ABSTRACT
BackgroundBeing complex and highly heterogeneous with regard to the etiology and clinical manifestations of depression， neuroimaging studies make a breakthrough for exploring the biological subtypes of depression， while the current data-driven approach for the identification of subtyping depression using structural magnetic resonance imaging （MRI） data is insufficient. ObjectiveTo explore the biological subtypes of depression using diffusion tensor imaging （DTI） and machine learning methods. MethodsA total of 127 patients with depression who attended Beijing Anding Hospital from September 2017 to August 2021 and met the Diagnostic and Statistical Manual of Mental Disorders， fourth edition （DSM-IV） diagnostic criteria were included， and another 80 healthy individuals matched for gender and age were recruited through advertisements in surrounding communities during the same period. DTI findings， demographic characteristics and clinical data were collected from all participants. Tract-based spatial statistics （TBSS） and the Johns Hopkins University （JHU） white matter probability maps were used to extract fractional anisotropy （FA） values of white matter tracts. A semi-supervised machine learning technique was used to identify the subtypes， and the FA values for whole brain white matter of patients and controls were compared. ResultsPatients with depression were classified into two biological subtypes. FA values in multiple tracts including corpus callosum and corona radiata of subtype I patients were smaller than those of healthy controls （P<0.01， FDR corrected）， and FA values in middle cerebellar peduncle， left superior cerebellar peduncle and left cerebral peduncle of subtype II patients were larger than those of healthy controls （P<0.01， FDR-corrected）. Baseline Hamilton Depression Scale-17 item （HAMD-17） score yielded no statistical difference between subtype I and subtype II patients （P>0.05）， while subtype I patients scored lower on HAMD-17 than subtype II patients after 12 weeks of treatment （t=2.410， P<0.05）. ConclusionDepression patients exhibit two biological subtypes with distinct patterns of white matter damage. Furthermore， the subtypes respond differently to the medication treatment. ［Funded by the National Key Research and Development Program of China （number， 2016YFC1307200）， the Scientific Research and Cultivation Program of Beijing Municipal Hospitals （number，PX2023066）， Beijing Anding Hospital， Capital Medical University （number，YJ201904， YJ201911）； www.chictr.org.cn number： ChiCTR-OOC-17012566］
ABSTRACT
Objective:To assess the psychometric properties of the Chinese version of 12-item immediate mood scale(IMS-12) in patients with depression.Methods:From January to June 2018, a total of 459 patients with depression recruited from an outpatient clinic by convenient sampling approach.All the subjects were assessed by the Chinese version of the IMS-12, and 43 of them were assessed again at the end of the first week.The 16-item quick inventory of depressive symptomatology (QIDS-SR16), and the generalized anxiety disorder scale-7(GAD-7) were used as validity indicator.The factor structure of the scale was evaluated by exploratory and confirmatory factor analyses.The internal consistency of the Chinese version of the IMS-12 scale was evaluated by Cronbach’s alpha coefficient.The intraclass correlation coefficient (ICC) was used to evaluate test-retest reliability.Pearson’s correlation coefficient was used to evaluate calibration validity.The softwares of SAS 9.4 and Mplus 8.5 were used for statistical analysis.Results:The exploratory factor analysis indicated that the fitting result of the two-factor model was good(including depression and anxiety factors). The results of the confirmatory factor analysis indicated that the factor model fit well and met the reference standard ( χ2/ df=2.82, CFI=0.936, TLI=0.920, RMSEA=0.088). The Cronbach’s alpha coefficient of the Chinese version of the IMS-12 was 0.95, and the ICC for test-retest reliability was 0.85.The correlation coefficients of the total IMS-12 score with the QIDS-SR16 score and with the GAD-7 score were 0.69 and 0.70, respectively. Conclusion:The Chinese version of the IMS-12 has good reliability and validity and is suitable for the clinical assessment of depressive and anxiety symptoms in patients with depression.
ABSTRACT
Objective:To explore whether working memory span training can expand working memory capacity.Methods:A randomized controlled trial design was adopted and a total of 60 healthy college students were recruited and randomly divided into training group ( n=30, receiving adaptive training of spatial breadth task) and control group ( n=30, receiving non-adaptive training of low difficulty spatial breadth task). The cognitive behavior and event-related potential (ERP) data of all subjects when completing the change awareness task were collected before and after training.The SPSS 22.0 statistical software was used for data analysis. The differences between the training group and the control group before and after training were compared by repeated measurement analysis of variance. Results:Repeated measurement ANOVA showed that there were significant time and group interactions at the levels of cognitive behavior(K score, F=5.352, P=0.025) and ERP (CDA, F=4.644, P=0.037) levels. Further post test found that compared with pre-training (pre-test), the K-score ((0.51±0.93), (1.61±1.07), F=26.81, P<0.001) and CDA ((-1.49±1.07)μV, (-2.03±0.94)μV, F=4.731, P=0.041) of the training group increased significantly after training (post-test), and there was no significant difference in K-score and CDA of the control group before and after training (boh P>0.05). Conclusion:Working memory span task can be used as an effective training paradigm to improve working memory capacity.
ABSTRACT
Objective To assess the association between rs7597593 polymorphism of ZNF804A gene and schizophrenia,and to assess the relationship between rs7597593 polymorphism and working memory.Methods Schizophrenia patients and healthy controls were diagnosed in accordance with Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition (DSM-Ⅳ) ; 767 schizophrenia patients and 690 healthy controls were involved.Restriction fragment length polymorphism (RFLP) was carried out to genotype rs7597593 polymorphism.The cognitive function of working memory was assessed by the N-back task.Statistical analyses were carried out with SPSS19.0 software.Results The study found no significantly different genotype frequencies (x2=1.519,P=0.468) and allele frequencies(x2=1.263,P=0.261) of rs7597593 polymorphism between schizophrenia patients and healthy controls,however in the subgroup of higher IQ (IQ ≥ 110),there were significant different distributions of both genotype and allele (x2 =9.411 and 6.529; P=0.009 and 0.011 respectively).It was also found in this subgroup that risk T allele was associated with more error at 1-back task (F=6.854,P=0.009).Conclusion These results indicated that rs7597593 polymorphism was associated with individuals having spared cognitive function; carriers of T allele had worse cognitive function,which maybe a pathway that it contributes to schizophrenia.