A systematic review and meta-analysis of the stability of peripheral immune markers in healthy adults.

Peripheral immune markers are widely used to predict risk for inflammatory disease. However, whether single assessments of inflammatory biomarkers represent stable individual differences remains unclear. We reviewed 50 studies (N = 48,674; 57 % male; mean age 54 (range 13-79) years) that assessed markers of inflammation on >1 occasion, with time between measures ranging from 24 h to 7+ years. Separate random effects meta-analyses were conducted for each inflammatory marker and time interval. Markers that had broad coverage across most time intervals included C-reactive protein (CRP; k = 37), interleukin (IL)-6 (k = 22), TNF-α (k = 10), and fibrinogen (Fg; k = 9). For CRP, IL-6, and TNF-α, stability estimates generally decreased with time, with strong to moderate stability over intervals <6 months (r's = 0.80-0.61), modest to moderate stability over 6 months - 3 years (r's = 0.60-0.51), and low stability for >3 years (r's = 0.39-0.30). Estimates were less reliable for Fg for time intervals ≤ 3 years although they generally followed the same pattern; more reliable findings suggested greater stability for Fg than other markers for intervals >3 years (r = 0.53). These findings suggest that single measures of inflammatory biomarkers may be an adequate index of stable individual differences in the short term (<6 months), with repeated measures of inflammatory biomarkers recommended over intervals ≥ 6 months to 3 years, and absolutely necessary over intervals >3 years to reliably identify stable individual differences in health risk. These findings are consistent with stability estimates and clinical recommendations for repeated measurement of other cardiovascular measures of risk (e.g., blood lipids, blood pressure).

Osteochondral Tissue Chip Derived From iPSCs: Modeling OA Pathologies and Testing Drugs.

Osteoarthritis (OA) is a chronic disease mainly characterized by degenerative changes in cartilage, but other joint elements such as bone are also affected. To date, there are no disease-modifying OA drugs (DMOADs), owing in part to a deficiency of current models in simulating OA pathologies and etiologies in humans. In this study, we aimed to develop microphysiological osteochondral (OC) tissue chips derived from human induced pluripotent stem cells (iPSCs) to model the pathologies of OA. We first induced iPSCs into mesenchymal progenitor cells (iMPCs) and optimized the chondro- and osteo-inductive conditions for iMPCs. Then iMPCs were encapsulated into photocrosslinked gelatin scaffolds and cultured within a dual-flow bioreactor, in which the top stream was chondrogenic medium and the bottom stream was osteogenic medium. After 28 days of differentiation, OC tissue chips were successfully generated and phenotypes were confirmed by real time RT-PCR and histology. To create an OA model, interleukin-1ß (IL-1ß) was used to challenge the cartilage component for 7 days. While under control conditions, the bone tissue promoted chondrogenesis and suppressed chondrocyte terminal differentiation of the overlying chondral tissue. Under conditions modeling OA, the bone tissue accelerated the degradation of chondral tissue which is likely via the production of catabolic and inflammatory cytokines. These findings suggest active functional crosstalk between the bone and cartilage tissue components in the OC tissue chip under both normal and pathologic conditions. Finally, a selective COX-2 inhibitor commonly prescribed drug for OA, Celecoxib, was shown to downregulate the expression of catabolic and proinflammatory cytokines in the OA model, demonstrating the utility of the OC tissue chip model for drug screening. In summary, the iPSC-derived OC tissue chip developed in this study represents a high-throughput platform applicable for modeling OA and for the screening and testing of candidate DMOADs.