Transcriptomics, metabolomics, lipidomics, metabolic flux and mGWAS analyses of sphingolipid pathway highlights novel drugs for Alzheimer's disease. (31st December 2021)

• Record Type: Journal Article
• Authors: Baloni, Priyanka; Arnold, Matthias; Moreno, Herman; Nho, Kwangsik; Kastenmüller, Gabi; Suhre, Karsten; Buitrago, Luna; Louie, Gregory; Kueider‐Paisley, Alexandra; Saykin, Andrew J.; Ekroos, Kim; Meikle, Peter J.; Huynh, Kevin; Funk, Cory C.; Hood, Leroy; Price, Nathan D.; Baillie, Rebecca; Han, Xianlin; Kaddurah‐Daouk, Rima F.
• Is Part Of: Alzheimer's & dementia. Volume 17(2021)Supplement 5
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-12-31
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.056152
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Alzheimer's disease (AD) related neurodegeneration has been correlated with metabolic dysfunction. Sphingomyelins (SM), a class of lipids found in the cell membranes especially myelin sheath, have been shown to be disrupted in AD and in other neurodegenerative diseases. Ceramides, the simplest of the sphingolipids, are known to be associated with Aβ production and inflammation. In order to characterize the SM pathway for its molecular links to AD pathogenesis we used complementary multi‐omics approach and identified targets that can be used for intervention. Method: In this study we used post‐mortem brain transcriptome data of 1000 AD and cognitively normal individuals from ROS/MAP, Mayo clinic and Mount Sinai Brain bank cohort and identified differentially expressed genes in SM pathway. We also used the information derived from metabolic networks of brain and carried out metabolic flux analysis to identify reactions and genes that are altered in SM pathway. We performed multimodal neuroimaging analysis and identified genetic variants linked to genes in SM pathway and associated with AD pathogenesis. Lipidomic analyses and genetic association studies were also carried out to study the SM pathway dysregulation in AD. Result: The multi‐omics analysis suggested increase in ceramide and depletion of sphingosine‐1‐phosphate that alters sphingolipid homeostasis in AD. To test our hypothesis, we used APP/PS1 mice and modulated S1P activity by targeting the receptor using Fingolimod, an FDA‐approved drug for multiple sclerosis. Our study showed that altering S1P signaling rescues cognitive deficits in the treated mice and Fingolimod and other modulators of S1P metabolism might be potent drug repositioning candidates for AD. Conclusion: This study demonstrates the power of using diverse types of data to inform about underlying mechanisms of AD pathogenesis. It also raises the possibility of employing powerful new approaches to the repurposing of existing drugs used for treatment of other diseases.