ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025
Plasma Metabolic Profile with Machine Learning Reveals Distinct Diagnostic and Biological Signatures for Pathologic Myopia.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
4 citing papers in PubMed.
- Deep Proteomic Analysis With Machine Learning Identifies Aqueous Humor Biomarkers of ADAMTSL4-associated Congenital Ectopia Lentis.Investigative ophthalmology & visual science · 2026Article
- Integrated analysis of the aqueous humor microbiome and lens capsule transcriptome in high myopia cataract: a pilot study.Frontiers in medicine · 2026Article
- Plasma Metabolic Profile with Machine Learning Reveals Distinct Diagnostic and Biological Signatures for Pathologic Myopia.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Diagnostic challenges in high myopia: identification of sight-threatening complications and the role of artificial intelligence.Frontiers in ophthalmology · 2025Review
Corrections and comments
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Authors and funding
14 authors.
Funding
Abstract
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.
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Registered trials
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