81 research outputs found

    Definitions of Metabolic Health and Risk of Future Type 2 Diabetes in BMI Categories: A Systematic Review and Network Meta-analysis.

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    OBJECTIVE: Various definitions of metabolic health have been proposed to explain differences in the risk of type 2 diabetes within BMI categories. The goal of this study was to assess their predictive relevance. RESEARCH DESIGN AND METHODS: We performed systematic searches of MEDLINE records for prospective cohort studies of type 2 diabetes risk in categories of BMI and metabolic health. In a two-stage meta-analysis, relative risks (RRs) specific to each BMI category were derived by network meta-analysis and the resulting RRs of each study were pooled using random-effects models. Hierarchical summary receiver operating characteristic curves were used to assess predictive performance. RESULTS: In a meta-analysis of 140,845 participants and 5,963 incident cases of type 2 diabetes from 14 cohort studies, classification as metabolically unhealthy was associated with higher RR of diabetes in all BMI categories (lean RR compared with healthy individuals 4.0 [95% CI 3.0-5.1], overweight 3.4 [2.8-4.3], and obese 2.5 [2.1-3.0]). Metabolically healthy obese individuals had a high absolute risk of type 2 diabetes (10-year cumulative incidence 3.1% [95% CI 2.6-3.5]). Current binary definitions of metabolic health had high specificity (pooled estimate 0.88 [95% CI 0.84-0.91]) but low sensitivity (0.40 [0.31-0.49]) in lean individuals and satisfactory sensitivity (0.81 [0.76-0.86]) but low specificity (0.42 [0.35-0.49]) in obese individuals. However, positive (0.4) likelihood ratios were consistent with insignificant to small improvements in prediction. CONCLUSIONS: Although individuals classified as metabolically unhealthy have a higher RR of type 2 diabetes compared with individuals classified as healthy in all BMI categories, current binary definitions of metabolic health have limited relevance to the prediction of future type 2 diabetes.The research leading to these results has received support from the Innovative Medicines Initiative Joint Undertaking under EMIF grant agreement n° 115372, resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in kind contribution. This work was supported by the Netherlands Organization for Scientific Research (NWO), and the Medical Research Council UK (grant no. MC_U106179471). A.A. is supported by a Rubicon grant from the NWO (Project no. 825.13.004).This is an author-created, uncopyedited electronic version of an article accepted for publication in Diabetes Care. The American Diabetes Care Association (ADA), publisher of Diabetes Care, is not responsible for any errors or omissions in this version of the manuscript or any version derived from it by third parties. The definitive publisher-authenticated version will be available in a future issue of Diabetes Care in print and online at http://care.diabetesjournals.org

    Metabolomic profiling to dissect the role of visceral fat in cardiometabolic health

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    OBJECTIVE: Abdominal obesity is associated with increased risk of type 2 diabetes (T2D) and cardiovascular disease. The aim of this study was to assess whether metabolomic markers of T2D and blood pressure (BP) act on these traits via visceral fat (VF) mass. METHODS: Metabolomic profiling of 280 fasting plasma metabolites was conducted on 2,401 women from TwinsUK. The overlap was assessed between published metabolites associated with T2D, insulin resistance, or BP and those that were identified to be associated with VF (after adjustment for covariates) measured by dual‐energy X‐ray absorptiometry. RESULTS: In addition to glucose, six metabolites were strongly associated with both VF mass and T2D: lactate and branched‐chain amino acids, all of them related to metabolism and the tricarboxylic acid cycle; on average, 38.5% of their association with insulin resistance was mediated by their association with VF mass. Five metabolites were associated with BP and VF mass including the inflammation‐associated peptide HWESASXX, the steroid hormone androstenedione, lactate, and palmitate. On average, 29% of their effect on BP was mediated by their association with VF mass. CONCLUSIONS: Little overlap was found between the metabolites associated with BP and those associated with insulin resistance via VF mass

    Systematic Review with Meta-Analysis: Diagnostic Accuracy of Pro-C3 for Hepatic Fibrosis in Patients with Non-Alcoholic Fatty Liver Disease

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    The prevalence and severity of non-alcoholic fatty liver disease (NAFLD) is increasing, yet adequately validated tests for care paths are limited and non-invasive markers of disease progression are urgently needed. The aim of this work was to summarize the performance of Pro-C3, a biomarker of active fibrogenesis, in detecting significant fibrosis (F ≥ 2), advanced fibrosis (F ≥ 3), cirrhosis (F4) and non-alcoholic steatohepatitis (NASH) in patients with NAFLD. A sensitive search of five databases was performed in July 2021. Studies reporting Pro-C3 measurements and liver histology in adults with NAFLD without co-existing liver diseases were eligible. Meta-analysis was conducted by applying a bivariate random effects model to produce summary estimates of Pro-C3 accuracy. From 35 evaluated reports, eight studies met our inclusion criteria; 1568 patients were included in our meta-analysis of significant fibrosis and 2058 in that of advanced fibrosis. The area under the summary curve was 0.81 (95% CI 0.77–0.84) in detecting significant fibrosis and 0.79 (95% CI 0.73–0.82) for advanced fibrosis. Our results support Pro-C3 as an important candidate biomarker for non-invasive assessment of liver fibrosis in NAFLD. Further direct comparisons with currently recommended non-invasive tests will demonstrate whether Pro-C3 panels can outperform these tests, and improve care paths for patients with NAFLD

    The European NAFLD Registry: A real-world longitudinal cohort study of nonalcoholic fatty liver disease.

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    Non-Alcoholic Fatty Liver Disease (NAFLD), a progressive liver disease that is closely associated with obesity, type 2 diabetes, hypertension and dyslipidaemia, represents an increasing global public health challenge. There is significant variability in the disease course: the majority exhibit only fat accumulation in the liver but a significant minority develop a necroinflammatory form of the disease (non-alcoholic steatohepatitis, NASH) that may progress to cirrhosis and hepatocellular carcinoma. At present our understanding of pathogenesis, disease natural history and long-term outcomes remain incomplete. There is a need for large, well characterised patient cohorts that may be used to address these knowledge gaps and to support the development of better biomarkers and novel therapies. The European NAFLD Registry is an international, prospectively recruited observational cohort study that aims to establish a large, highly-phenotyped patient cohort and linked bioresource. Here we describe the infrastructure, data management and monitoring plans, and the standard operating procedures implemented to ensure the timely and systematic collection of high-quality data and samples. Already recruiting subjects at secondary/tertiary care centres across Europe, the Registry is supporting the European Union IMI2-funded LITMUS 'Liver Investigation: Testing Marker Utility in Steatohepatitis' consortium, which is a major international effort to robustly validate biomarkers that diagnose, risk stratify and/or monitor NAFLD progression and liver fibrosis stage. The European NAFLD Registry has the demonstrable capacity to support research and biomarker development at scale and pace

    Ligation of Macrophage Fcγ Receptors Recapitulates the Gene Expression Pattern of Vulnerable Human Carotid Plaques

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    Stroke is a leading cause of death in the United States. As ∼60% of strokes result from carotid plaque rupture, elucidating the mechanisms that underlie vulnerability is critical for therapeutic intervention. We tested the hypothesis that stable and vulnerable human plaques differentially express genes associated with matrix degradation. Examination established that femoral, and the distal region of carotid, plaques were histologically stable while the proximal carotid plaque regions were vulnerable. Quantitative RT-PCR was used to compare expression of 22 genes among these tissues. Distal carotid and femoral gene expression was not significantly different, permitting the distal carotid segments to be used as a paired control for their corresponding proximal regions. Analysis of the paired plaques revealed differences in 16 genes that impact plaque stability: matrix metalloproteinases (MMP, higher in vulnerable), MMP modulators (inhibitors: lower, activators: higher in vulnerable), activating Fc receptors (FcγR, higher in vulnerable) and FcγR signaling molecules (higher in vulnerable). Surprisingly, the relative expression of smooth muscle cell and macrophage markers in the three plaque types was not significantly different, suggesting that macrophage distribution and/or activation state correlates with (in)stability. Immunohistochemistry revealed that macrophages and smooth muscle cells localize to distinct and non-overlapping regions in all plaques. MMP protein localized to macrophage-rich regions. In vitro, treatment of macrophages with immune complexes, but not oxidized low density lipoprotein, C-reactive protein, or TNF-α, induced a gene expression profile similar to that of the vulnerable plaques. That ligation of FcγR recapitulates the pattern of gene expression in vulnerable plaques suggests that the FcγR → macrophage activation pathway may play a greater role in human plaque vulnerability than previously appreciated

    Serum kidney injury molecule 1 and β2-microglobulin perform as well as larger biomarker panels for prediction of rapid decline in renal function in type 2 diabetes

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    Aims/hypothesis: As part of the Surrogate Markers for Micro- and Macrovascular Hard Endpoints for Innovative Diabetes Tools (SUMMIT) programme we previously reported that large panels of biomarkers derived from three analytical platforms maximised prediction of progression of renal decline in type 2 diabetes. Here, we hypothesised that smaller (n ≤ 5), platform-specific combinations of biomarkers selected from these larger panels might achieve similar prediction performance when tested in three additional type 2 diabetes cohorts. Methods: We used 657 serum samples, held under differing storage conditions, from the Scania Diabetes Registry (SDR) and Genetics of Diabetes Audit and Research Tayside (GoDARTS), and a further 183 nested case–control sample set from the Collaborative Atorvastatin in Diabetes Study (CARDS). We analysed 42 biomarkers measured on the SDR and GoDARTS samples by a variety of methods including standard ELISA, multiplexed ELISA (Luminex) and mass spectrometry. The subset of 21 Luminex biomarkers was also measured on the CARDS samples. We used the event definition of loss of >20% of baseline eGFR during follow-up from a baseline eGFR of 30–75 ml min−1 [1.73 m]−2. A total of 403 individuals experienced an event during a median follow-up of 7 years. We used discrete-time logistic regression models with tenfold cross-validation to assess association of biomarker panels with loss of kidney function. Results: Twelve biomarkers showed significant association with eGFR decline adjusted for covariates in one or more of the sample sets when evaluated singly. Kidney injury molecule 1 (KIM-1) and β2-microglobulin (B2M) showed the most consistent effects, with standardised odds ratios for progression of at least 1.4 (p < 0.0003) in all cohorts. A combination of B2M and KIM-1 added to clinical covariates, including baseline eGFR and albuminuria, modestly improved prediction, increasing the area under the curve in the SDR, Go-DARTS and CARDS by 0.079, 0.073 and 0.239, respectively. Neither the inclusion of additional Luminex biomarkers on top of B2M and KIM-1 nor a sparse mass spectrometry panel, nor the larger multiplatform panels previously identified, consistently improved prediction further across all validation sets. Conclusions/interpretation: Serum KIM-1 and B2M independently improve prediction of renal decline from an eGFR of 30–75 ml min−1 [1.73 m]−2 in type 2 diabetes beyond clinical factors and prior eGFR and are robust to varying sample storage conditions. Larger panels of biomarkers did not improve prediction beyond these two biomarkers

    The Type 2 Diabetes Knowledge Portal: an Open access Genetic Resource Dedicated to Type 2 Diabetes and Related Traits

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    Associations between human genetic variation and clinical phenotypes have become a foundation of biomedical research. Most repositories of these data seek to be disease-agnostic and therefore lack disease-focused views. The Type 2 Diabetes Knowledge Portal (T2DKP) is a public resource of genetic datasets and genomic annotations dedicated to type 2 diabetes (T2D) and related traits. Here, we seek to make the T2DKP more accessible to prospective users and more useful to existing users. First, we evaluate the T2DKP\u27s comprehensiveness by comparing its datasets with those of other repositories. Second, we describe how researchers unfamiliar with human genetic data can begin using and correctly interpreting them via the T2DKP. Third, we describe how existing users can extend their current workflows to use the full suite of tools offered by the T2DKP. We finally discuss the lessons offered by the T2DKP toward the goal of democratizing access to complex disease genetic results

    Loss-of-function mutations in SLC30A8 protect against type 2 diabetes.

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    Neðst á síðunni er hægt að nálgast greinina í heild sinni með því að smella á hlekkinn View/OpenLoss-of-function mutations protective against human disease provide in vivo validation of therapeutic targets, but none have yet been described for type 2 diabetes (T2D). Through sequencing or genotyping of ~150,000 individuals across 5 ancestry groups, we identified 12 rare protein-truncating variants in SLC30A8, which encodes an islet zinc transporter (ZnT8) and harbors a common variant (p.Trp325Arg) associated with T2D risk and glucose and proinsulin levels. Collectively, carriers of protein-truncating variants had 65% reduced T2D risk (P = 1.7 × 10(-6)), and non-diabetic Icelandic carriers of a frameshift variant (p.Lys34Serfs*50) demonstrated reduced glucose levels (-0.17 s.d., P = 4.6 × 10(-4)). The two most common protein-truncating variants (p.Arg138* and p.Lys34Serfs*50) individually associate with T2D protection and encode unstable ZnT8 proteins. Previous functional study of SLC30A8 suggested that reduced zinc transport increases T2D risk, and phenotypic heterogeneity was observed in mouse Slc30a8 knockouts. In contrast, loss-of-function mutations in humans provide strong evidence that SLC30A8 haploinsufficiency protects against T2D, suggesting ZnT8 inhibition as a therapeutic strategy in T2D prevention.US National Institutes of Health (NIH) Training 5-T32-GM007748-33 Doris Duke Charitable Foundation 2006087 Fulbright Diabetes UK Fellowship BDA 11/0004348 Broad Institute from Pfizer, Inc. NIH U01 DK085501 U01 DK085524 U01 DK085545 U01 DK085584 Swedish Research Council Dnr 521-2010-3490 Dnr 349-2006-237 European Research Council (ERC) GENETARGET T2D GA269045 ENGAGE 2007-201413 CEED3 2008-223211 Sigrid Juselius Foundation Folkh lsan Research Foundation ERC AdG 293574 Research Council of Norway 197064/V50 KG Jebsen Foundation University of Bergen Western Norway Health Authority Lundbeck Foundation Novo Nordisk Foundation Wellcome Trust WT098017 WT064890 WT090532 WT090367 WT098381 Uppsala University Swedish Research Council and the Swedish Heart- Lung Foundation Academy of Finland 124243 102318 123885 139635 Finnish Heart Foundation Finnish Diabetes Foundation, Tekes 1510/31/06 Commission of the European Community HEALTH-F2-2007-201681 Ministry of Education and Culture of Finland European Commission Framework Programme 6 Integrated Project LSHM-CT-2004-005272 City of Kuopio and Social Insurance Institution of Finland Finnish Foundation for Cardiovascular Disease NIH/NIDDK U01-DK085545 National Heart, Lung, and Blood Institute (NHLBI) National Institute on Minority Health and Health Disparities N01 HC-95170 N01 HC-95171 N01 HC-95172 European Union Seventh Framework Programme, DIAPREPP Swedish Child Diabetes Foundation (Barndiabetesfonden) 5U01DK085526 DK088389 U54HG003067 R01DK072193 R01DK062370 Z01HG000024info:eu-repo/grantAgreement/EC/FP7/20201

    A Genome-Wide Association Study of Diabetic Kidney Disease in Subjects With Type 2 Diabetes

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    dentification 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 x 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.Peer reviewe
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