Utilisation of a novel method of measuring spinal curvature from total body DXA scans to understand the risk factors for curve onset and progression.

Scoliosis is a 3D-tortional rotation of the spine, and large scoliotic curves are associated with increased pain, reduced lung function, lower body weight, reduced societal participation and reduced quality of life. Little is understood about risk factors for scoliosis initiation and progression because research is hampered by lack of population-based research. This is because radiographs cannot be performed on entire populations because of the exposure to relatively high levels of ionizing radiation, equivalent to an entire year’s background radiation. To address this, we have developed a novel automated method of measuring spinal curvature (scoliosis) from total body DXA scans for research purposes in collaboration with the University of Oxford. This PhD will apply this method to insert the scoliosis phenotype into UKBiobank plus many other additional research cohorts around the world that have total body DXA scans. These include cohorts that could be used to research adolescent scoliosis initiation (such as ALSPAC, RAINE, GOOD, CHOPs, Indiana Cohort study, Fenland Study, Pelotas birth cohort, ERF, deCODE, ORCADES and Generation R, n=27000 participants); cohorts that could be used to research adolescent scoliosis progression (such as ALSPAC, CHOPs and Birth to Twenty cohort, n=5000 participants, and many are planning future DXAs so this number will increase); and cohorts that could be used to research adult degenerative scoliosis (such as UK Biobank (planning to perform 93000 more DXAs) Twins UK, ERF, The Rotterdam Study , ORCADES, deCODE, CHS, B-PROOF, OPRA, MrOS Sweden, Health ABC and WHI, n=52500 participants currently).
The specific aims of this PhD are (1) To systematically review the literature to identify what is already known about potential risk factors for scoliosis initiation and progression, whilst understanding possible biases and confounders; (2) To utilise the population-based research cohorts to identify potential clinical risk factors for scoliosis initiation and progression; and (3) To utilise the population-based research cohorts to identify potential genetic risk factors for scoliosis initiation and progression, in collaboration with ISGIG.
Outcomes of this PhD will be (1) To learn transferable research skills in systematic literature reviewing and meta-analysis, cohort study design, statistical analysis including linear and logistic multivariable regression, how to deal with missing data, and scientific communication including oral and verbal presentations plus paper writing. Software use includes MatLab and Stata; (2) To receive formal training in epidemiology, statistical analysis, MatLab, ICH-GCP, IRAS; (3) To learn about the Lunar and Hologic total body DXA scanners and how to retrieve and manipulate the images, and collect data for research purposes; (4) To facilitate collaborations between large research groups by leading on insertion of the scoliosis phenotype into the population-based research cohorts. This will involve ethics applications and development of research governance paperwork; and (5) To publish at two to six papers from this main project, and present the findings at local, national and international research meetings.