This study approved by the Human Research Ethics committees of Tongji Hospital of Tongji University and Shanghai Mental Health Center (SMHC) in China, and all recruited participants ensured informd consent, data were collected from Feb. 2014 to Sept. 2018, statistical analysis conducted from Jun. 2019 to Jan. 2020.
Including 30 FES subjects were recruited from outpatients of the hospital, and 30 HC subjects matched for gender and age (n= 30) were recruited from the local community. Two senior associate chief physicians would determine whether individuals of FES were presence or absence of psychotic symptoms by the SCID (Structured Clinical Interview for Diagnostic) assessment form of DSM-IV(Diagnostic and Statistical Manual of Mental Disorders fourth edition) and ensured the first episode with a course of disease less than two years, had never taken antipsychotics or stopped antipsychotics for five half-life periods or more. Other inclusion criteria for both groups were as follows:(1) Han ethnicity, right-handed; (2) Wechsler Intelligence Scale(IQ) was >70. Exclusion criteria for all participants were as follows: (1) Inability to conduct the MRI examination;(2)Current neurological disorder and major somatic diseases; (3)History of severe head injuries; (4)Having received electro-convulsive therapy within six months; (5)long-term use of medication that could potentially affect cognitive function(i.e., anticholinergics, benzodiazepine). In this study, some FES subjects may have received a certain amount of antipsychotic drugs from the time of enrollment to the time of examination due to impulsivity and behavioral chaos, so antipsychotics drug doses at that time have been converted to olanzapine (OLZ) equivalent doses for further analysis.
2.2 Study materials
2.2.1 Demographics and clinical assessments
The Demographics and clinical data collected through two modules. Module one completed by researchers, including demographic survey forms, previous medical history tables, clinical symptom assessments, and cognitive assessments. Demographic survey forms include gender, age, race, marital status, hand habits, occupation, years of education, birth and current residence, family status, and general family relationships; previous medical history table contain the history of precious physical diseases and combined medications (non-antipsychotics), it mainly investigates the history of hospitalization and illnesses that can cause mental symptoms such as hyperthyroidism, encephalitis, head injury and so on. The following five clinical measures were used to evaluate clinical symptoms: PANSS(Positive and Negative Syndrome Scale); CGI (Clinical Global Impression Scale); GAF (Global Assessment Functio）; MADRS (Montgomery-Åsberg Depression Rating Scale); And MCCB (MATRICS Consensus Cognitive Battery) for assessing cognitive functions.
Module two completed by the patients, including the Chinese version of CTQ (Childhood Trauma Questionnaire) and FACES Ⅱ（Family Adaptability and Cohesion Scale Ⅱ）. CTQ was a scale consisting of 28 self-assessed items used to assess children's traumatic experience, includes five sub-dimensions (i.e., emotional abuse and neglect, physical abuse and neglect, sexual abuse), CTQ had good reliability and validity in patients with mental disabilities, and its Cronbach alpha coefficient of Chinese version was 0.824. FACES Ⅱ was translated into Chinese by Fei, composed of two sub-dimensions: family cohesion and family adaptability, 15 items per dimension, each item graded from 1 to 5 points. The Cronbach alpha coefficient of the total and subscales was > 0.6 in schizophrenic families.
2.2.2 Statistical Analysis
Demographics and clinical assessments comparisons between groups were conducted with the SPSS software (SPSS version22.0, http://www.spss.com.hk/statistics/) for all tests. Clinical assessments, CTQ, FACES Ⅱ, and other continuous variables were compared using a two-sample, two-tailed t-test (significance level of P < 0.05). Categorical variables (i.e., gender) between the two groups assessed using a χ2 test (significance level of P < 0.05). Next, we performed multivariate statistics across clinical measurement dimensions using the Pearson correlation test (significance level of P < 0.05) and Bonferroni correction.
2.3 MRI data Acquisition
SMHC conducted MRI scans using a Siemens 3.0T MAGNETOM Trio Tim MRI Scanner, and all subjects were equipped with foam ear tips to reduce noise, foam pads were placed between the subject's head and the coil to minimize subject's head movement, and required to lie down and keep awake but eyes closed and head still. A total of 240 Whole-brain T2*-weighted echo-planer images (EPI) was obtained with slice thickness 3 mm, TR 2000 ms, TE 30 ms, flip angle 77°, matrix 74 × 74, a field of view (FOV) 220*220 mm2, voxel size=3×3×3 and 50 layers continuous scan. A high-resolution T1-weighted anatomical scan (MPRAGE) also obtained from each participant; TR 2530ms, echo time (TE)=3.65 ms, flip angle=70°, slice thickness=1 mm, FOV=256×256 mm2, matrix=256×256 and number of layers=224 layers. All scans were visually inspected and reviewed by a radiologist to ensure that there were no evident gross abnormalities.
Image preprocessing and analysis were performed using CONN(version 18b, http://www.nitrc.org/projects/conn) and SPM(version 12b; www.fil.ion.ucl.ac.uk/spm) toolbox, ran in Matlab 2013b (Mathworks Inc., Sherborn, MA, USA). After format conversion(DICOM to NIFTI), all functional data preprocessing according to a standard two-step normalize pipeline, including the following steps：(1) Removal of initial ten scans;(2) Slice-timing correction;(3) Realignment;(4) Outlier detection;(5) Normalization into Montreal Institute of Neurology (MNI) Space with resampled voxel to 3 mm * 3 mm * 3 mm volume; (6) Smooth with isotropic Gaussian kernel of 8 mm full-width half-maximum (FWHM); (7) Denoised to remove confounding variables including grey matter, white matter, and CSF BLOD signal noise;(8) Band-pass Filter in 0.01 to 0.08 Hz; (9) Linear detrending.
2.5 Functional Network Connectivity Analysis
After functional MRI preprocessing, blood oxygen level-dependent (BOLD) time series extracted from 264 areas by using a Power template, and a 6 mm sphere based on coordinates was used to define the Regions-of-interest (ROIs). Firstly, according to our hypothesis, previous studies described and verified ten brain subnetworks based on the Power template, including default mode network (DMN), ventral attention network(VAN), dorsal-ventral attention network (DAN), frontal-parietal network (FPN), cingulo-opercular network (CON), sensorimotor network (SMN), subcortical network (Subc), salience network (SAN), visual network (VIS ) and auditory network(AUD). BOLD time courses of all voxels in the ROIs mentioned above were averaged. Secondly, according to the definitions made by previous researches, for the brain network area definitions above, we measured two types of network connectivity, including seed-to-voxel maps for each RSN versus whole brain and ROI-to-ROI maps for between-network connectivity.
Bivariate-regression analyses performed separately to measure the static correlation strength for seed regions between CTQ sub-dimension scores. The multiple comparison corrections approaches performed at a peak voxel threshold of p≤0.001 and FDR(false discovery rate) correction with p＜0.05 using both for seed-to-voxel and ROI-to-ROI analysis, the gender, age and dose of antipsychotics were included as covariate regressors.