Metabolic analysis of knee synovial fluid as a potential diagnostic approach for osteoarthritis

β-Hydroxybutyrate enhances chondrocyte mitophagy and reduces cartilage degeneration in osteoarthritis via the HCAR2/AMPK/PINK1/Parkin pathway

Osteoarthritis (OA) is widely recognized as the prevailing joint disease associated with aging. The ketogenic diet (KD) has been postulated to impede the advancement of various inflammatory ailments. β-Hydroxybutyrate (βOHB), a prominent constituent of ketone bodies, has recently been proposed to possess crucial signaling capabilities. In this study, we propose to explore the role and mechanism of βOHB in OA. Tissue staining and inflammatory factor assay were employed to evaluate the impacts of KD and βOHB on OA rats. The oxidative stress conditions in chondrocytes were induced using tert-butyl hydroperoxide (TBHP). The mechanisms were determined using the siRNA of hydroxycarboxylic acid receptor 2 (HCAR2), the antagonist of adenosine monophosphate-activated protein kinase (AMPK), and the inhibitor of mitophagy. The administration of KD demonstrated a reduction in pathological damage to cartilage, as well as a decrease in plasma levels of inflammatory factors. Furthermore, it resulted in an increase in the concentration of βOHB in the blood and synovial fluid. In vitro experiments showed that βOHB facilitated mitophagy and adenosine triphosphate production. Besides, βOHB mitigated chondrocyte senescence, inflammatory factors secretion, extracellular matrix degradation, and apoptosis induced by TBHP. Subsequent investigations indicated that the protective effects of βOHB were no longer observed following the knockdown of HCAR2, the antagonist of AMPK, or the inhibitor of mitophagy. Moreover, in vivo studies suggested that βOHB played a protective role by targeting the HCAR2-AMPK-PINK1 axis. In conclusion, βOHB enhanced chondrocyte mitophagy through the HCAR2/AMPK/PINK1/Parkin pathway, offering a potential therapeutic approach for the treatment of OA.

Metabolomics in Osteoarthritis Knee: A Systematic Review of Literature

Introduction

Osteoarthritis (OA) is a common degenerative disorder of the synovial joints and is usually an age-related disease that occurs due to continuous wear and tear of the cartilage in the joints. Presently, there is no proven medical management to halt the progression of the disease in the early stages. The purpose of our systematic review is to analyze the possible metabolites and metabolic pathways that are specifically involved in OA pathogenesis and early treatment of the disease.

Materials and Methods

The articles were collected from PubMed, Cochrane, Google Scholar, Embase, and Scopus databases. "Knee", "Osteoarthritis", "Proteomics", "Lipidomics", "Metabolomics", "Metabolic Methods", and metabolic* were employed for finding the articles. Only original articles with human or animal OA models with healthy controls were included.

Results

From the initial screening, a total of 458 articles were identified from the 5 research databases. From these, 297 articles were selected in the end for screening, of which 53 papers were selected for full-text screening. Finally, 50 articles were taken for the review based on body fluid: 6 urine studies, 15 plasma studies, 16 synovial fluid studies, 11 serum studies, 4 joint tissue studies, and 1 fecal study. Many metabolites were found to be elevated in OA. Some of these metabolites can be used to stage the OA Three pathways that were found to be commonly involved are the TCA cycle, the glycolytic pathway, and the lipid metabolism.

Conclusion

All these studies showed a vast array of metabolites and metabolic pathways associated with OA. Metabolites like lysophospholipids, phospholipids, arginine, BCCA, and histidine were identified as potential biomarkers of OA but a definite association was not identified, Three pathways (glycolytic pathway, TCA cycle, and lipid metabolic pathways) have been found as highly significant in OA pathogenesis. These metabolic pathways could provide novel therapeutic targets for the prevention and progression of the disease.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43465-024-01169-5.

Data-driven identification of predictive risk biomarkers for subgroups of osteoarthritis using interpretable machine learning

Osteoarthritis (OA) is increasing in prevalence and has a severe impact on patients' lives. However, our understanding of biomarkers driving OA risk remains limited. We developed a model predicting the five-year risk of OA diagnosis, integrating retrospective clinical, lifestyle and biomarker data from the UK Biobank (19,120 patients with OA, ROC-AUC: 0.72, 95%CI (0.71-0.73)). Higher age, BMI and prescription of non-steroidal anti-inflammatory drugs contributed most to increased OA risk prediction ahead of diagnosis. We identified 14 subgroups of OA risk profiles. These subgroups were validated in an independent set of patients evaluating the 11-year OA risk, with 88% of patients being uniquely assigned to one of the 14 subgroups. Individual OA risk profiles were characterised by personalised biomarkers. Omics integration demonstrated the predictive importance of key OA genes and pathways (e.g., GDF5 and TGF-β signalling) and OA-specific biomarkers (e.g., CRTAC1 and COL9A1). In summary, this work identifies opportunities for personalised OA prevention and insights into its underlying pathogenesis.

Inflammation and Organic Cation Transporters Novel (OCTNs)

Inflammation is a physiological condition characterized by a complex interplay between different cells handled by metabolites and specific inflammatory-related molecules. In some pathological situations, inflammation persists underlying and worsening the pathological state. Over the years, two membrane transporters namely OCTN1 (SLC22A4) and OCTN2 (SLC22A5) have been shown to play specific roles in inflammation. These transporters form the OCTN subfamily within the larger SLC22 family. The link between these proteins and inflammation has been proposed based on their link to some chronic inflammatory diseases such as asthma, Crohn's disease (CD), and rheumatoid arthritis (RA). Moreover, the two transporters show the ability to mediate the transport of several compounds including carnitine, carnitine derivatives, acetylcholine, ergothioneine, and gut microbiota by-products, which have been specifically associated with inflammation for their anti- or proinflammatory action. Therefore, the absorption and distribution of these molecules rely on the presence of OCTN1 and OCTN2, whose expression is modulated by inflammatory cytokines and transcription factors typically activated by inflammation. In the present review, we wish to provide a state of the art on OCTN1 and OCTN2 transport function and regulation in relationships with inflammation and inflammatory diseases focusing on the metabolic signature collected in different body districts and gene polymorphisms related to inflammatory diseases.

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.

Comparative study of 1H-NMR metabolomic profile of canine synovial fluid in patients affected by four progressive stages of spontaneous osteoarthritis

The study aimed to assess the metabolomic profile of the synovial fluid (SF) of dogs affected by spontaneous osteoarthritis (OA) and compare any differences based on disease progression. Sixty client-owned dogs affected by spontaneous OA underwent clinical, radiographic, and cytologic evaluations to confirm the diagnosis. The affected joints were divided into four study groups based on the Kallgreen-Lawrence classification: OA1 (mild), OA2 (moderate), OA3 (severe), and OA4 (extremely severe/deforming). The osteoarthritic joint's SF was subjected to cytologic examination and 1H-NMR analysis. The metabolomic profiles of the study groups' SF samples were statistically compared using one-way ANOVA. Sixty osteoarthritic joints (45 stifles, 10 shoulders and 5 elbows) were included in the study. Fourteen, 28, and 18 joints were included in the OA1, OA2, and OA3 groups, respectively (0 joints in the OA4 group). Metabolomic analysis identified 48 metabolites, five of which were significantly different between study groups: Mannose and betaine were elevated in the OA1 group compared with the OA2 group, and the 2-hydroxyisobutyrate concentration decreased with OA progression; in contrast, isoleucine was less concentrated in mild vs. moderate OA, and lactate increased in severe OA. This study identified different 1H-NMR metabolomic profiles of canine SF in patients with progressive degrees of spontaneous OA, suggesting 1H-NMR metabolomic analysis as a potential alternative method for monitoring OA progression. In addition, the results suggest the therapeutic potentials of the metabolomic pathways that involve mannose, betaine, 2-hydroxyisobutyrate, isoleucine, and lactate.

Exploring biomarkers associated with severity of knee osteoarthritis in Southern China using widely targeted metabolomics

BACKGROUND

Metabolomics is a tool to study the pathogenesis of diseases and their associated metabolites, but there are still insufficient metabolomic studies on severe knee osteoarthritis.To investigate the differences in serum metabolites between healthy populations and knee osteoarthritis (KOA) patients in Southern China using widely targeted metabolomics, and to explore biomarkers and their metabolic pathways that could be associated with the severity of KOA.

METHODS

There were 10 healthy individuals in the control group and 32 patients with KOA. According to the Kellgren-Lawrence (KL) grading system, KOA was further divided into mild (n = 13, KL grade 1 and 2) and severe (n = 19, KL grade 3 and 4). Serum samples from all participants were collected and analyzed metabolomics based on ultra-performance liquid chromatography/electrospray ionization/tandem mass spectrometry. We screened for differential metabolites between patients and controls, and between mild and severe KOA. We explored the metabolic pathways involved in differential metabolism using the Kyoto Encyclopedia of Genes and Genomes database.

RESULTS

Sixty-one metabolites were differentially expressed in the sera of the patient group compared with the control group (45 upregulated and 16 downregulated). Analysis of the mild and severe KOA groups showed a total of 12 differential metabolites. Receiver operating characteristic curve analysis showed N-alpha-acetyl-L-asparagine was a good predictor of advanced osteoarthritis(OA).Differential metabolites are enriched in multiple pathways such as arachidonic acid metabolism.

CONCLUSION

Widely targeted metabolomics found that upregulation of the amino acid metabolite N-α-acetyl-L-asparagine was significantly associated with severe KOA and could be a biomarker for predicting severity of KOA. Arachidonic acid metabolism may play an important role in patients with severe KOA.

Osteoarthritic chondrocytes undergo a glycolysis-related metabolic switch upon exposure to IL-1b or TNF

BACKGROUND

Osteoarthritis is an age-related disease that currently faces a lack of symptomatic treatment. Inflammation, which is mainly sustained by pro-inflammatory cytokines such as IL-1b, TNF, and IL-6, plays an important role in osteoarthritis progression. In this context, pro-inflammatory cytokines are widely used to mimic the inflammatory component of osteoarthritis in vitro. However, the therapeutic failures of clinical trials evaluating anti-cytokines drugs highlight the lack of overall understanding of the effects of these cytokines on chondrocytes.

METHODS

Here, we generated a comprehensive transcriptomic and proteomic dataset of osteoarthritic chondrocytes treated with these cytokines to describe their pro-inflammatory signature and compare it to the transcriptome of non-osteoarthritic chondrocytes. Then, the dysregulations highlighted at the molecular level were functionally confirmed by real-time cellular metabolic assays.

RESULTS

We identified dysregulation of metabolic-related genes in osteoarthritic chondrocytes but not in non-osteoarthritic chondrocytes. A metabolic shift, toward increased glycolysis at the expense of mitochondrial respiration, was specifically confirmed in osteoarthritic chondrocytes treated with IL-1b or TNF.

CONCLUSION

These data show a strong and specific association between inflammation and metabolism in osteoarthritic chondrocytes, which was not found in non-osteoarthritic chondrocytes. This indicates that the link between inflammation and metabolic dysregulation may be exacerbated during chondrocyte damage in osteoarthritis. Video Abstract.

Utilizing metabolomics to identify potential biomarkers and perturbed metabolic pathways in osteoarthritis: A systematic review

PURPOSE

Osteoarthritis (OA) is a joint disease that is clinically diagnosed using components of history, physical exam, and characteristic radiographic findings, such as joint space narrowing. Currently, there are no laboratory findings that are specific to a diagnosis of OA. The purpose of this systematic review is to evaluate the state of current studies of metabolomic biomarkers that can aid in the diagnosis and treatment of OA.

METHODS

Articles were gathered from PubMed and Web of Science using the search terms "osteoarthritis" and "biomarkers" and "metabolomics". Last search of databases took place December 3rd, 2022. Duplicates were manually screened, along with any other results that were not original journal articles. Only original reports involving populations with diagnosed primary or secondary OA (human participants) or surgically induced OA (animal participants) and a healthy control group for comparison were considered for inclusion. Metabolites and metabolic pathways reported in included articles were then manually extracted and evaluated for importance based on reported a priori p-values and/or area under the receiver-operator curve (AUC).

RESULTS

Of the 161 results that were returned in the database searches, 43 unique articles met the inclusion criteria. Articles were categorized based on body fluid analyzed: 6 studies on urine samples, 13 studies on plasma samples, 11 studies on synovial fluid (SF) samples, 11 studies on serum samples, 1 study on both synovial fluid and serum, and 1 study that involved both plasma and synovial fluid. To synthesize results, individual metabolites, as well as metabolic pathways that involve frequently reported metabolites, are presented for each study. Indications as to whether metabolite levels were increased or decreased are also included if this data was included in the original articles.

CONCLUSIONS

These studies clearly show that there are a wide range of metabolic pathways perturbed in OA. For this period, there was no consensus on a single metabolite, or panel of metabolites, that would be clinically useful in early diagnosis of OA or distinguishing OA from a healthy control. However, many common metabolic pathways were identified in the studies, including TCA cycle, fatty acid metabolism, amino acid metabolism (notably BCAA metabolism and tryptophan metabolism via kynurenine pathway), nucleotide metabolism, urea cycle, cartilage matrix components, and phospholipid metabolism. Future research is needed to define effective clinical biomarkers of osteoarthritis from metabolomic and other data.

β-Hydroxybutyrate alleviates cartilage senescence through hnRNP A1-mediated up-regulation of PTEN

Senescence chondrocytes play an important role in Osteoarthritis (OA) progression. However, alleviating OA progression through senescent chondrocyte intervention still faces great challenges. β-Hydroxybutyrate (BHB) exhibits anti-senescence effects in a variety of age-related dis-eases, but its role in osteoarthritis remains poorly understood. To explore the molecular mechanisms, gene sequencing was used to identify critical genes and potential cellular signaling pathways and male SD rats were used to generate an osteoarthritis model. Results showed that BHB attenuated the senescence of Osteoarthritis chondrocytes (OA-Chos) and alleviated OA progression. Gene ontology (GO) enrichment analysis revealed significant changes in cell cycle genes, with PTEN being the most significant differentially expressed gene. BHB up-regulated the expression of PTEN in OA-Chos, thereby alleviating chondrocyte senescence. Furthermore, BHB facilitated the expression of PTEN by binding to hnRNP A1 and inhibiting the phosphorylation of Akt. This study provided evidence that BHB mitigated chondrocyte senescence and delayed OA, and could thus be used as a novel therapeutic approach for osteoarthritis treatment.

Salivary metabolome indicates a shift in tyrosine metabolism in patients with burning mouth syndrome: a prospective case-control study

ABSTRACT

The pathophysiology of primary burning mouth syndrome (BMS) remains controversial. Targeted analyses or "omics" approach of saliva provide diagnostic or pathophysiological biomarkers. This pilot study's primary objective was to explore the pathophysiology of BMS through a comparative analysis of the salivary metabolome among 26 BMS female cases and 25 age- and sex-matched control subjects. Secondary objectives included comparative analyses of inflammatory cytokines, neuroinflammatory markers, and steroid hormones among cases and control subjects, and among BMS patients according to their clinical characteristics. Salivary metabolome, neuroinflammatory markers, cytokines, and steroids were, respectively, analysed by liquid chromatography coupled with mass spectrometry, ELISA and protease activity assay, and multiparametric Luminex method. Among the 166 detected metabolites, univariate analysis did not find any discriminant metabolite between groups. Supervised multivariate analysis divided patients into 2 groups with an accuracy of 60% but did not allow significant discrimination (permutation test, P = 0.35). Among the metabolites contributing to the model, 3 belonging to the tyrosine pathway ( l -dopa, l -tyrosine, and tyramine) were involved in the discrimination between cases and control subjects, and among BMS patients according to their levels of pain. Among the detectable molecules, levels of cytokines, steroid hormones, and neuroinflammatory markers did not differ between cases and control subjects and were not associated with characteristics of BMS patients. These results do not support the involvement of steroid hormones, inflammatory cytokines, or inflammatory neurogenic mediators in the pathophysiology of pain in BMS, whereas the observed shift in tyrosine metabolism may indicate an adaptative response to chronic pain or an impaired dopaminergic transmission.

Analysis of gut microbiome composition, function, and phenotype in patients with osteoarthritis

Gut microbiome (GMB) disturbance can induce chronic low-grade inflammation, which is closely related to the occurrence and development of osteoarthritis (OA). However, the relationship between GMB and OA remains unclear. In this study, we collected stool samples from OA patients and healthy people, and performed Alpha diversity, Beta diversity, MetaStat, and LEfSe analysis by 16S rRNA sequencing to find out the species with significant difference between the two groups. Random forest analysis was performed to find out biomarkers that could distinguish between OA patients and healthy people. PICRUSt and Bugbase analysis were used to compare the difference in functions and phenotypes. Multivariate linear regression analysis (MaAsLin) was used to adjust for gender, age, and body mass index (BMI). The results showed that there was a significant difference in the overall composition of GMB between the two groups (p = 0.005). After adjusting for gender, age, and BMI, we found that p_Bacteroidota (Q = 0.039), c_Bacteroidia (Q = 0.039), and o_Bacteroidales (Q = 0.040) were enriched in the OA group, while s_Prevotella_copri (Q = 0.001) was enriched in the healthy control group. Prevotella could distinguish between OA patients and healthy people with a better diagnostic power (AUC = 77.5%, p < 0.001, 95% CI: 66.9-88.1%). The functions of DNA transcription, amino acid metabolism (including histidine, lysine, and isoleucine), ATP metabolism, and phospholipid metabolism significantly decreased, while glucose metabolism, protein acetylation, and aspartate kinase activity significantly increased in the OA group. In terms of phenotypes, we found that the relative abundance of aerobic (p = 0.003) and Gram-negative (p < 0.001) was higher in the OA group, while contains mobile elements (p = 0.001) and Gram-positive (p < 0.001) were higher in the healthy control group. Our study preliminarily demonstrated that there were differences in the composition, function, and phenotype of GMB in stool samples between OA patients and healthy people, which provided a novel perspective on further study in OA.

1H-NMR metabolomic profile of healthy and osteoarthritic canine synovial fluid before and after UC-II supplementation

The aim of the study was to compare the metabolomic synovial fluid (SF) profile of dogs affected by spontaneous osteoarthritis (OA) and supplemented with undenatured type II collagen (UC-II), with that of healthy control dogs. Client-owned dogs were enrolled in the study and randomized in two different groups, based on the presence/absence of OA (OA group and OA-free group). All dogs were clinically evaluated and underwent SF sampling for ¹H-Nuclear Magnetic Resonance spectroscopy (¹H-NMR) analysis at time of presentation. All dogs included in OA group were supplemented with UC-II orally administered for 30 days. After this period, they were reassessed (OA-T30). The differences in the ¹H-NMR metabolic SFs profiles between groups (OA-free, OA-T0 and OA-T30) were studied. The multivariate statistical analysis performed on SFs under different conditions (OA-T0 vs OA-T30 SFs; OA-T0 vs OA-free SFs and OA-T30 vs OA-free SFs) gave models with excellent goodness of fit and predictive parameters, revealed by a marked separation between groups. β-Hydroxybutyrate was identified as a characteristic compound of osteoarthritic joints, showing the important role of fat metabolism during OA. The absence of β-hydroxybutyrate after UC-II supplementation suggests the supplement's effectiveness in rebalancing the metabolism inside the joint. The unexpectedly high level of lactate in the OA-free group suggests that lactate could not be considered a good marker for OA. These results prove that ¹H-NMR-based metabolomic analysis is a valid tool to study and monitor OA and that UC-II improves clinical symptoms and the SF metabolic profile in OA dogs.

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.

Inflammatory cytokines and mechanical injury induce post-traumatic osteoarthritis-like changes in a human cartilage-bone-synovium microphysiological system

BACKGROUND

Traumatic knee injuries in humans trigger an immediate increase in synovial fluid levels of inflammatory cytokines that accompany impact damage to joint tissues. We developed a human in vitro cartilage-bone-synovium (CBS) coculture model to study the role of mechanical injury and inflammation in the initiation of post-traumatic osteoarthritis (PTOA)-like disease.

METHODS

Osteochondral plugs (cartilage-bone, CB) along with joint capsule synovium explants (S) were harvested from 25 cadaveric distal femurs from 16 human donors (Collin's grade 0-2, 23-83years). Two-week monocultures (cartilage (C), bone (B), synovium (S)) and cocultures (CB, CBS) were established. A PTOA-like disease group was initiated via coculture of synovium explants with mechanically impacted osteochondral plugs (CBS+INJ, peak stress 5MPa) with non-impacted CB as controls. Disease-like progression was assessed through analyses of changes in cell viability, inflammatory cytokines released to media (10-plex ELISA), tissue matrix degradation, and metabolomics profile.

RESULTS

Immediate increases in concentrations of a panel of inflammatory cytokines occurred in CBS+INJ and CBS cocultures and cultures with S alone (IL-1, IL-6, IL-8, and TNF-α among others). CBS+INJ and CBS also showed increased chondrocyte death compared to uninjured CB. The release of sulfated glycosaminoglycans (sGAG) and associated ARGS-aggrecan neoepitope fragments to the medium was significantly increased in CBS and CBS+INJ groups. Distinct metabolomics profiles were observed for C, B, and S monocultures, and metabolites related to inflammatory response in CBS versus CB (e.g., kynurenine, 1-methylnicotinamide, and hypoxanthine) were identified.

CONCLUSION

CBS and CBS+INJ models showed distinct cellular, inflammatory, and matrix-related alterations relevant to PTOA-like initiation/progression. The use of human knee tissues from donors that had no prior history of OA disease suggests the relevance of this model in highlighting the role of injury and inflammation in earliest stages of PTOA progression.

Metabolic Profiling of Serum for Osteoarthritis Biomarkers

Osteoarthritis is a prevalent aging disease in the world, and in recent years it has shown a trend toward younger age, which is becoming a major health problem in the world and seriously endangers the health of the elderly. However, the etiology and pathogenesis of osteoarthritis are still unclear, causing great trouble for treatment. To screen out candidate biomarkers that could be used for the identification of osteoarthritis and explore the pathogenesis of osteoarthritis, we performed an untargeted metabolomics analysis of nine New Zealand rabbit serum samples by LC-MS/MS, including three normal serum samples (control group) and six osteoarthritis serum samples (case group). Finally, 44 differential metabolites were identified, and the ROC analysis results indicated that a total of 36 differential metabolites could be used as candidate biomarkers. Further metabolic pathway enrichment analysis was performed on these differential metabolites, and we found that a total of 17 metabolic pathways were affected, which may provide directions for the study of osteoarthritis mechanisms.

Lysophosphatidylcholine: Potential Target for the Treatment of Chronic Pain

The bioactive lipid lysophosphatidylcholine (LPC), a major phospholipid component of oxidized low-density lipoprotein (Ox-LDL), originates from the cleavage of phosphatidylcholine by phospholipase A2 (PLA2) and is catabolized to other substances by different enzymatic pathways. LPC exerts pleiotropic effects mediated by its receptors, G protein-coupled signaling receptors, Toll-like receptors, and ion channels to activate several second messengers. Lysophosphatidylcholine (LPC) is increasingly considered a key marker/factor positively in pathological states, especially inflammation and atherosclerosis development. Current studies have indicated that the injury of nervous tissues promotes oxidative stress and lipid peroxidation, as well as excessive accumulation of LPC, enhancing the membrane hyperexcitability to induce chronic pain, which may be recognized as one of the hallmarks of chronic pain. However, findings from lipidomic studies of LPC have been lacking in the context of chronic pain. In this review, we focus in some detail on LPC sources, biochemical pathways, and the signal-transduction system. Moreover, we outline the detection methods of LPC for accurate analysis of each individual LPC species and reveal the pathophysiological implication of LPC in chronic pain, which makes it an interesting target for biomarkers and the development of medicine regarding chronic pain.

Fundamentals of OA. An initiative of Osteoarthritis and Cartilage. Obesity and metabolic factors in OA

OBJECTIVE

Obesity was once considered a risk factor for knee osteoarthritis (OA) primarily for biomechanical reasons. Here we provide an additional perspective by discussing how obesity also increases OA risk by altering metabolism and inflammation.

DESIGN

This narrative review is presented in four sections: 1) metabolic syndrome and OA, 2) metabolic biomarkers of OA, 3) evidence for dysregulated chondrocyte metabolism in OA, and 4) metabolic inflammation: joint tissue mediators and mechanisms.

RESULTS

Metabolic syndrome and its components are strongly associated with OA. However, evidence for a causal relationship is context dependent, varying by joint, gender, diagnostic criteria, and demographics, with additional environmental and genetic interactions yet to be fully defined. Importantly, some aspects of the etiology of obesity-induced OA appear to be distinct between men and women, especially regarding the role of adipose tissue. Metabolomic analyses of serum and synovial fluid have identified potential diagnostic biomarkers of knee OA and prognostic biomarkers of disease progression. Connecting these biomarkers to cellular pathophysiology will require future in vivo studies of joint tissue metabolism. Such studies will help reveal when a metabolic process or a metabolite itself is a causal factor in disease progression. Current evidence points towards impaired chondrocyte metabolic homeostasis and metabolic-immune dysregulation as likely factors connecting obesity to the increased risk of OA.

CONCLUSIONS

A deeper understanding of how obesity alters metabolic and inflammatory pathways in synovial joint tissues is expected to provide new therapeutic targets and an improved definition of "metabolic" and "obesity" OA phenotypes.

Tai Chi Improves Brain Functional Connectivity and Plasma Lysophosphatidylcholines in Postmenopausal Women With Knee Osteoarthritis: An Exploratory Pilot Study

Objective: A pre/post pilot study was designed to investigate neurobiological mechanisms and plasma metabolites in an 8-week Tai-Chi (TC) group intervention in subjects with knee osteoarthritis.

Methods: Twelve postmenopausal women underwent Tai-Chi group exercise for 8 weeks (60 min/session, three times/week). Outcomes were measured before and after Tai Chi intervention including pain intensity (VAS), Brief Pain Inventory (BPI), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), plasma metabolites (amino acids and lipids), as well as resting-state functional magnetic resonance imaging (rs-fMRI, 10 min, eyes open), diffusion tensor imaging (DTI, 12 min), and structural MRI (4.5 min) in a subgroup. Clinical data was analyzed using paired t-tests; plasma metabolites were analyzed using Wilcoxon signed-rank tests; and rs-fMRI data were analyzed using seed-based correlations of the left and right amygdala in a two-level mixed-effects model (FSL software). Correlations between amygdala-medial prefrontal cortex (mPFC) connectivity and corresponding changes in clinical outcomes were examined. DTI connectivity of each amygdala was modeled using a Bayesian approach and probabilistic tractography. The associations between neurobiological effects and pain/physical function were examined.

Results: Significant pre/post changes were observed with reduced knee pain (VAS with most pain: p = 0.018; WOMAC-pain: p = 0.021; BPI with worst level: p = 0.018) and stiffness (WOMAC-stiffness, p = 0.020), that likely contributed to improved physical function (WOMAC-physical function: p = 0.018) with TC. Moderate to large effect sizes pre/post increase in rs-fMRI connectivity were observed between bilateral mPFC and the amygdala seed regions (i.e., left: d = 0.988, p = 0.355; right: d = 0.600, p = 0.282). Increased DTI connectivity was observed between bilateral mPFC and left amygdala (d = 0.720, p = 0.156). There were moderate-high correlations (r = 0.28–0.60) between TC-associated pre-post changes in amygdala-mPFC functional connectivity and pain/physical function improvement. Significantly higher levels of lysophosphatidylcholines were observed after TC but lower levels of some essential amino acids. Amino acid levels (alanine, lysine, and methionine) were lower after 8 weeks of TC and many of the lipid metabolites were higher after TC. Further, plasma non-HDL cholesterol levels were lower after TC.

Conclusion: This pilot study showed moderate to large effect sizes, suggesting an important role that cortico-amygdala interactions related to TC have on pain and physical function in subjects with knee osteoarthritis pain. Metabolite analyses revealed a metabolic shift of higher lyso-lipids and lower amino acids that might suggest greater fatty acid catabolism, protein turnover and changes in lipid redistribution in response to TC exercise. The results also support therapeutic strategies aimed at strengthening functional and structural connectivity between the mPFC and the amygdala. Controlled clinical trials are warranted to confirm these observed preliminary effects.

Fecal metabolomics reveals products of dysregulated proteolysis and altered microbial metabolism in obesity-related osteoarthritis

OBJECTIVE

The objective of this exploratory study was to determine if perturbations in gut microbial composition and the gut metabolome could be linked to individuals with obesity and osteoarthritis (OA).

METHODS

Fecal samples were collected from obese individuals diagnosed with radiographic hand plus knee OA (n = 59), defined as involvement of at least 3 joints across both hands, and a Kellgren-Lawrence (KL) grade 2-4 (or total knee replacement) in at least one knee. Controls (n = 33) were without hand OA and with KL grade 0-1 knees. Fecal metabolomes were analyzed by a UHPLC/Q Exactive HFx mass spectrometer. Microbiome composition was determined in fecal samples by 16 S ribosomal RNA amplicon sequencing (rRNA-seq). Stepwise logistic regression models were built to determine microbiome and/or metabolic characteristics of OA.

RESULTS

Untargeted metabolomics analysis indicated that OA cases had significantly higher levels of di- and tripeptides and significant perturbations in microbial metabolites including propionic acid, indoles, and other tryptophan metabolites. Pathway analysis revealed several significantly perturbed pathways associated with OA including leukotriene metabolism, amino acid metabolism and fatty acid utilization. Logistic regression models selected metabolites associated with the gut microbiota and leaky gut syndrome as significant predictors of OA status, particularly when combined with the rRNA-seq data.

CONCLUSIONS

Adults with obesity and knee plus hand OA have distinct fecal metabolomes characterized by increased products of proteolysis, perturbations in leukotriene metabolism, and changes in microbial metabolites compared with controls. These metabolic perturbations indicate a possible role of dysregulated proteolysis in OA.

Synovial Fluid Biomarkers in Knee Osteoarthritis: A Systematic Review and Quantitative Evaluation Using BIPEDs Criteria

OBJECTIVE

The aim of this systematic review was to analyze the evidence about the efficacy of the several synovial fluid (SF) biomarkers proposed for knee osteoarthritis (OA), categorizing them by both molecular characteristics and clinical use according to the BIPEDs criteria, to provide a comprehensive and structured overview of the current literature.

DESIGN

A systematic review was performed in May 2020 on PubMed, Cochrane Library, and Embase databases about SF biomarkers in patients with knee OA. The search was limited to articles in the last 20 years on human studies, involving patients with knee OA, reporting SF biomarkers. The evidence for each selected SF biomarker was quantified according to the 6 categories of BIPEDs classification.

RESULTS

A total of 159 articles were included in the qualitative data synthesis and 201 different SF biomarkers were identified. Among these, several were investigated multiple times in different articles, for a total of 373 analyses. The studies included 13,557 patients with knee OA. The most promising SF biomarkers were C4S, IL-6, IL-8, Leptin, MMP-1/3, TIMP-1, TNF-α, and VEGF. The "burden of disease" and "diagnostic" categories were the most represented with 132 and 106 different biomarkers, respectively.

CONCLUSIONS

The systematic review identified numerous SF biomarkers. However, despite the high number of studies on the plethora of identified molecules, the evidence about the efficacy of each biomarker is supported by limited and often conflicting findings. Further research efforts are needed to improve the understanding of SF biomarkers for a better management of patients with knee OA.

High-Density Lipoprotein Cholesterol and Apolipoprotein A1 in Synovial Fluid: Potential Predictors of Disease Severity of Primary Knee Osteoarthritis

OBJECTIVES

The aim of this study was to detect levels of common lipid species in serum and synovial fluid (SF) of primary knee osteoarthritis (OA) patients and investigate their correlations with disease severity.

MATERIALS AND METHODS

The study enrolled 184 OA patients receiving arthroscopic debridement or total knee arthroplasty and 180 healthy controls between April 2012 and March 2018. Total triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), apolipoprotein A1 (ApoA1), and apolipoprotein B (ApoB) levels were analyzed in serum and SF of OA patients, and in serum of healthy individuals. The Noyes rating criteria, Kellgren-Lawrence (KL) grading system, and Western Ontario McMaster University Osteoarthritis Index (WOMAC) scores were, respectively, used to assess cartilage damage, radiographic severity, and symptomatic severity of OA.

RESULTS

No significant differences were found in serum TG and ApoB levels between the 2 groups, while OA patients had higher TC and LDL-C levels and lower HDL-C and ApoA1 levels (P < 0.05). Pearson correlation analysis revealed SF HDL-C and ApoA1 levels were negatively correlated with cartilage damage scores, KL grades as well as WOMAC scores (P < 0.05), which were still significant after adjusting for confounding factors (P < 0.05). Receiver operating characteristic curve analysis revealed SF HDL-C (area under the curve [AUC]: 0.816) and ApoA1 (AUC: 0.793) were also good predictors of advanced-stage OA (P < 0.001).

CONCLUSION

SF HDL-C and ApoA1 levels were negatively correlated with cartilage damage, radiographic severity, and symptomatic severity of primary knee OA, emerging as potential biomarkers for radiographic advanced-stage OA, which may serve as predictors of disease severity.

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.

Soluble biological markers in osteoarthritis

In recent years, markers research has focused on the structural components of cartilage matrix. Specifically, a second generation of degradation markers has been developed against type II collagen neoepitopes generated by specific enzymes. A particular effort has been made to measure the degradation of minor collagens III and X of the cartilage matrix. However, because clinical data, including longitudinal controlled studies, are very scarce, it remains unclear whether they will be useful as an alternative to or in combination with current more established collagen biological markers to assess patients with osteoarthritis (OA). In addition, new approaches using high-throughput technologies allowed to detect new types of markers and improve the knowledge about the metabolic changes linked to OA. The relative advances coming from phenotype research are a first attempt to classify the heterogeneity of OA, and several markers could improve the phenotype characterization. These phenotypes could improve the selection of patients in clinical trials limiting the size of the studies by selecting patients with OA characteristics corresponding to the metabolic pathway targeted by the molecules evaluated. In addition, the inclusion of rapid progressors only in clinical trials would facilitate the demonstration of efficacy of the investigative drug to reduce joint degradation. The combination of selective biochemical markers appears as a promising and cost-effective approach to fulfill this unmet clinical need. Among the various potential roles of biomarkers in OA, their ability to monitor drug efficacy is probably one of the most important, in association with clinical and imaging parameters. Biochemical markers have the unique property to detect changes in joint tissue metabolism within a few weeks.

Metabolomics and Inflammatory Mediator Profiling for the Differentiation of Life-Threatening and Non-Severe Appendicitis in the Pediatric Population

While children with appendicitis often have excellent clinical outcomes, some develop life-threatening complications including sepsis and organ dysfunction requiring pediatric intensive care unit (PICU) support. Our study applied a metabolomics and inflammatory protein mediator (IPM) profiling approach to determine the bio-profiles of children who developed severe appendicitis compared with those that did not. We performed a prospective case-control study of children aged 0-17 years with a diagnosis of appendicitis. Cases had severe disease resulting in PICU admission. Primary controls had moderate appendicitis (perforation without PICU); secondary controls had mild appendicitis (non-perforated). Serum samples were analyzed using Proton Nuclear Magnetic Resonance (¹H NMR) Spectroscopy and Gas Chromatography-Mass Spectrometry (GC-MS); IPM analysis was performed using plasma bead-based multiplex profiling. Comparisons were made using multivariate data statistical analysis. Fifty-three children were included (15 severe, 38 non-severe). Separation between severe and moderate appendicitis demonstrated excellent sensitivity and specificity (100%, 88%; 14 compounds), separation between severe and mild appendicitis also showed excellent sensitivity and specificity (91%, 90%; 16 compounds). Biomarker patterns derived from metabolomics and IPM profiling are capable of distinguishing children with severe appendicitis from those with less severe disease. These findings provide an important first step towards developing non-invasive diagnostic tools for clinicians in early identification of children who are at a high risk of developing severe appendicitis.

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.

A review of applications of metabolomics in osteoarthritis

Osteoarthritis (OA) represents the most prevalent and disabling arthritis worldwide due to its heterogeneous and progressive articular degradation. However, effective and timely diagnosis and fundamental treatment for this disorder are lacking. Metabolomics, a growing field in life science research in recent years, has the potential to detect many metabolites and thus explains the underlying pathophysiological processes. Hence, new specific metabolic markers and related metabolic pathways can be identified for OA. In this review, we aimed to provide an overview of studies related to the metabolomics of OA in animal models and humans to describe the metabolic changes and related pathways for OA. The present metabolomics studies reveal that the pathogenesis of OA may be significantly related to perturbations of amino acid metabolism. These altered amino acids (e.g., branched-chain amino acids, arginine, and alanine), as well as phospholipids, were identified as potential biomarkers to distinguish patients with OA from healthy individuals.

Vibrational Spectroscopy in Assessment of Early Osteoarthritis-A Narrative Review

Osteoarthritis (OA) is a degenerative disease, and there is currently no effective medicine to cure it. Early prevention and treatment can effectively reduce the pain of OA patients and save costs. Therefore, it is necessary to diagnose OA at an early stage. There are various diagnostic methods for OA, but the methods applied to early diagnosis are limited. Ordinary optical diagnosis is confined to the surface, while laboratory tests, such as rheumatoid factor inspection and physical arthritis checks, are too trivial or time-consuming. Evidently, there is an urgent need to develop a rapid nondestructive detection method for the early diagnosis of OA. Vibrational spectroscopy is a rapid and nondestructive technique that has attracted much attention. In this review, near-infrared (NIR), infrared, (IR) and Raman spectroscopy were introduced to show their potential in early OA diagnosis. The basic principles were discussed first, and then the research progress to date was discussed, as well as its limitations and the direction of development. Finally, all methods were compared, and vibrational spectroscopy was demonstrated that it could be used as a promising tool for early OA diagnosis. This review provides theoretical support for the application and development of vibrational spectroscopy technology in OA diagnosis, providing a new strategy for the nondestructive and rapid diagnosis of arthritis and promoting the development and clinical application of a component-based molecular spectrum detection technology.

Nuclear magnetic resonance spectroscopy of biofluids for osteoarthritis

BACKGROUND

Osteoarthritis is a common degenerative musculoskeletal disease of synovial joints. It is characterized by a metabolic imbalance resulting in articular cartilage degradation, reduced elastoviscosity of synovial fluid and an altered chondrocyte phenotype. This is often associated with reduced mobility, pain and poor quality of life. Subsequently, with an ageing world population, osteoarthritis is of increasing concern to public health. Nuclear magnetic resonance (NMR) spectroscopy can be applied to characterize the metabolomes of biofluids, determining changes associated with osteoarthritis pathology, identifying potential biomarkers of disease and alterations to metabolic pathways.

SOURCES OF DATA

A comprehensive search of PubMed and Web of Science databases using combinations of the following keywords: 'NMR Spectroscopy', 'Blood', 'Plasma', 'Serum', 'Urine', 'Synovial Fluid' and 'Osteoarthritis' for articles published from 2000 to 2020.

AREAS OF AGREEMENT

The number of urine metabolomics studies using NMR spectroscopy to investigate osteoarthritis is low, whereas the use of synovial fluid is significantly higher. Several differential metabolites have previously been identified and mapped to metabolic pathways involved in osteoarthritis pathophysiology.

AREAS OF CONTROVERSY

Conclusions are sometimes conservative or overinflated, which may reflect the variation in reporting standards. NMR metabolic experimental design may require further consideration, as do the animal models used for such studies.

GROWING POINTS

There are various aspects which require improvement within the field. These include stricter adherence to the Metabolomics Standards Initiative, inclusive of the standardization of metabolite identifications; increased utilization of integrating NMR metabolomics with other 'omic' disciplines; and increased deposition of raw experimental files into open access online repositories, allowing greater transparency and enabling additional future analyses.

AREAS TIMELY FOR DEVELOPING RESEARCH

Overall, this research area could be improved by the inclusion of more heterogeneous cohorts, reflecting varying osteoarthritis phenotypes, and larger group sizes ensuring studies are not underpowered. To correlate local and systemic environments, the use of blood for diagnostic purposes, over the collection of synovial fluid, requires increased attention. This will ultimately enable biomarkers of disease to be determined that may provide an earlier diagnosis, or provide potential therapeutic targets for osteoarthritis, ultimately improving patient prognosis.

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.

Reporter gene comparison demonstrates interference of complex body fluids with secreted luciferase activity

Reporter gene assays are widely used to study cellular signaling and transcriptional activity. Few studies describe the use of reporter genes for studying cellular responses on complex body fluids, such as urine and blood. Selection of the optimal reporter gene is crucial for study outcome. Here, we compared the characteristics of five reporter genes (Firefly luciferase, stable- and unstable Nano luciferase, secretable Gaussia luciferase and Red Fluorescent Protein) to study complex body fluids. For this comparison, the NFκB Response Element (NFκB-RE) and Smad Binding Element (SBE) were identically cloned into the five different reporter vectors. Reporter characteristics were evaluated by kinetic and concentration-response measurements in SW1353 and HeLa cell lines. Finally, reporter compatibility with complex body fluids (fetal calf serum, knee joint synovial fluid and human serum) and inter-donor variation were evaluated. Red Fluorescent Protein demonstrated poor inducibility as a reporter gene and slow kinetics compared to luciferases. Intracellularly measured luciferases, such as Firefly luciferase and Nano luciferase, revealed good compatibility with complex body fluids. Secreted Gaussia luciferase appeared to be incompatible with complex body fluids, due to variability in inter-donor signal interference. Unstable Nano luciferase demonstrated clear inducibility, high sensitivity and compatibility with complex body fluids and therefore can be recommended for cellular signaling studies using complex body fluids.

Metabolic Signature of Articular Cartilage Following Mechanical Injury: An Integrated Transcriptomics and Metabolomics Analysis

Mechanical injury to the articular cartilage is a key risk factor in joint damage and predisposition to osteoarthritis. Integrative multi-omics approaches provide a valuable tool to understand tissue behavior in response to mechanical injury insult and help to identify key pathways linking injury to tissue damage. Global or untargeted metabolomics provides a comprehensive characterization of the metabolite content of biological samples. In this study, we aimed to identify the metabolic signature of cartilage tissue post injury. We employed an integrative analysis of transcriptomics and global metabolomics of murine epiphyseal hip cartilage before and after injury. Transcriptomics analysis showed a significant enrichment of gene sets involved in regulation of metabolic processes including carbon metabolism, biosynthesis of amino acids, and steroid biosynthesis. Integrative analysis of enriched genes with putatively identified metabolite features post injury showed a significant enrichment for carbohydrate metabolism (glycolysis, galactose, and glycosylate metabolism and pentose phosphate pathway) and amino acid metabolism (arginine biosynthesis and tyrosine, glycine, serine, threonine, and arginine and proline metabolism). We then performed a cross analysis of global metabolomics profiles of murine and porcine ex vivo cartilage injury models. The top commonly modulated metabolic pathways post injury included arginine and proline metabolism, arginine biosynthesis, glycolysis/gluconeogenesis, and vitamin B6 metabolic pathways. These results highlight the significant modulation of metabolic responses following mechanical injury to articular cartilage. Further investigation of these pathways would provide new insights into the role of the early metabolic state of articular cartilage post injury in promoting tissue damage and its link to disease progression of osteoarthritis.

Metabolomics in chronic pain research

BACKGROUND AND OBJECTIVE

Metabolomics deals with the identification and quantification of small molecules (metabolites) in biological samples. As metabolite levels can reflect normal or altered metabolic pathways, their measurement provides information to improve the understanding, diagnosis and management of diseases. Despite its immense potential, metabolomics applications to pain research have been sparse. This paper describes current metabolomics techniques, reviews published human metabolomics pain research and compares successful metabolomics research in other areas of medicine with the goal of highlighting opportunities offered by metabolomics to advance pain medicine.

DATABASES AND DATA TREATMENT

Non-systematic review.

RESULTS

Our search identified 19 studies that adopted a metabolomics approach in: fibromyalgia (7), chronic widespread pain (4), other musculoskeletal pain conditions (5), neuropathic pain (1), complex regional pain syndrome (1) and pelvic pain (1). The studies used either mass spectrometry or nuclear magnetic resonance. Most are characterized by small sample sizes. Some consistency has been found for alterations in glutamate and testosterone metabolism, and metabolic imbalances caused by the gut microbiome.

CONCLUSIONS

Metabolomics research in chronic pain is in its infancy. Most studies are at the pilot stage. Metabolomics research has been successful in other areas of medicine. These achievements should motivate investigators to expand metabolomics research to improve the understanding of the basic mechanisms of human pain, as well as provide tools to diagnose, predict and monitor chronic pain conditions. Metabolomics research can lead to the identification of biomarkers to support the development and testing of treatments, thereby facilitating personalized pain medicine.

Ex Vivo Equine Cartilage Explant Osteoarthritis Model: A Metabolomics and Proteomics Study

Osteoarthritis is an age-related degenerative musculoskeletal disease characterized by loss of articular cartilage, synovitis, and subchondral bone sclerosis. Osteoarthritis pathogenesis is yet to be fully elucidated with no osteoarthritis-specific biomarkers in clinical use. Ex vivo equine cartilage explants (n = 5) were incubated in tumor necrosis factor-α (TNF-α)/interleukin-1β (IL-1β)-supplemented culture media for 8 days, with the media removed and replaced at 2, 5, and 8 days. Acetonitrile metabolite extractions of 8 day cartilage explants and media samples at all time points underwent one-dimensional (1D) ¹H nuclear magnetic resonance metabolomic analysis, with media samples also undergoing mass spectrometry proteomic analysis. Within the cartilage, glucose and lysine were elevated following TNF-α/IL-1β treatment, while adenosine, alanine, betaine, creatine, myo-inositol, and uridine decreased. Within the culture media, 4, 4, and 6 differentially abundant metabolites and 154, 138, and 72 differentially abundant proteins were identified at 1–2, 3–5, and 6–8 days, respectively, including reduced alanine and increased isoleucine, enolase 1, vimentin, and lamin A/C following treatment. Nine potential novel osteoarthritis neopeptides were elevated in the treated media. Implicated pathways were dominated by those involved in cellular movement. Our innovative study has provided insightful information on early osteoarthritis pathogenesis, enabling potential translation for clinical markers and possible new therapeutic targets.

The Metabolomics of Chronic Pain Conditions: A Systematic Review

BACKGROUND

Chronic pain is a significant public health problem in the United States, affecting approximately 100 million people. Yet there is a lack of robust biomarkers for clinical use in chronic pain conditions. Downstream effects of environmental, genomic, and proteomic variations in individuals with chronic pain conditions can be identified and quantified using a metabolomic approach.

AIM/DESIGN

The purpose of this systematic review was to examine the literature for reports of potential metabolomic signatures associated with chronic pain conditions.

METHODS

We searched relevant electronic databases for published studies that used various metabolomic approaches to investigate chronic pain conditions among subjects of all ages.

RESULTS

Our search identified a total of 586 articles, 18 of which are included in this review. The reviewed studies used metabolomics to investigate fibromyalgia (n = 5), osteoarthritis (n = 4), migraine (n = 3), musculoskeletal pain (n = 2), and other chronic pain conditions (n = 1/condition). Results show that several known and newly identified metabolites differ in individuals with chronic pain conditions compared to those without these conditions. These include amino acids (e.g., glutamine, serine, and phenylalanine) and intermediate products (e.g., succinate, citrate, acetylcarnitine, and N-acetylornithine) of pathways that metabolize various macromolecules.

CONCLUSION

Though more high-quality research is needed, this review provides insights into potential biomarkers for future metabolomics studies in people with chronic pain conditions.

Optimization of Synovial Fluid Collection and Processing for NMR Metabolomics and LC-MS/MS Proteomics

Synovial fluid (SF) is of great interest for the investigation of orthopedic pathologies, as it is in close proximity to various tissues that are primarily altered during these disease processes and can be collected using minimally invasive protocols. Multi-"omic" approaches are commonplace, although little consideration is often given for multiple analysis techniques at sample collection. Nuclear magnetic resonance (NMR) metabolomics and liquid chromatography tandem mass spectrometry (LC-MS/MS) proteomics are two complementary techniques particularly suited to the study of SF. However, currently there are no agreed upon standard protocols that are published for SF collection and processing for use with NMR metabolomic analysis. Furthermore, the large protein concentration dynamic range present within SF can mask the detection of lower abundance proteins in proteomics. While combinational ligand libraries (ProteoMiner columns) have been developed to reduce this dynamic range, their reproducibility when used in conjunction with SF, or on-bead protein digestion protocols, has yet to be investigated. Here we employ optimized protocols for the collection, processing, and storage of SF for NMR metabolite analysis and LC-MS/MS proteome analysis, including a Lys-C endopeptidase digestion step prior to tryptic digestion, which increased the number of protein identifications and improved reproducibility for on-bead ProteoMiner digestion.

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.

GC-MS method for metabolic profiling of mouse femoral head articular cartilage reveals distinct effects of tissue culture and development

OBJECTIVE

The metabolic profile of cartilage is important to define as it relates to both normal and pathophysiological conditions. Our aim was to develop a precise, high-throughput method for gas/chromatography-mass/spectrometry (GC-MS) semi-targeted metabolic profiling of mouse cartilage.

METHOD

Femoral head (hip) cartilage was isolated from 5- and 15-week-old male C57BL/6J mice immediately after death for in vivo analyses. In vitro conditions were evaluated in 5-week-old samples cultured ±10% fetal bovine serum (FBS). We optimized cartilage processing for GC-MS analysis and evaluated group-specific differences by multivariate and parametric statistical analyses.

RESULTS

55 metabolites were identified in pooled cartilage (4 animals per sample), with 29 metabolites shared between in vivo and in vitro conditions. Multivariate analysis of these common metabolites demonstrated that culturing explants was the strongest factor altering cartilage metabolism, followed by age and serum starvation. In vitro culture altered the relative abundance of specific metabolites; whereas, cartilage development between five and 15-weeks of age reduced the levels of 36 out of 43 metabolites >2-fold, especially in TCA cycle and alanine, aspartate, and glutamate pathways. In vitro serum starvation depleted six out of 41 metabolites.

CONCLUSION

This study describes the first GC-MS method for mouse cartilage metabolite identification and quantification. We observed fundamental differences in femoral head cartilage metabolic profiles between in vivo and in vitro conditions, suggesting opportunities to optimize in vitro conditions for studying cartilage metabolism. In addition, the reductions in TCA cycle and amino acid metabolites during cartilage maturation illustrate the plasticity of chondrocyte metabolism during development.

Metabolomics of osteoarthritis: emerging novel markers and their potential clinical utility

OA is a multifactorial and progressive disease with no cure yet. Substantial efforts have been made and several biochemical and genetic markers have been reported, but neither alone nor in combination is adequate to identify early OA changes or determine disease progression with sufficient predictive values. Recent advances in metabolomics and its application to the study of OA have led to elucidation of involvement of several metabolic pathways and new specific metabolic markers for OA. Some of these metabolic pathways affect amino acid metabolism, including branched chain amino acids and arginine, and phospholipid metabolism involving conversion of phosphatidylcholine to lysophosphatidylcholine. These metabolic markers appear to be clinically actionable and may potentially improve the clinical management of OA patients. In this article, we review the recent studies of metabolomics of OA, discuss those novel metabolic markers and their potential clinical utility, and indicate future research directions in the field.

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.

Application of Metabolomics to Osteoarthritis: from Basic Science to the Clinical Approach

PURPOSE OF THE REVIEW

Osteoarthritis (OA) is a multifactorial and progressive disease affecting whole synovial joint. The extract pathogenic mechanisms and diagnostic biomarkers of OA remain unclear. In this article, we review the studies related to metabolomics of OA, discuss the biomarkers as a tool for early OA diagnosis. Furthermore, we examine the major studies on the application of metabolomics methodology in the complex context of OA and create a bridge from findings in basic science to their clinical utility.

RECENT FINDINGS

Recently, the tissue metabolomics signature permits a view into transitional phases between the healthy and OA joint. Both nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry-based metabolomics approaches have been used to interrogate the metabolic alterations that may indicate the complex progression of OA. Specifically, studies on alterations pertaining to lipids, glucose, and amino acid metabolism have aided in the understanding of the complex pathogenesis of OA. The discovery of identified metabolites could be important for diagnosis and staging of OA, as well as for the assessment of efficacy of new drugs.

Osteoarthritic Synovial Fluid Modulates Cell Phenotype and Metabolic Behavior In Vitro

Synovial fluid holds a population of mesenchymal stem cells (MSC) that could be used for clinical treatment. Our goal was to characterize the inflammatory and metabolomic profile of the synovial fluid from osteoarthritic patients and to identify its modulatory effect on synovial fluid cells. Synovial fluid was collected from non-OA and OA patients, which was centrifuged to isolate cells. Cells were cultured for 21 days, characterized with specific markers for MSC, and exposed to a specific cocktail to induce chondrogenic, osteogenic, and adipogenic differentiation. Then, we performed a MTT assay exposing SF cells from non-OA and OA patients to a medium containing non-OA and OA synovial fluid. Synovial fluid from non-OA and OA patients was submitted to ELISA to evaluate BMP-2, BMP-4, IL-6, IL-10, TNF-α, and TGF-β1 concentrations and to a metabolomic evaluation using ¹H-NMR. Synovial fluid cells presented spindle-shaped morphology in vitro. Samples from OA patients formed a higher number of colonies than the ones from non-OA patients. After 21 days, the colony-forming cells from OA patients differentiated into the three mesenchymal cell lineages, under the appropriated induction protocols. Synovial fluid cells increased its metabolic activity after being exposed to the OA synovial fluid. ELISA assay showed that OA synovial fluid samples presented higher concentration of IL-10 and TGF-β1 than the non-OA, while the NMR showed that OA synovial fluid presents higher concentrations of glucose and glycerol. In conclusion, SFC activity is modulated by OA synovial fluid, which presents higher concentration of IL-10, TGF-β, glycerol, and glucose.

Metabolite assignment of ultrafiltered synovial fluid extracted from knee joints of reactive arthritis patients using high resolution NMR spectroscopy

Currently, there are no reliable biomarkers available that can aid early differential diagnosis of reactive arthritis (ReA) from other inflammatory joint diseases. Metabolic profiling of synovial fluid (SF)-obtained from joints affected in ReA-holds great promise in this regard and will further aid monitoring treatment and improving our understanding about disease mechanism. As a first step in this direction, we report here the metabolite specific assignment of ¹ H and ¹³ C resonances detected in the NMR spectra of SF samples extracted from human patients with established ReA. The metabolite characterization has been carried out on both normal and ultrafiltered (deproteinized) SF samples of eight ReA patients (n = 8) using high-resolution (800 MHz) ¹ H and ¹ H─¹³ C NMR spectroscopy methods such as one-dimensional ¹ H CPMG and two-dimensional J-resolved¹ H NMR and homonuclear ¹ H─¹ H TOCSY and heteronuclear¹ H─¹³ C HSQC correlation spectra. Compared with normal SF samples, several distinctive ¹ H NMR signals were identified and assigned to metabolites in the ¹ H NMR spectra of ultrafiltered SF samples. Overall, we assigned 53 metabolites in normal filtered SF and 64 metabolites in filtered pooled SF sample compared with nonfiltered SF samples for which only 48 metabolites (including lipid/membrane metabolites as well) have been identified. The established NMR characterization of SF metabolites will serve to guide future metabolomics studies aiming to identify/evaluate the SF-based metabolic biomarkers of diagnostic/prognostic potential or seeking biochemical insights into disease mechanisms in a clinical perspective.

Metabolite Profiling of Clinical Cancer Biofluid Samples by NMR Spectroscopy

Metabolomics is a comprehensive characterization of the small polar molecules (metabolites) in different biological systems. One of the analytical platforms commonly used to study metabolic alterations in biofluid samples is proton nuclear magnetic resonance (¹H NMR) spectroscopy. NMR spectroscopy is very specific, quantitative, and highly reproducible. Moreover, sample preparation for NMR experiments is very simple and straightforward, and this gives NMR spectroscopy a distinct advantage over other metabolic profiling methods. It has already been shown that ¹H NMR-based profiling of biological fluids can be effective in differentiating benign from malignant lesions and in investigating the efficacy of specific cancer treatments. Therefore, ¹H NMR spectroscopy may become a promising tool for early noninvasive diagnosis and rapid assessment of treatment effects in cancer patients. Here, we describe a detailed protocol for ¹H NMR metabolite profiling in serum, plasma, and urine samples, including sample collection procedures, sample preparation for ¹H NMR experiments, spectral acquisition and processing, and quantitative profiling of ¹H NMR spectra. We also discuss several aspects of appropriate study design and some multivariate statistical methods that are commonly used to analyze metabolomics datasets.

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.

1H NMR Metabolomics Identifies Underlying Inflammatory Pathology in Osteoarthritis and Rheumatoid Arthritis Synovial Joints

Despite osteoarthritis (OA) and rheumatoid arthritis (RA) being typically age-related, their underlying etiologies are markedly different. We used ¹H nuclear magnetic resonance (NMR) spectroscopy to identify differences in metabolite profiles in low volumes of OA and RA synovial fluid (SF). SF was aspirated from knee joints of 10 OA and 14 RA patients. 100 μL SF was analyzed using a 700 MHz Avance IIIHD Bruker NMR spectrometer with a TCI cryoprobe. Spectra were analyzed by Chenomx, Bruker TopSpin and AMIX software. Statistical analysis was undertaken using Metaboanalyst. 50 metabolites were annotated, including amino acids, saccharides, nucleotides and soluble lipids. Discriminant analysis identified group separation between OA and RA cohorts, with 32 metabolites significantly different between OA and RA SF (false discovery rate (FDR) < 0.05). Metabolites of glycolysis and the tricarboxylic acid cycle were lower in RA compared to OA; these results concur with higher levels of inflammation, synovial proliferation and hypoxia found in RA compared to OA. Elevated taurine in OA may indicate increased subchondral bone sclerosis. We demonstrate that quantifiable differences in metabolite abundance can be measured in low volumes of SF by ¹H NMR spectroscopy, which may be clinically useful to aid diagnosis and improve understanding of disease pathogenesis.