Background

Cortical bone density measured using pQCT is a composite of tissue mineral density - which is higher in older, more mature bone - and cortical porosity. Bone resorption may affect both components; if older, denser bone is remodelled and replaced with new bone, overall tissue density will fall. The number of remodelling events, their duration and the size of the intracortical tunnels created will all impact on cortical porosity. Higher levels of bone remodelling in bone diseases such osteogenesis imperfecta are associated with larger cortical pores and degraded bone architecture. Bone remodelling activity is higher during periods of growth; height velocity is strongly associated with fracture risk in childhood, with the peaks of fracture incidence in boys and girls corresponding to the period immediately following maximal height velocity in both sexes. Thus bone resorption and its regulation are key determinants of both short term functional outcomes during skeletal development and of longer term bone mass accrual and bone architecture.

Our previous findings suggest that the RANK/RANKL/OPG system plays an important role in bone development, presumably as a consequence of effects on bone resorption for which this system is a key regulator (Boyle et al). For example, in our previous studies in Sheffield, we found that levels of OPG (a decoy receptor which acts as an endogenous inhibitor of RANKL-dependent osteoclast activation) are reduced in obese children with prior fractures and reduced bone mass (submitted for publication). A trend was also observed towards increased bone mass as OPG increases (t=1.58; unpublished data based on analyses in 103 children, 53 obese). In meta-analyses based on ALSPAC and the GOOD cohort, RANK and OPG polymorphisms previously reported to be associated with BMD in GWAS studies in adults were also associated with cortical BMD at age 16-18 (submitted for publication), as was a newly identified RANKL polymorphism (paper in preparation).

Whereas setting of the RANK/RANKL/OPG system and hence levels of bone resorption are likely to be influenced by constitutional factors such as genetic polymorphisms, this system may also represent the mechanism whereby other factors influence bone resorption. For example, serum OPG is related to fat mass which is in turn related to bone mass, so it may be that external influences to the skeleton like fat mass affect bone mass via perturbations of the RANK/RANKL/OPG system. Furthermore, to the extent that any tendency for fat mass to affect the latter is genetically determined, it may be that RANK/RANKL/OPG polymorphisms contribute to important gene-environmental interactions for skeletal development.

Aims and purpose

We aim to gain an understanding of the role played by bone resorption in skeletal development, and the extent to which this reflects perturbations in the RANK/RANKL/OPG system, by studying the ALSPAC cohort at age 15.5 years in order to address the following questions:-

1. We will investigate whether bone resorption, based on measurement of fasting serum CTx, affects bone mass. CTx levels will be related to total body DXA including the spine sub-region to study trabecular bone, and pQCT of the mid-tibia to examine cortical bone, as measured concurrently.

2. We will establish whether bone resorption is determined by setting of the RANK/RANKL/OPG axis, by examining whether serum CTx is associated with serum RANKL, OPG or their ratio as measured concurrently, and by studying whether RANKL/OPG levels show similar relationships to skeletal development to those observed for CTx levels in (1).

3. External influences on bone resorption and the RANK/RANKL/OPG system will be identified, by studying associations between RANKL/OPG/CTx levels and other factors known to influence skeletal development such as fat and lean mass (DXA at age 15.5), physical activity (accelerometers at age 14), early life factors such as maternal vitamin D status (measured in last trimester in all mothers), childhood vitamin D (measured in all children at 10), and other metabolic factors such as fasting insulin.

4. Constitutional determinants of the RANK/RANKL/OPG system and bone resorption will be determined by identifying genetic markers for RANKL/OPG levels, based on association with RANK/RANKL/OPG polymorphisms as previously analysed in all ALSPAC children in studies to identify genetic determinants of cortical BMD described above, and with genome wide genetic data which is currently available in 3000 ALSPAC children.

5. To establish whether the RANK/RANKL/OPG system contributes to gene-environmental interactions during skeletal development, we will establish whether associations between external factors and RANKL/OPG/CTx levels identified in (3) interact with genetic markers identified in (4).

6. We will investigate whether high levels of CTx or RANKL, or low levels of OPG, or genetic determinants thereof, can be used to identify children at increased risk of fracture, either alone or in combination.

Summary of plan of investigation

This project will be based on the 2940 children who attended the ALSPAC research clinic at age 15.5 years and had fasting blood samples collected and underwent total body DXA scans. The present proposal is intended to cover the cost of transferring an aliquot of these samples to Sheffield and subsequent analysis of serum RANKL, OPG and CTx by validated immunoassay. Error checking and descriptive statistics will be performed by a 50% time research assistant based at ALSPAC funded by this project. After linkage to the ALSPAC database, these serum levels will be analysed in relation to results collected at the same research clinic ie pQCT scans, total body DXA scans, fasting insulin. These data will also be analysed in relation to RANK/RANKL/OPG genetic polymorphisms as previously analysed in all available children, and to available child GWAS data. RANKL, OPG and CTx levels will also be analysed for associations with other potential influences on skeletal metabolism based on measures collected at other time points, such as habitual level of physical data (Actigraph data at age 14) and vitamin D levels (third trimester mothers, children aged 10).