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In order to evaluate whether telomere maintenance is associated with type 2 diabetes remission, newly diagnosed type 2 diabetes patients without glucose-lowering treatment (183 out of 1002) from the CORDIOPREV study (NCT00924937) were randomized to consume a Mediterranean or low-fat diet. Patients were classified as Responders, those who reverted from type 2 diabetes during the 5 years of dietary intervention ( n = 69), and Non-Responders, who did not achieve diabetes remission by the end of the follow-up period ( n = 104). We found no differences in diabetes remission between the two diets, and we determined telomere length (TL) by measuring qPCR, telomerase activity using the TRAP assay, and direct redox balance based on the ratio of reduced glutathione (GSH) to oxidized glutathione (GSSH) via colorimetric assay. Responders exhibited higher baseline TL in comparison with Non-Responders ( p = 0.040), and a higher TL at baseline significantly predicted a higher probability of type 2 diabetes remission (OR 2.13; 95% CI, 1.03 to 4.41). After the dietary intervention, Non-Responders showed significant telomere shortening (-0.19, 95% CI -0.32 to 0.57; p = 0.005). Telomere shortening was significantly pronounced in type 2 diabetes patients with a worse profile of insulin resistance and/or beta-cell functionality: high hepatic insulin resistance fasting, a high disposition index (-0.35; 95% CI, -0.54 to -0.16; p < 0.001), and a low disposition index (-0.25; 95% CI, -0.47 to -0.01; p = 0.037). In addition, changes in TL were correlated to the GSH/GSSG ratio. Responders also showed increased telomerase activity compared with baseline ( p = 0.048), from 0.16 (95% CI, 0.08 to 0.23) to 0.28 (95% CI, 0.15 to 0.40), with a more marked increase after the dietary intervention compared with Non-Responders (+0.07; 95% CI, -0.06-0.20; p = 0.049). To conclude, telomere maintenance may play a key role in the molecular mechanisms underlying type 2 diabetes remission in newly diagnosed patients. However, further larger-scale prospective studies are necessary to corroborate our findings.

Objective: We aimed to identify a lipidic profile associated with type 2 diabetes mellitus (T2DM) development in coronary heart disease (CHD) patients, to provide a new, highly sensitive model which could be used in clinical practice to identify patients at T2DM risk., Methods: This study considered the 462 patients of the CORDIOPREV study (CHD patients) who were not diabetic at the beginning of the intervention. In total, 107 of them developed T2DM after a median follow-up of 60 months. They were diagnosed using the American Diabetes Association criteria. A novel lipidomic methodology employing liquid chromatography (LC) separation followed by HESI, and detection by mass spectrometry (MS) was used to annotate the lipids at the isomer level. The patients were then classified into a Training and a Validation Set (60-40). Next, a Random Survival Forest (RSF) was carried out to detect the lipidic isomers with the lowest prediction error, these lipids were then used to build a Lipidomic Risk (LR) score which was evaluated through a Cox. Finally, a production model combining the clinical variables of interest, and the lipidic species was carried out., Results: LC-tandem MS annotated 440 lipid species. From those, the RSF identified 15 lipid species with the lowest prediction error. These lipids were combined in an LR score which showed association with the development of T2DM. The LR hazard ratio per unit standard deviation was 2.87 and 1.43, in the Training and Validation Set respectively. Likewise, patients with higher LR Score values had lower insulin sensitivity (P = 0.006) and higher liver insulin resistance (P = 0.005). The receiver operating characteristic (ROC) curve obtained by combining clinical variables and the selected lipidic isomers using a generalised lineal model had an area under the curve (AUC) of 81.3%., Conclusion: Our study showed the potential of comprehensive lipidomic analysis in identifying patients at risk of developing T2DM. In addition, the lipid species combined with clinical variables provided a new, highly sensitive model which can be used in clinical practice to identify patients at T2DM risk. Moreover, these results also indicate that we need to look closely at isomers to understand the role of this specific compound in T2DM development. Trials registration NCT00924937., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Metabolic diseases, such as obesity, metabolic syndrome (MetS) and type 2 diabetes (T2D), are now a widespread pandemic in the developed world. These pathologies show sex differences in their development and prevalence, and sex steroids, mainly estrogen and testosterone, are thought to play a prominent role in this sexual dimorphism. The influence of sex hormones on these pathologies is not only reflected in differences between men and women, but also between women themselves, depending on the hormonal changes associated with the menopause. The observed sex differences in gut microbiota composition have led to multiple studies highlighting the interaction between steroid hormones and the gut microbiota and its influence on metabolic diseases, ultimately pointing to a new therapy for these diseases based on the manipulation of the gut microbiota. This review aims to shed light on the role of sexual hormones in sex differences in the development and prevalence of metabolic diseases, focusing on obesity, MetS and T2D. We focus also the interaction between sex hormones and the gut microbiota, and in particular the role of microbiota in aspects such as gut barrier integrity, inflammatory status, and the gut-brain axis, given the relevance of these factors in the development of metabolic diseases., (© 2023. The Author(s).)

Background: Type 2 diabetes mellitus (T2DM) is one of the most widely spread diseases, affecting around 90% of the patients with diabetes. Metabolomics has proven useful in diabetes research discovering new biomarkers to assist in therapeutical studies and elucidating pathways of interest. However, this technique has not yet been applied to a cohort of patients that have remitted from T2DM., Methods: All patients with a newly diagnosed T2DM at baseline (n = 190) were included. An untargeted metabolomics approach was employed to identify metabolic differences between individuals who remitted (RE), and those who did not (non-RE) from T2DM, during a 5-year study of dietary intervention. The biostatistical pipeline consisted of an orthogonal projection on the latent structure discriminant analysis (O-PLS DA), a generalized linear model (GLM), a receiver operating characteristic (ROC), a DeLong test, a Cox regression, and pathway analyses., Results: The model identified a significant increase in 12 metabolites in the non-RE group compared to the RE group. Cox proportional hazard models, calculated using these 12 metabolites, showed that patients in the high-score tercile had significantly (p-value < 0.001) higher remission probabilities (Hazard Ratio, HR, high versus low  = 2.70) than those in the lowest tercile. The predictive power of these metabolites was further studied using GLMs and ROCs. The area under the curve (AUC) of the clinical variables alone is 0.61, but this increases up to 0.72 if the 12 metabolites are considered. A DeLong test shows that this difference is statistically significant (p-value = 0.01)., Conclusions: Our study identified 12 endogenous metabolites with the potential to predict T2DM remission following a dietary intervention. These metabolites, combined with clinical variables, can be used to provide, in clinical practice, a more precise therapy., Trial Registration: ClinicalTrials.gov, NCT00924937., (© 2022. The Author(s).)

Milk products are an important component of human diets, with beneficial effects for human health, but also one of the major sources of nutritionally undesirable saturated fatty acids (SFA). Recent discoveries showing the importance of the rumen microbiome on dairy cattle health, metabolism and performance highlight that milk composition, and potentially milk SFA content, may also be associated with microorganisms, their genes and their activities. Understanding these mechanisms can be used for the development of cost-effective strategies for the production of milk with less SFA. This work aimed to compare the rumen microbiome between cows producing milk with contrasting FA profile and identify potentially responsible metabolic-related microbial mechanisms. Forty eight Holstein dairy cows were fed the same total mixed ration under the same housing conditions. Milk and rumen fluid samples were collected from all cows for the analysis of fatty acid profiles (by gas chromatography), the abundances of rumen microbiome communities and genes (by whole-genome-shotgun metagenomics), and rumen metabolome (using 500 MHz nuclear magnetic resonance). The following groups: (i) 24 High-SFA (66.9-74.4% total FA) vs. 24 Low-SFA (60.2-66.6%% total FA) cows, and (ii) 8 extreme High-SFA (69.9-74.4% total FA) vs. 8 extreme Low-SFA (60.2-64.0% total FA) were compared. Rumen of cows producing milk with more SFA were characterized by higher abundances of the lactic acid bacteria Lactobacillus, Leuconostoc , and Weissella , the acetogenic Proteobacteria Acetobacter and Kozakia, Mycobacterium , two fungi ( Cutaneotrichosporon and Cyphellophora ), and at a lesser extent Methanobrevibacter and the protist Nannochloropsis . Cows carrying genes correlated with milk FA also had higher concentrations of butyrate, propionate and tyrosine and lower concentrations of xanthine and hypoxanthine in the rumen. Abundances of rumen microbial genes were able to explain between 76 and 94% on the variation of the most abundant milk FA. Metagenomics and metabolomics analyses highlighted that cows producing milk with contrasting FA profile under the same diet, also differ in their rumen metabolic activities in relation to adaptation to reduced rumen pH, carbohydrate fermentation, and protein synthesis and metabolism., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Stergiadis, Cabeza-Luna, Mora-Ortiz, Stewart, Dewhurst, Humphries, Watson, Roehe and Auffret.)

Although sex disparity in immunological function and susceptibility to various inflammatory and infectious disease is recognized in adults, far less is known about the situation in young infants during immune development. We have used an outbred piglet model to explore potential early sex disparity underlying both mucosal immune development and systemic responses to novel antigen. Despite similarities in intestinal barrier function and therefore, presumably, antigen exposure, females had less CD172 + (Sirp-α) antigen presenting cells and expression of MHCIIDR at 28 days old compared to males, along with greater regulatory T-cell numbers. This suggests that, during infancy, females may have greater potential for local immune regulation than their male counterparts. However, females also presented with significantly greater systemic antibody responses to injected ovalbumin and dietary soya. Females also synthesized significantly more IgA in mesenteric lymph nodes, whereas males synthesized more in caecal mucosa, suggesting that plasma cells were retained within the MLN in females, but increased numbers of plasma cells circulated through to the mucosal tissue in males. Significant effects of inulin and Bifidobacterium lactis NCC2818 on the developing immune system were also sex-dependent. Our results may start to explain inconsistencies in outcomes of trials of functional foods in infants, as distinction between males and females is seldom made. Since later functionality of the immune system is highly dependent on appropriate development during infancy, stratifying nutritional interventions by sex may present a novel means of optimizing treatments and preventative strategies to reduce the risk of the development of immunological disorders in later life., (Copyright © 2019 Christoforidou, Mora Ortiz, Poveda, Abbas, Walton, Bailey and Lewis.)

Introduction: The rapid expansion of Type 2 Diabetes (T2D), that currently affects 90% of people suffering from diabetes, urges us to develop a better understanding of the metabolic processes involved in the disease process in order to develop better therapies. The most commonly used model for T2D research is the db/db (BKS.Cg-Dock7 < m > +/+ Lepr < db >/J) mouse model. Yet, a systematic 1 H NMR based metabolomics characterisation of most tissues in this animal model has not been published. Here, we provide a systematic organ-specific metabolomics analysis of this widely employed model using NMR spectroscopy., Objectives: The aim of this study was to characterise the metabolic modulations associated with T2D in db/db mice in 18 relevant biological matrices., Methods: High-resolution 1 H-NMR and 2D-NMR spectroscopy were applied to 18 biological matrices of 12 db/db mice (WT control n = 6, db/db = 6) aged 22 weeks, when diabetes is fully established., Results: 61 metabolites associated with T2D were identified. Kidney, spleen, eye and plasma were the biological matrices carrying the largest metabolomics modulations observed in established T2D, based on the total number of metabolites that showed a statistical difference between the diabetic and control group in each tissue (16 in each case) and the strength of the O-PLS DA model for each tissue. Glucose and glutamate were the most commonly associated metabolites found significantly increased in nine biological matrices. Investigated sections where no increase of glucose was associated with T2D include all intestinal segments (i.e. duodenum, jejunum, ileum and colon). Microbial co-metabolites such as acetate and butyrate, used as carbon sources by the host, were identified in excess in the colonic tissues of diabetic individuals., Conclusions: The metabolic biomarkers identified using 1 H NMR-based metabolomics will represent a useful resource to explore metabolic pathways involved in T2D in the db/db mouse model.

Introduction: Death is the permanent cessation of the critical functions of the organism as a whole. However, the shutdown of a complex biological organism does not abruptly terminate at time of death. New high-throughput technologies allow the systematic investigation of the biochemical modulations occurring after death. Recent genomics studies have demonstrated that genes remain active after death, triggering upregulation of some genes and initiating feedback loops. These genes were mostly involved in pathways related to immunity, inflammation and cancer. These genetic modulations suggest many biochemical events persist after death, which can be captured using a metabolomics approach., Objectives: This proof of concept work aimed to determine whether NMR spectroscopy could identify metabolomics changes occurring after death, and characterise the nature of these metabolomics modulations., Methods: High-resolution 1 H-NMR spectroscopy was applied to six biological matrices: heart, kidney, liver, spleen, skin and white adipose tissue of ten adult mice at three different type points., Results: Forty-three metabolites were associated with post mortem metabolomics modulations. Kidney, heart and spleen showed the highest metabolic perturbations. Conversely, skin and white adipose tissue were the least altered matrices. Early metabolic modulations were associated with energy metabolism and DNA synthesis, by contrast, late metabolomics modulations were associated with microbial metabolism., Conclusions: NMR has proven potential to determine the time of death based on post-mortem metabolomics modulations. This could be useful in the context of transplants, forensic studies and as internal quality control in metabolomics studies. Further investigations are required to validate these findings in humans in order to determine which compounds robustly reflect post-mortem metabolic fluctuations to accurately determine the time of death.

A procedure based on 13 C CPMAS NMR was developed to study procyanidins (PCs) and prodelphinidins (PDs) directly in milled sainfoin plant tissues. Blackcurrant and Tilia samples enabled reference spectra of purified proanthocyanidin (PA) fractions, crude extracts, and milled plant tissues, with characteristic resonances at 155, 144, and 132 ppm. PC/PD ratios were estimated from the I 132 /I 155 intensity ratio and differed by 2.5 to 5.9% compared to thiolysis data. Normalization to the 155 ppm signal intensity from reference spectra enabled analysis of PA contents with an error of ca. 8 g PAs/100 g plant tissue. The procedure estimates the lignin contribution and allows for a correction of the PA content. In six sainfoin accessions, estimated PA contents were 1.6- to 20.8-fold higher than the thiolysis and 1.4- to 2.6-fold higher than the HCl-butanol-acetone results. Method differences may reflect the presence of unextractable, possibly high molecular weight PAs in sainfoin.

Choline is a crucial methyl donor necessary for epigenetic regulation. In this issue of Cell Host & Microbe, Romano et al. (2017) demonstrate that choline-utilizing gut bacteria compete with their host for this essential resource, calling for a systematic consideration of gut microbial composition for personalized diet recommendations., (Copyright © 2017. Published by Elsevier Inc.)

Background: Sainfoin (Onobrychis viciifolia) is a highly nutritious tannin-containing forage legume. In the diet of ruminants sainfoin can have anti-parasitic effects and reduce methane emissions under in vitro conditions. Many of these benefits have been attributed to condensed tannins or proanthocyanidins in sainfoin. A combination of increased use of industrially produced nitrogen fertilizer, issues with establishment and productivity in the first year and more reliable alternatives, such as red clover led to a decline in the use of sainfoin since the middle of the last century. In recent years there has been a resurgence of interest in sainfoin due to its potential beneficial nutraceutical and environmental attributes. However, genomic resources are scarce, thus hampering progress in genetic analysis and improvement. To address this we have used next generation RNA sequencing technology to obtain the first transcriptome of sainfoin. We used the library to identify gene-based simple sequence repeats (SSRs) and potential single nucleotide polymorphisms (SNPs)., Results: One genotype from each of five sainfoin accessions was sequenced. Paired-end (PE) sequences were generated from cDNA libraries of RNA extracted from 7 day old seedlings. A combined assembly of 92,772 transcripts was produced de novo using the Trinity programme. About 18,000 transcripts were annotated with at least one GO (gene ontology) term. A total of 63 transcripts were annotated as involved in the tannin biosynthesis pathway. We identified 3786 potential SSRs. SNPs were identified by mapping the reads of the individual assemblies against the combined assembly. After stringent filtering a total of 77,000 putative SNPs were identified. A phylogenetic analysis of single copy number genes showed that sainfoin was most closely related to red clover and Medicago truncatula, while Lotus japonicus, bean and soybean are more distant relatives., Conclusions: This work describes the first transcriptome assembly in sainfoin. The 92 K transcripts provide a rich source of SNP and SSR polymorphisms for future use in genetic studies of this crop. Annotation of genes involved in the condensed tannin biosynthesis pathway has provided the basis for further studies of the genetic control of this important trait in sainfoin.

Background: Sainfoin is a perennial forage legume with beneficial properties for animal husbandry due to the presence of secondary metabolites. However, worldwide cultivation of sainfoin is marginal due to the lack of varieties with good agronomic performance, adapted to a broad range of environmental conditions. Little is known about the genetics of sainfoin and only few genetic markers are available to assist breeding and genetic investigations. The objective of this study was to develop a set of SSR markers useful for genetic studies in sainfoin and their characterization in diverse germplasm., Results: A set of 400 SSR primer combinations were tested for amplification and their ability to detect polymorphisms in a set of 32 sainfoin individuals, representing distinct varieties or landraces. Alleles were scored for presence or absence and polymorphism information content of each SSR locus was calculated with an adapted formula taking into account the tetraploid character of sainfoin. Relationships among individuals were visualized using cluster and principle components analysis. Of the 400 primer combinations tested, 101 reliably detected polymorphisms among the 32 sainfoin individuals. Among the 1154 alleles amplified 250 private alleles were observed. The number of alleles per locus ranged from 2 to 24 with an average of 11.4 alleles. The average polymorphism information content reached values of 0.14 to 0.36. The clustering of the 32 individuals suggested a separation into two groups depending on the origin of the accessions., Conclusions: The SSR markers characterized and tested in this study provide a valuable tool to detect polymorphisms in sainfoin for future genetic studies and breeding programs. As a proof of concept, we showed that these markers can be used to separate sainfoin individuals based on their origin.