Alcohol Use Disorder (AUD) is comorbid with several psychiatric disorders, including intellectual disability (ID), bipolar disorder (BD), and schizophrenia (SCZ), but the shared transcriptional characteristics are not well understood. The goal of this study was to identify common transcriptional features and regulatory patterns across AUD, ID, BD and SCZ using an integrated transcriptomic approach of publicly available transcriptomic datasets. Transcriptomic datasets were analyzed to identify differentially expressed genes (DEGs), followed by functional enrichment, protein–protein interaction, regulatory-network and machine-learning analyzes. Common DEGs were identified across the four disorders, and the prioritized hub genes and transcription factors were further evaluated for their exploratory discriminatory performance by using GSE5389 dataset (11 controls and 10 cases). Total 49 common DEGs were identified, of which 31 were upregulated and 18 were downregulated. Functional analysis revealed immune and extracellular associations like immune response, chemokine activity, complement activity, TNF signaling, IL-17 signaling, and prostaglandin-related pathways. Five hub genes (TTR, SOCS3, CXCL10, MMP9, and C4A) were identified for further analysis. Regulatory-network analysis identified four prominent transcription factors (YY1, FOXC1, JUND and GATA2) and six prominent miRNAs, including hsa-miR-20a-5p, hsa-miR-124-3p, hsa-miR-146a-5p and hsa-miR-330-3p etc. Machine-learning analysis suggested variable exploratory discriminatory performance. The TF-based SVM-RBF model resulted in the highest AUC (0.873), and the highest reported LOOCV accuracy (0.857) was achieved with SVM-RBF. Transcriptional overlap and related molecular features are identified across AUD, ID, BD and SCZ. The findings presented provide an exploratory basis for further investigation, but do not establish causality, diagnostic utility, or therapeutic relevance. The reproducibility and biological significance of the identified features should be confirmed with independent datasets and experimental validation.
Aim This review delineates the mechanistic contributions of micronutrients and heavy metals to cancer and metabolic disorders by integrating ionomics with multi-elemental analytics and pharmacoinformatics for biomarker discovery, while critically synthesizing current evidence and establishing a framework for future clinical validation. Summary Micronutrients and heavy metals are indispensable for physiological homeostasis, and their dysregulation is increasingly implicated in cancer and metabolic disorders. Ionomics has emerged as a powerful system-level approach for investigating elemental distribution, homeostasis, and interactions under physiological and pathological conditions. This review summarizes recent advances in ionomics, highlighting multi-matrix elemental profiling across whole blood, serum, plasma, urine, hair, nails, and tumor tissues. Distinct ionomic signatures consistently show elevated copper (Cu), chromium (Cr), arsenic (As), cadmium (Cd), mercury (Hg), and lead (Pb), together with reduced selenium (Se), zinc (Zn), and manganese (Mn), indicating strong associations between elemental dyshomeostasis and disease progression. Disease-specific ionomic alterations across biological matrices further identify candidate elemental signatures with potential utility for diagnosis, prognosis, and therapeutic monitoring. However, the available evidence remains largely descriptive and associative, with substantial methodological heterogeneity that limits immediate clinical implementation. Conclusion Overall, ionomics provides valuable insights into disease-associated elemental dysregulation and highlights promising candidate biomarkers for cancer and metabolic disorders. Rather than demonstrating clinical potential biomarker readiness, this review provides a comprehensive evidence synthesis that maps recurring ionomic signatures, identifies current methodological and biological knowledge gaps, and establishes a foundation for future prospective validation, standardized analytical workflows, and precision medicine applications.
Background: Ferroptosis is a regulated form of cell death driven by iron-dependent lipid peroxidation and oxidative stress. It has emerged as a key contributor to the pathophysiology of cancer, neurodegenerative disorders, and cardiovascular diseases. Coumarins, a diverse class of benzopyrone-derived compounds, exhibit antioxidant, pro-oxidant, and iron-chelating properties, suggesting their potential role in modulating ferroptotic pathways. Aim: This review aims to systematically evaluate the role of certain coumarins as modulators of ferroptosis and to explore their therapeutic implications across major disease contexts. Methods: A comprehensive literature analysis was conducted focusing on experimental and preclinical studies investigating the interaction between coumarins and ferroptosis-related mechanisms, including iron metabolism, lipid peroxidation, and antioxidant defense systems such as the GPX4/GSH axis. Results: Available preclinical evidence indicates that coumarins exert dual regulatory effects on ferroptosis. In in vitro and limited in vivo cancer models, several derivatives promote ferroptotic cell death through GPX4 inhibition, increased lipid peroxidation, and disruption of system Xc − activity. Conversely, in preclinical neuronal and cardiovascular systems, coumarins exhibit protective effects in vitro and in vivo by enhancing antioxidant defenses, activating Nrf2 signaling, and maintaining redox balance. These context-dependent actions are closely linked to structural diversity and pharmacokinetic properties of the compounds. Conclusion: Coumarins represent promising, yet underexplored, modulators of ferroptosis. However, clinical translation is currently restricted by major barriers, including low bioavailability and other pharmacokinetic challenges, a complete lack of direct clinical evidence, and the absence of standardized ferroptosis assessment methods. Addressing these limitations through robust in vivo validation is essential to clarify their therapeutic applicability.
Parasitic infections remain a major global public health challenge, disproportionately affecting populations in low- and middle-income countries and contributing to significant morbidity, mortality, and socioeconomic burden. Accurate and timely diagnosis is essential for effective disease control; however, conventional diagnostic methods, including microscopy, serology, and molecular assays, exhibit important limitations in sensitivity, specificity, and field applicability, particularly in early-stage and low-intensity infections. In recent years, advances in omics technologies have enabled the identification of emerging biomarkers that provide dynamic and highly sensitive indicators of host–parasite interactions.This review provides a comprehensive overview of emerging biomarkers for human parasitic infections, including parasite-derived markers such as circulating cell-free DNA, extracellular vesicles, microRNAs, and novel antigens, as well as host-derived signatures such as microRNAs, cytokine profiles, proteomic, and metabolomic biomarkers. These biomarkers offer significant advantages, including early detection, improved sensitivity in low-parasite-burden infections, and the ability to reflect real-time infection status and treatment response. However, their clinical translation remains constrained by challenges such as biological variability, lack of standardization, and the need for advanced analytical platforms.The integration of multi-omics approaches, coupled with machine learning and the development of point-of-care technologies, represents a promising strategy to overcome these limitations. Emerging biomarkers are poised to transform the diagnostic landscape of parasitic diseases by enabling more precise, non-invasive, and scalable diagnostic solutions, ultimately supporting improved disease management and global control efforts.
Background Epithelioid sarcoma (ES) is a malignant soft-tissue neoplasm with a low incidence, aggressive behaviour, epithelioid morphology, and a high risk of local recurrence and metastasis. Recognition of SMARCB1/INI1 deletion and resultant SWI/SNF complex dysfunction has reshaped its diagnosis and enabled targeted therapy. Objectives This scoping review aimed to map the literature on molecular diagnostic approaches and systemic therapeutic strategies in epithelioid sarcoma, with emphasis on translational relevance, clinical outcomes, and evidence gaps. Methods A scoping review was conducted in accordance with PRISMA-ScR guidelines. PubMed/MEDLINE, Web of Science, and Embase were searched for studies published between January 2010 and June 2026. After de-duplication, two reviewers screened titles and abstracts, and full texts were assessed against predefined eligibility criteria (≥3 ES patients). Data were synthesized narratively. Results Twenty-three studies (published 2011–2026; 8 to 1123 ES patients each) met the inclusion criteria. Loss of SMARCB1/INI1 expression was the consistent diagnostic finding, reported by immunohistochemistry in the large majority of classic and proximal ES (e.g., 19/21 [90%] and 47/54 [87%] in the largest series) and confirmed genetically by homozygous SMARCB1 deletion (36/40 by FISH). Multi-omics analyses established that classic and proximal ES are distinct molecular and immunologic entities. Conventional chemotherapy produced low objective response rates (first-line real-world rwORR 15%; median OS 15.2 months). The EZH2 inhibitor tazemetostat achieved an objective response in 15% (9/62) of patients with a median OS of 19 months. Conclusions Molecular diagnostics, centered on SMARCB1/INI1 loss, have reshaped the classification of epithelioid sarcoma, and EZH2 inhibition provides the first biologically targeted option for SMARCB1-deficient disease; however, response rates remain modest and the overall evidence base is limited and heterogeneous. Future advances will require biomarker development, innovative trial designs, and international collaboration to improve outcomes in this ultra-rare malignancy.
