Search Results (2,355)

The gut microbiome, often termed the human “second genome”, profoundly influences host physiology through metabolic interactions, immune modulation, and gut–brain axis signaling. Dysbiosis is implicated in the pathogenesis of obesity, inflammatory bowel disease (IBD), malignancies, and neuropsychiatric disorders. However, traditional gut microbiota interventions, such as probiotic supplementation and fecal microbiota transplantation (FMT), still exhibit significant limitations in precision therapeutics. Probiotic intervention fails to achieve precise regulation at the strain or genetic level, and although FMT demonstrates definitive efficacy against recurrent Clostridioides difficile infection (rCDI), its therapeutic outcomes and safety profiles show marked interindividual variability in ulcerative colitis (UC), metabolic syndrome, and other diseases, with insufficient treatment specificity to meet the practical demands of clinical precision intervention. Recent advancements in genome editing technologies, particularly Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)–CRISPR-associated (Cas) proteins systems and base editors, have enabled targeted functional manipulation of specific gut commensals and optimization of community architectures. These engineered strategies, combined with sophisticated delivery systems, demonstrate substantial potential in disease treatment, diagnostic monitoring, and immune modulation. This review systematically examines core editing methodologies, innovative delivery platforms, and targeted design strategies, elucidating their applications in metabolic disorders, IBD, cancer immunotherapy, and neuropsychiatric conditions. We critically analyze current technical bottlenecks and biosafety concerns while prospecting future directions, including in situ editing, artificial intelligence (AI)-driven design, and personalized engineering. Collectively, these insights aim to facilitate the clinical translation of gut microbiome engineering from bench to bedside. Full article

Background: Although emerging evidence indicates that major depressive disorder (MDD) raises the risk of developing ovarian cancer (OC) and worsens survival, the biological mechanisms underlying this relationship remain unclear. This study explores the MDD-OC association using single-cell transcriptomics and genetic approaches. Methods: Using single-cell RNA-seq profiles of peripheral blood from MDD and OC patients, we compared shifts in immune cell subsets and selected the consistently expanded CD8⁺ effector memory (CD8_EM) T cells population for follow-up, validated using flow cytometry. We integrated expression quantitative trait loci (eQTL) data from CD8_EM T cell-specific genes with OC genome-wide association study (GWAS) summary statistics through two-sample Mendelian randomization (MR). In vitro experiments were additionally conducted to assess CLSTN3’s role in OC cell proliferation. Results: Among the 554 differentially expressed genes (DEGs) identified in CD8_EM T cells, MR showed a nominal association between CLSTN3 and ovarian cancer risk (OR 1.21, 95% CI 1.03–1.43), though this did not withstand correction for multiple comparisons. Colocalization analysis confirmed that CLSTN3 expression, regulated by the genetic variant rs3759416, shares a causal variant with the OC GWAS signal (PPH4 = 99.99%). Functionally, siRNA-mediated CLSTN3 silencing in HOC7 cells significantly reduced cell viability (CCK-8 assay). Conclusions: By focusing on CD8_EM T cells shared by MDD and ovarian cancer, we identified CLSTN3 as a candidate molecule through nominated by the convergence of genetic, transcriptomic, and functional evidence. These findings provide preliminary insights into the connection between depression and OC, though further validation is warranted. Full article

Background/Objectives: Childhood interstitial lung disease (chILD) represents a heterogeneous group of rare pulmonary disorders. Practical diagnostic approaches tested for feasibility and impact in comprehensive cohorts are lacking. We aimed to assess a simple etiologically focused classification approach, clarify the role of genetic testing and quantify the impact of non-pulmonary organ manifestations. Methods: We hypothesized that chILD can be classified in a clinically meaningful and versatile way by answering three questions: Which children have an etiological chILD diagnosis due to (1) identified (exposure-related) cause/lung injury, or (2) systemic disease? (3) In how many children without an etiological diagnosis can a genetic cause be identified? We also calculated the predictive value of non-pulmonary organ involvement for underlying systemic conditions. Results: Among 1693 patients, 24.7% were grouped as ILD related to exposure, 22.7% as ILD with systemic condition, 16.6% as ILD with genetic diagnosis of systemic disease, 10.0% as ILD with genetic diagnosis affecting the lungs only, and 25.8% as ILD without genetic diagnosis. The average genetic diagnostic yield was 50.8%, with higher rates in interstitial pneumonia (61.4%) or pulmonary alveolar proteinosis (87.1%). The presence of ≥two non-pulmonary organ manifestations increased the likelihood of an underlying systemic disease by three to five-fold. Conclusions: An etiological diagnostic strategy effectively classifies chILD and guides genetic testing. Exome or genome sequencing should be considered if ≥two non-pulmonary organs are involved or if the initial diagnosis becomes uncertain due to an unusual disease course or signs of a second underlying condition. Full article

Multisystemic eosinophilic epitheliotropic disease (MEED) is a rare and severe equine disorder characterized by chronic eosinophilic inflammation, epithelial disruption, and multi-organ involvement, with an undefined genetic basis. We performed the high-depth (~40×) whole-genome sequencing of an affected horse and compared it to 40 control genomes. Over 6.3 million variants were identified, with moderate- and high-impact variants enriched in low-frequency categories, including rare and private variants absent from the controls. The affected horse was dominated by missense mutations, with relatively few high-impact variants, consistent with the distributed protein-altering effects rather than a single highly penetrant mutation. Gene prioritization and pathway analyses highlighted the disruption of cytoskeletal organization, microtubule dynamics, epithelial integrity, and immune regulation. The network analysis further revealed the interconnected structural and inflammatory pathways, suggesting a link between an impaired epithelial barrier function and immune homeostasis. Together, these findings provide the first population genomic insight into MEED and support a model in which cumulative mutations contribute to the epithelial instability and persistent inflammation characteristic of the disease. Full article

Systemic lupus erythematosus (SLE) is a prototypic systemic autoimmune disorder arising from the convergence of genetic susceptibility, epigenetic remodeling, environmental exposures, and dysregulated immune networks. Although traditionally characterized by autoantibody production and immune complex mediated tissue injury, advances in genomics, systems immunology, and multi-omics profiling have revealed that lupus represents a multilayered failure of immune homeostasis driven by interconnected molecular circuits. Genetic variants enriched in regulatory immune enhancers establish a permissive transcriptional landscape that sensitizes innate nucleic acid sensing pathways and interferon signaling. Epigenetic remodeling further amplifies inflammatory transcriptional programs, while environmental triggers such as ultraviolet radiation and viral infection initiate bursts of nucleic acid release and immune activation. Defective apoptotic cell clearance, mediated in part by scavenger receptor dysfunction and complement abnormalities, increases the availability of immunogenic nucleic acids that engage pattern recognition receptors and drive chronic type I interferon production. This interferon-dominated environment rewires immune cell metabolism, alters differentiation trajectories of T and B lymphocytes, and sustains autoreactive immune circuits. Emerging multi-omics studies reveal distinct molecular endotypes defined by interferon signatures, metabolic states, and immune cell composition, highlighting the heterogeneity of disease mechanisms across patients. In this review, we integrate genetic, epigenetic, metabolic, and immunological insights to propose a systems-level model of lupus pathogenesis in which defective debris clearance, nucleic acid sensing, interferon amplification, and metabolic reprograming form a self-reinforcing pathogenic network. Understanding this integrated molecular architecture provides a foundation for biomarker-guided therapeutic strategies and precision medicine approaches aimed at disrupting the key nodes that sustain chronic autoimmunity in SLE. Full article

Attention deficit hyperactivity disorder (ADHD) is a common and highly heterogeneous neurodevelopmental condition with complex biological underpinnings. Despite substantial progress in identifying genetic and neurobiological correlates, the cellular mechanisms linking genetic variation to functional brain alterations remain poorly understood. Human induced pluripotent stem cell (iPSC) technology provides a powerful platform to investigate these mechanisms by enabling the generation of patient-specific neural cell types and the direct interrogation of molecular, cellular, and network-level phenotypes. In this review, we summarise the current understanding of the neurobiological mechanisms underlying ADHD, including dopaminergic dysregulation, delayed neurodevelopmental maturation, and excitatory/inhibitory imbalance. We then discuss how iPSC-based models, combined with genome engineering and advanced functional assays, can be used to dissect gene-specific effects, study neural circuit development, and establish scalable platforms for therapeutic discovery. Finally, we outline key methodological considerations for designing robust iPSC-based models of ADHD. Together, these approaches provide new opportunities to bridge genetic risk with cellular function and accelerate the development of mechanistically informed therapeutic strategies. Full article

Amyotrophic lateral sclerosis (ALS) is an adult-onset neurodegenerative disease characterized by progressive loss of motor neurons in the brain and spinal cord. While most cases are sporadic, around 10% are familial. Recent genetic studies show that many apparently isolated cases carry pathogenic mutations, highlighting the importance of penetrance, the probability that a causal mutation manifests clinically. This review focuses on mutation penetrance in ALS (C9orf72, SOD1, TARDBP, FUS genes), its variability across genes, age, and environmental or genetic modifiers, and its implications for genetic counseling. Identification of pathogenic mutations informs the monitoring of relatives and, in some cases, gives access to targeted therapies or clinical trials. Counseling of asymptomatic relatives must consider incomplete penetrance, which can lead to delayed or absent disease manifestation. ALS exists on a clinical and genetic continuum including related disorders, such as frontotemporal dementia, further influencing risk interpretation. Advances in panel, whole-exome and whole-genome sequencing refine our understanding of penetrance and enable precise diagnostics, and potential tailored therapies. Understanding penetrance is therefore essential to translate mutation discovery into informed clinical decisions and genetic counseling in ALS. Full article

Background: Polyamines, including putrescine (PU), spermidine (SPD), and spermine (SPM), are ubiquitous bioactive compounds essential for cell proliferation, genomic stability, autophagy, and the regulation of oxidative and inflammatory responses. Growing evidence, particularly for SPD, suggests that polyamine-rich diets may protect against age-related conditions such as cardiovascular disease, metabolic syndrome, and neurodegenerative disorders. As endogenous polyamine synthesis declines with age, dietary intake becomes increasingly important, especially in older adults. Methods: This study estimated each polyamine (PU, SPD and SPM) and total polyamine intake in the Spanish population using food consumption data from the Spanish Ministry of Agriculture, Fisheries and Food. Intakes were evaluated across four age groups, and major dietary sources were identified. Results: Total polyamine intake increased with age, reaching 393 µmol/day in adults over 65 years. PU accounted for 49% of total intake, followed by SPD (29%) and SPM (22%). Plant-based foods were the primary contributors to SPD intake, particularly vegetables (36%), fruits (26%), and cereals (18%). PU intake was also predominantly plant-derived, mainly from fruits (58%) and vegetables (23%), whereas SPM intake was largely associated with meat products (59%). A theoretical Mediterranean diet model yielded a slightly higher total polyamine intake of 406.6 µmol/day and a substantially greater SPD intake than that observed in older adults (193.99 µmol/day versus 121.62 µmol/day). Conclusions: Overall, estimated polyamine intake in the Spanish population fell below the optimal level of 540 µmol/day proposed in the literature. These findings highlight the need for public health strategies promoting consumption of polyamine-rich foods, particularly vegetables, legumes, whole grains, and fruits, to support healthy aging and reduce the risk of age-related diseases. Full article

Restless legs syndrome (RLS) is a common sensorimotor disorder with limited treatment options and incompletely understood pathophysiology. Genome-wide association studies have identified numerous risk loci, but translating these findings into causal genes and therapeutic targets remains challenging. We performed a proteome-wide association study (PWAS) integrating RLS genome-wide association study (GWAS) data from FinnGen with two brain pQTL datasets (ROSMAP and Banner). We validated the identified proteins using TWAS, SMR, and colocalization analyses using brain pQTL and eQTL datasets. To further investigate peripheral protein associations, we performed SMR using plasma pQTL data from the UK Biobank Pharma Proteomics Project (UKB-PPP). We also conducted a phenome-wide association study (PheWAS) to screen for potential off-target effects of the prioritized genes, followed by drug prediction using DSigDB and molecular docking. PWAS identified GLO1, along with GRWD1 and MAP2K5, as significantly associated with RLS. GLO1 was identified by brain-based SMR (p = 0.0001), colocalization (PP.H4 = 0.96), TWAS (p = 0.048), and was confirmed by plasma-based SMR (p = 3.16 × 10⁻⁹) as the only protein associated with RLS. PheWAS analysis, without associations for 783 non-RLS phenotypes, confirmed the specificity of GLO1. Among 27 predicted GLO1-targeting compounds, Gambierol had the strongest binding affinity (−8.3 kcal/mol). This proteogenomic study identifies GLO1 as a prioritized causal gene and promising drug target for RLS, combining brain and plasma data to provide new insights into pathogenesis and candidate drug development. Full article

Schizophrenia is a chronic, progressive, and multifactorial disorder that leads to significant disability and social maladaptation in patients. Although considerable progress has been made in research, the etiology and pathogenesis of schizophrenia remain incompletely understood. However, the involvement of genetic factors in the development of this disease has been established. Using the GWAS catalog, we identified variants within the TCF4 gene that showed a significant association with schizophrenia. The GWAS catalog lists 30 variants within the TCF4 gene associated with schizophrenia. Among these, 12 variants demonstrate a specific association with schizophrenia in the absence of reported comorbidities. The presence and allele frequencies of these variants were subsequently analyzed in two population databases: Database of Population Frequencies of Genetic Variants in the Russian Federation (DPF) and gnomAD. For the functional annotation of the genetic variants, we utilized specialized tracks within the UCSC Genome Browser. The CpG Islands track served to identify potential regulatory regions. The GeneHancer database was used to predict SNP localization within enhancer regions and their potential target genes. To characterize the epigenetic landscape and functional chromatin states, the ENCODE Regulation and ENCODE cCREs tracks were utilized. Comparative analysis revealed significant heterogeneity in the allele and genotype frequencies of TCF4 polymorphisms between the Russian population and other global cohorts. This observed inter-ethnic variability may partly explain the discrepant genetic association findings for schizophrenia reported across different ancestral groups. Therefore, further functional studies are essential to define the precise mechanisms by which TCF4 variants contribute to disease pathogenesis. Full article

Objectives: Myelodysplastic syndromes (MDSs) are a heterogeneous group of clonal hematopoietic disorders characterized by ineffective hematopoiesis, genomic instability, and a high risk of progression to acute myeloid leukemia. Oxidative stress (OS) has emerged as a central factor in MDS pathophysiology, contributing to DNA damage, altered cellular signaling, and disease progression. Recent advances in artificial intelligence (AI) and machine learning (ML) offer a transformative approach for integrating multidimensional datasets including oxidative stress markers, hematologic parameters, and molecular profiles to enhance diagnosis, prognostication, and therapeutic monitoring in MDS. Methods: A comprehensive literature search was conducted in PubMed and Scopus, using the keywords “OS biomarkers,” “AI,” and “MDS’’. Results: Modified redox biomarkers can be correlated with oxidative imbalance and disease progression. ML models such as neural networks, decision trees, and support vector machines effectively capture complex relationships among redox biomarkers, enhancing risk stratification and prediction of treatment response. AI-driven proteomic analyses further revealed OS-related protein signatures linked to MDS pathophysiology. Overall, AI and ML enable the transformation of multidimensional OS data into clinically actionable tools for personalized management in MDS. Conclusions: Integrating biomarker research with AI-based analytics holds promise for advancing personalized diagnostics, prognostication, and therapeutic strategies in MDS, paving the way toward precision medicine. Full article

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder caused by the interaction between genetic and environmental influences, potentially mediated by epigenetic mechanisms such as DNA methylation. Genome-wide DNA methylation profiling was performed using the Infinium MethylationEPIC v2.0 array on peripheral blood mononuclear cells (PBMCs) from 100 children with ASD and 50 typically developing controls. Differential methylation analyses were conducted by adjusting for age, sex, and estimated blood-cell-type composition as covariates. Functional enrichment, SFARI gene-overlap analysis, and cross-cohort validation were performed. We identified 3507 differentially methylated positions (DMPs) in the ASD cohort. Functional enrichment revealed pathways involved in neuronal signaling, synaptic activity, and immune regulation, suggesting coordinated neurodevelopmental and immune processes in ASD. Stratification by clinical severity demonstrated common and unique biological characteristics between the moderate and severe ASD groups. Furthermore, DMP-associated genes significantly overlapped with high-confidence ASD risk genes from the SFARI database and established transcriptomic signatures of neurodevelopmental disorders. Comparisons with independent post mortem brain tissue and peripheral blood datasets revealed partial overlap and directional concordance. However, the strength of concordance varied across datasets and was limited in the most directly comparable peripheral blood cohort. Our findings suggested that DNA methylation profiling of PBMCs provided peripheral epigenetic signatures and candidate loci for further validation in larger independent cohorts. Full article

Chemical modifications of RNA add a dynamic regulatory layer to gene expression beyond the genome and epigenome. Among these modifications, 5-methylcytidine (m⁵C) has emerged as a key epitranscriptomic modification that influences RNA stability, translation, localization, and stress responses across diverse biological systems. Recent advances in high-resolution mapping and functional interrogation of m⁵C have revealed its involvement in development, metabolism, immune regulation, and disease pathogenesis. Notably, many of these processes are highly relevant to women’s health, which is shaped by hormone-responsive tissues, reproductive transitions, and pregnancy-associated physiological adaptations. In this review, we provide a comprehensive and integrative overview of m⁵C RNA modification with a focus on its roles in female biology and disease. We summarize the molecular machinery responsible for m⁵C deposition, recognition, and regulation, as well as current detection technologies. We further highlight emerging evidence linking m⁵C dysregulation to early embryonic development, women-specific cancers, gynecologic and reproductive disorders, pregnancy complications, and metabolic and cardiovascular diseases. In addition, we discuss the interplay between m⁵C and sex hormone signaling, as well as the potential of m⁵C as a biomarker and therapeutic target. Finally, we identify key knowledge gaps, including the need for tissue-specific, longitudinal, single-cell, and spatial epitranscriptomic studies in women. By integrating epitranscriptomics into women’s health research, this review underscores m⁵C as a previously underappreciated regulatory layer with significant implications for precision medicine and clinical translation. Full article

Schizophrenia (SCZ) is a severe neuropsychiatric disorder characterized by a progressive clinical course and associated with a wide range of gene transcription signatures. This review examined studies retrieved from PubMed (published between 2005 and 2025) that investigated transcription factors (TFs) correlated with SCZ. Approximately 150 studies aligning with the eligibility criteria were selected. The synthesized evidence identified more than 40 TFs implicated in the pathogenesis and risk of SCZ. Based on functionality, these TFs were categorized into four groups: (1) progenitor cell TFs (TCF4, POU3F2, NKX2.1, EGR3), (2) stem cell TFs (MYC, SOX2, ASCL1, REST, NR2E1), (3) metabolic reprogramming TFs (HIF1, SREBPs, STATs, SOX9, NRF1, NRF2, p53, FOXO, ATF4, NF-κB), and (4) nuclear TFs (AhR, RXR). The discussion shed light on how these TFs in consort with hundreds of potential genes could shape the pathophysiology of SCZ. Indeed, SCZ represents a complex genomic, nuclear, metabolic, and immune disorder characterized by a diseased cellular microenvironment, with hypoxia emerging as a key feature. Although targeting TFs pharmacologically remains challenging, innovative therapeutic strategies—such as antineoplastic and antipsychotic agents that modulate the cellular microenvironment—may offer promising new directions for SCZ treatment. Full article

Background/Objectives: Opioid use disorder (OUD) is caused by a complex interplay between genetic and non-genetic factors. DNA methylation is an epigenetic mechanism that modulates gene expression. Data on DNA methylation and opioid addiction and treatment are limited. This association study was designed to assess the difference in genome-wide methylation patterns between individuals with OUD in methadone maintenance treatment (MMT) (n = 114) and those with OUD who achieved long-term abstinence (>10 years) without mu opioid receptor agonist treatment (n = 136). Methods: Differential DNA methylation analysis was performed in whole blood using the Illumina EPIC array. Results: A total of 135 differentially methylated probes (DMPs) reached epigenome-wide significance (p < 1 × 10⁻⁷), controlling for sex, age, estimates of blood cell proportions, and the first two principal components based on genome-wide SNP genotypes. The methylation sites were annotated to 157 genes, including 32% long non-coding RNAs. These genes are related to several systems, including cell adhesion (e.g., SAXO4), immune system and inflammation (e.g., UBTF, USP39, C10orf90, PRKCA), stress response (e.g., CRHR1, GPR19), and spermatogenesis (e.g., SPATA16, COX7B2). DMP cg11641410 is located in lncRNA ENSG00000254687, an antisense to OPRK1. Six of the DMPs were also identified in a related longitudinal study of MMT. Conclusions: At this point, it is not possible to determine whether the minor methylation differences observed in this study cause clinically relevant changes in gene expression. However, these findings have the potential to identify biomarkers and to provide new targets for treatment optimization. Full article