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Saliva samples as a tool to study the effect of meal timing on metabolic and inflammatory biomarkers
(2020)
Meal timing affects metabolic regulation in humans. Most studies use blood samples fortheir investigations. Saliva, although easily available and non-invasive, seems to be rarely used forchrononutritional studies. In this pilot study, we tested if saliva samples could be used to studythe effect of timing of carbohydrate and fat intake on metabolic rhythms. In this cross-over trial, 29 nonobese men were randomized to two isocaloric 4-week diets: (1) carbohydrate-rich meals until13:30 and high-fat meals between 16:30 and 22:00 or (2) the inverse order of meals. Stimulated salivasamples were collected every 4 h for 24 h at the end of each intervention, and levels of hormones andinflammatory biomarkers were assessed in saliva and blood. Cortisol, melatonin, resistin, adiponectin, interleukin-6 and MCP-1 demonstrated distinct diurnal variations, mirroring daytime reports inblood and showing significant correlations with blood levels. The rhythm patterns were similar forboth diets, indicating that timing of carbohydrate and fat intake has a minimal effect on metabolicand inflammatory biomarkers in saliva. Our study revealed that saliva is a promising tool for thenon-invasive assessment of metabolic rhythms in chrononutritional studies, but standardisation of sample collection is needed in out-of-lab studies.
Saliva samples as a tool to study the effect of meal timing on metabolic and inflammatory biomarkers
(2020)
Meal timing affects metabolic regulation in humans. Most studies use blood samples fortheir investigations. Saliva, although easily available and non-invasive, seems to be rarely used forchrononutritional studies. In this pilot study, we tested if saliva samples could be used to studythe effect of timing of carbohydrate and fat intake on metabolic rhythms. In this cross-over trial, 29 nonobese men were randomized to two isocaloric 4-week diets: (1) carbohydrate-rich meals until13:30 and high-fat meals between 16:30 and 22:00 or (2) the inverse order of meals. Stimulated salivasamples were collected every 4 h for 24 h at the end of each intervention, and levels of hormones andinflammatory biomarkers were assessed in saliva and blood. Cortisol, melatonin, resistin, adiponectin, interleukin-6 and MCP-1 demonstrated distinct diurnal variations, mirroring daytime reports inblood and showing significant correlations with blood levels. The rhythm patterns were similar forboth diets, indicating that timing of carbohydrate and fat intake has a minimal effect on metabolicand inflammatory biomarkers in saliva. Our study revealed that saliva is a promising tool for thenon-invasive assessment of metabolic rhythms in chrononutritional studies, but standardisation of sample collection is needed in out-of-lab studies.
Reduced expression of the Indy ("I am Not Dead, Yet") gene in lower organisms promotes longevity in a manner akin to caloric restriction. Deletion of the mammalian homolog of Indy (mIndy, Slc13a5) encoding for a plasma membrane-associated citrate transporter expressed highly in the liver, protects mice from high-fat diet-induced and aging-induced obesity and hepatic fat accumulation through a mechanism resembling caloric restriction. We studied a possible role of mIndy in human hepatic fat metabolism. In obese, insulin-resistant patients with nonalcoholic fatty liver disease, hepatic mIndy expression was increased and mIndy expression was also independently associated with hepatic steatosis. In nonhuman primates, a 2-year high-fat, high-sucrose diet increased hepatic mIndy expression. Liver microarray analysis showed that high mIndy expression was associated with pathways involved in hepatic lipid metabolism and immunological processes. Interleukin-6 (IL-6) was identified as a regulator of mIndy by binding to its cognate receptor. Studies in human primary hepatocytes confirmed that IL-6 markedly induced mIndy transcription through the IL-6 receptor and activation of the transcription factor signal transducer and activator of transcription 3, and a putative start site of the human mIndy promoter was determined. Activation of the IL-6-signal transducer and activator of transcription 3 pathway stimulated mIndy expression, enhanced cytoplasmic citrate influx, and augmented hepatic lipogenesis in vivo. In contrast, deletion of mIndy completely prevented the stimulating effect of IL-6 on citrate uptake and reduced hepatic lipogenesis. These data show that mIndy is increased in liver of obese humans and nonhuman primates with NALFD. Moreover, our data identify mIndy as a target gene of IL-6 and determine novel functions of IL-6 through mINDY. Conclusion: Targeting human mINDY may have therapeutic potential in obese patients with nonalcoholic fatty liver disease. German Clinical Trials Register: DRKS00005450.
Multi-element determination in human samples is very challenging. Especially in human intervention studies sample volumes are often limited to a few microliters and due to the high number of samples a high-throughput is indispensable. Here, we present a state-of-the-art ICP-MS/MS-based method for the analysis of essential (trace) elements, namely Mg, Ca, Fe, Cu, Zn, Mo, Se and I, as well as food-relevant toxic elements such as As and Cd. The developed method was validated regarding linearity of the calibration curves, method LODs and LOQs, selectivity and trueness as well as precision. The established reliable method was applied to quantify the element serum concentrations of participants of a human intervention study (LeguAN). The participants received isocaloric diets, either rich in plant protein or in animal protein. While the serum concentrations of Mg and Mo increased in participants receiving the plant protein-based diet (above all legumes), the Se concentration in serum decreased. In contrast, the animal protein-based diet, rich in meat and dairy products, resulted in an increased Se concentration in serum.
Background: There is a growing interest in the role of inflammageing for chronic disease development. Cytokines are potent soluble immune mediators that can be used as target biomarkers of inflammageing; however, their measurement in human samples has been challenging. This study aimed to assess the reliability of a pro- and anti-inflammatory cytokine panel in a sample of healthy people measured with a novel electrochemiluminescent multiplex immunoassay platform (Meso Scale Discovery, MSD), and to characterize their associations with metabolic and inflammatory phenotypes.
Aim: Assessment of the feasibility and reliability of immune-inflammatory biomarker measurements. Methods: The following biomarkers were assessed in 207 predominantly healthy participants at baseline and after 4 months: MMF, TGF-beta, suPAR and clusterin. Results: Intraclass correlation coefficients (95% CIs) ranged from good for TGF-beta (0.75 [95% CI: 0.33-0.90]) to excellent for MMF (0.81 [95% CI: 0.64-0.90]), clusterin (0.83 [95% CI: 0.78-0.87]) and suPAR (0.91 [95% CI: 0.88-0.93]). Measurement of TGF-beta was challenged by the large number of values below the detection limit. Conclusion: Single measurements of suPAR, clusterin and MMF could serve as feasible and reliable biomarkers of immune-inflammatory pathways in biomedical research.
The clinical benefits of rehabilitation in cardiovascular disease are well established. Among cardiovascular disease patients, however, patients with type 2 diabetes mellitus require a distinct approach. Specific challenges to clinicians and healthcare professionals in patients with type 2 diabetes include the prevalence of peripheral and autonomic neuropathy, retinopathy, nephropathy, but also the intake of glucose-lowering medication. In addition, the psychosocial wellbeing, driving ability and/or occupational status can be affected by type 2 diabetes. As a result, the target parameters of cardiovascular rehabilitation and the characteristics of the cardiovascular rehabilitation programme in patients with type 2 diabetes often require significant reconsideration and a multidisciplinary approach. This review explains how to deal with diabetes-associated comorbidities in the intake screening of patients with type 2 diabetes entering a cardiovascular rehabilitation programme. Furthermore, we discuss diabetes-specific target parameters and characteristics of cardiovascular rehabilitation programmes for patients with type 2 diabetes in a multidisciplinary context, including the implementation of guideline-directed medical therapy.
The consumption of arabinoxylan, a soluble fibre fraction, has been shown to improve glycemic control in type 2 diabetic subjects. Soluble dietary fibre may modulate gastrointestinal or adipose tissue hormones regulating food intake. The present study investigated the effects of arabinoxylan consumption on serum glucose, insulin, lipids, leptin, adiponectin and resistin in subjects with impaired glucose tolerance. In a randomized, single-blind, controlled, crossover intervention trial, 11 adults consumed white bread rolls as either placebo or supplemented with 15g arabinoxylan for 6 weeks with a 6-week washout period. Fasting serum glucose, insulin, triglycerides, unesterified fatty acids, apolipoprotein A1 and B, adiponectin, resistin and leptin were assessed before and after intervention. Fasting serum glucose, serum triglycerides and apolipoprotein A-1 were significantly lower during arabinoxylan consumption compared to placebo (p = 0.029, p = 0.047; p = 0.029, respectively). No effects of arabinoxylan were observed for insulin, adiponectin, leptin and resistin as well as for apolipoprotein B, and unesterified fatty acids. In conclusion, the consumption of AX in subjects with impaired glucose tolerance improved fasting serum glucose, and triglycerides. However, this beneficial effect was not accompanied by changes in fasting adipokine concentrations.
Aims/hypothesis Polycystic ovary syndrome (PCOS) is a risk factor of type 2 diabetes. Screening for impaired glucose metabolism (IGM) with an OGTT has been recommended, but this is relatively time-consuming and inconvenient. Thus, a strategy that could minimise the need for an OGTT would be beneficial. Materials and methods Consecutive PCOS patients (n=118) with fasting glucose < 6.1 mmol/l were included in the study. Parameters derived from medical history, clinical examination and fasting blood samples were assessed by decision tree modelling for their ability to discriminate women with IGM (2-h OGTT value >= 7.8 mmol/l) from those with NGT. Results According to the OGTT results, 93 PCOS women had NGT and 25 had IGM. The best decision tree consisted of HOMA-IR, the proinsulin:insulin ratio, proinsulin, 17-OH progesterone and the ratio of luteinising hormone:follicle-stimulating hormone. This tree identified 69 women with NGT. The remaining 49 women included all women with IGM (100% sensitivity, 74% specificity to detect IGM). Pruning this tree to three levels still identified 53 women with NGT (100% sensitivity, 57% specificity to detect IGM). Restricting the data matrix used for tree modelling to medical history and clinical parameters produced a tree using BMI, waist circumference and WHR. Pruning this tree to two levels separated 27 women with NGT (100% sensitivity, 29% specificity to detect IGM). The validity of both trees was tested by a leave-10%-out cross-validation. Conclusions/interpretation Decision trees are useful tools for separating PCOS women with NGT from those with IGM. They can be used for stratifying the metabolic screening of PCOS women, whereby the number of OGTTs can be markedly reduced.
Background
High blood glucose and diabetes are amongst the conditions causing the greatest losses in years of healthy life worldwide. Therefore, numerous studies aim to identify reliable risk markers for development of impaired glucose metabolism and type 2 diabetes. However, the molecular basis of impaired glucose metabolism is so far insufficiently understood. The development of so called 'omics' approaches in the recent years promises to identify molecular markers and to further understand the molecular basis of impaired glucose metabolism and type 2 diabetes. Although univariate statistical approaches are often applied, we demonstrate here that the application of multivariate statistical approaches is highly recommended to fully capture the complexity of data gained using high-throughput methods.
Methods
We took blood plasma samples from 172 subjects who participated in the prospective Metabolic Syndrome Berlin Potsdam follow-up study (MESY-BEPO Follow-up). We analysed these samples using Gas Chromatography coupled with Mass Spectrometry (GC-MS), and measured 286 metabolites. Furthermore, fasting glucose levels were measured using standard methods at baseline, and after an average of six years. We did correlation analysis and built linear regression models as well as Random Forest regression models to identify metabolites that predict the development of fasting glucose in our cohort.
Results
We found a metabolic pattern consisting of nine metabolites that predicted fasting glucose development with an accuracy of 0.47 in tenfold cross-validation using Random Forest regression. We also showed that adding established risk markers did not improve the model accuracy. However, external validation is eventually desirable. Although not all metabolites belonging to the final pattern are identified yet, the pattern directs attention to amino acid metabolism, energy metabolism and redox homeostasis.
Conclusions
We demonstrate that metabolites identified using a high-throughput method (GC-MS) perform well in predicting the development of fasting plasma glucose over several years. Notably, not single, but a complex pattern of metabolites propels the prediction and therefore reflects the complexity of the underlying molecular mechanisms. This result could only be captured by application of multivariate statistical approaches. Therefore, we highly recommend the usage of statistical methods that seize the complexity of the information given by high-throughput methods.