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Article Dans Une Revue Journals of Gerontology Series A: Biological Sciences and Medical Sciences Année : 2024

Integrative Multimodal Metabolomics to Early Predict Cognitive Decline Among Amyloid Positive Community-Dwelling Older Adults

Isabelle Ader

Résumé

Alzheimer’s disease is strongly linked to metabolic abnormalities. We aimed to distinguish amyloid-positive people who progressed to cognitive decline from those who remained cognitively intact. We performed untargeted metabolomics of blood samples from amyloid-positive individuals, before any sign of cognitive decline, to distinguish individuals who progressed to cognitive decline from those who remained cognitively intact. A plasma-derived metabolite signature was developed from Supercritical Fluid chromatography coupled with high-resolution mass spectrometry (SFC-HRMS) and nuclear magnetic resonance (NMR) metabolomics. The 2 metabolomics data sets were analyzed by Data Integration Analysis for Biomarker discovery using Latent approaches for Omics studies (DIABLO), to identify a minimum set of metabolites that could describe cognitive decline status. NMR or SFC-HRMS data alone cannot predict cognitive decline. However, among the 320 metabolites identified, a statistical method that integrated the 2 data sets enabled the identification of a minimal signature of 9 metabolites (3-hydroxybutyrate, citrate, succinate, acetone, methionine, glucose, serine, sphingomyelin d18:1/C26:0 and triglyceride C48:3) with a statistically significant ability to predict cognitive decline more than 3 years before decline. This metabolic fingerprint obtained during this exploratory study may help to predict amyloid-positive individuals who will develop cognitive decline. Due to the high prevalence of brain amyloid-positivity in older adults, identifying adults who will have cognitive decline will enable the development of personalized and early interventions.
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hal-04615498 , version 1 (18-06-2024)

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Marie Tremblay-Franco, Cécile Canlet, Audrey Carriere, Jean Nakhle, Anne Galinier, et al.. Integrative Multimodal Metabolomics to Early Predict Cognitive Decline Among Amyloid Positive Community-Dwelling Older Adults. Journals of Gerontology Series A: Biological Sciences and Medical Sciences, 2024, 79 (5), pp.glae077. ⟨10.1093/gerona/glae077⟩. ⟨hal-04615498⟩
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