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Camps-Vilaro A, Subirana I, Ramos R, Cainzos-Achirica M, Tizon-Marcos H, Fito M, Degano IR, Marrugat J. Five-Year Changes in Inflammatory, Metabolic, and Oxidative Biomarkers and 10-Year Cardiovascular Disease Incidence: The REGICOR Cohort Study. Int J Mol Sci 2023; 24:ijms24097934. [PMID: 37175639 PMCID: PMC10178750 DOI: 10.3390/ijms24097934] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 04/18/2023] [Accepted: 04/20/2023] [Indexed: 05/15/2023] Open
Abstract
Ischemic cardiovascular diseases (CVD) originate from an imbalance between atherosclerotic plaque formation, instability, and endothelial healing dynamics. Our aim was to examine the relationship between 5-year changes in inflammatory, metabolic, and oxidative biomarkers and 10-year CVD incidence in a population without previous CVD. This was a prospective cohort study of individuals aged 35-74 years (n = 419) randomly selected from 5263 REGICOR participants without CVD recruited in 2005. Biomarkers were measured at baseline and in 2010. Participants were followed up until 2020 for a composite CVD endpoint including coronary artery disease, stroke, and peripheral artery disease. We used Cox regression to analyze the effect of biomarker levels on the occurrence of the composite endpoint, adjusted for traditional CVD risk factors and baseline levels of each biomarker. Individuals with elevated IL-6 or insulin after 5 years had a higher independent risk of CVD at 10 years, compared to those with lower levels. Each rise of 1 pg/mL of IL-6 or 10 pg/mL of insulin increased the 10-year risk of a CVD event by 32% and 2%, respectively. Compared to a model with traditional CVD risk factors only, the inclusion of IL-6 and insulin improved continuous reclassification by 51%. Elevated serum levels of IL-6 and insulin were associated with a higher risk of CVD at 10 years, independently of traditional CVD risk factors.
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Affiliation(s)
- Anna Camps-Vilaro
- REGICOR Study Group, Hospital del Mar Medical Research Institute (IMIM), 08003 Barcelona, Spain
- CIBER of Cardiovascular Diseases (CIBERCV), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain
- Doctoral College, University of Vic-Central University of Catalonia (UVic-UCC), 08500 Vic, Spain
| | - Isaac Subirana
- REGICOR Study Group, Hospital del Mar Medical Research Institute (IMIM), 08003 Barcelona, Spain
- CIBER of Cardiovascular Diseases (CIBERCV), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain
| | - Rafel Ramos
- Medical Science Department, School of Medicine, University of Girona, 17003 Girona, Spain
- Vascular Health Research Group, Institut Universitari per a la Recerca en Atenció Primària Jordi Gol i Gurina, 17002 Girona, Spain
- Girona Biomedical Research Institute, 17190 Girona, Spain
- Primary Care Services, Catalan Institute of Health, 17005 Girona, Spain
| | - Miguel Cainzos-Achirica
- Biomedical Research in Heart Diseases Group, Hospital del Mar Medical Research Institute (IMIM), 08003 Barcelona, Spain
- Department of Cardiology, Hospital del Mar, 08003 Barcelona, Spain
| | - Helena Tizon-Marcos
- CIBER of Cardiovascular Diseases (CIBERCV), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain
- Biomedical Research in Heart Diseases Group, Hospital del Mar Medical Research Institute (IMIM), 08003 Barcelona, Spain
- Department of Cardiology, Hospital del Mar, 08003 Barcelona, Spain
| | - Montse Fito
- Cardiovascular Risk and Nutrition Research Group, Hospital del Mar Medical Research Institute (IMIM), 08003 Barcelona, Spain
- CIBER of Pathophysiology of Obesity and Nutrition (CIBEROBN), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain
| | - Irene R Degano
- REGICOR Study Group, Hospital del Mar Medical Research Institute (IMIM), 08003 Barcelona, Spain
- CIBER of Cardiovascular Diseases (CIBERCV), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain
- Faculty of Medicine, University of Vic-Central University of Catalonia (UVic-UCC), 08500 Vic, Spain
| | - Jaume Marrugat
- REGICOR Study Group, Hospital del Mar Medical Research Institute (IMIM), 08003 Barcelona, Spain
- CIBER of Cardiovascular Diseases (CIBERCV), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain
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Campos Muñiz C, León-García PE, Serrato Diaz A, Hernández-Pérez E. [Diabetes mellitus prediction based on the triglyceride and glucose index]. Med Clin (Barc) 2023; 160:231-236. [PMID: 35933191 DOI: 10.1016/j.medcli.2022.07.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 07/06/2022] [Accepted: 07/07/2022] [Indexed: 10/16/2022]
Abstract
INTRODUCTION In Mexico, type 2 Diabetes mellitus (DM2) presents epidemiological levels with a prevalence rate of 9.12% and with the highest overweight and obesity rates worldwide. To overcome this situation, strategies must be created focused on the identification of subjects at risk. The Triglyceride and Glucose (TyG) index, was created for the detection of insulin resistance, has recently been used in the prediction of DM. The objective of the present study was to determine the predictive power of the TyG index in a cohort from Mexico City. METHODS 3195 patients were selected from a cohort of patients from the chronic degenerative area of the Health Centers of the Public Health Services of Mexico City. The ability of the TyG index in predicting diabetes was evaluated as: ln [Fasting triglycerides (mg/dl) x fasting glucose (mg/dl)/2]. after a follow-up of at least 4.5 years. A CHAID test was determined that was corroborated by a ROC test. RESULTS the value of the TyG index was significantly higher for patients who develop DM2. Values of AUC=0.934, 95% CI: 0.924-0.924. Obtaining a cut-off point of 9.45 in women; in men: DM2 AUC=0.824, 95% CI: 0.824-0.873, and cut-off point 9.12. CONCLUSIONS The TyG index is a good marker in the prediction of DM2. The CHAID determination is a useful tool in the prediction of DM2.
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Affiliation(s)
- Carolina Campos Muñiz
- Departamento de Ciencias de la Salud, División de Ciencias Biológicas y de la Salud, Universidad Autónoma Metropolitana Iztapalapa, Ciudad de México, México
| | - Plácido Enrique León-García
- Secretaría de Salud Pública del Distrito Federal, Servicios de Salud Pública del Distrito Federal, Ciudad de México, México
| | - Alejandra Serrato Diaz
- Departamento de Hidrobiología, División de Ciencias Biológicas y de la Salud, Universidad Autónoma Metropolitana Iztapalapa, Ciudad de México, México
| | - Elizabeth Hernández-Pérez
- Departamento de Ciencias de la Salud, División de Ciencias Biológicas y de la Salud, Universidad Autónoma Metropolitana Iztapalapa, Ciudad de México, México.
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Gancheva S, Kahl S, Herder C, Strassburger K, Sarabhai T, Pafili K, Szendroedi J, Schlensak M, Roden M. Metabolic surgery-induced changes of the growth hormone system relate to improved adipose tissue function. Int J Obes (Lond) 2023; 47:505-511. [PMID: 36959287 DOI: 10.1038/s41366-023-01292-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Revised: 02/26/2023] [Accepted: 03/01/2023] [Indexed: 03/25/2023]
Abstract
AIMS Body weight loss improves insulin resistance and growth hormone secretion in obesity, which may be regulated by leptin according to preclinical studies. How changes in leptin, lipids and insulin sensitivity after bariatric (metabolic) surgery affect the human growth hormone system is yet unclear. PARTICIPANTS AND METHODS People with obesity (OBE, n = 79, BMI 50.8 ± 6.3 kg/m2) were studied before, 2, 12, 24 and 52 weeks after metabolic surgery and compared to lean healthy humans (control; CON, n = 24, BMI 24.3 ± 3.1 kg/m2). Tissue-specific insulin sensitivity was assessed by hyperinsulinemic-euglycemic clamps with D-[6,6-2H2]glucose. Fasting leptin, growth hormone (GH), insulin-like growth factor 1 (IGF-1) and IGF-binding proteins (IGFBP1, IGFBP3) were measured using ELISA. RESULTS At baseline, OBE exhibited higher glycemia and leptinemia as well as pronounced peripheral, adipose tissue and hepatic insulin resistance compared to CON. GH and IGFBP1 were lower, while IGF1 was comparable between groups. At 52 weeks, OBE had lost 33% body weight and doubled their peripheral insulin sensitivity, which was paralleled by continuous increases in GH, IGF-1 and IGFBP1 as well as decrease in leptin. The rise in GH correlated with reductions in free fatty acids, adipose tissue insulin resistance and insulinemia, but not with changes in body weight, peripheral insulin sensitivity, glycemia or leptinemia. The rise in IGF-1 correlated with reduction in high-sensitive C-reactive protein. CONCLUSION Reversal of alterations of the GH-IGF-1 axis after surgically-induced weight loss is unlikely related to improved leptin secretion and/or insulin sensitivity, but is rather associated with restored adipose tissue function and reduced low-grade inflammation.
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Affiliation(s)
- Sofiya Gancheva
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital, Heinrich-Heine University, Düsseldorf, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
- German Center for Diabetes Research (DZD e.V.), Partner Düsseldorf, Munich-Neuherberg, Düsseldorf, Germany
| | - Sabine Kahl
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
- German Center for Diabetes Research (DZD e.V.), Partner Düsseldorf, Munich-Neuherberg, Düsseldorf, Germany
| | - Christian Herder
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital, Heinrich-Heine University, Düsseldorf, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
- German Center for Diabetes Research (DZD e.V.), Partner Düsseldorf, Munich-Neuherberg, Düsseldorf, Germany
| | - Klaus Strassburger
- German Center for Diabetes Research (DZD e.V.), Partner Düsseldorf, Munich-Neuherberg, Düsseldorf, Germany
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
| | - Theresia Sarabhai
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital, Heinrich-Heine University, Düsseldorf, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
- German Center for Diabetes Research (DZD e.V.), Partner Düsseldorf, Munich-Neuherberg, Düsseldorf, Germany
| | - Kalliopi Pafili
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital, Heinrich-Heine University, Düsseldorf, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
- German Center for Diabetes Research (DZD e.V.), Partner Düsseldorf, Munich-Neuherberg, Düsseldorf, Germany
| | - Julia Szendroedi
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital, Heinrich-Heine University, Düsseldorf, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
- German Center for Diabetes Research (DZD e.V.), Partner Düsseldorf, Munich-Neuherberg, Düsseldorf, Germany
- Department of Internal Medicine I and Clinical Chemistry, Heidelberg University Hospital, Heidelberg, Germany
| | | | - Michael Roden
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital, Heinrich-Heine University, Düsseldorf, Germany.
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany.
- German Center for Diabetes Research (DZD e.V.), Partner Düsseldorf, Munich-Neuherberg, Düsseldorf, Germany.
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Yang J, Wang M, Yang D, Yan H, Wang Z, Yan D, Guo N. Integrated lipids biomarker of the prediabetes and type 2 diabetes mellitus Chinese patients. Front Endocrinol (Lausanne) 2022; 13:1065665. [PMID: 36743922 PMCID: PMC9897314 DOI: 10.3389/fendo.2022.1065665] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 12/30/2022] [Indexed: 01/22/2023] Open
Abstract
INTRODUCTION Dyslipidemia is a hallmark of T2DM, and as such, analyses of lipid metabolic profiles in affected patients have the potential to permit the development of an integrated lipid metabolite-based biomarker model that can facilitate early patient diagnosis and treatment. METHODS Untargeted and targeted lipidomics approaches were used to analyze serum samples from newly diagnosed 93 Chinese participants in discovery cohort and 440 in validation cohort via UHPLC-MS and UHPLC-MS/MS first. The acid sphingomyelinase protein expression was analyzed by Western blot. RESULTS AND DISCUSSION Through these analyses, we developed a novel integrated biomarker signature composed of LPC 22:6, PC(16:0/20:4), PE(22:6/16:0), Cer(d18:1/24:0)/SM(d18:1/19:0), Cer(d18:1/24:0)/SM(d18:0/16:0), TG(18:1/18:2/18:2), TG(16:0/16:0/20:3), and TG(18:0/16:0/18:2). The area under the curve (AUC) values for this integrated biomarker signature for prediabetes and T2DM patients were 0.841 (cutoff: 0.565) and 0.894 (cutoff: 0.633), respectively. Furthermore, theresults of western blot analysis of frozen adipose tissue from 3 week (prediabetes) and 12 week (T2DM) Goto-Kakizaki (GK) rats also confirmed that acid sphingomyelinase is responsible for significant disruptions in ceramide and sphingomyelin homeostasis. Network analyses of the biomarkers associated with this biosignature suggested that the most profoundly affected lipid metabolism pathways in the context of diabetes include de novo ceramide synthesis, sphingomyelin metabolism, and additional pathways associated with phosphatidylcholine synthesis. Together, these results offer new biological insights regarding the role of serum lipids in the context of insidious T2DM development, and may offer new avenues for future diagnostic and/or therapeutic research.
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Affiliation(s)
- Jiaying Yang
- Experimental Research Center, China Academy of Chinese Medical Sciences, Beijing, China
- College of Pharmacy, Heilongjiang University of Traditional Chinese Medicine, Heilongjiang, China
| | - Mei Wang
- Experimental Research Center, China Academy of Chinese Medical Sciences, Beijing, China
| | - Dawei Yang
- Zhong Yuan Academy of Biological Medicine, Liaocheng People’s Hospital, Liaocheng, Shandong, China
| | - Han Yan
- Experimental Research Center, China Academy of Chinese Medical Sciences, Beijing, China
| | - Zhigang Wang
- College of Pharmacy, Heilongjiang University of Traditional Chinese Medicine, Heilongjiang, China
- *Correspondence: Zhigang Wang, ; Dan Yan, ; Na Guo,
| | - Dan Yan
- Beijing Institute of Clinical Pharmacy, Beijing Friendship Hospital, Capital Medical University, Beijing, China
- *Correspondence: Zhigang Wang, ; Dan Yan, ; Na Guo,
| | - Na Guo
- Experimental Research Center, China Academy of Chinese Medical Sciences, Beijing, China
- *Correspondence: Zhigang Wang, ; Dan Yan, ; Na Guo,
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Sottili M, Filardi T, Cantini G, Cosmi L, Morano S, Luconi M, Lenzi A, Crescioli C. Human cell-based anti-inflammatory effects of rosiglitazone. J Endocrinol Invest 2022; 45:105-114. [PMID: 34170488 DOI: 10.1007/s40618-021-01621-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Accepted: 06/17/2021] [Indexed: 12/20/2022]
Abstract
PURPOSE The C-X-C motif chemokine ligand 10 (CXCL10) participates in diabetes and diabetic cardiomyopathy development from the early stages. Rosiglitazone (RGZ) exhibits anti-inflammatory properties and can target cardiomyocytes secreting CXCL10, under interferon (IFN)γ and tumor necrosis factor (TNF)α challenge. Cardiomyocyte remodeling, CD4 + T cells and dendritic cells (DCs) significantly contribute to the inflammatory milieu underlying and promoting disease development. We aimed to study the effect of RGZ onto inflammation-induced secretion of CXCL10, IFNγ, TNFα, interleukin (IL)-6 and IL-8 by human CD4 + T and DCs, and onto IFNγ/TNFα-dependent signaling in human cardiomyocytes associated with chemokine release. METHODS Cells maintained within an inflammatory-like microenvironment were exposed to RGZ at near therapy dose (5 µM). ELISA quantified cytokine secretion; qPCR measured mRNA expression; Western blot analyzed protein expression and activation; immunofluorescent analysis detected intracellular IFNγ/TNFα-dependent trafficking. RESULTS In human CD4 + T cells and DCs, RGZ inhibited CXCL10 release likely with a transcriptional mechanism, and reduced TNFα only in CD4 + T cells. In human cardiomyocytes, RGZ impaired IFNγ/TNFα signal transduction, blocking the phosphorylation/nuclear translocation of signal transducer and activator of transcription 1 (Stat1) and nuclear factor-kB (NF-kB), in association with a significant decrease in CXCL10 expression, IL-6 and IL-8 release. CONCLUSION As the combination of Th1 biomarkers like CXCL10, IL-8, IL-6 with classical cardiovascular risk factors seems to improve the accuracy in predicting T2D and coronary events, future studies might be desirable to further investigate the anti-Th1 effect of RGZ.
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Affiliation(s)
- M Sottili
- Department of Experimental and Clinical Biomedical Sciences "Mario Serio", University of Florence, Viale Pieraccini 6, 50139, Florence, Italy
| | - T Filardi
- Department of Experimental Medicine, "Sapienza" University of Rome, Viale Regina Elena 324, 00161, Rome, Italy
| | - G Cantini
- Department of Experimental and Clinical Biomedical Sciences "Mario Serio", University of Florence, Viale Pieraccini 6, 50139, Florence, Italy
- DENOTHE Center of Excellence for Research, Transfer and High Education, University of Florence, 50139, Florence, Italy
| | - L Cosmi
- Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
| | - S Morano
- Department of Experimental Medicine, "Sapienza" University of Rome, Viale Regina Elena 324, 00161, Rome, Italy
| | - M Luconi
- Department of Experimental and Clinical Biomedical Sciences "Mario Serio", University of Florence, Viale Pieraccini 6, 50139, Florence, Italy
- DENOTHE Center of Excellence for Research, Transfer and High Education, University of Florence, 50139, Florence, Italy
- Istituto Nazionale Biostrutture E Biosistemi (INBB), viale delle Medaglie d'Oro 305, 00136, Rome, Italy
| | - A Lenzi
- Department of Experimental Medicine, "Sapienza" University of Rome, Viale Regina Elena 324, 00161, Rome, Italy
| | - C Crescioli
- Department of Movement, Human and Health Sciences, Section of Health Sciences, University of Rome "Foro Italico", Piazza L. de Bosis 6, 00135, Rome, Italy.
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Bauer A, Zierer A, Gieger C, Büyüközkan M, Müller-Nurasyid M, Grallert H, Meisinger C, Strauch K, Prokisch H, Roden M, Peters A, Krumsiek J, Herder C, Koenig W, Thorand B, Huth C. Comparison of genetic risk prediction models to improve prediction of coronary heart disease in two large cohorts of the MONICA/KORA study. Genet Epidemiol 2021; 45:633-650. [PMID: 34082474 DOI: 10.1002/gepi.22389] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 04/20/2021] [Accepted: 05/04/2021] [Indexed: 12/19/2022]
Abstract
It is still unclear how genetic information, provided as single-nucleotide polymorphisms (SNPs), can be most effectively integrated into risk prediction models for coronary heart disease (CHD) to add significant predictive value beyond clinical risk models. For the present study, a population-based case-cohort was used as a trainingset (451 incident cases, 1488 noncases) and an independent cohort as testset (160 incident cases, 2749 noncases). The following strategies to quantify genetic information were compared: A weighted genetic risk score including Metabochip SNPs associated with CHD in the literature (GRSMetabo ); selection of the most predictive SNPs among these literature-confirmed variants using priority-Lasso (PLMetabo ); validation of two comprehensive polygenic risk scores: GRSGola based on Metabochip data, and GRSKhera (available in the testset only) based on cross-validated genome-wide genotyping data. We used Cox regression to assess associations with incident CHD. C-index, category-free net reclassification index (cfNRI) and relative integrated discrimination improvement (IDIrel ) were used to quantify the predictive performance of genetic information beyond Framingham risk score variables. In contrast to GRSMetabo and PLMetabo , GRSGola significantly improved the prediction (delta C-index [95% confidence interval]: 0.0087 [0.0044, 0.0130]; IDIrel : 0.0509 [0.0131, 0.0894]; cfNRI improved only in cases: 0.1761 [0.0253, 0.3219]). GRSKhera yielded slightly worse prediction results than GRSGola .
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Affiliation(s)
- Alina Bauer
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Astrid Zierer
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Christian Gieger
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,German Center for Diabetes Research (DZD), Partner München-Neuherberg, München-Neuherberg, Germany.,Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Mustafa Büyüközkan
- Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Department of Physiology and Biophysics, Weill Cornell Medicine, New York, USA
| | - Martina Müller-Nurasyid
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU, Munich, Germany.,Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany.,Department of Internal Medicine I (Cardiology), Hospital of the Ludwig-Maximilians-University (LMU) Munich, Munich, Germany
| | - Harald Grallert
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,German Center for Diabetes Research (DZD), Partner München-Neuherberg, München-Neuherberg, Germany.,Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Christa Meisinger
- German Center for Diabetes Research (DZD), Partner München-Neuherberg, München-Neuherberg, Germany.,Chair of Epidemiology, LMU Munich, UNIKA-T Augsburg, Augsburg, Germany.,Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU, Munich, Germany.,Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany
| | - Holger Prokisch
- Institute of Human Genetics, School of Medicine, Technische Universität München, München, Germany.,Institute of Neurogenomics, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
| | - Michael Roden
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany.,Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,German Center for Diabetes Research (DZD), Partner Düsseldorf, München-Neuherberg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,German Center for Diabetes Research (DZD), Partner München-Neuherberg, München-Neuherberg, Germany.,Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
| | - Jan Krumsiek
- Institute of Computational Biology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Department of Physiology and Biophysics, Weill Cornell Medicine, New York, USA
| | - Christian Herder
- Department of Endocrinology and Diabetology, Medical Faculty and University Hospital Düsseldorf, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany.,Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,German Center for Diabetes Research (DZD), Partner Düsseldorf, München-Neuherberg, Germany
| | - Wolfgang Koenig
- Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany.,Deutsches Herzzentrum München, Technische Universität München, Munich, Germany.,German Centre for Cardiovascular Research (DZHK), partner site Munich Heart Alliance, Munich, Germany
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,German Center for Diabetes Research (DZD), Partner München-Neuherberg, München-Neuherberg, Germany
| | - Cornelia Huth
- Institute of Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.,German Center for Diabetes Research (DZD), Partner München-Neuherberg, München-Neuherberg, Germany
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7
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Thorand B, Zierer A, Büyüközkan M, Krumsiek J, Bauer A, Schederecker F, Sudduth-Klinger J, Meisinger C, Grallert H, Rathmann W, Roden M, Peters A, Koenig W, Herder C, Huth C. A Panel of 6 Biomarkers Significantly Improves the Prediction of Type 2 Diabetes in the MONICA/KORA Study Population. J Clin Endocrinol Metab 2021; 106:e1647-e1659. [PMID: 33382400 PMCID: PMC7993565 DOI: 10.1210/clinem/dgaa953] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Indexed: 12/29/2022]
Abstract
CONTEXT Improved strategies to identify persons at high risk of type 2 diabetes are important to target costly preventive efforts to those who will benefit most. OBJECTIVE This work aimed to assess whether novel biomarkers improve the prediction of type 2 diabetes beyond noninvasive standard clinical risk factors alone or in combination with glycated hemoglobin A1c (HbA1c). METHODS We used a population-based case-cohort study for discovery (689 incident cases and 1850 noncases) and an independent cohort study (262 incident cases, 2549 noncases) for validation. An L1-penalized (lasso) Cox model was used to select the most predictive set among 47 serum biomarkers from multiple etiological pathways. All variables available from the noninvasive German Diabetes Risk Score (GDRSadapted) were forced into the models. The C index and the category-free net reclassification index (cfNRI) were used to evaluate the predictive performance of the selected biomarkers beyond the GDRSadapted model (plus HbA1c). RESULTS Interleukin-1 receptor antagonist, insulin-like growth factor binding protein 2, soluble E-selectin, decorin, adiponectin, and high-density lipoprotein cholesterol were selected as the most relevant biomarkers. The simultaneous addition of these 6 biomarkers significantly improved the predictive performance both in the discovery (C index [95% CI], 0.053 [0.039-0.066]; cfNRI [95% CI], 67.4% [57.3%-79.5%]) and the validation study (0.034 [0.019-0.053]; 48.4% [35.6%-60.8%]). Significant improvements by these biomarkers were also seen on top of the GDRSadapted model plus HbA1c in both studies. CONCLUSION The addition of 6 biomarkers significantly improved the prediction of type 2 diabetes when added to a noninvasive clinical model or to a clinical model plus HbA1c.
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Affiliation(s)
- Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- Correspondence: Barbara Thorand, PhD, MPH, Helmholtz Zentrum München GmbH, Institute of Epidemiology, Ingolstädter Landstraße 1, D-85764 Neuherberg, Germany.
| | - Astrid Zierer
- Institute of Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health, Neuherberg, Germany
| | - Mustafa Büyüközkan
- Institute of Computational Biology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Jan Krumsiek
- Institute of Computational Biology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Alina Bauer
- Institute of Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health, Neuherberg, Germany
| | - Florian Schederecker
- Institute of Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health, Neuherberg, Germany
| | | | - Christa Meisinger
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- Chair of Epidemiology, Ludwig-Maximilians-Universität München, UNIKA-T Augsburg, Augsburg, Germany
- Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health, Neuherberg, Germany
| | - Harald Grallert
- Institute of Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Wolfgang Rathmann
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Michael Roden
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- German Centre for Cardiovascular Research (DZHK), partner site Munich Heart Alliance, Munich, Germany
| | - Wolfgang Koenig
- German Centre for Cardiovascular Research (DZHK), partner site Munich Heart Alliance, Munich, Germany
- Deutsches Herzzentrum München, Technische Universität München, Munich, Germany
- Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
| | - Christian Herder
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Cornelia Huth
- Institute of Epidemiology, Helmholtz Zentrum München—German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany
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8
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Pre-diagnostic biomarkers of type 2 diabetes identified in the UAE's obese national population using targeted metabolomics. Sci Rep 2020; 10:17616. [PMID: 33077739 PMCID: PMC7572402 DOI: 10.1038/s41598-020-73384-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Accepted: 09/16/2020] [Indexed: 12/14/2022] Open
Abstract
Currently, type 2 diabetes mellitus (T2DM) and obesity are major global public health issues, and their prevalence in the United Arab Emirates (UAE) are among the highest in the world. In 2019, The UAE diabetes national prevalence was 15.4%. In recent years there has been a considerable investigation of predictive biomarkers associated with these conditions. This study analysed fasting (8 h) blood samples from an obese, normoglycemic cohort and an obese, T2DM cohort of UAE nationals, employing clinical chemistry analysis, 1D 1H NMR and mass spectroscopy (FIA-MS/MS and LC-MS/MS) techniques. The novel findings reported for the first time in a UAE population revealed significant differences in a number of metabolites in the T2DM cohort. Metabolic fingerprints identified by NMR included BCAAs, trimethylamine N-oxide, β-hydroxybutyrate, trimethyl uric acid, and alanine. A targeted MS approach showed significant differences in lysophosphatidylcholines, phosphatidylcholines, acylcarnitine, amino acids and sphingomyelins; Lyso.PC.a.C18.0, PC.ae.C34.2, C3.DC..C4.OH, glutamine and SM.C16.1, being the most significant metabolites. Pearson's correlation studies showed associations between these metabolites and the clinical chemistry parameters across both cohorts. This report identified differences in metabolites in response to T2DM in agreement with many published population studies. This contributes to the global search for a bank of metabolite biomarkers that can predict the advent of T2DM and give insight to its pathogenic mechanisms.
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9
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Gudmundsdottir V, Zaghlool SB, Emilsson V, Aspelund T, Ilkov M, Gudmundsson EF, Jonsson SM, Zilhão NR, Lamb JR, Suhre K, Jennings LL, Gudnason V. Circulating Protein Signatures and Causal Candidates for Type 2 Diabetes. Diabetes 2020; 69:1843-1853. [PMID: 32385057 PMCID: PMC7372075 DOI: 10.2337/db19-1070] [Citation(s) in RCA: 56] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Accepted: 05/04/2020] [Indexed: 12/16/2022]
Abstract
The increasing prevalence of type 2 diabetes poses a major challenge to societies worldwide. Blood-based factors like serum proteins are in contact with every organ in the body to mediate global homeostasis and may thus directly regulate complex processes such as aging and the development of common chronic diseases. We applied a data-driven proteomics approach, measuring serum levels of 4,137 proteins in 5,438 elderly Icelanders, and identified 536 proteins associated with prevalent and/or incident type 2 diabetes. We validated a subset of the observed associations in an independent case-control study of type 2 diabetes. These protein associations provide novel biological insights into the molecular mechanisms that are dysregulated prior to and following the onset of type 2 diabetes and can be detected in serum. A bidirectional two-sample Mendelian randomization analysis indicated that serum changes of at least 23 proteins are downstream of the disease or its genetic liability, while 15 proteins were supported as having a causal role in type 2 diabetes.
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Affiliation(s)
- Valborg Gudmundsdottir
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Icelandic Heart Association, Holtasmari 1, Kopavogur, Iceland
| | - Shaza B Zaghlool
- Department of Biophysics and Physiology, Weill Cornell Medicine - Qatar, Doha, Qatar
| | - Valur Emilsson
- Icelandic Heart Association, Holtasmari 1, Kopavogur, Iceland
- Faculty of Pharmaceutical Sciences, University of Iceland, Reykjavik, Iceland
| | - Thor Aspelund
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Icelandic Heart Association, Holtasmari 1, Kopavogur, Iceland
| | - Marjan Ilkov
- Icelandic Heart Association, Holtasmari 1, Kopavogur, Iceland
| | | | | | - Nuno R Zilhão
- Icelandic Heart Association, Holtasmari 1, Kopavogur, Iceland
| | | | - Karsten Suhre
- Department of Biophysics and Physiology, Weill Cornell Medicine - Qatar, Doha, Qatar
| | | | - Vilmundur Gudnason
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Icelandic Heart Association, Holtasmari 1, Kopavogur, Iceland
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10
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Truncated Pneumolysin from Streptococcus pneumoniae as a TLR4-Antagonizing New Drug for Chronic Inflammatory Conditions. Cells 2020; 9:cells9051183. [PMID: 32397494 PMCID: PMC7290803 DOI: 10.3390/cells9051183] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 05/05/2020] [Accepted: 05/07/2020] [Indexed: 11/17/2022] Open
Abstract
Microbial proteins have recently been found to have more benefits in clinical disease treatment because of their better-developed strategy and properties than traditional medicine. In this study, we investigated the effectiveness of a truncated peptide synthesized from the C-terminal sequence of pneumolysin, i.e., C70PLY4, in Streptococcus pneumoniae, in treating chronic inflammatory conditions. It has been shown that C70PLY4 significantly blocks the transendothelial migration of neutrophils and attenuates the formation of atherosclerotic plaque and the secretion of soluble forms of the intercellular adhesion molecule-1 (ICAM-1), the vascular cell adhesion molecule 1 (VCAM-1), and E-selectin in high-fat-diet/streptozotocin-induced inflammatory rats. The mechanism and the docking simulation analysis further indicated that C70PLY4 might serve as a Toll-like receptor 4 (TLR4) antagonist by competing for the binding site of MD2, an indispensable protein for lipopolysaccharide (LPS)–TLR4 interaction signaling, on the TLR4 structure. Moreover, compared to the full-length PLY, C70PLY4 seems to have no cytotoxicity in human vascular endothelial cells. Our study elucidated a possible therapeutic efficacy of C70PLY4 in reducing chronic inflammatory conditions and clarified the underlying mechanism. Thus, our findings identify a new drug candidate that, by blocking TLR4 activity, could be an effective treatment for patients with chronic inflammatory diseases.
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11
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Simons N, Bijnen M, Wouters KAM, Rensen SS, Beulens JWJ, van Greevenbroek MMJ, ’t Hart LM, Greve JWM, van der Kallen CJH, Schaper NC, Schalkwijk CG, Stehouwer CDA, Brouwers MCGJ. The endothelial function biomarker soluble E-selectin is associated with nonalcoholic fatty liver disease. Liver Int 2020; 40:1079-1088. [PMID: 31960587 PMCID: PMC7317803 DOI: 10.1111/liv.14384] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2019] [Revised: 01/10/2020] [Accepted: 01/12/2020] [Indexed: 12/12/2022]
Abstract
BACKGROUND & AIMS Plasma soluble E-selectin (sE-selectin) is a frequently used biomarker of systemic endothelial dysfunction. The present study explored the relationship between nonalcoholic fatty liver disease (NAFLD) and plasma sE-selectin levels. METHODS Expression of E-selectin in liver, visceral adipose tissue (VAT) and muscle was studied in relation to plasma sE-selectin in severely obese individuals (n = 74). The course of hepatic E-selectin expression in relation to hepatic steatosis and inflammation was examined in C57BL/6J LDLR-/- mice on a Western-type diet. The relationship between biomarkers of NAFLD, that is, plasma aminotransferase (ALT) and NAFLD susceptibility genes (rs738409 [PNPLA3] and rs1260326 [GCKR]), and plasma sE-selectin was studied in the combined CODAM (n = 571) and Hoorn (n = 694) studies. RESULTS E-selectin expression in liver, not VAT or muscle, was associated with plasma sE-selectin in severely obese individuals (β = 0.26; 95% CI: 0.05-0.47). NAFLD severity was associated with hepatic E-selectin expression (P = .02) and plasma sE-selectin (P = .003). LDLR-/- mice on a Western-type diet displayed increased hepatic E-selectin expression that followed the same course as hepatic inflammation, but not steatosis. In the CODAM study, plasma ALT was associated with plasma sE-selectin, independent of potential confounders (β = 0.25; 95% CI: 0.16-0.34). Both rs738409 and rs1260326 were associated with higher plasma sE-selectin in the combined CODAM and Hoorn studies (P = .01 and P = .004 respectively). CONCLUSIONS NAFLD and related markers are associated with higher expression of hepatic E-selectin and higher levels of plasma sE-selectin. Further studies are required to investigate the role of E-selectin in the pathogenesis of NAFLD and the applicability of sE-selectin as a plasma biomarker of NAFLD/NASH.
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Affiliation(s)
- Nynke Simons
- Department of Internal MedicineDivision of Endocrinology and Metabolic DiseasesMaastricht University Medical CenterMaastrichtThe Netherlands,Department of Internal MedicineDivision of General Internal MedicineLaboratory for Metabolism and Vascular MedicineMaastricht University Medical CenterMaastrichtThe Netherlands,CARIM School for Cardiovascular DiseasesMaastricht UniversityMaastrichtThe Netherlands
| | - Mitchell Bijnen
- Department of Internal MedicineDivision of General Internal MedicineLaboratory for Metabolism and Vascular MedicineMaastricht University Medical CenterMaastrichtThe Netherlands,CARIM School for Cardiovascular DiseasesMaastricht UniversityMaastrichtThe Netherlands
| | - Kristiaan A. M. Wouters
- Department of Internal MedicineDivision of General Internal MedicineLaboratory for Metabolism and Vascular MedicineMaastricht University Medical CenterMaastrichtThe Netherlands,CARIM School for Cardiovascular DiseasesMaastricht UniversityMaastrichtThe Netherlands
| | - Sander S. Rensen
- Department of General SurgeryMaastricht University Medical CenterMaastrichtThe Netherlands,NUTRIM School of Nutrition and Translational Research in MetabolismMaastricht UniversityMaastrichtThe Netherlands
| | - Joline W. J. Beulens
- Department of Epidemiology and BiostatisticsAmsterdam University Medical Center – location VUmcthe Amsterdam Public Health Research Institute AmsterdamAmsterdamThe Netherlands,Julius Center for Health Sciences and Primary CareUniversity Medical Center UtrechtUtrechtThe Netherlands
| | - Marleen M. J. van Greevenbroek
- Department of Internal MedicineDivision of General Internal MedicineLaboratory for Metabolism and Vascular MedicineMaastricht University Medical CenterMaastrichtThe Netherlands,CARIM School for Cardiovascular DiseasesMaastricht UniversityMaastrichtThe Netherlands
| | - Leen M. ’t Hart
- Department of Epidemiology and BiostatisticsAmsterdam University Medical Center – location VUmcthe Amsterdam Public Health Research Institute AmsterdamAmsterdamThe Netherlands,Department of Cell and Chemical BiologyLeiden University Medical CenterLeidenThe Netherlands,Department of Biomedical Data SciencesSection Molecular EpidemiologyLeiden University Medical CenterLeidenThe Netherlands
| | - Jan Willem M. Greve
- Department of General SurgeryMaastricht University Medical CenterMaastrichtThe Netherlands,NUTRIM School of Nutrition and Translational Research in MetabolismMaastricht UniversityMaastrichtThe Netherlands,Department of General SurgeryZuyderland Medical CenterHeerlenThe Netherlands
| | - Carla J. H. van der Kallen
- Department of Internal MedicineDivision of General Internal MedicineLaboratory for Metabolism and Vascular MedicineMaastricht University Medical CenterMaastrichtThe Netherlands,CARIM School for Cardiovascular DiseasesMaastricht UniversityMaastrichtThe Netherlands
| | - Nicolaas C. Schaper
- Department of Internal MedicineDivision of Endocrinology and Metabolic DiseasesMaastricht University Medical CenterMaastrichtThe Netherlands,CARIM School for Cardiovascular DiseasesMaastricht UniversityMaastrichtThe Netherlands,CAPHRI School for Public Health and Primary CareMaastricht UniversityMaastrichtThe Netherlands
| | - Casper G. Schalkwijk
- Department of Internal MedicineDivision of General Internal MedicineLaboratory for Metabolism and Vascular MedicineMaastricht University Medical CenterMaastrichtThe Netherlands,CARIM School for Cardiovascular DiseasesMaastricht UniversityMaastrichtThe Netherlands
| | - Coen D. A. Stehouwer
- Department of Internal MedicineDivision of General Internal MedicineLaboratory for Metabolism and Vascular MedicineMaastricht University Medical CenterMaastrichtThe Netherlands,CARIM School for Cardiovascular DiseasesMaastricht UniversityMaastrichtThe Netherlands,Department of Internal MedicineDivision of General Internal MedicineMaastricht University Medical CenterMaastrichtThe Netherlands
| | - Martijn C. G. J. Brouwers
- Department of Internal MedicineDivision of Endocrinology and Metabolic DiseasesMaastricht University Medical CenterMaastrichtThe Netherlands,Department of Internal MedicineDivision of General Internal MedicineLaboratory for Metabolism and Vascular MedicineMaastricht University Medical CenterMaastrichtThe Netherlands,CARIM School for Cardiovascular DiseasesMaastricht UniversityMaastrichtThe Netherlands
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12
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Wang Y, Koh WP, Sim X, Yuan JM, Pan A. Multiple Biomarkers Improved Prediction for the Risk of Type 2 Diabetes Mellitus in Singapore Chinese Men and Women. Diabetes Metab J 2020; 44:295-306. [PMID: 31769241 PMCID: PMC7188981 DOI: 10.4093/dmj.2019.0020] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2019] [Accepted: 03/19/2019] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Multiple biomarkers have performed well in predicting type 2 diabetes mellitus (T2DM) risk in Western populations. However, evidence is scarce among Asian populations. METHODS Plasma triglyceride-to-high density lipoprotein (TG-to-HDL) ratio, alanine transaminase (ALT), high-sensitivity C-reactive protein (hs-CRP), ferritin, adiponectin, fetuin-A, and retinol-binding protein 4 were measured in 485 T2DM cases and 485 age-and-sex matched controls nested within the prospective Singapore Chinese Health Study cohort. Participants were free of T2DM at blood collection (1999 to 2004), and T2DM cases were identified at the subsequent follow-up interviews (2006 to 2010). A weighted biomarker score was created based on the strengths of associations between these biomarkers and T2DM risks. The predictive utility of the biomarker score was assessed by the area under receiver operating characteristics curve (AUC). RESULTS The biomarker score that comprised of four biomarkers (TG-to-HDL ratio, ALT, ferritin, and adiponectin) was positively associated with T2DM risk (P trend <0.001). Compared to the lowest quartile of the score, the odds ratio was 12.0 (95% confidence interval [CI], 5.43 to 26.6) for those in the highest quartile. Adding the biomarker score to a base model that included smoking, history of hypertension, body mass index, and levels of random glucose and insulin improved AUC significantly from 0.81 (95% CI, 0.78 to 0.83) to 0.83 (95% CI, 0.81 to 0.86; P=0.002). When substituting the random glucose levels with glycosylated hemoglobin in the base model, adding the biomarker score improved AUC from 0.85 (95% CI, 0.83 to 0.88) to 0.86 (95% CI, 0.84 to 0.89; P=0.032). CONCLUSION A composite score of blood biomarkers improved T2DM risk prediction among Chinese.
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Affiliation(s)
- Yeli Wang
- Health Services and Systems Research, Duke-NUS Medical School, Singapore
| | - Woon-Puay Koh
- Health Services and Systems Research, Duke-NUS Medical School, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
| | - Jian-Min Yuan
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - An Pan
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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13
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Huth C, Bauer A, Zierer A, Sudduth-Klinger J, Meisinger C, Roden M, Peters A, Koenig W, Herder C, Thorand B. Biomarker-defined pathways for incident type 2 diabetes and coronary heart disease-a comparison in the MONICA/KORA study. Cardiovasc Diabetol 2020; 19:32. [PMID: 32164753 PMCID: PMC7066738 DOI: 10.1186/s12933-020-01003-w] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Accepted: 02/21/2020] [Indexed: 12/16/2022] Open
Abstract
Background Biomarkers may contribute to our understanding of the pathophysiology of various diseases. Type 2 diabetes (T2D) and coronary heart disease (CHD) share many clinical and lifestyle risk factors and several biomarkers are associated with both diseases. The current analysis aims to assess the relevance of biomarkers combined to pathway groups for the development of T2D and CHD in the same cohort. Methods Forty-seven serum biomarkers were measured in the MONICA/KORA case-cohort study using clinical chemistry assays and ultrasensitive molecular counting technology. The T2D (CHD) analyses included 689 (568) incident cases and 1850 (2004) non-cases from three population-based surveys. At baseline, the study participants were 35–74 years old. The median follow-up was 14 years. We computed Cox regression models for each biomarker, adjusted for age, sex, and survey. Additionally, we assigned the biomarkers to 19 etiological pathways based on information from literature. One age-, sex-, and survey-controlled average variable was built for each pathway. We used the R2PM coefficient of determination to assess the explained disease risk. Results The associations of many biomarkers, such as several cytokines or the iron marker soluble transferrin receptor (sTfR), were similar in strength for T2D and CHD, but we also observed important differences. Lipoprotein (a) (Lp(a)) and N-terminal pro B-type natriuretic peptide (NT-proBNP) even demonstrated opposite effect directions. All pathway variables together explained 49% of the T2D risk and 21% of the CHD risk. The insulin-like growth factor binding protein 2 (IGFBP-2, IGF/IGFBP system pathway) best explained the T2D risk (about 9% explained risk, independent of all other pathway variables). For CHD, the myocardial-injury- and lipid-related-pathways were most important and both explained about 4% of the CHD risk. Conclusions The biomarker-derived pathway variables explained a higher proportion of the T2D risk compared to CHD. The ranking of the pathways differed between the two diseases, with the IGF/IGFBP-system-pathway being most strongly associated with T2D and the myocardial-injury- and lipid-related-pathways with CHD. Our results help to better understand the pathophysiology of the two diseases, with the ultimate goal of pointing out targets for lifestyle intervention and drug development to ideally prevent both T2D and CHD development.
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Affiliation(s)
- Cornelia Huth
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany. .,German Center for Diabetes Research (DZD), München-Neuherberg, Germany.
| | - Alina Bauer
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
| | - Astrid Zierer
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany
| | | | - Christa Meisinger
- Chair of Epidemiology, Ludwig-Maximilians-Universität München, UNIKA-T Augsburg, Augsburg, Germany.,Independent Research Group Clinical Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health (GmbH), Neuherberg, Germany
| | - Michael Roden
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany.,Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg, Germany.,German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Wolfgang Koenig
- German Centre for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany.,Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany.,Deutsches Herzzentrum München, Technische Universität München, Munich, Germany
| | - Christian Herder
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany.,Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany.,Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Barbara Thorand
- Institute of Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health (GmbH), Ingolstädter Landstraße 1, 85764, Neuherberg, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg, Germany
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14
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Biomarkers of Vascular Injury and Type 2 Diabetes: A Prospective Study, Systematic Review and Meta-Analysis. J Clin Med 2019; 8:jcm8122075. [PMID: 31783601 PMCID: PMC6947572 DOI: 10.3390/jcm8122075] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2019] [Revised: 11/18/2019] [Accepted: 11/25/2019] [Indexed: 12/23/2022] Open
Abstract
Data on biomarkers of vascular injury and type 2 diabetes (T2D) risk from prospective studies are lacking. We evaluated seven biomarkers of vascular injury in relation to T2D. Additionally, a meta-analysis was performed. From the EPIC–Heidelberg cohort, 2224 participants were followed-up from baseline for 16 (median) years. E-Selectin, P-Selectin, intercellular adhesion molecule 3 (ICAM3), thrombomodulin, thrombopoietin, glycoprotein IIb/IIIa and fibrinogen levels were measured in baseline blood samples. The systematic review and meta-analysis included prospective studies identified through MEDLINE and Web of Science that investigated the association between mentioned biomarkers and T2D. The study population included 55% women, median age was 50 years, and 163 developed T2D. ICAM3 was associated with lower T2D risk (fully adjusted HRhighest vs. lowest tertile 0.62 (95% CI: 0.43, 0.91)), but no other studies on ICAM3 were identified. Overall, fifteen studies were included in the systematic review and meta-analysis (6,171 cases). E-Selectin was associated with higher T2D risk HRper SD: 1.34 (95% CI: 1.16, 1.54; I2 = 63%, n = 9 studies), while thrombomodulin was associated with lower risk HRper SD: 0.82 (95% CI: 0.71, 0.95; I2 = 0%, n = 2 studies). In the EPIC–Heidelberg, ICAM3 was associated with lower T2D risk. The meta-analysis showed a consistent positive association between E-Selectin and T2D. It was also suggestive of an inverse association between thrombomodulin and T2D, although further studies are needed to corroborate this finding.
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15
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Dummer TJB, Awadalla P, Boileau C, Craig C, Fortier I, Goel V, Hicks JMT, Jacquemont S, Knoppers BM, Le N, McDonald T, McLaughlin J, Mes-Masson AM, Nuyt AM, Palmer LJ, Parker L, Purdue M, Robson PJ, Spinelli JJ, Thompson D, Vena J, Zawati M. The Canadian Partnership for Tomorrow Project: a pan-Canadian platform for research on chronic disease prevention. CMAJ 2019; 190:E710-E717. [PMID: 29891475 DOI: 10.1503/cmaj.170292] [Citation(s) in RCA: 64] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/12/2018] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Understanding the complex interaction of risk factors that increase the likelihood of developing common diseases is challenging. The Canadian Partnership for Tomorrow Project (CPTP) is a prospective cohort study created as a population-health research platform for assessing the effect of genetics, behaviour, family health history and environment (among other factors) on chronic diseases. METHODS Volunteer participants were recruited from the general Canadian population for a confederation of 5 regional cohorts. Participants were enrolled in the study and core information obtained using 2 approaches: attendance at a study assessment centre for all study measures (questionnaire, venous blood sample and physical measurements) or completion of the core questionnaire (online or paper), with later collection of other study measures where possible. Physical measurements included height, weight, percentage body fat and blood pressure. Participants consented to passive follow-up through linkage with administrative health databases and active follow-up through recontact. All participant data across the 5 regional cohorts were harmonized. RESULTS A total of 307 017 participants aged 30-74 from 8 provinces were recruited. More than half provided a venous blood sample and/or other biological sample, and 33% completed physical measurements. A total of 709 harmonized variables were created; almost 25% are available for all participants and 60% for at least 220 000 participants. INTERPRETATION Primary recruitment for the CPTP is complete, and data and biosamples are available to Canadian and international researchers through a data-access process. The CPTP will support research into how modifiable risk factors, genetics and the environment interact to affect the development of cancer and other chronic diseases, ultimately contributing evidence to reduce the global burden of chronic disease.
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Affiliation(s)
- Trevor J B Dummer
- School of Population and Public Health (Dummer), University of British Columbia, Vancouver, BC; Ontario Institute for Cancer Research (Awadalla); CARTaGENE (Boileau), Montréal, Que.; Research Institute of the McGill University Health Centre (Craig, Fortier); Research and Innovation, University of Toronto (Goel); Ontario Agency for Health Protection and Promotion (Goel); Atlantic PATH, Dalhousie University (Hicks), Halifax, NS; Centre hospitalier universitaire Sainte-Justine (Jacquemont); Centre of Genomics and Policy, McGill University (Knoppers, Zawati), Montréal, Que.; BC Cancer Research Centre (Le, McDonald), Vancouver, BC; Public Health Ontario (McLaughlin), Toronto, Ont.; Institut du cancer de Montréal, Université de Montréal (Mes-Masson); Pediatrics, CHU Sainte-Justine Research Center (Nuyt), Montréal, Que.; School of Public Health, University of Adelaide (Palmer), Adelaide, Australia; Department of Medicine, Dalhousie University (Parker); Division of Cancer Epidemiology and Genetics, National Cancer Institute (Purdue), Bethesda, Md.; CancerControl Alberta, Alberta Health Services (Robson, Vena), Edmonton, Alta.; Population Oncology, BC Cancer (Spinelli), Vancouver, BC; Atlantic PATH, Dalhousie University (Thompson), Halifax, NS
| | - Philip Awadalla
- School of Population and Public Health (Dummer), University of British Columbia, Vancouver, BC; Ontario Institute for Cancer Research (Awadalla); CARTaGENE (Boileau), Montréal, Que.; Research Institute of the McGill University Health Centre (Craig, Fortier); Research and Innovation, University of Toronto (Goel); Ontario Agency for Health Protection and Promotion (Goel); Atlantic PATH, Dalhousie University (Hicks), Halifax, NS; Centre hospitalier universitaire Sainte-Justine (Jacquemont); Centre of Genomics and Policy, McGill University (Knoppers, Zawati), Montréal, Que.; BC Cancer Research Centre (Le, McDonald), Vancouver, BC; Public Health Ontario (McLaughlin), Toronto, Ont.; Institut du cancer de Montréal, Université de Montréal (Mes-Masson); Pediatrics, CHU Sainte-Justine Research Center (Nuyt), Montréal, Que.; School of Public Health, University of Adelaide (Palmer), Adelaide, Australia; Department of Medicine, Dalhousie University (Parker); Division of Cancer Epidemiology and Genetics, National Cancer Institute (Purdue), Bethesda, Md.; CancerControl Alberta, Alberta Health Services (Robson, Vena), Edmonton, Alta.; Population Oncology, BC Cancer (Spinelli), Vancouver, BC; Atlantic PATH, Dalhousie University (Thompson), Halifax, NS
| | - Catherine Boileau
- School of Population and Public Health (Dummer), University of British Columbia, Vancouver, BC; Ontario Institute for Cancer Research (Awadalla); CARTaGENE (Boileau), Montréal, Que.; Research Institute of the McGill University Health Centre (Craig, Fortier); Research and Innovation, University of Toronto (Goel); Ontario Agency for Health Protection and Promotion (Goel); Atlantic PATH, Dalhousie University (Hicks), Halifax, NS; Centre hospitalier universitaire Sainte-Justine (Jacquemont); Centre of Genomics and Policy, McGill University (Knoppers, Zawati), Montréal, Que.; BC Cancer Research Centre (Le, McDonald), Vancouver, BC; Public Health Ontario (McLaughlin), Toronto, Ont.; Institut du cancer de Montréal, Université de Montréal (Mes-Masson); Pediatrics, CHU Sainte-Justine Research Center (Nuyt), Montréal, Que.; School of Public Health, University of Adelaide (Palmer), Adelaide, Australia; Department of Medicine, Dalhousie University (Parker); Division of Cancer Epidemiology and Genetics, National Cancer Institute (Purdue), Bethesda, Md.; CancerControl Alberta, Alberta Health Services (Robson, Vena), Edmonton, Alta.; Population Oncology, BC Cancer (Spinelli), Vancouver, BC; Atlantic PATH, Dalhousie University (Thompson), Halifax, NS
| | - Camille Craig
- School of Population and Public Health (Dummer), University of British Columbia, Vancouver, BC; Ontario Institute for Cancer Research (Awadalla); CARTaGENE (Boileau), Montréal, Que.; Research Institute of the McGill University Health Centre (Craig, Fortier); Research and Innovation, University of Toronto (Goel); Ontario Agency for Health Protection and Promotion (Goel); Atlantic PATH, Dalhousie University (Hicks), Halifax, NS; Centre hospitalier universitaire Sainte-Justine (Jacquemont); Centre of Genomics and Policy, McGill University (Knoppers, Zawati), Montréal, Que.; BC Cancer Research Centre (Le, McDonald), Vancouver, BC; Public Health Ontario (McLaughlin), Toronto, Ont.; Institut du cancer de Montréal, Université de Montréal (Mes-Masson); Pediatrics, CHU Sainte-Justine Research Center (Nuyt), Montréal, Que.; School of Public Health, University of Adelaide (Palmer), Adelaide, Australia; Department of Medicine, Dalhousie University (Parker); Division of Cancer Epidemiology and Genetics, National Cancer Institute (Purdue), Bethesda, Md.; CancerControl Alberta, Alberta Health Services (Robson, Vena), Edmonton, Alta.; Population Oncology, BC Cancer (Spinelli), Vancouver, BC; Atlantic PATH, Dalhousie University (Thompson), Halifax, NS
| | - Isabel Fortier
- School of Population and Public Health (Dummer), University of British Columbia, Vancouver, BC; Ontario Institute for Cancer Research (Awadalla); CARTaGENE (Boileau), Montréal, Que.; Research Institute of the McGill University Health Centre (Craig, Fortier); Research and Innovation, University of Toronto (Goel); Ontario Agency for Health Protection and Promotion (Goel); Atlantic PATH, Dalhousie University (Hicks), Halifax, NS; Centre hospitalier universitaire Sainte-Justine (Jacquemont); Centre of Genomics and Policy, McGill University (Knoppers, Zawati), Montréal, Que.; BC Cancer Research Centre (Le, McDonald), Vancouver, BC; Public Health Ontario (McLaughlin), Toronto, Ont.; Institut du cancer de Montréal, Université de Montréal (Mes-Masson); Pediatrics, CHU Sainte-Justine Research Center (Nuyt), Montréal, Que.; School of Public Health, University of Adelaide (Palmer), Adelaide, Australia; Department of Medicine, Dalhousie University (Parker); Division of Cancer Epidemiology and Genetics, National Cancer Institute (Purdue), Bethesda, Md.; CancerControl Alberta, Alberta Health Services (Robson, Vena), Edmonton, Alta.; Population Oncology, BC Cancer (Spinelli), Vancouver, BC; Atlantic PATH, Dalhousie University (Thompson), Halifax, NS
| | - Vivek Goel
- School of Population and Public Health (Dummer), University of British Columbia, Vancouver, BC; Ontario Institute for Cancer Research (Awadalla); CARTaGENE (Boileau), Montréal, Que.; Research Institute of the McGill University Health Centre (Craig, Fortier); Research and Innovation, University of Toronto (Goel); Ontario Agency for Health Protection and Promotion (Goel); Atlantic PATH, Dalhousie University (Hicks), Halifax, NS; Centre hospitalier universitaire Sainte-Justine (Jacquemont); Centre of Genomics and Policy, McGill University (Knoppers, Zawati), Montréal, Que.; BC Cancer Research Centre (Le, McDonald), Vancouver, BC; Public Health Ontario (McLaughlin), Toronto, Ont.; Institut du cancer de Montréal, Université de Montréal (Mes-Masson); Pediatrics, CHU Sainte-Justine Research Center (Nuyt), Montréal, Que.; School of Public Health, University of Adelaide (Palmer), Adelaide, Australia; Department of Medicine, Dalhousie University (Parker); Division of Cancer Epidemiology and Genetics, National Cancer Institute (Purdue), Bethesda, Md.; CancerControl Alberta, Alberta Health Services (Robson, Vena), Edmonton, Alta.; Population Oncology, BC Cancer (Spinelli), Vancouver, BC; Atlantic PATH, Dalhousie University (Thompson), Halifax, NS
| | - Jason M T Hicks
- School of Population and Public Health (Dummer), University of British Columbia, Vancouver, BC; Ontario Institute for Cancer Research (Awadalla); CARTaGENE (Boileau), Montréal, Que.; Research Institute of the McGill University Health Centre (Craig, Fortier); Research and Innovation, University of Toronto (Goel); Ontario Agency for Health Protection and Promotion (Goel); Atlantic PATH, Dalhousie University (Hicks), Halifax, NS; Centre hospitalier universitaire Sainte-Justine (Jacquemont); Centre of Genomics and Policy, McGill University (Knoppers, Zawati), Montréal, Que.; BC Cancer Research Centre (Le, McDonald), Vancouver, BC; Public Health Ontario (McLaughlin), Toronto, Ont.; Institut du cancer de Montréal, Université de Montréal (Mes-Masson); Pediatrics, CHU Sainte-Justine Research Center (Nuyt), Montréal, Que.; School of Public Health, University of Adelaide (Palmer), Adelaide, Australia; Department of Medicine, Dalhousie University (Parker); Division of Cancer Epidemiology and Genetics, National Cancer Institute (Purdue), Bethesda, Md.; CancerControl Alberta, Alberta Health Services (Robson, Vena), Edmonton, Alta.; Population Oncology, BC Cancer (Spinelli), Vancouver, BC; Atlantic PATH, Dalhousie University (Thompson), Halifax, NS
| | - Sébastien Jacquemont
- School of Population and Public Health (Dummer), University of British Columbia, Vancouver, BC; Ontario Institute for Cancer Research (Awadalla); CARTaGENE (Boileau), Montréal, Que.; Research Institute of the McGill University Health Centre (Craig, Fortier); Research and Innovation, University of Toronto (Goel); Ontario Agency for Health Protection and Promotion (Goel); Atlantic PATH, Dalhousie University (Hicks), Halifax, NS; Centre hospitalier universitaire Sainte-Justine (Jacquemont); Centre of Genomics and Policy, McGill University (Knoppers, Zawati), Montréal, Que.; BC Cancer Research Centre (Le, McDonald), Vancouver, BC; Public Health Ontario (McLaughlin), Toronto, Ont.; Institut du cancer de Montréal, Université de Montréal (Mes-Masson); Pediatrics, CHU Sainte-Justine Research Center (Nuyt), Montréal, Que.; School of Public Health, University of Adelaide (Palmer), Adelaide, Australia; Department of Medicine, Dalhousie University (Parker); Division of Cancer Epidemiology and Genetics, National Cancer Institute (Purdue), Bethesda, Md.; CancerControl Alberta, Alberta Health Services (Robson, Vena), Edmonton, Alta.; Population Oncology, BC Cancer (Spinelli), Vancouver, BC; Atlantic PATH, Dalhousie University (Thompson), Halifax, NS
| | - Bartha Maria Knoppers
- School of Population and Public Health (Dummer), University of British Columbia, Vancouver, BC; Ontario Institute for Cancer Research (Awadalla); CARTaGENE (Boileau), Montréal, Que.; Research Institute of the McGill University Health Centre (Craig, Fortier); Research and Innovation, University of Toronto (Goel); Ontario Agency for Health Protection and Promotion (Goel); Atlantic PATH, Dalhousie University (Hicks), Halifax, NS; Centre hospitalier universitaire Sainte-Justine (Jacquemont); Centre of Genomics and Policy, McGill University (Knoppers, Zawati), Montréal, Que.; BC Cancer Research Centre (Le, McDonald), Vancouver, BC; Public Health Ontario (McLaughlin), Toronto, Ont.; Institut du cancer de Montréal, Université de Montréal (Mes-Masson); Pediatrics, CHU Sainte-Justine Research Center (Nuyt), Montréal, Que.; School of Public Health, University of Adelaide (Palmer), Adelaide, Australia; Department of Medicine, Dalhousie University (Parker); Division of Cancer Epidemiology and Genetics, National Cancer Institute (Purdue), Bethesda, Md.; CancerControl Alberta, Alberta Health Services (Robson, Vena), Edmonton, Alta.; Population Oncology, BC Cancer (Spinelli), Vancouver, BC; Atlantic PATH, Dalhousie University (Thompson), Halifax, NS
| | - Nhu Le
- School of Population and Public Health (Dummer), University of British Columbia, Vancouver, BC; Ontario Institute for Cancer Research (Awadalla); CARTaGENE (Boileau), Montréal, Que.; Research Institute of the McGill University Health Centre (Craig, Fortier); Research and Innovation, University of Toronto (Goel); Ontario Agency for Health Protection and Promotion (Goel); Atlantic PATH, Dalhousie University (Hicks), Halifax, NS; Centre hospitalier universitaire Sainte-Justine (Jacquemont); Centre of Genomics and Policy, McGill University (Knoppers, Zawati), Montréal, Que.; BC Cancer Research Centre (Le, McDonald), Vancouver, BC; Public Health Ontario (McLaughlin), Toronto, Ont.; Institut du cancer de Montréal, Université de Montréal (Mes-Masson); Pediatrics, CHU Sainte-Justine Research Center (Nuyt), Montréal, Que.; School of Public Health, University of Adelaide (Palmer), Adelaide, Australia; Department of Medicine, Dalhousie University (Parker); Division of Cancer Epidemiology and Genetics, National Cancer Institute (Purdue), Bethesda, Md.; CancerControl Alberta, Alberta Health Services (Robson, Vena), Edmonton, Alta.; Population Oncology, BC Cancer (Spinelli), Vancouver, BC; Atlantic PATH, Dalhousie University (Thompson), Halifax, NS
| | - Treena McDonald
- School of Population and Public Health (Dummer), University of British Columbia, Vancouver, BC; Ontario Institute for Cancer Research (Awadalla); CARTaGENE (Boileau), Montréal, Que.; Research Institute of the McGill University Health Centre (Craig, Fortier); Research and Innovation, University of Toronto (Goel); Ontario Agency for Health Protection and Promotion (Goel); Atlantic PATH, Dalhousie University (Hicks), Halifax, NS; Centre hospitalier universitaire Sainte-Justine (Jacquemont); Centre of Genomics and Policy, McGill University (Knoppers, Zawati), Montréal, Que.; BC Cancer Research Centre (Le, McDonald), Vancouver, BC; Public Health Ontario (McLaughlin), Toronto, Ont.; Institut du cancer de Montréal, Université de Montréal (Mes-Masson); Pediatrics, CHU Sainte-Justine Research Center (Nuyt), Montréal, Que.; School of Public Health, University of Adelaide (Palmer), Adelaide, Australia; Department of Medicine, Dalhousie University (Parker); Division of Cancer Epidemiology and Genetics, National Cancer Institute (Purdue), Bethesda, Md.; CancerControl Alberta, Alberta Health Services (Robson, Vena), Edmonton, Alta.; Population Oncology, BC Cancer (Spinelli), Vancouver, BC; Atlantic PATH, Dalhousie University (Thompson), Halifax, NS
| | - John McLaughlin
- School of Population and Public Health (Dummer), University of British Columbia, Vancouver, BC; Ontario Institute for Cancer Research (Awadalla); CARTaGENE (Boileau), Montréal, Que.; Research Institute of the McGill University Health Centre (Craig, Fortier); Research and Innovation, University of Toronto (Goel); Ontario Agency for Health Protection and Promotion (Goel); Atlantic PATH, Dalhousie University (Hicks), Halifax, NS; Centre hospitalier universitaire Sainte-Justine (Jacquemont); Centre of Genomics and Policy, McGill University (Knoppers, Zawati), Montréal, Que.; BC Cancer Research Centre (Le, McDonald), Vancouver, BC; Public Health Ontario (McLaughlin), Toronto, Ont.; Institut du cancer de Montréal, Université de Montréal (Mes-Masson); Pediatrics, CHU Sainte-Justine Research Center (Nuyt), Montréal, Que.; School of Public Health, University of Adelaide (Palmer), Adelaide, Australia; Department of Medicine, Dalhousie University (Parker); Division of Cancer Epidemiology and Genetics, National Cancer Institute (Purdue), Bethesda, Md.; CancerControl Alberta, Alberta Health Services (Robson, Vena), Edmonton, Alta.; Population Oncology, BC Cancer (Spinelli), Vancouver, BC; Atlantic PATH, Dalhousie University (Thompson), Halifax, NS
| | - Anne-Marie Mes-Masson
- School of Population and Public Health (Dummer), University of British Columbia, Vancouver, BC; Ontario Institute for Cancer Research (Awadalla); CARTaGENE (Boileau), Montréal, Que.; Research Institute of the McGill University Health Centre (Craig, Fortier); Research and Innovation, University of Toronto (Goel); Ontario Agency for Health Protection and Promotion (Goel); Atlantic PATH, Dalhousie University (Hicks), Halifax, NS; Centre hospitalier universitaire Sainte-Justine (Jacquemont); Centre of Genomics and Policy, McGill University (Knoppers, Zawati), Montréal, Que.; BC Cancer Research Centre (Le, McDonald), Vancouver, BC; Public Health Ontario (McLaughlin), Toronto, Ont.; Institut du cancer de Montréal, Université de Montréal (Mes-Masson); Pediatrics, CHU Sainte-Justine Research Center (Nuyt), Montréal, Que.; School of Public Health, University of Adelaide (Palmer), Adelaide, Australia; Department of Medicine, Dalhousie University (Parker); Division of Cancer Epidemiology and Genetics, National Cancer Institute (Purdue), Bethesda, Md.; CancerControl Alberta, Alberta Health Services (Robson, Vena), Edmonton, Alta.; Population Oncology, BC Cancer (Spinelli), Vancouver, BC; Atlantic PATH, Dalhousie University (Thompson), Halifax, NS
| | - Anne-Monique Nuyt
- School of Population and Public Health (Dummer), University of British Columbia, Vancouver, BC; Ontario Institute for Cancer Research (Awadalla); CARTaGENE (Boileau), Montréal, Que.; Research Institute of the McGill University Health Centre (Craig, Fortier); Research and Innovation, University of Toronto (Goel); Ontario Agency for Health Protection and Promotion (Goel); Atlantic PATH, Dalhousie University (Hicks), Halifax, NS; Centre hospitalier universitaire Sainte-Justine (Jacquemont); Centre of Genomics and Policy, McGill University (Knoppers, Zawati), Montréal, Que.; BC Cancer Research Centre (Le, McDonald), Vancouver, BC; Public Health Ontario (McLaughlin), Toronto, Ont.; Institut du cancer de Montréal, Université de Montréal (Mes-Masson); Pediatrics, CHU Sainte-Justine Research Center (Nuyt), Montréal, Que.; School of Public Health, University of Adelaide (Palmer), Adelaide, Australia; Department of Medicine, Dalhousie University (Parker); Division of Cancer Epidemiology and Genetics, National Cancer Institute (Purdue), Bethesda, Md.; CancerControl Alberta, Alberta Health Services (Robson, Vena), Edmonton, Alta.; Population Oncology, BC Cancer (Spinelli), Vancouver, BC; Atlantic PATH, Dalhousie University (Thompson), Halifax, NS
| | - Lyle J Palmer
- School of Population and Public Health (Dummer), University of British Columbia, Vancouver, BC; Ontario Institute for Cancer Research (Awadalla); CARTaGENE (Boileau), Montréal, Que.; Research Institute of the McGill University Health Centre (Craig, Fortier); Research and Innovation, University of Toronto (Goel); Ontario Agency for Health Protection and Promotion (Goel); Atlantic PATH, Dalhousie University (Hicks), Halifax, NS; Centre hospitalier universitaire Sainte-Justine (Jacquemont); Centre of Genomics and Policy, McGill University (Knoppers, Zawati), Montréal, Que.; BC Cancer Research Centre (Le, McDonald), Vancouver, BC; Public Health Ontario (McLaughlin), Toronto, Ont.; Institut du cancer de Montréal, Université de Montréal (Mes-Masson); Pediatrics, CHU Sainte-Justine Research Center (Nuyt), Montréal, Que.; School of Public Health, University of Adelaide (Palmer), Adelaide, Australia; Department of Medicine, Dalhousie University (Parker); Division of Cancer Epidemiology and Genetics, National Cancer Institute (Purdue), Bethesda, Md.; CancerControl Alberta, Alberta Health Services (Robson, Vena), Edmonton, Alta.; Population Oncology, BC Cancer (Spinelli), Vancouver, BC; Atlantic PATH, Dalhousie University (Thompson), Halifax, NS
| | - Louise Parker
- School of Population and Public Health (Dummer), University of British Columbia, Vancouver, BC; Ontario Institute for Cancer Research (Awadalla); CARTaGENE (Boileau), Montréal, Que.; Research Institute of the McGill University Health Centre (Craig, Fortier); Research and Innovation, University of Toronto (Goel); Ontario Agency for Health Protection and Promotion (Goel); Atlantic PATH, Dalhousie University (Hicks), Halifax, NS; Centre hospitalier universitaire Sainte-Justine (Jacquemont); Centre of Genomics and Policy, McGill University (Knoppers, Zawati), Montréal, Que.; BC Cancer Research Centre (Le, McDonald), Vancouver, BC; Public Health Ontario (McLaughlin), Toronto, Ont.; Institut du cancer de Montréal, Université de Montréal (Mes-Masson); Pediatrics, CHU Sainte-Justine Research Center (Nuyt), Montréal, Que.; School of Public Health, University of Adelaide (Palmer), Adelaide, Australia; Department of Medicine, Dalhousie University (Parker); Division of Cancer Epidemiology and Genetics, National Cancer Institute (Purdue), Bethesda, Md.; CancerControl Alberta, Alberta Health Services (Robson, Vena), Edmonton, Alta.; Population Oncology, BC Cancer (Spinelli), Vancouver, BC; Atlantic PATH, Dalhousie University (Thompson), Halifax, NS
| | - Mark Purdue
- School of Population and Public Health (Dummer), University of British Columbia, Vancouver, BC; Ontario Institute for Cancer Research (Awadalla); CARTaGENE (Boileau), Montréal, Que.; Research Institute of the McGill University Health Centre (Craig, Fortier); Research and Innovation, University of Toronto (Goel); Ontario Agency for Health Protection and Promotion (Goel); Atlantic PATH, Dalhousie University (Hicks), Halifax, NS; Centre hospitalier universitaire Sainte-Justine (Jacquemont); Centre of Genomics and Policy, McGill University (Knoppers, Zawati), Montréal, Que.; BC Cancer Research Centre (Le, McDonald), Vancouver, BC; Public Health Ontario (McLaughlin), Toronto, Ont.; Institut du cancer de Montréal, Université de Montréal (Mes-Masson); Pediatrics, CHU Sainte-Justine Research Center (Nuyt), Montréal, Que.; School of Public Health, University of Adelaide (Palmer), Adelaide, Australia; Department of Medicine, Dalhousie University (Parker); Division of Cancer Epidemiology and Genetics, National Cancer Institute (Purdue), Bethesda, Md.; CancerControl Alberta, Alberta Health Services (Robson, Vena), Edmonton, Alta.; Population Oncology, BC Cancer (Spinelli), Vancouver, BC; Atlantic PATH, Dalhousie University (Thompson), Halifax, NS
| | - Paula J Robson
- School of Population and Public Health (Dummer), University of British Columbia, Vancouver, BC; Ontario Institute for Cancer Research (Awadalla); CARTaGENE (Boileau), Montréal, Que.; Research Institute of the McGill University Health Centre (Craig, Fortier); Research and Innovation, University of Toronto (Goel); Ontario Agency for Health Protection and Promotion (Goel); Atlantic PATH, Dalhousie University (Hicks), Halifax, NS; Centre hospitalier universitaire Sainte-Justine (Jacquemont); Centre of Genomics and Policy, McGill University (Knoppers, Zawati), Montréal, Que.; BC Cancer Research Centre (Le, McDonald), Vancouver, BC; Public Health Ontario (McLaughlin), Toronto, Ont.; Institut du cancer de Montréal, Université de Montréal (Mes-Masson); Pediatrics, CHU Sainte-Justine Research Center (Nuyt), Montréal, Que.; School of Public Health, University of Adelaide (Palmer), Adelaide, Australia; Department of Medicine, Dalhousie University (Parker); Division of Cancer Epidemiology and Genetics, National Cancer Institute (Purdue), Bethesda, Md.; CancerControl Alberta, Alberta Health Services (Robson, Vena), Edmonton, Alta.; Population Oncology, BC Cancer (Spinelli), Vancouver, BC; Atlantic PATH, Dalhousie University (Thompson), Halifax, NS
| | - John J Spinelli
- School of Population and Public Health (Dummer), University of British Columbia, Vancouver, BC; Ontario Institute for Cancer Research (Awadalla); CARTaGENE (Boileau), Montréal, Que.; Research Institute of the McGill University Health Centre (Craig, Fortier); Research and Innovation, University of Toronto (Goel); Ontario Agency for Health Protection and Promotion (Goel); Atlantic PATH, Dalhousie University (Hicks), Halifax, NS; Centre hospitalier universitaire Sainte-Justine (Jacquemont); Centre of Genomics and Policy, McGill University (Knoppers, Zawati), Montréal, Que.; BC Cancer Research Centre (Le, McDonald), Vancouver, BC; Public Health Ontario (McLaughlin), Toronto, Ont.; Institut du cancer de Montréal, Université de Montréal (Mes-Masson); Pediatrics, CHU Sainte-Justine Research Center (Nuyt), Montréal, Que.; School of Public Health, University of Adelaide (Palmer), Adelaide, Australia; Department of Medicine, Dalhousie University (Parker); Division of Cancer Epidemiology and Genetics, National Cancer Institute (Purdue), Bethesda, Md.; CancerControl Alberta, Alberta Health Services (Robson, Vena), Edmonton, Alta.; Population Oncology, BC Cancer (Spinelli), Vancouver, BC; Atlantic PATH, Dalhousie University (Thompson), Halifax, NS
| | - David Thompson
- School of Population and Public Health (Dummer), University of British Columbia, Vancouver, BC; Ontario Institute for Cancer Research (Awadalla); CARTaGENE (Boileau), Montréal, Que.; Research Institute of the McGill University Health Centre (Craig, Fortier); Research and Innovation, University of Toronto (Goel); Ontario Agency for Health Protection and Promotion (Goel); Atlantic PATH, Dalhousie University (Hicks), Halifax, NS; Centre hospitalier universitaire Sainte-Justine (Jacquemont); Centre of Genomics and Policy, McGill University (Knoppers, Zawati), Montréal, Que.; BC Cancer Research Centre (Le, McDonald), Vancouver, BC; Public Health Ontario (McLaughlin), Toronto, Ont.; Institut du cancer de Montréal, Université de Montréal (Mes-Masson); Pediatrics, CHU Sainte-Justine Research Center (Nuyt), Montréal, Que.; School of Public Health, University of Adelaide (Palmer), Adelaide, Australia; Department of Medicine, Dalhousie University (Parker); Division of Cancer Epidemiology and Genetics, National Cancer Institute (Purdue), Bethesda, Md.; CancerControl Alberta, Alberta Health Services (Robson, Vena), Edmonton, Alta.; Population Oncology, BC Cancer (Spinelli), Vancouver, BC; Atlantic PATH, Dalhousie University (Thompson), Halifax, NS
| | - Jennifer Vena
- School of Population and Public Health (Dummer), University of British Columbia, Vancouver, BC; Ontario Institute for Cancer Research (Awadalla); CARTaGENE (Boileau), Montréal, Que.; Research Institute of the McGill University Health Centre (Craig, Fortier); Research and Innovation, University of Toronto (Goel); Ontario Agency for Health Protection and Promotion (Goel); Atlantic PATH, Dalhousie University (Hicks), Halifax, NS; Centre hospitalier universitaire Sainte-Justine (Jacquemont); Centre of Genomics and Policy, McGill University (Knoppers, Zawati), Montréal, Que.; BC Cancer Research Centre (Le, McDonald), Vancouver, BC; Public Health Ontario (McLaughlin), Toronto, Ont.; Institut du cancer de Montréal, Université de Montréal (Mes-Masson); Pediatrics, CHU Sainte-Justine Research Center (Nuyt), Montréal, Que.; School of Public Health, University of Adelaide (Palmer), Adelaide, Australia; Department of Medicine, Dalhousie University (Parker); Division of Cancer Epidemiology and Genetics, National Cancer Institute (Purdue), Bethesda, Md.; CancerControl Alberta, Alberta Health Services (Robson, Vena), Edmonton, Alta.; Population Oncology, BC Cancer (Spinelli), Vancouver, BC; Atlantic PATH, Dalhousie University (Thompson), Halifax, NS
| | - Ma'n Zawati
- School of Population and Public Health (Dummer), University of British Columbia, Vancouver, BC; Ontario Institute for Cancer Research (Awadalla); CARTaGENE (Boileau), Montréal, Que.; Research Institute of the McGill University Health Centre (Craig, Fortier); Research and Innovation, University of Toronto (Goel); Ontario Agency for Health Protection and Promotion (Goel); Atlantic PATH, Dalhousie University (Hicks), Halifax, NS; Centre hospitalier universitaire Sainte-Justine (Jacquemont); Centre of Genomics and Policy, McGill University (Knoppers, Zawati), Montréal, Que.; BC Cancer Research Centre (Le, McDonald), Vancouver, BC; Public Health Ontario (McLaughlin), Toronto, Ont.; Institut du cancer de Montréal, Université de Montréal (Mes-Masson); Pediatrics, CHU Sainte-Justine Research Center (Nuyt), Montréal, Que.; School of Public Health, University of Adelaide (Palmer), Adelaide, Australia; Department of Medicine, Dalhousie University (Parker); Division of Cancer Epidemiology and Genetics, National Cancer Institute (Purdue), Bethesda, Md.; CancerControl Alberta, Alberta Health Services (Robson, Vena), Edmonton, Alta.; Population Oncology, BC Cancer (Spinelli), Vancouver, BC; Atlantic PATH, Dalhousie University (Thompson), Halifax, NS
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Simon MC, Möller-Horigome A, Strassburger K, Nowotny B, Knebel B, Müssig K, Herder C, Szendroedi J, Roden MW. Correlates of Insulin-Stimulated Glucose Disposal in Recent-Onset Type 1 and Type 2 Diabetes. J Clin Endocrinol Metab 2019; 104:2295-2304. [PMID: 30689904 DOI: 10.1210/jc.2018-02057] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2018] [Accepted: 01/23/2019] [Indexed: 02/10/2023]
Abstract
CONTEXT AND OBJECTIVE Not only type 2 diabetes (T2D), but also type 1 diabetes (T1D), can be associated with insulin resistance, as assessed using insulin-stimulated whole-body glucose disposal (M-value). We hypothesized that different factors would affect the M-value at the onset of T1D and T2D. DESIGN AND PATIENTS We examined 132 patients with T1D or T2D matched for sex, age, and body mass index with a known diabetes duration of <12 months. Multivariable linear regression analyses were applied to test the associations between glycemic control, blood lipid levels, adiponectin, and proinflammatory immune mediators and the M-value, obtained from the hyperinsulinemic-euglycemic clamp. RESULTS Despite comparable age, body mass index, and near-normoglycemic control, the mean M-value was lower in those with T2D than in those with T1D. Patients with T1D had a lower waist/hip ratio and serum triglycerides but higher serum adiponectin than patients with T2D. However, the circulating proinflammatory markers were not different. Even with adjustments for glucose-lowering treatments, the fasting blood glucose correlated negatively with the M-value in both groups. However, gamma-glutamyl transferase-independently of any treatments-correlated negatively only in T2D. In contrast, serum adiponectin correlated positively with the M-values. CONCLUSIONS Fasting glycemia correlated with insulin-stimulated glucose disposal in both diabetes types. However, altered liver and adipose tissue function were associated with insulin-stimulated glucose disposal only in T2D, underpinning the specific differences between these diabetes types.
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Affiliation(s)
- Marie-Christine Simon
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
- German Center for Diabetes Research, München-Neuherberg, Germany
| | - Akiko Möller-Horigome
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
- German Center for Diabetes Research, München-Neuherberg, Germany
| | - Klaus Strassburger
- German Center for Diabetes Research, München-Neuherberg, Germany
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
| | - Bettina Nowotny
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
- German Center for Diabetes Research, München-Neuherberg, Germany
| | - Birgit Knebel
- German Center for Diabetes Research, München-Neuherberg, Germany
- Institute for Clinical Biochemistry and Pathobiochemistry, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
| | - Karsten Müssig
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
- German Center for Diabetes Research, München-Neuherberg, Germany
- Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Christian Herder
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
- German Center for Diabetes Research, München-Neuherberg, Germany
| | - Julia Szendroedi
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
- German Center for Diabetes Research, München-Neuherberg, Germany
- Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Michael W Roden
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany
- German Center for Diabetes Research, München-Neuherberg, Germany
- Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
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17
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Tsantoulas C, Laínez S, Wong S, Mehta I, Vilar B, McNaughton PA. Hyperpolarization-activated cyclic nucleotide-gated 2 (HCN2) ion channels drive pain in mouse models of diabetic neuropathy. Sci Transl Med 2018; 9:eaam6072. [PMID: 28954930 DOI: 10.1126/scitranslmed.aam6072] [Citation(s) in RCA: 79] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2016] [Revised: 02/22/2017] [Accepted: 09/06/2017] [Indexed: 01/12/2023]
Abstract
Diabetic patients frequently suffer from continuous pain that is poorly treated by currently available analgesics. We used mouse models of type 1 and type 2 diabetes to investigate a possible role for the hyperpolarization-activated cyclic nucleotide-gated 2 (HCN2) ion channels as drivers of diabetic pain. Blocking or genetically deleting HCN2 channels in small nociceptive neurons suppressed diabetes-associated mechanical allodynia and prevented neuronal activation of second-order neurons in the spinal cord in mice. In addition, we found that intracellular cyclic adenosine monophosphate (cAMP), a positive HCN2 modulator, is increased in somatosensory neurons in an animal model of painful diabetes. We propose that the increased intracellular cAMP drives diabetes-associated pain by facilitating HCN2 activation and consequently promoting repetitive firing in primary nociceptive nerve fibers. Our results suggest that HCN2 may be an analgesic target in the treatment of painful diabetic neuropathy.
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Affiliation(s)
- Christoforos Tsantoulas
- Wolfson Centre for Age-Related Diseases, King's College London, Guy's Campus, London Bridge, London SE1 1UL, UK
| | - Sergio Laínez
- Wolfson Centre for Age-Related Diseases, King's College London, Guy's Campus, London Bridge, London SE1 1UL, UK
| | - Sara Wong
- Wolfson Centre for Age-Related Diseases, King's College London, Guy's Campus, London Bridge, London SE1 1UL, UK
| | - Ishita Mehta
- Wolfson Centre for Age-Related Diseases, King's College London, Guy's Campus, London Bridge, London SE1 1UL, UK
| | - Bruno Vilar
- Wolfson Centre for Age-Related Diseases, King's College London, Guy's Campus, London Bridge, London SE1 1UL, UK
| | - Peter A McNaughton
- Wolfson Centre for Age-Related Diseases, King's College London, Guy's Campus, London Bridge, London SE1 1UL, UK.
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18
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Subirana I, Fitó M, Diaz O, Vila J, Francés A, Delpon E, Sanchis J, Elosua R, Muñoz-Aguayo D, Dégano IR, Marrugat J. Prediction of coronary disease incidence by biomarkers of inflammation, oxidation, and metabolism. Sci Rep 2018; 8:3191. [PMID: 29453342 PMCID: PMC5816603 DOI: 10.1038/s41598-018-21482-y] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2017] [Accepted: 01/31/2018] [Indexed: 01/16/2023] Open
Abstract
The effect of circulating biomarkers in predicting coronary artery disease (CAD) is not fully elucidated. This study aimed to determine the relationship with CAD and the predictive capacity of nine biomarkers of inflammation (TNF-α, IL-10, IL-6, MCP-1, CRP), oxidation (GHS-Px), and metabolism (adiponectin, leptin, and insulin). This was a case-cohort study, within the REGICOR population-cohorts (North-Eastern Spain), of 105 CAD cases and 638 individuals randomly selected from a cohort of 5,404 participants aged 35–74 years (mean follow-up = 6.1 years). Biomarkers’ hazard ratio (HR)/standard deviation was estimated with Cox models adjusted for age, sex, and classical risk factors. Discrimination improvement and reclassification were analyzed with the c-index and the Net reclassification index (NRI). GHS-Px (adjusted HRs = 0.77; 95%CI:0.60–0.99), insulin (1.46; 1.08–1.98), leptin (1.40; 1.03–1.90), IL-6 (1.34; 1.03–1.74), and TNF-α (1.80; 1.26–2.57) were significantly associated with CAD incidence. In the model adjusted for all biomarkers, TNF-α (1.87;1.31–2.66) and insulin (1.59;1.16–2.19) were independently associated with CAD. This final model, compared to a model without biomarkers, showed a c-index difference of 1.3% (−0.7, 3.2) and a continuous NRI of 33.7% (2.6, 61.9). TNF-α and insulin are independently associated with CAD incidence and they improve reclassification when added to a model including classical risk factors.
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Affiliation(s)
- Isaac Subirana
- CIBER of Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.,Cardiovascular Epidemiology and Genetics Research Group, Program of Epidemiology and Public Health, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Montserrat Fitó
- Cardiovascular Risk and Nutrition Research Group, Program of Epidemiology and Public Health, IMIM, Barcelona, Spain.,CIBER of Physiopathology of Obesity and Nutrition (CIBEROBN), ISCIII, Madrid, Spain
| | - Oscar Diaz
- Cardiovascular Epidemiology and Genetics Research Group, Program of Epidemiology and Public Health, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Joan Vila
- CIBER of Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain.,Cardiovascular Epidemiology and Genetics Research Group, Program of Epidemiology and Public Health, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | | | | | - Juan Sanchis
- Servei de Cardiologia, INCLIVA, Departament de Medicina, Hospital Clínico Universitario de Valencia, Universitat de Valencia, Valencia, Spain
| | - Roberto Elosua
- Cardiovascular Epidemiology and Genetics Research Group, Program of Epidemiology and Public Health, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain.,CIBER of Cardiovascular Diseases (CIBERCV), ISCIII, Madrid, Spain
| | - Daniel Muñoz-Aguayo
- Cardiovascular Risk and Nutrition Research Group, Program of Epidemiology and Public Health, IMIM, Barcelona, Spain.,CIBER of Physiopathology of Obesity and Nutrition (CIBEROBN), ISCIII, Madrid, Spain
| | - Irene R Dégano
- CIBER of Cardiovascular Diseases (CIBERCV), ISCIII, Madrid, Spain. .,REGICOR Group, Program of Epidemiology and Public Health, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain.
| | - Jaume Marrugat
- CIBER of Cardiovascular Diseases (CIBERCV), ISCIII, Madrid, Spain. .,REGICOR Group, Program of Epidemiology and Public Health, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain.
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19
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Proinflammatory cytokine MIF plays a role in the pathogenesis of type-2 diabetes mellitus, but does not affect hepatic mitochondrial function. Cytokine 2017; 99:214-224. [PMID: 28780379 DOI: 10.1016/j.cyto.2017.07.012] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2017] [Revised: 07/08/2017] [Accepted: 07/13/2017] [Indexed: 02/02/2023]
Abstract
BACKGROUND Macrophage migration inhibitory factor (MIF) is a proinflammatory cytokine that plays an important role in the pathogenesis of type 2 diabetes mellitus (T2DM). Although the effect of high glucose on liver function has been described, the role of MIF in hepatic mitochondrial function during T2DM has not been studied. OBJECTIVE We examine the influence of MIF to hepatic mitochondrial function in T2DM mouse model. METHODS WT and Mif-/- BALB/c mice were treated with a single dose of streptozotocin (STZ). After an 8-week follow-up, serum glucose, proinflammatory cytokines, C-reactive protein (CRP), alanine aminotransferase (ALT) and aspartate aminotransferase (AST) enzyme quantification, and liver histological analyses were performed. Liver mitochondria were extracted, and mitochondrial function was evaluated by oximetry, swelling and peroxide production. RESULTS Following treatment with STZ, WT mice (WT/STZ) developed significant hyperglycemia and high serum levels of MIF, tumor necrosis factor (TNF)-α, interleukin-β (IL-β), and CRP. Liver damage enzymes ALT and AST were found at high levels. In contrast, Mif-/-STZ lacked serum MIF levels and showed smaller increases in blood glucose, less TNF-α, IL-1β, CPR, ALT and AST, and failure to develop clinical signs of disease compared to the WT/STZ group. Mitochondria extracted from the Mif-/-STZ liver showed similar respiratory control (RC) to WT/STZ or healthy mice with glutamate/malate or succinate as substrates. The four respiratory chain complexes also had comparable activities. WT/STZ-isolated mitochondria showed low swelling with calcium compared to mitochondria from Mif-/-STZ or healthy mice. Peroxide production was comparable in all groups. CONCLUSION These results show although high systemic levels of MIF contribute to the development of T2DM pathology, the liver mitochondria remain unaltered. Importantly, the absence of MIF reduced the pathology of T2DM, also without altering liver mitochondrial function. These support MIF as a therapeutic target for the treatment of this disease in humans.
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20
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Raciti GA, Spinelli R, Desiderio A, Longo M, Parrillo L, Nigro C, D'Esposito V, Mirra P, Fiory F, Pilone V, Forestieri P, Formisano P, Pastan I, Miele C, Beguinot F. Specific CpG hyper-methylation leads to Ankrd26 gene down-regulation in white adipose tissue of a mouse model of diet-induced obesity. Sci Rep 2017; 7:43526. [PMID: 28266632 PMCID: PMC5339897 DOI: 10.1038/srep43526] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2016] [Accepted: 01/27/2017] [Indexed: 12/16/2022] Open
Abstract
Epigenetic modifications alter transcriptional activity and contribute to the effects of environment on the individual risk of obesity and Type 2 Diabetes (T2D). Here, we have estimated the in vivo effect of a fat-enriched diet (HFD) on the expression and the epigenetic regulation of the Ankyrin repeat domain 26 (Ankrd26) gene, which is associated with the onset of these disorders. In visceral adipose tissue (VAT), HFD exposure determined a specific hyper-methylation of Ankrd26 promoter at the −436 and −431 bp CpG sites (CpGs) and impaired its expression. Methylation of these 2 CpGs impaired binding of the histone acetyltransferase/transcriptional coactivator p300 to this same region, causing hypo-acetylation of histone H4 at the Ankrd26 promoter and loss of binding of RNA Pol II at the Ankrd26 Transcription Start Site (TSS). In addition, HFD increased binding of DNA methyl-transferases (DNMTs) 3a and 3b and methyl-CpG-binding domain protein 2 (MBD2) to the Ankrd26 promoter. More importantly, Ankrd26 down-regulation enhanced secretion of pro-inflammatory mediators by 3T3-L1 adipocytes as well as in human sera. Thus, in mice, the exposure to HFD induces epigenetic silencing of the Ankrd26 gene, which contributes to the adipose tissue inflammatory secretion profile induced by high-fat regimens.
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Affiliation(s)
- Gregory A Raciti
- URT of the Institute of Experimental Endocrinology and Oncology "G. Salvatore", National Council of Research, Naples, 80131, Italy.,Department of Translational Medical Sciences, University of Naples "Federico II", Naples, 80131, Italy
| | - Rosa Spinelli
- URT of the Institute of Experimental Endocrinology and Oncology "G. Salvatore", National Council of Research, Naples, 80131, Italy.,Department of Translational Medical Sciences, University of Naples "Federico II", Naples, 80131, Italy
| | - Antonella Desiderio
- URT of the Institute of Experimental Endocrinology and Oncology "G. Salvatore", National Council of Research, Naples, 80131, Italy.,Department of Translational Medical Sciences, University of Naples "Federico II", Naples, 80131, Italy
| | - Michele Longo
- URT of the Institute of Experimental Endocrinology and Oncology "G. Salvatore", National Council of Research, Naples, 80131, Italy.,Department of Translational Medical Sciences, University of Naples "Federico II", Naples, 80131, Italy
| | - Luca Parrillo
- URT of the Institute of Experimental Endocrinology and Oncology "G. Salvatore", National Council of Research, Naples, 80131, Italy.,Department of Translational Medical Sciences, University of Naples "Federico II", Naples, 80131, Italy
| | - Cecilia Nigro
- URT of the Institute of Experimental Endocrinology and Oncology "G. Salvatore", National Council of Research, Naples, 80131, Italy.,Department of Translational Medical Sciences, University of Naples "Federico II", Naples, 80131, Italy
| | - Vittoria D'Esposito
- URT of the Institute of Experimental Endocrinology and Oncology "G. Salvatore", National Council of Research, Naples, 80131, Italy.,Department of Translational Medical Sciences, University of Naples "Federico II", Naples, 80131, Italy
| | - Paola Mirra
- URT of the Institute of Experimental Endocrinology and Oncology "G. Salvatore", National Council of Research, Naples, 80131, Italy.,Department of Translational Medical Sciences, University of Naples "Federico II", Naples, 80131, Italy
| | - Francesca Fiory
- URT of the Institute of Experimental Endocrinology and Oncology "G. Salvatore", National Council of Research, Naples, 80131, Italy.,Department of Translational Medical Sciences, University of Naples "Federico II", Naples, 80131, Italy
| | - Vincenzo Pilone
- Bariatric and Metabolic Surgery Unit, University of Salerno, Salerno, 84084, Italy
| | - Pietro Forestieri
- Department of Clinical Medicine and Surgery, University of Naples "Federico II", Naples, 80131, Italy
| | - Pietro Formisano
- URT of the Institute of Experimental Endocrinology and Oncology "G. Salvatore", National Council of Research, Naples, 80131, Italy.,Department of Translational Medical Sciences, University of Naples "Federico II", Naples, 80131, Italy
| | - Ira Pastan
- Laboratory of Molecular Biology (LMB), National Cancer Institute (NCI), National Institute of Health (NIH), Bethesda, MD 20892, USA
| | - Claudia Miele
- URT of the Institute of Experimental Endocrinology and Oncology "G. Salvatore", National Council of Research, Naples, 80131, Italy.,Department of Translational Medical Sciences, University of Naples "Federico II", Naples, 80131, Italy
| | - Francesco Beguinot
- URT of the Institute of Experimental Endocrinology and Oncology "G. Salvatore", National Council of Research, Naples, 80131, Italy.,Department of Translational Medical Sciences, University of Naples "Federico II", Naples, 80131, Italy
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21
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Herder C, Fürstos JF, Nowotny B, Begun A, Strassburger K, Müssig K, Szendroedi J, Icks A, Roden M. Associations between inflammation-related biomarkers and depressive symptoms in individuals with recently diagnosed type 1 and type 2 diabetes. Brain Behav Immun 2017; 61:137-145. [PMID: 28041985 DOI: 10.1016/j.bbi.2016.12.025] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2016] [Revised: 12/28/2016] [Accepted: 12/28/2016] [Indexed: 01/27/2023] Open
Abstract
Depressive disorders represent a frequent comorbidity of both type 1 (T1D) and type 2 diabetes (T2D). Inflammation-related processes have been implicated in the development of both diabetes and depression. This study aimed to investigate whether biomarkers of subclinical inflammation were associated with depressive symptoms in individuals with recently diagnosed diabetes and if such associations differed by diabetes type. This cross-sectional study was based on 295 individuals with T2D (67% men, mean age 53years) and 139 individuals with T1D (60% men, mean age 36years) of the German Diabetes Study. The main inclusion criterion was a known disease duration of <1year. Depressive symptoms were assessed with the Allgemeine Depressionsskala, Langversion (ADS-L) questionnaire, the German version of the Center for Epidemiological Studies Depression scale (CES-D) questionnaire. Associations between biomarkers of subclinical inflammation and the ADS-L as continuous score were assessed using multiple linear regression models adjusting for age, sex, body mass index, HbA1c, lipids, hypertension, medication and comorbidities. Serum high-sensitivity C-reactive protein (hsCRP) and the ratio of high-molecular-weight (HMW)/total adiponectin were positively associated with ADS-L in T2D (both P<0.01), but not in T1D. In contrast, serum levels of soluble intercellular adhesion molecule (sICAM)-1 were positively associated with ADS-L only in T1D (P=0.035). The latter association was significantly different between both diabetes types (Pinteraction=0.036). No associations were observed for interleukin (IL)-6, IL-18 and soluble E-selectin. Only the association between HMW/total adiponectin and ADS-L in T2D remained significant after correction for multiple testing. In conclusion, our study shows that the ratio HMW/total adiponectin is associated with depressive symptoms in individuals with recently diagnosed T2D. It also provides suggestive evidence that further biomarkers of subclinical inflammation and endothelial activation may be associated with depressive symptoms in individuals with recently diagnosed T1D and T2D.
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Affiliation(s)
- Christian Herder
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225 Düsseldorf, Germany; German Center for Diabetes Research (DZD), Ingolstädter Landstraβe 1, 85764 München-Neuherberg, Germany.
| | - Jan-Felix Fürstos
- German Center for Diabetes Research (DZD), Ingolstädter Landstraβe 1, 85764 München-Neuherberg, Germany; Paul Langerhans Group for Health Services Research and Health Economics, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225 Düsseldorf, Germany.
| | - Bettina Nowotny
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225 Düsseldorf, Germany; German Center for Diabetes Research (DZD), Ingolstädter Landstraβe 1, 85764 München-Neuherberg, Germany; Department of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Moorenstraβe 5, 40225 Düsseldorf, Germany.
| | - Alexander Begun
- German Center for Diabetes Research (DZD), Ingolstädter Landstraβe 1, 85764 München-Neuherberg, Germany; Paul Langerhans Group for Health Services Research and Health Economics, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225 Düsseldorf, Germany.
| | - Klaus Strassburger
- German Center for Diabetes Research (DZD), Ingolstädter Landstraβe 1, 85764 München-Neuherberg, Germany; Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225 Düsseldorf, Germany.
| | - Karsten Müssig
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225 Düsseldorf, Germany; German Center for Diabetes Research (DZD), Ingolstädter Landstraβe 1, 85764 München-Neuherberg, Germany; Department of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Moorenstraβe 5, 40225 Düsseldorf, Germany.
| | - Julia Szendroedi
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225 Düsseldorf, Germany; German Center for Diabetes Research (DZD), Ingolstädter Landstraβe 1, 85764 München-Neuherberg, Germany; Department of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Moorenstraβe 5, 40225 Düsseldorf, Germany.
| | - Andrea Icks
- German Center for Diabetes Research (DZD), Ingolstädter Landstraβe 1, 85764 München-Neuherberg, Germany; Paul Langerhans Group for Health Services Research and Health Economics, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225 Düsseldorf, Germany; Institute for Health Services Research and Health Economics, Centre for Health and Society, Medical Faculty, Heinrich Heine University Düsseldorf, Moorenstraβe 5, 40225 Düsseldorf, Germany.
| | - Michael Roden
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf'm Hennekamp 65, 40225 Düsseldorf, Germany; German Center for Diabetes Research (DZD), Ingolstädter Landstraβe 1, 85764 München-Neuherberg, Germany; Department of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Moorenstraβe 5, 40225 Düsseldorf, Germany.
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22
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Wahl S, Boulesteix AL, Zierer A, Thorand B, Avan de Wiel M. Assessment of predictive performance in incomplete data by combining internal validation and multiple imputation. BMC Med Res Methodol 2016; 16:144. [PMID: 27782817 PMCID: PMC5080703 DOI: 10.1186/s12874-016-0239-7] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2016] [Accepted: 09/30/2016] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Missing values are a frequent issue in human studies. In many situations, multiple imputation (MI) is an appropriate missing data handling strategy, whereby missing values are imputed multiple times, the analysis is performed in every imputed data set, and the obtained estimates are pooled. If the aim is to estimate (added) predictive performance measures, such as (change in) the area under the receiver-operating characteristic curve (AUC), internal validation strategies become desirable in order to correct for optimism. It is not fully understood how internal validation should be combined with multiple imputation. METHODS In a comprehensive simulation study and in a real data set based on blood markers as predictors for mortality, we compare three combination strategies: Val-MI, internal validation followed by MI on the training and test parts separately, MI-Val, MI on the full data set followed by internal validation, and MI(-y)-Val, MI on the full data set omitting the outcome followed by internal validation. Different validation strategies, including bootstrap und cross-validation, different (added) performance measures, and various data characteristics are considered, and the strategies are evaluated with regard to bias and mean squared error of the obtained performance estimates. In addition, we elaborate on the number of resamples and imputations to be used, and adopt a strategy for confidence interval construction to incomplete data. RESULTS Internal validation is essential in order to avoid optimism, with the bootstrap 0.632+ estimate representing a reliable method to correct for optimism. While estimates obtained by MI-Val are optimistically biased, those obtained by MI(-y)-Val tend to be pessimistic in the presence of a true underlying effect. Val-MI provides largely unbiased estimates, with a slight pessimistic bias with increasing true effect size, number of covariates and decreasing sample size. In Val-MI, accuracy of the estimate is more strongly improved by increasing the number of bootstrap draws rather than the number of imputations. With a simple integrated approach, valid confidence intervals for performance estimates can be obtained. CONCLUSIONS When prognostic models are developed on incomplete data, Val-MI represents a valid strategy to obtain estimates of predictive performance measures.
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Affiliation(s)
- Simone Wahl
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstädter Landstrasse, Neuherberg, 1, 85764 Germany
- Institute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstädter Landstrasse, Neuherberg, 1, 85764 Germany
- German Center for Diabetes Research (DZD e.V.), Ingolstädter Landstrasse, Neuherberg, 1, 85764 Germany
| | - Anne-Laure Boulesteix
- Department of Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Marchioninistrasse, Munich, 15, 81377 Germany
| | - Astrid Zierer
- Institute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstädter Landstrasse, Neuherberg, 1, 85764 Germany
| | - Barbara Thorand
- Institute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Ingolstädter Landstrasse, Neuherberg, 1, 85764 Germany
- German Center for Diabetes Research (DZD e.V.), Ingolstädter Landstrasse, Neuherberg, 1, 85764 Germany
| | - Mark Avan de Wiel
- Department of Epidemiology and Biostatistics, VU University Medical Center, PO Box 7057, Amsterdam, 1007 MB The Netherlands
- Department of Mathematics, VU University, De Boelelaan 1081a, Amsterdam, 1081 HV The Netherlands
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23
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HCN2 ion channels: basic science opens up possibilities for therapeutic intervention in neuropathic pain. Biochem J 2016; 473:2717-36. [DOI: 10.1042/bcj20160287] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2016] [Accepted: 05/18/2016] [Indexed: 01/22/2023]
Abstract
Nociception — the ability to detect painful stimuli — is an invaluable sense that warns against present or imminent damage. In patients with chronic pain, however, this warning signal persists in the absence of any genuine threat and affects all aspects of everyday life. Neuropathic pain, a form of chronic pain caused by damage to sensory nerves themselves, is dishearteningly refractory to drugs that may work in other types of pain and is a major unmet medical need begging for novel analgesics. Hyperpolarisation-activated cyclic nucleotide (HCN)-modulated ion channels are best known for their fundamental pacemaker role in the heart; here, we review data demonstrating that the HCN2 isoform acts in an analogous way as a ‘pacemaker for pain’, in that its activity in nociceptive neurons is critical for the maintenance of electrical activity and for the sensation of chronic pain in pathological pain states. Pharmacological block or genetic deletion of HCN2 in sensory neurons provides robust pain relief in a variety of animal models of inflammatory and neuropathic pain, without any effect on normal sensation of acute pain. We discuss the implications of these findings for our understanding of neuropathic pain pathogenesis, and we outline possible future opportunities for the development of efficacious and safe pharmacotherapies in a range of chronic pain syndromes.
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24
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Szendroedi J, Saxena A, Weber KS, Strassburger K, Herder C, Burkart V, Nowotny B, Icks A, Kuss O, Ziegler D, Al-Hasani H, Müssig K, Roden M. Cohort profile: the German Diabetes Study (GDS). Cardiovasc Diabetol 2016; 15:59. [PMID: 27053136 PMCID: PMC4823856 DOI: 10.1186/s12933-016-0374-9] [Citation(s) in RCA: 83] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/10/2015] [Accepted: 03/24/2016] [Indexed: 12/16/2022] Open
Abstract
Background The German Diabetes Study (GDS) is a prospective longitudinal cohort study describing the impact of subphenotypes on the course of the disease. GDS aims at identifying prognostic factors and mechanisms underlying the development of related comorbidities. Study design and methods The study comprises intensive phenotyping within 12 months after clinical diagnosis, at 5-year intervals for 20 years and annual telephone interviews in between. Dynamic tests, including glucagon, mixed meal, intravenous glucose tolerance and hyperinsulinemic clamp tests, serve to assess beta-cell function and tissue-specific insulin sensitivity. Magnetic resonance imaging and multinuclei spectroscopy allow quantifying whole-body fat distribution, tissue-specific lipid deposition and energy metabolism. Comprehensive analyses of microvascular (nerve, eye, kidney) and macrovascular (endothelial, cardiorespiratory) morphology and function enable identification and monitoring of comorbidities. The GDS biobank stores specimens from blood, stool, skeletal muscle, subcutaneous adipose tissue and skin for future analyses including multiomics, expression profiles and histology. Repeated questionnaires on socioeconomic conditions, patient-reported outcomes as quality of life, health-related behavior as physical activity and nutritional habits are a specific asset of GDS. This study will recruit 3000 patients and a group of humans without familiy history of diabetes. 237 type 1 and 456 type 2 diabetes patients have been already included. Electronic supplementary material The online version of this article (doi:10.1186/s12933-016-0374-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Julia Szendroedi
- Institute for Clinical Diabetology, Leibniz Institute for Diabetes Research, German Diabetes Center at Heinrich Heine University, Düsseldorf, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg, Germany.,Department of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Aaruni Saxena
- Institute for Clinical Diabetology, Leibniz Institute for Diabetes Research, German Diabetes Center at Heinrich Heine University, Düsseldorf, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg, Germany.,Department of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Katharina S Weber
- Institute for Clinical Diabetology, Leibniz Institute for Diabetes Research, German Diabetes Center at Heinrich Heine University, Düsseldorf, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Klaus Strassburger
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany.,Institute for Biometrics and Epidemiology, Leibniz Institute for Diabetes Research, German Diabetes Center at Heinrich Heine University, Düsseldorf, Germany
| | - Christian Herder
- Institute for Clinical Diabetology, Leibniz Institute for Diabetes Research, German Diabetes Center at Heinrich Heine University, Düsseldorf, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Volker Burkart
- Institute for Clinical Diabetology, Leibniz Institute for Diabetes Research, German Diabetes Center at Heinrich Heine University, Düsseldorf, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Bettina Nowotny
- Institute for Clinical Diabetology, Leibniz Institute for Diabetes Research, German Diabetes Center at Heinrich Heine University, Düsseldorf, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Andrea Icks
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany.,Institute for Biometrics and Epidemiology, Leibniz Institute for Diabetes Research, German Diabetes Center at Heinrich Heine University, Düsseldorf, Germany.,Public Health Unit, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Oliver Kuss
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany.,Institute for Biometrics and Epidemiology, Leibniz Institute for Diabetes Research, German Diabetes Center at Heinrich Heine University, Düsseldorf, Germany
| | - Dan Ziegler
- Institute for Clinical Diabetology, Leibniz Institute for Diabetes Research, German Diabetes Center at Heinrich Heine University, Düsseldorf, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg, Germany.,Department of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Hadi Al-Hasani
- German Center for Diabetes Research (DZD), München-Neuherberg, Germany.,Institute for Clinical Biochemistry and Pathobiochemistry German Diabetes Center, Leibniz Institute for Diabetes Research, Düsseldorf, Germany
| | - Karsten Müssig
- Institute for Clinical Diabetology, Leibniz Institute for Diabetes Research, German Diabetes Center at Heinrich Heine University, Düsseldorf, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg, Germany.,Department of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Michael Roden
- Institute for Clinical Diabetology, Leibniz Institute for Diabetes Research, German Diabetes Center at Heinrich Heine University, Düsseldorf, Germany. .,German Center for Diabetes Research (DZD), München-Neuherberg, Germany. .,Department of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany.
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25
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Röhling M, Herder C, Stemper T, Müssig K. Influence of Acute and Chronic Exercise on Glucose Uptake. J Diabetes Res 2016; 2016:2868652. [PMID: 27069930 PMCID: PMC4812462 DOI: 10.1155/2016/2868652] [Citation(s) in RCA: 59] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2015] [Revised: 01/31/2016] [Accepted: 02/03/2016] [Indexed: 02/06/2023] Open
Abstract
Insulin resistance plays a key role in the development of type 2 diabetes. It arises from a combination of genetic predisposition and environmental and lifestyle factors including lack of physical exercise and poor nutrition habits. The increased risk of type 2 diabetes is molecularly based on defects in insulin signaling, insulin secretion, and inflammation. The present review aims to give an overview on the molecular mechanisms underlying the uptake of glucose and related signaling pathways after acute and chronic exercise. Physical exercise, as crucial part in the prevention and treatment of diabetes, has marked acute and chronic effects on glucose disposal and related inflammatory signaling pathways. Exercise can stimulate molecular signaling pathways leading to glucose transport into the cell. Furthermore, physical exercise has the potential to modulate inflammatory processes by affecting specific inflammatory signaling pathways which can interfere with signaling pathways of the glucose uptake. The intensity of physical training appears to be the primary determinant of the degree of metabolic improvement modulating the molecular signaling pathways in a dose-response pattern, whereas training modality seems to have a secondary role.
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Affiliation(s)
- Martin Röhling
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Munich, 85764 Neuherberg, Germany
| | - Christian Herder
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Munich, 85764 Neuherberg, Germany
| | - Theodor Stemper
- Department Fitness and Health, University Wuppertal, 42119 Wuppertal, Germany
| | - Karsten Müssig
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Munich, 85764 Neuherberg, Germany
- Department of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
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26
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Ye W, Zheng Y, Zhang S, Yan L, Cheng H, Wu M. Oxamate Improves Glycemic Control and Insulin Sensitivity via Inhibition of Tissue Lactate Production in db/db Mice. PLoS One 2016; 11:e0150303. [PMID: 26938239 PMCID: PMC4777529 DOI: 10.1371/journal.pone.0150303] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2015] [Accepted: 02/02/2016] [Indexed: 12/18/2022] Open
Abstract
Oxamate (OXA) is a pyruvate analogue that directly inhibits the lactate dehydrogenase (LDH)-catalyzed conversion process of pyruvate into lactate. Earlier and recent studies have shown elevated blood lactate levels among insulin-resistant and type 2 diabetes subjects and that blood lactate levels independently predicted the development of incident diabetes. To explore the potential of OXA in the treatment of diabetes, db/db mice were treated with OXA in vivo. Treatment of OXA (350–750 mg/kg of body weight) for 12 weeks was shown to decrease body weight gain and blood glucose and HbA1c levels and improve insulin secretion, the morphology of pancreatic islets, and insulin sensitivity in db/db mice. Meanwhile, OXA reduced the lactate production of adipose tissue and skeletal muscle and serum lactate levels and decreased serum levels of TG, FFA, CRP, IL-6, and TNF-α in db/db mice. The PCR array showed that OXA downregulated the expression of Tnf, Il6, leptin, Cxcr3, Map2k1, and Ikbkb, and upregulated the expression of Irs2, Nfkbia, and Pde3b in the skeletal muscle of db/db mice. Interestingly, LDH-A expression increased in the islet cells of db/db mice, and both treatment of OXA and pioglitazone decreased LDH-A expression, which might be related to the improvement of insulin secretion. Taken together, increased lactate production of adipose tissue and skeletal muscle may be at least partially responsible for insulin resistance and diabetes in db/db mice. OXA improved glycemic control and insulin sensitivity in db/db mice primarily via inhibition of tissue lactate production. Oxamic acid derivatives may be a potential drug for the treatment of type 2 diabetes.
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Affiliation(s)
- Weiran Ye
- Department of Endocrinology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, P. R. China
| | - Yijia Zheng
- Department of Endocrinology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, P. R. China
| | - Shanshan Zhang
- Department of Endocrinology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, P. R. China
| | - Li Yan
- Department of Endocrinology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, P. R. China
| | - Hua Cheng
- Department of Endocrinology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, P. R. China
| | - Muchao Wu
- Department of Endocrinology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, P. R. China
- * E-mail:
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27
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Chmielewski S, Piaszyk-Borychowska A, Wesoly J, Bluyssen HAR. STAT1 and IRF8 in Vascular Inflammation and Cardiovascular Disease: Diagnostic and Therapeutic Potential. Int Rev Immunol 2015; 35:434-454. [DOI: 10.3109/08830185.2015.1087519] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Affiliation(s)
- Stefan Chmielewski
- Department of Human Molecular Genetics, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Poznan, Poland
- Department of Nephrology, Klinikum Rechts der Isar, Technical University of Munich, Munich, Germany
| | - Anna Piaszyk-Borychowska
- Department of Human Molecular Genetics, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Poznan, Poland
| | - Joanna Wesoly
- Laboratory of High Throughput Technologies, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Poznan, Poland
| | - Hans A. R. Bluyssen
- Department of Human Molecular Genetics, Institute of Molecular Biology and Biotechnology, Faculty of Biology, Adam Mickiewicz University, Poznan, Poland
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28
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Long-term exposure to ambient air pollution and serum leptin in older adults: results from the MOBILIZE Boston study. J Occup Environ Med 2015; 56:e73-7. [PMID: 25192230 DOI: 10.1097/jom.0000000000000253] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
OBJECTIVE Long-term exposure to traffic-related air pollution has been linked to increased risk of obesity and diabetes and may be associated with higher serum levels of the adipokine leptin, but this hypothesis has not been previously evaluated in humans. METHODS In a cohort of older adults, we estimated the association between serum leptin concentrations and two markers of long-term exposure to traffic pollution, adjusting for participant characteristics, temporal trends, socioeconomic factors, and medical history. RESULTS An interquartile range increase (0.11 μg/m) in annual mean residential black carbon was associated with 12% (95% confidence interval: 3%, 22%) higher leptin levels. Leptin levels were not associated with residential distance to major roadway. CONCLUSIONS If confirmed, these findings support the emerging evidence suggesting that certain sources of traffic pollution may be associated with adverse cardiometabolic effects.
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29
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Foerster J, Hyötyläinen T, Oresic M, Nygren H, Boeing H. Serum Lipid and Serum Metabolite Components in relation to anthropometric parameters in EPIC-Potsdam participants. Metabolism 2015; 64:1348-58. [PMID: 26271139 DOI: 10.1016/j.metabol.2015.07.004] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2014] [Revised: 06/27/2015] [Accepted: 07/01/2015] [Indexed: 12/17/2022]
Abstract
BACKGROUND/AIM Lipidomic and metabolomic techniques become more and more important in human health research. Recent developments in analytical techniques enable the investigation of high amounts of substances. The high numbers of metabolites and lipids that are detected with among others mass spectrometric techniques challenge in most cases the statistical processes to bring out stable and interpretable results. This study targets to use the novel non-established statistical method treelet transform (TT) to investigate high numbers of metabolites and lipids and to compare the results with the established method principal component analysis (PCA). Serum lipid and metabolite profiles are investigated regarding their association to anthropometric parameters associated to obesity. METHODS From 226 participants of the EPIC (European Prospective Investigation into Cancer and Nutrition)-Potsdam study blood samples were investigated with an untargeted metabolomics approach regarding serum metabolites and lipids. Additionally, participants were surveyed anthropometrically to assess parameters of obesity, such as body mass index (BMI), waist-to-hip-ratio (WHR) and body fat mass. TT and PCA are used to generate treelet components (TCs) and factors summarizing serum metabolites and lipids in new, latent variables without too much loss of information. With partial correlations TCs and factors were associated to anthropometry under the control for relevant parameters, such as sex and age. RESULTS TT with metabolite variables (p=121) resulted in 5 stable and interpretable TCs explaining 18.9% of the variance within the data. PCA on the same variables generated 4 quite complex, less easily interpretable factors explaining 37.5% of the variance. TT on lipidomic data (p=353) produced 3 TCs as well as PCA on the same data resulted in 3 factors; the proportion of explained variance was 17.8% for TT and 39.8% for PCA. In both investigations TT ended up with stable components that are easier to interpret than the factors from the PCA. In general, the generated TCs and factors were similar in their structure when the factors are considered regarding the original variables loading high on them. Both TCs and factors showed associations to anthropometric measures. CONCLUSIONS TT is a suitable statistical method to generate summarizing, latent variables in data sets with more variables than observations. In the present investigation it resulted in similar latent variables compared to the established method of PCA. Whereby less variance is explained by the summarizing constructs of TT compared to the factors of PCA, TCs are easier to interpret. Additionally the resulting TCs are quite stable in bootstrap samples.
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Affiliation(s)
- Jana Foerster
- Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Arthur-Scheunert-Allee 114-116, 14558 Nuthetal, Germany.
| | - Tuulia Hyötyläinen
- Systems Medicine, Steno Diabetes Centre, Niels Steensens Vej 2, 2820 Gentofte, Denmark
| | - Matej Oresic
- Systems Medicine, Steno Diabetes Centre, Niels Steensens Vej 2, 2820 Gentofte, Denmark
| | - Heli Nygren
- VTT Technical Research Centre of Finland, Tietotie 2, P.O. Box 1000, FI-02044 VTT, Espoo, Finland
| | - Heiner Boeing
- Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Arthur-Scheunert-Allee 114-116, 14558 Nuthetal, Germany
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30
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[Mortality follow-up of the German Health Interview and Examination Survey for Adults (DEGS) : methods and first results]. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2015; 57:1331-7. [PMID: 25267318 DOI: 10.1007/s00103-014-2053-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
OBJECTIVES Within the framework of the German Health Interview and Examination Survey for Adults (DEGS), the Robert Koch Institute (RKI) conducted a nationwide mortality follow-up study. As there is no national mortality register in Germany, mortality and causes of death were investigated individually and under observance of state-specific data protection conditions. METHODS The German Health Interview and Examination Survey 1998 (GNHIES98) provided the database including 7,124 participants aged 18-79 years. A total of 6,979 participants of GNHIES98 (98 %) who consented to be re-contacted were invited between October 2008 and October 2011 to also participate in the first data collection wave of DEGS (DEGS1). In this context, the vital status and the causes of death for deceased participants were assessed. Age- and sex-specific probabilities of survival and death rates were calculated and grouped by main causes of death according to ICD-10 groups. RESULTS A total of 671 individuals (285 women, 386 men) died between the two survey contacts. For all deceased persons the date of death and for 539 (80.3 %) the causes of death could be determined. With a median follow-up time of 12.0 years, 8,0742.5 person years were available for survival analysis. The crude overall death rate amounted to 8.3 per 1,000 persons-years (women: 7.2; men: 9.5). Among 539 persons with available information on causes of death, 209 (38.8 %) were attributable to cardiovascular diseases, 188 (34.9 %) to cancer, 135 (25.0 %) to other causes, and seven (1.3 %) could not be unambiguously assigned. CONCLUSIONS A mortality follow-up was successfully integrated in the longitudinal component of DEGS as part of the national health monitoring at the RKI. Death rates and cause-specific mortality in relation to highly prevalent chronic diseases and risk factors provide essential information for assessing the potential of prevention and quality of care among adults in Germany. This requires a regular and complete conduction of mortality follow-ups.
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31
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Fichna M, Fichna P, Gryczyńska M, Czarnywojtek A, Żurawek M, Ruchała M. Steroid replacement in primary adrenal failure does not appear to affect circulating adipokines. Endocrine 2015; 48:677-85. [PMID: 25129652 PMCID: PMC4351438 DOI: 10.1007/s12020-014-0388-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2014] [Accepted: 08/06/2014] [Indexed: 01/17/2023]
Abstract
Despite continuous efforts for an optimal steroid replacement, recent observations suggest increased cardiometabolic risk and related mortality in primary adrenal insufficiency (PAI). Adipokines are peptides from the adipose tissue, markers of cardiometabolic dysfunction. This study was aimed to evaluate serum levels of adipokines: leptin, adiponectin, and resistin in PAI during conventional steroid substitution. The analysis comprised 63 patients (mean age 42.7 ± 14.1 years) and 63 healthy controls. Serum adipokines, lipid profile, and plasma glucose were assessed in both cohorts. ACTH, serum insulin, HOMA-IR, DHEA-S, cortisol and 24 h urinary free cortisol were determined in PAI. Body mass composition was analyzed by Dual-Energy X-ray Absorptiometry. Mean BMI in the control group was 24.1 ± 3.9 kg/m(2) and 23.7 ± 3.9 kg/m(2) in the PAI cohort. Serum leptin and adiponectin levels were similar in both groups, whereas resistin appeared significantly lower among affected subjects (p = 0.0002). Its levels were weakly correlated with HOMA-IR (p = 0.048). Leptin was independently correlated with fasting insulin, HOMA-IR, BMI, and body fat (p < 0.001). At the multiple regression analysis only weight (p = 0.017), total and HDL cholesterol (p < 0.001) appeared significant predictors of adiponectin level. No adipokine correlations with serum cortisol or daily hydrocortisone dose were found. Patients receiving DHEA substitution displayed lower leptin and adiponectin levels (p < 0.05). In conclusion, our study did not provide evidence of an adverse adipokine profile in patients with PAI under conventional glucocorticoid replacement. Serum adipokines in treated PAI follow similar correlations to those reported in healthy subjects. Further prospective studies are warranted to verify and explain plausible excess of cardiovascular mortality in PAI.
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Affiliation(s)
- Marta Fichna
- Institute of Human Genetics, Polish Academy of Sciences, 32 Strzeszynska, 60-479, Poznan, Poland,
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Khalili P, Sundström J, Jendle J, Lundin F, Jungner I, Nilsson PM. Sialic acid and incidence of hospitalization for diabetes and its complications during 40-years of follow-up in a large cohort: the Värmland survey. Prim Care Diabetes 2014; 8:352-357. [PMID: 24996911 DOI: 10.1016/j.pcd.2014.06.002] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2013] [Revised: 05/09/2014] [Accepted: 06/03/2014] [Indexed: 10/25/2022]
Abstract
AIM To examine the association of sialic acid (SA) with first recorded diabetes mellitus-related hospitalization. METHODS From a population-based study in Värmland, Sweden, between 1962 and 1965, 87,035 men and women were selected and followed for first recorded diabetes-related hospitalization until 2005. The association of SA was calculated and stratified for gender by Cox's proportional hazards models. Adjustments were made for conventional risk factors and socioeconomic status. Association analyses were made for comparisons between SA-levels above and below median. RESULTS The mean age was 47.2 (SD 13.0) years and the total numbers of incident diabetes-related hospitalizations in men and women were 3445 and 3273, respectively. Hazard ratios per one standard deviation of SA were 1.12 (95% CI: 1.08-1.17, p<0.0001) in men and 1.17 (95% CI: 1.13-1.22, p<0.0001) in women. Interaction analyses indicated a relatively higher SA-associated risk in women than in men with above median SA levels. CONCLUSIONS In this large population-based cohort followed for more than 40 years, elevated SA, as a marker of systemic inflammation, was independently associated with risk of diabetes and diabetes-related hospitalizations.
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Affiliation(s)
- Payam Khalili
- Department of Cardiology and Acute Internal Medicine, Central Hospital, Karlstad, Sweden; Faculty of Health Sciences and Medicine, Örebro University, Örebro, Sweden.
| | - Johan Sundström
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Johan Jendle
- Faculty of Health Sciences and Medicine, Örebro University, Örebro, Sweden; Endocrine and Diabetes Center, Central Hospital, Karlstad, Sweden
| | - Fredrik Lundin
- Statistical Unit, Värmland County Council, Karlstad, Sweden
| | - Ingmar Jungner
- Department of Medicine, Clinical Epidemiological Unit, Karolinska Institute, Stockholm, Sweden
| | - Peter M Nilsson
- Faculty of Health Sciences and Medicine, Örebro University, Örebro, Sweden; Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden
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Hribal ML, Fiorentino TV, Sesti G. Role of C reactive protein (CRP) in leptin resistance. Curr Pharm Des 2014; 20:609-15. [PMID: 23688010 PMCID: PMC4155811 DOI: 10.2174/13816128113199990016] [Citation(s) in RCA: 47] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2013] [Accepted: 05/13/2013] [Indexed: 01/23/2023]
Abstract
Increased plasma levels of both leptin and C reactive protein (CRP) have been reported in a number of conditions, including obesity, and have been linked to cardiovascular pathophysiological processes and increased cardiovascular risk; interestingly these two biomarkers appear to be able to reciprocally regulate their bioavailability, through complex mechanisms that have not been completely clarified yet. Here we first review clinical evidence suggesting not only that the circulatory levels of CRP and leptin show an independent correlation, but also that assessing them in tandem may result in an increased ability to predict cardiovascular disease. We summarize also molecular studies showing that leptin is able to promote CRP production from hepatocytes and endothelial cells in vitro and discuss the studies addressing the possibility that in vivo leptin administration may be able to modulate plasma CRP levels. Furthermore, we describe two studies demonstrating that CRP directly binds leptin in extra-cellular settings, thus impairing its biological actions. Finally we report genetic evidence that common variations at the leptin receptor locus are associated with CRP blood levels. Overall, the data reviewed here show that the chronic elevation of CRP observed in obese subjects may worsen leptin resistance, contributing to the pathogenesis of cardiovascular disease, and highlight a potential link between conditions, such as leptin resistance and endothelial dysfunction, that may be amenable of pharmacological treatment targeted to the disruption of leptin-CRP interaction.
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Affiliation(s)
| | | | - Giorgio Sesti
- Department of Medical and Surgical Sciences, University of Catanzaro Magna Graecia, Viale Europa, località Germaneto 88100 Catanzaro, Italy.
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Teichert T, Vossoughi M, Vierkötter A, Sugiri D, Schikowski T, Hoffmann B, Schulte T, Roden M, Raulf-Heimsoth M, Luckhaus C, Krämer U, Herder C. Investigating the spill-over hypothesis: analysis of the association between local inflammatory markers in sputum and systemic inflammatory mediators in plasma. ENVIRONMENTAL RESEARCH 2014; 134:24-32. [PMID: 25042033 DOI: 10.1016/j.envres.2014.06.021] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2014] [Revised: 06/11/2014] [Accepted: 06/21/2014] [Indexed: 06/03/2023]
Abstract
Exposure to air pollutants represents a risk factor not only for respiratory diseases and lung cancer, but also for cardiometabolic diseases. It has been hypothesised that local inflammation in the lung and systemic subclinical inflammation are linked by impaired lung function and the spill-over of proinflammatory factors from the lung into the circulation which could act as intermediaries between environmental exposures and disease risk. We wanted to investigate whether local and systemic inflammatory markers are associated, which would support the spill-over hypothesis. Sputum and plasma samples were obtained from 257 women of the German SALIA cohort. We performed immunoassays to measure multiple biomarkers of airway inflammation in sputum as well as cytokines, chemokines and soluble adhesion molecules in plasma. Correlations were calculated and adjusted for potentially confounding variables. Even though several significant associations were detected between inflammatory mediators in sputum and plasma, correlation coefficients were rather low ranging from r≥-0.20 to r≤0.20. Comparatively stronger associations were observed between nitrite, eosinophil cationic protein, leukotrienes C/D/E4 and interleukin-8 in sputum. Notably, correlations were positive with all proinflammatory biomarkers and interleukin-1 receptor antagonist in plasma, whereas negative correlations were observed with the anti-inflammatory adipokine adiponectin. In conclusion, local inflammation in the lung and systemic subclinical inflammation appear mainly independently regulated in elderly women from the general population. Although we found multiple significant correlations between inflammatory biomarkers in sputum and plasma, our results do not provide clear support for the spill-over hypothesis.
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Affiliation(s)
- Tom Teichert
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf׳m Hennekamp 65, 40225 Düsseldorf, Germany.
| | - Mohammad Vossoughi
- IUF-Leibniz Research Institute for Environmental Medicine at Heinrich Heine University Düsseldorf, Auf׳m Hennekamp 50, 40225 Düsseldorf, Germany.
| | - Andrea Vierkötter
- IUF-Leibniz Research Institute for Environmental Medicine at Heinrich Heine University Düsseldorf, Auf׳m Hennekamp 50, 40225 Düsseldorf, Germany.
| | - Dorothea Sugiri
- IUF-Leibniz Research Institute for Environmental Medicine at Heinrich Heine University Düsseldorf, Auf׳m Hennekamp 50, 40225 Düsseldorf, Germany.
| | - Tamara Schikowski
- IUF-Leibniz Research Institute for Environmental Medicine at Heinrich Heine University Düsseldorf, Auf׳m Hennekamp 50, 40225 Düsseldorf, Germany; Swiss Tropical and Public Health Institute, Socinstrasse 57, 4051 Basel, Switzerland; University of Basel, Petersplatz 1, 4003 Basel, Switzerland.
| | - Barbara Hoffmann
- IUF-Leibniz Research Institute for Environmental Medicine at Heinrich Heine University Düsseldorf, Auf׳m Hennekamp 50, 40225 Düsseldorf, Germany; Medical Faculty, Heinrich Heine University of Düsseldorf, Moorenstraße 5, 40225 Düsseldorf, Germany.
| | - Thomas Schulte
- Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich Heine University Düsseldorf, Bergische Landstraße 2, 40629 Düsseldorf, Germany.
| | - Michael Roden
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf׳m Hennekamp 65, 40225 Düsseldorf, Germany; Department of Endocrinology and Diabetology, University Hospital Düsseldorf, Heinrich Heine University, Universitätsstraße 1, 40225 Düsseldorf, Germany; German Center for Diabetes Research (DZD e.V.), Partner Düsseldorf, Auf׳m Hennekamp 65, 40225 Düsseldorf, Germany.
| | - Monika Raulf-Heimsoth
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr-Universität Bochum (IPA), Center of Allergology/Immunology, Bürkle-de-la-Camp Platz 1, 44789 Bochum, Germany.
| | - Christian Luckhaus
- Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich Heine University Düsseldorf, Bergische Landstraße 2, 40629 Düsseldorf, Germany.
| | - Ursula Krämer
- IUF-Leibniz Research Institute for Environmental Medicine at Heinrich Heine University Düsseldorf, Auf׳m Hennekamp 50, 40225 Düsseldorf, Germany.
| | - Christian Herder
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Auf׳m Hennekamp 65, 40225 Düsseldorf, Germany; German Center for Diabetes Research (DZD e.V.), Partner Düsseldorf, Auf׳m Hennekamp 65, 40225 Düsseldorf, Germany.
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Bianco HT, Izar MC, Fonseca HA, Póvoa RM, Saraiva JF, Forti A, Jardim PCBV, Introcaso L, Yugar-Toledo J, Xavier HT, Faludi AA, Fonseca FAH. Relevance of target-organ lesions as predictors of mortality in patients with diabetes mellitus. Arq Bras Cardiol 2014; 103:272-81. [PMID: 25098376 PMCID: PMC4206357 DOI: 10.5935/abc.20140112] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2013] [Revised: 05/05/2014] [Accepted: 05/09/2014] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND Patients with diabetes are in extract higher risk for fatal cardiovascular events. OBJECTIVE To evaluate major predictors of mortality in subjects with type 2 diabetes. METHODS A cohort of 323 individuals with type 2 diabetes from several regions of Brazil was followed for a long period. Baseline electrocardiograms, clinical and laboratory data obtained were used to determine hazard ratios (HR) and confidence interval (CI) related to cardiovascular and total mortality. RESULTS After 9.2 years of follow-up (median), 33 subjects died (17 from cardiovascular causes). Cardiovascular mortality was associated with male gender; smoking; prior myocardial infarction; long QTc interval; left ventricular hypertrophy; and eGFR <60 mL/min. These factors, in addition to obesity, were predictors of total mortality. Cardiovascular mortality was adjusted for age and gender, but remained associated with: smoking (HR = 3.8; 95% CI 1.3-11.8; p = 0.019); prior myocardial infarction (HR = 8.5; 95% CI 1.8-39.9; p = 0.007); eGFR < 60 mL/min (HR = 9.5; 95% CI 2.7-33.7; p = 0.001); long QTc interval (HR = 5.1; 95% CI 1.7-15.2; p = 0.004); and left ventricular hypertrophy (HR = 3.5; 95% CI 1.3-9.7; p = 0.002). Total mortality was associated with obesity (HR = 2.3; 95% CI 1.1-5.1; p = 0.030); smoking (HR = 2.5; 95% CI 1.0-6.1; p = 0.046); prior myocardial infarction (HR = 3.1; 95% CI 1.4-6.1; p = 0.005), and long QTc interval (HR = 3.1; 95% CI 1.4-6.1; p = 0.017). CONCLUSIONS Biomarkers of simple measurement, particularly those related to target-organ lesions, were predictors of mortality in subjects with type 2 diabetes.
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Affiliation(s)
| | | | | | - Rui Manuel Póvoa
- Universidade Federal de São Paulo (Unifesp), São Paulo, SP
- Brazil
| | | | - Adriana Forti
- Centro de Diabetes e Hipertensão de Fortaleza, Fortaleza, CE -
Brazil
| | | | - Luis Introcaso
- Centro de Investigação Clínica de Brasília,
Brasília, DF - Brazil
| | - Juan Yugar-Toledo
- Escola de Medicina de São José do Rio Preto, São
José do Rio Preto, SP - Brazil
| | - Hermes Tóros Xavier
- Centro de Investigação Clínica de Santos, Santos,
SP - Brazil
- Universidade de São Paulo (USP), São Paulo, SP -
Brazil
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Impact of counterbalance between macrophage migration inhibitory factor and its inhibitor Gremlin-1 in patients with coronary artery disease. Atherosclerosis 2014; 237:426-32. [PMID: 25463068 DOI: 10.1016/j.atherosclerosis.2014.09.010] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2014] [Revised: 09/02/2014] [Accepted: 09/14/2014] [Indexed: 12/12/2022]
Abstract
OBJECTIVE Monocyte infiltration is a critical step in the pathophysiology of plaque instability in coronary artery disease (CAD). Macrophage migration inhibitory factor (MIF) is involved in atherosclerotic plaque progression and instability leading to intracoronary thrombosis. Gremlin-1 (Grem1) has been recently identified as endogenous inhibitor of MIF. To date there are no data on the clinical impact of this interaction in cardiovascular patients. METHODS AND RESULTS Plasma levels of MIF and Grem1 were determined by enzyme-linked immunoassay in patients with acute coronary syndromes (ACS, n = 120; stable CAD, n = 166 and healthy control subjects, n = 25). MIF levels were significantly increased in ACS compared to stable CAD and healthy control (ACS: median 2.85; IQR 3.52 ng/ml; versus SAP: median 1.22; IQR 2.99 ng/ml; versus healthy control: median 0.10; IQR 0.09 ng/ml, p < 0.001). Grem1 levels were significantly higher in ACS and stable CAD patients compared to healthy control (ACS: median 211.00; IQR 130.47 ng/ml; SAP: median 220.20; IQR 120.93 ng/ml, versus healthy control: median 90.57; IQR 97.68 ng/ml, p < 0.001). Grem1/MIF ratio was independently associated with ACS, whereas the single parameters were not associated with the presence of ACS. Furthermore, Grem1/MIF ratio was associated with angiographic signs of intracoronary thrombi and severity of thrombus burden. CONCLUSION These novel findings suggest a potential role of Grem1/MIF ratio to indicate acuity of CAD and the grade of plaque stability. Prospective angiographic cohort studies involving plaque imaging techniques are warranted to further characterize the prognostic role of this novel risk marker in CAD patients.
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Luksiene D, Tamosiunas A, Baceviciene M, Radisauskas R, Malinauskiene V, Peasey A, Bobak M. Trends in prevalence of dyslipidaemias and the risk of mortality in Lithuanian urban population aged 45-64 in relation to the presence of the dyslipidaemias and the other cardiovascular risk factors. PLoS One 2014; 9:e100158. [PMID: 24955583 PMCID: PMC4067295 DOI: 10.1371/journal.pone.0100158] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2014] [Accepted: 05/22/2014] [Indexed: 11/18/2022] Open
Abstract
The aim of this study was to provide reliable information on dyslipidaemias, to estimate the trend of the prevalence of dyslipidaemias and other selected cardiovascular disease (CVD) risk factors at population level, and to evaluate the risk of all-cause and CVD mortality in relation to presence of mixed dyslipidaemias and other CVD risk factors. Methods Data from the five surveys (1983–2008) are presented. A random sample of 9,209 subjects aged 45–64 was selected for statistical analysis. During follow-up there were 1653 death cases from any cause, 864 deaths from CVD. Estimates of hazard ratios (HR) and 95% confidence intervals (CI) were based on the multivariate Cox proportional hazards regression for all-cause mortality and CVD mortality. Results During 25 year period the prevalence of normal total cholesterol level (<5.2 mmol/L) significantly increased only in women; triglycerides and high density lipoprotein (HDL) cholesterol did not change in men and women. Findings in our longitudinal study showed that in men and women mixed dyslipidaemias (HDL cholesterol <1.03 mmol/L plus triglycerides ≥1.70 mmol/L) significantly increased the risk for all-cause and CVD mortality (respectively in men HR = 1.30; HR = 1.15, in women HR = 1.83; HR = 2.13). These mixed dyslipidaemia combinations combination with the other risk factors such as arterial hypertension, high fasting glucose level increased all-cause and CVD mortality risk in men and women; while, these mixed dyslipidaemias plus smoking increased all-cause and CVD mortality risk only in men compared to never smokers without these dyslipidaemias (respectively HR = 1.89; HR = 1.92); and these dyslipidaemias plus obesity increased all-cause and CVD mortality risk in women (respectively HR = 2.25; HR = 2.39) and CVD mortality risk in men (HR = 1.72), as compared to responders without obesity and these dyslipidaemias. Conclusion Mixed dyslipidaemias (reduced HDL cholesterol plus elevated triglycerides) significantly increased the risk for all-cause and CVD mortality in this Lithuanian population aged 45–64 years.
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Affiliation(s)
- Dalia Luksiene
- Institute of Cardiology, Academy of Medicine, Lithuanian University of Health Sciences, Kaunas, Lithuania
- * E-mail:
| | - Abdonas Tamosiunas
- Institute of Cardiology, Academy of Medicine, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Migle Baceviciene
- Institute of Cardiology, Academy of Medicine, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Ricardas Radisauskas
- Institute of Cardiology, Academy of Medicine, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Vilija Malinauskiene
- Institute of Cardiology, Academy of Medicine, Lithuanian University of Health Sciences, Kaunas, Lithuania
| | - Anne Peasey
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
| | - Martin Bobak
- Department of Epidemiology and Public Health, University College London, London, United Kingdom
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Herder C, Kowall B, Tabak AG, Rathmann W. The potential of novel biomarkers to improve risk prediction of type 2 diabetes. Diabetologia 2014; 57:16-29. [PMID: 24078135 DOI: 10.1007/s00125-013-3061-3] [Citation(s) in RCA: 53] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2013] [Accepted: 08/24/2013] [Indexed: 01/05/2023]
Abstract
The incidence of type 2 diabetes can be reduced substantially by implementing preventive measures in high-risk individuals, but this requires prior knowledge of disease risk in the individual. Various diabetes risk models have been designed, and these have all included a similar combination of factors, such as age, sex, obesity, hypertension, lifestyle factors, family history of diabetes and metabolic traits. The accuracy of prediction models is often assessed by the area under the receiver operating characteristic curve (AROC) as a measure of discrimination, but AROCs should be complemented by measures of calibration and reclassification to estimate the incremental value of novel biomarkers. This review discusses the potential of novel biomarkers to improve model accuracy. The range of molecules that serve as potential predictors of type 2 diabetes includes genetic variants, RNA transcripts, peptides and proteins, lipids and small metabolites. Some of these biomarkers lead to a statistically significant increase of model accuracy, but their incremental value currently seems too small for routine clinical use. However, only a fraction of potentially relevant biomarkers have been assessed with regard to their predictive value. Moreover, serial measurements of biomarkers may help determine individual risk. In conclusion, current risk models provide valuable tools of risk estimation, but perform suboptimally in the prediction of individual diabetes risk. Novel biomarkers still fail to have a clinically applicable impact. However, more efficient use of biomarker data and technological advances in their measurement in clinical settings may allow the development of more accurate predictive models in the future.
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Teichert T, Vossoughi M, Vierkötter A, Sugiri D, Schikowski T, Schulte T, Roden M, Luckhaus C, Herder C, Krämer U. Association between traffic-related air pollution, subclinical inflammation and impaired glucose metabolism: results from the SALIA study. PLoS One 2013; 8:e83042. [PMID: 24340078 PMCID: PMC3858363 DOI: 10.1371/journal.pone.0083042] [Citation(s) in RCA: 54] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2013] [Accepted: 11/08/2013] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Environmental and lifestyle factors regulate the expression and release of immune mediators. It has been hypothesised that ambient air pollution may be such an external factor and that the association between air pollution and impaired glucose metabolism may be attributable to inflammatory processes. Therefore, we assessed the associations between air pollution, circulating immune mediators and impaired glucose metabolism. METHODS We analysed concentrations of 14 pro- and anti-inflammatory immune mediators as well as fasting glucose and insulin levels in plasma of 363 women from the Study on the influence of Air pollution on Lung function, Inflammation and Aging (SALIA, Germany). Exposure data for a group of pollutants such as nitrogen oxides (NO2, NOx) and different fractions of particulate matter were available for the participants' residences. We calculated the association between the pollutants and impaired glucose metabolism by multiple regression models. RESULTS The study participants had a mean age of 74.1 (SD 2.6) years and 48% showed impaired glucose metabolism based on impaired fasting glucose or previously diagnosed type 2 diabetes. Only long-term exposure NO2 and NOx concentrations showed positive associations (NO2: OR 1.465, 95% CI 1.049-2.046, NOx: OR 1.409, 95% CI 1.010-1.967) per increased interquartile range of NO2 (14.65 µg/m(3)) or NOx (43.16 µg/m(3)), respectively, but statistical significance was lost after correction for multiple comparisons. Additional adjustment for circulating immune mediators or the use of anti-inflammatory medication had hardly any impact on the observed ORs. CONCLUSIONS Our results suggest that exposure to nitrogen oxides may contribute to impaired glucose metabolism, but the associations did not reach statistical significance so that further studies with larger sample sizes are required to substantiate our findings. Our data do not preclude a role of inflammatory mechanisms in adipose or other tissues which may not be reflected by immune mediators in plasma.
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Affiliation(s)
- Tom Teichert
- Institute of Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Mohammad Vossoughi
- IUF – Leibniz Research Institute for Environmental Medicine at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Andrea Vierkötter
- IUF – Leibniz Research Institute for Environmental Medicine at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Dorothea Sugiri
- IUF – Leibniz Research Institute for Environmental Medicine at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Tamara Schikowski
- IUF – Leibniz Research Institute for Environmental Medicine at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Swiss Tropical and Public Health Institute, Basel, Switzerland
- University of Basel, Basel, Switzerland
| | - Thomas Schulte
- Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Michael Roden
- Institute of Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Department of Endocrinology and Diabetology, University Hospital Düsseldorf, Heinrich Heine University, Düsseldorf, Germany
- German Center for Diabetes Research (DZD e.V.), Düsseldorf, Germany
| | - Christian Luckhaus
- Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Christian Herder
- Institute of Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research (DZD e.V.), Düsseldorf, Germany
- * E-mail:
| | - Ursula Krämer
- IUF – Leibniz Research Institute for Environmental Medicine at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
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Lipoproteínas modificadas como marcadores de riesgo cardiovascular en la diabetes mellitus. ACTA ACUST UNITED AC 2013; 60:518-28. [DOI: 10.1016/j.endonu.2012.12.007] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2012] [Revised: 12/17/2012] [Accepted: 12/19/2012] [Indexed: 11/17/2022]
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Lucas R, Parikh SJ, Sridhar S, Guo DH, Bhagatwala J, Dong Y, Caldwell R, Mellor A, Caldwell W, Zhu H, Dong Y. Cytokine profiling of young overweight and obese female African American adults with prediabetes. Cytokine 2013; 64:310-5. [PMID: 23769592 PMCID: PMC4058336 DOI: 10.1016/j.cyto.2013.05.025] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2012] [Revised: 05/03/2013] [Accepted: 05/24/2013] [Indexed: 02/08/2023]
Abstract
Approximately 5-10% of subjects with prediabetes become diabetic every year. Inflammation is involved in the development of obesity-related type 2 diabetes (T2D). However, to date, the relationship between inflammation and prediabetes, defined by hemoglobin A1c (HbA1c) ≥5.7 and <6.5%, remains largely unexplored, especially in African Americans. Therefore, in this study we examined a comprehensive panel of 13 cytokines involved in the inflammatory response in overweight/obese subjects with prediabetes. A total of 21 otherwise healthy, overweight/obese, young adult African American females with prediabetes, together with 20 matched overweight/obese controls, were selected for this study. Plasma cytokines were assessed by multiplex cytokine profiling. Plasma concentrations of interleukin (IL)-5, IL-6, IL-7, tumor necrosis factor-α (TNF-α), and granulocyte-monocyte colony-stimulating factor (GM-CSF) were significantly higher in the prediabetic group, as compared to the control group (all p<0.05). Plasma concentrations of all the other cytokines, interferon-γ (IFN-γ), IL-1β, IL-2, IL-4, IL-8, IL-10, IL-12p70 and IL-13, seemed to be elevated in the prediabetic group, but failed to reach statistical significances. Upon merging both groups, HbA1c was found to be positively correlated with IFN-γ, IL-1β, IL-2, IL-5, IL-7, IL-8, TNF-α and GM-CSF. This study demonstrates elevated levels of various pro-inflammatory cytokines in overweight/obese young subjects with prediabetes, which place them at higher risk of developing T2D and cardiovascular diseases. Our data also call for further investigations in animal models and population cohorts to establish the roles of a variety of pro-inflammatory cytokines in the early development of obesity-related T2D.
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Affiliation(s)
- Rudolf Lucas
- Vascular Biology Center, Georgia Regents University, Augusta, Georgia
- Department of Pharmacology and Toxicology, Georgia Regents University, Augusta, Georgia
- Division of Pulmonary Medicine, Georgia Regents University, Augusta, Georgia
| | - Samip J. Parikh
- Internal Medicine, Department of Medicine, Georgia Regents University, Augusta, Georgia
- Georgia Prevention Center, Institute for Public and Preventive Health, Department of Pediatrics, Georgia Regents University Augusta, Georgia
| | - Supriya Sridhar
- Vascular Biology Center, Georgia Regents University, Augusta, Georgia
| | - De-Huang Guo
- Georgia Prevention Center, Institute for Public and Preventive Health, Department of Pediatrics, Georgia Regents University Augusta, Georgia
| | - Jigar Bhagatwala
- Internal Medicine, Department of Medicine, Georgia Regents University, Augusta, Georgia
- Georgia Prevention Center, Institute for Public and Preventive Health, Department of Pediatrics, Georgia Regents University Augusta, Georgia
| | - Yutong Dong
- Georgia Prevention Center, Institute for Public and Preventive Health, Department of Pediatrics, Georgia Regents University Augusta, Georgia
| | - Ruth Caldwell
- Vascular Biology Center, Georgia Regents University, Augusta, Georgia
| | - Andrew Mellor
- Immunotherapy Center, Georgia Regents University, Augusta, Georgia
| | - William Caldwell
- Department of Pharmacology and Toxicology, Georgia Regents University, Augusta, Georgia
| | - Haidong Zhu
- Georgia Prevention Center, Institute for Public and Preventive Health, Department of Pediatrics, Georgia Regents University Augusta, Georgia
| | - Yanbin Dong
- Georgia Prevention Center, Institute for Public and Preventive Health, Department of Pediatrics, Georgia Regents University Augusta, Georgia
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Sanderson J, Thompson SG, White IR, Aspelund T, Pennells L. Derivation and assessment of risk prediction models using case-cohort data. BMC Med Res Methodol 2013; 13:113. [PMID: 24034146 PMCID: PMC3848813 DOI: 10.1186/1471-2288-13-113] [Citation(s) in RCA: 265] [Impact Index Per Article: 24.1] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2013] [Accepted: 09/09/2013] [Indexed: 01/01/2023] Open
Abstract
BACKGROUND Case-cohort studies are increasingly used to quantify the association of novel factors with disease risk. Conventional measures of predictive ability need modification for this design. We show how Harrell's C-index, Royston's D, and the category-based and continuous versions of the net reclassification index (NRI) can be adapted. METHODS We simulated full cohort and case-cohort data, with sampling fractions ranging from 1% to 90%, using covariates from a cohort study of coronary heart disease, and two incidence rates. We then compared the accuracy and precision of the proposed risk prediction metrics. RESULTS The C-index and D must be weighted in order to obtain unbiased results. The NRI does not need modification, provided that the relevant non-subcohort cases are excluded from the calculation. The empirical standard errors across simulations were consistent with analytical standard errors for the C-index and D but not for the NRI. Good relative efficiency of the prediction metrics was observed in our examples, provided the sampling fraction was above 40% for the C-index, 60% for D, or 30% for the NRI. Stata code is made available. CONCLUSIONS Case-cohort designs can be used to provide unbiased estimates of the C-index, D measure and NRI.
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Affiliation(s)
- Jean Sanderson
- Department of Public Health and Primary Care, Strangeways Research Laboratory, University of Cambridge, Worts Causeway, Cambridge CB1 8RN, UK.
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Echouffo-Tcheugui JB, Dieffenbach SD, Kengne AP. Added value of novel circulating and genetic biomarkers in type 2 diabetes prediction: a systematic review. Diabetes Res Clin Pract 2013; 101:255-69. [PMID: 23647943 DOI: 10.1016/j.diabres.2013.03.023] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2012] [Revised: 10/13/2012] [Accepted: 03/15/2013] [Indexed: 02/02/2023]
Abstract
AIMS To provide a systematic overview of the added value of novel circulating and genetic biomarkers in predicting type 2 diabetes (T2DM). METHODS We searched MEDLINE and EMBASE (January 2000 to September 2012) for studies that reported a measure of improvement in the performance of T2DM risk prediction models subsequent to adding novel biomarkers to traditional risk factors. We extracted data on study methods and metrics of incremental predictive value of novel biomarkers. RESULTS We included 34 publications from 30 studies. All studies reported a change in the area under the receiver-operating characteristic curve, which was modest, ranging from -0.004 to 0.1, with claims of statistically significant improvements in eleven studies. The net reclassification index was evaluated in 11 studies, and ranged from -2.2% to 10.2% after inclusion of genetic markers in six studies (statistically significant in two cases), and from -0.5% to 27.5% after inclusion of non-genetic markers in five studies (non-significant in two studies). The integrated discrimination index (0-2.04) was reported in eight studies, being statistically significant in five of these. CONCLUSIONS Currently known novel circulating and genetic biomarkers do not substantially improve T2DM risk prediction above and beyond the ability of traditional risk factors.
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Affiliation(s)
- Justin B Echouffo-Tcheugui
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, 1518 Clifton Road, Northeast Atlanta, GA 30322, USA.
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Kanhai DA, Kranendonk ME, Uiterwaal CSPM, van der Graaf Y, Kappelle LJ, Visseren FLJ. Adiponectin and incident coronary heart disease and stroke. A systematic review and meta-analysis of prospective studies. Obes Rev 2013; 14:555-67. [PMID: 23495931 DOI: 10.1111/obr.12027] [Citation(s) in RCA: 55] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2012] [Revised: 01/30/2013] [Accepted: 01/31/2013] [Indexed: 12/15/2022]
Abstract
The plasma concentration of adiponectin, an adipokine that has anti-inflammatory, anti-atherogenic and insulin sensitizing properties, is lower in obese subjects and could therefore be a target for therapy. In order to review and meta-analyse prospective cohort studies investigating adiponectin concentration and the risk for incident coronary heart disease (CHD) or stroke, a systematic search of MEDLINE, EMBASE and Cochrane databases was performed. Two independent reviewers selected prospective cohort studies investigating the relationship between adiponectin level and incident CHD or stroke using 'adiponectin' and 'cardiovascular disease' or 'stroke' and their synonyms, excluding patients with clinically manifest vascular disease. Random-effects models were used to calculate pooled relative risks (RRs) and 95% confidence intervals (95% CI). Generalized least squares regression was used to assess dose-response relationships for adiponectin concentrations from studies that provided RRs solely based upon categorical data regression. In total, 16 prospective cohort studies, comprising 23,919 patients and 6,870 CHD or stroke outcome events, were included in the meta-analyses. An increase of 1 standard deviation in log-transformed adiponectin did not lower the risk for CHD (RR 0.97; 95% CI 0.86-1.09). A 10 μg mL(-1) increase in adiponectin conferred a RR of 0.91 (95% CI 0.80-1.03) for CHD and a RR 1.01 (95% CI 0.97-1.06) for stroke. In conclusion, plasma adiponectin is not related to the risk for incident CHD or stroke.
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Affiliation(s)
- D A Kanhai
- Department of Vascular Medicine, University Medical Center Utrecht (UMC Utrecht), Utrecht, The Netherlands
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The prevalence of latent Mycobacterium tuberculosis infection based on an interferon-γ release assay: a cross-sectional survey among urban adults in Mwanza, Tanzania. PLoS One 2013; 8:e64008. [PMID: 23700446 PMCID: PMC3660306 DOI: 10.1371/journal.pone.0064008] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2013] [Accepted: 04/08/2013] [Indexed: 11/19/2022] Open
Abstract
INTRODUCTION One third of the world's population is estimated to be latently infected with Mycobacterium tuberculosis (LTBI). Surveys of LTBI are rarely performed in resource poor TB high endemic countries like Tanzania although low-income countries harbor the largest burden of the worlds LTBI. The primary objective was to estimate the prevalence of LTBI in household contacts of pulmonary TB cases and a group of apparently healthy neighborhood controls in an urban setting of such a country. Secondly we assessed potential impact of LTBI on inflammation by quantitating circulating levels of an acute phase reactant: alpha-1-acid glycoprotein (AGP) in neighborhood controls. METHODS The study was nested within the framework of two nutrition studies among TB patients in Mwanza, Tanzania. Household contacts- and neighborhood controls were invited to participate. The study involved a questionnaire, BMI determination and blood samples to measure AGP, HIV testing and a Quantiferon Gold In tube (QFN-IT) test to detect signs of LTBI. RESULTS 245 household contacts and 192 neighborhood controls had available QFN-IT data. Among household contacts, the proportion of QFT-IT positive was 59% compared to 41% in the neighborhood controls (p = 0.001). In a linear regression model adjusted for sex, age, CD4 and HIV, a QFT-IT positive test was associated with a 10% higher level of alpha-1-acid glycoprotein(AGP) (10(B) 1.10, 95% CI 1.01; 1.20, p = 0.03), compared to individuals with a QFT-IT negative test. CONCLUSION LTBI is highly prevalent among apparently healthy urban Tanzanians even without known exposure to TB in the household. LTBI was found to be associated with elevated levels of AGP. The implications of this observation merit further studies.
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Job strain-associated inflammatory burden and long-term risk of coronary events: findings from the MONICA/KORA Augsburg case-cohort study. Psychosom Med 2013; 75:317-25. [PMID: 23460721 DOI: 10.1097/psy.0b013e3182860d63] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
BACKGROUND We examined the association between job strain and coronary heart disease (CHD) and investigated the role of markers of inflammation and endothelial dysfunction as possible mediators of job strain-associated CHD risk. METHODS The sample (n = 1027) included employed participants (35-64 years old, 68% male) from the population-based MONICA/KORA (Monitoring of Trends and Determinants in Cardiovascular Disease/Kooperative Gesundheitsforschung in der Region Augsburg) studies. At baseline Karasek's Job Strain Index was assessed during standardized personal interviews, and nine biological markers were measured (1984-1995). Participants were followed (average, 12 years) to assess incident events (sudden cardiac death or fatal and nonfatal myocardial infarction). In this case-cohort design, the final sample contained 114 cases and 913 noncases. RESULTS Baseline distributions of cardiometabolic risk factors were significantly different between cases and noncases, with no detectable job strain-specific differences. However, cases with high job strain had higher monocyte chemoattractant protein-1, interleukin (IL)-8, and IL-18 compared with noncases with high job strain. High-sensitivity C-reactive protein, IL-6, and soluble intercellular adhesion molecule-1 were increased in cases versus noncases, regardless of work stress. Job strain was associated with incident coronary events in Cox proportional hazards models adjusted for age, sex, and survey (hazard ratio = 2.57, 95% confidence interval = 1.09-6.07) and after adjustment for CHD risk factors (2.35, 1.003-5.49). Adjustment for monocyte chemoattractant protein-1 or IL-8 increased this risk estimate by 14.5% or 9.4%, respectively, whereas adjustment for C-reactive protein and soluble intercellular adhesion molecule-1 led to decreased hazard ratios (-9.9% and -5.5%, respectively). CONCLUSIONS Job strain increased CHD risk in healthy workers; the associated inflammatory burden may contribute to stress-related coronary pathogenesis.
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Rubio-Martín E, Soriguer F, Gutiérrez-Repiso C, Garrido-Sánchez L, de Adana MSR, García-Fuentes E, Morcillo S, Esteva I, Chaves FJ, Rojo-Martinez G. C-reactive protein and incidence of type 2 diabetes in the Pizarra study. Eur J Clin Invest 2013; 43:159-67. [PMID: 23278315 DOI: 10.1111/eci.12027] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/16/2012] [Accepted: 11/13/2012] [Indexed: 12/11/2022]
Abstract
AIM To determine the association between serum levels of high-sensitivity C-reactive protein (hs-CRP) and the incidence of type 2 diabetes in a prospective cohort from southern Spain (Pizarra study). MATERIALS AND METHODS The study formed part of the Pizarra cohort study, a prospective study started in 1995 with a follow-up of 11 years. Anthropometric and metabolic variables were measured at baseline and at 6 years and 11 years of follow-up. All subjects underwent an oral glucose tolerance test. Serum levels of TNFα and its receptors, hs-CRP, IL-6, leptin, adiponectin and FABP4 were measured at 6 years of follow-up. RESULTS After adjusting for age, sex and obesity, subjects with levels of hs-CRP> 2.9 mg/L in the second study (2003-4) had a higher risk of developing type 2 diabetes by the third study (2008-9) (OR = 7.97; 95% CI = 1.72-36.89; P = 0.008), and subjects with adiponectin levels > 13.2 mg/L had a lower risk of developing type 2 diabetes (OR = 0.23, P = 0.02). High values of hs-CRP and high values of adiponectin were associated positively (OR = 8.26; 95% CI = 1.84-37.19; P = 0.006) and negatively (OR = 0.17; 95% CI = 0.04-0.69; P = 0.01), respectively, with the risk of having HbA1c ≥ 6.5% at 11 years of follow-up. CONCLUSIONS Subjects with high serum hs-CRP levels and low serum adiponectin levels have a higher risk of developing type 2 diabetes within five years.
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Affiliation(s)
- Elehazara Rubio-Martín
- Department of Endocrinology and Nutrition, Hospital Universitario Carlos Haya, Málaga, Spain.
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Floegel A, Stefan N, Yu Z, Mühlenbruch K, Drogan D, Joost HG, Fritsche A, Häring HU, Hrabě de Angelis M, Peters A, Roden M, Prehn C, Wang-Sattler R, Illig T, Schulze MB, Adamski J, Boeing H, Pischon T. Identification of serum metabolites associated with risk of type 2 diabetes using a targeted metabolomic approach. Diabetes 2013; 62:639-48. [PMID: 23043162 PMCID: PMC3554384 DOI: 10.2337/db12-0495] [Citation(s) in RCA: 733] [Impact Index Per Article: 66.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Metabolomic discovery of biomarkers of type 2 diabetes (T2D) risk may reveal etiological pathways and help to identify individuals at risk for disease. We prospectively investigated the association between serum metabolites measured by targeted metabolomics and risk of T2D in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam (27,548 adults) among all incident cases of T2D (n = 800, mean follow-up 7 years) and a randomly drawn subcohort (n = 2,282). Flow injection analysis tandem mass spectrometry was used to quantify 163 metabolites, including acylcarnitines, amino acids, hexose, and phospholipids, in baseline serum samples. Serum hexose; phenylalanine; and diacyl-phosphatidylcholines C32:1, C36:1, C38:3, and C40:5 were independently associated with increased risk of T2D and serum glycine; sphingomyelin C16:1; acyl-alkyl-phosphatidylcholines C34:3, C40:6, C42:5, C44:4, and C44:5; and lysophosphatidylcholine C18:2 with decreased risk. Variance of the metabolites was largely explained by two metabolite factors with opposing risk associations (factor 1 relative risk in extreme quintiles 0.31 [95% CI 0.21-0.44], factor 2 3.82 [2.64-5.52]). The metabolites significantly improved T2D prediction compared with established risk factors. They were further linked to insulin sensitivity and secretion in the Tübingen Family study and were partly replicated in the independent KORA (Cooperative Health Research in the Region of Augsburg) cohort. The data indicate that metabolic alterations, including sugar metabolites, amino acids, and choline-containing phospholipids, are associated early on with a higher risk of T2D.
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Affiliation(s)
- Anna Floegel
- Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany.
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Twig G, Afek A, Shamiss A, Derazne E, Tzur D, Gordon B, Tirosh A. White blood cells count and incidence of type 2 diabetes in young men. Diabetes Care 2013; 36:276-82. [PMID: 22961572 PMCID: PMC3554323 DOI: 10.2337/dc11-2298] [Citation(s) in RCA: 92] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
OBJECTIVE Association between white blood cell (WBC) count and diabetes risk has been recently suggested. We assessed whether WBC count is an independent risk factor for diabetes incidence among young healthy adults. RESEARCH DESIGN AND METHODS WBC count was measured in 24,897 young (mean age 30.8 ± 5.36 years), normoglycemic men with WBC range of 3,000 to 12,000 cells/mm(3). Participants were periodically screened for diabetes during a mean follow-up of 7.5 years. RESULTS During 185,354 person-years of follow-up, diabetes was diagnosed in 447 subjects. A multivariate model adjusted for age, BMI, family history of diabetes, physical activity, and fasting glucose and triglyceride levels revealed a 7.6% increase in incident diabetes for every increment of 1,000 cells/mm(3) (P = 0.046). When grouped in quintiles, a baseline WBC count above 6,900 cells/mm(3) had an independent 52% increase in diabetes risk (hazard ratio 1.52 [95% CI 1.06-2.18]) compared with the lowest quintile (WBC <5,400 cells/mm(3)). Men at the lowest WBC quintile were protected from diabetes incidence even in the presence of overweight, family history of diabetes, or elevated triglyceride levels. After simultaneous control for risk factors, BMI was the primary contributor of the variation in multivariate models (P < 0.001), followed by age and WBC count (P < 0.001), and family history of diabetes and triglyceride levels (P = 0.12). CONCLUSIONS WBC count, a commonly used and widely available test, is an independent risk factor for diabetes in young men at values well within the normal range.
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Affiliation(s)
- Gilad Twig
- Department of Medicine “B,” Chaim Sheba Medical Center, Tel-Hashomer, Israel
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