Search Results (91)

Background: Iron-refractory iron deficiency anemia (IRIDA) is a rare hereditary disorder caused by pathogenic variants in TMPRSS6, characterized by microcytic anemia, low circulating iron levels, and inappropriately high hepcidin levels. Although IRIDA is typically an autosomal recessive disorder, some individuals with a monoallelic pathogenic exonic TMPRSS6 variant exhibit the phenotype, suggesting additional contributing factors. The mechanisms underlying monoallelic IRIDA remain unclear, complicating diagnosis. This study aimed to investigate the potential role of non-coding TMPRSS6 variants and polygenic inheritance in monoallelic IRIDA. Methods: We performed full-gene sequencing of TMPRSS6 in a cohort of 27 subjects, including 6 families (7 symptomatic monoallelic, 7 asymptomatic monoallelic, and 4 wild-type subjects) and 9 isolated symptomatic monoallelic subjects. Whole-exome sequencing of other iron-regulating genes was conducted to evaluate polygenic inheritance. Non-coding variants were assessed for inheritance patterns using family segregation analysis, when available, and for pathogenic potential using in silico prediction tools. Results: Sequencing identified 219 non-coding variants, of which 31 (14 trans-inherited and 17 with unknown inheritance) were exclusive to symptomatic subjects. Two trans-inherited variants (rs80140288 (c.229+945C>T) and rs146953827 (c.230-938_230-937del)) were predicted to affect splicing, while two additional variants (rs78987624 (c.-7001G>A) and rs117575523 (c.*503C>G)) were located in regulatory regions (with unknown inheritance). Whole-exome sequencing did not support polygenic involving other iron-regulating genes. Conclusions: This study highlights four candidate non-coding variants that may contribute to IRIDA expression in monoallelic subjects, offering new insights into its genetic basis. Functional validation is required to confirm their role in disease pathogenesis, refine genotype-phenotype correlations, and improve diagnostic accuracy in monoallelic IRIDA. Full article

Atherosclerosis is a chronic, multifactorial vascular disease and the leading global cause of cardiovascular morbidity. Its development reflects interconnected disturbances in lipid metabolism, endothelial function, inflammation, smooth muscle cell (SMC) phenotypic switching, and extracellular matrix remodeling. Genetic predisposition, including monogenic disorders such as familial hypercholesterolemia and polygenic risk variants, modulates disease susceptibility by altering lipid homeostasis as well as inflammatory and thrombotic pathways. Epigenetic regulators and noncoding RNAs, such as histone modifications, microRNAs, and long noncoding RNAs, further shape gene expression and link environmental cues to vascular pathology. Endothelial injury promotes lipoprotein retention and oxidation, triggering monocyte recruitment and macrophage-driven foam cell formation, cytokine secretion, and necrotic core development. Persistent inflammation, macrophage heterogeneity, and SMC plasticity collectively drive plaque growth and destabilization. Emerging insights into immune cell metabolism, intracellular signaling networks, and novel regulatory RNAs are expanding therapeutic possibilities beyond lipid-lowering. Current and evolving treatments include statins, proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors, anti-inflammatory agents targeting interleukin-1 beta (IL-1β) or NOD-, LRR-, and pyrin domain-containing protein 3 (NLRP3), and advanced approaches such as gene editing, siRNA, and nanoparticle-based delivery. Integrating multi-omics, biomarker-guided therapy, and precision medicine promises improved risk stratification and next-generation targeted interventions. This review summarizes recent molecular advances and highlights translational opportunities for enhancing atherosclerosis prevention and treatment. Full article

This review integrates molecular, clinical, and translational data to provide an updated understanding of GJB2-related deafness and its emerging treatment landscape. Truncating mutations in GJB2 typically cause severe-profound hearing loss (HL) phenotypes, whereas non-truncating alleles are often associated with milder or progressive phenotypes. Geographic variation in variant prevalence contributes to regional differences in disease burden. Beyond the coding region, deletions and cis-regulatory mutations within the DFNB1 locus, including GJB6 and CRYL1, can influence HL severity when compounded with other pathogenic GJB2 variants. DFNB1 hearing loss generally presents as symmetric, bilateral, and flat to gently sloping across frequencies, with preserved cochlear neurons that support excellent cochlear implant (CI) outcomes. Early implantation CI in GJB2-positive children yields superior speech and language development compared with non-GJB2 etiologies. Emerging therapies include dual-AAV (AAV1 + AAV-ie/ScPro) delivery, achieving cell-specific Cx26 restoration, adenine base-editing for dominant-negative variants, and allele-specific suppression using RNA interference or antisense oligonucleotides. Concurrent progress in human iPSC-derived cochlear organoids provides a physiologic model to advance toward clinical trials. By integrating genotype-phenotype correlations, natural history insights, and advances in molecular therapeutics, this review presents a comprehensive update on GJB2-related HL and highlights how gene-based strategies are poised to change the treatment of this condition. Full article

Analysis of coding areas has long been used to study monogenic illnesses, but despite the extensive use of whole-exome sequencing (WES), up to half of suspected cases remain genetically unexplained. Variants outside coding areas can alter splicing, transcript stability, or gene regulation, compromising normal gene activity. These include mutations in noncoding RNAs, promoters, enhancers, deep intronic sequences, and untranslated regions (UTRs). Several well-known disorders have been linked to these mechanisms, including β-thalassemia caused by deep intronic mutations leading to aberrant splicing, familial hypercholesterolemia caused by promoter defects affecting LDLR expression, and inherited retinal diseases driven by noncoding variants influencing retinal gene regulation. These instances show that pathogenic variation is not limited to the exome and can have significant clinical implications. This review summarizes current understanding of noncoding and regulatory variants in monogenic diseases, discusses how they influence diagnosis and therapy, and highlights integrative approaches combining genomic, transcriptomic, and epigenomic data. Multi-layered research has increased diagnostic accuracy and unveiled new therapeutic potentials, although noncoding variations make the connection between genotype and phenotype more complex. Noncoding regions will need to be incorporated into standard diagnostic procedures to convert molecular insights into concrete therapeutic applications in the future. Predictive algorithms, patient-derived model systems, and functional validation testing will all help to simplify this process. Full article

Background/Objectives: Systemic lupus erythematosus (SLE) is a multifactorial autoimmune disease strongly influenced by genetic factors. Genome-wide association studies (GWASs) have identified numerous non-coding susceptibility loci, but their functional roles remain poorly understood. The single-nucleotide variant (SNV) rs2836882, located in an enhancer near the ETS2 proto-oncogene, has been implicated in immune regulation, though its contribution to SLE is unclear. Methods: We analyzed rs2836882 in 246 Italian patients with SLE and 216 matched controls using TaqMan genotyping. A weighted genetic risk score (wGRS) combining rs2836882 with other known SLE variants was calculated. ETS2 mRNA expression was quantified by RT-qPCR in PBMCs from 60 individuals, and in silico analyses assessed the variant’s functional context. Results: The rs2836882 risk allele was significantly associated with SLE (OR = 1.54, p = 0.02). Patients showed a markedly higher wGRS than controls (p < 0.00001), confirming an additive genetic burden. In silico data indicated that rs2836882 lies within an active enhancer region (H3K4me1/H3K27ac+) containing PU.1 binding motifs and functions as an expression quantitative trait locus (eQTL) for ETS2. Expression analysis demonstrated that carriers of the risk allele exhibited significantly increased ETS2 expression compared to non-carriers (p = 0.002) in both groups. Conclusions: In conclusion, rs2836882 is a functional regulatory variant that enhances ETS2 transcription and contributes to increased SLE susceptibility. These findings establish a mechanistic link between a non-coding GWAS locus and disease risk, emphasizing the role of regulatory variants in autoimmune pathogenesis and supporting the integration of functional non-coding variants into genetic risk models for improved patient stratification. Full article

Background: Long non-coding RNAs (lncRNAs) are regulatory molecules that have multifaceted impacts on the carcinogenic molecular landscape—with pathologic consequences when aberrantly expressed. Anaplastic thyroid cancer (ATC) is a rapidly progressing and highly lethal malignancy, with mortality rates approaching 100%. The molecular/transcriptomic signature of ATC has significant gaps in understanding; thus, a comprehensive study of ATC non-coding RNA transcript regulation is necessary. Results: The lncRNA Double Homeobox A Pseudogene 10 (DUXAP10) was identified in patient genomic datasets as a highly upregulated transcript in ATC vs. normal thyroid tissue. DUXAP10 expression was transcriptionally repressed with CRISPR-interference (CRISPRi), and data supports an extensive role of DUXAP10 in several cancer-promoting phenotypes in ATC, both in vitro and in vivo. Our two DUXAP10-CRISPRi cell lines significantly reduced the rapid growth and metastatic behaviors characteristic of ATC, affecting proliferation, viability, clonogenicity, apoptosis, invasion, migration, tumorigenesis, and metastasis. Conclusion: Thus, DUXAP10 is a proposed prognostic marker and therapeutic target for ATC disease propagation and progression. Full article

Background/Objective: Genome-wide association studies (GWAS) have linked many noncoding variants to complex traits and diseases, but distinguishing as-sociation from causation remains difficult. Deep learning models—particularly CNN- and Transformer-based architectures—are widely used for this task, yet comparisons are hindered by inconsistent benchmarks and evaluation practices. We aimed to establish a standardized assessment of leading models for predicting variant effects in enhancers and for prioritizing putative causal SNPs. Methods: We evaluated state-of-the-art deep learning models under consistent training and evaluation conditions on nine datasets derived from MPRA, raQTL, and eQTL ex-periments. These datasets profile the regulatory impact of 54,859 single-nucleotide polymorphisms (SNPs) across four human cell lines. Performance was compared for two related tasks: predicting the direction and magnitude of regulatory impact in enhancers and identifying likely causal SNPs within linkage disequilibrium (LD) blocks. We addi-tionally assessed the effect of fine-tuning on Transformer-based models and the impact of certainty in experimental results. Results: CNN models such as TREDNet and SEI performed best for predicting the reg-ulatory impact of SNPs in enhancers. Hybrid CNN–Transformer models (e.g., Borzoi) performed best for causal variant prioritization within LD blocks. Fine-tuning benefits Transformers but remains insufficient to close the performance gap. Conclusions: Under a unified benchmark, CNN architectures are most reliable for esti-mating enhancer regulatory effects of SNPs, while hybrid CNN–Transformer models are superior for causal SNP identification within LD. These comparisons help guide model selection for variant-effect prediction in noncoding regions. Full article

Inflammatory bowel disease (IBD) demonstrates chronic relapsing inflammation extending beyond adaptive immunity dysfunction. “Trained immunity”—the reprogramming of innate immune memory in myeloid cells and hematopoietic progenitors—maintains intestinal inflammation; however, the mechanism by which gut microbiome orchestration determines protective versus pathological outcomes remains unclear. Microbial metabolites demonstrate context-dependent dual effects along the gut–bone marrow axis. Short-chain fatty acids typically induce tolerogenic immune memory, whereas metabolites like succinate and polyamines exhibit dual roles: promoting inflammation in certain contexts while enhancing barrier integrity in others, influenced by cell-specific receptors and microenvironmental factors. Interventions include precision probiotics and postbiotics delivering specific metabolites, fecal microbiota transplantation addressing dysbiotic trained immunity, targeted metabolite supplementation, and pharmacologic reprogramming of pathological myeloid training states. Patient stratification based on microbiome composition and host genetics enhances therapeutic precision. Future research requires integration of non-coding RNAs regulating trained immunity, microbiome–immune–neuronal axis interactions, and host genetic variants modulating microbiome–immunity crosstalk. Priorities include developing companion diagnostics, establishing regulatory frameworks for microbiome therapeutics, and defining mechanistic switches for personalized interventions. Full article

Cellular gene expression varies in different physiological or pathological conditions. Conventional gene expression analysis assumes that each gene produces a single mRNA, which is not accurate. On average, genes express more than three mRNA isoforms. A particular cell type expresses different mRNA isoforms from a specific gene depending on its developmental or differentiation state. Different isoforms encode distinct proteins or noncoding regulatory RNAs, each with its own unique functions. Pathological states also alter the expression of transcript variants, which can either cause a disease or facilitate recovery. Still, the detection of mRNA isoforms or variants is not preferred to avoid complex analyses. As a result, gene expression studies often fail to identify the actual mRNA isoforms or variants associated with pathophysiology. In this article, we summarize the data on mRNA isoforms and disease-associated variants identified in various physiological and pathological conditions. These findings emphasize the importance of detecting mRNA isoforms for a better understanding of physiological or pathological conditions. Full article

Psoriasis is a chronic inflammatory skin disorder affecting approximately 2% of the global population, characterized by abnormal keratinocyte proliferation and dysregulated immune responses. This review examines the emerging role of long non-coding RNAs (lncRNAs) in psoriasis pathogenesis, highlighting their significance as regulatory molecules in disease initiation, progression, and chronicity. LncRNAs demonstrate distinct expression patterns in psoriatic lesions, with upregulated transcripts such as MALAT1, XIST, MIR31HG, and HOTAIR promoting keratinocyte hyperproliferation, inhibiting apoptosis, and amplifying inflammatory cascades through mechanisms including microRNA sponging and transcription factor modulation. These molecules primarily target key signaling pathways including NF-κB, STAT3, and PI3K/AKT. Conversely, downregulated lncRNAs like NEAT1, MEG3, and PRINS normally function as tumor suppressor molecules that maintain epidermal homeostasis through pro-apoptotic and anti-inflammatory mechanisms. Their reduced expression contributes to the pathological hyperproliferative phenotype characteristic of psoriatic skin. Importantly, genetic variants within lncRNA loci have been identified as significant contributors to psoriasis susceptibility and treatment responses across different populations. Single- nucleotide polymorphisms in genes such as TRAF3IP2-AS1, HOTAIR, and CDKN2B-AS1 demonstrate population-specific associations with disease risk and therapeutic outcomes, suggesting their potential utility as pharmacogenomic markers. The complex regulatory networks involving lncRNAs provide new insights into psoriasis pathogenesis and offer promising avenues for personalized treatment strategies. Integration of lncRNA profiling into clinical practice may enhance our understanding of disease heterogeneity and improve therapeutic outcomes for psoriatic patients. Full article

Background/Objectives: Male infertility is a major health concern with a complex etiopathology, yet a substantial proportion of cases remain idiopathic. Mitochondrial dysfunction and non-coding RNA (ncRNA) deregulation have both been implicated in impaired spermatogenesis, but their interplay remains poorly understood. This study aimed to identify infertility-specific variants in ncRNAs that affect mitochondrial dynamics and homeostasis and to explore their roles. Methods: Whole-genome sequencing (WGS) was performed on genomic DNA samples from teratozoospermic, asthenozoospermic, oligozoospermic, and normozoospermic men. Variants uniquely present in infertile individuals and mapped to ncRNAs that affect mitochondrial dynamics were selected and prioritized using bioinformatics tools. An independent transcriptomic validation was conducted using RNA-sequencing data from testicular biopsies of men with non-obstructive azoospermia (NOA) to determine whether the ncRNAs harboring WGS-derived variants were transcriptionally altered. Results: We identified several infertility-specific variants located in lncRNAs known to interact with mitochondrial regulators, including GAS5, HOTAIR, PVT1, MEG3, and CDKN2B-AS1. Transcriptomic analysis confirmed significant deregulation of these lncRNAs in azoospermic testicular samples. Bioinformatic analysis also implicated the disruption of lncRNA–miRNA–mitochondria networks, potentially contributing to mitochondrial membrane potential loss, elevated reactive oxygen species (ROS) production, impaired mitophagy, and germ cell apoptosis. Conclusions: Our integrative genomic and transcriptomic analysis highlights lncRNA–mitochondrial gene interactions as a novel regulatory layer in male infertility, while the identified lncRNAs hold promise as biomarkers and therapeutic targets. However, future functional studies are warranted to elucidate their mechanistic roles and potential for clinical translation in reproductive medicine. Full article

Transcribed conserved non-coding elements (TCNEs), which are non-coding genomic elements that can regulate vital gene expression, play an unclear role in the development of severe diseases mainly associated with carcinogenesis. Currently, there are no mature tools for the identification of TCNEs. To compensate for the lack of a systematic interpretation of the functional characterization and regulatory mechanisms of TCNE spatiotemporal activities, we developed a flexible pipeline, called captureTCNE, to depict the landscape of TCNEs and applied it to our breast cancer cohort (SEU-BRCA). Meanwhile, we investigated the genome-wide characteristics of TCNEs and unraveled that TCNEs harbor enhancer-like chromatin signatures as well as participate in the transcriptional machinery to regulate essential genes or architect biological regulatory networks of breast cancer. Specifically, the TCNE transcripts could recruit RBPs, such as ENOX1 and PTBP1, which are involved in gene expression regulation, to participate in the formation of regulatory networks and the association with altered splicing patterns. In particular, the presence of a non-classical secondary structure, called RNA G-quadruplex, on TCNE transcripts contributed to the recruitment of RBPs associated with subtype-specific transcriptional processes related to the estrogen response in breast cancer. Ultimately, we also analyzed the mutational signatures of variant-containing TCNEs and discerned twenty-one genes as essential components of the regulatory mechanism of TCNEs in breast cancer. Our study provides an effective TCNE identification pipeline and insights into the regulatory mechanisms of TCNEs in breast cancer, contributing to further knowledge of TCNEs and the emergence of innovative therapeutic strategies for breast cancer. Full article

Background: Breast cancer (BC), one of the most common cancers, has increased in Mexico during the past decade, along with other chronic and metabolic diseases. Methods: Herein, we analyzed 121 SNPs (85 SNPs related to BC and/or glucose-associated metabolic pathways and 36 SNP classified as ancestry markers) in 92 confirmed BC cases and 126 unaffected BC women from Northeastern Mexico. The relationship of these 121 SNPs with BC, considering BMI, menopause status, and age as cofactors, was explored using a gene–environment (G × E) interaction multi-locus model. Results: Twelve gene variants were significantly associated with BC: three located in exome (rs3856806 PPARG, rs12792229 MMP8, and rs5218 KCNJ11-ABCC8), and nine in non-coding regions, which are involved in accelerated decay of the mRNA transcripts, regulatory regions, and flanking regions (rs3917542 PON1; rs3750804 and rs3750805 TCF7L2; rs1121980 and rs3751812 FTO; rs12946618 RPTOR; rs2833483 SCAF4; rs11652805 AMZ2P1-GNA13; and rs1800955 SCT-DEAF1-DRD4). Conclusions: This study identified an association between BC and menopause, age (above 45), obesity, and overweight status with gene variants implicated in diabetes mellitus, obesity, insulin resistance, inflammation, and remodeling of the extracellular matrix. Full article

Neonatal encephalopathy suspected to be due to hypoxic ischaemic encephalopathy (NESHIE) carries the risk of death or severe disability (cognitive defects and cerebral palsy). Previous genetic studies on NESHIE have predominantly focused on exomes or targeted genes. The objective of this study was to identify genetic variants associated with moderate–severe NESHIE through whole-genome, unbiased analysis. Variant filtering and prioritization were performed, followed by association testing both on a case–control basis and to compare the grades of severity and/or progression. Association testing on neonates with NESHIE (N = 172) and ancestry-matched controls (N = 288) produced 71 significant genetic variants (false discovery rate corrected p-value < 6.2 × 10⁻⁴), all located in non-coding regions and not previously implicated in NESHIE. Disease-associated variants in non-coding regions are considered to affect regulatory functions, possibly by modifying gene expression, promoters, enhancers, or DNA structure. The most significant variant was at position 6:162010973 in the Parkin RBR E3 ubiquitin protein ligase (PRKN) intron. Intronic variants were also identified in genes involved in inflammatory processes (SLCO3A1), DNA repair (ZGRF1), synaptogenesis (CNTN5), haematopoiesis (ASXL2), and the transcriptional response to hypoxia (PADI4). Ten variants were associated with a higher severity or lack of improvement in NESHIE, including one in ADAMTS3, which encodes a procollagen amino protease with a role in angiogenesis and lymphangiogenesis. This analysis represents one of the first efforts to analyze whole-genome data to investigate the genetic complexity of NESHIE in diverse ethnolinguistic groups of African origin and provides direction for further study. Full article

Background: Low-density lipoprotein cholesterol (LDL-C) is a well-established risk factor for cardiovascular disease, and it plays a causal role in the development of atherosclerosis. Genome-wide association studies (GWASs) have successfully identified hundreds of genetic variants associated with LDL-C. Most of these risk loci fall in non-coding regions of the genome, and it is unclear how these non-coding variants affect circulating lipid levels. One hypothesis is that genetically mediated variation in transcript abundance, detected via the analysis of expressed quantitative trait loci (eQTLs), is key to the biologic function of causal variants. Here, we investigate the hypothesis that non-coding GWAS risk variants affect the homeostatic expression of a nearby putatively causal gene for serum LDL-C levels. Methods: We establish a set of twenty-one expert-curated and validated genes implicated in hypercholesterolemia via dose-dependent pharmacologic modulation in human adults, for which the relevant tissue type has been established. We show that the expression of these LDL-C genes is impacted by eQTLs in relevant tissues and that there are significant genomic-risk loci in LDL-GWAS near these causal genes. We evaluate, using statistical colocalization, whether a single variant or set of variants in each genetic locus is responsible for the GWAS and eQTL signals. Results: Genome-wide association study results for serum LDL-C levels demonstrate that the 402 identified genomic-risk loci for LDL-C are highly enriched for known causal genes for LDL-C (OR 527, 95% CI 126–5376, p < 2.2 × 10⁻¹⁶). However, we find limited evidence for colocalization between GWAS signals near validated hypercholesterolemia genes and eQTLs in relevant tissues (colocalization rate of 26% at a locus-level colocalization probability > 50%). Conclusions: Our results highlight the complexity of genetic regulatory effects for causal hypercholesterolemia genes; we suggest that context-responsive eQTLs may explain the effects of non-coding GWAS hits that do not overlap with standard eQTLs. Full article