bioRxivNeurosciencePreprint
Mitochondrial Complex I Modulator Restores Network Resilience in Advanced Alzheimer's Disease Through Metabolic Reprogramming
Esraa GabaliD, Thi Kim Oanh NguyeniD, Tetiana KovalenkoiD, Huanyao GaoiD, Noa RappaportiD, Cory C. FunkiD, Priyanka BaloniiD, Eugenia V. TrushinaiD
Abstract
Mitochondrial dysfunction and lipid dysregulation are among the earliest abnormalities in Alzheimers disease (AD), yet their mechanistic interplay and therapeutic potential remain poorly understood. Here, we investigated whether restoration of mitochondrial function can reverse metabolic dysfunction and promote resilience in advanced-stage AD. Female APP/PS1 mice were treated with the brain-penetrant mitochondrial complex I (mtCI) modulator CP2 beginning at 19 months of age, when pathology and cognitive deficits were well established. To define the metabolic mechanisms underlying therapeutic response, we developed iMiceBrain, the first brain-specific genome-scale metabolic model of the mouse brain, and integrated transcriptomics, targeted metabolomics, lipidomics, and metabolic network analyses. CP2 treatment broadly reprogrammed AD-associated molecular signatures and restored pathways involved in mitochondrial function, glucose utilization, lipid metabolism, synaptic activity, and cellular stress responses. Metabolic modeling identified enhanced mitochondrial substrate flexibility, activation of fatty acid utilization, restoration of pyruvate dehydrogenase flux, and normalization of cholesterol metabolism as key features of the therapeutic response. Lipidomic analyses further demonstrated correction of disease-associated alterations in cholesteryl esters, phospholipids, and sphingolipids. Together, these findings demonstrate that mild mtCI modulation restores metabolic resilience by coordinating mitochondrial and lipid metabolism, establishing it as a disease-modifying therapeutic strategy for AD.
- organism: mouse
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 1
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