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

Hahn, A.; Batushansky, Albert; Rawle, Rachel A.; Lopes, Erika Barboza Prado; June, Ronald K.; Griffin, Timothy M.

doi:10.1016/j.joca.2021.08.008

Cited by 13 publications

(9 citation statements)

References 55 publications

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“…Importantly, our induced moderate form of exercise resulted in protection against cartilage damage after 7-week of exercise. In addition to the significant changes in cartilage, evaluation of trabecular bone in the exercise DMM group revealed a more plate-like micro-structure with increased connectivity, similar to findings observed by Hahn et al (2021) , and known for offering higher bone strength ( Teo et al, 2007 ). Moreover, there was an early, albeit temporary, improvement in subchondral bone osteosclerosis in the exercise group; expressed by the significantly smaller increase in bone density of the subchondral bone.…”

Section: Discussionsupporting

confidence: 62%

“…However, a more severe model of OA on rats (ACL-T and DMM together) showed moderate to reduce progression of OA and this improvement was enhanced by reducing body weight load to 60%. In mice, exercise has also been explored, where OA was induced by high fat diet ( Griffin et al, 2012 ; Hahn et al, 2021 ), age ( Lapveteläinen et al, 1995 ), ACL rupture ( Hsia et al, 2021 ), spaceflight/limb unloading ( Kwok et al, 2021 ), ACL-T ( Oka et al, 2021 ) or DMM exacerbated by restricted movement ( Kim et al, 2013 ). Similar to the rat model, high intensity exercise resulted in aggravated OA whilst moderate treadmill or voluntary wheel exercise improved OA parameters in the joint.…”

Section: Introductionmentioning

confidence: 99%

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Moderate exercise protects against joint disease in a murine model of osteoarthritis

Huesa

Dunning²,

MacDougall³

et al. 2022

Front. Physiol.

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Exercise is recommended as a non-pharmacological therapy for osteoarthritis (OA). Various exercise regimes, with differing intensities and duration, have been used in a range of OA rodent models. These studies show gentle or moderate exercise reduces the severity of OA parameters while high intensity load bearing exercise is detrimental. However, these studies were largely conducted in rats or in mouse models induced by severe injury, age or obesity, whilst destabilization of the medial meniscus (DMM) in mice has become a widely accepted model due to its lower variability, moderate progression and timescale. The present study was undertaken to provide insight into the effect of moderate exercise on early joint pathology in the DMM mouse model. Exercise was induced a week after induction by forced wheel walking for three or 7 weeks. Joints were analyzed by microcomputed tomography and histology. Assessment of skeletal parameters revealed that exercise offered protection against cartilage damage after 7 weeks of exercise, and a temporary protection against osteosclerosis was displayed after 3 weeks of exercise. Furthermore, exercise modified the metaphyseal trabecular microarchitecture of the osteoarthritic leg in both time points examined. Collectively, our findings corroborate previous studies showing that exercise has an important effect on bone in OA, which subsequently, at 8 weeks post-induction, translates into less cartilage damage. Thus, providing an exercise protocol in a surgical mouse model of OA, which can be used in the future to further dissect the mechanisms by which moderate exercise ameliorates OA.

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Section: Discussionsupporting

confidence: 62%

Section: Introductionmentioning

confidence: 99%

Moderate exercise protects against joint disease in a murine model of osteoarthritis

Huesa

Dunning²,

MacDougall³

et al. 2022

Front. Physiol.

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“…When performing an ensemble of clustering solutions there are a bevy of potential clustering methods including partitional, hierarchical, and density-based methods that can be utilized. In this implementation we focused on a combination of hierarchical clustering solutions as they are commonly used clustering method in the metabolomics field(Carlson et al ., 2018; Carlson et al ., 2019a; Carlson et al ., 2019b; Hahn et al ., 2021; Hislop et al ., 2022; Kim et al ., 2014; Pang et al ., 2021; Wallace et al ., 2022; Wang-Sattler et al ., 2012; Zignego et al ., 2015). However, we acknowledge that there are many other potential combinations of clustering solutions that can be explored to provide a consensus on the appropriate number of clusters within a given dataset.…”

Section: Discussionmentioning

confidence: 99%

“…Metabolomics has yielded many important insights into biological processes and diseases (Carlson et al ., 2018; Carlson et al ., 2019a; Carlson et al ., 2019b; Hahn et al ., 2021; Hislop et al ., 2022; Kim et al ., 2014; Wang-Sattler et al ., 2012; Zignego et al ., 2015). Arguably, metabolomics could be employed more broadly and to greater effect by resolving persistent challenges in the analysis workflow.…”

Section: Introductionmentioning

confidence: 99%

Ensemble Clustering Combined with Clustering Optimization – A Novel Workflow for Analyzing Metabolomics Data

Hislop

Heveran

June

2022

Preprint

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Metabolomic studies have improved the understanding of a broad range of biological tissues, fluids, and systems. Typically, metabolomic analyses employ a workflow that starts with detecting peaks from mass spectrometry data and is followed by a series of statistical analysis aimed at identifying dysregulated metabolites, group differences, and group similarities in dysregulated metabolites and pathways. Generating these group similarities relies on clustering analyses. However, current clustering methods are highly subjective and can be prone to errors, indicating the need for an updated workflow that improves upon these issues. Here we present a novel metabolomics workflow that can produce unbiased, reproducible clustering results: ensemble clustering combined with cluster optimization (ECCO). The first step, clustering optimization, is used to identify an optimal number of clusters without bias. The second step, ensemble clustering, is then performed by finding the consensus clustering solution across thirteen distance algorithms. This step improves the repeatability of analyses and eliminates bias through eliminating the need to choose one distance algorithm in clustering solutions. We employ ECCO to analyze synovial fluid metabolites from patients with early and late osteoarthritis (OA). This method improves upon the detection of distinct metabolomic endotypes compared with conventional analyses. Furthermore, novel pathways were identified corresponding with different stages of OA. These results demonstrate the utility of ECCO in metabolomics workflows that involve clustering data. ECCO, which we provide as an open-source tool, can improve the repeatability, reliability, and ease-of-use of metabolomics analyses, and is therefore expected to increase the confidence of biological interpretation from these data.

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“…These patient studies are complemented by animal experiments. A collaboration between Ron June's and Tim Griffin's groups has used a mouse model of high fat diet and exercise to determine effects of the metabolome of synovial fluid and its correlation with systemic metabolism as well as inflammation and structural OA progression [20 ▪ ]. This study provides excellent baseline data on metabolic effects of these two lifestyle modifications on joint metabolism, as well as how these changes correlate to systemic parameters.…”

Section: Metabolomicsmentioning

confidence: 99%

The impact of omics research on our understanding of osteoarthritis and future treatments

Beier¹

2022

Current Opinion in Rheumatology

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Purpose of reviewTo review recent studies using Omics approaches (genomics, proteomics, metabolomics, single cell analyses) in patient populations and animal models of osteoarthritis (OA), with the goal of identifying disease-modifying mechanisms that could serve as therapeutic and diagnostic targets. Recent findingsThe number of genes, pathways and molecules with potential roles in OA pathogenesis has grown substantially over the last 18 months. Studies have expanded from their traditional focus on cartilage and gene expression to other joint tissues, proteins and metabolites. Single cell approaches provide unprecedented resolution and exciting insights into the heterogeneity of cellular activities in OA. Functional validation and investigation of underlying mechanisms in animal models of OA, in particular genetically engineered mice, link Omics findings to pathophysiology and potential therapeutic applications.

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

Cited by 13 publications

References 55 publications

Moderate exercise protects against joint disease in a murine model of osteoarthritis

Moderate exercise protects against joint disease in a murine model of osteoarthritis

Ensemble Clustering Combined with Clustering Optimization – A Novel Workflow for Analyzing Metabolomics Data

The impact of omics research on our understanding of osteoarthritis and future treatments

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