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

• Published in: PLoS medicine Vol. 11; no. 9; p. e1001713
• Main Authors: Proitsi, Petroula, Lupton, Michelle K, Velayudhan, Latha, Newhouse, Stephen, Fogh, Isabella, Tsolaki, Magda, Daniilidou, Makrina, Pritchard, Megan, Kloszewska, Iwona, Soininen, Hilkka, Mecocci, Patrizia, Vellas, Bruno, Williams, Julie, Stewart, Robert, Sham, Pak, Lovestone, Simon, Powell, John F
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 01-09-2014; Public Library of Science (PLoS)
• Subjects: Aged; Aged, 80 and over; Alzheimer Disease - blood; Alzheimer Disease - diagnosis; Alzheimer Disease - genetics; Alzheimer's disease; Biology and Life Sciences; Blood cholesterol; Cholesterol; Cholesterol - blood; Cholesterol - genetics; Female; Genes; Genetic aspects; Genetic Predisposition to Disease - genetics; Genome-Wide Association Study - methods; Humans; Lipids; Longitudinal Studies; Low density lipoproteins; Male; Medical research; Medicine and Health Sciences; Mendelian Randomization Analysis - methods; Older people; Physiological aspects; Polymorphism, Single Nucleotide - genetics; Risk Factors; Single nucleotide polymorphisms; Studies; Triglycerides; Triglycerides - blood; Triglycerides - genetics; United Kingdom; Germany
• ISSN: 1549-1676; 1549-1277; 1549-1676
• DOI: 10.1371/journal.pmed.1001713

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.
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.
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.