Biomedical subjects

Yang Chen

Publications and source records attributed to Yang Chen.

9 recordsLinked to original sources

PubMed2026

Dual Roles of RAD23b and RAD4 on the Desiccation Tolerance of Germinated Seeds.

Desiccation tolerance (DT) is a survival trait enabling orthodox seeds to withstand extremely low water content. While some protective factors are characterised, it remains mechanistically obscure. Here, based on PEG-induced DT re-establishment in germinated Brassica napus L. seeds, we investigated the dual functions of nucleotide excision repair (NER) components RAD23b and RAD4 in DNA repair and transcriptional regulation of root development. PEG pre-treatment alleviated dehydration-induced DNA damage and activated NER genes, suggesting the involvement of NER in seed DT. Unexpectedly, Arabidopsis atrad23b mutant and BnRAD23b/BnRAD4 over-expressing seeds all exhibited significantly decreased DT after dry back, which evoked a hypothesis that BnRAD23b-BnRAD4 functions beyond NER. Normally, BnRAD4 interacted with BnRAD23b and repressed the expression of root development genes NAC103, EMB1444, RRA1 by directly binding to STRE elements within their promoters. Dehydration stress alleviated this repression, drove transcriptional reprogramming and might redirect the complex to execute DNA repair. Genetic analyses revealed that germinated seeds of atnac103, atemb1444, and atrra1 single mutants all exhibited reduced DT, and double mutants under atrad23b background almost abolished DT. This study suggests that RAD23b and RAD4 may regulate DT re-establishment of germinated seeds through balancing genome integrity and radicle development, with implications for DT study broadly.

Brassica napus L.↗

PubMed2026

Distinct molecular profiles of indeterminate and malignant thyroid nodules in patients under 21 years of age.

Although uncommon, thyroid nodules (TN) in pediatric and young adult patients carry higher malignancy risk and often present with a high burden of metastatic disease than adults. The molecular features underlying this distinct clinical behavior remain unclear. We analyzed Afirma Genomic Sequencing Classifier (GSC) data from 283,621 TN, comparing patients <21 and ≥21 years. Cytology (Bethesda), GSC benign (B) vs suspicious (S) calls, and Afirma Xpression Atlas (XA) variant/fusion profiles were evaluated in GSC-S and Bethesda V/VI samples. Genome-wide expression was used to derive pathway signatures and thyroid cancer-related scores: BRAF-RAS score (BRS), ERK, follicular and epithelial-to-mesenchymal transition (FMT, EMT) and thyroid differentiation scores (TDS). Among 2,397 patients <21 (median age 18.9; 81.4% female) and 281,224 adults ≥21 (median age 59.8; 77.1% female), <21 samples showed more Bethesda V/VI cytology (14.5% vs 5.0%; p<0.0001) and a lower GSC-B rate (43.5% vs 68.8%; p<0.0001). In GSC-S samples, total variant detection was higher in <21 (45.3% vs 37.4%), with enriched BRAF p.V600E, TSHR, and DICER1 variants, while HRAS variants were more common in adults (all p<0.01). Gene fusions involving RET, NTRK3 and ALK were enriched in <21 (14.5% vs 5.5%; p<0.0001). TERT promoter mutations were absent in <21 yrs GSC-S and Bethesda V/VI samples (vs 4.2% and 9.3% in adults). GSC-S <21 showed cell-cycle pathway enrichment. RET/NTRK/ALK-positive <21 demonstrated enrichment of angiogenesis and EMT pathways, higher ERK/EMT/FMT scores, and lower BRS/TDS scores vs genotyped-matched adults. These molecular differences provide mechanistic insight into the more invasive phenotype in pediatric and young adult TN.

BRAF↗

PubMed2026

Enhancing pan-cancer spatial transcriptomics at single-cell resolution with stPainter.

Subcellular spatial transcriptomics can resolve tissue architecture at cellular scale, but sparse gene panels and limited detection sensitivity constrain downstream analysis. Existing enhancement methods often require tissue-matched single-cell RNA sequencing (scRNA-seq) references and dataset-specific retraining. Here we show that stPainter, a conditional generative model pretrained on a pan-cancer scRNA-seq atlas, can enhance spatial transcriptomics data without matched references or retraining. Using a latent diffusion architecture guided by Stochastic Differential Equations (SDE), stPainter reconstructs expanded expression profiles from sparse measurements and produces latent representations for clustering and cell-state analysis. When we apply stPainter upon 6 spatial transcriptomics datasets of different cancer types, we demonstrate that our model empowers downstream biological analyses, including fine-grained subpopulation clustering and pathway enrichment. Comparison with spatially resolved proteomics (CODEX) provided independent support for regional agreement between imputed cellular compositions and protein-level tissue organization. These results establish stPainter as a scalable approach for analyzing tumor microenvironments without auxiliary sequencing data.

Spatial Transcriptomics↗

PubMed2026

Proteomic analysis identifies pathways related to immune dysregulation in patients with hematologic malignancies after COVID-19 infection.

Patients with hematologic malignancies (HMs) are particularly vulnerable to coronavirus disease 2019 (COVID-19) because of underlying immune dysfunction and treatment-related immunosuppression. However, proteomic features associated with different clinical trajectories in this population remain insufficiently characterized. We performed serum proteomic analysis in 40 HM patients with COVID-19 and 15 healthy controls. Compared with controls, HM patients showed impaired immune-related responses during the acute phase of COVID-19. Acute-phase proteomic patterns differed across outcome groups; however, because outcome groups were closely intertwined with initial COVID-19 severity, ICU admission, and systemic illness, and because multivariable adjustment was not performed due to the limited sample size, these patterns should be interpreted as severity- and outcome-associated profiles rather than independent trajectory-specific markers. Fatal cases showed evidence of dysregulated immune activation, whereas patients later classified as having long COVID exhibited broader suppression of immune-related pathways. In addition to immune alterations, pathways related to platelet activation and cardiac-related dysfunction were associated with adverse clinical trajectories. Enzyme-linked immunosorbent assay validation supported the association of selected proteins with outcome groups during acute infection. These findings provide a proteomic overview of COVID-19 in HM patients and offer a basis for future mechanistic studies and larger external validation cohorts.IMPORTANCEPatients with hematologic malignancies are highly vulnerable to severe coronavirus disease 2019 (COVID-19), acute death, and long COVID due to preexisting immune dysfunction. However, the proteomic signatures linked to adverse clinical trajectories remain poorly understood. Our serum proteomic study identifies distinct acute-phase immune profiles associated with different outcomes: broad immune suppression characterizes long COVID, while dysregulated immune activation is associated with fatal cases. Platelet activation and cardiac-related pathways are also linked to poor outcomes. These findings provide key molecular insights for this high-risk population, supporting future biomarker development, risk stratification, and targeted clinical management.CLINICAL TRIALSThis study is registered with ClinicalTrials.gov as NCT05683353.

Humans↗

PubMed2026

Construction of precision clinical-proteomics risk model based on machine learning for predicting heart failure in type II diabetes mellitus.

BACKGROUND AND AIMS: Heart failure (HF) is a severe complication in type 2 diabetes mellitus (T2DM), but current risk stratification scores have limited predictive accuracy. We aimed to develop novel prediction tools integrating clinical variables with proteomics to improve risk stratification of hospitalization for HF in T2DM. METHODS AND RESULTS: In this study, we included 2111 UK Biobank participants with T2DM but no prior HF, and profiled 2920 proteins to predict 10-year incident HF hospitalization. Participants were randomly divided into training (70%), tuning (10%), and validation (20%) sets.Three prediction models were developed: a Clinical model based on demographic characteristics, comorbidities, medication use, and laboratory indices; a Protein model based on 40 proteins selected by the Light Gradient Boosting Machine (LGBM); and the Clinical OMics and Protein ASSessment for Heart Failure (COMPASS-HF) model, which integrated both clinical variables and the LGBM-selected proteins. Models were evaluated for area under the curve (AUC), sensitivity, and specificity. During follow-up, 168 participants (7.96%) developed incident HF. The COMPASS-HF model showed better discrimination than the Clinical model, with an AUC of 0.897 (95% CI: 0.850-0.945) versus 0.790 (95% CI: 0.723-0.856). It also demonstrated higher sensitivity (0.882; 95% CI: 0.725-0.967) and consistent performance in subgroups. COMPASS-HF effectively stratified risk of hospitalization for HF, with cumulative incidence rates of 31.9% in the high-risk group and 1.2% in the low-risk group. CONCLUSIONS: By combining clinical and proteomic variables, we developed a high-performance HF prediction model for T2DM, enabling precise risk stratification and informing early intervention strategies.

Humans↗

PubMed2026

Genetic insights into the relationship between age at menarche and mental health-related phenotypes.

BACKGROUND: Multiple observational studies have reported associations between age at menarche (AAM) and mental health problems, yet their shared genetic architecture remains poorly characterized. METHODS: We leveraged genome-wide association study summary statistics for AAM and 15 mental health-related phenotypes. We conducted a multi-method integrative analysis encompassing linkage disequilibrium score regression, pleiotropic analysis under the composite null hypothesis, functional mapping and annotation, multi-marker analysis of genomic annotation, pathway enrichment, and bidirectional two-sample Mendelian randomization (MR) to explore shared genetic architecture and potential causal relationships. RESULTS: Our study identified significant genetic correlations between AAM and eight mental health-related phenotypes (miserableness, fed-up feelings, nervous feelings, ever thought that life is not worth living, ever self-harmed, depression, ever smoker, and age started smoking in former smokers). A total of 155 pleiotropic loci, 18 colocalized loci (e.g., 6q16.3), and 203 pleiotropic genes (e.g., LIN28B) were identified. These genes are expressed in multiple regions, including the cerebral cortex and hypothalamus, and are involved in various biological processes and signaling pathways. Additionally, MR analysis revealed causal associations between AAM and 5 mental health-related phenotypes (mood swings, miserableness, fed-up feelings, and age at which smokers started smoking in former/current smokers). CONCLUSIONS: Our study revealed extensive genetic associations between AAM and mental health-related phenotypes, and further explored the potential causal relationships between them. These findings enhance our understanding of the relationship from a genetic perspective and establish a foundation for future research to explore the biological pathways and environmental interactions contributing to these associations.

Genome-Wide Association Study↗

PubMed2026

A single-nucleus and spatial transcriptomic atlas of poplar leaves reveals the regulation of leaf polarity and cuticle deposition.

Leaf adaxial-abaxial polarity is fundamental for plant morphogenesis and environmental adaptation through asymmetric cell differentiation. Emerging evidence reveals dorsoventral metabolic gradients act downstream of transcriptional networks to fine-tune cellular specialization. While conserved transcription factors (e.g., HD-ZIP III and KANADI) establish initial polarity, the molecular networks driving position-specific cellular differentiation and their integration with metabolic adaptation remain unclear. Leveraging single-nucleus and spatial transcriptomics, we resolve major cell classes (mesophyll, epidermal, and vascular-associated) and their adaxial-abaxial subtypes, revealing dorsoventral polarity in transcriptional profiles and metabolic pathways. Adaxial cells are enriched in phenylpropanoid/flavonoid biosynthesis, while abaxial cells show preferential activation of stress and hormone signaling. Notably, we identify MYC2 as a key regulator of adaxial cuticle biosynthesis, binding to promoters of lipid biosynthetic and transport genes (e.g., CER10 and LTPG1) and promoting cuticle thickening. Our study uncovers how positional identity shapes transcriptional and metabolic polarity in leaves, with MYC2 emerging as a central regulator coordinating organ-specific adaptations. These findings provide insights into the spatial regulation of plant development and stress resilience, offering potential strategies for engineering stress-tolerant woody crops.

Plant Leaves↗

PubMed2026

Could the preoperative urethral curve be used to predict immediate urinary continence following Retzius-sparing robot-assisted radical prostatectomy? A retrospective multi-center study.

PURPOSE: Immediate urinary continence (UC) recovery following Retzius-sparing robot-assisted radical prostatectomy (RS-RARP) remains highly variable, highlighting the need for reliable preoperative prediction. We aimed to develop and validate models to identify patients likely to achieve immediate UC recovery following RS-RARP. MATERIALS AND METHODS: A total of 580 prostate cancer patients who underwent RS-RARP from four medical centers were assigned to a training set (n=348), an internal validation set (n=103) and an external validation set (n=129). Independent predictors were identified through univariate analysis and LASSO regression. A nomogram was constructed using multivariate logistic regression. Its performance was evaluated with receiver operating characteristic (ROC) curve, calibration curves, and decision curve analysis. RESULTS: Immediate UC recovery was observed in 84.5% (294/348) of patients in the training cohort, 80.6% (83/103) in the internal validation cohort, and 81.4% (105/129) in the external validation cohort, respectively. Multivariate analysis identified membranous urethral length (MUL) (OR=1.23, P=0.029) and urethral curvature (OR=2.84, P<0.001) as independent predictors, while prostate volume (PV) (OR=0.84, P <0.001) as a protective factor. The nomogram integrating MUL, PV, and urethral curvature demonstrated superior predictive accuracy, with an AUC of 0.87 (95% CI, 0.83-0.91) in the training cohort. The bootstrap-corrected calibration slope was 0.96, and the Brier score was 0.08. Calibration curves and decision curve analysis confirmed the predictive accuracy and clinical utility of the nomogram. CONCLUSIONS: Our study introduces a novel quantitative method for assessing urethral curvature. The mpMRI-based model, integrating urethral curvature and prostate spatial configuration, offers enhanced predictive accuracy for postoperative immediate UC recovery.

Humans↗

PubMed2025

Design of optimized epigenetic regulators for durable gene silencing with application to PCSK9 in nonhuman primates.

Epigenetic editing is a promising strategy for modifying gene expression while avoiding the permanent alterations and potential genotoxicity of genome-editing technologies. Here we designed optimized epigenetic regulators (EpiRegs) by testing combinations of transcription activator-like effector (TALE)-based and catalytically deactivated Cas9 (dCas9)-based epigenetic modification effectors and fusion protein structures. TALE-based EpiReg (EpiReg-T) achieved a final efficiency of 98% in mice, surpassing the initial dCas9-based efficiency of 64%. We demonstrated the approach in macaques by introducing DNA methylation and histone modifications to inhibit proprotein convertase subtilisin/kexin type 9 (PCSK9) expression, thereby lowering low-density lipoprotein cholesterol levels. A single dose of EpiReg-T delivered with lipid nanoparticles achieved efficient (>90%) and long-lasting (343 days) silencing of PCSK9 in the liver. Integrative multiomic analyses revealed minimal off-target effects in EpiReg-T-treated monkeys, mice and human-derived cells. EpiReg can be redirected to other genes by reengineering the DNA-binding domain. Our findings represent a step toward the clinical application of epigenetic editing for the treatment of human diseases.

Animals↗