Bovine liver slices combined with an androgen transcriptional activation assay: an in-vitro model to study the metabolism and bioactivity of steroids

Previously we described the properties of a rapid and robust yeast androgen bioassay for detection of androgenic anabolic compounds, validated it, and showed its added value for several practical applications. However, biotransformation of potent steroids into inactive metabolites, or vice versa, is not included in this screening assay. Within this context, animal-friendly in-vitro cellular systems resembling species-specific metabolism can be of value. We therefore investigated the metabolic capacity of precision-cut slices of bovine liver using 17β-testosterone (T) as a model compound, because this is an established standard compound for assessing the metabolic capacity of such cellular systems. However, this is the first time that slice metabolism has been combined with bioactivity measurements. Moreover, this study also involves bioactivation of inactive prohormones, for example dehydroepiandrosterone (DHEA) and esters of T, and although medium extracts are normally analyzed by HPLC, here the metabolites formed were identified with more certainty by ultra-performance liquid chromatography time-of-flight mass spectrometry (UPLC–TOFMS) with accurate mass measurement. Metabolism of T resulted mainly in the formation of the less potent phase I metabolites 4-androstene-3,17-dione (4-AD), the hydroxy-T metabolites 6α, 6β, 15β, and 16α-OH-T, and the phase II metabolite T-glucuronide. As a consequence the overall androgenic activity, as determined by the yeast androgen bioassay, decreased. In order to address the usefulness of bovine liver slices for activation of inactive steroids, liver slices were exposed to DHEA and two esters of T. This resulted in an increase of androgenic activity, because of the formation of 4-AD and T

The genetic epidemiology of joint shape and the development of osteoarthritis

Congruent, low-friction relative movement between the articulating elements of a synovial joint is an essential pre-requisite for sustained, efficient, function. Where disorders of joint formation or maintenance exist, mechanical overloading and osteoarthritis (OA) follow. The heritable component of OA accounts for ~ 50% of susceptible risk. Although almost 100 genetic risk loci for OA have now been identified, and the epidemiological relationship between joint development, joint shape and osteoarthritis is well established, we still have only a limited understanding of the contribution that genetic variation makes to joint shape and how this modulates OA risk. In this article, a brief overview of synovial joint development and its genetic regulation is followed by a review of current knowledge on the genetic epidemiology of established joint shape disorders and common shape variation. A summary of current genetic epidemiology of OA is also given, together with current evidence on the genetic overlap between shape variation and OA. Finally, the established genetic risk loci for both joint shape and osteoarthritis are discussed

Novel diagnostic DNA methylation episignatures expand and refine the epigenetic landscapes of Mendelian disorders.

Overlapping clinical phenotypes and an expanding breadth and complexity of genomic associations are a growing challenge in the diagnosis and clinical management of Mendelian disorders. The functional consequences and clinical impacts of genomic variation may involve unique, disorder-specific, genomic DNA methylation episignatures. In this study, we describe 19 novel episignature disorders and compare the findings alongside 38 previously established episignatures for a total of 57 episignatures associated with 65 genetic syndromes. We demonstrate increasing resolution and specificity ranging from protein complex, gene, sub-gene, protein domain, and even single nucleotide-level Mendelian episignatures. We show the power of multiclass modeling to develop highly accurate and disease-specific diagnostic classifiers. This study significantly expands the number and spectrum of disorders with detectable DNA methylation episignatures, improves the clinical diagnostic capabilities through the resolution of unsolved cases and the reclassification of variants of unknown clinical significance, and provides further insight into the molecular etiology of Mendelian conditions