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      Diabetes risk and amino acid profiles: cross-sectional and prospective analyses of ethnicity, amino acids and diabetes in a South Asian and European cohort from the SABRE (Southall And Brent REvisited) Study

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          Abstract

          Aims/hypothesis

          South Asian individuals have an increased risk of diabetes compared with Europeans that is unexplained by obesity and traditional or established metabolic measures. Circulating amino acids (AAs) may provide additional explanatory insights. In a unique cohort of European and South Asian men, we compared cross-sectional associations between AAs, metabolic and obesity traits, and longitudinal associations with incident diabetes.

          Methods

          Nuclear magnetic spectroscopy was used to measure the baseline (1988–1991) levels of nine AAs in serum samples from a British population-based cohort of 1,279 European and 1,007 South Asian non-diabetic men aged 40–69 years. Follow-up was complete for 19 years in 801 European and 643 South Asian participants.

          Results

          The serum concentrations of isoleucine, phenylalanine, tyrosine and alanine were significantly higher in South Asian men, while cross-sectional correlations of AAs with glycaemia and insulin resistance were similar in the two ethnic groups. However, most AAs were less strongly correlated with measures of obesity in the South Asian participants. Diabetes developed in 227 (35%) South Asian and 113 (14%) European men. Stronger adverse associations were observed between branched chain and aromatic AAs and incident diabetes in South Asian men. Tyrosine was a particularly strong predictor of incident diabetes in South Asian individuals, even after adjustment for metabolic risk factors, including obesity and insulin resistance (adjusted OR for a 1 SD increment, 1.47, 95% CI 1.17,1.85, p = 0.001) compared with Europeans (OR 1.10, 0.87, 1.39, p = 0.4; p = 0.045 for ethnicity × tyrosine interaction).

          Conclusions/interpretation

          Branched chain and aromatic AAs, particularly tyrosine, may be a focus for identifying novel aetiological mechanisms and potential treatment targets for diabetes in South Asian populations and may contribute to their excess risk of diabetes.

          Electronic supplementary material

          The online version of this article (doi:10.1007/s00125-015-3517-8) contains peer-reviewed but unedited supplementary material, which is available to authorised users.

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          Most cited references43

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          A Proportional Hazards Model for the Subdistribution of a Competing Risk

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            Insulin sensitivity indices obtained from oral glucose tolerance testing: comparison with the euglycemic insulin clamp.

            Several methods have been proposed to evaluate insulin sensitivity from the data obtained from the oral glucose tolerance test (OGTT). However, the validity of these indices has not been rigorously evaluated by comparing them with the direct measurement of insulin sensitivity obtained with the euglycemic insulin clamp technique. In this study, we compare various insulin sensitivity indices derived from the OGTT with whole-body insulin sensitivity measured by the euglycemic insulin clamp technique. In this study, 153 subjects (66 men and 87 women, aged 18-71 years, BMI 20-65 kg/m2) with varying degrees of glucose tolerance (62 subjects with normal glucose tolerance, 31 subjects with impaired glucose tolerance, and 60 subjects with type 2 diabetes) were studied. After a 10-h overnight fast, all subjects underwent, in random order, a 75-g OGTT and a euglycemic insulin clamp, which was performed with the infusion of [3-3H]glucose. The indices of insulin sensitivity derived from OGTT data and the euglycemic insulin clamp were compared by correlation analysis. The mean plasma glucose concentration divided by the mean plasma insulin concentration during the OGTT displayed no correlation with the rate of whole-body glucose disposal during the euglycemic insulin clamp (r = -0.02, NS). From the OGTT, we developed an index of whole-body insulin sensitivity (10,000/square root of [fasting glucose x fasting insulin] x [mean glucose x mean insulin during OGTT]), which is highly correlated (r = 0.73, P < 0.0001) with the rate of whole-body glucose disposal during the euglycemic insulin clamp. Previous methods used to derive an index of insulin sensitivity from the OGTT have relied on the ratio of plasma glucose to insulin concentration during the OGTT. Our results demonstrate the limitations of such an approach. We have derived a novel estimate of insulin sensitivity that is simple to calculate and provides a reasonable approximation of whole-body insulin sensitivity from the OGTT.
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              Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond.

              Identification of key factors associated with the risk of developing cardiovascular disease and quantification of this risk using multivariable prediction algorithms are among the major advances made in preventive cardiology and cardiovascular epidemiology in the 20th century. The ongoing discovery of new risk markers by scientists presents opportunities and challenges for statisticians and clinicians to evaluate these biomarkers and to develop new risk formulations that incorporate them. One of the key questions is how best to assess and quantify the improvement in risk prediction offered by these new models. Demonstration of a statistically significant association of a new biomarker with cardiovascular risk is not enough. Some researchers have advanced that the improvement in the area under the receiver-operating-characteristic curve (AUC) should be the main criterion, whereas others argue that better measures of performance of prediction models are needed. In this paper, we address this question by introducing two new measures, one based on integrated sensitivity and specificity and the other on reclassification tables. These new measures offer incremental information over the AUC. We discuss the properties of these new measures and contrast them with the AUC. We also develop simple asymptotic tests of significance. We illustrate the use of these measures with an example from the Framingham Heart Study. We propose that scientists consider these types of measures in addition to the AUC when assessing the performance of newer biomarkers.
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                Author and article information

                Contributors
                t.tillin@ucl.ac.uk
                Journal
                Diabetologia
                Diabetologia
                Diabetologia
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                0012-186X
                1432-0428
                19 February 2015
                19 February 2015
                2015
                : 58
                : 5
                : 968-979
                Affiliations
                [ ]UCL Institute of Cardiovascular Science, 170 Tottenham Court Road, London, W1T 7HA UK
                [ ]Computational Medicine, Institute of Health Sciences, University of Oulu, Oulu, Finland
                [ ]NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland
                [ ]Oulu University Hospital, Oulu, Finland
                [ ]Computational Medicine, School of Social and Community Medicine and the Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
                [ ]Institute of Cardiovascular and Medical Sciences, University of Glasgow School of Medicine, Glasgow, UK
                [ ]MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge, UK
                [ ]Endocrinology and Medicine, Department of Medicine, Imperial College London, London, UK
                [ ]Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK
                Article
                3517
                10.1007/s00125-015-3517-8
                4392114
                25693751
                89f495fd-9554-44c6-9d39-2a50bc849925
                © The Author(s) 2015

                Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.

                History
                : 7 November 2014
                : 15 January 2015
                Categories
                Article
                Custom metadata
                © Springer-Verlag Berlin Heidelberg 2015

                Endocrinology & Diabetes
                amino acids,cohort,diabetes,ethnicity,european,south asian
                Endocrinology & Diabetes
                amino acids, cohort, diabetes, ethnicity, european, south asian

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