Lens Capsule microRNA Profiling Across the Primary Angle-Closure Disease Spectrum: Association with Anterior Segment Crowding
Hae Min Park, Hyun Soo Cho, Yeji Yeon, Min-Ji Cha, Jong Sub Lee, Soorack Ryu, Jooyoung Yoon, Yu Jeong Kim, Won June LeeWe aimed to compare anterior lens capsule microRNA (miRNA) expression across the primary angle-closure disease (PACD) spectrum and a control group, and to examine associations between differentially expressed miRNAs and anterior segment biometric parameters. In this cross-sectional study, anterior lens capsule specimens were collected during cataract surgery from 27 eyes (seven controls, nine primary angle-closure suspect (PACS) eyes, six primary angle-closure (PAC) eyes, and five primary angle-closure glaucoma (PACG) eyes). The expression of 84 miRNAs was profiled, and the ΔCt values were compared across groups and correlated with anterior segment biometric parameters. Experimentally validated target genes of significant miRNAs were retrieved from miRTargetLink 2.0. miR-188-5p was the only miRNA that differed significantly between control and PACD eyes (control 11.27 ± 2.29 vs. PACD 8.21 ± 2.09; p = 0.003), with higher expression in PACS (p = 0.022) and PAC (p = 0.006). Higher miR-188-5p expression correlated with greater LV (r = −0.64, p = 0.033), narrower AOD500 (r = 0.50, p = 0.015), and shorter AXL (r = 0.41, p = 0.032). miR-146b-5p and miR-335-5p showed subgroup-specific differences and correlated with LV and AXL/AOD500, respectively, though these findings were exploratory. However, these findings did not remain significant after correction for multiple testing. Network analysis identified four experimentally validated targets of miR-188-5p (GREM2, ITGA7, CEMIP, FGF5) relevant to extracellular matrix turnover, hypoxia and inflammation. miR-188-5p was upregulated in the anterior lens capsule across the PACD spectrum and was associated with biometric hallmarks of a crowded anterior segment, suggesting its potential as a diagnostic or therapeutic candidate for PACD, pending validation in larger, functional studies.