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dc.contributor.authorProitsi, Petroula
dc.contributor.authorLupton, Michelle K
dc.contributor.authorVelayudhan, Latha
dc.contributor.authorNewhouse, Stephen
dc.contributor.authorFogh, Isabella
dc.contributor.authorTsolaki, Magda
dc.contributor.authorDaniilidou, Makrina
dc.contributor.authorPritchard, Megan
dc.contributor.authorKloszewska, Iwona
dc.contributor.authorSoininen, Hilkka
dc.contributor.authorMecocci, Patrizia
dc.contributor.authorVellas, Bruno
dc.contributor.authorAlzheimer's Disease Neuroimaging Initiative
dc.contributor.authorWilliams, Julie
dc.contributor.authorGERAD1 Consortium
dc.contributor.authorStewart, Robert
dc.contributor.authorSham, Pak
dc.contributor.authorLovestone, Simon
dc.contributor.authorPowell, John F
dc.description.abstractBACKGROUND: Although altered lipid metabolism has been extensively implicated in the pathogenesis of Alzheimer disease (AD) through cell biological, epidemiological, and genetic studies, the molecular mechanisms linking cholesterol and AD pathology are still not well understood and contradictory results have been reported. We have used a Mendelian randomization approach to dissect the causal nature of the association between circulating lipid levels and late onset AD (LOAD) and test the hypothesis that genetically raised lipid levels increase the risk of LOAD. METHODS AND FINDINGS: We included 3,914 patients with LOAD, 1,675 older individuals without LOAD, and 4,989 individuals from the general population from six genome wide studies drawn from a white population (total n=10,578). We constructed weighted genotype risk scores (GRSs) for four blood lipid phenotypes (high-density lipoprotein cholesterol [HDL-c], low-density lipoprotein cholesterol [LDL-c], triglycerides, and total cholesterol) using well-established SNPs in 157 loci for blood lipids reported by Willer and colleagues (2013). Both full GRSs using all SNPs associated with each trait at p<5×10-8 and trait specific scores using SNPs associated exclusively with each trait at p<5 × 10-8 were developed. We used logistic regression to investigate whether the GRSs were associated with LOAD in each study and results were combined together by meta-analysis. We found no association between any of the full GRSs and LOAD (meta-analysis results: odds ratio [OR]=1.005, 95% CI 0.82-1.24, p = 0.962 per 1 unit increase in HDL-c; OR=0.901, 95% CI 0.65-1.25, p=0.530 per 1 unit increase in LDL-c; OR=1.104, 95% CI 0.89-1.37, p=0.362 per 1 unit increase in triglycerides; and OR=0.954, 95% CI 0.76-1.21, p=0.688 per 1 unit increase in total cholesterol). Results for the trait specific scores were similar; however, the trait specific scores explained much smaller phenotypic variance. CONCLUSIONS: Genetic predisposition to increased blood cholesterol and triglyceride lipid levels is not associated with elevated LOAD risk. The observed epidemiological associations between abnormal lipid levels and LOAD risk could therefore be attributed to the result of biological pleiotropy or could be secondary to LOAD. Limitations of this study include the small proportion of lipid variance explained by the GRS, biases in case-control ascertainment, and the limitations implicit to Mendelian randomization studies. Future studies should focus on larger LOAD datasets with longitudinal sampled peripheral lipid measures and other markers of lipid metabolism, which have been shown to be altered in LOAD. Please see later in the article for the Editors' Summary.
dc.publisherPublic Library of Science (PLoS)
dc.rightsAttribution 4.0 International
dc.subjectAlzheimer's Disease Neuroimaging Initiative
dc.subjectGERAD1 Consortium
dc.subjectAlzheimer Disease
dc.subjectGenetic Predisposition to Disease
dc.subjectRisk Factors
dc.subjectLongitudinal Studies
dc.subjectPolymorphism, Single Nucleotide
dc.subjectAged, 80 and over
dc.subjectGenome-Wide Association Study
dc.subjectMendelian Randomization Analysis
dc.titleGenetic predisposition to increased blood cholesterol and triglyceride lipid levels and risk of Alzheimer disease: a Mendelian randomization analysis.
prism.publicationNamePLoS Med
dc.contributor.orcidProitsi, Petroula [0000-0002-2553-6974]
dc.contributor.orcidVelayudhan, Latha [0000-0002-7712-930X]
dc.contributor.orcidNewhouse, Stephen [0000-0002-1843-9842]
dc.contributor.orcidFogh, Isabella [0000-0002-6266-8933]
dc.contributor.orcidTsolaki, Magda [0000-0002-2072-8010]
dc.contributor.orcidPritchard, Megan [0000-0001-8872-3614]
dc.contributor.orcidMecocci, Patrizia [0000-0003-0729-5246]
dc.contributor.orcidWilliams, Julie [0000-0002-4069-0259]
dc.contributor.orcidStewart, Robert [0000-0002-4435-6397]
dc.contributor.orcidLovestone, Simon [0000-0003-0473-4565]
rioxxterms.typeJournal Article/Review
pubs.funder-project-idWellcome Trust (100140/Z/12/Z)
pubs.funder-project-idMedical Research Council (MR/L023784/1)

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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International