Biomedical subjects

Ping Li

Publications and source records attributed to Ping Li.

12 recordsLinked to original sources

PubMed2026

Evolutionary patterns and repeated adaptive strategies of deep-sea anemones.

Sea anemones occupy the full depth range of the oceans, yet their evolutionary patterns and adaptive strategies to the enigmatic deep sea have remained contentious and poorly resolved. Here, we assemble genomes (n = 13) and transcriptomes for 15 species collected between 432 and 6,000 m and integrate them with publicly available actiniarian data. We find support for a shallow-water origin of Actiniaria through a framework that emphasizes genome-scale changes associated with habitat transitions. Most strikingly, these changes include repeated dismantling of the circadian toolkit across deep-sea lineages. In addition to convergent gene losses in photo- and temperature-regulatory genes, we find that some deep-sea lineages have experienced recurrent loss or pseudogenization of key meiotic genes (e.g., Meiosin, Ythdc2, Spo11, and Mlh3), suggesting reduced meiotic capacity in some lineages. Despite this extensive genomic erosion, deep-sea anemones exhibit molecular tuning: specific amino acid substitutions improve enzyme performance under low-temperature conditions relevant to the deep sea, while selective expansions of gene families related to neural excitability, membrane systems, and other functions may help maintain physiological performance in this environment. Functional assays in yeast indicate enhanced performance of the deep-sea variants at 4°C. These results define a "loss-optimization-innovation" triad that underlies bathymetric adaptations and may apply to other deep-sea fauna worldwide.

Actiniaria↗

PubMed2026

Multi-omics evidence reveals robust airborne-human resistome connectivity driven by high-risk ARGs and mediated by Staphylococcus.

Airborne microbiomes are considered an important source of human antimicrobial resistance (AMR) exposure, yet multi-omics evidence linking airborne and human nasal resistomes remains limited. Here, we integrated metagenomic sequencing and whole-genome sequencing of antibiotic-resistant Staphylococcus isolates to investigate the connectivity between air and human nasal resistomes in dairy farm environments. Metagenomic taxonomic profiling showed that Staphylococcus was prominent in total suspended particles (TSP) and consistently detected across all samples. Among environmental reservoirs, TSP resistomes exhibited the strongest similarity to human nasal resistomes. This connectivity was supported by multiple lines of evidence, including highly similar resistome profiles, extensive homologous antibiotic resistance gene (ARG) pairs, strain-level similarity of resistant Staphylococcus isolates, and conserved mobile ARG genetic contexts. Notably, this connectivity was primarily driven by high-risk ARGs, while Staphylococcus was frequently associated with mobile ARGs and represented the only shared pathogenic genomes carrying both ARGs and virulence factor genes between airborne and nasal samples. Although lower ARG diversity, nasal resistomes exhibited higher ARG burden, risk scores, antibiotic-resistant bacterial genome abundance, and prevalence of resistant Staphylococcus. Occupational exposure further increased total and high-risk ARG burdens among farm workers. Together, these findings indicate that TSP can serve as an important route of occupational AMR exposure, with high-risk ARGs and Staphylococcus contributing to connectivity between airborne and nasal resistomes. Incorporating the host microbiome may therefore provide a more complete assessment of human-associated AMR exposure within a One Health framework.

Airborneresistome↗

PubMed2026

Phylogeographic epidemiology of Dabie bandavirus in East Asia: divergent transmission networks and genotype‑linked clinical severity.

BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS), caused by Dabie bandavirus (SFTSV), exhibits geographically decoupled incidence and fatality patterns across East Asia. We aimed to elucidate the distinct ecological drivers and phylogeographic dynamics underlying this inland-coastal epidemiological divergence. METHODS: Integrating 1820 high-quality global genomes of SFTSV with well-characterized clinical cohorts (936 patients) and nationwide surveillance data (27,457 cases) from China, we constructed a comprehensive analytical framework. Ecological modeling, Bayesian phylogeography, and genotype-phenotype association analyses were employed to trace the evolutionary trajectories and clinical implications of the virus. RESULTS: A pronounced "inland-high-incidence vs. coastal-high-fatality" pattern of SFTS was identified. The incidence of SFTS exhibited divergent sensitivities to meteorological factors; inland transmission was sensitive to thermal fluctuations, whereas coastal dynamics were constrained by a sunshine threshold (> 200 h/month). In contrast, spatial divergence in clinical severity correlated with the distribution of regional viral genetic structures. Inland regions mainly co-circulated genotypes A, C, and D, while coastal regions were dominated by genotype B. Zhejiang province was identified as a genetic hub with significantly higher recombination frequencies than inland regions (11.0% vs. 3.5%, P < 0.001). Bayesian phylogeographic inference indicated frequent lineage exchange of Zhejiang province in China with the Republic of Korea and Japan. Clinically, genotypes B and D were associated with elevated mortality in coastal and inland regions, respectively, suggesting that the severe coastal phenotype is shaped by its genotype B-dominated structure. Additionally, the RdRp-N828S mutation emerged as a robust molecular correlate of fatal outcomes, warranting further functional validation. CONCLUSIONS: Divergent meteorological factors and plausible maritime transmission networks may underlie the geographically decoupled epidemiology of SFTS. These findings highlight that risk assessment must extend beyond incidence alone and provide a phylogeographically informed framework for targeted surveillance and genotype-specific interventions in high-risk hotspots.

Humans↗

PubMed2026

Preimplantation genetic testing for concurrent Meckel Syndrome and hereditary breast cancer in a Chinese family harboring a novel NPHP3 pathogenic variant and a canonical BRCA2 frameshift variant.

Meckel syndrome (MKS) is a lethal autosomal recessive disease with high phenotypic and genetic heterogeneity. Defects in NPHP3 cause MKS type 7. Herein, we report a case of a Chinese family with a newborn male proband presenting with occipital encephalocele and polycystic kidneys. Whole-exome sequencing was performed on genomic DNA extracted from peripheral blood. Potential variants were assessed for pathogenicity. Two compound heterozygous variants of NPHP3 (c. 950T>C, p. Phe317Ser, and c.2694-2_2694-1delAG) were identified, which were inherited from both parents, with c.950T>C representing a novel variant. Two BRCA2 variants (c.5576_5579delTTAA, p. Ile1859Lysfs*3, and c.9357A>C,p. Leu 3119 Phe) were identified, which were inherited from the father. After the proband was diagnosed with MKS7, the couple chose preimplantation genetic testing for monogenic disorders (PGT-M) to simultaneously prevent the transmission of NPHP3 and BRCA2 pathogenic variants, leading to a successful pregnancy. Our study expands the NPHP3 variant spectrum and contributes to the molecular diagnosis and genetic counseling of MKS. This case indicates that PGT-M is a viable option for NPHP3-related MKS and BRCA-positive patients to avoid transmission while maintaining their families. Successful application of PGT-M provides a potential approach for treating other monogenic diseases.

Journal Article↗

PubMed2026

Natural variation in the PmbHLH162 promoter regulates anthocyanin biosynthesis and accumulation in Prunus mume.

Anthocyanin accumulation is a vital agronomic and ornamental trait, as it not only contributes to adaptation to environmental stress but also enhances ornamental value. In this study, a genome-wide association study (GWAS) was conducted using 328 accessions of mei (Prunus mume) to identify single-nucleotide polymorphisms (SNPs) associated with red pigmentation in petals, filaments, and xylem. Based on these significant SNPs, we defined 2 haplotypes (bHLH162hap1 and bHLH162hap2) and identified PmbHLH162, a bHLH transcription factor gene responsible for anthocyanin biosynthesis regulation. Transient silencing of PmbHLH162 in mei petals via Agrobacterium-mediated transformation resulted in significant color fading, whereas its overexpression dramatically elevated anthocyanin levels. Haplotype analysis showed that 2 promoter variants in bHLH162hap2 (Chr03_2669885 A/C and Chr03_2670272 A/G) alter the binding affinity of transcription factors PmWRKY18 and PmWRKY70. Stronger binding to the G/C alleles gave rise to higher PmbHLH162 expression in bHLH162hap2, thereby promoted red pigmentation in multiple tissues. By contrast, accessions carrying bHLH162hap1 displayed light/colorless phenotype without accumulation of red pigment. Furthermore, PmbHLH162 interacted respectively with PmMYC2, PmTT8, and PmEGL1 to form heterodimers, and markedly enhanced PmMYC2-mediated transcriptional activation of the anthocyanin biosynthetic structural genes PmCHS and PmANS. Geographic haplotype analysis revealed that bHLH162hap2 was predominantly enriched in high-latitude northern populations but was declining markedly at lower latitudes. Collectively, our study reveals the genetic and molecular basis underlying anthocyanin accumulation in mei and identifies a PmbHLH162-PmMYC2 regulatory module in which PmbHLH162 enhances PmMYC2-mediated activation of key anthocyanin biosynthetic genes. The additional interactions of PmbHLH162 with the MBW-associated bHLH factors PmTT8 and PmEGL1 further suggest potential crosstalk between this module and the canonical anthocyanin regulatory network.

Anthocyanins↗

PubMed2026

Stromal Hedgehog Signaling Drives Segment-Specific Malignant Transformation of Gastrointestinal Stem Cells by Producing Bone Morphogenetic Protein Antagonists.

BACKGROUND & AIMS: Hedgehog signaling plays a complex role in epithelial-stromal interactions, but its effects on gastrointestinal stem cells mediated by heterogeneous stromal cell populations remain incompletely defined. Here, we investigate how stromal Hedgehog signaling regulates gastric stem cells and tumorigenesis in a segment-specific manner. METHODS: We genetically activated Hedgehog signaling in distinct stromal cell lineages using Col1a2-, Pdgfra-, Gli1-, Acta2-, and Prrx1-CreERT mouse lines, combined with lineage tracing, RNA sequencing, chromatin immunoprecipitation-quantitative polymerase chain reaction, and pharmacologic interventions. Human gastric cancer data from The Cancer Genome Atlas were also analyzed. RESULTS: We show that genetic activation of Hedgehog signaling in stromal cells marked by Col1a2, Pdgfra, or Gli1, but not by Acta2, induces tumorigenesis in the stomach and gastroesophageal junction, but not in the small or large intestine. Hedgehog signaling increases the expression of multiple bone morphogenetic protein antagonists in gastric but not colonic stromal cells, via Gli1-mediated transcription. These bone morphogenetic protein antagonists, in turn, activate Wnt/β-catenin signaling in gastric stem cells, driving their proliferation and initiating gastric cancer expressing CD44 and Sox9, but not Lgr5. Activating bone morphogenetic protein or inhibiting Wnt signaling blocks tumor initiation. Analysis of patient data from The Cancer Genome Atlas reveals elevated Hedgehog signaling in gastric cancers, which correlates with suppressed bone morphogenetic protein signaling. CONCLUSIONS: These findings uncover a gastrointestinal segment-specific oncogenic role for Hedgehog signaling in Col1a2+Acta2- stromal cells, mediated through the bone morphogenetic protein-Wnt-β-catenin axis.

BMP Antagonists↗

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

Exploring the mechanism of Acanthopanax in treating vertigo: A network pharmacology and molecular docking study.

Acanthopanax has therapeutic efficacy against vertigo; however, the underlying mechanism remains unclear. This study aimed to elucidate the mechanism by which Acanthopanax treats vertigo through integrated network pharmacology and molecular docking techniques, and retrieved all target genes of Acanthopanax for vertigo treatment from July to October 2025. Vertigo-related target genes were subsequently identified from public databases, including GeneCards and Online Mendelian Inheritance in Man. The intersection between Acanthopanax-derived targets and vertigo-related targets was analyzed to identify candidate target genes. Using the STRING platform, we constructed protein-protein interaction networks for the identified candidate targets and mined the core functional modules within these networks. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed on candidate targets via the clusterProfiler package. A carp bile poisoning-liver injury target-pathway network was constructed via Cytoscape 3.8.2 software, network topology analysis was conducted, and the core components and targets were screened. The results found that A total of 295 candidate targets for the treatment of vertigo caused by Eleutherococcus senticosus were identified. Pathway enrichment analysis revealed that Eleutherococcus senticosus treatment for vertigo may be closely associated with pathways related to IL-17, TNF, phosphoinositide 3-kinase (PI3K)-Akt, p53, HIF-1, and Forkhead box O signaling. The core targets for the treatment of A. senticosus vertigo include TP53, AKT1, STAT3, TNF, and JUN. Network pharmacology and molecular docking studies suggest that A. senticosus may treat vertigo by regulating targets such as JUN, TNF, AKT1, STAT3, and STAT3 through pathways such as the IL-17, TNF, phosphoinositide 3-kinase-Akt, p53, HIF-1, and Forkhead box O signaling pathways. These mechanisms warrant further investigation in future o and in vitro studies.

Molecular Docking Simulation↗

PubMed2025

Genome-wide CRISPR screens identify critical targets to enhance CAR-NK cell antitumor potency.

Adoptive cell therapy using engineered natural killer (NK) cells is a promising approach for cancer treatment, with targeted gene editing offering the potential to further enhance their therapeutic efficacy. However, the spectrum of actionable genetic targets to overcome tumor and microenvironment-mediated immunosuppression remains largely unexplored. We performed multiple genome-wide CRISPR screens in primary human NK cells and identified critical checkpoints regulating resistance to immunosuppressive pressures. Ablation of MED12, ARIH2, and CCNC significantly improved NK cell antitumor activity against multiple treatment-refractory human cancers in vitro and in vivo. CRISPR editing augmented both innate and CAR-mediated NK cell function, associated with enhanced metabolic fitness, increased secretion of proinflammatory cytokines, and expansion of cytotoxic NK cell subsets. Through high-content genome-wide CRISPR screening in NK cells, this study reveals critical regulators of NK cell function and provides a valuable resource for engineering next-generation NK cell therapies with improved efficacy against cancer.

Humans↗

PubMed2025

Plasma Proteomic Profiles Predict Individual Future Osteoarthritis Risk.

OBJECTIVE: Osteoarthritis (OA) is a widespread degenerative joint disease that causes a considerable socioeconomic burden. Despite progress in genetic and environmental insights, early diagnosis is still limited by the lack of evident symptoms during the initial phases and accurate biomarkers. This study aims to identify plasma proteins associated with future risk of OA and develop a predictive model. METHODS: We conducted a large-scale proteomic analysis of 45,307 participants from the UK Biobank, excluding those with baseline OA. Plasma samples were assayed using the Olink Explore Proximity Extension Assay targeting 1,463 unique proteins. Clinical variables and OA outcomes were extracted and linked to electronic health records. A predictive model was constructed using the LightGBM machine learning method, and SHapley Additive exPlanations (SHAP) were applied to evaluate the importance of variables. RESULTS: We identified a panel of proteins significantly associated with the risk of developing OA. Notably, after adjusting for multiple confounders, collagen type IX alpha 1 chain (COL9A1) and cartilage acidic protein 1 (CRTAC1) were the most significant predictors of incident OA, with hazard ratios of 1.54 (95% confidence interval [CI] 1.48-1.61) and 1.65 (95% CI 1.54-1.78), respectively. SHAP analysis allowed a profound interpretation of the contribution of each protein and clinical variable to the model, revealing the multifactorial nature of OA risk prediction. The temporal trajectories of plasma proteins indicated that the levels of COL9A1 and CRTAC1 began to deviate from normal for more than a decade before OA onset, suggesting their potential use in early detection strategies. The predictive model, developed using the LightGBM algorithm, integrated proteins with clinical covariates and demonstrated an area under the curve (AUC) of 0.729 for 5-year OA prediction, 0.721 for 10-year prediction, and 0.723 for all incident OA. The predictive accuracy of the model was further enhanced for hip and knee OA, achieving AUCs of 0.820 and 0.803 for 5-year predictions. CONCLUSION: Our study identified the role of plasma proteomics in predicting future OA risk, which could contribute to preemptive measures. The innovative model, which integrates proteomic biomarkers with clinical data, offers a potential tool for risk assessment, potentially optimizing OA management strategies and enhancing prevention efforts.

Humans↗

PubMed2025

Assessing the causal effect of genetically predicted metabolites and metabolic pathways on vitiligo: Evidence from Mendelian randomization and animal experiments.

Vitiligo is a common chronic skin depigmentation disorder that seriously decreases the patients' overall quality of life. Human blood metabolites could contribute to unraveling the underlying biological mechanisms of vitiligo. We used GWAS summary statistics to assess the causal association between genetically predicted 1400 serum metabolites and vitiligo risk by Mendelian randomization (MR). Then, after constructing the mouse model of vitiligo, we did non-targeted metabolomics analysis on the mouse serum and validated MR's pathway enrichment results ulteriorly. In the initial phase, MR analysis revealed causative associations between 36 metabolites and vitiligo risk, including 8 metabolite ratios and 28 individual metabolites (19 known and 9 unknown metabolites). In the validation stage, 7 metabolites were successfully validated. Of the 28 individual metabolites, most are related to lipid metabolism. Genetically predicted higher 4-oxo-retinoic acid showed the strongest protective effect on vitiligo, while the most potent risk effect was the increase in quinate. The metabolites associated with vitiligo risk are mainly enriched in alpha-linolenic acid metabolism, linoleic acid metabolism, arginine biosynthesis and metabolism pathways, validated through the serum metabolomics of vitiligo mouse. By integrating genomics and metabolomics, this study provides new insights into the association between metabolites and vitiligo, highlighting the potential roles of specific metabolites in the pathogenesis of vitiligo. These metabolites associated with vitiligo could serve as new biomarkers, further research could help to reveal how these metabolites influence specific pathways in the development of vitiligo.

Animals↗

PubMed2024

Four novel mutations identified in the COL4A3, COL4A4 and COL4A5 genes in 10 families with Alport syndrome.

BACKGROUND: Alport syndrome (AS) is an inherited nephropathy caused by mutations in the type IV collagen genes. It is clinically characterized by damage to the eyes, ears and kidneys. Diagnosis of AS is hampered by its atypical clinical picture, particularly when the typical features, include persistent hematuria and microscopic changes in the glomerular basement membrane (GBM), are the only clinical manifestations in the patient. METHODS: We screened 10 families with suspected AS using whole exome sequencing (WES) and analyzed the harmfulness, conservation, and protein structure changes of mutated genes. In further, we performed in vitro functional analysis of two missense mutations in the COL4A5 gene (c.2359G > C, p.G787R and c.2605G > A, p.G869R). RESULTS: We identified 11 pathogenic variants in the type IV collagen genes (COL4A3, COL4A4 and COL4A5). These pathogenic variants include eight missense mutations, two nonsense mutations and one frameshift mutation. Notably, Family 2 had digenic mutations in the COL4A3 (p.G1170A) and UMOD genes (p.M229K). Family 3 had a digenic missense mutation (p.G997E) in COL4A3 and a frameshift mutation (p.P502L fs*151) in COL4A4. To our knowledge, four of the 11 mutations are novel mutations. In addition, we found that COL4A5 mutation relation mRNA levels were significantly decreased in HEK 293 T cell compared to control, while the cellular localization remained the same. CONCLUSIONS: Our research expands the spectrum of COL4A3-5 pathogenic variants, which is helpful for clinical and scientific research.

Humans↗