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Human untargeted metabolomics studies annotate only ~10% of molecular features. We introduce reference-data-driven analysis to match metabolomics tandem mass spectrometry (MS/MS) data against metadata-annotated source data as a pseudo-MS/MS reference library. Applying this approach to food source data, we show that it increases MS/MS spectral usage 5.1-fold over conventional structural MS/MS library matches and allows empirical assessment of dietary patterns from untargeted data.

ObjectiveSince previous studies indicate that metabolism is altered in rheumatoid arthritis (RA) fibroblast-like synoviocytes (FLS), we undertook this study to determine if changes in the genome-wide chromatin and DNA states in genes associated with nutrient transporters could help to identify activated metabolic pathways in RA FLS.MethodsData from a previous comprehensive epigenomic study in FLS were analyzed to identify differences in genome-wide states and gene transcription between RA and osteoarthritis. We utilized the single nearest genes to regions of interest for pathway analyses. Homer promoter analysis was used to identify enriched motifs for transcription factors. The role of solute carrier transporters and glutamine metabolism dependence in RA FLS was determined by small interfacing RNA knockdown, functional assays, and incubation with CB-839, a glutaminase inhibitor. We performed 1 H nuclear magnetic resonance to quantify metabolites.ResultsThe unbiased pathway analysis demonstrated that solute carrier-mediated transmembrane transport was one pathway associated with differences in at least 4 genome-wide states or gene transcription. Thirty-four transporters of amino acids and other nutrients were associated with a change in at least 4 epigenetic marks. Functional assays revealed that solute carrier family 4 member 4 (SLC4A4) was critical for invasion, and glutamine was sufficient as an alternate source of energy to glucose. Experiments with CB-839 demonstrated decreased RA FLS invasion and proliferation. Finally, we found enrichment of motifs for c-Myc in several nutrient transporters.ConclusionOur findings demonstrate that changes in the epigenetic landscape of genes are related to nutrient transporters, and metabolic pathways can be used to identify RA-specific targets, including critical solute carrier transporters, enzymes, and transcription factors, to develop novel therapeutic agents.

Osteoarthritis (OA) is a progressive degenerative disease resulting in joint deterioration. Synovial inflammation is present in the OA joint and has been associated with radiographic and pain progression. Several OA risk factors, including ageing, obesity, trauma and mechanical loading, play a role in OA pathogenesis, likely by modifying synovial biology. In addition, other factors, such as mitochondrial dysfunction, damage-associated molecular patterns, cytokines, metabolites and crystals in the synovium, activate synovial cells and mediate synovial inflammation. An understanding of the activated pathways that are involved in OA-related synovial inflammation could form the basis for the stratification of patients and the development of novel therapeutics. This Review focuses on the biology of the OA synovium, how the cells residing in or recruited to the synovium interact with each other, how they become activated, how they contribute to OA progression and their interplay with other joint structures.

Elderly-onset rheumatoid arthritis (EORA) and polymyalgia rheumatica (PMR) are common rheumatic diseases in older adults. Oxylipins are bioactive lipids derived from omega-6 (n-6) and omega-3 (n-3) polyunsaturated fatty acids (PUFAs) that serve as activators or suppressors of systemic inflammation. We hypothesized that arthritis symptoms in older adults were related to oxylipin-related perturbations. Arthritis in older adults (ARTIEL) is an observational prospective cohort with 64 patients older than 60 years of age with newly diagnosed arthritis. Patients’ blood samples at baseline and 3 months posttreatment were compared with 18 controls. A thorough clinical examination was conducted. Serum oxylipins were determined by mass spectrometry. Data processing and statistical analysis were performed in R. Forty-four patients were diagnosed with EORA and 20 with PMR. At diagnosis, EORA patients had a mean DAS28CRP (Disease Activity Score 28 using C-reactive protein) of 5.77 (SD 1.02). One hundred percent of PMR patients reported shoulder pain and 90% reported pelvic pain. Several n-6- and n-3-derived oxylipin species were significantly different between controls and arthritis patients. The ratio of n-3/n-6 PUFA was significantly downregulated in EORA but not in PMR patients as compared to controls. The top two candidates as biomarkers for differentiating PMR from EORA were 4-HDoHE, a hydroxydocosahexaenoic acid, and 8,15-dihydroxy-eicosatrienoic acid (8,15-diHETE). The levels of n-3-derived anti-inflammatory species increased in EORA after treatment. These results suggest that certain oxylipins may be key effectors in arthrtis in older adults and that the imbalance between n-6- and n-3-derived oxylipins might be related to pathobiology in this population.

INTRODUCTION: To study metabolic signatures can be used to identify predictive biomarkers for a patient's therapeutic response. OBJECTIVES: We hypothesized that the characterization of a patients’ metabolic profile, utilizing one-dimensional nuclear magnetic resonance ((1)H-NMR), may predict a response to tocilizumab in patients with rheumatoid arthritis (RA). METHODS: 40 active RA patients meeting the 2010 ACR/EULAR classification criteria initiating treatment with tocilizumab were recruited. Clinical outcomes were determined at baseline, and after six and twelve months of treatment. EULAR response criteria at 6 and 12 months to categorize patients as responders and non-responders. Blood was collected at baseline and after six months of tocilizumab therapy. (1)H-NMR was used to acquire a spectra of plasma samples. Chenomx NMR suite 8.5 was used for metabolite identification and quantification. SPSS v.27 and MetaboAnalyst 4.0 were used for statistical and pathway analysis. RESULTS: Isobutyrate, 3-hydroxybutyrate, lysine, phenylalanine, sn-glycero-3-phosphocholine, tryptophan and tyrosine were significantly elevated in responders at the baseline. OPLS-DA at baseline partially discriminated between RA responders and non-responders. A multivariate diagnostic model showed that concentrations of 3-hydroxybutyrate and phenylalanine improved the ability to specifically predict responders classifying 77.1% of the patients correctly. At 6 months, levels of methylamine, sn-glycero-3-phosphocholine and tryptophan tended to still be low in non-responders. CONCLUSION: The relationship between plasma metabolic profiles and the clinical response to tocilizumab suggests that (1)H-NMR may be a promising tool for RA therapy optimization. More studies are needed to determine if metabolic profiling can predict the response to biological therapies in RA patients.

Human untargeted metabolomics studies succeed in annotating only ~10% of molecular features. We, therefore, introduce reference data-driven analysis that uses the source data as a pseudo-MS/MS reference library to match against human metabolomics MS/MS data. We demonstrate this approach with food source data, allowing an empirical assessment of dietary patterns from untargeted data but is broadly applicable and provides an additional layer of interpretability to metabolomics data.

Monosodium urate crystals (MSUc) induce inflammation invivo without prior priming, raising the possibility of an initial cell-autonomous phase. Here, using genome-wide transcriptomic analysis and biochemical assays, we demonstrate that MSUc alone induce a metabolic-inflammatory transcriptional program in non-primed human and murine macrophages that is markedly distinct to that induced by LPS. Genes uniquely upregulated in response to MSUc belong to lipid and amino acid metabolism, glycolysis, and SLC transporters. This upregulation leads to a metabolic rewiring in sera from individuals and mice with acute gouty arthritis. Mechanistically, the initiating inflammatory-metabolic changes in acute gout flares are regulated through a persistent expression and increased binding of JUN to the promoter of target genes through JNK signaling-but not P38-in a process that is different than after LPS stimulation and independent of inflammasome activation. Finally, pharmacological JNK inhibition limits MSUc-induced inflammation in animal models of acute gouty inflammation.

Gas chromatography-mass spectrometry (GC-MS) represents an analytical technique with significant practical societal impact. Spectral deconvolution is an essential step for interpreting GC-MS data. No public GC-MS repositories that also enable repository-scale analysis exist, in part because deconvolution requires significant user input. We therefore engineered a scalable machine learning workflow for the Global Natural Product Social Molecular Networking (GNPS) analysis platform to enable the mass spectrometry community to store, process, share, annotate, compare, and perform molecular networking of GC-MS data. The workflow performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization, using a Fast Fourier Transform-based strategy to overcome scalability limitations. We introduce a “balance score” that quantifies the reproducibility of fragmentation patterns across all samples. We demonstrate the utility of the platform with breathomics analysis applied to the early detection of oesophago-gastric cancer, and by creating the first molecular spatial map of the human volatilome.

Background Oxylipins are biological lipids that have been implicated in inflammation. We previously found that certain oxylipins correlated with clinical manifestations in psoriatic arthritis (PsA) patients. Here, we compare oxylipin profiles in PsA patients and those with psoriasis (PsO) without inflammatory arthritis to identify oxylipins that associate with specific disease manifestations to better understand disease pathogenesis and identify new biomarkers. Methods Consecutive patients with PsA (who met the CASPAR classification criteria for PsA) and PsO were recruited from the Rheumatology Outpatient Clinic. A thorough clinical examination was performed, including entheseal (Leeds enthesitis index (LEI)) and joint involvement (SJC/TJC 66/68). Patients were evaluated for pain and global disease activity on a visual analog scale (VAS) ranging from 0 to 100. This was followed by disease activity scores calculation: cDAPSA (Disease Activity Index for Psoriatic Arthritis) and Psoriasis Area and Severity Index (PASI). Serum oxylipins were determined by mass spectrometry and their association with clinical characteristics (PASI/LEI and cDAPSA) was analyzed using Metaboanalyst 4.0 and R version 3.6.1. Results Twenty PsO (average age 52 [10.8], 55% males) and 19 PsA patients (average age 60.5 [11.4], 63.1% males) were included. PsO patients had an average body mass index (BMI) of 33.7 (6.84) and an average PASI of 3.8 (4.2). PsA patients had an average BMI of 31.9 (5.6), TJC of 9.3 (10.41), SJC of 3.7 (4.23), with an average cDAPSA of 23.3 (11.4). 63.1% of PsA patients had enthesitis (average LEI 2.2 [3]) and the same percentage had psoriasis (average PASI 3(5]). Sera were analyzed for oxylipin levels. PsO and PsA patients with higher PASI score (> 2.5) had significantly lower serum concentrations of pro-inflammatory oxylipins, most of them arachidonic acid derived (AA). Oxylipin profiling did not associate with cDAPSA. Interestingly, several AA-derived oxylipins (5,15 di-HETE (5S,15S-dihydroxy-6E,8Z,10Z,13E-eicosatetraenoic acid), 5-oxoETE (5-Oxo-eicosatetraenoic acid), PGE2 (prostaglandin E2), 11bPGE2 (11 beta prostaglandin D2), and LTB4 (leukotriene B4)) were significantly increased in PsA patients with enthesitis compared to those without. Conclusions The AA-derived proinflammatory oxylipins were lower in both PsO and PsA patients with higher skin scores. Joint disease activity was not associated with the concentrations of oxylipins. Yet, enthesitis was associated with an increase of AA-derived pro-inflammatory oxylipins in PsA patients. Further studies are needed to determine whether oxylipin profiling can be a good biomarker of enthesitis in PsA patients.

The response of macrophages to monosodium urate crystals (MSUc) is incompletely understood partly due to the use of a toll-like receptor (TLR)-induced priming step in cell lines. Yet, MSUc induce inflammation in vivo without prior priming, raising the possibility of an initial cell-autonomous phase that is TLR-independent. Here, using genome wide transcriptomic analysis and biochemical assays we demonstrate that MSUc alone induce a metabolic-inflammatory transcriptional program in non-primed human and murine macrophages that is markedly distinct to that induced by LPS. Genes uniquely upregulated in response to MSUc belonged to lipid and amino acid metabolism, glycolysis, and SLC transporters. This upregulation led to a metabolic rewiring in sera from individuals and mice with acute gouty arthritis. Mechanistically, the initiating inflammatory-metabolic changes in acute gout flares are regulated through a persistent expression and increased binding of JUN to the promoter of target genes through JNK signaling -but not P38- in a process that is different than after LPS stimulation and unexpectedly independent of inflammasome activation. Finally, pharmacological JNK inhibition limited MSUc-induced inflammation in animal models of acute gouty inflammation. MSUc alone induce a unique strong macrophage activation and distinct phenotype that forces a reconsideration of initiating mechanisms in acute gout flares.

At the 2021 Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) annual meeting, a separate group was created (Young-GRAPPA) to address the challenges of young researchers and physicians beginning their careers. This paper presents the initial organizational framework and different components and aims of this group. We were able to enroll over 50 young researchers as a result of this meeting.

We engineered a machine learning approach, MSHub, to enable auto-deconvolution of gas chromatography–mass spectrometry (GC–MS) data. We then designed workflows to enable the community to store, process, share, annotate, compare and perform molecular networking of GC–MS data within the Global Natural Product Social (GNPS) Molecular Networking analysis platform. MSHub/GNPS performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization and quantifies the reproducibility of fragmentation patterns across samples., Fil: Aksenov, Alexander A. University of California. Skaggs School of Pharmacy and Pharmaceutical Sciences; Estados Unidos, Fil: Aksenov, Alexander A. University of California. Skaggs School of Pharmacy and Pharmaceutical Sciences. Collaborative Mass Spectrometry Innovation Center; Estados Unidos, Fil: Laponogov, Ivan. South Kensington Campus. Imperial College London. Department of Surgery and Cancer; Reino Unido, Fil: Zhang, Zheng. University of California. Skaggs School of Pharmacy and Pharmaceutical Sciences; Estados Unidos, Fil: Doran, Sophie L. F. South Kensington Campus. Imperial College London. Department of Surgery and Cancer; Reino Unido, Fil: Belluomo, Ilaria. South Kensington Campus. Imperial College London. Department of Surgery and Cancer; Reino Unido, Fil: Veselkov, Dennis. Intelligify Limited. Reino Unido. South Kensington Campus. Imperial College. Department of Computing; Reino Unido, Fil: Bittremieux, Wout. University of California. Skaggs School of Pharmacy and Pharmaceutical Sciences; Estados Unidos, Fil: Bittremieux, Wout. University of California. Skaggs School of Pharmacy and Pharmaceutical Sciences. Collaborative Mass Spectrometry Innovation Center; Estados Unidos, Fil: Bittremieux, Wout. University of Antwerp. Department of Computer Science; Belgica, Fil: Nothias, Louis Felix. University of California. Skaggs School of Pharmacy and Pharmaceutical Sciences; Estados Unidos, Fil: Nothias, Louis Felix. University of California. Skaggs School of Pharmacy and Pharmaceutical Sciences. Collaborative Mass Spectrometry Innovation Center; Estados Unidos, Fil: Nothias-Esposito, Mélissa. University of California. Skaggs School of Pharmacy and Pharmaceutical Sciences; Estados Unidos, Fil: Nothias-Esposito, Mélissa. University of California. Skaggs School of Pharmacy and Pharmaceutical Sciences. Collaborative Mass Spectrometry Innovation Center; Estados Unidos, Fil: Maloney, Katherine N. University of California. Skaggs School of Pharmacy and Pharmaceutical Sciences; Estados Unidos, Fil: Maloney, Katherine N. Point Loma Nazarene University. Department of Chemistry; Estados Unidos, Fil: Misra, Biswapriya B. Wake Forest School of Medicine. Section of Molecular Medicine. Department of Internal Medicine. Center for Precision Medicine; Estados Unidos, Fil: Melnik, Alexey V. University of California. Skaggs School of Pharmacy and Pharmaceutical Sciences; Estados Unidos, Fil: Smirnov, Aleksandr. University of North Carolina at Charlotte. Department of Bioinformatics and Genomics; Estados Unidos, Fil: Du, Xiuxia. University of North Carolina at Charlotte. Department of Bioinformatics and Genomics; Estados Unidos, Fil: Jones, Kenneth L. University of North Carolina at Charlotte. Department of Bioinformatics and Genomics; Estados Unidos, Fil: Dorrestein, Kathleen. University of California. Skaggs School of Pharmacy and Pharmaceutical Sciences; Estados Unidos, Fil: Dorrestein, Kathleen. University of California. Skaggs School of Pharmacy and Pharmaceutical Sciences. Collaborative Mass Spectrometry Innovation Center; Estados Unidos, Fil: Panitchpakdi, Morgan. University of California. Skaggs School of Pharmacy and Pharmaceutical Sciences; Estados Unidos, Fil: Ernst, Madeleine. University of California. Skaggs School of Pharmacy and Pharmaceutical Sciences; Estados Unidos, Fil: Ernst, Madeleine. Statens Serum Institut. Danish Center for Neonatal Screening. Department of Congenital Disorders. Section for Clinical Mass Spectrometry; Dinamarca, Fil: van der Hooft, Justin J. J. University of California. Skaggs School of Pharmacy and Pharmaceutical Sciences; Estados Unidos, Fil: van der Hooft, Justin J. J. Wageningen University. Bioinformatics Group; Países Bajos, Fil: Gonzalez, Mabel. Universidad de los Andes. Department of Chemistry; Colombia, Fil: Carazzone, Chiara. Universidad de los Andes. Department of Chemistry; Colombia, Fil: Amézquita, Adolfo. Universidad de los Andes. Department of Biological Sciences; Colombia, Fil: Callewaert, Chris. Center for Microbial Ecology and Technology; Belgica, Fil: Callewaert, Chris. University of California. Department of Pediatrics; Estados Unidos, Fil: Morton, James T. University of California. Department of Pediatrics; Estados Unidos, Fil: Morton, James T. Simons Foundation. Flatiron Institute. Center for Computational Biology; Estados Unidos, Fil: Quinn, Robert A. Michigan State University. Department of Biochemistry and Molecular Biology; Estados Unidos, Fil: Bouslimani, Amina. University of California. Skaggs School of Pharmacy and Pharmaceutical Sciences; Estados Unidos, Fil: Bouslimani, Amina. University of California. Skaggs School of Pharmacy and Pharmaceutical Sciences. Collaborative Mass Spectrometry Innovation Center; Estados Unidos, Fil: Orio, Andrea Albarracín. Universidad Católica de Córdoba. IRNASUS. CONICET. Facultad de Ciencias Agropecuarias; Argentina, Fil: Petras, Daniel. University of California. Skaggs School of Pharmacy and Pharmaceutical Sciences; Estados Unidos, Fil: Petras, Daniel. University of California. Skaggs School of Pharmacy and Pharmaceutical Sciences. Collaborative Mass Spectrometry Innovation Center; Estados Unidos, Fil: Smania, Andrea M. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Departamento de Química Biológica Ranwel Caputto; Argentina, Fil: Smania, Andrea M. Centro de Investigaciones en Química Biológica de Córdoba. Universidad Nacional de Córdoba. CONICET; Argentina, Fil: Couvillion, Sneha P. Pacific Northwest National Laboratory. Biological Sciences Division; Estados Unidos, Fil: Burnet, Meagan C. Pacific Northwest National Laboratory. Biological Sciences Division; Estados Unidos, Fil: Nicora, Carrie D. Pacific Northwest National Laboratory. Biological Sciences Division; Estados Unidos, Fil: Zink, Erika. Pacific Northwest National Laboratory. Biological Sciences Division; Estados Unidos, Fil: Metz, Thomas O. Pacific Northwest National Laboratory. Biological Sciences Division; Estados Unidos, Fil: Artaev, Viatcheslav. LECO Corporation; Estados Unidos, Fil: Humston-Fulmer, Elizabeth. LECO Corporation; Estados Unidos, Fil: Gregor, Rachel. Ben-Gurion University of the Negev. Department of Chemistry and the National Institute for Biotechnology in the Negev; Israel, Fil: Meijler, Michael M. Ben-Gurion University of the Negev. Department of Chemistry and the National Institute for Biotechnology in the Negev; Israel, Fil: Mizrahi, Itzhak. Ben-Gurion University of the Negev. Department of Life Sciences and the National Institute for Biotechnology in the Negev; Israel, Fil: Eyal, Stav. Ben-Gurion University of the Negev. Department of Life Sciences and the National Institute for Biotechnology in the Negev; Israel, Fil: Anderson, Brooke. University of California. Division of Biological Sciences; Estados Unidos, Fil: Dutton, Rachel. University of California. Division of Biological Sciences; Estados Unidos, Fil: Lugan, Raphaël. Université d’Avignon et des Pays du Vaucluse, Agrosciences. UMR Qualisud; Francia, Fil: Boulch, Pauline Le. Université d’Avignon et des Pays du Vaucluse, Agrosciences. UMR Qualisud; Francia, Fil: Guitton, Yann. INRAe. Oniris. Laboratoire d’Etude des Résidus et Contaminants dans les Aliments (LABERCA); Francia, Fil: Prevost, Stephanie. INRAe. Oniris. Laboratoire d’Etude des Résidus et Contaminants dans les Aliments (LABERCA); Francia, Fil: Poirier, Audrey. INRAe. Oniris. Laboratoire d’Etude des Résidus et Contaminants dans les Aliments (LABERCA); Francia, Fil: Dervilly, Gaud. INRAe. Oniris. Laboratoire d’Etude des Résidus et Contaminants dans les Aliments (LABERCA); Francia, Fil: Le Bizec, Bruno. Oniris. Laboratoire d’Etude des Résidus et Contaminants dans les Aliments (LABERCA); Francia, Fil: Fait, Aaron. Ben Gurion University of the Negev. Sede Boqer Campus. The Jacob Blaustein Institutes for Desert Research. The French Associates Institute for Agriculture and Biotechnology of Dryland; Israel, Fil: Persi, Noga Sikron. Ben Gurion University of the Negev. Sede Boqer Campus. The Jacob Blaustein Institutes for Desert Research. The French Associates Institute for Agriculture and Biotechnology of Dryland; Israel, Fil: Song, Chao. Ben Gurion University of the Negev. Sede Boqer Campus. The Jacob Blaustein Institutes for Desert Research. The French Associates Institute for Agriculture and Biotechnology of Dryland; Israel, Fil: Gashu, Kelem. Ben Gurion University of the Negev. Sede Boqer Campus. The Jacob Blaustein Institutes for Desert Research. The French Associates Institute for Agriculture and Biotechnology of Dryland; Israel, Fil: Coras, Roxana. University of California. Department of Medicine. Division of Rheumatology; Estados Unidos, Fil: Guma, Monica. University of California. Department of Medicine. Division of Rheumatology; Estados Unidos, Fil: Manasson, Julia. New York University School of Medicine. Department of Medicine. Division of Rheumatology; Estados Unidos, Fil: Scher, Jose U. New York University School of Medicine. Department of Medicine. Division of Rheumatology; Estados Unidos, Fil: Barupal, Dinesh Kumar. Icahn School of Medicine at Mount Sinai. Department of Environmental Medicine and Public Health; Estados Unidos, Fil: Alseekh, Saleh. Max Planck Institute for Molecular Plant Physiology; Alemania, Fil: Alseekh, Saleh. Center of Plant Systems Biology and Biotechnology (CPSBB); Bulgaria, Fil: Fernie, Alisdair R. Max Planck Institute for Molecular Plant Physiology; Alemania, Fil: Fernie, Alisdair R. Center of Plant Systems Biology and Biotechnology (CPSBB); Bulgaria, Fil: Mirnezami, Reza. Royal Free Hospital NHS Foundation Trust. Department of Colorectal Surgery; Reino Unido, Fil: Vasiliou, Vasilis. Yale University. Yale School of Public Health. Department of Environmental Health Sciences; Estados Unidos, Fil: Schmid, Robin. University of Münster. Institute of Inorganic and Analytical Chemistry; Alemania, Fil: Borisov, Roman S. A.V. Topchiev Institute of Petrochemical Synthesis RAS; Rusia, Fil: Kulikova, Larisa N. Рeoples’ Friendship University of Russia (RUDN University); Rusia, Fil: Knight, Rob. University of California. Department of Pediatrics; Estados Unidos, Fil: Knight, Rob. University of California. UCSD Center for Microbiome Innovation; Estados Unidos, Fil: Knight, Rob. University of California. Department of Bioengineering; Estados Unidos, Fil: Wang, Mingxun. University of California. Skaggs School of Pharmacy and Pharmaceutical Sciences; Estados Unidos, Fil: Wang, Mingxun. University of California. Skaggs School of Pharmacy and Pharmaceutical Sciences. Collaborative Mass Spectrometry Innovation Center; Estados Unidos, Fil: Hanna, George B. South Kensington Campus. Imperial College London. Department of Surgery and Cancer; Reino Unido, Fil: Dorrestein, Pieter C. University of California. Skaggs School of Pharmacy and Pharmaceutical Sciences; Estados Unidos, Fil: Dorrestein, Pieter C. University of California. Skaggs School of Pharmacy and Pharmaceutical Sciences. Collaborative Mass Spectrometry Innovation Center; Estados Unidos, Fil: Dorrestein, Pieter C. University of California. Department of Pediatrics; Estados Unidos, Fil: Veselkov, Kirill. South Kensington Campus. Imperial College London. Department of Surgery and Cancer; Reino Unido

SummaryThe human metabolome has remained largely unknown, with most studies annotating ∼10% of features. In nucleic acid sequencing, annotating transcripts by source has proven essential for understanding gene function. Here we generalize this concept to stool, plasma, urine and other human metabolomes, discovering that food-based annotations increase the interpreted fraction of molecular features 7-fold, providing a general framework for expanding the interpretability of human metabolomic “dark matter.”

OBJECTIVE. Eicosanoids modulate inflammation via complex networks involving different pathways and downstream mediators, including oxylipins. Although altered eicosanoids are linked to rheumatoid arthritis (RA), suggesting that metabolization is enhanced, the role of oxylipins in disease stratification remains unexplored. This study was undertaken to characterize oxylipin networks during the earliest stages of RA and evaluate their associations with clinical features and treatment outcomes. METHODS. In total, 60 patients with early RA (according to the American College of Rheumatology/European League Against Rheumatism 2010 criteria), 11 individuals with clinically suspect arthralgia (CSA), and 28 healthy control subjects were recruited. Serum samples were collected at the time of onset. In the early RA group, 50 patients who had not been exposed to disease-modifying antirheumatic drug (DMARD) or glucocorticoid treatment at the time of recruitment were prospectively followed up at 6 and 12 months after having received conventional synthetic DMARDs. A total of 75 oxylipins, mostly derived from arachidonic, eicosapentanoic, and linoleic acids, were identified in the serum by liquid chromatography tandem mass spectrometry. RESULTS. Univariate analyses demonstrated differences in expression patterns of 14 oxylipins across the RA, CSA, and healthy control groups, with each exhibiting a different trajectory. Network analyses revealed a strong grouping pattern of oxylipins in RA patients, whereas in individuals with CSA, a fuzzy network of oxylipins with higher degree and closeness was found. Partial least-squares discriminant analyses yielded variable important projection scores of >1 for 22 oxylipins, which allowed the identification of 2 clusters. Cluster usage differed among the groups (P = 0.003), and showed associations with disease severity and low rates of remission at 6 and 12 months in RA patients who were initially treatment-naive. Pathway enrichment analyses revealed different precursors and pathways between the groups, highlighting the relevance of the arachidonic acid pathway in individuals with CSA and the lipooxygenase pathway in patients with early RA. In applying distinct oxylipin signatures, subsets of seropositive and seronegative RA could be identified. CONCLUSION. Oxylipin networks differ across stages during the earliest phases of RA. These distinct oxylipin networks could potentially elucidate pathways with clinical relevance for disease progression, clinical heterogeneity, and treatment response.

Background: Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease that affects synovial joints, leading to inflammation, joint destruction, loss of function, and disability. Although recent pharmaceutical advances have improved treatment of RA, patients with RA often inquire about dietary interventions to improve RA symptoms, as they perceive rapid changes in their symptoms after consumption of certain foods. There is evidence that some ingredients have pro- or anti-inflammatory effects. In addition, recent literature has shown a link between diet and microbiome changes. Both diet and the gut microbiome are linked to circulating metabolites that may modulate inflammation. However, evidence of the effects of an anti-inflammatory and probiotic-rich diet in patients with RA is scarce. There is also a need for biological data to support its anti-inflammatory effects. Methods: The main goal of this study is to delineate the design process for a diet tailored to our RA population. To achieve this goal, we collected information on diet, supplements, cooking methods, and intake of different ingredients for each patient. Different groups were interviewed, and their feedback was assessed to design a diet that incorporates suggested anti-inflammatory ingredients in a manner that was easy for patients to adopt based on their lifestyles and backgrounds. Results: We designed a diet that includes a high intake of potential anti-inflammatory ingredients. Feedback from highly motivated patients was critical in constructing an anti-inflammatory diet (ITIS diet) with elevated adherence. Conclusion: In order to tailor our diet, we surveyed our patients on several different parameters. We obtained important feedback on how feasible our ITIS diet is for RA patients. Using this feedback, we made minor improvements and finalized the design of the ITIS diet. This diet is being used in an on-going pilot study to determine their anti-inflammatory effect in pain and joint swelling in RA patients. Trial registration: Not applicable. Keywords: Rheumatoid arthritis, Diet design, Anti-inflammatory diet, ITIS diet, Microbiome

Objective To characterize the ecological effects of biologic therapies on the gut bacterial and fungal microbiome in psoriatic arthritis (PsA)/spondyloarthritis (SpA) patients. Methods Fecal samples from PsA/SpA patients pre- and posttreatment with tumor necrosis factor inhibitors (TNFi; n = 15) or an anti-interleukin-17A monoclonal antibody inhibitor (IL-17i; n = 14) underwent sequencing (16S ribosomal RNA, internal transcribed spacer and shotgun metagenomics) and computational microbiome analysis. Fecal levels of fatty acid metabolites and cytokines/proteins implicated in PsA/SpA pathogenesis or intestinal inflammation were correlated with sequence data. Additionally, ileal biopsies obtained from SpA patients who developed clinically overt Crohn's disease (CD) after treatment with IL-17i (n = 5) were analyzed for expression of IL-23/Th17-related cytokines, IL-25/IL-17E-producing cells, and type 2 innate lymphoid cells (ILC2s). Results There were significant shifts in abundance of specific taxa after treatment with IL-17i compared to TNFi, particularly Clostridiales (P = 0.016) and Candida albicans (P = 0.041). These subclinical alterations correlated with changes in bacterial community co-occurrence, metabolic pathways, IL-23/Th17-related cytokines, and various fatty acids. Ileal biopsies showed that clinically overt CD was associated with expansion of IL-25/IL-17E-producing tuft cells and ILC2s (P < 0.05), compared to pre-IL-17i treatment levels. Conclusion In a subgroup of SpA patients, the initiation of IL-17A blockade correlated with features of subclinical gut inflammation and intestinal dysbiosis of certain bacterial and fungal taxa, most notably C albicans. Further, IL-17i-related CD was associated with overexpression of IL-25/IL-17E-producing tuft cells and ILC2s. These results may help to explain the potential link between inhibition of a specific IL-17 pathway and the (sub)clinical gut inflammation observed in SpA.

We present ReDU ( https://redu.ucsd.edu/ ), a system for metadata capture of public mass spectrometry-based metabolomics data, with validated controlled vocabularies. Systematic capture of knowledge enables the reanalysis of public data and/or co-analysis of one’s own data. ReDU enables multiple types of analyses, including finding chemicals and associated metadata, comparing the shared and different chemicals between groups of samples, and metadata-filtered, repository-scale molecular networking. Repository-scale reanalysis of public mass spectrometry-based metabolomics data is facilitated by the Reanalysis of Data User (ReDU) interface, a system that uses consistent formatting and controlled vocabularies for metadata capture.

The human metabolome has remained largely unknown, with most studies annotating ~10% of features. In nucleic acid sequencing, annotating transcripts by source has proven essential for understanding gene function. Here we generalize this concept to stool, plasma, urine and other human metabolomes, discovering that food-based annotations increase the interpreted fraction of molecular features 7-fold, providing a general framework for expanding the interpretability of human metabolomic “dark matter.”

Rheumatoid arthritis (RA) is a systemic, immune-mediated inflammatory disease that has transitioned from a debilitating disease to a chronic, controllable disease. This has been possible due to the introduction of new treatment strategies like “treat-to-target”, in which the clinician treats the patient aggressively enough to reach low disease activity or remission, and the introduction of new therapeutic agents, such as biological therapies, which can lead to the prevention of damage by early diagnosis and initiation of treatment. Attention is now being directed towards identifying the optimal treatment for each patient, one that will be the most efficient and have the least number of side effects. Much work has been done to find serological and synovial biomarkers of response to various RA treatments. Proteomics, genomics and, in the past few years, metabolomics, have all been used in the quest of identifying these biomarkers. Blood-based liquid biopsies provide a minimally invasive alternative to synovial biopsies to identify cellular and molecular signatures that can be used to longitudinally monitor response and allow for personalized medicine approach. Liquid biopsies are comprised of cell free DNA, immune circulating cells, and extracellular vesicles, and are being increasingly and successfully used in the field of oncology for diagnosis, progression, prognosis, and prediction of response to treatment. Recently, researchers have also begun investigating the usefulness of liquid biopsies in the field of rheumatology; in this review we will focus on the potential of liquid biopsy blood samples as biomarkers of response to treatment in patients with RA.

Metabolomics data are difficult to find and reuse, even in public repositories. We, therefore, developed the Reanalysis of Data User (ReDU) interface (https://redu.ucsd.edu/), a community- and data-driven approach that solves this problem at the repository scale. ReDU enables public data discovery and co- or re-analysis via uniformly formatted, publicly available MS/MS data and metadata in the Global Natural Product Social Molecular Networking Platform (GNPS), consistent with findable, accessible, interoperable, and reusable (FAIR) principles.1

Background Elderly-onset RA (EORA), which is defined as rheumatoid arthritis (RA) with an onset at >60 years of age, and polymyalgia rheumatica (PMR) are common rheumatic diseases in the elderly. Eicosanoids are biological lipids that serve a specific role as either activators or suppressors of systemic inflammation and have been involved in the development and progression of arthritis. Objectives We hypothesized that eicosanoid-related perturbations are related to arthritic symptoms in the elderly, and that by defining this eicosanoid profile, we might be able to define elements of inflammation pathobiology in this population. Methods Arthritis in the Elderly (ARTIEL) is a recent collection cohort with patients older than 60 years of age who have newly diagnosed arthritis. Blood samples were collected from these patients at baseline (pre-treatment) and 3 months after treatment, along with physician and patient outcome measures through 12 months. These patients were also compared with randomly-selected control individuals of the same age and gender. A thorough clinical examination was conducted and patients completed a health assessment questionnaire (HAQ). Disease activity score (DAS)28CRP was also calculated. Serum eicosanoids were determined by mass spectrometry at baseline and after 3 months of treatment and were classified into groups according to their eicosanoid precursors: eicosapentaenoic acid (EPA), docosohexanoic acid (DHA) or arachidonic acid (AA). Data processing and statistical analysis were performed in R. Results 64 patients (average: 75.15, standard deviation (SD) 6.80) and 18 controls (average: 75.39, SD, 6.04) were analyzed. Of these, 44 were diagnosed with RA and 20 with PMR. At the start of the study, patients had a mean DAS28CRP of 5.72 (SD, 1.05) and a mean HAQ of 1.64 (SD, 0.73). In addition, 84% of the patients reported scapular pain and 56% reported pelvic pain at baseline. After three months of treatment, patients had a mean DAS28CRP of 2.38 (SD, 1.23) and a mean HAQ of 0.36 (SD, 0.41). Several eicosanoids, especially anti-inflammatory species derived from EPA and DHA, were significantly downregulated in both RA and PMR patients at the start of the study as compared to normal controls (Figure 1). Three months after treatment, the levels of anti-inflammatory eicosanoid species derived from EPA and DHA went back to normal only in patients who responded to therapy. Conclusion These results suggest that certain eicosanoids may be key effectors in arthritis in the elderly and that the imbalance between pro and anti-inflammatory eicosanoids before and after treatment might be related to clinical and therapeutic outcomes in this population. References [1] A systematic review on the role of eicosanoid pathways in rheumatoid arthritis. Hoxha M. Adv Med Sci. 2018 Mar;63(1):22-29. [2] Kobak S, Bes C. An autumn tale: geriatric rheumatoid arthritis. Therapeutic advances in musculoskeletal disease. 2018 Jan;10(1):3-11. PMID: 29290762 [3] Quehenberger O, Dennis EA. The human plasma lipidome. New England Journal of Medicine. 2011 Nov 10;365(19):1812-23. PMID: 22070478 Disclosure of Interests Roxana Coras: None declared, Rekha Narasimhan: None declared, Arthur Kavanaugh Grant/research support from: UCB Pharma, Lourdes Mateo Soria: None declared, Oswald Quehenberger: None declared, Monica Guma: None declared, Melania Martinez-Morillo: None declared

Introduction Eicosanoids are biological lipids that serve as both activators and suppressors of inflammation. Eicosanoid pathways are implicated in synovitis and joint destruction in inflammatory arthritis, yet they might also have a protective function, underscoring the need for a comprehensive understanding of how eicosanoid pathways might be imbalanced. Until recently, sensitive and scalable methods for detecting and quantifying a high number of eicosanoids have not been available. Objective Here, we intend to describe a detailed eicosanoid profiling in patients with psoriatic arthritis (PsA) and evaluate correlations with parameters of disease activity. Methods Forty-one patients with PsA, all of whom satisfied the CASPAR classification criteria for PsA, were studied. Outcomes reflecting the activity of peripheral arthritis as well as skin psoriasis, Disease Activity Score (DAS)28, Clinical Disease Index (CDAI) and Body Surface Area (BSA) were assessed. Serum eicosanoids were determined by LC-MS, and the correlation between metabolite levels and disease scores was evaluated. Results Sixty-six eicosanoids were identified by reverse-phase LC/MS. Certain eicosanoids species including several pro-inflammatory eicosanoids such as PGE2, HXB3 or 6,15-dk,dh,PGF1a correlated with joint disease score. Several eicosapentaenoic acid (EPA)-derived eicosanoids, which associate with anti-inflammatory properties, such as 11-HEPE, 12-HEPE and 15-HEPE, correlated with DAS28 (Disease Activity Score) and CDAI (Clinical Disease Activity Index) as well. Of interest, resolvin D1, a DHA-derived anti-inflammatory eicosanoid, was down-regulated in patients with high disease activity. Conclusion Both pro- and anti-inflammatory eicosanoids were associated with joint disease score, potentially representing pathways of harm as well as benefit. Further studies are needed to determine whether these eicosanoid species might also play a role in the pathogenesis of joint inflammation in PsA.

Background:traditional approaches and lipidomics support the relevance of eicosanoids in rheumatic conditions, such as rheumatoid arthritis (RA). Previous studies from our group and others have revealed altered levels of arachidonic acid in RA, pointing to a possible consumption or enhanced metabolisation. However, the potential alterations of its actual metabolites are difficult to assess with conventional approaches, and new, untargeted, high-throughput technologies are needed. More importantly, whether these alterations are related to the disease course and could be found at the very early stage of the disease is unknown.Objectives:to characterize the eicosanoid profiles during the earliest stages of RA and their potential clinical associations.Methods:60 very early RA patients (50 recruited at diagnosis and treatment-naïve) fulfilling 2010 ACR/EULAR criteria, 11 clinical suspect arthralgia (CSA) individuals and 28 healthy controls (HC) were recruited. Samples were collected at the moment of the diagnosis. Serum oxylipins profiles were analyzed by mass spectrometry (LC-MS/MS). Treatment-naïve patients underwent csDMARD treatment and were followed for 6 (n=49) and 12 months (n=38). Data analysis was performed in R and MetaboAnalyst.Results:A total of 75 oxylipins, mostly derived from arachidonic (AA), eicosapentanoic (EPA) and linoleic (LA) acid, were identified. No effect was observed for age, gender or BMI. Correlation and network analyses revealed different patterns among oxylipins across RA patients, CSA and HC (Figure 1A). The 8-HETrE, PGE3 and 20-HETE showed the pattern (linear increase) HC→CSA→RA (p=1.47·10-4, 5.34·10-4 and 5.68·10-4, respectively; and adjusted FDR1 (Figure 1C), which allowed the identification of two clusters (I and II). Cluster usage (I/II) differed among groups (p=0.003): HC (27/1), CSA (7/4) and RA (37/23). Patients exhibiting cluster II showed higher VAS global assessment (p=0.016) and pain (p=0.003) than their cluster I-counterparts. More importantly, cluster II patients were less likely to achieve DAS28 remission at 6 (12/17 vs 10/32, p=0.008) and 12 months (6/9 vs 9/29, p=0.066) upon conventional DMARD treatment compared to those showing cluster I.OPLS-DA analyses revealed a good discrimination between CSA and HC groups, and 7 compounds (13-HODE, PGB2, 9-oxo-ODE, 12-oxo-ETE, 19,20-di-HDPA, 5-HETrE and 15-HEPE) were associated with the course HC->CSA. Different precursors (2 LA, 3 AAA, 1 EPA and 1 DHA) and pathways were noted (3 LOX, 4 CYP450). Regarding RA subsets, differences were noted by seropositivity. Whereas 9 compounds were associated with the pattern HC→seronegative RA (8-HETrE, PGE3, 20-HETE, 19,20-di-HDPA, PGEM, PGJ2, 12-oxo-LTB4, 14,15-EET and LTB4), a distinct set was observed for the pattern HC→seropositive RA (PGE3, 20-oh-PGE2, 5-HETE, PGE2, 12-oxo-ETE, 20-HETE, PGEM, 4-HDoHE, LTB4, 9-oxo-ODE, 12-oxo-LTB4, 8,9-EET). No differences in the major pathways were noted.Conclusion:Oxylipin networks differ across disease stages during the very early phase of RA, and can inform on specific signatures related to the disease progression. Oxylipins can delineate profiles with clinical relevance and are able to predict treatment response.Figure:Disclosure of Interests:None declared

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease that affects synovial joints, leading to inflammation, joint destruction, loss of function, and disability. Although recent pharmaceutical advances have improved the treatment of RA, patients often inquire about dietary interventions to improve RA symptoms, as they perceive pain and/or swelling after the consumption or avoidance of certain foods. There is evidence that some foods have pro- or anti-inflammatory effects mediated by diet-related metabolites. In addition, recent literature has shown a link between diet-related metabolites and microbiome changes, since the gut microbiome is involved in the metabolism of some dietary ingredients. But diet and the gut microbiome are not the only factors linked to circulating pro- and anti-inflammatory metabolites. Other factors including smoking, associated comorbidities, and therapeutic drugs might also modify the circulating metabolomic profile and play a role in RA pathogenesis. This article summarizes what is known about circulating pro- and anti-inflammatory metabolites in RA. It also emphasizes factors that might be involved in their circulating concentrations and diet-related metabolites with a beneficial effect in RA.

Background Metabolomics is an emerging field of biomedical research that may offer a better understanding of the mechanisms of underlying conditions including inflammatory arthritis. Perturbations caused by inflamed synovial tissue can lead to correlated changes in concentrations of certain metabolites in the synovium and thereby function as potential biomarkers in blood. Here, we explore the hypothesis of whether characterization of patients’ metabolomic profiles in blood, utilizing 1H-nuclear magnetic resonance (NMR), predicts synovial marker profiling in rheumatoid arthritis (RA). Methods Nineteen active, seropositive patients with RA, on concomitant methotrexate, were studied. One of the involved joints was a knee or a wrist appropriate for arthroscopy. A Bruker Avance 700 MHz spectrometer was used to acquire NMR spectra of serum samples. Gene expression in synovial tissue obtained by arthroscopy was analyzed by real-time PCR. Data processing and statistical analysis were performed in Python and SPSS. Results Analysis of the relationships between each synovial marker-metabolite pair using linear regression and controlling for age and gender revealed significant clustering within the data. We observed an association of serine/glycine/phenylalanine metabolism and aminoacyl-tRNA biosynthesis with lymphoid cell gene signature. Alanine/aspartate/glutamate metabolism and choline-derived metabolites correlated with TNF-α synovial expression. Circulating ketone bodies were associated with gene expression of synovial metalloproteinases. Discriminant analysis identified serum metabolites that classified patients according to their synovial marker levels. Conclusion The relationship between serum metabolite profiles and synovial biomarker profiling suggests that NMR may be a promising tool for predicting specific pathogenic pathways in the inflamed synovium of patients with RA. Electronic supplementary material The online version of this article (10.1186/s13075-018-1655-3) contains supplementary material, which is available to authorized users.