Plasma Metabolic Profile with Machine Learning Reveals Distinct Diagnostic and Biological Signatures for Pathologic Myopia

作者：Ziheng Qi, Jiao Qi, Ye Zhang, Yanhui Wang, Yuchen Feng, Zifan Yang, Yating Wang, Weikang Shu, Dongling Guo, Ching Kang, Keke Zhang, Yi Lu, Jingjing Wan, Xiangjia Zhu · 发表于：Advanced Science · 年份：2025 · DOI：10.1002/advs.202505861 · 被引用次数：6 · 研究领域：Glaucoma and retinal disorders、Corneal surgery and disorders、Retinal Diseases and Treatments

Pathologic myopia (PM), characterized by serious myopic macular degeneration (MMD), is a detrimental subtype of high myopia (HM) and has become one of the leading causes of blindness worldwide. In this concern, precise and high-throughput molecular diagnosis and further pathologic insights are urgently needed. Here, through the combined strategy of nanoparticle-enhanced laser desorption/ionization mass spectrometry-based rapid metabolic analysis (<30 s) and machine learning, a precise molecular diagnostic approach of PM (HM with MMD grade ≥ 2) is proposed, which achieves areas under the curve of 0.874 and 0.889 for diagnosing PM and early-stage PM, respectively. Further, the biomarkers indicate the PM-associated systemic metabolic reprogramming of amino acid and lipid metabolism, which may mediate dysfunctional oxidative stress, inflammation, hormone/neurotransmitter systems, and energy metabolism. Notably, MMD grade 4, featuring characteristic macula atrophy, exhibits specificity in this metabolic reprogramming. Of these biomarkers, azelaic acid shows a significant protective effect in the ARPE-19 cells under abnormal oxidative stress, which may be involved in PM development as a key antioxidative active metabolite. This work will contribute to PM molecular diagnosis and pathology exploration.