Phosphodiesterase 10A Is a Mediator of Osteogenic Differentiation and Mechanotransduction in Bone Marrow-Derived Mesenchymal Stromal Cells

Differential Effects of PTH (1-34), PTHrP (1-36), and Abaloparatide on the Murine Osteoblast Transcriptome

Teriparatide (PTH (1-34)), PTHrP (1-36), and abaloparatide (ABL) have been used for the treatment of osteoporosis, but their efficacy long term is significantly limited. The 3 peptides exert time- and dose-dependent differential responses in osteoblasts, leading us to hypothesize they may also differentially modulate the osteoblast transcriptome. Treatment of mouse calvarial osteoblasts with 1 nM of the peptides for 4 hours results in RNA sequencing data with PTH (1-34) regulating 367 genes, including 194 unique genes; PTHrP (1-36) regulating 117 genes, including 15 unique genes; and ABL regulating 179 genes, including 20 unique genes. There were 83 genes shared among all 3 peptides. Gene ontology analyses showed similarities in Wnt signaling, cAMP-mediated signaling, ossification, but differences in morphogenesis of a branching structure in biological processes; receptor ligand activity, transcription factor activity, and cytokine receptor/binding activity in molecular functions. The peptides increased Vdr, Cited1, and Pde10a messenger RNAs (mRNAs) in a pattern similar to Rankl, that is, PTH (1-34) greater than ABL greater than PTHrP (1-36). mRNA abundance of other genes, including Wnt4, Wnt7, Wnt11, Sfrp4, Dkk1, Kcnk10, Hdac4, Epn3, Tcf7, Crem, Fzd5, Ppp2r2a, and Dvl3, showed that some genes were regulated similarly by all 3 peptides; others were not. Finally, small interfering RNA knockdowns of SIK1/2/3 and CRTC1/2/3 in PTH (1-34)-treated cells revealed that Vdr and Wnt4 genes are regulated by salt-inducible kinases (SIKs) and CREB-regulated transcriptional coactivators (CRTCs), while others are not. Although many studies have examined PTH signaling in the osteoblast/osteocyte, ours is the first to compare the global effects of these peptides on the osteoblast transcriptome or to analyze the roles of the SIKs and CRTCs.

Mechanoresponsive regulation of fibroblast-to-myofibroblast transition in three-dimensional tissue analogues: mechanical strain amplitude dependency of fibrosis

The spatiotemporal interaction and constant iterative feedback between fibroblasts, extracellular matrix, and environmental cues are central for investigating the fibroblast-induced musculoskeletal tissue regeneration and fibroblast-to-myofibroblast transition (FMT). In this study, we created a fibroblast-laden 3D tissue analogue to study (1) how mechanical loading exerted on three-dimensional (3D) tissues affected the residing fibroblast phenotype and (2) to identify the ideal mechanical strain amplitude for promoting tissue regeneration without initiating myofibroblast differentiation. We applied uniaxial tensile strain (0, 4, 8, and 12%) to the cell-laden 3D tissue analogues to understand the interrelation between the degree of applied mechanical loading amplitudes and FMT. Our data demonstrated that 4% mechanical strain created an anabolic effect toward tissue regeneration, but higher strain amplitudes over-stimulated the cells and initiated fibrotic tissue formation. Under increased mechanical strain amplitudes, fibroblasts were activated from a homeostatic state to a proto-myofibroblast state which resulted in increased cellularity accompanied by increased expressions of extracellular matrix (ECM) components, activation stressors (TGF-β1 and TGF-βR1), and profibrotic markers. This further transformed fibroblasts into α-smooth muscle actin expressing myofibroblasts. Understanding the interplay between the applied degree of mechanical loading exerted on 3D tissues and residing fibroblast phenotypic response is important to identify specific mechanomodulatory approaches for tissue regeneration and the informed mechanotherapy-guided tissue healing strategies.

Identification of novel off targets of baricitinib and tofacitinib by machine learning with a focus on thrombosis and viral infection

As there are no clear on-target mechanisms that explain the increased risk for thrombosis and viral infection or reactivation associated with JAK inhibitors, the observed elevated risk may be a result of an off-target effect. Computational approaches combined with in vitro studies can be used to predict and validate the potential for an approved drug to interact with additional (often unwanted) targets and identify potential safety-related concerns. Potential off-targets of the JAK inhibitors baricitinib and tofacitinib were identified using two established machine learning approaches based on ligand similarity. The identified targets related to thrombosis or viral infection/reactivation were subsequently validated using in vitro assays. Inhibitory activity was identified for four drug-target pairs (PDE10A [baricitinib], TRPM6 [tofacitinib], PKN2 [baricitinib, tofacitinib]). Previously unknown off-target interactions of the two JAK inhibitors were identified. As the proposed pharmacological effects of these interactions include attenuation of pulmonary vascular remodeling, modulation of HCV response, and hypomagnesemia, the newly identified off-target interactions cannot explain an increased risk of thrombosis or viral infection/reactivation. While further evidence is required to explain both the elevated thrombosis and viral infection/reactivation risk, our results add to the evidence that these JAK inhibitors are promiscuous binders and highlight the potential for repurposing.