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Click here to search FindAPhD.com for PhD studentship opportunitiesAbout the Project
The goal of this PhD is to combine statistical and molecular genetics approaches to identify and assess the therapeutic potential of OP drug targets.
This PhD encompasses three aims:
(a) Achieving major advances in understanding the genetics of OP by performing the largest whole-exome and genome sequencing study of OP in ~500,000 subjects from The UK Biobank Study(4).
(b) Identifying and prioritising candidate genes for future functional validation as drug targets by: (i) identifying novel low frequency, loss of function variants in protein coding regions of OP associated loci(5), (ii) screening identified candidates for predicted adverse effects by mining phenome-wide association data across >2000 traits and diseases(6), and (iii) screening implicated genes in my collaborators’ established in vivo mouse(7) and zebrafish skeletal phenotyping programs(8).
(c) Identifying novel molecular biomarkers that are causally related to OP, and that represent excellent opportunities for drug repositioning, by performing Mendelian randomization analysis of thousands of proteomic and metabolic biomarkers in hundreds of thousands of individuals(9).
References
2. Sambrook, P.N. et al. Preventing osteoporosis: outcomes of the Australian Fracture Prevention Summit. Med J Aust 176 Suppl, S1-16 (2002).
3. Baron, R. & Hesse, E. Update on bone anabolics in osteoporosis treatment: rationale, current status, and perspectives. J Clin Endocrinol Metab 97, 311-25 (2012).
4. Bycroft, C. et al. The UK Biobank resource with deep phenotyping and genomic data. Nature 562, 203-209 (2018).
5. Sanseau, P. et al. Use of genome-wide association studies for drug repositioning. Nat Biotechnol 30, 317-20 (2012).
6. Diogo, D. et al. Phenome-wide association studies across large population cohorts support drug target validation. Nature Communications 9(2018).
7. Freudenthal, B. et al. Rapid phenotyping of knockout mice to identify genetic determinants of bone strength. Journal of Endocrinology 231, R31-R46 (2016).
8. Hammond, C.L. & Moro, E. Using transgenic reporters to visualize bone and cartilage signaling during development in vivo. Front Endocrinol (Lausanne) 3, 91 (2012).
9. Evans, D.M. et al. Mining the Human Phenome Using Allelic Scores That Index Biological Intermediates. Plos Genetics 9(2013).