A systematic review of interpersonal psychotherapy for postpartum depression.

BACKGROUND: The current study endeavored to systematically integrate and quantitatively evaluate the effectiveness of interpersonal psychological interventions for postpartum depression patients. METHODS: Four electronic databases Pubmed, Embase, Cochrane and Web of Science were employed for literature retrieval, and the search time was from the inception of the database to May 30, 2022. Literature screening and data extraction were performed independently by two researchers. RESULTS: A total of 528 studies were screened, and 9 of them were finally included. There were 1012 subjects, 518 of them were assigned in experimental group and 494 in control. Evidence from interpersonal psychological interventions indicated that the data on postpartum depression, satisfaction with family, and social support in both groups after intervention included: depression score [MD = -2.80, 95%CI (-3.86 to -1.74), P < 0.05], satisfaction score [MD = 8.41, 95%CI (1.49 to -15.33), P < 0.05], and social support score [MD = 1.83, 95%CI (-2.10 to -5.76)] of postpartum depression patients. P values < 0.05 indicated substantial improvement as compared to control. LIMITATIONS: During the research process, it is impossible for the experimental group and the researchers to use double-blind trials simultaneously, which may present a Hawthorne effect, but this can be avoided by general psychological intervention for the control. CONCLUSIONS: Interpersonal psychotherapy could improve depression in patients with postpartum depression, but the appropriate intervention time was between 4 and 8 weeks, and it also improved satisfaction with family of patients, and the longer the intervention, the higher the satisfaction with the family.

Predicting the diagnosis of various mental disorders in a mixed cohort using blood-based multi-protein model: a machine learning approach.

The lack of objective diagnostic methods for mental disorders challenges the reliability of diagnosis. The study aimed to develop an easily accessible and useable objective method for diagnosing major depressive disorder (MDD), schizophrenia (SZ), bipolar disorder (BPD), and panic disorder (PD) using serum multi-protein. Serum levels of brain-derived neurotrophic factor (BDNF), VGF (non-acronymic), bicaudal C homolog 1 (BICC1), C-reactive protein (CRP), and cortisol, which are generally recognized to be involved in different pathogenesis of various mental disorders, were measured in patients with MDD (n = 50), SZ (n = 50), BPD (n = 55), and PD along with 50 healthy controls (HC). Linear discriminant analysis (LDA) was employed to construct a multi-classification model to classify these mental disorders. Both leave-one-out cross-validation (LOOCV) and fivefold cross-validation were applied to validate the accuracy and stability of the LDA model. All five serum proteins were included in the LDA model, and it was found to display a high overall accuracy of 96.9% when classifying MDD, SZ, BPD, PD, and HC groups. Multi-classification accuracy of the LDA model for LOOCV and fivefold cross-validation (within-study replication) reached 96.9 and 96.5%, respectively, demonstrating the feasibility of the blood-based multi-protein LDA model for classifying common mental disorders in a mixed cohort. The results suggest that combining multiple proteins associated with different pathogeneses of mental disorders using LDA may be a novel and relatively objective method for classifying mental disorders. Clinicians should consider combining multiple serum proteins to diagnose mental disorders objectively.

Case report: Cases of narcolepsy misdiagnosed as other psychiatric disorders.

Narcolepsy is characterized by uncontrollable excessive daytime sleepiness, paroxysmal cataplexy, sleep paralysis, and hallucinations. It is often misdiagnosed as psychiatric disorders such as depression and schizophrenia, resulting from the overlap in symptoms and a lack of understanding of narcolepsy. In the present study, three cases of narcolepsy misdiagnosed as depression, dissociative disorder, and schizophrenia are presented to emphasize the high occurrence of the misdiagnosis of narcolepsy in clinical practice. The main reasons for this dilemma are attributed to the lack of adequate sleep, medicine, education, as well as specialized professional technicians. A multi-disciplinary team composed of psychiatrists and sleep specialists should be established to deal with this problem.

Development and validation of a nomogram based on lymphocyte subsets to distinguish bipolar depression from major depressive disorder.

Objective: Bipolar depression (BD) and major depressive disorder (MDD) are both common affective disorders. The common depression episodes make it difficult to distinguish between them, even for experienced clinicians. Failure to properly diagnose them in a timely manner leads to inappropriate treatment strategies. Therefore, it is important to distinguish between BD and MDD. The aim of this study was to develop and validate a nomogram model that distinguishes BD from MDD based on the characteristics of lymphocyte subsets. Materials and methods: A prospective cross-sectional study was performed. Blood samples were obtained from participants who met the inclusion criteria. The least absolute shrinkage and selection operator (LASSO) regression model was used for factor selection. A differential diagnosis nomogram for BD and MDD was developed using multivariable logistic regression and the area under the curve (AUC) with 95% confidence interval (CI) was calculated, as well as the internal validation using a bootstrap algorithm with 1,000 repetitions. Calibration curve and decision curve analysis (DCA) were used to evaluate the calibration and clinical utility of the nomogram, respectively. Results: A total of 166 participants who were diagnosed with BD (83 cases) or MDD (83 cases), as well as 101 healthy controls (HCs) between June 2018 and January 2022 were enrolled in this study. CD19+ B cells, CD3+ T cells, CD3-CD16/56+ NK cells, and total lymphocyte counts were strong predictors of the diagnosis of BD and MDD and were included in the differential diagnosis nomogram. The AUC of the nomogram and internal validation were 0.922 (95%; CI, 0.879-0.965), and 0.911 (95% CI, 0.838-0.844), respectively. The calibration curve used to discriminate BD from MDD showed optimal agreement between the nomogram and the actual diagnosis. The results of DCA showed that the net clinical benefit was significant. Conclusion: This is an easy-to-use, repeatable, and economical nomogram for differential diagnosis that can help clinicians in the individual diagnosis of BD and MDD patients, reduce the risk of misdiagnosis, facilitate the formulation of appropriate treatment strategies and intervention plans.

ERK1/2-dependent BDNF synthesis and signaling is required for the antidepressant effect of microglia stimulation.

Depressed mice have lower numbers of microglia in the dentate gyrus (DG). Reversal of this decline by a single low dose of lipopolysaccharide (LPS) may have antidepressant effects, but there is little information on the molecular mechanisms underlying this effect. It is known that impairment of brain-derived neurotrophic factor (BDNF) signaling is involved in the development of depression. Here, we used a combination of neutralizing antibodies, mutant mice, and pharmacological approaches to test the role of BDNF-tyrosine kinase receptor B (TrkB) signaling in the DG in the effect of microglial stimulation. Our results suggest that inhibition of BDNF signaling by infusion of an anti-BDNF antibody, the BDNF receptor antagonist K252a, or knock-in of the mutant BDNF Val68Met allele abolished the antidepressant effect of LPS in chronically stressed mice. Increased BDNF synthesis in DG, mediated by extracellular signal-regulated kinase1/2 (ERK1/2) signaling but not protein kinase B (Akt)-mammalian target of rapamycin (mTOR) signaling, was essential for the antidepressant effect of microglial stimulation. These results suggest that increased BDNF synthesis through activation of ERK1/2 caused by a single LPS injection and subsequent TrkB signaling are required for the antidepressant effect of hippocampal microglial stimulation.

Aberrated Multidimensional EEG Characteristics in Patients with Generalized Anxiety Disorder: A Machine-Learning Based Analysis Framework.

Although increasing evidences support the notion that psychiatric disorders are associated with abnormal communication between brain regions, scattered studies have investigated brain electrophysiological disconnectivity of patients with generalized anxiety disorder (GAD). To this end, this study intends to develop an analysis framework for automatic GAD detection through incorporating multidimensional EEG feature extraction and machine learning techniques. Specifically, resting-state EEG signals with a duration of 10 min were obtained from 45 patients with GAD and 36 healthy controls (HC). Then, an analysis framework of multidimensional EEG characteristics (including univariate power spectral density (PSD) and fuzzy entropy (FE), and multivariate functional connectivity (FC), which can decode the EEG information from three different dimensions) were introduced for extracting aberrated multidimensional EEG features via statistical inter-group comparisons. These aberrated features were subsequently fused and fed into three previously validated machine learning methods to evaluate classification performance for automatic patient detection. We showed that patients exhibited a significant increase in beta rhythm and decrease in alpha1 rhythm of PSD, together with the reduced long-range FC between frontal and other brain areas in all frequency bands. Moreover, these aberrated features contributed to a very good classification performance with 97.83 ± 0.40% of accuracy, 97.55 ± 0.31% of sensitivity, 97.78 ± 0.36% of specificity, and 97.95 ± 0.17% of F1. These findings corroborate previous hypothesis of disconnectivity in psychiatric disorders and further shed light on distribution patterns of aberrant spatio-spectral EEG characteristics, which may lead to potential application of automatic diagnosis of GAD.

Combining S100B and Cytokines as Neuro-Inflammatory Biomarkers for Diagnosing Generalized Anxiety Disorder: A Proof-of-Concept Study Based on Machine Learning.

Introduction: S100 calcium-binding protein B (S100B) is a neurotrophic factor that regulates neuronal growth and plasticity by activating astrocytes and microglia through the production of cytokines involved in Generalized Anxiety Disorder (GAD). However, few studies have combined S100B and cytokines to explore their role as neuro-inflammatory biomarkers in GAD. Methods: Serum S100B and cytokines (IL-1ß, IL-2, IL-4, and IL-10) of 108 untreated GAD cases and 123 healthy controls (HC) were determined by enzyme-linked immunosorbent assay (ELISA), while Hamilton Anxiety Rating Scale (HAMA) scores and Hamilton Depression Rating Scale (HAMD) scores were measured to evaluate anxiety and depression severity. This was used to help physicians identify persons having GAD. Machine learning techniques were applied for feature ordering of cytokines and S100B and the classification of persons with GAD and HC. Results: The serum S100B, IL-1ß, and IL-2 levels of GAD cases were significantly lower than HC (P < 0.001), and the IL-4 level in persons with GAD was significantly higher than HC (P < 0.001). At the same time, IL-10 had no significant difference between the two groups (P = 0.215). The feature ranking distinguishing GAD from HC using machine learning ranked the features in the following order: IL-2, IL-1ß, IL-4, S100B, and IL-10. The accuracy of S100B combined with IL-1ß, IL-2, IL-4, and IL-10 in distinguishing persons with GAD from HC was 94.47 ± 2.06% using an integrated back propagation neural network based on a bagging algorithm (BPNN-Bagging). Conclusion: The serum S-100B, IL-1ß, and IL-2 levels in persons with GAD were down-regulated while IL-4 was up-regulated. The combination of S100B and cytokines had a good diagnosis value in determining GAD with an accuracy of 94.47%. Machine learning was a very effective method to study neuro-inflammatory biomarkers interacting with each other and mediated by plenty of factors.

Prevalence of depressive disorders and treatment in China: a cross-sectional epidemiological study.

BACKGROUND: In China, depressive disorders have been estimated to be the second leading cause of years lived with disability. However, nationally representative epidemiological data for depressive disorders, in particular use of mental health services by adults with these disorders, are unavailable in China. The present study, part of the China Mental Health Survey, 2012-15, aims to describe the socioeconomic characteristics and the use of mental health services in people with depressive disorders in China. METHODS: The China Mental Health Survey was a cross-sectional epidemiological survey of mental disorders in a multistage clustered-area probability sample of adults of Chinese nationality (≥18 years) from 157 nationwide representative population-based disease surveillance points in 31 provinces across China. Trained investigators interviewed the participants with the Composite International Diagnostic Interview 3.0 to ascertain the presence of lifetime and 12-month depressive disorders according to DSM-IV criteria, including major depressive disorder, dysthymic disorder, and depressive disorder not otherwise specified. Participants with 12-month depressive disorders were asked whether they received any treatment for their emotional problems during the past 12 months and, if so, the specific types of treatment providers. The Sheehan Disability Scale (SDS) was used to assess impairments associated with 12-month depressive symptoms. Data-quality control procedures included logic check by computers, sequential recording check, and phone-call check by the quality controllers, and reinterview check by the psychiatrists. Data were weighted according to the age-sex-residence distribution data from China's 2010 census population survey to adjust for differential probabilities of selection and differential response, as well as to post-stratify the sample to match the population distribution. FINDINGS: 28 140 respondents (12 537 [44·6%] men and 15 603 [55·4%] women) completed the survey between July 22, 2013, and March 5, 2015. Ethnicity data (Han or non-Han) were collected for only a subsample. Prevalence of any depressive disorders was higher in women than men (lifetime prevalence odds ratio [OR] 1·44 [95% CI 1·20-1·72] and 12-month prevalence OR 1·41 [1·12-1·78]), in unemployed people than employed people (lifetime OR 2·38 [95% CI 1·68-3·38] and 12-month OR 2·80 [95% CI 1·88-4·18]), and in people who were separated, widowed, or divorced compared with those who were married or cohabiting (lifetime OR 1·87 [95% CI 1·39-2·51] and 12-month OR 1·85 [95% CI 1·40-2·46]). Overall, 574 (weighted % 75·9%) of 744 people with 12-month depressive disorders had role impairment of any SDS domain: 439 (83·6%) of 534 respondents with major depressive disorder, 207 (79·8%) of 254 respondents with dysthymic disorder, and 122 (59·9%) of 189 respondents with depressive disorder not otherwise specified. Only an estimated 84 (weighted % 9·5%) of 1007 participants with 12-month depressive disorders were treated in any treatment sector: 38 (3·6%) in speciality mental health, 20 (1·5%) in general medical, two (0·3%) in human services, and 21 (2·7%) in complementary and alternative medicine. Only 12 (0·5%) of 1007 participants with depressive disorders were treated adequately. INTERPRETATION: Depressive disorders in China were more prevalent in women than men, unemployed people than employed, and those who were separated, widowed, or divorced than people who were married or cohabiting. Most people with depressive disorders reported social impairment. Treatment rates were very low, and few people received adequate treatment. National programmes are needed to remove barriers to availability, accessibility, and acceptability of care for depression in China. FUNDING: National Health Commission and Ministry of Science and Technology of People's Republic of China. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Higher baseline serum adiponectin predicts better treatment remission in patients with generalized anxiety disorder treated with escitalopram.

BACKGROUND: Generalized anxiety disorder (GAD) is partly attibuted to the dysregulation of nuero-inflammation which can be mediated by adiponectin. We conducted this study was to explore the characteristics of peripheral adiponectin and its role in predicting treatment outcome in patients with generalized anxiety disorder (GAD) treated by escitalopram or venlafaxine. METHODS: A total of 70 untreated GAD inpatients who met the diagnosis criteria of the Diagnostic and Statistical Manual of Mental Disorders IV (DSM-IV) were enrolled and randomly selected for treatment with escitalopram (n=36) or venlafaxine (n=34) for 8 weeks. The serum adiponectin level of GAD and healthy controls (HCs) was measured by enzyme-linked immunosorbent assay (ELISA) before treatment. Hamilton Anxiety Rating Scale (HAM-A) assessment was conducted at baseline and at 1, 2, 4, and 8 weeks after treatment respectively. Serum adiponectin levels were compared between GAD patients and HCs, as well as between remission and nonremission cases; the correlation between baseline adiponectin level and HAM-A reduction rate were also analyzed. RESULTS: The serum adiponectin levels were higher in GAD patients compared to HCs (t=2.304; P=0.023), the serum adiponectin levels were higher in remission cases compared to nonremission cases (t=2.255, P=0.027), and the receiver operating characteristic (ROC) area in predicting treatment remission was 0.652±0.066 (P=0.029). The correlation between baseline adiponectin level and HAM-A reduction rate of GAD cases treated with escitalopram and venlafaxine in the endpoint was 0.362 (P=0.030) and -0.026 (P=0.883), respectively, and the ROC area of baseline adiponectin level in predicting treatment remission was 0.72±0.086 (P=0.024) and 0.473±0.102 (P=0.469), respectively. CONCLUSIONS: Peripheral adiponectin is upregulated in GAD, and it seems higher baseline adiponectin level predicts a better treatment remission treated by escitalopram but not with venlafaxine, which suggests adiponectin maybe a potential key biomarker in Chinese GAD.

Tolerance-inducing effect and properties of innate immune stimulation on chronic stress-induced behavioral abnormalities in mice.

Over-activation of the innate immune system constitutes a risk factor for the development of nervous system disorders but may reduce the severity of these disorders by inducing tolerance effect. Here, we studied the tolerance-inducing effect and properties of innate immune stimulation on chronic social defeat stress (CSDS)-induced behavioral abnormalities in mice. A single injection of the innate immune enhancer lipopolysaccharide (LPS) one day before stress exposure prevented CSDS-induced impairment in social interaction and increased immobility time in the tail suspension test and forced swimming test. This effect was observed at varying doses (100, 500, and 1000 µg/kg) and peaked at 100 µg/kg. A single LPS injection (100 µg/kg) either one or five but not ten days before stress exposure prevented CSDS-induced behavioral abnormalities. A second LPS injection ten days after the first LPS injection, or a 2 × or 4 × LPS injections ten days before stress exposure also induced tolerance against stress-induced behavioral abnormalities. Our results furthermore showed that a single LPS injection one day before stress exposure skewed the neuroinflammatory response in the hippocampus and prefrontal cortex of CSDS-exposed mice toward an anti-inflammatory phenotype. Inhibiting the central innate immune response by pretreatment with minocycline or PLX3397 abrogated the tolerance-inducing effect of LPS preconditioning on CSDS-induced behavioral abnormalities and neuroinflammatory responses in the brain. These results provide evidence for a prophylactic effect of innate immune stimulation on stress-induced behavioral abnormalities via changes in microglial activation, which may help develop novel strategies for the prevention of stress-induced psychological disorders.

Aberrant amplitude low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) in generalized anxiety disorder (GAD) and their roles in predicting treatment remission.

BACKGROUND: Generalized anxiety disorder (GAD) is a common affective disorder characterized by comprehensive anxiety with dysregulation of brain activity which can be reflected by functional magnetic resonance imaging (f-MRI). We aimed to examine abnormal aberrant amplitude low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) in GAD and evaluate their ability to predict treatment remission. METHODS: Using resting-state fMRI (Rs-fMRI), we examined ALFF and ReHo in 30 GAD patients and 30 healthy control (HC) participants. Using on DEPASF4.3 Advanced Edition, voxel-based two-sample t-test analysis was performed on the ALFF and ReHo maps to compare GAD to HC groups, and to compare remitters (n=9) and non-remitters (n=21). Pearson's correlation analysis was used to explore the relationship between baseline Hamilton Anxiety Rating Scale (HAM-A) scores/illness duration and mean ALFF/ReHo values. The severity of GAD symptoms was rated with HAM-A. Remission was defined as HAM-A ≤7 by week 8. RESULTS: Compared to the HC group, GAD patients showed lower ALFF in the right postcentral and right precentral gyrus; lower ReHo in the right precentral, right postcentral, and left precentral gyrus; and higher ReHo in the left posterior cingulate cortex. ALFF values for left postcentral gyrus was negatively correlated with baseline HAM-A, while that of the middle frontal gyrus was positively correlated with baseline HAM-A scores. ReHo value of the left postcentral gyrus was negatively correlated with baseline HAM-A, while that of the right middle frontal gyrus was positively correlated with baseline HAM-A scores. ALFF of the right frontal_superior_orbital and right frontal-medial-orbital cortex was positively correlated with illness duration. ReHo of the left supplementary motor area cortex was negatively correlated with illness duration. Remitters showed higher ALFF in the left hippocampus and higher ReHo value in the right postcentral cortex compared to nonremitters. CONCLUSIONS: These results suggest that altered regional brain activity and local synchronization may be related to the pathophysiology of GAD and have certain value in predicting remission in treatment.

The association of catechol-O-methyltransferase (COMT) rs4680 polymorphisms and generalized anxiety disorder in the Chinese Han population.

The catechol-O-methyltransferase (COMT) Val158Met polymorphism has been reported to be implicated in generalized anxiety disorder (GAD) as well as the treatment response to antidepressants in patients with GAD, but the findings are inconsistent. In this study, we explore the association among COMT, GAD, and the antidepressant response in the Chinese Han population. One hundred and two patients with GAD and 120 healthy controls (HC) were recruited. All the patients were treated with escitalopram or venlafaxine for 8 weeks. The Hamilton Rating Scale for Anxiety (HAMA) was used to assess the treatment response. All the participants were genotyped for the COMT Val158Met polymorphism using the polymerase chain reaction method. No significant differences in the frequency of the COMT rs4680 polymorphism were found between the GAD and HC groups, or between patients with different genders. Further, we found no significant correlation between the COMT rs4680 polymorphism, gender, and the antidepressant treatment outcomes after eight weeks in the GAD patients. This study indicated that the COMT rs4680 genotype might not be related to GAD or to the genders of the GAD patients, nor did it have any effect on the antidepressant therapeutic response in the GAD patients. Even so, our research will be helpful by providing guidance and direction for future, more in depth, research.

The roles of brain-derived neurotrophic factor (BDNF) and glial cell line-derived neurotrophic factor (GDNF) in predicting treatment remission in a Chinese Han population with generalized anxiety disorder.

Neurotrophic factors, particularly brain-derived neurotrophic factor (BDNF) and glial cell line-derived neurotrophic factor (GDNF), are involved in neuroplasticity in the nervous system. To explore the characteristics of BDNF and GDNF and their roles in predicting treatment remission in a Chinese Han population with generalized anxiety disorder (GAD), 85 GAD patients were treated with escitalopram or venlafaxine randomly for 8 weeks. The serum BDNF/GDNF levels were detected, while Hamilton Anxiety Rating Scale (HAMA) scores were measured at baseline and after 8 weeks of treatment. The differences in serum BDNF/GDNF levels between GAD patients (n = 85) and healthy controls (n = 73) and between remission and nonremission were then compared. The serum BDNF levels were lower in GAD patients (1197.24 ±â€¯367.41 µg/L) than in healthy controls (1378.09 ±â€¯382.46 µg/L) (P < 0.05). The serum GDNF levels were also lower in GAD patients (10.19 ±â€¯9.86 µg/L) than in healthy controls (13.73 ±â€¯9.44 µg/L) (P < 0.05). The BDNF level was negatively correlated with baseline HAMA score (P < 0.05). The GDNF level was negatively correlated with baseline HAMA score (P < 0.05). The BDNF level was positively correlated with GDNF level (P < 0.05). Both baseline BDNF/GDNF levels in remission and nonremission showed no statistically significant differences. No significant correlation was found between baseline BDNF level and the HAMA reduction rate or between baseline GDNF levels and the HAMA reduction rate. Both serum BDNF and GDNF were demonstrated to be potential biomarkers of GAD, it seems that serum BDNF and GDNF levels can be used to assess the baseline anxiety severity of GAD but cannot serve as a factor to predict treatment remission.

Association of NPSR1 rs324981 polymorphism and treatment response to antidepressants in Chinese Han population with generalized anxiety disorder.

In previous studies, neuropeptide S (NPS) and its cognate receptor (NPSR) have been involved in the pathogenesis of anxiety disorders in previous studies. Here, we aimed to investigate the association of NPSR1 polymorphism with generalized anxiety disorder (GAD) and its treatment response in Chinese Han population. Three hundred and thirty seven patients and one hundred and seventy seven healthy controls were involved in our study for 8 weeks. Further, Hamilton Anxiety Scale (HAMA) was used to assess anxiety symptom at baseline and the 1st, 2nd, 4th, 8th week. And all participants were genotyped for NPSR1 (rs324981) variants by polymerase chain reaction. Using Repeated-measures analysis, it showed significant reduction on HAMA scores in patients treated with escitalopram (F = 1.03, P = 0.362) and venlafaxine (F = 0.27, P = 0.763) respectively through 8 weeks treatment. Additionally, patients with AA and TT homozygous genotypes treated with venlafaxine XR had a higher reduction of HAMA scores compared to AT heterozygotic carriers (F = 4.18, P = 0.004), while no significant differences were found in patients treated with escitalopram (F = 1.05, P = 0.383). Thus, our study provides preliminary evidence that NPSR1 AA and TT homozygous genotypes have better treatment responses to venlafaxine XR in Chinese GAD patients, but not to escitalopram. Further studies are needed to verify the observation.

Association Analysis of the Brain-Derived Neurotrophic Factor Gene Val66Met Polymorphism and Gender with Efficacy of Antidepressants in the Chinese Han Population with Generalized Anxiety Disorder.

BACKGROUND AND AIM: This study was designed to explore the relationship between the brain-derived neurotrophic factor (BDNF) Val66Met polymorphism and antidepressants' efficacy in the Chinese Han population with generalized anxiety disorder (GAD). MATERIALS AND METHODS: We recruited 206 patients who met the diagnostic criteria for GAD into the test group, and assigned 209 healthy participants to the control group. All participants were genotyped for the BDNF Val66Met polymorphism. GAD patients were treated with escitalopram or extended-release venlafaxine. We used the Hamilton Rating Scale for Anxiety (HAM-A) to assess the response to 8-weeks of antidepressant treatment for GAD. RESULTS: We did not identify any significant differences in the allelic or genotype frequencies of the BDNF Val66Met polymorphism between the test and control group. Furthermore, we did not detect any significant difference in the allele or genotype frequency of BDNF Val66Met between patients with different treatment responses. Finally, we did not detect any significant difference in the HAM-A score reduction rate among patients with different genotypes, gender, or treatment drugs. CONCLUSIONS: No significant difference was found in the BDNF Val66Met polymorphism between patients with GAD and healthy controls, nor was this polymorphism significantly associated with antidepressant drug efficacy for GAD.

Early improvement predicts 8-week treatment outcome in patients with generalized anxiety disorder treated with escitalopram or venlafaxine.

INTRODUCTION: To investigate whether early improvement can predict 8-week treatment outcome in generalized anxiety disorder (GAD) patients. METHODS: For 8 weeks, 226 GAD patients were randomly treated with escitalopram or venlafaxine. Early improvement was defined as a ≧20% reduction from baseline in Hamilton anxiety rating scale at week 1 or 2. The positive and negative predictive values were calculated. RESULTS: The positive and negative predictive values of early improvement in escitalopram or venlafaxine group at week 1 were (85.19%, 67.53%) vs (84.62%, 65.33%) DISCUSSION: The early improvement achieved within the first week treatment can predict a good 8-week treatment outcome in GAD patients.

Association analysis of COMT/MTHFR polymorphisms and major depressive disorder in Chinese Han population.

BACKGROUND: In several previous biochemical and genetic studies, the Val158Met polymorphism of the gene encoding catechol-O-methyltransferase (COMT) and the C677T polymorphism of Methylenetetrahydrofolate reductase (MTHFR) have been suggested to be involved in the pathogenesis as well as the treatment response of major depressive disorder (MDD), but the results have been inconsistent. In this study, we investigate the association of COMT/MTHFR and their interactions with MDD and antidepressant response in Chinese Han population. METHODS: Three hundred and sixty eight depressed patients who met DSM-IV criteria for MDD were recruited for the study. Two hundred and nineteen normal controls were recruited from the local community. Patients and normal controls were genotyped for the functional COMT val158met and MTHFR C677T polymorphisms. Patients were characterized for clinical response to antidepressant treatment as measured by intra-individual changes of Hamilton Depression (HAMD-17) scores over 6 weeks. RESULTS: The T allele (OR=1.81; CI95%=1.40-2.34, P<0.001) and C/T genotype (OR=3.66; CI95% =2.53-5.28, P<0.001) of MTHFR C677T were significantly different between case and control groups. The COMT Met/Val genotype was more common among depressed individuals than among controls (OR=1.52, CI95%=1.04-2.21, P=0.02). LIMITATION: There is disequilibrium in age and sex between case and control groups. Though we control the two variables in the statistic analysis, to be more accurate, we need to increase sample size in further study. CONCLUSION: Individuals with the genotype COMT Met/Val and MTHFR C/T have more probability of suffering from MDD. However, there is no association between gene polymorphism and treatment response.

[Research on association of BDNF gene Val66Met polymorphism with efficacy of antidepressants and plasma BDNF level].

OBJECTIVE: To assess the association of BDNF gene Val66Met polymorphism with efficacy of antidepressant treatment and plasma BDNF level. METHODS: Two hundred and forty-nine ethnic Han Chinese patients with depression(study group), who have met the diagnostic criteria of DSM-IV, were prescribed with venlafaxine or paroxetine. Two hundred and two healthy individuals were recruited as the control group. General demographic information such as gender, age, educational status, occupation, and marriage status were collected. HAMD-17 was adopted as the primary rating tool to evaluate the severity of depression on the baseline and at the end of 1st, 2nd, 4th, 6th week of treatment. PCR-restriction fragment length polymorphism was applied to determine the Val66Met polymorphism of the BDNF gene in the two groups. Plasma BDNF concentration was measured with ELISA before and after 6 weeks of treatment. RESULTS: No significant differences have been found in HAMD scores and reduction of HAMD scores on the baseline and at the end of 1 st, 2nd, 4th, 6th weeks of treatment for each genotype. Nor were significant differences found in the Val66Met genotypes and allelic frequency between patients who achieved remission or not after 6 weeks' treatment as well as the healthy volunteers. The plasma BDNF level in depression patients was lower than that in healthy controls. The BDNF level has increased significantly after 6 weeks' treatment with both venlafaxine and paroxetine, but was still lower than the healthy controls. The BDNF level in the patients achieved remission who were treated with venlafaxine was similar to the normal controls, while those treated with paroxetine was still lower than normal controls. The BDNF level in patients who have not achieved remission was lower than normal controls. The BDNF level was not associated with the Val66Met polymorphism on the baseline and the end of 6th week. CONCLUSION: No association has been found between the efficacy of venlafaxine or paroxetine and the BDNF Val66Met polymorphism. The BDNF level of patients with depression is significantly lower than healthy controls on the baseline, and can be enhanced with the treatment. Particularly, the BDNF level in patients who achieved remission after the treatment of venlafaxine can rise to normal. The level of BDNF has certain value in the forecasting of efficacy in the anti-depression therapy. BDNF level is not associated with the Val66Met polymorphism of the BDNF gene.

Risk factors for medication-induced amenorrhea in first-episode female Chinese patients with schizophrenia treated with risperidone.

BACKGROUND: Amenorrhea is a common adverse effect of treatment with antipsychotic medications that influences both fertility and adherence to medication regimens. Most research suggests that medication-induced prolactinemia is the main cause of amenorrhea but few prospective studies have assessed this hypothesis. AIM: Identify risk factors for amenorrhea following treatment with antipsychotic medication. METHODS: The study used a prospective, nested case-control design. First-episode, drug naïve female patients with schizophrenia who were in the middle of their menstrual cycle at the time of admission were enrolled. Serum levels of six reproductive hormones were assessed before and after a 12-week course of treatment with risperidone: progesterone, estradiol, prolactin, follicular stimulating hormone, luteinizing hormone, and testosterone. The hormone levels of 31 patients who had no menstruation during the entire 12 weeks of treatment (the amenorrhea group) were compared to those of 31 age-matched subjects who had normal menstrual periods over the 12 weeks of treatment (the control group). RESULTS: We found a dramatic 4-fold increase in prolactin levels in women of childbearing age treated with risperidone, but the pretreatment and posttreatment levels of prolactin were not different between patients who did and did not develop amenorrhea with treatment. However, there were significantly lower pretreatment levels of estradiol and progesterone in patients who subsequently developed amenorrhea with risperidone treatment than in patients who did not develop amenorrhea. A conditional logistic regression analysis found that pretreatment levels of estradiol remained significantly associated with the development of amenorrhea during treatment even when adjusting for the pretreatment levels of the other five reproductive hormones assessed. CONCLUSION: These findings do not support the suggestion that amenorrhea associated with the use of antipsychotic medication is the result of hyperprolactinemia. If our finding of the predictive power of pretreatment levels of estradiol is confirmed in larger studies, this information would be of use to clinicians in selecting antipsychotic medications for female patients with schizophrenia; patients at highest risk of developing amenorrhea could be preferentially treated with the medications that are at lowest risk of inducing amenorrhea.