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Development of a dual-channel analytical approach for diabetic biomarker discovery in blood via integrative metabolomics and lipidomics

Journal 2025 · IF 4 · 发表于 2025 年 8 月 27 日
作者: Yehai Li,Shixin Liu,Yunsha Zhang,BoYa Guan,Chaojun Zhu,Hongbin Liu,Liang Xu
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摘要

Conventional metabolomics and lipidomics typically require separate sample preparations, which can introduce systematic bias and reduce throughput, thereby hindering comprehensive elucidation of diabetic metabolic networks. In this study, we exploited the pH-responsive behavior of ZrO₂–SiO₂ composite microspheres to establish the first single-sample, dual-channel solid-phase extraction (SPE) pretreatment method: under acidic conditions, Zr⁴⁺–PO₄³⁻ coordination selectively adsorbs phospholipids, whereas under basic conditions, NH₄⁺ competes to gently elute them. The flow-through and elution fractions are used for metabolomic and lipidomic analyses, respectively. We integrated the entire workflow into an automated pretreatment platform and coupled it with high-resolution LC–IMS–QTOF detection to enable high-throughput processing. Method validation demonstrated high phospholipid recovery and excellent preservation of polar metabolites (representative results: LPC 18:0 elution recovery 100.1 % ± 3.0 %; DPPC elution recovery 94.0 % ± 2.0 %; 25-OH-VD₃ flow-through retention 99.0 % ± 2.0 %). In serum from diabetic patients and healthy controls, 390 differential metabolites were identified in the metabolome, significantly enriched in energy metabolism pathways such as galactose metabolism; lipidomics revealed disturbances in glycerophospholipid metabolism, indicating membrane signaling remodeling. Importantly, the dual-channel approach captured for the first time the coordinated disruption of the galactose–ether-lipid metabolic axis—a sequential reduction in UDP-galactose levels leading to diminished plasmalogen biosynthesis—providing direct molecular evidence for the pathogenic sequence in which disrupted glycolytic energy metabolism precipitates membrane structural dysfunction. This method not only markedly improves the consistency and throughput of omics data but also lays a technical foundation for advancing precision diagnostics and treatment of diabetes from “blood glucose management” to “metabolic network regulation.”

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