Causality Investigation between Gut Microbiome and Sleep-Related Traits: A Bidirectional Two-Sample Mendelian Randomization Study.

Recent research has highlighted associations between sleep and microbial taxa and pathways. However, the causal effect of these associations remains unknown. To investigate this, we performed a bidirectional two-sample Mendelian randomization (MR) analysis using summary statistics of genome-wide association studies (GWAS) from 412 gut microbiome traits (N = 7738) and GWAS studies from seven sleep-associated traits (N = 345,552 to 386,577). We employed multiple MR methods to assess causality, with Inverse Variance Weighted (IVW) as the primary method, alongside a Bonferroni correction ((p < 2.4 × 10-4) to determine significant causal associations. We further applied Cochran's Q statistical analysis, MR-Egger intercept, and Mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) for heterogeneity and pleiotropy assessment. IVW estimates revealed 79 potential causal effects of microbial taxa and pathways on sleep-related traits and 45 inverse causal relationships, with over half related to pathways, emphasizing their significance. The results revealed two significant causal associations: genetically determined relative abundance of pentose phosphate decreased sleep duration (p = 9.00 × 10-5), and genetically determined increase in fatty acid level increased the ease of getting up in the morning (p = 8.06 × 10-5). Sensitivity analyses, including heterogeneity and pleiotropy tests, as well as a leave-one-out analysis of single nucleotide polymorphisms, confirmed the robustness of these relationships. This study explores the potential causal relationships between sleep and microbial taxa and pathways, offering novel insights into their complex interplay.

Human lineage mutations regulate RNA-protein binding of conserved genes NTRK2 and ITPR1 involved in human evolution.

Background: The role of human lineage mutations (HLMs) in human evolution through post-transcriptional modification is unclear. Aims: To investigate the contribution of HLMs to human evolution through post-transcriptional modification. Methods: We applied a deep learning model Seqweaver to predict how HLMs impact RNA-binding protein affinity. Results: We found that only 0.27% of HLMs had significant impacts on RNA-binding proteins at the threshold of the top 1% of human common variations. These HLMs enriched in a set of conserved genes highly expressed in adult excitatory neurons and prenatal Purkinje neurons, and were involved in synapse organisation and the GTPase pathway. These genes also carried excess damaging coding mutations that caused neurodevelopmental disorders, ataxia and schizophrenia. Among these genes, NTRK2 and ITPR1 had the most aggregated evidence of functional importance, suggesting their essential roles in cognition and bipedalism. Conclusions: Our findings suggest that a small subset of human-specific mutations have contributed to human speciation through impacts on post-transcriptional modification of critical brain-related genes.

Human umbilical cord mesenchymal stem cells promote steroid-induced osteonecrosis of the femoral head repair by improving microvascular endothelial cell function.

Recently, there has been growing interest in using cell therapy through core decompression (CD) to treat osteonecrosis of the femoral head (ONFH). Our study aimed to investigate the effectiveness and mechanism of human umbilical cord mesenchymal stem cells (hUCMSCs) in treating steroid-induced ONFH. We constructed a steroid-induced ONFH rabbit model as well as dexamethasone (Dex)-treated bone microvascular endothelial cells (BMECs) model of human femoral head. We injected hUCMSCs into the rabbit femoral head via CD. The effects of hUCMSCs on steroid-induced ONFH rabbit model and Dex-treated BMECs were evaluated via micro-CT, microangiography, histology, immunohistochemistry, wound healing, tube formation, and western blotting assay. Furthermore, we conducted single-cell RNA sequencing (scRNA-seq) to examine the characteristics of endothelial cells, the activation of signaling pathways, and inter-cellular communication in ONFH. Our data reveal that hUCMSCs improved the femoral head microstructure and bone repair and promoted angiogenesis in the steroid-induced ONFH rabbit model. Importantly, hUCMSCs improved the migration ability and angioplasty of Dex-treated BMECs by secreting COL6A2 to activate FAK/PI3K/AKT signaling pathway via integrin α1ß1.

Circadian rhythm-associated lncRNA RP11-414H17.5 as a key therapeutic target in osteosarcoma affects the tumor immune microenvironment and enhances malignancy.

BACKGROUND: It has previously been proven that circadian rhythm disruption is associated with the incidence and deterioration of several tumors, which potentially leads to increased tumor susceptibility and a worse prognosis for tumor-bearing patients. However, their potential role in osteosarcoma has yet to be sufficiently investigated. METHODS: Transcriptomic and clinical data of 84 osteosarcoma samples and 70 normal bone tissue samples were obtained from the TARGET and GTEx databases, circadian rhythm-related genes were obtained from Genecards, and circadian rhythm-related lncRNAs (CRLs) were obtained by Pearson correlation analysis, differential expression analysis, and protein-protein interaction (PPI) analysis. COX regression and LASSO regression were performed on the CRLs in order to construct a circadian rhythm-related prognostic prediction signature (CRPS). CRPS reliability was verified by Kaplan-Meier (KM), principal component analysis (PCA), nomogram, and receiver operating characteristic (ROC) curve. CRPS effects on the immune microenvironment of osteosarcoma were explored by enrichment analysis and immune infiltration analysis, and the effect of critical gene RP11-414H17.5 on osteosarcoma was experimentally verified. RESULT: CRPS consisting of three CRLs was constructed and its area under the curve (AUC) values predicted that osteosarcoma prognosis reached 0.892 in the training group and 0.843 in the test group, with a p value of < 0.05 for the KM curve and stable performance across different clinical subgroups. PCA analysis found that CRPS could significantly distinguish between different risk subgroups, and exhibited excellent performance in the prediction of the immune microenvironment. The experiment verified that RP11-414H17.5 can promote metastasis and inhibit apoptosis of osteosarcoma cells. CONCLUSION: The study revealed that circadian rhythm plays a crucial role in osteosarcoma progression and identified the impact of the key gene RP11-414H17.5 on osteosarcoma, which provides novel insights into osteosarcoma diagnosis and therapy.

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.

Tizoxanide as a novel theraputic candidate for osteoarthritis.

Osteoarthritis (OA) is a frequently seen degenerative joint disease in the elderly. Its pathogenesis is highly related to the local inflammatory reaction and autophagy. Tizoxanide (Tiz), the main active metabolite of nitazoxanide, has proved its anti-inflammatory properties in several diseases. However, the exact role of Tiz in OA remains to explore. In this study, we investigated the anti-arthritic effects and the underlying molecular mechanisms of Tiz on rat OA. The results showed that Tiz could attenuate the IL-1ß-induced inflammatory disorders, cartilage matrix damage and autophagy reduction in rat chondrocytes. Moreover, employment of autophagy inhibitor 3-methyladenine (3-MA) could antagonize the protective effects of Tiz in IL-1ß-treated rat chondrocytes. Additionally, Tiz also inhibited the IL-1ß-induced PI3K/AKT/mTOR and P38/JNK phosphorylation in chondrocytes. In vivo, intra-articular injection of Tiz could significantly alleviate the progression of cartilage damage in rat OA model. Briefly, our study demonstrated the therapeutic potential of Tiz in OA, suggesting that Tiz administration might serve as a promising strategy in OA therapy.

Dissecting the role of lactate metabolism LncRNAs in the progression and immune microenvironment of osteosarcoma.

BACKGROUND: The process of lactate metabolism has been proved to play a critical role in the progression of various cancers and to influence the immune microenvironment, but its potential role in osteosarcoma remains unclear. METHODS: We have acquired transcriptomic and clinical data from 84 osteosarcoma samples and 70 normal bone samples from the TARGET and GTEx databases. We identified differentially expressed lactate metabolism-related LncRNAs (LRLs) in osteosarcoma and performed Cox regression and LASSO regression to establish LRLs prognostic signature (LRPS). The reliability of LRPS performance was examined by separate prognostic analysis, viability curves and receiver operating characteristic (ROC) curves. Furthermore, the effects of LRPS on the immune microenvironment of osteosarcoma were investigated, and the functions of the focal genes were experimentally validated. RESULT: A total of 856 differentially expressed LRLs were identified and 5 of them were selected to construct LRPS, which was a better prognostic predictor for osteosarcoma compared with other published prognostic signatures (AUC up to 0.947 and 0.839 in the training and test groups, respectively, with adj-p<0.05 for KM curves). We found that LRPS significantly affected the immune infiltration of osteosarcoma, while RP11-472M19.2 significantly promoted the metastasis of osteosarcoma, which was well validated experimentally. Encouragingly, a number of sensitive drugs were identified for LRPS and RP11-472M19.2 high-risk groups. CONCLUSION: Our study shows that lactate metabolism plays a crucial role in the development of osteosarcoma and has been well validated experimentally, providing extremely important insights into the clinical treatment and in-depth research of osteosarcoma.

Gastrodin alleviates rat chondrocyte senescence and mitochondrial dysfunction through Sirt3.

Several researchers have focused on understanding the pathogenesis and treatment strategies for osteoarthritis (OA). Gastrodin (GAS) is a potential anti-inflammatory agent. In this study, we constructed an in vitro OA chondrocyte model by treating chondrocytes with IL-1ß. Next, we determined the expression of aging-related markers and mitochondrial functions in chondrocytes treated with GAS. Further, we constructed a "drug-component-target-pathway-disease" interactive network and determined the effect of GAS on the functions and pathways related to OA. Finally, we constructed the OA rat model by removing the medial meniscus of the right knee and transection of the anterior cruciate ligament. The results revealed that GAS reduced senescence and improved mitochondrial functions in OA chondrocytes. We used network pharmacology and bioinformatics to screen for key molecules Sirt3 and the PI3K-AKT pathway involved in regulating the effect of GAS on OA. Further studies showed an increase in SIRT3 expression and reduced chondrocyte aging, mitochondrial damage, and the phosphorylation of the PI3K-AKT pathway. The results showed that GAS ameliorates pathological changes related to aging, increases SIRT3 expression, and protects the ECM in the OA rat model. These results were consistent with our bioinformatics results and previous studies. In summary, GAS slows down the aging of chondrocytes and mitochondrial damage in OA by regulating the phosphorylation of the PI3K-AKT pathway via SIRT3.

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.

Procyanidin B2 ameliorates the progression of osteoarthritis: An in vitro and in vivo study.

OBJECTIVE: Osteoarthritis (OA) is characterized by cartilage degeneration and inflammation. Procyanidin B2 (PCB2), a natural flavonoid compound, exhibits potential anti-inflammatory and anti-oxidative effects against several diseases. However, its curative effects on OA remain unclear. PURPOSE: Herein, we explored the anti-arthritic effects of PCB2 on OA onset and progress and its potential mechanism. METHODS: CCK-8 assays and EdU staining were used to assess the cytotoxic effects and cell proliferation activity of PCB2. Flow cytometry was used to detect apoptosis in chondrocytes. ELISA, qPCR, and western blotting, were applied to explore the expression of apoptosis and senescence-associated secretion phenotype (SASP) factors. The Nrf2/NF-κB signaling cascade was explored using immunofluorescence and western blotting. Additionally, we silenced the Nrf2 gene using siRNAs to verify its function in PCB2 regulation of senescence and apoptosis phenotypes. Safranin O-Fast Green (SO) and immunohistochemical staining were used to explore the effects of PCB2 on OA model rats. RESULTS: PCB2 dampened interleukin (IL)-1ß-triggered expression of SASP factors in vitro. Additionally, PCB2 diminished IL-1ß-triggered destruction of the extracellular matrix (ECM) via downregulating the expression of MMPs, while upregulating the expression of collagen II and aggrecan. In addition, PCB2 treatment reduced IL-1ß-induced apoptosis of chondrocytes. Mechanistically, PCB2 could attenuated chondrocyte senescence in vitro via the Nrf2/NF-κB pathway. Moreover, PCB2 exhibited anti-apoptotic properties via the Nrf2/BAX/Bcl-2 pathway. PCB2 alleviated knee cartilage degeneration in an OA rat model. CONCLUSIONS: Our results suggest that PCB2 may be used as a therapeutic agent for OA.

An Integrative Analysis of Identified Schizophrenia-Associated Brain Cell Types and Gene Expression Changes.

Schizophrenia (SCZ) is a severe mental disorder that may result in hallucinations, delusions, and extremely disordered thinking. How each cell type in the brain contributes to SCZ occurrence is still unclear. Here, we leveraged the human dorsolateral prefrontal cortex bulk RNA-seq data, then used the RNA-seq deconvolution algorithm CIBERSORTx to generate SCZ brain single-cell RNA-seq data for a comprehensive analysis to understand SCZ-associated brain cell types and gene expression changes. Firstly, we observed that the proportions of brain cell types in SCZ differed from normal samples. Among these cell types, astrocyte, pericyte, and PAX6 cells were found to have a higher proportion in SCZ patients (astrocyte: SCZ = 0.163, control = 0.145, P.adj = 4.9 × 10-4, effect size = 0.478; pericyte: SCZ = 0.057, control = 0.066, P.adj = 1.1 × 10-4, effect size = 0.519; PAX6: SCZ = 0.014, control = 0.011, P.adj = 0.014, effect size = 0.377), while the L5/6_IT_CAR3 cells and LAMP5 cells are the exact opposite (L5/6_IT_Car3: SCZ = 0.102, control = 0.108, P.adj = 0.016, effect size = 0.369; LAMP5: SCZ = 0.057, control = 0.066, P.adj = 2.2 × 10-6, effect size = 0.617). Next, we investigated gene expression in cell types and functional pathways in SCZ. We observed chemical synaptic transmission dysregulation in two types of GABAergic neurons (PVALB and LAMP5), and immune reaction involvement in GABAergic neurons (SST) and non-neuronal cell types (endothelial and oligodendrocyte). Furthermore, we observed that some differential expression genes from bulk RNA-seq displayed cell-type-specific abnormalities in the expression of molecules in SCZ. Finally, the cell types with the SCZ-related transcriptomic changes could be considered to belong to the same module since we observed two major similar coordinated transcriptomic changes across these cell types. Together, our results offer novel insights into cellular heterogeneity and the molecular mechanisms underlying SCZ.

Dissecting the effect of sphingolipid metabolism gene in progression and microenvironment of osteosarcoma to develop a prognostic signature.

Sphingolipid metabolism (SM) fuels tumorigenesis and the malignant progression of osteosarcoma (OS), which leads to an unfavorable prognosis. Elucidating the molecular mechanisms underlying SM in osteosarcoma and developing a SM-based prognostic signature could be beneficial in the clinical setting. This study included 88 frozen OS samples to recognize the vital SM-relevant genes in the development of OS utilizing univariate Cox regression. The Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis was conducted on the SM- relevant genes to minimize the risk of overfitting. The prognostic signature was generate utilizing the multivariable Cox regression analysis and was verified in the validation cohort. Moreover, cellular and molecular mechanisms associated with SM have an unfavorable prognosis for OS patients and have been widely studied. Resultantly, an SM-based prognostic risk model was established according to critical prognostic genes (CBS, GLB1, and HACD1), which had an excellent ability to predict the prognosis of OS patients (AUC for the train cohort was 0.887 and AUC for validation cohort was 0.737). The high-risk OS patients identified based on this prognostic signature had significantly poor immune microenvironment, indicated by significantly low immune score (mean=216.290 ± 662.463), reduced infiltrations of 25 immune cells, including NK cells (LogFC= -0.3597), CD8+T cells ((LogFC=-0.2346), Cytolytic activity ((LogFC=-0.1998), etc. The immunosuppressive microenvironment could be due to dysregulated SM of glycolipids. Further, a nomogram was constructed by integrating the SM-based prognostic signature and clinical paraments to facilitate clinical application. The nomogram could accurately predict the prognosis of OS invalids. Collectively, this study clarified the function of SM in the development of OS and helped develop a tool for risk stratification based on SM-related genes with application in clinical settings. The results of our study will aid in identifying high-risk patients and provide individualized treatments.

Evaluation of the Effectiveness of Derived Features of AlphaFold2 on Single-Sequence Protein Binding Site Prediction.

Though AlphaFold2 has attained considerably high precision on protein structure prediction, it is reported that directly inputting coordinates into deep learning networks cannot achieve desirable results on downstream tasks. Thus, how to process and encode the predicted results into effective forms that deep learning models can understand to improve the performance of downstream tasks is worth exploring. In this study, we tested the effects of five processing strategies of coordinates on two single-sequence protein binding site prediction tasks. These five strategies are spatial filtering, the singular value decomposition of a distance map, calculating the secondary structure feature, and the relative accessible surface area feature of proteins. The computational experiment results showed that all strategies were suitable and effective methods to encode structural information for deep learning models. In addition, by performing a case study of a mutated protein, we showed that the spatial filtering strategy could introduce structural changes into HHblits profiles and deep learning networks when protein mutation happens. In sum, this work provides new insight into the downstream tasks of protein-molecule interaction prediction, such as predicting the binding residues of proteins and estimating the effects of mutations.

Locus-level antagonistic selection shaped the polygenic architecture of human complex diseases.

BACKGROUND: We aimed to evaluate the potential role of antagonistic selection in polygenic diseases: if one variant increases the risk of one disease and decreases the risk of another disease, the signals of genetic risk elimination by natural selection will be distorted, which leads to a higher frequency of risk alleles. METHODS: We applied local genetic correlations and transcriptome-wide association studies to identify genomic loci and genes adversely associated with at least two diseases. Then, we used different population genetic metrics to measure the signals of natural selection for these loci and genes. RESULTS: First, we identified 2120 cases of antagonistic pleiotropy (negative local genetic correlation) among 87 diseases in 716 genomic loci (antagonistic loci). Next, by comparing with non-antagonistic loci, we observed that antagonistic loci explained an excess proportion of disease heritability (median 6%), showed enhanced signals of balancing selection, and reduced signals of directional polygenic adaptation. Then, at the gene expression level, we identified 31,991 cases of antagonistic pleiotropy among 98 diseases at 4368 genes. However, evidence of altered signals of selection pressure and heritability distribution at the gene expression level is limited. CONCLUSION: We conclude that antagonistic pleiotropy is widespread among human polygenic diseases, and it has distorted the evolutionary signal and genetic architecture of diseases at the locus level.

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.

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.

Loss of Setd2 associates with aberrant microRNA expression and contributes to inflammatory bowel disease progression in mice.

Both SETD2-mediated H3K36me3 and miRNAs play critical epigenetic roles in inflammatory bowel disease (IBD) and involve in the dysfunctional intestinal barrier. However, little is known about cross-talk between these two types of regulators in IBD progression. We performed small RNA sequencing of Setd2 epithelium-specific knockout mice (Setd2Vil-KO) and wild-type controls, both with DSS-induced colitis, and designed a framework for integrative analysis. Firstly, we integrated the downloaded ChIP-seq data with miRNA expression profiles and identified a significant intersection of pre-miRNA expression and H3K36me3 modification. A significant inverse correlation was detected between changes of H3K36me3 modification and expression of the 171 peak-covered miRNAs. We further integrated RNA-seq data with predicted miRNA targets to screen negatively regulated miRNA-mRNA pairs and found the H3K36me3-associated differentially expressed microRNAs significantly enriched in cell-cell junction and signaling pathways. Using network analysis, we identified ten hub miRNAs, among which six are H3K36me3-associated, suggesting therapeutic targets for IBD patients with SETD2-deficiency.

Spatiotemporal 7q11.23 protein network analysis implicates the role of DNA repair pathway during human brain development.

Recurrent deletions and duplications of chromosome 7q11.23 copy number variants (CNVs) are associated with several psychiatric disorders. Although phenotypic abnormalities have been observed in patients, causal genes responsible for CNV-associated diagnoses and traits are still poorly understood. Furthermore, the targeted human brain regions, developmental stages, protein networks, and signaling pathways, influenced by this CNV remain unclear. Previous works showed GTF2I involved in Williams-Beuren syndrome, but pathways affected by GTF2I are indistinct. We first constructed dynamic spatiotemporal networks of 7q11.23 genes by combining data from the brain developmental transcriptome with physical interactions of 7q11.23 proteins. Topological changes were observed in protein-protein interaction (PPI) networks throughout different stages of brain development. Early and late fetal periods of development in the cortex, striatum, hippocampus, and amygdale were observed as the vital periods and regions for 7q11.23 CNV proteins. CNV proteins and their partners are significantly enriched in DNA repair pathway. As a driver gene, GTF2I interacted with PRKDC and BRCA1 to involve in DNA repair pathway. The physical interaction between GTF2I with PRKDC was confirmed experimentally by the liquid chromatography-tandem mass spectrometry (LC-MS/MS). We identified that early and late fetal periods are crucial for 7q11.23 genes to affect brain development. Our results implicate that 7q11.23 CNV genes converge on the DNA repair pathway to contribute to the pathogenesis of psychiatric diseases.