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1.
  • van Zuydam, NR, et al. (creator_code:aut_t)
  • A Genome-Wide Association Study of Diabetic Kidney Disease in Subjects With Type 2 Diabetes
  • 2018
  • record:In_t: Diabetes. - : American Diabetes Association. - 1939-327X .- 0012-1797. ; 67:7, s. 1414-1427
  • swepub:Mat_article_t (swepub:level_refereed_t)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.
  • Abdul-Ghani, Muhammad A., et al. (creator_code:aut_t)
  • Fasting Versus Postload Plasma Glucose Concentration and the Risk for Future Type 2 Diabetes Results from the Botnia Study
  • 2009
  • record:In_t: Diabetes Care. - : American Diabetes Association. - 1935-5548 .- 0149-5992. ; 32:2, s. 281-286
  • swepub:Mat_article_t (swepub:level_refereed_t)abstract
    • OBJECTIVE - The purpose of this study was to assess the efficacy of the postload plasma glucose concentration in predicting future risk of type 2 diabetes, compared with prediction models based oil measurement. of the fasting plasma glucose (FPG) concentration. RESEARCH DESIGN AND METHODS - A total of 2,442 subjects from the Botnia Study, who were free Of type 2 diabetes at baseline, received an oral glucose tolerance test (OGTT) at baseline and after 7-8 years of follow-up. Future risk for type 2 diabetes was assessed with area under the receiver-operating characteristic curve for prediction models based up measurement of the FPG concentration 1) with or without a 1-h plasma glucose concentration during the OGTT and 2) with or without the metabolic syndrome. RESULTS - Prediction models based on measurement of the FPG concentration were weak predictors for the risk of Future type 2 diabetes. Addition of a 1-h plasma glucose Concentration markedly enhanced prediction Of the risk of future type 2 diabetes. A cut point of 155 mg/dl for the 1-h plasma glucose concentration during the OGTT and presence Of the metabolic syndrome were used to Stratify subjects in each glucose tolerance group into low, intermediate, and high risk for future type 2 diabetes. CONCLUSIONS - The plasma glucose concentration at 1 h during the OGTT is a Strong predictor of future risk for type 2 diabetes and adds to the prediction power of models based on measurements made during the fasting state. A plasma glucose cut point of 155 mg/dl Plus the Adult Treatment Panel III criteria for the metabolic syndrome can be used to stratify nondiabetic subjects into low-, intermediate-, and high-risk groups.
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3.
  • Abdul-Ghani, Muhammad A., et al. (creator_code:aut_t)
  • Minimal Contribution of Fasting Hyperglycemia to the Incidence of Type 2 Diabetes in Subjects With Normal 2-h Plasma Glucose
  • 2010
  • record:In_t: Diabetes Care. - : American Diabetes Association. - 1935-5548 .- 0149-5992. ; 33:3, s. 557-561
  • swepub:Mat_article_t (swepub:level_refereed_t)abstract
    • OBJECTIVE - To assess the relative contribution of increased fasting and postload plasma glucose concentrations to the incidence of type 2 diabetes in subjects with a normal 2-h plasma glucose concentration. RESEARCH DESIGN AND METHODS - A total of 3,450 subjects with 2-h plasma glucose concentration < 140 mg/dl at baseline were followed up in the San Antonio Heart Study (SAHS) and the Botnia Study for 7-8 years. The incidence of type 2 diabetes at follow-up was related to the fasting, 1-h, and 2-h plasma glucose concentrations. RESULTS - in subjects with 2-h plasma glucose < 140 mg/dl, the incidence of type 2 diabetes increased with increasing fasting plasma glucose (FPG) and 1-h and 2-h plasma glucose concentrations. In a multivariate logistic analysis, after adjustment for all diabetes risk factors, the FPG concentration was a Strong predictor Of type 2 diabetes in both the SAHS and the Botnia Study (P < 0.0001). However, when the 1-h plasma glucose, but not 2-h plasma glucose, concentration was added to the model, FPG concentration was no longer a significant predictor of type 2 diabetes in both Studies (NS). When subjects were matched for the level of 1-h plasma glucose concentration, the incidence Of type 2 diabetes markedly increased with the increase in 1-h plasma glucose, but the increase in FPG was not associated with a significant increase in the incidence of type 2 diabetes. CONCLUSIONS - An increase in postload glycemia in the normal range is associated with an increase in the incidence of type 2 diabetes. After controlling for 1-h plasma glucose concentration, the increase in FPG concentration is not associated with an increase in the incidence of type 2 diabetes.
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4.
  • Abdul-Ghani, Muhammad A., et al. (creator_code:aut_t)
  • The shape of plasma glucose concentration curve during OGTT predicts future risk of type 2 diabetes
  • 2010
  • record:In_t: Diabetes/Metabolism Research & Reviews. - : Wiley. - 1520-7552 .- 1520-7560. ; 26:4, s. 280-286
  • swepub:Mat_article_t (swepub:level_refereed_t)abstract
    • Background The aim of the study is to assess the relationship between the shape of plasma glucose concentration during the OGTT and future risk for T2DM. Methods 2445 non-diabetic subjects from the Botnia study received an OGTT at baseline and after 7-8 years of follow-up. Results NGT and IFG subjects who returned their plasma glucose concentration following an ingested glucose load below FPG within 60 min had increased insulin sensitivity, greater insulin secretion and lower risk for future T2DM compared to NGT and IFG subjects whose post-load plasma glucose concentration required 120 min or longer to return their plasma glucose level to FPG level. IGT subjects who had a lower plasma glucose concentration at 1-h compared to 2-h during oGrr had greater insulin sensitivity, better beta cell function and lower risk for future T2DM. Conclusions These data suggest that the shape of glucose curve can be utilized to assess future risk for T2DM. Copyright (C) 2010 John Wiley & Sons, Ltd.
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5.
  • Abdul-Ghani, Muhammad A., et al. (creator_code:aut_t)
  • Two-Step Approach for the Prediction of Future Type 2 Diabetes Risk
  • 2011
  • record:In_t: Diabetes Care. - : American Diabetes Association. - 1935-5548 .- 0149-5992. ; 34:9, s. 2108-2112
  • swepub:Mat_article_t (swepub:level_refereed_t)abstract
    • OBJECTIVE-To develop a model for the prediction of type 2 diabetes mellitus (T2DM) risk on the basis of a multivariate logistic model and 1-h plasma glucose concentration (1-h PG). RESEARCH DESIGN AND METHODS-The model was developed in a cohort of 1,562 non-diabetic subjects from the San Antonio Heart Study (SAHS) and validated in 2,395 nondiabetic subjects in the Botnia Study. A risk score on the basis of anthropometric parameters, plasma glucose and lipid profile, and blood pressure was computed for each subject. Subjects with a risk score above a certain cut point were considered to represent high-risk individuals, and their 1-h PG concentration during the oral glucose tolerance test was used to further refine their future T2DM risk. RESULTS-We used the San Antonio Diabetes Prediction Model (SADPM) to generate the initial risk score. A risk-score value of 0.065 was found to be an optimal cut point for initial screening and selection of high-risk individuals. A 1-h PG concentration >140 mg/dL in high-risk individuals (whose risk score was >0.065) was the optimal cut point for identification of subjects at increased risk. The two cut points had 77.8, 77.4, and 44.8% (for the SAHS) and 75.8, 71.6, and 11.9% (for the Botnia Study) sensitivity, specificity, and positive predictive value, respectively, in the SAHS and Botnia Study. CONCLUSIONS-A two-step model, based on the combination of the SADPM and 1-h PG, is a useful tool for the identification of high-risk Mexican-American and Caucasian individuals. Diabetes Care 34:2108-2112, 2011
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6.
  • Ahlqvist, Emma, et al. (creator_code:aut_t)
  • A link between GIP and osteopontin in adipose tissue and insulin resistance.
  • 2013
  • record:In_t: Diabetes. - : American Diabetes Association. - 1939-327X .- 0012-1797. ; 62:6, s. 2088-2094
  • swepub:Mat_article_t (swepub:level_refereed_t)abstract
    • Low grade inflammation in obesity is associated with accumulation of the macrophagederived cytokine osteopontin in adipose tissue and induction of local as well as systemic insulin resistance. Since GIP (glucose-dependent insulinotropic polypeptide) is a strong stimulator of adipogenesis and may play a role in the development of obesity, we explored whether GIP directly would stimulate osteopontin (OPN) expression in adipose tissue and thereby induce insulin resistance. GIP stimulated OPN protein expression in a dose-dependent fashion in rat primary adipocytes. The level of OPN mRNA was higher in adipose tissue of obese individuals (0.13±}0.04 vs 0.04±}0.01, P<0.05) and correlated inversely with measures of insulin sensitivity (r=-0.24, P=0.001). A common variant of the GIP receptor (GIPR) (rs10423928) gene was associated with lower amount of the exon 9 containing isoform required for transmembrane activity. Carriers of the A-allele with a reduced receptor function showed lower adipose tissue OPN mRNA levels and better insulin sensitivity. Together, these data suggest a role for GIP not only as an incretin hormone, but also as a trigger of inflammation and insulin resistance in adipose tissue. Carriers of GIPR rs10423928 A-allele showed protective properties via reduced GIP effects. Identification of this unprecedented link between GIP and OPN in adipose tissue might open new avenues for therapeutic interventions.
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7.
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8.
  • Ahlqvist, Emma, et al. (creator_code:aut_t)
  • Novel diabetes subgroups – Authors' reply
  • 2018
  • record:In_t: The Lancet Diabetes and Endocrinology. - 2213-8587. ; 6:6, s. 440-441
  • swepub:Mat_article_t (swepub:level_refereed_t)
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9.
  • Ahlqvist, Emma, et al. (creator_code:aut_t)
  • Novel subgroups of adult-onset diabetes and their association with outcomes : a data-driven cluster analysis of six variables
  • 2018
  • record:In_t: The Lancet Diabetes and Endocrinology. - 2213-8587 .- 2213-8595. ; 6:5, s. 361-369
  • swepub:Mat_article_t (swepub:level_refereed_t)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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10.
  • Ahuja, Vasudha, et al. (creator_code:aut_t)
  • Accuracy of 1-Hour Plasma Glucose During the Oral Glucose Tolerance Test in Diagnosis of Type 2 Diabetes in Adults : A Meta-analysis
  • 2021
  • record:In_t: Diabetes Care. - : American Diabetes Association. - 1935-5548 .- 0149-5992. ; 44:4, s. 1062-1069
  • swepub:Mat_researchreview_t (swepub:level_refereed_t)abstract
    • OBJECTIVE: One-hour plasma glucose (1-h PG) during the oral glucose tolerance test (OGTT) is an accurate predictor of type 2 diabetes. We performed a meta-analysis to determine the optimum cutoff of 1-h PG for detection of type 2 diabetes using 2-h PG as the gold standard. RESEARCH DESIGN AND METHODS: We included 15 studies with 35,551 participants from multiple ethnic groups (53.8% Caucasian) and 2,705 newly detected cases of diabetes based on 2-h PG during OGTT. We excluded cases identified only by elevated fasting plasma glucose and/or HbA1c. We determined the optimal 1-h PG threshold and its accuracy at this cutoff for detection of diabetes (2-h PG ≥11.1 mmol/L) using a mixed linear effects regression model with different weights to sensitivity/specificity (2/3, 1/2, and 1/3). RESULTS: Three cutoffs of 1-h PG, at 10.6 mmol/L, 11.6 mmol/L, and 12.5 mmol/L, had sensitivities of 0.95, 0.92, and 0.87 and specificities of 0.86, 0.91, and 0.94 at weights 2/3, 1/2, and 1/3, respectively. The cutoff of 11.6 mmol/L (95% CI 10.6, 12.6) had a sensitivity of 0.92 (0.87, 0.95), specificity of 0.91 (0.88, 0.93), area under the curve 0.939 (95% confidence region for sensitivity at a given specificity: 0.904, 0.946), and a positive predictive value of 45%. CONCLUSIONS: The 1-h PG of ≥11.6 mmol/L during OGTT has a good sensitivity and specificity for detecting type 2 diabetes. Prescreening with a diabetes-specific risk calculator to identify high-risk individuals is suggested to decrease the proportion of false-positive cases. Studies including other ethnic groups and assessing complication risk are warranted.
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