Association of aerobic glycolysis with the structural connectome reveals a benefit-risk balancing mechanism in the human brain

Yuhan Chen, Qixiang Lin, Xuhong Liao, Changsong Zhou*, Yong He*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

5 Citations (Scopus)


Aerobic glycolysis (AG), that is, the nonoxidative metabolism of glucose, contributes significantly to anabolic pathways, rapid energy generation, task-induced activity, and neuroprotection; yet high AG is also associated with pathological hallmarks such as amyloid-β deposition. An important yet unresolved question is whether and how the metabolic benefits and risks of brain AG is structurally shaped by connectome wiring. Using positron emission tomography and magnetic resonance imaging techniques as well as computational models, we investigate the relationship between brain AG and the macroscopic connectome. Specifically, we propose a weighted regional distance-dependent model to estimate the total axonal projection length of a brain node. This model has been validated in a macaque connectome derived from tract-tracing data and shows a high correspondence between experimental and estimated axonal lengths. When applying this model to the human connectome, we find significant associations between the estimated total axonal projection length and AG across brain nodes, with higher levels primarily located in the default- mode and prefrontal regions. Moreover, brain AG significantly mediates the relationship between the structural and functional connectomes. Using a wiring optimization model, we find that the estimated total axonal projection length in these high-AG regions exhibits a high extent of wiring optimization. If these high- AG regions are randomly rewired, their total axonal length and vulnerability risk would substantially increase. Together, our results suggest that high-AG regions have expensive but still optimized wiring cost to fulfill metabolic requirements and simultaneously reduce vulnerability risk, thus revealing a benefit-risk balancing mechanism in the human brain.

Original languageEnglish
Article numbere2013232118
Number of pages8
JournalProceedings of the National Academy of Sciences of the United States of America
Issue number1
Early online date21 Dec 2020
Publication statusPublished - 5 Jan 2021

Scopus Subject Areas

  • General

User-Defined Keywords

  • Computational models
  • Connectomics
  • Default mode
  • Metabolism
  • Neuroimaging


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