Global and targeted metabolomics of synovial fluid discovers special osteoarthritis metabolites

Unraveling the molecular landscape of osteoarthritis: A comprehensive review focused on the role of non-coding RNAs

Osteoarthritis (OA) poses a significant global health challenge, with its prevalence anticipated to increase in the coming years. This review delves into the emerging molecular biomarkers in OA pathology, focusing on the roles of various molecules such as metabolites, noncoding RNAs (ncRNAs), including microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs). Advances in omics technologies have transformed biomarker identification, enabling comprehensive analyses of the complex pathways involved in OA pathogenesis. Notably, ncRNAs, especially miRNAs and lncRNAs, exhibit dysregulated expression patterns in OA, presenting promising opportunities for diagnosis and therapy. Additionally, the intricate interplay between epigenetic modifications and OA progression highlights the regulatory role of epigenetics in gene expression dynamics. Genome-wide association studies have pinpointed key genes undergoing epigenetic changes, providing insights into the inflammatory processes and chondrocyte hypertrophy typical of OA. Understanding the molecular landscape of OA, including biomarkers and epigenetic mechanisms, holds significant potential for developing innovative diagnostic tools and therapeutic strategies for OA management.

Metabolic profiling of synovial fluid in human temporomandibular joint osteoarthritis

Introduction

Temporomandibular joint (TMJ) osteoarthritis (OA) is a common TMJ degenerative disease with an unclear mechanism. Synovial fluid (SF), an important component of TMJ, contains various proteins and metabolites that may directly contribute to OA. The present study aimed to investigate the influence of SF in TMJOA at the metabolite level.

Methods

Untargeted and widely targeted metabolic profiling were employed to identify metabolic changes in SF of 90 patients with different TMJOA grades according to TMJ magnetic resonance imaging.

Results

A total 1498 metabolites were detected. Most of the metabolites were amino acids and associated metabolites, benzene and substituted derivatives, and lipids. Among patients with mild, moderate and severe TMJOA, 164 gradually increasing and 176 gradually decreasing metabolites were identified, indicating that biosynthesis of cofactors, choline metabolism, mineral absorption and selenocompound metabolism are closely related to TMJOA grade. Combined metabolomics and clinical examination revealed 37 upregulated metabolites and 16 downregulated metabolites in patients with pain, of which 19 and 26 metabolites were positively and negatively correlated, respectively, with maximum interincisal opening. A model was constructed to diagnose TMJOA grade and nine biomarkers were identified. The identified metabolites are key to exploring the mechanism of TMJOA.

Discussion

In the present study, a metabolic profile was constructed and assessed using a much larger number of human SF samples from patients with TMJOA, and a model was established to contribute to the diagnosis of TMJOA grade. The findings expand our knowledge of metabolites in human SF of TMJOA patients, and provide an important basis for further research on the pathogenesis and treatment of TMJOA.

Differential Metabolites in Osteoarthritis: A Systematic Review and Meta-Analysis

(1) Many studies have attempted to utilize metabolomic approaches to explore potential biomarkers for the early detection of osteoarthritis (OA), but consistent and high-level evidence is still lacking. In this study, we performed a systematic review and meta-analysis of differential small molecule metabolites between OA patients and healthy individuals to screen promising candidates from a large number of samples with the aim of informing future prospective studies. (2) Methods: We searched the EMBASE, the Cochrane Library, PubMed, Web of Science, Wan Fang Data, VIP Date, and CNKI up to 11 August 2022, and selected relevant records based on inclusion criteria. The risk of bias was assessed using the Newcastle-Ottawa quality assessment scale. We performed qualitative synthesis by counting the frequencies of changing directions and conducted meta-analyses using the random effects model and the fixed-effects model to calculate the mean difference and 95% confidence interval. (3) Results: A total of 3798 records were identified and 13 studies with 495 participants were included. In the 13 studies, 132 kinds of small molecule differential metabolites were extracted, 58 increased, 57 decreased and 17 had direction conflicts. Among them, 37 metabolites appeared more than twice. The results of meta-analyses among four studies showed that three metabolites increased, and eight metabolites decreased compared to healthy controls (HC). (4) Conclusions: The main differential metabolites between OA and healthy subjects were amino acids (AAs) and their derivatives, including tryptophan, lysine, leucine, proline, phenylalanine, glutamine, dimethylglycine, citrulline, asparagine, acetylcarnitine and creatinine (muscle metabolic products), which could be potential biomarkers for predicting OA.

Cross-talk of inflammation and chondrocyte intracellular metabolism in osteoarthritis

Osteoarthritis is a disease that impacts millions around the world, leading to significant financial and medical burden for patients and the healthcare system. However, no effective biomarkers or disease modifying therapeutics exist for the early identification and management of the disease. Inflammation drives chondrocytes to express extracellular matrix (ECM) degrading enzymes and interruption of this pathway is a viable target to prevent degradation of cartilage. It has been demonstrated that inflammation can alter the intracellular metabolism of chondrocytes, a process known as metabolic reprogramming. This metabolic reprogramming is critical for cartilage breakdown by shifting chondrocytes to an ECM-catabolic state and likely as a potential therapeutic target for osteoarthritis. Metabolic modulators hold the potential to reduce chondrocyte inflammatory responses and protect cartilage. In this narrative review, we explore some of the existing examples of interactions between metabolism and inflammatory pathways in chondrocytes. We summarize the impact of inflammatory stimulation on various metabolic pathways and describe several examples by which targeting of metabolism is able to modulate ECM-degrading activity of chondrocytes to protect against cartilage damage.

Emerging molecular biomarkers in osteoarthritis pathology

Osteoarthritis (OA) is the most common form of arthritis resulting in joint discomfort and disability, culminating in decline in life quality. Attention has been drawn in recent years to disease-associated molecular biomarkers found in readily accessible biofluids due to low invasiveness of acquisition and their potential to detect early pathological molecular changes not observed with traditional imaging methodology. These biochemical markers of OA have been found in synovial fluid, blood, and urine. They include emerging molecular classes, such as metabolites and noncoding RNAs, as well as classical biomarkers, like inflammatory mediators and by-products of degradative processes involving articular cartilage. Although blood-based biomarkers tend to be most studied, the use of synovial fluid, a more isolated biofluid in the synovial joint, and urine as an excreted fluid containing OA biomarkers can offer valuable information on local and overall disease activity, respectively. Furthermore, larger clinical studies are required to determine relationships between biomarkers in different biofluids, and their impacts on patient measures of OA. This narrative review provides a concise overview of recent studies of OA using these four classes of biomarkers as potential biomarker for measuring disease incidence, staging, prognosis, and therapeutic intervention efficacy.

A new strategy for osteoarthritis therapy: Inhibition of glycolysis

Osteoarthritis (OA) is a common degenerative disease of the joints. It is primarily caused by age, obesity, mechanical damage, genetics, and other factors, leading to cartilage degradation, synovial inflammation, and subchondral sclerosis with osteophyte formation. Many recent studies have reported that glycolysis disorders are related lead to OA. There is a close relationship between glycolysis and OA. Because of their hypoxic environment, chondrocytes are highly dependent on glycolysis, their primary energy source for chondrocytes. Glycolysis plays a vital role in OA development. In this paper, we comprehensively summarized the abnormal expression of related glycolytic enzymes in OA, including Hexokinase 2 (HK2), Pyruvate kinase 2 (PKM2), Phosphofructokinase-2/fructose-2, 6-Bisphosphatase 3 (PFKFB3), lactate dehydrogenase A (LDHA), and discussed the potential application of glycolysis in treating OA. Finally, the natural products that can regulate the glycolytic pathway were summarized. Targeting glucose transporters and rate-limiting enzymes to glycolysis may play an essential role in treating OA.

What's New in the Diagnosis of Periprosthetic Joint Infections: Focus on Synovial Fluid Biomarkers

Periprosthetic joint infections are some of the leading causes of revision prosthetic surgery, accounting for 25% of failed total knee replacements and 15% of failed total hip replacements. The search for a biomarker that, together with clinical and radiological findings, could improve the management of such patients is currently a significant challenge for orthopaedic surgeons. Synovial fluid is a viscous and mucinous substance produced by the synovium, a specialized connective tissue that lines diarthrodial joints. Synovial fluid is an ultrafiltrate of plasma but also contains proteins secreted from the surrounding tissues, including the articular cartilage and synovium. Therefore, synovial fluid represents a source of disease-related proteins that could be used as potential biomarkers in several articular diseases. Based on these findings, the study of synovial fluid has been gaining increasing importance in recent years. This review aims to assess the accuracy and the limitations of the most promising synovial fluid biomarkers-i.e., Alpha-Defensin, Leukocyte Esterase, C-Reactive Protein, Interleukin-6, Calprotectin, Presepsin and Neopterin-in the diagnosis of PJI. Special attention will be given to emerging synovial biomarkers, which could soon be important in diagnosing PJIs.

The Usefulness of Synovial Fluid Proteome Analysis in Orthopaedics: Focus on Osteoarthritis and Periprosthetic Joint Infections

Synovial fluid (SF) is a viscous and mucinous substance produced by the synovium, a specialized connective tissue that lines diarthrodial joints. SF represents a source of disease-related proteins that could be used as potential biomarkers in several articular diseases. Based on these findings the study of SF has been gaining increasing importance, in recent years. This review aims to summarize the usefulness of synovial fluid in orthopaedics research and clinical practice, mainly focusing on osteoarthritis (OA) and periprosthetic joint infections (PJIs). Proteomics of the SF has shown the up-regulation of several components of the classic complement pathway in OA samples, including C1, C2, C3, C4A, C4B, C5, and C4 C4BPA, thus depicting that complement is involved in the pathogenesis of OA. Moreover, proteomics has demonstrated that some pro-inflammatory cytokines, namely IL-6, IL-8, and IL-18, have a role in OA. Several SF proteins have been studied to improve the diagnosis of PJIs, including alpha-defensin (Alpha-D), leukocyte esterase (LE), c-reactive protein (CRP), interleukin-6 (IL-6), calprotectin and presepsin. The limits and potentials of these SF biomarkers will be discussed.

Glutamine metabolism modulates chondrocyte inflammatory response

Osteoarthritis is the most common joint disease in the world with significant societal consequences but lacks effective disease-modifying interventions. The pathophysiology consists of a prominent inflammatory component that can be targeted to prevent cartilage degradation and structural defects. Intracellular metabolism has emerged as a culprit of the inflammatory response in chondrocytes, with both processes co-regulating each other. The role of glutamine metabolism in chondrocytes, especially in the context of inflammation, lacks a thorough understanding and is the focus of this work. We display that mouse chondrocytes utilize glutamine for energy production and anabolic processes. Furthermore, we show that glutamine deprivation itself causes metabolic reprogramming and decreases the inflammatory response of chondrocytes through inhibition of NF-κB activity. Finally, we display that glutamine deprivation promotes autophagy and that ammonia is an inhibitor of autophagy. Overall, we identify a relationship between glutamine metabolism and inflammatory signaling and display the need for increased study of chondrocyte metabolic systems.

The Hepatoprotective Effect of Leonurine Hydrochloride Against Alcoholic Liver Disease Based on Transcriptomic and Metabolomic Analysis

Excessive alcohol consumption can eventually progress to alcoholic liver disease (ALD). The underlying mechanism of ALD toxicity is primarily associated with oxidative damage. Many alkaloids have been reported to possess potential antioxidative efficacy, while the mechanism of their hepatoprotective activity against ALD is still not clear. In this study, eight alkaloids were selected from a monomer library of Traditional Chinese Medicine and evaluated for their antioxidant activity against ALD by the evaluation of Glutathione (GSH) and Malondialdehyde (MDA). The result suggested that Leonurine hydrochloride (LH) was a potent antioxidant that could reduce alcoholic liver damage. To further investigate the underlying mechanism of LH against ALD, the molecular pathway induced by LH was identified by RNA-seq analyses. Transcriptome data revealed the principal mechanism for the protective effect of LH against ALD might be attributed to the differentially expressed genes (DEGs) of PI3K-AKT, AMPK, and HIF-1 signaling pathways involved in the lipid metabolism. Given the hepatoprotective mechanism of LH is involved in lipid metabolism, the lipid metabolism induced by LH was further analyzed by UHPLC-MS/MS. Metabolome analysis indicated that LH significantly regulated glycerophospholipid metabolism including phosphatidylcholine, 1-acyl-sn-glycero-3-phosphocholine, phosphatidylethanolamine and 1-acyl-sn-glycero-3-phosphoethanolamine in the liver. Overall, this study revealed that the hepatoprotective mechanism of LH against alcoholic liver damage might be associated with the genes involved in glycerophospholipid metabolism.

Metabolic discrimination of synovial fluid between rheumatoid arthritis and osteoarthritis using gas chromatography/time-of-flight mass spectrometry

INTRODUCTION

Rheumatoid arthritis (RA) and osteoarthritis (OA) are clinicopathologically different.

OBJECTIVES

We aimed to assess the feasibility of metabolomics in differentiating the metabolite profiles of synovial fluid between RA and OA using gas chromatography/time-of-flight mass spectrometry.

METHODS

We first compared the global metabolomic changes in the synovial fluid of 19 patients with RA and OA. Partial least squares-discriminant, hierarchical clustering, and univariate analyses were performed to distinguish metabolites of RA and OA. These findings were then validated using synovial fluid samples from another set of 15 patients with RA and OA.

RESULTS

We identified 121 metabolites in the synovial fluid of the first 19 samples. The score plot of PLS-DA showed a clear separation between RA and OA. Twenty-eight crucial metabolites, including hypoxanthine, xanthine, adenosine, citrulline, histidine, and tryptophan, were identified to be capable of distinguishing RA metabolism from that of OA; these were found to be associated with purine and amino acid metabolism.

CONCLUSION

Our results demonstrated that metabolite profiling of synovial fluid could clearly discriminate between RA and OA, suggesting that metabolomics may be a feasible tool to assist in the diagnosis and advance the comprehension of pathological processes for diseases.

Effects of long-term exercise and a high-fat diet on synovial fluid metabolomics and joint structural phenotypes in mice: an integrated network analysis

OBJECTIVE

To explore how systemic factors that modify knee osteoarthritis risk are connected to 'whole-joint' structural changes by evaluating the effects of high-fat diet and wheel running exercise on synovial fluid (SF) metabolomics.

METHODS

Male mice were fed a defined control or high-fat (60% kcal fat) diet from 6 to 52 weeks of age, and half the animals were housed with running wheels from 26 to 52 weeks of age (n = 9-13 per group). Joint tissue structure and osteoarthritis pathology were evaluated by histology and micro-computed tomography. Systemic metabolic and inflammatory changes were evaluated by body composition, glucose tolerance testing, and serum biomarkers. SF metabolites were analyzed by high performance-liquid chromatography mass spectrometry. We built correlation-based network models to evaluate the connectivity between systemic and local metabolic biomarkers and osteoarthritis structural pathology within each experimental group.

RESULTS

High-fat diet caused moderate osteoarthritis, including cartilage pathology, synovitis and increased subchondral bone density. In contrast, voluntary exercise had a negligible effect on these joint structure components. 1,412 SF metabolite features were detected, with high-fat sedentary mice being the most distinct. Diet and activity uniquely altered SF metabolites attributed to amino acids, lipids, and steroids. Notably, high-fat diet increased network connections to systemic biomarkers such as interleukin-1β and glucose intolerance. In contrast, exercise increased local joint-level network connections, especially among subchondral bone features and SF metabolites.

CONCLUSION

Network mapping showed that obesity strengthened SF metabolite links to blood glucose and inflammation, whereas exercise strengthened SF metabolite links to subchondral bone structure.

Mass Spectrometry-based Biomarkers for Knee Osteoarthritis: A Systematic Review

Introduction: Knee osteoarthritis (OA) is a joint disease, affecting multiple tissues in the joint. Early detection and intervention may delay OA development and avoid total knee arthroplasty. Specific biomarker profiles for early detection and guiding clinical decision-making of OA have not yet been identified. One technique that can contribute to the finding of this "OA biomarker" is mass spectrometry (MS), which offers the possibility to analyze different molecules in tissues or fluids. Several proteomic, lipidomic, metabolomic and other -omic approaches aim to identify these molecular profiles; however, variation in methods and techniques complicate the finding of promising candidate biomarkers.Areas covered: In this systematic review, we aim to provide an overview of molecules in OA knee patients. Possible biomarkers in several tissue types of OA and non-OA patients, as well as current limitations and possible future suggestions will be discussed.Expert opinion: According to this review, we do not believe one specific biomarker will function as predictive molecule for OA. Likely, a group of molecules will give insight in OA development and possible therapeutic targets. For clinical implementation of MS-analysis in clinical decision-making, standardized procedures, large cohort studies and sharing protocols and data is necessary.

Metabolic Reprogramming and Inflammatory Response Induced by D-Lactate in Bovine Fibroblast-Like Synoviocytes Depends on HIF-1 Activity

Acute ruminal acidosis (ARA) occurs after an excessive intake of rapidly fermentable carbohydrates and is characterized by the overproduction of D-lactate in the rumen that reaches the bloodstream. Lameness presentation, one of the primary consequences of ARA in cattle, is associated with the occurrence of laminitis and aseptic polysynovitis. Fibroblast-like synoviocytes (FLS) are predominant cells of synovia and play a key role in the pathophysiology of joint diseases, thus increasing the chances of the release of pro-inflammatory cytokines. Increased D-lactate levels and disturbances in the metabolism of carbohydrates, pyruvates, and amino acids are observed in the synovial fluid of heifers with ARA-related polysynovitis prior to neutrophil infiltration, suggesting an early involvement of metabolic disturbances in joint inflammation. We hypothesized that D-lactate induces metabolic reprogramming, along with an inflammatory response, in bovine exposed FLS. Gas chromatography-mass spectrometry (GC-MS)-based metabolomics revealed that D-lactate disrupts the metabolism of bovine FLS, mainly enhancing glycolysis and gluconeogenesis, pyruvate metabolism, and galactose metabolism. The reverse-transcription quantitative PCR (RT-qPCR) analysis revealed an increased expression of metabolic-related genes, including hypoxia-inducible factor 1 (HIF-1)α, glucose transporter 1 (Glut-1), L-lactate dehydrogenase subunit A (L-LDHA), and pyruvate dehydrogenase kinase 1 (PDK-1). Along with metabolic disturbances, D-lactate also induced an overexpression and the secretion of IL-6. Furthermore, the inhibition of HIF-1, PI3K/Akt, and NF-κB reduced the expression of IL-6 and metabolic-related genes. The results of this study reveal a potential role for D-lactate in bFLS metabolic reprogramming and support a close relationship between inflammation and metabolism in cattle.

The role of metabolism in chondrocyte dysfunction and the progression of osteoarthritis

Osteoarthritis (OA) is a degenerative joint disease characterized by low-grade inflammation and high levels of clinical heterogeneity. Aberrant chondrocyte metabolism is a response to changes in the inflammatory microenvironment and may play a key role in cartilage degeneration and OA progression. Under conditions of environmental stress, chondrocytes tend to adapt their metabolism to microenvironmental changes by shifting from one metabolic pathway to another, for example from oxidative phosphorylation to glycolysis. Similar changes occur in other joint cells, including synoviocytes. Switching between these pathways is implicated in metabolic alterations that involve mitochondrial dysfunction, enhanced anaerobic glycolysis, and altered lipid and amino acid metabolism. The shift between oxidative phosphorylation and glycolysis is mainly regulated by the AMP-activated protein kinase (AMPK) and mechanistic target of rapamycin (mTOR) pathways. Chondrocyte metabolic changes are likely to be a feature of different OA phenotypes. Determining the role of chondrocyte metabolism in OA has revealed key features of disease pathogenesis. Future research should place greater emphasis on immunometabolism and altered metabolic pathways as a means to understand the pathophysiology of age-related OA. This knowledge will advance the development of new drugs against therapeutic targets of metabolic significance.

Serum fatty acid chain length associates with prevalent symptomatic end-stage osteoarthritis, independent of BMI

Higher body mass index (BMI) is associated with osteoarthritis (OA) in both weight-bearing and non-weight-bearing joints, suggesting a link between OA and poor metabolic health beyond mechanical loading. This risk may be influenced by systemic factors accompanying BMI. Fluctuations in concentrations of metabolites may mark or even contribute to development of OA. This study explores the association of metabolites with radiographic knee/hip OA prevalence and progression. A ¹H-NMR-metabolomics assay was performed on plasma samples of 1564 cases for prevalent OA and 2,125 controls collected from the Rotterdam Study, CHECK, GARP/NORREF and LUMC-arthroplasty cohorts. OA prevalence and 5 to 10 year progression was assessed by means of Kellgren-Lawrence (KL) score and the OARSI-atlas. End-stage knee/hip OA (TJA) was defined as indication for arthroplasty surgery. Controls did not have OA at baseline or follow-up. Principal component analysis of 227 metabolites demonstrated 23 factors, of which 19 remained interpretable after quality-control. Associations of factor scores with OA definitions were investigated with logistic regression. Fatty acids chain length (FALen), which was included in two factors which associated with TJA, was individually associated with both overall OA as well as TJA. Increased Fatty Acid chain Length is associated with OA.

Inflammatory and Noninflammatory Synovial Fluids Exhibit New and Distinct Tribological Endotypes

Inferior synovial lubrication is a hallmark of osteoarthritis (OA), and synovial fluid (SF) lubrication and composition are variable among OA patients. Hyaluronic acid (HA) viscosupplementation is a widely used therapy for improving SF viscoelasticity and lubrication, but it is unclear how the effectiveness of HA viscosupplements varies with arthritic endotype. The objective of this study was to investigate the effects of the HA viscosupplement, Hymovis®, on the lubricating properties of diseased SF from patients with noninflammatory OA and inflammatory arthritis (IA). The composition (cytokine, HA, and lubricin concentrations) of the SF was measured as well as the mechanical properties (rheology, tribology) of the SF alone and in a 1:1 mixture with the HA viscosupplement. Using rotational rheometry, no difference in SF viscosity was detected between disease types, and the addition of HA significantly increased all fluids' viscosities. In noninflammatory OA SF, friction coefficients followed a typical Stribeck pattern, and their magnitude was decreased by the addition of HA. While some of the IA SF also showed typical Stribeck behavior, a subset showed more erratic behavior with highly variable and larger friction coefficients. Interestingly, this aberrant behavior was not eliminated by the addition of HA, and it was associated with low concentrations of lubricin. Aberrant SF exhibited significantly lower effective viscosities compared to noninflammatory OA and IA SF with typical tribological behavior. Collectively, these results suggest that different endotypes of arthritis exist with respect to lubrication, which may impact the effectiveness of HA viscosupplements in reducing friction.

Metabolomic Profiling in the Characterization of Degenerative Bone and Joint Diseases

Osteoarthritis and inflammatory arthropathies are a cause of significant morbidity globally. New research elucidating the metabolic derangements associated with a variety of bone and joint disorders implicates various local and systemic metabolites, which further elucidate the underlying molecular mechanisms associated with these destructive disease processes. In osteoarthritis, atty acid metabolism has been implicated in disease development, both locally and systemically. Several series of rheumatoid arthritis patients have demonstrated overlapping trends related to histidine and glyceric acid, while other series showed similar results of increased cholesterol and glutamic acid. Studies comparing osteoarthritis and rheumatoid arthritis reported elevated gluconic acid and glycolytic- and tricarboxylic acid-related substrates in patients with osteoarthritis, while lysosphingolipids and cardiolipins were elevated only in patients with rheumatoid arthritis. Other bone and joint disorders, including osteonecrosis, intervertebral disc degeneration, and osteoporosis, also showed significant alterations in metabolic processes. The identification of the molecular mechanisms of osteoarthritis and inflammatory arthropathies via metabolomics-based workflows may allow for the development of new therapeutic targets to improve the quality of life in these patient populations.

Can joint fluid metabolic profiling (or "metabonomics") reveal biomarkers for osteoarthritis and inflammatory joint disease?: A systematic review

Aims

Metabolic profiling is a top-down method of analysis looking at metabolites, which are the intermediate or end products of various cellular pathways. Our primary objective was to perform a systematic review of the published literature to identify metabolites in human synovial fluid (HSF), which have been categorized by metabolic profiling techniques. A secondary objective was to identify any metabolites that may represent potential biomarkers of orthopaedic disease processes.

Methods

A systematic review was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines using the MEDLINE, Embase, PubMed, and Cochrane databases. Studies included were case series, case control series, and cohort studies looking specifically at HSF.

Results

The primary analysis, which pooled the results from 17 published studies and four meeting abstracts, identified over 200 metabolites. Seven of these studies (six published studies, one meeting abstract) had asymptomatic control groups and collectively suggested 26 putative biomarkers in osteoarthritis, inflammatory arthropathies, and trauma. These can broadly be categorized into amino acids plus related metabolites, fatty acids, ketones, and sugars.

Conclusion

The role of metabolic profiling in orthopaedics is fast evolving with many metabolites already identified in a variety of pathologies. However, these results need to be interpreted with caution due to the presence of multiple confounding factors in many of the studies. Future research should include largescale epidemiological metabolic profiling studies incorporating various confounding factors with appropriate statistical analysis to account for multiple testing of the data.

Cite this article:Bone Joint Res. 2020;9(3):108–119.

Metabolomic analysis of synovial fluid from Thoroughbred racehorses diagnosed with palmar osteochondral disease using magnetic resonance imaging

BACKGROUND

Palmar osteochondral disease (POD) is a common cause of lameness in competition horses. Magnetic resonance imaging (MRI) is the most sensitive diagnostic modality currently available, however it may not be financially or logistically practical for routine screening of POD. There is increasing interest in the use of metabolomics for diagnosis prior to progression to irreversible damage.

OBJECTIVES

To determine metabolite levels in synovial fluid (SF) of horses with a clinical diagnosis of POD based on diagnostic analgesia and MRI, with the hypothesis that metabolomic profiles differ between diseased and healthy joints.

STUDY DESIGN

Prospective clinical study.

METHODS

Synovial fluid was collected from metacarpo/tarsophalangeal joints (MC/TPJ) of 29 horses (n = 51 joints), including 14 controls (n = 26) and 15 cases (n = 25), the latter with lameness localised to the MC/TPJ and MR changes consistent with POD (n = 23). Spectra were produced using ¹ H-nuclear magnetic resonance (NMR) spectroscopy and analysed.

RESULTS

Twenty-five metabolites were recognised associated with various biosynthetic and degradation pathways. The metabolite abundances within the controls demonstrated increased variability compared with the clinical group. The low level of variance between the spectra of the two groups was explained by five principal components. Cross-validation of the cohort demonstrated modest separation of predictive power (R²  = 0.67; Q²  = 0.34). Although statistical significance was not achieved, the most influential metabolites were glucose and lactate.

MAIN LIMITATIONS

The modest sample size and variation in signalment, background and presenting condition of the controls may have impacted the discriminative power of the constructed models. The lack of matched controls, differences in time of fluid collection and freezing times may have also reduced accuracy when representing metabolite profiles.

CONCLUSIONS

This study identified and quantified metabolites present in MC/TPJ SF of clinical cases with POD.

Metabolomic profiles of induced pluripotent stem cells derived from patients with rheumatoid arthritis and osteoarthritis

Background

Metabolomics is the systemic study of the unique fingerprints of metabolites involved in cellular processes and biochemical reactions. The metabolomic approach is useful in diagnosing and predicting the development of rheumatoid arthritis (RA) and osteoarthritis (OA) and is emerging as a useful tool for identifying disease biomarkers. The aim of this study was to compare the metabolic blueprint of fibroblast-like synoviocyte (FLS) cells and induced pluripotent stem cells (iPSCs) derived from RA and OA patients.

Methods

Somatic cells of RA patients (n = 3) and OA patients (n = 3) were isolated, transduced with a lentiviral plasmid, and reprogrammed into iPSCs displaying pluripotency. Metabolic profiling of RA and OA patient–derived FLS cells and iPSCs was performed using liquid chromatography/mass spectrometry and statistical analysis. After normalization by the sum of the peak intensities through LC/MS, 37 metabolites were detected across RA and OA patients.

Results

The metabolites of RA and OA were distinguishable according to the PLS-DA analysis. LysoPC (20:4), 4-methoxychalcone, phosphorylcholine, and nicotinamide (NAM) were significantly higher in RA iPSCs than in OA iPSCs (p < 0.05). The NMNAT-3 enzyme, which catalyzes an important step in the biosynthesis of NAD⁺ from adenosine triphosphate, was also upregulated in RA iPSCs. Interestingly, the proliferation of RA iPSCs was significantly greater than OA iPSC proliferation (p < 0.05). NAM played a critical role in the proliferation of RA iPSCs but not in OA iPSCs. When iPSCs were treated with 100 nM of the NAM inhibitor tannic acid (TA), the proliferation of RA iPSCs was significantly reduced (p < 0.001).

Conclusions

The metabolites of RA and OA FLS cells and RA and OA iPSCs were all clearly distinguishable from each other. NAM played a critical role in the proliferation of RA iPSCs but not in OA iPSCs. TA effectively inhibited the expression of NAM in RA iPSCs and is a possible effective treatment for RA patients.

Metabolomic approach to the exploration of biomarkers associated with disease activity in rheumatoid arthritis

We aimed to investigate metabolites associated with the 28-joint disease activity score based on erythrocyte sedimentation rate (DAS28-ESR) in patients with rheumatoid arthritis (RA) using capillary electrophoresis quadrupole time-of-flight mass spectrometry. Plasma and urine samples were collected from 32 patients with active RA (DAS28-ESR≥3.2) and 17 with inactive RA (DAS28-ESR<3.2). We found 15 metabolites in plasma and 20 metabolites in urine which showed a significant but weak positive or negative correlation with DAS28-ESR. When metabolites between active and inactive patients were compared, 9 metabolites in plasma and 15 in urine were found to be significantly different. Consequently, we selected 11 metabolites in plasma and urine as biomarker candidates which significantly correlated positively or negatively with DAS28-ESR, and significantly differed between active and inactive patients. When a multiple logistic regression model was built to discriminate active and inactive cohorts, three variables-histidine and guanidoacetic acid from plasma and hypotaurine from urine-generated a high area under the receiver operating characteristic (ROC) curve value (AUC = 0.8934). Thus, this metabolomics approach appeared to be useful for investigating biomarkers of RA. Combination of plasma and urine analysis may lead to more precise and reliable understanding of the disease condition. We also considered the pathophysiological significance of the found biomarker candidates.

Activation of The Phosphatidylcholine to Lysophosphatidylcholine Pathway Is Associated with Osteoarthritis Knee Cartilage Volume Loss Over Time

To identify serum biomarker(s) for predicting knee cartilage volume loss over time, we studied 139 knee osteoarthritis (OA) patients from a previous 24-month clinical trial cohort. Targeted metabolomic profiling was performed on serum collected at baseline. The pairwise metabolite ratios as proxies for enzymatic reaction were calculated and used in the analysis. Cartilage volume loss between baseline and 24 months was assessed quantitatively by magnetic resonance imaging (MRI). Data revealed an association between the serum ratio of lysophosphatidylcholine 18:2 (lysoPC 18:2) to phosphatidylcholine 44:3 (PC44:3) and the cartilage volume loss in the lateral compartment (β = -0.21 ± 0.04, p = 8.53*10^-7) and with joint degradation markers, COMP (r = 0.32, p = 0.0002) and MMP1 (r = 0.26, p = 0.002). The significance remained after adjustment for age, sex, BMI, diabetes, hypertension, dyslipidemia, and the treatment taken in the original study. As the ratio indicated the over activation of the conversion pathway of PC to lysoPC catalyzed by phospholipase A₂ (PLA₂), we assessed and found that a specific PLA₂, PLA₂G5, was significantly increased in human OA cartilage and synovial membrane (85% and 19% respectively, both p < 0.04) compared to controls, and its overexpression correlated with IL-6 (r = 0.63, p = 0.0008). Our data suggest that the serum lysoPC 18:2 to PC44:3 ratio is highly associated with a greater risk of cartilage volume loss of the knee and warrants further investigation in an independent cohort.

Non-targeted metabolomics reveals diagnostic biomarker in the tongue coating of patients with chronic gastritis

Analysis of the properties of the tongue has been used in traditional Chinese medicine for disease diagnosis. Notably, tongue analysis, which is non-invasive and convenient compared with gastroscopy and pathological examination, can be used to assess chronic gastritis (CG). In order to find potential diagnostic biomarkers and study the metabolic mechanisms of the endogenous small molecules in the tongue coating related to CG, a non-targeted metabolomic analysis method was developed using ultra high performance liquid chromatography combined with quadrupole time-of-flight mass spectrometry (UHPLC-Q/TOF-MS). It was performed using two different columns in positive and negative ion scanning modes separately. The stability of the samples was evaluated and the age and gender factors of the subjects were excluded to ensure the reliability of the data in this study. Finally, under the four analysis models, 130, 229, 113 and 92 differential compounds were found using multivariate statistical methods respectively. 37 potential biomarkers were putatively identified after removing the duplicate compounds and five potential diagnostic biomarkers were putatively identified by receiver operating characteristic (ROC) curve analysis, including inosine, oleamide, adenosine, N-acetylglucosamine (GlcNAc) and xanthine. The main metabolic pathways associated with CG were purine metabolism, amino acid metabolism, sphingolipid metabolism and energy metabolism, which suggested that oxygen free radicals and energy metabolism were altered in patients with CG. These results provided a potential new basis for the quantitative diagnosis and pathogenesis of CG.

Can Metabolic Pathways Be Therapeutic Targets in Rheumatoid Arthritis?

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

The Metabolome and Osteoarthritis: Possible Contributions to Symptoms and Pathology

Osteoarthritis (OA) is a progressive, deteriorative disease of articular joints. Although traditionally viewed as a local pathology, biomarker exploration has shown that systemic changes can be observed. These include changes to cytokines, microRNAs, and more recently, metabolites. The metabolome is the set of metabolites within a biological sample and includes circulating amino acids, lipids, and sugar moieties. Recent studies suggest that metabolites in the synovial fluid and blood could be used as biomarkers for OA incidence, prognosis, and response to therapy. However, based on clinical, demographic, and anthropometric factors, the local synovial joint and circulating metabolomes may be patient specific, with select subsets of metabolites contributing to OA disease. This review explores the contribution of the local and systemic metabolite changes to OA, and their potential impact on OA symptoms and disease pathogenesis.

Effects of Different Pollens on Primary Metabolism and Lignin Biosynthesis in Pear

To investigate the effect of pollination on the fruit quality of ‘Dangshan Su’ pear, ‘Dangshan Su’ was fertilized by the pollen of ‘Wonhwang’ (Pyrus pyrifolia Nakai.) (DW) and ‘Jingbaili’ (Pyrus ussuriensis Maxim.) (DJ). The analysis of primary metabolites was achieved through untargeted metabolomics, and the quantitative analysis of intermediate metabolites of lignin synthesis was undertaken using targeted metabolomics. The untargeted metabolomics analysis was performed via gas chromatography-mass spectrometry (GC-MS). The targeted metabolomics analysis was performed using ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) under the multiple reaction monitoring (MRM) mode. The results showed that the metabolite content was significantly different between DW and DJ. Compared with that in DJ, the sugar and amino acid content in DW was higher and the fatty acid content was lower at 47 days after pollination (DAPs), and the sugar, amino acid, and fatty acid content in DW was lower at 63 DAPs. The intermediate metabolites of lignin synthesis were analyzed using the orthogonal partial least squares discriminant analysis (OPLS-DA) model, and the differential metabolites at 47 DAPs were p-coumaric acid, ferulic acid, sinapaldehyde, coniferyl alcohol, and sinapyl alcohol. The differential significant metabolite at 63 DAPs was p-coumaric acid. At 47 DAPs and 63 DAPs, the p-coumaric acid level was significantly different, and the p-coumaric acid content was positively correlated with lignin synthesis. The pollination pollen affects the quality of ‘Dangshan Su’ pear fruit through regulation of the sugar, amino acid, and fatty acid content; at the same time, regulating the levels of intermediate metabolites of lignin synthesis, especially the p-coumaric acid content, to affect lignin synthesis ultimately affects the stone cell content and improves the quality of the pears.

What did we learn from 'omics' studies in osteoarthritis

PURPOSE OF REVIEW

'Omics' technologies developed for the massive analysis of the major biologically relevant molecules (genes, proteins, metabolites) have been applied to the study of osteoarthritis (OA) for more than a decade.

RECENT FINDINGS

'Omics' studies have undoubtedly contributed to increase the knowledge on pathogenic processes related with OA and have provided hundreds to thousands of molecules that might have a putative biomarker utility for this disease.

SUMMARY

This review describes the most recent 'omics' studies in OA research, their conclusions, and discuss those remaining challenges. Still many validation studies must be performed in large and well-characterized cohorts for the translation of the findings from 'omics' strategies to clinical applications. The development of tools for the intelligent integration of 'omics' data with clinical and imaging information is also mandatory to take full profit of the work that has been already performed.

Preanalytical Processing and Biobanking Procedures of Biological Samples for Metabolomics Research: A White Paper, Community Perspective (for "Precision Medicine and Pharmacometabolomics Task Group"-The Metabolomics Society Initiative)

BACKGROUND

The metabolome of any given biological system contains a diverse range of low molecular weight molecules (metabolites), whose abundances can be affected by the timing and method of sample collection, storage, and handling. Thus, it is necessary to consider the requirements for preanalytical processes and biobanking in metabolomics research. Poor practice can create bias and have deleterious effects on the robustness and reproducibility of acquired data.

CONTENT

This review presents both current practice and latest evidence on preanalytical processes and biobanking of samples intended for metabolomics measurement of common biofluids and tissues. It highlights areas requiring more validation and research and provides some evidence-based guidelines on best practices.

SUMMARY

Although many researchers and biobanking personnel are familiar with the necessity of standardizing sample collection procedures at the axiomatic level (e.g., fasting status, time of day, "time to freezer," sample volume), other less obvious factors can also negatively affect the validity of a study, such as vial size, material and batch, centrifuge speeds, storage temperature, time and conditions, and even environmental changes in the collection room. Any biobank or research study should establish and follow a well-defined and validated protocol for the collection of samples for metabolomics research. This protocol should be fully documented in any resulting study and should involve all stakeholders in its design. The use of samples that have been collected using standardized and validated protocols is a prerequisite to enable robust biological interpretation unhindered by unnecessary preanalytical factors that may complicate data analysis and interpretation.

Application of global metabolomic profiling of synovial fluid for osteoarthritis biomarkers

Osteoarthritis affects over 250 million individuals worldwide. Currently, there are no options for early diagnosis of osteoarthritis, demonstrating the need for biomarker discovery. To find biomarkers of osteoarthritis in human synovial fluid, we used high performance liquid-chromatography mass spectrometry for global metabolomic profiling. Metabolites were extracted from human osteoarthritic (n = 5), rheumatoid arthritic (n = 3), and healthy (n = 5) synovial fluid, and a total of 1233 metabolites were detected. Principal components analysis clearly distinguished the metabolomic profiles of diseased from healthy synovial fluid. Synovial fluid from rheumatoid arthritis patients contained expected metabolites consistent with the inflammatory nature of the disease. Similarly, unsupervised clustering analysis found that each disease state was associated with distinct metabolomic profiles and clusters of co-regulated metabolites. For osteoarthritis, co-regulated metabolites that were upregulated compared to healthy synovial fluid mapped to known disease processes including chondroitin sulfate degradation, arginine and proline metabolism, and nitric oxide metabolism. We utilized receiver operating characteristic analysis to determine the diagnostic value of each metabolite and identified 35 metabolites as potential biomarkers of osteoarthritis, with an area under the receiver operating characteristic curve >0.9. These metabolites included phosphatidylcholine, lysophosphatidylcholine, ceramides, myristate derivatives, and carnitine derivatives. This pilot study provides strong justification for a larger cohort-based study of human osteoarthritic synovial fluid using global metabolomics. The significance of these data is the demonstration that metabolomic profiling of synovial fluid can identify relevant biomarkers of joint disease.