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      Hepatic insulin resistance both in prediabetic and diabetic patients determines postprandial lipoprotein metabolism: from the CORDIOPREV study

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          Abstract

          Background/aims

          Previous evidences have shown the presence of a prolonged and exaggerated postprandial response in type 2 diabetes mellitus (T2DM) and its relation with an increase of cardiovascular risk. However, the response in prediabetes population has not been established. The objective was to analyze the degree of postprandial lipemia response in the CORDIOPREV clinical trial (NCT00924937) according to the diabetic status.

          Methods

          1002 patients were submitted to an oral fat load test meal (OFTT) with 0.7 g fat/kg body weight [12 % saturated fatty acids (SFA), 10 % polyunsaturated fatty acids (PUFA), 43 % monounsaturated fatty acids (MUFA), 10 % protein and 25 % carbohydrates]. Serial blood test analyzing lipid fractions were drawn at 0, 1, 2, 3 and 4 h during postprandial state. Postprandial triglycerides (TG) concentration at any point >2.5 mmol/L (220 mg/dL) has been established as undesirable response. We explored the dynamic response in 57 non-diabetic, 364 prediabetic and 581 type 2 diabetic patients. Additionally, the postprandial response was evaluated according to basal insulin resistance subgroups in patients non-diabetic and diabetic without pharmacological treatment (N = 642).

          Results

          Prevalence of undesirable postprandial TG was 35 % in non-diabetic, 48 % in prediabetic and 59 % in diabetic subgroup, respectively (p < 0.001). Interestingly, prediabetic patients displayed higher plasma TG and large triacylglycerol-rich lipoproteins (TRLs-TG) postprandial response compared with those non-diabetic patients (p < 0.001 and p = 0.003 respectively). Moreover, the area under the curve (AUC) of TG and AUC of TRLs-TG was greater in the prediabetic group compared with non-diabetic patients (p < 0.001 and p < 0.005 respectively). Patients with liver insulin resistance (liver-IR) showed higher postprandial response of TG compared with those patients with muscle-IR or without any insulin-resistance respectively (p < 0.001).

          Conclusions

          Our findings demonstrate that prediabetic patients show a lower phenotypic flexibility after external aggression, such as OFTT compared with nondiabetic patients. The postprandial response increases progressively according to non-diabetic, prediabetic and type 2 diabetic state and it is higher in patients with liver insulin-resistance. To identify this subgroup of patients is important to treat more intensively in order to avoid future cardiometabolic complications.

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          Most cited references28

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          New insights into the pathophysiology of dyslipidemia in type 2 diabetes.

          Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality for patients with type 2 diabetes, despite recent significant advances in management strategies to lessen CVD risk factors. A major cause is the atherogenic dyslipidemia, which consists of elevated plasma concentrations of both fasting and postprandial triglyceride-rich lipoproteins (TRLs), small dense low-density lipoprotein (LDL) and low high-density lipoprotein (HDL) cholesterol. The different components of diabetic dyslipidemia are not isolated abnormalities but closely linked to each other metabolically. The underlying disturbances are hepatic overproduction and delayed clearance of TRLs. Recent results have unequivocally shown that triglyceride-rich lipoproteins and their remnants are atherogenic. To develop novel strategies for the prevention and treatment of dyslipidaemia, it is essential to understand the pathophysiology of dyslipoproteinaemia in humans. Here, we review recent advances in our understanding of the pathophysiology of diabetic dyslipidemia.
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            Challenging homeostasis to define biomarkers for nutrition related health.

            A primary goal of nutrition research is to optimize health and prevent or delay disease. Biomarkers to quantify health optimization are needed since many if not most biomarkers are developed for diseases. Quantifying "normal homeostasis" and developing validated biomarkers are formidable tasks because of the robustness of homeostasis and of inter-individual diversity. In this paper, we discuss the science, strategies, and technologies for measuring parameters that define individual health. The following concepts are central to define the physiology of the healthy individual: (i) responses to a challenge of homeostasis will be more informative than static homeostatic measures; (ii) processes involved in maintaining homeostasis usually are multi-factorial and require quantitative analyses of the many individual components involved; (iii) health includes a large variation in "normality" and the effects of nutritional interventions may remain hidden in this "diversity of robustness," if incompletely analyzed. Specifically, comprehensive multi-parameter ("omics") analysis may identify key parameters (biomarkers) and lead to a greater understanding of health supporting processes. Perturbation tests that accurately target aspects of the overarching drivers of health (metabolism, oxidation, inflammation, and psychological stress) may be instrumental in creating knowledge for maintaining health and preventing disease through nutrition.
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              Raised Circulating Fetuin-A After 28-Day Overfeeding in Healthy Humans: Figure 1

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                Author and article information

                Contributors
                analeoaa@hotmail.com
                jfalcala@gmail.com
                delgadolista@gmail.com
                azarel_00@hotmail.com
                javi_lopez1988@hotmail.com
                acamargo.bqm@gmail.com
                angarios2004@yahoo.es
                cmhinojo@yahoo.es
                jimynaceo@hotmail.com
                javier.caballero.ext@juntadeandalucia.es
                ben.vanommen@tno.nl
                b1mapom@uco.es
                pablopermar@yahoo.es
                jlopezmir@gmail.com
                Journal
                Cardiovasc Diabetol
                Cardiovasc Diabetol
                Cardiovascular Diabetology
                BioMed Central (London )
                1475-2840
                19 April 2016
                19 April 2016
                2016
                : 15
                : 68
                Affiliations
                [ ]Lipid and Atherosclerosis Unit, IMIBIC/Reina Sofia University Hospital/University of Cordoba, Cordoba, Spain
                [ ]CIBER Fisiopatologia Obesidad y Nutricion (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
                [ ]Biochemical Laboratory, Hospital Universitario Reina Sofia, Cordoba, Spain
                [ ]TNO, Zeist, The Netherlands
                [ ]Department of Cell Biology, Physiology, and Immunology, IMIBIC/Reina Sofia University Hospital/University of Cordoba, Cordoba, Spain
                Article
                380
                10.1186/s12933-016-0380-y
                4837552
                27095446
                bc252e16-1bc1-43e4-b783-567ecd324457
                © Leon-Acuña et al. 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 14 January 2016
                : 30 March 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100004837, Ministerio de Ciencia e Innovación;
                Categories
                Original Investigation
                Custom metadata
                © The Author(s) 2016

                Endocrinology & Diabetes
                phenotypic flexibility,triglycerides,postprandial lipemia,prediabetic,cordioprev study,insulin resistance

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