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Depletion of the splicing factor RBM39 disrupts spliceosome function and induces widespread RNA splicing defects, leading to antiproliferative effects in susceptible cancer cells. Here, we report the discovery and characterization of a new series of biphenyl-containing RBM39 degraders. The lead compound 42 promotes RBM39 degradation through formation of a ternary complex with RBM39 and DCAF15/DDB1 in a Cullin-RING E3 ligase- and proteasome-dependent manner, consistent with a molecular glue mechanism. Transcriptomic analyses in HCT-116 and K562 cells revealed extensive alternative splicing alterations and suppression of cell-cycle-associated pathways, resulting in G2/M-phase arrest without apoptosis. Comparative cellular profiling identified 41 (YSA64) as a potent analog in acute myeloid leukemia MV4-11 cells and Ewing sarcoma A673 cells, disease contexts that have been minimally explored for RBM39 degraders. Notably, 41 exhibited favorable oral pharmacokinetics and significant antitumor efficacy in MV4-11 xenograft models. Collectively, this work expands the chemical space of RBM39 degraders and supports their continued development as RNA splicing-targeted anticancer agents.

Alterations of the gut microbiome have been reported in central nervous system demyelinating diseases. While the gut microbiome in pediatric multiple sclerosis (MS) has been studied, the role of the gut microbiome in other pediatric-onset acquired demyelinating syndromes (ADS) remains unknown. We compared the gut microbiome composition between myelin oligodendrocyte glycoprotein antibody-positive (MOG+) and antibody-negative (MOG-) participants with pediatric-onset ADS. Participants aged &#x2264;21 years enrolled in the Canadian Pediatric Demyelinating Disease Network microbiome study (2015-2018) with a single episode or relapsing non-MS, non-neuromyelitis optica spectrum disease attacks of demyelination with symptom onset <18 years were included. Stool sample-derived DNA underwent 16S rRNA (V4) sequencing. Serum MOG-IgG antibodies were tested within 30 days of first attack onset. Alpha-diversity (Shannon, Margalef's index, Chao1) and beta-diversity (weighted UniFrac) were analysed. Phylum/genus-level taxa were assessed using negative binomial models with false discovery rate correction. Rate ratios were sex- and age-adjusted (aRR). Forty-six participants (18 MOG+/28 MOG-) were included. Mean age at stool sample collection (MOG+/MOG-) was 14.7/17.2 years. Alpha-/beta-diversities did not differ between MOG+/MOG- participants (p > 0.3). At the phylum level, the relative abundance of Proteobacteria was lower in MOG+ than MOG- participants (aRR:0.22;95%CI:0.07-0.69;q = 0.03). At the genus level, the relative abundance of Escherichia/Shigella was lower in MOG+ than MOG- participants (aRR:0.01;95%CI:0.001-0.07;q = 0.001), CONCLUSIONS: While alpha/beta-diversities did not differ between MOG+/MOG- participants, taxa-level differences were observed. Our findings suggest that the gut microbiome composition may differ by MOG serostatus among pediatric-onset ADS participants. Future work is warranted, utilizing larger cohorts and longitudinal follow-up.

Adrenocortical tumors (ACTs) are rare pediatric malignancies, typically presenting with signs of virilization or hypercortisolism. However, non-classical presentations may delay diagnosis and complicate management. Our study aimed to illustrate the diagnostic and therapeutic challenges posed by atypical forms of pediatric ACTs through a series of five diverse clinical cases. We report five cases of pediatric ACTs with unusual features: bilateral tumors, acute stroke due to hypertensive crisis, incidental discovery after trauma, misleading hormonal workup, or gradual onset of premature pubarche, and hemorrhagic lesion,. In two cases, the diagnosis was delayed due to initial absence of endocrine evaluation. One patient experienced tumor rupture following biopsy, leading to metastasis and death despite intensive treatment. Histopathological scoring (Wieneke score) was heterogeneous and did not always correlate with outcome. Two patients had underlying cancer predisposition syndromes (Li-Fraumeni and Beckwith-Wiedemann). This case series highlights the wide phenotypic variability of pediatric ACTs, which may mimic benign or unrelated conditions. Early recognition, systematic hormonal evaluation, and avoidance of biopsy are critical for improving prognosis. Multidisciplinary management is essential, and genetic screening should be systematically considered, even in the absence of suggestive personal or familial history.

Background/Objectives: Brain death determination in children is clinically challenging. When standard clinical examination cannot be completed or reliably interpreted, ancillary testing is required-yet many established methods depend on infrastructure or patient transport that may not be feasible in critically ill pediatric patients. Orbital ultrasonography is bedside-applicable and non-invasive, but remains poorly characterized in children. Methods: We conducted a single-center retrospective study of 28 pediatric patients evaluated for suspected brain death between January 2021 and February 2025. Patients were classified as brain death-positive [BD(+), n = 20] or brain death-negative [BD(-), n = 8] based on clinical criteria independent of imaging findings. Orbital color Doppler parameters (ophthalmic artery, central retinal artery, posterior ciliary artery) and optic nerve sheath diameter (ONSD) were measured under a standardized protocol by a single experienced operator. Ophthalmic artery resistive index (OA-RI) was defined a priori as the primary outcome; ONSD was the secondary outcome. Group comparisons used the Mann-Whitney U test with Cliff's delta effect sizes; false discovery rate correction was applied to secondary and exploratory comparisons. ROC analyses were performed to assess discriminative performance. The study was reported in accordance with the STARD 2015 guidelines for diagnostic accuracy research. Results: OA-RI was markedly higher in BD(+) patients (0.84 [IQR 0.80-0.90] vs. 0.65 [0.58-0.69]; p < 0.001; &#x3b4; = 0.975). ROC analysis yielded an AUC of 0.99 (95% CI: 0.96-1.00); at a cut-off of &#x2265;0.77, sensitivity was 95.0% and specificity 100.0%. ONSD also differed significantly between groups (4.75 [4.15-5.08] mm vs. 3.90 [3.40-4.15] mm; p = 0.012; &#x3b4; = 0.619; AUC = 0.81, 95% CI: 0.62-1.00; cut-off &#x2265; 4.2 mm; sensitivity and specificity both 75.0%). Across all three orbital vessels, end-diastolic velocity was consistently reduced and resistive indices elevated in BD(+) patients. Systolic velocities did not differ meaningfully between groups. Cut-off values represent cohort-specific statistical optima and should be interpreted as exploratory. Conclusions: Orbital Doppler ultrasonography demonstrates a coherent high-resistance hemodynamic pattern in pediatric brain death. OA-RI showed strong discriminative performance and may serve as a useful bedside adjunct in selected cases where ancillary testing is indicated. ONSD provides complementary anatomical evidence. These findings are exploratory and require prospective validation in larger, multicenter pediatric cohorts.

Pediatric stroke, although relatively rare, poses considerable health risks with substantial morbidity and mortality. Despite its clinical impact, comprehensive global assessments of its long-term trends and disparities remain limited. Using estimates from the Global Burden of Disease (GBD) 2021 study, we evaluated the burden of pediatric stroke-including both hemorrhagic stroke (HS) and ischemic stroke (IS)-across 204 countries and territories from 1990 to 2021. Our original analyses included the calculation of the estimated annual percentage change (EAPC) of age-standardized rates, stratified by age, sex, and sociodemographic index (SDI). In 2021, there were approximately 2.7 million prevalent pediatric stroke cases worldwide, with HS contributing 41.4% and IS 58.6%. Globally, stroke-related disability-adjusted life years (DALYs) declined from about 5.9 million in 1990 to 2.4 million in 2021. However, the incidence among adolescents aged 10-19&#xa0;years increased during this period. Marked geographic disparities were observed, with low-SDI regions experiencing disproportionately higher burdens, particularly from HS. India recorded the highest number of DALYs and incident cases in 2021. These findings provide a comprehensive global analysis focused specifically on pediatric stroke, underscoring that although the overall burden has declined, persistent and widening disparities highlight the need for targeted strategies, improved early recognition and strengthened healthcare systems in resource-limited regions.

Sepsis-induced acute kidney injury (S-AKI) is a common and serious complication in critically ill children with a poor prognosis, and its early and accurate prediction remains challenging due to the lack of reliable biomarkers. Urinary small-molecule metabolomics offers a promising approach to capture the dynamic metabolic changes during the progression of S-AKI. In this two-center prospective observational study, we enrolled 360 children from both centers. Urine samples were collected within 24h after hospitalized children diagnosed with sepsis, stored at -80&#x2009;&#xb0;C, and analyzed using gas chromatography-mass spectrometry (GC-MS). Based on urinary metabolic fingerprints (U-MF), we developed and validated a machine learning model for early prediction of S-AKI. The Shapley Additive Explanations (SHAP) algorithm was applied to visually explain the optimal model. A panel of 10 metabolites was selected as common discriminative features. Among the 4 machine learning models evaluated, the support vector machine (SVM) demonstrated the best performance in both the discovery cohort (AUC 0.94, 95% CI: 0.91-0.98) and the external validation cohort (AUC 0.89, 95% CI: 0.82-0.96), enabling early prediction of S-AKI within 24&#x2009;h. Furthermore, the U-MF panel was integrated into an open-access online platform to facilitate clinical translation. Our findings suggest that U-MF combined with machine learning holds promise as a robust and noninvasive approach with potential utility for early prediction of S-AKI in pediatric patients.

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Biomarkers are needed to predict treatment response and guide therapeutic decisions in Crohn disease (CD). We aimed to develop and validate a multi-omics machine learning (ML) model to predict response to nutritional therapy in pediatric CD. Treatment-naive children with newly diagnosed CD who were initiating exclusive enteral nutrition (EEN) were prospectively enrolled in this study. Metabolomics and lipidomics were measured in the serum and stool, as well as the fecal microbiome. Following feature selection via minimum redundancy maximum relevance, random-forest models were constructed for single- and multi-omics and performances were evaluated. The models were externally validated in an independent prospective cohort of treatment-naive children and young adults with CD treated with EEN. The discovery cohort consisted of 50 children (mean&#x2009;&#xb1;&#x2009;SD age 14.3&#x2009;&#xb1;&#x2009;2.7&#x2009;years), of whom 34 (68%) responded to EEN. Combining complementary signals from host metabolism, gut microbiota, and lipid profiles from serum and stool in a multi-omics ML model yielded a model for predicting treatment response (training accuracy 94%; 95% CI, 82%-100%). Key predictive features included serum metabolites (2-hydroxyglutaric acid, Cer[d18:0/22:0], and HexCer[d18:1/d26:1]), fecal metabolites (3-methyladipic acid, DG[16:0&#x202f;20:0], PC aa C42:2), and microbial taxa (family Bifidobacteriaceae and genus CAG-56). The validation cohort consisted of 21 patients of whom 12 (57%) responded to EEN. The multi-omics model performance achieved an area under the receiver operating characteristic curve (AUROC) of 0.81 (95% CI, 0.6-1.0). Clinical and endoscopic features did not improve the predictive ability of the model. As a proof-of-concept, we showed that integrated multi-omics ML models can predict EEN response in pediatric CD patients, supporting their potential use in precision nutrition and personalized care strategies. This study developed and externally validated a multi-omics machine-learning model integrating serum and fecal metabolomics, lipidomics, and microbiome data to predict pediatric Crohn disease response to exclusive enteral nutrition, achieving high accuracy. This study advances personalized medicine in pediatric IBD.

While the discovery of the glymphatic system has greatly advanced our understanding of waste clearance and fluid dynamics in central nervous system diseases, the neurofluid dynamics in pediatric acute leukemia remain to be elucidated. This study sought to evaluate MRI markers putatively related to neurofluid dynamics in pediatric acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML), including perivascular space (PVS) burden, free water (FW) fraction, and diffusion tensor imaging along the PVS (DTI-ALPS). Seventy-two children with acute leukemia and 72 age- and sex-matched typically developing (TD) children (50 ALL and TDs1; 22 AML and TDs2) were included in this prospective study. Group differences in brain volumetric measures and glymphatic-related MRI markers were evaluated. In addition, MRI metrics that differed significantly between groups were further examined for associations with clinical variables and total sleep scale scores using partial correlation analyses. Compared to TDs, ALL and AML showed no significant differences in intracranial volume. Compared with TDs, decreased brain parenchymal volume and gray matter volume were found in both children with ALL and AML (all FDR-corrected P&#x2009;&#x2264;&#x2009;0.04). Compared with TDs, the ALL group exhibited reduced white matter volume and increased cerebrospinal fluid volume (all FDR-corrected P&#x2009;&#x2264;&#x2009;0.001), while the AML group showed no significant differences in these measures. For glymphatic-related MRI markers, decreased PVS volume and count, FW value, and DTI-ALPS index were observed in both ALL and AML (all FDR-corrected P&#x2009;&#x2264;&#x2009;0.02). In addition, the DTI-ALPS index was negatively correlated with risk stratification and total scale scores in children with ALL (all P&#x2009;&#x2264;&#x2009;0.03). This preliminary, cross-sectional study identified a neuroimaging pattern in pediatric acute leukemia, characterized by reduced brain parenchyma volume and alterations in MRI markers putatively linked to neurofluid dynamics. In patients with ALL, a lower ALPS index was correlated with higher clinical risk stratification and greater sleep disturbance. These observations support future studies to clarify the biological relevance of neurofluid-related imaging features in acute leukemia. ChiCTR2000031353; registered date: 2020-04.

Blood-Heat syndrome is a core syndrome of Traditional Chinese Medicine (TCM) in Henoch-Sch&#xf6;nlein purpura nephritis (HSPN), yet its biological basis remains unclear. This study aimed to systematically elucidate the scientific basis of Blood-Heat syndrome within the context of HSPN and to identify its objective biomarkers using a multidimensional biological approach. In the clinical research part, we divided it into a discovery cohort and a validation cohort. The discovery cohort employed Data-Independent Acquisition (DIA) proteomics technology to analyze serum samples from HSPN patients with Blood-Heat syndrome (n = 15), those without Blood-Heat syndrome (non-Blood-Heat, n = 30), and healthy controls (n = 30). The findings were then validated through ELISA in both the discovery cohort and an independent validation cohort (n = 30 for blood heat syndrome, n = 30 for non-blood heat syndrome). In the basic research component, we established a rat model combining HSPN with Blood-Heat syndrome to replicate the clinical findings. Proteomic analysis identified 87 specific differentially expressed proteins (DEPs) associated with Blood-Heat syndrome. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed significant enrichment in the sphingolipid signaling pathway (P = 0.02). We further identified a panel of nine core biomarkers (AHSG, HRG, KNG1, HP, AZGP1, PTX3, MAPK1, A1BG, and COL1A1), which demonstrated excellent diagnostic performance in distinguishing between healthy control group and blood-heat syndrome, as well as between blood-heat syndrome and non-blood-heat syndrome (with AUC values all &#x2265;0.7). ELISA validation showed that, compared to the healthy control group and non-Blood-Heat group, the levels of AHSG, HRG, and KNG1 were significantly downregulated in the Blood-Heat group, while the other six markers were significantly upregulated (P < 0.01 for all). This trend was fully replicated in the HSPN Blood-Heat syndrome rat model. Based on multidimensional evidence from clinical proteomics and animal model replication, this study suggests that Blood-Heat syndrome in the context of HSPN has a reproducible molecular phenotype. The functional enrichment of its differential proteins involves the sphingolipid signaling pathway, accompanied by an enhanced inflammatory background represented by ERK2 upregulation. Based on these findings, we propose a core scientific hypothesis of "Blood-Heat-related stress-sphingolipid signaling-associated alterations-ERK2-mediated inflammatory amplification," providing a direction for future mechanistic validation and targeted intervention research.

CD4+ Th1 cells migrate to sites of inflammation, where they are indispensable for eliminating intracellular pathogens. The lineage-defining transcription factor T-bet establishes the T-helper 1 (Th1) transcriptional program, directing IFN-&#x3b3; to drive effector responses and inducing subordinate transcription factors to shape the Th1 phenotype. Aberrant Th1 cell activity drives the pathogenesis of multiple autoimmune diseases, but the detailed mechanisms by which Th1 cells maintain or lose their integrity remain largely uncharacterized. Using immunogenomics and high-resolution immune phenotyping in human CD4+ cells, we discovered that the transcription factor ZEB2 is lineage restricted to Th1 effector memory (EM) cells. Detailed molecular validation using CRISPR/Cas9 deletion of ZEB2, whole genome transcriptomics, and pathway mapping, supported by protein expression and assay for functional changes, revealed that ZEB2 is a signaling hub for multiple pathways, stabilizing the integrity and function of human CD4+ Th1 EM cells. Furthermore, our disease-linked pathway mapping and discovery of reduced ZEB2 in a cohort of pediatric ulcerative colitis patients suggests that ZEB2 is implicated in the control of Th1-mediated autoimmune disease. ZEB2 is lineage restricted to human Th1 Effector Memory (EM) cells. ZEB2 regulates IFN-&#x3b3; and a transcriptional program to stabilize the integrity of Th1 EM cells. ZEB2 is reduced in pediatric Ulcerative Colitis in Th1EM cells, confirming disease-linked pathway mapping.

Type 1 diabetes (T1D) has a large genetic component, and expanded genetic studies of T1D can enhance biological and therapeutic discovery and improve risk prediction. Here we performed genome-wide genetic association and fine-mapping analyses in 20,355 T1D and 797,363 nondiabetic individuals of European ancestry and in 10,107 T1D and 19,639 nondiabetic individuals at the MHC locus, which identified 160 risk signals. We trained a machine learning model, T1GRS, to predict T1D using genetic risk, which improved classification in Europeans and performed similarly in African Americans, compared to previous scores. T1GRS particularly improved prediction in T1D, with fewer high-risk HLA haplotypes and more complex risk profiles, and revealed 154 nonlinear interactions between MHC and non-MHC loci. Finally, we identified four genetic subclusters based on T1GRS features with significant differences in age of onset and diabetic complications. Overall, improved genetic discovery and prediction will have wide clinical, therapeutic and research applications for T1D.

Adult intussusception is a rare clinical condition. Unlike in pediatric cases, adult intussusception often has a definable lead point, with benign or malignant tumors being the most common etiology. Small intestinal lipoma is a rare cause of adult intussusception. It typically presents with non-specific symptoms and an insidious onset, frequently leading to misdiagnosis or discovery only during emergency surgery. Abdominal computed tomography (CT) plays a pivotal role in preoperative diagnosis, yet its specific findings in lipoma-induced intussusception warrant further emphasis. A 30-year-old man presented with a one-week history of abdominal pain and distension, followed by dark red bloody stools for four days. Physical examination revealed abdominal distension and right lower quadrant tenderness without rebound tenderness. Laboratory tests showed mildly elevated inflammatory markers. Abdominal CT revealed ileocolic intussusception with a well-defined lesion at the lead point demonstrating homogeneous fat attenuation (approximately -53 Hounsfield units), a finding pathognomonic for a lipoma. Emergency exploratory laparotomy confirmed an irreducible ileal intussusception into the cecum and ascending colon. An ileocecal resection with side-to-side anastomosis was performed. Pathological examination of the resected specimen confirmed a 4.0 cm &#xd7; 3.0 cm &#xd7; 2.5 cm submucosal ileal lipoma with overlying mucosal erosion. The patient recovered well after surgery despite a minor wound infection, and no recurrence was observed during the five-month follow-up period. CT is the modality of choice for diagnosing ileal lipoma-induced intussusception, as it can definitively identify the pathognomonic fat-density lead point. Surgical resection remains the definitive treatment, yielding good outcomes.

The transition from untargeted discovery to targeted validation in metabolomics is a major challenge, often hindered by poor method transferability and retention time (RT) variation between liquid chromatography-mass spectrometry (LC-MS) platforms. To address this, "Scout-MRM Builder," an R-based package for the automated creation of highly multiplexed targeted methods from untargeted high-resolution MS2 data, is presented here. A Scout-Triggered Multiple Reaction Monitoring (StMRM) strategy is employed, using N-Alkylpyridinium-3-Sulfonate (NAPS) standards as dynamic RT markers ("scouts"). A specific list of transitions is triggered by the detection of each scout, ensuring robustness against RT shifts. Ion pairs are automatically extracted, scouts are identified, and ready-to-use StMRM methods, including pseudo-MRM transitions for features lacking fragmentation spectra, are generated. From an untargeted analysis of porcine liver extracts, a single StMRM method monitoring 1312 transitions was generated from 558 features. High reproducibility was demonstrated, with 89.9% of detected transitions exhibiting a relative standard deviation (RSD) below 20%. When applied to a model of liver ischemia-reperfusion injury, results highly comparable to the initial untargeted analysis were obtained. A common core of potential biomarkers was identified, with slightly improved statistical performance. In conclusion, the Scout-MRM Builder provides a powerful framework to bridge the gap between discovery and validation, enabling robust targeted analysis at an untargeted scale through enhanced method transferability and reliability.

Cross-study inconsistencies in autism spectrum disorder (ASD) blood microRNA biomarker studies suggest that methodological heterogeneity may substantially limit reproducibility. We conducted an exploratory meta-analysis of publicly available ASD blood miRNA datasets from the Gene Expression Omnibus, applying rigorous inclusion criteria and standardized analytical protocols. Three datasets were included (GSE89596, GSE67979, GSE222046) comprising 614 miRNAs across 90 participants (45 ASD, 45 controls). Random-effects meta-analysis was performed using Hedges' g effect sizes, with comprehensive heterogeneity assessment and leave-one-dataset-out cross-validation. No miRNAs survived multiple testing correction (Benjamini-Hochberg FDR&#x2009;<&#x2009;0.05), though seven candidate signals showed consistent evidence with unadjusted p&#x2009;<&#x2009;0.01 and large effect sizes. These candidates demonstrated near-zero between-study heterogeneity and consistent directionality across validation analyses. Potential age-related and platform-related differences were observed, with near-zero correlation between adult and pediatric effect sizes (Kendall's &#x3c4; = -0.022); however, these two sources of variability were fully confounded in the available data and could not be separated. Some miRNAs exhibited extreme between-study variability (I&#xb2; > 80%), indicating substantial methodological differences. Cross-validation revealed that excluding the single adult dataset reduced sign consistency from 89.9% to 68.9%. Our findings suggest that age-related and methodological factors, including technical platform differences, may contribute to limited reproducibility in ASD blood miRNA research, and that blood-derived signals should be interpreted as potentially reflecting peripheral physiological states rather than central disease mechanisms. A supplementary cross-tissue analysis using post-mortem prefrontal cortex data (GSE59286; n&#x2009;=&#x2009;45) provided direct empirical support for this interpretation: the majority of blood candidate miRNAs showed no corresponding expression in brain tissue, with only hsa-miR-29c-5p demonstrating directional concordance across both tissues. These findings suggest that age stratification, platform harmonization, and cross-tissue validation should be considered essential prerequisites for reliable ASD miRNA biomarker discovery, rather than optional refinements.

Oncogenic fusions, arising from chromosomal rearrangements, occur in several cancers, particularly in those of pediatric origin. Advances in sequencing technologies have improved fusion detection; yet, understanding their mechanisms and tumorigenic potential remains challenging. This is partly due to the limited availability of faithful human-based model systems. Organoids have emerged as a physiologically relevant model system with in vivo-like traits and have recently allowed to obtain novel mechanistic and therapeutic insights for oncogenic fusion-bearing cancers. This review discusses how, through bottom-up tumor modeling as well as tumoroid derivation, these models are being employed to increase our understanding of fusion-bearing cancers, and how they can help future therapeutic discovery for these tumors.

Childhood obesity is a major predictor of lifelong chronic disease, yet the biological mechanisms linking early-life exposures to adiposity remain incompletely understood. Inflammatory and metabolic proteins have been implicated in obesity-related pathways, but their clinical utility in children is limited by biological variability and the invasiveness of sample collection. DNA methylation (DNAm)-derived protein proxies, or EpiScores, offer a stable, non-invasive alternative tool for capturing systemic physiological processes and may provide novel insights into the early biological embedding of obesity risk. We examined associations between 105 DNAm-derived protein EpiScores and body mass index (BMI) z-scores in a socioeconomically diverse cohort of 31 school-aged children. EpiScores were generated using the MethylDetectR platform, and linear regression models, adjusted for sex, age, race, saliva cell-type proportions, and socioeconomic status (SES; maternal education and annual household income), were used to evaluate associations. Parallel models excluding SES were compared to quantify confounding. False discovery rate (FDR) correction was applied. Functional enrichment and protein-protein interaction (PPI) analyses were performed using STRINGdB. Fifteen EpiScores demonstrated nominal significance with BMI z-score (p&#x2009;&#x2264;&#x2009;0.05) and were further evaluated using a discovery-level FDR threshold (FDR q&#x2009;&#x2264;&#x2009;0.20). VEGFA, MMP-12, MMP-1, and CDL5 showed strong positive associations, while PAPP-A, Resistin, and TGF-&#x3b1; were inversely related to BMI z-score. Adjustment for socioeconomic status (SES) modestly altered several effect estimates, most notably for MMP-1 and CCL17, indicating partial social confounding. Functional enrichment revealed overrepresentation of cytokine-mediated signaling, extracellular matrix organization and angiogenesis pathways, highlighting coordinated immune, metabolic and vascular remodeling processes. Salivary DNAm-derived protein EpiScores capture biologically coherent and socially patterned molecular signatures of adiposity in children. These DNAm-based proxies provide a noninvasive means of detecting early alterations in metabolic regulation and may inform future longitudinal studies integrating biological and socioeconomic determinants of obesity risk.

Extreme-phenotype comparisons allowed the discovery of novel asthma genetic risk loci. However, this approach remains unexplored in epigenome-wide association studies (EWAS). We aimed to identify bulk and cell-specific methylation markers of asthma with severe exacerbations across diverse ancestry groups. We conducted a meta-EWAS of 739,543 CpGs in whole blood among 1,192 African American and Latino pediatric populations, comparing non-asthmatics and asthma exacerbators. Genome-wide CpGs were followed up for replication in a meta-analysis across 1,516 ethnically diverse participants and in a cross-tissue evaluation of 393 nasal samples. We conducted differentially methylated region (DMRs), cell-type-deconvoluted, and quantitative trait loci analyses (whole-genome sequencing n=1,668; RNA-seq n=1,209). We examined enrichment in traits, pathways, and druggable genes, and analyzed DNAm predictors of plasma proteins and aging. DNAm at 505 CpGs and 119 DMRs in whole blood were associated with asthma exacerbations ( p <9x10 -8 , &#x3bb;=1.05). We replicated 25 CpGs in blood cells, cross-validated 7 in nasal samples, and detected 42 cell-specific DNAm markers mainly driven by T cells. DNAm at 134 CpGs was associated with gene expression in whole blood, including 118 associations with T-cell receptor genes, and 446 CpGs were regulated by &#x2265;1 genetic variant. We found enrichment for previous associations with environmental exposures, immune disorders, immune and inflammatory pathways, and druggable genes by developmental drugs. 21 methylation-predicted plasma proteins, involved in host defense, and one lung aging clock were associated with asthma exacerbations. The first meta-EWAS of extreme asthma phenotypes identified hundreds of novel DNAm markers, suggesting novel methylation biomarkers and candidate drugs for asthma and supporting the role of T cells.

The complex relationship between the gut microbiome and immune system development during infancy is considered a key factor in the rising rates of pediatric allergic diseases. Food protein-induced allergic proctocolitis (AP), the earliest identified form of non-IgE-mediated food allergy in infants, occurs at the mucosal surface where dietary proteins, intestinal microbes, and immune cells directly interact, and increases the risk for life threatening IgE-mediated food allergy, making it an important model for understanding early food allergic disease development. The question of how specific microbial compositions and functional pathways contribute to AP development and progression remains poorly understood. We performed metagenomic sequencing on 740 longitudinal stool samples from 163 infants (84 with AP, 79 without AP) enrolled in the prospective GMAP cohort. Taxonomic profiling, functional pathway analysis, strain-level characterization, and machine learning-based classification were applied to identify microbial differences across disease stages. Here we show that infants with AP exhibit different microbial compositions, characterized by enrichment of Escherichia coli and Bifidobacterium bifidum during early life, including pre-symptomatic stages, while species like Bifidobacterium breve and Klebsiella species are more abundant in infants without AP. These findings suggest the presence of microbial signatures that may be detectable before clinical symptoms emerge, and demonstrate that strain-level differences within E. coli populations may represent AP-associated lineages with distinct gene content profiles that were not previously recognized. For example, biofilm formation and cell adhesion genes in E. coli were particularly enriched in AP-associated clades. Short chain fatty acid (SCFA) and other functional pathways were also associated with AP, including reduced SCFA production during the symptomatic phase, and then a potentially compensatory increased production following AP resolution. Our results provide the first comprehensive strain-level characterization of the gut microbiome in AP, and functional implications, and generate new hypotheses to be tested regarding candidate microbial features associated with AP for future biomarker discovery and/or intervention targets. This work advances our understanding of how specific microbial taxa and functional pathways may contribute to non-IgE-mediated food allergies and opens new avenues for microbiome-targeted therapeutic approaches as well as novel prevention targets for IgE-mediated food allergies. The online version contains supplementary material available at 10.1186/s13073-026-01646-6.