Urine metabolome profiling of immune-mediated inflammatory diseases

Parent Perspectives of Diagnostic and Monitoring Tests Undertaken by Their Child with Inflammatory Bowel Disease

PURPOSE

To assess parent perspectives of the current and potential future tests for their child with inflammatory bowel disease (IBD).

METHODS

New Zealand parents of a child with IBD were invited to complete an anonymous online survey. Experiences relating to their child's blood or faecal tests, medical imaging (abdominal ultrasound [US], abdominal computerised tomography [CT] and magnetic resonance enterography) and colonoscopy were collected. Perceived attitudes to potential future testing of urine, saliva, and breath, were sought.

RESULTS

Twenty-eight parents, 93% female completed the survey, and 86% were aged between 35 and 54 years. Baseline information was provided by parents for 27 of 28 children, 70.3% had Crohn's disease with a mean disease duration of 2.67 years. Blood tests were the most requested and completed tests, while CT was the least ordered and most refused test. Colonoscopy was rated as the least comfortable and generated the most worry. Explanation of test significantly improved parent's levels of understanding when their child had blood, faecal, imaging (US) or colonoscopy tests. Providing an explanation, test invasiveness and the impact of the blood results may have on their child's treatment significantly improved parents' comfort levels. However, explanation of colonoscopy generated a significant parental concerns. Saliva, urine and blood tests were chosen as the most preferred disease monitoring tests.

CONCLUSION

Parents preferred any tests less invasive than colonoscopy for monitoring their child's IBD. Although providing explanation of their child's tests enhanced parents' understanding, it can also affect parents' levels of concern and comfort.

Time Course of Metabolic Alterations Associated with the Progression of Systemic Lupus Erythematosus in MRL/lpr Mice Based on GC/MS

Exploring the dynamic changes of metabolites and metabolic pathways during the development of the disease can help to further understand the etiology and pathogenesis of systemic lupus erythematosus (SLE). In this study, serum metabolomics based on gas chromatography/mass spectrometry (GC/MS) was employed to investigate the metabolic alterations at different stages of SLE using lupus-prone mice (MRL/lpr) of 9, 11, and 13 weeks of age. Multivariate statistical analysis was performed to view the alterations of metabolic profiles between MRL/lpr mice and age-matched C57BL/6 mice, and t-test and fold change criteria were used to identify differential metabolites at each stage. 11 changed metabolites were found in MRL/lpr mice at 9 weeks of age, which were mainly involved in the tricarboxylic acid (TCA) cycle, glycolysis, and butanoate metabolism; with the increase of week age, the TCA cycle was still disturbed, and the biosynthesis of fatty acids was significantly upregulated since 11 weeks of age; in addition, urea, urate, and indole-3-lactate were increased at 13 weeks of age. We found a time course of metabolic alterations in MRL/lpr mice, which may be related to the progression of SLE. These findings could provide a reference for studying the mechanism of SLE and judging the pathological stage and severity of the disease. The MS data have been deposited in Mendeley (https://www.mendeley.com/).

Prediction of Autoimmune Diseases by Targeted Metabolomic Assay of Urinary Organic Acids

Autoimmune diseases (ADs) are chronic disorders characterized by the loss of self-tolerance, and although being heterogeneous, they share common pathogenic mechanisms. Self-antigens and inflammation markers are established diagnostic tools; however, the metabolic imbalances that underlie ADs are poorly described. The study aimed to employ metabolomics for the detection of disease-related changes in autoimmune diseases that could have predictive value. Quantitative analysis of 28 urine organic acids was performed using Gas Chromatography-Mass Spectrometry in a group of 392 participants. Autoimmune thyroiditis, inflammatory bowel disease, psoriasis and rheumatoid arthritis were the most prevalent autoimmune diseases of the study. Statistically significant differences were observed in the tricarboxylate cycle metabolites, succinate, methylcitrate and malate, the pyroglutamate and 2-hydroxybutyrate from the glutathione cycle and the metabolites methylmalonate, 4-hydroxyphenylpyruvate, 2-hydroxyglutarate and 2-hydroxyisobutyrate between the AD group and the control. Artificial neural networks and Binary logistic regression resulted in the highest predictive accuracy scores (66.7% and 74.9%, respectively), while Methylmalonate, 2-Hydroxyglutarate and 2-hydroxybutyrate were proposed as potential biomarkers for autoimmune diseases. Urine organic acid levels related to the mechanisms of energy production and detoxification were associated with the presence of autoimmune diseases and could be an adjunct tool for early diagnosis and prediction.

Research progress and perspective in metabolism and metabolomics of psoriasis

ABSTRACT

Psoriasis is considered a systemic disease associated with metabolic abnormalities, and it is important to understand the mechanisms by which metabolism affects pathophysiological processes both holistically and systematically. Metabolites are closely related to disease phenotypes, especially in systemic diseases under multifactorial modulation. The emergence of metabolomics has provided information regarding metabolite changes in lesions and circulation and deepened our understanding of the association between metabolic reprogramming and psoriasis. Metabolomics has great potential for the development of effective biomarkers for clinical diagnosis, therapeutic monitoring, prediction of the efficacy of psoriasis management, and further discovery of new metabolism-based therapeutic targets.

Omics-Driven Biomarkers of Psoriasis: Recent Insights, Current Challenges, and Future Prospects

Advances in omics technologies have made it possible to unravel biomarkers from different biological levels. Intensive studies have been carried out to uncover the dysregulations in psoriasis and to identify molecular signatures associated with the pathogenesis of psoriasis. In this review, we presented an overview of the current status of the omics-driven biomarker research and emphasized the transcriptomic, epigenomic, proteomic, metabolomic, and glycomic signatures proposed as psoriasis biomarkers. Furthermore, insights on the limitations and future directions of the current biomarker discovery strategies were discussed, which will continue to comprehend broader visions of psoriasis research, diagnosis, and therapy especially in the context of personalized medicine.

Translational Potential of Metabolomics on Animal Models of Inflammatory Bowel Disease-A Systematic Critical Review

In the development of inflammatory bowel disease (IBD), the gut microbiota has been established as a key factor. Recently, metabolomics has become important for understanding the functional relevance of gut microbial changes in disease. Animal models for IBD enable the study of factors involved in disease development. However, results from animal studies may not represent the human situation. The aim of this study was to investigate whether results from metabolomics studies on animal models for IBD were similar to those from studies on IBD patients. Medline and Embase were searched for relevant studies up to May 2017. The Covidence systematic review software was used for study screening, and quality assessment was conducted for all included studies. Data showed a convergence of ~17% for metabolites differentiated between IBD and controls in human and animal studies with amino acids being the most differentiated metabolite subclass. The acute dextran sodium sulfate model appeared as a good model for analysis of systemic metabolites in IBD, but analytical platform, age, and biological sample type did not show clear correlations with any significant metabolites. In conclusion, this systematic review highlights the variation in metabolomics results, and emphasizes the importance of expanding the applied detection methods to ensure greater coverage and convergence between the various different patient phenotypes and animal models of inflammatory bowel disease.

Metabolomics in the development and progression of rheumatoid arthritis: A systematic review

OBJECTIVE

A systematic review and analysis of data from several rheumatoid arthritis metabolomics studies attempts to determine which metabolites can be used as potential biomarkers for the diagnosis of rheumatoid arthritis and to explore the pathogenesis of rheumatoid arthritis.

METHODS

We searched all the subject-related documents published by EMBASE, PubMed, Web of Science, and Cochrane Library from the database to the September 2019 publication. Two researchers independently screened the literature and extracted the data. QUADOMICS tool was used to assess the quality of studies included in this systematic review.

RESULTS

A total of 10 studies met the inclusion criteria of systematic review, including 502 patients with rheumatoid arthritis and 373 healthy people. Among them, the biological samples utilised for metabolomic analysis include: serum (n=8), urine (n=1) and synovial fluid (n=1). Some metabolites play an important role in rheumatoid arthritis: glucose, lactic acid, citric acid, leucine, methionine, isoleucine, valine, phenylalanine, threonine, serine, proline, glutamate, histidine, alanine, cholesterol, glycerol, and ribose.

CONCLUSIONS

Metabolomics provides important new opportunities for further research in rheumatoid arthritis and is expected to elucidate the pathogenesis of rheumatoid arthritis that has not been fully understood before.

Fatty Acid and Carnitine Metabolism Are Dysregulated in Systemic Sclerosis Patients

Systemic sclerosis (SSc) is a rare chronic disease of unknown pathogenesis characterized by fibrosis of the skin and internal organs, vascular alteration, and dysregulation of the immune system. In order to better understand the immune system and its perturbations leading to diseases, the study of the mechanisms regulating cellular metabolism has gained a widespread interest. Here, we have assessed the metabolic status of plasma and dendritic cells (DCs) in patients with SSc. We identified a dysregulated metabolomic signature in carnitine in circulation (plasma) and intracellularly in DCs of SSc patients. In addition, we confirmed carnitine alteration in the circulation of SSc patients in three independent plasma measurements from two different cohorts and identified dysregulation of fatty acids. We hypothesized that fatty acid and carnitine alterations contribute to potentiation of inflammation in SSc. Incubation of healthy and SSc dendritic cells with etoposide, a carnitine transporter inhibitor, inhibited the production of pro-inflammatory cytokines such as IL-6 through inhibition of fatty acid oxidation. These findings shed light on the altered metabolic status of the immune system in SSc patients and opens up for potential novel avenues to reduce inflammation.

Urinary proteome and metabolome in dogs (Canis lupus familiaris): The effect of chronic kidney disease

Chronic kidney disease (CKD) is a progressive and irreversible disease. Although urine is an ideal biological sample for proteomics and metabolomics studies, sensitive and specific biomarkers are currently lacking in dogs. This study characterised dog urine proteome and metabolome aiming to identify and possibly quantify putative biomarkers of CKD in dogs. Twenty-two healthy dogs and 28 dogs with spontaneous CKD were selected and urine samples were collected. Urinary proteome was separated by SDS-PAGE and analysed by mass spectrometry, while urinary metabolome was analysed in protein-depleted samples by 1D ¹H NMR spectra. The most abundant proteins in urine samples from healthy dogs were uromodulin, albumin and, in entire male dogs, arginine esterase. In urine samples from CKD dogs, the concentrations of uromodulin and albumin were significantly lower and higher, respectively, than in healthy dogs. In addition, these samples were characterised by a more complex protein pattern indicating mixed glomerular (protein bands ≥65 kDa) and tubular (protein bands <65 kDa) proteinuria. Urine spectra acquired by NMR allowed the identification of 86 metabolites in healthy dogs, belonging to 49 different pathways mainly involved in amino acid metabolism, purine and aminoacyl-tRNA biosynthesis or tricarboxylic acid cycle. Seventeen metabolites showed significantly different concentrations when comparing healthy and CKD dogs. In particular, carnosine, trigonelline, and cis-aconitate, might be suggested as putative biomarkers of CKD in dogs. SIGNIFICANCE: Urine is an ideal biological sample, however few proteomics and metabolomics studies investigated this fluid in dogs and in the context of CKD (chronic kidney disease). In this research, applying a multi-omics approach, new insights were gained regarding the molecular changes triggered by this disease in canine urinary proteome and metabolome. In particular, the involvement of the tubular component was highlighted, suggesting uromodulin, trigonelline and carnosine as possible biomarkers of CKD in dogs.

Nuclear magnetic resonance-based targeted profiling of urinary acetate and citrate following cyclophosphamide therapy in patients with lupus nephritis

OBJECTIVE

Metabolomics, the study of global alterations in small metabolites, is a useful tool to look for novel biomarkers. Recently, we reported a reprogramming of the serum metabolomic profile by nuclear magnetic resonance (NMR) spectroscopy following treatment in lupus nephritis (LN). This study aimed to compare the urine excretory levels of citrate and acetate in patients with biopsy-proven LN before and six months after cyclophosphamide induction therapy and to evaluate their correlation with the Systemic Lupus Erythematosus Disease Activity Index 2K (SLEDAI 2K) and renal SLEDAI.

METHODS

Urine obtained from LN patients (N = 18, 16 female) at diagnosis and six months following induction therapy with cyclophosphamide and healthy controls (HC; N = 18, median age = 35 years, all female) were stored at -80°C. Metabolomic profiling was done using high resolution 800 MHz 1D ¹H NMR spectroscopy. The urinary ratio of metabolites was calculated as (metabolite×1000)/creatinine. Disease activity was measured using the SLEDAI. Metabolomic profiles were compared between groups and correlated with clinical parameters.

RESULTS

Compared to HC, LN patients had significantly lower median urinary citrate/creatinine levels (LN = 18.26, range 12.80-27.62; HC = 107.7, range 65.39-138.4; p < 0.0001) which significantly increased after six months of cyclophosphamide treatment (51.05, range 11.51-170.2; p = 0.03). LN patients also differed from HC by having a higher mean urinary acetate/creatinine ratio (LN = 17.44, range 11.6-32.7; HC = 9.61, range 7.97-13.71; p = 0.054) with a non-significant fall in values after six months of treatment. The Area under curve for differentiating LN from HC for urinary citrate was 0.9136, and urinary acetate was 0.6883. The urinary acetate levels correlated with SLEDAI (r = 0.337, p = 0.048). Urinary citrate levels correlated positively with C3 (r = 0.362, p = 0.03) and negatively with urine protein/creatinine (r = -0.346, p = 0.039).

CONCLUSIONS

Urinary citrate, which reflects dampened aerobic glycolysis and oxidative phosphorylation, improved significantly and is a potential non-invasive biomarker for diagnosis and monitoring treatment response in LN.

Microbiota and metabolites in rheumatic diseases

As a gigantic community in the human body, the microbiota exerts pleiotropic roles in human health and disease ranging from digestion and absorption of nutrients from food, defense against infection of pathogens, to regulation of immune system development and immune homeostasis. Recent advances in "omics" studies and bioinformatics analyses have broadened our insights of the microbiota composition of the inner and other surfaces of the body and their interactions with the host. Apart from the direct contact of microbes at the mucosal barrier, metabolites produced or metabolized by the gut microbes can serve as important immune regulators or initiators in a wide variety of diseases, including gastrointestinal diseases, metabolic disorders and systemic rheumatic diseases. This review focuses on the most recent understanding of how the microbiota and metabolites shape rheumatic diseases. Studies that explore the mechanistic interplay between microbes, metabolites and the host could thereby provide clues for novel methods in the diagnosis, therapy, and prevention of rheumatic diseases.

Discovering new metabolite alterations in primary sjögren's syndrome in urinary and plasma samples using an HPLC-ESI-QTOF-MS methodology

Sjögren's Syndrome (SjS) is a complex autoimmune disease characterized by the affection of the exocrine glands and the involvement of multiple organs. Although a greater number of biomarker studies have been carried out in recent years, the origin and pathogenesis are not yet well known and therefore there is a need to continue studying this pathology. This work aims to find metabolic changes in biological samples (plasma and urine), which could help identify the metabolic pathways affected by the SjS pathogenesis. The samples collected from SjS patients and healthy volunteers were analyzed by a fingerprinting metabolomic approach based on HPLC-ESI-QTOF-MS methodology. After feature pre-selection by univariate statistical tests, an integrated PLS-DA model using data from urine and plasma was constructed obtaining a good classification between cases and controls (AUROC = 0.839 ± 0.021). 31 and 38 metabolites in plasma and urine, respectively, showed significant differences between healthy volunteers and SjS patients and were proposed for their identification. From them, 12 plasma and 24 urinary metabolites could be annotated. In general, the main metabolic pathways altered in SjS patients were related to the metabolism of phospholipids, fatty acids, and amino acids, specially tryptophan, proline and phenylalanine.

Real-time health monitoring through urine metabolomics

Current healthcare practices are reactive and based on limited physiological information collected months or years apart. By enabling patients and healthy consumers access to continuous measurements of health, wearable devices and digital medicine stand to realize highly personalized and preventative care. However, most current digital technologies provide information on a limited set of physiological traits, such as heart rate and step count, which alone offer little insight into the etiology of most diseases. Here we propose to integrate data from biohealth smartphone applications with continuous metabolic phenotypes derived from urine metabolites. This combination of molecular phenotypes with quantitative measurements of lifestyle reflect the biological consequences of human behavior in real time. We present data from an observational study involving two healthy subjects and discuss the challenges, opportunities, and implications of integrating this new layer of physiological information into digital medicine. Though our dataset is limited to two subjects, our analysis (also available through an interactive web-based visualization tool) provides an initial framework to monitor lifestyle factors, such as nutrition, drug metabolism, exercise, and sleep using urine metabolites.

Targeted Metabolomic Analysis of Serum Fatty Acids for the Prediction of Autoimmune Diseases

Autoimmune diseases (ADs) are rapidly increasing worldwide and accumulating data support a key role of disrupted metabolism in ADs. This study aimed to identify an improved combination of Total Fatty Acids (TFAs) biomarkers as a predictive factor for the presence of autoimmune diseases. A retrospective nested case-control study was conducted in 403 individuals. In the case group, 240 patients diagnosed with rheumatoid arthritis, thyroid disease, multiple sclerosis, vitiligo, psoriasis, inflammatory bowel disease, and other AD were included and compared to 163 healthy individuals. Targeted metabolomic analysis of serum TFAs was performed using GC-MS, and 28 variables were used as input for the predictive models. The primary analysis identified 12 variables that were statistically significantly different between the two groups, and metabolite-metabolite correlation analysis revealed 653 significant correlation coefficients with 90% level of significance (p < 0.05). Three predictive models were developed, namely (a) a logistic regression based on Principal Component Analysis (PCA), (b) a straightforward logistic regression model and (c) an Artificial Neural Network (ANN) model. PCA and straightforward logistic regression analysis, indicated reasonably well adequacy (74.7 and 78.9%, respectively). For the ANN, a model using two hidden layers and 11 variables was developed, resulting in 76.2% total predictive accuracy. The models identified important biomarkers: lauric acid (C12:0), myristic acid (C14:0), stearic acid (C18:0), lignoceric acid (C24:0), palmitic acid (C16:0) and heptadecanoic acid (C17:0) among saturated fatty acids, Cis-10-pentadecanoic acid (C15:1), Cis-11-eicosenoic acid (C20:1n9), and erucic acid (C22:1n9) among monounsaturated fatty acids and the Gamma-linolenic acid (C18:3n6) polyunsaturated fatty acid. The metabolic pathways of the candidate biomarkers are discussed in relation to ADs. The findings indicate that the metabolic profile of serum TFAs is associated with the presence of ADs and can be an adjunct tool for the early diagnosis of ADs.

Selective Histone Deacetylase 6 Inhibition Normalizes B Cell Activation and Germinal Center Formation in a Model of Systemic Lupus Erythematosus

Autoantibody production by plasma cells (PCs) plays a pivotal role in the pathogenesis of systemic lupus erythematosus (SLE). The molecular pathways by which B cells become pathogenic PC secreting autoantibodies in SLE are incompletely characterized. Histone deactylase 6 (HDAC6) is a unique cytoplasmic HDAC that modifies the interaction of a number of tubulin- associated proteins; inhibition of HDAC6 has been shown to be beneficial in murine models of SLE, but the downstream pathways accounting for the therapeutic benefit have not been clearly delineated. In the current study, we sought to determine whether selective HDAC6 inhibition would abrogate abnormal B cell activation in SLE. We treated NZB/W lupus mice with the selective HDAC6 inhibitor, ACY-738, for 4 weeks beginning at 20 weeks-of age. After only 4 weeks of treatment, manifestation of lupus nephritis (LN) were greatly reduced in these animals. We then used RNAseq to determine the genomic signatures of splenocytes from treated and untreated mice and applied computational cellular and pathway analysis to reveal multiple signaling events associated with B cell activation and differentiation in SLE that were modulated by HDAC6 inhibition. PC development was abrogated and germinal center (GC) formation was greatly reduced. When the HDAC6 inhibitor-treated lupus mouse gene signatures were compared to human lupus patient gene signatures, the results showed numerous immune, and inflammatory pathways increased in active human lupus were significantly decreased in the HDAC6 inhibitor treated animals. Pathway analysis suggested alterations in cellular metabolism might contribute to the normalization of lupus mouse spleen genomic signatures, and this was confirmed by direct measurement of the impact of the HDAC6 inhibitor on metabolic activities of murine spleen cells. Taken together, these studies show HDAC6 inhibition decreases B cell activation signaling pathways and reduces PC differentiation in SLE and suggest that a critical event might be modulation of cellular metabolism.

Profiling of Amino Acids in Urine Samples of Patients Suffering from Inflammatory Bowel Disease by Capillary Electrophoresis-Mass Spectrometry

Urine represents a convenient biofluid for metabolomic studies due to its noninvasive collection and richness in metabolites. Here, amino acids are valuable biomarkers for their ability to reflect imbalances of different biochemical pathways. An impact of amino acids on pathology, prognosis and therapy of various diseases, including inflammatory bowel disease (IBD), is therefore the subject of current clinical research. This work is aimed to develop a capillary electrophoresis-tandem mass spectrometry (CE-MS/MS) method for the quantification of the 20 proteinogenic amino acids in human urine samples obtained from patients suffering from IBD and treated with thiopurines. The optimized CE-MS/MS method, with minimum sample preparation (just “dilute and shoot”), exhibited excellent linearity for all the analytes (coefficients of determination were higher than 0.99), with inter-day and intra-day precision yielding relative standard deviations in the range of 0.91–15.12% and with accuracy yielding relative errors in the range of 85.47–112.46%. Total analysis time, an important parameter for the sample throughput demanded in routine practice, was shorter in ca. 17% when compared to established CE-MS methods. Favorable performance of the proposed CE-MS/MS method was also confirmed by the comparison with corresponding ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS) method. Consistent data for the investigated amino acid metabolome were obtained using both methods. For the first time, the amino acid profiling by CE-MS approach was applied on the clinical IBD samples. Here, significant differences observed in the concentration levels of some amino acids between IBD patients undergoing thiopurine treatment and healthy volunteers could result from the simultaneous action of the disease and the corresponding therapy. These findings indicate that amino acids analysis could be a valuable tool for the study of mechanism of the IBD treatment by thiopurines.

Can Metabolic Pathways Be Therapeutic Targets in Rheumatoid Arthritis?

The metabolic rewiring of tumor cells and immune cells has been viewed as a promising source of novel drug targets. Many of the molecular pathways implicated in rheumatoid arthritis (RA) directly modify synovium metabolism and transform the resident cells, such as the fibroblast-like synoviocytes (FLS), and the synovial tissue macrophages (STM), toward an overproduction of enzymes, which degrade cartilage and bone, and cytokines, which promote immune cell infiltration. Recent studies have shown metabolic changes in stromal and immune cells from RA patients. Metabolic disruption in the synovium provide the opportunity to use in vivo metabolism-based imaging techniques for patient stratification and to monitor treatment response. In addition, these metabolic changes may be therapeutically targetable. Thus, resetting metabolism of the synovial membrane offers additional opportunities for disease modulation and restoration of homeostasis in RA. In fact, rheumatologists already use the antimetabolite methotrexate, a chemotherapy agent, for the treatment of patients with inflammatory arthritis. Metabolic targets that do not compromise systemic homeostasis or corresponding metabolic functions in normal cells could increase the drug armamentarium in rheumatic diseases for combination therapy independent of systemic immunosuppression. This article summarizes what is known about metabolism in synovial tissue cells and highlights chemotherapies that target metabolism as potential future therapeutic strategies for RA.

Assessing the Effectiveness of Direct Data Merging Strategy in Long-Term and Large-Scale Pharmacometabonomics

Because of the extended period of clinic data collection and huge size of analyzed samples, the long-term and large-scale pharmacometabonomics profiling is frequently encountered in the discovery of drug/target and the guidance of personalized medicine. So far, integration of the results (ReIn) from multiple experiments in a large-scale metabolomic profiling has become a widely used strategy for enhancing the reliability and robustness of analytical results, and the strategy of direct data merging (DiMe) among experiments is also proposed to increase statistical power, reduce experimental bias, enhance reproducibility and improve overall biological understanding. However, compared with the ReIn, the DiMe has not yet been widely adopted in current metabolomics studies, due to the difficulty in removing unwanted variations and the inexistence of prior knowledges on the performance of the available merging methods. It is therefore urgently needed to clarify whether DiMe can enhance the performance of metabolic profiling or not. Herein, the performance of DiMe on 4 pairs of benchmark datasets was comprehensively assessed by multiple criteria (classification capacity, robustness and false discovery rate). As a result, integration/merging-based strategies (ReIn and DiMe) were found to perform better under all criteria than those strategies based on single experiment. Moreover, DiMe was discovered to outperform ReIn in classification capacity and robustness, while the ReIn showed superior capacity in controlling false discovery rate. In conclusion, these findings provided valuable guidance to the selection of suitable analytical strategy for current metabolomics.

Biomarker Discovery for Immunotherapy of Pituitary Adenomas: Enhanced Robustness and Prediction Ability by Modern Computational Tools

Pituitary adenoma (PA) is prevalent in the general population. Due to its severe complications and aggressive infiltration into the surrounding brain structure, the effective management of PA is required. Till now, no drug has been approved for treating non-functional PA, and the removal of cancerous cells from the pituitary is still under experimental investigation. Due to its superior specificity and safety profile, immunotherapy stands as one of the most promising strategies for dealing with PA refractory to the standard treatment, and various studies have been carried out to discover immune-related gene markers as target candidates. However, the lists of gene markers identified among different studies are reported to be highly inconsistent because of the greatly limited number of samples analyzed in each study. It is thus essential to substantially enlarge the sample size and comprehensively assess the robustness of the identified immune-related gene markers. Herein, a novel strategy of direct data integration (DDI) was proposed to combine available PA microarray datasets, which significantly enlarged the sample size. First, the robustness of the gene markers identified by DDI strategy was found to be substantially enhanced compared with that of previous studies. Then, the DDI of all reported PA-related microarray datasets were conducted to achieve a comprehensive identification of PA gene markers, and 66 immune-related genes were discovered as target candidates for PA immunotherapy. Finally, based on the analysis of human protein⁻protein interaction network, some promising target candidates (GAL, LMO4, STAT3, PD-L1, TGFB and TGFBR3) were proposed for PA immunotherapy. The strategy proposed together with the immune-related markers identified in this study provided a useful guidance for the development of novel immunotherapy for PA.

Plasma Nuclear Magnetic Resonance Metabolomics Discriminates Between High and Low Endoscopic Activity and Predicts Progression in a Prospective Cohort of Patients With Ulcerative Colitis

BACKGROUND AND AIMS

Endoscopic assessment of ulcerative colitis [UC] is one of the most accurate measures of disease activity, but frequent endoscopic investigations are disliked by patients and expensive for the healthcare system. A minimally invasive test that provides a surrogate measure of endoscopic activity is required.

METHODS

Plasma nuclear magnetic resonance [NMR] spectra from 40 patients with UC followed prospectively over 6 months were analysed with multivariate statistics. NMR metabolite profiles were compared with endoscopic [Ulcerative Colitis Endoscopic Index of Severity: UCEIS], histological [Nancy Index] and clinical [Simple Clinical Colitis Activity Index: SCCAI] severity indices, along with routine blood measurements.

RESULTS

A blinded principal component analysis spontaneously separated metabolite profiles of patients with low [≤3] and high [>3] UCEIS. Orthogonal partial least squares discrimination analysis identified low and high UCEIS metabolite profiles with an accuracy of 77 ± 5%. Plasma metabolites driving discrimination included decreases in lipoproteins and increases in isoleucine, valine, glucose and myo-inositol in high compared to low UCEIS. This same metabolite profile distinguished between low [Nancy 0-1] and high histological activity [Nancy 3-4] with a modest although significant accuracy [65 ± 6%] but was independent of SCCAI and all blood parameters measured. A different metabolite profile, dominated by changes in lysine, histidine, phenylalanine and tyrosine, distinguished between improvement in UCEIS [decrease ≥1] and worsening [increase ≥1] over 6 months with an accuracy of 74 ± 4%.

CONCLUSION

Plasma NMR metabolite analysis has the potential to provide a low-cost, minimally invasive technique that may be a surrogate for endoscopic assessment, with predictive capacity.

Urinary organic acids as biomarkers in the assessment of pulmonary function in children with asthma

Childhood asthma prevalence continues to rise despite advancements in prevention and medical management strategies. The purpose of this study was to investigate correlations between urinary organic acids and pulmonary diagnostic tests, asthma control in Greek asthmatic children. We hypothesized that urinary organic acids are positively associated with poor pulmonary function in children with asthma. Seventy-two children, 5 to 12 years old with asthma were recruited from a pediatric asthma clinic in Athens, Greece. Pulmonary function was assessed using spirometry and exhaled nitric oxide analysis. Asthma control was measured qualitatively using the Asthma Control Questionnaire. Targeted metabolomic analysis of 34 urinary organic acids in children was conducted by gas chromatography-mass spectrometry. A statistically significant difference between girls and boys was found for asthma control score (P = .02), lactic acid (P = .03), but not for any other organic acids (P > .05). Statistically significant correlations were found between lactic acid and Forced Expiratory Volume in 1 second (FEV₁) (P = .02), Forced Vital Capacity (FVC) (P = .03); 4- hydroxyphenylacetic acid and FEV₁ (P = .01), FVC (P = .01); 5-hydroxyindoleacetic acid and FEV₁/FVC (P = .03), eNO (P = .05); glycolic acid with Peak Expiratory Flow (PEF) (P = .03); and malic acid with asthma control (P = .02). In conclusion, metabolomics was used to determine correlations between urinary organic acids and conventional pulmonary diagnostic tests in Greek asthmatic children. Metabolomics could be a promising approach for asthma research and in detection of novel biomarkers for asthma monitoring and therapeutic targets for childhood asthma. This study contributes towards a better understanding of the biochemical pathways involved in asthma.

Review: Synovial Cell Metabolism and Chronic Inflammation in Rheumatoid Arthritis

Metabolomic studies of body fluids show that immune-mediated inflammatory diseases such as rheumatoid arthritis (RA) are associated with metabolic disruption. This is likely to reflect the increased bioenergetic and biosynthetic demands of sustained inflammation and changes in nutrient and oxygen availability in damaged tissue. The synovial membrane lining layer is the principal site of inflammation in RA. Here, the resident cells are fibroblast-like synoviocytes (FLS) and synovial tissue macrophages, which are transformed toward overproduction of enzymes that degrade cartilage and bone and cytokines that promote immune cell infiltration. Recent studies have shown metabolic changes in both FLS and macrophages from RA patients, and these may be therapeutically targetable. However, because the origins and subset-specific functions of synoviocytes are poorly understood, and the signaling modules that control metabolic deviation in RA synovial cells are yet to be explored, significant additional research is needed to translate these findings to clinical application. Furthermore, in many inflamed tissues, different cell types can forge metabolic collaborations through solute carriers in their membranes to meet a high demand for energy or biomolecules. Such relationships are likely to exist in the synovium and have not been studied. Finally, it is not yet known whether metabolic change is a consequence of disease or whether primary changes to cellular metabolism might underlie or contribute to the pathogenesis of early-stage disease. In this review article, we collate what is known about metabolism in synovial tissue cells and highlight future directions of research in this area.

A review of validated biomarkers obtained through metabolomics

INTRODUCTION

Studying changes in the whole set of small molecules, final products of biochemical reactions in living systems or metabolites, is extremely appealing because they represent the best approach to identifying what occurs in an organism when samples are collected. However, their usefulness as potential biomarkers is limited by discoveries obtained in small groups without proper validation or even confirmation of the chemical structure. Areas covered: During the past 5 years, more than 900 papers have been published on metabolomics for biomarker discovery, but the numbers are much lower when some criteria of validation are applied. In total, 102 papers have been included in this review. The most frequent disease areas in which these markers have been discovered include the following: cancer, diabetes, and related diseases and neurodegenerative, cardiovascular, autoimmune, liver, and kidney diseases. Expert commentary: Metabolomics has been demonstrated as rapidly growing due to the improvements in instrumentation, mainly mass spectrometry, and data mining software. For application in the clinic, the results should be validated in different stages, from analytical validation to validation in independent sets of samples, using thousands of samples from different sources.

Metabolomic profile of systemic sclerosis patients

Systemic sclerosis (SSc) is an autoimmune disease of unknown aetiology characterized by vascular lesions, immunological alterations and diffuse fibrosis of the skin and internal organs. Since recent evidence suggests that there is a link between metabolomics and immune mediated disease, serum metabolic profile of SSc patients and healthy controls was investigated by ¹H-NMR and GC-MS techniques. The results indicated a lower level of aspartate, alanine, choline, glutamate, and glutarate in SSc patients compared with healthy controls. Moreover, comparing patients affected by limited SSc (lcSSc) and diffuse SSc (dcSSc), 6 discriminant metabolites were identified. The multivariate analysis performed using all the metabolites significantly different revealed glycolysis, gluconeogenesis, energetic pathways, glutamate metabolism, degradation of ketone bodies and pyruvate metabolism as the most important networks. Aspartate, alanine and citrate yielded a high area under receiver-operating characteristic (ROC) curves (AUC of 0.81; CI 0.726–0.93) for discriminating SSc patients from controls, whereas ROC curve generated with acetate, fructose, glutamate, glutamine, glycerol and glutarate (AUC of 0.84; CI 0.7–0.98) discriminated between lcSSc and dcSSc. These results indicated that serum NMR-based metabolomics profiling method is sensitive and specific enough to distinguish SSc from healthy controls and provided a feasible diagnostic tool for the diagnosis and classification of the disease.

Emerging concepts in non-invasive monitoring of Crohn's disease

Inflammatory bowel disease (IBD) is an umbrella term for Crohn's disease (CD) and ulcerative colitis (UC). In light of evolving epidemiology of CD, its clinical management is still complex and remains a challenge for contemporary physicians. With the advent of new diagnostic and treatment paradigms, there is a growing need for new biomarkers to guide decision-making, differential diagnosis, disease activity monitoring, as well as prognosis. However, both clinical and endoscopic scoring systems, widely utilized for disease monitoring and prognosis, have drawbacks and limitations. In recent years, biochemical peptides have become available for IBD monitoring and more frequently used as surrogate markers of gut inflammation. Emerging concepts that revolve around molecular, stem cell, epigenetic, microbial or metabolomic pathways associated with vascular and epithelial gut barrier could lead to development of new CD biomarkers. Measurement of cell-derived microvesicles (MVs) in the blood of IBD patients is another emerging concept helpful in future disease management. In this review, we discuss novel concepts of non-invasive biomarkers, which may become useful in monitoring of CD activity and prognosis. We discuss metabolomics as a new powerful tool for clinicians to guide differential IBD diagnosis. In the coming years, new developments of prognostic tools are expected, aiming for breakthroughs in the management of patients with CD.

Feline urine metabolomic signature: characterization of low-molecular-weight substances in urine from domestic cats

Objectives This aim of this study was to characterize the composition and content of the feline urine metabolome. Methods Eight healthy domestic cats were acclimated at least 10 days before starting the study. Urine samples (~2 ml) were collected by ultrasound-guided cystocentesis. Samples were centrifuged at 1000 × g for 8 mins, and the supernatant was analyzed by gas chromatography/time-of-flight mass spectrometery. The urine metabolome was characterized using an untargeted metabolomics approach. Results Three hundred and eighteen metabolites were detected in the urine of the eight cats. These molecules are key components of at least 100 metabolic pathways. Feline urine appears to be dominated by carbohydrates, carbohydrate conjugates, organic acid and derivatives, and amino acids and analogs. The five most abundant molecules were phenaceturic acid, hippuric acid, pseudouridine phosphate and 3-(4-hydroxyphenyl) propionic acid. Conclusions and relevance This study is the first to characterize the feline urine metabolome. The results of this study revealed the presence of multiple low-molecular-weight substances that were not known to be present in feline urine. As expected, the origin of the metabolites detected in urine was diverse, including endogenous compounds and molecules biosynthesized by microbes. Also, the diet seemed to have had a relevant role on the urine metabolome. Further exploration of the urine metabolic phenotype will open a window for discovering unknown, or poorly understood, metabolic pathways. In turn, this will advance our understanding of feline biology and lead to new insights in feline physiology, nutrition and medicine.

Ion Mobility Spectrometry-Mass Spectrometry Coupled with Gas-Phase Hydrogen/Deuterium Exchange for Metabolomics Analyses

Ion mobility spectrometry-mass spectrometry (IMS-MS) in combination with gas-phase hydrogen/deuterium exchange (HDX) and collision-induced dissociation (CID) is evaluated as an analytical method for small-molecule standard and mixture characterization. Experiments show that compound ions exhibit unique HDX reactivities that can be used to distinguish different species. Additionally, it is shown that gas-phase HDX kinetics can be exploited to provide even further distinguishing capabilities by using different partial pressures of reagent gas. The relative HDX reactivity of a wide variety of molecules is discussed in light of the various molecular structures. Additionally, hydrogen accessibility scoring (HAS) and HDX kinetics modeling of candidate (in silico) ion structures is utilized to estimate the relative ion conformer populations giving rise to specific HDX behavior. These data interpretation methods are discussed with a focus on developing predictive tools for HDX behavior. Finally, an example is provided in which ion mobility information is supplemented with HDX reactivity data to aid identification efforts of compounds in a metabolite extract. Graphical Abstract ᅟ.

Metabolomics in Immunology Research

There is a growing appreciation that metabolic processes and individual metabolites can shape the function of immune cells and thereby play important roles in the outcome of immune responses. In this respect, the use of MS- and NMR spectroscopy-based platforms to characterize and quantify metabolites in biological samples has recently yielded important novel insights into how our immune system functions and has contributed to the identification of biomarkers for immune-mediated diseases. Here, these recent immunological studies in which metabolomics has been used and made significant contributions to these fields will be discussed. In particular the role of metabolomics to the rapidly advancing field of cellular immunometabolism will be highlighted as well as the future prospects of such metabolomic tools in immunology.

Metabolic Adaptations of CD4+ T Cells in Inflammatory Disease

A controlled and self-limiting inflammatory reaction generally results in removal of the injurious agent and repair of the damaged tissue. However, in chronic inflammation, immune responses become dysregulated and prolonged, leading to tissue destruction. The role of metabolic reprogramming in orchestrating appropriate immune responses has gained increasing attention in recent years. Proliferation and differentiation of the T cell subsets that are needed to address homeostatic imbalance is accompanied by a series of metabolic adaptations, as T cells traveling from nutrient-rich secondary lymphoid tissues to sites of inflammation experience a dramatic shift in microenvironment conditions. How T cells integrate information about the local environment, such as nutrient availability or oxygen levels, and transfer these signals to functional pathways remains to be fully understood. In this review, we discuss how distinct subsets of CD4⁺ T cells metabolically adapt to the conditions of inflammation and whether these insights may pave the way to new treatments for human inflammatory diseases.

Quantitative Serum Nuclear Magnetic Resonance Metabolomics in Large-Scale Epidemiology: A Primer on -Omic Technologies

Detailed metabolic profiling in large-scale epidemiologic studies has uncovered novel biomarkers for cardiometabolic diseases and clarified the molecular associations of established risk factors. A quantitative metabolomics platform based on nuclear magnetic resonance spectroscopy has found widespread use, already profiling over 400,000 blood samples. Over 200 metabolic measures are quantified per sample; in addition to many biomarkers routinely used in epidemiology, the method simultaneously provides fine-grained lipoprotein subclass profiling and quantification of circulating fatty acids, amino acids, gluconeogenesis-related metabolites, and many other molecules from multiple metabolic pathways. Here we focus on applications of magnetic resonance metabolomics for quantifying circulating biomarkers in large-scale epidemiology. We highlight the molecular characterization of risk factors, use of Mendelian randomization, and the key issues of study design and analyses of metabolic profiling for epidemiology. We also detail how integration of metabolic profiling data with genetics can enhance drug development. We discuss why quantitative metabolic profiling is becoming widespread in epidemiology and biobanking. Although large-scale applications of metabolic profiling are still novel, it seems likely that comprehensive biomarker data will contribute to etiologic understanding of various diseases and abilities to predict disease risks, with the potential to translate into multiple clinical settings.

Metabolic Adaptations of Uropathogenic E. coli in the Urinary Tract

Escherichia coli ordinarily resides in the lower gastrointestinal tract in humans, but some strains, known as Uropathogenic E. coli (UPEC), are also adapted to the relatively harsh environment of the urinary tract. Infections of the urine, bladder and kidneys by UPEC may lead to potentially fatal bloodstream infections. To survive this range of conditions, UPEC strains must have broad and flexible metabolic capabilities and efficiently utilize scarce essential nutrients. Whole-organism (or "omics") methods have recently provided significant advances in our understanding of the importance of metabolic adaptation in the success of UPECs. Here we describe the nutritional and metabolic requirements for UPEC infection in these environments, and focus on particular metabolic responses and adaptations of UPEC that appear to be essential for survival in the urinary tract.

Assessment of metabolic phenotypic variability in children's urine using 1H NMR spectroscopy

The application of metabolic phenotyping in clinical and epidemiological studies is limited by a poor understanding of inter-individual, intra-individual and temporal variability in metabolic phenotypes. Using 1H NMR spectroscopy we characterised short-term variability in urinary metabolites measured from 20 children aged 8-9 years old. Daily spot morning, night-time and pooled (50:50 morning and night-time) urine samples across six days (18 samples per child) were analysed, and 44 metabolites quantified. Intraclass correlation coefficients (ICC) and mixed effect models were applied to assess the reproducibility and biological variance of metabolic phenotypes. Excellent analytical reproducibility and precision was demonstrated for the 1H NMR spectroscopic platform (median CV 7.2%). Pooled samples captured the best inter-individual variability with an ICC of 0.40 (median). Trimethylamine, N-acetyl neuraminic acid, 3-hydroxyisobutyrate, 3-hydroxybutyrate/3-aminoisobutyrate, tyrosine, valine and 3-hydroxyisovalerate exhibited the highest stability with over 50% of variance specific to the child. The pooled sample was shown to capture the most inter-individual variance in the metabolic phenotype, which is of importance for molecular epidemiology study design. A substantial proportion of the variation in the urinary metabolome of children is specific to the individual, underlining the potential of such data to inform clinical and exposome studies conducted early in life.

The metabolomics of psoriatic disease

Metabolomics is an emerging new "omics" field involving the systematic analysis of the metabolites in a biologic system. These metabolites provide a molecular snapshot of cellular activity and are thus important for understanding the functional changes in metabolic pathways that drive disease. Recently, metabolomics has been used to study the local and systemic metabolic changes in psoriasis and its cardiometabolic comorbidities. Such studies have revealed novel insights into disease pathogenesis and suggest new biochemical signatures that may be used as a marker of psoriatic disease. This review will discuss common strategies in metabolomics analysis, current findings in the metabolomics of psoriasis, and emerging trends in psoriatic metabolomics.