Khosla, Sundeep

Abstract Context: In women, cortical bone mass decreases significantly at menopause. By contrast, loss of trabecular bone begins in the third decade and accelerates after menopause. Objective: The aim of the study was to investigate the effects of estrogen on cortical and trabecular bone. Design: The Kronos Early Estrogen Prevention Study is a double-blind, randomized, placebo-controlled trial of menopausal hormone treatment (MHT) in women, enrolled within 6–36 months of their final menstrual period. Setting: The study was conducted at the Mayo Clinic, Rochester, Minnesota. Intervention: Subjects were treated with placebo (n = 31), or .45 mg/d conjugated equine estrogens (n = 20), or transdermal 50 μg/d 17β-estradiol (n = 25) with pulsed micronized progesterone. Main Outcome Measures: Cortical and trabecular microarchitecture at the distal radius was assessed by high-resolution peripheral quantitative computed tomography. Results: At the distal radius, cortical volumetric bone mineral density (vBMD) decreased, and cortical porosity increased in the placebo group; MHT prevented these changes. By contrast, MHT did not prevent decreases in trabecular microarchitecture at the radius. However, MHT prevented decreases in trabecular vBMD at the thoracic spine (assessed in a subset of subjects; n = 51). These results indicate that MHT prevents deterioration in radial cortical vBMD and porosity in recently menopausal women. Conclusion: The maintenance of cortical bone in response to estrogen likely has important clinical implications because cortical bone morphology plays an important role in bone strength. However, effects of MHT on trabecular bone at the radius differ from those at the thoracic spine. Underlying mechanisms for these site-specific effects of MHT on cortical vs trabecular bone require further investigation.

Abstract Hip fracture risk rises exponentially with age, but there is little knowledge about how fracture-related alterations in hip structure differ from those of aging. We employed computed tomography (CT) imaging to visualize the three-dimensional (3D) spatial distribution of bone mineral density (BMD) in the hip in relation to age and incident hip fracture. We used intersubject image registration to integrate 3D hip CT images into a statistical atlas comprising women aged 21 to 97 years (n = 349) and a group of women with (n = 74) and without (n = 148) incident hip fracture 4 to 7 years after their imaging session. Voxel-based morphometry was used to generate Student's t test statistical maps from the atlas, which indicated regions that were significantly associated with age or with incident hip fracture. Scaling factors derived from intersubject image registration were employed as measures of bone size. BMD comparisons of young, middle-aged, and older American women showed preservation of load-bearing cortical and trabecular structures with aging, whereas extensive bone loss was observed in other trabecular and cortical regions. In contrast, comparisons of older Icelandic fracture women with age-matched controls showed that hip fracture was associated with a global cortical bone deficit, including both the superior cortical margin and the load-bearing inferior cortex. Bone size comparisons showed larger dimensions in older compared to younger American women and in older Icelandic fracture women compared to controls. The results indicate that older Icelandic women who sustain incident hip fracture have a structural phenotype that cannot be described as an accelerated pattern of normal age-related loss. The fracture-related cortical deficit noted in this study may provide a biomarker of increased hip fracture risk that may be translatable to dual-energy X-ray absorptiometry (DXA) and other clinical images. © 2013 American Society for Bone and Mineral Research.

Abstract High-resolution peripheral quantitative computed tomography (HR-pQCT) has recently been introduced as a clinical research tool for in vivo assessment of bone quality. The utility of this technology to address important skeletal health questions requires translation to standardized multicenter data pools. Our goal was to evaluate the feasibility of pooling data in multicenter HR-pQCT imaging trials. Reproducibility imaging experiments were performed using structure and composition-realistic phantoms constructed from cadaveric radii. Single-center precision was determined by repeat scanning over short-term (<72 hours), intermediate-term (3–5 months), and long-term intervals (28 months). Multicenter precision was determined by imaging the phantoms at nine different HR-pQCT centers. Least significant change (LSC) and root mean squared coefficient of variation (RMSCV) for each interval and across centers was calculated for bone density, geometry, microstructure, and biomechanical parameters. Single-center short-term RMSCVs were <1% for all parameters except cortical thickness (Ct.Th) (1.1%), spatial variability in cortical thickness (Ct.Th.SD) (2.6%), standard deviation of trabecular separation (Tb.Sp.SD) (1.8%), and porosity measures (6% to 8%). Intermediate-term RMSCVs were generally not statistically different from short-term values. Long-term variability was significantly greater for all density measures (0.7% to 2.0%; p < 0.05 versus short-term) and several structure measures: cortical thickness (Ct.Th) (3.4%; p < 0.01 versus short-term), cortical porosity (Ct.Po) (15.4%; p < 0.01 versus short-term), and trabecular thickness (Tb.Th) (2.2%; p < 0.01 versus short-term). Multicenter RMSCVs were also significantly higher than short-term values: 2% to 4% for density and micro–finite element analysis (µFE) measures (p < 0.0001), 2.6% to 5.3% for morphometric measures (p < 0.001), whereas Ct.Po was 16.2% (p < 0.001). In the absence of subject motion, multicenter precision errors for HR-pQCT parameters were generally less than 5%. Phantom-based multicenter precision was comparable to previously reported in in vivo single-center precision errors, although this was approximately two to five times worse than ex vivo short-term precision. The data generated from this study will contribute to the future design and validation of standardized procedures that are broadly translatable to multicenter study designs. © 2013 American Society for Bone and Mineral Research.

AbstractThe mechanisms of estrogen receptor (ER)-α activity can be categorized into those involving direct (classical) or indirect (nonclassical) DNA binding. Although various mouse models have demonstrated the importance of ERα in bone, the specific gene expression patterns affected by these modes of ERα action are unknown. In this report, the gene expression patterns of ERα-deficient (ERKO) mice and nonclassical ER knock-in (NERKI) mice, which can function only by nonclassical means, were analyzed. Three-month-old mice were ovariectomized and implanted with estrogen pellets for 1 month to normalize estrogen levels. Microarray analysis of flushed cortical bone revealed 28% (210 of 763) of the genes differentially expressed in ERKO mice were altered in NERKI mice, suggesting estrogen response element-dependent regulation of these genes in bone. Pathway analysis revealed alterations in genes involved in focal adhesion and extracellular matrix interactions. However, the majority of genes regulated in ERKO mice (72%) were unique (i.e. not altered in NERKI mice), suggesting these are regulated by nonclassical mechanisms. To further explore the pathways affected in ERKO mice, we performed focused quantitative PCR arrays for genes involved in various aspects of bone physiology. Genes involved in bone formation, senescence, apoptosis, and autophagy were significantly regulated. Overall, the majority of the genes regulated by ERα in bone are via nonclassical pathways. However, because NERKI mice display an osteoporotic phenotype, it can be deduced that the minority of the estrogen response element-dependent genes/pathways play critical roles in the regulation of bone physiology. These data demonstrate the importance of classical ERα signaling in regulating bone metabolism.

To determine if the revised US FRAX can identify those at high risk for fractures at any skeletal site, we studied 250 women and 249 men ≥ 40 years old from an age-stratified random sample of Rochester, MN residents. At baseline, femoral neck (FN) bone density was assessed, as were the clinical risk factors included in FRAX, along with additional fracture risk factors such as bone turnover markers and fall history. Fracture ascertainment through periodic interviews and comprehensive medical record review was performed over 10 years of followup. In both women and men, a higher FRAX probability at baseline was associated with greater subsequent likelihood of a major osteoporotic fracture. However, a relative 10% increase in the FRAX 10-year fracture probability was also associated with a 1.4-fold increase (95% confidence interval (CI) 1.1–1.7) in other fractures in women and a 1.7-fold increase (95% CI 0.8–3.1) in men. Furthermore, FRAX predicted asymptomatic vertebral fractures and fractures generally in both sexes. The addition of risk factors not currently included in FRAX did not appear to improve the accuracy of fracture risk prediction. FRAX may provide a conservative estimate of risk for major osteoporotic fractures, but it also predicts fractures generally.

Abstract Skeletal muscle and bone form highly-integrated systems that undergo significant age-related changes, but the relationships between muscle mass and trabecular versus cortical bone or trabecular microarchitecture have not been systematically investigated. Thus, we examined the association between appendicular skeletal muscle mass (ASM) relative to height squared (relative ASM) and bone parameters at several sites assessed by conventional as well as high-resolution peripheral QCT in a cohort of 272 women and 317 men aged 20 to 97 years. In women, relative ASM was associated with cortical thickness (CtTh) at the femoral neck, lumbar spine, radius, and tibia (age-and physical activity adjusted r = 0.19–0.32; all p < 0.01). Relative ASM was also associated with trabecular volumetric bone mineral density (vBMD) at the femoral neck and spine (all p < 0.05), and trabecular bone volume to tissue volume (BV/TV), number (TbN), thickness (TbTh), and separation (TbSp) at the radius (all p ≤ 0.05). In all men, relative ASM was associated with CtTh at all sites (age- and physical activity–adjusted r = 0.17–0.28; all p < 0.01). Associations between relative ASM and trabecular vBMD at the spine in men were lost after adjusting for age; however, relative ASM was associated with trabecular vBMD at the femoral neck and TbN and TbSp at the radius (all p < 0.01). We also investigated circulating factors associated with bone health that may be indicative of relative ASM and found that serum insulin-like growth factor (IGF) binding protein-2 (IGFBP-2) levels were the most robust negative predictors of relative ASM in both sexes. Collectively, these data add to the growing body of evidence supporting the highly-integrated nature of skeletal muscle and bone, and provide new insights into potential biomarkers that reflect the health of the musculoskeletal system. © 2012 American Society for Bone and Mineral Research.

Abstract Advanced bone imaging with quantitative computed tomography (QCT) has had limited success in significantly improving fracture prediction beyond standard areal bone mineral density (aBMD) measurements. Thus, we examined whether a machine learning paradigm, gradient boosting machine (GBM) modeling, which can incorporate diverse measurements of bone density and geometry from central QCT imaging and of bone microstructure from high-resolution peripheral QCT imaging, can improve fracture prediction. We studied two cohorts of postmenopausal women: 105 with and 99 without distal forearm fractures (Distal Forearm Cohort) and 40 with at least one grade 2 or 3 vertebral deformity and 78 with no vertebral fracture (Vertebral Cohort). Within each cohort, individual bone density, structure, or strength variables had areas under receiver operating characteristic curves (AUCs) ranging from 0.50 to 0.84 (median 0.61) for discriminating women with and without fracture. Using all possible variables in the GBM model, the AUCs were close to 1.0. Fracture predictions in the Vertebral Cohort using the GBM models built with the Distal Forearm Cohort had AUCs of 0.82–0.95, whereas predictions in the Distal Forearm Cohort using models built with the Vertebral Cohort had AUCs of 0.80–0.83. Attempts at capturing a comparable parametric model using the top variables from the Distal Forearm Cohort resulted in resulted in an AUC of 0.81. Relatively high AUCs for differing fracture types suggest that an underlying fracture propensity is being captured by this modeling approach. More complex modeling, such as with GBM, creates stronger fracture predictions and may allow deeper insights into information provided by advanced bone imaging techniques. © 2012 American Society for Bone and Mineral Research.