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PubMed2026

Prioritizing Parkinson's disease risk-associated mitochondrial candidate genes via multi-omics integrative analysis.

BACKGROUND: Mitochondrial dysfunction has been implicated in Parkinson's disease (PD), but the genetically regulated mitochondrial genes associated with PD risk remain incompletely defined. METHODS: We conducted a summary-data-based genetic epidemiology study integrating summary-based Mendelian randomization (SMR), Heterogeneity in dependent instruments (HEIDI) filtering, and Bayesian colocalization to prioritize mitochondrial-related molecular features associated with PD risk. Mitochondrial-related genes were defined using MitoCarta3.0. Genetically predicted gene expression and plasma protein abundance were evaluated using expression quantitative trait loci (eQTL) data from eQTLGen and GTEx v8, and protein quantitative trait loci (pQTL) data was assessed using International Parkinson's Disease Genomics Consortium (IPDGC) as the discovery genome-wide association study (GWAS) and FinnGen as the replication dataset. Prespecified QTL analyses were interpreted using FDR correction, HEIDI filtering, and colocalization support. DNA methylation QTL analysis, mitochondrial phenotype MR, and single-nucleus RNA-seq analysis were performed as complementary analyses. RESULTS: In the primary eQTL analysis, higher genetically predicted TTC19 expression was associated with lower PD risk (OR = 0.80, 95% CI: 0.74-0.87, PPH4 = 0.80), whereas higher MALSU1 expression was associated with increased PD risk (OR = 2.21, 95% CI: 1.59-3.06, PPH4 = 0.96). Both associations survived FDR correction, passed HEIDI filtering, and showed colocalization support. GTEx whole-blood data supported the direction of the TTC19 association. No mitochondrial protein reached significance after FDR correction and colocalization filtering in the primary pQTL analysis. Complementary methylation analysis highlighted cg06270993 as an exploratory regulatory signal for MALSU1. CONCLUSIONS: This MR-colocalization study prioritizes TTC19 and MALSU1 as genetically supported mitochondrial-related candidate genes associated with PD risk. Further validation is required to define their functional roles in PD pathogenesis.

Humans↗
PubMed2025

Systematically investigating and identifying bacteriocins in the human gut microbiome.

Human gut microbiota produces unmodified bacteriocins, natural antimicrobial peptides that protect against pathogens and regulate host physiology. However, current bioinformatic tools limit the comprehensive investigation of bacteriocins' biosynthesis, obstructing research into their biological functions. Here, we introduce IIBacFinder, a superior analysis pipeline for identifying unmodified class II bacteriocins. Through large-scale bioinformatic analysis and experimental validation, we demonstrate their widespread distribution across the bacterial kingdom, with most being habitat specific. Analyzing over 280,000 bacterial genomes, we reveal the diverse potential of human gut bacteria to produce these bacteriocins. Guided by meta-omics analysis, we synthesized 26 hypothetical bacteriocins from gut commensal species, with 16 showing antibacterial activities. Further ex vivo tests show minimal impact of narrow-spectrum bacteriocins on human fecal microbiota. Our study highlights the huge biosynthetic potential of unmodified bacteriocins in the human gut, paving the way for understanding their biological functions and health implications.

Humans↗
PubMed2026

Unraveling a Diagnostic Enigma: A TECPR2 Case Solved Through Multi-Omic Genomics.

TECPR2 is a key regulator of autophagy, encoded by the TECPR2 gene. Pathogenic variants in this gene have been linked to a rare hereditary sensory and autonomic neuropathy with intellectual disability (HSAN9). We report a teenage female with a syndromic intellectual disability disorder associated with neuromuscular abnormalities. Multi-omics analysis including genomics, transcriptomics, and proteomics, together with muscle biopsy from the affected individual, were used in this clinical case. Through trio exome sequencing we identified two heterozygous variants in the TECPR2 gene, NM_014844.4: c.480G>A; p.(Gln160=) and c.2846C>A; p.(Ala949Glu). Both were classified as variants of uncertain significance due to the lack of supporting evidence for pathogenicity. Subsequent long-read sequencing phased the variants and confirmed they were in trans. Additional functional studies using RNAseq and proteomics analyses verified the pathogenicity of the variants. This case study demonstrated the value of a multi-omics assisted analysis, which complemented the traditional phenotype-first approach in reaching a definitive clinical diagnosis.

Humans↗
PubMed2025

Integrated proteomic network analysis reveals PTPRC as a central hub protein orchestrating co-expression modules and metabolic dysregulation in renal carcinoma: PTPRC protein molecular action.

The occurrence of renal carcinoma is closely related to a variety of molecular mechanisms and metabolic disorders. PTPRC (protein tyrosine phosphatase receptor C), as an important regulatory protein, was studied to reveal the role of PTPRC in renal carcinoma through comprehensive proteomic network analysis, especially its core position in the coordination of co-expression modules and metabolic disorders. This study was the first to download and process multiple publicly available renal cancer transcriptome data to conduct differential gene expression analysis across datasets. Functional enrichment and disease ontology analysis were performed on the transcriptome of renal cancer, and weighted gene co-expression network (WGCNA) was constructed. The results showed that comprehensive principal component analysis revealed significant differences in the transcriptome of renal cancer, and functional annotation revealed specific pathways associated with renal cancer. WGCNA analysis identified tumor-associated co-expression modules, while multi-omics analysis further identified core regulatory networks including PTPRC. As a central hub protein, PTPRC plays an important coordinating role in the co-expression module and metabolic dysregulation of renal carcinoma. This discovery provides a new perspective for understanding the molecular mechanism of kidney cancer.

Humans↗
PubMed2025

EP300-mediated lactylation leads to ulcerative colitis via CD86-positive plasmacytoid dendritic cells: A Mendelian randomization and mediation analysis.

This study explores the potential mechanism between lactylation and ulcerative colitis (UC) using two-sample Mendelian randomization and multi-omics analysis. This study employed expression quantitative trait loci and protein quantitative trait loci as exposures, with UC from the Finnish database as the outcome, to conduct Mendelian randomization analysis on lactylation-related target genes, aiming to investigate the causal relationships between these exposures and the outcome. Sensitivity and pleiotropy tests, combined with colocalization analysis, are performed to identify the best target genes and ensure the robustness of the results. Finally, immune cells are included for mediation analysis between lactylation and UC to explore potential mechanisms of action. Through Mendelian randomization analysis combined with sensitivity and pleiotropy tests, 2 lactylation target genes were found to have a significant causal relationship with UC. Subsequent colocalization analysis confirmed EP300 as a potential gene target. After including immune cells in the mediation analysis, it was discovered that there is a potential mechanism involving EP300, CD86+ plasmacytoid dendritic cells (pDCs), and UC. There is a significant causal relationship between lactylation and UC. Furthermore, the lactylation-modified gene EP300 may lead to UC occurrence by regulating CD86+ pDCs.

Humans↗
PubMed2026

Integrated multi-omics profiling identifies aging-related molecular signatures and convergent interferon signaling in systemic lupus erythematosus.

BACKGROUND: Systemic lupus erythematosus (SLE) is characterized by chronic immune activation and molecular alterations that overlap with aging-related biological processes. However, how these alterations are organized across molecular layers and whether they converge on shared regulatory networks remain incompletely understood. METHODS: We performed an integrative multi-omics analysis combining in-house proteomic and phosphoproteomic data from 130 patients with SLE and 90 healthy controls (HCs) and publicly available transcriptomic datasets comprising 1,461 SLE patients. Proteins and phosphorylation sites were annotated using established aging-related gene resources. Differential protein abundance and phosphorylation changes were analyzed across disease-status and disease-activity comparisons. Nominal P-value thresholds were used for exploratory feature selection, whereas FDR-adjusted P values were used to assess robustness after multiple-testing correction. Kinase-substrate enrichment, transcription factor annotation, and cell-type-resolved transcriptomic comparison were used to explore potential regulatory programs. RESULTS: We identified 128 nominally altered proteins annotated to aging-related biological processes, including genomic instability, mitochondrial dysfunction, and epigenetic alterations. Phosphoproteomic analysis revealed 36 nominally altered phosphorylation sites, including previously unreported sites in IFI16 (S153, S780) and PKCδ (S507, S664). Clustering analysis demonstrated heterogeneous protein co-regulation patterns across disease states. Kinase activity inference suggested altered activity of TBK1 and IKKβ. TF analysis further highlighted STAT1, RELA, and PML as potential central nodes within the inferred regulatory network. Notably, these multi-omic alterations were not randomly distributed but showed convergence toward shared signaling pathways, particularly those related to interferon responses. CONCLUSIONS: This integrative multi-omics study identifies inflammatory and interferon-dominated molecular alterations in SLE PBMCs that overlap with aging-related biological processes and converge on shared regulatory networks. These findings provide a hypothesis-generating framework for investigating the intersection between chronic immune activation and aging-related molecular remodeling in SLE.

Humans↗
PubMed2025

JASMINE: A powerful representation learning method for enhanced analysis of incomplete multi-omics data.

Integrative analysis of multi-omics data provides a more comprehensive and nuanced view of a subject's biological state. However, high-dimensionality and ubiquitous modality missingness present significant analytical challenges. Existing methods for incomplete multi-omics data are scarce, do not fully leverage both modality-specific and shared information, and produce task-biased representations. We propose JASMINE, a self-supervised representation learning method for incomplete multi-omics data that preserves both modality-specific and joint information and enhances sample similarity structure. JASMINE produces embeddings that achieve superior performance across multiple tasks for two different incomplete multi-omics datasets while requiring only a single round of training per dataset.

missing data↗
PubMed2026

Genome-wide epigenomic atlas and multi-omics responses of Eriocheir sinensis to natural extreme heat.

BACKGROUND: Global climate warming has led to increasingly frequent and prolonged extreme summer heat events, posing severe environmental challenges to aquaculture systems. Extreme summer heat can disrupt the performance of pond-cultured ectotherms. The Chinese mitten crab (Eriocheir sinensis) is an economically important freshwater crustacean, but coordinated molecular differences following contrasting natural summers remain incompletely characterized. RESULTS: We performed a comprehensive multi-omics analysis integrating meteorological monitoring, mRNA/lncRNA transcriptomics, small-RNA profiling of miRNAs, DNA methylomics, and LC-MS metabolomics in E. sinensis populations collected from Yancheng, China, between 2020 and 2024. Across the ten farms, survival was significantly lower in 2024, whereas yield and the proportion of large individuals showed nonsignificant downward trends. Gene-set analyses showed negative enrichment of cellular heat-response, protein-folding, oxidative-phosphorylation, and mitochondrial ATP-production terms in the 2024 cohort at the time of sampling. The integrated transcript annotation contained 72,240 lncRNAs and 63,833 mRNAs, and CpG was the predominant methylation context. Differential methylation analysis identified 73 regions and 185 cytosines, with hypomethylated events predominating within the significant subset. Metabolomic profiles differed between annual cohorts and mapped to carbohydrate, lipid, and amino-acid pathways. Cross-omics integration prioritized eight candidate genes-ADCY9, UNC79, UBN1, IFT52, ACO2, LOC126986070, LOC127001126, and LOC126997895-and qPCR reproduced the reported directions of expression for selected RNAs. CONCLUSION: This study provides the first integrative multi-omics framework for understanding chronic heat adaptation in E. sinensis. By linking transcriptomic, epigenomic, and metabolic remodeling, we elucidate the molecular mechanisms underlying energy imbalance, epigenetic reprogramming, and immune dysregulation during prolonged thermal stress. These findings offer valuable insights and genomic resources for breeding heat-tolerant crab strains and improving aquaculture resilience under ongoing climate change.

DNA methylation↗
PubMed2026

Proteogenomic analysis of pediatric and AYA high-grade glioma reveals age-dependent biology, female-male differences, and kinase targets.

High-grade gliomas (HGGs) in children and adolescents and young adults (AYA) exhibit distinct biology across the neurodevelopmental spectrum. To dissect tumor-intrinsic molecular characteristics independent of developmental variation, we perform comprehensive proteogenomic analyses of tumors from 112 HGG patients aged 0-40 years. Our multi-omics analysis identifies two AYA subgroups-adolescents (aged 15-26 years) and young adults (aged 26-40 years)-with distinct molecular profiles and survival outcomes. Tumor-normal comparisons and survival modeling highlight roles of oxidative phosphorylation and neuronal system biology in glioma progression. Causal network analysis and cell line studies provide a rationale for personalized therapies targeting candidate kinases, such as CDK8. Survival modeling, clustering, and immune-landscape analyses identify proteins, post-translational modifications, and immune signatures linked to outcomes and reveal clinically relevant differences between male and female patients.

adolescent and young adult glioma↗
PubMed2026

Pan-cancer analysis identifies APOC1 as a TAM-derived modulator of adaptive immune resistance and predictor of therapeutic response.

BACKGROUND: Apolipoprotein C1 (APOC1) has been implicated in several malignancies, yet its expression patterns, clinical significance, and immunomodulatory roles across cancer types remain poorly characterized. METHODS: We performed a comprehensive multi-omic analysis of APOC1 across 33 cancer types integrating transcriptomic, proteomic, genomic, epigenomic, and pharmacogenomic data from TCGA, GTEx, CPTAC, and multiple independent external cohorts. Immune infiltration was assessed using seven complementary algorithms. Spatial transcriptomics and single-cell RNA sequencing were employed to determine the cellular source of APOC1 expression. RESULTS: APOC1 upregulation in most cancers was associated with cancer type-specific prognosis. After adjustment for clinical covariates and macrophage infiltration, high APOC1 remained an independent adverse factor in KIRC, LGG, and STAD. APOC1 expression positively correlated with genomic instability hallmarks, including homologous recombination deficiency and aneuploidy, with these associations largely independent of immune infiltration; in contrast, associations with tumor mutational burden were substantially confounded by macrophage abundance. Immune infiltration analysis revealed a pattern consistent with adaptive immune resistance: APOC1 correlated positively with immune-activating signatures (STAT1, MHC-II, TCR signaling) and immunosuppressive M2 macrophages and Tregs, yet negatively with anti-tumor effectors (activated NK cells, dendritic cells). Spatial transcriptomics and single-cell RNA sequencing identified tumor-associated macrophages (TAMs) as the primary cellular source of APOC1, with transcripts co-localizing with CD68 in tissue sections. APOC1 expression correlated with multiple immune checkpoint molecules and was elevated in responders to immune checkpoint blockade, consistent with an inflamed yet regulated tumor microenvironment. Pharmacogenomic analyses revealed that APOC1-high tumors display distinct drug response profiles, characterized by resistance to MAPK pathway inhibitors and potential sensitivity to the HDAC inhibitor Entinostat. CONCLUSION: This pan-cancer analysis establishes APOC1 as a context-dependent biomarker and a TAM-derived modulator of adaptive immune resistance, with prognostic and therapeutic implications across malignancies. APOC1-expressing TAMs represent a potential target for combination immunotherapy strategies.

APOC1↗
PubMed2026

Integrated Genomic and Proteomic Analysis Reveals T-B Lymphocyte Signatures in the MYCN Driven "Immune Desert" of Specific Neuroblastoma Subtypes.

AIMS: This study aims to systematically dissect how MYCN amplification shapes the immunosuppressive tumor microenvironment (TME) in high-risk neuroblastoma, elucidating key mechanisms underlying immune evasion. METHODS: We performed an integrated multi-omics analysis of bulk RNA-seq (n = 721), single-cell RNA-seq (n = 9), proteomic data (n = 49) and spatial transcriptomics (Visium, with external validation in melanoma). Analyses included unsupervised clustering, cell-cell communication inference, transcriptional regulatory network reconstruction, and spatial proximity assessment to map the immune landscape. RESULTS: A distinct molecular subtype (Class C), defined by MYCN amplification and poor prognosis, exhibited a comprehensive "immune desert" phenotype characterized by low immune scores and minimal leukocyte infiltration. Single-cell analysis confirmed significant depletion of T and B lymphocytes within the Class C TME. Dysregulated transcriptional networks were identified, including upregulation of REL and EOMES in T cells-with EOMES potentially driving exhaustion via regulation of Transient Receptor Potential (TRP) genes, and REL inhibition enhancing cytotoxic function in vitro. A unique immunosuppressive B-cell subset (B7) engaged in enhanced crosstalk with exhausted T cells and harbored a MYC-centered network linked to cell cycle dysregulation and poor survival. Spatial transcriptomics revealed significant proximity between B7-active regions and Treg/exhaustion-enriched areas, externally validated in melanoma. Proteomic data validated elevated REL expression in MYCN-amplified tumors. CONCLUSION: This work delineates the immunosuppressive architecture of MYCN-driven neuroblastoma, revealing novel regulatory nodes within specific lymphocyte compartments. Integrating single-cell, spatial, and proteomic evidence, we propose REL inhibition as a therapeutic candidate, the EOMES/TRP axis as a bioinformatically supported hypothesis, and the B7/MYC hub as a hypothesis supported by transcriptomic and spatial evidence.

Humans↗
PubMed2026

Integrated transcriptomic and metabolomic analysis reveals candidate regulatory networks associated with starch accumulation in tetraploid potato.

Potato (Solanum tuberosum L.) tuber starch is a major determinant of crop quality and industrial value, yet the regulatory mechanisms underlying starch accumulation in autotetraploid cultivars remain poorly resolved. Here, we performed integrated transcriptomic and metabolomic analyses using a segregating tetraploid population derived from parents with contrasting starch content. Extreme phenotypes were selected to systematically dissect the molecular basis of starch accumulation. Transcriptome profiling revealed extensive transcriptional reprogramming between high- and low-starch genotypes, with differentially expressed genes significantly enriched in carbohydrate metabolism, particularly the starch and sucrose metabolism pathway. Notably, multiple transcription factor families, including AP2/ERF, MYB, and bHLH, were prominently represented, suggesting coordinated regulatory control. Metabolomic analysis identified substantial metabolic divergence, with differentially accumulated metabolites predominantly enriched in starch and sucrose metabolism as well as secondary metabolic pathways. Most metabolites exhibited negative associations with starch content, indicating competitive carbon allocation between primary and secondary metabolism. Integrative multi-omics analysis further resolved a core regulatory module comprising key structural genes and transcription factors tightly associated with starch-related metabolites. In particular, genes involved in sucrose cleavage and ADP-glucose metabolism, together with trehalose-6-phosphate synthase (TPS) and UDP-glucose-associated pathways, emerged as critical nodes linking carbon flux to starch biosynthesis. Correlation network analysis suggested that AP2/ERF-, MYB-, and bHLH-type transcription factors modulate these pathways by coordinating structural gene expression and metabolic flux distribution. Collectively, our study establishes a transcriptional-metabolic framework for starch accumulation in tetraploid potato, highlighting the central role of carbon allocation and signaling intermediates in shaping starch content, and providing candidate targets for molecular breeding and genome editing.

Solanum tuberosum↗
PubMed2025

Integrative metabolomic and proteomic analysis of diabetic kidney disease progression with younger-onset type 2 diabetes.

AIM: Younger-onset type 2 diabetes (YT2D) confers a disproportionately high risk of diabetic kidney disease (DKD), yet early biomarkers and underlying mechanisms remain poorly defined. We aimed to identify metabolites associated with DKD progression and integrate metabolomic and proteomic data to elucidate pathways involved in a multi-ethnic Asian cohort. MATERIALS AND METHODS: In this prospective study, 787 YT2D patients (diagnosed at ≤ age 40) were followed for a median of 5.7 years. DKD progression was defined as an annual decline in estimated glomerular filtration rate (eGFR) of ≥3 mL/min/1.73 m2 or ≥ 40% reduction in eGFR from baseline. Plasma metabolites were measured by nuclear magnetic resonance spectroscopy. Multivariable regression analysis was performed in a discovery (N = 550) and internal validation cohort (N = 237). Integrative metabolomic-proteomic analysis (N = 428) was performed using sparse partial least squares discriminant analysis (sPLS-DA). RESULTS: Ninety-eight metabolites were differentially expressed between DKD progressors and non-progressors, of which total branched-chain amino acids (BCAAs) (OR = 0.60, 95% CI 0.46-0.79), valine (OR = 0.62, 95% CI 0.48-0.81), and leucine (OR = 0.56, 95% CI 0.43-0.74) associated with DKD progression, independent of metabolic risk factors. Integrative analysis identified three components comprising 23 proteins and 30 metabolites, involved in the citrate cycle and apoptosis, which improved prediction of DKD progression beyond clinical risk factors (AUC 0.69-0.83). CONCLUSION: Lower plasma BCAA levels are independently associated with DKD progression in YT2D. Integrative multi-omics analysis highlights disruptions in metabolic and apoptotic pathways, providing insights into DKD pathophysiology and potential biomarkers for early risk stratification.

Humans↗
PubMed2025

Altered ruminal microbiome tryptophan metabolism and their derived 3-indoleacetic acid inhibit ruminal inflammation in subacute ruminal acidosis goats.

BACKGROUND: Subacute ruminal acidosis (SARA) is a digestive disorder that often severely jeopardizes the health and lactation performance of ruminants fed a high-energy diet. Different dairy ruminants exhibit varying degrees of inflammation accompanied by variations in the rumen microbiota when SARA occurs. Our understanding of the occurrence of SARA and varying degrees of rumen epithelial inflammation is lacking. Hence, we performed rumen metagenomic, metagenome-assembled genome and metabolomic analyses, with transcriptome and single-nucleus RNA sequence analyses, to explore the microbial mechanism of SARA occurrence and different degrees of inflammation. RESULTS: A total of 36 goats fed two diets with gradually increasing levels of rumen-degradable starch (RDS) were included in this study, and SARA goats fed 70% concentrate diets supplemented with whole corn (HGW-SARA) and SARA goats fed 70% concentrate diets supplemented with crushed corn (HGC-SARA) were identified. Moreover, 11 goats fed a control basal diet, named LGW-CON, were also included. Compared with those in the LGW-CON group, the rumen fermentation capacity was enhanced, accompanied by ruminal epithelial and systemic inflammation, in goats from HGW-SARA and HGC-SARA. Between them, HGC-SARA goats presented less inflammation. Notably, the ruminal inflammation-related pathways were increased only in the HGW-SARA group but not in the HGC-SARA group. Metagenomic analysis revealed that the β diversity of SARA goats was significantly different from that of LGW-CON goats. Ruminococcus significantly increased in both SARA groups, whereas Prevotella and Bacteroidales significantly decreased, which was accompanied by a decrease in cellulose and hemicellulose enzymes and an increase in lysozymes and lipopolysaccharide synthesis enzymes. Multi-omics analysis of the ruminal contents and tissues suggested that epithelial inflammation was caused by disturbed ruminal microbiome-induced Th17 cell differentiation and IL-17 signalling pathway activation. Comparative analyses between the HGW-SARA and HGC-SARA groups highlighted the importance of Selenomonas and Bifidobacterium, as well as bacterial tryptophan metabolism, in the production of 3-indoleacetic acid, which mitigated ruminal epithelial inflammation by modulating Th17 cells and inhibiting IL-17 signalling. Ruminal microbiota transplantation from HGW-SARA goats to healthy dairy goats and mice revealed the role of microbes in epithelial inflammation. Additionally, 3-indoleacetic acid supplementation reduced rumen inflammation and the IL-17 concentration in the serum, improved VFAs absorption, and enhanced milk production. CONCLUSIONS: This study unveiled that after SARA was induced by high-concentrate feeding, the rumen homeostasis was disrupted, and rumen fiber degradation capacity of dairy goats decreased, but the LPS synthesis capacity increased, and inflammation of the rumen epithelium was observed. However, the ruminal microbial species from the Bifidobacterium and Selenomonas genera and bacterial 3-indole acetic acid are pivotal in mitigating ruminal epithelial inflammation during SARA in dairy goats. This could potentially be attributed to the modulation of ruminal Th17 cell proportions and the inhibition of IL-17 signalling pathways. Video Abstract.

Rumen↗
PubMed2026

A Multi-omics Regulated Cell Death Framework Defines Immune Phenotypes and Guides Precision Therapy in Colorectal Cancer.

Colorectal cancer (CRC) is molecularly and immunologically heterogeneous, contributing to variable treatment response. Because regulated cell death (RCD) intersects with tumor metabolism, immune regulation, and therapeutic susceptibility, we built an RCD-centered framework for CRC stratification. Multi-cohort transcriptomic data were used to infer RCD subtypes with non-negative matrix factorization (NMF) and non-negative least squares (NNLS). Genomic, bulk RNA-seq, single-cell RNA-seq, and spatial transcriptomic datasets were integrated to characterize subtype-associated biology. Machine-learning models were developed for immunotherapy response and survival-risk estimation. Candidate compounds were screened by GDSC2-based drug-sensitivity modeling and molecular docking, and FSTL3 was functionally assessed in vitro. The framework separated CRC samples into two RCD-related phenotypes resembling immune-hot and immune-cold states. RCD1 showed immune activation and higher mutational burden, whereas RCD2 showed immune-suppressed features, intratumoral heterogeneity, and aggressive biology. RCD-associated signatures showed potential for predicting immunotherapy response and survival risk. Dasatinib was prioritized for immune-cold, high-risk tumors, with preliminary evidence supporting its activity in CRC cells, while functional assays suggested a role for FSTL3 in growth, invasion, epithelial-mesenchymal transition, and apoptosis regulation. These findings suggest that RCD-based multi-omics analysis may refine CRC stratification and help generate therapeutic hypotheses.

Colorectal cancer↗
PubMed2026

Hotgenes: an R package for reducing bottlenecks in bulk omics data exploration and collaboration.

SUMMARY: A critical part of omics analysis is the transition from early data exploration to final interpretation, often including different analytical platforms and the proliferation of figures, tables, and files. To minimize potential errors and delays that can occur during this process, we have developed an R package called "Hotgenes" that contains a wide range of flexible utilities available in a single modular Shiny application. With Hotgenes, differential expression results generated from bulk omics platforms can be imported and shared among collaborators with minimal coding. Furthermore, the modular Hotgenes user interface can be customized by advanced users to fit the needs of their evolving pipelines. AVAILABILITY AND IMPLEMENTATION: Hotgenes is implemented in R and is freely available at https://github.com/pfizer-opensource/Open-Hotgenes. A permanent archived version is available at https://doi.org/10.5281/zenodo.20129460.

Software↗
PubMed2026

Integrative cross-tissue transcriptome-wide association and metabolomic analysis reveals novel genetic risk loci for aortic aneurysm.

BACKGROUND: Aortic aneurysm (AA) is a life-threatening cardiovascular condition with a strong genetic component, however, its molecular mechanisms remain poorly understood. Although genome-wide association studies (GWAS) have identified numerous risk loci, most prior studies have investigated genetic and metabolic factors separately, leaving the causal pathways from genetic variants to disease largely unexplored. METHODS: We established an integrative framework combining cross-tissue transcriptome-wide association studies (TWAS) with metabolomic mediation analysis. First, we integrated GWAS data from FinnGen R12 with multi-tissue expression quantitative trait loci (eQTL) data from Genotype-Tissue Expression Project (GTEx) V8, then performed cross-tissue TWAS using the Unified Test for MOlecular SignaTures (UTMOST) and single-tissue validation with the Functional Summary-based Imputation (FUSION) to prioritize susceptibility genes. Second, we applied Mendelian randomization (MR), colocalization, and Fine-mapping Of CaUsal gene Sets (FOCUS) to assess causality and identify high-confidence genes. Third, we performed metabolite mediation analysis to uncover metabolic pathways linking genetic variants to disease risk. Finally, we validated key findings in mouse models of thoracic aortic aneurysm (TAA) and abdominal aortic aneurysm (AAA) using Quantitative Real-Time Reverse Transcription Polymerase Chain Reaction (RT-qPCR) and Western blotting. RESULTS: We identified multiple novel susceptibility genes for AA and its subtypes. Key genes included ADH family members (ADH1A, ADH1B, ADH4, ADH6) and ZNF827, which showed cross-subtype associations with strong colocalization evidence in vascular tissues. Metabolite mediation analysis revealed significant pathways involving N-acetylphenylalanine and methionine sulfoxide. Functional enrichment revealed distinct biological mechanisms: AA and AAA were primarily associated with metabolic pathways, whereas TAA-related genes were enriched in developmental and contractile processes. PheWAS indicated no significant off-target associations. Critically, experimental validation in mouse models confirmed significant upregulation of ZNF827 in TAA and ADH6 in AAA at both mRNA and protein levels, corroborating the genetic predictions. CONCLUSION: This integrated cross-omics analysis identifies novel genetic loci and, crucially, uncovers specific nutrient-related metabolic pathways that mediate genetic risk. These findings provide a mechanistic basis for future nutritional and metabolic intervention studies in AA and its subtypes.

MAGMA↗
PubMed2025

Insights into dill (Anethum graveolens) flavor formation via integrative analysis of chromosomal-scale genome, metabolome and transcriptome.

INTRODUCTION: Dill (Anethum graveolens) is a significant medicinal herb belonging to the Apiaceae family. Owing to its high levels of volatile organic compounds (VOCs), dill is commonly utilized for essential oil extraction and medicine purpose. However, the biosynthesis of the crucial VOC in dill remains obscure. OBJECTIVES: Identify the key VOCs related to the flavor formation in dill and dissect the regulatory mechanism of their synthesis. METHODS: The dill chromosomal-level genome was constructed by PacBio HiFi, Hi-C, and BGISEQ second generation sequencing and assembly. The VOCs in dill leaves were identified through GC-MS. The potential mechanism involved in regulating the VOC accumulation in dill flavor formation was analyzed by multi-omics analysis. RESULTS: A 1.17 Gb chromosome-scale genome of dill with a contig N50 of 10.78 Mb was constructed. A total of 46,538 genes were annotated across 11 assembled chromosomes. Comparative genomics analysis suggested that transposable element insertions, especially LTR-Gypsy, have contributed to the evolution and expansion of the dill genome. The flavor formation of dill was mainly attributed to terpenoids, especially α-phellandrene, β-ocimene, and o-cymene. The contribution of expansion and replication of terpenoid synthesis pathway genes, especially terpene synthase (TPS), to the abundant terpenoid production of dill was identified. Differential gene expression patterns observed at various developmental stages and tissues provided key candidate genes for the regulation of terpenoid synthesis, as well as transcription factors. The different accumulation of esters and aromatics also affected the flavor formation of dill. The key genes implicated in the synthesis of anethole, namely AIS and AMT were further identified. CONCLUSION: This study constructed the chromosome level genome and identified the main VOCs and related key genes in flavor formation of dill, shedding lights on our understanding of terpenoid biosynthesis but also offered guidance for future genetic research on molecular breeding in Anethum graveolens.

Transcriptome↗