1H NMR spectroscopy of serum reveals unique metabolic fingerprints associated with subtypes of surgically induced osteoarthritis in sheep

Integrated proteomic and metabolomic analysis reveals the potential therapeutic mechanism of Quanduzhong capsule in rats with spontaneous hypertension and knee osteoarthritis

ETHNOPHARMACOLOGICAL RELEVANCE

Quanduzhong capsule (QDZ), derived from Eucommia ulmoides Oliv., has been traditionally used in Chinese medicine for its beneficial effects on musculoskeletal health. Its clinical application has extended to conditions such as spontaneous hypertension combined with knee osteoarthritis (SKOA). However, the specific mechanisms by which QDZ alleviates symptoms and improves outcomes in this complex condition remain to be fully elucidated.

AIM OF THE STUDY

This study aims to evaluate the therapeutic potential of QDZ in treating SKOA. By performing serum proteomics and metabolomics, we seek to explore the related biological pathways and elucidate the mechanisms underlying QDZ's effects on SKOA.

MATERIALS AND METHODS

Serum samples from control, spontaneous hypertension (SHR), SKOA, and SKOA treated with QDZ groups were analyzed using data-independent acquisition-based proteomics to identify differentially expressed proteins. Serum levels of angiotensin II, norepinephrine, endothelin-1, classical pro-inflammatory factors such as macrophage colony-stimulating factor, tumor necrosis factor-alpha, and interleukin-1 beta were measured. Additionally, serum metabolomics was performed to examine the changes in metabolite profiles. Correlation analysis was conducted to link changed proteins and metabolites with key pathways affected by QDZ.

RESULTS

Proteomics analysis revealed significant alterations in serum protein expression between control, SHR, and SKOA groups, with changes in pathways related to immune regulation and vascular function. KEGG enrichment analysis highlighted pathways such as endocytosis, synaptic vesicle cycling, and immune responses were enriched in SKOA group compared with control group. QDZ treatment significantly modulated above pathways and reduced inflammatory and cardiovascular markers which were upregulated in SKOA group. Metabolomics analysis showed that QDZ reversed SKOA-induced changes in amino acid and organic acid metabolism, affecting pathways including valine, leucine, and isoleucine metabolism, as well as the TCA cycle. Correlation analysis revealed significant relationships between key proteins and metabolites, underscoring the integrated role of immune and metabolic pathways in QDZ's effects.

CONCLUSIONS

Our results indicate QDZ has a significant therapeutic potential for SKOA by modulating both protein and metabolite profiles associated with inflammation, vascular dysfunction, and metabolic imbalance. Our findings provide insights into the mechanisms through which QDZ exerts its effects and support its use as a promising treatment for SKOA. This study highlights the impact of QDZ on proteomic and metabolomic alterations, offering a basis for its broader application in treating SKOA.

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.

Causal association of genetically determined plasma metabolites with osteoarthritis: a two-sample Mendelian randomization study

Background

We aimed to elucidate the causal relationship between plasma metabolites and the vulnerability to Osteoarthritis (OA), encompassing both hip OA and knee OA.

Methods

We conducted a two-way two-sample Mendelian randomization (MR) analysis to investigate the association of 1,400 plasma metabolites with OA. The Inverse Variance Weighted (IVW) model served as the primary two-sample MR Analysis method, with supplementary analysis using the Weighted Median (WM) and MR Egger methods. To ensure the robustness of our findings, sensitivity analyses were performed, incorporating Cochran's Q test, MR-Egger intercept test, MR-PRESSO, and Leave-One-Out analyses. To validate the identified metabolites, we utilized the Steiger test and linkage disequilibrium score regression.

Results

A total of 94 plasma metabolites were associated with osteoarthritis, with 60 associated with hip OA and 106 associated with knee OA. IVW analysis revealed that tryptophan levels showed the strongest positive association with hip OA (OR [95% CI]: 1.119 [1.024, 1.223]), while X-24757 levels exhibited the highest positive association with knee osteoarthritis (OR [95% CI]: 1.095 [1.032, 1.162]). Ethylparaben sulfate levels were found to have the greatest positive association with hip OA (OR [95% CI]: 1.118 [1.015, 1.231]). Notably, the plasma metabolite X-2475 showed a strong robust random effect across all three types of osteoarthritis. Metabolic pathway analysis revealed that the pathogenesis of osteoarthritis in the hip was mediated by acetylarginine, specifically in four important metabolic pathways: ethanol degradation (p = 0.044), amino sugar metabolism (p = 0.090), fatty acid biosynthesis (p = 0.095), and aspartate metabolism (p = 0.097816).

Conclusion

There is a significant association between tryptophan levels and the risk of hip OA, as well as X-24757 levels and the risk of knee osteoarthritis. Additionally, X-24757 levels are also linked to the risk of hip OA. Moreover, this study has identified four crucial metabolic pathways in hip osteoarthritis, which are all regulated by acetylarginine. These findings provide valuable insights into potential biomarkers for OA and highlight potential pathways for its prevention and clinical intervention.

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.

Nuclear magnetic resonance-based metabolomic study of rat serum after anterior cruciate ligament injury

Anterior cruciate ligament (ACL) injury, a common sports injury, is associated with a high risk of subsequent osteoarthritis (OA), which can cause serious pain and disability. Understanding the detailed mechanism underlying the predisposition of knee with ACL injury to secondary OA at an early stage is key to preventing future degradation and progression to a clinically significant disease. A total of 56 male Sprague Dawley rats (age, 8 weeks; weight, 180-220 g) were randomly divided into three experimental groups: control, ACL transection (ACLT; where surgical procedure was performed with ACLT), and sham (where surgical procedure was performed without ACLT). The ACLT and sham groups were further divided into three subgroups based on when the rats were sacrificed: 4, 8, and 12 weeks after the surgical procedure. The control group and the aforementioned subgroups contained 8 rats each. We used nuclear magnetic resonance (NMR)-based metabolomic analysis to analyze rat serum samples for the metabolic characteristics and the underlying mechanisms. In total, 28 metabolites were identified in the NMR spectra of the rat sera. At 4 and 8 weeks postoperatively, the sham group demonstrated metabolic profiles different from those of the ACLT group. However, this difference was not observed 12 weeks postoperatively. In total, five metabolites (acetate, succinate, sn-glycero-3-phosphocholine, glucose, and phenylalanine) and five metabolic pathways (phenylalanine, tyrosine, and tryptophan biosynthesis; phenylalanine metabolism; pyruvate metabolism; starch and sucrose metabolism; and histidine metabolism) demonstrated significant differences between the ACLT and sham groups. ACL injury was noted to considerably affect biochemical homeostasis and metabolism; however, these metabolic changes persisted briefly. Moreover, glucose was a characteristic metabolite, and several energy-related metabolic pathways were significantly disturbed. Therefore, an ACL injury may lead to considerable impairments in energy metabolism. Abnormal glucose levels facilitate chondrocyte function impairment and thereby lead to OA progression. Furthermore, lactate may aid in identifying metabolic changes specific to knee trauma not related to an ACL injury. Overall, the metabolic changes in rat serum after an ACL injury were closely related to disturbances in energy metabolism and amino acid metabolism. The current results may aid in understanding the pathogenesis of posttraumatic osteoarthritis.

Causality of genetically determined metabolites and metabolic pathways on osteoarthritis: a two-sample mendelian randomization study

BACKGROUND

Osteoarthritis (OA) is one of the most prevalent musculoskeletal diseases and is the leading cause of pain and disability in the aged population. However, the underlying biological mechanism has not been fully understood. This study aims to reveal the causal effect of circulation metabolites on OA susceptibility.

METHODS

A two-sample Mendelian Randomization (MR) analysis was performed to estimate the causality of GDMs on OA. A genome-wide association study (GWAS) of 486 metabolites was used as the exposure, whereas 8 different OA phenotypes, including any-site OA (All OA), knee and/or hip OA (knee/hip OA), knee OA, hip OA, spine OA, finger and/or thumb OA (hand OA), finger OA, thumb OA, were set the outcomes. Inverse-variance weighted (IVW) was used for calculating causal estimates. Methods including weight mode, weight median, MR-egger, and MR-PRESSO were used for the sensitive analysis. Furthermore, metabolic pathway analysis was performed via the web-based Metaconflict 4.0. All statistical analyses were performed in R software.

RESULTS

In this MR analysis, a total of 235 causative associations between metabolites and different OA phenotypes were observed. After false discovery rate (FDR) correction and sensitive analysis, 9 robust causative associations between 7 metabolites (e.g., arginine, kynurenine, and isovalerylcarnitine) and 5 OA phenotypes were finally identified. Additionally, eleven significant metabolic pathways in 4 OA phenotypes were identified by metabolic pathway analysis.

CONCLUSION

The finding of our study suggested that identified metabolites and metabolic pathways can be considered useful circulating metabolic biomarkers for OA screening and prevention in clinical practice, and can also serve as candidate molecules for future mechanism exploration and drug target selection.

Causal associations between serum amino acid levels and osteoarthritis: A Mendelian randomization study

OBJECTIVE

The association between serum amino acid (AA) levels and osteoarthritis (OA) risk remains unclear.

METHOD

We performed a two-sample Mendelian randomization (MR) analysis to analyze the causal effects of. serum AA levels on the OA risk by using summary-level genome-wide association study (GWAS) data. Inverse variance weighted (IVW) and Wald ratio were used as the main analysis.We also applied MR-Egger, Weighted median and Robust Adjusted Profile Score (MR.RAPS) methods. Heterogeneity and horizontally pleiotropic outliers were checked. The causal effects of AAs on early-onset all OA were explored. We also performed multivariable MR (MVMR) and conducted the bidirectional MR.

RESULTS

The results suggested that genetically predicted alanine (Ala), tyrosine (Tyr) and isoleucine (Ile) levels were significantly associated with OA risk (e.g., association between Ala and hip/knee OA risk: OR = 0.82, 95% CI = 0.75 ∼ 0.90, p = 1.54E-05). The study yielded little evidence of associations between genetically predicted AA levels with early-onset all OA risk. When adjusting the BMI in the MVMR model, suggestive causal effects of Ala and Tyr were also identified, while the effects of Ile substantially attenuated with OA risk. No significant associations between OA and AA levels were observed after testing for bidirectionality.

CONCLUSIONS

Some AAs, such as Ala, Tyr and Ile likely affects the OA risk especially at hip or knee joints. The findings highlight the important role that serum AAs might play in the development of OA and provided new treatment approaches to OA.

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.

Effects of mechanical stimulation on metabolomic profiles of SW1353 chondrocytes: shear and compression

Mechanotransduction is a biological phenomenon where mechanical stimuli are converted to biochemical responses. A model system for studying mechanotransduction are the chondrocytes of articular cartilage. Breakdown of this tissue results in decreased mobility, increased pain, and reduced quality of life. Either disuse or overloading can disrupt cartilage homeostasis, but physiological cyclical loading promotes cartilage homeostasis. To model this, we exposed SW1353 cells to cyclical mechanical stimuli, shear and compression, for different durations of time (15 and 30 min). By utilizing liquid chromatography-mass spectroscopy (LC-MS), metabolomic profiles were generated detailing metabolite features and biological pathways that are altered in response to mechanical stimulation. In total, 1457 metabolite features were detected. Statistical analyses identified several pathways of interest. Taken together, differences between experimental groups were associated with inflammatory pathways, lipid metabolism, beta-oxidation, central energy metabolism, and amino acid production. These findings expand our understanding of chondrocyte mechanotransduction under varying loading conditions and time periods. This article has an associated First Person interview with the first author of the paper.

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.

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 influence of sample collection, handling and low temperature storage upon NMR metabolic profiling analysis in human synovial fluid

The impact of metabolism upon the altered pathology of joint disease is rapidly becoming recognized as an important area of study. Synovial joint fluid is an attractive and representative biofluid of joint disease. A systemic review revealed little evidence of the metabolic stability of synovial joint fluid collection, handling or storage, despite recent reports characterizing the metabolic phenotype in joint disease. We aim to report the changes in small molecule detection within human synovial fluid (HSF) using nuclear magnetic resonance (NMR) spectroscopy at varying storage temperatures, durations and conditions. HSF was harvested by arthrocentesis from patients with isolated monoarthropathy or undergoing joint replacement (n = 30). Short-term storage (0-12 h, 4°C & 18°C) and the effect of repeated freeze-thaw cycles (-80°C to 18°C) was assessed. Long-term storage was evaluated by early (-80°C, <21days) and late analysis (-80°C, 10-12 months). 1D NMR spectroscopy experiments, NOESYGPPR1D and CPMG identified metabolites and semi-quantification was performed. Samples demonstrated broad stability to freeze-thaw cycling and refrigeration of <4 h. Short-term room temperature or refrigerated storage showed significant variation in 2-ketoisovalerate, valine, dimethylamine, succinate, 2-hydroxybutyrate, and acetaminophen glucuronide. Lipid and macromolecule detection was variable. Long-term storage demonstrated significant changes in: acetate, acetoacetate, creatine, N,N-dimethylglycine, dimethylsulfone, 3-hydroxybutyrate and succinate. Changeable metabolites during short-term storage appeared to be energy-synthesis intermediates. Most metabolites were stable for the first four hours at room temperature or refrigeration, with notable exceptions. We therefore recommend that HSF samples should be kept refrigerated for no more than 4 hours prior to freezing at -80°C. Furthermore, storage of HSF samples for 10-12 months before analysis can affect the detection of selected metabolites.

Metabolomic Signature of Amino Acids, Biogenic Amines and Lipids in Blood Serum of Patients with Severe Osteoarthritis

Metabolomic analysis is an emerging new diagnostic tool, which holds great potential for improving the understanding of osteoarthritis (OA)-caused metabolomic shifts associated with systemic inflammation and oxidative stress. The main aim of the study was to map the changes of amino acid, biogenic amine and complex lipid profiles in severe OA, where the shifts should be more eminent compared with early stages. The fasting serum of 70 knee and hip OA patients and 82 controls was assessed via a targeted approach using the AbsoluteIDQ™ p180 kit. Changes in the serum levels of amino acids, sphingomyelins, phoshatidylcholines and lysophosphatidylcholines of the OA patients compared with controls suggest systemic inflammation in severe OA patients. Furthermore, the decreased spermine to spermidine ratio indicates excessive oxidative stress to be associated with OA. Serum arginine level was positively correlated with radiographic severity of OA, potentially linking inflammation through NO synthesis to OA. Further, the level of glycine was negatively associated with the severity of OA, which might refer to glycine deficiency in severe OA. The current study demonstrates significant changes in the amino acid, biogenic amine and low-molecular weight lipid profiles of severe OA and provides new insights into the complex interplay between chronic inflammation, oxidative stress and OA.

A Tale of Two Biomarkers: Untargeted 1H NMR Metabolomic Fingerprinting of BHBA and NEFA in Early Lactation Dairy Cows

Disorders of energy metabolism, which can result from a failure to adapt to the period of negative energy balance immediately after calving, have significant negative effects on the health, welfare and profitability of dairy cows. The most common biomarkers of energy balance in dairy cows are β-hydroxybutyrate (BHBA) and non-esterified fatty acids (NEFA). While elevated concentrations of these biomarkers are associated with similar negative health and production outcomes, the phenotypic and genetic correlations between them are weak. In this study, we used an untargeted ¹H NMR metabolomics approach to investigate the serum metabolomic fingerprints of BHBA and NEFA. Serum samples were collected from 298 cows in early lactation (calibration dataset N = 248, validation N = 50). Metabolomic fingerprinting was done by regressing ¹H NMR spectra against BHBA and NEFA concentrations (determined using colorimetric assays) using orthogonal partial least squares regression. Prediction accuracies were high for BHBA models, and moderately high for NEFA models (R² of external validation of 0.88 and 0.75, respectively). We identified 16 metabolites that were significantly (variable importance of projection score > 1) correlated with the concentration of one or both biomarkers. These metabolites were primarily intermediates of energy, phospholipid, and/or methyl donor metabolism. Of the significant metabolites identified; (1) two (acetate and creatine) were positively correlated with BHBA but negatively correlated with NEFA, (2) nine had similar associations with both BHBA and NEFA, (3) two were correlated with only BHBA concentration, and (4) three were only correlated with NEFA concentration. Overall, our results suggest that BHBA and NEFA are indicative of similar metabolic states in clinically healthy animals, but that several significant metabolic differences exist that help to explain the weak correlations between them. We also identified several metabolites that may be useful intermediate phenotypes in genomic selection for improved metabolic health.

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.

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.

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.

A systematic review of the small molecule studies of osteoarthritis using nuclear magnetic resonance and mass spectroscopy

OBJECTIVE

To perform a systematic review of the small molecule metabolism studies of osteoarthritis utilising nuclear magnetic resonance (NMR) or mass spectroscopy (MS) analysis (viz., metabolomics or metabonomics), thereby providing coherent conclusions and reference material for future study.

METHOD

We applied PRISMA guidelines (PROSPERO 95068) with the following MESH terms: 1. "osteoarthritis" AND ("metabolic" OR "metabonomic" OR "metabolomic" OR "metabolism") 2. ("synovial fluid" OR "cartilage" OR "synovium" OR "serum" OR "plasma" OR "urine") AND ("NMR" or "Mass Spectroscopy"). Databases searched were "Medline" and "Embase". Studies were searched in English and excluded review articles not containing original research. Study outcomes were significant or notable metabolites, species (human or animal) and the Newcastle-Ottawa Score.

RESULTS

In the 27 studies meeting the inclusion criteria, there was a shift towards anaerobic and fatty acid metabolism in OA disease, although whether this represents the inflammatory state remains unclear. Lipid structure and composition was altered within disease subclasses including phosphatidyl choline (PC) and the sphingomyelins. Macromolecular proteoglycan destruction was described, but the correlation to disease factors was not demonstrated. Collated results suggested arachidonate signalling pathways and androgen sex hormones as future metabolic pathways for investigation.

CONCLUSION

Our meta-analysis demonstrates significant small molecule differences between sample types, between species (such as human and bovine), with potential OA biomarkers and targets for local or systemic therapies. Studies were limited by numbers and a lack of disease correlation. Future studies should use NMR and MS analysis to further investigate large population subgroups including inflammatory arthropathy, OA subclasses, age and joint differences.

Alteration of Metabolic Pathways in Osteoarthritis

Sir Archibald Edward Garrod, who pioneered the field of inborn errors of metabolism and first elucidated the biochemical basis of alkaptonuria over 100 years ago, suggested that inborn errors of metabolism were "merely extreme examples of variations of chemical behavior which are probably everywhere present in minor degrees, just as no two individuals of a species are absolutely identical in bodily structure neither are their chemical processes carried out on exactly the same lines", and that this "chemical individuality [confers] predisposition to and immunities from various mishaps which are spoken of as diseases". Indeed, with advances in analytical biochemistry, especially the development of metabolomics in the post-genomic era, emerging data have been demonstrating that the levels of many metabolites do show substantial interindividual variation, and some of which are likely to be associated with common diseases, such as osteoarthritis (OA). Much work has been reported in the literature on the metabolomics of OA in recent years. In this narrative review, we provided an overview of the identified alteration of metabolic pathways in OA and discussed the role of those identified metabolites and related pathways in OA diagnosis, prognosis, and treatment.

Metabolomics as a promising tool for early osteoarthritis diagnosis

Osteoarthritis (OA) is the main cause of disability worldwide, due to progressive articular cartilage loss and degeneration. According to recent research, OA is more than just a degenerative disease due to some metabolic components associated to its pathogenesis. However, no biomarker has been identified to detect this disease at early stages or to track its development. Metabolomics is an emerging field and has the potential to detect many metabolites in a single spectrum using high resolution nuclear magnetic resonance (NMR) techniques or mass spectrometry (MS). NMR is a reproducible and reliable non-destructive analytical method. On the other hand, MS has a lower detection limit and is more destructive, but it is more sensitive. NMR and MS are useful for biological fluids, such as urine, blood plasma, serum, or synovial fluid, and have been used for metabolic profiling in dogs, mice, sheep, and humans. Thus, many metabolites have been listed as possibly associated to OA pathogenesis. The goal of this review is to provide an overview of the studies in animal models and humans, regarding the use of metabolomics as a tool for early osteoarthritis diagnosis. The concept of osteoarthritis as a metabolic disease and the importance of detecting a biomarker for its early diagnosis are highlighted. Then, some studies in plasma and synovial tissues are shown, and finally the application of metabolomics in the evaluation of synovial fluid is described.

Review of Soluble Biomarkers of Osteoarthritis: Lessons From Animal Models

Objective Osteoarthritis (OA) is one of the leading causes of disability within the adult population. Currently, its diagnosis is mainly based on clinical examination and standard radiography. To date, there is no way to detect the disease at a molecular level, before the appearance of structural changes and symptoms. So an attractive alternative for monitoring OA is the measurement of biochemical markers in blood, urine, or synovial fluid, which could reflect metabolic changes in joint tissue and therefore disease onset and progression. Animal models are relevant to investigate the early stage of OA and metabolic changes occurring in joint tissues. The goal of this narrative review is to summarize the scientific data available in the literature on soluble biomarkers in animal models of OA. Design A literature search was conducted using the PubMed/Medline and Scopus databases between February 1995 and December 2015. All original articles, systematic and narrative reviews published in French or in English were considered. Results We summarized the data of 69 studies and proposed a classification scheme for OA biomarkers in animal studies, largely inspired by the BIPEDS classification. Conclusions Studies about biomarkers and animal models indicate that some markers could be valuable to monitor OA progression and assess therapeutic response in some animal models.

Methylsulfonylmethane: Applications and Safety of a Novel Dietary Supplement

Methylsulfonylmethane (MSM) has become a popular dietary supplement used for a variety of purposes, including its most common use as an anti-inflammatory agent. It has been well-investigated in animal models, as well as in human clinical trials and experiments. A variety of health-specific outcome measures are improved with MSM supplementation, including inflammation, joint/muscle pain, oxidative stress, and antioxidant capacity. Initial evidence is available regarding the dose of MSM needed to provide benefit, although additional work is underway to determine the precise dose and time course of treatment needed to provide optimal benefits. As a Generally Recognized As Safe (GRAS) approved substance, MSM is well-tolerated by most individuals at dosages of up to four grams daily, with few known and mild side effects. This review provides an overview of MSM, with details regarding its common uses and applications as a dietary supplement, as well as its safety for consumption.

Utility of circulating serum miRNAs as biomarkers of early cartilage degeneration in animal models of post-traumatic osteoarthritis and inflammatory arthritis

OBJECTIVE

The purpose of this study was to determine if serum microRNA (miRNA) signatures were biomarkers of early cartilage degeneration in preclinical mouse models of post-traumatic osteoarthritis (OA) and inflammatory arthritis.

METHODS

Cartilage degeneration was induced in 10-12 week old male C57BL6 mice by destabilization of the medial meniscus (DMM) or intra-articular injection of methylated-bovine-serum-albumin (AIA), with sham-operated or saline-injected control animals (n = 6/treatment/time). Total serum RNA and knee joints were isolated at 1, 4 and 16 weeks post-induction. Cartilage degeneration was scored histologically. Serum miRNA expression profiling was performed using Agilent microarrays and validated by qPCR.

RESULTS

DMM-operated and AIA mice had characteristic cartilage degeneration (proteoglycan loss, chondrocyte hypertrophy, structural damage), that increased significantly with time compared with controls, and with distinct temporal differences between arthritis models. However, expression profiling revealed no statistically significant dysregulation of serum miRNAs between AIA vs saline-injected or DMM vs sham-operated control mice at the critical early disease stages. The inability to detect DMM or AIA serum miRNA signatures compared with controls was not due to the insensitivity of the expression profiling approach since significant changes were observed in miRNA expression between the arthritis models and between time points.

CONCLUSION

While distinct patterns of progressive cartilage degradation were induced in the arthritis models, we were unable to identify any serum miRNAs that were significantly dysregulated in early stages of disease compared with controls. This suggests circulating serum miRNAs may not be useful as cartilage biomarkers in distinguishing the early or progressive stages of arthritis cartilage degeneration.

Cartilaginous Metabolomic Study Reveals Potential Mechanisms of Osteophyte Formation in Osteoarthritis

Osteophyte is one of the inevitable consequences of progressive osteoarthritis with the main characteristics of cartilage degeneration and endochondral ossification. The pathogenesis of osteophyte formation is not fully understood to date. In this work, metabolomic approaches were employed to explore potential mechanisms of osteophyte formation by detecting metabolic variations between extracts of osteophyte cartilage tissues (n = 32) and uninvolved control cartilage tissues (n = 34), based on the platform of ultraperformance liquid chromatography tandem quadrupole time-of-flight mass spectrometry, as well as the use of multivariate statistic analysis and univariate statistic analysis. The osteophyte group was significantly separated from the control group by the orthogonal partial least-squares discriminant analysis models, indicating that metabolic state of osteophyte cartilage had been changed. In total, 28 metabolic variations further validated by mass spectrum (MS) match, tandom mass spectrum (MS/MS) match, and standards match mainly included amino acids, sulfonic acids, glycerophospholipids, and fatty acyls. These metabolites were related to some specific physiological or pathological processes (collagen dissolution, boundary layers destroyed, self-restoration triggered, etc.) which might be associated with the procedure of osteophyte formation. Pathway analysis showed phenylalanine metabolism (PI = 0.168, p = 0.004) was highly correlative to this degenerative process. Our findings provided a direction for targeted metabolomic study and an insight into further reveal the molecular mechanisms of ostophyte formation.

The biology of meniscal pathology in osteoarthritis and its contribution to joint disease: beyond simple mechanics

The meniscal cartilages in the knee function to improve congruity of the medial and lateral femoro-tibial joints and play critical roles in load distribution and joint stability. Meniscal tears of various configurations are one of the most common conditions of the knee and are associated with an increased risk of developing osteoarthritis (OA). While this risk has been largely attributed to loss of the biomechanical functions of the menisci, there is accumulating evidence suggesting that other aspects of meniscal biology may play a role in determining the long-term consequences of meniscal damage for joint health. In this narrative review, we examine the existing literature and present some new data implicating synthesis and secretion of enzymes and other pro-catabolic mediators by injured and degenerate menisci, contributing to the pathological change in other knee joint tissues in OA.

Metabolic analysis of osteoarthritis subchondral bone based on UPLC/Q-TOF-MS

Osteoarthritis (OA), one of the most widespread musculoskeletal joint diseases among the aged, is characterized by the progressive loss of articular cartilage and continuous changes in subchondral bone. The exact pathogenesis of osteoarthritis is not completely clear. In this work, ultra-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UPLC/Q-TOF-MS) in combination with multivariate statistical analysis was applied to analyze the metabolic profiling of subchondral bone from 42 primary osteoarthritis patients. This paper described a modified two-step method for extracting the metabolites of subchondral bone from primary osteoarthritis patients. Finally, 68 metabolites were identified to be significantly changed in the sclerotic subchondral bone compared with the non-sclerotic subchondral bone. Taurine and hypotaurine metabolism and beta-alanine metabolism were probably relevant to the sclerosis of subchondral bone. Taurine, L-carnitine, and glycerophospholipids played a vital regulation role in the pathological process of sclerotic subchondral bone. In the sclerotic process, beta-alanine and L-carnitine might be related to the increase of energy consumption. In addition, our findings suggested that the intra-cellular environment of sclerotic subchondral bone might be more acidotic and hypoxic compared with the non-sclerotic subchondral bone. In conclusion, this study provided a new insight into the pathogenesis of subchondral bone sclerosis. Our results indicated that metabolomics could serve as a promising approach for elucidating the pathogenesis of subchondral bone sclerosis in primary osteoarthritis. Graphical Abstract Metabolic analysis of osteoarthritis subchondral bone.

Serum Metabolite Profiles Are Altered by Erlotinib Treatment and the Integrin α1-Null Genotype but Not by Post-Traumatic Osteoarthritis

The risk of developing post-traumatic osteoarthritis (PTOA) following joint injury is high. Furthering our understanding of the molecular mechanisms underlying PTOA and/or identifying novel biomarkers for early detection may help to improve treatment outcomes. Increased expression of integrin α1β1 and inhibition of epidermal growth factor receptor (EGFR) signaling protect the knee from spontaneous OA; however, the impact of the integrin α1β1/EGFR axis on PTOA is currently unknown. We sought to determine metabolic changes in serum samples collected from wild-type and integrin α1-null mice that underwent surgery to destabilize the medial meniscus and were treated with the EGFR inhibitor erlotinib. Following (1)H nuclear magnetic resonance spectroscopy, we generated multivariate statistical models that distinguished between the metabolic profiles of erlotinib- versus vehicle-treated mice and the integrin α1-null versus wild-type mouse genotype. Our results show the sex-dependent effects of erlotinib treatment and highlight glutamine as a metabolite that counteracts this treatment. Furthermore, we identified a set of metabolites associated with increased reactive oxygen species production, susceptibility to OA, and regulation of TRP channels in α1-null mice. Our study indicates that systemic pharmacological and genetic factors have a greater effect on serum metabolic profiles than site-specific factors such as surgery.

On the predictive utility of animal models of osteoarthritis

Animal models of osteoarthritis are extensively used for investigating disease pathways and for preclinical testing of novel therapies. Their predictive utility, however, has often been questioned, mainly because preclinical efficacy of novel therapeutics is poorly translated in clinical trials. In the current narrative review, we consider the preclinical models that were used to support undertaking clinical trials for disease-modifying osteoarthritis drugs, and compare outcomes between clinical and preclinical studies. We discuss this in light of the 1999 Food and Drug Administration draft guidelines for industry for use in the development of drugs, devices, and biological products intended for the treatment of osteoarthritis, which raised five considerations on the usefulness of osteoarthritis models. We systematically discuss what has been learnt regarding these five points since 1999, with emphasis on replicating distinct risk factors and subtypes of human osteoarthritis, and on comprehensive evaluation of the disease in animals, including pathology of all joint tissues, biomarker analysis, and assessment of pain and joint function. Finally, we discuss lessons learnt and propose some recommendations for how the evidence from preclinical research might be strengthened with a view to improving success in clinical translation.

Animal Models of Osteoarthritis: Comparisons and Key Considerations

Osteoarthritis (OA) is unquestionably one of the most important chronic health issues in humans, affecting millions of individuals and costing billions of dollars annually. Despite widespread awareness of this disease and its devastating impact, the pathogenesis of early OA is not completely understood, hampering the development of effective tools for early diagnosis and disease-modifying therapeutics. Most human tissue available for study is obtained at the time of joint replacement, when OA lesions are end stage and little can be concluded about the factors that played a role in disease development. To overcome this limitation, over the past 50 years, numerous induced and spontaneous animal models have been utilized to study disease onset and progression, as well as to test novel therapeutic interventions. Reflecting the heterogeneity of OA itself, no single "gold standard" animal model for OA exists; thus, a challenge for researchers lies in selecting the most appropriate model to answer a particular scientific question of interest. This review provides general considerations for model selection, as well as important features of species such as mouse, rat, guinea pig, sheep, goat, and horse, which researchers should be mindful of when choosing the "best" animal model for their intended purpose. Special consideration is given to key variations in pathology among species as well as recommended guidelines for reporting the histologic features of each model.

Use of quantitative MRI for the detection of progressive cartilage degeneration in a mini-pig model of osteoarthritis caused by anterior cruciate ligament transection

BACKGROUND

To investigate the progression of cartilage degeneration using delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) and T2 mapping in a mini-pig model of osteoarthritis (OA) caused by anterior cruciate ligament transection (ACLT).

METHODS

Twelve mini-pigs underwent ACLT in the left knee and were monitored by dGEMRIC (T1, gadolinium [Gd]) and T2 mapping after 2, 4, or 6 weeks (n = 4 each). No ACLT surgery was performed in four healthy control mini-pigs, which were also monitored by dGEMRIC and T2 mapping. Cartilage samples from the weight-bearing regions of the left medial femoral condyles were collected for macroscopic, histological, immunohistochemical, and biochemical analysis. Correlations between biochemical contents and T1,Gd and T2 values were evaluated using Pearson correlation analysis.

RESULTS

T1,Gd values were gradually reduced and T2 values increased over time. Cartilage surfaces showed roughness at 4 weeks and additional defects at 6 weeks. Glycosaminoglycan (GAG) distribution and content gradually reduced over time (P < 0.05), and collagen distribution and anisotropy were obviously changed at 6 weeks. However, collagen content did not differ significantly among postoperative timepoints. GAG content was positively related to T1,Gd values (r = 0.888; P < 0.001) and negatively related to T2 values (r = -0.865; P < 0.001). Collagen content had no discernible correlation with T1,Gd or T2 values.

CONCLUSION

dGEMRIC and T2 mapping can monitor the progression of cartilage degeneration in a mini-pig model of ACLT-induced OA, permitting early detection of OA.

Metabolic profiling of synovial fluid in a unilateral ovine model of anterior cruciate ligament reconstruction of the knee suggests biomarkers for early osteoarthritis

Joint injuries and subsequent osteoarthritis (OA) are the leading causes of chronic joint disease. In this work, we explore the possibility of applying magnetic resonance spectroscopy-based metabolomics to detect host responses to an anterior cruciate ligament (ACL) reconstruction injury in synovial fluid in an ovine model. Using multivariate statistical analysis, we were able to distinguish post-injury joint samples (ACL and sham surgery) from the uninjured control samples, and as well the ACL surgical samples from sham surgery. In all samples there were 65 metabolites quantified, of which six could be suggested as biomarkers for early post-injury degenerative changes in the knee joints: isobutyrate, glucose, hydroxyproline, asparagine, serine, and uridine. Our results raise a cautionary note indicating that surgical interventions into the knee can result in metabolic alterations that need to be distinguished from those caused by the early onset of OA. Our findings illustrate the potential application of metabolomics as a diagnostic and prognostic tool for detection of injuries to the knee joint. The ability to detect a unique pattern of metabolic changes in the synovial fluid of sheep offers the possibility of extending the approach to precision medicine protocols in patient populations in the future.

Metabolite profiling and pathway analysis of acute hepatitis rats by UPLC-ESI MS combined with pattern recognition methods

BACKGROUND & AIMS

Metabolomics is comprehensive analysis of low-molecular-weight endogenous metabolites in a biological sample. It could enable mapping of perturbations of early biochemical changes in diseases and hence provide an opportunity to develop predictive biomarkers that could provide valuable insights into the mechanisms of diseases. The aim of this study was to elucidate the changes in endogenous metabolites and to phenotype the metabolic profiling of d-galactosamine (GalN)-inducing acute hepatitis in rats by UPLC-ESI MS.

METHODS

The systemic biochemical actions of GalN administration (ip, 400 mg/kg) have been investigated in male wistar rats using conventional clinical chemistry, liver histopathology and metabolomic analysis of UPLC- ESI MS of urine. The urine was collected predose (-24 to 0 h) and 0-24, 24-48, 48-72, 72-96 h post-dose. Mass spectrometry of the urine was analysed visually and via conjunction with multivariate data analysis.

RESULTS

Results demonstrated that there was a time-dependent biochemical effect of GalN dosed on the levels of a range of low-molecular-weight metabolites in urine, which was correlated with developing phase of the GalN-inducing acute hepatitis. Urinary excretion of beta-hydroxybutanoic acid and citric acid was decreased following GalN dosing, whereas that of glycocholic acid, indole-3-acetic acid, sphinganine, n-acetyl-l-phenylalanine, cholic acid and creatinine excretion was increased, which suggests that several key metabolic pathways such as energy metabolism, lipid metabolism and amino acid metabolism were perturbed by GalN.

CONCLUSION

This metabolomic investigation demonstrates that this robust non-invasive tool offers insight into the metabolic states of diseases.

Osteoarthritis year 2013 in review: biomarkers; reflecting before moving forward, one step at a time

In 2010, in Osteoarthritis and Cartilage, we published a comprehensive systematic review applying the consensus BIPED criteria (Burden of Disease, Investigative, Prognostic, Efficacy of Intervention and Diagnostic) criteria on serum and urinary biochemical markers for knee and hip osteoarthritis (OA) using publications that were available at that time. It appeared that none of the biochemical markers at that time were sufficiently discriminating to allow diagnosis and prognosis of OA in individual or limited numbers of patients, nor performed so consistently that they could function as primary outcome parameters in clinical trials. Also at present, almost 3 years later, this ultimate goal has not been reached (yet). Frankly, it might be questioned whether we are making the most adequate steps ahead and maybe we have to take a step back to reconsider our approaches. Some reflections are made and discussed: A critical review of molecular metabolism in OA and validation of currently investigated marker molecules in this may be vital and may lead to new and better markers. Creating cohorts in which synovial fluid (SF) is obtained in a systematic way, together with serum and urine, may also bring the field a further step ahead. Thirdly, better understanding of different phenotypes (subtypes) of OA may facilitate identification and validation of biochemical markers. Finally, the systems biology approach as discussed in the last years OA in review on biomarkers, although very complex, might provide steps forward. Looking ahead, we are optimistic but realistic in our expectations, we believe that the field can be brought forward by critically and cautiously reconsidering our approaches, and making changes forward, one step at a time.