Optimizing the individual dosing of paroxetine in major depressive disorder with therapeutic drug monitoring.

INTRODUCTION: Previous studies have examined the correlation between paroxetine concentrations and therapeutic efficacy in patients diagnosed with major depressive disorder (MDD), but findings have been contradictory. AIMS: This study aimed to investigate the relationships among plasma concentrations, severity of symptoms, and adverse drug reactions (ADRs) to optimize individual dosing. METHODS: Eighty-seven MDD patients, after completing treatment with paroxetine, were divided into low-concentration (LC, n = 38), medium-concentration (MC, n = 27), and high-concentration (HC, n = 22) groups, based on cutoff value concentrations with the 50% response rate and the laboratory alert level from the 2017 consensus guidelines for therapeutic drug monitoring in neuropsychopharmacology. The severity of depression and anxiety was evaluated using a 17-item Hamilton Depression Scale (HAMD-17) and Hamilton Anxiety Scale (HAMA), respectively. Dosage, plasma concentrations, scale scores, and ADRs were recorded across the three groups at different treatment stages to define the therapeutic reference range. RESULTS: The 4-week plasma concentration of paroxetine (65.00 ng/mL) could predict the clinical response in MDD patients at 8 weeks. Symptom relief in patients with 4-week paroxetine concentrations ranging from 65.00 to 120.00 ng/mL at 8 weeks was greater than in those with concentrations below 65.00 ng/mL, with no significant difference observed above this range. In addition, more cases of liver injury and weight gain were observed in patients with high paroxetine concentrations. CONCLUSION: Our results support that early paroxetine concentration may predict clinical efficacy and the incidence of ADRs, thus improving individual dosing regimens for MDD patients.

Intranasal Delivery of circATF7IP siRNA via Lipid Nanoparticles Alleviates LPS-induced Depressive-Like Behaviors.

Major depressive disorder (MDD) is a prevalent mental disorder that significantly impacts social and psychological function, but no effective medication is currently available. Circular RNAs (circRNAs) have been reported to participate in the pathogenesis of MDD which are envisioned as promising therapeutic targets. However, nonviral-based delivery strategies targeting circRNA against MDD are not thoroughly investigated. Here, it is identified that circATF7IP is significantly upregulated in plasma samples and positively correlated with 24-Hamilton Depression Scale (HAMD-24) scores of MDD patients. Synergistic amine lipid nanoparticles (SALNPs) are designed to deliver siRNA targeting circATF7IP (si-circATF7IP) into the hippocampus brain region by intranasal administration. Intranasal delivery of SALNP-si-circATF7IP successfully alleviated the depressive-like behaviors in the LPS-induced mouse depression model via decreasing CD11b+CD45dim microglia population and pro-inflammatory cytokine productions (TNF-α and IL-6). These results indicate that the level of circATF7IP positively correlates with MDD pathogenesis, and SALNP delivery of si-circATF7IP via intranasal administration is an effective strategy to ameliorate LPS-induced depressive-like behaviors.

Multi-Scale Spatial-Temporal Attention Networks for Functional Connectome Classification.

Many neuropsychiatric disorders are considered to be associated with abnormalities in the functional connectivity networks of the brain. The research on the classification of functional connectivity can therefore provide new perspectives for understanding the pathology of disorders and contribute to early diagnosis and treatment. Functional connectivity exhibits a nature of dynamically changing over time, however, the majority of existing methods are unable to collectively reveal the spatial topology and time-varying characteristics. Furthermore, despite the efforts of limited spatial-temporal studies to capture rich information across different spatial scales, they have not delved into the temporal characteristics among different scales. To address above issues, we propose a novel Multi-Scale Spatial-Temporal Attention Networks (MSSTAN) to exploit the multi-scale spatial-temporal information provided by functional connectome for classification. To fully extract spatial features of brain regions, we propose a Topology Enhanced Graph Transformer module to guide the attention calculations in the learning of spatial features by incorporating topology priors. A Multi-Scale Pooling Strategy is introduced to obtain representations of brain connectome at various scales. Considering the temporal dynamic characteristics between dynamic functional connectome, we employ Locality Sensitive Hashing attention to further capture long-term dependencies in time dynamics across multiple scales and reduce the computational complexity of the original attention mechanism. Experiments on three brain fMRI datasets of MDD and ASD demonstrate the superiority of our proposed approach. In addition, benefiting from the attention mechanism in Transformer, our results are interpretable, which can contribute to the discovery of biomarkers. The code is available at https://github.com/LIST-KONG/MSSTAN.

Abnormal Insula Network Characteristics in Panic Disorder.

BACKGROUND: Panic disorder (PD) is a common disabling condition characterized by recurrent panic attacks. Emotional and behavioral impairments are associated with functional connectivity (FC) and network abnormalities. We used the whole brain FC, modular networks, and graph-theory analysis to investigate extensive network profiles in PD. METHOD: The functional MRI data from 82 PD and 97 controls were included. Intrinsic FC between each pair of 160 regions, 6 intra-networks, and 15 inter-networks were analyzed. The topological properties were explored. RESULTS: PD patients showed altered FCs within the right insula, between frontal cortex-posterior cingulate cortex (PCC), frontal cortex-cerebellum, and PCC-occipital cortex (corrected P values < 0.001). Lower connections within the Sensorimotor Network (SMN) and SMN-Occipital Network (OCN) were detected (P values < 0.05). Various decreased global and local network features were found in PD (P values < 0.05). In addition, significant correlations were found between PD symptoms and nodal efficiency (Ne) in the insula (r = -0.273, P = 0.016), and the FC of the intra-insula (r = -0.226, P = 0.041). CONCLUSIONS: PD patients present with abnormal functional brain networks, especially the decreased FC and Ne within insula, suggesting that dysfunction of information integration plays an important role in PD.

Current State of Consultation-Liaison Psychiatry in China and Future Directions.

This article provides an overview of the history and current status of consultation-liaison psychiatry (CLP) in China and its development within the Chinese Society of Psychosomatic Medicine. Over the past decade, various CLP practice models have been developed to meet the diverse needs of different regions in China. Notably, the Chinese Multidisciplinary Integrated Centers of Psychosomatic Medicine have been established as regional hubs throughout the country. Additionally, this article delves into the role of Chinese traditional medicine in the practice of CLP in China. Finally, several projects involving CLP-based multidisciplinary collaboration are highlighted. We hope this article offers a bird's-eye view of CLP in China and opens a window for future collaboration with CLP initiatives in other countries.

Network pharmacology and experimental evidence: ERK/CREB/BDNF signaling pathway is involved in the antidepressive roles of Kaiyu Zhishen decoction.

ETHNOPHARMACOLOGICAL RELEVANCE: Major Depressive Disorder (MDD) emerges as a complex psychosomatic condition, notable for its considerable suicidality and mortality rates. Increasing evidence suggests the efficacy of Chinese herbal medicine in mitigating depression symptoms and offsetting the adverse effects associated with conventional Western therapeutics. Notably, clinical trials have revealed the adjunctive antidepressant potential of Kaiyu Zhishen Decoction (KZD) alongside Western medication. However, the standalone antidepressant efficacy of KZD and its underlying mechanisms merit in-depth investigation. AIM OF THE STUDY: This research aims to elucidate the impact of KZD on MDD and delineate its mechanistic pathways through integrated network pharmacological assessments and empirical in vitro and in vivo analyses. MATERIALS AND METHODS: To ascertain the optimal antidepressant dosage and mechanism of KZD, a Chronic Unpredictable Mild Stress (CUMS)-induced depression model in mice was established to evaluate depressive behaviors. High-Performance Liquid Chromatography (HPLC) and network pharmacological approaches were employed to predict KZD's antidepressant mechanisms. Subsequently, hippocampal samples were subjected to 4D-DIA proteomic sequencing and validated through Western blot, immunofluorescence, Nissl staining, and pathway antagonist applications. Additionally, cortisol-stimulated PC12 cells were utilized to simulate neuronal damage, analyzing protein and mRNA levels of MAPK-related signals and cell proliferation markers. RESULTS: The integration of network pharmacology and HPLC identified kaempferol and quercetin as KZD's principal active compounds for MDD treatment. Proteomic and network pharmacological KEGG pathway analyses indicated the MAPK signaling pathway as a critical regulatory mechanism for KZD's therapeutic effect on MDD. KZD was observed to mitigate CUMS-induced upregulation of p-ERK/ERK, CREB, and BDNF protein expressions in hippocampal cells by attenuating oxidative stress, thereby ameliorating neuronal damage and exerting antidepressant effects. The administration of PD98059 counteracted KZD's improvements in depression-like behaviors and downregulated p-ERK/ERK and BDNF protein expressions in the hippocampus. CONCLUSIONS: This investigation corroborates KZD's pivotal, dose-dependent role in antidepressant activity. Both in vivo and in vitro experiments demonstrate KZD's capacity to modulate the ERK-CREB-BDNF signaling pathway by diminishing ROS expression induced by oxidative stress, enhancing neuronal repair, and thus, manifesting antidepressant properties. Accordingly, KZD represents a promising herbal candidate for further antidepressant research.

Distinguishing bipolar depression, bipolar mania, and major depressive disorder by gut microbial characteristics.

BACKGROUND: Gut microbial disturbance has been widely confirmed in mood disorders. However, little is known about whether gut microbial characteristics can distinguish major depressive disorder (MDD), bipolar depression (BP-D), and bipolar mania (BP-M). METHODS: This was a prospective case-control study. The composition of gut microbiota was profiled using 16S ribosomal RNA (rRNA) gene sequencing of fecal samples and compared between healthy controls (HC; n = 46), MDD (n = 51), BP-D (n = 44), and patients with BP-M (n = 45). RESULTS: Gut microbial compositions were remarkably changed in the patients with MDD, BP-D, and BP-M. Compared to HC, distinct gut microbiome signatures were found in MDD, BP-D, and BP-M, and some gut microbial changes were overlapping between the three mood disorders. Furthermore, we identified a signature of 7 operational taxonomic units (OUT; Prevotellaceae-related OUT22, Prevotellaceae-related OUT31, Prevotellaceae-related OTU770, Ruminococcaceae-related OUT70, Bacteroidaceae-related OTU1536, Propionibacteriaceae-related OTU97, Acidaminococcaceae-related OTU34) that can distinguish patients with MDD from those with BP-D, BP-M, or HC, with area under the curve (AUC) values ranging from 0.910 to 0.996. CONCLUSION: Our results provide the clinical rationale for the discriminative diagnosis of MDD, BP-D, and BP-M by characteristic gut microbial features.

The Impact of Recent Life Events, Internalizing Symptoms, and Emotion Regulation on the Severity of Non-Suicidal Self-Injury in Adolescents: A Mediation Analysis.

Background: Previous studies have demonstrated a strong association between recent stressful life events and non-suicidal self-injury (NSSI) among adolescents. Internalizing symptoms and difficulty in emotion regulation (DER) may mediate this relationship. This study aimed to investigate the relationship between recent stressful life events and NSSI severity in adolescents and the potential moderating role of internalizing symptoms and DER. Methods: A total of 224 adolescent inpatients (78.6% female) participated in the study, with an age range of 12-18 years old. Data on recent stressful life events, internalizing symptoms, DER, and NSSI behaviors were collected using a clinician-rated questionnaire. A structural equation model was used to test the hypothesized model. Results: The rate of NSSI reporting among adolescents in the past 12 months was 65.18%. Recent stressful life events were found to be directly associated with NSSI severity (ß = 0.128, P = 0.023). A chain-mediating effect between recent stressful life events and NSSI was also confirmed (ß = 0.034, P = 0.023), with DER and internalizing symptoms playing a chain-mediating role and DER having a significantly indirect association with NSSI through internalizing symptoms. Conclusion: Recent stressful life events appear to play a role in the etiology of NSSI, particularly punishment and interpersonal relationship events that warrant special attention. DER and internalizing symptoms play a chain-mediating role in the relationship between life events and NSSI. Reducing recent stressful life events, screening for internalizing symptoms, and improving emotion regulation may decrease NSSI behavior among adolescents.

Suppression of wavelength-dependent polarization fading using hybrid-polarization scheme in OFDR.

What we believe to be a new hybrid-polarization diversity scheme which can eliminate the polarization state variation caused by wavelength tuning of laser in optical frequency domain reflectometry is proposed in the paper. In the scheme, a 45° polarizer is used to maintain the polarization of signals. It decreases the polarization angle fluctuation to 2.81° and realizes a -145 dB test sensitivity with a 32 dB Rayleigh scattering signal-to-noise ratio in a 10 m fiber single test. The polarization fading suppression is achieved for tests with a large wavelength tuning range from 1480 nm to 1640 nm. Meanwhile, a 6 µm spatial resolution is also achieved. The proposed scheme can be applied to the structure measurement of high-precision optical fiber devices with high spatial resolution and sensitivity.

Childhood abuse influences clinical features of major depressive disorder by modulating the functional network of the right amygdala subregions.

Childhood trauma and the amygdala play essential roles in major depressive disorder (MDD) mechanisms. However, the neurobiological mechanism among them remains unclear. Therefore, we explored the relationship among the amygdala subregion's abnormal functional connectivity (FC), clinical features, and childhood trauma in MDD. We obtained resting-state functional magnetic resonance imaging (fMRI) in 115 MDD patients and 91 well-matched healthy controls (HC). Amygdala subregions were defined according to the Human Brainnetome Atlas. The case vs. control difference in FCs was extracted. After controlling for age, sex, and education years, the mediations between the detected abnormal FCs and clinical features were analyzed, including the onset age of MDD and the Hamilton Depression Scale-24 (HAMD-24) reductive rate. Compared with HC subjects, we found, only the right amygdala subregions, namely the right medial amygdala (mAmyg.R) and the right lateral amygdala (lAmyg.R), showed a significant decrease in whole-brain FCs in MDD patients. Only childhood abuse experiences were significantly associated with amygdala subregion connectivity and clinical features in MDD patients. Additionally, The FCs between the mAmyg.R and extensive frontal, temporal, and subcortical regions mediated between the early life abuses and disease onset or treatment outcome. The findings indicate that the abnormal connectivity of the right amygdala subregions is involved in MDD's pathogenesis and clinical characteristics.

Psychological stress-induced microbial metabolite indole-3-acetate disrupts intestinal cell lineage commitment.

The brain and gut are intricately connected and respond to various stimuli. Stress-induced brain-gut communication is implicated in the pathogenesis and relapse of gut disorders. The mechanism that relays psychological stress to the intestinal epithelium, resulting in maladaptation, remains poorly understood. Here, we describe a stress-responsive brain-to-gut metabolic axis that impairs intestinal stem cell (ISC) lineage commitment. Psychological stress-triggered sympathetic output enriches gut commensal Lactobacillus murinus, increasing the production of indole-3-acetate (IAA), which contributes to a transferrable loss of intestinal secretory cells. Bacterial IAA disrupts ISC mitochondrial bioenergetics and thereby prevents secretory lineage commitment in a cell-intrinsic manner. Oral α-ketoglutarate supplementation bolsters ISC differentiation and confers resilience to stress-triggered intestinal epithelial injury. We confirm that fecal IAA is higher in patients with mental distress and is correlated with gut dysfunction. These findings uncover a microbe-mediated brain-gut pathway that could be therapeutically targeted for stress-driven gut-brain comorbidities.

A Gpr35-tuned gut microbe-brain metabolic axis regulates depressive-like behavior.

Gene-environment interactions shape behavior and susceptibility to depression. However, little is known about the signaling pathways integrating genetic and environmental inputs to impact neurobehavioral outcomes. We report that gut G-protein-coupled receptor, Gpr35, engages a microbe-to-brain metabolic pathway to modulate neuronal plasticity and depressive behavior in mice. Psychological stress decreases intestinal epithelial Gpr35, genetic deletion of which induces depressive-like behavior in a microbiome-dependent manner. Gpr35-/- mice and individuals with depression have increased Parabacteroides distasonis, and its colonization to wild-type mice induces depression. Gpr35-/- and Parabacteroides distasonis-colonized mice show reduced indole-3-carboxaldehyde (IAld) and increased indole-3-lactate (ILA), which are produced from opposing branches along the bacterial catabolic pathway of tryptophan. IAld and ILA counteractively modulate neuroplasticity in the nucleus accumbens, a brain region linked to depression. IAld supplementation produces anti-depressant effects in mice with stress or gut epithelial Gpr35 deficiency. Together, these findings elucidate a gut microbe-brain signaling mechanism that underlies susceptibility to depression.

Prediction of Early Antidepressant Efficacy in Patients with Major Depressive Disorder Based on Multidimensional Features of rs-fMRI and P11 Gene DNA Methylation: Prédiction de l'efficacité précoce d'un antidépresseur chez des patients souffrant du trouble dépressif majeur d'après les caractéristiques multidimensionnelles de la méthylation de l'ADN du gène P11 et de la IRMf-rs.

OBJECTIVE: This study established a machine learning model based on the multidimensional data of resting-state functional activity of the brain and P11 gene DNA methylation to predict the early efficacy of antidepressant treatment in patients with major depressive disorder (MDD). METHODS: A total of 98 Han Chinese MDD were analysed in this study. Patients were divided into 51 responders and 47 nonresponders according to whether the Hamilton Depression Rating Scale-17 items (HAMD-17) reduction rate was ≥50% after 2 weeks of antidepressant treatment. At baseline, the Illumina HiSeq Platform was used to detect the methylation of 74 CpG sites of the P11 gene in peripheral blood samples. Resting-state functional magnetic resonance imaging (rs-fMRI) scan detected the amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), and functional connectivity (FC) in 116 brain regions. The least absolute shrinkage and selection operator analysis method was used to perform feature reduction and feature selection. Four typical machine learning methods were used to establish support vector machine (SVM), random forest (RF), Naïve Bayes (NB), and logistic regression (LR) prediction models based on different combinations of functional activity of the brain, P11 gene DNA methylation and clinical/demographic features after screening. RESULTS: The SVM model based on ALFF, ReHo, FC, P11 methylation, and clinical/demographic features showed the best performance, with 95.92% predictive accuracy and 0.9967 area under the receiver operating characteristic curve, which was better than RF, NB, and LR models. CONCLUSION: The multidimensional data features combining rs-fMRI, DNA methylation, and clinical/demographic features can predict the early antidepressant efficacy in MDD.

Microstructural abnormalities of white matter in the cingulum bundle of adolescents with major depression and non-suicidal self-injury.

BACKGROUND: Non-suicidal self-injury (NSSI) is prevalent in major depressive disorder (MDD) during adolescence, but the underlying neural mechanisms are unclear. This study aimed to investigate microstructural abnormalities in the cingulum bundle associated with NSSI and its clinical characteristics. METHODS: 130 individuals completed the study, including 35 healthy controls, 47 MDD patients with NSSI, and 48 MDD patients without NSSI. We used tract-based spatial statistics (TBSS) with a region of interest (ROI) analysis to compare the fractional anisotropy (FA) of the cingulum bundle across the three groups. receiver-operating characteristics (ROC) analysis was employed to evaluate the ability of the difficulties with emotion regulation (DERS) score and mean FA of the cingulum to differentiate between the groups. RESULTS: MDD patients with NSSI showed reduced cingulum integrity in the left dorsal cingulum compared to MDD patients without NSSI and healthy controls. The severity of NSSI was negatively associated with cingulum integrity (r = -0.344, p = 0.005). Combining cingulum integrity and DERS scores allowed for successful differentiation between MDD patients with and without NSSI, achieving a sensitivity of 70% and specificity of 83%. CONCLUSIONS: Our study highlights the role of the cingulum bundle in the development of NSSI in adolescents with MDD. The findings support a frontolimbic theory of emotion regulation and suggest that cingulum integrity and DERS scores may serve as potential early diagnostic tools for identifying MDD patients with NSSI.

Escitalopram-induced QTc prolongation and its relationship with KCNQ1, KCNE1, and KCNH2 gene polymorphisms.

BACKGROUND: Escitalopram can cause prolongation of the QT interval on the electrocardiogram (ECG). However, only some patients get pathological QTc prolongation in clinic. We investigated the influence of KCNQ1, KCNE1, and KCNH2 gene polymorphisms along with clinical factors on escitalopram-induced QTc prolongation. METHODS: A total of 713 patients prescribed escitalopram were identified and had at least one ECG recording in this retrospective study. 472 patients with two or more ECG data were divided into QTc prolongation (n = 119) and non-prolongation (n = 353) groups depending on the threshold change in QTc of 30 ms above baseline value (∆QTc ≥ 30 ms). 45 patients in the QTc prolongation group and 90 patients in the QTc non-prolongation group were genotyped for 43 single nucleotide polymorphisms (SNPs) of KCNQ1, KCNE1, and KCNH2 genes. RESULTS: Patients with QTc prolongation (∆QTc ≥ 30 ms) got higher escitalopram dose (10.3 mg) than patients without QTc prolongation (9.4 mg), although no significant relationship was found between QTc interval and escitalopram dose in the linear mixed model. Patients who were older/coronary disease/hypertension or carried with KCNE1 rs1805127 C allele, KCNE1 rs4817668 C allele, KCNH2 rs3807372 AG/GG genotype were significantly at risk for QTc prolongation (∆QTc ≥ 30 ms). Concomitant antipsychotic treatment was associated with a longer QTc interval. LIMITATIONS: A relatively small sample size and lack of the blood concentration of escitalopram restricted the accurate relationship between escitalopram dose and QTc interval. CONCLUSION: Our study revealed that KCNQ1, KCNE1, and KCNH2 gene polymorphisms along with clinical factors provide a complementary effect in escitalopram-induced QTc prolongation.

Identification and discovery of imaging genetic patterns using fusion self-expressive network in major depressive disorder.

Introduction: Major depressive disorder (MDD) is a prevalent mental illness, with severe symptoms that can significantly impair daily routines, social interactions, and professional pursuits. Recently, imaging genetics has received considerable attention for understanding the pathogenesis of human brain disorders. However, identifying and discovering the imaging genetic patterns between genetic variations, such as single nucleotide polymorphisms (SNPs), and brain imaging data still present an arduous challenge. Most of the existing MDD research focuses on single-modality brain imaging data and neglects the complex structure of brain imaging data. Methods: In this study, we present a novel association analysis model based on a self-expressive network to identify and discover imaging genetics patterns between SNPs and multi-modality imaging data. Specifically, we first build the multi-modality phenotype network, which comprises voxel node features and connectivity edge features from structural magnetic resonance imaging (sMRI) and resting-state functional magnetic resonance imaging (rs-fMRI), respectively. Then, we apply intra-class similarity information to construct self-expressive networks of multi-modality phenotype features via sparse representation. Subsequently, we design a fusion method guided by diagnosis information, which iteratively fuses the self-expressive networks of multi-modality phenotype features into a single new network. Finally, we propose an association analysis between MDD risk SNPs and the multi-modality phenotype network based on a fusion self-expressive network. Results: Experimental results show that our method not only enhances the association between MDD risk SNP rs1799913 and the multi-modality phenotype network but also identifies some consistent and stable regions of interest (ROIs) multi-modality biological markers to guide the interpretation of MDD pathogenesis. Moreover, 15 new potential risk SNPs highly associated with MDD are discovered, which can further help interpret the MDD genetic mechanism. Discussion: In this study, we discussed the discriminant and convergence performance of the fusion self-expressive network, parameters, and atlas selection.

The Interaction of LAMA2 and Duration of Illness Affects the Thickness of the Right Transverse Temporal Gyrus in Major Depressive Disorder.

Background: Depression is a heritable brain disorder. Laminin genes were recently identified to affect the brain's overall thickness through neurogenesis, differentiation, and migration in depression. This study aims to explore the effects of the LAMA2's single nucleotide polymorphisms (SNP), a subunit gene of laminin, on the detected brain regions of patients with major depressive disorder (MDD). Methods: The study included 89 patients with MDD and 60 healthy controls with T1-weighted structural magnetic resonance imaging and blood samples for genotyping. The interactions between LAMA2 gene SNPs and diagnosis as well as duration of illness (DOI) were explored on brain measures controlled for age, gender, and site. Results: The right transverse temporal gyrus and right parahippocampal gyrus showed reduced thickness in MDD. Almost all seven LAMA2 SNPs showed significant interactions with diagnosis on both gyrus (corrected p < 0.05 or trending). In MDD, rs6569604, rs2229848, rs2229849, rs2229850, and rs2784895 interacted with DOI on the right transverse temporal gyrus (corrected p < 0.05), but not the right parahippocampal gyrus. Conclusion: The thickness of the right transverse temporal gyrus in patients with MDD may be affected by LAMA2 gene and DOI.

Network analysis of psychosomatic symptoms in pharmacists during the pandemic.

We explored the networks and discriminant abilities of the current Psychosomatic Symptoms Scale (PSSS) in pharmacists for future abbreviation. Ten thousand seven hundred twenty-one pharmacists participated in this study through an online investigation. We used network analysis to reveal the central and bridge symptoms between the subscales (psychological and somatic symptoms) of the PSSS. Then, we utilized item response theory (IRT) to identify discriminant abilities of the current 26-item of PSSS. Over twenty percent of the pharmacists were troubled with significant psychosomatic issues during the pandemic. Risk factors included age, lack of support, and impaired general health conditions. The network analysis revealed that "Irritability" was central to the psychological subscale and "Fatigue" was central to the somatic subscale. "Irritability-Fatigue," "Fatigue-Obsession," and "Self-injury idea-Perineum discomfort" was bridging between the somatic and psychological subscales. IRT found that "Anhedonia," "Depression," "Tightness," "Palpitations," and "Difficulty breathing" were highly discriminated. A future version of PSSS could be abbreviated according to the highlighted items, and they should also be emphasized in future psychosomatic research and targets for intervention. (PsycInfo Database Record (c) 2023 APA, all rights reserved).