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Mapping the Immune cell-specific gene regulatory network in bipolar disorder: A framework from scTWMR to exploratory drug-target annotation.

BACKGROUND: Although the involvement of the immune system in the genetic susceptibility of bipolar disorder (BD) is widely acknowledged, the causal relationship between gene expression in specific immune cell subtypes and BD requires systematic elucidation. METHODS: We implemented an analytical framework integrating single-cell transcriptome-wide Mendelian randomization (scTWMR) with colocalization analysis. This approach utilized cis-expression quantitative trait loci (cis-eQTLs) derived from 14 distinct immune cell types as instrumental variables to interrogate BD genome-wide association study (GWAS) summary statistics (comprising 41,917 cases and 371,549 controls). Subsequent investigations encompassed functional enrichment analysis, protein-protein interaction (PPI) network construction, phenome-wide association study (PheWAS), and performed an exploratory drug-target annotation. RESULTS: Our analysis identified 33 gene-immune cell associations. Colocalization analysis provided robust evidence (PPH4 > 90%) for shared causal variants implicating the MAD1L1, APOM, and NFKBIL1 loci. Significantly enriched biological pathways included cell cycle regulation, circadian rhythm entrainment, and neuroinflammation. The PPI network revealed a core regulatory module centered on histone-encoding and immune-related genes. Exploratory drug-target annotation nominated compounds for further investigation for compounds targeting APOM, TMEM258, and NFKBIL1. CONCLUSION: This study systematically delineates a genetically supported regulatory network of immune cell-specific gene expression in BD, predominantly implicating CD8⁺ effector T cells, plasma cells, and B cells. The findings corroborate established pathological pathways while uncovering novel cell type-specific therapeutic targets, thereby providing a genetic framework for prioritizing candidate targets for future investigation.

Bipolar disorder

Integrative analysis of the roles and prognostic value of RNA-binding proteins in papillary renal cell carcinoma.

RNA-binding proteins (RBPs) serve essential roles in various cancer types, but their functions in papillary renal cell carcinoma (pRCC) have not been elucidated to date. In our work, differentially expressed RBPs in pRCC were identified after acquisition of RNA-sequencing and clinical data related to pRCC from The Cancer Genome Atlas database(TCGA). Functional enrichment analysis and protein interaction network analysis, along with univariate and multivariate Cox regression analyses, were performed to uncover potential biological effects of the identified RBPs and screen the hub RBPs for pRCC prognosis. We identified 251 up-regulated and 129 down-regulated RBPs, and filtered out seven hub RBPs, namely, SRSF8, CD3EAP, HBS1L, ELAC2, MRPL34, NOP2 and IGF2BP2, for their prognostic relevance. A prognostic risk score model for overall survival of pRCC patients was constructed based on the seven hub RBPs. Further analysis showed that the low-risk group had higher survival rate than the high-risk group in both training and validation cohorts. The predictive accuracy was verified in the Human Protein Atlas database.In addition, we introduced the GSE15641 dataset from the Gene Expression Omnibus (GEO) database for independent external validation, and confirmed the expression levels of HBS1L, MRPL34 and IGF2BP2 through real-time quantitative PCR (RT-qPCR) and Western blotting (WB) using human renal tubular epithelial cell line HK-2 and human papillary renal cell carcinoma cell line Caki-2. In pRCC, CD3EAP was significantly elevated, while ELAC2, IGF2BP2, MRPL34, SRSF8 and HBS1L were significantly reduced. There was no significant difference between tumor and normal tissues in NOP2 expression. Risk score and tumor grade were independent prognostic factors associated with overall survival. In addition, we established a nomogram based on the seven prognostic RBPs to help predict overall survival at 1-3 years. In conclusion, seven differentially expressed hub RBPs were identified as potential prognostic biomarkers for pRCC. Our prognostic model might serve as a support for better treatment decision-making. Our work could provide potential new ideas for diagnosis and research on targeted drugs for pRCC.

Bioinformatics

Integrative analysis of transcriptome and chromatin accessibility reveals promoter-proximal regulation and identifies candidate ABC transporters associated with cold stress responses in maize.

BACKGROUND: Low-temperature stress is a formidable environmental constraint that severely limits the growth and productivity of maize (Zea mays L.), particularly during the highly vulnerable early seedling stage. While cold tolerance is a critical agronomic objective, the integrated transcriptional and epigenetic regulatory mechanisms that govern this trait remain largely elusive. Characterizing these coordinated molecular networks is fundamental to the genetic enhancement of cold resilience in maize. METHODS: Using two maize inbred lines contrasting in chilling response (ZHB12 tolerant, B73 sensitive), we performed integrative time‑course RNA‑seq and ATAC‑seq to thoroughly and systematically characterize the precise dynamic interplay between gene expression and chromatin accessibility under cold stress conditions at the seedling stage. RESULTS: Physiological assessments confirmed that ZHB12 possesses superior cold tolerance, manifested by significantly attenuated electrolyte leakage and reduced foliar damage compared to B73. Transcriptomic profiling revealed a massive, time-dependent divergence in gene expression between the two genotypes, with a major regulatory transition identified at 24 h of cold exposure. Functional enrichment analysis demonstrated that ZHB12 preferentially activates a robust defense repertoire, including Photosystem II electron transport, diterpenoid biosynthesis, and ATP biosynthetic pathways. Notably, multiple ATP-binding cassette (ABC) transporter genes were coordinately upregulated under chilling, suggesting their potential involvement in cellular homeostasis. ATAC-seq analysis indicated that cold stress is associated with chromatin remodeling in ZHB12, with increased accessibility observed in proximal promoter regions. Integrative analysis identified a core set of dual-responsive genes, in which increased promoter accessibility coincided with transcriptional upregulation. These genes were predominantly enriched in transporter activity and transcriptional regulation, suggesting potential epigenetic link to the superior stress response of ZHB12. CONCLUSION: Our findings reveal extensive transcriptional and chromatin accessibility changes in ZHB12 under cold stress. The observed associations between promoter accessibility and gene activation, particularly in genes involved in transport processes, highlight candidate regulators potentially contributing to cold tolerance. This study provides a molecular framework and identifies high-value candidate genes that may inform future efforts in breeding cold-tolerant maize, pending functional validation.

Zea mays

Identification and validation of the important role of KIF11 in the development and progression of endometrial cancer.

BACKGROUND: Human kinesin family member 11 (KIF11) plays a vital role in regulating the cell cycle and is implicated in the tumorigenesis and progression of various cancers, but its role in endometrial cancer (EC) is still unclear. Our current research explored the prognostic value, biological function and targeting strategy of KIF11 in EC through approaches including bioinformatics, machine learning and experimental studies. METHODS: The GSE17025 dataset from the GEO database was analyzed via the limma package to identify differentially expressed genes (DEGs) in EC. Functional enrichment analysis of the DEGs was conducted using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. DEGs were further screened for hub genes through protein-protein interaction (PPI) network analysis and machine learning. The role of the hub gene KIF11 in EC was analyzed using clinical data from the TCGA database. The expression of KIF11 in EC was subsequently validated in clinical samples. In vitro experiments were utilized to evaluate the effects of KIF11 on biological functions such as proliferation, migration, apoptosis, and the cell cycle in endometrial cancer cells. RESULTS: A total of 877 DEGs, which are widely involved in important biological processes such as cell division, tubulin binding, and the cell cycle, were identified. Through PPI network analysis and machine learning, KIF11 was selected as the hub gene for subsequent analysis and experimental validation. An analysis of TCGA data revealed that KIF11 is highly expressed in EC and is associated with tumor grade, stage, and a low survival rate. The overexpression of KIF11 in tumor tissues was further confirmed in EC patient samples. KIF11 knockdown had inhibitory effects on cell proliferation, migration and invasion. Flow cytometry analysis revealed that KIF11 knockdown induced G2/M phase arrest and promoted apoptosis in EC cells. CONCLUSION: Our study demonstrated that KIF11 was upregulated in EC and was strongly associated with a poor prognosis. Notably, we found that reduced KIF11 expression inhibited EC cell proliferation, migration and invasion. KIF11 knockdown caused more EC cells to arrest in the G2/M phase and undergo apoptosis. The findings of our study emphasized that KIF11 may be a promising prognostic biomarker and therapeutic target for EC patients.

Humans

Phosphoproteomic Profiling of Early-Stage Non-Small Cell Lung Cancer Provides Preliminary Evidence of Phosphorylation-Regulated Rho GTPase Signaling Driving Cytoskeletal Remodeling, Angiogenesis, and Cell Cycle Progression.

Non-small cell lung cancer (NSCLC) is the primary cause of cancer-related deaths worldwide. This can be attributed to the difficulty in early detection and the limited efficacy of available treatments, partly due to an incomplete understanding of the disease biology. Identification of key proteins involved in early-stage progression and understanding the underlying mechanisms can greatly contribute to the development of diagnostic and treatment strategies for NSCLC. Quantitative phosphoproteomic analysis was done on paired tumor tissues and adjacent normal lung tissues from early-stage NSCLC adenocarcinoma (LUAD) patients to allow for the identification of proteins with differential phosphorylation and their associated pathways. A total of 6483 phosphoproteins were identified, with 1229 proteins having significantly higher phosphorylation and 701 proteins having significantly lower phosphorylation in the tumor tissues. All MS data were deposited in ProteomeXchange with the identifier PXD071583. Function enrichment analysis showed that the differentially phosphorylated proteins and phosphosites were primarily involved in Rho GTPase signaling and cytoskeleton remodeling. Analysis of protein interaction networks suggests that the predicted kinase activity likely drives malignant transformation in NSCLC LUAD, presumably through Rho GTPase-mediated angiogenesis and cell cycle progression. More importantly, this study identified several protein phosphosites with differential phosphorylation and inferred kinase-phosphosite activities that have not previously been reported in NSCLC LUAD.

Humans

Genomic and proteogenomic insights into Spontaneous Coronary Artery Dissection (SCAD): A systematic review of emerging multi-omic evidence.

BACKGROUND: Spontaneous coronary artery dissection (SCAD) is a major cause of myocardial infarction in young women without traditional cardiovascular risk factors (Hayes et al., 2018; Adlam et al., 2018 [1, 2]). Despite growing awareness, its biological underpinnings remain incompletely understood, and clinical management is largely based on observational evidence rather than mechanistic insight (Saw et al., 2014; Lettieri et al., 2015; Steg et al., 2024 [3-5]). OBJECTIVES: To systematically integrate genomic, epitranscriptomic, proteomic, and metabolomic data in order to characterize the multi-omic architecture of SCAD and identify potential biomarkers and therapeutic targets. METHODS: A systematic review was conducted in accordance with the PRISMA 2020 statement (Arbelo et al., 2023 [6]). PubMed/MEDLINE was searched for original studies investigating genomic and multi-omic features of SCAD. Data were extracted on study design, patient characteristics, identified variants, circulating biomarkers, and implicated biological pathways. Functional enrichment analysis was performed using the DAVID bioinformatics resource (Page et al., 2021 [7]). RESULTS: A total of 16 studies were included. Genome-wide association studies consistently identified susceptibility loci related to arterial structure and extracellular matrix integrity, including ADAMTSL4, PHACTR1/EDN1, LRP1, and FBN1 (Huang et al., 2009; Saw et al., 2020; Turley et al., 2020 [8-10]). Rare variant analyses further supported the role of genes involved in extracellular matrix remodeling and vascular smooth muscle cell function, including COL3A1, COL4A1/2, SMAD3, and TLN1 (Adlam et al., 2023; Turley et al., 2021, 2019; Carss et al., 2020; Zekavat et al., 2022; Wang et al., 2022 [11-16]), while ancestry-specific signals such as TSR1 variants were observed in distinct populations (Turley et al., 2023 [17]). Proteogenomic approaches linked genetic susceptibility loci to circulating proteins involved in matrix remodeling and inflammation, including cathepsin B and ECM1 (Maioli et al., 2010 [18]). Epitranscriptomic analyses identified differential microRNA expression profiles associated with vascular injury and repair pathways (Sun et al., 2019 [19]). CONCLUSIONS: SCAD is characterized by a complex, multi-layered biological architecture involving genetic susceptibility, extracellular matrix dysregulation, and vascular signaling pathways. Integration of multi-omic data provides novel insights into disease mechanisms and highlights potential biomarkers and targets for precision medicine approaches in SCAD.

Animals

Comprehensive Analysis of miRNAs and Predicted Protein Interaction Networks in Skeletal Muscle Development of Myostatin-Deficient Rabbits.

Myostatin (MSTN), encoded by the MSTN gene, is a critical negative regulator of skeletal muscle mass. This study aims to identify and characterize the miRNAs involved in the development of the double-muscling phenotype in MSTN-deficient rabbits. We performed high-throughput sequencing to analyze the miRNA expression profiles in gluteus maximus tissue from wild type (MSTN+/+) and MSTN-KO (MSTN+/- and MSTN-/- inclusive) rabbits. Differentially expressed miRNAs (DEmiRNAs) were identified, and their potential target genes were predicted. Functional enrichment analysis of these target mRNAs was conducted using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) database to elucidate the involved biological pathways and regulatory networks. A total of 25 DEmiRNAs (13 downregulated and 12 upregulated, |log2FC|&#x2009;&#x2265;&#x2009;1.0, adjusted p&#x2009;<&#x2009;0.05) and 1178 differentially expressed mRNAs (408 upregulated and 770 downregulated, |log2FC|&#x2009;&#x2265;&#x2009;2.0, adjusted p&#x2009;<&#x2009;0.05) were identified in MSTN-KO compared to MSTN+/+ rabbits. Bioinformatics analysis revealed that the target genes of these DEmiRNAs were significantly enriched in key pathways governing muscle growth and metabolism, including the PI3K-Akt signaling pathway, MAPK signaling pathway, and pathways related to ECM-receptor interaction and insulin signaling. Notably, many predicted target mRNAs are expressed by genes that encode key inhibitors of myogenesis (e.g., HDAC4) and major extracellular matrix components (e.g., COL4A3, POSTN). Our results demonstrate that MSTN deficiency induces a distinct and widespread change in the miRNA expression landscape of skeletal muscle.

Animals

Unveiling novel transcriptomic prognostic biomarkers for specific breast cancer subtypes and treatment regimens.

BACKGROUND: Breast cancer (BRCA) is the most common cancer in women worldwide, yet current gene expression panels offer limited insight into treatment responses across different subtypes and therapies. This study aimed to identify reliable biomarkers for predicting treatment outcomes in specific BRCA subtypes and treatment regimens. METHODS: This study analyzed transcriptomic data from The Cancer Genome Atlas to identify differentially expressed genes (DEGs) in patient groups treated with different combinations of hormone therapy (H), chemotherapy (C), radiotherapy (R), and targeted therapy (T). Non-negative matrix factorization clustering was performed to stratify patients into clusters representing different BRCA subtypes. Functional enrichment analysis was performed, and survival assessments were conducted using the METABRIC dataset. RESULTS: A total of 1,148 DEGs were identified across treatment regimens, with 75 common DEGs shared across multiple regimens. Among these, 12 candidate biomarkers were associated with luminal subtypes treated with H, including LRP1B, of which high expression predicted cancer recurrence. In triple-negative breast cancer (TNBC) treated with C, 76 candidate biomarkers were identified, including TTYH1 for recurrence and ANXA8L1 and MPZ for non-recurrence. Functional analyses identified intermediate filament organization and keratinization as pathways associated with specific candidate biomarkers of TNBC following C. Survival analysis using METABRIC strengthened the prognostic ability of LRP1B and TTYH1 to predict worse survival and ANXA8L1 and MPZ to predict prolonged survival, with four additional prognostic biomarkers. CONCLUSION: This study identified gene expression prognostic biomarkers for luminal and TNBC subtypes, thereby supporting personalized therapies. Further experimental validation is required to confirm these findings for clinical application. CLINICAL TRIAL REGISTRY: No.

Breast cancer

Chromosome-Level Genome Assembly of Eden's Whale Clarifies the Taxonomy and Speciation of Bryde's Whale Complex.

Eden's whale (Balaenoptera edeni), a poorly understood baleen cetacean, has long been shrouded in taxonomic ambiguity due to limited genomic resources, obscuring its distinction from closely related species and its position within the cetacean Tree of Life. In this paper, we present a high-quality chromosomal-level genome of B. edeni and conduct comparative genomic analyses to address long-standing taxonomic confusion and elucidate speciation of balaenopterids. Our phylogenomic analysis and demographic reconstruction reveal that B. edeni is a distinct sister to Bryde's whale (Balaenoptera brydei), sharing a common ancestor that diverged approximately 7.84 million years ago during the late Miocene. Their genetic divergence exceeds typical intraspecific variation in whales, supporting the reinstatement of B. brydei as a valid species. Chromosomal syntenic analyses suggest that macro-fragment inversions contributed to speciation in balaenopterid whales and uncover unexpected large-scale complex genome rearrangements in Bryde's whale, offering novel insights into cetacean genome evolution. Functional enrichment analysis of inverted regions between B. edeni and Balaenoptera musculus indicates their predominant association with metabolism and biosynthesis, as well as responses to various substances, stress, and stimuli. These genomic resources for B. edeni not only lay a critical foundation for comparative genetic and evolutionary research of cetaceans but also advance our understanding of the taxonomy and evolutionary dynamics of the Bryde's whale complex, with broader implications for baleen whale conservation and biodiversity.

Animals

Zhiling Jiangya decoction treats hypertension in rats: An integrative study of network pharmacology, immune infiltration, molecular simulation, and 16S rDNA sequencing.

OBJECTIVE: This study integrated network pharmacology, immune infiltration analysis, molecular docking, molecular dynamics simulation, ADMET prediction, 16S rDNA sequencing, and rat experiments to elucidate the potential mechanisms underlying the antihypertensive effects of Zhiling Jiangya Decoction (ZLJYD). METHODS: Active compounds and their potential targets were screened from the PubChem, TCMSP, NovoPro, and SwissTargetPrediction databases. Hypertension-related targets were retrieved from the OMIM and GeneCards databases, and overlapping targets were identified. The STRING database and Cytoscape 3.10.1 software were used to construct a protein-protein interaction network and a herb-component-target-disease network. Gene Ontology functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed to identify the key biological processes and signaling pathways involved. Using the CIBERSORT algorithm combined with correlation analysis, we investigated the association between key targets and immune cell infiltration. Molecular docking, molecular dynamics simulations, and ADMET predictions were performed to assess the binding stability and pharmacokinetic properties of the main compounds with their corresponding targets. Finally, the antihypertensive efficacy of ZLJYD was validated using a spontaneously hypertensive rat model, and alterations in gut microbiota were analyzed using 16S rDNA sequencing. RESULTS: A total of 123 active compounds and 267 hypertension-related targets of ZLJYD were identified. Enrichment analysis revealed that these targets were primarily associated with the PI3K-Akt signaling pathway and lipid and atherosclerosis pathways. Immune infiltration analysis suggested that the therapeutic effects of ZLJYD may involve the regulation of follicular helper T cells, na&#xef;ve B cells, and na&#xef;ve CD4&#x207a; T cells. Molecular docking and dynamics simulations supported the stable binding of key compounds to their target proteins, while ADMET predictions indicated favorable pharmacokinetic properties and safety profiles. Rat experiments demonstrated that ZLJYD significantly reduced blood pressure in spontaneously hypertensive rats, partially alleviated gut microbiota dysbiosis, and altered microbial community structure and phylogenetic diversity. CONCLUSION: This study systematically elucidates the potential mechanisms underlying the antihypertensive effects of ZLJYD through multiple components, targets, and pathways, particularly immune regulation and gut microbiota remodeling. These findings provide mechanistic insights into its potential therapeutic application.

16S rDNA sequencing

Identification of candidate genes for reproductive traits&#xa0;in Chinese Holstein cattle using single-step genome-wide association study.

In dairy farming, reproductive efficiency is vital to both profitability and sustainability. However, years of selective breeding for increased milk yield have adversely affected reproductive potential. This study aimed to pinpoint genomic regions and identify potential candidate genes associated with reproductive traits in Chinese Holstein cattle. In this study, a single-step genome-wide association study (ssGWAS) was conducted using 33,202 phenotypic records from 16,379 animals, 55,244 pedigree records, and genomic data from 1,698 cows. These data were integrated into the ssGWAS analysis, resulting in a total pedigree structure of 21,635 animals. A total of 12 significant markers were identified for calving interval (IC), days open (DO), number of services per conception (NS), and conception rate (CR). Among these significant SNPs, three SNPs were for IC, two SNPs were for DO, three SNPs were for NS, and four SNPs were for CR. Several promising candidate genes located near these SNPs have been identified, including SFXN4, B3GAT2, GRK5, PRDX3, and MTHFD1L, highlighting their potential involvement in fertility-related biological processes. Furthermore, functional enrichment analysis identified significant enrichment of pathways associated with cell adhesion and embryonic development, suggesting a potential mechanistic role for DSG family members (DSG1, DSG2, DSG3, and DSG4) in fertility regulation. Collectively, our findings enhance understanding of the complex genetic basis of reproductive traits in dairy cattle and may offer a valuable set of genomic targets for precision breeding of Chinese Holsteins. Integrating these markers into genomic selection programs may contribute to genetic improvements in reproductive efficiency and support the long-term sustainability of dairy production.

Animals

Comprehensive analysis of circRNA-miRNA-mRNA network related to angiogenesis in recurrent implantation failure.

BACKGROUND: Abnormal endometrial blood flow causes a decrease in endometrial receptivity and is considered a relatively independent risk factor for recurrent implantation failure (RIF). This study aimed to explore the potentially functional circRNA-miRNA-mRNA network in RIF, and further explore its mechanism. METHODS: Datasets were downloaded from the GEO database to identify differentially expressed circRNAs, miRNAs and mRNAs. The circRNA-miRNA-mRNA and PPI networks were constructed using Cytoscape 3.6.0 and the STRING database, the hub genes were identified with the cytoHubba plug-in, and a circRNA-miRNA-hub mRNA regulatory sub-network was constructed. Then, GO and KEGG pathway enrichment analyses of the hub genes were performed to comprehensively analyze the mechanism of hub mRNAs in RIF. Due to the results of circRNAs-miRNAs-hub mRNAs regulatory network, we verified the expression of circRNA_0001721, circRNA_0000714, miR-17-5p, miR-29b-3p, HIF1A and VEGFA in the RIF mouse model by qRT&#x2012;PCR and western blotting. RESULTS: We initially identified 175 DEmRNAs, 48 DEmiRNAs and 56 DEcircRNAs in RIF associated with angiogenesis and constructed a circRNA-miRNA&#x2012;mRNA network and PPI network. We further identified six hub genes in the acquired network. Based on these genes, functional enrichment analysis revealed that the HIF-1 signaling pathway plays a vital role in endometrial angiogenesis in RIF. In addition, the interaction networks of circRNA_0001721/miR-17-5p/HIF1A and the circRNA_0000714/miR-29b-3p/VEGFA axis were predicted. In the RIF mouse model, circRNA_0001721, circRNA_0000714, HIF1A and VEGFA were down-regulated, whereas miR-17-5p and miR-29b-3p were up-regulated according to qRT&#x2012;PCR and western blotting. CONCLUSION: This study revealed that the HIF-1 signaling pathway plays a vital role in endometrial angiogenesis in RIF. The circRNA_0001721/miR-17-5p/HIF1A and circRNA_0000714/miR-29b-3p/VEGFA axes might play a role in the pathogenesis of endometrial angiogenesis in RIF.

MicroRNAs

Bidirectional causal relationships between plasma proteins, neuroimaging metrics and risk of Alzheimer's disease.

BACKGROUND: Changes in neuroimaging metrics are among the first detectable pathophysiological alterations in Alzheimer's disease (AD). Proteins are closely linked to fluctuations in neuroimaging metrics. Therefore, the analysis of the proteomic signature associated with neuroimaging metrics holds significant promise for uncovering therapeutic targets that contribute to AD. METHODS: GWAS data concerning the Brain Imaging Data Structure (BIDs). The AD cohort comprised a total of 401,661 individuals diagnosed with AD, alongside 10,520 control participants. For a bidirectional MR analysis involving neuroimaging metrics, proteomics, and AD, the methods utilized included inverse variance weighted (IVW), MR Egger, weighted median, weighted mode, and the Wald ratio approaches. RESULTS: We identified 12 neuroimaging metrics that demonstrate significant relevance to AD (thickness of the left total hemisphere, volume of the right thalamus, and et al.). These metrics are structural magnetic resonance imaging (MRI) biomarkers that remain stable throughout the entire course of AD, from the preclinical stage through mild cognitive impairment (MCI) to dementia. Additionally, we found a substantial number of 1633 proteins that also show a noteworthy causal relationship with AD. Functional enrichment analysis indicated that these proteins were predominantly focused within various pathways linked to AD, encompassing those involved in the synaptic vesicle cycle, synaptic membranes, neurotransmitter release, and the activity of GABA receptors. In addition, our research indicates that the significant relationships observed between the identified proteins and AD are influenced by neuroimaging metrics. Notably, we found that these neuroimaging metrics play a crucial role in mediating a substantial 67% of the inverse relationship that exists between PTPRC and the phenotypic characteristics associated with AD. CONCLUSIONS: This study successfully establishes a connection between proteomic and neuroimaging metrics, as well as the AD that influence them. By creating this relationship, the research offers important information that aids in comprehending the intricate mechanisms involved in AD.

Alzheimer Disease

Integrative proteomic analysis provides novel therapeutic insights for etiological subtypes of diabetes.

AIMS: Type 2 diabetes (T2D) is a highly heterogeneous disease characterised by subtypes with variations in aetiology, disease progression, and risk of complications. However, potential drug targets for these subtypes have not been explored. This study aims to investigate potential drug targets by integrating proteomics. MATERIALS AND METHODS: Summary-level data of circulating proteins were extracted from the UK Biobank and the deCODE Health Study. Genetic associations with five diabetes subtypes were obtained from Swedish All New Diabetics in Scania and Malm&#xf6; Diet and Cancer cohort, including severe autoimmune diabetes (SAID), severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD), and mild age-related diabetes (MARD). The associations between circulating proteins and diabetes subtypes were assessed through Mendelian randomisation, followed by multiple sensitivity and colocalization analyses. Additionally, tissue-specific, pathway and functional enrichment analysis, assessment of protein druggability, and the protein-protein interaction (PPI) networks were used to further explore biological mechanisms and therapeutic potential. RESULTS: Genetically predicted levels of 2, 2, 9, 3, and 5 circulating proteins were associated with SIRD, SIDD, MARD, MOD, and SAID, respectively. Colocalization analyses further revealed links between GRN with MARD/SIRD, LILRB5 with SIDD/MARD, CR1 with MARD, TNFSF12 with MOD, and DAPK2 with SAID. Enrichment analysis suggested that these proteins were mainly enriched in blood and adipose tissues and involved in immune and inflammatory related pathways. PPI analysis revealed GRN, TNFSF12, and DAPK2 are associated with known T2D targets. CONCLUSIONS: Our study identified several potential drug targets for different subtypes of diabetes using an integrated genetic approach, yielding new insights for precision medicine of diabetes.

Humans

TNF&#x3b1;-induced endothelial extracellular vesicles regulate astrocyte function: an integrated transcriptomic and proteomic study.

Endothelial cells and astrocytes are critical structural and functional components of the blood-brain barrier. In many neuroinflammatory diseases, endothelial cells are among the first to respond to inflammatory stimuli and release extracellular vesicles (EVs). However, whether inflammatory stimulation alters EV RNA cargo and subsequently regulates astrocyte function remains unclear. In this study, we performed integrated RNA sequencing and proteomic analyses to investigate the effects of TNF&#x3b1;-stimulated endothelial EVs on astrocytes. RNA profiling revealed significant alterations in EV cargo after TNF&#x3b1; stimulation, including 867 upregulated and 577 downregulated mRNAs, 317 upregulated and 15 downregulated lncRNAs, and 88 upregulated and 62 downregulated miRNAs. The results of functional enrichment analysis suggested that altered EV RNAs may primarily promote inflammatory responses, cell migration, and RNA splicing in astrocytes while reducing their regulatory effects on neuronal projection and calcium homeostasis. Further integrative analysis of EV RNAs and astrocytic proteomics revealed key overlapping targets, including upregulated expression of ICAM1, SOD2, TFPI2, and TNFAIP8, whereas NFKBIA expression was consistently decreased. Network analysis revealed NF-&#x3ba;B as the central regulatory node. Reduced levels of EV-derived NFKBIA mRNA were associated with decreased I&#x3ba;B&#x3b1; protein levels in astrocytes, which promoted NF-&#x3ba;B activation and inflammatory cytokine release. Finally, overexpression of I&#x3ba;B&#x3b1; in astrocytes significantly attenuated TNF&#x3b1; EV-induced IL-1&#x3b2; and IL-6 secretion. Collectively, these findings demonstrate that TNF&#x3b1;-stimulated endothelial EVs coordinately regulate astrocyte function through mRNA, lncRNA, and miRNA cargo and that the I&#x3ba;B&#x3b1;/NF-&#x3ba;B axis may be a key mechanism underlying endothelial EV-mediated inflammatory disruption of the blood-brain barrier.

Astrocytes

Proteomic profiling identifies miR-423-5p as a modulator of oncogenic metabolism in HCC.

BACKGROUND: Hepatocellular carcinoma (HCC) remains a significant clinical challenge due to limited diagnostic and therapeutic options. Non-coding RNAs (ncRNAs), such as microRNAs (miRNAs), play key roles in cancer biology. Our previous findings showed that miR-423-5p enhances anti-cancer effects on HCC patients treated with sorafenib by promoting autophagy. Here, we investigated the molecular mechanisms underlying miR-423-5p function through a comprehensive proteomic approach. METHODS: We generated an HCC cell line stably overexpressing miR-423-5p via lentiviral transduction. Total proteins were extracted from SNU-387 cells, enzymatically digested into peptides, and subsequently analysed by liquid chromatography-tandem mass spectrometry (LC-MS/M). Raw spectral data were processed and quantified using MaxQuant. Differentially expressed proteins (DEPs) were defined based on fold-change (|log2FC| &#x2265; 1) and false discovery rate (FDR < 0.05). The full proteomic dataset is available via the ProteomeXchange repository (identifier: PXD064869). Functional enrichment analysis of DEPs were performed using DAVID and Reactome. To assess clinical relevance, predicted and validated miR-423-5p targets were integrated with The Cancer Genome Atlas (TCGA) Liver Hepatocellular Carcinoma (LIHC) dataset using GEPIA platform. Survival analyses were performed using the Kaplan-Meier method. RESULTS: Proteomic profiling identified 698 DEPs in miR-423-5p-overexpressing cells compared to controls with significant enrichment in metabolic pathways, related to purine/pyrimidine metabolism and gluconeogenesis. Integration with bioinformatic predictions and miRTarBase validation identified 43 DEPs as potential direct targets of miR-423-5p. Among these, seven proteins (ACACA, ANKRD52, DVL3, MCM5, MCM7, RRM2, SPNS1, and SRM) were significantly associated with patient prognosis in the TCGA-LIHC cohort. These targets were downregulated in miR-423-5p-overexpressing cells but upregulated in advanced-stage HCC tissues, suggesting a potential role for miR-423-5p in the regulation of HCC pathogenesis. Stage-specific expression analysis showed increased levels from stage I to III, followed by a decline at stage IV. Notably, we experimentally confirmed miR-423-5p-mediated suppression of MCM7, DVL3, IMPDH1, and SRM (SPEE), supporting their functional involvement in HCC progression. CONCLUSION: Overall, our findings support a tumour-suppressive role for miR-423-5p in HCC, mediated by modulation of metabolic pathways and suppression of oncogenic proteins. These results suggest that miR-423-5p and its downstream effectors may serve as promising biomarkers and potential therapeutic targets in HCC. HIGHLIGHTS: miR-423-5p acts as a tumor suppressor in HCC by targeting key nodes of pro-tumorigenic signalling. miR-423-5p significantly altered metabolic pathways, including purine/pyrimidine metabolism and gluconeogenesis. Seven miR-423-5p targets correlate with poor prognosis in TCGA-LIHC patients and are downregulated in miR-423-5p overexpressing HCC cells. miR-423-5p over-expression induces a significant downregulation of MCM7, DVL3, IMPDH1, SPEE in HCC cell models. miR-423-5p limits tumor metabolic plasticity, suggesting therapeutic potential.

MicroRNAs

Elucidating the In&#xa0;Vitro Adverse Effect of Functionalized Single-Walled Carbon Nanotubes Against Breast Cancer Cells at the Proteomics Level.

The tremendous therapeutic potential of carbon-based nanomaterials (CNMs) has been limited by inconsistent data regarding the nanotoxicity assessment. Although a bulk of studies have been performed to assess the in&#xa0;vitro cytotoxicity mechanism of CNMs, the exact factors responsible for the cytotoxicity of CNMs have not been fully understood. With the rapid advancement of mass spectrometry technologies, proteomics has emerged as a powerful strategy for systematically investigating the molecular and cellular mechanisms underlying toxicity induced by nanomaterials. This study examined the in&#xa0;vitro cytotoxicity of single-walled carbon nanotubes (SWCNTs) in human MCF-7 breast cancer cells by conducting a comparative proteome-level analysis using mass spectrometry. Initially, the characterized SWCNTs were incubated with MCF-7 cells for 3, 6, and 24&#x2009;h. Proteins were subsequently extracted from each treatment group and subjected to nano-liquid chromatography-tandem mass spectrometry (nLC-MS/MS) analysis. The relative abundance of the identified proteins was determined by comparison with the control group, and differential expression patterns, including upregulated and downregulated proteins, were assessed. A total of 3482 unique protein groups were identified across all exposure periods. Among these, 3466 protein groups were detected following 3&#x2009;h of exposure, 3469 following 6&#x2009;h of exposure, and 3480 following 24&#x2009;h of exposure. Compared with the control group, the identified differentially expressed proteins exhibited fold changes ranging from 2-fold to 20-fold across the incubation periods. In total, 70 proteins were found to be significantly regulated following SWCNT exposure. Of the differentially expressed proteins, 45 were significantly upregulated, whereas 25 were significantly downregulated. Visualization of these regulations over time was shown in a heatmap of log2-transformed fold-change values to explore time-specific proteomic alterations. Functional enrichment analysis of these proteins also showed that the regulated proteins were significantly associated with Reactome pathways, including ER-to-Golgi anterograde transport, Golgi-to-ER retrograde transport, COPI-mediated vesicle trafficking, regulation of insulin-like growth factor transport and uptake by insulin-like growth factor-binding proteins, protein metabolism, and posttranslational protein modification. Furthermore, a systematic comparison of previous studies within the present findings was provided to situate our study within the broader context of understanding CNT-induced cellular toxicity. Collectively, these findings provided an important proteomic evidence of the adverse effects of SWCNTs on MCF-7 cells. Furthermore, this study showed a comprehensive proteomic landscape of cellular responses to SWCNT exposure, contributing to a better understanding of the molecular mechanisms underlying SWCNT-induced cytotoxicity and bridging the gap between protein regulation and the resulting cellular responses. In this study, we characterized the proteomic landscape of MCF-7 cells following SWCNT exposure, revealing molecular mechanisms associated with cellular responses and cytotoxicity. The identified differentially expressed proteins established a link between altered protein regulation and SWCNT-induced cellular effects. Moreover, these proteins need to be further validated in different cell models and would potentially represent promising candidates for the identification of novel molecular targets involved in SWCNT-induced cytotoxicity.

MCF&#x2010;7 cells

Transcriptomic insights into the coordinated regulation of signaling, apoptosis, immunity, and metabolism during Sinonovacula constricta larval metamorphosis.

Metamorphosis is a critical ontogenetic transition for marine bivalves, marking the shift from planktonic to benthic lifestyles, where successful transformation dictates survival. The razor clam Sinonovacula constricta is economically important; however, low larval metamorphosis rates remain a major bottleneck in seedling production. To elucidate the mechanisms governing this process, we performed a comparative transcriptome analysis of S. constricta larvae at pre- and post-metamorphosis stages using Illumina sequencing. A total of 3701 differentially expressed genes (DEGs) were identified, including 3254 up-regulated and 447 down-regulated genes. Functional annotation of the respective top 20 significantly up-regulated and down-regulated DEGs indicated their potential pivotal roles in signal transduction (e.g., up-regulated: CAV1, CHRNA2; down-regulated: APP, NOTCH1), cellular proliferation and differentiation (e.g., up-regulated: TUBA, EGF1; down-regulated: KIF23, TTC25), transcriptional and epigenetic regulation (e.g., up-regulated: NFIL3; down-regulated: OVO, HMX1), substance transport (e.g., up-regulated: LRP2, LRP1B; down-regulated: SLC51A, Slc33a1), substance metabolism (e.g., up-regulated: CPK3, CYP26A1; down-regulated: RDMT1, ADAC), immunomodulation (e.g., up-regulated: CPN2, CRISP2), and protein homeostasis (e.g., up-regulated: HSP27, NAS-27). Functional enrichment analysis further revealed that DEGs were significantly enriched in pathways related to signal transduction and developmental regulation (e.g., Ras, TNF), cell death and homeostasis (e.g., apoptosis), immune responses (e.g., Toll-like receptor), energy metabolism (e.g., lipid), cardiovascular related (e.g., Fluid shear stress), cell junction and architecture (e.g., Tight junction), and infectious disease (e.g., measles). These results suggest a synergistic interplay between signaling, apoptosis, immunity, and metabolism during S. constricta metamorphosis. This study advances our understanding of marine bivalve metamorphosis and offers candidate genes for further mechanistic studies.

Animals