Independent t test and Chi-square test were used for the statistical analyses of continuous and categorical clinicodemographic variables, respectively. The P value was set at 0.05.
We used analysis of covariance (ANCOVA) to examine the differences in the brain age gaps between participants with schizophrenia and HCs in the TAMI and BT cohorts, with chronological age, sex, MMSE score, and duration of education as the covariates. Moreover, the false discovery rate (FDR) method was used to correct P values for multiple comparisons [53 ]. After FDR correction, the significance level was set at 0.05. The partial eta-squared (partial η2) values were calculated as effect size measures. The BrainNet Viewer (http://www.nitrc.org/projects/bnv/ ) was used for result visualizations [54 (link)].
After comparing the brain age gaps between the two groups, we performed a multiple regression analysis for brain regions that aged faster than usual. In each regression model, the dependent variable was brain age gaps for a given brain region; the independent variables were clinicodemographic characteristics, including PANSS subscale scores (for positive symptoms, negative symptoms, and general psychopathology symptoms), illness duration, age of onset, history of nicotine use, and body mass index; and the control variables were chronological age and sex. In addition, after excluding participants without any antipsychotic information and controlling for chronological age and sex, we used a regression analysis to investigate the association between brain age gaps and chlorpromazine (CPZ) equivalent dosage. Finally, the FDR method was used to control for differences in the comparison procedures.
We used analysis of covariance (ANCOVA) to examine the differences in the brain age gaps between participants with schizophrenia and HCs in the TAMI and BT cohorts, with chronological age, sex, MMSE score, and duration of education as the covariates. Moreover, the false discovery rate (FDR) method was used to correct P values for multiple comparisons [53 ]. After FDR correction, the significance level was set at 0.05. The partial eta-squared (partial η2) values were calculated as effect size measures. The BrainNet Viewer (
After comparing the brain age gaps between the two groups, we performed a multiple regression analysis for brain regions that aged faster than usual. In each regression model, the dependent variable was brain age gaps for a given brain region; the independent variables were clinicodemographic characteristics, including PANSS subscale scores (for positive symptoms, negative symptoms, and general psychopathology symptoms), illness duration, age of onset, history of nicotine use, and body mass index; and the control variables were chronological age and sex. In addition, after excluding participants without any antipsychotic information and controlling for chronological age and sex, we used a regression analysis to investigate the association between brain age gaps and chlorpromazine (CPZ) equivalent dosage. Finally, the FDR method was used to control for differences in the comparison procedures.
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