| Literature DB >> 28628780 |
Igor Nenadić1, Maren Dietzek2, Kerstin Langbein2, Heinrich Sauer2, Christian Gaser3.
Abstract
BrainAGE (brain age gap estimation) is a novel morphometric parameter providing a univariate score derived from multivariate voxel-wise analyses. It uses a machine learning approach and can be used to analyse deviation from physiological developmental or aging-related trajectories. Using structural MRI data and BrainAGE quantification of acceleration or deceleration of in individual aging, we analysed data from 45 schizophrenia patients, 22 bipolar I disorder patients (mostly with previous psychotic symptoms / episodes), and 70 healthy controls. We found significantly higher BrainAGE scores in schizophrenia, but not bipolar disorder patients. Our findings indicate significantly accelerated brain structural aging in schizophrenia. This suggests, that despite the conceptualisation of schizophrenia as a neurodevelopmental disorder, there might be an additional progressive pathogenic component.Entities:
Keywords: Aging; Bipolar disorder; BrainAGE score; Machine learning; Magnetic Resonance Imaging (MRI); Psychosis; Schizophrenia
Mesh:
Year: 2017 PMID: 28628780 DOI: 10.1016/j.pscychresns.2017.05.006
Source DB: PubMed Journal: Psychiatry Res Neuroimaging ISSN: 0925-4927 Impact factor: 2.376