Citations

Abstract The trabecular meshwork (TM) and ciliary body (CB) regulate aqueous humor dynamics and intraocular pressure (IOP), and TM/Schlemm’s canal (SC) dysfunction underlies glaucoma. Here, we present a spatially resolved multi-omics atlas of human TM and CB, integrating snRNA-seq, scRNA-seq, and snATAC-seq from over one million cells and nuclei across 112 donors with Xenium spatial transcriptomics. We identified 9 major cell classes and 21 cell types, revealing heterogeneity, including undercharacterized fibroblast and epithelial subpopulations. Spatial mapping supported TM fibroblast zonation and CB epithelial organization. Regulatory analyses identified cell type–specific programs, including OTX/PAX networks in CB epithelium and SMAD3/TGF-β signaling in fibroblasts. Integration with glaucoma loci showed enrichment of non-coding variants in regulatory elements associated with POAG and PACG. Age- and ancestry-associated remodeling revealed divergent fibroblast aging with increased PIEZO1 , suggesting impaired outflow and elevated IOP. Together, this high-resolution atlas links cellular, regulatory, and genetic variation to anterior segment function and glaucoma susceptibility.

Abstract Background Keratoconus (KC) is a multifactorial disorder with unclear etiology, characterized by localized thinning and a cone-like protrusion of the cornea. The complex etiology of KC exacerbates the lack of an animal model. Previous studies by Tachibana et al. (2002) described an inbred mouse strain (SKC) with a spontaneous, androgen-dependent, cone-like corneal morphology. This study aimed to investigate the corneal phenotypes of SKC mice through an in-depth ophthalmic examination. Methods Mice (n=53) were examined via slit lamp biomicroscopy with fluorescein staining. Spectral-domain optical coherence tomography (SD-OCT) enabled central corneal thickness (CCT) measurement in selected mice (n=26 eyes), and OCT-based pachymetry mapping (n=16 eyes). In vivo corneal confocal microscopy was conducted on eyes to assess cellular morphology (n= 9 eyes). Eyes were collected for histology analysis (n=22). Results Lesions and epithelial breaks were present in ∼95% of eyes (n=101). Neovascularization, perforation, scarring, and hydrops were seen primarily in males. An opaque, unilateral cone-like morphology was exclusive to males (n=11). Male and female corneas showed no significant difference in CCT, though pachymetry mapping revealed regional thinning patterns in both sexes. Loosened epithelial tight junctions, stromal fibrosis, vascularization, and inflammation of variable severity were identified in both sexes. Conclusion This study identified previously unreported corneal phenotypes in SKC mice through ophthalmic examination. Unlike previous studies, gross and histological abnormalities were observed in female SKC mice. Our findings suggest a lower penetrance of the cone-like phenotype (∼20%) than previously reported (∼33%) and support that the conical phenotype in male mice may be secondary to keratitis.

Abstract Objective: Several attributes of female reproductive history, including age at natural menopause (ANM), have been related to primary open-angle glaucoma (POAG). We assembled 18 previously reported common genetic variants that predict ANM to determine their association with ANM or POAG. Methods: Using data from the Nurses’ Health Study (7,143 women), we validated the ANM weighted genetic risk score in relation to self-reported ANM. Subsequently, to assess the relation with POAG, we used data from 2,160 female POAG cases and 29,110 controls in the National Eye Institute Glaucoma Human Genetics Collaboration Heritable Overall Operational Database (NEIGHBORHOOD), which consists of 8 datasets with imputed genotypes to 5.6+ million markers. Associations with POAG were assessed in each dataset, and site-specific results were meta-analyzed using the inverse weighted variance method. Results: The genetic risk score was associated with self-reported ANM (P = 2.2 × 10–77) and predicted 4.8% of the variance in ANM. The ANM genetic risk score was not associated with POAG (Odds Ratio (OR) = 1.002; 95% Confidence Interval (CI): 0.998, 1.007; P = 0.28). No single genetic variant in the panel achieved nominal association with POAG (P ≥0.20). Compared to the middle 80 percent, there was also no association with the lowest 10th percentile or highest 90th percentile of genetic risk score with POAG (OR = 0.75; 95% CI: 0.47, 1.21; P = 0.23 and OR = 1.10; 95% CI: 0.72, 1.69; P = 0.65, respectively). Conclusions: A genetic risk score predicting 4.8% of ANM variation was not related to POAG; thus, genetic determinants of ANM are unlikely to explain the previously reported association between the two phenotypes.