Fibromyalgia is a complex, relatively unknown disease characterised by chronic, widespread musculoskeletal pain. The gut-brain axis connects the gut microbiome with the brain through the enteric nervous system (ENS); its disruption has been associated with psychiatric and gastrointestinal disorders. To gain an insight into the pathogenesis of fibromyalgia and identify diagnostic biomarkers, we combined different omics techniques to analyse microbiome and serum composition. We collected faeces and blood samples to study the microbiome, the serum metabolome and circulating cytokines and miRNAs from a cohort of 105 fibromyalgia patients and 54 age- and environment-matched healthy individuals. We sequenced the V3 and V4 regions of the 16S rDNA gene from faeces samples. UPLC-MS metabolomics and custom multiplex cytokine and miRNA analysis (FirePlex™ technology) were used to examine sera samples. Finally, we combined the different data types to search for potential biomarkers. We found that the diversity of bacteria is reduced in fibromyalgia patients. The abundance of the Bifidobacterium and Eubacterium genera (bacteria participating in the metabolism of neurotransmitters in the host) in these patients was significantly reduced. The serum metabolome analysis revealed altered levels of glutamate and serine, suggesting changes in neurotransmitter metabolism. The combined serum metabolomics and gut microbiome datasets showed a certain degree of correlation, reflecting the effect of the microbiome on metabolic activity. We also examined the microbiome and serum metabolites, cytokines and miRNAs as potential sources of molecular biomarkers of fibromyalgia. Our results show that the microbiome analysis provides more significant biomarkers than the other techniques employed in the work. Gut microbiome analysis combined with serum metabolomics can shed new light onto the pathogenesis of fibromyalgia. We provide a list of bacteria whose abundance changes in this disease and propose several molecules as potential biomarkers that can be used to evaluate the current diagnostic criteria.

Urine contains extracellular vesicles (EVs) that concentrate molecules and protect them from degradation. Thus, isolation and characterisation of urinary EVs could increase the efficiency of biomarker discovery. We have previously identified proteins and RNAs with differential abundance in urinary EVs from prostate cancer (PCa) patients compared to benign prostate hyperplasia (BPH). Here, we focused on the analysis of the metabolites contained in urinary EVs collected from patients with PCa and BPH. Targeted metabolomics analysis of EVs was performed by ultra‐high‐performance liquid chromatography–mass spectrometry. The correlation between metabolites and clinical parameters was studied, and metabolites with differential abundance in PCa urinary EVs were detected and mapped into cellular pathways. We detected 248 metabolites belonging to different chemical families including amino acids and various lipid species. Among these metabolites, 76 exhibited significant differential abundance between PCa and BPH. Interestingly, urine EVs recapitulated many of the metabolic alterations reported in PCa, including phosphathidylcholines, acyl carnitines, citrate and kynurenine. Importantly, we found elevated levels of the steroid hormone, 3beta‐hydroxyandros‐5‐en‐17‐one‐3‐sulphate (dehydroepiandrosterone sulphate) in PCa urinary EVs, in line with the potential elevation of androgen synthesis in this type of cancer. This work supports urinary EVs as a non‐invasive source to infer metabolic changes in PCa.

Although colorectal cancer (CRC) is the second leading cause of death in developed countries, current diagnostic tests for early disease stages are suboptimal. We have performed a combination of UHPLC-MS metabolomics and 16S microbiome analyses on 224 feces samples in order to identify early biomarkers for both advanced adenomas (AD) and CRC. We report differences in fecal levels of cholesteryl esters and sphingolipids in CRC. We identified Fusobacterium, Parvimonas and Staphylococcus to be increased in CRC patients and Lachnospiraceae family to be reduced. We finally described Adlercreutzia to be more abundant in AD patients’ feces. Integration of metabolomics and microbiome data revealed tight interactions between bacteria and host and performed better than FOB test for CRC diagnosis. This study identifies potential early biomarkers that outperform current diagnostic tools and frame them into the stablished gut microbiota role in CRC pathogenesis.

Is it possible to use free and extracellular vesicle-associated microRNAs (miRNAs) from human endometrial fluid (EF) samples as non-invasive biomarkers for implantative endometrium? The free and extracellular vesicle-associated miRNAs can be used to detect implantative endometrium in a non-invasive manner. miRNAs and extracellular vesicles (EVs) from EF have been described as mediators of the embryo–endometrium crosstalk. Therefore, the analysis of miRNA from this fluid could become a non-invasive technique for recognizing implantative endometrium. This analysis could potentially help improve the implantation rates in ART. In this prospective study, we first optimized different protocols for EVs and miRNA analyses using the EF of a setup cohort (n = 72). Then, we examined differentially expressed miRNAs in the EF of women with successful embryo implantation (discovery cohort n = 15/validation cohort n = 30) in comparison with those for whom the implantation had failed (discovery cohort n = 15/validation cohort n = 30). Successful embryo implantation was considered when pregnancy was confirmed by vaginal ultrasound showing a gestational sac 4 weeks after embryo transfer (ET). The EF of the setup cohort was obtained before starting fertility treatment during the natural cycle, 16–21 days after the beginning of menstruation. For the discovery and validation cohorts, the EF was collected from women undergoing frozen ET on Day 5, and the samples were collected immediately before ET. In this study, we compared five different methods; two of them based on direct extraction of RNA and the other three with an EV enrichment step before the RNA extraction. Small RNA sequencing was performed to determine the most efficient method and find a predictive model differentiating between implantative and non-implantative endometrium. The models were confirmed using quantitative PCR in two sets of samples (discovery and validation cohorts) with different implantation outcomes. The protocols using EV enrichment detected more miRNAs than the methods based on direct RNA extraction. The two most efficient protocols (using polymer-based precipitation (PBP): PBP-M and PBP-N) were used to obtain two predictive models (based on three miRNAs) allowing us to distinguish between an implantative and non-implantative endometrium. The first Model 1 (PBP-M) (discovery: AUC = 0.93; P-value = 0.003; validation: AUC = 0.69; P-value = 0.019) used hsa-miR-200b-3p, hsa-miR-24-3p and hsa-miR-148b-3p. Model 2 (PBP-N) (discovery: AUC = 0.92; P-value = 0.0002; validation: AUC = 0.78; P-value = 0.0002) used hsa-miR-200b-3p, hsa-miR-24-3p and hsa-miR-99b-5p. Functional analysis of these miRNAs showed strong association with key implantation processes such as in utero embryonic development or transforming growth factor-beta signaling. The FASTQ data are available in the GEO database (access number GSE178917). One important factor to consider is the inherent variability among the women involved in the trial and among the transferred embryos. The embryos were pre-selected based on morphology, but neither genetic nor molecular studies were conducted, which would have improved the accuracy of our tests. In addition, a limitation in miRNA library construction is the low amount of input RNA. We describe new non-invasive protocols to analyze miRNAs from small volumes of EF. These protocols could be implemented in clinical practice to assess the status of the endometrium before attempting ET. Such evaluation could help to avoid the loss of embryos transferred to a non-implantative endometrium. J.I.-P. was supported by a predoctoral grant from the Basque Government (PRE_2017_0204). This study was partially funded by the Grant for Fertility Innovation (GFI, 2011) from Merck (Darmstadt, Germany). It was also supported by the Spanish Ministry of Economy and Competitiveness MINECO within the National Plan RTI2018-094969-B-I00, the European Union's Horizon 2020 research and innovation program (860303), the Severo Ochoa Centre of Excellence Innovative Research Grant (SEV-2016-0644) and the Instituto de Salud Carlos III (PI20/01131). The funding entities did not play any role in the study design, collection, analysis and interpretation of data, writing of the report or the decision to submit the article for publication. The authors declare no competing interests.

Background and Aims: Alcohol-associated liver disease (ALD) accounts for 70% of liver-related deaths in Europe, with no effective approved therapies. Although mitochondrial dysfunction is one of the earliest manifestations of alcohol-induced injury, restoring mitochondrial activity remains a problematic strategy due to oxidative stress. Here, we identify methylation-controlled J protein (MCJ) as a mediator for ALD progression and hypothesize that targeting MCJ may help in recovering mitochondrial fitness without collateral oxidative damage. Approach and Results: C57BL/6 mice [wild-type (Wt)] Mcj knockout and Mcj liver-specific silencing (MCJ-LSS) underwent the NIAAA dietary protocol (Lieber-DeCarli diet containing 5% (vol/vol) ethanol for 10 days, plus a single binge ethanol feeding at day 11). To evaluate the impact of a restored mitochondrial activity in ALD, the liver, gut, and pancreas were characterized, focusing on lipid metabolism, glucose homeostasis, intestinal permeability, and microbiota composition. MCJ, a protein acting as an endogenous negative regulator of mitochondrial respiration, is downregulated in the early stages of ALD and increases with the severity of the disease. Whole-body deficiency of MCJ is detrimental during ALD because it exacerbates the systemic effects of alcohol abuse through altered intestinal permeability, increased endotoxemia, and dysregulation of pancreatic function, which overall worsens liver injury. On the other hand, liver-specific Mcj silencing prevents main ALD hallmarks, that is, mitochondrial dysfunction, steatosis, inflammation, and oxidative stress, as it restores the NAD⁺/NADH ratio and SIRT1 function, hence preventing de novo lipogenesis and improving lipid oxidation. Conclusions: Improving mitochondrial respiration by liver-specific Mcj silencing might become a novel therapeutic approach for treating ALD.

Accurate diagnosis of colorectal cancer (CRC) still relies on invasive colonoscopy. Noninvasive methods are less sensitive in detecting the disease, particularly in the early stage. In the current work, a metabolomics analysis of fecal samples was carried out by ultra-high-performance liquid chromatography–tandem mass spectroscopy (UPLC-MS/MS). A total of 1380 metabolites were analyzed in a cohort of 120 fecal samples from patients with normal colonoscopy, advanced adenoma (AA) and CRC. Multivariate analysis revealed that metabolic profiles of CRC and AA patients were similar and could be clearly separated from control individuals. Among the 25 significant metabolites, sphingomyelins (SM), lactosylceramides (LacCer), secondary bile acids, polypeptides, formiminoglutamate, heme and cytidine-containing pyrimidines were found to be dysregulated in CRC patients. Supervised random forest (RF) and logistic regression algorithms were employed to build a CRC accurate predicted model consisting of the combination of hemoglobin (Hgb) and bilirubin E,E, lactosyl-N-palmitoyl-sphingosine, glycocholenate sulfate and STLVT with an accuracy, sensitivity and specificity of 91.67% (95% Confidence Interval (CI) 0.7753–0.9825), 0.7 and 1, respectively.