Large-scale survey, animal models and computational modeling identify histological neurodegenerative biomarkers for traumatic optic neuropathy

比例(比率) 医学 神经科学 病理 生物 物理 量子力学
作者
Yuehua Zhang,Boyue Xu,Shiwei Huang,Zhihong Shi,Wei Xiong,Ruijun Wang,G. Liu,Linlin Chen,Zhigang Ge,Yongjie Zhang,Honglei Liu,Bingjing Jia,Chunxia Wang,Hailong Shi,Jun Kang,Ningyu An,Shuxian Huang,Defu Chen,Shenghai Huang,Yukun Luo
出处
期刊:JCI insight [American Society for Clinical Investigation]
标识
DOI:10.1172/jci.insight.190682
摘要

Traumatic optic neuropathy (TON) is a leading cause of blindness following closed traumatic brain injury, with no effective treatments available. Previous interventional clinical trials were complicated by its low prevalence, variability in neurodegenerative severity, and unavailability of reliable biomarkers. We analyzed data from 1226 patients enrolled in the prospective National Multi-Center Collaborative Clinical Research Program of China (2017-2024) to establish a clinical profile and identify non-invasive biomarkers for neurodegenerative severity. Subgroup analysis of monocular TON patients revealed potential biomarkers including visual functional parameters, inner retinal thickness, and time post-injury. The ganglion cell complex (GCC) thickness showed a strong correlation with retinal ganglion cell somata (R² = 0.87, p < .0001) and axon density (R² = 0.89, p < .0001) in a clinically relevant large animal model. Computational analysis demonstrated that using GCC thickness as a biomarker could substantially enhance the statistical power of clinical trials (by up to 4.5-fold), as confirmed by real-world data. This study presented the largest epidemiological analysis of TON to date and established GCC thickness as a crucial biomarker for stratifying disease severity and improving the efficiency of clinical trials. Chinese Clinical Trial Registry (ChiCTR-OOC-17013437). National Key R&D Program of China (Grant No.2022YFA1105500); Key Science and Technology Program of Wenzhou (Grant No.ZY2022021); National Natural Science Foundation of China (Grant No.82471080).
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