Aging at the cellular level is a complex process resulting from accumulation of various damages leading to functional impairment and a reduced quality of life at the level of the organism. With a rise in the elderly population, the worldwide incidence of osteoporosis (OP) and osteoarthritis (OA) has increased in the past few decades. A decline in the number and “fitness” of mesenchymal stromal cells (MSCs) in the bone marrow (BM) niche has been suggested as one of the factors contributing to bone abnormalities in OP and OA. It is well recognized that MSCs in vitro acquire culture-induced aging features such as gradual telomere shortening, increased numbers of senescent cells, and reduced resistance to oxidative stress as a result of serial population doublings. In contrast, there is only limited evidence that human BM-MSCs “age” similarly in vivo. This review compares the various aspects of in vitro and in vivo MSC aging and suggests how our current knowledge on rejuvenating cultured MSCs could be applied to develop future strategies to target altered bone formation processes in OP and OA.

RA is a complex disease that develops as a series of events often referred to as disease continuum. RA would benefit from novel biomarker development for diagnosis where new biomarkers are still needed (even if progresses have been made with the inclusion of ACPA into the ACR/EULAR 2010 diagnostic criteria) and for prognostic notably in at risk of evolution patients with autoantibody-positive arthralgia. Risk biomarkers for rapid evolution or cardiovascular complications are also highly desirable. Monitoring biomarkers would be useful in predicting relapse. Finally, predictive biomarkers for therapy outcome would allow tailoring therapy to the individual. Increasing numbers of cytokines have been involved in RA pathology. Many have the potential as biomarkers in RA especially as their clinical utility is already established in other diseases and could be easily transferable to rheumatology. We will review the current knowledge’s relation to cytokine used as biomarker in RA. However, given the complexity and heterogeneous nature of RA, it is unlikely that a single cytokine may provide sufficient discrimination; therefore multiple biomarker signatures may represent more realistic approach for the future of personalised medicine in RA.

Immune age-related abnormalities may synergise with osteoarthritis (OA) pathology. We explored whether abnormalities in the blood immune cell composition are present in OA, beyond defects typically associated with ageing. Blood was collected from 121 healthy controls (HC) and 114 OA patients. Synovial biopsies were obtained from another 52 OA patients. Flow cytometry was used to establish the frequencies of lineage subsets, naïve, memory and regulatory T and B-cells, cells with an abnormal phenotype related to inflammation (IRC) and memory-like CD8(+) T-cells. Multivariate analysis of covariance (MANCOVA) was used to determine whether the relative subset frequencies differed between HC and OA, controlling for age. Expected histology and T/B-cell infiltration were observed. Following age adjusted analysis, we confirmed the lack of age association in HC for CD4(+), B, NK and NKT cells but a negative trend for CD8(+) T-cells. In OA, CD4(+) T-cell and B-cell frequency were lower compared to HC while CD8(+) T-cell frequencies were higher. CD8(+) memory-like cells were more likely to be found in OA (odds ratio = 15). Increased CD8(+) IRC frequencies were also present in OA. The relationship between age and CD4(+) or CD8(+) naïve T-cells in HC were changed in OA while the age relationships with memory cells were lost. The increase in CD4(+) Treg with age was also lost in OA. B-cells showed limited evidence of disturbance. Immune dysfunction may be present in OA beyond what appears related to ageing; this requires further investigation.

Beyond the joints, TNFi (tumour necrosis factor inhibitor) therapy may confer systemic benefits in rheumatoid arthritis (RA). Several studies have investigated the role of TNFi on insulin resistance/sensitivity (IR/IS). This question is of general interest given the emerging evidence linking inflammation and insulin resistance. The main aim of this review was to summarise the published data and to determine the effects of TNFi on IR/IS. We searched the PubMed and ISI Web of Knowledge databases for studies which examined the effects of TNFi on IR/IS. The studies were assessed independently by two reviewers according to a pre-specified protocol. The data on Homeostatic Model Assessment for Insulin resistance (HOMA) and Quantitative Insulin Sensitivity Check Index (QUICKI) were pooled and reported as standard difference in means (SDM) with 95% confidence interval (CI) using a random-effects model. A total of eight studies with 260 subjects met the selection criteria. The duration of the studies was from 8 weeks to 12 months. There was statistically significant reduction in HOMA index in six out of eight studies and four reported significant increment in QUICKI. The pooled analysis revealed significant reduction in HOMA [SDM-0.148, 95%CI[-0.278 to -0.017], p=0.026] and increment in QUICKI [SDM 0.312, 95%CI[0.019 to 0.606], p=0.037] with TNFi. There is emerging evidence to support that TNFi therapy improves IS and reduces IR in RA. Further, well conducted trials are needed to determine if such effects translate to lower incidence of diabetes in RA or other autoimmune conditions on biologic therapy.

Uncultured mesenchymal stromal cells (MSCs) are increasingly used in therapies; however, the effects of donor age on their biological characteristics and gene expression remain unclear. The aim of this study was to investigate age-related changes in bone marrow (BM) MSCs following minimal or no culture manipulation. Iliac crest BM was aspirated from 67 healthy donors (19-89 years old) and directly used for the colony-forming unit-fibroblast (CFU-F) assay or CD45^lowCD271⁺ cell enumeration. The colonies were analysed for colony area and integrated density (ID) when grown in standard MSC media or media supplemented with human serum from young (YS) or old (OS) donors. There was a notable age-related decline in the number of MSCs per millilitre of BM aspirate revealed by the CFU-F assay (r=−0.527, p<0.0001) or flow cytometry (r=−0.307, p=0.0116). Compared to young donors (19-40 years old), colony IDs were significantly lower in older donors (61-89 years old), particularly for smaller-sized colonies (42% lower, p<0.01). When cultured in media supplemented with OS, young and old donor MSCs formed colonies with lower IDs, by 21%, p<0.0001, and 27%, p<0.05, respectively, indicating the formation of smaller sparser colonies. No significant differences in the expression of selected adipogenic, osteogenic, stromal, and bone remodelling genes as well as CD295, CD146, CD106, and connexin 43 surface molecules were found in sorted CD45^lowCD271⁺ MSCs from young and old donors (n=8 donors each). Altogether, these results show similar trends for age-related decline in BM MSC numbers measured by the CFU-F assay and flow cytometry and reveal age-related effects of human serum on MSC colony formation. No significant differences in selected gene expression in uncultured CD45^lowCD271⁺ MSCs suggest that old donor MSCs may not be inferior in regard to their multipotential functions. Due to large donor-to-donor variation in all donor groups, our data indicate that an individual’s chronological age is not a reliable predictor of their MSC number or potency.

Objectives Anticitrullinated protein antibody (ACPA)+ individuals with non-specific musculoskeletal symptoms are at risk of inflammatory arthritis (IA). This study aims to demonstrate the predictive value of T cell subset quantification for progression towards IA and compare it with previously identified clinical predictors of progression. Methods 103 ACPA+ individuals without clinical synovitis were observed 3-monthly for 12 months and then as clinically indicated. The end point was the development of IA. Naïve, regulatory T cells (Treg) and inflammation related cells (IRCs) were quantified by flow cytometry. Areas under the ROC curve (AUC) were calculated. Adjusted logistic regressions and Cox proportional hazards models for time to progression to IA were constructed. Results Compared with healthy controls (age adjusted where appropriate), ACPA+ individuals demonstrated reduced naïve (22.1% of subjects) and Treg (35.8%) frequencies and elevated IRC (29.5%). Of the 103 subjects, 48(46.6%) progressed. Individually, T cell subsets were weakly predictive (AUC between 0.63 and 0.66), although the presence of 2 T cell abnormalities had high specificity. Three models were compared: model-1 used T cell subsets only, model-2 used previously published clinical parameters, model-3 combined clinical data and T cell data. Model-3 performed the best (AUC 0.79 (95% CI 0.70 to 0.89)) compared with model-1 (0.75 (0.65 to 0.86)) and particularly with model-2 (0.62 (0.54 to 0.76)) demonstrating the added value of T cell subsets. Time to progression differed significantly between high-risk, moderate-risk and low-risk groups from model-3 (p=0.001, median 15.4 months, 25.8 months and 63.4 months, respectively). Conclusions T cell subset dysregulation in ACPA+ individuals predates the onset of IA, predicts the risk and faster progression to IA, with added value over previously published clinical predictors of progression.