Human Osteochondral Explants: Reliable Biomimetic Models to Investigate Disease Mechanisms and Develop Personalized Treatments for Osteoarthritis.

INTRODUCTION: Likely due to ignored heterogeneity in disease pathophysiology, osteoarthritis (OA) has become the most common disabling joint disease, without effective disease-modifying treatment causing a large social and economic burden. In this study we set out to explore responses of aged human osteochondral explants upon different OA-related perturbing triggers (inflammation, hypertrophy and mechanical stress) for future tailored biomimetic human models. METHODS: Human osteochondral explants were treated with IL-1ß (10 ng/ml) or triiodothyronine (T3; 10 nM) or received 65% strains of mechanical stress (65% MS). Changes in chondrocyte signalling were determined by expression levels of nine genes involved in catabolism, anabolism and hypertrophy. Breakdown of cartilage was measured by sulphated glycosaminoglycans (sGAGs) release, scoring histological changes (Mankin score) and mechanical properties of cartilage. RESULTS: All three perturbations (IL-1ß, T3 and 65% MS) resulted in upregulation of the catabolic genes MMP13 and EPAS1. IL-1ß abolished COL2A1 and ACAN gene expression and increased cartilage degeneration, reflected by increased Mankin scores and sGAGs released. Treatment with T3 resulted in a high and significant upregulation of the hypertrophic markers COL1A1, COL10A1 and ALPL. However, 65% MS increased sGAG release and detrimentally altered mechanical properties of cartilage. CONCLUSION: We present consistent and specific output on three different triggers of OA. Perturbation with the pro-inflammatory IL-1ß mainly induced catabolic chondrocyte signalling and cartilage breakdown, while T3 initiated expression of hypertrophic and mineralization markers. Mechanical stress at a strain of 65% induced catabolic chondrocyte signalling and changed cartilage matrix integrity. The major strength of our ex vivo models was that they considered aged, preserved, human cartilage of a heterogeneous OA patient population. As a result, the explants may reflect a reliable biomimetic model prone to OA onset allowing for development of different treatment modalities.

The Genome of the Netherlands: design, and project goals.

Within the Netherlands a national network of biobanks has been established (Biobanking and Biomolecular Research Infrastructure-Netherlands (BBMRI-NL)) as a national node of the European BBMRI. One of the aims of BBMRI-NL is to enrich biobanks with different types of molecular and phenotype data. Here, we describe the Genome of the Netherlands (GoNL), one of the projects within BBMRI-NL. GoNL is a whole-genome-sequencing project in a representative sample consisting of 250 trio-families from all provinces in the Netherlands, which aims to characterize DNA sequence variation in the Dutch population. The parent-offspring trios include adult individuals ranging in age from 19 to 87 years (mean=53 years; SD=16 years) from birth cohorts 1910-1994. Sequencing was done on blood-derived DNA from uncultured cells and accomplished coverage was 14-15x. The family-based design represents a unique resource to assess the frequency of regional variants, accurately reconstruct haplotypes by family-based phasing, characterize short indels and complex structural variants, and establish the rate of de novo mutational events. GoNL will also serve as a reference panel for imputation in the available genome-wide association studies in Dutch and other cohorts to refine association signals and uncover population-specific variants. GoNL will create a catalog of human genetic variation in this sample that is uniquely characterized with respect to micro-geographic location and a wide range of phenotypes. The resource will be made available to the research and medical community to guide the interpretation of sequencing projects. The present paper summarizes the global characteristics of the project.

Lipid metabolism in long-lived families: the Leiden Longevity Study.

Mechanisms underlying the variation in human life expectancy are largely unknown, but lipid metabolism and especially lipoprotein size was suggested to play an important role in longevity. We have performed comprehensive lipid phenotyping in the Leiden Longevity Study (LLS). By applying multiple logistic regression analysis we tested for the first time the effects of parameters in lipid metabolism (i.e., classical serum lipids, lipoprotein particle sizes, and apolipoprotein E levels) on longevity independent of each other. Parameters in lipid metabolism were measured in offspring of nonagenarian siblings from 421 families of the LLS (n = 1,664; mean age, 59 years) and in the partners of the offspring as population controls (n = 711; mean age, 60 years). In the initial model, where lipoprotein particles sizes, classical serum lipids and apolipoprotein E were included, offspring had larger low-density lipoprotein (LDL) particle sizes (p = 0.017), and lower triglyceride levels (p = 0.026), indicating that they displayed a more beneficial lipid profile. After backwards regression only LDL size (p = 0.014) and triglyceride levels (p = 0.05) were associated with offspring from long-lived families. Sex-specific backwards regression analysis revealed that LDL particle sizes were associated with male longevity (increase in log odds ratio (OR) per unit = 0.21; p = 0.023). Triglyceride levels (decrease OR per unit = 0.22; p = 0.01), but not LDL particle size, were associated with female longevity. Due to the analysis of a comprehensive lipid profile, we confirmed an important role of lipid metabolism in human longevity, with LDL size and triglyceride levels as major predicting factors.