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PubMed2026

Integrated multi-omics strategies for identifying novel therapies in psoriasis.

MOTIVATION: Psoriasis is a chronic, immune-mediated disorder with an unmet need for effective treatments. To systematically prioritize therapeutic targets, we integrated proteome-wide Mendelian randomization (MR) with expression validation in blood/skin, genetic susceptibility analysis, differential gene expression (DGE) from bulk and single-cell RNA sequencing (scRNA-seq), colocalization, pathway enrichment, and protein-protein interaction analyses. RESULTS: Proteome-wide MR identified 29 candidate protein targets (Bonferroni-corrected), all replicated in independent datasets. Fifteen targets showed significant expression associations in blood or skin. Eleven proteins-UBLCP1, IL23A, ASF1A, RARRES2, ICAM1, PRSS53, ICAM5, GCA, IL2RA, DBI, and NFKB1-exhibited consistent directional effects with their genes. Genetic susceptibility analysis confirmed 20 target-specific polygenic scores for psoriasis and five for psoriatic arthritis. DGE analysis identified 13 targets in bulk and 13 in scRNA-seq-primarily in keratinocytes and immune cells-with IL2RA, COMP, and A2ML1 dysregulated across both. Colocalization analysis implicated shared causal variants for psoriasis in ASF1A, CD8A, CTF1, IL7R, MMP12, RARRES2, XCL2, DBI, IL23A, IL2RA, SGSH, and TIMD4. Enrichment analyses highlighted involvement in cytotoxicity, immune regulation, and JAK-STAT signaling. Eighteen targets interacted with approved anti-psoriasis drugs. Notably, drugs targeting IL2RA, IL7R, CTF1, ICAM1, MMP12, NFKB1, CD8A, DDX58, IL12A, SGSH, and FAP are approved or in trials for other diseases, suggesting repurposing potential. Our integrative multi-omics approach prioritized 29 high-confidence targets, including 13 novel candidates (RARRES2, ASF1A, CTF1, DBI, B3GNT2, CD8A, TIMD4, CRTAM, SGSH, XCL2, DAPK2, A2ML1, and FAP). Several high-priority targets-such as IL2RA, IL23, MMP12, RARRES2, IL7R, and ICAM1-were supported across analytical layers. These findings provide a robust foundation for psoriasis drug development. AVAILABILITY AND IMPLEMENTATION: The code used for the analyses in this manuscript has been archived in Zenodo at [DOI: 10.5281/zenodo.19692128].

Psoriasis↗

PubMed2024

A metabolomics pipeline highlights microbial metabolism in bloodstream infections.

The growth of antimicrobial resistance (AMR) highlights an urgent need to identify bacterial pathogenic functions that may be targets for clinical intervention. Although severe infections profoundly alter host metabolism, prior studies have largely ignored microbial metabolism in this context. Here, we describe an iterative, comparative metabolomics pipeline to uncover microbial metabolic features in the complex setting of a host and apply it to investigate gram-negative bloodstream infection (BSI) in patients. We find elevated levels of bacterially derived acetylated polyamines during BSI and discover the enzyme responsible for their production (SpeG). Blocking SpeG activity reduces bacterial proliferation and slows pathogenesis. Reduction of SpeG activity also enhances bacterial membrane permeability and increases intracellular antibiotic accumulation, allowing us to overcome AMR in culture and in vivo. This study highlights how tools to study pathogen metabolism in the natural context of infection can reveal and prioritize therapeutic strategies for addressing challenging infections.

Metabolomics↗

PubMed2026

Research updates in cystic fibrosis related diabetes: Understanding pathophysiology, expanding animal and human islet models, and advancing clinical and translational research.

In 2024-2025, the Cystic Fibrosis Foundation (US) and Cystic Fibrosis Trust (UK) hosted an International CFRD Consortium round-table webinar series for basic science, translational, and clinical researchers with the goal of sharpening mechanistic understanding of CFRD pathogenesis and prioritizing therapeutic development. This review summarizes the research priorities identified in the International CFRD Consortium, including (i) further investigation into the role of pancreatic fibrosis, vascular abnormalities, and α-cell dysfunction in the development of CFRD; (ii) the creation and refinement of novel animal and human cell- and tissue-based models to understand the complex interplay of exocrine and endocrine cells in the CF pancreas; (iii) development and validation of circulating and imaging biomarkers, together with dynamic glucose testing to explore β-cell function and kinetics in people with CF across the dysglycemia spectrum; and (iv) prospective clinical studies to guide CFRD treatment options and investigate the changing landscape of aging, increasing prevalence of obesity and diabetes and their complications in the era of cystic fibrosis transmembrane conductance regulator (CFTR) modulators. Collectively, these priorities aim to accelerate transition from mechanism to intervention and expand evidence-based care for people with CF at risk of, or living with, CFRD.

Humans↗

PubMed2025

Integrative analyses of mendelian randomization and bioinformatics reveal casual relationship and genetic links between COVID-19 and knee osteoarthritis.

BACKGROUND: Clinical and epidemiological analyses have found an association between coronavirus disease 2019 (COVID-19) and knee osteoarthritis (KOA). Infection with COVID-19 may increase the risk of developing KOA. OBJECTIVES: This study aimed to investigate the potential causal relationship between COVID-19 and KOA using Mendelian randomization (MR) and to explore the underlying mechanisms through a systematic bioinformatics approach. METHODS: Our investigation focused on exploring the potential causal relationship between COVID-19, acute upper respiratory tract infection (URTI) and KOA utilizing a bidirectional MR approach. Additionally, we conducted differential gene expression analysis using public datasets related to these three conditions. Subsequent analyses, including transcriptional regulation analysis, immune cell infiltration analysis, single-cell analysis, and druggability evaluation, were performed to explore potential mechanisms and prioritize therapeutic targets. RESULTS: The results indicate that COVID-19 has a one-way impact on KOA, while URTI does not play a causal role in this association. Ribosomal dysfunction may serve as an intermediate factor connecting COVID-19 with KOA. Specifically, COVID-19 has the potential to influence the metabolic processes of the extracellular matrix, potentially impacting the joint homeostasis. A specific group of genes (COL10A1, BGN, COL3A1, COMP, ACAN, THBS2, COL5A1, COL16A1, COL5A2) has been identified as a shared transcriptomic signature in response to KOA with COVID-19. Imatinib, Adiponectin, Myricetin, Tranexamic acid, and Chenodeoxycholic acid are potential drugs for the treatment of KOA patients with COVID-19. CONCLUSIONS: This study uniquely combines Mendelian randomization and bioinformatics tools to explore the possibility of a causal relationship and genetic association between COVID-19 and KOA. These findings are expected to provide novel perspectives on the underlying biological mechanisms that link COVID-19 and KOA.

Humans↗

PubMed2026

Immune cell-specific genetic architecture of Alzheimer's disease revealed by multi-omics analysis for therapeutic target discovery and prioritization.

Alzheimer's disease (AD) is a multifactorial neurodegenerative condition in which accumulating genetic and molecular evidence implicates dysregulation of peripheral immune processes in disease pathogenesis. Nevertheless, the contribution of distinct peripheral immune cell subsets and associated gene regulatory landscapes to AD risk remains incompletely defined. To address this gap, we integrated single-cell expression quantitative trait loci (sc‑eQTL) data from the OneK1K cohort with AD GWAS summary statistics. We systematically interrogated immune cell-specific genes for their contributions to AD risk by integrating genetic causal inference with Bayesian colocalization analyses, and identified 24 eGenes that passed both the MR significance threshold (P < 0.05) and the criterion for strong shared genetic signals (PP.H4 > 0.8). Notable candidates included GATS, HLA-DOB, HLA-DQA1, PM20D1, and others, with each gene demonstrating a cell-type-specific association restricted to its corresponding immune cell type, such as monocytes, CD8 + T cells, or B cells. Independent peripheral blood single-cell transcriptomic data further supported disease-associated shifts in cell-type-specific expression patterns in AD. Phenome-wide association studies (PheWAS) indicated limited associations with off-target traits, indicating a favorable safety profile for therapeutic intervention, with the exceptions of B4GALNT3, PM20D1, and CNN2. Integration of immune gene targets with pharmacological databases yielded three candidate compound, including NSC321521 (targeting HLA-DQA1), phenoxybenzamine (targeting GSTP1), and rimexolone (targeting BIN1). Among these compounds, Predicted blood-brain barrier permeability was observed only for phenoxybenzamine and rimexolone, with docking studies indicating stable interactions, such as those between NSC321521 and HLA-DQA1, phenoxybenzamine and GSTP1, and rimexolone and BIN1. This integrative approach highlights key immune‑cell‑specific genes involved in AD and proposes repurposable drugs with central nervous system potential, paving the way for more targeted immunomodulatory strategies in AD.

Humans↗

PubMed2026

Longitudinal multiorgan transcriptomic atlas of salt-induced hypertension.

High dietary salt intake elevates blood pressure and drives multiorgan damage. However, the molecular programs underlying progressive organ injury remain poorly defined. Here, we present a longitudinal multiorgan transcriptomic atlas of salt-induced hypertensive injury. We profiled kidney cortex, kidney medulla, heart, and liver across 4 stages, spanning early hypertension to advanced pathology in Dahl salt-sensitive rats. We identified dynamic and tissue-specific molecular trajectories, including a shared early proliferative response that converges on proinflammatory and fibrotic remodeling. Notably, we uncovered compartment-specific renal responses, showing that the cortex and medulla, despite their proximity, follow distinct molecular trajectories during disease progression. We further identified 79 stage- and tissue-specific transcription factors that drive gene expression dynamics in salt-induced hypertensive injury. Integration with human genome-wide association studies revealed conserved pathways in endocrine signaling, ion transport, lipid metabolism, and detoxification, establishing cross-species relevance and highlighting mechanistic targets of clinical importance. Compound-transcriptome analysis revealed stage- and organ-specific therapeutic opportunities, prioritizing kinase and epigenetic modulators as candidates to rebalance maladaptive gene programs. Overall, this study provides a resource for understanding molecular mechanisms from early salt-induced hypertension to tissue-specific injury and underscores the need for precision interventions.

Animals↗

PubMed2026

Decoding age-stratified clinical and molecular heterogeneity in male breast cancer through multiomic profiling.

OBJECTIVE: Age-associated molecular heterogeneity is well described in female breast cancer but remains insufficiently characterized in male breast cancer (MBC). We profiled age-stratified clinical and molecular differences between younger (≤55 years) male breast cancer (YMBC) and older (>55 years) male breast cancer (OMBC). METHODS: We retrospectively analyzed 347 patients with MBC diagnosed at Fudan University Shanghai Cancer Center by integrating clinicopathological data, RNA sequencing, and whole-exome sequencing (WES). Survival, differential expression, and mutational signature analyses were performed. Tumor microenvironment features were inferred using xCell and ESTIMATE, and weighted gene co-expression network analysis (WGCNA) was conducted to identify age-associated co-expression modules. Candidate therapeutics were prioritized using the Genomics of Drug Sensitivity in Cancer (GDSC) resource and evaluated using patient-derived organoids (PDOs). RESULTS: Compared with OMBC, YMBC more frequently had human epidermal growth factor receptor 2 (HER2)-positive status (14.91% vs. 4.02%) and triple-negative tumors (4.92% vs. 1.78%), and had worse 5-year recurrence-free survival (hazard ratio=2.19, P=0.018). Transcriptomic analyses indicated enrichment of neural-related programs and reduced immune-related signaling in YMBC, and xCell/ESTIMATE supported lower immune infiltration. Consistently, WGCNA identified age-associated modules linking neural-related programs with reduced immune infiltration. Immunohistochemistry supported increased perineural invasion and lower CD8+ T cell infiltration in YMBC. GDSC-guided prioritization with PDO testing nominated sepantronium bromide (YM155) as a candidate vulnerability in YMBC. WES showed a higher NBPF10 mutation frequency in YMBC (54.5% vs. 14.3%, P<0.05). CONCLUSIONS: Integrated multi-omics profiling revealed age-stratified clinical and molecular heterogeneity in MBC. YMBC patients demonstrated inferior recurrence-free survival, neural signaling enrichment, an immune-cold microenvironment, and enriched NBPF10 mutations. These findings support age as a meaningful stratification variable in MBC risk assessment and treatment planning, and highlight the need for caution when considering treatment de-escalation in younger patients, while nominating YM155 as a candidate agent for prospective evaluation.

Male breast cancer↗

PubMed2026

PLK1/FOXM1-associated tumor-cell state and macrophage-related immune features in endometrial cancer.

BACKGROUND: Polo-like kinase 1 (PLK1) and forkhead box M1 (FOXM1) have been widely studied in various cancers; however, their expression characteristics in endometrial cancer (EC) and their potential association with tumor microenvironment remodeling remain insufficiently characterized. METHODS: This study integrated The Cancer Genome Atlas uterine corpus endometrial carcinoma cohort, Gene Expression Omnibus, pan-cancer transcriptomic data, Human Protein Atlas/Clinical Proteomic Tumor Analysis Consortium, and local immunohistochemistry data to evaluate PLK1 expression and clinicopathological relevance across transcriptomic, proteomic, and histopathological data. Differential expression, survival, gene-set enrichment, transcription-factor enrichment, and immune-infiltration analyses characterized PLK1-associated features. In vitro experiments combined EC cell lines AN3CA and HEC-1A with co-immunoprecipitation, Western blotting, Transwell assays, and a THP-1 conditioned-medium model. Drug-response prediction and structure-based analysis prioritized candidate therapeutic hypotheses. RESULTS: PLK1 was consistently upregulated at both mRNA and protein levels in EC and was associated with higher tumor grade and International Federation of Gynecology and Obstetrics (FIGO) stage. In survival analysis, higher PLK1 expression was associated with poorer overall survival in univariable models but not after adjustment for age, tumor grade, and FIGO stage. Functional enrichment analysis showed that PLK1-associated genes were mainly involved in cell-cycle and mitotic processes. FOXM1 was identified as a potential candidate component of the PLK1-associated transcriptional program and was positively correlated with PLK1 expression and cell-cycle-related features. In vitro experiments supported an interaction between PLK1 and FOXM1 and suggested that FOXM1 Thr600 phosphorylation-related alterations were associated with migration and invasion phenotypes. Furthermore, the PLK1/FOXM1-associated tumor-cell state was linked to macrophage-related immune features and changes in the M2-like marker profile of THP-1-derived macrophage-like cells. Drug response analyses suggested differential predicted sensitivity patterns in PLK1-high tumors, providing candidate therapeutic hypotheses for further validation. CONCLUSION: The PLK1/FOXM1-associated tumor-cell state may represent a distinct molecular feature associated with proliferative activity, invasive phenotypes, and macrophage-related immune features in EC. This study provides preliminary evidence supporting the biological relevance of this molecular feature and highlights potential therapeutic directions for future investigation.

FoxM1↗

PubMed2026

The Biobank Rare Variant consortium powers the discovery of rare genetic associations through global collaboration.

Rare coding variants can have large effects on disease risk and provide direct routes from human genetics to disease mechanisms and therapeutic targets, but their discovery is constrained by sample size, particularly for low-prevalence diseases. Here we establish the Biobank Rare Variant Analysis (BRaVa) consortium, a global rare variant association resource that integrates sequencing and linked health-record data from ten biobanks and cohorts comprising over 1.2 million individuals across diverse ancestries. We performed gene-based meta-analyses of rare coding variation across 33 clinical endpoints and 11 quantitative traits. Aggregating evidence across biobanks and ancestries identified 514 gene-trait associations, including 31 not previously reported in prior studies or curated association resources following systematic literature review. Notably, 36.1% of gene-level associations were undetectable in any individual biobank, and 91 emerged only through cross-ancestry meta-analysis, demonstrating that federated integration enables discovery beyond the reach of single cohorts. Similar gains were observed at the variant level, where 25.0% of phenotype-locus associations were detectable only through meta-analysis. Effect size estimates were correlated across ancestries with concordant directions of effect, supporting the generalizability of rare variant associations. The identified signals implicate pathways involved in transcriptional and epigenetic regulation, metabolism, vascular and epithelial biology, and immune function, highlighting rare coding variation as an engine for biological discovery across medical record phenotypes. For example, damaging variation in ANKRD12 implicates inflammatory transcriptional dysregulation in asthma and chronic obstructive pulmonary disease, and ultra-rare predicted loss-of-function variants in NAA15 link protein acetylation processes to type 2 diabetes risk. BRaVa establishes a scalable framework and freely available community resource for rare variant meta-analysis across global biobanks. Public release of gene- and variant-level association summary statistics provides a reference map of rare coding variant associations to support disease gene discovery, biological interpretation, and therapeutic target prioritization as sequencing-linked health-record resources continue to expand.

Journal Article↗

PubMed2025

Integration of multiple omics reveals key targets and cellular mechanisms for intervention in sarcopenia.

BACKGROUND: Sarcopenia, an age-related syndrome characterized by progressive loss of muscle mass, strength, and function, presents a significant global health burden with limited therapeutic interventions. This study integrates genomic causality, multi-tissue omics, and cellular mediation analyses to identify and prioritize mechanistically grounded therapeutic targets. METHODS: A multi-tiered analytical framework was applied, beginning with two-sample Mendelian randomization (MR) to infer causal relationships between 4907 plasma proteins (cis-pQTLs from 35,559 individuals) and sarcopenia traits in Pan-UK Biobank participants. Bayesian colocalization and transcriptomic validation in human sarcopenia muscle biopsies were employed to prioritize targets. Cellular mediation analysis quantified contributions of immune and stromal cell subtypes to protein-trait pathways using transcriptomic deconvolution. RESULTS: MR identified 1237 plasma proteins causally associated with sarcopenia traits, with six targets (HGFAC, GATM, HMOX2, F2, LMAN2L, HPGDS) validated through colocalization, transcriptomic expression, and sarcopenia-related dysregulation. Cellular mediation revealed immune mechanisms underlying HGFAC's effects, with CD4+ regulatory T cells mediating 3.49 % of its impact on sarcopenia traits. Prothrombin exhibited muscle-protective effects independent of coagulation. CONCLUSION: This study establishes a causal map linking plasma proteins to sarcopenia through immune-stromal interactions. The integration of MR, multi-omics validation, and cellular mediation prioritizes six proteins as actionable targets, supporting repurposing of thrombin inhibitors and development of immunometabolic therapies. The framework bridges genomic causality with cellular pathophysiology, advancing precision strategies for age-related muscle decline.

Humans↗

PubMed2026

Large-Scale Proteomic Profiling of Incident Heart Failure and Its Subtypes in Older Adults.

BACKGROUND: Heart failure (HF) and its main subtypes, heart failure with preserved ejection fraction (HFpEF) and heart failure with reduced ejection fraction (HFrEF), impose an enormous health burden on elders. Assessment of the circulating proteome to illuminate pathogenesis could open new opportunities for treatment. METHODS: We conducted a plasma proteomics screen of incident HF and its subtypes in 2 older population-based cohorts, the CHS (Cardiovascular Health Study) and the AGES-RS (Aging, Gene/Environment Susceptibility-Reykjavik Study). The 2 studies used SomaLogic platforms, with 4404 aptamers in common. Multivariable Cox models were fit to evaluate individual-protein associations with HF, HFpEF, and HFrEF separately in each cohort, and study-specific associations were combined by fixed-effects meta-analysis. Replication was performed in the ARIC (Atherosclerosis Risk in Communities) cohort. Two-sample Mendelian randomization of HF and its subtypes, along with colocalization analysis, was performed to support causal inference. RESULTS: Among 8599 participants, 1590 experienced incident HF (536 HFpEF, 471 HFrEF). There were 119 proteins associated with HF, 15 proteins with HFpEF, and 11 proteins with HFrEF, at Bonferroni-corrected significance. Among these, 9 have never previously been identified for cardiovascular diseases, and another 61 represent new associations with incident HF or its subtypes. Of these 70 proteins, 55 of the 66 available replicated externally. Mendelian randomization analysis revealed 7 proteins genetically associated with HF at nominal significance; 2 were separately associated with HFpEF, and another 2 with HFrEF. Seven of these 9 proteins (NPDC1 [neural proliferation differentiation and control protein 1], APOF [apolipoprotein F], LMAN2 [lectin, mannose-binding 2], ADIPOQ [adiponectin], CD14 [cluster of differentiation 14], ARHGAP1 [Rho GTPase-activating protein 1], C9 [complement 9]) showed new, possibly causal associations, although we did not detect evidence for colocalization. CONCLUSIONS: In this large-scale proteomic study involving 3 longitudinal cohorts of older adults, we identified and replicated 55 novel protein markers of HF or its subtypes, and 7 new, possibly causal proteins. These proteins may enhance risk prediction, improve understanding of pathobiology, and help prioritize targets for therapeutic development of these foremost disorders in elders.

Humans↗

PubMed2026

Deconstructing the Alternative Lengthening of Telomeres: Integromics Prioritizes Five Master Hubs Dictating Clinical Survival and Therapeutic Vulnerabilities.

The Alternative Lengthening of Telomeres (ALT) pathway drives replicative immortality in aggressive malignancies, particularly sarcomas and gliomas. Clinical ALT stratification has relied on screening for structural ATRX and DAXX mutations. However, this genotypic approach fails to capture the dynamic macro-reprogramming required to sustain ALT. Here, we established and validated a 28-gene transcriptomic signature that captures the ALT-associated transcriptomic phenotype of the ALT phenotype. Using multivariate Cox proportional hazards models and time-dependent ROC analyses, we demonstrate that this signature is a robust, independent predictor of poor overall survival in Sarcoma (SARC) and Lower Grade Glioma (LGG) cohorts, outperforming the prognostic value of traditional ATRX/DAXX mutational status. Genomic mapping revealed this transcriptional synchrony is structurally facilitated by non-random focal clustering on Chromosome 8. To deconstruct the machinery driving this lethal phenotype, we employed an integromic approach, synthesizing protein-protein and metabolic flux networks. Topological algorithms prioritized five indispensable hubs: TP53, ATM, ATR, PCNA, and UBE2I. Gene-metabolite profiling identified PCNA as a bottleneck funneling extreme deoxyribonucleotide (dNTP) demand to sustain break-induced telomeric recombination. To translate these vulnerabilities into actionable treatments, we mapped these hubs to a precision pharmacological network. We propose a multi-targeted strategy combining FDA-approved PARP inhibitors to exploit ATR-mediated synthetic lethality, alongside antimetabolites to induce nucleotide starvation. This study redefines ALT risk stratification and provides a data-driven framework to target and treat resistant ALT-positive tumors.

Alternative Lengthening of Telomeres↗

PubMed2026

Decoding Primary Open-Angle Glaucoma: A Multi-Omics Approach to Identify Druggable Effector Genes.

PURPOSE: Genomewide association studies (GWAS) have identified numerous primary open angle glaucoma (POAG) risk loci, yet most reside in non-coding regions with unclear function. Mapping these loci to effector genes can elucidate disease mechanisms, identify functionally conserved variants, improve cross-ancestry risk prediction by reducing population-specific noise, and uncover shared therapeutic targets. METHODS: Here, we integrate European POAG GWAS with six types of multi-omics molecular Quantitative Trait Locis (xQTLs) using multi-trait colocalization to identify candidate effector variants and evaluate their cross-population relevance using genetic risk score (GRS) analysis, and their therapeutic potential through drug target prioritization. RESULTS: We identified 25 POAG effector variants colocalized with at least one xQTLs. In non-European populations, effector variants showed stronger effect size correlations with Europeans than non-colocalized variants (Pearson r2 = African 0.85 vs. 0.71; East Asian 0.81 vs. 0.69; and Latin American 0.91 vs. 0.75). Effector variants also had smaller allele frequency variations across populations (average interquartile range [IQR] = 0.15 vs. 0.20). The genetic risk score based on effector variants performed comparably to the genome-wide significant single-nucleotide polymorphism (SNP)-based GRS in non-European populations. Drug prioritization identified zinc, copper, sunitinib, probucol, and astemizole as potential common therapeutic agents for POAG and its subtypes. CONCLUSIONS: Our findings offer deeper insight into the molecular mechanisms underlying glaucoma and effector variants for developing more robust GRS models and broadly effective therapeutic strategies for POAG.

Humans↗

PubMed2026

Genetic diversity and molecular mechanisms in hypertrophic cardiomyopathy: toward personalized therapy.

Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiac muscle disorder, yet contemporary genomic and mechanistic research still lacks a cohesive model explaining how diverse genetic architectures give rise to heterogeneous phenotypes. This review synthesizes advances across sarcomeric and nonsarcomeric mutations, including intermediate-effect variants, polygenic modifiers, and ancestry-dependent sources of variant misclassification to elucidate how these factors govern disease penetrance and clinical expression. It critically evaluates how genetic diversity intersects with key molecular pathways, including sarcomeric hypercontractility, calcium dysregulation, mitochondrial energy deficiency, and transforming growth factor-β (TGF-β) and protein kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling, to drive hypertrophic and fibrotic remodeling. Emerging mechanism-based therapies, such as myosin inhibition, allele-specific silencing, clustered regularly interspaced short palindromic repeats (CRISPR)-based correction, and metabolic modulation, are examined with respect to their capacity to modify upstream molecular drivers rather than downstream hemodynamic consequences. Persistent challenges, including variants of uncertain significance classification, ancestry-biased databases, inequitable access to genetic testing, and unresolved safety concerns for gene-based therapies, are critically assessed as major barriers to precision-medicine integration. By linking genetic architecture, molecular pathogenesis, and targeted interventions, this review advances a contemporary, mechanistically grounded framework that informs both individualized management and future research directions. Future research should prioritize pathway-specific therapeutics, functional and mechanistic validation of emerging variants, deeper physiologic phenotyping to refine disease modeling, and accelerate translation throughout the continuum of HCM pathophysiology.

Humans↗

PubMed2025

Multi-context modeling of driver pathways reveals common and specific mechanisms across 23 cancer types.

Discovery of cancer driver pathways is essential for targeted therapies, since these pathways govern tumor progression and treatment resistance. However, their context-specific patterns across populations remain poorly understood. Leveraging pan-cancer genomic data, we apply our two models, EntCDP and ModSDP, to perform stratified analyses from four perspectives: region, tumor type, age group, and risk factors. Our results reveal the regional biases in perturbed pathways, such as PI3K-Akt in Chinese patients and GPCR in American patients with bladder cancer. Subtype comparisons highlight the mTOR signaling in lung adenocarcinoma and the FoxO signaling in lung squamous cell carcinoma. Pediatric-adult comparisons emphasize the enrichment of Ras signaling in pediatric acute myeloid leukemia and PAK signaling in pediatric glioblastoma, respectively. Risk factor associations further link Notch-mediated pathways to alcohol consumption and CDKN-regulated pathways to obesity-related cancers. Our findings demonstrate the utility of stratified driver pathway analysis in uncovering common and specific mechanisms, which can help prioritize context-aware therapeutic targets.

Humans↗

PubMed2026

Identification of putative causal associations between MicroRNAs and breast cancer via Mendelian randomization and bioinformatic analysis.

MicroRNAs (miRNAs) are implicated in breast cancer progression and prognosis. This study employed a Mendelian randomization (MR) framework to investigate causal relationships between plasma circulating miRNAs and breast cancer. miRNA expression quantitative trait loci were extracted from 2 independent cohorts. High-confidence miRNAs and their associated single-nucleotide polymorphisms were selected for 2-sample MR analyses using inverse-variance weighted and MR-Egger methods. Differential expression analysis and univariate Cox regression identified survival-associated genes in breast cancer, while enrichment analyses revealed pathways and biological processes linked to candidate targets. Pan-cancer analyses of miRNAs and targets were conducted via the ENCORI platform. Initial MR analyses in the discovery phase identified hsa-miR-100-5p, hsa-miR-125b-5p, and hsa-miR-339-5p as significantly associated with reduced breast cancer risk (P < .05), suggesting potential protective roles. A total of 1291 survival-associated differentially expressed genes were identified, with 39 overlapping targets implicated in miRNA-mediated breast cancer intervention. Enrichment analyses highlighted their involvement in cell cycle regulation and p53 signaling pathway. In the validation cohort, only hsa-miR-339-5p confirmed a protective effect on breast cancer risk, while hsa-miR-100-5p and hsa-miR-125b-5p did not reach significance. Pan-cancer profiling demonstrated aberrant miRNA expression across malignancies, prognostic relevance in multiple cancers, and significant negative correlations between miRNAs and target genes in breast tumors. Our findings provide novel insights into the causal roles of miRNAs in breast cancer pathogenesis and underscore their potential as noninvasive biomarkers and therapeutic targets. Future studies should prioritize functional validation and clinical translation of these miRNAs.

Humans↗

PubMed2026

Multi-cohort integration and machine learning identify CPVL as a novel oncogenic driver in gastric cancer.

BACKGROUND: Gastric cancer (GC) remains a leading cause of cancer-related mortality worldwide, and the prognosis of advanced GC remains poor. Systematic identification of robust biomarkers through multi-cohort integration and computational prioritization may facilitate the discovery of novel therapeutic targets. AIM: To identify key genes associated with gastric cancer progression through integrative multi-omics analysis and to elucidate the biological functions and molecular mechanisms of the top-prioritized candidate gene. METHODS: Comprehensive bioinformatics analyses integrating The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Gene Expression Omnibus (GEO) datasets were performed using differential expression analysis, weighted gene co-expression network analysis (WGCNA), Cox regression, and eight machine-learning algorithms to systematically identify and prioritize GC-associated hub genes. Among the identified candidates, CPVL was selected for further validation based on its diagnostic and prognostic performance. CPVL expression and clinical relevance were validated by independent datasets and immunohistochemistry. Lentiviral constructs were used to overexpress or silence CPVL in GC cell lines. Functional assays were performed, including CCK-8, colony formation, EdU incorporation, and flow cytometry, to assess cell proliferation and cell-cycle distribution. Western blotting and JAK2 inhibitor (AZD1480) rescue experiments were performed to elucidate the underlying mechanisms, and a nude mouse xenograft model was used to evaluate tumorigenicity in vivo. RESULTS: Multi-cohort screening identified five hub genes (CPVL, AADAC, BCAT1, CPXM1, and FBN1). Among them, CPVL exhibited the highest diagnostic accuracy (AUC = 0.895) and the strongest correlation with poor overall survival, and was therefore selected for mechanistic investigation. CPVL expression was markedly upregulated in GC tissues and cell lines. Functional assays demonstrated that CPVL promotes GC cell proliferation and accelerates G1/S-phase transition. Mechanistically, CPVL activated the JAK2/STAT3 signaling pathway, upregulating Cyclin D1 and CDK4 while downregulating p27. Treatment with the JAK2 inhibitor AZD1480 partially reversed these effects. In vivo, CPVL knockdown significantly inhibited tumor growth. CONCLUSION: Through systematic multi-cohort integration and machine-learning prioritization, CPVL was identified as a novel oncogenic driver in gastric cancer. CPVL promotes tumor growth via activation of the JAK2/STAT3 pathway and regulation of the Cyclin D1/CDK4/p27 axis, highlighting its potential as a diagnostic biomarker and therapeutic target.

Biomarker↗

PubMed2026

Integrative post-GWAS analysis prioritizes immune regulatory pathways and candidate effector signals in systemic lupus erythematosus.

BACKGROUND: Systemic lupus erythematosus (SLE) has a complex polygenic architecture, but translating genome-wide association signals into biologically interpretable candidates remains challenging. We applied an integrative post-GWAS framework to refine SLE-associated loci and prioritize candidate regulatory mechanisms. METHODS: European-ancestry SLE GWAS summary statistics from FinnGen and Bentham et al. were meta-analysed, comprising 8417 cases and 354,277 controls. After quality filtering, 6,782,131 SNPs were retained. Downstream analyses included LAVA regional prioritization, Bayesian colocalization with GTEx v8 whole-blood and spleen eQTLs, independent replication in the Julià et al. Spanish cohort, pathway enrichment, bivariate LAVA cross-trait local genetic correlation, and therapeutic annotation. RESULTS: The discovery meta-analysis identified 46 genome-wide significant SLE-associated loci, including putative novel signals requiring database/literature qualification. LAVA identified 14 candidate index variants across 12 high-confidence regions, of which nine index variants were retained as the primary prioritized set based on LAVA support and/or convergent regulatory evidence. The strongest association mapped to the chr6p21.3/MHC region (rs389884), where four genes showed colocalization support, including CLIC1 in whole blood and C4A in spleen. Because the chr6p21.3/MHC rs389884 region lead variant was unavailable for replication and no suitable proxy was identified, this signal was interpreted as an emerging candidate for functional validation rather than a replicated causal signal. Seven available variants replicated with concordant effects. An exploratory Roadmap immune chromatin-state overlap analysis placed 15 of 45 non-MHC lead variants (33.3%) directly, and 34 of 45 (75.6%) within ±10 kb, in active immune enhancer/promoter states. Pathway analyses highlighted type I interferon, JAK-STAT signaling, cytokine regulation, and antigen presentation, while bivariate LAVA analyses supported shared local genetic architecture with rheumatoid arthritis, systemic sclerosis, and Sjögren syndrome. CONCLUSIONS: This integrative post-GWAS analysis refines SLE association signals into biologically interpretable candidate regions and supports interferon and JAK-STAT signaling as central genetically supported pathways in SLE.

CLIC1↗