Bone Strength Estimated by Micro-Finite Element Analysis (mfea) Is Heritable and Shares Genetic Predisposition With Areal BMD: The Framingham Study

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1 ORIGINAL ARTICLE JBMR Bone Strength Estimated by Micro-Finite Element Analysis (mfea) Is Heritable and Shares Genetic Predisposition With Areal BMD: The Framingham Study David Karasik, 1,2 Serkalem Demissie, 3 Darlene Lu, 3 Kerry E Broe, 1 Steven K Boyd, 4 Ching-Ti Liu, 3 Yi-Hsiang Hsu, 1,5,6 Mary L Bouxsein, 5,7 and Douglas P Kiel 1,5,6,8 1 Institute for Aging Research, Hebrew SeniorLife, Boston, MA, USA 2 Faculty of Medicine in the Galilee, Bar Ilan University, Safed, Israel 3 Biostatistics, Boston University School of Public Health, Boston, MA, USA 4 McCaig Institute for Bone and Joint Health, Cumming School of Medicine, University of Calgary, Calgary Canada 5 Harvard Medical School, Boston, MA, USA 6 Broad Institute of Harvard and MIT, Cambridge, MA, USA 7 Center for Advanced Orthopedic Studies, Beth Israel Deaconess Medical Center, Boston, MA, USA 8 Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA ABSTRACT Genetic factors contribute to the risk of bone fractures, partly because of effects on bone strength. High-resolution peripheral quantitative computed tomography (HR-pQCT) estimates bone strength using micro-finite element analysis (mfea). The goal of this study was to investigate if the bone failure load estimated by HR-pQCT-based mfea is heritable and to what extent it shares genetic regulation with areal bone mineral density (abmd). Bone microarchitecture was measured by HR-pQCT at the ultradistal tibia and ultradistal radius in adults from the Framingham Heart Study (n ¼ 1087, mean age 72 years; 57% women). Radial and tibial failure load in compression were estimated by mfea. Femoral neck (FN) and ultradistal forearm (UD) abmd were measured by dual-energy X-ray absorptiometry (DXA). Heritability (h 2 ) of failure load and abmd and genetic correlations between them was estimated adjusting for covariates (age and sex). Failure load values at the non-weight-bearing ultradistal radius and at the weight-bearing ultradistal tibia were highly correlated (r ¼ 0.906; p < 0.001). Estimates of h 2 adjusted for covariates were for the radius and for the tibia. Additional adjustment for height did not impact on the h 2 results, but adjustment for abmd at the UD and FN somewhat decreased h 2 point estimates: and for radius and tibia, respectively. In bivariate analysis, there was a high phenotypic and genetic correlation between covariate-adjusted failure load at the radius and UD abmd (r P ¼ 0.826, r G ¼ 0.954, respectively), whereas environmental correlations were lower (r E ¼ 0.696), all highly significant (p < 0.001). Similar correlations were observed between tibial failure load and femoral neck abmd (r P ¼ 0.577, r G ¼ 0.703, both p < 0.001; r E ¼ 0.432, p < 0.05). These data from adult members of families from a population-based cohort suggest that bone strength of distal extremities estimated by micro-finite element analysis is heritable and shares some genetic composition with areal BMD, regardless of the skeletal site American Society for Bone and Mineral Research. KEY WORDS: BONE HR-QCT/MICRO-CT; GENETIC EPIDEMIOLOGICAL STUDY; HERITABILITY; FINITE ELEMENT ANALYSIS; FAILURE LOAD Introduction Genetic factors contribute to the risk of osteoporotic fracture, which is a growing health problem as the population is aging. (1) At the present, areal bone mineral density (abmd) measured by dual-energy X-ray absorptiometry (DXA) is considered to be one of the best predictors of fractures. (2) Given that abmd correlates highly with bone strength, (3) it has been used as a phenotype for multiple previous genetic studies; however, it does not capture aspects of bone structure and bone strength that may contribute to fracture risk, such as bone size, shape, and trabecular and cortical density and morphology. abmd is characterized by high heritability (h 2 ), estimated to be 45% to 78% depending upon the skeletal site and age. (4,5) However, there is evidence that abmd does not capture all of the genetic contributions to osteoporotic fractures. (6 8) Received in original form January 31, 2017; revised form June 6, 2017; accepted June 10, Accepted manuscript online June 22, Address correspondence to: David Karasik, PhD, Institute for Aging Research, Hebrew SeniorLife, 1200 Centre Street, Boston, MA 02131, USA. karasik@hsl.harvard.edu For a Commentary on this article, please see Rivadeneira and Uitterlinden (J Bone Miner Res. 2017;32: DOI: /jbmr.3300). Journal of Bone and Mineral Research, Vol. 32, No. 11, November 2017, pp DOI: /jbmr American Society for Bone and Mineral Research 2151

2 The recent availability of high-resolution peripheral quantitative computed tomography (HR-pQCT) makes it possible to measure bone microarchitecture and volumetric BMD in vivo. (9) HR-pQCT provides measures of both trabecular and cortical microstructure, which differ between fracture cases and controls, and thus may be important predictors of fracture. (10 12) Thus, cross-sectional case-control studies have shown that HRpQCT measurements are associated with prevalent fragility fracture independent of abmd (reviewed in Cheung and colleagues (9) ). Importantly, HR-pQCT is able to estimate bone strength using micro-finite element analysis (mfea). Bone microarchitecture measures are moderately to highly correlated with traditional abmd measures. (13 15) At both the radius and tibia, mfea-derived failure load has been demonstrated to correlate highly with abmd. (16) Despite these correlations between measures of bone density and architecture, there are no data that indicate to what extent phenotypic correlations between the microarchitecture-derived failure load and abmd measures are attributable to shared genetic effects. Several recent studies supported the hypothesis that HRpQCT-derived bone microarchitecture and volumetric BMD (vbmd) traits are heritable (reviewed in Karasik and colleagues (17) ). However, there are less data on genetic regulation of HR-pQCT-derived bone strength estimates. Also, there are little data on whether a genetic variance captured by failure load measured with HR-pQCT is independent of that for conventional abmd. We, therefore, tested the hypothesis that the variance in mfea-estimated bone failure load is heritable, and although it shares genetic predisposition with conventional abmd measured by DXA, some of the heritability is independent of abmd. Materials and Methods Sample Participants represented a subsample of the community-based Framingham Study Offspring Cohort who had valid bone microarchitecture measured using HR-pQCT at the radius or tibia. (18) In brief, the Framingham Offspring Cohort comprises adult members of two-generational (mostly nuclear) families of European ancestry. Details and descriptions of the Framingham Osteoporosis Study, in particular family samples with bone phenotypes available for the analyses, were provided elsewhere, (17,19,20) as well as publicly available through the Database of Genotype and Phenotype (dbgap) at gov/dbgap. Participants who attended the ninth index Offspring exam ( ) were invited to come back to attend the Osteoporosis Study exam and have measurements of bone by HR-pQCT as well as DXA abmd of the hip and wrist. To be eligible for this analysis, participants with these measures had to have at least one additional family member with HR-pQCT measures. All study procedures were approved by the Hebrew SeniorLife Institutional Review Board as well as the Framingham Study Executive Committee and Observational Study Monitoring Board. All participants provided informed consent. Skeletal phenotypes Areal BMD (DXA) The participants underwent bone densitometry by DXA at the hip and forearm with a Lunar Prodigy fan beam densitometer (GE Lunar, Madison, WI, USA) using standard positioning recommended by the manufacturer between March 2012 and September The non-dominant forearm was scanned, unless a participant had a previous fracture as an adult, in which case the contralateral side was scanned. The non-dominant side was determined by asking which hand was preferentially used for writing. The left side was scanned for participants answering that both sides were used equally. For the hip DXA, the right hip was scanned unless there was a history of previous fracture or hip replacement, in which case the left hip was scanned. We excluded participants who had fractures on both sides, at the forearm or femur. The coefficient of variation (CV) in normal subjects for the abmd was 2.7% for ultradistal (UD) (17) and 1.7% for the femoral neck (FN) (21) sites. HR-pQCT measurements HR-pQCT was performed at the ultradistal radius and tibia (XtremeCT, Scanco Medical AG, Br uttisellen, Switzerland), following previously published methods. (10,22) HR-pQCT was performed on the radius at the non-dominant side and on the right tibia, unless the participant had a previous adult fracture, in which case the opposite side was scanned. The scan region extended over a 9.02-mm length (a stack of 110 slices were acquired with an isotropic voxel size of 82 mm), starting 9.5 mm and 22.5 mm proximal to a radial and tibial joint margin reference line, respectively. (23) The standard analysis of images and extended cortical analysis (24) were performed by one technologist using IPL v6.0 (Scanco Medical) and reviewed for quality by senior team members. Scans were qualitatively graded according to a 5-point progressive movement scale (1 ¼ perfect, 5 ¼ severe motion artifact). For the micro-finite element analysis, scans with extreme movement (a movement grade > 3) were excluded. (17,25,26) Data capture was supported by REDCap. (27) The following bone microarchitecture traits were obtained from the ultradistal radius and ultradistal tibia: total density (Tt. vbmd, mg/cm 3 HA); cortical density (Ct.vBMD, mg/cm 3 HA); cortical porosity (Ct.Po, %); cortical thickness (Ct.Th, mm); trabecular density (Tb.vBMD, mg/cm 3 HA); trabecular number (Tb.N, mm 1 ) and trabecular thickness (Tb.Th, mm); cortical cross-sectional area (Ct.Ar, mm 2 ) and total cross-sectional area (Tt.Ar, mm 2 ). Compressive strength represented as failure load (FL, Newtons) was estimated by micro-finite element analysis (mfea). (28,29) mfea was performed using the FAIM v6.0 (Numerics88 Solutions Ltd., Calgary, Canada) software. The estimated failure load was calculated by applying axial compression conditions with 1% apparent strain, a tissue modulus of GPa, and Poisson s ratio of 0.3 (30) to generate the force for which 2% of the bone tissue would be loaded beyond 0.7% strain. Other characteristics The following information was obtained for each participant at the time of the bone measurement (age) and at the closest index exam: height and weight (for details, see Karasik and colleagues (17) ). Height (without shoes) was measured to the nearest one-fourth inch using a standard stadiometer. Weight (in light dress) was measured using a standardized balance beam scale KARASIK ET AL. Journal of Bone and Mineral Research

3 Statistical analysis Descriptive statistics and analysis of phenotypic correlations between the failure load (FL) of both skeletal sites and bone microarchitecture, DXA abmd at two bone sites, and height were performed using SAS (version 9.1.3, SAS Institute Inc., Cary, NC, USA). Variance component analyses (VCA) were performed using SOLAR (version 2.0) (31) to estimate heritability (h 2 ) of each trait, as the proportion of the total trait variance attributable to the additive effects of multiple genes (polygenic component). Heritability estimates were calculated adjusted for age and sex (model 1). Two additional covariate models were tested, with height added to the Model 1 covariates (model 2) and abmd added to model 2 (model 3). Ultradistal forearm abmd measures were used in the analysis of the radial FL, and FN abmd for the tibial FL. Phenotypic correlation coefficient (r P ) between the FL and abmd was decomposed using the SOLAR version 2.0 as: qffiffiffiffiffiffiffiffiffi qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi r P ¼ r G h 2 1 h2 2 þ r E 1 h h 2 2 where rg and re represent the shared additive genetic and unmeasured environmental influences, respectively, while h 2 1 and h 2 2 are the heritabilities of trait 1 and trait 2, respectively. A significance level for the difference between estimated genetic correlation and rg ¼ 0 (no genetic correlation), as well as rg ¼ 1.0 (absolute genetic correlation) was calculated. For additional details regarding the bivariate extensions to VCA, see the following articles. (17,32 34) We calculated 95% confidence intervals (CI) of h 2 and correlations between traits empirically using N ¼ 200 nonparametric bootstrap samples (generated by resampling pedigrees with replacement 200 times). We calculated the h 2 and phenotypic, genetic, and environmental correlations for these bootstrap samples, and the lower and upper 95% CIs as the 2.5 and 97.5 percentiles of the bootstrap distribution. Results Table 1 shows descriptive statistics of the study participants and their HR-pQCT- and DXA-derived bone measurements. The average age of the Framingham subjects included in this study was 71.7 years; 57% were women (mostly postmenopausal, 98.7%). The sample included up to 1087 participants with HR-pQCT at the radial site and 1194 at the tibial site, who were members of pedigrees. The participant pairs generally belonged Table 1. Sample Characteristics and Bone Measurements Variable (unit) Mean (or %) SD Age (years) Height (inches) Sex (men/women) 43.0/57.0% Postmenopausal women 98.7% Failure load (N) Radial (n ¼ 1087) Tibial (n ¼ 1194) DXA abmd (g/cm 2 ) Ultradistal radius Femoral neck to 2- or 3-member families (Table 2), representing mostly pairs of relatives: sibling (258 pairs), avuncular (16), and first cousins (105), largely concordant by sex. The age difference between family members was years. Failure load values at the ultradistal radius and at the ultradistal tibia were highly correlated (r ¼ 0.906). There were also substantial phenotypic correlations between FL and height: and for radius and tibia, respectively (both p < ). As follows from Table 3, failure load values at the radius and tibia were strongly correlated with cortical area, trabecular bone volume (BV/TV), trabecular density, total density, cortical thickness, total area, and trabecular number, and less strongly with cortical density and trabecular area. As shown in Table 4, estimates of heritability adjusted for age and sex (model 1) were 0.52 for the radius and 0.50 for the tibia (both p < ), with no appreciable difference when adjusted for height (both p < ). Additional adjustment for the regional abmd notably decreased the point estimate for h 2 of the radius (0.22, p ¼ 0.045) and less profoundly for the tibia, h 2 ¼ 0.38 (p < 0.001); there was, however, overlap between the 95% confidence interval (CI) of unadjusted and adjusted for abmd models (for the radius, and , respectively). Table 2. Related Pairs Total related pairs (sex discordant related pairs) Type Siblings 258 (127) Avuncular 16 (9) Half-siblings 11 (4) Double 1st cousins 2 (1) 1st cousins 105 (53) 1st cousins, once removed 8 (3) 2nd cousins 3 (0) Pedigree size % % % 5 8.7% 6 3.0% 7 3.5% 8þ 20.4% Table 3. Phenotypic Correlations Between the Failure Load and Bone Microarchitecture and Density Traits at Two Bone Sites Variable Radial Tibial Cortical area, Ct.Ar (mm 2 ) Bone volume to total volume ratio, BV/TV Trabecular density, Tb.vBMD (mg/cm 3 HA) Total density, Tt.vBMD (mg/cm 3 HA ) Cortical thickness, Ct.Th (mm) Total area, TtAr (mm 2 ) Trabecular number, Tb.N (mm 1 ) Cortical density, Ct.vBMD (mg/cm 3 HA) Trabecular area, Tb.Ar (mm 2 ) Bold indicates R > 0.5. Journal of Bone and Mineral Research GENETIC CORRELATIONS OF mfea-estimated BONE STRENGTH 2153

4 Table 4. Heritability (Estimate SE [95% CI]) of Failure Load Adjusted for Covariates Model 1 a Model 2 b Model 3 c Radial bone ( ) ( ) ( ) Tibial bone ( ) ( ) ( ) a Model 1: adjusted for sex and age. b Model 2: model 1 plus height. c Model 3: model 2 plus proximate abmd (UD radial abmd or FN abmd). Table 5. Correlations Between the Failure Load and Areal Bone Mineral Density Measured by DXA at Two Bone Sites Model of adjustment r P [95% CI] a r G SE [95% CI] (p0, p1) b r E SE [95% CI] (p0) Radial FL and DXA UD radial abmd Age and sex [ ] Age, sex, and height [ ] Tibial FL and DXA FN abmd Age and sex [ ] Age, sex, and height [ ] [ ] ( ; 0.092) [ ] ( ; 0.155) [ ] ( ; ) [ ] ( ; ) [ ] ( ) [ ] (0.0009) [ ] (0.035) [ ] (0.039) a r P ¼ phenotypic; r G ¼ genetic; r E ¼ environmental correlation. Partial correlations. b p value for difference from r G ¼ 0 and p value for difference from r E ¼ 1.0, respectively. Bold indicates p Having established the heritabilities for failure load measures, we then tested for correlations between FL and DXA-derived abmd. There was a high phenotypic correlation between covariate-adjusted failure load at the radius and ultradistal abmd (r P ¼ 0.819; Table 5). In bivariate variance component analyses, there was a high genetic correlation between covariate-adjusted failure load at the radius and UD abmd ( [SE]); environmental correlation was also highly significant (r E ¼ , p ¼ ). Additional adjustment for height resulted in little change in correlations; thus, the 95% CI for the genetic correlation ( ) was overlapping between the unadjusted and adjusted for height models ( and , respectively). Correlations between covariate-adjusted failure load at the tibia and femoral neck abmd were slightly lower because these are distinct skeletal sites. Moderate phenotypic correlation was found between tibial failure load and FN abmd (r P ¼ 0.594), which was slightly attenuated by additional adjustment for height (0.577). r G was and r E ¼ These correlations showed little change after adjustment for height (Table 5). Discussion We previously reported data on the heritability estimates for bone microstructure and vbmd from the same sample of older men and women from a population-based cohort. (17) That study suggested that vbmd and bone microarchitecture indices of the non-weight-bearing and weight-bearing bones measured by HR-pQCT are heritable. To date, no studies of heritability of HR-pQCT-derived bone strength have been published. Thus, our finding of substantial heritabilities of height- and other covariate-adjusted failure load from 47% to 52% (radius) and 50% (tibia) is significant. This h 2 estimate is comparable with the heritability for covariate-adjusted ultradistal radius abmd (41.7% (17) ) and femoral neck abmd (54.3% (19) ) in the Framingham sample. Our heritability estimates are similar for the non-weightbearing radius and weight-bearing tibia, which is not surprising, given their failure load values were highly correlated (r ¼ 0.906). Moreover, further adjustment for height slightly augmented h 2 at both the radius and the tibia but did not change either of these estimates considerably. Although most microarchitecture traits positively correlate with height (see also Boutroy and colleagues (13) and Bjornerem and colleagues (35) ), and the adjustment for height did, in general, decrease h 2 in our study of individual microstructural traits, (17) the estimated failure load seems to be independent of a person s adult height (despite phenotypic correlations between failure load and height being relatively high, and for radius and tibia, respectively). One of the important findings from our data was that additional adjustment for abmd of the same or a proximal long bone seemingly decreased the failure load heritability, especially at the radial bone, where we had abmd measured at the similar site. Although the difference between failure load adjusted or not for abmd was not significant (confidence intervals overlapped), the point estimates showed a trend to be lower after adjustment for abmd. The variability that leads to the wide confidence intervals indicates that either the current study is underpowered to detect a true difference in failure load 2154 KARASIK ET AL. Journal of Bone and Mineral Research

5 heritability with and without abmd adjustment or a true difference does not exist. Notably, the adjustment did not fully eliminate failure load heritability (abmd-adjusted h 2 ¼ 22%, p ¼ 0.045), which suggests that h 2 of bone strength is independent of DXA-derived abmd. It is important to note that the abmd is not expected to fully explain the bone strength because of its two-dimensional nature; we now demonstrate that its genetic determinants are shared with bone strength only to some degree. There were high phenotypic correlations reported between HR-pQCT-derived failure load and total vbmd (r ¼ for the radius and r ¼ for the tibia), on the one hand, and between total vbmd at the radius and UD abmd (r ¼ 0.745); (17) therefore, an adjustment for regional abmd was expected to decrease heritability of the radial failure load. Unfortunately, the distal-tibia abmd was not available because it was not directly measured with the DXA scanner, so we used femoral neck abmd instead. High phenotypic correlation between covariate-adjusted failure load at the radius and ultradistal forearm abmd (0.819) can be attributed mostly to genetic correlation between these traits ( ), though environmental correlation between failure load at the radius and UD abmd was also substantial ( ). Correlations between failure load at the tibia and femoral neck abmd were slightly lower (r P ¼ 594, r G ¼ 0.713, and r E ¼ 0.453), indicating differences between these distinct skeletal sites, ultradistal tibia, and proximal femur. These correlations, as well as heritability estimates, are robust to sample-size fluctuations they did not change when 13 Framingham Offspring participants who fractured both ankles and 10 participants who fractured both forearms were excluded from the analysis. These high genetic correlations suggest that the genetic variance in HR-pQCT-measured failure load is partly captured by conventional abmd, suggesting that there are common (as well as specific) genetic factors that govern regional abmd and estimated failure load of the radius and tibia. Areal BMD measured by DXA is derived from planar images in which cortical and trabecular compartments are superimposed and is not able to capture size effects the way that vbmd does. Although areal DXA images are unable to discriminate between cortical and trabecular bone compartments, these measures still provide very useful insights into skeletal biology and are used clinically, as abmd seems to reflect the essence of bone structure and as is shown here bone strength to some degree. High genetic correlations between measures suggest the possibility of a shared etiology, possibly at the cellular and molecular level. (36) Note, however, that environmental correlations between the microarchitecture-based failure load and abmd were also substantial, which suggest that similar environment might influence these bone characteristics, although we do not have detailed information about environmental factors. Still, we may speculate that genetic factors contribute to variability of HR-pQCT-derived failure load and abmd more than do environmental factors, as genetic correlations are higher than environmental ones for both the radius and the tibia. There were several limitations of our study. First, although our sample was substantial, with up to 1087 phenotyped participants (radial site) and 1194 tibial, the sample was predominantly of white origin and the sample size still too modest to allow stratification by sex or by age. There might be sex- and age-specific genetic signals for bone microarchitecture (23,37) (similar to the abmd (38) ), thus larger studies are needed to clarify whether there are age, sex, and ethnic differences in these genetic effects. Second, we did not measure tibial abmd, thus we cannot calculate genetic correlations between abmd and HR-pQCT-derived failure load at the tibia. Also, failure load was estimated only in one direction as axial compressive strength. For the radius, this would correspond to the loading on the outstretched arm after a fall from standing height; (39) other types of loading may provide additional insights into the heritability of bone strength measured by failure load. Finally, because we used a fixed distance from the growth plate to begin the scans, the cortical versus trabecular compartment measures may have been influenced by limb length differences between individuals. Adjustment for height may not completely eliminate such differences. Thus some of our heritability values may have been affected by slightly different measurement starting sites used by DXA and HR-pQCT protocols. Importantly, our findings may be used to help inform other studies of the genetics of bone strength. Thus, knowledge of the shared heritability between the bone traits may prove helpful in defining the best phenotypes to be used in the planning of genetic studies of these novel measures. In conclusion, our findings of high heritability of the HR-pQCT-based mfeaestimated long bone failure load and that it shares some genetic regulation with areal BMD measured by DXA highlight the importance of further work to identify the specific variants underlying genetic susceptibility to fractures. Knowledge of molecular mechanisms underlying bone strength is important for fracture risk prediction and treatment outcomes. Disclosures SKB is co-owner of Numerics88 Solutions Ltd. All other authors state that they have no conflicts of interest. Acknowledgments Research reported in this publication was supported by the National Institute of Arthritis Musculoskeletal and Skin Diseases of the National Institutes of Health under award no. R01AR The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Additional support was provided by Friends of Hebrew SeniorLife and a research grant from the Investigator Initiated Studies Program of Merck Sharp & Dohme. DK was supported by ISF grant no. 1283/14. Authors roles: Study design and execution: DPK, MLB, KEB, and SD. Data collection: DPK, MLB, SKB, and KEB. Measurements: MLB, SKB, and DPK. Statistical analyses: SD, CTL, and DL. DK and SD take responsibility for the integrity of the data analysis. Drafting manuscript: DK. Data interpretation and approving final version of manuscript: all authors. References 1. Borrelli J. Taking control: the osteoporosis epidemic. Injury. 2012;43(8): Link TM. 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