Abstract

The genetic determinants of osteoporosis remain poorly understood, and there is a large unmet need for new treatments in our ageing society. Thus, new approaches for gene discovery in skeletal disease are required to complement the current genome-wide association studies in human populations. The International Knockout Mouse Consortium (IKMC) and the International Mouse Phenotyping Consortium (IMPC) provide such an opportunity. The IKMC generates knockout mice representing each of the known protein-coding genes in C57BL/6 mice and, as part of the IMPC initiative, the Origins of Bone and Cartilage Disease project identifies mutants with significant outlier skeletal phenotypes. This initiative will add value to data from large human cohorts and provide a new understanding of bone and cartilage pathophysiology, ultimately leading to the identification of novel drug targets for the treatment of skeletal disease.

Highlights

  • A novel strategy for osteoporosis gene discoveryStudies of human monogenic extreme phenotype disorders have been instrumental in discovering genetic and molecular mechanisms of common diseases including obesity and diabetes (Yamagata et al 1996, Montague et al 1997)

  • A new approach to osteoporosis gene discovery involves systematic identification of extreme skeletal phenotypes in mutant mouse lines that carry singlegene knockouts representing all the known proteincoding genes. This approach has been made possible by the International Knockout Mouse Consortium (IKMC), whose aim is to disrupt each of the protein-coding genes in C57BL/6 mice, and the International Mouse Phenotyping Consortium (IMPC) that has established a multidisciplinary and broad primary phenotype screen to characterise these mutant mice

  • By using samples from mice that have undergone the IMPC phenotyping pipeline, a bespoke rapid-throughput multi-parameter skeletal phenotyping platform has been applied systematically to detect significant phenotypes by screening minimal number of samples. This phenotyping programme exploits the excellent replication of human skeletal disease in mice, and novel susceptibility genes can be validated by interrogating human osteoporosis cohorts

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Summary

Introduction

Studies of human monogenic extreme phenotype disorders have been instrumental in discovering genetic and molecular mechanisms of common diseases including obesity and diabetes (Yamagata et al 1996, Montague et al 1997). A new approach to osteoporosis gene discovery involves systematic identification of extreme skeletal phenotypes in mutant mouse lines that carry singlegene knockouts representing all the known proteincoding genes This approach has been made possible by the International Knockout Mouse Consortium (IKMC), whose aim is to disrupt each of the protein-coding genes in C57BL/6 mice, and the International Mouse Phenotyping Consortium (IMPC) that has established a multidisciplinary and broad primary phenotype screen to characterise these mutant mice. By using samples from mice that have undergone the IMPC phenotyping pipeline, a bespoke rapid-throughput multi-parameter skeletal phenotyping platform has been applied systematically to detect significant phenotypes by screening minimal number of samples. This phenotyping programme exploits the excellent replication of human skeletal disease in mice, and novel susceptibility genes can be validated by interrogating human osteoporosis cohorts

Rapid skeletal phenotyping of
Gene discovery from skeletal extreme phenotypes
Regulatory mechanisms in bone turnover
Increased bone
Increased Osteopetrosis
Autosomal dominant Increased bone
Gene discovery drives therapeutic innovation
The Human Genome Project and association studies
Transcriptomics and osteoporosis
The mouse as an essential tool for osteoporosis gene discovery
International knockout mouse programmes
Pipeline phenotyping of knockout mice
Ancillary IMPC projects
OBCD phenotyping techniques
Pilot study
Other skeletal phenotyping programmes
Current OBCD project goals
Findings
Detailed analysis of extreme phenotypes
Full Text
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