Osteomodulin

Abstract: Exposure to microgravity causes bone loss in humans, and the underlying mechanism is thought to be at least partially due to a decrease in bone formation by osteoblasts. In the present study, we examined the hypothesis that microgravity changes osteoblast gene expression profiles, resulting in bone loss. For this study, we developed an in vitro system that simulates microgravity using the Random Positioning Machine (RPM) to study the effects of microgravity on 2T3 preosteoblast cells grown in gas-permeable culture disks. Exposure of 2T3 cells to simulated microgravity using the RPM for up to 9 days significantly inhibited alkaline phosphatase activity, recapitulating a bone loss response that occurs in real microgravity conditions without altering cell proliferation and shape. Next, we performed DNA microarray analysis to determine the gene expression profile of 2T3 cells exposed to 3 days of simulated microgravity. Among 10,000 genes examined using the microarray, 88 were downregulated and 52 were upregulated significantly more than twofold using simulated microgravity compared with the static 1-g condition. We then verified the microarray data for some of the genes relevant in bone biology using real-time PCR assays and immunoblotting. We confirmed that microgravity downregulated levels of alkaline phosphatase, runt-related transcription factor 2, osteomodulin, and parathyroid hormone receptor 1 mRNA; upregulated cathepsin K mRNA; and did not significantly affect bone morphogenic protein 4 and cystatin C protein levels. The identification of gravisensitive genes provides useful insight that may lead to further hypotheses regarding their roles in not only microgravity-induced bone loss but also the general patient population with similar pathological conditions, such as osteoporosis.

Abstract: Purpose Small leucine rich proteoglycans (SLRPs) constitute a family of secreted proteoglycans that are important for collagen fibrillogenesis, cellular growth, differentiation, and migration. Ten of the 13 known members of the SLRP gene family are arranged in tandem clusters on human chromosomes 1, 9, and 12. Their syntenic equivalents are on mouse chromosomes 1, 13, and 10, and rat chromosomes 13, 17, and 7. The purpose of this study was to determine whether there is evidence for control elements, which could regulate the expression of these clusters coordinately. Methods Promoters were identified using a comparative genomics approach and Genomatix software tools. For each gene a set of human, mouse, and rat orthologous promoters was extracted from genomic sequences. Transcription factor (TF) binding site analysis combined with a literature search was performed using MatInspector and Genomatix' BiblioSphere. Inspection for the presence of interspecies conserved scaffold/matrix attachment regions (S/MARs) was performed using ElDorado annotation lists. DNAseI hypersensitivity assay, chromatin immunoprecipitation (ChIP), and transient transfection experiments were used to validate the results from bioinformatics analysis. Results Transcription factor binding site analysis combined with a literature search revealed co-citations between several SLRPs and TFs Runx2 and IRF1, indicating that these TFs have potential roles in transcriptional regulation of the SLRP family members. We therefore inspected all of the SLRP promoter sets for matches to IRF factors and Runx factors. Positionally conserved binding sites for the Runt domain TFs were detected in the proximal promoters of chondroadherin (CHAD) and osteomodulin (OMD) genes. Two significant models (two or more transcription factor binding sites arranged in a defined order and orientation within a defined distance range) were derived from these initial promoter sets, the HOX-Runx (homeodomain-Runt domain), and the ETS-FKHD-STAT (erythroblast transformation specific-forkhead-signal transducers and activators of transcription) models. These models were used to scan the genomic sequences of all 13 SLRP genes. The HOX-Runx model was found within the proximal promoter, exon 1, or intron 1 sequences of 11 of the 13 SLRP genes. The ETS-FKHD-STAT model was found in only 5 of these genes. Transient transfections of MG-63 cells and bovine corneal keratocytes with Runx2 isoforms confirmed the relevance of these TFs to expression of several SLRP genes. Distribution of the HOX-Runx and ETS-FKHD-STAT models within 200 kb of genomic sequence on human chromosome 9 and 500 kb sequence on chromosome 12 also were analyzed. Two regions with 3 HOX-Runx matches within a 1,000 bp window were identified on human chromosome 9; one located between OMD and osteoglycin (OGN)/mimecan genes, and the second located upstream of the putative extracellular matrix protein 2 (ECM2) promoter. The intergenic region between OMD and mimecan was shown to coincide with different patterns of DNAse I hypersensitivity sites in MG-63 and U937 cells. ChiP analysis revealed that this region binds Runx2 in U937 cells (mimecan transcript note detectable), but binds Pitx3 in MG-63 cells (expressing high level of mimecan), thereby demonstrating its functional association with mimecan expression. Upon comparing the predictions of S/MARs on the relevant chromosomal context of human chromosomes 9 and 12 and their rodent equivalents, no convincing evidence was found that the tandemly arranged genes build a chromosomal loop. Conclusions Twelve of 13 known SLRP genes have at least one HOX-Runx module match in their promoter, exon 1, intron 1, or intergenic region. Although these genes are located in different clusters on different chromosomes, the common HOX-Runx module could be the basis for co-regulated expression.

Abstract: Background Parkinson’s disease (PD) is a progressive neurodegenerative disease affecting about 5 million people worldwide with no disease-modifying therapies. We sought blood-based biomarkers in order to provide molecular characterization of individuals with PD for diagnostic confirmation and prediction of progression. Methods and findings In 141 plasma samples (96 PD, 45 neurologically normal control [NC] individuals; 45.4% female, mean age 70.0 years) from a longitudinally followed Discovery Cohort based at the University of Pennsylvania (UPenn), we measured levels of 1,129 proteins using an aptamer-based platform. We modeled protein plasma concentration (log10 of relative fluorescence units [RFUs]) as the effect of treatment group (PD versus NC), age at plasma collection, sex, and the levodopa equivalent daily dose (LEDD), deriving first-pass candidate protein biomarkers based on p-value for PD versus NC. These candidate proteins were then ranked by Stability Selection. We confirmed findings from our Discovery Cohort in a Replication Cohort of 317 individuals (215 PD, 102 NC; 47.9% female, mean age 66.7 years) from the multisite, longitudinally followed National Institute of Neurological Disorders and Stroke Parkinson’s Disease Biomarker Program (PDBP) Cohort. Analytical approach in the Replication Cohort mirrored the approach in the Discovery Cohort: each protein plasma concentration (log10 of RFU) was modeled as the effect of group (PD versus NC), age at plasma collection, sex, clinical site, and batch. Of the top 10 proteins from the Discovery Cohort ranked by Stability Selection, four associations were replicated in the Replication Cohort. These blood-based biomarkers were bone sialoprotein (BSP, Discovery false discovery rate [FDR]-corrected p = 2.82 × 10−2, Replication FDR-corrected p = 1.03 × 10−4), osteomodulin (OMD, Discovery FDR-corrected p = 2.14 × 10−2, Replication FDR-corrected p = 9.14 × 10−5), aminoacylase-1 (ACY1, Discovery FDR-corrected p = 1.86 × 10−3, Replication FDR-corrected p = 2.18 × 10−2), and growth hormone receptor (GHR, Discovery FDR-corrected p = 3.49 × 10−4, Replication FDR-corrected p = 2.97 × 10−3). Measures of these proteins were not significantly affected by differences in sample handling, and they did not change comparing plasma samples from 10 PD participants sampled both on versus off dopaminergic medication. Plasma measures of OMD, ACY1, and GHR differed in PD versus NC but did not differ between individuals with amyotrophic lateral sclerosis (ALS, n = 59) versus NC. In the Discovery Cohort, individuals with baseline levels of GHR and ACY1 in the lowest tertile were more likely to progress to mild cognitive impairment (MCI) or dementia in Cox proportional hazards analyses adjusting for age, sex, and disease duration (hazard ratio [HR] 2.27 [95% CI 1.04–5.0, p = 0.04] for GHR, and HR 3.0 [95% CI 1.24–7.0, p = 0.014] for ACY1). GHR’s association with cognitive decline was confirmed in the Replication Cohort (HR 3.6 [95% CI 1.20–11.1, p = 0.02]). The main limitations of this study were its reliance on the aptamer-based platform for protein measurement and limited follow-up time available for some cohorts. Conclusions In this study, we found that the blood-based biomarkers BSP, OMD, ACY1, and GHR robustly associated with PD across multiple clinical sites. Our findings suggest that biomarkers based on a peripheral blood sample may be developed for both disease characterization and prediction of future disease progression in PD.

Abstract: Osteomodulin (OMD), a member of the small leucine-rich proteoglycan family, distributes in mineralized tissues and is positively regulated by bone morphogenetic protein 2 (BMP2) However, the exact function of OMD during mineralization and its association with BMP2 remain poorly understood Herein, the expression pattern of OMD during osteogenesis was investigated in human dental pulp stem cells Silencing OMD gene significantly suppressed the alkaline phosphatase activity, mineralized nodule formation and osteogenesis-associated gene transcription Besides, OMD could enhance BMP2-induced expression of SP7 and RUNX2 with concentration dependence in vitro Rat mandibular bone defect model revealed that scaffolds injected with the combination of OMD and suboptimal BMP2 exhibited more mature and abundant mineralized bone than that treated with OMD or suboptimal BMP2 alone Mechanistically, OMD could bind to BMP2 via its terminal leucine-rich repeats and formed complexes with BMP2 and its membrane receptors, thus promoting BMP/SMAD signal transduction In addition, OMD was a putative target gene of SMAD4, which plays a pivotal role in this pathway Collectively, these data elucidate that OMD may act as a positive coordinator in osteogenesis through BMP2/SMADs signaling