (T2D) is fundamental for prevention of the disease. Consequently, it is essential to search for new biomarkers that can improve the prediction of T2D. The aim of this study was to examine whether 5 DNA methylation loci in blood DNA (ABCG1, PHOSPHO1, SOCS3, SREBF1, and TXNIP), recently reported to be associated with T2D, might predict future T2D in subjects from the Botnia prospective study. We also tested if these CpG sites exhibit altered DNA methylation in human pancreatic islets, liver, adipose tissue, and skeletal muscle from diabetic vs. non-diabetic subjects. DNA methylation at the ABCG1 locus cg06500161 in blood DNA was associated with an increased risk for future T2D (OR = 1.09, 95% CI = 1.02–1.16, P-value = 0.007, Q-value = 0.018), while DNA methylation at the PHOSPHO1 locus cg02650017 in blood DNA was associated with a decreased risk for future T2D (OR = 0.85, 95% CI = 0.75–0.95, P-value = 0.006, Q-value = 0.018) after adjustment for age, gender, fasting glucose, and family relation. Furthermore, the level of DNA methylation at the ABCG1 locus cg06500161 in blood DNA correlated positively with BMI, HbA1c, fasting insulin, and triglyceride levels, and was increased in adipose tissue and blood from the diabetic twin among monozygotic twin pairs discordant for T2D. DNA methylation at the PHOSPHO1 locus cg02650017 in blood correlated positively with HDL levels, and was decreased in skeletal muscle from diabetic vs. non-diabetic monozygotic twins. DNA methylation of cg18181703 (SOCS3), cg11024682 (SREBF1), and cg19693031 (TXNIP) was not associated with future T2D risk in subjects from the Botnia prospective study.
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10.
  • Florez, Jose C., et al. (författare)
  • Haplotype Structure and Genotype-Phenotype Correlations of the Sulfonylurea Receptor and the Islet ATP-Sensitive Potassium Channel Gene Region.
  • 2004
  • Ingår i: Diabetes. - : American Diabetes Association. - 1939-327X .- 0012-1797. ; 53:5, s. 1360-1368
  • Tidskriftsartikel (refereegranskat)abstract
    • The genes for the sulfonylurea receptor (SUR1; encoded by ABCC8) and its associated islet ATP-sensitive potassium channel (Kir6.2; encoded by KCNJ11) are adjacent to one another on human chromosome 11. Multiple studies have reported association of the E23K variant of Kir6.2 with risk of type 2 diabetes. Whether and how E23K itself—or other variant(s) in either of these two closely linked genes—influences type 2 diabetes remains to be fully determined. To better understand genotype-phenotype correlation at this important candidate gene locus, we 1) characterized haplotype structures across the gene region by typing 77 working, high-frequency markers spanning 207 kb and both genes; 2) performed association studies of E23K and nearby markers in &gt;3,400 patients (type 2 diabetes and control) not previously reported in the literature; and 3) analyzed the resulting data for measures of insulin secretion. These data independently replicate the association of E23K with type 2 diabetes with an odds ratio (OR) in the new data of 1.17 (P = 0.003) as compared with an OR of 1.14 provided by meta-analysis of previously published, nonoverlapping data (P = 0.0002). We find that the E23K variant in Kir6.2 demonstrates very strong allelic association with a coding variant (A1369S) in the neighboring SUR1 gene (r2 &gt; 0.9) across a range of population samples, making it difficult to distinguish which gene and polymorphism in this region are most likely responsible for the reported association. We show that E23K is also associated with decreased insulin secretion in glucose-tolerant control subjects, supporting a mechanism whereby β-cell dysfunction contributes to the common form of type 2 diabetes. Like peroxisome proliferator–activated receptor γ, the SUR1/Kir6.2 gene region both contributes to the inherited risk of type 2 diabetes and encodes proteins that are targets for hypoglycemic medications, providing an intriguing link between the underlying mechanism of disease and validated targets for pharmacological treatment.
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