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. 2019 Jul 21;11(14):5124-5139.
doi: 10.18632/aging.102107.

Novel Serum Metabolites Associate With Cognition Phenotypes Among Bogalusa Heart Study Participants

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Free PMC article

Novel Serum Metabolites Associate With Cognition Phenotypes Among Bogalusa Heart Study Participants

Mengyao Shi et al. Aging (Albany NY). .
Free PMC article

Abstract

Background: Metabolomics study provides an opportunity to identify novel molecular determinants of altered cognitive function.

Methods: During 2013 to 2016 Bogalusa Heart Study (BHS) visit, 1,177 participants underwent untargeted, ultrahigh performance liquid chromatography-tandem mass spectroscopy metabolomics profiling. Global cognition and five cognition domains were also assessed. The cross-sectional associations of single metabolites with cognition were tested using multiple linear regression models. Weighted correlation network analysis was used to examine the covariable-adjusted correlations of modules of co-abundant metabolites with cognition. Analyses were conducted in the overall sample and according to both ethnicity and sex.

Results: Five known metabolites and two metabolite modules robustly associated with cognition across overall and stratified analyses. Two metabolites were from lipid sub-pathways including fatty acid metabolism [9-hydroxystearate; minimum P-value (min-P)=1.11×10-5], and primary bile acid metabolism (glyco-alpha-muricholate; min-P=4.10×10-5). One metabolite from the glycogen metabolism sub-pathway (maltose; min-P=9.77×10-6), one from the polyamine metabolism sub-pathway (N-acetyl-isoputreanine; min-P=1.03×10-5), and one from the purine metabolism sub-pathway (7-methylguanine; min-P=1.19×10-5) were also identified. Two metabolite modules reflecting bile acid metabolism and androgenic steroids correlated with cognition (min-P=5.00×10-4 and 3.00×10-3, respectively).

Conclusion: The novel associations of 5 known metabolites and 2 metabolite modules with cognition provide insights into the physiological mechanisms regulating cognitive function.

Keywords: Alzheimer’s disease; cognition; dementia; metabolite network; metabolomics.

Conflict of interest statement

CONFLICTS OF INTEREST: J.M.K. is employed by Metabolon, Inc. He contributed to the logistics, optimization, and interpretation of the untargeted metabolomics. Metabolon, Inc. was not involved in the study design, statistical analysis, or interpretation of the results.

Figures

Figure 1
Figure 1
A. Volcano plots of effect sizes versus –log10 P values for all 1202 metabolites among BHS participants, according to cognitive domain. (A) Global cognition; (B) Processing speed (digit coding test); (C) Processing speed (trail making test A).
Figure 2
Figure 2. Heat map displaying pairwise correlation coefficients for the six identified metabolites.
Figure 3A
Figure 3A
Correlations of metabolite modules with cognition. Global cognition (global cognition score).
Figure 3B
Figure 3B
Correlations of metabolite modules with cognition. Processing speed domain (digit coding test).
Figure 3C
Figure 3C
Correlations of metabolite modules with cognition. Processing speed domain (trail making test A).
Figure 4
Figure 4. Heat map displaying pairwise correlation coefficients for the network of metabolites representing the significant primary and secondary bile acid metabolism pathway.
Figure 5
Figure 5. Heat map displaying pairwise correlation coefficients for the network of metabolites representing the significant androgenic steroids pathway.

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