The genetics underlying imaging phenotypes and correlated physiological measures

Lead Research Organisation: University of Edinburgh
Department Name: Sch of Molecular. Genetics & Pop Health


Imaging techniques are widely used for early detection and diagnosis of disease. Although widely adopted in clinical practice, it is only partially understood how structural information in medical images relates to physiological function, which may amenable for treatment. Furthermore, our understanding of how imaging phenotypes are determined by genetics and to what degree the genetic control of disease and the imaging phenotypes is shared is very limited. Taken this into account, this project is focused in understanding how genetics control imaging phenotypes and correlated physiological measures. Specifically, structural information and functional information will be obtained from more than 500,000 fundus images.
Identifying which imaging phenotypes have genetic correlations (i.e. a genetic shared component) with the disease of interest would inform of shared control pathways and to match disease-subtypes and imaging phenotypes to different biological pathways. Furthermore, computational modelling approaches can be used to convert structural images into physiologically relevant traits. During this project we will develop both structural measurements and modelling-based estimates of blood flow (i.e. haemodynamics) in the eye from retinal images in UK Biobank, a large prospective epidemiological study of 500,000 individuals. Another objective of this project is knowing whether these low-level phenotypes have a bigger genetic contribution than high-level phenotypes. Our goal is to identify genes influencing the structural and haemodynamic measurements and dissect their genetic and environmental variation. Further studies will allow us to analyze if these genes could have a medical application, for instance, a druggable gene or a genetic biomarker.
In addition, one of the challenges of this project is the high number of samples in the project because each sample must be analyzed and then merged with all the other results. So, the purpose of this study, in addition to the knowledge obtained from the fundus images and its genetic analysis, is develop a new approach that combines different types of information towards an objective, such as early diagnosis, periodical revisions and stablishing new therapeutic targets.


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