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Abstract:
Obesity is a complex multigenic trait and has been linked to abnormal functionality of homeostasis brain networks (Schwartz 2000). In patients,volumetric changes of the hypothalamus correlated with changes in body mass index and eating behaviour (Gorges 2017), and higher grey mattervolume in the hypothalamus was associated with higher trait hunger in healthy adults (Yao 2016). Whether obesity-genes affect the humanhypothalamus has however not been addressed. We therefore aimed to determine the effects of obesity-risk alleles on the human hypothalamus using asegmentation protocol for in vivo magnetic resonance imaging (MRI) of the hypothalamus. In total, 338 healthy adults (162 women, 176 men, 20-80years) of the LIFE study (Loeffler 2015) who underwent multimodal MRI, anthropometric assessments and fasting blood draw were included. Volumeand mean diffusivity (MD) of the hypothalamus derived by segmentation on T1-weighted 3T MRI using a customized unified segmentation algorithm(Schindler 2013) and co-registration of diffusion-tensor images. Semi-manual segmentation showed good spatial agreement (DSC 0.88-0.94) andmean hypothalamus volume was higher in males compared to females (adjusted for age, F = 11.26, p = 0.001). In addition, mean MD, as an inversemeasure of hypothalamus barrier density, was lower in females compared to males (adjusted for age, F = 16.28, p < 0.001) and higher age correlatedwith higher MD (r = 0.42, p < 0.001). Ongoing development of the segmentation technique will enable to automattically define the hypothalamus inall LIFE-participants (total n = 2636) and other cohort studies, to eventually reach meaningful sample sizes for genetic analyses. This might help tobetter understand central mechanisms of obesity.
