Genetic determinants of trabecular bone score and their relationships with bone mineral density and fragility fractures — ASN Events
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  3. Genetic determinants of trabecular bone score and their relationships with bone mineral density and fragility fractures

Genetic determinants of trabecular bone score and their relationships with bone mineral density and fragility fractures (#26)

Haojie Lu 1 , Griffin Tibbitts 2 , Gloria Hoi-Yee Li 3 , Monika Frysz 4 , Nilabhra R Das 5 , James T Smith 6 , Mijin Jung 4 , Kaitlyn A Flynn 5 , Yuandan Zhang 5 , Benjamin Mullin 5 , Christine W Lary 2 , Katerina Trajanoska 1 , Lissette de Groot 7 , Ching-Lung Cheung 8 , Natasja M van Schoor 9 , André G Uitterlinden 1 , Nathalie van der Velde 10 , Benjamin G Faber 4 , Ryan C Chai 6 , David M Evans 11 , Jonathan H Tobias 4 , Peter I Croucher 6 , Graham R Williams 12 , J. H. Duncan Bassett 12 , Fernando Rivadeneira 1 , Douglas P Kiel 13 , John P Kemp 5 , Carolina Medina-Gomez on behalf of the GEFOS/CHARGE consortium 1
  1. Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
  2. Roux Institute at Northeastern University, Portland, Maine, USA
  3. Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, China
  4. Musculoskeletal Research Unit, University of Bristol, Bristol, Avon, UK
  5. Mater Research Institute - The University of Queensland, Woolloongabba, QLD, Australia
  6. Cancer Plasticity and Dormancy Program, Garvan Institute of Medical Research, Sydney, NSW, Australia
  7. Division of Human Nutrition, Wageningen University, Wageningen, The Netherlands
  8. Department of Pharmacology and Pharmacy, The University of Hong Kong, Hong Kong, China
  9. Epidemiology and Data Science, Vrije Universiteit, Amsterdam, The Netherlands
  10. Internal Medicine, Section of Geriatric Medicine, University of Amsterdam, Amsterdam, The Netherlands
  11. Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
  12. Molecular Endocrinology Laboratory, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
  13. Department of Medicine, Hebrew SeniorLife, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA

Background: Trabecular Bone Score (TBS) is derived from lumbar spine (LS) DXA-images and measures pixel-level gray-scale intensities and spatial distribution of bone. TBS is approved for use in conjunction with femoral neck bone mineral density (FN-BMD) to improve fracture risk assessment. However, it remains unclear whether TBS influences fracture risk through genetic mechanisms independent of FN-BMD. Addressing this knowledge gap has important implications for genetically informed fracture risk assessment and for the discovery of novel therapeutic targets that regulate bone strength independently of BMD.

Methods: We performed a genome-wide association study (GWAS) meta-analysis of TBS in 44,767 individuals from 8 cohorts that were predominantly European. TBS-associated SNPs were identified by GCTA-COJO and used in a multivariable Mendelian Randomization framework to estimate the effect of TBS on fractures after accounting for FN-BMD. TBS-associated genes were identified using MAGMA gene-based tests. Gene-set analyses determined whether TBS-associated genes were enriched for genes involved in rare skeletal disorders; genes regulating bone structure in mice, and genes upregulated in different bone and marrow cells. TBS-associated genes with previously unrecognized roles in bone biology were investigated further in ~1000 knockout mouse lines from the Origin of Bone and Cartilage Disease (OBCD) skeletal phenotyping program.

Results: GWAS identified TBS-associated SNPs in 37 loci. Several were not identified in recent GWAS of LS-BMD and FN-BMD that were twice the size of our study (N~80,000). Multivariate analyses showed that higher genetically predicted TBS was associated with lower risk of fracture after adjusting for FN-BMD (OR=0.77, CI95%=0.67–0.88). Gene-based tests identified 78 TBS-associated genes, and they were enriched for genes involved in osteosclerotic disorders (p=1×10-9), mutant mice with abnormal bone structure (p=8×10-6), and genes upregulated in osteoblasts (p=8×10-6). Consistent with our GWAS meta-analysis, OBCD phenotyping identified markedly reduced trabecular thickness and decreased trabecular bone volume (p<0.001) in mice deficient in Zinc finger protein 408 (Zfp408-/-).

Conclusions: Our study provides novel insights into the cellular and genetic determinants of TBS and highlights the potential of genetically predicted TBS to enhance fracture risk assessment.  Furthermore, the unique TBS phenotype provides insights into distinct genetic contributions to the spatial distribution of bone mineralization.