Dataset Information

Diet-Related Metabolites Associated with Cognitive Decline Revealed by Untargeted Metabolomics in a Prospective Cohort.

ABSTRACT:

Scope

Untargeted metabolomics may reveal preventive targets in cognitive aging, including within the food metabolome.

Methods and results

A case-control study nested in the prospective Three-City study includes participants aged ≥65 years and initially free of dementia. A total of 209 cases of cognitive decline and 209 controls (matched for age, gender, education) with slower cognitive decline over up to 12 years are contrasted. Using untargeted metabolomics and bootstrap-enhanced penalized regression, a baseline serum signature of 22 metabolites associated with subsequent cognitive decline is identified. The signature includes three coffee metabolites, a biomarker of citrus intake, a cocoa metabolite, two metabolites putatively derived from fish and wine, three medium-chain acylcarnitines, glycodeoxycholic acid, lysoPC(18:3), trimethyllysine, glucose, cortisol, creatinine, and arginine. Adding the 22 metabolites to a reference predictive model for cognitive decline (conditioned on age, gender, education and including ApoE-ε4, diabetes, BMI, and number of medications) substantially increases the predictive performance: cross-validated Area Under the Receiver Operating Curve = 75% [95% CI 70-80%] compared to 62% [95% CI 56-67%].

Conclusions

The untargeted metabolomics study supports a protective role of specific foods (e.g., coffee, cocoa, fish) and various alterations in the endogenous metabolism responsive to diet in cognitive aging.

SUBMITTER: Low DY

PROVIDER: S-EPMC6790579 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Publications

Diet-Related Metabolites Associated with Cognitive Decline Revealed by Untargeted Metabolomics in a Prospective Cohort.

Low Dorrain Yanwen DY Lefèvre-Arbogast Sophie S González-Domínguez Raúl R Urpi-Sarda Mireia M Micheau Pierre P Petera Melanie M Centeno Delphine D Durand Stephanie S Pujos-Guillot Estelle E Korosi Aniko A Lucassen Paul J PJ Aigner Ludwig L Proust-Lima Cécile C Hejblum Boris P BP Helmer Catherine C Andres-Lacueva Cristina C Thuret Sandrine S Samieri Cécilia C Manach Claudine C

Molecular nutrition & food research 20190709 18

<h4>Scope</h4>Untargeted metabolomics may reveal preventive targets in cognitive aging, including within the food metabolome.<h4>Methods and results</h4>A case-control study nested in the prospective Three-City study includes participants aged ≥65 years and initially free of dementia. A total of 209 cases of cognitive decline and 209 controls (matched for age, gender, education) with slower cognitive decline over up to 12 years are contrasted. Using untargeted metabolomics and bootstrap-enhanced ...[more]

PMID: 31218777

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Project description:BackgroundPostoperative cognitive decline (POCD) is the predominant complication affecting patients over 60 years old following major surgery, yet its prediction and prevention remain challenging. Understanding the biological processes underlying the pathogenesis of POCD is essential for identifying mechanistic biomarkers to advance diagnostics and therapeutics. This study aimed to provide a comprehensive analysis of immune cell trajectories differentiating patients with and without POCD and to derive a predictive score enabling the identification of high-risk patients during the preoperative period.Material and methodsTwenty-six patients aged 60 years old and older undergoing elective major orthopedic surgery were enrolled in a prospective longitudinal study, and the occurrence of POCD was assessed seven days after surgery. Serial samples collected before surgery, and one, seven, and 90 days after surgery were analyzed using a combined single-cell mass cytometry and plasma proteomic approach. Unsupervised clustering of the high-dimensional mass cytometry data was employed to characterize time-dependent trajectories of all major innate and adaptive immune cell frequencies and signaling responses. Sparse machine learning coupled with data-driven feature selection was applied to the pre-surgery immunological dataset to classify patients at risk for POCD.ResultsThe analysis identified cell-type and signaling-specific immune trajectories differentiating patients with and without POCD. The most prominent trajectory features revealed early exacerbation of JAK/STAT and dampening of inhibitory κB and nuclear factor-κB immune signaling responses in patients with POCD. Further analyses integrating immunological and clinical data collected before surgery identified a preoperative predictive model comprising one plasma protein and ten immune cell features that classified patients at risk for POCD with excellent accuracy (AUC=0.80, P=2.21e-02 U-test).ConclusionImmune system-wide monitoring of patients over 60 years old undergoing surgery unveiled a peripheral immune signature of POCD. A predictive model built on immunological data collected before surgery demonstrated greater accuracy in predicting POCD compared to known clinical preoperative risk factors, offering a concise list of biomarker candidates to personalize perioperative management.

Dataset Information

Diet-Related Metabolites Associated with Cognitive Decline Revealed by Untargeted Metabolomics in a Prospective Cohort.

Scope

Methods and results

Conclusions

Publications

Diet-Related Metabolites Associated with Cognitive Decline Revealed by Untargeted Metabolomics in a Prospective Cohort.

Similar Datasets

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