Effect of three consecutive meals on the physicochemical properties of HDL and LDL in individuals with the metabolic syndrome and patients with type 2 diabetes

Scheffer, P; Tushuizen, Maarten E.; Vermue, Hendrikus P.A.; Schindhelm, Roger K.; Rustemeijer, Cees; Diamant, Michaëla

doi:10.1038/ejcn.2011.114

Cited by 9 publications

(11 citation statements)

References 31 publications

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“…Our reported metabolic differences in response to a high-fat challenge between MetS and healthy subjects are in line with what is known from the literature (5,7,(22)(23)(24)(25)(26)(27)(28). Our finding that MetS subjects showed a differential response of the inflammatory markers IL-6, IL-18, 11,12-DiHETrE, and 19,20-DiHoPE to a high-fat challenge as compared to healthy subjects ( Fig.…”

Section: Healthy Subjects Vs Mets Subjectssupporting

confidence: 82%

Quantifying phenotypic flexibility as the response to a high‐fat challenge test in different states of metabolic health

et al. 2015

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Metabolism maintains homeostasis at chronic hypercaloric conditions, activating postprandial response mechanisms, which come at the cost of adaptation processes such as energy storage, eventually with negative health consequences. This study quantified the metabolic adaptation capacity by studying challenge response curves. After a high-fat challenge, the 8 h response curves of 61 biomarkers related to adipose tissue mass and function, systemic stress, metabolic flexibility, vascular health, and glucose metabolism was compared between 3 metabolic health stages: 10 healthy men, before and after 4 wk of highfat, high-calorie diet (1300 kcal/d extra), and 9 men with metabolic syndrome (MetS). The MetS subjects had increased fasting concentrations of biomarkers representing the 3 core processes, glucose, TG, and inflammation control, and the challenge response curves of most biomarkers were altered. After the 4 wk hypercaloric dietary intervention, these 3 processes were not changed, as compared with the preintervention state in the healthy subjects, whereas the challenge response curves of almost all endocrine, metabolic, and inflammatory processes regulating these core processes were altered, demonstrating major molecular physiologic efforts to maintain homeostasis. This study thus demonstrates that change in challenge response is a more sensitive biomarker of metabolic resilience than are changes in fasting concentrations.-Kardinaal, A. F. M., van Erk, M. J., Dutman, A. E., Stroeve, J. H. M., van de Steeg, E., Bijlsma, S., Kooistra, T., van Ommen, B., Wopereis, S. Quantifying phenotypic flexibility as the response to a highfat challenge test in different states of metabolic health. FASEB J. 29, 4600-4613 (2015). www.fasebj.org

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Section: Healthy Subjects Vs Mets Subjectssupporting

confidence: 82%

Quantifying phenotypic flexibility as the response to a high‐fat challenge test in different states of metabolic health

et al. 2015

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“…The OPGLTT induces expected responses in plasma glucose (Ramos-Roman et al 2012 ; Scheffer et al 2011 ), triglyceride (Casas-Agustench et al 2009 ; Esposito et al 2003 ; Krug et al 2012 ; Scheffer et al 2011 ; Zwirska-Korczala et al 2007 ) and amino acid concentrations (Pellis et al 2012 ). Plasma glucose response similar to an OGTT was observed, inducing an insulin response that was prolonged in comparison with the glucose response (Casas-Agustench et al 2009 ).…”

Section: Introductionmentioning

confidence: 99%

“…Hepatic lipoprotein production markers related to cholesterol transport showed inconsistent responses to an OPGLTT. Some studies report increased postprandial total cholesterol and low-density lipoprotein cholesterol (LDLc) levels (Saxena et al 2005 ; Scheffer et al 2011 ), and decreased postprandial HDLc levels (Coutinho et al 2008 ; Scheffer et al 2011 ; Thomsen et al 2003 ), and one study reported increased postprandial HDLc concentrations (Saxena et al 2005 ). Most studies report stable LDLc (Coutinho et al 2008 ; Derosa et al 2010 ; Esposito et al 2003 ; Iraklianou et al 2001 ; Saxena et al 2005 ; Wopereis et al 2013 ), HDLc (Esposito et al 2003 ; Iraklianou et al 2001 ; Wopereis et al 2013 ) and total cholesterol concentrations (Coutinho et al 2008 ; Esposito et al 2003 ; Thomsen et al 2003 ; Wopereis et al 2013 ).…”

Section: Introductionmentioning

confidence: 99%

Phenotypic flexibility as a measure of health: the optimal nutritional stress response test

Stroeve¹,

Wietmarschen²,

Kremer³

et al. 2015

Genes Nutr

114

110

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Nutrition research is struggling to demonstrate beneficial health effects, since nutritional effects are often subtle and long term. Health has been redefined as the ability of our body to cope with daily-life challenges. Physiology acts as a well-orchestrated machinery to adapt to the continuously changing environment. We term this adaptive capacity “phenotypic flexibility.” The phenotypic flexibility concept implies that health can be measured by the ability to adapt to conditions of temporary stress, such as physical exercise, infections or mental stress, in a healthy manner. This may offer a more sensitive way to assess changes in health status of healthy subjects. Here, we performed a systematic review of 61 studies applying different nutritional stress tests to quantify health and nutritional health effects, with the objective to define an optimal nutritional stress test that has the potential to be adopted as the golden standard in nutrition research. To acknowledge the multi-target role of nutrition, a relevant subset of 50 processes that govern optimal health, with high relevance to diet, was used to define phenotypic flexibility. Subsequently, we assessed the response of biomarkers related to this subset of processes to the different challenge tests. Based on the obtained insights, we propose a nutritional stress test composed of a high-fat, high-caloric drink, containing 60 g palm olein, 75 g glucose and 20 g dairy protein in a total volume of 400 ml. The use of such a standardized nutritional challenge test in intervention studies is expected to demonstrate subtle improvements of phenotypic flexibility, thereby enabling substantiation of nutritional health effects.Electronic supplementary materialThe online version of this article (doi:10.1007/s12263-015-0459-1) contains supplementary material, which is available to authorized users.

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“…We have demonstrated increased oxidisablity of LDL in both hypercholesterolaemic and normocholesterolaemic diabetic patients [58]. Patients with diabetes and metabolic syndrome have both a preponderance of small dense LDL and the increase in the polyunsaturated fatty acids in the particle, hence many important mechanisms that promote the atherogenicity of LDL in hyperglycaemia [59,60].…”

Section: Free Fatty Acidsmentioning

confidence: 99%

LDL as a Cause of Atherosclerosis

Tomkin

Owens²

2012

TOATHERTJ

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The low density lipoprotein particle is the major transporter of cholesterol around the body and has been shown to be a strong independent risk factor for atherosclerotic events. This review discusses the normal and abnormal metabolism of low density lipoprotein (LDL). Mechanisms by which LDL causes atherosclerosis are discussed with particular reference to the importance of alteration in LDL composition including attachment of other proteins to the circulating LDL particle.

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Effect of three consecutive meals on the physicochemical properties of HDL and LDL in individuals with the metabolic syndrome and patients with type 2 diabetes

Cited by 9 publications

References 31 publications

Quantifying phenotypic flexibility as the response to a high‐fat challenge test in different states of metabolic health

Quantifying phenotypic flexibility as the response to a high‐fat challenge test in different states of metabolic health

Phenotypic flexibility as a measure of health: the optimal nutritional stress response test

LDL as a Cause of Atherosclerosis

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