Methods

We use model-based and multivariate statistical methods of functional and structural magnetic resonance imaging (MRI) in combination with anthropometric data, neuropsychological tests, behavioural measures, peripheral blood measures and genotyping of young and old cohorts.

  • MRI: We use in-house developed preprocessing pipelines as well as the software packages SPM, FSL and FreeSurfer to analyse brain data. Some examples include cortical thickness analysis, Voxel-Based-Morphometry (VBM), automated segmentation algorithms, resting-state functional connectivity, diffusion-tensor-imaging (DTI), tract-based spatial statistics (TBSS) 
            
  • Anthropometry: Measures of Body-Mass-Index, waist-to-hip ratio, MRI-based visceral and subcutaneous boddy fat, bioelectrical impedance analysis, ...        

  • Neuropsychology: Memory performance, pattern recognition tasks, verbal fluency, cognitive flexibility, processing speed, ...

  • Eating behaviour: Analyses of food-frequency questionnaires, psychological eating-related questionnaires (e.g. Yale food addiction scale), measures of impulsivity and compulsivity,

  • Other lifestyle factors: Physical activity, smoking, ...     

  • GWAS & Genotyping: data-driven genome-wide association studies (GWAS) and hypothesis-driven analyses of APOE, BDNF, COMT, and other obesity-associated single nucleotide polymorphisms

  • Blood-based biomarkers: Glucose metabolism, insulin sensitivity, lipid metabolism, gastrointestinal hormones, adipokines, ...

  • Microbiome/Metabolomics: We use high-throughput methods such as 16S sequencing
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