Increased Dairy Product Intake Alters Serum Metabolite Profiles in Subjects at Risk of Developing Type 2 Diabetes

Lack of change in blood pressure and arterial stiffness after high dairy intake in hyperinsulinemic subjects: a cross-over randomized controlled trial

To evaluate the effects of high dairy (HD) (≥4 servings/day), compared to adequate dairy (AD) (2-3 servings/day as per Canada's Food Guide for Healthy Eating (2007)), on blood pressure (BP) and measures of arterial stiffness in hyperinsulinemic subjects. In this cross-over clinical trial, hyperinsulinemic adults were randomized to AD and HD for 6 weeks. Anthropometric, glycemic, and lipid parameters were analyzed and dietary intake was evaluated; BP, carotid-femoral pulse wave velocity, augmentation index, and measures of arterial stiffness were assessed. Twenty-seven participants completed the study. Dairy intake was 2.2 ± 1.2 servings/day during AD. In addition, lower total and low-density lipoprotein (LDL) cholesterol were observed without significant change in BP or arterial stiffness between before and after AD. During HD, the subjects consumed 5.8 ± 1.9 servings/day of dairy products, providing a higher intake of protein, saturated fat, calcium, phosphorus, sodium, and potassium compared to the baseline diet. After the HD, subjects had higher body fat, fasting insulin, homeostatic model assessment for insulin resistance (HOMA-IR) index, and triglycerides without altering BP or arterial stiffness compared to before HD. Overall, adequate or high intake of total dairy did not modify BP or arterial stiffness in hyperinsulinemic adults after 6 weeks.

Dairy Intake Modifies the Level of the Bile Acid Precursor and Its Correlation with Serum Proteins Associated with Cholesterol Clearance in Subjects with Hyperinsulinemia

Bile acids regulate glucose homeostasis and lipid metabolism. Further, the levels of bile acids can be influenced by the intake of dairy products. Although the serum proteome can provide information on the biological pathways associated with different metabolites, it is unknown whether the intake of dairy modifies such associations between bile acids and the proteome. The objectives of this study were to examine plasma bile acid profiles, find the correlations between bile acids and lipid as well as glycemic markers, and to uncover the correlation between bile acids and proteins after high dairy (HD) and adequate dairy (AD) intake among 25 overweight individuals with hyperinsulinemia. In this randomized crossover-trial study, hyperinsulinemia adults were randomized to both HD (≥4 servings/day) and AD (≤2 servings/day) for 6 weeks. Measurements and analyses were performed on before- as well as after- AD and HD conditions. The results indicated that plasma 7α-hydroxy-4-cholesten-3-one (7AC4) increased after HD in comparison with before HD intake (p = 0.03). After adjusting for BMI, age, and sex, 7AC4 positively correlated with triglyceride levels in the pre-AD (r = 0.44; p = 0.03) and post-HD (r = 0.42; p = 0.04). Further, 7AC4 correlated positively with proteins associated with high-density lipoprotein particle remodeling pathway and reverse cholesterol transport only after HD consumption. Thus, the consumption of higher dairy intake modifies the association between 7AC4-a biomarker for bile acid synthesis-and serum proteins involved in cholesterol clearance. Overall, higher dairy consumption may have a positive effect on cholesterol metabolism in subjects at risk of type 2 diabetes.

Maternal Dietary Protein Patterns and Neonatal Anthropometrics: A Prospective Study with Insights from NMR Metabolomics in Amniotic Fluid

This study aimed to characterize dietary protein patterns (DPPs) in a sample pool of 298 well-nourished pregnant women and explore potential associations between DPPs and neonatal anthropometrics. Maternal dietary data were collected using a validated food frequency questionnaire. Neonatal anthropometrics were abstracted from health booklets. A hierarchical cluster analysis identified three DPPs: "Dairy-focused", "Med-fusion", and "Traditional-inspired". The "Dairy-focused" DPP exhibited the highest protein intake (p < 0.001), predominantly animal protein (p < 0.001), while the "Traditional-inspired" DPP presented higher plant protein (p < 0.001) and fiber intakes (p < 0.001), and, therefore, a reduced carbohydrate-to-fiber quotient (p < 0.001). The "Med-fusion" DPP had the lowest protein-to-fat ratio (p < 0.001). Infants of women following the "Dairy-focused" DPP had the highest birth height centiles (p = 0.007) and the lowest ponderal index (p = 0.003). The NMR-metabolomics approach was implemented on a subset of women that provided amniotic fluid (AF) specimens (n = 62) to elucidate distinct metabolic signatures associated with DPPs. PCA and OPLS-DA models verified the adherence to three DPPs, revealing that the levels of several amino acids (AAs) were the highest in "Dairy-focused", reflecting its protein-rich nature. The "Traditional-inspired" DPP showed decreased AAs and glucose levels. This knowledge may contribute to optimizing maternal dietary recommendations. Further research is needed to validate these findings and better understand the relationships between maternal diet, AF metabolic signature, and neonatal anthropometrics.

Can individual fatty acids be used as functional biomarkers of dairy fat consumption in relation to cardiometabolic health? A narrative review

In epidemiological studies, dairy food consumption has been associated with minimal effect or decreased risk of some cardiometabolic diseases (CMD). However, current methods of dietary assessment do not provide objective and accurate measures of food intakes. Thus, the identification of valid and reliable biomarkers of dairy product intake is an important challenge to best determine the relationship between dairy consumption and health status. This review investigated potential biomarkers of dairy fat consumption, such as odd-chain, trans- and branched-chain fatty acids (FA), which may improve the assessment of full-fat dairy product consumption. Overall, the current use of serum/plasma FA as biomarkers of dairy fat consumption is mostly based on observational evidence, with a lack of well-controlled, dose-response intervention studies to accurately assess the strength of the relationship. Circulating odd-chain SFA and trans-palmitoleic acid are increasingly studied in relation to CMD risk and seem to be consistently associated with a reduced risk of type 2 diabetes in prospective cohort studies. However, associations with CVD are less clear. Overall, adding less studied FA such as vaccenic and phytanic acids to the current available evidence may provide a more complete assessment of dairy fat intake and minimise potential confounding from endogenous synthesis. Finally, the current evidence base on the direct effect of dairy fatty acids on established biomarkers of CMD risk (e.g. fasting lipid profiles and markers of glycaemic control) mostly derives from cross-sectional, animal and in vitro studies and should be strengthened by well-controlled human intervention studies.

Aberrant branched-chain amino acid catabolism in cardiovascular diseases

Globally, cardiovascular diseases are the leading cause of death. Research has focused on the metabolism of carbohydrates, fatty acids, and amino acids to improve the prognosis of cardiovascular diseases. There are three types of branched-chain amino acids (BCAAs; valine, leucine, and isoleucine) required for protein homeostasis, energy balance, and signaling pathways. Increasing evidence has implicated BCAAs in the pathogenesis of multiple cardiovascular diseases. This review summarizes the biological origin, signal transduction pathways and function of BCAAs as well as their significance in cardiovascular diseases, including myocardial hypertrophy, heart failure, coronary artery disease, diabetic cardiomyopathy, dilated cardiomyopathy, arrhythmia and hypertension.

Impact of a food-based dietary fat exchange model for replacing dietary saturated with unsaturated fatty acids in healthy men on plasma phospholipids fatty acid profiles and dietary patterns

PURPOSE

UK guidelines recommend dietary saturated fatty acids (SFAs) should not exceed 10% total energy (%TE) for cardiovascular disease prevention, with benefits observed when SFAs are replaced with unsaturated fatty acids (UFAs). This study aimed to assess the efficacy of a dietary exchange model using commercially available foods to replace SFAs with UFAs.

METHODS

Healthy men (n = 109, age 48, SD 11 year) recruited to the Reading, Imperial, Surrey, Saturated fat Cholesterol Intervention-1 (RISSCI-1) study (ClinicalTrials.Gov n°NCT03270527) followed two sequential 4-week isoenergetic moderate-fat (34%TE) diets: high-SFA (18%TE SFAs, 16%TE UFAs) and low-SFA (10%TE SFAs, 24%TE UFAs). Dietary intakes were assessed using 4-day weighed diet diaries. Nutrient intakes were analysed using paired t-tests, fasting plasma phospholipid fatty acid (PL-FA) profiles and dietary patterns were analysed using orthogonal partial least square discriminant analyses.

RESULTS

Participants exchanged 10.2%TE (SD 4.1) SFAs for 9.7%TE (SD 3.9) UFAs between the high and low-SFA diets, reaching target intakes with minimal effect on other nutrients or energy intakes. Analyses of dietary patterns confirmed successful incorporation of recommended foods from commercially available sources (e.g. dairy products, snacks, oils, and fats), without affecting participants' overall dietary intakes. Analyses of plasma PL-FAs indicated good compliance to the dietary intervention and foods of varying SFA content.

CONCLUSIONS

RISSCI-1 dietary exchange model successfully replaced dietary SFAs with UFAs in free-living healthy men using commercially available foods, and without altering their dietary patterns. Further intervention studies are required to confirm utility and feasibility of such food-based dietary fat replacement models at a population level.

Diabetes remission is modulated by branched chain amino acids according to the diet consumed: from the CORDIOPREV study

SCOPE

BCAA plasma levels may be differentially associated with type 2 diabetes mellitus (T2DM) remission through the consumption of the Mediterranean diet (Med) and a low-fat (LF) diet.

METHODS

183 newly-diagnosed T2DM patients within the CORDIOPREV study were randomized to consume the Med or a LF diet. BCAA plasma levels (isoleucine, leucine and valine) were measured at fasting and after 120 min of an oral glucose tolerance test (OGTT) at the baseline of the study and after 5 y of the dietary intervention.

RESULTS

Isoleucine, leucine and valine plasma levels after 120 min of an OGTT in the Med diet (N = 80) were associated by COX analysis with T2DM remission: HR per SD (95%CI): 0.53 (0.37-0.77), 0.75 (0.52-1.08) and 0.61 (0.45-0.82), respectively; no association was found in patients who consumed a LF diet (N = 103). BCAA plasma levels combined in a score showed a HR of 3.33 (1.55-7.19) of T2DM remission for patients with a high score values in the Med diet, while in those with a LF diet no association was found.

CONCLUSION

Our study suggests that BCAA measurements potentially be used as a tool to select the most suitable diet to induce T2DM remission by nutritional strategies. This article is protected by copyright. All rights reserved.

Odd-chain fatty acids as novel histone deacetylase 6 (HDAC6) inhibitors

The dysregulation of histone deacetylases (HDACs) is closely associated with tumorigenesis and has emerged as a promising target for anti-cancer drugs. Some odd-chain fatty acids are present in trace levels in human tissue. Despite limited health benefits, there is increasing experimental evidence of nutritional benefits of odd-chain fatty acids. This study examines the effects of five odd-chain fatty acids (valeric, heptanoic, nonanoic, undecanoic, and pentadecanoic acid) as novel HDAC6 inhibitors. Examination of these fatty acids on the proliferation and clonogenic ability in various cancer cell lines revealed that pentadecanoic and undecanoic acid can strongly inhibit cancer cell proliferation. Heptanoic and nonanoic acid showed moderate anti-proliferative effects, while valeric acid demonstrated weak anti-proliferative effects. HDAC6 inhibitory activities were in the order of pentadecanoic acid (C15:0) > undecanoic acid (C11:0) > nonanoic acid (C9:0) > heptanoic acid (C7:0) > valeric acid (C5:0), consistent with the anti-proliferative assay results. All of these fatty acids promoted the acetylation of α-tubulin in MCF-7 breast and A549 lung cancer cells dose-dependently. In-silico molecular docking analysis showed that increasing the aliphatic carbon chain length facilitates binding to HDAC6 residues, which might be important for the inhibitory potential of HDAC6. This study shows the potential utility of odd-chain fatty acids for epigenetic-based cancer therapy.

Milk consumption and multiple health outcomes: umbrella review of systematic reviews and meta-analyses in humans

In order to recapitulate the best available evidence of milk consumption and multiple health-related outcomes, we performed an umbrella review of meta-analyses and systematic reviews in humans. Totally, 41 meta-analyses with 45 unique health outcomes were included. Milk consumption was more often related to benefits than harm to a sequence of health-related outcomes. Dose–response analyses indicated that an increment of 200 ml (approximately 1 cup) milk intake per day was associated with a lower risk of cardiovascular disease, stroke, hypertension, colorectal cancer, metabolic syndrome, obesity and osteoporosis. Beneficial associations were also found for type 2 diabetes mellitus and Alzheimer's disease. Conversely, milk intake might be associated with higher risk of prostate cancer, Parkinson’s disease, acne and Fe-deficiency anaemia in infancy. Potential allergy or lactose intolerance need for caution. Milk consumption does more good than harm for human health in this umbrella review. Our results support milk consumption as part of a healthy diet. More well-designed randomized controlled trials are warranted.

A rapid GC method coupled with quadrupole or time of flight mass spectrometry for metabolomics analysis

Gas chromatography-mass spectrometry (GC-MS) is an ideal tool for analyzing the intermediates of tricarboxylic acid cycle and glycolysis, sugars, organic acids and amino acids, etc. High-throughput metabolomics methods are required by large-scale clinical researches, and time of flight mass spectrometry (TOF MS) having fast scanning rate is preferable for rapid GC. Quadrupole MS (qMS) instruments have 95% market share, and their potential in rapid metabolomics is worth being studied. In this work, a within 15-min GC program was established and matched by qMS scanning for plasma metabolome analysis after N-methyl-N-(trimethylsilyl)-trifluoroacetamide derivatization. Compared to the longer-time program GC-qMS method, the rapid GC-qMS method had nearly no metabolome information loss, and it had excellent profile performance in repeatability, intra-day and inter-day precision, sampling range, linearity and extraction recovery. Compared to TOF MS, qMS achieved similar results in investigating lung cancer serum metabolic disruptions. Partial least squares-discriminant analysis revealed that the two datasets acquired by qMS and TOF MS had very similar model parameters, and most of top ranked differential metabolites were the same. This study provides a rapid and economical GC-qMS metabolomics method for researchers. Still, MS having faster scanning rate and higher sensitivity are recommended, if possible, to detect more small peaks and some co-eluted peaks.

Statistical and Machine-Learning Analyses in Nutritional Genomics Studies

Nutritional compounds may have an influence on different OMICs levels, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, and metagenomics. The integration of OMICs data is challenging but may provide new knowledge to explain the mechanisms involved in the metabolism of nutrients and diseases. Traditional statistical analyses play an important role in description and data association; however, these statistical procedures are not sufficiently enough powered to interpret the large integrated multiple OMICs (multi-OMICS) datasets. Machine learning (ML) approaches can play a major role in the interpretation of multi-OMICS in nutrition research. Specifically, ML can be used for data mining, sample clustering, and classification to produce predictive models and algorithms for integration of multi-OMICs in response to dietary intake. The objective of this review was to investigate the strategies used for the analysis of multi-OMICs data in nutrition studies. Sixteen recent studies aimed to understand the association between dietary intake and multi-OMICs data are summarized. Multivariate analysis in multi-OMICs nutrition studies is used more commonly for analyses. Overall, as nutrition research incorporated multi-OMICs data, the use of novel approaches of analysis such as ML needs to complement the traditional statistical analyses to fully explain the impact of nutrition on health and disease.

A Metabolomics Workflow for Analyzing Complex Biological Samples Using a Combined Method of Untargeted and Target-List Based Approaches

In the highly dynamic field of metabolomics, we have developed a method for the analysis of hydrophilic metabolites in various biological samples. Therefore, we used hydrophilic interaction chromatography (HILIC) for separation, combined with a high-resolution mass spectrometer (MS) with the aim of separating and analyzing a wide range of compounds. We used 41 reference standards with different chemical properties to develop an optimal chromatographic separation. MS analysis was performed with a set of pooled biological samples human cerebrospinal fluid (CSF), and human plasma. The raw data was processed in a first step with Compound Discoverer 3.1 (CD), a software tool for untargeted metabolomics with the aim to create a list of unknown compounds. In a second step, we combined the results obtained with our internally analyzed reference standard list to process the data along with the Lipid Data Analyzer 2.6 (LDA), a software tool for a targeted approach. In order to demonstrate the advantages of this combined target-list based and untargeted approach, we not only compared the relative standard deviation (%RSD) of the technical replicas of pooled plasma samples (n = 5) and pooled CSF samples (n = 3) with the results from CD, but also with XCMS Online, a well-known software tool for untargeted metabolomics studies. As a result of this study we could demonstrate with our HILIC-MS method that all standards could be either separated by chromatography, including isobaric leucine and isoleucine or with MS by different mass. We also showed that this combined approach benefits from improved precision compared to well-known metabolomics software tools such as CD and XCMS online. Within the pooled plasma samples processed by LDA 68% of the detected compounds had a %RSD of less than 25%, compared to CD and XCMS online (57% and 55%). The improvements of precision in the pooled CSF samples were even more pronounced, 83% had a %RSD of less than 25% compared to CD and XCMS online (28% and 8% compounds detected). Particularly for low concentration samples, this method showed a more precise peak area integration with its 3D algorithm and with the benefits of the LDAs graphical user interface for fast and easy manual curation of peak integration. The here-described method has the advantage that manual curation for larger batch measurements remains minimal due to the target list containing the information obtained by an untargeted approach.