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. 2023 Feb 4:2023:4416410.
doi: 10.1155/2023/4416410. eCollection 2023.

Metabolomics Profiling of Age-Associated Metabolites in Malay Population

Affiliations

Metabolomics Profiling of Age-Associated Metabolites in Malay Population

Jen Kit Tan et al. Oxid Med Cell Longev. .

Abstract

Aging is a complex process characterized by progressive loss of functional abilities due to the accumulation of molecular damages. Metabolomics could offer novel insights into the predictors and mechanisms of aging. This cross-sectional study is aimed at identifying age-associated plasma metabolome in a Malay population. A total of 146 (90 females) healthy participants aged 28-69 were selected for the study. Untargeted metabolomics profiling was performed using liquid chromatography-tandem mass spectrometry. Association analysis was based on the general linear model. Gender-associated metabolites were adjusted for age, while age-associated metabolites were adjusted for gender or analyzed in a gender-stratified manner. Gender-associated metabolites such as 4-hydroxyphenyllactic acid, carnitine, cortisol, and testosterone sulfate showed higher levels in males than females. Deoxycholic acid and hippuric acid were among the metabolites with a positive association with age after being adjusted for gender, while 9(E),11(E)-conjugated linoleic acid, cortisol, and nicotinamide were negatively associated with age. In gender-stratified analysis, glutamine was one of the common metabolites that showed a direct association with age in both genders, while metabolites such as 11-deoxy prostaglandin F2β, guanosine monophosphate, and testosterone sulfate were inversely associated with age in males and females. This study reveals several age-associated metabolites in Malays that could reflect the changes in metabolisms during aging and may be used to discern the risk of geriatric syndromes and disorders later. Further studies are required to determine the interplay between these metabolites and environmental factors on the functional outcomes during aging.

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Conflict of interest statement

The authors declare that there is no conflict of interest regarding the publication of this paper.

Figures

Figure 1
Figure 1
PCA score plot of sample and QC combined from all runs. (a) Positive and (b) negative ion modes before batch effect correction. (c) Positive and (d) negative ion modes after batch effect correction.

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