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PubMed2026

A User-Friendly Protocol for Microinjection into Teleost Embryos to Study Gene Function.

Zebrafish (Danio rerio) and medaka (Oryzias latipes) are popular teleost models used in developmental biology and functional genomics. To achieve high-quality and reproducible microinjections, it is essential to have robust protocols for breeding, egg collection, and the precise delivery of genetic material. In this protocol, we present a comprehensive and optimized methodology for setting up breeding tanks under controlled photoperiod conditions to maximize egg yield while minimizing contamination. We provide detailed procedures for sex identification, pair selection, the use of grated breeding inserts, and methods to increase egg collection efficiency. We outline procedures for making injection gel beds, pulling needles, and calibration using one-microliter microcapillaries to achieve consistent nanoliter-scale injections. Our protocol outlines settings for the pico-liter injector that are optimized to deliver a precise amount per pulse with minimal variability. Finally, we demonstrate the application of these methods for gene knockdown using morpholino antisense oligonucleotides, gene knockout using CRISPR-Cas9, and gain-of-function mRNA overexpression experiments. Phenotypic assessments conducted at various developmental stages to evaluate gene-specific effects reveal consistent phenotypic outcomes between the morpholino and CRISPR-Cas9 approaches. This easy and comprehensive protocol enables efficient, precise, and scalable genetic manipulation of zebrafish and medaka embryos, thereby supporting advanced functional studies in developmental biology and disease modeling. To our knowledge, this is the first unified protocol for both zebrafish and medaka microinjection systems achieving 97.7% phenotype penetrance in CRISPR-Cas9 knockouts with precision together with a triple validation approach that confirms gene function across multiple techniques.

Animals↗
PubMed2026

Clinical Outcomes and Genomic Epidemiology of Multidrug-Resistant Methicillin-Resistant Staphylococcus aureus Keratitis.

PURPOSE: To characterize the clinical features, management, antimicrobial resistance patterns, and genomic epidemiology of methicillin-resistant Staphylococcus aureus (MRSA) keratitis at two North American centers. DESIGN: Retrospective interventional case series combined with laboratory investigation PARTICIPANTS: Seventy eyes of 67 patients presenting laboratory-confirmed MRSA keratitis were included METHODS: We performed a multicenter retrospective case series of patients with culture-proven MRSA keratitis treated between 2005 and 2022. Demographic and clinical data were collected. Antimicrobial susceptibility testing was conducted, and multidrug resistance (MDR) was defined as resistance to ≥3 antibiotic classes. A subset of isolates underwent whole-genome sequencing with core genome multilocus sequence typing. Vancomycin susceptibility, heteroresistance screening, and tolerance testing were performed on available isolates. MAIN OUTCOME MEASURES: Antimicrobial susceptibility and multidrug resistance rates, vancomycin phenotypic profiles, MRSA genotypic distribution, and final best-corrected visual acuity RESULTS: Median age was 63.5 years, and 61.4% were female. Ocular surface disease (67.7%) and prior ocular surgery (65.2%) were common. Only 25.4% had significant healthcare exposure in the preceding year. Most isolates (85.7%) were MDR. Fluoroquinolone susceptibility was low (moxifloxacin 19.7%). All isolates were susceptible to vancomycin (MIC₉₀ 2 µg/mL), and no vancomycin-intermediate, heteroresistant, or tolerant phenotypes were identified. Whole genome sequencing (n = 41) demonstrated predominance of clonal complexes 5 (68.3%) and 8 (29.2%). Visual outcomes were poor, with most patients (85.2%) having a final visual acuity worse than 20/60 among those with follow-up. CONCLUSIONS: MRSA keratitis is associated with high rates of multidrug resistance and poor visual outcomes despite guideline-based therapy. Infections were predominantly caused by CC5 MDR strains despite limited recent healthcare exposure. These findings highlight the persistence of highly resistant MRSA lineages in community-associated corneal infection and underscore the need for ongoing antimicrobial surveillance and optimized treatment strategies.

Humans↗
PubMed2026

eIF5A and polyamines restrict mRNA levels in response to ribosome stalls.

Obstacles to translation elongation stall ribosomes and allow deleterious proteins to accumulate, which threatens cellular health. Cells recognize and clear stalled ribosomes via several interrelated pathways, although the mechanisms by which cells distinguish stalled from normally elongating ribosomes and mount an appropriate response are incompletely understood. While recent work highlights how ribosome collisions help cells to recognize stalled ribosomes, how other factors contribute to detection remains unclear. Here, we report a requirement for the translational factor eIF5A in the mRNA decay response to ribosomal stalling, i.e., No-Go mRNA Decay (NGD). We identified the Caenorhabditis elegans polyamine transporter, catp-6, via a forward genetic screen as a factor required for NGD. During our mechanistic dissection of the catp-6 phenotype, we uncovered a role for cellular polyamines and the translation elongation factor eIF5A in NGD, and we show this requirement is conserved from C. elegans to Saccharomyces cerevisiae. Our analyses support the idea that cells use eIF5A to identify ribosomal stalls and execute NGD and uncover a molecular function for a core protein synthesis factor in limiting expression from stall-inducing mRNAs. Our work offers insight into how cells identify and remove problematic mRNAs from the translational pool. Our work also raises the possibility that dysregulated mRNA decay is an unrecognized pathophysiology associated with polyaminopathies and eIF5A disorders, of relevance to varied neurodegenerative and aging phenotypes and efforts to pharmacologically inhibit eIF5A.

Animals↗
PubMed2026

New Evidence in Heart Failure: 2026 Update.

Heart failure (HF) remains a major cause of morbidity, mortality, impaired quality of life and healthcare expenditure worldwide. The global burden of HF continues to increase due to population aging, improved survival, and the growing prevalence of cardiovascular, renal, and metabolic comorbidities. Simultaneously, the pace of scientific progress in HF has accelerated considerably. Recent advances have refined our understanding of HF epidemiology, prognosis, and disease trajectories, including emerging concepts of HF improvement, remission, and recovery. The Second Universal Definition of HF has also updated the classification framework, moving beyond the traditional ejection fraction-based categories. HF is now broadly classified into two major phenotypes: heart failure with reduced ejection fraction (HFrEF) and heart failure with preserved ejection fraction (HFpEF). Novel mechanistic insights highlight the role of inflammation, immune activation, metabolic dysfunction, mitochondrial biology, and multisystem interactions in HF progression. There has also been significant progress in the characterization and management of major comorbidities, including chronic kidney disease (CKD), diabetes, obesity, atrial fibrillation (AF), pulmonary hypertension, frailty, malnutrition, and cancer. Diagnostic innovations include novel biomarkers, multi-omics technologies, artificial intelligence-based approaches, advanced imaging techniques, congestion assessment tools, and emerging digital health solutions. Important advances have occurred in specific HF aetiologies, including cardiomyopathies, cardiac amyloidosis (CA), myocarditis, arrhythmia-induced cardiomyopathy (AiCM), and Chagas cardiomyopathy. Therapeutic developments continue to reshape HF management across the spectrum of left ventricular ejection fraction. Recent evidence has focused on optimization of guideline-directed medical therapy in HFrEF, expansion of evidence-based therapies in HFpEF, and growing roles for sodium-glucose cotransporter-2 inhibitors, finerenone, incretin-based therapies, and transcatheter valve interventions. Collectively, these advances support the transition from a predominantly phenotype-based approach towards a more personalized and biologically informed model of HF care, with the potential to further improve outcomes across the entire HF spectrum.

Journal Article↗
PubMed2026

Omics in hereditary optic neuropathies: A systematic review of clinical studies with an integrated point of view.

Hereditary optic neuropathies are characterized by bilateral visual loss due to the degeneration of retinal ganglion cells, resulting in optic nerve degeneration and atrophy. Although the genetic origin of the main isolated and syndromic hereditary optic neuropathies has been characterized, the clinical phenotypes exhibit significant and poorly understood variability in both penetrance and expressivity. Additionally, the genetic and environmental factors that influence the onset of these optic neuropathies remain poorly understood, with limited biomarkers to predict disease progression or as readouts for therapeutic trials. Data-driven omics strategies allow deep phenotyping to improve our understanding of pathophysiological mechanisms and to search for new biomarkers and therapeutic targets. We explore whether the omics strategies applied to patients with hereditary optic neuropathies have provided such new insights. MEDLINE, Web of Science and EMBASE databases were screened for studies with terms relating to hereditary optic neuropathies, transcriptomics, epigenomics, proteomics, metabolomics and lipidomics in clinical studies exploring patients' samples. Out of 1244 references identified, 22 articles were included after double-masked data curation. These articles focused only on the 3 main forms of hereditary optic neuropathies, namely, OPA1-related dominant optic atrophy (n = 4), Leber hereditary optic neuropathy (n = 13), and Wolfram syndrome (n = 5). While the methodological designs and results of these studies were highly heterogeneous, they revealed molecular alterations that we have attempted to discuss at the integrated multi-omics level. This data integration highlighted several common pathophysiological mechanisms such as energetic impairment, endoplasmic reticulum stress, proteotoxic and oxidative stresses, lipid remodeling and altered amino acid and purine metabolisms, while suggesting potential new biomarkers and therapeutic targets. These findings underscore the potential of integrated multi-omics approaches to deepen our understanding of the phenotypic complexity of hereditary optic neuropathies and to support the development of innovative diagnostic and therapeutic strategies.

Humans↗
PubMed2026

Amino acid reprogramming and biofilm-specific tricarboxylate transporters in PET-degrading Piscinibacter sakaiensis.

Plastic-degrading bacteria predominantly colonize polymer surfaces as biofilms, yet it remains unclear whether the biofilm phenotype contributes to metabolism beyond retaining extracellular enzymes. Here, we combine population-level RNA-sequencing across three conditions-biofilm cells on polyethylene terephthalate (PET), planktonic cells incubated with PET, and planktonic cells on maltose-with single-cell Raman spectroscopy to characterize the PET response of Piscinibacter sakaiensis (formerly Ideonella sakaiensis). This integrated approach reveals two metabolically distinct response layers. A carbon-source-driven response shared by all PET-exposed cells is dominated by a broad amino acid reprogramming, led by upregulation of branched-chain amino acid transport genes, enhanced serine biosynthesis, and reduced chemotaxis. A biofilm-specific layer selectively induces tripartite tricarboxylate transporter genes from three distinct genomic loci. This transcriptional feature is accompanied by a single-cell phenotype consistent with a protein-rich and saturated membrane. These results suggest that biofilm formation is not limited to enzyme retention but is associated with selective activation of transport systems, consistent with a putative role in capturing PET-derived intermediates at the polymer interface. This two-layer model separates general metabolic adaptation to PET from biofilm-specific functions and provides a framework for understanding how surface-associated bacterial physiology contributes to plastic degradation.IMPORTANCEPolyethylene terephthalate (PET) degradation in natural and engineered environments is largely mediated by surface-attached microbial communities, yet the physiological role of biofilm state during plastic degradation remains poorly understood. Using the model PET degrader Piscinibacter sakaiensis, we show that biofilm-associated cells are not simply retained near the polymer surface but exhibit a distinct metabolic program characterized by selective induction of tripartite tricarboxylate transporters. In contrast, extensive amino acid reprogramming occurs in both biofilm and planktonic PET-exposed cells, indicating that it is driven by carbon source rather than surface attachment. These findings reveal that PET degradation involves two separable physiological layers: a general metabolic response to PET-derived carbon shared across cell phenotypes, and a biofilm-specific transport response potentially linked to substrate capture at the plastic interface. This work advances our understanding of how microbial physiology is organized during plastic biodegradation and identifies transport processes as previously unrecognized components of PET-degrading biofilms.

PET biodegradation↗
PubMed2026

Prenatal exome sequencing of fetuses with central nervous system anomalies based on prenatal ultrasound and magnetic resonance imaging diagnosis: A retrospective cohort study with a systematic review and meta-analysis.

INTRODUCTION: Fetal central nervous system (CNS) abnormalities have diverse etiologies, with genetic factors as a major contributor. Prenatal exome sequencing (ES) is a powerful tool for precise molecular diagnosis of CNS anomalies, but its diagnostic yield varies among studies. This study aimed to evaluate the additional diagnostic yield of prenatal ES compared with chromosomal microarray analysis (CMA) in fetuses with CNS anomalies detected by prenatal imaging. MATERIAL AND METHODS: We collected ES results from fetuses diagnosed with CNS anomalies by prenatal imaging (2019-2024) who had negative results. Subgroup analyses assessed phenotype-specific ES diagnostic yield for associated genes and variants. A systematic review and meta-analysis incorporating our data and published studies further explored the association between phenotype and diagnostic yield. RESULTS: In the cohort study of 219 cases, ES identified pathogenic/likely pathogenic single nucleotide variations in 36 cases (16%). The highest diagnostic yield of ES was in cases with multisystem malformations (25%, 14/55), followed by multiple CNS anomalies (15%, 2/13) and isolated CNS anomalies (13%, 20/151). The most commonly identified isolated CNS anomaly was agenesis of the corpus callosum (31%, 5/16). Neural tube defects with urogenital anomalies were associated with a positive ES finding in 57% (4/7) of cases. The meta-analysis of 989 cases from 22 studies showed a pooled diagnostic yield of ES of 27% (95% CI, 21%-34%). The highest diagnostic yield of ES was in cases of corpus callosum anomalies with facial abnormalities (75%, 8/11) and neural tube defects with urogenital malformations (80%, 12/15). The diagnostic yield of ES for three or more CNS abnormalities was 43% (95% CI, 31%-58%), significantly higher than that for only two abnormalities (10%, 95% CI, 4%-18%). No significant difference in diagnostic yield was found between cases identified by prenatal MRI combined with ultrasound (27%, 95% CI, 20%-36%) and those identified by ultrasound alone (25%, 95% CI, 17%-35%). CONCLUSIONS: ES provided a significantly higher diagnostic yield than CMA for fetal CNS abnormalities, with diagnostic yields varying by phenotype. The systematic review and meta-analysis confirmed that the complexity and combination of malformations are key factors associated with differences in ES diagnostic yield.

Humans↗
PubMed2026

Environmentally relevant concentrations of DCOIT impaired lifespan and healthspan in Caenorhabditis elegans.

DCOIT (4,5-dichloro-2-n-octyl-4-isothiazolin-3-one) is an antifouling biocide widely used as an alternative to organotin compounds. While previous studies had focused on its effects on energy production, endocrine disruption, and lipid metabolism, its impact on aging and underlying mechanisms remained unclear. Here, we demonstrated that environmentally relevant concentrations of DCOIT (37, 370 and 3700 ng/L) significantly impaired both lifespan and healthspan in Caenorhabditis elegans. RNA-seq and validation assays revealed that DCOIT upregulated comt-4, a key gene in dopamine metabolism, leading to dopamine depletion and subsequent induction of oxidative stress. This redox imbalance critically contributed to accelerated aging phenotypes. Importantly, both genetic (comt-4 RNAi) and pharmacological (opicapone) interventions restored dopamine levels, alleviated oxidative stress, and reversed DCOIT-induced aging deficits. Our study established the comt-4/dopamine/oxidative stress axis as a central mechanism in DCOIT toxicity, suggesting dopamine modulation as a potential countermeasure against environmental toxicant-induced aging.

Animals↗
PubMed2026

Integrated analysis uncovers exogenous induction and molecular regulation of erinacine A accumulation in Hericium erinaceus.

Erinacine A, a cyathane-type diterpenoid mainly from Hericium erinaceus mycelia, exhibits prominent neurotrophic and neuroprotective activities, making it a promising candidate for managing neurodegenerative diseases. However, its low abundance and unclear genetic regulatory mechanisms hinder its application as a nutraceutical. This study aimed to decipher its regulatory mechanisms and enhance production. Four exogenous inducers were screened, with salicylic acid (SA) and ergosterol (ERG) significantly increasing erinacine A content by 62.21% and 146.70% at 20 days, respectively. Transcriptome and WGCNA of inducer-treated sample identified darkorange and magenta modules associated with erinacine A biosynthesis, with the eri gene cluster enriched in the darkorange module and eriG and eriF as hub genes. Forward genetic analysis via QTL mapping of the HeD127 dikaryon population revealed significant phenotypic variation in erinacine A content (0.341-13.085 mg/g) and identified two loci (erA-1 and erA-2) explaining 18.63% of phenotypic variation. Integrating these forward and reverse genetic analyses revealed that salicylic acid and ergosterol synergistically regulate core carbon metabolic pathways to augment acetyl-CoA supply for the mevalonate pathway, suppressed competitive metabolism, enhanced diterpene skeleton construction and structural modification. These results deepen our understanding of the genetic and molecular basis governing accumulation of erinacine A, and facilitate its application in neuroprotective pharmaceuticals.

Diterpenes↗
PubMed2026

Tissue-derived extracellular matrix hydrogels instruct epigenetic adaptation in metastatic colonization.

The extracellular matrix (ECM) plays a central role in regulating tumor progression and metastatic colonization by providing biochemical and mechanical signals that shape cancer cell fate. However, most organoid culture systems rely on basement membrane extracts that fail to reproduce the tissue-specific extracellular environments encountered during metastasis. Here, we develop tissue-derived decellularized matrix hydrogels to reconstruct organ-specific microenvironments and investigate epigenetic adaptation to ECM cues during metastatic colonization. Patient-derived colorectal cancer organoids cultured in colon-derived matrices exhibited enhanced maintenance of stem-like phenotypes and colon-specific chromatin accessibility landscapes compared with cultures grown in basement membrane extracts, demonstrating improved physiological relevance for primary tumor modeling. When exposed to matrices derived from secondary organs, the organoids showed distinct growth phenotypes accompanied by rapid, tissue-dependent chromatin accessibility remodeling, indicating that ECM composition alone can reshape regulatory programs governing metastatic adaptation. Notably, liver-derived matrices selectively activated hepatocyte nuclear factor 4 alpha (HNF4A)-associated transcriptional networks and created a context-specific dependence on c-MET signaling for survival. Functional perturbation of HNF4A or c-MET signaling confirmed that both are required for organoid formation specifically within the liver matrix environment. Together, these findings establish tissue-derived matrix hydrogels as instructive bioactive materials that actively regulate cancer cell epigenetic states and reveal microenvironment-specific therapeutic vulnerabilities during early metastatic colonization.

Journal Article↗
PubMed2026

A multi-model genome-wide association study identifies genetic variants underlying resistance to Largemouth Bass Ranavirus (LMBV) in Micropterus salmoides.

Largemouth bass (Micropterus salmoides) is an economically important freshwater aquaculture species, yet recurrent outbreaks of Largemouth Bass Ranavirus (LMBV) continue to impair production and cause substantial losses. The genetic basis of host variation in LMBV resistance remains insufficiently characterized. Here, we applied a multi-model genome-wide association study (GWAS) to identify loci associated with resistance following a controlled challenge with the LMBV-23PY strain. Whole-genome resequencing was performed for 146 phenotyped fish, including 72 susceptible and 74 resistant individuals. After stringent quality control, 877,262 high-quality variants were retained and tested using six GWAS models. Across binary survival status and survival time phenotypes, 32 shared suggestive variants were consistently detected across models, representing suggestive loci for LMBV-23PY resistance. Genes within ±50 kb of these loci were annotated, and functional enrichment highlighted immune- and redox-related biological processes. Three prioritized candidates-GSTT3L (glutathione S-transferase theta-3-like), CGRP2 (calcitonin gene-related peptide 2), and NPPC (natriuretic peptide C)-were associated with pathways involved in oxidative stress responses and immune regulation. Collectively, these results provide insight into the genetic architecture of LMBV-23PY resistance in largemouth bass and identify suggestive variants and associated candidate genes for downstream validation, functional interrogation, and the development of marker-assisted and genome-enabled breeding strategies.

Animals↗
PubMed2026

GATA2 deficiency: enhancer deregulation, immune surveillance failure, and clonal evolution.

Germline mutations in GATA2 cause a syndromic inborn error of immunity characterized by cytopenia, infections, immune dysregulation, and a marked predisposition to myelodysplastic syndrome and acute myeloid leukemia. Initially defined by the DCML phenotype-dendritic cell, monocyte, B- and NK-cell deficiency-GATA2 deficiency is now recognized as a disorder of global immune-hematopoietic homeostasis. Recent multi-omics and experimental models reveal enhancer-driven inflammatory rewiring, IRF8-dependent lineage imbalance, and premature hematopoietic aging. In parallel, adaptive immune defects, including impaired B- and T-cell development and function, contribute to defective immune surveillance. These alterations not only explain susceptibility to infection but also shape clonal evolution and malignant transformation. Clinically, improved risk stratification and transplant outcomes underscore the importance of early recognition and monitoring of immune dysfunction. GATA2 deficiency thus represents a paradigm linking immune dysregulation, inflammatory stress, and cancer predisposition.

Humans↗
PubMed2026

Complete genome sequence of multidrug-resistant Salmonella enterica subsp. enterica serovar Enteritidis SD191 isolated from chicken liver, harboring a novel imipenem resistance mechanism.

We present the complete genome sequence of Salmonella enterica subsp. enterica serovar Enteritidis SD191 isolated from Gallus gallus liver in China, harboring plasmid pSE191. The genome reveals multiple antibiotic resistance mechanisms and phenotypic imipenem resistance without canonical genes.

antibiotic resistance↗
PubMed2026

Azithromycin-resistant Salmonella enterica Typhi with AcrB R717L/Q mutations in the United States.

BACKGROUND AND OBJECTIVES: Azithromycin is a critical oral treatment for typhoid fever caused by Salmonella enterica serovar Typhi (Salmonella Typhi), since XDR has rendered other first-line treatment options ineffective. Azithromycin resistance conferred by amino acid changes in AcrB, an AcrAB-TolC efflux pump component, represents an emerging public health concern. Leveraging phenotypic and genotypic data from U.S. Salmonella Typhi surveillance systems, this study describes the prevalence, phenotype and genomic epidemiology of Salmonella Typhi with AcrB mutations in U.S. patients since the first detection in 2015. METHODS: AST and WGS data of >3000 Salmonella Typhi isolates were used to identify all cases with an AcrB mutation in the United States (2015-2025). We calculated annual prevalence and MIC ranges. Phylogenetic analysis was used to contextualize U.S. cases of Salmonella Typhi with an AcrB mutation within all globally reported cases. RESULTS: While the prevalence of AcrB mutations in the United States is low (1.5%), it has risen significantly in recent years, from 0.2% in 2016-2022 to 2.2% in 2023-2025. This increase is predominantly driven by clonal expansion of existing strains circulating in South Asia. AcrB mutations do not reliably confer resistance to azithromycin (MIC ≥ 32 mg/L), complicating clinical interpretation. CONCLUSIONS: The prevalence of AcrB mutations in Salmonella Typhi is increasing in the United States, and likely globally, given that U.S. data function as an informal proxy for regions without routine surveillance infrastructure. Clinical outcomes data are needed to inform Salmonella Typhi treatment guidelines and potentially amend clinical breakpoints for azithromycin.

Journal Article↗
PubMed2026

Review: The African turquoise killifish as a model for the integrative physiology of vertebrate aging.

With increasing emphasis on extending healthy lifespan, aging research requires vertebrate models that permit efficient mechanistic investigation and intervention testing within practical time and cost constraints. The African turquoise killifish (Nothobranchius furzeri) has attracted growing attention because it combines an exceptionally short life cycle with an intact vertebrate physiological context and an expanding genetic toolkit, enabling relatively rapid evaluation of candidate aging interventions and mechanistic analysis across molecular, tissue, and organismal levels. This review assesses N. furzeri from an integrative-physiology perspective, focusing on germline-soma interactions, gut microbiota-host crosstalk, nutrient sensing and metabolic remodeling, temperature responsiveness, and AMPK-mTOR-linked programs. It also examines expanding genome-engineering and reporter approaches that support mechanistic and tissue-resolved investigation of these physiological processes. Building on recent reviews of killifish biology, disease modeling, regeneration, and the hallmarks of aging, we synthesize evidence across major intervention domains, distinguish established phenotypic effects from incompletely resolved mechanisms, and highlight functional endpoints, methodological standardization, and the appropriate interpretation of the model's translational relevance. Together, these features position N. furzeri as a strategically useful vertebrate platform for rapid mechanistic testing, intervention evaluation, and prioritization of aging-related pathways. Future progress will require improved methodological standardization, tissue-resolved causal studies, and question-driven cross-species validation where appropriate.

Animals↗
PubMed2026

Ensemble DNA methylation clock demonstrates Immune-metabolic aging signatures associated with mortality.

Aging is a multifactorial process that is best described in terms of the progressive acquisition of multiple layers of phenotypic changes, such as epigenetic modifications, inflammation, and metabolic dysregulation. DNA methylation clocks have been extensively used to construct epigenetic clocks based on the DNAm profiles that can be used to estimate biological age and predict age-associated outcomes. Nevertheless, the vast majority of clocks constructed so far have been based on linear models, which are unlikely to fully account for the heterogeneity and non-linearity of survival-related DNAm signatures. In this work, we constructed a heterogeneous stacked ensemble survival model based on DNAm data obtained from the Framingham Heart Study. We first identified 190 CpG loci using elastic net Cox regression and subsequently constructed a survival prediction model based on the fusion of five complementary survival models by means of a neural network meta-learner. The prediction power of the survival model was evaluated in an external validation cohort, where we observed strong performance for predicting all-cause mortality that significantly exceeded PhenoAge and was statistically comparable to GrimAge. These performance estimates were derived in cohorts of European ancestry and externally validated in postmenopausal women aged 50-79 years, and should therefore be interpreted as applicable only to demographically similar populations.

Humans↗
PubMed2026

Clinical and endocrine correlates of genetic etiologies in severe hypospadias: Study from 34 patients.

OBJECTIVE: Hypospadias is a prevalent congenital anomaly (0.3%-1.0%); however, severe hypospadias (defined as proximal cases with the meatus at the penoscrotal junction, scrotum, or perineum) is a rare and clinically challenging entity with a multifactorial etiology. This study aimed to characterize the interrelationships among the clinical, endocrine, and genetic profiles in children with severe hypospadias. MATERIALS AND METHODS: We conducted a comprehensive analysis of 34 male patients with severe hypospadias. Preoperative hormone levels were measured using two methods: chemiluminescent immunoassay for luteinizing hormone and follicle-stimulating hormone, and liquid chromatography-tandem mass spectrometry for testosterone (T), dihydrotestosterone (DHT), dehydroepiandrosterone (DHEA), 17α-hydroxyprogesterone (17α-OHP), and other steroids. Genetic analysis was conducted via whole exome sequencing. RESULTS: The diagnostic yield of clinically relevant genetic variants (including pathogenic and likely pathogenic, and variants of uncertain significance) in our cohort was 41.2% (14/34) of patients. Patients carrying these variants exhibited a more complex phenotypic profile compared to non-carriers, including a significantly higher rate of patients with ≥3 associated malformations and a greater prevalence of cryptorchidism. Furthermore, the group with clinically relevant variants showed selective elevations in adrenal-derived precursors, specifically 17α-OHP and DHEA. Correlation analysis revealed significant positive associations of both 17α-OHP levels and the T/DHT ratio with the number of associated malformations. CONCLUSION: This study reveals significant genetic heterogeneity in patients with severe hypospadias. Those carrying genetic variants was associated with more severe clinical phenotypes, while certain endocrine variations, including the elevation of adrenal-derived hormones, were also observed in this cohort.

Humans↗
PubMed2026

ReMeDy: A Flexible Statistical Framework for Region-Based Detection of DNA Methylation Dysregulation.

Region-based epigenome-wide association studies have demonstrated improved statistical power and biological interpretability compared with probe-wise analyses of DNA methylation data. However, most existing region-based methods characterize methylation dysregulation primarily through changes in mean methylation levels associated with a phenotype of interest. Substantial evidence indicates that phenotype-associated methylation alterations may also manifest through changes in methylation variability or through joint shifts in mean and variability. Despite this, no existing statistical framework jointly models mean-variance methylation changes in a region-based manner. We propose ReMeDy, a flexible statistical framework that uses a hierarchical likelihood approach within a generalized linear model setting to identify differentially methylated regions, variably methylated regions, and regions exhibiting joint differential and variable methylation at a genome-wide scale. Unlike existing models, ReMeDy operates directly on biologically defined co-methylated regions, allowing it to naturally capture spatial correlation inherent in DNA methylation array data, while avoiding reliance on heuristic, user-defined tuning parameters such as smoothing spans and kernel bandwidths that can substantially influence results and introduce subjectivity. Through extensive simulation studies and comprehensive benchmarking against popular models, we demonstrate that ReMeDy maintains false discovery and Type-I error rates at nominal levels while achieving consistently higher statistical power across a wide range of realistic scenarios. Application to population-level DNA methylation data further shows that ReMeDy identifies biologically meaningful regions and pathways implicated in complex human diseases that are not captured by conventional mean-based analyses alone. ReMeDy is implemented as an open-source R package and is freely available at https://github.com/SChatLab/ReMeDy.

DNA Methylation↗