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O4-05-05: Genetic influences on metabolite levels in Alzheimer's disease

Proitsi, P., Min, K., Whiley, L.ORCID: 0000-0002-9088-4799, Newhouse, S., Johnston, C., Soininen, H., Kloszewska, I., Mecocci, P., Tsolaki, M., Vellas, B., Sham, P., Lovestone, S., Powell, J.F., Quigley, C.L. and Dobson, R.J.B. (2015) O4-05-05: Genetic influences on metabolite levels in Alzheimer's disease. Alzheimer's & Dementia, 11 (7S_Part_6). P279-P280.

Free to read: https://doi.org/10.1016/j.jalz.2015.07.373
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Abstract

Background

A better understanding of the biological mechanisms underlying Alzheimer's Disease (AD) is required. Studies have now demonstrated the promise of using associations with blood metabolites, as functional intermediate phenotypes in biomedical and pharmaceutical research1. Studies have further identified genetic variants in metabolism‐related genes that lead to clearly differentiated metabolic phenotypes, ‘genetically influenced metabotypes’ (GIMs), providing new insights to the role of inherited variation in blood metabolic diversity2. Recently, a number of blood metabolomic studies including ours have highlighted the role of lipid compounds in AD3‐4. The aim of this study was to investigate genetic influences on human plasma metabolites in >400 AD patients and healthy controls to survey regions of the genome associated with metabolic traits and identify AD specific associations.

Methods

We performed a comprehensive untargeted lipidomic analysis, using Ultra‐Performance Liquid Chromatography/Mass Spectrometry generating >2000 features and a Genome Wide Association (GWA) study followed by imputation. Linear regression analyses were run to identify genetic influences on each metabolic feature.

Results

We identified significant associations, after Bonferonni correction, between loci involved in lipid metabolism and a number of metabolite molecules. The most significantly associated SNP in our analysis was with a SNP on the FADS1 gene cluster, the top SNP identified by Shin et al2. One of the metabolites associated with the FADS locus has been previously identified by our group to be associated with AD in the same cohort4. Additional associations were identified with loci involved in AD risk.

Conclusions

These findings need to be replicated in larger well‐phenotyped cohorts, and the causal relationship between metabolites and AD to be explored. References: 1. Suhre K et al. Human metabolic individuality in biomedical and pharmaceutical research. Nature 2011. 2. Shin SY et al. An atlas of genetic influences on human blood metabolites. Nat Genet 2014. 3. Whiley L et al. Evidence of altered phosphatidylcholine metabolism in Alzheimer's disease. Neurobiol Aging 2014. 4. Proitsi P et al. Plasma lipidomics analysis finds long chain cholesteryl esters to be associated with Alzheimer's disease. Trans Psy 2015.

Item Type: Journal Article
Publisher: Elsevier Inc.
Copyright: © 2015 The Alzheimer's Association
Other Information: Podium presentation: Wednesday July 22, 2015
URI: http://researchrepository.murdoch.edu.au/id/eprint/59504
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