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- Looker, Helen C., et al.
(författare)
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Protein biomarkers for the prediction of cardiovascular disease in type 2 diabetes
- 2015
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Ingår i: Diabetologia. - : Springer Science and Business Media LLC. - 1432-0428 .- 0012-186X. ; 58:6, s. 1363-1371
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Tidskriftsartikel (refereegranskat)abstract
- Aims/hypothesis We selected the most informative protein biomarkers for the prediction of incident cardiovascular disease (CVD) in people with type 2 diabetes. Methods In this nested case-control study we measured 42 candidate CVD biomarkers in 1,123 incident CVD cases and 1,187 controls with type 2 diabetes selected from five European centres. Combinations of biomarkers were selected using cross-validated logistic regression models. Model prediction was assessed using the area under the receiver operating characteristic curve (AUROC). Results Sixteen biomarkers showed univariate associations with incident CVD. The most predictive subset selected by forward selection methods contained six biomarkers: N-terminal pro-B-type natriuretic peptide (OR 1.69 per 1 SD, 95% CI 1.47, 1.95), high-sensitivity troponin T (OR 1.29, 95% CI 1.11, 1.51), IL-6 (OR 1.13, 95% CI 1.02, 1.25), IL-15 (OR 1.15, 95% CI 1.01, 1.31), apolipoprotein C-III (OR 0.79, 95% CI 0.70, 0.88) and soluble receptor for AGE (OR 0.84, 95% CI 0.76, 0.94). The prediction of CVD beyond clinical covariates improved from an AUROC of 0.66 to 0.72 (AUROC for Framingham Risk Score covariates 0.59). In addition to the biomarkers, the most important clinical covariates for improving prediction beyond the Framingham covariates were estimated GFR, insulin therapy and HbA(1c). Conclusions/interpretation We identified six protein biomarkers that in combination with clinical covariates improved the prediction of our model beyond the Framingham Score covariates. Biomarkers can contribute to improved prediction of CVD in diabetes but clinical data including measures of renal function and diabetes-specific factors not included in the Framingham Risk Score are also needed.
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| 2. |
- Sandholm, Niina, et al.
(författare)
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The genetic landscape of renal complications in type 1 diabetes
- 2017
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Ingår i: Journal of the American Society of Nephrology. - 1046-6673. ; 28:2, s. 557-574
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Tidskriftsartikel (refereegranskat)abstract
- Diabetes is the leading cause of ESRD. Despite evidence for a substantial heritability of diabetic kidney disease, efforts to identify genetic susceptibility variants have had limited success. We extended previous efforts in three dimensions, examining a more comprehensive set of genetic variants in larger numbers of subjects with type 1 diabetes characterized for a wider range of cross-sectional diabetic kidney disease phenotypes. In 2843 subjects, we estimated that the heritability of diabetic kidney disease was 35% (P=6.4310-3). Genome-wide association analysis and replication in 12,540 individuals identified no single variants reaching stringent levels of significance and, despite excellent power, provided little independent confirmation of previously published associatedvariants.Whole-exome sequencing in 997 subjects failed to identify any large-effect coding alleles of lower frequency influencing the risk of diabetic kidney disease. However, sets of alleles increasing body mass index (P=2.2310-5) and the risk of type 2 diabetes (P=6.1310-4) associated with the risk of diabetic kidney disease.Wealso found genome-wide genetic correlation between diabetic kidney disease and failure at smoking cessation (P=1.1310-4). Pathway analysis implicated ascorbate and aldarate metabolism (P=9.0310-6), and pentose and glucuronate interconversions (P=3.0310-6) in pathogenesis of diabetic kidney disease. These data provide further evidence for the role of genetic factors influencing diabetic kidney disease in those with type 1 diabetes and highlight some key pathways that may be responsible. Altogether these results reveal important biology behind the major cause of kidney disease.
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| 3. |
- van Zuydam, Natalie, et al.
(författare)
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Genome-Wide Association Study of Peripheral Artery Disease
- 2021
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Ingår i: Circulation. - : Lippincott Williams & Wilkins. - 2574-8300. ; 14:5
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Tidskriftsartikel (refereegranskat)abstract
- Background: Peripheral artery disease (PAD) affects >200 million people worldwide and is associated with high mortality and morbidity. We sought to identify genomic variants associated with PAD overall and in the contexts of diabetes and smoking status. Methods: We identified genetic variants associated with PAD and then meta-analyzed with published summary statistics from the Million Veterans Program and UK Biobank to replicate their findings. Next, we ran stratified genome-wide association analysis in ever smokers, never smokers, individuals with diabetes, and individuals with no history of diabetes and corresponding interaction analyses, to identify variants that modify the risk of PAD by diabetic or smoking status. Results: We identified 5 genome-wide significant (P-association <= 5x10(-8)) associations with PAD in 449 548 (N-cases=12 086) individuals of European ancestry near LPA (lipoprotein [a]), CDKN2BAS1 (CDKN2B antisense RNA 1), SH2B3 (SH2B adaptor protein 3) - PTPN11 (protein tyrosine phosphatase non-receptor type 11), HDAC9 (histone deacetylase 9), and CHRNA3 (cholinergic receptor nicotinic alpha 3 subunit) loci (which overlapped previously reported associations). Meta-analysis with variants previously associated with PAD showed that 18 of 19 published variants remained genome-wide significant. In individuals with diabetes, rs116405693 at the CCSER1 (coiled-coil serine rich protein 1) locus was associated with PAD (odds ratio [95% CI], 1.51 [1.32-1.74], P-diabetes=2.5x10(-9), P-interactionwithdiabetes=5.3x10(-7)). Furthermore, in smokers, rs12910984 at the CHRNA3 locus was associated with PAD (odds ratio [95% CI], 1.15 [1.11-1.19], P-smokers=9.3x10(-10), P-interactionwithsmoking=3.9x10(-5)). Conclusions: Our analyses confirm the published genetic associations with PAD and identify novel variants that may influence susceptibility to PAD in the context of diabetes or smoking status.
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| 4. |
- van Zuydam, Natalie R., et al.
(författare)
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Genetic Predisposition to Coronary Artery Disease in Type 2 Diabetes Mellitus
- 2020
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Ingår i: Circulation. - : Lippincott Williams & Wilkins. - 2574-8300. ; 13:6, s. 640-648
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Coronary artery disease (CAD) is accelerated in subjects with type 2 diabetes mellitus (T2D).METHODS: To test whether this reflects differential genetic influences on CAD risk in subjects with T2D, we performed a systematic assessment of genetic overlap between CAD and T2D in 66 643 subjects (27 708 with CAD and 24 259 with T2D). Variants showing apparent association with CAD in stratified analyses or evidence of interaction were evaluated in a further 117 787 subjects (16 694 with CAD and 11 537 with T2D).RESULTS: None of the previously characterized CAD loci was found to have specific effects on CAD in T2D individuals, and a genome-wide interaction analysis found no new variants for CAD that could be considered T2D specific. When we considered the overall genetic correlations between CAD and its risk factors, we found no substantial differences in these relationships by T2D background.CONCLUSIONS: This study found no evidence that the genetic architecture of CAD differs in those with T2D compared with those without T2D.
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| 5. |
- Zhou, Kaixin, et al.
(författare)
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Heritability of variation in glycaemic response to metformin: a genome-wide complex trait analysis.
- 2014
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Ingår i: The Lancet Diabetes & Endocrinology. - 2213-8595. ; 2:6, s. 481-487
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Tidskriftsartikel (refereegranskat)abstract
- Metformin is a first-line oral agent used in the treatment of type 2 diabetes, but glycaemic response to this drug is highly variable. Understanding the genetic contribution to metformin response might increase the possibility of personalising metformin treatment. We aimed to establish the heritability of glycaemic response to metformin using the genome-wide complex trait analysis (GCTA) method.
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