Metabolomic Biomarker Candidates for Skeletal Muscle Loss in the Collagen-Induced Arthritis (CIA) Model

Identification of Plasma Metabolomic Biomarkers of Juvenile Idiopathic Arthritis

Identification of disease and therapeutic biomarkers remains a significant challenge in the early diagnosis and effective treatment of juvenile idiopathic arthritis (JIA). In this study, plasma metabolomic profiling was conducted to identify disease-related metabolic biomarkers associated with JIA. Plasma samples from treatment-naïve JIA patients and non-JIA reference patients underwent global metabolomic profiling across discovery (60 JIA, 60 non-JIA) and replication (49 JIA, 38 non-JIA) cohorts. Univariate analysis identified significant metabolites (q-value ≤ 0.05), followed by enrichment analysis using ChemRICH and metabolic network mapping with MetaMapp and Cytoscape. Receiver operating characteristic (ROC) analysis determined the top discriminating biomarkers based on area under the curve (AUC) values. A total of over 800 metabolites were measured, consisting of 714 known and 155 unknown compounds. In the discovery cohort, 587 metabolites were significantly altered in JIA patients compared with the reference population (q < 0.05). In the replication cohort, 288 metabolites were significantly altered, with 78 overlapping metabolites demonstrating the same directional change in both cohorts. JIA was associated with a notable increase in plasma levels of sphingosine metabolites and fatty acid ethanolamides and decreased plasma levels of sarcosine, iminodiacetate, and the unknown metabolite X-12462. Chemical enrichment analysis identified cycloparaffins in the form of naproxen and its metabolites, unsaturated lysophospholipids, saturated phosphatidylcholines, sphingomyelins, ethanolamines, and saturated ceramides as the top discriminating biochemical clusters. ROC curve analysis identified 11 metabolites classified as highly discriminatory based on an AUC > 0.90, with the top discriminating metabolite being sphinganine-1-phosphate (AUC = 0.98). This study identifies specific metabolic changes in JIA, particularly within sphingosine metabolism, through both discovery and replication cohorts. Plasma metabolomic profiling shows promise in pinpointing JIA-specific biomarkers, differentiating them from those in healthy controls and Crohn's disease, which may improve diagnosis and treatment.

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.

Carnosine, Zinc and Copper: A Menage a Trois in Bone and Cartilage Protection

Dysregulated metal homeostasis is associated with many pathological conditions, including arthritic diseases. Osteoarthritis and rheumatoid arthritis are the two most prevalent disorders that damage the joints and lead to cartilage and bone destruction. Recent studies show that the levels of zinc (Zn) and copper (Cu) are generally altered in the serum of arthritis patients. Therefore, metal dyshomeostasis may reflect the contribution of these trace elements to the disease's pathogenesis and manifestations, suggesting their potential for prognosis and treatment. Carnosine (Car) also emerged as a biomarker in arthritis and exerts protective and osteogenic effects in arthritic joints. Notably, its zinc(II) complex, polaprezinc, has been recently proposed as a drug-repurposing candidate for bone fracture healing. On these bases, this review article aims to provide an overview of the beneficial roles of Cu and Zn in bone and cartilage health and their potential application in tissue engineering. The effects of Car and polaprezinc in promoting cartilage and bone regeneration are also discussed. We hypothesize that polaprezinc could exchange Zn for Cu, present in the culture media, due to its higher sequestering ability towards Cu. However, future studies should unveil the potential contribution of Cu in the beneficial effects of polaprezinc.

Urinary metabolomic biomarker candidates for skeletal muscle wasting in patients with rheumatoid arthritis

BACKGROUND

Rheumatoid arthritis (RA) is an autoimmune disease that affects the joints, leading to chronic synovial inflammation and local tissue destruction. Extra-articular manifestations may also occur, such as changes in body composition. Skeletal muscle wasting is often observed in patients with RA, but methods for assessing loss of muscle mass are expensive and not widely available. Metabolomic analysis has shown great potential for identifying changes in the metabolite profile of patients with autoimmune diseases. In this setting, urine metabolomic profiling in patients with RA may be a useful tool to identify skeletal muscle wasting.

METHODS

Patients aged 40-70 years with RA have been recruited according to the 2010 ACR/EULAR classification criteria. Further, the Disease Activity Score in 28 joints using the C-reactive protein level (DAS28-CRP) determined the disease activity. The muscle mass was measured by Dual X-ray absorptiometry (DXA) to generate the appendicular lean mass index (ALMI) by summing the lean mass measurements for both arms and legs and dividing them by height squared (kg/height² ). Finally, urine metabolomic analysis by ¹ H nuclear magnetic resonance (¹ H-NMR) spectroscopy was performed and the metabolomics data set analysed using the BAYESIL and MetaboAnalyst software packages. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were applied to the ¹ H-NMR data, followed by Spearman's correlation analysis. The combined receiver operating characteristic curve (ROC) was calculated, as well as the logistic regression analyses to establish a diagnostic model. The significance level at P < 0.05 was set for all analyses.

RESULTS

The total set of subjects investigated included 90 patients with RA. Most patients were women (86.7%), with a mean age of 56.5 ± 7.3 years old and a median DAS28-CRP of 3.0 (IQR 1.0-3.0). Fifteen metabolites were identified in the urine samples with high variable importance in projection (VIP scores) by MetaboAnalyst. Of these, dimethylglycine (r = 0.205; P = 0.053), oxoisovalerate (r = -0.203; P = 0.055), and isobutyric acid (r = -0.249; P = 0.018) were significantly correlated with ALMI. Based on the low muscle mass (ALMI ≤6.0 kg/m² for women and ≤8.1 kg/m² for men) a diagnostic model have been established with dimethylglycine (area under the curve [AUC] = 0.65), oxoisovalerate (AUC = 0.49), and isobutyric acid (AUC = 0.83) with significant sensitivity and specificity.

CONCLUSIONS

Isobutyric acid, oxoisovalerate, and dimethylglycine from urine samples were associated with low skeletal muscle mass in patients with RA. These findings suggest that this group of metabolites may be further tested as biomarkers for identification of skeletal muscle wasting.

Phenolic-Compound-Rich Opuntia littoralis Ethyl Acetate Extract Relaxes Arthritic Symptoms in Collagen-Induced Mice Model via Bone Morphogenic Markers

Rheumatoid arthritis (RA) is an autoimmune disease that causes inflammation and progressive joint dysfunction. Opuntia littoralis (OL) has a high nutritional content and is thought to offer a number of health advantages. We aimed to evaluate the anti-arthritic potential of OL extracts against collagen-induced arthritis (CIA). We designed three OL cladode fractions from the concentrated aqueous extract: hexane, ethyl acetate (EAE), and hydro alcohol (HAE). We investigated the nitric oxide and MDA levels of EAE against lipopolysaccharide-induced RAW264.7 cells; then, we administered EAE to the mice with CIA to confirm the anti-inflammatory effects against RA. HPLC analysis of the OL extracts showed a high concentration of phenolic compounds in EAE. Treatment with EAE (10 and 20 mg/100 g body weight of mice) after 10 days of immunization with collagen showed a significant inhibition of joint inflammation, paw swelling, and edemas. MDA and cytokine levels (IL-1β, IL-6R, IL-6, IL-17, and IL-23) were significantly reduced. EAE effectively ameliorated COX-2, NF-kB, STAT-3, PTEN, and RANKL expression. OL-EAE therapy significantly upregulated the expression of miR-28 and miR-199a. In conclusion, the anti-inflammatory actions of OL-EAE altered the cellular localization of the inflammatory mediators, therefore preventing joint inflammation via partial epigenetic and metabolic regulations in experimental mice.

A Review of Metabolomic Profiling in Rheumatoid Arthritis: Bringing New Insights in Disease Pathogenesis, Treatment and Comorbidities

Metabolomic analysis provides a wealth of information that can be predictive of distinctive phenotypes of pathogenic processes and has been applied to better understand disease development. Rheumatoid arthritis (RA) is an autoimmune disease with the establishment of chronic synovial inflammation that affects joints and peripheral tissues such as skeletal muscle and bone. There is a lack of useful disease biomarkers to track disease activity, drug response and follow-up in RA. In this review, we describe potential metabolic biomarkers that might be helpful in the study of RA pathogenesis, drug response and risk of comorbidities. TMAO (choline and trimethylamine oxide) and TCA (tricarboxylic acid) cycle products have been suggested to modulate metabolic profiles during the early stages of RA and are present systemically, which is a relevant characteristic for biomarkers. Moreover, the analysis of lipids such as cholesterol, FFAs and PUFAs may provide important information before disease onset to predict disease activity and treatment response. Regarding therapeutics, TNF inhibitors may increase the levels of tryptophan, valine, lysine, creatinine and alanine, whereas JAK/STAT inhibitors may modulate exclusively fatty acids. These observations indicate that different disease modifying antirheumatic drugs have specific metabolic profiles and can reveal differences between responders and non-responders. In terms of comorbidities, physical impairment represented by higher fatigue scores and muscle wasting has been associated with an increase in urea cycle, FFAs, tocopherols and BCAAs. In conclusion, synovial fluid, blood and urine samples from RA patients seem to provide critical information about the metabolic profile related to drug response, disease activity and comorbidities.