OA susceptibility in mice is partially mediated by the gut microbiome, is transferrable via microbiome transplantation and is associated with immunophenotype changes.

OBJECTIVES: The Murphy Roths Large (MRL)/MpJ 'superhealer' mouse strain is protected from post-traumatic osteoarthritis (OA), although no studies have evaluated the microbiome in the context of this protection. This study characterised microbiome differences between MRL and wild-type mice, evaluated microbiome transplantation and OA and investigated microbiome-associated immunophenotypes. METHODS: Cecal material from mixed sex C57BL6/J (B6) or female MRL/MpJ (MRL) was transplanted into B6 and MRL mice, then OA was induced by disruption of the medial meniscus surgery (DMM). In other experiments, transplantation was performed after DMM and transplantation was performed into germ-free mice. Transplanted mice were bred through F2. OARSI, synovitis and osteophyte scores were determined blindly 8 weeks after DMM. 16S microbiome sequencing was performed and metagenomic function was imputed. Immunophenotypes were determined using mass cytometry. RESULTS: MRL-into-B6 transplant prior to DMM showed reduced OA histopathology (OARSI score 70% lower transplant vs B6 control), synovitis (60% reduction) and osteophyte scores (30% reduction) 8 weeks after DMM. When performed 48 hours after DMM, MRL-into-B6 transplant improved OA outcomes but not when performed 1-2 weeks after DMM. Protection was seen in F1 (60% reduction) and F2 progeny (30% reduction). Several cecal microbiome clades were correlated with either better (eg, Lactobacillus, R=-0.32, p=0.02) or worse (eg, Rikenellaceae, R=0.43, p=0.001) OA outcomes. Baseline immunophenotypes associated with MRL-into-B6 transplants and MRL included reduced double-negative T cells and increased CD25+CD4+ T cells. CONCLUSION: The gut microbiome is responsible in part for OA protection in MRL mice and is transferrable by microbiome transplantation. Transplantation induces resting systemic immunophenotyping changes that correlate with OA protection.

The Microbiome in Osteoarthritis: a Narrative Review of Recent Human and Animal Model Literature.

PURPOSE OF THE REVIEW: The microbiome has recently emerged as a powerful contributor to health and illness in chronic, systemic disorders. Furthermore, new microbiome niches beyond traditional gut locations are frequently being described. Over the past 5 years, numerous pivotal studies have demonstrated associations between changes in various microbiome niches and the development of osteoarthritis (OA). Herein, we review the most impactful recent literature, including microbiome associations with disease and the potential therapeutic value of microbiome manipulation. RECENT FINDINGS: The gut microbiome of human OA patients is enriched in specific bacterial clades, most notably Streptococcus, which correlates with OA pain, Firmicutes, and others. Most studies have focused on knee OA, although one publication demonstrated positive associations with 3 gut microbiome clades in hand OA. OA can be easily distinguished from RA by evaluating differences in oral microbiome composition. Most studies have also demonstrated a reduction in richness of the gut microbiome (alpha diversity) associated with OA. Several studies have identified bacterial signatures within human knee and hip cartilage, synovial fluid, and synovial tissue and have described changes in these patterns occurring with the development of OA. In animal models of OA, high-fat diet-induced obesity has been the most well-studied OA risk factor associated with changes in the microbiome, with numerous bacterial clades changed within the gut microbiome and associated with OA. Also in animal models, various oral supplementations, including dietary fiber, probiotics including Lactobacillus species, and cecal microbiome transplantation have all shown improvements in OA histopathology or cartilage healing. Microbiome changes are strongly associated with the OA disease process and with individual OA risk factors related to both the gut microbiome and the microbial DNA patterns in the joint. Microbiome-directed interventions have the potential to prevent or reduce the progression of OA. Future studies should investigate the mechanistic underpinnings of these microbiome associations and further define the therapeutic potential of microbiome augmentation.

Sex-Linked Discrepancies in C57BL6/J Mouse Osteoarthritis are Associated With the Gut Microbiome and are Transferrable by Microbiome Transplantation.

OBJECTIVE: Females have reduced osteoarthritis (OA) in surgical models. The objective of the current study was to evaluate a sex-linked gut microbiome in the pathogenesis of OA. METHODS: We induced OA via destabilization of the medial meniscus surgery in adult male and female C57BL6/J mice with and without opposite-sex microbiome transplantation. Eight weeks later, animals were euthanized, and OA severity, synovitis, and osteophyte scores were determined. Serum lipopolysaccharide was measured chromogenically, and serum cytokines were quantified via multiplex immunoassay. Cecal microbiome profiles were generated using 16S deep sequencing. RESULTS: Males had worse OA histology (3.5x, P = 6 × 10-7 ), synovitis (2.4x, P = 5 × 10-4 ), and osteophyte scores (3.7x, P = 3 × 10-4 ) than females. Male-into-female transplantation worsened all outcomes (histology 1.8x, P = 0.02; synovitis 2.0x, P = 3 × 10-5 ; osteophyte 2.1x, P = 0.01) compared to females, whereas female-into-male transplantation improved all outcomes except for synovitis (histology 0.53x, P = 2 × 10-4 ; osteophyte 0.28x, P = 5 × 10-4 ) compared to males. In the gut microbiome analysis, 44 clades were different in at least one group comparison; 5 clades were correlated with the Osteoarthritis Research Society International score (Lactobacillus R = -0.40, Aldercreutzia R = -0.40, rc4_4 R = -0.55, Sutterella R = -0.37, and Clostridiales R = 0.36). In the cytokine analysis, 10 analytes were different in at least one group comparison; 3 were different in two groups (female and female-into-male transplants vs male comparisons, all reduced in female and female-into-male transplants), including interleukin-12 (0.66x, P = 0.02; 0.66x, P = 0.02, respectively), eotaxin (0.74x, P = 5 × 10-6 ; 0.57x, P = 0.03), and tumor necrosis factor ⍺ (0.49x, P = 0.03; 0.52x, P = 0.009). CONCLUSION: Sex-linked differences in the mouse gut microbiome are associated with OA outcomes, are reversible by opposite-sex microbiome transplantation, and are associated with serum cytokine changes.

Murine cartilage microbial DNA deposition occurs rapidly following the introduction of a gut microbiome and changes with obesity, aging, and knee osteoarthritis.

Cartilage microbial DNA patterns have been recently characterized in osteoarthritis (OA). The objectives of this study were to evaluate the gut origins of cartilage microbial DNA, to characterize cartilage microbial changes with age, obesity, and OA in mice, and correlate these to gut microbiome changes. We used 16S rRNA sequencing performed longitudinally on articular knee cartilage from germ-free (GF) mice following oral microbiome inoculation and cartilage and cecal samples from young and old wild-type mice with/without high-fat diet-induced obesity (HFD) and with/without OA induced by destabilization of the medial meniscus (DMM) to evaluate gut and cartilage microbiota. Microbial diversity was assessed, groups compared, and functional metagenomic profiles reconstructed. Findings were confirmed in an independent cohort by clade-specific qPCR. We found that cartilage microbial patterns developed at 48 h and later timepoints following oral microbiome inoculation of GF mice. Alpha diversity was increased in SPF mouse cartilage samples with age (P = 0.013), HFD (P = 5.6E-4), and OA (P = 0.029) but decreased in cecal samples with age (P = 0.014) and HFD (P = 1.5E-9). Numerous clades were altered with aging, HFD, and OA, including increases in Verrucomicrobia in both cartilage and cecal samples. Functional analysis suggested changes in dihydroorotase, glutamate-5-semialdehyde dehydrogenase, glutamate-5-kinase, and phosphoribosylamine-glycine ligase, in both cecum and cartilage, with aging, HFD, and OA. In conclusion, cartilage microbial DNA patterns develop rapidly after the introduction of a gut microbiome and change in concert with the gut microbiome during aging, HFD, and OA in mice. DMM-induced OA causes shifts in both cartilage and cecal microbiome patterns independent of other factors.

Peripheral Blood DNA Methylation-Based Machine Learning Models for Prediction of Knee Osteoarthritis Progression: Biologic Specimens and Data From the Osteoarthritis Initiative and Johnston County Osteoarthritis Project.

OBJECTIVE: The lack of accurate biomarkers to predict knee osteoarthritis (OA) progression is a key unmet need in OA clinical research. The objective of this study was to develop baseline peripheral blood epigenetic biomarker models to predict knee OA progression. METHODS: Genome-wide buffy coat DNA methylation patterns from 554 individuals from the Osteoarthritis Biomarkers Consortium (OABC) were determined using Illumina Infinium MethylationEPIC 850K arrays. Data were divided into model development and validation sets, and machine learning models were trained to classify future OA progression by knee pain, radiographic imaging, knee pain plus radiographic imaging, and any progression (pain, radiographic, or both). Parsimonious models using the top 13 CpG sites most frequently selected during development were tested on independent samples from participants in the Johnston County Osteoarthritis (JoCo OA) Project (n = 128) and a previously published Osteoarthritis Initiative (OAI) data set (n = 55). RESULTS: Full models accurately classified future radiographic-only progression (mean ± SEM accuracy 87 ± 0.8%, area under the curve [AUC] 0.94 ± 0.004), pain-only progression (accuracy 89 ± 0.9%, AUC 0.97 ± 0.004), pain plus radiographic progression (accuracy 72 ± 0.7%, AUC 0.79 ± 0.006), and any progression (accuracy 78 ± 0.4%, AUC 0.86 ± 0.004). Pain-only and radiographic-only progressors were not distinguishable (mean ± SEM accuracy 58 ± 1%, AUC 0.62 ± 0.001). Parsimonious models showed similar performance and accurately classified future radiographic progressors in the OABC cohort and in both validation cohorts (mean ± SEM accuracy 80 ± 0.3%, AUC 0.88 ± 0.003 [using JoCo OA Project data], accuracy 80 ± 0.8%, AUC 0.89 ± 0.002 [using previous OAI data]). CONCLUSION: Our data suggest that pain and structural progression share similar early systemic immune epigenotypes. Further studies should focus on evaluating the pathophysiologic consequences of differential DNA methylation and peripheral blood cell epigenotypes in individuals with knee OA.

A Pilot Analysis of Genome-Wide DNA Methylation Patterns in Mouse Cartilage Reveals Overlapping Epigenetic Signatures of Aging and Osteoarthritis.

OBJECTIVE: Cartilage epigenetic changes are strongly associated with human osteoarthritis (OA). However, the influence of individual environmental OA risk factors on these epigenetic patterns has not been determined; herein we characterize cartilage DNA methylation patterns associated with aging and OA in a mouse model. METHODS: Murine knee cartilage DNA was extracted from healthy young (16-week, n = 6), old (82-week, n = 6), and young 4-week post-destabilization of the medial meniscus (DMM) OA (n = 6) C57BL6/J mice. Genome-wide DNA methylation patterns were determined via Illumina BeadChip. Gene set enrichment analysis was performed by Ingenuity Pathway Analysis. The top seven most differentially methylated positions (DMPs) were confirmed by pyrosequencing in an independent animal set. Results were compared to previously published human OA methylation data. RESULTS: Aging was associated with 20,940 DMPs, whereas OA was associated with 761 DMPs. Merging these two conditions revealed 279 shared DMPs. All demonstrated similar directionality and magnitude of change (Δß 1.0% ± 0.2%, mean methylation change ± SEM). Shared DMPs were enriched in OA-associated pathways, including RhoA signaling (P = 1.57 × 10-4 ), protein kinase A signaling (P = 3.38 × 10-4 ), and NFAT signaling (P = 6.14 × 10-4 ). Upstream regulators, including TET3 (P = 6.15 × 10-4 ), immunoglobulin (P = 6.14 × 10-4 ), and TLR7 (P = 7.53 × 10-4 ), were also enriched. Pyrosequencing confirmed six of the seven top DMPs in an independent cohort. CONCLUSION: Aging and early OA following DMM surgery induce similar DNA methylation changes within a murine OA model, suggesting that aging may induce pro-OA epigenetic "poising" within articular cartilage. Future research should focus on confirming and expanding these findings to other environmental OA risk factors, including obesity, as well as determining late OA changes in mice.

Identification of Cartilage Microbial DNA Signatures and Associations With Knee and Hip Osteoarthritis.

OBJECTIVE: Alterations of the gut microbiota have been implicated in many forms of arthritis, but an examination of cartilage microbial patterns has not been performed. This study was undertaken to characterize the microbial DNA profile of articular cartilage and determine changes associated with osteoarthritis (OA). METHODS: We performed 16S ribosomal RNA gene deep sequencing on eroded and intact cartilage samples from knee OA patients (n = 21 eroded and 21 intact samples) and hip OA patients (n = 34 eroded and 33 intact samples) and cadaver controls (n = 10 knee samples and 10 hip samples). Microbial DNA diversity was assessed, groups were compared, and metagenomic profiles were reconstructed. Confirmation was performed in an independent cohort by clade-specific quantitative polymerase chain reaction. Findings in human cartilage were compared to those in cartilage from OA-susceptible C57BL/6 (B6) mice and OA-resistant MRL/MpJ (MRL) mice. Germ-free B6 mouse cartilage was analyzed as a methodologic control. RESULTS: Alpha diversity was reduced in human OA versus control samples (P < 0.0001), and in hip versus knee samples (P < 0.0001). Numerous clades were different in human OA versus control samples, and similar findings were noted in comparisons of murine B6 versus MRL mice. Hip samples were microbiologically distinct from knee samples. OA microbial DNA demonstrated increased gram-negative constituents (P = 0.02). Functional analysis demonstrated increases in lipopolysaccharide production (P = 9.9 × 10-3 ), phosphatidylinositol signaling (P = 4.2 × 10-4 ), and nitrogen metabolism (P = 8 × 10-3 ) and decreases in sphingolipid metabolism (P = 7.7 × 10-4 ) associated with OA. CONCLUSION: Our study reveals a microbial DNA signature in human and mouse cartilage. Alterations in this signature, including increases in gram-negative constituents, occur during the development and progression of human OA. Furthermore, our findings indicate that strain-specific signatures exist within mouse cartilage that mirror human patterns. Further study of the establishment and potential pathogenic role of these DNA signatures is needed.

Use of caseinophosphopeptides as natural antioxidants in oil-in-water emulsions.

Chelators are valuable ingredients used to improve the oxidative stability of food emulsions. Caseins and casein peptides have phosphoseryl residues capable of binding transition metals. Thus, the ability of enriched caseinophosphopeptides to inhibit lipid oxidation in corn oil-in-water emulsions was investigated. Enriched caseinophosphopeptides (25 microM) inhibited the formation of lipid oxidation at both pH 3.0 and 7.0 as determined by lipid hydroperoxides and hexanal. Calcium (0-100 mM) had no influence on the antioxidant activity of the enriched caseinophosphopeptides. Casein hydrolysates were more effective inhibitors of lipid oxidation than the enriched caseinophosphopeptides at equal phosphorus content. Thus, antioxidant properties might not be uniquely attributed to chelating metals by phosphoseryl residues but also by scavenging free radicals. Overall, the observed antioxidant activity of casein hydrolysates means they could be utilized to decrease oxidative rancidity in foods.