Brain–clinical pattern alterations after treatment in schizophrenia

Abstract Discovering meaningful brain–clinical patterns would be a significant advancement for elucidating the pathophysiology underlying schizophrenia. In the present study, we analyzed associations between functional brain characters (average functional connectivity strength and its fluctuations) and clinical features (age onset, illness duration, and positive, negative, disorganized, excited, and depressed) using partial least squares. Also, we analyzed the brain–clinical relationship changes after 6-wk of treatment. At baseline, 2 identified latent brain–clinical dimensions collectively accounted for 33.2% of the covariance between clinical data and brain function. The illness onset age and duration significantly contributed to all latent dimensions. The disorganized symptoms contributed to the first latent variable, while the positive and depressed symptoms notably negatively contributed to the second variable. The average functional connectivity strength of first latent variable could positively predict the treatment effect, especially in the positive, negative, excited, and overall symptoms. No significant correlation between average functional connectivity strength and treatment effect was obtained in second latent variable. We also found that functional connectivity and its fluctuations altered after treatment, with similar patterns of brain characteristic alterations across the 2 latent variables. By simultaneously taking into account both clinical manifestations and brain abnormalities, the present results open new avenues for predicting treatment responses in schizophrenia.