miR-29a-5p rescues depressive-like behaviors in a CUMS-induced mouse model by facilitating microglia M2-polarization in the prefrontal cortex via TMEM33 suppression.

BACKGROUND: Depression accounts for a high proportion of neuropsychiatric disorders and is associated with abnormal states of neurons in specific brain regions. Microglia play a pivotal role in the inflammatory state during depression development; however, the exact mechanism underlying chronic mood states remains unknown. Thus, the present study aimed to determine whether microRNAs (miRNAs) alleviate stress-induced depression-like behavior in mice by regulating the expression levels of their target genes, explore the role of neuroinflammation induced by microglial activation in the pathogenesis and progression of depression, and determine whether the role of the miR-29a-5p/transmembrane protein 33 (TMEM33) axis. METHODS: In this study, chronic unpredictable mild stress (CUMS) mouse depression model, various behavioral tests, western blotting, dual-luciferase reporter assay, enzyme-linked immunosorbent assay, real-time quantitative reverse transcription PCR, immunofluorescence and lentivirus-mediated gene transfer were used. RESULTS: After exposure to the CUMS paradigm, miR-29a-5p was significantly down-regulated. This downregulation subsequently promoted the polarization of microglia M1 by upregulating the expression of TMEM33, resulting in enhanced inflammatory chemokines affecting neurons. Conversely, the upregulation of miR-29a-5p within the prefrontal cortex (PFC) suppressed TMEM33 expression, facilitated microglia M2-polarization, and ameliorated depressive-like behavior. LIMITATIONS: Only rodent models of depression were used, and human samples were not included. CONCLUSIONS: The results of this study suggest that miR-29a-5p deficits within the PFC mediate microglial anomalies and contribute to depressive-like behaviors. miR-29a-5p and TMEM33 may, therefore, serve as potential therapeutic targets for the treatment of depression.

Dose adjustment of paroxetine based on CYP2D6 activity score inferred metabolizer status in Chinese Han patients with depressive or anxiety disorders: a prospective study and cross-ethnic meta-analysis.

BACKGROUND: Understanding the impact of CYP2D6 metabolism on paroxetine, a widely used antidepressant, is essential for precision dosing. METHODS: We conducted an 8-week, multi-center, single-drug, 2-week wash period prospective cohort study in 921 Chinese Han patients with depressive or anxiety disorders (ChiCTR2000038462). We performed CYP2D6 genotyping (single nucleotide variant and copy number variant) to derive the CYP2D6 activity score and evaluated paroxetine treatment outcomes including steady-state concentration, treatment efficacy, and adverse reaction. CYP2D6 metabolizer status was categorized into poor metabolizers (PMs), intermediate metabolizers (IMs), extensive metabolizers (EMs), and ultrarapid metabolizers (UMs). The influence of CYP2D6 metabolic phenotype on paroxetine treatment outcomes was examined using multiple regression analysis and cross-ethnic meta-analysis. The therapeutic reference range of paroxetine was estimated by receiver operating characteristic (ROC) analyses. FINDINGS: After adjusting for demographic factors, the steady-state concentrations of paroxetine in PMs, IMs, and UMs were 2.50, 1.12, and 0.39 times that of EMs, with PM and UM effects being statistically significant (multiple linear regression, P = 0.03 and P = 0.04). Sex and ethnicity influenced the comparison between IMs and EMs. Moreover, poor efficacy of paroxetine was associated with UM, and a higher risk of developing adverse reactions was associated with lower CYP2D6 activity score. Lastly, cross-ethnic meta-analysis suggested dose adjustments for PMs, IMs, EMs, and UMs in the East Asian population to be 35%, 40%, 143%, and 241% of the manufacturer's recommended dose, and 62%, 68%, 131%, and 159% in the non-East Asian population. INTERPRETATION: Our findings advocate for precision dosing based on the CYP2D6 metabolic phenotype, with sex and ethnicity being crucial considerations in this approach. FUNDING: National Natural Science Foundation of China; Academy of Medical Sciences Research Unit.

Accelerated transcranial magnetic stimulation for major depressive disorder: A quick path to relief?

Transcranial magnetic stimulation (TMS) is a safe, tolerable, and evidence-based intervention for major depressive disorder (MDD). However, even after decades of research, nearly half of the patients with MDD fail to respond to conventional TMS, with responding slowly and requiring daily attendance at the treatment site for 4-6 weeks. To intensify antidepressant efficacy and shorten treatment duration, accelerated TMS protocols, which involve multiple sessions per day over a few days, have been proposed and evaluated for safety and viability. We reviewed and summarized the current knowledge in accelerated TMS, including stimulation parameters, antidepressant efficacy, anti-suicidal efficacy, safety, and adverse effects. Limitations and suggestions for future directions are also addressed, along with a brief discussion on the application of accelerated TMS during the COVID-19 pandemic. This article is categorized under: Neuroscience > Clinical Neuroscience.

rTMS ameliorates depressive-like behaviors and regulates the gut microbiome and medium- and long-chain fatty acids in mice exposed to chronic unpredictable mild stress.

INTRODUCTION: Repetitive transcranial magnetic stimulation (rTMS) is a clinically useful therapy for depression. However, the effects of rTMS on the metabolism of fatty acids (FAs) and the composition of gut microbiota in depression are not well established. METHODS: Mice received rTMS (15 Hz, 1.26 T) for seven consecutive days after exposure to chronic unpredictable mild stress (CUMS). The subsequent depressive-like behaviors, the composition of gut microbiota of stool samples, as well as medium- and long-chain fatty acids (MLCFAs) in the plasma, prefrontal cortex (PFC), and hippocampus (HPC) were evaluated. RESULTS: CUMS induced remarkable changes in gut microbiotas and fatty acids, specifically in community diversity of gut microbiotas and PUFAs in the brain. 15 Hz rTMS treatment alleviates depressive-like behaviors and partially normalized CUMS induced alterations of microbiotas and MLCFAs, especially the abundance of Cyanobacteria, Actinobacteriota, and levels of polyunsaturated fatty acids (PUFAs) in the hippocampus and PFC. CONCLUSION: These findings revealed that the modulation of gut microbiotas and PUFAs metabolism might partly contribute to the antidepressant effect of rTMS.

Prevalence and clinical correlates of abnormal glucose metabolism in young, first- episode and medication-naïve outpatients with major depressive disorder.

BACKGROUNDS: The high co-morbidity of abnormal glucose metabolism in depressed patients has been extensively studied, but few studies have explored abnormal glucose metabolism in young patients with major depressive disorder (MDD). This study aimed to examine the prevalence and clinical correlates of abnormal glucose metabolism in young patients with first-episode medication-naïve (FEMN) MDD. METHODS: A cross-sectional study was conducted on 1289 young Chinese outpatients with FEMN MDD. All subjects were assessed on the Hamilton Depression Rating Scale, Hamilton Anxiety Rating Scale (HAMA), Positive and Negative Syndrome Scale, and their sociodemographic information was collected, and blood pressure, blood glucose, lipid and thyroid hormone levels were measured. RESULTS: The prevalence of abnormal glucose metabolism was 12.57% in young FEMN MDD outpatients. Thyroid stimulating hormone (TSH) levels and HAMA scale scores were associated with fasting blood glucose levels in patients with FEMN MDD (P<0.05), and TSH could differentiate patients with abnormal normal glucose metabolism from those without abnormal glucose metabolism (Area Under Curve of 0.774). CONCLUSIONS: Our study showed a high prevalence of comorbid glucose metabolism abnormalities in young FEMN MDD outpatients. TSH may be a promising biomarker of abnormal glucose metabolism in young patients with FEMN MDD.

High-frequency repetitive transcranial magnetic stimulation regulates neural oscillations of the hippocampus and prefrontal cortex in mice by modulating endocannabinoid signalling.

BACKGROUND: Neural oscillations play a role in the antidepressant effects of repetitive transcranial magnetic stimulation (rTMS). However, the effects of high-frequency rTMS on the neural oscillations of the medial prefrontal cortex (mPFC) and hippocampus (HPC) and its molecular mechanism have not been fully clarified. METHODS: The depressive-like behaviours, local field potentials (LFPs) of the ventral HPC (vHPC)-mPFC, and alternations of endocannabinoid system (ECS) in the HPC and mPFC were observed after rTMS treatment. Meanwhile, depressive-like behaviours and LFPs were also observed after cannabinoid type-1 receptor (CB1R) antagonist AM281 or monoacylglycerol lipase inhibitor JZL184 injection. Moreover, the antidepressant effect of rTMS was further assessed in glutamatergic-CB1R and gamma-amino butyric acid (GABA)-ergic -CB1R knockout mice. RESULTS: Alternations of endocannabinoids and energy value and synchronisation of mPFC-vHPC, especially the decrease of theta oscillation induced by CUMS, were alleviated by rTMS. JZL184 has similar effects to rTMS and AM281 blocked the effects of rTMS. GABAergic-CB1R deletion inhibited CUMS-induced depressive-like behaviours whereas Glutaminergic-CB1R deletion dampened the antidepressant effects of rTMS. LIMITATIONS: The immediate effect of rTMS on field-potential regulation was not observed. Moreover, the role of region-specific regulation of the ECS in the antidepressant effect of rTMS was unclear and the effects of cell-specific CB1R knockout on neuronal oscillations of the mPFC and vHPC should be further investigated. CONCLUSION: Endocannabinoid system mediated the antidepressant effects and was involved in the regulation of LFP in the vHPC-mPFC of high-frequency rTMS.

The Feature of Sleep Spindle Deficits in Patients With Schizophrenia With and Without Auditory Verbal Hallucinations.

BACKGROUND: Previous sleep electroencephalography studies have detected abnormalities in sleep architecture and sleep spindle deficits in schizophrenia (SCZ), but the consistency of these results was not robust, which might be due to the small sample size and the influence of clinical factors such as the various medication therapies and symptom heterogeneity. This study aimed to regard auditory verbal hallucinations (AVHs) as a pointcut to downscale the heterogeneity of SCZ and explore whether some sleep architecture and spindle parameters were more severely impaired in SCZ patients with AVHs compared with those without AVHs. METHODS: A total of 90 SCZ patients with AVHs, 92 SCZ patients without AVHs, and 91 healthy control subjects were recruited, and parameters of sleep architecture and spindle activities were compared between groups. The correlation between significant sleep parameters and clinical indicators was analyzed. RESULTS: Deficits of sleep spindle activities at prefrontal electrodes and intrahemispheric spindle coherence were observed in both AVH and non-AVH groups, several of which were more serious in the AVH group. In addition, deficits of spindle activities at central and occipital electrodes and interhemispheric spindle coherence mainly manifested accompanying AVH symptoms, most of which were retained in the medication-naive first-episode patients, and were associated with Auditory Hallucination Rating Scale scores. CONCLUSIONS: Our results suggest that the underlying mechanism of spindle deficits might be different between SCZ patients with and without AVHs. In the future, the sleep feature of SCZ patients with different symptoms and the influence of clinical factors, such as medication therapy, should be further illustrated.

Gut microbial signatures and differences in bipolar disorder and schizophrenia of emerging adulthood.

INTRODUCTION: Gut microbial disturbance has been established as potential pathogenesis of mental disorders. However, the signatures and differences regarding patients with schizophrenia (SCH) or bipolar disorder (BD) in emerging adulthood as well as their subtypes have been poorly addressed. METHODS: In the present study, stool samples obtained from 63 emerging adult patients with schizophrenia (SCH), 50 with bipolar disorder (BD), and 40 healthy controls (HC) were analyzed by 16 S rRNA gene sequencing; psychiatric symptoms and psychological, social, and professional functioning were also assessed. RESULTS: We found that gut microbiota composition was remarkably changed in the patients with SCH and BD. Moreover, the distinct gut microbiome signatures and their potential function in bipolar depression (BP-D) and SCH with predominantly negative symptoms (SCH-N) as well as bipolar mania (BP-M) and SCH with predominantly positive symptoms (SCH-P) were also observed. Furthermore, we identified diagnostic potential biomarkers that can distinguish BD from HC (38 genera, AUC = 0.961), SCH from HC (32 genera, AUC = 0.962), and BD from Scheme (13 genera, AUC = 0.823). Potential diagnostic biomarkers that can distinguish BD-D from SCH-N (16 genera, AUC = 0.969) and BD-M from SCH-P (31 genera, AUC = 0.938) were also identified. CONCLUSION: This study provides further understanding of abnormal gut microbiome in emerging adulthood patients with SCH and BD and lay the potential foundation for the development of microbe-based clinical diagnosis for BD and SCH.

Heterogenous Subtypes of Late-Life Depression and Their Cognitive Patterns: A Latent Class Analysis.

Background: Late-life depression (LLD), characterized by cognitive deficits, is considered heterogeneous across individuals. Previous studies have identified subtypes with diverse symptom profiles, but their cognitive patterns are unknown. This study aimed to investigate the subtypes of LLD and the cognitive profile of each group. Methods: In total, 109 depressed older adults were enrolled. We performed latent class analysis using Geriatric Depression Scale items as indicators to generate latent classes. We compared the sociodemographic and clinical characteristics with cognitive functions between groups and conducted regression analysis to investigate the association between class membership and variables with significant differences. Results: Two classes were identified: the "pessimistic" group was characterized by pessimistic thoughts and the "worried" group with a relatively high prevalence of worry symptoms. The two groups did not differ in sociodemographic characteristics. The "pessimistic" group showed a higher rate of past history of depression and lower age of onset. The "worried" group had more physical comorbidities and a higher rate of past history of anxiety. The "pessimistic" group was more impaired in general cognitive function, executive function, information processing speed, and attention. Lower general and executive functions were associated with the membership in the "pessimistic" group. Conclusions: Subjects with pessimistic symptoms and subjects with a propensity to worry may form two distinct subtypes of late-life depression with different cognitive profiles. Further, the cognitive evaluation of subjects with pessimistic symptoms is of utmost importance.

The Impact of Electroacupuncture Early Intervention on the Brain Lipidome in a Mouse Model of Post-traumatic Stress Disorder.

The neuroprotective effect of electroacupuncture (EA) treatment has been well studied; growing evidence suggests that changes in lipid composition may be involved in the pathogenesis of post-traumatic stress disorder (PTSD) and may be a target for treatment. However, the influence of early EA intervention on brain lipid composition in patients with PTSD has never been investigated. Using a modified single prolonged stress (mSPS) model in mice, we assessed the anti-PTSD-like effects of early intervention using EA and evaluated changes in lipid composition in the hippocampus and prefrontal cortex (PFC) using a mass spectrometry-based lipidomic approach. mSPS induced changes in lipid composition in the hippocampus, notably in the content of sphingolipids, glycerolipids, and fatty acyls. These lipid changes were more robust than those observed in the PFC. Early intervention with EA after mSPS ameliorated PTSD-like behaviors and partly normalized mSPS-induced lipid changes, notably in the hippocampus. Cumulatively, our data suggest that EA may reverse mSPS-induced PTSD-like behaviors due to region-specific regulation of the brain lipidome, providing new insights into the therapeutic mechanism of EA.

A parallel-group study of near-infrared spectroscopy-neurofeedback in children with attention deficit hyperactivity disorder.

The present study aimed to assess the efficacy of Near-infrared spectroscopy (NIRS) real-time neurofeedback (NF) vs. atomoxetine (AT) in children with attention deficit hyperactivity disorder (ADHD). A parallel-group study was conducted to enroll children with ADHD between 8 and 12 years of age. Participants were assigned into the NIRS group and AT group as their wish. Subjects in the NIRS group received 12 sessions of NF training within 6 weeks, and subjects in the AT group were given oral medication. Changes in Swanson, Nolan, and Pelham-V rating scales (SNAP-IV), and performance of Go/No-Go and N-back working memory tasks at week 3, 6 and 8 were evaluated. Forty-nine patients completed the study, including 18 ADHD in the NIRS group and 31 in the AT group. Total scores of SNAP-IV significantly decreased from baseline to week 3, week 6, and week 8 in both groups. Patients in the NIRS group showed significant lower scores on the inattention subscale of SNAP-IV at week 3 and week 6, compared to the AT group. NIRS group had a shorter reaction time during the Go/No-Go task at week 6 and fewer errors during 2-back than the AT group at week 3. The findings revealed that NIRS real-time NF is more efficacious relative to AT in improving behavioral performance, highlighting its potential role and advantages in treating patients with ADHD.

The DIRECT consortium and the REST-meta-MDD project: towards neuroimaging biomarkers of major depressive disorder.

Despite a growing neuroimaging literature on the pathophysiology of major depressive disorder (MDD), reproducible findings are lacking, probably reflecting mostly small sample sizes and heterogeneity in analytic approaches. To address these issues, the Depression Imaging REsearch ConsorTium (DIRECT) was launched. The REST-meta-MDD project, pooling 2428 functional brain images processed with a standardized pipeline across all participating sites, has been the first effort from DIRECT. In this review, we present an overview of the motivations, rationale, and principal findings of the studies so far from the REST-meta-MDD project. Findings from the first round of analyses of the pooled repository have included alterations in functional connectivity within the default mode network, in whole-brain topological properties, in dynamic features, and in functional lateralization. These well-powered exploratory observations have also provided the basis for future longitudinal hypothesis-driven research. Following these fruitful explorations, DIRECT has proceeded to its second stage of data sharing that seeks to examine ethnicity in brain alterations in MDD by extending the exclusive Chinese original sample to other ethnic groups through international collaborations. A state-of-the-art, surface-based preprocessing pipeline has also been introduced to improve sensitivity. Functional images from patients with bipolar disorder and schizophrenia will be included to identify shared and unique abnormalities across diagnosis boundaries. In addition, large-scale longitudinal studies targeting brain network alterations following antidepressant treatment, aggregation of diffusion tensor images, and the development of functional magnetic resonance imaging-guided neuromodulation approaches are underway. Through these endeavours, we hope to accelerate the translation of functional neuroimaging findings to clinical use, such as evaluating longitudinal effects of antidepressant medications and developing individualized neuromodulation targets, while building an open repository for the scientific community.

Triple network hypothesis-related disrupted connections in schizophrenia: A spectral dynamic causal modeling analysis with functional magnetic resonance imaging.

OBJECTIVE: The symptom-related neurobiology characteristic of schizophrenia in the brain from a network perspective is still poorly understood, leading to a lack of potential biologically-based markers and difficulty identifying therapeutic targets. We aim to test the dysregulated cross-network interactions among the Salience Network (SN), Central Executive Network (CEN) and Default Mode Network (DMN) and how they contributed to different symptoms in schizophrenia patients. METHODS: We examined network interactions among the SN, CEN and DMN in 76 patients with schizophrenia vs. 80 well-matched controls using dynamic causal modeling (DCM). We further analyzed the relation between network dynamics and Positive and Negative Syndrome Scale (PANSS). RESULTS: We observed that the DMN, CEN and SN across healthy controls and schizophrenia patients showed several similarities within or between-network pattern in the resting state. Comparing schizophrenia to controls, SN-centered cross-network interactions were most significantly reduced. Crucially, the strength of connections from CEN subnetwork 1 to DMN subnetwork 1 was positively correlated with the Positive Score of PANSS. The connection from the DMN subnetwork 2 to CEN subnetwork 2 was negatively correlated with the Negative Score of PANSS. CONCLUSIONS: Our study provides strong evidence for the dysregulation among SN, CEN and DMN in a triple-network perspective in schizophrenia. The connection between DMN and CEN could be clinically-relevant neurobiological signature of schizophrenia symptoms. Our study indicated that the description of brain triple network hypothesis could be a novel and possible bio-marker for schizophrenia.

Gut microbiota dysbiosis in depressed women: The association of symptom severity and microbiota function.

BACKGROUND: The association between abnormal gut microbiome composition and depression is well established. However, the composition and functional capacity of the gut microbiota regarding depressed women has been poorly addressed. METHODS: Stool samples from 62 female patients with major depressive disorder (MDD) and 46 healthy controls (Con) were analyzed by 16S rRNA gene sequencing; Twenty fecal samples from the patient group and 21 fecal samples from the Con group were further analyzed by shotgun metagenomic sequencing. Psychiatric symptoms and psychological, social, and professional functioning was also assessed. RESULTS: Phylum Bacteroidetes, proteobaeteria, and Fusobacteria were greatly enriched in patients with MDD, while the Firmicutes and Actinobacteria phyla were consistently higher in Con. Notably, 18 microbial markers were identified on a random forest model and achieve an area under the curve of 0.92 between patients with MDD and the Con group. Forty-five species and their associated function were identified with statistically significant differences between patients with MDD and the Con group. LIMITATIONS: The number of recruited samples, especially samples enrolled for shotgun metagenomic sequencing was relatively small, and the stool samples were collected only at baseline, making it difficult to establish a causal association between changes in gut microbiota compositions and disease remission. CONCLUSIONS: This study characterizes the gut microbiota and their related function in female MDD. The gut microbiota-based biomarkers may be helpful in diagnosis and the altered gut microbial metabolites may contribute to the pathogenesis of MDD in women, representing potential microbial targets.

Baseline structural and functional magnetic resonance imaging predicts early treatment response in schizophrenia with radiomics strategy.

Multimodal neuroimaging features provide opportunities for accurate classification and personalized treatment options in the psychiatric domain. This study aimed to investigate whether brain features predict responses to the overall treatment of schizophrenia at the end of the first or a single hospitalization. Structural and functional magnetic resonance imaging (MRI) data from two independent samples (N = 85 and 63, separately) of schizophrenia patients at baseline were included. After treatment, patients were classified as responders and non-responders. Radiomics features of gray matter morphology and functional connectivity were extracted using Least Absolute Shrinkage and Selection Operator. Support vector machine was used to explore the predictive performance. Prediction models were based on structural features (cortical thickness, surface area, gray matter regional volume, mean curvature, metric distortion, and sulcal depth), functional features (functional connectivity), and combined features. There were 12 features after dimensionality reduction. The structural features involved the right precuneus, cuneus, and inferior parietal lobule. The functional features predominately included inter-hemispheric connectivity. We observed a prediction accuracy of 80.38% (sensitivity: 87.28%; specificity 82.47%) for the model using functional features, and 69.68% (sensitivity: 83.96%; specificity: 72.41%) for the one using structural features. Our model combining both structural and functional features achieved a higher accuracy of 85.03%, with 92.04% responder and 80.23% non-responders to the overall treatment to be correctly predicted. These results highlight the power of structural and functional MRI-derived radiomics features to predict early response to treatment in schizophrenia. Prediction models of the very early treatment response in schizophrenia could augment effective therapeutic strategies.

The impact of quetiapine on the brain lipidome in a cuprizone-induced mouse model of schizophrenia.

The antipsychotic effect of Quetiapine (Que) has been extensively studied and growing evidence suggests that Que has a beneficial effect, improving cognitive functions and promoting myelin repair. However, the effects of Que on the brain lipidome and the association between Que-associated cognitive improvement and changes in lipids remain elusive. In the present study, we assessed the cognitive protective effects of Que treatment and used a mass spectrometry-based lipidomic approach to evaluated changes in lipid composition in the hippocampus, prefrontal cortex (PFC), and striatum in a mouse model of cuprizone (CPZ)-induced demyelination. CPZ induces cognitive impairment and remarkable lipid changes in the brain, specifically in lipid species of glycerophospholipids and sphingolipids. Moreover, the changes in lipid classes of the PFC were more extensive than those observed in the hippocampus and striatum. Notably, Que treatment ameliorated cuprizone-induced cognitive impairment and partly normalized CPZ-induced lipid changes. Taken together, our data suggest that Que may rescue cognitive behavioral changes from CPZ-induced demyelination through modulation of the brain lipidome, providing new insights into the pharmacological mechanism of Que for schizophrenia.

The relations among worry, meta-worry, intolerance of uncertainty and attentional bias for threat in men at high risk for generalized anxiety disorder: a network analysis.

BACKGROUND: Improving the psychotherapies for generalized anxiety disorder (GAD) is dependent on a deeper understanding of the relations between GAD and its associated cognitive factors. In the present study, we investigate how the core feature of GAD (i.e., worry) and its associated cognitive factors, such as meta-worry, intolerance of uncertainty, and attention bias towards threat, relate to each other in men at high risk for GAD. METHODS: We used network analysis to explore the relations among these variables in a cross-sectional sample of 122 men at high risk for generalized anxiety disorder. Specifically, we computed the expected influence and predictability of each variable. RESULTS: In the final network, we found that worry and meta-worry had the highest expected influence and predictability. In contrast, attention bias towards threat showed the lowest expected influence and predictability. The estimates of the expected influence of the nodes were stable (correlation stability coefficient = 0.52). CONCLUSIONS: The present study is the first to investigate the relations among worry, meta-worry, intolerance of uncertainty, and attention bias towards threat in men at high risk for generalized anxiety disorder. These findings indicate that worry and meta-worry may play important roles in the present network. The implications for clinical interventions and future studies are discussed.

The impact of repetitive transcranial magnetic stimulation and fluoxetine on the brain lipidome in a rat model of chronic unpredictable stress.

The antidepressant effect of repetitive transcranial magnetic stimulation (rTMS) has been extensively studied; growing evidence suggests that changes in lipid composition may be involved in the pathogenesis of depression and may be a targeted mechanism for treatment. However, the influence of rTMS on lipid composition and the differences between these effects compared to antidepressants like fluoxetine (Flx) have never been investigated. Using a chronic unpredictable stress (CUS) model in rats, we assessed the antidepressive effects of rTMS and Flx treatments and evaluated changes in lipid composition in the hippocampus and prefrontal cortex (PFC) using a mass spectrometry-based lipidomic approach. Both rTMS and Flx treatments ameliorated depressive-like behaviors induced by CUS. Moreover, changes in lipid composition, especially glycerophospholipids, sphingolipids, and glycerolipids induced by CUS in the hippocampus were more robust than those observed in the PFC. CUS led to decreased levels of 20 carbon-containing fatty acyls and polyunsaturated fatty acyls in the PFC, and decreased levels of acyl carnitines (AcCa) in both the hippocampus and PFC. Notably, rTMS treatment had higher impact than Flx on composition of glycerophospholipids and sphingolipids in the hippocampus that were altered by CUS, while Flx attenuated CUS-induced changes in the PFC to a greater extent than rTMS. However, neither was able to restore fatty acyls and AcCa to baseline levels. Altogether, modulation of the brain lipidome may be involved in the antidepressant action of rTMS and Flx, and the degree to which these treatments induce changes in lipid composition within the hippocampus and PFC might explain their differential antidepressant effects.