Student-onderzoeker

MHeNs Research Institute, FHML, UM

Altered brain white matter microstructure (WMM), as measured using Diffusion Tensor Imaging (DTI), has been observed in multiple psychiatric and neurological diseases, as well cardiometabolic illnesses. Measures of WMM across major white matter tracts, including diffusivity and fractional anisotropy, have been shown to be highly heritable phenotypes in twin studies. However, what the actual genetic factors are that contribute to that heritability is still relatively unknown. This project aims to investigate the genetic factors contributing to WMM. Setting and Methods: This project will be carried out within the Mental Health and Neuroscience Research Institute, and will utilize the Maastricht Study dataset (n=~6000 with DTI data). The Maastricht Study is enriched for Type 2 Diabetes (T2D), and studies the effects of T2D on the brain and brain-based comorbidities (e.g. depression and cognitive impairment) , amongst other effects. The study has acquired clinical and neuroimaging data, and genome-wide genetic marker data. This internship project will employ neuroimaging analysis (e.g. using FSL, Freesurfer), and statistical analysis (MANOVA, regression analysis), and possibly statistical geneti c methods such as polygenic risk scoring and linear regression analysis. Impact: Understanding the genetic mechanisms underlying brain white matter microstructure could help in the development of more targeted therapy with higher success rates, help predict disease risk, facilitate early diagnosis, and predict treatment response. Knowledge of statistical analysis (MANOVA, regression analysis). Experience with SPSS and/or R is an asset. Knowledge of (statistical) genetics is an asset. Knowledge of neuroimaging (MRI, DTI) techniques. Experience with neuroimaging data processing and analysis is an asset.