| 11. |
- Natali, Andrea, et al.
(författare)
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Metformin is the key factor in elevated plasma growth differentiation factor-15 levels in type 2 diabetes : A nested, case–control study
- 2019
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Ingår i: Diabetes, Obesity and Metabolism. - : Wiley. - 1462-8902. ; 21:2, s. 412-416
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Tidskriftsartikel (refereegranskat)abstract
- Produced as a tissue defence response to hypoxia and inflammation, growth differentiation factor-15 (GDF-15) is elevated in people receiving metformin treatment. To gain insight into the relationship of GDF-15 with metformin and major cardiovascular risk factors, we analysed the data from the SUMMIT cohort (n = 1438), a four-centre, nested, case–control study aimed at verifying whether biomarkers of atherosclerosis differ according to the presence of type 2 diabetes and cardiovascular disease. While in univariate analysis, major cardiovascular risk factors, with the exception of gender and cholesterol, increased similarly and linearly across GDF-15 quartiles, the independent variables associated with GDF-15, both in participants with and without diabetes, were age, plasma creatinine, N-terminal pro-brain natriuretic peptide, diuretic use, smoking exposure and glycated haemoglobin. In participants with diabetes, metformin treatment was associated with a 40% rise in GDF-15 level, which was independent of the other major factors, and largely explained their elevated GDF-15 levels. The relatively high GDF-15 bioavailability might partly explain the protective cardiovascular effects of metformin.
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| 12. |
- Sandholm, Niina, et al.
(författare)
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Genome-wide meta-analysis and omics integration identifies novel genes associated with diabetic kidney disease
- 2022
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Ingår i: Diabetologia. - : Springer Science and Business Media LLC. - 0012-186X .- 1432-0428. ; 65:9, s. 1495-1509
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Tidskriftsartikel (refereegranskat)abstract
- Aims/hypothesis: Diabetic kidney disease (DKD) is the leading cause of kidney failure and has a substantial genetic component. Our aim was to identify novel genetic factors and genes contributing to DKD by performing meta-analysis of previous genome-wide association studies (GWAS) on DKD and by integrating the results with renal transcriptomics datasets. Methods: We performed GWAS meta-analyses using ten phenotypic definitions of DKD, including nearly 27,000 individuals with diabetes. Meta-analysis results were integrated with estimated quantitative trait locus data from human glomerular (N=119) and tubular (N=121) samples to perform transcriptome-wide association study. We also performed gene aggregate tests to jointly test all available common genetic markers within a gene, and combined the results with various kidney omics datasets. Results: The meta-analysis identified a novel intronic variant (rs72831309) in the TENM2 gene associated with a lower risk of the combined chronic kidney disease (eGFR<60 ml/min per 1.73 m2) and DKD (microalbuminuria or worse) phenotype (p=9.8×10−9; although not withstanding correction for multiple testing, p>9.3×10−9). Gene-level analysis identified ten genes associated with DKD (COL20A1, DCLK1, EIF4E, PTPRN–RESP18, GPR158, INIP–SNX30, LSM14A and MFF; p<2.7×10−6). Integration of GWAS with human glomerular and tubular expression data demonstrated higher tubular AKIRIN2 gene expression in individuals with vs without DKD (p=1.1×10−6). The lead SNPs within six loci significantly altered DNA methylation of a nearby CpG site in kidneys (p<1.5×10−11). Expression of lead genes in kidney tubules or glomeruli correlated with relevant pathological phenotypes (e.g. TENM2 expression correlated positively with eGFR [p=1.6×10−8] and negatively with tubulointerstitial fibrosis [p=2.0×10−9], tubular DCLK1 expression correlated positively with fibrosis [p=7.4×10−16], and SNX30 expression correlated positively with eGFR [p=5.8×10−14] and negatively with fibrosis [p<2.0×10−16]). Conclusions/interpretation: Altogether, the results point to novel genes contributing to the pathogenesis of DKD. Data availability: The GWAS meta-analysis results can be accessed via the type 1 and type 2 diabetes (T1D and T2D, respectively) and Common Metabolic Diseases (CMD) Knowledge Portals, and downloaded on their respective download pages (https://t1d.hugeamp.org/downloads.html; https://t2d.hugeamp.org/downloads.html; https://hugeamp.org/downloads.html). Graphical abstract: [Figure not available: see fulltext.]
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| 13. |
- Shore, Angela C, et al.
(författare)
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Use of Vascular Assessments and Novel Biomarkers to Predict Cardiovascular Events in Type 2 Diabetes : The SUMMIT VIP Study
- 2018
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Ingår i: Diabetes Care. - : American Diabetes Association. - 1935-5548 .- 0149-5992. ; 41:10, s. 2212-2219
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Tidskriftsartikel (refereegranskat)abstract
- OBJECTIVE: Cardiovascular disease (CVD) risk prediction represents an increasing clinical challenge in the treatment of diabetes. We used a panel of vascular imaging, functional assessments, and biomarkers reflecting different disease mechanisms to identify clinically useful markers of risk for cardiovascular (CV) events in subjects with type 2 diabetes (T2D) with or without manifest CVD.RESEARCH DESIGN AND METHODS: The study cohort consisted of 936 subjects with T2D recruited at four European centers. Carotid intima-media thickness and plaque area, ankle-brachial pressure index, arterial stiffness, endothelial function, and circulating biomarkers were analyzed at baseline, and CV events were monitored during a 3-year follow-up period.RESULTS: The CV event rate in subjects with T2D was higher in those with (n = 440) than in those without (n = 496) manifest CVD at baseline (5.53 vs. 2.15/100 life-years, P < 0.0001). New CV events in subjects with T2D with manifest CVD were associated with higher baseline levels of inflammatory biomarkers (interleukin 6, chemokine ligand 3, pentraxin 3, and hs-CRP) and endothelial mitogens (hepatocyte growth factor and vascular endothelial growth factor A), whereas CV events in subjects with T2D without manifest CVD were associated with more severe baseline atherosclerosis (median carotid plaque area 30.4 mm2 [16.1-92.2] vs. 19.5 mm2 [9.5-40.5], P = 0.01). Conventional risk factors, as well as measurements of arterial stiffness and endothelial reactivity, were not associated with CV events.CONCLUSIONS: Our observations demonstrate that markers of inflammation and endothelial stress reflect CV risk in subjects with T2D with manifest CVD, whereas the risk for CV events in subjects with T2D without manifest CVD is primarily related to the severity of atherosclerosis.
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| 14. |
- Ahuja, Vasudha, et al.
(författare)
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Accuracy of 1-Hour Plasma Glucose During the Oral Glucose Tolerance Test in Diagnosis of Type 2 Diabetes in Adults : A Meta-analysis
- 2021
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Ingår i: Diabetes Care. - : American Diabetes Association. - 1935-5548 .- 0149-5992. ; 44:4, s. 1062-1069
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Forskningsöversikt (refereegranskat)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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