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Biomedical subjects

Xueli Zhang

Publications and source records attributed to Xueli Zhang.

2 recordsLinked to original sources

Base editing for precision therapeutics.

Base editing (BE), the precise installation of single-nucleotide changes in DNA or RNA without inducing double-strand breaks, holds substantial therapeutic promise for correcting single-nucleotide variants, which constitute more than half of the known pathogenic genetic variants. Recent advances have improved base editor specificity, efficiency, and delivery, enabling clinically oriented procedures. Clinically, BE has shown early success or strong translational promise in sickle cell disease, β-thalassemia, leukemia (via CAR T and epitope engineering), hypercholesterolemia (PCSK9 and ANGPTL3), alpha-1-antitrypsin deficiency, and glycogen storage disease type Ia. Key remaining challenges include bystander editing within the activity window, residual off-target DNA and RNA editing, delivery constraints (payload size, tissue targeting, and redosing limits), immunogenicity, and the need for durable long-term safety evidence across relevant cell types and disease contexts. Continued technological refinements, careful preclinical validation, and rigorous clinical assessment will be essential to fully realize BE's transformative potential in precision medicine.

Humans

Stage-dependent proteomic alterations in aqueous humor of diabetic retinopathy patients based on data-independent acquisition and parallel reaction monitoring.

BACKGROUND: Diabetic retinopathy (DR), a microvascular complication of diabetes mellitus (DM), represents the predominant cause of preventable vision loss in working-age populations globally. While the pathophysiological mechanisms underlying DR progression remain incompletely understood, our study employs comprehensive proteomic profiling of aqueous humor (AH) to identify stage-specific biomarkers and therapeutic targets in type 2 diabetes mellitus (T2DM) patients across DR progression. METHODS: Utilizing data-independent acquisition (DIA) mass spectrometry, we quantified AH proteomes in a discovery cohort comprising 24 subjects: 18 T2DM patients stratified by DR severity [6 non-DR, 6 non-proliferative DR (NPDR), 6 proliferative DR (PDR)] and 6 cataract controls without diabetes (non-DM). Validation cohort analysis (including 10 AH samples in each group) was performed using parallel reaction monitoring (PRM) strategy for verification of target proteins. Comprehensive bioinformatics analyses included gene set enrichment analysis (GSEA), weighted gene co-expression network analysis (WGCNA), Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis, protein-protein interaction (PPI) network construction, receiver operating characteristic (ROC) curve analysis, and ConnectivityMap (Cmap)-based drug prediction. RESULTS: Proteomic profiling identified 739 quantifiable AH proteins (62% extracellular) with clear separation among the four clinical stages in the discovery cohort. GSEA uncovered altered expression of proteins mainly related to complement and coagulation cascades, folate metabolism, and the selenium micronutrient network in patients with DR. WGCNA-derived protein modules yielded 83 PRM-validated targets, including 5 hub proteins differentiating NPDR from non-DR and 33 hub proteins showed significant upregulation in PDR versus NPDR comparison. Clinical correlation analysis identified F2, FGG, FGB, RBP4, AMBP, VTN, C8A, CPB2, and C2 associated with clinical traits. C6, FAM3C, SPP1, and JCHAIN levels were altered post-anti-VEGF treatment. Pharmacological prediction identified potential therapeutic compounds, including perindopril, triciribine, and XAV-939 for NPDR, and topiramate, triciribine, and vecuronium for PDR. CONCLUSION: This study established a comprehensive AH proteomic signature of DR progression, offering insights into the pathogenesis of DR and highlighting potential biomarkers and novel therapeutic targets.

Humans