A metabolome atlas of the aging mouse brain

Jun Ding, Jian Ji, Zachary Rabow, Tong Shen, Jacob Folz, Christopher R. Brydges, Sili Fan, Xinchen Lu, Sajjan Mehta, Megan R. Showalter, Ying Zhang, Renee Araiza, Lynette R. Bower, K. C. Kent Lloyd and Oliver Fiehn ()
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Jun Ding: University of California, Davis
Jian Ji: Jiangnan University
Zachary Rabow: University of California, Davis
Tong Shen: University of California, Davis
Jacob Folz: University of California, Davis
Christopher R. Brydges: University of California, Davis
Sili Fan: University of California, Davis
Xinchen Lu: University of California, Davis
Sajjan Mehta: University of California, Davis
Megan R. Showalter: University of California, Davis
Ying Zhang: University of California, Davis
Renee Araiza: University of California, Davis
Lynette R. Bower: University of California, Davis
K. C. Kent Lloyd: University of California, Davis
Oliver Fiehn: University of California, Davis

Nature Communications, 2021, vol. 12, issue 1, 1-12

Abstract: Abstract The mammalian brain relies on neurochemistry to fulfill its functions. Yet, the complexity of the brain metabolome and its changes during diseases or aging remain poorly understood. Here, we generate a metabolome atlas of the aging wildtype mouse brain from 10 anatomical regions spanning from adolescence to old age. We combine data from three assays and structurally annotate 1,547 metabolites. Almost all metabolites significantly differ between brain regions or age groups, but not by sex. A shift in sphingolipid patterns during aging related to myelin remodeling is accompanied by large changes in other metabolic pathways. Functionally related brain regions (brain stem, cerebrum and cerebellum) are also metabolically similar. In cerebrum, metabolic correlations markedly weaken between adolescence and adulthood, whereas at old age, cross-region correlation patterns reflect decreased brain segregation. We show that metabolic changes can be mapped to existing gene and protein brain atlases. The brain metabolome atlas is publicly available ( https://mouse.atlas.metabolomics.us/ ) and serves as a foundation dataset for future metabolomic studies.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-26310-y

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DOI: 10.1038/s41467-021-26310-y

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