Brain-gut axis mechanism of subthreshold nonsuicidal self-injury addictive features in adolescents.

Nonsuicidal self-injury (NSSI) is associated with an increased risk of suicide. As the diagnostic criteria outlined in DSM-5 and other related clinical studies, a patient must have engaged in self-injurious behavior at least 5 times within the past year. However, patients with fewer than 5 self-injury behaviors should not be ignored. Our study included 46 adolescents aged 10-19 years with subthreshold NSSI (sNSSI), along with a control group of 50 healthy adolescents matched for age and other factors. We collected resting-state functional magnetic resonance imaging data and stool samples. The Ottawa Self-Injury Inventory and Deliberate Self-Harm Inventory were used to evaluate self-harm behaviors and addictive features. Local brain activity was assessed using fractional amplitude of low-frequency fluctuations (fALFF), and brain regions with abnormal fALFF were selected as seeds for whole-brain functional connectivity analysis. Stool samples were identified using 16S rDNA amplicon sequencing, and the LDA Effect Size method was used to explore significant differences between grouped samples. Mediation analysis was performed to investigate the brain-gut axis mechanisms of addictive features in sNSSI. We found that compared with healthy controls, sNSSI patients have abnormal fALFF in left thalamus and posterior cingulate cortex, dysconnectivities of left thalamus, and decreased Prevotellaceae. Our results suggested that addictive features of sNSSI may have a brain-gut mechanism. Furtherly, patients with 1-4 NSSI behaviors in the past year should have separate name for identification, such as "subthreshold NSSI".

The combined impact of social networks and connectedness on anxiety, stress, and depression during COVID-19 quarantine: a retrospective observational study.

Introduction: The COVID-19 pandemic and associated quarantine measures have precipitated a surge in mental health disorders, particularly depression and anxiety. Government policies and restrictions on physical activity have contributed to this phenomenon, as well as diminished subjective social connectedness and exacerbated objective social isolation. As two dimensions of social isolation, it is worth noting that subjectively perceived social connectedness serves as a protective factor for mental health, whereas the decline in the size of objectively evaluated social networks poses a significant risk. However, research investigating the combined influence of these two dimensions remains limited. Methods: This study used an online survey to collect data to investigate the effects of objective social connectedness and objective social networks on anxiety, stress, and depression during COVID-19 quarantine. A total of 485 participants were analyzed using statistical methods, including paired t-test, Pearson correlation analysis, linear regression, cluster analysis, ANOVA, and moderated mediated. Results: The study found that anxiety and depression scores increased during the quarantine, with age, education, and social connectedness scores associated with the increase. Pre-quarantine anxiety and depression levels were strongly correlated with mental health status during quarantine. Cluster analysis, respectively, revealed three clusters for those without increasing anxiety and depression scores. The study also found that objective social network influences the impact of subjective social connectedness on pre-quarantine mental health, which in turn affects anxiety and depression levels during quarantine. Conclusion: The study identified that quarantine increased anxiety and depression, with age being protective, and education and subjective social connectedness as risk factors. The study also emphasizes the comprehensive impact of objective and subjective social isolation. Although individuals perceive the same degree of social connectedness, those with smaller social networks are more prone to developing symptoms of anxiety and depression, which are also more likely to worsen during quarantine.

Biochemical and Endocrine Parameters for the Discrimination and Calibration of Bipolar Disorder or Major Depressive Disorder.

Objectives: Conventional biochemical indexes may have predictive values in clinical identification between bipolar disorder (BD) and major depressive disorder (MDD). Methods: This study included 2,470 (BD/MDD = 1,333/1,137) hospitalized patients in Shanghai as training sets and 2,143 (BD/MDD = 955/1,188) in Hangzhou as test sets. A total of 35 clinical biochemical indexes were tested, including blood cells, immuno-inflammatory factors, liver enzymes, glycemic and lipid parameters, and thyroid and gonadal hormones. A stepwise analysis of a multivariable logistic regression was performed to build a predictive model to identify BD and MDD. Results: Most of these biochemical indexes showed significant differences between BD and MDD groups, such as white blood cell (WBC) in the hematopoietic system, uric acid (UA) in immuno-inflammatory factors, direct bilirubin (DBIL) in liver function, lactic dehydrogenase (LDH) in enzymes, and fasting blood glucose (FBG) and low-density lipoprotein (LDL) in glucolipid metabolism (p-values < 0.05). With these predictors for discrimination, we observed the area under the curve (AUC) of the predictive model to distinguish between BD and MDD to be 0.772 among men and 0.793 among women, with the largest AUC of 0.848 in the luteal phase of women. The χ2 values of internal and external validation for male and female datasets were 2.651/10.264 and 10.873/6.822 (p-values < 0.05), respectively. The AUCs of the test sets were 0.696 for males and 0.707 for females. Conclusion: Discrimination and calibration were satisfactory, with fair-to-good diagnostic accuracy and external calibration capability in the final prediction models. Female patients may have a higher differentiability with a conventional biochemical index than male patients. Trial Registration: ICTRP NCT03949218. Registered on 20 November 2018. Retrospectively registered. https://www.clinicaltrials.gov/ct2/show/NCT03949218?id=NCT03949218&rank=1.

Early Diagnosis of Bipolar Disorder Coming Soon: Application of an Oxidative Stress Injury Biomarker (BIOS) Model.

Early distinction of bipolar disorder (BD) from major depressive disorder (MDD) is difficult since no tools are available to estimate the risk of BD. In this study, we aimed to develop and validate a model of oxidative stress injury for predicting BD. Data were collected from 1252 BD and 1359 MDD patients, including 64 MDD patients identified as converting to BD from 2009 through 2018. 30 variables from a randomly-selected subsample of 1827 (70%) patients were used to develop the model, including age, sex, oxidative stress markers (uric acid, bilirubin, albumin, and prealbumin), sex hormones, cytokines, thyroid and liver function, and glycolipid metabolism. Univariate analyses and the Least Absolute Shrinkage and Selection Operator were applied for data dimension reduction and variable selection. Multivariable logistic regression was used to construct a model for predicting bipolar disorder by oxidative stress biomarkers (BIOS) on a nomogram. Internal validation was assessed in the remaining 784 patients (30%), and independent external validation was done with data from 3797 matched patients from five other hospitals in China. 10 predictors, mainly oxidative stress markers, were shown on the nomogram. The BIOS model showed good discrimination in the training sample, with an AUC of 75.1% (95% CI: 72.9%-77.3%), sensitivity of 0.66, and specificity of 0.73. The discrimination was good both in internal validation (AUC 72.1%, 68.6%-75.6%) and external validation (AUC 65.7%, 63.9%-67.5%). In this study, we developed a nomogram centered on oxidative stress injury, which could help in the individualized prediction of BD. For better real-world practice, a set of measurements, especially on oxidative stress markers, should be emphasized using big data in psychiatry.

Analysis of Seasonal Clinical Characteristics in Patients With Bipolar or Unipolar Depression.

This study was to investigate the characteristics of seasonal symptoms and non-enzymatic oxidative stress in the first hospitalized patients with bipolar and unipolar depression, aiming to differentiate bipolar depression from unipolar depression and reduce their misdiagnosis. A total of 450 patients with bipolar depression and 855 patients with depression were included in the present study. According to the season when the patients were admitted to the hospital due to the acute onset of depression, they were further divided into spring, summer, autumn and winter groups. According to the characteristics of symptoms of bipolar disorder in the DSM-5, the characteristic symptoms of bipolar disorder were collected from the medical record information, and clinical biochemical indicators that can reflect the oxidative stress were also recorded. The seasonal risk factors in patients with bipolar or unipolar depression were analyzed. The relationship of age and gender with the bipolar or unipolar depression which attacked in winter was explored. There were significant differences between groups in the melancholic features, atypical features and conjugated bilirubin in spring. In summer, there were significant differences between groups in the melancholic features, uric acid and conjugated bilirubin. In autumn, there were marked differences between groups in melancholic features, anxiety and pain, atypical features, uric acid, total bilirubin, conjugated bilirubin and albumin. In winter, the conjugated bilirubin and prealbumin were significantly different between two groups. The melancholic features and uric acid that in summer as well as melancholic features, uric acid and total bilirubin in autumn were the seasonal independent risk factors for the unipolar depression as compared to bipolar depression. In winter, significant difference was noted in the age between two groups. In conclusion, compared with patients with unipolar depression, patients with bipolar depression have seasonal characteristics. Clinical symptoms and indicators of oxidative stress may become factors for the differentiation of seasonal unipolar depression from bipolar depression. Young subjects aged 15-35 years are more likely to develop bipolar depression in winter.

Employing biochemical biomarkers for building decision tree models to predict bipolar disorder from major depressive disorder.

BACKGROUND: Conventional biochemical parameters may have predictive values for use in clinical identification between bipolar disorder (BD) and major depressive disorder (MDD). METHODS: This study enrolled 2470 hospitalized patients with BD (n = 1333) or MDD (n = 1137) at reproductive age from 2009 to 2018 in China. We extracted 8 parameters, uric acid (UA), direct bilirubin (DBIL), indirect bilirubin (IDBIL), lactic dehydrogenase (LDH), free triiodothyronine (FT3), thyroid-stimulating hormone (TSH), high-density lipoprotein (HDL) and prealbumin of male, patients and 12 parameters, UA, DBIL, IBIL, LDH, FT3, TSH, glutamic-pyruvic transaminase (GPT), white blood cell (WBC), alkaline phosphatase (ALP), fasting blood glucose (FBG), triglyceride and low-density lipoprotein (LDL) of female patients. Backward stepwise multivariate regression analysis and the Chi-Square Automatic Interaction Detection (CHAID) segmentation analysis via SPSS Decision Tree were implemented to define the discrimination of BD and MDD. RESULTS: DBIL was extracted as the first splitting variable, with LDH and IBIL as the second, TSH and prealbumin as the third in the model of male patients (p-value < .05). For the model of female patients, DBIL was also extracted as the first splitting variable, with UA, LDH, and IBIL as the second, triglyceride and FT3 as the third (p-value < .05). The predictive accuracies of the Decision Tree and multiple logistic regression models were similar (74.9% vs 76.9% in males; 74.4% vs 79.5% in females). CONCLUSIONS: This study suggests the value of the Decision Tree models, which employ biochemical parameters as diagnostic predictors for BD and MDD. The CHAID Decision Tree identified that patients with concomitantly increased LDH, IBIL, and decreased DBIL could be in the group that showed the highest risk of being diagnosed as BD.

Peripheral biomarkers to predict the diagnosis of bipolar disorder from major depressive disorder in adolescents.

The onset of bipolar disorder (BD) occurs in childhood or adolescence in half of the patients. Early stages of BD usually present depressive episodes, which makes it difficult to be distinguished from major depressive disorder (MDD). Objective biomarkers for discriminating BD from MDD in adolescent patients are limited. We collected basic demographic data and the information of the first blood examination performed after the admission to psychiatry unit of BD and MDD inpatients during 2009-2018. We recruited 261 adolescents (aged from 10 to 18), including 160 MDD and 101 BD. Forward-Stepwise Selection of binary logistic regression was used to construct predictive models for the total sample and subgroups by gender. Independent external validation was made by 255 matched patients from another hospital in China. Regression models of total adolescents, male and female subgroups showed accuracy of 73.3%, 70.6% and 75.2%, with area under curves (AUC) as 0.785, 0.816 and 0.793, respectively. Age, direct bilirubin (DBIL), lactic dehydrogenase (LDH), free triiodothyronine (FT3) and C-reactive protein (CRP) were final factors included into the models. The discrimination was well at external validation (AUC = 0.714). This study offers the evidence that accessible information of common clinical laboratory examination might be valuable in distinguishing BD form MDD in adolescents. With good diagnostic accuracies and external validation, the total regression equation might potentially be applied to individualized clinical inferences on adolescent BD patients.

Hypothalamic-Pituitary-End-Organ Axes: Hormone Function in Female Patients with Major Depressive Disorder.

Classic hypothalamic-pituitary-end-organ feedback loops - the hypothalamic-pituitary-adrenal axis (HPAA), hypothalamic-pituitary-thyroidal axis (HPTA), and hypothalamic-pituitary-gonadal axis (HPGA) - are associated with the neuroendocrine and immune systems in major depressive disorder (MDD). Female patients with MDD present with evident neuroendocrine and immunological changes. Glucocorticoid, thyroid hormone, and reproductive steroid levels fluctuate with menstrual cycles, which might lead to glucocorticoid receptor resistance, impairment of triiodothyronine conversion, and sex hormone secretion disorders. In this review, we summarize the independent and interactive functions of these three axes in female MDD patients. The similar molecular structure of steroids implies an interrelationship between the hypothalamic-pituitary-end-organ axes and the competitive inhibitory effects at the receptor level, especially when considering the HPAA and HPGA.

Lack of Association Between PLA2G6 Genetic Variation and Parkinson's Disease: A Systematic Review.

BACKGROUND: The phospholipase A2 Group 6 (PLA2G6, also known as PLA2, PARK14, and iPLA2) gene encodes a group VIA calcium-independent phospholipase A2. Genetic polymorphism of PLA2G6 has been indicated to be involved in conferring susceptibility for Parkinson's disease (PD), whereas conclusive results have not been obtained. Thus, we intended to conduct a systematic review to determine if PLA2G6 genetic variation confers a greater susceptibility to PD. METHODS: All case-control studies that investigated the association of the PLA2G6 polymorphisms with the risk of PD published before 15 July 2018 were included. The literature was comprehensively searched and identified in five English databases (EBSCO, Pubmed, OVID, EMBASE and ISI Web of Knowledge) and four Chinese databases (Wanfang database, Chinese Biomedical Literature Database, China Academic Journals Database and VIP database). We performed analyses of study characteristics, heterogeneity, and forest plot in analyses analogous to dominant, codominant and additive models with the pooled odds ratio (OR) in fixed- or random-effects models as the measure of association. RESULTS: A total of 664 potentially relevant studies were retrieved with the initial search, of which eight studies fulfilled the inclusion criteria, and included 2,779 PD patients and 3,291 control participants,. Among all the reported 27 genetic variants, 15 single nucleotide polymorphisms (SNPs) were present only in patients, and only five available SNPs (rs2267369, rs140758033, c.1959T>A (Gly653Gly), rs76718524, rs199935023) were pooled in the meta-analysis. However, there was no evidence for a significant association between the five SNPs and PD risk in dominant, codominant and allele models, suggesting a lack of association between PLA2G6 genetic variation and PD susceptibility. CONCLUSION: The present study assessed the association of PLA2G6 genetic polymorphism with the risk PD, and the result strongly demonstrates that PLA2G6 polymorphism is not associated with PD susceptibility.

Altered resting-state fMRI signals and network topological properties of bipolar depression patients with anxiety symptoms.

BACKGROUND: This study aims to explore the changes in functional neuroimaging in bipolar depression patients with anxiety symptoms (BDP-A). METHODS: Forty-five BDP-A patients, 22 bipolar depression patients without anxiety symptoms (BDP-NA), and 48 healthy controls (HC) were finally involved. The low-frequency oscillation characteristics, functional connectivity (FC), and network properties among the three groups of participants were analyzed. RESULTS: Compared with the BDP-NA group, BDP-A patients exhibited significantly decreased amplitude of low-frequency fluctuation (ALFF) in the left middle frontal gyrus (MFG), superior occipital gyrus, and inferior parietal, but supramarginal and angular gyri (IPL). Enhanced FC from left IPL to middle temporal gyrus, from left precentral gyrus (PreCG) to bilateral angular gyri, medial superior frontal gyrus, and left superior frontal gyrus (SFG)/MFG were also revealed. Compared with HC, the BDP-A group showed remarkably increased ALFF in the left MFG/PreCG, right superior parietal gyrus, while decreased ALFF in the left inferior frontal gyrus, opercular part, and SFG. In addition, higher regional homogeneity in the left MFG/PreCG was found. LIMITATIONS: The limitations are as follows: (1) relatively small sample size; (2) not all the patients were drug-naive; (3) lack of pure anxiety disorder patients as a controlled group; (4) mental health conditions of HC were not systemic evaluated. CONCLUSIONS: BDP-A patients showed significant differences in resting-state fMRI properties when compared with BDP-NA or HC group. These results may infer the dysfunction of the dorsal attention network, the default network, and the fronto-limbic system as well as disrupted brain network efficiency in BDP-A patients.

Ifenprodil rapidly ameliorates depressive-like behaviors, activates mTOR signaling and modulates proinflammatory cytokines in the hippocampus of CUMS rats.

RATIONALE: The rapid-onset and long-lasting antidepressant properties of ketamine have prompted investigations into a variety of agents that target N-methyl-D-aspartate receptors (NMDARs) for the treatment of major depressive disorder (MDD). According to the literature, ifenprodil (a GluN2B-containing NMDAR antagonist) can potentiate the antidepressant-like effects of certain antidepressant drugs in mice. Here, we report that a single injection of ifenprodil (3 mg/kg, intraperitoneally (i.p.)) was sufficient to provoke rapid antidepressant-like effects in chronic unpredictable mild stress (CUMS) rats. Moreover, ifenprodil activated mTOR signaling and reversed the CUMS-induced elevation of interleukin-1ß (IL-1ß), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α) in the hippocampus after acute administration. Unfortunately, in our study, ifenprodil had no influence on corticosterone levels in the plasma. Our data indicate that ifenprodil per se might exert antidepressant-like effects by modulating neuroplasticity and inflammatory processes rather than the typical hormonal factors affected by stressors. OBJECTIVES: To explore the potential rapid antidepressant-like effects and mechanisms of ifenprodil, a GluN2B subunit-selective NMDAR antagonist. METHODS: Male Sprague-Dawley rats were used in 3 separate experiments. In experiment 1, we used the forced swim test (FST) and sucrose preference test (SPT) to identify the rapid antidepressant-like effects of ifenprodil in chronic unpredictable mild stress (CUMS) rats after acute administration. In experiment 2, we assessed neurochemical changes involved in synaptic plasticity within the hippocampus of CUMS rats. In experiment 3, we assessed the levels of corticosterone in the plasma and proinflammatory cytokines in the hippocampus in CUMS rats after ifenprodil treatment. RESULTS: Ifenprodil rapidly ameliorated depressive-like behaviors in the FST and SPT, activated mTOR signaling, dephosphorylated eukaryotic elongation factor 2, enhanced BDNF expression, and promoted the synthesis of the synaptic protein GluA1 synthesis after acute administration. Moreover, ifenprodil reversed the CUMS-induced elevation of interleukin-1ß (IL-1ß), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α) in the hippocampus after acute administration. Unfortunately, ifenprodil had no influence on corticosterone levels in the plasma in our study. CONCLUSIONS: Our data indicate that ifenprodil per se might exert antidepressant-like effects through its effects on neuroplasticity and inflammatory processes rather than the typical hormonal factors affected by stressors.

Causes of drug discontinuation in patients with major depressive disorder in China.

BACKGROUND: This research was designed to investigate patient-reported and doctor-reported reasons for the discontinuation of pharmacological treatment in Chinese patients with major depressive disorder (MDD), which was part of the National Survey on Symptomatology of Depression (NSSD) from 2014 to 2015. METHODS: This cross-sectional study included 649 patients who had discontinued antidepressant medications and 711 patients who had remained on them, selected from a group of 3516 candidates who have had at least one depressive episode. Differences in the two groups' sociodemographic factors, clinical characteristics, medication use, and self-reported reasons for drug discontinuation were compared via Student's t-test or chi-square test. Logistic regression analysis was then used to determine the association of all non-subjective dichotomous and ordinal categorical variables, including the additional 63 items of our physician-evaluated symptomatic assessment, with drug compliance. RESULTS: Compared to the spontaneous drug discontinuation (SDD) group, the drug adherence (DA) group had significantly lower rates of the following: family history of mental disease (9.0% vs 13.6%), highest level of education achieved being post-graduate or above (1.6% vs 4.7%), smoking (5.8% vs 9.7%), and other health problems (33.9% vs 42.4%) (p's < 0.05). On the other hand, first-episode depression (48.5% vs 21.9%) and taking of mood stabilizer(s) (8.3% vs 5.6%) were higher in the former group than in the latter (p's < 0.05). Logistic Regression Analysis showed that five symptoms, such as depressed mood, were correlated positively with SDD, while another six symptoms, such as psychomotor retardation, were correlated negatively with it. The receiver operating characteristic (ROC) curve of this model yielded an area under the curve (AUC) of 0.701 (95% CI, 0.673-0.729). Notably, there were three main reasons given by patients in the DA group as to why they discontinued their medication(s): (1) concern about long-term side effects (36.1%), (2) no perceived need for taking said medication(s) long-term (34.2%), and (3) believing oneself to have been cured completely (30.0%). CONCLUSIONS: The aforementioned factors may affect patient compliance and elicit maladaptive thinking even from patients with good educational backgrounds, increasing the risk of drug discontinuation. Compliance of pharmacological treatment might be improved by increasing clarification and elucidation of different symptom clusters to the patient and combating the main reasons for drug discontinuation.

Internet-Based Management for Depressive Disorder.

The advances in the Internet and related technologies may lead to changes in professional roles of psychiatrists and psychotherapists. The application of artificial intelligence (AI) and electronic measurement-based care (eMBC) in the treatment of depressive disorder has addressed more interest. AI could play a role in population health management and patient administration as well as assist physicians to make a decision in the real-world clinical practice. The eMBC strengthens MBC through web/mobile devices and telephone consulting services, to monitor disease progression, and customizes the MBC interface in electronic medical record systems (EMRs).

The Relationship Between Neuroimmunity and Bipolar Disorder: Mechanism and Translational Application.

Neuroimmune system may be involved in the pathological process of bipolar disorder (BD), but the essential association is not fully understood. Accumulating evidence has shown that BD involves the activation of immune cells and the release of inflammatory substances in the central nerve system (CNS). Meanwhile, neuroimmune responses also interact with other hypothesis of the etiology of BD that are widely recognized, such as neurotransmitter systems, neuroendocrine systems, neurotrophic factors, and oxidative stress. Simultaneously, related genes and immune changes in peripheral blood vary with it. Overall, neuroimmunity may play an important role in the pathogenesis of BD, and the inflammatory cytokines, especially interleukin-6 and tumor necrosis factor-alpha, have potential value for the clinical diagnosis and prognosis of BD, as well as predicting the therapeutic effects of drugs. Large-scale studies are needed to extend the evidence on neuroimmunity in BD, and to examine its clinical value for applications such as early prediction and treatment.