Abstract
Brain aging refers to the age-depended atrophy of large parts of the brain. However, there is considerable difference in the speed of brain aging between different subjects. Based on machine learning algorithms we have determined the individual deviation from the mean regression over the population. We aim at exploring how depressive disorders, childhood traumatization and polygenetic risk scores (PRS) impact on brain age. PRS (Van der Auwera et al. Biol Psychiatry, 2015) are based on the recent results from genome-wide association analyses (GWAS) of schizophrenia, educational attainment (EA) and body-mass index (BMI).
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