About
We aim to examine how polygenetic risk scores predict obesity and vascular pathology, and whether that effect is mediated by factors such as cognition, affective symptoms, dietary patterns and brain differences. We will develop two lines of research. (i) The first line (Project 1) is aimed at testing whether neurobehavioral phenotypes mediate the effect of obesity-related polygenetic scores (obPGS) on obesity. (ii) The second line (Project 2) will evaluate the phenotypic overlap between vascular pathology and depressive symptoms and their association with alterations in brain connectivity and cognition. Health conditions under investigation: obesity, vascular pathologies, affective symptoms. In modern societies, determining which factors compromise successful aging is a major goal for scientists and clinicians. Obesity is an example of such factors that can put general health in jeopardy; especially since it can trigger the development of other metabolic diseases. The present project will enrich our comprehension of obesity and vascular pathologies, paving a solid way to the development of future precision medicine strategies aimed at preventing and/or treating obesity and vascular pathologies. As such, this aim is well aligned with UK Biobank?s stated purpose of improving the prevention, diagnosis and treatment of complex health problems. We will analyze the following data: (i) vascular markers (e.g., blood pressure, cholesterol levels or body fat composition), (ii) affective symptomatology (e.g., depression symptoms), (iii) cognitive functioning; (iv) MRI acquisitions; (iv) genotype data. Project 1: we will test whether neurobehavioural phenotypes (e.g., executive functions, brain differences) mediate the effect of obesity-related polygenetic scores (obPGS) on obesity. We will isolate which parts of the obPGS relate to these specific neurobehavioural phenotypes. Project 2: we will use structural equation modeling to examine the associations between (i) vascular factors, (ii) depressive symptoms, (iii) cognitive function, and (iv) brain connectivity. We will analyze all participants (n=100,000) with complete data available for (i) vascular markers (e.g., blood pressure, cholesterol levels or body fat composition), (ii) affective symptomatology (e.g., depression symptoms), (iii) cognitive functioning; (iv) MRI acquisitions; (iv) full genome data.