Circulating serum metabolites as predictors of dementia: a machine learning approach in a 21-year follow-up of the Whitehall II cohort study

Circulating serum metabolites as predictors of dementia: a machine learning approach in a 21-year follow-up of the Whitehall II cohort study

Abstract Background Age is the strongest risk factor for dementia and there is considerable interest in identifying scalable, blood-based biomarkers in predicting dementia. We examined the role of midlife serum metabolites using a machine learning approach and determined whether the selected metabol...

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Bibliographic Details
Main Authors: Marcos D. Machado-Fragua, Benjamin Landré, Mathilde Chen, Aurore Fayosse, Aline Dugravot, Mika Kivimaki, Séverine Sabia, Archana Singh-Manoux
Format: Article
Language:English
Published: BMC 2022-09-01
Series:BMC Medicine
Subjects:
Biomarkers
Metabolites
Dementia
Risk score
Predictive accuracy
C-statistic
Online Access:https://doi.org/10.1186/s12916-022-02519-6

Internet

https://doi.org/10.1186/s12916-022-02519-6

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