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Baloni, P.* ; Funk, C.C.* ; Yan, J.* ; Yurkovich, J.T.* ; Kueider-Paisley, A.* ; Nho, K.* ; Heinken, A.* ; Jia, W.* ; MahmoudianDehkordi, S.* ; Louie, G.* ; Saykin, A.J.* ; Arnold, M. ; Kastenmüller, G. ; Griffiths, W.J.* ; Thiele, I.* ; Kaddurah-Daouk, R.* ; Price, N.D.*

Metabolic network analysis reveals altered bile acid synthesis and metabolism in Alzheimer's Disease.

Cell Rep. Med. 1:100138 (2020)
Publ. Version/Full Text Research data DOI
Open Access Gold
Creative Commons Lizenzvertrag
Increasing evidence suggests Alzheimer's disease (AD) pathophysiology is influenced by primary and secondary bile acids, the end product of cholesterol metabolism. We analyze 2,114 post-mortem brain transcriptomes and identify genes in the alternative bile acid synthesis pathway to be expressed in the brain. A targeted metabolomic analysis of primary and secondary bile acids measured from post-mortem brain samples of 111 individuals supports these results. Our metabolic network analysis suggests that taurine transport, bile acid synthesis, and cholesterol metabolism differ in AD and cognitively normal individuals. We also identify putative transcription factors regulating metabolic genes and influencing altered metabolism in AD. Intriguingly, some bile acids measured in brain tissue cannot be explained by the presence of enzymes responsible for their synthesis, suggesting that they may originate from the gut microbiome and are transported to the brain. These findings motivate further research into bile acid metabolism in AD to elucidate their possible connection to cognitive decline. Baloni et al. use a systems biology approach to identify alterations in cholesterol and bile acid metabolism in Alzheimer disease (AD). Expression of alternative bile acid and neural cholesterol clearance pathway along with transporters of taurine and bile acids suggest the role of the gut-brain axis in AD.
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Publication type Article: Journal article
Document type Scientific Article
Keywords Alzheimer's Disease ; Bile Acids ; Cholesterol Metabolism ; Genome-scale Metabolic Models ; Metabolomics ; Transcriptional Regulatory Networks ; Transcriptomics
ISSN (print) / ISBN 2666-3791
e-ISSN 2666-3791
Quellenangaben Volume: 1, Issue: 8, Pages: , Article Number: 100138 Supplement: ,
Publisher Cell Press
Reviewing status Peer reviewed