{"title":"血浆代谢谱与机器学习揭示病理性近视的独特诊断和生物学特征。","authors":"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","doi":"10.1002/advs.202505861","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":117,"journal":{"name":"Advanced Science","volume":" ","pages":"e05861"},"PeriodicalIF":14.3000,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Plasma Metabolic Profile with Machine Learning Reveals Distinct Diagnostic and Biological Signatures for Pathologic Myopia.\",\"authors\":\"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\",\"doi\":\"10.1002/advs.202505861\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":117,\"journal\":{\"name\":\"Advanced Science\",\"volume\":\" \",\"pages\":\"e05861\"},\"PeriodicalIF\":14.3000,\"publicationDate\":\"2025-07-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advanced Science\",\"FirstCategoryId\":\"88\",\"ListUrlMain\":\"https://doi.org/10.1002/advs.202505861\",\"RegionNum\":1,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Science","FirstCategoryId":"88","ListUrlMain":"https://doi.org/10.1002/advs.202505861","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
Plasma Metabolic Profile with Machine Learning Reveals Distinct Diagnostic and Biological Signatures for Pathologic Myopia.
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.
期刊介绍:
Advanced Science is a prestigious open access journal that focuses on interdisciplinary research in materials science, physics, chemistry, medical and life sciences, and engineering. The journal aims to promote cutting-edge research by employing a rigorous and impartial review process. It is committed to presenting research articles with the highest quality production standards, ensuring maximum accessibility of top scientific findings. With its vibrant and innovative publication platform, Advanced Science seeks to revolutionize the dissemination and organization of scientific knowledge.