208 research outputs found

    Characteristics associated with polypharmacy in people with type 2 diabetes:the Dutch Diabetes Pearl cohort

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    Contains fulltext : 232027.pdf (Publisher’s version ) (Open Access)AIM: To describe the prevalence and characteristics of polypharmacy in a Dutch cohort of individuals with type 2 diabetes. METHODS: We included people with type 2 diabetes from the Diabetes Pearl cohort, of whom 3886 were treated in primary care and 2873 in academic care (secondary/tertiary). With multivariable multinomial logistic regression analyses stratified for line of care, we assessed which sociodemographic, lifestyle and cardiometabolic characteristics were associated with moderate (5-9 medications) and severe polypharmacy (≥10 medications) compared with no polypharmacy (0-4 medications). RESULTS: Mean age was 63 ± 10 years, and 40% were women. The median number of daily medications was 5 (IQR 3-7) in primary care and 7 (IQR 5-10) in academic care. The prevalence of moderate and severe polypharmacy was 44% and 10% in primary care, and 53% and 29% in academic care respectively. Glucose-lowering and lipid-modifying medications were most prevalent. People with severe polypharmacy used a relatively large amount of other (i.e. non-cardiovascular and non-glucose-lowering) medication. Moderate and severe polypharmacy across all lines of care were associated with higher age, low educational level, more smoking, longer diabetes duration, higher BMI and more cardiovascular disease. CONCLUSIONS: Severe and moderate polypharmacy are prevalent in over half of people with type 2 diabetes in primary care, and even more in academic care. People with polypharmacy are characterized by poorer cardiometabolic status. These results highlight the significance of polypharmacy in type 2 diabetes

    An RBP4 promoter polymorphism increases risk of type 2 diabetes

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    Aims/hypothesis: Retinol-binding protein 4 (RBP4), originally known for retinol transport, was recently identified as an adipokine affecting insulin resistance. The RBP4 -803GA promoter polymorphism influences binding of hepatic nuclear factor 1α and is associated with type 2 diabetes in case-control studies. We hypothesised that the RBP4 -803GA polymorphism increases type 2 diabetes risk at a population-based level. In addition, information on retinol intake and plasma vitamin A levels enabled us to explore the possible underlying mechanism. Methods: In the Rotterdam Study, a prospective, population-based, follow-up study, the -803GA polymorphism was genotyped. In Cox proportional hazards models, associations of the -803GA polymorphism and retinol intake with type 2 diabetes risk were examined. Moreover, the interaction of the polymorphism with retinol intake on type 2 diabetes risk was assessed. In a subgroup of participants the association of the polymorphism and vitamin A plasma levels was investigated. Results: Homozygous carriers of the -803A allele had increased risk of type 2 diabetes (HR 1.83; 95% CI 1.26-2.66). Retinol intake was not associated with type 2 diabetes risk and showed no interaction with the RBP4 -803GA polymorphism. Furthermore, there was no significant association of the polymorphism with plasma vitamin A levels. Conclusions/interpretation: Our results provide evidence that homozygosity for the RBP4 -803A allele is associated with increased risk of type 2 diabetes in the Rotterdam population. This relationship was not clearly explained by retinol intake and vitamin A plasma levels. Therefore, we cannot differentiate between a retinol-dependent or -independent mechanism of this RBP4 variant

    New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

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    Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

    A Methodological Perspective on Genetic Risk Prediction Studies in Type 2 Diabetes: Recommendations for Future Research

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    Fueled by the successes of genome-wide association studies, numerous studies have investigated the predictive ability of genetic risk models in type 2 diabetes. In this paper, we review these studies from a methodological perspective, focusing on the variables included in the risk models as well as the study designs and populations investigated. We argue and show that differences in study design and characteristics of the study population have an impact on the observed predictive ability of risk models. This observation emphasizes that genetic risk prediction studies should be conducted in those populations in which the prediction models will ultimately be applied, if proven useful. Of all genetic risk prediction studies to date, only a few were conducted in populations that might be relevant for targeting preventive interventions

    Cerebral Accumulation of Dietary Derivable Plant Sterols does not Interfere with Memory and Anxiety Related Behavior in Abcg5−/− Mice

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    Plant sterols such as sitosterol and campesterol are frequently applied as functional food in the prevention of atherosclerosis. Recently, it became clear that plasma derived plant sterols accumulate in murine brains. We questioned whether plant sterols in the brain are associated with alterations in brain cholesterol homeostasis and subsequently with brain functions. ATP binding cassette (Abc)g5−/− mice, a phytosterolemia model, were compared to Abcg5+/+ mice for serum and brain plant sterol accumulation and behavioral and cognitive performance. Serum and brain plant sterol concentrations were respectively 35–70-fold and 5–12-fold increased in Abcg5−/− mice (P < 0.001). Plant sterol accumulation resulted in decreased levels of desmosterol (P < 0.01) and 24(S)-hydroxycholesterol (P < 0.01) in the hippocampus, the brain region important for learning and memory functions, and increased lanosterol levels (P < 0.01) in the cortex. However, Abcg5−/− and Abcg5+/+ displayed no differences in memory functions or in anxiety and mood related behavior. The swimming speed of the Abcg5−/− mice was slightly higher compared to Abcg5+/+ mice (P < 0.001). In conclusion, plant sterols in the brains of Abcg5−/− mice did have consequences for brain cholesterol metabolism, but did not lead to an overt phenotype of memory or anxiety related behavior. Thus, our data provide no contra-indication for nutritional intake of plant sterol enriched nutrition

    Statin treatment increases lipoprotein(a) levels in subjects with low molecular weight apolipoprotein(a) phenotype

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    Background and aims: We aimed to evaluate the effect of statin treatment initiation on lipoprotein(a) [Lp(a)] levels in patients with dyslipidemia, and the interactions with the apolipoprotein(a) [apo(a)] phenotype, LPA single nucleotide polymorphisms (SNPs) and change in LDL cholesterol. Methods: The study population consisted of patients with dyslipidemia, predominantly familial hypercholesterolemia, who first initiated statin treatment (initiation group; n = 39) or were already on stable statin treatment for at least 4 months (control group; n = 42). Plasma Lp(a) levels were determined with a particle-enhanced immunoturbidimetric assay before and at least 2 months after start of statin treatment in individuals of the initiation group, and at two time points with an interval of at least 2 months in the control group. High and low molecular weight (HMW and LMW, respectively) apo(a) phenotype was determined by immunoblotting, and the common LPA SNPs rs10455872, rs3798220 and rs41272110 by Taqman assay. Results: Plasma Lp(a) levels did not increase significantly in the initiation group (median 20.5 (IQR 10.9–80.7) to 23.3 (10.8–71.8) mg/dL; p = 0.09) nor in the control group (30.9 (IQR 9.2–147.0) to 31.7 (IQR 10.9–164.0) mg/dL; p = 0.61). In patients with the LMW apo(a) phenotype, Lp(a) levels increased significantly from 66.4 (IQR 23.5–148.3) to 97.4 (IQR 24.9–160.4) mg/dL (p = 0.026) in the initiation group, but not in the control group and not in patients characterized by the HMW apo(a) phenotype. Interactions with common LPA SNPs and change in LDL cholesterol were not significant. Conclusions: Statins affect Lp(a) levels differently in patients with dyslipidemia depending on the apo(a) phenotype. Statins increase Lp(a) levels exclusively in patients with the LMW apo(a) phenotype

    Interactions of dietary whole-grain intake with fasting glucose- and insulin-related genetic loci in individuals of European descent: a meta-analysis of 14 cohort studies.

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    OBJECTIVE: Whole-grain foods are touted for multiple health benefits, including enhancing insulin sensitivity and reducing type 2 diabetes risk. Recent genome-wide association studies (GWAS) have identified several single nucleotide polymorphisms (SNPs) associated with fasting glucose and insulin concentrations in individuals free of diabetes. We tested the hypothesis that whole-grain food intake and genetic variation interact to influence concentrations of fasting glucose and insulin. RESEARCH DESIGN AND METHODS: Via meta-analysis of data from 14 cohorts comprising ∼ 48,000 participants of European descent, we studied interactions of whole-grain intake with loci previously associated in GWAS with fasting glucose (16 loci) and/or insulin (2 loci) concentrations. For tests of interaction, we considered a P value <0.0028 (0.05 of 18 tests) as statistically significant. RESULTS: Greater whole-grain food intake was associated with lower fasting glucose and insulin concentrations independent of demographics, other dietary and lifestyle factors, and BMI (β [95% CI] per 1-serving-greater whole-grain intake: -0.009 mmol/l glucose [-0.013 to -0.005], P < 0.0001 and -0.011 pmol/l [ln] insulin [-0.015 to -0.007], P = 0.0003). No interactions met our multiple testing-adjusted statistical significance threshold. The strongest SNP interaction with whole-grain intake was rs780094 (GCKR) for fasting insulin (P = 0.006), where greater whole-grain intake was associated with a smaller reduction in fasting insulin concentrations in those with the insulin-raising allele. CONCLUSIONS: Our results support the favorable association of whole-grain intake with fasting glucose and insulin and suggest a potential interaction between variation in GCKR and whole-grain intake in influencing fasting insulin concentrations

    2017 Update of ESC/EAS Task Force on practical clinical guidance for proprotein convertase subtilisin/kexin type 9 inhibition in patients with atherosclerotic cardiovascular disease or in familial hypercholesterolaemia

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    A correction has been published: European Heart Journal, Volume 39, Issue 22, 7 June 2018, Pages 2105Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2017.info:eu-repo/semantics/publishedVersio

    Association of an APOC3 promoter variant with type 2 diabetes risk and need for insulin treatment in lean persons

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    Aims/hypothesis: An APOC3 promoter haplotype has been previously associated with type 1 diabetes. In this population-based study, we investigated whether APOC3 polymorphisms increase type 2 diabetes risk and need for insulin treatment in lean participants. Methods: In the Rotterdam Study, a population-based prospective cohort (n = 7,983), Cox and logistic regression models were used to analyse the associations and interactive effects of APOC3 promoter variants (-482C > T, -455T > C) and BMI on type 2 diabetes risk and insulin treatment. Analyses were followed by replication in an independent case-control sample (1,817 cases, 2,292 controls) and meta-analysis. Results: In lean participants, the -482T allele was associated with increased risk of prevalent and incident type 2 diabetes: OR -482CT 1.47 (95% CI 1.13-1.92), -482TT 1.40 (95% CI 0.83-2.35), p = 0.009 for trend; HR -482CT 1.35 (95% CI 0.96-1.89), -482TT 1.68 (95% CI 0.91-3.1), p = 0.03 for trend, respectively. These results were confirmed by replication. Meta-analysis was highly significant (-482T meta-analysis p = 1.1 × 10-4). A borderline significant interaction was observed for insulin use among participants with type 2 diabetes (-482CT*BMI p = 0.06, -455TC*BMI p = 0.02). Conclusions/interpretation: At a population-based level, the influence of APOC3 promoter variants on type 2 diabetes risk varies with the level of adiposity. Lean carriers of the -482T allele had increased type 2 diabetes risk, while such an effect was not observed in overweight participants. Conversely, in overweight participants the -455C allele seemed protective against type 2 diabetes. The interaction of the variants with need for insulin treatment may indicate beta cell involvement in lean participants. Our findings suggest overlap in the genetic backgrounds of type 1 diabetes and type 2 diabetes in lean patients
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