Fertility-sparing surgery in children and adolescents with borderline ovarian tumors: a retrospective study.

OBJECTIVE: To describe the characteristics of children and adolescents with borderline ovarian tumors (BOTs) and evaluate the efficacy and safety of fertility-sparing surgery (FSS) in these patients. METHODS: Patients with BOTs younger than 20 years who underwent FSS were included in this study. RESULTS: A total of 34 patients were included, with a median patient age of 17 (range, 3-19) years; 97.1% (33/34) of cases occurred after menarche. Of the patients, 82.4% had mucinous borderline tumors (MBOTs), 14.7% had serous borderline tumors (SBOTs), and 2.9% had seromucinous borderline tumor (SMBOT). The median tumor size was 20.4 (range, 8-40)cm. All patients were at International Federation of Gynecology and Obstetrics stage I and all underwent FSS: cystectomy (unilateral ovarian cystectomy, UC, 14/34, 41.2% and bilateral ovarian cystectomy, BC, 1/34, 2.9%), unilateral salpingo-oophorectomy (USO; 18/34; 52.9%), or USO + contralateral ovarian cystectomy (1/34; 2.9%). The median follow-up time was 65 (range, 10-148) months. Recurrence was experienced by 10 of the 34 patients (29.4%). One patient with SBOT experienced progression to low-grade serous carcinoma after the third relapse. Two patients had a total of four pregnancies, resulting in three live births. The recurrence rate of UC was significantly higher in MBOTs than in USO (p = 0.005). The 5-year disease-free survival rate was 67.1%, and the 5-year overall survival rate was 100%. CONCLUSIONS: Fertility-sparing surgery is feasible and safe for children and adolescents with BOTs. For patients with MBOTs, USO is recommended to lower the risk of recurrence.

Altered N-linked glycosylation in depression: A pre-clinical study.

BACKGROUND: Neuroimmune plays an important role in major depressive disorders (MDD). N-linked protein glycosylation (NLG) might contribute to depression by regulating the neuroinflammatory response. As microglia is the main executor of neuroimmune function in the central neural system (CNS), targeting the process of N-linked protein glycosylation of microglia in the mice used for studying depression might potentially offer new avenues for the strategy for MDD. METHODS: The chronic unpredictable mild stress (CUMS) mouse model was established for the whole brain microglia isolating. Then, RNA samples of microglia were extracted for transcriptome sequencing and mRNA analysis. Immunofluorescence (IF) was used to identify the expression level of NLG-related enzyme, B4galt1, in microglia. RESULTS: The data showed that NLG was positively related to depression. Moreover, the NLG-related gene, B4galt1 increased expression in the microglia of CUMS mice. Then, the inhibition of NLG reversed the depressive behavior in CUMS mice. The expression level of B4galt1 in CUMS mice was upregulating following the NLG-inhibitor treatment. Similar results haven't been observed in neurons. Information obtained from these experiments showed increasing expression of B4galt1 in microglia following depressive-like behaviors. CONCLUSIONS: These findings indicate that NLG in microglia is associated with MDD, and suggest that therapeutically targeting NLG might be an effective strategy for depression. LIMITATIONS: How to modulate the B4galt1 or NLG pathways in microglia efficiently and economically request new technologies.

Emden: A novel method integrating graph and transformer representations for predicting the effect of mutations on clinical drug response.

Precision medicine based on personalized genomics provides promising strategies to enhance the efficacy of molecular-targeted therapies. However, the clinical effectiveness of drugs has been severely limited due to genetic variations that lead to drug resistance. Predicting the impact of missense mutations on clinical drug response is an essential way to reduce the cost of clinical trials and understand genetic diseases. Here, we present Emden, a novel method integrating graph and transformer representations that predicts the effect of missense mutations on drug response through binary classification with interpretability. Emden utilized protein sequences-based features and drug structures as inputs for rapid prediction, employing competitive representation learning and demonstrating strong generalization capabilities and robustness. Our study showed promising potential for clinical drug guidance and deep insight into computer-assisted precision medicine. Emden is freely available as a web server at https://www.psymukb.net/Emden.

Predictors of mortality in patients with isolated gastrointestinal perforation.

Gastrointestinal (GI) perforation is common in the emergency department and has a high mortality rate. The present study aimed to identify risk factors for mortality in patients with GI perforation. The objective was to assess and prognosticate the surgical outcomes of patients, aiming to ascertain the efficacy of the procedure for individual patients. A retrospective cohort study of patients with GI perforation who underwent surgery in a public tertiary hospital in China from January 2012 to June 2022 was performed. Demographics, clinical characteristics, laboratory and imaging results, and outcomes were collected from electronic medical records. The primary outcome measure was in-hospital mortality, and patients were divided into survivor and non-survivor groups based on this measure. Univariate and multivariable logistic regression analyses were performed to obtain independent factors associated with mortality. A total of 529 patients with GI perforation were eligible for inclusion. The in-hospital mortality rate after emergency surgery was 10.59%. The median age of the patients was 60 years (interquartile range, 44-72 years). Multivariable logistic regression analysis indicated that age, shock on admission, elevated serum creatinine (sCr) and white blood cell (WBC) count <3.5x109 or >20x109 cells/l were predictors of in-hospital mortality. In conclusion, advanced age, shock on admission, elevated sCr levels and significantly abnormal WBC count are associated with higher in-hospital mortality following emergency laparotomy.

Angle-dependent phononic dynamics for data-driven source localization.

The source angle localization problem is studied based on scattering of elastic waves in two dimensions by a phononic array and the exceptional points of its band structure. Exceptional points are complex singularities of a parameterized eigen-spectrum, where two modes coalesce with identical mode shapes. These special points mark the qualitative transitions in the system behavior and have been proposed for sensing applications. The equi-frequency band structures are analyzed with focus on the angle-dependent modal behaviors. At the exceptional points and critical angles, the eigen-modes switch their energy characteristics and symmetry, leading to enhanced sensitivity as the scattering response of the medium is inherently angle-dependent. An artificial neural network is trained with randomly weighted and superposed eigen-modes to achieve deep learning of the angle-dependent dynamics. The trained algorithm can accurately classify the incident angle of an unknown scattering signal, with minimal sidelobe levels and suppressed main lobewidth. The neural network approach shows superior localization performance compared with standard delay-and-sum technique. The proposed application of the phononic array highlights the physical relevance of band topology and eigen-modes to a technological application, adds extra strength to the existing localization methods, and can be easily enhanced with the fast-growing data-driven techniques.

Inferring the Effects of Protein Variants on Protein-Protein Interactions with Interpretable Transformer Representations.

Identifying pathogenetic variants and inferring their impact on protein-protein interactions sheds light on their functional consequences on diseases. Limited by the availability of experimental data on the consequences of protein interaction, most existing methods focus on building models to predict changes in protein binding affinity. Here, we introduced MIPPI, an end-to-end, interpretable transformer-based deep learning model that learns features directly from sequences by leveraging the interaction data from IMEx. MIPPI was specifically trained to determine the types of variant impact (increasing, decreasing, disrupting, and no effect) on protein-protein interactions. We demonstrate the accuracy of MIPPI and provide interpretation through the analysis of learned attention weights, which exhibit correlations with the amino acids interacting with the variant. Moreover, we showed the practicality of MIPPI in prioritizing de novo mutations associated with complex neurodevelopmental disorders and the potential to determine the pathogenic and driving mutations. Finally, we experimentally validated the functional impact of several variants identified in patients with such disorders. Overall, MIPPI emerges as a versatile, robust, and interpretable model, capable of effectively predicting mutation impacts on protein-protein interactions and facilitating the discovery of clinically actionable variants.

Pulmonary resection of residual lesions of pulmonary metastasis from gestational trophoblastic neoplasia.

OBJECTIVE: To evaluate the prognosis and recurrence in patients with residual lesions of pulmonary metastasis from gestational trophoblastic neoplasia after initial treatment, and to explore the clinical significance of pulmonary resection. METHODS: A retrospective analysis was performed on 606 patients with residual lesions from pulmonary metastasis after receiving standardized chemotherapy as initial treatment in Peking Union Medical College Hospital from January 2002 to December 2018. Patients were divided into surgery (51 patients) and non-surgery (555 patients) groups. The prognosis of these patients was compared. Risk factors affecting recurrence were analyzed to explore the effect of pulmonary resection. RESULTS: Among low risk patients, complete remission rate was 100% and recurrence rate was <1% in both groups. Among high risk patients, complete remission and recurrence rates were 93.5% and 10.3% in the surgery group and 94.7% and 14.3% in the non-surgery group, respectively. There was no significant difference in prognostic features between the two groups (all p>0.05). No significant difference was found in recurrence rates based on recurrence risk factors (≥3.2 cm residual lung lesions, prognosis score ≥9.0, and drug resistance) between the two groups (all p>0.05). CONCLUSION: After standardized chemotherapy, pulmonary resection was not necessary for initially treated stage III gestational trophoblastic neoplasia patients whose blood ß human chorionic gonadotropin levels normalized and residual lung lesions remained stable. These patients should be closely monitored during follow-up, regardless of the size of the residual lung lesions or high/low risk score, especially within a year after complete remission.

Untargeted metabolomics analysis in drug-naïve patients with severe obsessive-compulsive disorder.

Introduction: Obsessive-compulsive disorder (OCD), characterized by the presence of obsessions and/or compulsions, is often difficult to diagnose and treat in routine clinical practice. The candidate circulating biomarkers and primary metabolic pathway alteration of plasma in OCD remain poorly understood. Methods: We recruited 32 drug-naïve patients with severe OCD and 32 compared healthy controls and applied the untargeted metabolomics approach by ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) to assess their circulating metabolic profiles. Both univariate and multivariate analyses were then utilized to filtrate differential metabolites between patients and healthy controls, and weighted Correlation Network Analysis (WGCNA) was utilized to screen out hub metabolites. Results: A total of 929 metabolites were identified, including 34 differential metabolites and 51 hub metabolites, with an overlap of 13 metabolites. Notably, the following enrichment analyses underlined the importance of unsaturated fatty acids and tryptophan metabolism alterations in OCD. Metabolites of these pathways in plasma appeared to be promising biomarkers, such as Docosapentaenoic acid and 5-Hydroxytryptophan, which may be biomarkers for OCD identification and prediction of sertraline treatment outcome, respectively. Conclusion: Our findings revealed alterations in the circulating metabolome and the potential utility of plasma metabolites as promising biomarkers in OCD.

Analysis of appendicitis management during COVID-19 pandemic: A study of Chinese adult cohorts.

Background: Healthcare seeking behavior has been widely impacted due to the restricted movements of individuals during the Coronavirus disease-19 (COVID-19) pandemic. This study aims to perform risk stratification in patients requiring timely intervention during the recovery periods. Methods: Operation notes of acute appendicitis (AA) patients within a hospital were analyzed during three six-month periods (23 January-23 July in 2019, 2020, and 2021, respectively). Patient data were collected retrospectively including demographics, pre-emergency status, perioperative information, postoperative outcomes, and follow-up results. Results: 321 patients were included in this study, with 111, 86, and 124 patients in 2019, 2020, and 2021 groups, respectively. The median age of patients decreased by 4 years in 2020 as compared to that in 2019. The proportion of pre-hospitalization symptoms duration of more than 48 h in the 2020 group was higher (36.05% in 2020 vs. 22.52% in 2019). Length of hospital stay (LOS) in 2020 was shorter than it was during the same period in 2019 (4.77 vs. 5.64) and LOS in 2021 was shorter than in 2019 (4.13 vs. 5.64). Compared to the lockdown period, the proportion of patients with recurrent AA was higher in the post-lockdown period (15.1% vs. 27.4%). The median age was 34 years (vaccinated) vs. 37 years (unvaccinated). Logistic regression suggests that elevated C-reactive protein (CRP) (OR = 1.018, CI = 1.010-1.028), white cell count (WBC) (OR = 1.207, CI = 1.079-1.350), female (OR = 2.958, CI = 1.286-6.802), recurrent (OR = 3.865, CI = 1.149-12.997), and fecalith (OR = 2.308, CI = 1.007-5.289) were associated with complicated appendicitis (CA). Conclusion: The lockdown measures during the COVID-19 epidemic are shown to be correlated with a reduction in the proportion of AA patients who underwent surgery, particularly in older adults. Risk factors for CA include elevated CRP, WBC, female, recurrent, and fecalith.

Management and Predictors of Treatment Failure in Patients with Chemo-Resistant/Relapsed Gestational Trophoblastic Neoplasia with Lung Metastasis.

The aim of the study was to assess the effectiveness of a combined treatment modality of salvage chemotherapy and pulmonary resection in chemo-resistant/relapsed gestational trophoblastic neoplasia (GTN) with lung metastasis and identify predictors of treatment failure. Data of patients with chemo-resistant/relapsed GTN with lung metastasis who received salvage chemotherapy combined with pulmonary resection were retrospectively analyzed. Among 134 included patients, the number of preoperative chemotherapy regimens ranged from 2−8 (median, 3), and courses ranged from 4−37 (median, 14). Pulmonary lobectomies, segmentectomies, wedge resections, and lobectomies plus wedge resections were performed in 84, 5, 35, and 10 patients, respectively. After completion of treatment, 130 (97.0%) patients achieved complete remission. In the entire cohort, the 5-year overall survival (OS) rate was 87.6%. OS rates were similar between stage III and stage IV disease cohorts (89.4% vs. 75.0%, p = 0.137). Preoperative ß-human chorionic gonadotropin (ß-hCG) levels > 10 IU/L (p = 0.027) and number of preoperative chemotherapy regimens > 3 (p = 0.018) were predictors of treatment failure. The combined treatment modality of salvage chemotherapy and pulmonary resection is effective in patients with chemo-resistant/relapsed GTN with lung metastasis, improving their prognoses. Patients with preoperative serum ß-hCG >10 IU/L and those with >3 chemotherapy regimens preoperatively may not benefit from this multidisciplinary treatment.

A Comprehensive Study of De Novo Mutations on the Protein-Protein Interaction Interfaces Provides New Insights into Developmental Delay.

Mutations, especially those at the protein-protein interaction (PPI) interface, have been associated with various diseases. Meanwhile, though de novo mutations (DNMs) have been proven important in neuropsychiatric disorders, such as developmental delay (DD), the relationship between PPI interface DNMs and DD has not been well studied. Here we curated developmental delay DNM datasets from the PsyMuKB database and showed that DD patients showed a higher rate and deleteriousness in DNM missense on the PPI interface than sibling control. Next, we identified 302 DD-related PsychiPPIs, defined as PPIs harboring a statistically significant number of DNM missenses at their interface, and 42 DD candidate genes from PsychiPPI. We observed that PsychiPPIs preferentially affected the human protein interactome network hub proteins. When analyzing DD candidate genes using gene ontology and gene spatio-expression, we found that PsychiPPI genes carrying PPI interface mutations, such as FGFR3 and ALOX5, were enriched in development-related pathways and the development of the neocortex, and cerebellar cortex, suggesting their potential involvement in the etiology of DD. Our results demonstrated that DD patients carried an excess burden of PPI-truncating DNM, which could be used to efficiently search for disease-related genes and mutations in large-scale sequencing studies. In conclusion, our comprehensive study indicated the significant role of PPI interface DNMs in developmental delay pathogenicity.

Effectiveness of craniotomy and long-term survival in 35 patients with gestational trophoblastic neoplasia with brain metastases: a clinical retrospective analysis.

OBJECTIVE: To investigate the clinical characteristics, treatments, and prognostic factors among patients with gestational trophoblastic neoplasia (GTN) exhibiting brain metastases who underwent craniotomy. METHODS: Thirty-five patients with GTN who had brain metastases and subsequently underwent craniotomies between January 1990 and December 2018 at Peking Union Medical College Hospital were identified using the GTN database. Their clinical manifestations, treatments, outcomes, and prognostic factors were retrospectively analyzed. RESULTS: All 35 patients underwent decompressive craniotomy, hematoma removal, and metastatic tumor resection combined with multiagent chemotherapy. Eighty percent (28/35) achieved complete remission, 11.4% (4/35) achieved partial remission, and 8.6% (3/35) had progressive disease. Not counting 2 patients who were lost to follow-up, 81.8% of the patients (27/33) were alive after a median follow-up of 72 months. The 5-year overall survival rate was 80.4%. Univariate analysis revealed that a history of chemotherapy failure (p=0.020) and a >1-week interval between craniotomy and chemotherapy commencement (p=0.027) were adverse risk factors for survival. Multivariate analysis showed that previous chemotherapy failure remained an independent risk factor for poor survival (odds ratio=11.50; 95% confidence interval=1.55-85.15; p=0.017). CONCLUSION: Decompressive craniotomy is a life-saving option if metastatic hemorrhage and intracranial hypertension produce a risk of cerebral hernia in patients with GTN who have brain metastases. Higher survival rates and improved prognoses can be achieved through perioperative multidisciplinary cooperation and timely standard postoperative chemotherapy.

De novo mutations identified by whole-genome sequencing implicate chromatin modifications in obsessive-compulsive disorder.

Obsessive-compulsive disorder (OCD) is a chronic anxiety disorder with a substantial genetic basis and a broadly undiscovered etiology. Recent studies of de novo mutation (DNM) exome-sequencing studies for OCD have reinforced the hypothesis that rare variation contributes to the risk. We performed, to our knowledge, the first whole-genome sequencing on 53 parent-offspring families with offspring affected with OCD to investigate all rare de novo variants and insertions/deletions. We observed higher mutation rates in promoter-anchored chromatin loops (empirical P = 0.0015) and regions with high frequencies of histone marks (empirical P = 0.0001). Mutations affecting coding regions were significantly enriched within coexpression modules of genes involved in chromatin modification during human brain development. Four genes­SETD5, KDM3B, ASXL3, and FBL­had strong aggregated evidence and functionally converged on transcription's epigenetic regulation, suggesting an important OCD risk mechanism. Our data characterized different genome-wide DNMs and highlighted the contribution of chromatin modification in the etiology of OCD.

A Comprehensive Evaluation of Cross-Omics Blood-Based Biomarkers for Neuropsychiatric Disorders.

The identification of peripheral multi-omics biomarkers of brain disorders has long been hindered by insufficient sample size and confounder influence. This study aimed to compare biomarker potential for different molecules and diseases. We leveraged summary statistics of five blood quantitative trait loci studies (N = 1980 to 22,609) and genome-wide association studies (N = 9725 to 500,199) from 14 different brain disorders, such as Schizophrenia (SCZ) and Alzheimer's Disease (AD). We applied summary-based and two-sample Mendelian Randomization to estimate the associations between blood molecules and brain disorders. We identified 524 RNA, 807 methylation sites, 29 proteins, seven cytokines, and 22 metabolites having a significant association with at least one of 14 brain disorders. Simulation analyses indicated that a cross-omics combination of biomarkers had better performance for most disorders, and different disorders could associate with different omics. We identified an 11-methylation-site model for SCZ diagnosis (Area Under Curve, AUC = 0.74) by analyzing selected candidate markers in published datasets (total N = 6098). Moreover, we constructed an 18-methylation-sites model that could predict the prognosis of elders with mild cognitive impairment (hazard ratio = 2.32). We provided an association landscape between blood cross-omic biomarkers and 14 brain disorders as well as a suggestion guide for future clinical discovery and application.

A selection pressure landscape for 870 human polygenic traits.

Characterizing the natural selection of complex traits is important for understanding human evolution and both biological and pathological mechanisms. We leveraged genome-wide summary statistics for 870 polygenic traits and attempted to quantify signals of selection on traits of different forms in European ancestry across four periods in human history and evolution. We found that 88% of these traits underwent polygenic change in the past 2,000-3,000 years. Recent selection was associated with ancient selection signals in the same trait. Traits related to pigmentation, body measurement and nutritional intake exhibited strong selection signals across different time scales. Our findings are limited by our use of exclusively European data and the use of genome-wide association study data, which identify associations between genetic variants and phenotypes that may not be causal. In sum, we provide an overview of signals of selection on human polygenic traits and their characteristics across human evolution, based on a European subset of human genetic diversity. These findings could serve as a foundation for further populational and medical genetic studies.

Microglial Activation of GLP-1R Signaling in Neuropathic Pain Promotes Gene Expression Adaption Involved in Inflammatory Responses.

Background: Neuropathic pain is a common chronic pain, which is related to hypersensitivity to stimulus and greatly affects the quality of life of patients. Maladaptive gene changes and molecular signaling underlie the sensitization of nociceptive pathways. We previously found that the activation of microglial glucagon-like peptide 1 receptor (GLP-1R) could potently relieve formalin-, bone cancer-, peripheral nerve injury-, and diabetes-induced pain hypersensitivity. So far, little is known about how the gene profile changes upon the activation of GLP-1R signaling in the pathophysiology of neuropathic pain. Methods: Spinal nerve ligation (SNL) was performed to induce neuropathic pain in rats. Mechanical allodynia was assessed using von Frey filaments. The expression of IL-10, ß-endorphin, and µ-opioid receptor (MOR) was examined by real-time quantitative polymerase chain reaction (qPCR) and whole-cell recording. Measurements of cellular excitability of the substantia gelatinosa (SG) neurons by whole-cell recording were carried out. R packages of differential gene expression analysis based on the negative binomial distribution (DESeq2) and weighted correlation network analysis (WGCNA) were used to analyze differential gene expression and the correlated modules among GLP-1R clusters in neuropathic pain. Results: The GLP-1R agonist, exenatide, has an antiallodynic effect on neuropathic pain, which could be reversed by intrathecal injections of the microglial inhibitor minocycline. Furthermore, differential gene expression analysis (WGCNA) indicated that intrathecal injections of exenatide could reverse the abnormal expression of 591 genes in the spinal dorsal horn induced by nerve injury. WGCNA revealed 58 modules with a close relationship between the microglial GLP-1R pathway and features of nerve injuries, including pain, ligation, paw withdrawal latency (PWL), and anxiety. The brown module was identified as the highest correlated module, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis indicated that inflammatory responses were most correlated with PWL. To further unravel the changes of hyperalgesia-related neuronal electrophysiological activity mediated by microglia GLP-1 receptors, whole-cell recording identified that MOR agonism stimulated a robust outward current in the sham groups compared with the spinal nerve ligation (SNL) groups. This inhibitory effect on the SNL group was more sensitive than that of the sham group after bath application of ß-endorphin. Conclusions: Our results further confirmed that the GLP-1R pathway is involved in alleviating pain hypersensitivity mediated by spinal microglia activation, and inflammatory responses were the most correlated pathway associated with PWL changes in response to exenatide treatment. We found that the identification of gene regulation in response to GLP-1R activation is an effective strategy for identifying new therapeutic targets for neuropathic pain. Investigation for the activation of spinal microglial GLP-1R which might ameliorate inflammatory responses through gene expression and structural changes is providing a potential biomarker in pain management.

Integrative enrichment analysis of gene expression based on an artificial neuron.

BACKGROUND: Huntington's disease is a kind of chronic progressive neurodegenerative disease with complex pathogenic mechanisms. To data, the pathogenesis of Huntington's disease is still not fully understood, and there has been no effective treatment. The rapid development of high-throughput sequencing technologies makes it possible to explore the molecular mechanisms at the transcriptome level. Our previous studies on Huntington's disease have shown that it is difficult to distinguish disease-associated genes from non-disease genes. Meanwhile, recent progress in bio-medicine shows that the molecular origin of chronic complex diseases may not exist in the diseased tissue, and differentially expressed genes between different tissues may be helpful to reveal the molecular origin of chronic diseases. Therefore, developing integrative analysis computational methods for the multi-tissues gene expression data, exploring the relationship between differentially expressed genes in different tissues and the disease, can greatly accelerate the molecular discovery process. METHODS: For analysis of the intra- and inter- tissues' differentially expressed genes, we designed an integrative enrichment analysis method based on an artificial neuron (IEAAN). Firstly, we calculated the differential expression scores of genes which are seen as features of the corresponding gene, using fold-change approach with intra- and inter- tissues' gene expression data. Then, we weighted sum all the differential expression scores through a sigmoid function to get differential expression enrichment score. Finally, we ranked the genes according to the enrichment score. Top ranking genes are supposed to be the potential disease-associated genes. RESULTS: In this study, we conducted large amounts of experiments to analyze the differentially expressed genes of intra- and inter- tissues. Experimental results showed that genes differentially expressed between different tissues are more likely to be Huntington's disease-associated genes. Five disease-associated genes were selected out in this study, two of which have been reported to be implicated in Huntington's disease. CONCLUSIONS: We proposed a novel integrative enrichment analysis method based on artificial neuron (IEAAN), which displays better prediction precision of disease-associated genes in comparison with the state-of-the-art statistical-based methods. Our comprehensive evaluation suggests that genes differentially expressed between striatum and liver tissues of health individuals are more likely to be Huntington's disease-associated genes.

RNA-seq co-expression network analysis reveals anxiolytic behavior of mice with Efnb2 knockout in parvalbumin+ neurons.

Anxiety disorders are the most common psychiatric disorders, and the change in the activity of the prefrontal cortex (PFC) is considered as the underlying pathological mechanism. Parvalbumin-expressing (PV+) inhibition contributes to the overall activity of the PFC. However, the molecular mechanism underlying the excitation-inhibition imbalance of PV+ neurons in the PFC is unknown. Efnb2 is a membrane-bound molecule that plays an important role in the nervous system through binding the Eph receptor. To investigate whether the loss of Efnb2 in PV+ affects anxiety, we examined the behavior of wild type and Efnb2 in PV+ neurons knockout (KO) mice. We monitored the defensive responses to aversive stimuli of elevated plus maze (EPM) and found that KO mice exhibited obvious fearless and anxiolytic behaviors. To further investigate the underlying regulatory mechanism, we performed RNA sequencing, analyzed the differentially expressed genes (DEGs), and constructed the weighted gene co-expression network analysis (WGCNA). The WGCNA identified 12 characteristic modules. Among them, the MEgreen module showed the most significant correlation with KO mice of EPM stimuli. The Gene Ontology enrichment and the Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed that this was related to the distal axon, Ras signaling pathway and insulin signaling pathway. Furthermore, the whole-cell voltage clamp recordings also proved that Efnb2 gene knock-out could affect synaptic function. Together with the transcriptomic analysis of mice with Efnb2 knockout on PV+ neurons, our findings suggest that Efnb2 gene in the PV+ neuron of PFC may be a crucial factor for fear and anxiety, which provide an insight into anxiety pathophysiology.

Spatiotemporal 22q11.21 Protein Network Implicates DGCR8-Dependent MicroRNA Biogenesis as a Risk for Late-Fetal Cortical Development in Psychiatric Diseases.

Chromosome 22q11.21 copy number variant (CNV) is a vital risk factor that can be a genetic predisposition to neurodevelopmental disorders (NDD). As 22q11.21 CNV affects multiple genes, causal disease genes and mechanisms affected are still poorly understood. Thus, we aimed to identify the most impactful 22q11.21 CNV genes and the potential impacted human brain regions, developmental stages, and signaling pathways. We constructed the spatiotemporal dynamic networks of 22q11.21 CNV genes using the brain developmental transcriptome and physical protein-protein interactions. The affected brain regions, developmental stages, driver genes, and pathways were subsequently investigated via integrated bioinformatics analysis. As a result, we first identified that 22q11.21 CNV genes affect cortical area mainly during late-fetal periods. Interestingly, we observed that connections between a driver gene DGCR8 and its interacting partners, MECP2 and CUL3, also network hubs, only existed in the network of late-fetal period within cortical region, suggesting their functional specificity during brain development. We also confirmed the physical interaction result between DGCR8 and CUL3 by liquid chromatography-tandem mass spectrometry. As a whole, our results could suggest that the disruption of DGCR8-dependent microRNA biogenesis plays a vital role in NDD for late-fetal cortical development.