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

Tendon is a simple aligned fibre composite, consisting of collagen-rich fascicles surrounded by a softer interfascicular matrix (IFM). The composition and interactions between these material phases are fundamental in ensuring tissue mechanics meet functional requirements. However the IFM is poorly defined, therefore tendon structure-function relationships are incompletely understood. We hypothesised that the IFM has a more complex proteome, with faster turnover than the fascicular matrix (FM). Using laser-capture microdissection and mass spectrometry, we demonstrate that the IFM contains more proteins and that many proteins show differential abundance between matrix phases. The IFM contained more protein fragments (neopeptides), indicating greater matrix degradation in this compartment, which may act to maintain healthy tendon structure. Protein abundance did not alter with ageing, but neopeptide numbers decreased in the aged IFM, indicating decreased turnover which may contribute to age-related tendon injury. These data provide important insights into how differences in tendon composition and turnover contribute to tendon structure-function relationships and the effects of ageing.

Energy storing tendons, such as the human Achilles and equine superficial digital flexor tendon (SDFT), are highly prone to injury, the incidence of which increases with aging. The cellular and molecular mechanisms that result in increased injury in aged tendons are not well established but are thought to result in altered matrix turnover. However, little attempt has been made to fully characterize the tendon proteome nor determine how the abundance of specific tendon proteins changes with aging and/or injury. The aim of this study was, therefore, to assess the protein profile of normal SDFTs from young and old horses using label-free relative quantification to identify differentially abundant proteins and peptide fragments between age groups. The protein profile of injured SDFTs from young and old horses was also assessed. The results demonstrate distinct proteomic profiles in young and old tendon, with alterations in the levels of proteins involved in matrix organization and regulation of cell tension. Furthermore, we identified several new peptide fragments (neopeptides) present in aged tendons, suggesting that there are age-specific cleavage patterns within the SDFT. Proteomic profile also differed between young and old injured tendon, with a greater number of neopeptides identified in young injured tendon. This study has increased the knowledge of molecular events associated with tendon aging and injury, suggesting that maintenance and repair of tendon tissue may be reduced in aged individuals and may help to explain why the risk of injury increases with aging.

Introduction: Age is an important factor in the development of osteoarthritis. Microarray studies provide insight into cartilage aging but do not reveal the full transcriptomic phenotype of chondrocytes such as small noncoding RNAs, pseudogenes, and microRNAs. RNA-Seq is a powerful technique for the interrogation of large numbers of transcripts including nonprotein coding RNAs. The aim of the study was to characterise molecular mechanisms associated with age-related changes in gene signatures. Methods: RNA for gene expression analysis using RNA-Seq and real-time PCR analysis was isolated from macroscopically normal cartilage of the metacarpophalangeal joints of eight horses; four young donors (4 years old) and four old donors (>15 years old). RNA sequence libraries were prepared following ribosomal RNA depletion and sequencing was undertaken using the Illumina HiSeq 2000 platform. Differentially expressed genes were defined using Benjamini-Hochberg false discovery rate correction with a generalised linear model likelihood ratio test (P < 0.05, expression ratios ± 1.4 log₂ fold-change). Ingenuity pathway analysis enabled networks, functional analyses and canonical pathways from differentially expressed genes to be determined. Results: In total, the expression of 396 transcribed elements including mRNAs, small noncoding RNAs, pseudogenes, and a single microRNA was significantly different in old compared with young cartilage (± 1.4 log₂ fold-change, P < 0.05). Of these, 93 were at higher levels in the older cartilage and 303 were at lower levels in the older cartilage. There was an over-representation of genes with reduced expression relating to extracellular matrix, degradative proteases, matrix synthetic enzymes, cytokines and growth factors in cartilage derived from older donors compared with young donors. In addition, there was a reduction in Wnt signalling in ageing cartilage. Conclusion: There was an age-related dysregulation of matrix, anabolic and catabolic cartilage factors. This study has increased our knowledge of transcriptional networks in cartilage ageing by providing a global view of the transcriptome.

Introduction: The risk of tendon injury and disease increases significantly with increasing age. The aim of the study was to characterise transcriptional changes in human Achilles tendon during the ageing process in order to identify molecular signatures that might contribute to age-related degeneration. Methods: RNA for gene expression analysis using RNA-Seq and quantitative real-time polymerase chain reaction analysis was isolated from young and old macroscopically normal human Achilles tendon. RNA sequence libraries were prepared following ribosomal RNA depletion, and sequencing was undertaken by using the Illumina HiSeq 2000 platform. Expression levels among genes were compared by using fragments per kilobase of exon per million fragments mapped. Differentially expressed genes were defined by using Benjamini-Hochberg false discovery rate approach (P <0.05, expression ratios 1.4 log₂ fold change). Alternative splicing of exon variants were also examined by using Cufflinks. The functional significance of genes that showed differential expression between young and old tendon was determined by using ingenuity pathway analysis. Results: In total, the expression of 325 transcribed elements, including protein-coding transcripts and non-coding transcripts (small non-coding RNAs, pseudogenes, long non-coding RNAs and a single microRNA), was significantly different in old compared with young tendon (±1.4 log₂ fold change, P <0.05). Of these, 191 were at higher levels in older tendon and 134 were at lower levels in older tendon. The top networks for genes differentially expressed with tendon age were from cellular function, cellular growth, and cellular cycling pathways. Notable differential transcriptome changes were also observed in alternative splicing patterns. Several of the top gene ontology terms identified in downregulated isoforms in old tendon related to collagen and post-translational modification of collagen. Conclusions: This study demonstrates dynamic alterations in RNA with age at numerous genomic levels, indicating changes in the regulation of transcriptional networks. The results suggest that ageing is not primarily associated with loss of ability to synthesise matrix proteins and matrix-degrading enzymes. In addition, we have identified non-coding RNA genes and differentially expressed transcript isoforms of known matrix components with ageing which require further investigation.