Jason R. Maher

Heavy metal lead exposure, osteoporotic-like phenotype in an animal model, and depression of Wnt signaling.

Background: Exposure to lead (Pb) from environmental and industrial sources remains an overlooked serious public health risk. Elucidating the effect of Pb on bone cell function is therefore critical for understanding its risk associated with diseases of low bone mass. Objectives: We tested the hypothesis that Pb negatively affects bone mass. We also assessed the underlying mechanisms of Pb on bone signaling pathways. Methods: We used a model of low-level Pb exposure in a rodent beginning before conception and continuing over 18 months. We characterized the effect of Pb on bone quality using dual-energy X-ray absorptiometry (DXA), micro-computed tomography, Raman spectroscopy, and histology. We assessed the effect of Pb on bone and adipocyte formation by mineral deposition, lipid droplet formation, and Western blot and RNA analysis. Results: Pb-exposed animals had decreased bone mass that resulted in bones that were more susceptible to fracture. Pb decreased osteoblastic cell number leading to a depression of bone formation. Accompanying this, Pb exposure elevated sclerostin protein levels in the skeleton, and correspondingly reduced levels of β-catenin and Runx2 in stromal precursor cells. Pb also increased skeletal expression of peroxisome proliferator-activated receptor-γ (PPAR-γ). These results indicate a shift in mesenchymal differentiation wherein Pb promoted enhanced adipogenesis and decreased osteoblastogenesis. Substantial differences in bone marrow composition were observed, highlighted by an increase in adipocytes. Conclusions: The disruption Pb has on bone mass and bone homeostasis is principally explained by inhibition of the Wnt/β-catenin pathway, which may provide a molecular basis for novel therapeutic strategies to combat Pb-induced bone pathologies.

Determination of Ideal Offset for Spatially Offset Raman Spectroscopy

A key design parameter in spatially offset Raman spectroscopy (SORS) is the choice of offset distance between the illumination and collection areas. To investigate this choice, we performed SORS measurements on a simple two-layer chemical phantom. We show that while the SORS ratio, or the ratio of signal from the bottom layer to the top layer, monotonically increases with spatial offset, the signal-to-noise ratio (SNR) does not. Specifically, we show that there exists a specific spatial offset that yields the best SNR for signal originating in the bottom layer of a two-layer sample. We also show that this SNR-optimal offset depends upon the strength of the particular Raman band. This work presents the considerations that should be taken into account when designing optical probes for use in SORS.

Mechanisms of bone fragility in a mouse model of glucocorticoid-treated rheumatoid arthritis: Implications for insufficiency fracture risk

OBJECTIVE Glucocorticoid (GC) therapy is associated with increased risk of fracture in patients with rheumatoid arthritis (RA). To elucidate the cause of this increased risk, we examined the effects of chronic erosive inflammatory arthritis and GC treatment on bone quality, structure, and biomechanical properties in a murine model. METHODS Mice with established arthritis and expressing human tumor necrosis factor α (TNFα) transgene (Tg) and their wild-type (WT) littermates were continually treated with GC (prednisolone 5 mg/kg/day via subcutaneous controlled-release pellet) or placebo for 14, 28, or 42 days. Microstructure, biomechanical properties, chemical composition, and morphology of the tibiae and lumbar vertebral bodies were assessed by micro-computed tomography, biomechanical testing, Raman spectroscopy, and histology, respectively. Serum markers of bone turnover were also determined. RESULTS TNF-Tg and GC treatment additively decreased mechanical strength and stiffness in both the tibiae and the vertebral bodies. GC treatment in the TNF-Tg mice increased the ductility of tibiae under torsional loading. These changes were associated with significant alterations in the biochemical and structural composition of the mineral and organic components of the bone matrix, a decrease in osteoblast activity and bone formation, and an increase in osteoclast activity. CONCLUSION Our findings indicate that the concomitant decrease in bone strength and increase in bone ductility associated with chronic inflammation and GC therapy, coupled with the significant changes in the bone quality and structure, may increase the susceptibility of the bone to failure under low-energy loading. This may explain the mechanism of symptomatic insufficiency fractures in patients with RA receiving GC therapy who do not have radiographic manifestations of fracture.

Raman spectroscopy detects deterioration in biomechanical properties of bone in a glucocorticoid-treated mouse model of rheumatoid arthritis

Although glucocorticoids are frequently prescribed for the symptomatic management of inflammatory disorders such as rheumatoid arthritis, extended glucocorticoid exposure is the leading cause of physician-induced osteoporosis and leaves patients at a high risk of fracture. To study the biochemical effects of glucocorticoid exposure and how they might affect biomechanical properties of the bone, Raman spectra were acquired from ex vivo tibiae of glucocorticoid- and placebo-treated wild-type mice and a transgenic mouse model of rheumatoid arthritis. Statistically significant spectral differences were observed due to both treatment regimen and mouse genotype. These differences are attributed to changes in the overall bone mineral composition, as well as the degree of phosphate mineralization in tibial cortical bone. In addition, partial least squares regression was used to generate a Raman-based prediction of each tibias biomechanical strength as quantified by a torsion test. The Raman-based predictions were as accurate as those produced by microcomputed tomography derived parameters, and more accurate than the clinically-used parameter of bone mineral density. These results suggest that Raman spectroscopy could be a valuable tool for monitoring bone biochemistry in studies of bone diseases such as osteoporosis, including tests of drugs being developed to combat these diseases.

Bone fragility beyond strength and mineral density: Raman spectroscopy predicts femoral fracture toughness in a murine model of rheumatoid arthritis.

Clinical prediction of bone fracture risk primarily relies on measures of bone mineral density (BMD). BMD is strongly correlated with bone strength, but strength is independent of fracture toughness, which refers to the bones resistance to crack initiation and propagation. In that sense, fracture toughness is more relevant to assessing fragility-related fracture risk, independent of trauma. We hypothesized that bone biochemistry, determined by Raman spectroscopy, predicts bone fracture toughness better than BMD. This hypothesis was tested in tumor necrosis factor-transgenic mice (TNF-tg), which develop inflammatory-erosive arthritis and osteoporosis. The left femurs of TNF-tg and wild type (WT) littermates were measured with Raman spectroscopy and micro-computed tomography. Fracture toughness was assessed by cutting a sharp notch into the anterior surface of the femoral mid-diaphysis and propagating the crack under 3 point bending. Femoral fracture toughness of TNF-tg mice was significantly reduced compared to WT controls (p=0.04). A Raman spectrum-based prediction model of fracture toughness was generated by partial least squares regression (PLSR). Raman spectrum PLSR analysis produced strong predictions of fracture toughness, while BMD was not significantly correlated and produced very weak predictions. Raman spectral components associated with mineralization quality and bone collagen were strongly leveraged in predicting fracture toughness, reiterating the limitations of mineralization density alone.

Overconstrained library-based fitting method reveals age- and disease-related differences in transcutaneous Raman spectra of murine bones

Abstract. Clinical diagnoses of bone health and fracture risk typically rely on measurements of bone density or structure, but the strength of a bone is also dependent on its chemical composition. Raman spectroscopy has been used extensively in ex vivo studies to measure the chemical composition of bone. Recently, spatially offset Raman spectroscopy (SORS) has been utilized to measure bone transcutaneously. Although the results are promising, further advancements are necessary to make noninvasive, in vivo measurements of bone with SORS that are of sufficient quality to generate accurate predictions of fracture risk. In order to separate the signals from bone and soft tissue that contribute to a transcutaneous measurement, we developed an overconstrained extraction algorithm that is based on fitting with spectral libraries. This approach allows for accurate spectral unmixing despite the fact that similar chemical components (e.g., type I collagen) are present in both bone and soft tissue. The algorithm was utilized to transcutaneously detect biochemical differences in the tibiae of wild-type mice between 1 and 7 months of age and between the tibiae of wild-type mice and a mouse model of osteogenesis imperfecta. These results represent the first diagnostically sensitive, transcutaneous measurements of bone using SORS.

Sensitivity of spatially offset Raman spectroscopy (SORS) to subcortical bone tissue

The development of spatially offset Raman spectroscopy (SORS) has enabled deep, non-invasive chemical characterization of turbid media. Here, we use SORS to measure subcortical bone tissue and depth-resolved biochemical variability in intact, exposed murine bones. We also apply the technique to study a mouse model of the genetic bone disorder osteogenesis imperfecta. The results suggest that SORS is more sensitive to disease-related biochemical differences in subcortical trabecular bone and marrow than conventional Raman measurements.

Transcutaneous monitoring of steroid-induced osteoporosis with Raman spectroscopy

Although glucocorticoids are among the most frequently prescribed anti-inflammatory agents used in the treatment of rheumatoid arthritis, extended exposure to this steroid hormone is the leading cause of iatrogenic osteoporosis. Recently, Raman spectroscopy has been utilized to exploit biochemical differences between osteoporotic and normal bones in order to predict fracture risk. In this presentation, we report the results of ongoing research in our laboratory towards the clinical translation of this technique. We will discuss strategies for the transcutaneous acquisition of spectra from the tibiae of mice that are of sufficient quality to generate accurate predictions of fracture risk.

Steroid-induced osteoporosis monitored by Raman spectroscopy

Glucocorticoids are frequently used to treat inflammatory disorders such as rheumatoid arthritis. Unfortunately, extended exposure to this steroid is the leading cause of physician-induced osteoporosis, leaving patients susceptible to fractures at rates of 30-50%. In this presentation, we report correlations between Raman spectra and biomechanical strength tests on bones of glucocorticoid- and placebo- treated mice. Both wild-type mice and a transgenic model of rheumatoid arthritis have been studied. A two-way ANOVA model reveals statistically significant spectral differences as influenced by glucocorticoid treatment and mouse type.

Steroid Induced Osteoporosis Detected by Raman Spectroscopy

A Raman spectroscopy system has been constructed to study the chemical perturbations to cortical bone associated with steroid induced osteoporosis. Transcutaneous measurements of bone are also discussed.