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Integrative Long-Read Multi-Omics of a Patient With GPI Deficiency: A Molecular Case Study of a Candidate Dual-Effect GPI Variant.

The molecular determinants of phenotypic severity in red cell enzymopathies are often obscured by the disconnect between coding sequence variants and their regulatory landscapes. Here we present a single-patient molecular case study that uses an integrative multi-omic approach-combining short-read WGS, PacBio HiFi long-read sequencing, native CpG methylation profiling, and Iso-Seq full-length transcriptomics-to characterize a severe, transfusion-dependent hemolytic anaemia. We identified a compound heterozygous state in the glucose-6-phosphate isomerase (GPI) gene, with no wild-type allele present. One allele (Haplotype 1) carried a missense variant (p.His191Arg); the other (Haplotype 2) carried a distinct missense variant, c.1414C>T (p.Arg472Cys), previously reported as biochemically unstable. Long-read phasing placed the two variants in trans. Allele-resolved transcript counts showed a directionally consistent but statistically non-significant trend toward higher expression of Haplotype 2 across two Iso-Seq replicates. Notably, the c.1414C>T transition abolishes a local CpG dinucleotide; in a small number of haplotype-2 reads spanning this position, the corresponding cytosine on the wild-type/Haplotype-1 background was methylated. We did not measure GPI protein abundance, enzymatic activity, or stability in this patient, and we do not establish that methylation at this site regulates GPI transcription. On the basis of these correlative observations in a single patient, we propose-as a hypothesis for future testing-that a coding variant might simultaneously perturb protein stability and disrupt a local epigenetic mark, and we outline the experiments required to test whether such a dual effect contributes to disease. This case illustrates the value of integrative long-read multi-omics for generating mechanistic hypotheses about variants of uncertain significance, while underscoring that causal claims require dedicated functional validation.

Humans↗

Bioinformatics in crop research: using genomic data for crop improvement.

Sustainable crop development aims to maintain or increase yields while reducing environmental impact and managing the challenges imposed by climate change. As the global population grows and arable land becomes scarcer, the integration of molecular breeding with bioinformatics has emerged as an effective strategy for long-term crop improvement. Bioinformatics enables researchers to analyze and interpret the vast quantities of genetic data generated by high-throughput sequencing, making it possible to identify molecular markers, candidate genes, and regulatory networks linked to specific agronomic traits, which breeders then translate into focused, ecologically sustainable breeding programs. This approach has enabled major progress across several fronts: the identification of genes conferring resistance to biotic stressors (pests, pathogens) and abiotic stressors (drought, salinity, heat); the development of nutrient-efficient, low-input crop varieties; the improvement of agronomic performance and nutritional quality through identification of yield- and quality-related genes; and the conservation and deployment of genetic diversity to safeguard long-term breeding sustainability. By combining genomic data with precision breeding techniques, researchers are developing crops that are better adapted to a growing population and a changing climate, positioning the integration of molecular breeding and bioinformatics as a central pillar of future global food security.

bioinformatics↗

Integration of environment and disease into 'omics' analysis.

Over the last decade, 'omics' technologies have been heralded as 'dream toolboxes' that will make revolutionary changes in disease prevention and treatment possible. However, these expectations have yet to be fulfilled. These promises were made and prospects predicted without full appreciation of the intrinsic complexity of common diseases and the significant contribution of environmental factors to disease risk and causation, which have hardly been considered in the omic approaches. The concept of gene-environment interaction, as well as the limitations, difficulties and urgent need to integrate environment into omics analysis are reviewed and discussed.

Delivery of Health Care↗

RePo index: a multidimensional framework to quantify genetic resilience in data-limited amphibian faunas.

This study explores the resilience of Chilean amphibians to environmental disturbances through an integrative approach that combines ecological, demographic, bibliometric, and molecular information. A total of 58 species distributed across 14 genera and 9 families were evaluated via the resilience potential (RePo) index, which incorporates eleven criteria grouped into five dimensions: distribution, population trends, emerging diseases, evolutionary history, and genetic records. The results revealed high ecological vulnerability: 83% of the species were classified as non resilient (45% with no resilience and 38% with low resilience), and none reached the high-resilience category. At the family level, Telmatobiidae presented the lowest resilience values, whereas Leptodactylidae presented the highest. At the genus level, Insuetophrynus was identified as the most vulnerable taxon, with no molecular records and an extremely restricted distribution. In contrast, species such as Rhinella spinulosa and Pleurodema thaul presented moderate resilience, suggesting greater adaptive potential and relevance for functional studies. From a bibliometric perspective, a bias toward classical research topics (distribution, physiology, and taxonomy) was detected, with limited representation of integrative approaches such as genetic conservation or climate change. The conceptual modularity in the literature was low (Q = 0.1328), indicating weak thematic differentiation and little integration of omics tools. Most species lack transcriptomic and genomic data, severely limiting the assessment of their adaptive mechanisms. In this context, the RePo index has emerged as an integrative tool useful for operationalizing concepts such as evolutionarily significant units (ESUs) and management units (MUs), which are essential for evidence-based conservation. Finally, this study highlights the need to incorporate high-throughput sequencing (HTS) technologies and to participate in international initiatives, such as the Amphibian Genomics Consortium, as a strategic path forward for advancing adaptive conservation of Chilean amphibians.

Animals↗

BIOCARD framework: integrating fecal bile acids, lipids, and metabolites to assess response to a cardiovascular health intervention.

Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality, particularly in under-resourced populations. Although nutritional interventions are important for CVD prevention, their outcomes are commonly evaluated using conventional clinical and behavioral indicators, which may not fully capture early molecular responses. In this study, we developed the BIOCARD framework, an exploratory fecal multi-omics platform integrating bile acids, lipids, and metabolites to evaluate intervention outcomes related to cardiovascular health. Fecal samples were collected from caregiver-child participants enrolled in a 10-week randomized controlled trial comparing a multicomponent garden-based intervention (SHA) with an education-only control group (MSP). Fecal polar metabolites, lipids, and bile acids were analyzed by UHPLC-HRMS-based approaches and integrated with conventional health indicators. Traditional clinical indicators in the present study showed limited sensitivity for detecting intervention-related differences. In contrast, fecal multi-omics analyzes revealed intervention-associated differences in metabolites, lipids, and bile acids, with children showing more apparent molecular variation than parents. Network analysis further revealed associations between selected molecular features and cardiovascular-related indicators, including blood pressure, body fat, skin carotenoids, and Healthy Eating Index scores. Together, these findings suggest that the BIOCARD framework may serve as an exploratory molecular approach to complement traditional outcome measures and improve the evaluation of nutritional interventions for cardiovascular health.

Humans↗

Integration of transcriptomics and metabolomics for understanding of global responses to nutritional stresses in Arabidopsis thaliana.

Plant metabolism is a complex set of processes that produce a wide diversity of foods, woods, and medicines. With the genome sequences of Arabidopsis and rice in hands, postgenomics studies integrating all "omics" sciences can depict precise pictures of a whole-cellular process. Here, we present, to our knowledge, the first report of investigation for gene-to-metabolite networks regulating sulfur and nitrogen nutrition and secondary metabolism in Arabidopsis, with integration of metabolomics and transcriptomics. Transcriptome and metabolome analyses were carried out, respectively, with DNA macroarray and several chemical analytical methods, including ultra high-resolution Fourier transform-ion cyclotron MS. Mathematical analyses, including principal component analysis and batch-learning self-organizing map analysis of transcriptome and metabolome data suggested the presence of general responses to sulfur and nitrogen deficiencies. In addition, specific responses to either sulfur or nitrogen deficiency were observed in several metabolic pathways: in particular, the genes and metabolites involved in glucosinolate metabolism were shown to be coordinately modulated. Understanding such gene-to-metabolite networks in primary and secondary metabolism through integration of transcriptomics and metabolomics can lead to identification of gene function and subsequent improvement of production of useful compounds in plants.

Arabidopsis↗

Multi-Omics Landscape of Paraspinal Muscles in Spinal Muscular Atrophy With Scoliosis.

Most spinal muscular atrophy (SMA) patients develop severe scoliosis by late adolescence. Given that the paraspinal muscles-particularly the multifidus-are indispensable for maintaining spinal stability, their site-specific multi-omics characteristics in SMA remain insufficiently defined. Herein, integrated multi-omics sequencing was performed on bilateral multifidus samples from SMA patients and surgical controls. We identified 5219 differentially expressed genes, 1063 differentially expressed proteins and 370 differential metabolites between the control and SMA, showing significant enrichment in glucose and amino acid metabolism pathways, specifically key steps of glycolysis/gluconeogenesis. Key enzymes in the glycolytic process such as PFKM, ENO3 and PKM1 were markedly downregulated. Notably, a comparative analysis of the bilateral paraspinal muscles in SMA revealed asymmetrical metabolic signatures in carbohydrate and amino acid processing between the concave and convex sides. Key regulatory enzymes exhibited significant differential expression: PYGL, a central driver of starch and sucrose metabolism; creatine kinase, involved in arginine and proline metabolism; and PGAM2, a key mediator of glycine, serine, and threonine metabolism. These metabolic signatures indicate a complex metabolic reprogramming in the multifidus, where asymmetric disparities point to the influence of mechanical loading, while systemic dysregulation aligns with the effects of SMN depletion.

Humans↗

Expression and genomic profiling of colorectal cancer.

Colorectal cancer still represents a paradigm for the elucidation of the cellular, genetic and molecular mechanisms that underly solid tumor initiation, progression to malignancy, and metastasis to distal organ sites. The relative ease with which pathological specimens can be obtained by either surgery or endoscopy from different stages of tumor progression has facilitated the application of omics technologies to allow the genome-wide analysis both at the RNA (gene expression) and DNA (aneuploidy) levels. Here, we have reviewed the multiplicity of studies appeared to date in the scientific literature on the expression and genomic analysis of colorectal cancer, and attempted an integration of the profiling data generated and made available in the public domain. This approach is likely to pinpoint specific chromosomal loci and the corresponding genes which (i) play rate-limiting roles in colorectal cancer, (ii) represent putative diagnostic and prognostic markers for the accurate prediction of clinical outcome and response to treatment, and (iii) encompass potential therapeutic targets. Moreover, cross-species data mining and integration of the human colorectal cancer profiles with those obtained from mouse models of intestinal tumorigenesis will even more contribute to the elucidation of highly conserved pathways and cellular functions underlying malignancy in the GI tract. Notwithstanding the above promises, tumor heterogeneity, limited cohort sizes, and methodological differences among experimental and bioinformatic approaches still poses main obstacles towards the optimal utilization and integration of omics profiles.

Adenoma↗

Mitochondria-Related Pathogenic Genes in Paediatric Asthma: A Multi-Omics Mendelian Randomization Study.

Mitochondrial dysfunction is implicated in asthma pathogenesis, but causal roles of mitochondrial-related genes in paediatric asthma remain unclear. We performed a multi-omics Mendelian randomization study integrating GWAS data from paediatric asthma cohorts with blood-based methylation quantitative trait loci (mQTLs), expression QTLs (eQTLs) and protein QTLs (pQTLs) datasets. Causal inference was assessed using Summary-data-based Mendelian Randomization (SMR) and HEIDI testing, complemented by colocalization analysis. Findings were validated in independent cohorts and evaluated for tissue specificity using GTEx. Functional enrichment and protein-protein interaction (PPI) network analyses were conducted. SMR analysis identified 80 methylation sites spanning 54 genes, 26 gene expressions, and three proteins significantly associated with paediatric asthma. Colocalization analysis confirmed strong evidence for 10 methylation sites (7 genes), the STX17 eQTL (PP.H4 = 0.98) and the UNG pQTL (PP.H4 = 0.84). Tissue-specific eQTL validation replicated the STX17 association. Multi-omics integration associated ALAS1 (cg13241645, cg15698299) and TXNRD1 (cg09884423) with asthma at both methylation and expression levels, with colocalization supporting both ALAS1 associations. Furthermore, integrated mQTL-eQTL analysis suggests that DNA methylation potentially regulates ALAS1 and TXNRD1 expression. Functional enrichment and network analyses revealed that these candidate genes converge on mitochondrial metabolic pathways and identified seven hub genes with potential regulatory significance (SDHB, MFN2, GLDC, PHB2, TXNRD1, ATP5MC1 and PHB). This study provides multi-omics evidence supporting a causal role for mitochondrial-related genes, particularly ALAS1 and TXNRD1, in paediatric asthma, offering new insights into pathogenesis and potential therapeutic targets.

Humans↗

Glycerophospholipid remodeling under osmotic stress in grass carp gills.

Salinity fluctuations represent a pervasive environmental challenge for freshwater fishes, yet the cellular and metabolic programs governing early osmoregulatory responses remain understudied. Here, we investigated the time-dependent gill responses of juvenile grass carp (Ctenopharyngodon idella) subjected to an acute, sublethal salinity increase 9 parts per thousand (ppt). Histological and biochemical analyses revealed progressive gill lesions accompanied by elevated lactate dehydrogenase (LDH) activity and lipid peroxidation, indicating rapid tissue injury under osmotic stress. Integrative metabolomic and transcriptomic profiling uncovered pronounced temporal reprogramming, consistently highlighting glycerophospholipid metabolism as a central axis of response. In particular, phosphatidylcholine (PC) species exhibited dynamic remodeling, coupled with transcriptional enrichment of lipid turnover, membrane transport, and innate immune pathways. Network-based integration identified a PC-centered remodeling module characterized by accelerated PC headgroup turnover, disruption of the PLA2-LPCAT2 lyso-PC reacylation cycle, and enhanced ABC transporter-associated lipid and sterol export, reflected by cholesteryl sulfate accumulation and a shifted n-6 polyunsaturated fatty acid-derived oxylipin signature. Functional assays further demonstrated that PC and linoleic acid (LA) supplementation improved cell viability and alleviated oxidative stress and pro-inflammatory signaling in grass carp cells under salinity challenge. Collectively, these findings reveal phospholipid-centered membrane remodeling as an early, integrative mechanism linking osmotic stress to gill injury and immune activation in freshwater fish, providing insights into potential strategies of environmental stress adaptation.

Animals↗

Proteomics in environmental pollution research: Advances, challenges, and future directions.

Environmental proteomics has emerged as a powerful approach for elucidating the molecular mechanisms underlying pollutant-induced biological effects. Although this field has developed rapidly, the systematic review of recent proteomics applications in environmental pollution research remains limited. This review explored the emerging roles of toxicoproteomics in biomarker discovery and mechanistic elucidation, as well as ecotoxicoproteomics in ecological risk assessment and bioremediation strategies. Here, we review the field, highlighting recent trends such as the integration of proteomics with genomics, transcriptomics, and metabolomics to provide a comprehensive view of biological responses to environmental stressors. We further discuss the growing application of artificial intelligence in improving proteomics data interpretation and accelerating biomarker discovery. In addition, recent technological advances in environmental proteomics are highlighted, including next-generation tissue microarray proteomics, nanoscale proteomics, single-cell proteomics, and spatial proteomics. Despite its potential, proteomics faces challenges, such as high operational costs, computational complexity in analysis, and technical limitations in low-abundance protein detection. We propose that the convergence of proteomics with artificial intelligence and multi-omics approaches offers promising solutions to these challenges, enhancing the practical application of proteomics in environmental monitoring and risk assessment.

Proteomics↗

Changes of DNA methylation and gene expression profile in placental villi and chorioamniotic membranes under preeclampsia.

BACKGROUND: Preeclampsia (PE) is a serious pregnancy complication with elusive pathogenesis. Although epigenetic dysregulation is implicated, its layer-specific placental roles are poorly defined. This study aimed to identify shared and layer-specific epigenetic alterations in PE by profiling DNA methylation and gene expression in placental villi (PV) and chorioamniotic membranes (CAM). RESEARCH DESIGN AND METHODS: PV and CAM samples were collected from 7 normal and 8 PE pregnancies, and three public DNA methylation datasets (GSE98224, GSE44667, GSE75196) were integrated. Differentially methylated genes (DMGs) and differentially expressed genes (DEGs) were identified based on whole-genome methylation and transcriptome sequencing. Layer-specific and shared gene sets were identified by cross-analysis, with functional annotation using Gene Ontology (GO). RESULTS: EM-seq revealed a hypermethylation-dominant, tissue-specific methylation landscape in PE placentas. Cross-tissue comparison identified shared DMGs between the two layers, including nine key genes consistently altered in public datasets. Integrated analysis in PV further identified 22 co-dysregulated genes, enriched in thermoregulation, maternal-fetal immunity, signal transduction, and cell differentiation. CONCLUSIONS: This study elucidates the shared and layer-specific dysregulation of gene networks at methylomic and transcriptomic levels in PE placenta. Comparing PV and CAM highlights placental epigenetic heterogeneity and dysfunction, offering novel clues for mechanistic research and layer-targeted therapies.

Humans↗

Long non-coding RNAs link DNA methylation to immune regulatory networks in bovine subclinical mastitis.

Long non-coding RNAs (lncRNAs) are emerging as important regulators of inflammatory and immune signaling, yet their contribution to bovine subclinical mastitis remains poorly defined. Here, we characterized the lncRNA expression landscape associated with disease in milk somatic cells of healthy and subclinical mastitic Vrindavani cattle. We identified 11,403 high-confidence lncRNAs, of which 104 were differentially expressed in subclinical mastitis (adjusted P&#x2009;<&#x2009;0.05; |log2FC| &#x2265; 1), with the vast majority upregulated in mastitic samples. Predicted cis- and trans-associated target analyses identified 637 non-redundant genes, and KEGG analysis identified 8 significantly enriched cis-associated pathways and 152 significantly enriched trans-associated pathways (adjusted P&#x2009;<&#x2009;0.05), predominantly enriched for immune and inflammation-related pathways. These findings prioritized a subset of mastitis-associated lncRNAs for subsequent methylation and interaction-network analyses. A subset of these lncRNAs further overlapped differentially methylated regions (DMRs), suggesting a potential association between lncRNA expression changes and DNA methylation alterations. Integration of lncRNA-miRNA and miRNA-mRNA interactions identified lncRNA-miRNA-mRNA interaction networks involving DMR-associated lncRNAs. Among the prioritized candidates, MSTRG.28878.1 showed overlap with a hypomethylated promoter-associated DMR, increased expression, and multiple connections within the predicted interaction network. Together, these findings identify candidate lncRNAs, methylation-associated loci, and predicted molecular interactions associated with bovine subclinical mastitis and provide a resource for future functional investigation of candidate non-coding RNA-associated mechanisms in disease.

Animals↗

Integrative Genomic, Transcriptomic and Epigenomic Analysis Reveals cis-regulatory Contributions to High-altitude Adaptation in Tibetan Pigs.

The Qinghai-Tibet Plateau, characterized by its extreme environmental conditions, presents significant challenges to life, making it an ideal region for studying adaptation and evolution. Tibetan pigs, known for their high genetic diversity and exceptional adaptability to high altitudes, serve as excellent models for investigating high-altitude adaptation. While previous studies have extensively identified genetic determinants associated with high-altitude adaptation, the molecular mechanisms, particularly cis-regulatory patterns, remain poorly understood. Here, we conducted a selective sweep analysis using 484 genomes from Chinese and Western pig breeds across various altitudes, revealing 38.56 Mb of genomic regions under selection in Tibetan pigs. Enrichment analysis identified the lung as the primary functional tissue involved in high-altitude adaptation, supported by tissue-specific transcriptional and regulatory patterns observed between Tibetan and Meishan pigs (low altitude). By integrating genomic, RNA-seq, ATAC-seq, and H3K27ac HiChIP data, we constructed comprehensive enhancer-promoter regulatory maps of candidate genes and pinpointed promising genetic determinants associated with high-altitude adaptation, including SNPs in EPAS1, KLF13, SPRED1, and CFD. These loci were predicted to influence chromatin accessibility and the interactions of regulatory elements, with altered binding strength of relevant transcription factors. Further in vitro experiments confirmed that these loci function as allele-specific enhancers, modulating the expression of target genes. Our findings elucidate the regulatory basis of high-altitude adaptation in Tibetan pigs and provide valuable insights for exploring hypoxia-related diseases in livestock and humans.

Animals↗

A CqbZIP55-CqPIF3 regulatory module associated with light-responsive flavonoid biosynthesis during quinoa seedling de-etiolation.

Quinoa (Chenopodium quinoa) is an emerging leafy vegetable and microgreen crop rich in health-promoting flavonoids, yet the regulatory mechanisms linking light perception to early metabolic adaptation remain unclear. Here, we integrated phenotypic, transcriptomic, metabolomic, and molecular analyses to investigate early de-etiolation responses in quinoa seedlings. Short-term light exposure rapidly promoted seedling establishment and induced transcriptional programs associated with photosynthesis, carbon metabolism, hormone signaling, and flavonoid biosynthetic gene expression, whereas metabolite changes were more limited, indicating temporal uncoupling between transcriptional activation and metabolic accumulation. Genome-wide bZIP analysis identified CqbZIP55 as a light-responsive regulator that directly binds and activates the CqCHS promoter. CqPIF3 also bound the CqCHS promoter and showed stronger transactivation activity than CqbZIP55 in transient reporter assays. Protein interaction and dual-luciferase assays showed that CqbZIP55 physically interacts with CqPIF3 and modulates CqPIF3-associated promoter activity. Exogenous quercetin upregulated CqbZIP55 and prolonged CqCHS expression, suggesting a candidate metabolite-associated reinforcement mechanism. Together, these findings support functional interplay between CqbZIP55 and CqPIF3 in light-responsive regulation of flavonoid biosynthetic gene expression in quinoa seedlings, while further quinoa-based perturbation and in vivo promoter-occupancy assays are required to establish their physiological role in planta. This study provides a framework for further investigation of photoprotective metabolic regulation in quinoa.

Chenopodium quinoa↗

Integrated single-cell and spatial transcriptomic analyses reveal malignant epithelial glycolytic heterogeneity and spatial niche remodeling during colorectal cancer progression.

Colorectal cancer (CRC) progression is shaped by metabolic reprogramming and complex interactions within the tumor microenvironment. However, the cellular heterogeneity, spatial organization, and clinical relevance of glycolytic activity in CRC remain incompletely understood. In this study, we integrated single-cell RNA sequencing, bulk transcriptomics, and spatial transcriptomics data to systematically characterize glycolytic heterogeneity in CRC. Glycolytic activity was quantified using five independent scoring methods, consistently showing that epithelial cells exhibited the highest glycolytic activity across the two single-cell cohorts. Stratification of CopyKAT-verified aneuploid malignant epithelial cells into high-glycolysis (HG) and low-glycolysis (LG) subgroups by glycolysis scores revealed that HG cells exhibited higher stemness scores and chromosomal copy number variations. Cell-cell communication analysis revealed that, compared with LG cells, HG cells exhibited increased interaction frequency and strength with immune and stromal populations, indicating enhanced malignant epithelial-microenvironment crosstalk. Spatial transcriptomics analyses further revealed that glycolytic activity varied across normal colorectal tissue, primary CRC, and colorectal liver metastases, accompanied by progressive remodeling of epithelial-associated spatial niches and MIF-mediated intercellular communication. Bulk transcriptomic analysis identified a glycolysis-related prognostic signature with robust predictive performance, which served as an independent prognostic factor for overall survival in CRC cohorts. Collectively, these findings indicate that glycolytic heterogeneity is a key feature of CRC malignant epithelial cells and is closely associated with tumor progression, microenvironmental remodeling, and clinical outcomes.

Humans↗

A three-metabolite microbiota-associated signature for early risk stratification of gestational diabetes mellitus.

BACKGROUND: Gestational diabetes mellitus (GDM) is associated with adverse pregnancy outcomes and long-term metabolic and cardiovascular risk. However, oral glucose tolerance testing at 24-28 gestational weeks limits early risk stratification. Gut microbiota-associated metabolites may reflect early metabolic abnormalities, including those relevant to cardiometabolic health, but robust early-pregnancy biomarkers remain limited. METHODS: We conducted a multicenter nested case-control and prospective study involving 2,693 pregnant women. Untargeted metabolomics and metagenomics were integrated to identify GDM-associated metabolites and gut microbial alterations. Three consistently dysregulated metabolites, 3-hydroxydecanoic acid, &#x3b3;-Glu-Leu, and propionic acid, were quantified by targeted LC-MS/MS. Candidate algorithms were compared using repeated 10-fold cross-validation, and a final generalized linear model was externally and prospectively validated. RESULTS: Women who later developed GDM showed an adverse early-pregnancy metabolic profile, including higher BMI, triglycerides, and platelet count. Untargeted metabolomics identified 14 persistently altered metabolites enriched in energy, oxidative stress, and amino acid metabolism pathways. Metagenomics revealed taxonomic restructuring and coordinated microbiota-metabolite associations. The three-metabolite model achieved AUCs of 0.838 (95% CI, 0.791-0.885) in training, 0.840 (95% CI, 0.769-0.911) in internal validation, 0.955 (95% CI, 0.925-0.985) and 0.917 (95% CI, 0.875-0.958) in two external cohorts, and 0.969 (95% CI, 0.937-1.000) in the prospective cohort. CONCLUSION: Early microbiota-associated metabolic dysregulation is detectable before routine GDM diagnosis. This compact three-metabolite panel may support early GDM risk stratification and provides metabolic evidence relevant to broader cardiometabolic risk assessment in pregnancy.

Humans↗

A regulatory network underlying idiopathic pulmonary fibrosis.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung disease in which genetic susceptibility interacts with epithelial, immune, and mesenchymal remodeling. Although the chromosome 11p15.5 locus contains established IPF susceptibility signals near MUC5B and TOLLIP, the broader regulatory architecture of this region remains incompletely resolved. METHODS: We integrated IPF genome-wide association study summary statistics with methylation, expression, and protein quantitative trait loci using summary-data-based Mendelian randomization (SMR). SMR-prioritized candidates were evaluated in independent transcriptomic and methylation cohorts and further contextualized using microRNA, transcription-factor, protein-interaction, machine-learning, single-cell, and spatial transcriptomic analyses. Fibrosis-associated expression patterns were assessed in a bleomycin-induced pulmonary fibrosis rat model. RESULTS: The analyses recovered the established MUC5B and TOLLIP signals and prioritized BRSK2 as a comparatively underexplored candidate supported by eQTL-based SMR and independent molecular evidence. The BRSK2 pQTL association did not pass the HEIDI test and was therefore not interpreted as convergent protein-level genetic evidence. Network analyses linked BRSK2 to cell-cycle, metabolic-stress, and senescence-related programs, while cross-cohort machine learning prioritized FOXA2, CDC25B, and NFE2 as informative network features. Single-cell and spatial analyses localized BRSK2 preferentially to fibroblast and myofibroblast compartments and to regions with greater histological fibrosis severity. In fibrotic rat lungs, BRSK2 expression increased, whereas FOXA2 and CDC25B decreased at the transcript and protein levels. CONCLUSIONS: These findings refine the molecular landscape of the chromosome 11p15.5 IPF susceptibility locus and prioritize BRSK2 as a candidate component of an IPF-associated profibrotic fibroblast state. Its causal contribution, direct regulatory relationships, and therapeutic tractability require targeted mechanistic validation.

Idiopathic Pulmonary Fibrosis↗