Urinary metabolomic study of systemic lupus erythematosus based on gas chromatography/mass spectrometry

Targeted metabolomics combined with machine learning to identify and validate new biomarkers for early SLE diagnosis and disease activity

BACKGROUND

The early diagnosis of systemic lupus erythematosus (SLE) and the assessment of disease activity progression remain a great challenge. Targeted metabolomics has great potential to identify new biomarkers of SLE.

METHODS

Serum from 44 healthy participants and 89 SLE patients were analyzed using HM400 high-throughput targeted metabolomics. Machine learning (ML) with seven learning models and trained the model several times iteratively selected the two best prediction model in a competitive way, which were independent validated by enzyme-linked immunosorbent (ELISA) with 90 SLE patients.

RESULTS

In this study, 146 differential metabolites, most of them organic acids, amino acids, and bile acids, were detected between patients with initial SLE and healthy participants, and 8 potential biomarkers were found by intersection of ML and statistics (area under the curve [AUC] > 0.95) showing a significant positive correlation with clinical indicators. In addition, we identified and validated 2 potential biomarkers for SLE classification (P < 0.05, AUC > 0.775; N-Methyl-L-glutamic acid, L-2-aminobutyric acid) showing a significant correlation with the SLE Disease Activity Index. These differential metabolites were mainly involved in metabolic pathways, amino acid biosynthesis, 2-oxocarboxylic acid metabolism and other pathways.

CONCLUSION

This study indicated that the tricarboxylic acid cycle might be associated with SLE drug therapy. We identified 8 diagnostic models biomarkers and 2 biomarkers that could be used to identify initial SLE and distinguish different activity degree, which will promote the development of new tools for the diagnosis and evaluation of SLE.

N-nitrosamines induced gender-dimorphic effects on infant rats at environmental levels

The safety of drinking water has always been a concern for people all over the world. N-nitrosamines (NAs), a kind of nitrogenous disinfection by-products (N-DBPs), are generally detected as a mixture in drinking water at home and abroad. Studies have shown that individual NAs posed strong carcinogenicity at high concentrations. However, health risks of NAs at environmental levels (concentrations in drinking water) are still unclear. Therefore, the potential health risks of environmentally relevant NAs exposure in drinking water needs to be conducted. In this study, blood biochemical analysis and metabolomics based on nuclear magnetic resonance (NMR) were performed to comprehensively investigate NAs induced metabolic disturbance in infant rats at environmental levels. Results of blood biochemical indices analysis indicated that AST in the serum of male rats in NAs-treated group exhibited a significant gender-specific difference. Multivariate statistics showed that two and eight significantly disturbed metabolic pathways were identified in the serum samples of NAs-treated male and female rats, respectively. In the urine samples of NAs-treated female rats, glycine, serine, and threonine metabolism pathway was significantly disturbed; while three significantly disturbed metabolic pathways were found in the urine of NAs-treated male rats. Finally, results of spearman correlation coefficients suggested that the disturbances of metabolism profile in serum and urine were correlated with changes in the gut microbiota (data derived from our published paper). Data presented here aimed to generate new health risk data of NAs mixture exposure at environmental levels and provide theoretical support for drinking water safety management. ENVIRONMENTAL IMPLICATION: N-nitrosamines (NAs) are a kind of nitrogenous disinfection by-products (N-DBPs) generated during drinking water disinfection processes. Herein, health risks of NAs at environmental levels (concentrations in drinking water) are investigated using blood biochemical analysis and nuclear magnetic resonance (NMR)-based metabolomics. Results confirmed NAs induced gender-specific on the metabolism in rat and the disturbances of metabolism profile in serum and urine were correlated with changes in the gut microbiota. Data presented here aimed to generate new health risk data of NAs mixture exposure at environmental levels and provide theoretical support for drinking water safety management.

Dysbiotic Gut Microbiota-Derived Metabolites and Their Role in Non-Communicable Diseases

Dysbiosis, generally defined as the disruption to gut microbiota composition or function, is observed in most diseases, including allergies, cancer, metabolic diseases, neurological disorders and diseases associated with autoimmunity. Dysbiosis is commonly associated with reduced levels of beneficial gut microbiota-derived metabolites such as short-chain fatty acids (SCFA) and indoles. Supplementation with these beneficial metabolites, or interventions to increase their microbial production, has been shown to ameliorate a variety of inflammatory diseases. Conversely, the production of gut 'dysbiotic' metabolites or by-products by the gut microbiota may contribute to disease development. This review summarizes the various 'dysbiotic' gut-derived products observed in cardiovascular diseases, cancer, inflammatory bowel disease, metabolic diseases including non-alcoholic steatohepatitis and autoimmune disorders such as multiple sclerosis. The increased production of dysbiotic gut microbial products, including trimethylamine, hydrogen sulphide, products of amino acid metabolism such as p-Cresyl sulphate and phenylacetic acid, and secondary bile acids such as deoxycholic acid, is commonly observed across multiple diseases. The simultaneous increased production of dysbiotic metabolites with the impaired production of beneficial metabolites, commonly associated with a modern lifestyle, may partially explain the high prevalence of inflammatory diseases in western countries.

Metabolite Alterations in Autoimmune Diseases: A Systematic Review of Metabolomics Studies

Autoimmune diseases, characterized by the immune system's loss of self-tolerance, lack definitive diagnostic tests, necessitating the search for reliable biomarkers. This systematic review aims to identify common metabolite changes across multiple autoimmune diseases. Following PRISMA guidelines, we conducted a systematic literature review by searching MEDLINE, ScienceDirect, Google Scholar, PubMed, and Scopus (Elsevier) using keywords "Metabolomics", "Autoimmune diseases", and "Metabolic changes". Articles published in English up to March 2023 were included without a specific start date filter. Among 257 studies searched, 88 full-text articles met the inclusion criteria. The included articles were categorized based on analyzed biological fluids: 33 on serum, 21 on plasma, 15 on feces, 7 on urine, and 12 on other biological fluids. Each study presented different metabolites with indications of up-regulation or down-regulation when available. The current study's findings suggest that amino acid metabolism may serve as a diagnostic biomarker for autoimmune diseases, particularly in systemic lupus erythematosus (SLE), multiple sclerosis (MS), and Crohn's disease (CD). While other metabolic alterations were reported, it implies that autoimmune disorders trigger multi-metabolite changes rather than singular alterations. These shifts could be consequential outcomes of autoimmune disorders, representing a more complex interplay. Further studies are needed to validate the metabolomics findings associated with autoimmune diseases.

Urine myo-inositol as a novel prognostic biomarker for diabetic kidney disease: a targeted metabolomics study using nuclear magnetic resonance

BACKGROUND

As a leading cause of chronic kidney disease, clinical demand for noninvasive biomarkers of diabetic kidney disease (DKD) beyond proteinuria is increasing. Metabolomics is a popular method to identify mechanisms and biomarkers. We investigated urinary targeted metabolomics in DKD patients.

METHODS

We conducted a targeted metabolomics study of 26 urinary metabolites in consecutive patients with DKD stage 1 to 5 (n = 208) and healthy controls (n = 26). The relationships between estimated glomerular filtration rate (eGFR) or urine protein-creatinine ratio (UPCR) and metabolites were evaluated. Multivariate Cox analysis was used to estimate relationships between urinary metabolites and the target outcome, end-stage renal disease (ESRD). C statistics and time-dependent receiver operating characteristics (ROC) were used to assess diagnostic validity.

RESULTS

During a median 4.5 years of follow-up, 103 patients (44.0%) progressed to ESRD and 65 (27.8%) died. The median fold changes of nine metabolites belonged to monosaccharide and tricarboxylic acid (TCA) cycle metabolites tended to increase with DKD stage. Myo-inositol, choline, and citrates were correlated with eGFR and choline, while mannose and myo-inositol were correlated with UPCR. Elevated urinary monosaccharide and TCA cycle metabolites showed associations with increased morality and ESRD progression. The predictive power of ESRD progression was high, in the order of choline, myo-inositol, and citrate. Although urinary metabolites alone were less predictive than serum creatinine or UPCR, myo-inositol had additive effect with serum creatinine and UPCR. In time-dependent ROC, myo-inositol was more predictive than UPCR of 1-year ESRD progression prediction.

CONCLUSION

Myo-inositol can be used as an additive biomarker of ESRD progression in DKD.

Immunometabolomics provides a new perspective for studying systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a chronic multi-organ autoimmune disease characterized by clinical heterogeneity, unpredictable progression, and flare ups. Due to the heterogeneous nature of lupus, it has been challenging to identify sensitive and specific biomarkers for its diagnosis and monitoring. Despite the fact that the mechanism of SLE remains unknown, impressive progress has been made over the last decade towards understanding how different immune cells contribute to its pathogenesis. Research suggests that cellular metabolic programs could affect the immune response by regulating the activation, proliferation, and differentiation of innate and adaptive immune cells. Many studies have shown that the dysregulation of the immune system is associated with changes to metabolite profiles. The study of metabolite profiling may provide a means for mechanism exploration and novel biomarker discovery for disease diagnostic, classification, and monitoring. Here we review the latest advancements in understanding the role of immunometabolism in SLE, as well as the systemic metabolite profiling of this disease along with possible clinical application.

The Bladder Microbiome, Metabolome, Cytokines, and Phenotypes in Patients with Systemic Lupus Erythematosus

Emerging studies reveal unique bacterial communities in the human bladder, with alteration of composition associated to disease states. Systemic lupus erythematosus (SLE) is a complex autoimmune disease that is characterized by frequent impairment of the kidney. Here, we explored the bladder microbiome, metabolome, and cytokine profiles in SLE patients, as well as correlations between microbiome and metabolome, cytokines, and disease profiles. We recruited a group of 50 SLE patients and 50 individually matched asymptomatic controls. We used transurethral catheterization to collect urine samples, 16S rRNA gene sequencing to profile bladder microbiomes, and liquid chromatography-tandem mass spectrometry to perform untargeted metabolomic profiling. Compared to controls, SLE patients possessed unique bladder microbial communities and increased alpha diversity. These differences were accompanied by differences in urinary metabolomes, cytokines, and patients’ disease profiles. The SLE-enriched genera, including Bacteroides, were positively correlated with several SLE-enriched metabolites, including olopatadine. The SLE-depleted genera, such as Pseudomonas, were negatively correlated to SLE-depleted cytokines, including interleukin-8. Alteration of the bladder microbiome was associated with disease profile. For example, the genera Megamonas and Phocaeicola were negatively correlated with serum complement component 3, and Streptococcus was positively correlated with IgG. Our present study reveals associations between the bladder microbiome and the urinary metabolome, cytokines, and disease phenotypes. Our results could help identify biomarkers for SLE.

IMPORTANCE Contrary to dogma, the human urinary bladder possesses its own unique bacterial community with alteration of composition associated with disease states. Systemic lupus erythematosus (SLE) is a complex autoimmune disease often characterized by kidney impairment. Here, we explored the bladder microbiome, metabolome, and cytokine profiles in SLE patients, as well as correlations between the microbiome and metabolome, cytokines, and disease profiles. Compared to controls, SLE patients possessed a unique bladder microbial community and elevated alpha diversity. These differences were accompanied by differences in bladder metabolomes, cytokines, and patients’ disease profiles. SLE-enriched genera were positively correlated with several SLE-enriched metabolites. SLE-depleted genera were negatively correlated to SLE-depleted cytokines. Alteration of the bladder microbiome was associated with disease profile. Thus, our study reveals associations between the bladder microbiome and the bladder metabolome, cytokines, and disease phenotypes. These results could help identify biomarkers for SLE.

Metabolites and metabolic pathways associated with rheumatoid arthritis and systemic lupus erythematosus

Rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) are chronic autoimmune diseases that result from the combined influence of genetic and environmental factors that promotes the loss of tolerance to cellular components. The complexity of these diseases converts them into a major challenge at the diagnostic and treatment level. Therefore, it is convenient to implement the use of tools for a better understanding of the physiopathology of these diseases to propose reliable biomarkers. The "omics" disciplines like metabolomics and lipidomics allow to study RA and SLE in a higher degree of detail since they evaluate the metabolites and metabolic pathways involved in disease pathogenesis. This review has compiled the information of metabolomics and lipidomics studies where samples obtained from RA and SLE patients were evaluated to find the metabolites and pathways differences between patients and healthy controls. In both diseases, there is a decrease in several amino acids and oxidative stress-related metabolites like glutathione. These findings may be useful for functional metabolomics studies aiming to reprogram the metabolism in a disease setting to recover normal immune cell homeostasis and function.

Metabolomics in Autoimmune Diseases: Focus on Rheumatoid Arthritis, Systemic Lupus Erythematous, and Multiple Sclerosis

The metabolomics approach represents the last downstream phenotype and is widely used in clinical studies and drug discovery. In this paper, we outline recent advances in the metabolomics research of autoimmune diseases (ADs) such as rheumatoid arthritis (RA), multiple sclerosis (MuS), and systemic lupus erythematosus (SLE). The newly discovered biomarkers and the metabolic mechanism studies for these ADs are described here. In addition, studies elucidating the metabolic mechanisms underlying these ADs are presented. Metabolomics has the potential to contribute to pharmacotherapy personalization; thus, we summarize the biomarker studies performed to predict the personalization of medicine and drug response.

Plasma Metabolomic and Intestinal Microbial Analyses of Patients With Severe Aplastic Anemia

Aplastic anemia results from bone marrow failure caused by an autoimmune abnormality, but the pathogenesis of severe aplastic anemia (SAA) is not well characterized. To identify potential metabolic markers of SAA and to further elucidate the pathogenetic mechanisms of SAA, we performed a metabolomic study of plasma samples and characterized the intestinal microbiota of patients with SAA and healthy controls. Patients with SAA had more Enterobacteriales and Lactobacillales, but fewer Bacteroidales, Clostridiales, and Erysipelotrichales than healthy controls. At the species level, the abundances of Escherichia coli and others including Clostridium citroniae were higher, whereas those of Prevotella copri, Roseburia faecis, and Ruminococcus bromii were lower. Eight metabolites showed significantly different plasma concentrations in the SAA and healthy control groups. Coumaric acid, L-phenylalanine, and sulfate were present at higher concentrations in the SAA group; whereas L-glutamic γ-semialdehyde, theobromine, 3a, 7a-dihydroxy-5b-cholestane, γ-δ-dioxovaleric acid, and (12Z)-9, 10-dihydroxyoctadec-12-enoic acid were present at lower concentrations. In conclusion, patients with SAA show abnormalities in both their plasma metabolomes and intestinal microbial compositions. These differences might reflect the molecular mechanisms involved in the defective immunity that characterizes SAA.

Gut Microbiome and Metabolites in Systemic Lupus Erythematosus: Link, Mechanisms and Intervention

Systemic lupus erythematosus (SLE), often considered the prototype of autoimmune diseases, is characterized by over-activation of the autoimmune system with abnormal functions of innate and adaptive immune cells and the production of a large number of autoantibodies against nuclear components. Given the highly complex and heterogeneous nature of SLE, the pathogenesis of this disease remains incompletely understood and is presumed to involve both genetic and environmental factors. Currently, disturbance of the gut microbiota has emerged as a novel player involved in the pathogenesis of SLE. With in-depth research, the understanding of the intestinal bacteria-host interaction in SLE is much more comprehensive. Recent years have also seen an increase in metabolomics studies in SLE with the attempt to identify potential biomarkers for diagnosis or disease activity monitoring. An intricate relationship between gut microbiome changes and metabolic alterations could help explain the mechanisms by which gut bacteria play roles in the pathogenesis of SLE. Here, we review the role of microbiota dysbiosis in the aetiology of SLE and how intestinal microbiota interact with the host metabolism axis. A proposed treatment strategy for SLE based on gut microbiome (GM) regulation is also discussed in this review. Increasing our understanding of gut microbiota and their function in lupus will provide us with novel opportunities to develop effective and precise diagnostic strategies and to explore potential microbiota-based treatments for patients with lupus.

Fecal Metabolites Were Altered, Identified as Biomarkers and Correlated With Disease Activity in Patients With Systemic Lupus Erythematosus in a GC-MS-Based Metabolomics Study

Gut metabolites are products of the crosstalk between microbes and their host and play an important role in the occurrence, development, diagnosis, and treatment of autoimmune diseases. This work profiled the fecal metabolome of patients with systemic lupus erythematosus (SLE) using gas chromatography-mass spectrometry (GC-MS) and analyzed the potential roles of metabolites in the diagnosis and development of SLE. Fecal sample from 29 SLE patients without any other diseases and 30 healthy controls (HCs) were analyzed by metabolomics profiling. All participants took no antibiotics in the month before sampling and clinical data collecting. The metabolome profiles of patients with SLE and HCs were significantly different. Thirty fecal metabolites, such as deoxycholic acid, erucamide, L-tryptophan and putrescine, were significantly enriched, while nine metabolites, such as glyceric acid, γ-tocopherol, (Z)-13-octadecenoic acid and 2,4-di-tert-butylphenol, were depleted in SLE patients vs. HCs. The areas under the curve (AUCs) of L-valine, pyrimidine, erucamide, and L-leucine during ROC analysis were 0.886, 0.833, 0.829, and 0.803, indicating their good diagnostic potential. Moreover, the combination of L-valine, erucamide and 2,4-di-tert-butylphenol gave an AUC of 0.959. SLE-altered metabolites were significantly located in 28 pathways, such as ABC transporters (p = 3.40E-13) and aminoacyl-tRNA biosynthesis (p = 2.11E-12). Furthermore, SLE-altered fecal metabolites were closely correlated with SLE indicators, e.g., L-tryptophan was positively correlated with the SLEDAI-2K (p = 0.007). Our results suggest that the SLE fecal metabolome is closely associated with the occurrence and development of SLE and is of great diagnostic value.

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.

Metabolic determinants of lupus pathogenesis

The metabolism of healthy murine and more recently human immune cells has been investigated with an increasing amount of details. These studies have revealed the challenges presented by immune cells to respond rapidly to a wide variety of triggers by adjusting the amount, type, and utilization of the nutrients they import. A concept has emerged that cellular metabolic programs regulate the size of the immune response and the plasticity of its effector functions. This has generated a lot of enthusiasm with the prediction that cellular metabolism could be manipulated to either enhance or limit an immune response. In support of this hypothesis, studies in animal models as well as human subjects have shown that the dysregulation of the immune system in autoimmune diseases is associated with a skewing of the immunometabolic programs. These studies have been mostly conducted on autoimmune CD4⁺ T cells, with the metabolism of other immune cells in autoimmune settings still being understudied. Here we discuss systemic metabolism as well as cellular immunometabolism as novel tools to decipher fundamental mechanisms of autoimmunity. We review the contribution of each major metabolic pathway to autoimmune diseases, with a focus on systemic lupus erythematosus (SLE), with the relevant translational opportunities, existing or predicted from results obtained with healthy immune cells. Finally, we review how targeting metabolic programs may present novel therapeutic venues.

Urine Nuclear Magnetic Resonance (NMR) Metabolomics in Age-Related Macular Degeneration

Biofluid biomarkers of age-related macular degeneration (AMD) are still lacking, and their identification is challenging. Metabolomics is well-suited to address this need, and urine is a valuable accessible biofluid. This study aimed to characterize the urinary metabolomic signatures of patients with different stages of AMD and a control group (>50 years). It was a prospective, cross-sectional study, where subjects from two cohorts were included: 305 from Coimbra, Portugal (AMD patients n = 252; controls n = 53) and 194 from Boston, United States (AMD patients n = 147; controls n = 47). For all participants, we obtained color fundus photographs (for AMD staging) and fasting urine samples, which were analyzed using 1H nuclear magnetic resonance (NMR) spectroscopy. Our results revealed that in both cohorts, urinary metabolomic profiles differed mostly between controls and late AMD patients, but important differences were also found between controls and subjects with early AMD. Analysis of the metabolites responsible for these separations revealed that, even though distinct features were observed for each cohort, AMD was in general associated with depletion of excreted citrate and selected amino acids at some stage of the disease, suggesting enhanced energy requirements. In conclusion, NMR metabolomics enabled the identification of urinary signals of AMD and its severity stages, which might represent potential metabolomic biomarkers of the disease.

Metabolite Markers for Characterizing Sasang Constitution Type through GC-MS and 1H NMR-Based Metabolomics Study

Sasang constitutional medicine classifies human beings into four types based on their physical and psychological characteristics. Despite its potential value in achieving personalized medicine, the diagnosis of sasang constitution (SC) type is complex and subjective. In this study, gas chromatography–mass spectrometry and ¹H nuclear magnetic resonance–based metabolic analyses were conducted to find maker metabolites in serum and urine according to different SC types. Although some samples were overlapped on orthogonal projection to latent structure discriminant analysis score plots, serum samples showed separation between different SC types. Levels of lactate, glutamate, triglyceride, and fatty acids in serum and glycolic acid in urine of Tae-Eum type were higher than those of So-Eum and So-Yang type. Fatty acids, triglyceride, and lactate levels were found to be metabolites related to body mass index, indicating that marker metabolites for the diagnosis of SC type could be associated with obese. However, Tae-Eum type showed higher lactate levels in serum than So-Yang type for both normal weight and overweight groups, suggesting that the contents of serum lactate might be dependent on the SC type regardless of body weight. These results suggest that metabolomics analysis could be used to determine SC type.

Emerging role of metabolomics in rheumatology

The pursuit for understanding disease pathogenesis, in this age of rapid laboratory diagnostics and fast-paced research, has led scientists worldwide to take recourse in hypothesis-free approaches for molecular diagnosis. Metabolomics is one such powerful tool that explores comprehensibly the metabolic alternations in human diseases. It involves study of small molecules of less than 1 kD in size by either LSMS or nuclear magnetic resonance. Unlike genomics, which tells us what may have happened, metabolomics reflects what did happen. The NMR technique has an advantage of analyzing metabolites without sample preparation, thereby diminishing artifacts, is less cumbersome and with the latest database on Metabolome; about 30 000 metabolites can be identified. The study of metabolomics for several rheumatic diseases, including rheumatoid arthritis, lupus, osteoarthritis and vasculitis, has revealed distinctive metabolic signatures. Thus, metabolomics is a technique that promises precision medicine with better biomarkers, robust predictors of drug response and of disease outcome, discovery of newer metabolites and pathways in disease pathogenesis, and finally, targeted drug development. This review intends to decipher its relevance in common rheumatic diseases.

Advances in mass spectrometry-based metabolomics for investigation of metabolites

Metabolomics is the systematic study of all the metabolites present within a biological system, which consists of a mass of molecules, having a variety of physical and chemical properties and existing over an extensive dynamic range in biological samples. Diverse analytical techniques are needed to achieve higher coverage of metabolites. The application of mass spectrometry (MS) in metabolomics has increased exponentially since the discovery and development of electrospray ionization and matrix-assisted laser desorption ionization techniques. Significant advances have also occurred in separation-based MS techniques (gas chromatography-mass spectrometry, liquid chromatography-mass spectrometry, capillary electrophoresis-mass spectrometry, and ion mobility-mass spectrometry), as well as separation-free MS techniques (direct infusion-mass spectrometry, matrix-assisted laser desorption ionization-mass spectrometry, mass spectrometry imaging, and direct analysis in real time mass spectrometry) in the past decades. This review presents a brief overview of the recent advanced MS techniques and their latest applications in metabolomics. The software/websites for MS result analyses are also reviewed.

Metabolomics is the systematic study of all the metabolites present within a biological system, supply functional information and has received extensive attention in the field of life sciences.

Coagulation cascade and complement system in systemic lupus erythematosus

This study was conducted to (1) characterize coagulation cascade and complement system in systemic lupus erythematosus (SLE); (2) evaluate the associations between coagulation cascade, complement system, inflammatory response and SLE disease severity; (3) test the diagnostic value of a combination of D-dimer and C4 for lupus activity. Transcriptomics, proteomics and metabolomics were performed in 24 SLE patients and 24 healthy controls. The levels of ten coagulations, seven complements and three cytokines were measured in 112 SLE patients. Clinical data were collected from 2025 SLE patients. The analysis of multi-omics data revealed the common links for the components of coagulation cascade and complement system. The results of ELISA showed coagulation cascade and complement system had an interaction effect on SLE disease severity, this effect was pronounced among patients with excess inflammation. The analysis of clinical data revealed a combination of D-dimer and C4 provided good diagnostic performance for lupus activity. This study suggested that coagulation cascade and complement system become 'partners in crime', contributing to SLE disease severity and identified the diagnostic value of D-dimer combined with C4for lupus activity.

Metabolomic analysis identifies altered metabolic pathways in Multiple Sclerosis

Multiple sclerosis (MS) is a chronic, demyelinating disease that affects the central nervous system and is characterized by a complex pathogenesis and difficult management. The identification of new biomarkers would be clinically useful for more accurate diagnoses and disease monitoring. Metabolomics, the identification of small endogenous molecules, offers an instantaneous molecular snapshot of the MS phenotype. Here the metabolomic profiles (utilizing plasma from patients with MS) were characterized with a Gas cromatography-mass spectrometry-based platform followed by a multivariate statistical analysis and comparison with a healthy control (HC) population. The obtained partial least square discriminant analysis (PLS-DA) model identified and validated significant metabolic differences between individuals with MS and HC (R2X=0.223, R2Y=0.82, Q2=0.562; p<0.001). Among discriminant metabolites phosphate, fructose, myo-inositol, pyroglutamate, threonate, l-leucine, l-asparagine, l-ornithine, l-glutamine, and l-glutamate were correctly identified, and some resulted as unknown. A receiver operating characteristic (ROC) curve with AUC 0.84 (p=0.01; CI: 0.75-1) generated with the concentrations of the discriminant metabolites, supported the strength of the model. Pathway analysis indicated asparagine and citrulline biosynthesis as the main canonical pathways involved in MS. Changes in the citrulline biosynthesis pathway suggests the involvement of oxidative stress during neuronal damage. The results confirmed metabolomics as a useful approach to better understand the pathogenesis of MS and to provide new biomarkers for the disease to be used together with clinical data.

Mixing omics: combining genetics and metabolomics to study rheumatic diseases

Metabolomics is an exciting field in systems biology that provides a direct readout of the biochemical activities taking place within an individual at a particular point in time. Metabolite levels are influenced by many factors, including disease status, environment, medications, diet and, importantly, genetics. Thanks to their dynamic nature, metabolites are useful for diagnosis and prognosis, as well as for predicting and monitoring the efficacy of treatments. At the same time, the strong links between an individual's metabolic and genetic profiles enable the investigation of pathways that underlie changes in metabolite levels. Thus, for the field of metabolomics to yield its full potential, researchers need to take into account the genetic factors underlying the production of metabolites, and the potential role of these metabolites in disease processes. In this Review, the methodological aspects related to metabolomic profiling and any potential links between metabolomics and the genetics of some of the most common rheumatic diseases are described. Links between metabolomics, genetics and emerging fields such as the gut microbiome and proteomics are also discussed.