Biomedical subjects

Li Liu

Publications and source records attributed to Li Liu.

At least 19 recordsLinked to original sources

PubMed2026

Adolescent depression as a systemic multimorbidity catalyst: integrated genetic and metabolic pathway analysis.

BACKGROUND: Although adolescent depression has been linked to individual chronic conditions, its broader role in shaping multimorbidity risk remains understudied. METHODS: A total of 87,562 UK Biobank participants were included, of whom 18,851 had documented adolescent depression. Cox proportional hazards models were applied to evaluate associations between adolescent depression and 24 chronic diseases, followed by stratified analyses by sex and age. Two-sample Mendelian randomization (MR) was then conducted to infer causality for diseases showing significant associations. Genomic colocalization analyses were performed using relevant GWAS data to identify shared causal variants. Mediation analyses were performed to detect possible mediating factors, including the frailty index, KDM biological age acceleration, allostatic load and 30 circulating biomarkers. RESULTS: Adolescent depression was associated with elevated risk for 12 chronic diseases, with strongest associations for hypothyroidism (HR = 1.29 [1.18-1.42]), diabetes (HR = 1.25 [1.13-1.38]) and chronic obstructive pulmonary disease (COPD) (HR = 1.74 [1.50-2.01]). Risks were notably higher among females and younger adults. MR confirmed likely causal relationships for hypothyroidism (OR = 1.45 [1.03-2.05]), diabetes (OR = 1.01 [1.01-1.02]) and COPD (OR = 1.04 [1.02-1.06]). Genomic colocalization revealed a shared genetic signal at the CDSN/PSORS1C1 locus between adolescent depression and hypothyroidism. Mediation analyses revealed disease-specific pathways: creatinine for hypothyroidism, testosterone for diabetes, KDM biological ageing for COPD and frailty index across all three conditions. CONCLUSIONS: Adolescent depression confers systemic vulnerability through genetic and metabolic mechanisms, with amplified risks in females and individuals aged ≤55 years. These findings support early, integrated interventions to mitigate long-term multimorbidity.

Humans↗

PubMed2026

Inflammatory Serum Olink Proteomics in Cancer-Related Pain Treated with Opioids: A Pilot Cross-Sectional and Longitudinal Study.

Opioid analgesia shows substantial interindividual variability in cancer patients, yet the underlying serum inflammatory alterations remain poorly characterized. This study collected plasma samples from 44 cancer pain patients before and after opioid initiation, quantifying 92 immunoinflammation proteins by Olink proteomics. Cross-sectional analysis identified nine differentially expressed proteins between responders and nonresponders. A five-protein nomogram involving TGF-α, EN-RAGE, CASP-8, ST1A1, and IL-10RA demonstrated superior predictive performance for opioid efficacy (AUC 0.902) compared to traditional CRP (AUC 0.625). Longitudinal analysis of this population revealed upregulation of β-NGF, MCP-4, IL-1alpha, and IL-13, and downregulation of CD6, IL-12beta, and SCF after treatment. STRING analysis clustered these proteins into three functional groups: efficacy-related (NGF), bowel-inflammation-related (IL-12/IL-13), and CD6-related. Notably, expression of IL-12β showed a significant efficacy-constipation interaction: constipation completely reversed the efficacy-IL-12 association, and higher IL-12 levels predicted favorable response only in nonconstipated patients. These findings established a pretreatment protein signature for predicting opioid efficacy and revealed systemic immune reprogramming following opioid therapy.

Humans↗

PubMed2026

Systematic Approach for Compound Angus Populations Revealing Positional Candidate Genes and Improving Prediction Accuracy in Carcass Traits.

Carcass traits, which reflect growth performance and muscle development, are economically important in beef cattle, yet their genetic determinants remain poorly characterized. Both single-population Genome-wide association studies (GWAS) methods, such as BLINK, and cross-population meta-analysis approaches are widely used to identify genetic variants, yet their comparative performance in genomic prediction for complex traits in structured populations remains underexplored. Few studies have directly compared these methods in genomic prediction. To address this gap, this study aims to (i) identify positional candidate genes associated with carcass traits and (ii) evaluate the context-dependent advantages of Covariate Adjustment (CA) and meta in genomic prediction. In this study, we analyzed carcass weight (CW), live weight (LW), and dressing percentage (DP) in 279 crossbred Angus cattle genotyped with the PHR0105_Bt140K_v1.0 SNP chip. GWAS was performed on the full population using BLINK, and results from three subpopulations were combined via meta-analysis, with significance thresholds for both approaches determined by a shuffle-based method. Candidate genes located within ±10 kb of significant SNPs were associated with different carcass traits, including STRIT1, SEL1L3, NOC4L and ANK1 for DP; SNCA and DNAH5 for CW; and GYPC, GPR158, and GUCY1A1 for LW. Prediction accuracy under MAS and MABLUP showed meta slightly outperformed BLINK in MAS, while BLINK was better with covariate adjustment; after incorporating kinship in MABLUP, meta achieved higher accuracy and population partitioning was negligible. Overall, MABLUP yielded the highest accuracy (0.52-0.79) versus MAS (0.37-0.54) in all traits. These findings provide a methodological basis for selecting appropriate GWAS strategies in structured populations and highlight candidate genes.

GS↗

PubMed2026

Lineage structure and penicillin-binding protein variability in clinical Streptococcus pneumoniae isolates from Southwest China exhibiting reduced susceptibility to penicillin.

BACKGROUND: Reduced susceptibility to penicillin in Streptococcus pneumoniae is mediated primarily by alterations in penicillin-binding proteins (PBPs) and often coexists with multidrug resistance within successful lineages. The region-specific genomic characterization of clinically relevant pneumococci with reduced penicillin susceptibility in Southwest China remains limited. METHODS: We performed whole-genome sequencing of 204 clinical S. pneumoniae isolates collected from five institutions in Southwest China (2018-2022) that met our operational screening definition of reduced susceptibility to penicillin (PEN MIC ≥0.12 μg/mL). Molecular serotypes, MLST types, and Global Pneumococcal Sequence Clusters (GPSCs) were assigned; virulence and antimicrobial resistance determinants were profiled; and a core genome phylogeny was reconstructed with international contextualization through the use of PubMLST genomes meeting the same MIC criterion. Amino acid variability in PBP1a/PBP2b/PBP2x was quantified using TIGR4 numbering, and highly variable noncatalytic residues located within 15 Å of catalytic motifs were prioritized via structure-guided screening. RESULTS: The isolates showed a high burden of resistance to non-β-lactam antibiotics (erythromycin, 98.5%; tetracycline, 82.8%; trimethoprim-sulfamethoxazole, 64.7%), while fluoroquinolone susceptibility was largely preserved (≥97%), and vancomycin/linezolid resistance was not detected. Twenty-seven serotypes were identified, among which 19F (23.5%) and 19A (14.2%) were dominant, and the estimated PCV13 coverage was 69.6%. GPSC1 was the dominant lineage (36.8%), and the lineage composition among our isolates differed markedly from those in the PubMLST-USA and PubMLST-Thailand subsets. Virulence and resistance gene carriage differed markedly between GPSC1 and non-GPSC1 isolates, with enrichment of pilus operons, mef(A)/msr(D), and folA/folP in GPSC1. PBP variations were clustered in transpeptidase domains and motif-adjacent regions while essential catalytic residues were conserved; with the structure-guided filter, 12, 11, and 11 motif-proximal noncatalytic candidate sites were prioritized in PBP1a, PBP2b, and PBP2x, respectively. CONCLUSION: Clinical S. pneumoniae isolates with reduced penicillin susceptibility collected in Southwest China demonstrated resistance and accessory gene profiles that were strongly structured by a GPSC-defined lineage background. Our site-resolved, structure-guided PBP analysis provides a regional PBP variability landscape and a compact set of recurrent motif-proximal candidate substitutions to support surveillance and downstream functional validation.

Streptococcus pneumoniae↗

PubMed2026

Advancing cancer detection and treatment using longitudinal routine clinical data.

Cancer management remains fragmented across its continuum, from late-stage diagnosis and salvage therapies to non-personalized surveillance. Here, we present Oncoformer, a unified multimodal transformer model trained on the China Oncology Multimodal Prediction and Surveillance Study (COMPASS) cohort (3.67 million individuals, 17.7 million clinical visits) and validated on independent external cohorts, including the UK Biobank. Oncoformer integrates longitudinal electronic health records with chest X-ray imaging to address multiple clinical tasks: pan-cancer diagnosis (area under the receiver operating characteristic curve [AUROC] = 0.956), future cancer prediction up to 1 year before diagnosis (AUROC = 0.869), tumor stage inference (mean AUROC > 0.90), patient-specific treatment-response forecasting, and recurrence-free survival stratification across ten cancer types (all p < 0.01). Staging predictions were independently validated against postoperative pathological endpoints and shown to converge on core cancer genomic pathways. By translating routine clinical data into a dynamic view of cancer evolution, Oncoformer provides a framework for risk-informed cancer prediction and treatment stratification using routine clinical data.

Humans↗

PubMed2026

Multimodal features and prognostic risk assessment in locally advanced gastric cancer patients following neoadjuvant therapy based on machine learning algorithms: a multicenter study.

BACKGROUND: Neoadjuvant therapy (NAT) is recommended for locally advanced gastric cancer (LAGC), but some patients respond poorly. We aimed to construct a multimodal model integrating CT images, transcriptomic sequencing, and clinicopathological data to assess prognosis in LAGC patients receiving NAT. MATERIALS AND METHODS: This multicenter study included 505 LAGC patients who underwent NAT. Radiomic features were extracted from preoperative CT images of 505 patients. RNA-seq was performed on 277 post-NAT specimens, with additional data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases (n = 804). Patients were divided into training (168 cases), internal validation (72 cases), and external validation cohorts. Machine learning algorithms identified key radiomic, molecular, and clinical features associated with NAT response, which were then integrated into a multimodal model to predict overall survival (OS) and disease-free survival (DFS). RESULTS: Six radiomic and three molecular features significantly associated with NAT response were selected. Radiomic risk (hazard ratio [HR]: 4.0, P < 0.001) and molecular risk (HR: 7.1, P < 0.001) were independent prognostic factors. By integrating radiomic risk, molecular risk, and clinical characteristics, a multimodal model (MuMo) was constructed.The C-index results (OS, C-index = 0.855; DFS, C-index = 0.786) demonstrated that MuMo outperformed the single-modality models and ypTNM staging.Mechanistic analysis suggested that the efficacy of neoadjuvant therapy was significantly enriched in immune-inflammatory pathways. CONCLUSIONS: MuMo can effectively predict postoperative survival risk in LAGC patients receiving NAT, serving as a powerful tool for optimizing prognostic assessment.

Humans↗

PubMed2026

Systematic characterization of neurotransmitter receptor dysregulation identifies a neural-related prognostic signature associated with biochemical recurrence in prostate cancer.

BACKGROUND: The nervous system is increasingly recognized to play a critical role in tumor initiation and progression. Central to this complex relationship are the interactions between neurotransmitters secreted by neurons and their receptors (neurotransmitter receptors, NTRs) expressed on cancer cells, which activate multiple intracellular signaling pathways. However, the spectrum of NTR dysregulation and its association with biochemical recurrence (BCR) in prostate cancer (PCa) has not been explored. Therefore, the aim of this study was to fill this gap. METHODS: We systematically characterized the expression profiles of 130 NTR genes by integrating bulk and single-cell transcriptomic data. Consistently dysregulated NTR (cdNTR) genes were identified and used to construct a PCa signature (PCaSig) using elastic-net regression. The robustness of PCaSig was evaluated across three independent cohorts. In addition, the associations of PCaSig with clinicopathological characteristics, genomic alterations, tumor immune-related characteristics, and biological pathways were comprehensively investigated. RESULTS: Thirteen cdNTR genes with strong cell-type specificity, particularly in luminal epithelial cells, were identified. PCaSig robustly stratified patients into distinct BCR risk groups across multiple independent cohorts and remained an independent predictor after adjustment for clinicopathological factors. High PCaSig scores were associated with aggressive clinicopathological features, elevated tumor mutation burden (TMB), suppression of neurotransmitter-related signaling, and activation of cell-cycle and immune-related pathways. Notably, PCaSig refined prognostic stratification regardless of TMB status and was associated with distinct immune-related characteristics, including immune checkpoint expression and immune cell infiltration. Incorporation of PCaSig into a clinical nomogram significantly improved prognostic accuracy and clinical net benefit. CONCLUSIONS: These findings establish NTR dysregulation as a previously underappreciated dimension of PCa and support PCaSig as a clinically relevant tool for personalized management.

Neurotransmitter receptor (NTR)↗

PubMed2026

Characterization and genomic analysis of Bacillus halotolerans G3-2: a potential biocontrol agent against apple Alternaria leaf blotch disease.

BACKGROUND: Apple Alternaria leaf blotch (ALB) is a devastating disease threatening the apple industry worldwide. Biocontrol offers an effective and environmentally friendly alternative for disease management. RESULTS: Bacillus strain G3-2 exhibits strong antagonistic activity against Alternaria alternata (a major causal pathogen of ALB). In dual-culture assays, G3-2 inhibited A. alternata by 88.39%; in detached-leaf inoculation assays, it reduced the lesion area by >88%. 16S rRNA sequencing and phylogenetic analysis identified this strain as Bacillus halotolerans. Oxford Nanopore Technology (ONT) sequencing generated a 4.18-Mb complete genome (43.8% G + C) containing 4149 protein-coding genes, 30 rRNAs and 86 tRNAs. CAZy annotation identified 182 genes encoding carbohydrate-active enzymes (CAZymes), including glycoside hydrolases, glycosyltransferase, and carbohydrate esterases, suggesting potential for glycosylated secondary metabolite production. AntiSMASH analysis detected nine biosynthetic gene clusters, including those for surfactin, fengycin, bacillaene and laterocidine. Plate assays confirmed that G3-2 has the ability to produce protease, cellulase and siderophore. Moreover, it exhibits ~70% inhibition against several other phytopathogenic fungi. CONCLUSIONS: These findings demonstrate that G3-2 suppresses A. alternata through antibiosis (lipopeptides and polyketides), nutrient competition (siderophores) and cell-wall degradation (proteases and cellulases). Moreover, our study revealed that it has great potential to be used as a broad-spectrum, environmentally friendly biocontrol agent. © 2026 Society of Chemical Industry.

Alternaria↗

PubMed2026

Characterization and analysis of the full-length transcriptome of Frankliniella occidentalis (Thysanoptera: Thripidae).

BACKGROUND: Frankliniella occidentalis, an insect belonging to the order Thysanoptera, causes severe damage to agricultural and horticultural crops, resulting in significant economic losses worldwide. The development of molecular and sequencing technologies has helped elucidate the molecular mechanisms regulating its growth and development as well as its damaging activity. However, much remains to be explored. To further investigate the molecular complexity of this species, we sequenced the full-length transcriptome of mixed samples obtained from specimens at all developmental stages. RESULTS: Of all transcripts, 89.04% matched with the reference genome; additionally, 29,750 alternative splicing events, 2,342 genes with poly(A) sites, and 153 candidate fusion transcript events were identified, and 4,235 long noncoding RNAs were discovered. CONCLUSIONS: This is the first full-length transcriptome of F. occidentalis reported to date. This study greatly contributes to the understanding of the molecular complexity and diversity of this insect, providing a basis to develop specific molecular targets as well as resources for gene function studies in other insects.

Animals↗

PubMed2026

Quizartinib for patients with newly diagnosed FLT3-ITD-positive AML who received maintenance therapy in QuANTUM-First.

QuANTUM-First demonstrated improved overall survival (OS) in patients with newly diagnosed acute myeloid leukemia with FMS-like receptor tyrosine kinase 3-internal tandem duplication (FLT3-ITD) treated with quizartinib + standard chemotherapy. Herein, we evaluated the impact of postconsolidation/posttransplant single-agent maintenance therapy on clinical outcomes in patients receiving maintenance, focusing on measurable residual disease (MRD) status at maintenance onset. OS, event-free survival, and relapse-free survival were prespecified exploratory analyses. Cumulative incidence of relapse, analyses by allogeneic hematopoietic cell transplant (allo-HCT), and analyses by MRD status were post hoc and not powered for statistical significance. Samples for FLT3-ITD MRD analysis were collected from patients with composite complete remission ≤30 days before receiving maintenance and assessed using an ultrasensitive amplicon-based assay. More patients who had received an allo-HCT and quizartinib treatment received maintenance (71%) vs placebo (55%); OS benefit was not demonstrated among these patients. In patients who did not undergo allo-HCT, quizartinib maintenance was associated with a significant OS benefit (hazard ratio [HR], 0.401; 95% confidence interval [CI], 0.192-0.838), including a benefit in patients who were MRD negative at the start of maintenance (OS HR, 0.194; 95% CI, 0.056-0.676). Patients who were MRD negative at the completion of consolidation achieved 89.1% (95% CI, 70.0-96.4) survival at 3 years with quizartinib maintenance in the absence of allo-HCT. These data suggest that for patients who achieve FLT3-ITD MRD negativity after induction and consolidation with quizartinib, maintenance with quizartinib provides a significant survival benefit and, in some patients, may eliminate the need for allo-HCT. This trial was registered at www.clinicaltrials.gov as NCT02668653.

Humans↗

PubMed2026

Genetic heterogeneity affects the risk of incident depression, comorbidity, and response to environment: A prospective trajectory study.

BACKGROUND: Depression exhibits significant heterogeneity in its genetic underpinnings. The role of genetic components in the development of depression and its comorbidities remains insufficiently explored. METHODS: First, depression risk loci from a large-scale genome-wide meta-analysis were annotated to Gene Ontology (GO) terms by functional enrichment. GO-based polygenic risk scores (GO-PRS) were then calculated for individuals in the UK Biobank. Principal component analysis (PCA) was applied for dimensionality reduction, followed by cluster analysis to identify genetic subtypes of depression. Multistate models were applied to assess the impact of genetic patterns on the trajectory from healthy status to incident depression, and depression to 26 subsequent diseases, as well as the associations between environmental factors and disease trajectories across genetic subtypes. RESULTS: Participants were categorized into three genetic subtypes: immune-dominant, neuro-dominant, and comprehensive-risk. Significant differences in risk of depression and subsequent diseases, and susceptibility to environmental factors were observed across subtypes. Comprehensive-risk subtype showed higher risks of depression compared to immune-dominant (HR: 1.10, 95% CI: 1.05-1.15) and neuro-dominant subtype (HR: 1.12, 95% CI: 1.08-1.16). Comprehensive-risk subtype exhibited higher risks of transition from depression to subsequent diseases, such as anemia compared to immune-dominant subtype, and diseases of the digestive system compared to neuro-dominant subtype. Environmental factors were more strongly associated with the transition from depression to subsequent diseases in immune-dominant and comprehensive-risk subtypes, including cardiovascular, respiratory, and metabolic diseases. CONCLUSIONS: Our findings highlight the genetic heterogeneity of depression and comorbidities, and shed light on how genetic components modulate responses to environmental factors.

Humans↗

PubMed2026

Essence: A benchmarking-validated transformer framework for early diagnosis of Parkinson's disease using cerebrospinal fluid protein biomarkers.

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by motor and non-motor symptoms. The lack of objective molecular biomarkers limits early diagnosis and personalized treatment. Here, we propose Essence, a benchmarking-validated framework integrating cerebrospinal fluid (CSF) proteomics with traditional and deep learning models to identify robust protein signatures for PD. Using data from two independent cohorts, 1266 high-confidence proteins are quantified, among which 178 exhibit differential abundance between PD and healthy controls (HC). Through systematic benchmarking of ten machine learning algorithms and four neural architectures, the Transformer model consistently outperforms alternatives across multiple feature selection strategies, achieving an area under the receiver operating characteristic curve (AUC) of 1.0000 with only 35 features. Functional analyses of the top-ranked 35 proteins reveal enrichment in neuroinflammatory, synaptic, and oxidative stress-related pathways. Importantly, spatial transcriptomic profiling based on the Allen Brain Atlas shows region-specific expression of these biomarkers in PD-relevant brain structures, including the striatum, subthalamic nucleus, hippocampus, and white matter tracts. This anatomical alignment supports the functional relevance of the identified markers and highlights their potential utility in early-stage diagnosis and mechanistic understanding of PD.

Benchmarking↗

PubMed2026

The causal effect of family history of cardiovascular disease on erectile dysfunction: a randomized clinical study and Mendelian randomization study.

Erectile dysfunction (ED) is increasingly recognized as an early clinical marker of cardiovascular disease (CVD); however, the causal role of familial predisposition to CVD in ED development remains insufficiently defined. This study investigated whether genetic susceptibility associated with a parental history of CVD exerts a causal influence on ED risk, integrating clinical data with Mendelian randomization (MR) analysis. A cohort of 288 men who attended the Department of Andrology of Xiangya Hospital (Changsha, China) between June 2017 and June 2023 were recruited, comprising 223 patients with clinically confirmed ED and 65 controls. Detailed demographic, cardiovascular, and ED severity data were collected. Genetic variants associated with ED and parental CVD history were obtained from genome-wide association study (GWAS) summary statistics, and two-sample MR analyses were conducted to evaluate causal effects. Clinically, men with ED were significantly older, exhibited higher body mass index (BMI), and demonstrated lower testosterone levels compared with controls. A trend toward an association between family history of CVD and ED was observed. MR analyses provided robust evidence of causality, with paternal CVD history increasing ED risk and maternal CVD history exerting an even stronger effect. Sensitivity analyses confirmed the stability of these findings without evidence of pleiotropic bias. Collectively, these results indicate that familial genetic susceptibility to CVD independently contributes to the risk of ED. These findings underscore the clinical importance of incorporating family history into ED risk stratification and highlight the need for early screening and preventive strategies in men with a family history of CVD. Proactive management of this high-risk population may mitigate the future burden of ED and its cardiovascular sequelae.

Humans↗

PubMed2026

Competing subclones and fitness diversity shape tumor evolution across cancer types.

MOTIVATION: Intratumor heterogeneity arises from ongoing somatic evolution and complicates cancer diagnosis, prognosis, and treatment. Reconstructing evolutionary dynamics typically requires spatiotemporal samples, which are often unavailable in clinical settings. Computational approaches that can infer tumor evolutionary history from single-timepoint bulk sequencing data remain limited. RESULTS: We present estimating evolutionary events through single-timepoint sequencing (TEATIME), a novel computational framework that models tumors as mixtures of two competing cell populations: an ancestral clone with baseline fitness and a derived subclone with elevated fitness. Using cross-sectional bulk sequencing data, TEATIME estimates mutation rates, timing of subclone emergence, relative fitness, and number of generations of growth. To quantify intratumor fitness asymmetries, we introduce a novel metric-fitness diversity-which captures the imbalance between competing cell populations and serves as a measure of functional intratumor heterogeneity. Applying TEATIME to 33 tumor types from The Cancer Genome Atlas, we revealed divergent as well as convergent evolutionary patterns. Notably, we found that immune-hot microenvironments constraint subclonal expansion and limit fitness diversity. Moreover, we detected temporal dependencies in mutation acquisition, where early driver mutations in ancestral clones epistatically shape the fitness landscape, predisposing specific subclones to selective advantages. These findings underscore the importance of intratumor competition and tumor-microenvironment interactions in shaping evolutionary trajectories, driving intratumor heterogeneity. Lastly, we demonstrate that TEATIME-derived evolutionary parameters and fitness diversity offer novel prognostic insights across multiple cancer types. AVAILABILITY AND IMPLEMENTATION: R implementation of TEATIME is available on GitHub (https://github.com/liliulab/TEATIME) and Zenodo (https://zenodo.org/records/17422174).

Neoplasms↗

PubMed2026

TIGAR deficiency enhances cardiac resilience through epigenetic programming of Parkin expression.

Mitochondrial dysfunction devastates the heart in major cardiovascular diseases, yet the mechanisms governing mitochondrial quality control remain elusive. We discovered that TIGAR (TP53-induced glycolysis and apoptosis regulator) deficiency established profound cardiac protection through developmental epigenetic programming of Parkin expression. Using mice with whole-body and cardiomyocyte-specific TIGAR knockout, we demonstrated remarkable cardioprotection following myocardial infarction with maintained ejection fraction, and complete resistance to diet-induced cardiac hypertrophy despite comparable weight gain. TIGAR deficiency triggered dramatic increases in Parkin expression across all somatic tissues except testes, where Parkin levels remained extraordinarily high (100-fold greater than cardiac levels) regardless of TIGAR status, revealing tissue-specific regulatory mechanisms. This protection was entirely Parkin dependent, as double-knockout mice lost all cardioprotective benefits. Crucially, adult TIGAR manipulation failed to alter Parkin levels, demonstrating that this pathway operated exclusively during critical developmental windows to program lifelong cardiac resilience. Whole-genome bisulfite sequencing identified reduced DNA methylation in Prkn intron 10 as the key regulatory mechanism, with CRISPR deletion dramatically increasing Parkin expression in multiple cell lines. Our findings reveal how early cardiac metabolism programs lifelong cardiac function through epigenetic mechanisms, and identify developmental metabolic programming as a potential therapeutic target for preventing both ischemic heart disease and metabolic cardiomyopathy.

Animals↗

PubMed2026

Dual Transcranial Direct Current Stimulation Modulates Hierarchical Functional Network Organization in Post-Stroke Cognitive Impairment: A Randomized Controlled Trial.

OBJECTIVE: To evaluate the clinical efficacy of dual transcranial direct current stimulation (tDCS) in patients with post-stroke cognitive impairment (PSCI) and to explore the effects on the hierarchical organization of functional brain networks, ranging from regional synchronization to inter-regional connectivity and global network topology. METHODS: In this randomized, double-blind, sham-controlled trial, 74 PSCI patients received conventional therapy alongside either active dual-tDCS (n = 38) or sham stimulation (n = 36). Active tDCS targeted the dorsolateral prefrontal cortex (DLPFC) via anodal-left/cathodal-right nodes (2.0 mA, 20 min/day, 20 sessions). The primary outcome was the Montreal Cognitive Assessment (MoCA). Secondary outcomes included the Mini-Mental Status Examination (MMSE), Stroop Test (ST), Trail Making Test (TMT), Wechsler Memory Scale (WMS), and Barthel Index (BI). A subgroup of 36 participants (18 per group) underwent resting-state functional magnetic resonance imaging (rs-fMRI) to analyze regional homogeneity (ReHo), functional connectivity (FC), and network topology. Partial correlations assessed the association between neuroimaging alterations and clinical improvements. RESULTS: The tDCS group showed significantly greater improvements in MoCA scores (tDCS: 5.74 ± 2.76 vs. sham: 2.69 ± 2.69; t = 4.799, p < 0.001) as well as in attention and memory domains compared to the sham group. The rs-fMRI changes included increased ReHo in the right middle temporal gyrus (MTG) and the left inferior frontal gyrus (IFG), and reduced FC between the right MTG-left superior frontal gyrus and left IFG-cerebellum (p < 0.05, FWE-corrected). Additionally, small-worldness and global efficiency increased (p < 0.05) with these alterations correlating with clinical recovery. Adverse events were rare and self-limiting. CONCLUSION: Dual-tDCS over bilateral DLPFC safely improves cognitive recovery in PSCI. These clinical gains are associated with rs-fMRI alterations, specifically in regional synchronization, inter-regional connectivity, and global topology, which suggest a potential biomarker for monitoring tDCS efficacy, offering a rationale for precision neuromodulation in stroke rehabilitation.

Humans↗

PubMed2025

Amylin inhibits gastric cancer progression by targeting CCN1 and affecting the PI3K/AKT signalling pathway.

METHODS: This study used a combination of in vitro and in vivo experiments to investigate the role of amylin in the progression of GC. The expression of amylin in GC and its clinical correlation were evaluated using 38 pairs of GC and healthy human clinical samples. In vitro studies, human GC cell lines were treated with amylin to evaluate the effects of amylin on the proliferation, apoptosis and migration of GC cells. In in vivo studies, xenograft mouse models were established by subcutaneous injection of GC cells into nude mice, followed by treatment with amylin to assess tumor growth. Finally, Next-Generation Sequencing Technology (RNA-seq) was used to explore the potential mechanism of amylin on GC. RESULTS: We found that amylin expression was reduced in GC compared to adjacent normal gastric tissues and that elevated amylin expression was negatively correlated with adverse pathological factors (p < 0.05). Additionally, we demonstrated that amylin impeded the growth, invasion, migration, and colony formation of GC cells and suppressed the epithelial-to-mesenchymal transformation of these cells (p < 0.05). Tumour xenograft model experiments confirmed the tumour-suppressive effect of amylin in subcutaneous tumours in nude mice (p < 0.05). Transcriptome sequencing (RNA-seq) revealed that amylin significantly down-regulated CCN1 gene expression in GC cells (p < 0.001). Further intervention targeting CCN1 verified its significance as a target of amylin's anti-carcinogenic function in GC. Additionally, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that amylin exerted its oncogenic effects by inhibiting the PI3K/Akt signalling pathway (p < 0.05). CONCLUSIONS: Our findings demonstrate that amylin plays a crucial role in suppressing gastric cancer progression by targeting CCN1 and inhibiting the PI3K/Akt signalling pathway. These results suggest that amylin could serve as a potential therapeutic agent for GC treatment.

Humans↗

PubMed2025

Polygenic enrichment analysis in multi-omics levels identifies cell/tissue specific associations with schizophrenia based on single-cell RNA sequencing data.

OBJECTIVE: Understanding the specific cellular origin and tissue heterogeneity in schizophrenia is critically important for exploring the disease etiology. This study aims to investigate these aspects by performing multiple analyses based on omics data. METHOD: We performed single-cell disease relevance score (scDRS) algorithm to link brain single-cell RNA sequencing (scRNA-seq) with schizophrenia risk across multi-omics scales at single-cell resolution. This approach identified cell types with overexpression of schizophrenia-related genes implicated by multi-omics panels (ATAC-seq, RNA-seq, TWAS, and GWAS). Schizophrenia-related genes from these multi-omics panels were extracted and combined with scRNA-seq data to calculate scDRS. Subsequently, the cell-type vs. disease association and tissue heterogeneity were assessed using scDRS for each omics panel. RESULTS: We identified two novel cell subpopulations in the brain that differentially express SCUBE3 (59 cells, 7.0 %) and FN1 (21 cells, 2.5 %). At the individual cell level, schizophrenia-associated cell subpopulations included microglial cell associated with ATAC-seq panel (Passociation = 0.002, Pheterogeneity = 0.009) and deep layer neuron suggestively associated with GWAS panel (Passociation = 0.033, Pheterogeneity = 0.017). At the brain tissue level, microglial cell was significantly associated with cortical plate in ATAC-seq panel (Passociation = 0.002, Pheterogeneity = 0.011). Gene level analysis identified several genes associated with schizophrenia across multi-omics panels. CONCLUSIONS: Our study outlines the signature of cell subpopulations, brain regions, and disease risk genes in schizophrenia at single-cell resolution across multi-omics scales. These findings provide a reference for future precision medicine approaches targeting specific cell types and brain regions in schizophrenia.

Schizophrenia↗