Serum metabolomic and lipidomic profiling identifies diagnostic biomarkers for seropositive and seronegative rheumatoid arthritis patients

Exploring the significance of microbiota metabolites in rheumatoid arthritis: uncovering their contribution from disease development to biomarker potential

Rheumatoid arthritis (RA) is a multifaceted autoimmune disorder characterized by chronic inflammation and joint destruction. Recent research has elucidated the intricate interplay between gut microbiota and RA pathogenesis, underscoring the role of microbiota-derived metabolites as pivotal contributors to disease development and progression. The human gut microbiota, comprising a vast array of microorganisms and their metabolic byproducts, plays a crucial role in maintaining immune homeostasis. Dysbiosis of this microbial community has been linked to numerous autoimmune disorders, including RA. Microbiota-derived metabolites, such as short-chain fatty acids (SCFAs), tryptophan derivatives, Trimethylamine-N-oxide (TMAO), bile acids, peptidoglycan, and lipopolysaccharide (LPS), exhibit immunomodulatory properties that can either exacerbate or ameliorate inflammation in RA. Mechanistically, these metabolites influence immune cell differentiation, cytokine production, and gut barrier integrity, collectively shaping the autoimmune milieu. This review highlights recent advances in understanding the intricate crosstalk between microbiota metabolites and RA pathogenesis and also discusses the potential of specific metabolites to trigger or suppress autoimmunity, shedding light on their molecular interactions with immune cells and signaling pathways. Additionally, this review explores the translational aspects of microbiota metabolites as diagnostic and prognostic tools in RA. Furthermore, the challenges and prospects of translating these findings into clinical practice are critically examined.

Serum and urine lipidomic profiles identify biomarkers diagnostic for seropositive and seronegative rheumatoid arthritis

Objective

Seronegative rheumatoid arthritis (RA) is defined as RA without circulating autoantibodies such as rheumatoid factor and anti-citrullinated protein antibodies; thus, early diagnosis of seronegative RA can be challenging. Here, we aimed to identify diagnostic biomarkers for seronegative RA by performing lipidomic analyses of sera and urine samples from patients with RA.

Methods

We performed untargeted lipidomic analysis of sera and urine samples from 111 RA patients, 45 osteoarthritis (OA) patients, and 25 healthy controls (HC). These samples were divided into a discovery cohort (n = 97) and a validation cohort (n = 84). Serum samples from 20 patients with systemic lupus erythematosus (SLE) were also used for validation.

Results

The serum lipidome profile of RA was distinguishable from that of OA and HC. We identified a panel of ten serum lipids and three urine lipids in the discovery cohort that showed the most significant differences. These were deemed potential lipid biomarker candidates for RA. The serum lipid panel was tested using a validation cohort; the results revealed an accuracy of 79%, a sensitivity of 71%, and a specificity of 86%. Both seropositive and seronegative RA patients were differentiated from patients with OA, SLE, and HC. Three urinary lipids showing differential expression between RA from HC were identified with an accuracy of 84%, but they failed to differentiate RA from OA. There were five lipid pathways that differed between seronegative and seropositive RA.

Conclusion

Here, we identified a panel of ten serum lipids as potential biomarkers that can differentiate RA from OA and SLE, regardless of seropositivity. In addition, three urinary lipids had diagnostic utility for differentiating RA from HC.

An integrated metabo-lipidomics profile of induced sputum for the identification of novel biomarkers in the differential diagnosis of asthma and COPD

BACKGROUND

Due to their complexity and to the presence of common clinical features, differentiation between asthma and chronic obstructive pulmonary disease (COPD) can be a challenging task, complicated in such cases also by asthma-COPD overlap syndrome. The distinct immune/inflammatory and structural substrates of COPD and asthma are responsible for significant differences in the responses to standard pharmacologic treatments. Therefore, an accurate diagnosis is of central relevance to assure the appropriate therapeutic intervention in order to achieve safe and effective patient care. Induced sputum (IS) accurately mirrors inflammation in the airways, providing a more direct picture of lung cell metabolism in comparison to those specimen that reflect analytes in the systemic circulation.

METHODS

An integrated untargeted metabolomics and lipidomics analysis was performed in IS of asthmatic (n = 15) and COPD (n = 22) patients based on Ultra-High-Pressure Liquid Chromatography-Mass Spectrometry (UHPLC-MS) and UHPLC-tandem MS (UHPLC-MS/MS). Partial Least Squares-Discriminant Analysis (PLS-DA) was applied to resulting dataset. The analysis of main enriched metabolic pathways and the association of the preliminary metabolites/lipids pattern identified to clinical parameters of asthma/COPD differentiation were explored. Multivariate ROC analysis was performed in order to determine the discriminatory power and the reliability of the putative biomarkers for diagnosis between COPD and asthma.

RESULTS

PLS-DA indicated a clear separation between COPD and asthmatic patients. Among the 15 selected candidate biomarkers based on Variable Importance in Projection scores, putrescine showed the highest score. A differential IS bio-signature of 22 metabolites and lipids was found, which showed statistically significant variations between asthma and COPD. Of these 22 compounds, 18 were decreased and 4 increased in COPD compared to asthmatic patients. The IS levels of Phosphatidylethanolamine (PE) (34:1), Phosphatidylglycerol (PG) (18:1;18:2) and spermine were significantly higher in asthmatic subjects compared to COPD.

CONCLUSIONS

This is the first pilot study to analyse the IS metabolomics/lipidomics signatures relevant in discriminating asthma vs COPD. The role of polyamines, of 6-Hydroxykynurenic acid and of D-rhamnose as well as of other important players related to the alteration of glycerophospholipid, aminoacid/biotin and energy metabolism provided the construction of a diagnostic model that, if validated on a larger prospective cohort, might be used to rapidly and accurately discriminate asthma from COPD.

Synovial 5-Lipoxygenase-Derived Oxylipins Define a Lympho-Myeloid-Enriched Synovium

OBJECTIVE

Oxylipins are bioactive lipids derived from polyunsaturated fatty acids (PUFAs) that modulate inflammation and may remain overexpressed in refractory synovitis. In plasma, they could also be biomarkers of synovial pathology. The aim of this study is to determine if synovial oxylipins in inflamed joints correlate with plasma oxylipins and with synovial histologic patterns.

METHODS

Patients with established rheumatoid or psoriatic arthritis with active disease despite treatment were recruited, and paired synovial tissue (ST) and plasma were collected. Oxylipins were determined by liquid chromatography with tandem mass spectrometry and were classified into groups according to their PUFA precursor and enzyme. The expression of CD20, CD68, CD3, and CD138 was obtained to describe synovial histology. Cell-specific expression of oxylipin-related genes was identified by examining available synovial single-cell RNA sequencing data.

RESULTS

We included a total of 32 ST and 26 paired-plasma samples. A total of 71 oxylipins were identified in ST, but only 24 were identified in plasma. Only levels of 9,10-dihydroxyoctadecenoic acid and tetranor-Prostaglandin FM had a significant positive correlation between plasma and ST. Several oxylipins and oxylipin-related genes were differentially expressed among synovial phenotypes. Specifically, several 5-lipoxygenase (LOX)-derived oxylipins were statistically elevated in the lympho-myeloid phenotype and associated with B cell expression in rheumatoid arthritis samples.

CONCLUSION

The lack of correlation between ST and plasma oxylipins suggests that ST lipid profiling better characterizes active pathways in treated joints. Synovial 5-LOX-derived oxylipins were highly expressed in lympho-myeloid-enriched synovium. Combination therapy with 5-LOX inhibitors to improve refractory inflammation may be needed in patients with this histologic group.

Relationship Between the Lipidome Profile and Disease Activity in Patients with Rheumatoid Arthritis

Lipid mediators have been suggested to play important roles in the pathogenesis of rheumatoid arthritis (RA). Lipidomics has recently allowed for the comprehensive analysis of lipids and has revealed the potential of lipids as biomarkers for the early diagnosis of RA and prediction of therapeutic responses. However, the relationship between disease activity and the lipid profile in RA remains unclear. In the present study, we performed a plasma lipidomic analysis of 278 patients with RA during treatment and examined relationships with disease activity using the Disease Activity Score in 28 joints (DAS28)-erythrocyte sedimentation rate (ESR). In all patients, five lipids positively correlated and seven lipids negatively correlated with DAS28-ESR. Stearic acid [FA(18:0)] (r = -0.45) and palmitic acid [FA(16:0)] (r = -0.38) showed strong negative correlations. After adjustments for age, body mass index (BMI), and medications, stearic acid, palmitic acid, bilirubin, and lysophosphatidylcholines negatively correlated with disease activity. Stearic acid inhibited osteoclast differentiation from peripheral blood monocytes in in vitro experiments, suggesting its contribution to RA disease activity by affecting bone metabolism. These results indicate that the lipid profile correlates with the disease activity of RA and also that some lipids may be involved in the pathogenesis of RA.

Plasma Lipidomic Profiling Using Mass Spectrometry for Multiple Sclerosis Diagnosis and Disease Activity Stratification (LipidMS)

This investigation explores the potential of plasma lipidomic signatures for aiding in the diagnosis of Multiple Sclerosis (MS) and evaluating the clinical course and disease activity of diseased patients. Plasma samples from 60 patients with MS (PwMS) were clinically stratified to either a relapsing-remitting (RRMS) or a chronic progressive MS course and 60 age-matched controls were analyzed using state-of-the-art direct infusion quantitative shotgun lipidomics. To account for potential confounders, data were filtered for age and BMI correlations. The statistical analysis employed supervised and unsupervised multivariate data analysis techniques, including a principal component analysis (PCA), a partial least squares discriminant analysis (oPLS-DA) and a random forest (RF). To determine whether the significant absolute differences in the lipid subspecies have a relevant effect on the overall composition of the respective lipid classes, we introduce a class composition visualization (CCV). We identified 670 lipids across 16 classes. PwMS showed a significant increase in diacylglycerols (DAG), with DAG 16:0;0_18:1;0 being proven to be the lipid with the highest predictive ability for MS as determined by RF. The alterations in the phosphatidylethanolamines (PE) were mainly linked to RRMS while the alterations in the ether-bound PEs (PE O-) were found in chronic progressive MS. The amount of CE species was reduced in the CPMS cohort whereas TAG species were reduced in the RRMS patients, both lipid classes being relevant in lipid storage. Combining the above mentioned data analyses, distinct lipidomic signatures were isolated and shown to be correlated with clinical phenotypes. Our study suggests that specific plasma lipid profiles are not merely associated with the diagnosis of MS but instead point toward distinct clinical features in the individual patient paving the way for personalized therapy and an enhanced understanding of MS pathology.

Exploring the differences in serum metabolite profiles after intake of red meat in women with rheumatoid arthritis and a matched control group

PURPOSE

Studies have suggested that women with RA tend to avoid red meat more often than women without RA, based on their perception that it exacerbates their symptoms. Therefore, the aim of this study is to investigate and compare the postprandial metabolic response following the consumption of a red meat meal in patients with RA and a matched control group.

METHODS

Participants were challenged with a meal with red meat and blood samples were collected before and at 0.5, 1, 2, 3 and 5 h after the meal. Serum metabolites were quantified by Nuclear Magnetic Resonance (NMR) analysis. Orthogonal Projections to Latent Structures with Discriminant Analysis (OPLS-DA) was used to evaluate separation by metabolites due to diagnosis of RA or not and to identify changes in metabolites related to RA. Incremental area under the curve was calculated for univariate comparisons for 23 metabolites.

RESULTS

The matched groups, including 22 women with RA and 22 women without RA, did not differ significantly in age, body mass index, diet quality or reported physical activity. OPLS-DA models had a limited quality indicating that there were no differences in metabolite patterns between the groups. However, phenylalanine was significantly higher in concentration in women with RA compared to controls in both fasting and postprandial samples.

CONCLUSION

To conclude, this well-controlled postprandial intervention study found a significantly higher concentration of phenylalanine in both fasting and postprandial samples of women with RA compared to matched women without RA. These findings warrant further investigation in larger studies.

TRIAL REGISTRATION

The PIRA (Postprandial Inflammation in Rheumatoid Arthritis) trial is Registered at Clinicaltrials.gov (NCT04247009).

Kynurenic Acid Plays a Protective Role in Hepatotoxicity Induced by HFPO-DA in Male Mice

Following its introduction as an alternative to perfluorooctanoic acid, hexafluoropropylene oxide dimer acid (HFPO-DA) has been extensively detected in various environmental matrices. Despite this prevalence, limited information is available regarding its hepatotoxicity biomarkers. In this study, toxicokinetic simulations indicated that under repeated treatment, HFPO-DA in mice serum reached a steady state by the 4th day. To assess its subacute hepatic effects and identify potential biomarkers, mice were administered HFPO-DA orally at doses of 0, 0.1, 0.5, 2.5, 12.5, or 62.5 mg/kg/d for 7 d. Results revealed that the lowest observed adverse effect levels were 0.5 mg/kg/d for hepatomegaly and 2.5 mg/kg/d for hepatic injury. Serum metabolomics analysis identified 34, 58, and 118 differential metabolites in the 0.1, 0.5, and 2.5 mg/kg/d groups, respectively, compared to the control group. Based on weighted gene coexpression network analysis, eight potential hepatotoxicity-related metabolites were identified; among them, kynurenic acid (KA) in mouse serum exhibited the highest correlation with liver injury. Furthermore, liver-targeted metabolomics analysis demonstrated that HFPO-DA exposure induced metabolic migration of the kynurenine pathway from KA to nicotinamide adenine dinucleotide, resulting in the activation of endoplasmic reticulum stress and the nuclear factor kappa-B signaling pathway. Notably, pretreatment with KA significantly attenuated liver injury induced by HFPO-DA exposure in mice, highlighting the pivotal roles of KA in the hepatotoxicity of HFPO-DA.

Association Between Human Metabolomics and Rheumatoid Arthritis: A Systematic Review and Meta-analysis

OBJECTIVE

The underdiagnosis and inadequate treatment of rheumatoid arthritis (RA) can be attributed to the various clinical manifestations presented by patients. To address this concern, we conducted an extensive review and meta-analysis, focusing on RA-related metabolites.

METHODS

A comprehensive literature search was conducted in PubMed, the Cochrane Library, Web of Science, and Embase to identify relevant studies published up to October 5, 2022. The quality of the included articles was evaluated and, subsequently, a meta-analysis was conducted using Review Manager software to analyze the association between metabolites and RA.

RESULTS

Forty nine studies met the inclusion criteria for the systematic review, and six of these studies were meta-analyzed to evaluate the association between 28 reproducible metabolites and RA. The results indicated that, compared to controls, the levels of histidine (RoM = 0.83, 95% CI = 0.79-0.88, I2 = 0%), asparagine (RoM = 0.83, 95% CI = 0.75-0.91, I2 = 0%), methionine (RoM = 0.82, 95% CI = 0.69-0.98, I2 = 85%), and glycine (RoM = 0.81, 95% CI = 0.67-0.97, I2 = 68%) were significantly lower in RA patients, while hypoxanthine levels (RoM = 1.14, 95% CI = 1.09-1.19, I2 = 0%) were significantly higher.

CONCLUSION

This study identified histidine, methionine, asparagine, hypoxanthine, and glycine as significantly correlated with RA, thus offering the potential for the advancement of biomarker discovery and the elucidation of disease mechanisms in RA.

Early cellular and molecular signatures correlate with severity of West Nile virus infection

Infection with West Nile virus (WNV) drives a wide range of responses, from asymptomatic to flu-like symptoms/fever or severe cases of encephalitis and death. To identify cellular and molecular signatures distinguishing WNV severity, we employed systems profiling of peripheral blood from asymptomatic and severely ill individuals infected with WNV. We interrogated immune responses longitudinally from acute infection through convalescence employing single-cell protein and transcriptional profiling complemented with matched serum proteomics and metabolomics as well as multi-omics analysis. At the acute time point, we detected both elevation of pro-inflammatory markers in innate immune cell types and reduction of regulatory T cell activity in participants with severe infection, whereas asymptomatic donors had higher expression of genes associated with anti-inflammatory CD16+ monocytes. Therefore, we demonstrated the potential of systems immunology using multiple cell-type and cell-state-specific analyses to identify correlates of infection severity and host cellular activity contributing to an effective anti-viral response.

Effect of Salvia miltiorrhiza Bunge extracts on improving the efficacy and reducing the toxicity of Tripterygium wilfordii polyglycosides in the treatment of rheumatoid arthritis

ETHNOPHARMACOLOGICAL RELEVANCE

Tripterygium wilfordii polyglycosides (TWP), extracted from the traditional Chinese herb Tripterygium wilfordii, has been widely used in the treatment of rheumatoid arthritis (RA). However, the toxicity of TWP to a variety of organs such as liver, kidney and testis greatly limits its clinical application. Salvia miltiorrhiza Bunge is often used in the treatment of RA due to its blood circulation promoting, stasis resolving, and anti-inflammatory effects. Salvia miltiorrhiza Bunge has also been reported to possess multiple organ protective effects.

AIM OF THE STUDY

To investigate the influences of two main components of Salviorrhiza miltiorrhiza Bunge, hydrophilic salvianolic acids (SA) and lipophilic tanshinones (Tan), on the efficacy and toxicity of TWP in treating RA and to explore the underlying mechanisms.

MATERIALS AND METHODS

SA and Tan were extracted from Salvia miltiorrhiza Bunge and the extracts were quantitated by HPLC and identified by UPLC-Q/TOF-MS. Then, a collagen-induced arthritis (CIA) rat model was established using bovine type II collagen (CII) and incomplete Freund's adjuvant (IFA). CIA rats were treated with TWP and/or SA/Tan. After 21 days of continuous treatment, arthritis symptoms and organs toxicity were evaluated. Meanwhile, serum metabolomics were investigated by the UPLC-Q/TOF-MS to understand the underlying mechanism.

RESULTS

SA and Tan extracts could significantly alleviate arthritis symptoms in CIA rats and decrease the serum levels of inflammatory factors TNF-α, IL-1β and IL-6 when combined with TWP. Meanwhile, both extracts alleviated injury of liver, kidney and testis caused by TWP, and the hydrophilic extract SA was superior. Moreover, a total of 38 endogenous differential metabolites were identified between the CIA model group and the TWP group, among which 33 metabolites were significantly recovered after the combination of SA or Tan. Metabolic pathway analysis showed that SA and Tan can affect metabolic pathways including linoleic acid metabolism, glycerophospholipid metabolism, sphingolipid metabolism and steroid biosynthesis metabolism pathway.

CONCLUSIONS

Our findings indicated for the first time that two Salviorrhiza miltiorrhiza Bunge extracts could improve the efficacy and reduce the toxicity of TWP in the treatment of RA by adjusting metabolic pathways, and the hydrophilic extract SA was superior.

Gut microbiota in pre-clinical rheumatoid arthritis: From pathogenesis to preventing progression

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by progressive polyarthritis that leads to cartilage and bone damage. Pre-clinical RA is a prolonged state before clinical arthritis and RA develop, in which autoantibodies (antibodies against citrullinated proteins, rheumatoid factors) can be present due to the breakdown of immunologic self-tolerance. As early treatment initiation before the onset of polyarthritis may achieve sustained remission, optimize clinical outcomes, and even prevent RA progression, the pre-clinical RA stage is showing the prospect to be the window of opportunity for RA treatment. Growing evidence has shown the role of the gut microbiota in inducing systemic inflammation and polyarthritis via multiple mechanisms, which may involve molecular mimicry, impaired intestinal barrier function, gut microbiota-derived metabolites mediated immune regulation, modulation of the gut microbiota's effect on immune cells, intestinal epithelial cells autophagy, and the interaction between the microbiome and human leukocyte antigen alleles as well as microRNAs. Since gut microbiota alterations in pre-clinical RA have been reported, potential therapies for modifying the gut microbiota in pre-clinical RA, including natural products, antibiotic therapy, fecal microbiota transplantation, probiotics, microRNAs therapy, vitamin D supplementation, autophagy inducer-based treatment, prebiotics, and diet, holds great promise for the successful treatment and even prevention of RA via altering ongoing inflammation. In this review, we summarized current studies that include pathogenesis of gut microbiota in RA progression and promising therapeutic strategies to provide novel ideas for the management of pre-clinical RA and possibly preventing arthritis progression.

Precise Lipidomics Decipher Circulating Ceramide and Sphingomyelin Cycle Associated with the Progression of Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a long-term autoimmune condition that causes joint and surrounding tissue inflammation. Lipid mediators are involved in inflammation and deterioration of the joints. Despite attempts to discover effective drug targets to intervene with lipid metabolism in the disease, progress has been limited. In this study, precise lipidomic technology was employed to quantify a broad range of serum ceramides and sphingomyelin (SM) in a large cohort, revealing an association between the accumulation of circulating ceramides and disturbed ceramide/SM cycles during the progression of RA. In our investigation, we discovered that eight ceramides exhibited a positive correlation with the activity of RA, thereby enhancing the accuracy of RA diagnosis, particularly in patients with serum antibody-negative RA. Furthermore, the enzyme SM phosphodiesterase 3 (SMPD3) was found to disrupt the circulating SM cycle and accelerate the progression of RA. The activity of SMPD3 can be inhibited by methotrexate, resulting in decreased metabolic conversion of SM to ceramide. These findings suggest that targeting the SM cycle may provide a new therapeutic option for RA.

Glucocorticoid receptors involved in ginsenoside compound K ameliorate adjuvant arthritis by inhibiting the glycolysis of fibroblast-like synoviocytes via the NF-κB/HIF-1α pathway

CONTEXT

Ginsenoside metabolite compound K (CK) is an active metabolite produced by ginsenosides in vivo that has an anti-arthritic effect related to the glucocorticoid receptor (GR). However, the potential mechanisms of CK remain unclear.

OBJECTIVE

This study explores the role and potential mechanisms of CK in vivo and in vitro.

MATERIALS AND METHODS

Adjuvant arthritis (AA) model was induced in Sprague-Dawley (SD) rats; the rats were randomly divided into four groups (n = 10): normal, AA, CK (80 mg/kg), and dexamethasone (Dex) group (1 mg/kg). From day 15, rats were treated with CK (once a day, i.g.) and Dex (once every 3 days, i.p.) for 18 days. To further verify the mechanism of CK, fibroblast-like synoviocytes (FLS) were stimulated by tumour necrosis factor α (TNF-α) to establish an inflammatory model in vitro.

RESULTS

CK (80 mg/kg) reduced paw swelling (52%) and arthritis global assessment (31%) compared to that in AA rats. In addition, CK (80 mg/kg) suppressed GLUT1 (38%), HK2 (50%), and PKM2 (56%) levels compared with those in AA FLS. However, the effects of CK (30 μM) on these events were weakened or enhanced after GR knockdown or overexpression in FLS stimulated by TNF-α (30 ng/mL). CK (80 mg/kg) also downregulated the expression of P65 (61%), p-IκB (92%), and HIF-1α (59%).

DISCUSSION AND CONCLUSIONS

The inhibition of CK on glycolysis and the NF-κB/HIF-1α pathway is potentially mediated through activating GR. These findings provide experimental evidence for elucidating the molecular mechanism of CK in treating rheumatoid arthritis (RA).

Metabolomic profiles, polygenic risk scores and risk of rheumatoid arthritis: a population-based cohort study in the UK Biobank

OBJECTIVE

To investigate the relationship between metabolomic profiles, genome-wide polygenic risk scores (PRSs) and risk of rheumatoid arthritis (RA).

METHODS

143 nuclear magnetic resonance-based plasma metabolic biomarkers were measured among 93 800 participants in the UK Biobank. The Cox regression model was used to assess the associations between these metabolic biomarkers and RA risk, and genetic correlation and Mendelian randomisation analyses were performed to reveal their causal relationships. Subsequently, a metabolic risk score (MRS) comprised of the weighted sum of 17 clinically validated metabolic markers was constructed. A PRS was derived by assigning weights to genetic variants that exhibited significant associations with RA at a genome-wide level.

RESULTS

A total of 620 incident RA cases were recorded during a median follow-up time of 8.2 years. We determined that 30 metabolic biomarkers were potentially associated with RA, while no further significant causal associations were found. Individuals in the top decile of MRS had an increased risk of RA (HR 3.52, 95% CI: 2.80 to 4.43) compared with those below the median of MRS. Further, significant gradient associations between MRS and RA risk were observed across genetic risk strata. Specifically, compared with the low genetic risk and favourable MRS group, the risk of incident RA in the high genetic risk and unfavourable MRS group has almost elevated by fivefold (HR 6.10, 95% CI: 4.06 to 9.14).

CONCLUSION

Our findings suggested the metabolic profiles comprising multiple metabolic biomarkers contribute to capturing an elevated risk of RA, and the integration of genome-wide PRSs further improved risk stratification.

An untargeted serum and urine lipidomics research based on UPLC-MS revealed the lipid alterations on adjuvant-induced arthritis rats

Rheumatoid arthritis (RA) is a systemic autoimmune disease dominated by chronic inflammatory lesions of peripheral synovial joints. Growing evidence suggests that abnormal lipid metabolism levels contribute to the progression of RA. Although several metabolomics studies have shown abnormality in the RA lipidome, the relationship between the overall lipid metabolites and RA has not been systematically evaluated. In this study, an untargeted lipidomics method based on ultra performance liquid chromatography-mass spectrometry (UPLC-MS) was used to analyze the serum and urine lipidomes of adjuvant-induced arthritis rats to study the characteristics of lipid metabolism changes in the rats and search lipid markers for diagnosing RA. By combining with orthogonal partial least squares discriminant analysis, a total of 52 potential lipid markers were identified, mainly involved in sphingolipid metabolism, glycerophospholipid metabolism, sterol lipid metabolism, glycerolipid metabolism and fatty acid metabolism, which provided crucial insight into lipid metabolism disturbances in RA. Further receiver operating characteristic analysis revealed that the areas under the curve of PC(22:4/16:0), PI(18:1/16:0) and LacCer(d18:1/12:0) from serum and 25-hydroxycholesterol from urine were 0.94, 1.00, 1.00 and 1.00, respectively, indicating the high predictive ability of this method for RA. In this study, our results indicated that a combination of serum and urine analysis can provide a more comprehensive and reliable assessment of RA, and a UPLC-MS-based lipidomics strategy is a powerful tool to search for potential lipid markers associated with RA and explore the pathogenesis of RA.

The role of dendritic cells and their immunometabolism in rheumatoid arthritis

Dendritic cells (DCs) play crucial roles in the pathogenesis of rheumatoid arthritis (RA), a prototypic autoimmune disease characterized by chronic synovitis and joint destruction. Conventional dendritic cells (cDCs) with professional antigen-presenting functions are enriched in the RA synovium. In the synovium, the cDCs are activated and show both enhanced migratory capacities and T cell activation in comparison with peripheral blood cDCs. Plasmacytoid dendritic cells, another subtype of DCs capable of type I interferon production, are likely to be tolerogenic in RA. Monocyte-derived dendritic cells (moDCs), once called "inflammatory DCs", are localized in the RA synovium, and they induce T-helper 17 cell expansion and enhanced proinflammatory cytokine production. Recent studies revealed that synovial proinflammatory hypoxic environments are linked to metabolic reprogramming. Activation of cDCs in the RA synovium is accompanied by enhanced glycolysis and anabolism. In sharp contrast, promoting catabolism can induce tolerogenic DCs from monocytes. Herein, we review recent studies that address the roles of DCs and their immunometabolic features in RA. Immunometabolism of DCs could be a potential therapeutic target in RA.

Integrative network fusion-based multi-omics study for biomarker identification and patient classification of rheumatoid arthritis

BACKGROUND

Cold-dampness Syndrome (RA-Cold) and Hot-dampness Syndrome (RA-Hot) are two distinct groups of rheumatoid arthritis (RA) patients with different clinical symptoms based on traditional Chinese medicine (TCM) theories and clinical empirical knowledge. However, the biological basis of the two syndromes has not been fully elucidated, which may restrict the development of personalized medicine and drug discovery for RA diagnosis and therapy.

METHODS

An integrative strategy combining clinical transcriptomics, phenomics, and metabolomics data based on clinical cohorts and adjuvant-induced arthritis rat models was performed to identify novel candidate biomarkers and to investigate the biological basis of RA-Cold and RA-Hot.

RESULTS

The main clinical symptoms of RA-Cold patients are joint swelling, pain, and contracture, which may be associated with the dysregulation of T cell-mediated immunity, osteoblast differentiation, and subsequent disorders of steroid biosynthesis and phenylalanine metabolism. In contrast, the main clinical symptoms of RA-Hot patients are fever, irritability, and vertigo, which may be associated with various signals regulating angiogenesis, adrenocorticotropic hormone release, and NLRP3 inflammasome activation, leading to disorders of steroid biosynthesis, nicotinamide, and sphingolipid metabolism. IL17F, 5-HT, and IL4I1 were identified as candidate biomarkers of RA-Cold, while S1P and GLNS were identified as candidate biomarkers of RA-Hot.

CONCLUSIONS

The current study presents the most comprehensive metabonomic and transcriptomic profiling of serum, urine, synovial fluid, and synovial tissue samples obtained from RA-Cold and RA-Hot patients and experimental animal models to date. Through the integration of multi-omics data and clinical independent validation, a list of novel candidate biomarkers of RA-Cold and RA-Hot syndromes were identified, that may be useful in improving RA diagnosis and therapy.

Rapid skin biomarker discovery using hydrogel-phase sampling followed by semi-automated liquid-phase re-extraction high-resolution mass spectrometry

A facile and rapid skin metabolomics protocol is proposed. The liquid microjunction-surface sampling probe system has been partly automated, and used in conjunction with hydrogel probes for skin metabolite analysis. A control device was built to precisely control the segmented solvent flow and analyte re-extraction into the liquid microjunction. This mode provides rapid online re-extraction of the analytes from hydrogel probes. Humectant was added to the hydrogel, and moist heat treatment was used to make the hydrogel probes rugged for sampling in the clinical setting. The developed method was validated for the analysis of choline - a putative biomarker of psoriasis. A linear relationship over six calibration levels from 3.18 × 10^-5 to 3.18 × 10^-4 mol m^-2 has been obtained. The limit of detection was 6.6 × 10^-6 mol m^-2, while the recoveries range from 92 to 109%. The within-run and between-run precision were evaluated and the coefficients of variation range from 1.84 to 7.13%. Furthermore, the developed method has been used to screen patients (n = 10) and healthy participants (control group; n = 10) for psoriasis-related skin metabolites. Metabolomic profiling of the skin excretion-related signals identified potential biomarkers of psoriasis: choline, pipecolic acid, ornithine, urocanic acid, and methionine.

Serum metabolomic profiling identifies potential biomarkers in arthritis in older adults: an exploratory study

BACKGROUND

Seronegative elderly-onset rheumatoid arthritis (EORA)^neg and polymyalgia rheumatica (PMR) have similar clinical characteristics making them difficult to distinguish based on clinical features. We hypothesized that the study of serum metabolome could identify potential biomarkers of PMR vs. EORA^neg.

METHODS

Arthritis in older adults (ARTIEL) is an observational prospective cohort with patients older than 60 years of age with newly diagnosed arthritis. Patients' blood samples were compared at baseline with 18 controls. A thorough clinical examination was conducted. A Bruker Avance 600 MHz spectrometer was used to acquire Nuclear Magnetic Resonance (NMR) spectra of serum samples. Chenomx NMR suite 8.5 was used for metabolite identification and quantification.Student t-test, one-way ANOVA, binary linear regression and ROC curve, Pearson's correlation along with pathway analyses were conducted.

RESULTS

Twenty-eight patients were diagnosed with EORA^neg and 20 with PMR. EORA^neg patients had a mean disease activity score (DAS)-Erythrocyte Sedimentation Rate (ESR) of 6.21 ± 1.00. All PMR patients reported shoulder pain, and 90% reported pelvic pain. Fifty-eight polar metabolites were identified. Of these, 3-hydroxybutyrate, acetate, glucose, glycine, lactate, and o-acetylcholine (o-ACh), were significantly different between groups. Of interest, IL-6 correlated with different metabolites in PMR and EORA^neg suggesting different inflammatory activated pathways. Finally, lactate, o-ACh, taurine, and sex (female) were identified as distinguishable factors of PMR from EORA^neg with a sensitivity of 90%, specificity of 92.3%, and an AUC of 0.925 (p < 0.001).

CONCLUSION

These results suggest that EORA^neg and PMR have different serum metabolomic profiles that might be related to their pathobiology and can be used as biomarker to discriminate between both diseases.

Patients with ACPA-positive and ACPA-negative rheumatoid arthritis show different serological autoantibody repertoires and autoantibody associations with disease activity

Patients with rheumatoid arthritis (RA) can test either positive or negative for circulating anti-citrullinated protein antibodies (ACPA) and are thereby categorized as ACPA-positive (ACPA+) or ACPA-negative (ACPA-), respectively. In this study, we aimed to elucidate a broader range of serological autoantibodies that could further explain immunological differences between patients with ACPA+ RA and ACPA- RA. On serum collected from adult patients with ACPA+ RA (n = 32), ACPA- RA (n = 30), and matched healthy controls (n = 30), we used a highly multiplex autoantibody profiling assay to screen for over 1600 IgG autoantibodies that target full-length, correctly folded, native human proteins. We identified differences in serum autoantibodies between patients with ACPA+ RA and ACPA- RA compared with healthy controls. Specifically, we found 22 and 19 autoantibodies with significantly higher abundances in ACPA+ RA patients and ACPA- RA patients, respectively. Among these two sets of autoantibodies, only one autoantibody (anti-GTF2A2) was common in both comparisons; this provides further evidence of immunological differences between these two RA subgroups despite sharing similar symptoms. On the other hand, we identified 30 and 25 autoantibodies with lower abundances in ACPA+ RA and ACPA- RA, respectively, of which 8 autoantibodies were common in both comparisons; we report for the first time that the depletion of certain autoantibodies may be linked to this autoimmune disease. Functional enrichment analysis of the protein antigens targeted by these autoantibodies showed an over-representation of a range of essential biological processes, including programmed cell death, metabolism, and signal transduction. Lastly, we found that autoantibodies correlate with Clinical Disease Activity Index, but associate differently depending on patients' ACPA status. In all, we present candidate autoantibody biomarker signatures associated with ACPA status and disease activity in RA, providing a promising avenue for patient stratification and diagnostics.

Rapid, sensitive, and high-throughput quantification of broad serological ceramides by using isotope dilution liquid chromatography-negative ion electrospray tandem mass spectrometry

Ceramides are important intermediates in the metabolism of sphingolipids. High-throughput liquid chromatography-mass spectrometry has been used extensively for monitoring the levels of serological ceramides, but is still limited by inadequate coverage or lack of sensitivity. Herein, a rapid, sensitive, and high-throughput isotope dilution liquid chromatography-negative ion electrospray tandem mass spectrometry (IDLC-nESI-MS/MS) method was developed and verified for accurate quantification of 41 ceramides, involving ceramides with C16-20 sphingosine, dihydro-ceramide, and dehydro-ceramide. This method was validated with excellent linearity (R² > 0.99) and good recovery in the range of 90-110%. Intra- and inter-day imprecision were below 5.57% and 7.83% respectively. The improved high-throughput quantitative method developed in this study may aid in the accurate characterization of ceramides for understanding ceramide biology and application in disease diagnosis.

Biomarkers (mRNAs and non-coding RNAs) for the diagnosis and prognosis of rheumatoid arthritis

In recent years, diagnostic and therapeutic approaches for rheumatoid arthritis (RA) have continued to improve. However, in the advanced stages of the disease, patients are unable to achieve long-term clinical remission and often suffer from systemic multi-organ damage and severe complications. Patients with RA usually have no overt clinical manifestations in the early stages, and by the time a definitive diagnosis is made, the disease is already at an advanced stage. RA is diagnosed clinically and with laboratory tests, including the blood markers C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) and the autoantibodies rheumatoid factor (RF) and anticitrullinated protein antibodies (ACPA). However, the presence of RF and ACPA autoantibodies is associated with aggravated disease, joint damage, and increased mortality, and these autoantibodies have low specificity and sensitivity. The etiology of RA is unknown, with the pathogenesis involving multiple factors and clinical heterogeneity. The early diagnosis, subtype classification, and prognosis of RA remain challenging, and studies to develop minimally invasive or non-invasive biomarkers in the form of biofluid biopsies are becoming more common. Non-coding RNA (ncRNA) molecules are composed of long non-coding RNAs, small nucleolar RNAs, microRNAs, and circular RNAs, which play an essential role in disease onset and progression and can be used in the early diagnosis and prognosis of RA. In this review of the diagnostic and prognostic approaches to RA disease, we provide an overview of the current knowledge on the subject, focusing on recent advances in mRNA-ncRNA as diagnostic and prognostic biomarkers from the biofluid to the tissue level.

ST3GAL3 Promotes the Inflammatory Response of Fibroblast-Like Synoviocytes in Rheumatoid Arthritis by Activating the TLR9/MyD88 Pathway

This study is aimed at investigating the role of β-galactoside-α2,3-sialyltransferase III (ST3GAL3) in fibroblast-like synoviocytes (FLS) in rheumatoid arthritis (RA), as well as its potential mechanism of action. The Gene Expression Omnibus (GEO) database and gene set enrichment analysis (GSEA) were used to analyse the expression of ST3GAL3 and the enrichment signalling pathways associated with ST3GAL3 in RA. The effects of ST3GAL3 on tumour necrosis factor- (TNF-) α and interleukin- (IL-) 1β-treated MH7A cells were determined using methyl thiazolyl tetrazolium (MTT), transwell, and enzyme-linked immunosorbent assays (ELISA). The expression of proliferation-associated proteins and Toll-like receptor (TLR) pathway-enriched proteins was analysed using western blotting. As a main result, ST3GAL3 was screened as an overlapping upregulated gene from GSE101193 and GSE94519 datasets. ST3GAL3 expression in MH7A cells significantly increased with increasing treatment time with TNF-α or IL-1β. TLR9/myeloid differentiation primary response protein 88 (MyD88) is a downstream activation pathway of ST3GAL3. ST3GAL3 overexpression promoted MH7A cell proliferation and migration. Additionally, ST3GAL3 overexpression upregulated the expression of proliferation-associated proteins (cyclinD, cyclinE, and proliferating cell nuclear antigen) and TLR pathway enrichment factors (TLR9 and MyD88) and increased the production of matrix metallopeptidase (MMP) 1, MMP3, interleukin- (IL-) 6, and IL-8, whereas si-ST3GAL3 had the opposite effect. The addition of TLR9 agonists (CpG 2216 and CpG 2006) reversed the effects of si-ST3GAL3 on MH7A cell proliferation, migration, and inflammation. TLR9-specific siRNA reversed the effects of ST3GAL3 overexpression on MH7A cell proliferation, migration, and inflammation. In conclusion, ST3GAL3 is likely involved in RA pathogenesis by activating the TLR9/MyD88 pathway.

Association of the serological status of rheumatoid arthritis patients with two circulating protein biomarkers: A useful tool for precision medicine strategies

Rheumatoid arthritis (RA) is an autoimmune disease characterized by chronic inflammation of the joints and presence of systemic autoantibodies, with a great clinical and molecular heterogeneity. Rheumatoid Factor (RF) and anti-citrullinated protein antibodies (ACPA) are routinely used for the diagnosis of RA. However, additional serological markers are needed to improve the clinical management of this disease, allowing for better patient stratification and the desirable application of precision medicine strategies. In the present study, we investigated those systemic molecular changes that are associated with the RF and ACPA status of RA patients. To achieve this objective, we followed a proteomic biomarker pipeline from the discovery phase to validation. First, we performed an iTRAQ-based quantitative proteomic experiment on serum samples from the RA cohort of the Hospital of Santiago de Compostela (CHUS). In this discovery phase, serum samples from the CHUS cohort were pooled according to their RF/ACPA status. Shotgun analysis revealed that, in comparison with the double negative group (RF-/ACPA-), the abundance of 12 proteins was altered in the RF+/ACPA+ pool, 16 in the RF+/ACPA- pool and 10 in the RF-/ACPA+ pool. Vitamin D binding protein and haptoglobin were the unique proteins increased in all the comparisons. For the verification phase, 80 samples from the same cohort were analyzed individually. To this end, we developed a Multiple Reaction Monitoring (MRM) method that was employed in a comprehensive targeted analysis with the aim of verifying the results obtained in the discovery phase. Thirty-one peptides belonging to 12 proteins associated with RF and/or ACPA status were quantified by MRM. In a final validation phase, the serum levels of alpha-1-acid glycoprotein 1 (A1AG1), haptoglobin (HPT) and retinol-binding protein 4 (RET4) were measured by immunoassays in the RA cohort of the Hospital of A Coruña (HUAC). The increase of two of these putative biomarkers in the double seropositive group was validated in 260 patients from this cohort (p = 0.009 A1AG1; p = 0.003 HPT). The increased level of A1AG1 showed association with RF rather than ACPA (p = 0.023), whereas HPT showed association with ACPA rather than RF (p = 0.013). Altogether, this study has allowed a further classification of the RA seropositive patients into two novel clusters: RF+A1AG+ and ACPA+HPT+. The determination of A1AG1 and HPT in serum would provide novel information useful for RA patient stratification, which could facilitate the effective implementation of personalized medicine in routine clinical practice.

Precision Medicine Approaches with Metabolomics and Artificial Intelligence

Recent technological innovations in the field of mass spectrometry have supported the use of metabolomics analysis for precision medicine. This growth has been allowed also by the application of algorithms to data analysis, including multivariate and machine learning methods, which are fundamental to managing large number of variables and samples. In the present review, we reported and discussed the application of artificial intelligence (AI) strategies for metabolomics data analysis. Particularly, we focused on widely used non-linear machine learning classifiers, such as ANN, random forest, and support vector machine (SVM) algorithms. A discussion of recent studies and research focused on disease classification, biomarker identification and early diagnosis is presented. Challenges in the implementation of metabolomics–AI systems, limitations thereof and recent tools were also discussed.

Imperatorin Inhibits Proliferation, Migration, and Inflammation via Blocking the NF-κB and MAPK Pathways in Rheumatoid Fibroblast-like Synoviocytes

Rheumatoid arthritis (RA) is a chronic joint inflammatory disease associated with the aberrant activation of fibroblast-like synoviocytes (FLSs). Searching for natural compounds that may suppress the activation of FLSs has become a complementary approach for RA treatment. Here, we investigated the effects and mechanisms of imperatorin (IPT) on proliferation, migration, and inflammation in primary cultured arthritic FLSs. We found that IPT significantly suppressed TNFα-induced proliferation and migration of arthritic FLSs, but showed little effect on survival and apoptosis. In addition, IPT treatment significantly reduced the TNFα-induced expression of pro-inflammatory cytokines (IL-1β, TNFα, IL-6, and IL-8) in arthritic FLSs. Further mechanism studies suggested that IPT inhibited the activations of p38 and extracellular signal-regulated kinase (ERK). Also, IPT blocked the nuclear factor of κB (NF-κB) activation by suppressing the phosphorylation and degradation of IκBα, thereby preventing the translocation of p65. Collectively, our results demonstrated that IPT could inhibit the over-activated phenotypes of arthritic FLSs via the mitogen-activated protein kinase (MAPK) (p38 and ERK) and NF-κB pathways leading to the down-regulation of pro-inflammatory cytokines, which might be beneficial to the anti-proliferative and anti-migratory activities of FLS cells. These findings suggest that IPT has the potential to be developed as a novel agent for RA treatment.

Metabolic Profiling in Rheumatoid Arthritis, Psoriatic Arthritis, and Psoriasis: Elucidating Pathogenesis, Improving Diagnosis, and Monitoring Disease Activity

Immune-mediated inflammatory diseases (IMIDs), such as rheumatoid arthritis (RA), psoriatic arthritis (PsA), and psoriasis (Ps), represent autoinflammatory and autoimmune disorders, as well as conditions that have an overlap of both categories. Understanding the underlying pathogeneses, making diagnoses, and choosing individualized treatments remain challenging due to heterogeneous disease phenotypes and the lack of reliable biomarkers that drive the treatment choice. In this review, we provide an overview of the low-molecular-weight metabolites that might be employed as biomarkers for various applications, e.g., early diagnosis, disease activity monitoring, and treatment-response prediction, in RA, PsA, and Ps. The literature was evaluated, and putative biomarkers in different matrices were identified, categorized, and summarized. While some of these candidate biomarkers appeared to be disease-specific, others were shared across multiple IMIDs, indicating common underlying disease mechanisms. However, there is still a long way to go for their application in a routine clinical setting. We propose that studies integrating omics analyses of large patient cohorts from different IMIDs should be performed to further elucidate their pathomechanisms and treatment options. This could lead to the identification and validation of biomarkers that might be applied in the context of precision medicine to improve the clinical outcomes of these IMID patients.

Lipidomic Profiling in Synovial Tissue

The analysis of synovial tissue offers the potential for the comprehensive characterization of cell types involved in arthritis pathogenesis. The studies performed to date in synovial tissue have made it possible to define synovial pathotypes, which relate to disease severity and response to treatment. Lipidomics is the branch of metabolomics that allows the quantification and identification of lipids in different biological samples. Studies in animal models of arthritis and in serum/plasma from patients with arthritis suggest the involvement of different types of lipids (glycerophospholipids, glycerolipids, sphingolipids, oxylipins, fatty acids) in the pathogenesis of arthritis. We reviewed studies that quantified lipids in different types of tissues and their relationship with inflammation. We propose that combining lipidomics with currently used “omics” techniques can improve the information obtained from the analysis of synovial tissue, for a better understanding of pathogenesis and the development of new therapeutic strategies.