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Sökning: WFRF:(Petrie Mark C) > Karolinska Institutet

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1.
  • Ingelsson, Erik, et al. (författare)
  • Detailed Physiologic Characterization Reveals Diverse Mechanisms for Novel Genetic Loci Regulating Glucose and Insulin Metabolism in Humans
  • 2010
  • Ingår i: Diabetes. - 0012-1797 .- 1939-327X. ; 59:5, s. 1266-1275
  • Konferensbidrag (refereegranskat)abstract
    • OBJECTIVE-Recent genome-wide association studies have revealed loci associated with glucose and insulin-related traits. We aimed to characterize 19 such loci using detailed measures of insulin processing, secretion, and sensitivity to help elucidate their role in regulation of glucose control, insulin secretion and/or action. RESEARCH DESIGN AND METHODS-We investigated associations of loci identified by the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) with circulating proinsulin, measures of insulin secretion and sensitivity from oral glucose tolerance tests (OGTTs), euglycemic clamps, insulin suppression tests, or frequently sampled intravenous glucose tolerance tests in nondiabetic humans (n = 29,084). RESULTS-The glucose-raising allele in MADD was associated with abnormal insulin processing (a dramatic effect on higher proinsulin levels, but no association with insulinogenic index) at extremely persuasive levels of statistical significance (P = 2.1 x 10(-71)). Defects in insulin processing and insulin secretion were seen in glucose-raising allele carriers at TCF7L2, SCL30A8, GIPR, and C2CD4B. Abnormalities in early insulin secretion were suggested in glucose-raising allele carriers at MTNR1B, GCK, FADS1, DGKB, and PROX1 (lower insulinogenic index; no association with proinsulin or insulin sensitivity). Two loci previously associated with fasting insulin (GCKR and IGF1) were associated with OGTT-derived insulin sensitivity indices in a consistent direction. CONCLUSIONS-Genetic loci identified through their effect on hyperglycemia and/or hyperinsulinemia demonstrate considerable heterogeneity in associations with measures of insulin processing, secretion, and sensitivity. Our findings emphasize the importance of detailed physiological characterization of such loci for improved understanding of pathways associated with alterations in glucose homeostasis and eventually type 2 diabetes. Diabetes 59:1266-1275, 2010
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2.
  • Broadaway, K Alaine, et al. (författare)
  • Loci for insulin processing and secretion provide insight into type 2 diabetes risk.
  • 2023
  • Ingår i: American Journal of Human Genetics. - : Elsevier. - 0002-9297 .- 1537-6605. ; 110:2, s. 284-299
  • Tidskriftsartikel (refereegranskat)abstract
    • Insulin secretion is critical for glucose homeostasis, and increased levels of the precursor proinsulin relative to insulin indicate pancreatic islet beta-cell stress and insufficient insulin secretory capacity in the setting of insulin resistance. We conducted meta-analyses of genome-wide association results for fasting proinsulin from 16 European-ancestry studies in 45,861 individuals. We found 36 independent signals at 30 loci (p value < 5 × 10-8), which validated 12 previously reported loci for proinsulin and ten additional loci previously identified for another glycemic trait. Half of the alleles associated with higher proinsulin showed higher rather than lower effects on glucose levels, corresponding to different mechanisms. Proinsulin loci included genes that affect prohormone convertases, beta-cell dysfunction, vesicle trafficking, beta-cell transcriptional regulation, and lysosomes/autophagy processes. We colocalized 11 proinsulin signals with islet expression quantitative trait locus (eQTL) data, suggesting candidate genes, including ARSG, WIPI1, SLC7A14, and SIX3. The NKX6-3/ANK1 proinsulin signal colocalized with a T2D signal and an adipose ANK1 eQTL signal but not the islet NKX6-3 eQTL. Signals were enriched for islet enhancers, and we showed a plausible islet regulatory mechanism for the lead signal in the MADD locus. These results show how detailed genetic studies of an intermediate phenotype can elucidate mechanisms that may predispose one to disease.
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4.
  • Jackson, Alice M., et al. (författare)
  • Apparent Treatment-Resistant Hypertension Across the Spectrum of Heart Failure Phenotypes in the Swedish HF Registry
  • 2022
  • Ingår i: JACC. Heart failure. - : ELSEVIER SCI LTD. - 2213-1779 .- 2213-1787. ; 10:6, s. 380-392
  • Tidskriftsartikel (refereegranskat)abstract
    • BACKGROUND Hypertension is common in patients with heart failure (HF), but less is known about resistant hypertension.OBJECTIVES This study sought to investigate apparent treatment-resistant hypertension (aTRH) in patients with HF in the SwedeHF (Swedish Heart Failure Registry), across the spectrum of HF phenotypes (heart failure with reduced ejection fraction [HFrEF], heart failure with mildly reduced ejection fraction [HFmrEF], and heart failure with preserved ejection fraction [HFpEF]).METHODS aTRH was defined as systolic blood pressure $140 mm Hg ($135 mm Hg in diabetes) despite treatment with an angiotensin-converting enzyme inhibitor, angiotensin receptor blocker, or sacubitril-valsartan, as well as a calcium-channel blocker and a diuretic; non-treatment-resistant hypertension (TRH) was defined as systolic blood pressure above these thresholds but not on the 3-drug combination; and normal blood pressure was defined as under these thresholds. In each left ventricular ejection fraction (LVEF) category, patient factors associated with aTRH and non-TRH and out-comes (HF hospitalization and cardiovascular death composite, its components, and all-cause death) according to hy-pertension category were examined.RESULTS Among 46,597 patients, aTRH was present in 2,693 (10%), 1,514 (14%), and 1,450 (17%) patients with HFrEF, HFmrEF, and HFpEF, respectively. Older age, obesity, diabetes, and kidney disease were associated with a greater like-lihood of aTRH and non-TRH (vs normal blood pressure). Associations were generally similar irrespective of LVEF category. Compared with normal blood pressure, aTRH was associated with a lower adjusted risk of the composite outcome in HFrEF and HFmrEF (HR: 0.79 [95% CI: 0.74-0.85] and HR: 0.86 [95% CI: 0.77-0.96]) but not in HFpEF (HR: 0.93 [95% CI: 0.84-1.04]).CONCLUSIONS aTRH was most common in HFpEF and least common in HFrEF. Associated patient characteristics were similar irrespective of LVEF category. aTRH (vs normal blood pressure) was associated with a lower risk of first HF hospitalization or cardiovascular death in HFrEF and HFmrEF but not in HFpEF. (J Am Coll Cardiol HF 2022;10:380-392) (c) 2022 by the American College of Cardiology Foundation.
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5.
  • Seferovic, Petar M., et al. (författare)
  • Sodium-glucose co-transporter 2 inhibitors in heart failure: beyond glycaemic control. A position paper of the Heart Failure Association of the European Society of Cardiology
  • 2020
  • Ingår i: European Journal of Heart Failure. - : WILEY. - 1388-9842 .- 1879-0844. ; 22:9, s. 1495-1503
  • Tidskriftsartikel (refereegranskat)abstract
    • Heart failure (HF) is common and associated with a poor prognosis, despite advances in treatment. Over the last decade cardiovascular outcome trials with sodium-glucose co-transporter 2 (SGLT2) inhibitors in patients with type 2 diabetes mellitus have demonstrated beneficial effects for three SGLT2 inhibitors (empagliflozin, canagliflozin and dapagliflozin) in reducing hospitalisations for HF. More recently, dapagliflozin reduced the risk of worsening HF or death from cardiovascular causes in patients with chronic HF with reduced left ventricular ejection fraction, with or without type 2 diabetes mellitus. A number of additional trials in HF patients with reduced and/or preserved left ventricular ejection fraction are ongoing and/or about to be reported. The present position paper summarises recent clinical trial evidence and discusses the role of SGLT2 inhibitors in the treatment of HF, pending the results of ongoing trials in different populations of patients with HF.
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6.
  • Zanetti, Daniela, et al. (författare)
  • Plasma proteomic signatures of a direct measure of insulin sensitivity in two population cohorts
  • 2023
  • Ingår i: Diabetologia. - : Springer. - 0012-186X .- 1432-0428. ; 66:9, s. 1643-1654
  • Tidskriftsartikel (refereegranskat)abstract
    • Aims/hypothesis The euglycaemic-hyperinsulinaemic clamp (EIC) is the reference standard for the measurement of whole-body insulin sensitivity but is laborious and expensive to perform. We aimed to assess the incremental value of high-through-put plasma proteomic profiling in developing signatures correlating with the M value derived from the EIC.Methods We measured 828 proteins in the fasting plasma of 966 participants from the Relationship between Insulin Sensitivity and Cardiovascular disease (RISC) study and 745 participants from the Uppsala Longitudinal Study of Adult Men (ULSAM) using a high-throughput proximity extension assay. We used the least absolute shrinkage and selection operator (LASSO) approach using clinical variables and protein measures as features. Models were tested within and across cohorts. Our primary model performance metric was the proportion of the M value variance explained (R-2).Results A standard LASSO model incorporating 53 proteins in addition to routinely available clinical variables increased the M value R-2 from 0.237 (95% CI 0.178, 0.303) to 0.456 (0.372, 0.536) in RISC. A similar pattern was observed in ULSAM, in which the M value R-2 increased from 0.443 (0.360, 0.530) to 0.632 (0.569, 0.698) with the addition of 61 proteins. Models trained in one cohort and tested in the other also demonstrated significant improvements in R-2 despite differences in baseline cohort characteristics and clamp methodology (RISC to ULSAM: 0.491 [0.433, 0.539] for 51 proteins; ULSAM to RISC: 0.369 [0.331, 0.416] for 67 proteins). A randomised LASSO and stability selection algorithm selected only two proteins per cohort (three unique proteins), which improved R-2 but to a lesser degree than in standard LASSO models: 0.352 (0.266, 0.439) in RISC and 0.495 (0.404, 0.585) in ULSAM. Reductions in improvements of R-2 with randomised LASSO and stability selection were less marked in cross-cohort analyses (RISC to ULSAM R-2 0.444 [0.391, 0.497]; ULSAM to RISC R-2 0.348 [0.300, 0.396]). Models of proteins alone were as effective as models that included both clinical variables and proteins using either standard or randomised LASSO. The single most consistently selected protein across all analyses and models was IGF-binding protein 2.Conclusions/interpretation A plasma proteomic signature identified using a standard LASSO approach improves the cross-sectional estimation of the M value over routine clinical variables. However, a small subset of these proteins identified using a stability selection algorithm affords much of this improvement, especially when considering cross-cohort analyses. Our approach provides opportunities to improve the identification of insulin-resistant individuals at risk of insulin resistance-related adverse health consequences.
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