Genetic variants that are associated with phenotypic variability, or variance quantitative trait loci (vQTLs), have been detected for multiple human traits. Gene-environment interactions can lead to differential phenotypic variability across genotype groups, therefore, genetic variants that interact with environmental exposures can manifest as vQTLs. Although changes in DNA methylation variability have been observed in several diseases, vQTLs for methylation levels (vmeQTL) have not yet been explored in depth. We optimize the value of monozygotic twin studies to identify and replicate vmeQTLs for blood DNA methylation variance at 358 CpGs in 988 adult monozygotic twin pairs from two European twin registries. Over a third of vmeQTLs capture identical vmeQTL-environmental factor interactions in both datasets, and the majority of interactions are observed with blood cell counts. Correspondingly, over 60% of CpGs affected by genotype-monocyte and genotype-T cell interactions replicate as CpGs affected by genetic effects in the relevant cell type in an independent dataset. Most vmeQTLs also replicate in 1,348 UK non-twin adults and show longitudinal stability in a sample subset. Integrating gene expression and phenotype association results identifies multiple vmeQTLs that capture GxE effects relevant to human health. Examples include vmeQTLs interacting with blood cell type to influence DNA methylation in FAM65A, NAPRT, and CSGALNACT1 underlying immune disease susceptibility and progression. Our findings identify novel genetic effects on human DNA methylation variability within a unique monozygotic twin study design. The results show the potential of vmeQTLs to identify gene-environment interactions and provide novel insights into complex traits.

Glaucoma is a leading cause of irreversible blindness, yet the circulating proteins and metabolic pathways that causally contribute to different glaucoma subtypes remain poorly defined. We analyzed baseline plasma proteomics in 1485 glaucoma cases (447 primary open‑angle glaucoma [POAG], 177 primary angle-closure glaucoma [PACG], 120 normal-tension glaucoma [NTG]) in the UK Biobank using Cox models with graded adjustment. We then integrated five independent protein quantitative trait loci resources with FINLAND R12 genome-wide association study data to perform two‑sample Mendelian randomization (MR) and cross‑cohort meta‑analysis for overall glaucoma and each subtype. To prioritize effector genes and pathways, we conducted summary-data-based Mendelian randomization (SMR) using eQTLGen and two‑step mediation MR using metabolite quantitative trait loci data for ∼1400 plasma metabolites from the Canadian Longitudinal Study on Aging cohort. In fully adjusted Cox models, 484 proteins were associated with incident glaucoma, 135 with NTG, 59 with POAG, and 1 with PACG (false discovery rate <0.05). Multicohort MR and meta‑analysis identified eight proteins with robust causal effects: NRP2, TSPAN1, and HAVCR2 for overall glaucoma; NRXN3 for PACG; MANSC4 for NTG; and LTBP2, CD69, and SMAD1 for POAG. SMR supported NRP2 (overall glaucoma) and SMAD1 (POAG) as causal genes. Mediation MR revealed that sphingomyelins, acylcarnitines, and bile acid-related metabolites partially mediated the effects of several proteins, defining shared (e.g., sphingolipid) and subtype‑specific metabolic pathways. By integrating epidemiologic, proteomic, genetic, and metabolomic data, we identify convergent systemic protein and metabolic signatures associated with glaucoma susceptibility and its clinical subtypes. These findings nominate NRP2, SMAD1, and related pathways as promising biomarkers and therapeutic targets and support a systems‑level view of glaucoma pathogenesis beyond intraocular pressure alone.

Salinity–alkalinity stress is one of the major abiotic stresses that limit rice production in the world. The salinity–alkalinity tolerance of rice at the germination stage has a direct effect on the survival and final yield of seedlings in direct sowing. However, there are few reports of quantitative trait locus (QTL) mapping and mapping-based cloning of alkaline tolerance at the bud burst stage. Here, new alkaline tolerance loci were constructed for F2:3 and BC3F4 by using IR36 and Long-Dao124 (LD124) rice varieties with significant differences in alkaline tolerance. Through linkage analysis and a fine-mapping strategy, qAT3 was identified as the major QTL for alkaline tolerance at the bud burst stage, which could explain 14.79% of the phenotypic variation on average. Then the interval was fine-mapped to 110.265 kb, and the candidate gene LOC_Os03g03150 was predicted by quantitative real-time polymerase chain reaction (qRT-PCR) analysis and sequencing analysis. This provides a key theory for the molecular breeding of alkali-tolerant genes and the study of the molecular mechanism of alkali tolerance in LD124.

Pulmonary hypertension (PH) underscores the urgent need for novel therapeutic targets. This study aimed to employ a proteome-wide Mendelian randomization (MR) approach to systematically identify circulating proteins causally associated with PH, thereby providing genetically validated candidate targets for drug development. We adopted a 2-sample MR design, integrating large-scale plasma proteomic quantitative trait loci (pQTL) data (encompassing 4148 proteins) and summary statistics from a large-scale PH genome-wide association study (2047 cases, 8301 controls). Candidate targets were screened through a multilayered analytical pipeline comprising proteomic MR, transcriptomic MR, and summary-data-based Mendelian randomization. The ultimately identified MR-Identified Causal Candidate Targets (MR-ICTs) underwent rigorous Bayesian colocalization analysis, followed by biological characterization through functional enrichment analysis, single-cell transcriptomics, and phenome-wide association studies. Through robust genetic causal inference, this study provides that circulating proteins such as LYZ, GREM2, NID1, and PF4V1 play causal roles in PH pathogenesis. These findings offer a set of rigorously genetically validated, high-priority therapeutic targets for developing novel PH treatments, specifically addressing key pathological mechanisms such as innate immunity, BMP signaling pathway dysregulation, and platelet activation. Our multi-dimensional analysis ultimately identified 6 MR-ICTs causally associated with PH. Notably, the causal associations for lysozyme C (LYZ), gremlin-2 (GREM2), nidogen-1 (NID1), and platelet factor 4 variant 1 (PF4V1) were stringently validated by Bayesian colocalization analysis (posterior probability for hypothesis 4 [PPH4], indicating a shared causal variant, > 0.99). Functional enrichment analysis revealed significant involvement of these targets in immune response and TGF-β signaling pathways. Single-cell analysis further elucidated their cell-type-specific expression, with LYZ predominantly expressed in monocytes and PF4V1 almost exclusively in platelets.

This study aimed to investigate the potential causal roles of specific circulating microRNAs (miRNAs) and immune cell subsets in the pathogenesis of hypertrophic scars and keloids using a 2-step Mendelian randomization framework. We employed a 2-sample Mendelian randomization approach to evaluate the causal relationships between miRNAs, immune cell genotypes, and scar phenotypes. The analysis integrated miRNA expression quantitative trait loci, immune cell genome-wide association studies, and scar datasets. A 2-step mediation analysis was conducted to assess the indirect effects of miRNAs on scars through immune cell genotypes, using inverse variance weighted methods and complementary sensitivity analyses to ensure robustness. Our analysis identified significant associations between specific miRNAs and scar phenotypes. Notably, miR-6887-5p exhibited a total effect on keloid formation risk (β = 0.324, 95% confidence interval [CI]: 0.073-0.576) and a direct effect (β = 0.283, 95% CI: 0.027, 0.538), with a marginally significant mediation effect through B-cell activating factor receptor on CD20- CD38- B cells (β = 0.042, 95% CI: -0.001, 0.084, P = .047). For hypertrophic scars, miR-345-5p demonstrated a significant total effect (β = -0.501, 95% CI: -0.903, -0.099) and direct effect (β = -0.469, 95% CI: -0.872, -0.066), with a significant mediation effect through CD28+ CD45RA- CD8dim T cell percentage (β = -0.032, 95% CI: -0.062, -0.002, P = .034). miR-4801 showed a significant total effect (β = -0.246, 95% CI: -0.429, -0.064) and direct effect (β = -0.218, 95% CI: -0.402, -0.033), with a marginally significant mediation effect through T cell absolute count (β = -0.028, 95% CI: -0.057, -0.000, P = .043). These findings highlight the interplay between miRNAs and immune cell subsets in scar pathogenesis. This study provides preliminary evidence for the causal roles of specific miRNAs and immune cell subsets in scar formation, emphasizing the potential of miRNA-immune cell axes as therapeutic targets. While the identified associations offer important insights into the molecular mechanisms of scar heterogeneity, further validation through mechanistic studies and clinical trials is necessary to translate these genetic insights into clinical interventions.

Integrating QTL mapping with transcriptome analysis uncovers candidate genes of ear length in maize.

Improving feed efficiency in cattle is increasingly important for both environmental and economic reasons. Although feed efficiency traits are under considerable genetic control, with an average moderate heritability estimate of 0.33, genetic evaluations are limited by the difficulties in measuring feed intake and the lack of records from most commercial herds. Most genetic evaluations rely on small numbers of records from research farms, resulting in under-represented genetic variation and pronounced sampling errors in heritability estimates. To enhance the discovery of genetic mechanisms underlying feed efficiency and to address measurement limitations and the under-representation of genetic variation, we used joint phenotypic and genotypic measurements from two distinct herds for GWAS and in-depth genomic analysis. By applying this approach, our exploratory analysis discovered fourteen significant markers with effects on residual feed intake (RFI) ranging from -1.41 to 1.44 kg/day. Quantitative trait loci (QTLs) enrichment analysis specifically pointed to traits that contributed to RFI, including dry matter intake (DMI), body weight (BW), and protein yield. Gene enrichment analysis, which was largely biased by a local cluster of vomeronasal receptor genes within a single ~ 500 kb region on BTA18, suggested three sets of genes of interest: a vomeronasal pheromone receptor cluster (VN1R1 and four additional response to pheromone genes on BTA18), genes linked to social and behavioral responses (EPC2 on BTA2; SYN3 on BTA5), and fat metabolism-related genes (KIF5C on BTA2; SV2B on BTA21). Of these candidate genes, likely functional amino acid (AA) variations were observed in the VN1R1 putative protein (314 AA) after screening a sample of 27 Israeli Holstein genomes. These functional variations included two truncation mutations that could encode 89 and 239 AA polypeptides. Consistent with these findings, whole-genome sequence data analysis of RFI-characterized Irish bulls identified a significant association between the 89 AA truncation and high RFI, further validating our results and indicating that although such variation was common, the presence of an intact VN1R1 receptor was associated with a beneficial effect on feed efficiency. Moreover, the 89 AA truncation was observed in diverse cattle breeds, including American, Israeli, Irish, and New Zealand Holstein. These findings are compatible with feed efficiency, a complex trait governed by neural (behavioral) and metabolic components. Further characterization of these factors would allow genetic selection to reduce feed costs and environmental footprints.

Maltose is one of the most abundant sugars in brewer's wort, and its efficient utilization is critical for successful fermentation. However, maltose consumption varies naturally among Saccharomyces eubayanus strains isolated from different host trees, such as Quercus and Nothofagus. To identify the genetic determinants underlying these phenotypic differences, we performed bulk segregant analysis (BSA) and quantitative trait loci (QTL) mapping using an F2 offspring derived from QC18 (Quercus-associated) and CL467.1 (Nothofagus-associated) strains. QTL mapping identified two significant genomic regions on subtelomeric loci of chromosomes V-R and XVI-L, each containing complete MAL loci composed of MAL32 (encoding maltase), MAL31 (transporter), and MAL33 (transcriptional activator) genes. Comparative polymorphism analyses identified mutations in MAL32 and MAL33 of QC18, including frameshift mutations resulting in premature stop codons. Functional validation demonstrated that the heterologous expression of MAL33ChrV from CL467.1 fully restored maltose utilization in QC18, indicating the functional presence of MAL33 cis-regulatory sequences and MAL32 and MAL31 genes in QC18. While structural protein predictions identified truncation and impaired functionality in the maltose-responsive activation domain of Mal33p from QC18, overexpression of QC18's own MAL33ChrV allele also improved maltose metabolism, suggesting dosage-dependent transcriptional limitations rather than complete functional loss. These results indicate that allelic variations in the maltose-responsive activation domain of Mal33p result in differences in maltose consumption between strains. We hypothesized that reduced maltose metabolism in QC18 is an adaptive response to the distinct sugar composition in Quercus robur bark, contrasting with the starch-rich environment of Nothofagus pumilio. These findings highlight subtelomeric MAL gene diversity as a reservoir of genetic variation, representing a key evolutionary mechanism that influences maltose adaptation among natural Saccharomyces isolates.

HIV-1 remains a global health challenge, emphasizing the need to identify new host factors that influence pathogenesis to serve as drug targets. Identifying genetic determinants of HIV-1 control across diverse populations remains a top priority. We conducted a multi-ancestry genome-wide association study (GWAS) of HIV-1 set-point viral load (spVL) leveraging genotype and viral load data from 10,723 individuals living with HIV-1. To prioritize candidate genes and mechanisms, we integrated GWAS findings with transcriptome-wide association study (TWAS) and expression quantitative trait loci (eQTL) data. We implicate the potential role of zinc finger proteins in pathogenesis through identification of a novel signal in the zinc finger protein 586 (ZNF586) gene on chromosome 19, which is predicted to regulate RNA polymerase II transcription. The top variant, (rs35962362-G) is intronic to the ZNF586 gene, and is associated with an approximate 0.1 log increase in spVL per mutant allele. Our subsequent TWAS along with interrogation of eQTL data suggest that increased ZNF586 expression is associated with increased spVL in whole blood. Our findings suggest ZNF586 as a novel host factor for HIV-1 control and highlight the role of zinc finger proteins as potential contributors to viral persistence. Although ZNF586 has not previously been linked to HIV pathogenesis, its potential role in maintaining retroviral latency and modulating genomic regulation warrants further investigation.

Integration and modularity can have a profound impact on the function and evolution of environmentally responsive traits, especially when they result in discrete, alternative forms-that is, developmental polyphenism. An unresolved issue for understanding this impact is the degree to which the genetic architectures of the individual components of a plastic trait permit independent versus coordinated evolution. The association of trait variation with genomic variation can provide a test of whether the same loci influence different components of the same integrated phenotype. An example of a coordinated, plastic trait is in the shark-tooth nematode Pristionchus pacificus, which develops into either a bacterial-feeding or a predatory adult morph, depending on its perception of local food availability. Moreover, this polyphenism, when measured as morph induction in response to a common set of cues, differs across natural isolates of the species. By creating recombinant inbred lines (RILs) from natural isolates that have diverged in their morph-induction bias, followed by quantitative trait locus analysis, we tested whether and the extent to which component traits of this resource polyphenism are linked. We found that RILs with more frequent induction of the predatory morph also produced Eu individuals that were more effective predators. We also found that these two traits are associated with the same major-effect locus, suggesting that their causal genes are physically linked, if not the same, and are therefore likely to experience coordinated selection. In contrast, we found that morphological variation was not linked to these two traits and that such variation within each morph was even independent of variation in the other. Our findings show that the same coordinated plastic trait exhibits a blend of genetic correlation and independence, whose balance shapes the trait's evolutionary potential.

Background Dizziness/vertigo is a multifactorial neurological disorder with complex ge-netic and cellular bases, yet its molecular mechanisms remain unclear. Understanding how gene regulation contributes to dizziness/vertigo may reveal novel neurobiological and therapeutic insights. Methods We established a multi-omics integrative framework combining genome-wide association study (GWAS) data with expression quantitative trait loci (eQTL) from brain single-cell types, CD4+ T cells, oneK1K immune cells, and plasma. Two-sample Mendelian randomization (MR) and colocalization analyses were applied to identify causal genes. Single-cell RNA sequencing (scRNA-seq) of the auditory nerve was used to as-sess cell type–specific expression, intercellular communication, and pseudotime dynam-ics. Gene–gene interaction and drug–target networks were further constructed to identify potential therapeutic candidates. Results Six key genes—Activin A Receptor Type 2A (ACVR2A), Phospholipid Transfer Protein (PLTP), Androgen Dependent TFPI Regulating Protein (ADTRP), Methylenetetrahydrofolate Dehydrogenase (NADP + Dependent) 1 Like (MTHFD1L), Collagen Type VII Alpha 1 Chain (COL7A1), and Pantothenate Kinase 4 (PANK4)—showed strong causal and colocalization evidence for dizziness/vertigo. Single-cell analysis revealed distinct cell type–specific expression, with fibroblasts and adipocytes playing central roles in signaling and gene regulation. Pseudo-time trajectories indicated coordinated upregulation of ACVR2A, MTHFD1L, PANK4, and PLTP during later developmental stages. Interaction network analysis positioned these genes as major hubs, and DrugBank screening identified Sotatercept as a promising candidate targeting ACVR2A. Conclusion This integrative analysis links gene expres-sion regulation to dizziness/vertigo across neuroimmune and metabolic systems. The findings uncover coordinated molecular pathways underlying disease susceptibility and highlight novel therapeutic targets, providing a foundation for precision treatment strate-gies.

Gestational diabetes mellitus (GDM) is a prevalent metabolic disorder during pregnancy associated with adverse maternal and fetal outcomes, highlighting the urgent need for novel, genetically supported drug targets due to suboptimal glycemic control and safety concerns with existing therapies. This study integrated cis-expression quantitative trait loci (cis-eQTL) of druggable genes with genome-wide association data to identify putative causal genes for GDM through two-sample Mendelian randomization (MR), with significant associations further validated using multi-tissue summary data-based Mendelian randomization (SMR), colocalization analysis, cis-protein quantitative trait loci (cis-pQTL) MR, and single-cell RNA sequencing (scRNA-seq) to confirm tissue- and cell type specific expression. MR analysis identified 15 genes significantly associated with GDM risk after Bonferroni correction, with SMR and colocalization analyses confirming robust associations for five key genes: higher expression of NRBP1, LPL, and BTN3A2 was causally linked to reduced GDM risk, while elevated GSTM1 and GRINA levels were associated with increased risk. ScRNA-seq revealed distinct expression patterns in placental cell types, with NRBP1 and GRINA highly expressed in trophoblasts and certain immune cell populations. Phenome-wide association studies revealed no significant pleiotropic effects, and pharmacological drug-target databases identified several compounds with potential regulatory interactions. This multi-omics study successfully identifies several genetically supported, druggable targets for GDM, providing a robust foundation for developing mechanism-based therapeutics and precision prevention strategies in pregnancy metabolism.

ABSTRACT Purpose This study investigated the causal effect of 3-carboxy-4-methyl-5-propyl-2-furanpropanoic acid (CMPF) on erectile dysfunction (ED) and elucidated its underlying molecular mechanisms through multi-omics integration. Methods Mendelian randomization (MR) was applied to evaluate the causal effects of CMPF on ED and metabolic risk factors. Network pharmacology was used to identify overlapping molecular targets, followed by molecular docking to assess binding affinity. Multi-omics validation incorporated Summary-data-based MR (SMR) analyses of expression and protein quantitative trait loci (eQTL/pQTL) to confirm genetically regulated CMPF-related targets. Results MR analyses demonstrated a protective effect of CMPF on ED in both discovery (OR: 0.78, 95% CI: 0.62–0.98) and replication cohorts (OR: 0.82, 95% CI: 0.69–0.98), along with favorable associations with glucose metabolism, blood pressure, and lipid traits. Network analysis identified 42 shared targets, with DPP4, LGALS3, and NR3C2 as hub targets. Molecular docking showed strong binding affinities (≤−6.0 kcal/mol). SMR analyses highlighted LGALS3 as a key genetic mediator, supported by consistent eQTL and pQTL signals. Conclusions CMPF exerts protective effects against ED and metabolic dysfunction through multi-target modulation, with LGALS3, DPP4, and NR3C2 as central regulators. These findings support CMPF as a diet-derived bioactive metabolite with potential for nutritional interventions and multi-target therapeutic strategies in ED.

Objective Autoimmune thyroiditis (AIT), a prevalent autoimmune disorder that frequently leads to hypothyroidism. A critical unmet need exists for disease-modifying therapies that target its underlying pathogenesis. This study aimed to identify and validate novel therapeutic targets for AIT. Methods We employed an integrative genomics approach, combining genome-wide association studies (GWAS) with molecular quantitative trait loci (QTL) analyses, including expression (eQTL), protein (pQTL), and DNA methylation QTL (mQTL), across two independent AIT cohorts for discovery and replication. We performed two-sample bidirectional Mendelian randomization (MR) with sensitivity analyses, followed by summary-data-based MR (SMR) and heterogeneity in dependent instruments (HEIDI) tests. Top candidates were further evaluated via phenome-wide association study (PheWAS) and computational drug screening. Guided by these findings, we quantified plasma levels of the top-priority candidate, Ribonuclease T2 (RNASET2), via ELISA in AIT patients and non-AIT controls. To functionally validate its therapeutic potential, we developed a novel three-dimension (3D) inflammatory thyrocyte spheroid model and evaluated potential therapeutic effects of recombinant RNASET2. Loss-of-function (small interfering RNA-mediated knockdown) and gain-of-function (recombinant protein RNASET2 rescue) experiments further supported RNASET2 as a therapeutic target. Results Multi-omics integration consistently nominated RNASET2 as a causal protective factor against AIT. Signals of pQTL and eQTL for RNASET2 were associated with decreased AIT risk, while three mQTLs were correlated with increased risk. PheWAS indicated minimal pleiotropic effects, supporting its therapeutic suitability. Computational drug screening nominated genistein, a soy isoflavone known to upregulate RNASET2 expression, as a repurposing candidate. Empirically, plasma RNASET2 levels were moderately elevated in AIT patients, potentially reflecting a compensatory anti-inflammatory response. Crucially, recombinant RNASET2 effectively mitigated inflammation and apoptosis in the thyrocyte spheroid model, confirming its functional protective role. Consistently, RNASET2 knockdown heightened susceptibility to inflammatory cell death and cytokine expression, a phenotype reversed by recombinant RNASET2 supplementation. Conclusions By integrating large-scale genomic analyses with functional validation, our study establishes RNASET2 as a promising therapeutic target for AIT. RNASET2 augmentation represents a potential disease-modifying strategy, providing a translational bridge from genetic discovery to clinical application.

The Smarcal1-Usp37 locus modulates glycogen aggregation in astrocytes of the aged hippocampus.

The molecular pathways linking genetic variants to Parkinson's disease (PD) onset and progression remain incompletely defined; however, risk alleles in multiple genes, including GBA1, strongly implicate lipid metabolism. To systematically identify causal biomarker signatures, we analyzed comprehensive metabolome profiles from blood plasma in 149 PD patients and 150 controls, along with complementary genetic, RNA-sequencing, and metabolic data from other available clinical and pathologic cohorts. Using colocalization and summary-data-based Mendelian randomization, we tested whether expression and metabolic quantitative trait loci mediate the association between implicated genetic variants and PD risk. We further integrated differential metabolomics and proteomics from blood and brain to reveal pertinent mechanisms. We show that common PD risk variants at the serine palmitoyltransferase small subunit B (SPTSSB) locus, a key regulator of de novo sphingolipid biosynthesis, are associated with increased SPTSSB brain expression and elevated plasma ceramides. Additional analyses strongly support our hypothesis that a common SPTSSB causal variant is responsible for PD risk as well as the expression and metabolic quantitative trait loci. Multiple sphingolipids and fatty acid derivatives were perturbed in PD, and we identified both unique and shared features with the Alzheimer's disease metabolome. A PD acylcarnitine signature was further replicated in human postmortem brain tissue, when comparing those with or without preclinical Lewy body pathology. Integrated analysis of complementary brain proteomic profiles revealed dysregulation of mitochondrial processes dependent on acylcarnitines, including fatty acid beta-oxidation, the tricarboxylic acid cycle, and oxidative phosphorylation. Our results identify promising biomarkers and reveal a causal chain linking genetic variation to altered gene/protein expression, lipid dysmetabolism, and the manifestation of PD.

Rice yield-related traits are regulated by numerous quantitative trait loci (QTLs). Pyramiding these QTLs offers a promising strategy for crop yield improvement; however, this approach is constrained by the limited understanding of the interactions among these QTLs. In this study, we demonstrated that the QTL DTH8 significantly increases branch numbers, panicle length, and number of total grains per panicle in rice. Notably, the DTH89311 allele exhibited a more pronounced effect on enhancing yield-related traits compared to DTH8Nip. Furthermore, QTL pyramiding involving SD1 and DTH8 indicated that the regulation of panicle architecture by DTH8 partially depends on SD1. Genetic analysis revealed an interaction between these two QTL/genes with respect to panicle-related traits. Dual-luciferase and ChIP-PCR analyses suggested that DTH8 might regulate the expression of SD1, thereby governing branch numbers, panicle length, and number of total grains per panicle. Additionally, our findings highlight the importance of avoiding the simultaneous pyramiding of sd1 and DTH89311 in practical breeding programs due to their genetic and molecular interactions.

Detection and mapping of gm13, a QTL governing recessive resistance to rice gall midge.

Identification of endoplasmic reticulum stress-related genes associated with Alzheimer's disease risk: A multi-omics Mendelian randomization analysis.

This study aims to explore shared key genes between head and neck neoplasm (HNN) and aging. Using single-cell RNA sequencing data of peripheral blood from HNSCC patients, aging individuals, and healthy controls, we identified cross-group co-expressed, downregulated cell subpopulations as core targets. Integrated pseudotime trajectory analysis and intercellular communication modeling were employed to investigate the dynamic evolution and functional interaction patterns of these subpopulations. Differentially expressed genes were identified, followed by Mendelian randomization (MR) analysis to assess their causal associations with HNN. Co-localization analysis was performed using GWAS data for HNN and expression quantitative trait loci (eQTL) datasets. Key genes were further subjected to metabolic pathway enrichment analysis. T cell subsets were found to be represented in both HNN and aging. Among them, CD4_naive T cells were down-regulated in both groups, leading to the identification of 24 differentially expressed genes. MR studies have shown that CCR, LEF1, NOSIP and FHIT have causal relationships with HNN. In the validation phase, however, only FHIT was retained, for which co-localization analysis revealed limited evidence of a shared causal variant between the GWAS and eQTL signals (H4 = 0.01). The metabolic enrichment highlighted metabolic pathways associated with these genes. This study identified CD4_naive T cells down-regulation as a shared feature of HNN and aging and highlighted FHIT as potential molecular links. These findings may provide novel insights into the intersection of aging and tumorigenesis based on MR and single-cell analysis, offering potential targets for combined therapeutic strategies.