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... Bone Reports 20 (2024) 101735 Contents lists available at ScienceDirect Bone Reports journal homepage: www.elsevier.com/locate/bonr Am I big boned? Bone length scaled reference data for HRpQCT measures of the radial and tibial diaphysis in White adults Stuart J. Warden a, b, *, Robyn K. Fuchs b, c, Ziyue Liu b, d, Katelynn R. Toloday a, Rachel Surowiec e, Sharon M. Moe b, f a Department of Physical Therapy, School of Health and Human Sciences, Indiana University, Indianapolis, IN, United States of America Indiana Center for Musculoskeletal Health, Indiana University, IN, United States of America College of Osteopathic Medicine, Marian University, Indianapolis, IN, United States of America d Department of Biostatistics, School of Medicine, Indiana University, Indianapolis, IN, United States of America e Department of Biomedical Engineering, Purdue University, Indianapolis, IN, United States of America f Division of Nephrology and Hypertension, Department of Medicine, School of Medicine, Indiana University, Indianapolis, IN, United States of America b c A R T I C L E I N F O A B S T R A C T Keywords: Bone allometry Bone strength Cortical bone Normative data Osteoporosis Cross-sectional size of a long bone shaft influences its mechanical properties. We recently used high-resolution peripheral quantitative computed tomography (HRpQCT) to create reference data for size measures of the radial and tibial diaphyses. However, data did not take into account the impact of bone length. Human bone exhibits relatively isometric allometry whereby cross-sectional area increases proportionally with bone length. The consequence is that taller than average individuals will generally have larger z-scores for bone size outcomes when length is not considered. The goal of the current work was to develop a means of determining whether an individual's cross-sectional bone size is suitable for their bone length. HRpQCT scans performed at 30 % of bone length proximal from the distal end of the radius and tibia were acquired from 1034 White females (age = 18.0 to 85.3 y) and 392 White males (age = 18.4 to 83.6 y). Positive relationships were confirmed between bone length and cross-sectional areas and estimated mechanical properties. Scaling factors were calculated and used to scale HRpQCT outcomes to bone length. Centile curves were generated for both raw and bone length scaled HRpQCT data using the LMS approach. Excel-based calculators are provided to facilitate calculation of z-scores for both raw and bone length scaled HRpQCT outcomes. The raw z-scores indicate the magnitude that an individual's HRpQCT outcomes differ relative to expected sex- and age-specific values, with the scaled z-scores also considering bone length. The latter enables it to be determined whether an individual or population of interest has normal sized bones for their length, which may have implications for injury risk. In addition to providing a means of expressing HRpQCT bone size outcomes relative to bone length, the current study also provides centile curves for outcomes previously without reference data, including tissue mineral density and moments of inertia. 1. Introduction Bone strength is influenced by the amount and quality of material present in addition to how the material is distributed (Fuchs et al., 2019). The distribution of bone material is colloquially referred to as bone structure or size and is often assessed via cross-sectional bone images acquired using 3D imaging modalities such as computed to mography and magnetic resonance imaging. High-resolution peripheral quantitative computed tomography (HRpQCT) is a powerful imaging modality capable of providing non-invasive measures of bone cross- sectional properties, along with volumetric bone mineral density (vBMD) and micro-finite element (FE) estimates of bone strength (Whittier et al., 2020). HRpQCT is principally used to assess structure at sites rich in trabecular bone (e.g., distal radius), with outcomes predicting incident fracture (Mikolajewicz et al., 2020; Samelson et al., 2019) and revealing the effects of aging, disease, and intervention (Lespessailles et al., 2016). However, there is growing interest in assessing more proximal sites containing a higher proportion of cortical bone (Cheung et al., 2014; Hughes et al., 2018; Kazakia et al., 2014; O'Leary et al., 2021; Orwoll * Corresponding author at: Department of Physical Therapy, School of Health and Human Sciences, Indiana University, 1140 W. Michigan St., CF-120, Indian apolis, IN 46202, United States of America. E-mail address: stwarden@iu.edu (S.J. Warden). https://doi.org/10.1016/j.bonr.2024.101735 Received 9 December 2023; Accepted 4 January 2024 Available online 6 January 2024 2352-1872/ 2024 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/). S.J. Warden et al. Bone Reports 20 (2024) 101735 et al., 2022; Patsch et al., 2013; Warden et al., 2022a; Warden et al., 2021a). Most bone loss during aging occurs from within the cortical compartment (Zebaze et al., 2010), and assessment of cortical bone-rich diaphyseal sites may provide unique insight into bone changes occurring in disease states and with lifestyle and pharmaceutical interventions. We recently used a second-generation HRpQCT scanner to create reference data for cortical bone outcomes obtained at 30 % of bone length proximal from the distal end of the radius and tibia (Warden et al., 2022b). The data can be used to calculate z-scores to indicate the number of standard deviations an individual's outcomes vary from ageand sex-matched median outcomes. However, the reference data did not take into account the impact of bone length on cross-sectional bone size. There has long been a fascination with the relationship between bone length and cross-sectional size. Galileo (Galilei, 1638) predicted that bones in different sized animals would exhibit positive allometry. That is, he predicted bone size would increase to a relatively greater extent than length in order to maintain the same strength. More recently, skeletal allometry in mammals, including humans, has been reported to be more modest with the relationship between bone length and crosssectional size being closer to isometric (Biewener, 2005; Ruff, 1984). Specifically, the bones of taller people are generally expanded versions of bones of people who are shorter, with bone cross-sectional area increasing proportionally as bone length increases. The net result is that taller-than-average individuals will generally have larger z-scores for bone size outcomes using currently available reference HRpQCT data, and vice versa for shorter individuals. The goal of the current study was to develop a means of determining whether an individual's cross-sectional bone size is suitable not only for their age and sex, but also their bone length. The primary aims were to: 1) explore the relationship between bone length and HRpQCT measures of radial and tibial diaphysis size in adults and 2) generate bone length scaled age- and sex-specific reference data for the HRpQCT measures across adulthood. In doing so, the current study also aimed to provide centile curves for outcomes previously without reference data, including tissue mineral density and moments of inertia. The ultimate goal was to provide calculators to enable the computation of subject-specific per centiles and z-scores for both raw and bone length scaled HRpQCT outcomes. maneuvers without arms from standardized chair (seat height = 45 cm) were performed to assess physical function, as we have previously detailed (Warden et al., 2022c). Self-reported physical function was assessed using the physical functioning domain of the National Institutes of Health Patient Reported Outcomes Measurement Information System (PROMIS-PF), performed via computerized adaptive testing. PROMIS scores are standardized and expressed as T-scores with a population mean of 50 and standard deviation of 10 (Cella et al., 2007). Spine and total hip aBMD were assessed by dual-energy x-ray absorptiometry (DXA) (Norland Elite; Norland at Swissray, Fort Atkinson, WI). 2.2. High-resolution peripheral quantitative computed tomography (HRpQCT) The non-dominant arm and contralateral leg were imaged using an HRpQCT scanner (XtremeCT II; Scanco Medical, Bruttisellen, Switzerland). Phantoms were imaged daily to confirm scanner stability. Bone length was measured in triplicate using a segmometer (Realmet Flexible Segmometer, NutriActiva, Minneapolis, MN) and as described by Bonaretti et al. (Bonaretti et al., 2017). Per convention, ulna length (mm) was measured as a surrogate for radial length. The skin overlying the distal apex of the ulnar styloid was marked and the elbow placed on a rigid surface. The Euclidean distance between the surface and styloid mark was measured. Tibial length (mm) was measured between skin marks placed at the distal tip of the medial malleolus and medial knee joint line. Short-term precision for repeat mark placement and length measures of the ulna and tibia in 15 individuals tested on two consec utive days showed root mean square standard deviations of 2.8 mm (1.1 %) and 6.3 mm (1.7 %), respectively. Scans were acquired and reconstructed as previously described (Warden et al., 2021a). Subjects laid supine with their limb immobilized using an anatomically formed carbon fiber cast. The scanner operated at 68 kVp and 1.47 mA to acquire 168 slices (10.2 mm of bone length) with a voxel size of 60.7 m. After performance of a scout view, reference lines were placed at the medial edge of the distal radius articular surface and center of the distal tibia joint surface. Scan stacks were centered 30 % of bone length proximal to the reference lines. The 30 % location was chosen as it is accessible in most individuals when using the manufac turer's standard forearm and leg casts on a second generation HRpQCT scanner. Assessment of more proximal sites requires use of custom casts and different reference line landmarks to stay within the z-axis limits of the scanner. Scans were scored for motion artifacts on a standard scale of 1 (no motion) to 5 (discontinuities in the cortical shell) (Sode et al., 2011). Scans scoring 3 were repeated when time permitted. Scans with a motion artifact of 4 or 5 were excluded from analyses. A manufacturer provided evaluation script using a dual threshold technique was used to contour the outer periosteal surface and inner trabecular/medullary compartment. Manufacturer provided evaluation scripts were used to obtain outcomes (Table 1). A standard cortical bone script was used to obtain CtvBMD, CtAr, CtPm, CtTh, and CtPo. The script utilized a low-pass Gaussian filter (sigma 0.8, support 1.0 voxel) and fixed thresholds of 320 and 450 mgHA/cm3 to extract trabecular and cortical bone, respectively. Only cortical outcomes were recorded as diaphyseal sites contain limited trabecular bone. The manufacturer's bone midshaft evaluation script was used with a low-pass Gaussian filter (sigma 0.8, support 1.0) and outer threshold of 450 mgHA/cm3. The evaluation provided outcomes for the whole bone (i.e. cortical and any trabecular bone) as the script was run with a single outer contour and without an inside clock-wise (i.e. negative excluding) contour. Outcomes obtained were TotDen (identified as Mean1 in the manu facturer's script), TMD (identified as Mean2 in the manufacturer's script), TA, BA, BA/TA, IMIN, IMAX, and pMOI. Stiffness and failure load were estimated by FE analysis (Scanco Medical FE software version 1.13). Each voxel within the segmented images was assigned a modulus of 10 GPa and Poisson's ratio of 0.3. Axial compression was applied and failure load estimated when 5 % of elements exceeded 1 % strain (Arias- 2. Methods 2.1. Participants HRpQCT scans were performed on 1856 adults (aged 18 years) between 12/2017 and 12/2022 within the Musculoskeletal Function, Imaging, and Tissue Resource Core (FIT Core) of the Indiana Center for Musculoskeletal Health's Clinical Research Center (Indianapolis, Indi ana). Participants were recruited to the core by investigators seeking standardized musculoskeletal outcomes for their research subjects, as well as from the local community via self-referral. The FIT Core has Institutional Review Board approval from Indiana University to assess all-comers who provide written informed consent. To be eligible for inclusion in the current dataset, participants were required to: 1) self-identify as being of White ancestry, 2) be ambulatory and 3) have no self-reported diabetes, liver or kidney disease, past or present history of cancer, thyroid disorders, cystic fibrosis, or rare bone disease (e.g., osteopetrosis or X-linked hypophosphatemia). Individuals with the later conditions were excluded due to their overrepresentation in the FIT Core cohort resulting from investigator-initiated trials and their known or potential impact on HRpQCT outcomes (van den Bergh et al., 2021). Height (m) and weight (kg) were measured without shoes using a calibrated stadiometer (Seca 264; Seca GmbH & Co., Hamburg, Ger many) and scale (MS140-300; Brecknell, Fairmont, MN), respectively. Grip strength using a JamarPlus+ digital hand dynamometer (Sammons Preston, Bolingbrook, IL) and time to complete five sit-to-stand 2 S.J. Warden et al. Bone Reports 20 (2024) 101735 2005). Participant characteristics were described according to decade stage of life (1829, 3039, 4049, 5059, 6069, and 70+ yrs). Spearman partial correlation controlling for age was used to assess the relationship between HRpQCT outcomes and bone length. Scaling factors were calculated for HRpQCT outcomes exhibiting a Spearman partial correlation (on age) with bone length of R2 0.05. Scaling factors were calculated using the simple allometric linear regression model, Y = X, applied in natural logarithmic form as: Table 1 HR-pQCT outcomes. Outcome Abbreviation Units Description Total density (Mean1)b TotDen mgHA/ cm3 Tissue mineral density (Mean2)b TMD mgHA/ cm3 Cortical vBMDa CtvBMD mgHA/ cm3 Total areab TA mm2 Bone areab BA mm2 Cortical areaa CtAr mm2 Bone area/total areab BA/TA % Cortical perimetera CtPm mm Cortical thicknessa Cortical porositya CtTh mm CtPo % Minimum second moment of areab IMIN mm4 Maximum second moment of areab IMAX mm4 Polar moment of inertiab pMOI mm4 Stiffnessc kN/mm Failure loadc N Average density of all voxels within the periosteal contour, including tissue and voids (i.e. medullary cavity and pores) Average density of all voxels within the periosteal contour with a density >450 mgHA/cm3 (excludes medullary cavity and pores) Average density of all voxels within the segmented cortical compartment (includes pores) Area within the periosteal contour, including tissue and voids (i.e. medullary cavity and pores) Area within the periosteal contour with a density >450 mgHA/cm3 (excludes medullary cavity and pores) Average cross-sectional area of the segmented cortical compartment (includes pores) Proportion of voxels within the periosteal contour with a density >450 mgHA/cm3 Average length of the outer periosteal surface within the segmented cortical compartment Thickness of cortical bone including any pores Percentage of void voxels from the total cortical voxels in the segmented cortical compartment Estimated ability of all the components within the outer contour with a density >450 mg/ cm3 to resist bending on the direction of least bending resistance Estimated ability of all the components within the outer contour with a density >450 mg/ cm3 to resist bending on the direction of most bending resistance Estimated ability of all the components within the outer contour with a density >450 mg/ cm3 to resist torsional loading Total reaction force divided by the applied displacement within the finite model Failure load indirectly estimated from linear finite element model loge Y = loge + loge X + loge with Y the HRpQCT outcome of interest, X the predictor variable (i.e., bone length), the scaling exponent or power (scaling factor), the proportionality constant, and the multiplicative error. HRpQCT out comes exhibiting a Spearman partial correlation with bone length of R2 < 0.05 (i.e., <5 % of the variation explained) were considered to have low explanatory value. Scaling factors were used to scale HRpQCT outcomes as: / Yscaled = Yraw (X/X0 )SF with Yscaled the scaled value for the HRpQCT outcome, Yraw the original measured value for the HRpQCT outcome, X the bone length, X0 the sexspecific median bone length within the study population, and SF the scaling factor () from the linear regression model. Bone length (X) was normalized to sex-specific median bone length (X0) so that the scaled value retained the same units and were in a similar value range as the original measured value for the HRpQCT outcome. Sex-specific reference centile curves for raw and scaled HRpQCT outcomes were generated using the LMS method (Cole and Green, 1992) with R package GAMLSS (version 5.2.0) (Rigby and Stasinopoulos, 2005). The LMS method uses Box-Cox transformation to achieve normality at a given age (Box-Cox Cole and Green [BCCG] distribution). Nonparametric smooth curves are fit to the parameter values across the age range using penalized likelihood with penalty on the second derivatives. Centile curves and z-scores were calculated from the estimated parameter curves. LMS-derived z-scores are not suited for identifying extreme values because the LMS transformation method to achieve normality constrains maximum obtainable z-scores. Modified z-scores are provided for scores greater than +2 to address this. In modified zscores, the HRpQCT outcome is expressed relative to the sex- and agematched median in units of half the distance between 0 and + 2 zscores, as per the approach used for growth charts (Centers for Disease Control and Prevention, n.d.). 3. Results 3.1. Participant and scan characteristics Scans from 1426 participants (1034 females, 392 males) were included following exclusion of 430 participants due to: 1) race not White (n = 247, including 87 with a self-reported ineligible disease) and 2) race White, but self-reported ineligible disease or illness (n = 183). The final cohort included females and males ranging in age from 18.0 to 85.3 yrs. and 18.4 to 83.6 yrs., respectively. Participant characteristics stratified by decade of age are detailed in Table 2. Total hip and/or spine aBMD t-score was 1 to 2.5 and 2.5 in 336 (32.5 %) and 20 (1.9 %) females, respectively. One hundred fifty (38.3 %) and 21 (5.4 %) males had a total hip and/or spine aBMD t-score 1 to 2.5 and < 2.5, respectively. HRpQCT reference data in females was generated from 1023 and 919 scans of the radius and tibia, respectively (Table 2). Lower scan numbers than participants was due to: 1) scan not performed due to time con straints (n = 5 radius and 59 tibia scans); 2) excessive motion artifact (n = 26 radius and 9 tibia scans), and; 3) participant size (e.g. leg too large for the carbon fiber cast; leg too long to place the reference line and scan a Acquired using the manufacturer's standard cortical bone script, a low-pass Gaussian filter (sigma 0.8, support 1.0 voxel) and fixed thresholds of 450 and 320 mgHA/cm3 for cortical and trabecular bone, respectively. b Acquired using the manufacturer's bone midshaft evaluation script, a lowpass Gaussian filter (sigma 0.8, support 1.0 voxel) and fixed threshold of 450 mgHA/cm3. c Acquired using the manufacturer's FE analysis with voxels assigned a modulus of 10 GPa and Poisson's ratio of 0.3. Failure estimated when 5 % of elements exceeded 1 % strain. Moreno et al., 2019). 2.3. Statistical analyses All statistical analyses were performed for females and males sepa rately as skeletal proportions and cross-sectional properties differ across sexes independent of height and weight (Kun et al., 2023; Nieves et al., 3 S.J. Warden et al. Bone Reports 20 (2024) 101735 Table 2 Participant characteristics stratified by decade of agea. Characteristic Females n Height (m) Ulna length (cm) Tibia length (cm) Weight (kg) BMI (kg/m2) Physical function Grip strength (kg) 5 sit-to-stand test (s) PROMIS-PF (T-score) Bone densitometry Spine aBMD z-score Total hip aBMD z-score HRpQCT scans included (n) Radial diaphysis Tibial diaphysis Males n Height (m) Ulna length (cm) Tibia length (cm) Weight (kg) BMI (kg/m2) Physical function Grip strength (kg) 5 sit-to-stand test (s) PROMIS-PF (T-score) Bone densitometry Spine aBMD z-score Total hip aBMD z-score HRpQCT scans included (n) Radial diaphysis Tibial diaphysis Age group (yrs) 1829 3039 4049 5059 6069 70+ 184 1.66 (1.611.70) 25.5 (24.426.4) 37.0 (35.438.3) 71.5 (59.076.8) 25.9 (21.727.7) 113 1.66 (1.621.70) 25.4 (24.626.2) 36.9 (35.737.9) 71.4 (60.079.6) 25.9 (21.629.5) 126 1.64 (1.611.68) 25.3 (24.526.1) 36.5 (34.838.0) 74.1 (60.487.1) 27.6 (21.933.0) 224 1.63 (1.601.67) 25.3 (24.426.3) 36.7 (35.137.9) 74.1 (60.683.6) 27.7 (22.831.5) 286 1.63 (1.591.67) 25.2 (24.326.0) 36.7 (35.238.1) 73.5 (62.382.5) 27.8 (23.231.1) 101 1.62 (1.581.65) 25.3 (24.625.9) 36.5 (35.137.9) 69.3 (59.476.9) 26.5 (22.729.3) 27.9 (23.532.0) 8.6 (7.19.9) 58.0 (52.463.5) 29.5 (26.032.5) 8.7 (7.210.1) 57.1 (51.263.5) 26.8 (22.331.1) 9.0 (7.410.5) 54.7 (48.759.6) 25.3 (21.628.3) 9.3 (7.710.6) 52.5 (47.157.8) 23.9 (21.026.8) 10.3 (8.611.5) 50.5 (47.154.7) 21.8 (17.725.0) 10.9 (9.012.8) 48.6 (44.653.6) 0.37 ( 0.320.95) 0.76 (0.061.51) 0.42 ( 0.130.90) 0.64 (0.061.24) 0.32 ( 0.531.13) 0.47 ( 0.411.30) 0.04 ( 0.790.78) 0.27 ( 0.570.94) 0.39 ( 0.521.23) 0.27 ( 0.360.89) 1.07 (0.421.85) 0.66 (0.131.18) 182 162 112 103 123 115 224 195 283 257 99 87 105 1.79 (1.741.83) 28.2 (27.128.8) 40.1 (39.041.5) 85.2 (73.991.6) 26.5 (23.528.6) 45 1.77 (1.741.81) 27.6 (26.828.7) 39.1 (38.040.7) 85.2 (75.193.0) 27.3 (24.630.7) 37 1.78 (1.731.84) 27.9 (26.729.0) 39.5 (37.741.0) 88.4 (79.395.8) 28.0 (24.730.8) 41 1.76 (1.721.83) 27.9 (27.028.9) 39.4 (37.841.2) 88.8 (76.9100.3) 28.5 (24.431.4) 95 1.78 (1.741.81) 28.1 (26.929.2) 40.0 (38.341.3) 88.2 (76.197.2) 27.8 (24.230.4) 69 1.75 (1.701.79) 27.8 (26.928.9) 39.5 (37.640.7) 87.0 (75.895.8) 28.4 (25.131.4) 47.6 (40.755.5) 8.5 (7.09.6) 60.1 (55.864.7) 47.4 (40.454.9) 8.2 (6.19.6) 58.7 (53.166.2) 48.3 (43.053.2) 8.8 (7.39.4) 57.1 (50.564.5) 44.6 (42.048.6) 9.0 (7.39.9) 53.3 (47.760.6) 41.3 (32.948.1) 9.8 (7.911.1) 53.4 (49.257.3) 31.6 (24.839.2) 11.7 (8.913.2) 48.0 (45.251.6) 0.05 ( 0.630.59) 0.04 ( 0.860.80) 0.29 ( 0.900.05) 0.28 ( 1.10.25) 0.07 ( 1.020.55) 0.12 ( 0.800.49) 0.06 ( 0.580.72) 0.09 ( 0.810.52) 0.90 (0.011.66) 0.25 ( 0.550.88) 0.56 ( 0.221.19) 0.12 ( 0.680.30) 104 90 44 41 37 32 40 37 91 81 68 55 aBMD = areal bone mineral density; BMI = body mass index; HRpQCT = high-resolution peripheral quantitative computed tomography; PROMIS-PF = physical function domain of the National Institues of Health Patient-Reported Outcomes Measurement Information System. a Data are median (interquartile range), except for frequencies. stack within the constraints of the z-axis of the scanner; presence of a local tomography artifact due to absorbing tissue outside of field of view) (n = 47 tibia scans). Reference data in males was generated from 384 and 336 scans of the radius and tibia, respectively (Table 2). Lower scan numbers than par ticipants was due to: 1) scan not performed due to time constraints (n = 6 radius and 31 tibia scans); 2) excessive motion artifact (n = 2 radius and 1 tibia scans) and; 3) participant size (n = 24 tibia scans). load) (all partial correlations = 0.280 to 0.452) (Table 3). Bone length explained 7.9 % to 20.5 % of the variance in the estimated mechanical properties. The highest scaling factors at both sites and in both sexes were for bone length's relationship with the estimated ability to resist bending (IMIN, IMAX) and torsion (pMOI) (all scaling factors = 1.652 to 2.113). Estimated ability to resist compression forces (stiffness and failure load) scaled to length at both the radius and tibia with scaling factors ranging from 0.934 to 1.019 in females and 0.685 to 0.984 in males. 3.2. Correlations and scaling factors 3.3. Centile curves There were negative relationships between density outcomes (Tot Den, TMD, CtvBMD) and bone length at both the radius and tibia in females and males (all partial correlations = 0.191 to 0.055) (Table 3). However, correlations did not rise to the level of R2 0.05 required for density data to be scaled to bone length. Similarly, bone length had low value in explaining radial and tibial BA/TA, CtTh or CtPo in either sex (all R2 < 0.05). Bone length explained 8.7 % to 13.6 % of the variance in radius areas (TA, BA, CtAr) and 9.9 % to 19.3 % of the variance in tibial areas (TA, BA, CtAr) in both sexes (Table 3). Areas in females scaled to length with scaling factors ranging from 0.934 to 1.009 for both the radius and tibia. Areas in males scaled to length with scaling factors ranging from 0.685 to 0.888 at the tibia and 0.856 to 0.984 at the radius. There were positive relationships at both sites and in each sex be tween bone length and the estimated ability to resist bending (IMIN, IMAX), torsion (pMOI), and compression forces (stiffness and failure Centile curves for raw CtvBMD, CtTh and CtPo outcomes, which did not satisfactorily scale to bone length, have previously been published (Warden et al., 2022b). Similar curves for TotDen, TMD, and BA/TA at the radius and tibia are presented in Supplemental Files 1 and 2, respectively. The fitted median centile curve for TMD peaked between 35 and 40 years of age in both sexes before declining thereafter. The decline in females was more precipitous, especially between 40 and 60 years of age. HRpQCT raw values for outcomes correlating with bone length at R2 0.05 (TA, BA, CtAr, CtPm, IMIN, IMAX, pMOI, stiffness, failure load) were converted to scaled values using the scaling factors and the ratio of the individual's bone length to sex specific median bone length (females = 25 cm for radius and 37 cm for tibia; males = 28 cm for radius and 40 cm for tibia). For example, for a female with a radial bone length of 24.2 cm and raw IMIN outcome of 514 mm4, the scaled IMIN would be 4 S.J. Warden et al. Bone Reports 20 (2024) 101735 females and an additional 82 radius (+27 %) and 88 (+35 %) tibia scans in males. Beyond an expanded dataset, the current study provides cen tile curves for HRpQCT outcomes previously without reference data, including TotDen, TMD, TA, BA, BA/TA, IMIN, IMAX, and pMOI. In addition, we explored the relationship between bone length and HRpQCT outcomes, developed a means of scaling outcomes for bone length, and generated centile curves for bone length adjusted outcomes. To facilitate the utility of the latter curves, Excel-based calculators (Supplementary Files 5 and 6) were developed to calculate age- and sexmatched percentiles and z-scores for both raw and bone length adjusted outcomes. Many of the HRpQCT outcomes at the radial and tibial diaphysis in both sexes were related to bone length, consistent with established in terrelationships between bone length and cross-sectional size (Biewener, 2005; Ruff, 1984). Size outcomes (TA, BA, CtAr, CtPm) positively correlated with bone length confirming that individuals with longer bones also had wider bones. As bones with larger cross-sectional size have material distributed further from bending axes, bone length also correlated with estimates of bone rigidity and strength (IMIN, IMAX, pMOI, stiffness, failure load). There were no relationships between bone length and TotDen, TMD, CtvBMD, and BA/TA as the later HRpQCT outcomes are already expressed relative to bone size. There was no relationship between CtTh and bone length. This is consistent with previous work (Bjrnerem et al., 2013) and likely re flects a means of minimizing the energy costs of larger and heavier bones. Bending resistance increases to the fourth power of the radius of a bone. By placing material further from its central axis and increasing its radius, a larger bone is disproportionately stronger for the same mass and energy cost. The more distant distribution of material relatively thins the cortex such that CtTh does not correspondingly increase with the increase in size of longer bones. Despite the relatively thinner CtTh, compressive strength is preserved via the increase in CtAr as bone length increases (Seeman, 2003). Scaling factors were calculated for outcomes for which bone length explained at least 5 % of variance (i.e., R2 0.05). There is no accepted cut-off in the literature. Our cut-off was chosen based on the rationale that a lesser relationship implied bone length had limited explanatory value, and is a more liberal cut-off than (for example) the 10 % cut-off implemented when adjusting DXA Z-scores for height in children (Zemel et al., 2011). Outcomes expressed in linear dimensions (e.g., CtPm) exhibited negative allometry, with scaling factors around 0.5 indicating disproportionately lower increases in size relative to in creases in bone length. Relatively isometric allometry (scaling factors around one) was observed for outcomes expressed in squared linear dimensions (e.g., TA, BA, CtAr), indicating bone cross-sectional area measures increased proportionally as bone length increased. Outcomes to the fourth power of linear dimensions (e.g., IMIN, IMAX, pMOI) exhibited positive allometry with scaling factors around two. The latter indicates estimated bone rigidity had disproportionately greater in creases relative to increases in bone length. The scaling factors were used to scale HRpQCT outcomes to bone length, and centile curves were generated for both raw and bone length scaled HRpQCT data. The centile curves can be used to calculate zscores. Excel-based calculators are provided to facilitate this process (Supplementary Files 5 and 6). The raw and scaled z-scores indicate the magnitude that an individual's HRpQCT outcomes differ relative to ex pected sex- and age-specific values. The difference between the two zscores being that the scaled z-score also considers bone length. The consideration of bone length enables it to be determined whether an individual has normal sized bones for their bone length. For example, consider a 43-year-old female with a tibial length of 33.5 cm and tibial pMOI of 15,000 mm4. Their raw z-score for pMOI using the Excel-based calculator equates to 0.738 indicating they have lower than expected torsional rigidity for their sex and age. This may be sug gestive of reduced cross-sectional bone development and an increased risk of injury, such as a bone stress injury (Warden et al., 2021b). Table 3 Spearman partial (on age) correlation between bone length and HRpQCT out comes, and scaling factors (SF) for outcomes exhibiting correlation with an R2 > 0.05. Site and HRpQCT outcome Female Spearman Male R 2 SF Spearman R2 SF Radius TotDen TMD CtvBMD TA BA CtAr BA/TA CtPm CtTh CtPo IMIN IMAX pMOI Stiffness Failure load 0.067 0.109 0.088 0.376 0.369 0.367 0.048 0.356 0.170 0.010 0.418 0.325 0.371 0.370 0.363 0.004 0.012 0.008 0.141 0.136 0.135 0.002 0.127 0.029 0.010 0.175 0.105 0.138 0.137 0.132 1.009 0.934 0.934 0.503 2.095 1.852 1.951 0.966 0.934 0.120 0.144 0.145 0.329 0.303 0.296 0.082 0.329 0.138 0.008 0.353 0.284 0.320 0.291 0.280 0.014 0.021 0.021 0.108 0.092 0.087 0.007 0.108 0.019 <0.001 0.125 0.081 0.103 0.085 0.079 0.984 0.866 0.856 0.530 1.989 1.858 1.912 0.865 0.829 Tibia TotDen TMD CtvBMD TA BA CtAr BA/TA CtPm CtTh CtPo IMIN IMAX pMOI Stiffness Failure load 0.055 0.191 0.182 0.439 0.409 0.406 0.002 0.444 0.207 0.027 0.393 0.443 0.452 0.424 0.432 0.003 0.036 0.033 0.193 0.168 0.165 0.000 0.197 0.043 <0.001 0.154 0.196 0.205 0.179 0.187 0.999 0.959 0.949 0.544 1.831 2.113 2.009 1.007 1.019 0.218 0.209 0.222 0.419 0.328 0.314 0.147 0.172 0.070 0.159 0.374 0.397 0.418 0.318 0.328 0.048 0.044 0.049 0.176 0.107 0.099 0.022 0.415 0.005 0.025 0.140 0.158 0.175 0.101 0.107 0.888 0.702 0.685 0.508 1.652 1.755 1.713 0.700 0.719 514.5/(24.2/25)2.095 = 550.7 mm4. Centile curves fitted to scaled TA, BA, pMOI, and failure load out comes are presented for the radius (Fig. 1) and tibia (Fig. 2). Centile curves fitted to scaled CtAr, CtPm, IMIN, IMAX, and stiffness outcomes are provided in Supplemental Files 3 (radius) and 4 (tibia). 3.4. Percentile and z-score calculator, and centile curve plotter Excel-based calculators were developed for both the radius (Sup plemental File 5) and tibia (Supplemental File 6). Entry of basic de mographic information (sex, date of birth, scan date, and bone length) and one or more HRpQCT outcome (Fig. 3A) results in plotting of sexspecific centile curves (Fig. 3B). The centile curves are based on the curves fitted using the LMS approach fitted to raw data (TotDen, TMD, CtvBMD, Ct.Th) or bone-length scaled data (TA, BA, CtAr, CtPm, IMIN, IMAX, pMOI, stiffness, failure load), depending on whether the outcome was related to bone length at R2 0.05. Beneath each curve, the raw entered and bone length scaled value for the HRpQCT outcome is pro vided along with the associated z-score and percentile (Fig. 3C). The raw z-score and percentile are derived from curves fitted to the raw reference data, whereas the scaled z-score and percentile are derived from curves fitted to the scaled reference data. 4. Discussion The current study expands our previously published reference data for HRpQCT outcomes at the cortical bone rich radial and tibial di aphyses (Warden et al., 2022b). We included data in the current analyses from an additional 173 radius (+20 %) and 171 tibia (+23 %) scans in 5 S.J. Warden et al. Bone Reports 20 (2024) 101735 Fig. 1. Bone length scaled data and fitted centile curves for total area (A, E), bone area (B, F), polar moment of inertia (C, G), and estimated failure load (D, H) at the radial diaphysis for females (top row) and males (bottom row). Fig. 2. Bone length scaled data and fitted centile curves for total area (A, E), bone area (B, F), polar moment of inertia (C, G), and estimated failure load (D,H) at the tibial diaphysis for females (top row) and males (bottom row). However, the individual also has a tibial length that is lower than the median 37 cm for females. When bone length is considered, a scaled pMOI of 18,314 mm4 is calculated (15,000/[33.5/37]2.009) and a scaled z-score of 0.002 obtained indicating relatively normal torsional ri gidity for their bone length. Scaled HRpQCT outcomes will be higher and lower than raw HRpQCT outcomes for individuals with bone lengths shorter and longer than median values in the current reference cohort, respectively. This is because scaled values were normalized to sex-specific median bone length. The latter was performed so that scaled outcomes would retain the same units and be within the same range as raw outcomes. However, the scaling approach in our cohort does raise the question of whether the bone lengths in our cohort are representative. Percutaneous measures of ulna (used as a surrogate for radius length) and tibia length are increasingly being performed prior to HRpQCT to enable the scanning region to be positioned relative to bone length, which has advantages over scanning at a fixed distance offset (Bonaretti et al., 2017; Ghasem-Zadeh et al., 2017; Okazaki et al., 2021; Shanb hogue et al., 2015). However, measured mean or median bone lengths are either not reported (Shanbhogue et al., 2015), not dichotomized by sex (Bonaretti et al., 2017; Shanbhogue et al., 2015) or acquired in a race and/or ethnicity with a different stature (Okazaki et al., 2021), negating the ability to compare to lengths acquired in the current study. GhasemZadeh et al. (Ghasem-Zadeh et al., 2017) did report forearm lengths in White females (25.7 cm) and males (28.1 cm) which compare favorably to our measured lengths of 25 cm and 28 cm in females and males, respectively. Similarly, comparable lengths of 24.7 cm and 27.5 cm have been reported in another cohort of White females and males, respec tively (Madden et al., 2012), and the 40 cm tibial length in males in our study matches the 40.2 cm measured in 18-year-old U.S. military re cruits (Nieves et al., 2005). In the absence of a wealth of percutaneously measured bone length data in the literature, a feasible proxy is to compare the heights of our individuals to population norms. Height and bone length are closely related, so much so that bone length is frequently used to estimate an individual's height. The average height within each decade of age in our cohort (Table 2; females = 1.621.64 m, males = 1.751.79 m) matches that of the U.S. White adult population (females = 1.62 m, males = 1.77 cm) (Fryar et al., 2021). The comparable height provides confidence that our measured median bone lengths are representative of the broader U. S. White population. We assessed other outcomes to explore the comparability of our 6 S.J. Warden et al. Bone Reports 20 (2024) 101735 principally developed for distal bone sites with a greater proportion of trabecular bone. The ability of the model to estimate failure load in other loading directions and at the cortical bone rich diaphysis remains to be established. Finally, we had more limited inclusion of males and older (age >70 yrs) adults and our data are specific to White individuals living in the Midwest of the United States. HRpQCT outcomes vary by race potentially requiring the generation of separate reference data for other races (van den Bergh et al., 2021). In summary, the current study expands our previous dataset by providing reference data for additional HRpQCT outcomes, including TotDen, TMD, TA, BA, BA/TA, IMIN, IMAX, and pMOI. More importantly, the study provides a means of scaling outcomes for bone length and provides reference data for bone length adjusted outcomes. The refer ence data enable HRpQCT outcomes in an individual (or population of interest) to be expressed relative to the reference cohort to determine if they are big boned for their age, sex and bone length. Supplementary data to this article can be found online at https://doi. org/10.1016/j.bonr.2024.101735. CRediT authorship contribution statement Stuart J. Warden: Conceptualization, Data curation, Formal anal ysis, Funding acquisition, Investigation, Methodology, Project admin istration, Supervision, Writing original draft, Writing review & editing. Robyn K. Fuchs: Conceptualization, Data curation, Formal analysis, Writing review & editing. Ziyue Liu: Formal analysis, Writing review & editing. Katelynn R. Toloday: Investigation, Writing review & editing. Rachel Surowiec: Data curation, Investi gation, Methodology, Writing review & editing. Sharon M. Moe: Conceptualization, Funding acquisition, Supervision, Writing review & editing. Declaration of competing interest Fig. 3. Screenshots of the Excel-based calculator for tibia outcomes (available in Supplemental File 5). Following entry of basic demographic information and one or more HRpQCT outcome (A), centile curves are plotted (B), and sex- and age-specific raw and bone length scaled z-scores and percentiles are calcu lated (C). None. Data availability Data will be made available on request. cohort to the broader population, including DXA-derived bone out comes, performance on physical function tests, and self-reported phys ical function (Table 1). DXA z-scores at the hip and spine were slightly higher than zero in females and approximated zero in males. Grip strength in our cohort according to decade stage of life mirrored refer ence values for individuals residing in the U.S. (Wang et al., 2018), whereas time to complete five sit-to-stand maneuvers matched or was slightly slower (Bohannon, 2006; Bohannon et al., 2010). Self-reported physical function (PROMIS-PF T-score) was slightly above the popula tion mean of 50, depending on sex and decade stage of life. These cu mulative data suggest our cohort had slightly above-to-normal general bone health and equivalent or a slightly higher level of functioning than the general U.S. population. Our study has several strengths, but it is also not without limitations. Data were obtained at a single center and variability in machine per formance at other centers may influence outcomes. The outcomes are specific to the sites scanned and the scanning, segmentation, and anal ysis procedures used. We used the manufacturer's bone midshaft eval uation script with a single outer contour and without an inner clockwise (i.e., negative excluding) contour. This means that outcomes using this script (including TotDen and TMD) include any trabecular bone present at the scan sites. This approach was selected as we wanted to include any trabecularized cortical bone, which increases with age (Zebaze et al., 2010). The micro-finite element model used to estimate bone strength is specific to axial compressive loading and was Acknowledgements This contribution was made possible by support from the National Institutes of Health (NIH/NIAMS P30 AR072581), and the Indiana Clinical Translational Science Award/Institute (NCATS UL1TR00252901). 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... Mechanical stimulation of soft tissue cells regulates osteoblast differentiation and activity through soluble factors Taylor A. Aric 1,2 Anloague, Ross 1,2 Melchior, Jesus 3 Delgado-Calle, Julia M. 1,2 Hum, Jonathan W. 1,2,4 Lowery of Biomedical Science, College of Osteopathic Medicine, Marian University, Indianapolis, Indiana, 46222, USA, 2Bone & Mineral Research Group, Marian University, Indianapolis, Indiana, 46222, USA, 3Department of Physiology & Cell Biology, University of Arkansas for Medical Sciences, Little Rock, Arkansas, 72205, USA, 4Indiana Center for Musculoskeletal Health, School of Medicine, Indiana University, Indianapolis, Indiana, 46202, USA Osteoblast Differentiation Profile Tibiae Explant Differentiation B A B A B 1.5 A: Represents the plate layout of the conditions used for the osteoblast differentiation. These tests were done in duplicate using a 50:50 mix of MSCgo Rapid growth media and conditioned media obtained from our preliminary experiments seen to the left. B: Represents a normal schedule to collect differentiated media tagged with EdU for proliferation studies to be completed. ST MC Po SSDt st- iSm+u In laA jur tLioDn y S In jur y AS LTDM S ++ CI nSjuD rSy In dCu Sc eDdS In duS C cDe Sd 0.0 0.0 A&B: Quantification of these analytes are from the cytometric bead array assay. They are represented as means SEM normalized to Injury Induced Strain; n=3 per condition. *indicates p<0.05 against Injury Induced Strain by paired T-Test Osteoblast Differentiation A B C HSkMCs & C2C12 Myoblasts Preliminary Data Co nt ro lC M S S Po tim TM st ula -I ti nj on ur y 0.5 CM 0.5 * No * 1.0 Enzyme-Linked Immunosorbent Assay (ELISA) results for bone formation marker P1NP (A) and bone resorption marker CTx (B) from neonatal tibiae explants exposed to osteogenic media +/- conditioned media (CM) from dermal fibroblasts subjected to cyclic short duration strain (CSDS) followed by acyclic long duration strain (ALDS) or control. * indicates p<0.05 compared to control conditioned media CM Co nt ro lC M S S Po tim TM st ula -I ti nj on ur y 1.0 IL-6 No IL-8 Fold Change A 1.5 In jur y Conclusions Observing the osteoblast differentiation of W-20-17 cells after being exposed to conditioned media, we see statistically significant increases in proliferation in all three cell lines when comparing our injury induced conditioned media exposed cells to our STM treatment conditioned media exposed cells, with the largest proliferation increase seen in human skeletal myocytes with a 10-fold change. Combining these results with the original data from tibiae explants, which shows a statistically significant increase in bone formation marker P1NP and a statistically significant decrease in bone resorption marker CTx, we are provided key insight into how STM might promote the proliferation of osteoblast cells and eventually leading to the rebuilding of bone. ST M Po S st tim -I ul nj ati ur on y Continuing with this experimental design, we plan to further progress in the work of osteoblast differentiation by obtaining conditioned media through STM stimulation of tissue biopsies using a FlexCell machine. We plan to continue to support the idea that soft tissue manual therapy stimulation of soft tissue cells may influence skeletal homeostasis. If we can continue to prove this hypothesis, it provides hope that STM can one day be used as an alternative treatment of osteoporosis for patients with low bone mass or are high in risk for fractures. ST M Po S st tim -I ul nj ati ur on y Osteoporosis is a disease of low bone mass that places individuals at enhanced risk for fracture, disability, and death. Hospitalizations for osteoporotic fractures exceeds those for heart attack, stroke, and breast cancer combined, and osteoporosis rates are expected to rise significantly in the coming decades. Despite this, there are limited pharmacological treatment options for osteoporosis, particularly for long-term management of this chronic condition, and the drug development pipeline is relatively bereft of new strategies and drug candidates. Consequently, there is an urgent need for new therapeutic strategies for treating osteoporosis. Here, we present a novel line of investigation examining the ability of non-invasive soft tissue manipulation (STM) to exert anabolic effects on the skeleton that may provide therapeutic benefit for individuals with low bone mass. Our rationale is premised on work showing that STM leads to decreased levels of chemokines and pro-inflammatory cytokines (such as Interleukin (IL)-1-alpha, IL-6, IL-8 and CXCL5) known to restrict the differentiation and/or activity of bone-forming osteoblasts. Additionally, STM is associated with increased serum levels of the bone formation marker N-terminal propeptide of type 1 procollagen and decreased serum levels of the bone resorption marker collagen type 1 C-telopeptide in young, healthy women and increased serum P1NP levels in some women with osteoporosis. To advance this work, we hypothesized that STM promotes the differentiation and/or activity of bone-forming osteoblasts and increases bone mass. Consistent with this, we show that conditioned media from primary dermal fibroblasts subjected to STM-like stimulation is bioactive and promotes a) increased osteoprogenitor cell proliferation and differentiation in vitro and b) increased bone formation in an ex vivo bone explant model using neonatal tibiae. Consistent with this, conditioned media from primary skeletal muscle myocyte and satellite cell cultures after STM-like stimulation promotes increased osteoprogenitor cell proliferation in vitro. Collectively, these data support the idea that STM stimulation of soft tissue cells may influence skeletal homeostasis. The experimental application of STM to improving bone mass is novel in its focus, which is significant given the relationship between low bone mass and high fracture risk in patients with osteoporosis and the need for new treatment strategies for this disease. Primary Dermal Fibroblasts Preliminary Data Change Abstract F o ld 1Division 1,2 Hiland, A represents pilot data of HSkMC. B represents pilot data of C2C12 myoblasts. Quantification is by multi-analyte membrane array and is represented by means SEM normalized to control; n=2 per condition. *indicates p<0.05 against control by paired T-Test. A-C represents data obtained using Click-iT Plus EdU Cell Proliferation Kit to quantify proliferation of various cell lines A: Primary Dermal Fibroblasts represented as means SEM normalized to MSCgo Rapid + Injury Induced CM + EdU; n=3 per condition. *indicates p<0.05 against MSCgo Rapid + Injury Induced CM + EdU by paired T-Test. B: C2C12 Myoblasts represented as means SEM normalized to MSCgo Rapid + Injury Induced CM + EdU; n=5 per condition. *indicates p<0.05 against MSCgo Rapid + Injury Induced CM + EdU by paired T-Test. C: Human Skeletal Myocytes represented as means SEM normalized to MSCgo Rapid + Injury Induced CM + EdU; n=2 per condition. *indicates p<0.05 against MSCgo Rapid + Injury Induced CM + EdU by paired T-Test. References & Acknowledgements Anloague, A., et al., Mechanical stimulation of human dermal fibroblasts regulates pro- inflammatory cytokines: potential insight into soft tissue manual therapies. BMC Res Notes, 2020. 13(1): p. 400. Raisz, L.G., Pathogenesis of osteoporosis: concepts, conflicts, and prospects. J Clin Invest, 2005. 115(12): p. 3318-25. Leboime, A., et al., Osteoporosis and mortality. Joint Bone Spine, 2010. 77 Suppl 2: p. S107-12. Wade, S.W., et al., Estimating prevalence of osteoporosis: examples from industrialized countries. Arch Osteoporosis, 2014. 9: p. 182. Singer, A., et al., Burden of illness for osteoporotic fractures compared with other serious diseases among postmenopausal women in the United States. Mayo Clin Proc, 2015. 90(1): p. 53-62. Bonjour, J.-P., et al., The importance and relevance of peak bone mass in the prevalence of osteoporosis. Salud publica de Mexico, 2009. 51: p. s5-s17. Watts, N.B., et al., American Association of Clinical Endocrinologists Medical Guidelines for Clinical Practice for the diagnosis and treatment of postmenopausal osteoporosis. Endocr Pract, 2010. 16 Suppl 3: p. 137. Suresh, E., M. Pazianas, and B. Abrahamsen, Safety issues with bisphosphonate therapy for osteoporosis. Rheumatology (Oxford), 2014. 53(1): p. 19-31. Kerschan-Schindl, K., Romosozumab: a novel bone anabolic treatment option for osteoporosis? Wien Med Wochenschr, 2019. Gullberg, B., O. Johnell, and J.A. Kanis, World-wide projections for hip fracture. Osteoporos Int, 1997. 7(5): p. 407-13. Kaneshiro, S., et al., IL-6 negatively regulates osteoblast differentiation through the SHP2/MEK2 and SHP2/Akt2 pathways in vitro. J Bone Miner Metab, 2014. 32(4): p. 378-92. Murakami, M. and N. Nishimoto, [IL-6 inhibitors prevent bone loss and cartilage degeneration in rheumatoid arthritis]. Clin Calcium, 2015. 25(12): p. 1851-7. Loghmani, M.T. and M. Whitted, Soft Tissue Manipulation: A Powerful Form of Mechanotherapy. Journal of Physiotherapy & Physical Rehabilitation, 2016. 1: p. 122. Thompson, W.R., et al., Understanding Mechanobiology: Physical Therapists as a Force in Mechanotherapy and Musculoskeletal Regenerative Rehabilitation. Phys Ther, 2016. 96(4): p. 560-9. Anloague, A., et al., In vitro mimicking of therapeutic soft tissue stimulation regulates pro-inflammatory cytokines. Research Square Preprint, 2019. Saetung, S., L.O. Chailurkit, and B. Ongphiphadhanakul, Thai traditional massage increases biochemical markers of bone formation in postmenopausal women: a randomized crossover trial. BMC Complement Altern Med, 2013. 13: p. 69. Saetung, S., L.O. Chailurkit, and B. Ongphiphadhanakul, Acute changes in biochemical markers of bone resorption and formation after Thai traditional massage. J Med Assoc Thai, 2010. 93(7): p. 771-5. Meltzer, K.R. and P.R. Standley, Modeled repetitive motion strain and indirect osteopathic manipulative techniques in regulation of human fibroblast proliferation and interleukin secretion. J Am Osteopath Assoc, 2007. 107(12): p. 527-36. Eagan, T.S., K.R. Meltzer, and P.R. Standley, Importance of strain direction in regulating human fibroblast proliferation and cytokine secretion: a useful in vitro model for soft tissue injury and manual medicine treatments. J Manipulative Physiol Ther, 2007. 30(8): p. 584-92. Lowery, J.W. and V. Rosen, Bone Morphogenetic Protein-Based Therapeutic Approaches. Cold Spring Harb Perspect Biol, 2017. We gratefully acknowledge critical feedback for this work from members of the Marian University Bone & Mineral Research Group and the consultation of Dr. Jesus Delgado-Calle.  ...

... Bone loss after acute sex-hormone removal via gonadectomy prior to skeletal maturity most striking in male but not female animals 1,2 1 1 1,3 Nick Momeni , Alyson Essex , Padmini Deosthale , Lilian Plotkin of Anatomy, Cell Biology, & Physiology, Indiana University School of Medicine, Indianapolis, IN 46202; 2 Marian University College of Osteopathic Medicine, Indianapolis, IN 46222, 3Roudebush Veterans Administration Medical Center, Indianapolis, IN 46202. BV/TV 0.10 35 30 25 20 # 15 * 10 0 5 * 0.02 0.00 0.25 Sham OVX Sham OVX 2 wk post-op 4 wk post-op Female Sham ORX Sham ORX 2 wk post-op 4 wk post-op Male Figure 1 Bone Volume/ Tissue Volume, Trabecular Thickness, Trabecular Number, and Volumetric Tissue Mineral Density (v-TMD) from male and female sham and operated animals 2 and 4 weeks post gonadectomy. N = 4-5/group. Volumetric -Tissue Mineral Density (v-TMD) 4 0.20 # * 2 Sham ORX 2 wk post-op Sham ORX 4 wk post-op Male * * * 1 0.15 0.10 # * * Sham OVX Sham OVX 2 wk post-op 4 wk post-op Female 0.00 Sham OVX Sham OVX 2 wk post-op 4 wk post-op Female Sham ORX Sham ORX 2 wk post-op 4 wk post-op Male Figure 2 4 weeks post-gonadectomy, males lose cortical bone volume, but both males and females lose TMD TMD 1.2 * 1.0 * Sham OVX Sham OVX 2 wk post-op 4 wk post-op Female Male 0.4 7 0.2 6 Endocortical BS Male Female 3 INDIANA UNIVERSITY SCHOOL OF MEDICINE Future studies will be needed to assess the cellular mechanisms responsible for this sex-dependent bone volume and mineral density loss with acute sex hormone removal. 1) Mohamad, Nur Vaizura, et al. A Concise Review of Testosterone and Bone Health. Clinical Interventions in Aging, Volume 11, 2016, pp. 13171324., https://doi.org/10.2147/cia.s115472. 1 0 Sex hormones, particularly androgens in males, are crucial for proper development of the skeletal system. Testosterone seems to play a role in maintaining cancellous bone in males. The large decreases in bone volume and tissue mineral density suggest without proper exposure to sex hormone levels, bone achieves a lower peak bone mineral density. References 4 2 Figure 2 Tissue Mineral Density (TMD), Cortical Area, and Endocortical Bone Surface from male and female sham and operated animals 2 and 4 weeks post gonadectomy. N = 5/group. * = p <0.05 via Two-way ANOVA vs. Sham , #= p <0.05 via Two-Way ANOVA. Conclusions * 5 Sham OVX Sham OVX 2 wk post-op 4 wk post-op Male mice demonstrated a larger decline in both cancellous and cortical bone after removal of sex hormones. * Sham ORX Sham ORX 2 wk post-op 4 wk post-op 0.6 Sham ORX Sham ORX 2 wk post-op 4 wk post-op The acute removal of sex hormones prior to skeletal maturity negatively impacts the tissue mineral density of bone in both male and female mice. Cortical Area 1.8 1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 0.8 0.0 * = p <0.05 via Two-way ANOVA vs. Sham , #= p <0.05 via Two-Way ANOVA. 0.05 mm2 3 Summary Cancellous bone is more sensitive than cortical bone to the decline in circulating sex hormones. 0.04 Trabecular Number Materials & Methods Images of the femurs were obtained using a SkyScan 1176 micoCT. The microCT images of the individual femurs were then reconstructed using Nrecon and DataViewer software. To analyze the cortical and trabecular bone separately, region of interests (ROIs) were drawn around the trabecular and cortical areas of each femur. Analysis programs were then executed to report the data of the cortical and trabecular bone volume. Tissue mineral density (TMD) was normalized to a phantom using houndsafield units. * Sham OVX Sham OVX 2 wk post-op 4 wk post-op Female Sham ORX Sham ORX 2 wk post-op 4 wk post-op Male g/cm3 Females undergo a rapid depletion of their estrogen levels once they enter menopause. It is understood that this decline in estrogen levels leads to increased activity of osteoclasts, more bone resorption, and ultimately a higher likelihood of developing osteoporosis. Males do not undergo a similar rapid loss of testosterone. This difference in depletion of sex hormones explains why women age 50 and older have a higher lifetime risk of fracture than men age 50 and older (1). However, it is common for males to lose testosterone levels as they age, and this loss of testosterone impacts bone mineral density. A previous study found that older men with higher testosterone levels better maintained their bone mineral density and had lower fracture risks (2). Other studies have postulated that testosterone stimulates osteoblasts to produce trabecular bone and aids osteocytes in preventing trabecular bone loss (3). While this provides insight into how chronic loss of testosterone impacts bone health, this study was aimed at discovering how acute removal of sex hormones impacted male and female mice. * * 5 0.06 * mm % # 0.08 0 Background Trabecular Thickness mm Menopause, an age-related loss of sex hormone production in women, is one of the most common causes of osteoporosis. Previous work has established that this loss of sex hormones, in particular estrogen, causes dramatic loss of bone volume and strength. Similarly, removal of sex steroids results in acute loss of bone mass in adult animals. Mouse models of sex steroid-deficiency include surgery removing the sex organs (orchidectomy, ORX, for males; ovariectomy, OVX, for females) are commonly used to understand the role of sex steroids in bone, but are typically preformed at animal maturity (16 weeks of age) and are analyzed six weeks post-operation. This study aimed to determine whether acute removal of the male or female sex hormones prior to maturity would impact the cortical and trabecular bone volume. Gonadectomy or sham operations were performed on mice at 11 weeks of age, and femurs were then harvested either 2 weeks (13 weeks of age) or 4 weeks postsurgery (15 weeks of age). Analysis of the cortical and cancellous bone volume of the femur were assessed by microCT. In cancellous bone, male animals two and four weeks ORX demonstrated decreases in the following parameters compared to sham operated, agematched controls (2 week; 4 week): bone volume (BV/TV, -70.9%; -86.6%), tissue mineral density (V-TMD, -8.69%; -17.9%), trabecular thickness (TbTh, -31.9%; -27.8%), and trabecular number (TbN, -57.5%; -81.4%). In cancellous bone, female animals two and four weeks OVX demonstrated decreases in the following parameters compared to sham operated, agematched controls: BV/TV (-61.2%; -41.0%), V-TMD (-30.7%; -15.6%), and TbN (-64.0%; 42.4%). In cortical bone, male animals four weeks ORX demonstrated decreases in the following parameters compared to sham operated, age-matched controls: cortical area (13.8%), Endocortical bone surface (-7.10%), and TMD (-10.2%). In cortical bone, female animals four weeks OVX demonstrated decreases in only TMD (-7.50%) compared to sham operated, age-matched controls. In summary, the acute removal of sex hormones has a larger impact on cancellous bone in both males and females, with male animals showing increasing bone loss as time progressed. Further studies are needed to understand the underlying mechanisms behind the progressive bone loss seen in males after sex hormone depletion. Figure 1 Trabecular bone loss in both male and female animals after both 2 and 4 weeks post gonadectomy, but only males have decreased volumetric tissue mineral density g/mm3 Abstract 1/mm 1 Department 2) Chin, Kok-Yong, and Soelaiman Ima-Nirwana. Sex Steroids and Bone Health Status in Men. International Journal of Endocrinology, vol. 2012, 2012, pp. 17., https://doi.org/10.1155/2012/208719. Sham ORX Sham ORX 2 wk post-op 4 wk post-op Male Sham OVX OVX Sham 2 wk post-op 4 wk post-op Female 3) Golds, Gary, et al. Male Hypogonadism and Osteoporosis: The Effects, Clinical Consequences, and Treatment of Testosterone Deficiency in Bone Health. International Journal of Endocrinology, vol. 2017, 2017, pp. 115., https://doi.org/10.1155/2017/4602129. DEPARTMENT OF ANATOMY, CELL BIOLOGY, & PHYSIOLOGY  ...

... Identification of a gene signature associated with elevated bone formation rate in aging mice Krista Jackson, Aaron Hudnall, Jonathan W. Lowery Division of Biomedical Science, Marian University College of Osteopathic Medicine, Indianapolis, Indiana Osteoporosis, a disease of low bone mass that results from bone resorption exceeding bone formation, places individuals at enhanced risk for fracture, disability, and death. There is an urgent and unmet need for novel targets in treating osteoporosis, requiring a better understanding of the endogenous mechanisms regulating bone formation. We reported that deletion of the Bmpr2 gene in skeletal progenitor cells of mice causes substantially elevated bone mass in young adulthood due to increased bone formation rate (Lowery et al, 2015). As yet unpublished work indicates the age-related decline in bone mass of Bmpr2 mutant mice is reduced approximately three-fold compared to control mice; quantification of serum bone turnover markers indicates this is caused by a sustained increase in bone formation rate to at least 35 weeks of age with no alteration in bone resorption. Here, we determine the gene signature associated with elevated bone formation rate using genome-wide transcriptome profiling in bones of 35-week-old control and Bmpr2 mutant mice. Applying stringent criteria comparing the expression data to eight well-accepted housekeeping genes (Ppib, Gapdh, Hprt, Tbp, Ppia, GusB, Prkg1, and Ywhaz), we found that, out of 24,980 exon-containing transcripts detected in both genotypes, 334 genes were up-regulated and 310 were down-regulated at least two-fold compared to controls. An additional 704 genes were detected in only one genotype. We refined this putative signature by performing transcriptome profiling in these animals at 55 weeks of age when bone formation rate is no longer elevated. This revealed that, of those genes altered at 35 weeks of age, 461 (71.5%) were either no longer up-regulated or down-regulated in Bmpr2 mutant mice by 55 weeks of age. Bioinformatic analyses on this refined gene set indicates that elevated bone formation rate in Bmpr2 mutant mice correlates with enrichment for genes containing binding sites for transcription factors associated with skeletal homeostasis, including FOXP1, SOX2, EGR1, E2F1, KLF4, CNOT3, STAT4, and FOXA1. Further, several genes corresponding with osteoblast differentiation and activity, such as Pak4 and Pla2g4a, the latter of which encodes cytosolic phospholipase A2 and whose deletion causes osteopenia, are up-regulated in Bmpr2 mutant mice. Collectively, our findings provide insight into the mechanisms regulating age-related bone loss and highlight potential targets for therapeutic modulation of bone mass. A 35 Weeks of Age 24336 genes 334 genes 310 genes 349 genes 355 genes Unchanged Up-regulated Down-regulated Not Detected in Control Not Detected in Mutant 55 Weeks of Age 21766 genes 4620 genes 201 genes 1387 genes 104 genes B Z3: 53 Z4: 1125 Z8: 1676 Z2: 65 Z14: 49 Z9: 2643 Z10: 3355 Z13: 148 Z5: 53 Figure 4: A: Example ENRICHR analysis on zone 15 genes. Z1: 18677 A B Z6: 64 Z7: 9 Z12: 142 Z11: 103 Conclusions, Significance & Future Directions: Z15: 4 C Figure 1. A: Bmpr2 mutant mice were generated by crossing Bmpr2fl/fl; Prx1-Cre+ males with Bmpr2fl/fl females. Volumetric bone mineral density (vBMD) was quantified by micro-CT in females at 15 and 55 weeks of age. Mean decline in mg hydroxyapatite per cubic centimeter for each genotype between 15 and 55 week old cohorts is indicated (mg HA/ccm); gray bars denote 95% confidence intervals. B: Quantification of the bone formation marker PINP in sera of control and Bmpr2 mutant mice using ELISA. Individual samples are represented by circles and group mean by horizontal lines SEM; p values determined by unpaired t test. RNA-Seq Workflow: 1) Humerii obtained from four each control and Bmpr2 mutant mice at 35 weeks and 55 weeks of age 2) Marrow removed by gentle centrifugation 3) Bones homogenized and total RNA collected 4) Each genotype pooled at equal RNA amounts per mouse 5) Pooled RNA samples shipped to GENEWIZ; quality control performed 6) rRNA depletion and library synthesized then sequenced 7) Bioinformatics analysis using ENRICHR Zones Zone 1: 18677 genes 35 Weeks of Age Unchanged 55 Weeks of Age Unchanged Zone 2: 65 genes Zone 3: 53 genes Zone 4: 1125 genes Zone 5: 53 genes Zone 6: 64 genes Zone 7: 9 genes Zone 8: 1676 genes Zone 9: 2643 genes Zone 10: 3355 genes Zone 11: 103 genes Zone 12: 142 genes Zone 13: 148 genes Zone 14: 49 genes Zone 15: 4 genes Up-regulated Down-regulated Not Detected Not Detected Up-regulated Down-regulated Unchanged Not Detected Unchanged Unchanged Up-regulated Down-regulated Down-regulated Up-regulated Not Detected Not Detected Up-regulated Down-regulated Up-regulated Down-regulated Not Detected Unchanged Up-regulated Down-regulated Unchanged Unchanged Up-regulated Down-regulated Figure 3: A: Results of RNA-Seq analyses at 35 and 55 weeks of age; expressed relative to control. B-C: Comparison of Bmpr2 mutant results relative to control at 35 and 55 weeks of age represented in Venn diagram (B) and tabular (C) forms. - Bmpr2 mutant mice display high bone mass in young adulthood and reduced agerelated bone loss. - Genome-wide transcriptome profiling of Bmpr2 mutant bones identified 461 differentially expressed genes associated with increased osteoblast activity. - The differential gene signature is enriched for genes containing binding sites for transcription factors associated with skeletal homeostasis. Several genes corresponding with osteoblast differentiation and activity are up-regulated in Bmpr2 mutant mice. - Collectively, our findings provide insight into the mechanisms regulating agerelated bone loss and highlight potential targets for therapeutic modulation of bone mass. - Future studies will involve functional studies to narrow the gene signature to those that regulate osteoblast function. We gratefully acknowledge our collaborators and funding sources: - Dr. Vicki Rosen (HSDM) - John Martin (HSDM) - MU-COM Faculty Research Development Award - Indiana Academy of Science Senior Research Grant For a video presentation of this poster and to join the conversation: http://bit.ly/2nPBTHS  ...

... Identification of commercially available antibodies that block ligand-binding by BMPR2 Ruthann Gorrell & Jonathan W. Lowery, PhD Division of Biomedical Science, Marian University College of Osteopathic Medicine, Indianapolis, Indiana, USA Osteoporosis, a disease of low bone mineral density, affects 10 million Americans and is a significant health problem and a considerable socioeconomic burden. Current treatments for osteoporosis have significant limitations, necessitating identifying new treatment strategies via building a better understanding of the endogenous mechanisms regulating bone mass. Recent research demonstrated that removal of the BMP type 2 receptor, BMPR2, in skeletal progenitor cells of Bmpr2cKO mice leads to reduced age-related bone loss due to a sustained elevation in bone formation rate. The molecular mechanism underlying this phenotype is being pursued in other work. In the present study, we sought to advance the translational potential of the genetic model by identifying antibodies that neutralize the ligandbinding function of the BMPR2 extracellular domain (BMPR2-ECD). Using a modified, cell-free immunoprecipitation assay quantified by ELISA, we examined the neutralizing ability of 3F6, which is a mouse monoclonal antibody raised against the ligand-binding region of BMPR2, and found a dose-dependent inhibition of BMPR2ECD ligand-binding. We then evaluated 1F12, which is another mouse monoclonal antibody raised against the ligand-binding region of BMPR2, and found that this antibody is also capable of neutralizing the ligand binding function of BMPR2-ECD. We extended the results by examining the ability of 3F6 to block endogenous BMPR2 function in the BMP-responsive HEK293T (human kidney embryonic 293 translation) cell line. Consistent with the results of our cell-free system, pre-treatment of HEK293T cells with 3F6 leads to reduced sensitivity to in response to BMP pathway activation by BMP2. These results provide proof-of-concept data for future studies evaluating inhibition of BMPR2 function in vivo as a means to reduce agerelated bone loss. Figure. 1 High peak bone mass and reduced age-related decline in bone mass of female BMPR2 mutant mice. AB: Trabecular volumetric bone mineral density (vBMD) quantified by micro-CT in tibiae of females control and BMPR2 mutant mice at 55 weeks of age (A) and change between 15 and 55 weeks of age (B). A: Validation of BMP2 ELISA B: Proof-of-principle of ligand-binding assay C: Standardization of ligand-binding by BMPR2-ECD D: Identification of BMPR2-ECD neutralization by 3F6 Central Research Question: Can ligand-binding ability of the BMPR2 extracellular domain (BMPR2-ECD) be blocked using commercially available antibodies? Acknowledgements: This work was performed in collaboration with: Laura Schoerning Jordan Newby Aaron Hudnall Julia Hum, PhD Warren Lawless Supported by a MU-COM Faculty Research Development award issued to JWL. Figure. 3 Antibody 3F6 inhibits BMP2-induced pathway activation in HEK293T cells. HEK293T cells were treated with BMP2 for four hours +/- thirty minute pre-treatment with 3F6 or control ascites. A-B: BMP pathway activation level, indicated by phoshorylation of S1/5/8 (pS1/5/8), is reduced in the presence of 3F6. C-D: Ascites control does not inhibit BMP2-induced pathway activation. Data are expressed as mean+/- SEM relative to BMP2 alone. * indicates p<0.05 by unpaired t test versus BMP2 alone. Conclusions: Our results provide proof-of-concept data that BMPR2 function can be blocked using a neutralizing antibody approach. Specifically, the mouse monoclonal antibodies 3F6 and 1F12 block BMPR2-ECD ligand-binding in a cell-free immunoprecipitation assay. 3F6 was additionally shown to block BMP2-induced pathway activation in HEK293T cells. An incidental finding from our study is that BMPR2 is the major receptor for BMP2 in HEK293T cells. Current and Future Directions: 1) Examination of 3F6 and 1F12 neutralizing activity of BMPR2 function in skeletal cells in vitro. 2) Examination of systemic delivery of 3F6 and/or 1F12 in vivo as a means of regulating postnatal bone mass. Figure. 2 Antibodies 3F6 and 1F12 inhibit BMPR2-ECD ligand-binding in a modified, cell-free immunoprecipitation assay quantified by ELISA. A: BMP2, bound to well, binds BMP2 (A1), so that quantitative ELISA showed dosedependent increases in absorbance (A2). B: Noggin bound BMP2 (B1), resulting in a dose-dependent decrease in signal (B2). C: BMPR2-ECD also bound BMP2 (C1), resulting in a dose-dependent decrease in signal (C2). D: 3F6 blocked BMPR2-ECD (D1), resulting in a dose-dependent decrease in BMPR2-ECD activity (D2). E: Second lot of 3F6 verified previous findings (D1&2). F: 1F12 also bound BMPR2-ECD, resulting in a decrease in BMPR2-ECD activity. *indicates p<0.05 by unpaired t test versus control. Follow this link for a video presentation of this poster and to leave feedback: Follow this link to the Lowery Lab Website: http://www.jonlowery.com/presentations http://www.jonlowery.com/research  ...

... Elucidating the antagonistic relationship between Bone Morphogenetic Protein and Activin signaling pathways in osteoprogenitor cells Sylvia Chlebek, Jordan Newby, Jon Arthur, Jonathan W. Lowery Division of Biomedical Science, Marian University College of Osteopathic Medicine Abstract Activin inhibition upstream of receptor engagement Working interpretations ACVR2A/B modulates signals for the TGF-beta superfamily of ligands, including BMP and Activin. Activin has been shown to counteract BMPs that signal through the ACVR2A/B receptors, however, Activin has not been shown to counteract BMPs that signal through BMPR2. Osteoporosis is a disease characterized by low bone mineral density due to the rate of bone resorption exceeding that of bone formation. Substantial evidence indicates the Bone Morphogenetic Protein (BMP) pathway promotes bone formation through action of the effectors SMAD1/5/8 while the Activin pathway negatively influences bone mass through action of the effectors SMAD2/3. Recent studies from our lab suggest that BMP and Activin ligands regulate bone mass in a see-saw-like mechanism via competition for a shared pool of receptors, i.e. receptor-level competition. In the present study we seek to test this hypothesis in vitro via signaling responsiveness assays using pathway-specific western blot analyses in the osteogenic cell line W-20-17. We first confirmed that W-20-17 cells respond to exogenous stimulation by BMP2 and Activin-A. Then, we administered recombinant versions of naturally-occurring extracellular ligand traps for BMP2 or Activin ligands (Noggin and Follistatin, respectively) to examine basal antagonism between these pathways. This revealed that, under basal conditions, SMAD1/5/8 activation is repressed by Activin signaling; interestingly, the converse relationship was not observed. To determine the molecular mechanism allowing for this relationship, we treated W-20-17 cells with SB431542, which is an intracellular inhibitor of Activin signaling that functions downstream of receptor engagement, and found no effect on SMAD1/5/8 activation. Collectively, our results suggest Activin-mediated repression of BMP signaling is ligand-dependent but occurs upstream of SMAD2/3 activation. Noggin is a BMP-specific antagonist protein, which upon addition to the W-20-17 cells resulted in a decrease in phosphorylation of SMAD 1/5/8 and no effect on the phosphorylation of SMAD 2/3. Here we observed that BMP inhibition upstream of the receptor does not impact SMAD 2/3 phosphorylation. Such also supports the signaling competency of W-20-17 cells at the basal level, as seen in the control group. Follistatin (FST) is an Activin binding protein, which upon addition to the W-20-17 cells resulted in an increase in the phosphorylation of SMAD 1/5/8. Here we observed that Activin inhibition upstream of the receptor allows for the upregulation of BMP signaling. SB-431542 is an intracellular inhibitor of Activin signaling, which upon addition to the W-20-17 cells resulted in a loss of SMAD 2/3 phosphorylation. Collectively, our data suggest that Activin mediated repression of BMP signaling is ligand dependent but occurs upstream of effector activation. -actin 5 4 4 3 2 1 0 2 S 1 : - a c tin SMAD1 5 p S 1 : - a c tin pS1/5/8 p S 1 :S 1 Future direction: Inhibition of specific Activin subunits 3 2 Hypothesis Sequestering individual Activin subunits will mimic the effect of Follistatin on W-20-17 cells. 1 1 0 0 BMP & Activin Signaling Pathways Inhbba Hprt Methods Identify which Activin subunits are endogenously expressed by W20-17 cells. Then, deliver neutralizing antibodies against these subunits and compare to pan-Activin inhibition by Follistatin. Predicted Results We predict that delivery of anti-Activin-A antibody will mimic the effect of Follistatin in W-2-17 cells and lead to increased phosphorylation of SMAD1/5/8. Activin inhibition downstream of receptor engagement Future direction: ACVR2B overexpression Hypothesis Increasing the expression level of ACVR2B (which is shared by BMP and Activin ligands) will alleviate Activin-mediated inhibition of BMP signal transduction. Methods cDNA encoding hACVR2B will delivered to W-20-17 cells. The expression vector contains an C-terminal V5 epitope tag and overexpression of hACVR2B will be confirmed by western blot. Subsequently, control and hACVR2B-overexpressing W-2017 cells will be treated with Follistatin and . BMP inhibition upstream of receptor engagement SMAD1 -actin 1 1 .5 1 .0 0 .5 2 S 1 : - a c tin pS1/5/8 SMAD1 2 .0 p S 1 : - a c tin pS1/5/8 p S 1 :S 1 2 1 0 0 .0 0 2 2 2 Predicted Results We predict that overexpression of hACVR2B will cause Follistatin treatment to no longer increase phosphorylation of SMAD1/5/8 in W20 cells. -actin SMAD2 -actin 1 0 1 0 S 2 : - a c tin SMAD2 pS2/3 p S 2 : - a c tin pS2/3 p S 2 :S 2 -actin For a video presentation of this poster and to join the conversation: 1 http://bit.ly/2nPBTHS 0  ...

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... Loss of BMPR2 expression in skeletal progenitor cells reduces age-related bone loss Michael S. Aaron M. 1 Hudnall , Jordan B. 1, 2 Newby , Vicki 3 Rosen , Jonathan W. 1 Lowery = -39.4 mgHA/ccm CI: -33.8,-45.0 Fig. 3 Sustained increase in bone formation rate in Bmpr2 mutant mice with no defect in bone resorption rate. A, B: Quantification of the bone formation marker PINP (A) and the bone resoprtion marker CTx (B) in sera of female control and Bmpr2 mutant mice at 35 and 55 weeks of age using ELISA. = -71.11 mgHA/ccm CI: -67.4,-74.8 vBMD (mgHA/ccm) vBMD (mgHA/ccm) Conclusions: vBMD (mgHA/ccm) Fig. 1 Conditional deletion of Bmpr2 in skeletal progenitors leads to high bone mass by ten weeksof-age due to elevated individual osteoblast activity level. A: At left, Bmpr2 mutant mice were generated by crossing Bmpr2fl/fl; Prx1-Cre+ males with Bmpr2fl/fl females (Lowery et al., Journal of Cell Science 2015). At middle, Prx1-Cre causes efficient deletion in the mesoderm of the appendicular skeleton by embryonic day 9.5 as evidenced by reporter staining in the forelimb (blue staining; adapted from Logan et al., Genesis 2002). At right, the resulting truncated Bmpr2 transcript is confirmed by RT-PCR in RNA from 15-week-old humerii (Lowery et al., Journal of Cell Science 2015). B, C: As previously reported (Lowery et al., Journal of Cell Science 2015), osteoblast density (B) using standard analysis of number of osteoblasts per mm of bone perimeter (N.Ob/B.Pm (/mm)) and bone formation rate (C, BFR) using standard analysis of BFR relative to bone surface (BFR/BS) in ten-weekold female mice. vBMD (mgHA/ccm) Osteoporosis is a disease of low bone mineral density (BMD) that affects 10 million Americans and accounts for 1.5 million fractures annually. With an additional 34 million Americans at risk for developing the disease, osteoporosis is both a significant health problem and a considerable socioeconomic burden. Current first-line therapies for osteoporosis involve anti-resorptive agents but many patients, such as those with drastically low BMD or high fracture risk, would benefit from augmenting bone formation as well as inhibiting bone loss. We recently reported that targeted deletion of the type 2 BMP receptor BMPR2 in skeletal progenitor cells of the limb bud using Prx1-Cre (Bmpr2 mutant mice) leads to dramatically increased bone mass and bone formation rate by ten weeks of age in the absence of changes in osteoclast number or function (Lowery et al., Journal of Cell Science 2015). In the present study, we examined the impact of Bmpr2 deletion on age-related bone loss in Bmpr2 mutant mice. Consistent with our previous results, 55-week-old female Bmpr2 mutant mice exhibit approximately four-fold higher bone mass in the tibia than control mice. Moreover, the age-related decline in bone mass from 15 weeks to 55 weeks of age in female Bmpr2 mutant mice is reduced 1.8-fold (CI, 1.5-2.2) compared to control mice. Bone mass of the L5 vertebrae, which is outside the Prx1-Cre expression domain, is unchanged in Bmpr2 mutant mice compared to control mice at all ages examined. Quantification of the serum bone turnover markers Procollagen Type I Nterminal Propeptide (PINP) and Collagen Type I C-telopeptide (CTx) suggest that high bone mass in aging female Bmpr2 mutant mice is preserved due to a sustained increase in bone formation rate to at least 35 weeks of age with no alteration in bone resorption. Collectively, our findings provide insight into the mechanisms regulating age-related bone loss and suggest that strategies aimed at controlling signaling through BMPR2 have the potential to impact bone mass in the aging adult skeleton. vBMD (mgHA/ccm) of Biomedical Science, Marian University College of Osteopathic Medicine; 2Department of Biology, Freed-Hardeman University; 3Department of Developmental Biology, Harvard School of Dental Medicine vBMD (mgHA/ccm) 1Department 1 Eaton , = 62.2 mgHA/ccm CI: 59.3,65.1 = 0.5 mgHA/ccm CI: -36.7,37.7 - Loss of Bmpr2 in embryonic skeletal progenitor cells leads to high bone mass due to increased osteoblast activity - Bmpr2 mutant mice exhibit high bone mass to at least 55 weeks of age and experience reduced age-related bone loss - Markers of bone formation rate are elevated to at least 35 weeks of age in Bmpr2 mutant mice with no observed change in bone resorption parameters at any age examined Current and Future Directions: = -57.1 mgHA/ccm CI: -112.11,-2.2 = -55.0 mgHA/ccm CI: -103.69,-10.4 Fig. 2 Reduced age-related decline in bone mass of female Bmpr2 mutant mice. A, B: Representative histology of tibiae from 55-week-old female control (A) and Bmpr2 mutant (B) mice. C-F: Trabecular (C-D) and mid-shaft (E-F) volumetric bone mineral density (vBMD) quantified by micro-CT in tibiae of females control and Bmpr2 mutant mice at 55 weeks of age (C, E) and change between 15 and 55 weeks of age (D, F). G-H: Volumetric bone mineral density (vBMD) quantified by micro-CT in L5 vertebrae, which is outside of the Prx1-Cre expression domain, of females control and Bmpr2 mutant mice at 55 weeks of age (G) and change between 15 and 55 weeks of age (H). - Examination of signal transduction changes associated with loss of BMPR2 in the aging skeleton using western blot and immunohistochemistry - Identification and characterization of the gene signature associated with sustained increase in bone formation in the absence of BMPR2 expression in the aging skeleton using RNA-Seq and qRT-PCR - Development of non-genetic means to reduce BMPR2 function and/or expression in the postnatal skeleton Follow this link for a video presentation of this poster and to leave feedback: Follow this link to the Lowery Lab Website: http://tinyurl.com/Eaton-ASBMR-2016 http://tinyurl.com/jlowerylab  ...

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