Back pain is a common condition with a high social impact and represents a global health burden. Intervertebral disc disease (IVDD) is one of the major causes of back pain; no therapeutics are currently available to reverse this disease. The impact of bone mineral density (BMD) on IVDD has been controversial, with some studies suggesting osteoporosis as causative for IVDD and others suggesting it as protective for IVDD. Functional studies to evaluate the influence of genetic components of BMD in IVDD could highlight opportunities for drug development and repurposing. By taking a holistic 3D approach, we established an aging zebrafish model for spontaneous IVDD. Increased BMD in aging, detected by automated computational analysis, is caused by bone deformities at the endplates. However, aged zebrafish spines showed changes in bone morphology, microstructure, mineral heterogeneity, and increased fragility that resembled osteoporosis. Elements of the discs recapitulated IVDD symptoms found in humans: the intervertebral ligament (equivalent to the annulus fibrosus) showed disorganized collagen fibers and herniation, while the disc center (nucleus pulposus equivalent) showed dehydration and cellular abnormalities. We manipulated BMD in young zebrafish by mutating sp7 and cathepsin K, leading to low and high BMD, respectively. Remarkably, we detected IVDD in both groups, demonstrating that low BMD does not protect against IVDD, and we found a strong correlation between high BMD and IVDD. Deep learning was applied to high-resolution synchrotron µCT image data to analyze osteocyte 3D lacunar distribution and morphology, revealing a role of sp7 in controlling the osteocyte lacunar 3D profile. Our findings suggest potential avenues through which bone quality can be targeted to identify beneficial therapeutics for IVDD.

Zebrafish scales are mineralised plates that can regenerate involving de novo bone formation. This presents an opportunity to uncover genes and pathways relevant to human musculoskeletal disease relevant to impaired bone formation. To investigate this hypothesis, we defined transcriptomic profiles of ontogenetic and regenerating scales, and identified 604 differentially expressed genes (DEGs) that were enriched for extracellular matrix, ossification, and cell adhesion pathways. Next, we showed that human orthologues of DEGs were 2.8 times more likely to cause human monogenic skeletal diseases (P<8×10−11), and they showed enrichment for human orthologues associated with polygenetic disease traits including stature, bone density and osteoarthritis (P<0.005). Finally, zebrafish mutants of two human orthologues that were robustly associated with height and osteoarthritis (COL11A2) or bone density only (SPP1) developed skeletal abnormalities consistent with our genetic association studies. Col11a2Y228X/Y228X mutants showed endoskeletal features consistent with abnormal growth and osteoarthritis, whereas spp1P160X/P160X mutants had elevated bone density (P<0.05). In summary, we show that transcriptomic studies of regenerating zebrafish scales have potential to identify new genes and pathways relevant to human skeletal disease.

The spine is the central skeletal support structure in vertebrates consisting of repeated units of bone, the vertebrae, separated by intervertebral discs that enable the movement of the spine. Spinal pathologies such as idiopathic back pain, vertebral compression fractures and intervertebral disc failure affect millions of people world-wide. Animal models can help us to understand the disease process, and zebrafish are increasingly used as they are highly genetically tractable, their spines are axially loaded like humans, and they show similar pathologies to humans during ageing. However biomechanical models for the zebrafish are largely lacking. Here we describe the results of loading intact zebrafish spinal motion segments on a material testing stage within a micro Computed Tomography machine. We show that vertebrae and their arches show predictable patterns of deformation prior to their ultimate failure, in a pattern dependent on their position within the segment. We further show using geometric morphometrics which regions of the vertebra deform the most during loading, and that Finite Element models of the trunk subjected reflect the real patterns of deformation and strain seen during loading and can therefore be used as a predictive model for biomechanical performance.

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