PLoS Medicine (Sep 2014)

Genetic predisposition to increased blood cholesterol and triglyceride lipid levels and risk of Alzheimer disease: a Mendelian randomization analysis.

  • Petroula Proitsi,
  • Michelle K Lupton,
  • Latha Velayudhan,
  • Stephen Newhouse,
  • Isabella Fogh,
  • Magda Tsolaki,
  • Makrina Daniilidou,
  • Megan Pritchard,
  • Iwona Kloszewska,
  • Hilkka Soininen,
  • Patrizia Mecocci,
  • Bruno Vellas,
  • Alzheimer's Disease Neuroimaging Initiative,
  • Julie Williams,
  • GERAD1 Consortium,
  • Robert Stewart,
  • Pak Sham,
  • Simon Lovestone,
  • John F Powell

DOI
https://doi.org/10.1371/journal.pmed.1001713
Journal volume & issue
Vol. 11, no. 9
p. e1001713

Abstract

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BackgroundAlthough 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 findingsWe 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 pConclusionsGenetic 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.