Search Results (417)

Moyamoya disease (MMD) is primarily associated with genetic variants in RNF213. RNF213 p.R4810K (c.14429G>A, p.Arg4810Lys) is a founder variant predominantly found in East Asian populations and is strongly associated with MMD, a rare cerebrovascular condition characterized by progressive stenosis of intracranial arteries and the development of abnormal collateral networks. Recent evidence suggests that RNF213 variants are also enriched in non-moyamoya intracranial arteriopathies, such as large-artery atherosclerotic stroke and intracranial arterial stenosis/occlusion (ICASO), particularly in east Asian individuals with early-onset or cryptogenic stroke. This expanded phenotypic spectrum, termed RNF213-related vasculopathy (RRV), represents a distinct pathogenic entity that may involve unique pathogenic processes separate from traditional atherosclerosis. In this review, we synthesize current genetic, clinical, radiological, and experimental findings that delineate the unique features of RRV. Patients with RRV typically exhibit a lower burden of traditional vascular risk factors, negative vascular remodeling in the absence of atheromatous plaques, and an increased propensity for disease progression. RNF213 variants may compromise vascular resilience by impairing adaptive responses to hemodynamic stress. Furthermore, emerging cellular and animal model data indicate that RNF213 influences angiogenesis, lipid metabolism, and stress responses, offering mechanistic insights into its role in maintaining vascular integrity. Recognizing RRV as a distinct clinical entity has important implications for diagnosis, risk stratification, and the development of genome-informed therapeutic strategies. Full article

Pediatric asthma is a multifactorial and heterogeneous disease determined by the dynamic interplay of genetic susceptibility, environmental exposures, and immune dysregulation. Recent advances have highlighted the pivotal role of epigenetic mechanisms, in particular, DNA methylation, histone modifications, and non-coding RNAs, in the regulation of inflammatory pathways contributing to asthma phenotypes and endotypes. This review examines the role of respiratory viruses such as respiratory syncytial virus (RSV), rhinovirus (RV), and other bacterial and fungal infections that are mediators of infection-induced epithelial inflammation that drive epithelial homeostatic imbalance and induce persistent epigenetic alterations. These alterations lead to immune dysregulation, remodeling of the airways, and resistance to corticosteroids. A focused analysis of T2-high and T2-low asthma endotypes highlights unique epigenetic landscapes directing cytokines and cellular recruitment and thereby supports phenotype-specific aspects of disease pathogenesis. Additionally, this review also considers the role of miRNAs in the control of post-transcriptional networks that are pivotal in asthma exacerbation and the severity of the disease. We discuss novel and emerging epigenetic therapies, such as DNA methyltransferase inhibitors, histone deacetylase inhibitors, miRNA-based treatments, and immunomodulatory probiotics, that are in preclinical or early clinical development and may support precision medicine in asthma. Collectively, the current findings highlight the translational relevance of including pathogen-related biomarkers and epigenomic data for stratifying pediatric asthma patients and for the personalization of therapeutic regimens. Epigenetic dysregulation has emerged as a novel and potentially transformative approach for mitigating chronic inflammation and long-term morbidity in children with asthma. Full article

The perianal skin is a unique “skin–gut” boundary that serves as a critical hotspot for the exchange and evolution of antibiotic resistance genes (ARGs). However, its role in the dissemination of antimicrobial resistance (AMR) has often been underestimated. To characterize the resistance patterns in the perianal skin environment of patients with perianal diseases and to investigate the drivers of AMR in this niche, a total of 51 bacterial isolates were selected from a historical strain bank containing isolates originally collected from patients with perianal diseases. All the isolates originated from the skin site and were subjected to antimicrobial susceptibility testing, whole-genome sequencing, and co-occurrence network analysis. The analysis revealed a highly structured resistance pattern, dominated by two distinct modules: one representing a classic Staphylococcal resistance platform centered around mecA and the bla operon, and a broad-spectrum multidrug resistance module in Gram-negative bacteria centered around tet(A) and predominantly carried by IncFIB and other IncF family plasmids. Further analysis pinpointed IncFIB-type plasmids as potent vehicles driving the efficient dissemination of the latter resistance module. Moreover, numerous unexplained resistance phenotypes were observed in a subset of isolates, indicating the potential presence of emerging and uncharacterized AMR threats. These findings establish the perianal skin as a complex reservoir of multidrug resistance genes and a hub for mobile genetic element exchange, highlighting the necessity of enhanced surveillance and targeted interventions in this clinically important ecological niche. Full article

Haploinsufficiency disorders are genetic diseases caused by reduced gene expression, leading to developmental, metabolic, and tumorigenic abnormalities. The dosage-sensitive Retinoic Acid Induced 1 (RAI1) gene, located within the 17p11.2 region, is central to the core features of Smith––Magenis syndrome (SMS) and Potocki––Lupski syndrome (PTLS), caused by the reciprocal microdeletions and microduplications of this region, respectively. SMS and PTLS present contrasting phenotypes. SMS is characterized by severe neurobehavioral manifestations, sleep disturbances, and metabolic abnormalities, and PTLS shows milder features. Here, we detail the molecular functions of RAI1 in its wild-type and haploinsufficiency conditions (RAI1+/−), as studied in animal and cellular models. RAI1 acts as a transcription factor critical for neurodevelopment and synaptic plasticity, a chromatin remodeler within the Histone 3 Lysine 4 (H3K4) writer complex, and a regulator of faulty 5′-capped pre-mRNA degradation. Alterations of RAI1 functions lead to synaptic scaling and transcriptional dysregulation in neural networks. This review highlights key molecular mechanisms of RAI1, elucidating its role in the interplay between genetics and phenotypic features and summarizes innovative therapeutic approaches for SMS. These data provide a foundation for potential therapeutic strategies targeting RAI1, its mRNA products, or downstream pathways. Full article

Background/Objectives: Degenerative joint diseases (DJDs) involve intricate molecular disruptions within bone, cartilage, and synovial tissues, often preceding overt radiographic changes. These tissues exhibit complex biomolecular architectures and their degeneration leads to microstructural disorganization and inflammation that are challenging to detect with conventional imaging techniques. This review aims to synthesize recent advances in imaging, computational modeling, and sequencing technologies that enable high-resolution, non-invasive characterization of joint tissue health. Methods: We examined advanced modalities including high-resolution MRI (e.g., T1ρ, sodium MRI), quantitative and dual-energy CT (qCT, DECT), and ultrasound elastography, integrating them with radiomics, deep learning, and multi-scale modeling approaches. We also evaluated RNA-seq, spatial transcriptomics, and mass spectrometry-based proteomics for omics-guided imaging biomarker discovery. Results: Emerging technologies now permit detailed visualization of proteoglycan content, collagen integrity, mineralization patterns, and inflammatory microenvironments. Computational frameworks ranging from convolutional neural networks to finite element and agent-based models enhance diagnostic granularity. Multi-omics integration links imaging phenotypes to gene and protein expression, enabling predictive modeling of tissue remodeling, risk stratification, and personalized therapy planning. Conclusions: The convergence of imaging, AI, and molecular profiling is transforming musculoskeletal diagnostics. These synergistic platforms enable early detection, multi-parametric tissue assessment, and targeted intervention. Widespread clinical integration requires robust data infrastructure, regulatory compliance, and physician education, but offers a pathway toward precision musculoskeletal care. Full article

Abdominal aortic aneurysm (AAA) is the most common aortic disease occurring below the renal arteries, caused by multiple etiologies. Currently, no effective drug treatment exists, and the specific pathogenesis remains unclear. Due to its insidious onset and diagnostic challenges, AAA often culminates in aortic rupture, which has a high mortality rate. During AAA development, vascular smooth muscle cells (VSMCs) undergo significant pathological alterations, including contractile dysfunction, phenotypic modulation, cellular degradation, and heightened inflammatory and oxidative stress responses. In particular, emerging evidence implicates vascular smooth muscle cell (VSMC) metabolic dysregulation and mitochondrial dysfunction as key contributors to AAA progression. In this review, we systematically summarize the current understanding of VSMC biology, including their developmental origins, structural characteristics, and functional roles in aortic wall homeostasis, along with the regulatory networks governing the VSMC phenotype and functional maintenance. This review highlights the urgent need for further investigation into the aortic wall VSMC pathophysiology to identify novel therapeutic targets for AAA. These insights may pave the way for innovative treatment strategies in aortic disease management. Full article

Dominant Optic Atrophy (DOA) is the most common inherited optic neuropathy and presents as gradual visual loss caused by the loss of retinal ganglion cells (RGCs). Over 60% of DOA cases are caused by pathogenic variants in the OPA1 gene, which encodes a mitochondrial GTPase essential in mitochondrial fusion. Currently, there are no treatments for DOA. Here, we tested the therapeutic potential of an approach to DOA using CRISPR activation (CRISPRa). Homology directed repair was used to introduce a common OPA1 pathogenic variant (c.2708_2711TTAGdel) into HEK293T cells as an in vitro model of DOA. Heterozygous c.2708_2711TTAGdel cells had reduced levels of OPA1 mRNA transcript, OPA1 protein, and mitochondrial network alterations. The effect of inactivated Cas9 fused to an activator (dCas9–VPR) was tested with a range of guide RNAs (gRNA) targeted to the promotor region of OPA1. gRNA3 and dCas9–VPR increased OPA1 expression at the RNA and protein level towards control levels. Importantly, the correct ratio of OPA1 isoform transcripts was maintained by CRISPRa. CRISPRa-treated cells showed an improvement in mitochondrial networks compared to untreated cells, indicating partial rescue of a disease-associated phenotype. Collectively, these data support the potential application of CRISPRa as a therapeutic intervention in DOA. Full article

Artificial intelligence and bioacoustics represent a paradigm shift in non-invasive poultry welfare monitoring through advanced vocalization analysis. This comprehensive systematic review critically examines the transformative evolution from traditional acoustic feature extraction—including Mel-Frequency Cepstral Coefficients (MFCCs), spectral entropy, and spectrograms—to cutting-edge deep learning architectures encompassing Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, attention mechanisms, and groundbreaking self-supervised models such as wav2vec2 and Whisper. The investigation reveals compelling evidence for edge computing deployment via TinyML frameworks, addressing critical scalability challenges in commercial poultry environments characterized by acoustic complexity and computational constraints. Advanced applications spanning emotion recognition, disease detection, and behavioral phenotyping demonstrate unprecedented potential for real-time welfare assessment. Through rigorous bibliometric co-occurrence mapping and thematic clustering analysis, this review exposes persistent methodological bottlenecks: dataset standardization deficits, evaluation protocol inconsistencies, and algorithmic interpretability limitations. Critical knowledge gaps emerge in cross-species domain generalization and contextual acoustic adaptation, demanding urgent research prioritization. The findings underscore explainable AI integration as essential for establishing stakeholder trust and regulatory compliance in automated welfare monitoring systems. This synthesis positions acoustic AI as a cornerstone technology enabling ethical, transparent, and scientifically robust precision livestock farming, bridging computational innovation with biological relevance for sustainable poultry production systems. Future research directions emphasize multi-modal sensor integration, standardized evaluation frameworks, and domain-adaptive models capable of generalizing across diverse poultry breeds, housing conditions, and environmental contexts while maintaining interpretability for practical farm deployment. Full article

Background: Deficiency of IL-36 Receptor Antagonist (DITRA) is a rare monogenic autoinflammatory disease, characterized by dysregulation of IL-36 signaling and phenotypically classified as a subtype of generalized pustular psoriasis. Objectives: This study aimed to explore the role of potentially coding and non-coding RNAs (ncRNAs) in the IL36RN interactome to identify putative pathogenic mechanisms, biomarkers, and therapeutic targets for DITRA. Methods: A systems biology approach was applied using the STRING database to construct the IL36RN protein–protein interaction network. Key ncRNA interactions were identified using RNAInter. The networks were visualized and analyzed with Cytoscape v3 and the CytoHubba plugin to identify central nodes and interaction hubs. Pathway enrichment analysis was then performed to determine the biological relevance of candidate ncRNAs and genes. Results: Analysis identified thirty-eight ncRNAs interacting with the IL36RN network, including six lncRNAs and thirty-two miRNAs. Of these, thirty-three were associated with key DITRA-related signaling pathways, while five remain to be validated. Additionally, seven protein-coding genes were highlighted, with three (TINCR, PLEKHA1, and HNF4A) directly implicated in biological pathways related to DITRA. Many of the identified ncRNAs have prior associations with immune-mediated diseases, including psoriasis, supporting their potential relevance in DITRA pathogenesis. Conclusions: This study provides novel insights into the ncRNA-mediated regulation of IL36RN and its network in the context of DITRA. The findings support the potential utility of specific ncRNAs and genes, such as TINCR, PLEKHA1, and HNF4A, as key genomic elements warrant further functional characterization to confirm their mechanistic roles and may inform biomarker discovery and targeted therapeutic development in DITRA. Full article

Background/Objectives: Studying protein–protein interaction (PPI) networks is crucial in understanding cancer phenotypes and molecular mechanisms. Here, we focus on PPIs involved in 12 different types of cancer (oncoPPIs), highlighting those protein pockets serving as outposts to modulate protein functioning. Methods: To explore these cavities linked to the cancer phenotype changes, we built a comprehensive pocketome of 314 crystallographically solved oncoPPIs. Based on this experimental data, we identified and investigated all ligandable protein pockets by employing 3D geometric and energetic descriptors. These pockets were classified as suitable for designing new oncoPPI modulators or PROTACs. The ligand-bound crystallographic pockets were analyzed to compare their properties across cancer types. Finally, 3D oncoPPI networks were built for each cancer type to identify highly connected proteins acting as hubs. Results: Combining interaction networks with structural pocket data helps identify cancer-relevant proteins and key interacting residues. Using this approach, we present clinical examples (e.g., S100A1, NRP1, CTNNB1, VCP) to show the therapeutic value of targeting ligandable 3D oncoPPIs. We also provide a publicly available reference dataset supporting future research. Conclusions: Notably, this study offers a flexible framework for evaluating and prioritizing novel disease targets. Full article

Network-based GWAS (NetWAS) has advanced brain imaging research by identifying genetic modules associated with brain alterations. However, how imaging risk genes exert functions in brain diseases, particularly their mediation through imaging quantitative traits (iQTs), remains underexplored. We propose a module-level polygenic risk score (MPRS)-based NetWAS framework to uncover genetic modules associated with Alzheimer’s disease (AD) through the mediation of an iQT, using amygdala density as a case study. Our framework integrates genotype data, brain imaging phenotypes, clinical diagnosis of AD, and protein–protein interaction (PPI) networks to identify AD-relevant modules (ADMs) influenced by iQT-associated genetic variants. Specifically, we conducted a genome-wide association study (GWAS) of amygdala density ($N=1515$) to identify variants associated with iQT. These variants were mapped onto a PPI network and network propagation was performed to prompt amygdala modules. The meta-GWAS of AD ($N_1=63,926$; $N_2=455,267$) was used to calculate MPRS to further identify AD-relevant modules (ADMs). Four modules that showed significant differences in MPRS between AD and controls were identified as ADM. Post-hoc analyses revealed that these ADMs demonstrated strong modularity, showed increased sensitivity to early stages of AD, and significantly mediated the link between ADMs and AD progression through the amygdala. Furthermore, these modules exhibited high tissue specificity within the amygdala and were enriched in AD-related biological pathways. Our MPRS-based framework bridges genetics, intermediate traits, and clinical outcomes and can be adapted for broader biomedical applications. Full article

Salmonella infection poses a serious threat to the poultry industry, causing significant economic losses. Under global warming conditions, the underlying molecular mechanisms by which heat stress affects bacterial infections in poultry remain unclear. This study conducted a Salmonella Typhimurium infection under heat stress in Guang Ming broilers. A total of 100 chickens were randomly divided into three groups: control group (CTL), Salmonella Typhimurium (ST) infection group, and heat stress and Salmonella Typhimurium (HS + ST) co-stimulation group. By integrating inflammatory phenotypes, liver transcriptome profiles, and weighted gene co-expression network analysis (WGCNA), we systematically investigated the key regulatory factors through which heat stress affects host susceptibility to Salmonella. The results demonstrated that heat stress reduced body weight gain, exacerbated Salmonella Typhimurium-induced inflammatory responses, and increased mortality. Transcriptome results revealed that heat stress led to excessive inflammatory responses and antioxidant defense imbalances. Combined differential expression analysis and WGCNA identified three hub regulatory genes: PTGDS and WISP2 showed significant correlations with the heterophil/lymphocyte ratio, while SLC6A9 was significantly correlated with serum IL-8 levels. Validation in HD11 cell infection models confirmed the differential expression of these genes under heat stress and Salmonella Typhimurium co-stimulation, indicating their critical roles in host immune regulation. This study elucidates the intrinsic regulatory relationships through which heat stress promotes Salmonella pathogenicity and inflammatory responses, providing important insights for disease-resistant poultry breeding and prevention strategies. Full article

Pepper anthracnose is a globally devastating fungal disease caused by Colletotrichum spp. In this study, we explored the molecular mechanisms underlying anthracnose resistance in Capsicum annuum by comparing a resistant variety 225 with a susceptible variety 307. Phenotypic analysis revealed that variety 225 displayed stronger resistance than variety 307. Through comparative transcriptome analysis and weighted gene co-expression network analysis (WGCNA), 17 gene modules were identified, among which the salmon module showed a strong association with resistance in variety 225. Within this module, 18 hub genes—including Ca59V2g00372.1 (CaTLP6), encoding a thaumatin-like protein (TLP)—were significantly upregulated upon infection. A genome-wide analysis identified 31 CaTLP genes in C. annuum, with members of group V (such as CaTLP6) exhibiting induced expression post-inoculation of Colletotrichum scovillei. Subcellular localization analysis indicated that group V CaTLP proteins were associated with the plasma membrane, suggesting a role in pathogen recognition. These findings highlight the significance of CaTLP genes, particularly those in group V, in pepper’s defense against anthracnose caused by C. scovillei and offer promising targets for breeding resistant cultivars. Full article

Rapid and accurate identification of pathogenic bacteria phenotypic traits, including virulence, drug resistance, and metabolic activity, is essential for clinical diagnosis and infectious disease control. Traditional methods are time-consuming, highlighting the need for more efficient approaches. This study develops a single-cell Raman spectroscopy approach to detect multiple phenotypic traits of Staphylococcus aureus (S. aureus) as a proof of concept. We constructed a single-cell Raman spectral database encompassing 6240 spectra from 10 strains of S. aureus with diverse phenotypic traits and developed a convolutional neural network (CNN) to predict these phenotypes from the Raman spectra. The CNN model achieved 93.90%, 98.73%, and 98.66% accuracy in identifying enterotoxin-producing strains, methicillin-resistant S. aureus (MRSA), and growth stages, respectively. Characteristic Raman peaks for enterotoxin producers mainly appeared at 781, 939, 1161, 1337, 1451, and 1524 cm⁻¹, whereas MRSA primarily exhibited peaks at 723, 780, 939, 1095, 1162, 1340, 1451, 1523, and 1660 cm⁻¹. During culture, nucleic acid-related peaks weakened, lipid peaks increased, and protein peaks initially increased and subsequently decreased. This integration of Raman spectroscopy and machine learning demonstrates considerable potential for rapid bacterial phenotyping. Future research should expand to a wider range of bacterial species and phenotypes to enhance the diagnosis, prevention, and management of infectious diseases. Full article

Background/Objectives: Sweet taste receptor TAS1R2 is expressed in skeletal muscle, yet its role in muscle metabolism remains poorly understood. Methods: Here, we leverage the BXD recombinant inbred mouse panel and Tas1r2 whole-body knockout (bKO) models to investigate the transcriptional impact of Tas1r2 deficiency on skeletal muscle function. Results: A gene network analysis revealed significant overlap in transcriptomic signatures between BXD strains with low Tas1r2 expression (BXD L_Tas1r2) and bKO muscle, particularly in pathways regulating oxidative phosphorylation, cytoplasmic ribosome function, and proteostasis. Notably, Tas1r2 expression negatively correlated with genes involved in fatty acid metabolism, suggesting its role in lipid utilization. Under high-fat diet (HFD) conditions, BXD_HFD L_Tas1r2 mice exhibited further enrichment in pathways linked to proteasome degradation, oxidative stress, and interleukin signaling, amplifying the transcriptomic convergence with bKO models. Key transcription factors (Mlxipl, Nfic, Rxrb) exhibited altered regulatory patterns under dietary stress, indicating that TAS1R2 influences metabolic adaptability through transcriptional reprogramming. Conclusions: Given that human TAS1R2 variants rarely result in complete loss of function (LOF), the BXD panel provides an effective dose-dependent model to bridge the gap between knockout phenotypes and human SNP carriers. Our findings establish TAS1R2 as a metabolic regulator in skeletal muscle and highlight the utility of genetically diverse mouse populations in dissecting gene-diet interactions relevant to human metabolic diseases. Full article