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PubMed2026

Dissecting the genetics of forage quality traits in soft red winter wheat in the U.S. southeast region.

Winter wheat plays a viable role in agriculture, not only as a primary grain crop but also as a valuable forage source that bridges fall-spring forage gaps in many regions, including the southeastern (SE) U.S. Despite its nutritive potential, genetic basis of forage-quality traits remains insufficiently understood, limiting breeding efforts for dual-purpose cultivars. This study aimed to dissect the genetic architecture of forage quality in 182 soft red winter wheat (SRWW) genotypes adapted to the SE U.S. using genome-wide association study (GWAS). Field experiments were carried out in randomized complete block design across three Georgia locations over two growing seasons (2023-2025), with forage sampled at the end of tillering and evaluated using near-infrared reflectance spectroscopy. Significant phenotypic variation was observed for dry matter (DM), crude protein (CP), acid and neutral detergent fiber (ADF, NDF), acid detergent lignin (ADL), total digestible nutrients (TDN), sugars (SUG), and relative forage quality (RFQ). Heritability estimates ranged from low-to-moderate in combined environments and from low-to-high within individual locations. Correlation analysis revealed strong positive associations among fiber-related traits and negative associations with TDN, RFQ, and SUG, while CP declined with increasing fiber. Genome-wide association analysis identified 282 significant marker-trait associations (P < 1×10-4) across 19 chromosomes, which were consolidated into 121 QTLs, including 27 major-effect QTLs. Three QTLs QRfq.uga-3B.1, QRfq.uga-3B.2 (RFQ) and QDm/Sug.uga-7A (DM, SUG) were stable across locations while QAdf/Adl.uga-2A (ADF, ADL) and QDm/Sug.uga-7A (DM, SUG) indicated multi-trait control. Notably, 25 of the 27 major QTLs were putatively novel, highlighting substantial untapped allelic diversity for forage-quality improvement in SE SRWW. Favorable allele accumulation resulted in an overall improvement in forage quality, increasing desirable nutritive traits (DM, RFQ, SUG, CP) while reducing undesirable traits (ADF, ADL). Candidate gene analysis linked six major QTLs with genes implicated in abiotic stress response, plant development, and metabolic regulation, supporting their functional relevance in forage-quality determination. Incorporating these loci into breeding programs provides a robust genetic framework for marker-assisted selection, enabling the development of dual-purpose wheat cultivars with enhanced forage quality, thereby strengthening wheat's utility as a reliable forage resource during periods of seasonal feed scarcity in SE production systems.

GWAS↗

PubMed2026

Genome-wide association study reveals candidate genes associated with body weight and wool traits in Ordos fine-wool sheep.

BACKGROUND: The Ordos fine-wool sheep is a high-quality fine-wool breed in China, renowned for its excellent wool quality, meat production, and adaptability to the arid and semi-arid regions of Inner Mongolia. Body weight and wool traits are important economic characteristics in sheep breeding. This study aimed to identify genetic loci associated with body weight (BW), wool length (WL), and wool fineness (WF) in Ordos fine-wool sheep. METHODS: A genome-wide association study (GWAS) was conducted in 388 Ordos fine-wool sheep genotyped using the GenoBaits® Ovine 40K SNP panel. Single nucleotide polymorphisms (SNPs) associated with BW, WL, and WF were identified, and candidate genes located near the SNPs reaching the suggestive threshold were subjected to functional annotation and enrichment analysis. RESULTS: A total of 22 SNPs were identified as potentially associated with BW, WL, and WF traits, corresponding to 27 annotated genes. Functional annotation highlighted six potential candidate genes, including LAMA2, ARHGAP18, IGFBP2, IGFBP5, CA10, and AXIN1, which may play important roles in regulating body weight and wool growth in sheep. CONCLUSIONS: The identified genes provide valuable candidate loci for BW, WL, and WF traits in Ordos fine-wool sheep. The results of this study provide preliminary references for further exploration of the genetic mechanisms of wool traits in Ordos fine-wool sheep and the development of molecular breeding markers.

GWAS↗

PubMed2026

Deciphering the Genetic Underpinnings of Liver Cirrhosis-Heart Failure Comorbidity Through Multi-Omics: CRIM1 as a Key Endothelial Mediator.

The co-occurrence of liver cirrhosis (LC) and heart failure (HF) poses considerable clinical challenges, yet the cellular and molecular determinants of this comorbidity remain poorly characterized. To address this, we developed an integrative multi-omics pipeline encompassing GWAS meta-analysis, gsMap-based spatial transcriptomic projection, GeneEnrich functional annotation, single-cell atlas construction, seismicGWAS and ECLIPSER cell-type scoring, eCAVIAR and fastenloc colocalization, hdWGCNA network inference, scTenifoldKnk in silico gene perturbation, and GCTA-COJO fine-mapping. Quality-controlled meta-analysis yielded 12,347,758 and 9,256,862 variant-level associations for LC and HF, respectively. Spatial projection confirmed preferential enrichment of disease signals within embryonic hepatic and cardiac compartments. Pathway analyses disclosed that LC-linked loci were concentrated in lipid metabolic programs, whereas HF-linked loci implicated mitochondrial bioenergetics and lysosomal degradation. At the cellular level, endothelial cells emerged as the dominant HF-associated population. Convergent evidence from five orthogonal algorithms pinpointed CRIM1 as the sole robustly supported shared gene, selectively enriched in HF endothelial cells; virtual perturbation further identified LCP1 and PTPRC as downstream regulatory nodes. Fine-mapping of the chromosome 2 locus harboring rs12476437 revealed multiple statistically independent signals in the vicinity of CRIM1. Collectively, these findings computationally prioritize the endothelial-CRIM1 axis as a previously unappreciated candidate mechanistic bridge between LC and HF requiring experimental validation.

Humans↗

PubMed2026

The genetic control of rapid genome content divergence in Arabidopsis thaliana.

Genome evolution in eukaryotes is predominantly driven by the dynamics of repetitive sequences, which vary widely in both copy number and sequence composition. Rates of repeat evolution differ between and within species and are likely modulated by both genetics and environment. To uncover factors shaping the rate of genome content evolution, we analyzed 1043 resequenced Arabidopsis thaliana genomes using a novel K-mer-based approach to characterize genome content variation and identify hypervariable regions underlying differences in repeat abundance. We next treated repeat abundance as a quantitative trait and performed genome-wide association analyses across more than 400 repeat families to identify the genetic basis of copy number variation. Integrating these results through a meta-GWAS approach revealed both cis-acting variants and more than 50 candidate trans-acting loci associated with repeat abundance genome-wide. Cis-acting variation was predominantly localized to pericentromeric and centromeric regions, whereas trans-acting loci were enriched for candidate genes involved in DNA replication, DNA repair, and DNA methylation regulation. The results are consistent with purifying selection acting against mutations that accelerate genome content divergence, favoring alleles that constrain repeat expansion. Together, these findings provide new insights into the genetic architecture and evolutionary forces shaping genome evolution in A. thaliana and establish a framework for investigating these processes in other plant species.

Arabidopsis↗

PubMed2026

Estimation Model of Pig Weight Based on Body Measurements and Analysis of Its Genetic Basis.

Body weight and body measurements are key indicators of growth and economic efficiency in pigs, but conventional weighing is labor-intensive and stressful, increasing disease risk and necessitating non-contact estimation. We measured five dimensions (body length, chest circumference, abdominal circumference, body width, and body height) in 811 Suzi black pigs and constructed six multiple linear regression models using different combinations. All models had R2 > 0.91, with adjusted R2 also exceeding 0.91, and the model combining length, chest, and abdominal circumference gave the lowest RMSE, balancing accuracy and practicality. Separately, we performed GWAS on 165 genotyped individuals (100 K SNP chip and GBS) for age (as a growth rate proxy), body weight, and the five measurements. No SNP reached genome-wide significance (p < 1.86 × 10-6), but three suggestive loci (p < 1.39 × 10-5) were detected: SNP 4_12 319 200 for age (35.55% variance), a pleiotropic SNP 1_60 912 826 associated with length, chest, and abdominal circumference (42.10%, 53.06%, and 45.97% variance), and SNP 1_60 638 159 for abdominal circumference. Positional mapping identified EPHA7 as the nearest candidate gene. Enrichment analyses revealed focal adhesion, receptor tyrosine kinase, IgSF-CAM, integrin, and PI3K-Akt pathways, with EPHA7 and FYN as key regulators. Notably, the three traits in the best model mapped to the same pleiotropic locus, suggesting a shared genetic basis. This study provides a practical estimation tool and suggestive markers, supporting non-contact weighing systems and molecular breeding.

Animals↗

PubMed2026

Integrating Genetics and Environment to Find Causal Mechanisms for Multiple Sclerosis.

Genome-wide association studies (GWAS) have identified hundreds of risk loci for multiple sclerosis (MS), but we have limited knowledge of the mechanisms through which genetic variants mediate risk. Similarly, epidemiological studies implicate numerous environmental risk factors in MS risk, but these cannot identify specific causal mechanisms. We review our current knowledge of genetic mechanisms in MS, including the critical role of expression quantitative trait locus (eQTL) mapping in translating genetic risk loci into causal mechanisms. Molecular and functional context has emerged as an important missing component of these studies, and we discuss how environmental risk factors can be modelled in a quantitative genetic context to identify disease mechanisms. In parallel, we highlight recent advances in which quantitative genetic methods establish a causal role for low vitamin D and obesity in MS, and to dissect the mechanisms through which these operate. As genetic, transcriptional, and epigenetic studies continue to expand, further mechanistic insights for MS are likely to come from the integration of genetic and environmental data.

Humans↗

PubMed2025

Genome-Wide Association Analyses of HPV16 and HPV18 Seropositivity Identify Susceptibility Loci for Cervical Cancer.

Infection by high-risk human papillomavirus is known to exacerbate cervical cancer development. The host immune response is crucial in disease regression. Large-scale genetic association studies for cervical cancer have identified few susceptibility variants, mainly at the human leukocyte antigen locus on chromosome 6. We hypothesized that the host immune response modifies cervical cancer risk and performed three genome-wide association analyses for HPV16, HPV18 and HPV16/18 seropositivity in 7814, 7924, and 7924 samples from the UK Biobank, followed by validation genotyping in the German Cervigen case-control series of cervical cancer and dysplasia. In GWAS analyses, we identified two loci associated with HPV16 seropositivity (6p21.32 and 15q26.2), two loci associated with HPV18 seropositivity (5q31.2 and 14q24.3), and one locus for HPV16 and/or HPV18 seropositivity (at 6p21.32). MAGMA gene-based analysis identified HLA-DQA1 and HLA-DQB1 as genome-wide significant (GWS) genes. In validation genotyping, the genome-wide significant lead variant at 6p21.32, rs9272293 associated with overall cervical disease (OR = 0.86, p = 0.004, 95% CI = 0.78-0.95, n = 3710) and HPV16 positive invasive cancer (OR = 0.73, p = 0.005, 95% CI = 0.59-0.91, n = 1431). This variant was found to be a robust eQTL for HLA-DRB1, HLA-DQB1-AS1, C4B, HLA-DRB5, HLA-DRB6, HLA-DQB1, and HLA-DPB1 in a series of cervical epithelial tissue samples. We additionally genotyped twenty-four HPV seropositivity variants below the GWS threshold out of which eleven variants were found to be associated with cervical disease in our cohort, suggesting that further seropositivity variants may determine cervical disease outcome. Our study identifies novel genomic risk loci that associate with HPV type-specific cervical cancer and dysplasia risk and provides evidence for candidate genes at one of the risk loci.

Humans↗

PubMed2026

Subtype-Specific Causal Effects of C16 and C24 Ceramides on Heart Failure: Evidence From Univariable and Multivariable Mendelian Randomization Analyses.

Ceramides (Cer) are bioactive lipids implicated in cardiovascular disease (CVD), yet their subtype-specific causal effects remain unclear. We performed a two-sample Mendelian randomization (MR) analysis using publicly available GWAS summary statistics to investigate the effects of C16:0-ceramide homologs (Cer16:0) and C24:1-ceramide homologs (Cer24:1) on six CVD outcomes. Instrumental variables were rigorously selected, and multiple MR methods were applied to ensure robust inference. Univariable MR identified a significant inverse association between Cer(d18:1/24:1) and heart failure (HF), which remained significant after false discovery rate correction. In contrast, the association for Cer(d17:1/16:0) did not remain significant after correction. No causal associations were observed for other CVD outcomes. When aggregating subtypes, genetically predicted higher total Cer16:0 levels were associated with increased HF risk, while no significant association was found for total Cer24:1. Multivariable MR further demonstrated that the protective effect of Cer(d18:1/24:1) on HF was robust, while estimates for C16 subtypes were attenuated and sensitive to model specification. In conclusion, our findings support a stable protective role of Cer(d18:1/24:1) in HF and highlight the complexity of subtype-specific effects among structurally related ceramides. These results underscore the importance of considering ceramide heterogeneity in cardiovascular research. Further studies are warranted to validate these findings and explore their clinical implications.

Ceramides↗

PubMed2026

Accelerated Biological Aging Increases the Risk of Head and Neck Cancer: Insights From Genetic Instruments of Epigenetic Clocks.

Epigenetic clocks are robust biomarkers of biological aging and have been associated with cancer susceptibility. However, the relationship between genetically predicted epigenetic age acceleration and head and neck cancer risk remains unclear. Using a large case-control study of 2189 head and neck squamous cell carcinoma (HNSCC) cases and 2189 age- and sex-matched controls, we investigated the associations between polygenic scores (PGSs) for multiple epigenetic clocks and HNSCC risk, and evaluated their potential causal roles using two-sample Mendelian randomization (MR). Genome-wide association study (GWAS)-identified single nucleotide polymorphisms (SNPs) associated with four epigenetic clocks (HannumAge, HorvathAge, GrimAge, and PhenoAge) were used to construct clock-specific PGSs. Logistic regression models were applied to assess associations between PGSs and HNSCC risk, while MR analyses, including inverse-variance weighted (IVW), weighted median, and MR-Egger methods, were used to infer potential causal relationships. Among the 48 epigenetic clock-associated SNPs, 12 showed nominal associations with HNSCC risk, and one variant (rs2275558 in PBX1) remained significant after Bonferroni correction (OR = 0.67, 95% CI: 0.60-0.76). PGSs for all four epigenetic clocks were higher in cases than in controls. In logistic regression analyses, each standard deviation increase in HannumAge PGS was associated with a 25% higher risk of HNSCC (OR = 1.25, 95% CI: 1.10-1.41), whereas HorvathAge, GrimAge, and PhenoAge PGSs showed weaker positive associations (ORs ranging from 1.06 to 1.10). Individuals in the highest PGS quartile for all four epigenetic clocks exhibiting 14%-25% higher risk than those in the lower three quartiles. MR analyses supported potential causal effects of genetically predicted HannumAge (IVW OR = 1.24 per SD increase, 95% CI: 1.09-1.42) and GrimAge (IVW OR = 1.23 per SD increase, 95% CI: 0.98-1.56) on HNSCC risk, with consistent estimates in weighted median analyses. Our results highlight biological aging as a potential etiologic mechanism for HNSCC and suggest that epigenetic clock-related genetic profiles may improve HNSCC risk stratification.

Humans↗

PubMed2025

Genetic basis and role of exotic accessions in cultivated cotton fiber quality improvement.

Exotic Gossypium accessions still harbor QTL‑validated alleles that, combined with CRISPR pyramiding and genomic selection, can break the entrenched fiber length-strength trade‑off. Cotton's four independent domestications twice in diploids and twice in allotetraploids offer a natural experiment in fiber improvement. Synthesizing three decades of data, we chart how polyploidy, selection and modern breeding have repeatedly reshaped the Gossypium genome. More than 15,000 quantitative trait locus (QTL) and genome wide association mapping studies (GWAS) hits converge on a handful of chromosomal "hotspots"; new MAGIC, NAM, NIL and long-read resources now narrow these peaks to < 200 kb, resolving causal genes such as GhHOX3, GhZF14 and GhMYB7. Multi-omics evidence links auxin, ethylene, gibberellin, brassinosteroid and strigolactone signaling to HDZIP IV, MYB, bHLH/HLH and ERF networks that drive fiber initiation, extreme cell elongation and cellulose deposition. Population genomics shows that ~ 40% of favorable fiber alleles are fixed in elite Gossypium hirsutum, yet wild diploids and landraces still harbor variants that could break the length strength trade-off. We propose a three-step roadmap genomic selection, CRISPR gene pyramiding and accelerated introgression to expand cotton's genetic base and deliver fibers suited to sustainable textile demands.

Gossypium↗

PubMed2025

Genomic prediction of agronomic traits in perennial ryegrass (Lolium perenne L.) and genotype x environment interactions at the limit of the species distribution.

KEY MESSAGE: Perennial ryegrass shows extensive genotype x environment interactions at the limit of its ecological niche. Accounting for GxE may improve prediction even when environmental and genetic samples are highly diverse. BACKGROUND: In breeding the aim is to identify and accumulate beneficial variants. However, detection of these variants may be challenging in the presence of extensive genotype x environment interactions (GxE). METHODS: The study assesses the performance of 264 diploid perennial ryegrass accessions in a multi-environment field trial. We investigate the extent of GxE, for yield (total dry matter) and persistence traits under environmental conditions experienced in Nordic and Baltic regions at the limit of the species distribution. Two different approaches to modelling GxE were tested and validated under three different breeding scenarios. RESULTS: Our analysis documented the presence of significant GxE for all traits. Validation showed improvements in prediction accuracy when accounting for GxE: up to 4% for yield when predicting in unobserved environments, and up to 22% and 9% for spring cover and winter kill, respectively, when predicting unobserved germplasm. Genome-wide-association-studies (GWAS) were utilized to detect genetic variants with marginal effects (environment-independent effect) and conditional effects (environment-dependent effects). Results showed the presence of large-effect genetic variants with marginal effects, in addition to few Quantitative Trait Loci (QTL) whose effects were adaptive under specific environmental conditions while neutral or deleterious under different environmental conditions. CONCLUSION: This study demonstrates the usefulness and limitations of genomic prediction models for predicting GxE in highly diverse samples and describes the extent of GxE at the limit of species distribution for perennial ryegrass. Our study points towards adaptive variation which may enhance persistence of perennial ryegrass populations in Nordic and Baltic growing conditions.

Lolium↗

PubMed2026

Genetic architecture and evolution of stripe rust resistance uncovered using diverse panels of wheat lines and North American Puccinia striiformis f. sp. tritici isolates.

Screening global wheat germplasm with a diverse collection of pathogen races expands the catalog of novel Yr loci and identifies new sources of broad-spectrum resistance against evolving Pst populations. Newly emerging highly virulent races of Puccinia striiformis f. sp. tritici (Pst) often defeat deployed resistance genes (Yr), highlighting the need for novel sources of durable resistance. A global diversity panel of 377 spring wheat (Triticum aestivum L.) lines was screened for all-stage resistance (ASR) against a panel of diverse 20 Pst isolates at the seedling stage and for adult-plant-stage resistance (APR) against natural mix of field races. Genome-wide association mapping identified 77 unique Yr loci. Of these, 34 overlapped with the previously mapped 1150 Yr loci, confirming the robustness of our GWAS results, while 43 were likely novel. Comparison of the nine adult-plant-stage Yr loci mapped in our study with known APR genes identified only one overlap, with Yr29. Except for Yr29, APR genes Yr18 and Yr36 were detected at low frequencies, indicating that resistance in our panel may arise from less characterized or novel sources. Two wheat lines, lacking widely effective Yr5 and Yr15 alleles, exhibited resistance to all 20 Pst races at the seedling stage and natural field races at the adult stage, suggesting that they may carry novel, broad-spectrum ASR alleles. Wheat improvement had no effect on the frequency of ASR alleles but resulted in a threefold increase in the frequency of APR alleles, suggesting that the latter were subjected to more consistent breeding selection over time. Our findings underscore the value of combined screening of diverse germplasm with diverse pathogen races to identify novel sources of broad-spectrum resistance for breeding stripe rust resistant cultivars.

Triticum↗

PubMed2026

Preliminary mapping of wheat (Triticum aestivum L.) tolerance genes to the English grain aphid (Sitobion avenae Fabricius) by genome-wide association study.

Six Sitobion avenae-tolerant wheat accessions, mapped 110 associated SNPs and six candidate genes were identified, providing valuable genetic resources for breeding wheat with tolerance to S. avenae. Wheat tolerance to the English grain aphid (Sitobion avenae) is rarely incorporated into integrated pest management strategies for wheat fields. The scarcity of tolerant accession and insufficient mapping of tolerance-related gene are key limiting factors. To address these gaps, 640 wheat accessions were evaluated for S. avenae tolerance, combined with genome-wide association study (GWAS) and qPCR validation. Six wheat accessions with stable tolerance were identified: Lerma Rojo 64, AC Vista, Hanxuan 10, Zimai, Ningnuomai 1, Louguding. A total of 110 single nucleotide polymorphism (SNP) loci associated with tolerance to S. avenae were mapped, and six candidate genes (TraesCS2D03G0041800, TraesCS2Dnew048215, TraesCS2D03G0046300, TraesCS6B03G0655800, TraesCS2Dnew048223, TraesCS2D03G0040800) were examined for transcriptional responses following aphid infestation via qRT-PCR. These genes are involved in cellular redox homeostasis, ADP-binding-mediated defense, and photosystem II (PSII) functionality. This study provides valuable genetic resources for breeding wheat with tolerance to S. avenae and lays a foundation for subsequent functional validation of these tolerance genes and its molecular mechanism exploration.

Animals↗

PubMed2026

Esketamine multi-omic biomarker evaluation in major depressive disorder (EMBER-MDD): concept, objectives and methodologies of a non-clinical investigator-initiated study.

Treatment resistance (TR) in major depressive disorder (MDD) affects a substantial minority of patients and is hard to recognize early, delaying intensified care. The Esketamine multi-omic biomarker evaluation in MDD (EMBER-MDD) is a non-interventional, investigator-initiated, in-vitro study within the EU Psych-STRATA programme, analyzing biospecimens collected in the randomized INTENSIFY study and the mirror OBS-TR cohort after participants complete treatment. EMBER-MDD aims to discover individual-omic and integrated multi-omic (hypothesis-free) biomarkers and signatures associated with TR risk, and molecular correlates of clinical response to esketamine nasal spray versus treatment as usual (TAU). Biomaterials will derive from approximately 420 adults with MDD (estimated n = 210 esketamine; n = 210 TAU) and include whole blood, RNA-stabilized whole blood, plasma and serum, sampled at baseline and, when feasible, during and after treatment (up to ~ 5,040 aliquots stored at - 80 °C). Genomics will use baseline DNA genotyping on Illumina Infinium GSA v3.0+MD arrays; epigenomics will profile genome-wide DNA methylation across time points using MethylationEPIC v2.0; transcriptomics will employ mRNA-seq (NovaSeq X/ X Plus); and proteomics/ metabolomics will be generated using high-throughput Olink and/ or Biocrates platforms. Each layer will undergo state-of-the-art preprocessing and analyses (e.g., GWAS/ PRS, EWAS, differential expression, WGCNA, pathway and network analyses), followed by integrative strategies including QTL mapping (meQTL/ eQTL/ pQTL/ mQTL) and intermediate-fusion machine learning with nested cross-validation, explainable AI (SHAP/ LIME) and treatment-effect modelling. All outputs are research-only and will not support individual efficacy, tolerability, or clinical decision-making. The study will deliver robust biosignatures and mechanistic hypotheses to guide future validation and inform stratified, molecularly guided intervention strategies in subsequent prospective trials. Trial registration number: 2023-506617-21-00 and 2025-178-f-S.

Humans↗

PubMed2026

Transcriptome-wide association analysis of Alzheimer's disease: construction and clinical validation of transcriptomic risk scores.

Early identification of individuals at high risk for Alzheimer's disease (AD) is crucial for disease prevention and intervention. This study aims to develop AD-specific transcriptomic risk scores (TRSs) through multi-tissue transcriptome-wide association study (TWAS) and to evaluate its clinical utility in AD diagnosis and risk prediction. Using GWAS summary statistics combined with expression quantitative trait loci (eQTL) data from 14 tissues, a multi-tissue TWAS approach was applied to identify AD-associated genes. Peripheral blood RNA expression data from the ADNI and GEO databases were used to construct the AD-specific TRSs. The associations of TRSs with AD pathological features and cognitive function were assessed in two independent cohorts. Furthermore, the diagnostic performance, differential diagnostic capability, and risk prediction efficiency of TRSs were evaluated. The TWAS identified 131 genes significantly associated with AD. The TRSs were significantly elevated in patients with AD and mild cognitive impairment (MCI) compared to cognitively normal (CN) individuals, and showed significant correlations with AD pathological markers and cognitive performance. When combined with APOE4 status, the TRSs demonstrated robust diagnostic ability for AD and MCI. When combined with age, the TRSs showed good diagnostic performance in distinguishing AD from frontotemporal dementia (FTD) (AUC = 0.86). Additionally, the TRSs effectively predicted the risk of progression to AD in non-AD individuals (HR = 1.74). The AD-specific TRSs developed in this study shows promising clinical utility in AD diagnosis, differential diagnosis, and risk prediction, providing valuable translational medical evidence for early screening and precision prevention of Alzheimer's disease.

Humans↗

PubMed2026

Holistic approaches for improvement of maize resistance against lodging stress: current status and future perspective.

Lodging is a major constraint in maize production, causing significant yield losses, reduced grain quality, and harvesting inefficiencies, thereby posing a serious challenge to global food security and climate-resilient agriculture. This review synthesizes current knowledge on the genetic, physiological, and agronomic determinants of maize lodging resistance and evaluates holistic strategies for improving tolerance to lodging stress. Recent advances in quantitative trait locus (QTL) mapping, genome-wide association studies (GWAS), functional gene characterization, genome editing, high-throughput phenotyping, and precision agronomy have provided powerful tools to enhance stalk biomechanics, root anchorage, and adaptive plant architecture. Integrating genomic discovery with advanced phenomics and optimized agronomic management offers a scalable framework for accelerating the development of high-yielding, lodging-resilient maize cultivars. However, critical gaps remain in understanding the genetic coordination between stalk strength and root system architecture, integrating multi-omics approaches to unravel regulatory networks, validating genome-editing interventions across diverse agro-ecologies, and developing environment-responsive predictive breeding models and cost-effective phenotyping tools, particularly for stress-prone regions. Addressing these challenges through coordinated multi-environment trials and integrative molecular-agronomic strategies will facilitate the translation of genomic discoveries into climate-resilient, high-performing maize cultivars. By consolidating molecular insights with applied breeding and management practices, this review provides a comprehensive framework that guides researchers in designing genome-informed and field-validated approaches to improve maize resistance to lodging stress and support sustainable crop production systems.

Zea mays↗

PubMed2026

Shared genetic architecture and cellular convergence between female reproductive disorders and pulmonary function: a genome-wide cross-trait analysis.

Female reproductive disorders (FRDs), including polycystic ovary syndrome, endometriosis, uterine leiomyomata, and infertility, have been epidemiologically associated with impaired pulmonary function. However, it remains unclear whether this cross-organ link reflects shared genetic etiology and, if so, which cellular mechanisms mediate it. We performed a systematic genome-wide cross-trait analysis of three FRDs and lung function traits (FEV₁, FVC, FEV₁/FVC) using GWAS summary statistics from individuals of European ancestry, integrating genetic correlation, bidirectional causal inference, pleiotropy mapping, and single-cell enrichment analyses. We identified significant negative genetic correlations between FRDs and lung volume traits, most prominently for FVC (rg range: - 0.077 to - 0.178). Bidirectional causal analyses indicated that FRDs have a detrimental effect on lung volume, with higher FRD genetic liability associated with reduced lung volume. Cross-trait meta-analysis identified 17 pleiotropic variants across 11 loci, with the 19q13.2 (LTBP4) and 12q13.13 (HOXC6/HOXC9) loci showing strong evidence of shared causal variants. Critically, single-cell analyses revealed that shared genetic risk converged on mesenchymal lineages across organs, specifically alveolar adventitial fibroblasts in the lung and stromal/smooth muscle cells in the endometrium. Transcriptome-wide analyses further nominated the estrogen-responsive gene RERG as a convergent gene linking these conditions with lung function. Our study revealed a shared genetic architecture between female reproductive disorders and lung function traits, providing a basis for further mechanistic investigations and potential clinical evaluation. Furthermore, our findings suggest that shared fibroproliferative and hormone-responsive pathways may offer insights into the biological mechanisms underlying these conditions.

Female↗

PubMed2026

Association Between Ticagrelor and Glucose Homeostasis Regulation: Insights from Genetic and Transcriptomic Analyses.

Emerging evidence has demonstrated the additional therapeutic benefits of ticagrelor in acute coronary syndrome (ACS) patients with diabetes. However, the underlying mechanisms of this association remain elusive. Mendelian randomization (MR) analysis using genome-wide association study (GWAS) data on ticagrelor, plasma proteomics and type 2 diabetes was employed to identify causal mediator proteins. RNA sequencing (RNA-seq) of ticagrelor-treated HepG2 cells revealed the molecular pathways regulating glucose metabolism. Genetically proxied ticagrelor was significantly associated with a reduced risk of diabetes (OR = 0.859, 95% CI: 0.783-0.934, P = 7.98E-05), and 24.41% of this effect was mediated by upregulation of BDH2 protein. In vitro experiments confirmed the enhanced effect of ticagrelor on glucose consumption. Transcriptome analysis revealed that mitochondrial respiratory chain transfer and oxidative phosphorylation (OXPHOS) were significantly enriched, and genes related to ATP biosynthesis were significantly upregulated. These findings highlight the non-platelet function of ticagrelor in maintaining glucose homeostasis, providing insights into potential drug repurposing in the future.

Humans↗