Alzheimer's research & therapy · 2025
Integrated plasma and red blood cell membrane lipidomics analysis unveils novel biomarker panel for Alzheimer's disease.
СтатьяНазвание и аннотация: Перевод в очереди
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He Dandan, Bao Yaran, Yuan Siyi, Wang Yingji, Cai Jingbo, Xu Fangfang, Chang Tiantian, Zhang Pei, Yue Menglu, Pan Xiaodong, Hao Haiping, Zheng Qiuling
Аннотация
BACKGROUND: Discovering new biomarkers for Alzheimer's disease (AD) are significant for early diagnosis and monitoring disease's progression. Blood-based lipid biomarkers, particularly from red cell membranes, offer a non-invasive alternative, providing insights into AD progression and potential therapeutic targets.
METHODS: This study innovatively incorporates red cell membrane (RCM) lipids, which reflect chronic physiological alterations and are linked to AD pathogenesis. A comprehensive lipid detection platform was employed to analyze lipid profiles from 156 individuals, including normal subjects, those with amnestic mild cognitive impairment, and AD patients. Differential lipids were identified and validated to be AD-associated by correlation analysis and big data analysis. Multi-dimensional criteria were applied to select potential lipid biomarkers.
RESULTS: PLS-DA revealed distinct lipidomic profiles between groups, with RCM samples showing superior separation. 138 differentially expressed lipids were identified and enriched in AD-related pathways, many uniquely associated with the RCM. Six lipids were selected as a potential biomarker panel for AD based on multi-dimensional criteria.
CONCLUSIONS: RCM shows broader lipidomic relevance and stronger biomarker potential compared to plasma. Integrating RCM lipids with plasma analysis enhances AD diagnostics and highlights the potential of RCM as an underexplored biomarker resource.
METHODS: This study innovatively incorporates red cell membrane (RCM) lipids, which reflect chronic physiological alterations and are linked to AD pathogenesis. A comprehensive lipid detection platform was employed to analyze lipid profiles from 156 individuals, including normal subjects, those with amnestic mild cognitive impairment, and AD patients. Differential lipids were identified and validated to be AD-associated by correlation analysis and big data analysis. Multi-dimensional criteria were applied to select potential lipid biomarkers.
RESULTS: PLS-DA revealed distinct lipidomic profiles between groups, with RCM samples showing superior separation. 138 differentially expressed lipids were identified and enriched in AD-related pathways, many uniquely associated with the RCM. Six lipids were selected as a potential biomarker panel for AD based on multi-dimensional criteria.
CONCLUSIONS: RCM shows broader lipidomic relevance and stronger biomarker potential compared to plasma. Integrating RCM lipids with plasma analysis enhances AD diagnostics and highlights the potential of RCM as an underexplored biomarker resource.