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Genetic Predisposition to Increased Blood Cholesterol and Triglyceride Lipid Levels and Risk of Alzheimer Disease: A Mendelian Randomization Analysis


Background:
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


Vyšlo v časopise: Genetic Predisposition to Increased Blood Cholesterol and Triglyceride Lipid Levels and Risk of Alzheimer Disease: A Mendelian Randomization Analysis. PLoS Med 11(9): e32767. doi:10.1371/journal.pmed.1001713
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pmed.1001713

Souhrn

Background:
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


Zdroje

1. ReitzC (2013) Dyslipidemia and the risk of Alzheimer's disease. Curr Atheroscler Rep 15: 307.

2. ReissAB (2005) Cholesterol and apolipoprotein E in Alzheimer's disease. Am J Alzheimers Dis Other Demen 20: 91–96.

3. DiPG, KimTW (2011) Linking lipids to Alzheimer's disease: cholesterol and beyond. Nat Rev Neurosci 12: 284–296.

4. HaroldD, AbrahamR, HollingworthP, SimsR, GerrishA, et al. (2009) Genome-wide association study identifies variants at CLU and PICALM associated with Alzheimer's disease. Nat Genet 41: 1088–1093.

5. HollingworthP, HaroldD, SimsR, GerrishA, LambertJC, et al. (2011) Common variants at ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer's disease. Nat Genet 43: 429–435.

6. LambertJC, ZelenikaD, HiltunenM, ChourakiV, CombarrosO, et al. (2011) Evidence of the association of BIN1 and PICALM with the AD risk in contrasting European populations. Neurobiol Aging 32: 756–5.

7. WhitmerRA, SidneyS, SelbyJ, JohnstonSC, YaffeK (2005) Midlife cardiovascular risk factors and risk of dementia in late life. Neurology 64: 277–281.

8. KivipeltoM, HelkalaEL, LaaksoMP, HanninenT, HallikainenM, et al. (2002) Apolipoprotein E epsilon4 allele, elevated midlife total cholesterol level, and high midlife systolic blood pressure are independent risk factors for late-life Alzheimer disease. Ann Intern Med 137: 149–155.

9. SolomonA, KivipeltoM, WolozinB, ZhouJ, WhitmerRA (2009) Midlife serum cholesterol and increased risk of Alzheimer's and vascular dementia three decades later. Dement Geriatr Cogn Disord 28: 75–80.

10. GreenRC, McNagnySE, JayakumarP, CupplesLA, BenkeK, et al. (2006) Statin use and the risk of Alzheimer's disease: the MIRAGE study. Alzheimers Dement 2: 96–103.

11. DufouilC, RichardF, FievetN, DartiguesJF, RitchieK, et al. (2005) APOE genotype, cholesterol level, lipid-lowering treatment, and dementia: the Three-City Study. Neurology 64: 1531–1538.

12. BeydounMA, Beason-HeldLL, Kitner-TrioloMH, BeydounHA, FerrucciL, et al. (2011) Statins and serum cholesterol's associations with incident dementia and mild cognitive impairment. J Epidemiol Community Health 65: 949–957.

13. MielkeMM, ZandiPP, ShaoH, WaernM, OstlingS, et al. (2010) The 32-year relationship between cholesterol and dementia from midlife to late life. Neurology 75: 1888–1895.

14. TanZS, SeshadriS, BeiserA, WilsonPW, KielDP, et al. (2003) Plasma total cholesterol level as a risk factor for Alzheimer disease: the Framingham Study. Arch Intern Med 163: 1053–1057.

15. StewartR, WhiteLR, XueQL, LaunerLJ (2007) Twenty-six-year change in total cholesterol levels and incident dementia: the Honolulu-Asia Aging Study. Arch Neurol 64: 103–107.

16. MRC/BHF Heart Protection Study of cholesterol lowering with simvastatin in 20,536 high-risk individuals: a randomised placebo-controlled trial. Lancet 360: 7–22.

17. FeldmanHH, DoodyRS, KivipeltoM, SparksDL, WatersDD, et al. (2010) Randomized controlled trial of atorvastatin in mild to moderate Alzheimer disease: LEADe. Neurology 74: 956–964.

18. JonesRW, KivipeltoM, FeldmanH, SparksL, DoodyR, et al. (2008) The Atorvastatin/Donepezil in Alzheimer's Disease Study (LEADe): design and baseline characteristics. Alzheimers Dement 4: 145–153.

19. SanoM, BellKL, GalaskoD, GalvinJE, ThomasRG, et al. (2011) A randomized, double-blind, placebo-controlled trial of simvastatin to treat Alzheimer disease. Neurology 77: 556–563.

20. WillerCJ, SchmidtEM, SenguptaS, PelosoGM, GustafssonS, et al. (2013) Discovery and refinement of loci associated with lipid levels. Nat Genet 45: 1274–1283.

21. LovestoneS, FrancisP, StrandgaardK (2007) Biomarkers for disease modification trials–the innovative medicines initiative and AddNeuroMed. J Nutr Health Aging 11: 359–361.

22. McKhannG, DrachmanD, FolsteinM, KatzmanR, PriceD, et al. (1984) Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease. Neurology 34: 939–944.

23. ClaytonDG, WalkerNM, SmythDJ, PaskR, CooperJD, et al. (2005) Population structure, differential bias and genomic control in a large-scale, case-control association study. Nat Genet 37: 1243–1246.

24. MoskvinaV, CraddockN, HolmansP, OwenMJ, O'DonovanMC (2006) Effects of differential genotyping error rate on the type I error probability of case-control studies. Hum Hered 61: 55–64.

25. PurcellS, NealeB, Todd-BrownK, ThomasL, FerreiraMA, et al. (2007) PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81: 559–575.

26. PattersonN, PriceAL, ReichD (2006) Population structure and eigenanalysis. PLoS Genet 2: e190.

27. WealeME (2010) Quality control for genome-wide association studies. Methods Mol Biol 628: 341–372.

28. HowieBN, DonnellyP, MarchiniJ (2009) A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet 5: e1000529.

29. JohnsonAD, HandsakerRE, PulitSL, NizzariMM, O'DonnellCJ, et al. (2008) SNAP: a web-based tool for identification and annotation of proxy SNPs using HapMap. Bioinformatics 24: 2938–2939.

30. ThomasDC, LawlorDA, ThompsonJR (2007) Re: Estimation of bias in nongenetic observational studies using “Mendelian triangulation” by Bautista, et al. Ann Epidemiol 17: 511–513.

31. PierceBL, BurgessS (2013) Efficient design for Mendelian randomization studies: subsample and 2-sample instrumental variable estimators. Am J Epidemiol 178: 1177–1184.

32. BurgessS, ButterworthA, ThompsonSG (2013) Mendelian randomization analysis with multiple genetic variants using summarized data. Genet Epidemiol 37: 658–665.

33. TeslovichTM, MusunuruK, SmithAV, EdmondsonAC, StylianouIM, et al. (2010) Biological, clinical and population relevance of 95 loci for blood lipids. Nature 466: 707–713.

34. ShepardsonNE, ShankarGM, SelkoeDJ (2011) Cholesterol level and statin use in Alzheimer disease: I. Review of epidemiological and preclinical studies. Arch Neurol 68: 1239–1244.

35. SolomonA, KareholtI, NganduT, WinbladB, NissinenA, et al. (2007) Serum cholesterol changes after midlife and late-life cognition: twenty-one-year follow-up study. Neurology 68: 751–756.

36. ReedB, VilleneuveS, MackW, DeCarliC, ChuiHC, et al. (2014) Associations between serum cholesterol levels and cerebral amyloidosis. JAMA Neurol 71: 195–200.

37. EbrahimS, DaveySG (2008) Mendelian randomization: can genetic epidemiology help redress the failures of observational epidemiology? Hum Genet 123: 15–33.

38. LawlorDA, HarbordRM, SterneJA, TimpsonN, DaveySG (2008) Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Stat Med 27: 1133–1163.

39. WaddingtonCH (1959) Canalization of development and genetic assimilation of acquired characters. Nature 183: 1654–1655.

40. DietschyJM, TurleySD (2001) Cholesterol metabolism in the brain. Curr Opin Lipidol 12: 105–112.

41. DuronE, HanonO (2008) Vascular risk factors, cognitive decline, and dementia. Vasc Health Risk Manag 4: 363–381.

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