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Genetic influences on bone loss in the San Antonio Family Osteoporosis study

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Abstract

Summary

The genetic contribution to age-related bone loss is not well understood. We estimated that genes accounted for 25–45% of variation in 5-year change in bone mineral density in men and women. An autosome-wide linkage scan yielded no significant evidence for chromosomal regions implicated in bone loss.

Introduction

The contribution of genetics to acquisition of peak bone mass is well documented, but little is known about the influence of genes on subsequent bone loss with age. We therefore measured 5-year change in bone mineral density (BMD) in 300 Mexican Americans (>45 years of age) from the San Antonio Family Osteoporosis Study to identify genetic factors influencing bone loss.

Methods

Annualized change in BMD was calculated from measurements taken 5.5 years apart. Heritability (h2) of BMD change was estimated using variance components methods and autosome-wide linkage analysis was carried out using 460 microsatellite markers at a mean 7.6 cM interval density.

Results

Rate of BMD change was heritable at the forearm (h2 = 0.31, p = 0.021), hip (h2 = 0.44, p = 0.017), spine (h2 = 0.42, p = 0.005), but not whole body (h2 = 0.18, p = 0.123). Covariates associated with rapid bone loss (advanced age, baseline BMD, female sex, low baseline weight, postmenopausal status, and interim weight loss) accounted for 10% to 28% of trait variation. No significant evidence of linkage was observed at any skeletal site.

Conclusions

This is one of the first studies to report significant heritability of BMD change for weight-bearing and non-weight-bearing bones in an unselected population and the first linkage scan for change in BMD.

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Acknowledgements

We are deeply grateful for the cooperation of the families participating in the SAFOS. This work was supported by research grants R01-AR43351 and P01-HL45522 awarded by the National Institutes of Health. Support for the Frederic C. Bartter General Clinical Research Center was made available by Clinical National Institutes of Health Grant M01-RR-01346. Development of SOLAR is supported by R01-HG59490. We would also like to express our gratitude to three anonymous reviewers for their thoughtful consideration of this work.

Disclaimers

Funding:National Institutes of Health research grants R01-AR43351, P01-HL45522, and R01-HG59490; Clinical National Institutes of Health grant M01-RR-01346.

Conflicts of interest

None.

Author information

Authors and Affiliations

  1. Department of Human Genetics, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA, USA

    J. R. Shaffer & C. M. Kammerer

  2. University of Texas Health Science Center, San Antonio, TX, USA

    J. M. Bruder & R. L. Bauer

  3. Southwest Foundation for Biomedical Research, San Antonio, TX, USA

    S. A. Cole, T. D. Dyer, L. Almasy, J. W. MacCluer & J. Blangero

  4. Division of Endocrinology, Diabetes and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA

    B. D. Mitchell

  5. 130 DeSoto Street, A300 Crabtree Hall, GSPH, Pittsburgh, PA, 15213, USA

    J. R. Shaffer

Authors
  1. J. R. Shaffer
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  2. C. M. Kammerer
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  3. J. M. Bruder
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Corresponding author

Correspondence to J. R. Shaffer.

Appendix

Appendix

DXA measurement and cross-validation

Due to an upgrade in equipment, densitometry was carried out on a pencil-beam Hologic Model 1500 at baseline examination (1997–2000) and a fan-beam Model 4500 W at follow-up examination (2002–2006). For both densitometers, areal BMD was calculated by manufacturer’s software as per current recommendations by dividing bone mineral content (g) by the projected area of the region scanned (cm2). Precision of pencil-beam DXA was 0.009 g/cm2 for spine, 0.007 g/cm2 for total hip, and 0.002 g/cm2 for the manufacturer’s spine phantom. Precision of fan-beam DXA was 0.006 g/cm2 for spine, 0.007 g/cm2 for hip, and 0.002 g/cm2 for radius. Based on the precision of our equipment, least significant change (at 95% confidence) was 3.2 mg/cm2/year for hip, 3.1 mg/cm2/year for spine, and 1.1 mg/cm2/year for forearm DXA measurements.

To address the comparability in our study of measurements taken from Hologic 1500 and 4500 W scanners, we performed cross-calibration of absorptiometry equipment used at baseline and follow-up on 10 participants. Measurements obtained from the two scanners showed near-perfect agreement (R2 values = 99.95%, 99.81%, and 99.87% for spine, total hip, and femoral neck sites, respectively; p-value <10–13 for all). Moreover, regression slopes (0.99, 0.99, and 1.01, respectively, for spine, total hip, and femoral neck; p-value < 10–13 for all) and paired T-tests (p > 0.1, for all) revealed no evidence of systematic or mean differences between absorptiometers. This evaluation of equipment indicates that measurements from Hologic 1500 and 4500 W scanners used in this study are comparable, and that 5-year change in BMD can be adequately calculated. Cross-calibration was not performed for forearm BMD, although we expect that measurements at this site are equally comparable.

Robustness of methods to measurement error

Though we found no evidence to suggest that systematic differences exist in the measurements between scanners, we have nonetheless employed statistical methods that are robust to potential differences. If present, such bias (e.g., systematic measurement error) would decrease our power to detect covariate effects and attenuate our estimate of heritability and linkage, but should not otherwise affect our results. That is, machine differences leading to biased estimates of BMD change could prevent us from assessing environmental and genetic factors affecting BMD change, but would not produce false positive results or lead to overestimation of effects sizes. Our findings, therefore, are conservative. Furthermore, we recognize that deviations from absolute agreement between machines would not adversely affect the genetic analyses as long as the relative BMD between individuals as measured by each scanner is accurate (i.e., variances are comparable). In other words, as long as BMD measured for an individual at baseline is accurate relative to the baseline measurements of the rest of the study sample, and the same holds for measurements at follow-up, the estimation of heritability will be unaffected by inter-machine differences. This is because the genetic modeling used to assess heritability decomposes the trait variance into genetic and environmental components irrespective of the trait mean.

To demonstrate this point, we removed the possibility of any inter-machine effects by first standardizing (mean=0, SD = 1) the BMD measurements in our sample separately at baseline and follow-up, and then analyzing yearly change in standardized values. This process retains the information of individuals’ measurements relative to the sample, but not of the absolute magnitude of measurements. In doing so, potential unknown machine differences that could invalidate direct inter-machine comparisons are avoided. Results (not shown) of change in standardized BMD are very similar to the absolute change reported herein. Likewise, results (not shown) of percent change in BMD were also similar.

Attenuation of heritability due to measurement error

The precision of DXA, which is excellent when looking at cross-sectional BMD measurements, is poor when looking at change over time, leading to considerable uncertainty of actual rates of change. Therefore, rates of change assessed in this study are notably crude, with a large percentage of observations being less than our measurement uncertainty (i.e., no measurable change). Since noise constitutes a substantial portion of the variation in observed rates of change, our results represent a considerable underestimation of the heritability of observed BMD change compared to that of true change (free of such measurement error) [19]. Noise due to our crude assessment of BMD change effectively drowns the heritability signal, and diminishes our ability to detect linkage.

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Shaffer, J.R., Kammerer, C.M., Bruder, J.M. et al. Genetic influences on bone loss in the San Antonio Family Osteoporosis study. Osteoporos Int 19, 1759–1767 (2008). https://doi.org/10.1007/s00198-008-0616-0

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