ObjectivesDietary interventions are a potentially powerful treatment option for knee osteoarthritis (OA). The objective of this study was to evaluate a well‐formulated ketogenic diet (KD) in the context of knee OA histology and pain using the destabilization of the medial meniscus (DMM) mouse model and correlate with gut microbiome and systemic cytokine levels.MethodsAdult male mice underwent unilateral DMM or sham surgery and were then fed eight weeks of KD or chow. At baseline and every two weeks, mechanical allodynia of the operated and contralateral knees was assessed via analgesiometry. Knee joints were collected for histology, gut microbiome analysis was performed on cecal material via 16S sequencing, and serum cytokines were analyzed via Bio‐Plex assay.ResultsKD mice had worse histopathologic OA after DMM (mean ± SEM Osteoarthritis Research Society International score: KD‐DMM: 4.0 ± 0.5 vs chow‐DMM: 2.7 ± 0.08; P = 0.02). KD mice had increased mechanical allodynia postsurgery (P = 0.005 in mixed‐effects model). The gut microbiome changed substantially with KD: 59 clades were altered by KD in DMM and 39 by KD in sham (36 were shared, 25 overlapped with previous murine OA studies). Several clades were correlated on an individual‐mouse level with both histology and allodynia (eg, Lactobacillus histology P = 0.004, allodynia P = 1 × 10−4). Serum analysis showed four cytokines increased with KD (interleukin [IL]‐1β, IL‐2, IL‐3, and IL‐13).ConclusionKD started immediately after OA induction via DMM is associated with worsened histologic outcomes. KD also worsens mechanical allodynia after either DMM or sham surgery. KD induces significant gut microbiome dysbiosis in clades previously associated with murine OA.

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.

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.

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. image

ObjectiveThe 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.MethodsGenome‐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).ResultsFull 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]).ConclusionOur 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.image

Purpose: Knee osteoarthritis (OA) is a heterogeneous disease characterized by a variety of clinical and molecular phenotypes. However, we do not yet have robust biomarkers to distinguish/predict these phenotypes. We previously published a pilot analysis of baseline peripheral blood cell DNA methylation patterns as biomarkers of future radiographic progression which was defined as an increase of ≥1 Kellgren-Lawrence Grade in the index between two visits. In the current study, we expand upon this methodology and apply it to the Johnston County Osteoarthritis Project (JoCoOA), targeting specific epigenetic regions for model development.

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 (Δβ 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.