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Thirty-Third Annual Meeting of the Society for Research in Psychopathology

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134. Prediction of brain age in individuals with psychotic disorders and their biological relatives

Structural brain abnormalities are well documented in psychotic disorders. Whether such changes reflect genetic liability versus consequence of the illness remains unclear. Predicted age difference (PAD) between chronological age and brain age (a machine learning-predicted age based on information from structural magnetic resonance neuroimaging), has recently been used as a biomarker for a number of neurological conditions. Individuals with schizophrenia have demonstrated greater PAD compared to healthy controls. In the current study, we investigated PADs across three study groups: adults with a psychotic disorder, biological relatives of individuals with psychotic disorders, and non-psychiatric control participants. Participants’ structural imaging data were used to predict brain age with a trained machine learning model (Liem et al., 2017). Results suggest that PAD is larger for individuals with a psychotic disorder as compared to biological relatives and healthy controls. Findings point to an older predicted age than chronological age at the time of scan. The PAD for relatives did not statistically differ from that of healthy controls. Our results suggest that factors associated with having a psychotic disorder, rather than genetic liability, may best explain the variation in the PAD across groups. Future analyses will examine clinical and cognitive correlates of the PAD.

Chen Shen
University of Minnesota

Caroline Demro
University of Minnesota

Seth Disner
Minneapolis Veterans Affairs Health Care System, University of Minnesota

Timothy Hendrickson
University of Minnesota

Scott Sponheim
Minneapolis Veterans Affairs Health Care System, University of Minnesota

 


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