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Author Notes:

Robert A. Scott Robert.Scott@mrc-epid.cam.ac.uk MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom

See publication for full list of author contributions.

See publication for full list of acknowledgements.

SDØ is supported by a grant from the Lundbeck Foundation.

PP is an Alzheimer’s Society Post-Doctoral Fellow. NJW is an NIHR Senior Investigator.

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.


Research Funding:

This study was supported by the Innovative Medicines Initiative Joint Undertaking under EMIF grant agreement n° 115372 (contributions from the European Union's Seventh Framework Programme (FP7/2007-2013) and EFPIA companies).

The work was further supported by the National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre and Dementia Unit at South London and Maudsley NHS Foundation Trust and [Institute of Psychiatry] King’s College London.

Funding for the EPIC-InterAct project was provided by the EU FP6 programme (grant number LSHM_CT_2006_037197).

ADGC funding: The National Institutes of Health, National Institute on Aging (NIH-NIA) supported this work through the following grants: ADGC, U01 AG032984, RC2 AG036528; NACC, U01 AG016976; NCRAD, U24 AG021886; NIA LOAD, U24 AG026395, U24 AG026390; Banner Sun Health Research Institute P30 AG019610; Boston University, P30 AG013846, U01 AG10483, R01 CA129769, R01 MH080295, R01 AG017173, R01 AG025259, R01AG33193; Columbia University, P50 AG008702, R37 AG015473; Duke University, P30 AG028377, AG05128; Emory University, AG025688; Group Health Research Institute, U01 AG06781, U01 HG004610, U01 HG006375; Indiana University, P30 AG10133; Johns Hopkins University, P50 AG005146, R01 AG020688; Massachusetts General Hospital, P50 AG005134; Mayo Clinic, P50 AG016574; Mount Sinai School of Medicine, P50 AG005138, P01 AG002219; New York University, P30 AG08051, MO1RR00096, UL1 RR029893, 5R01AG012101, 5R01AG022374, 5R01AG013616, 1RC2AG036502, 1R01AG035137; Northwestern University, P30 AG013854; Oregon Health & Science University, P30 AG008017, R01 AG026916; Rush University, P30 AG010161, R01 AG019085, R01 AG15819, R01 AG17917, R01 AG30146; TGen, R01 NS059873; University of Alabama at Birmingham, P50 AG016582, UL1RR02777; University of Arizona, R01 AG031581; University of California, Davis, P30 AG010129; University of California, Irvine, P50 AG016573, P50 AG016575, P50 AG016576, P50 AG016577; University of California, Los Angeles, P50 AG016570; University of California, San Diego, P50 AG005131; University of California, San Francisco, P50 AG023501, P01 AG019724; University of Kentucky, P30 AG028383, AG05144; University of Michigan, P50 AG008671; University of Pennsylvania, P30 AG010124; University of Pittsburgh, P50 AG005133, AG030653, AG041718; University of Southern California, P50 AG005142; University of Texas Southwestern, P30 AG012300; University of Miami, R01 AG027944, AG010491, AG027944, AG021547, AG019757; University of Washington, P50 AG005136; Vanderbilt University, R01 AG019085; and Washington University, P50 AG005681, P01 AG03991.

See publication for full funding statement.


  • Alzheimer Disease
  • Female
  • Genetic Predisposition to Disease
  • Humans
  • Male
  • Mendelian Randomization Analysis
  • Polymorphism, Single Nucleotide
  • Risk Factors

Associations between Potentially Modifiable Risk Factors and Alzheimer Disease: A Mendelian Randomization Study

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Journal Title:

PLoS Medicine


Volume 12, Number 6


, Pages e1001841-e1001841

Type of Work:

Article | Final Publisher PDF


Potentially modifiable risk factors including obesity, diabetes, hypertension, and smoking are associated with Alzheimer disease (AD) and represent promising targets for intervention. However, the causality of these associations is unclear. We sought to assess the causal nature of these associations using Mendelian randomization (MR). We used SNPs associated with each risk factor as instrumental variables in MR analyses. We considered type 2 diabetes (T2D, N SNPs = 49), fasting glucose (N SNPs = 36), insulin resistance (N SNPs = 10), body mass index (BMI, N SNPs = 32), total cholesterol (N SNPs = 73), HDL-cholesterol (N SNPs = 71), LDL-cholesterol (N SNPs = 57), triglycerides (N SNPs = 39), systolic blood pressure (SBP, N SNPs = 24), smoking initiation (N SNPs = 1), smoking quantity (N SNPs = 3), university completion (N SNPs = 2), and years of education (N SNPs = 1). We calculated MR estimates of associations between each exposure and AD risk using an inverse-variance weighted approach, with summary statistics of SNP–AD associations from the International Genomics of Alzheimer’s Project, comprising a total of 17,008 individuals with AD and 37,154 cognitively normal elderly controls. We found that genetically predicted higher SBP was associated with lower AD risk (odds ratio [OR] per standard deviation [15.4 mm Hg] of SBP [95% CI] : 0.75 [0.62–0.91]; p = 3.4 × 10 −3 ). Genetically predicted higher SBP was also associated with a higher probability of taking antihypertensive medication (p = 6.7 × 10 −8 ). Genetically predicted smoking quantity was associated with lower AD risk (OR per ten cigarettes per day [95% CI]: 0.67 [0.51–0.89] ; p = 6.5 × 10 −3 ), although we were unable to stratify by smoking history; genetically predicted smoking initiation was not associated with AD risk (OR = 0.70 [0.37, 1.33]; p = 0.28). We saw no evidence of causal associations between glycemic traits, T2D, BMI, or educational attainment and risk of AD (all p > 0.1). Potential limitations of this study include the small proportion of intermediate trait variance explained by genetic variants and other implicit limitations of MR analyses. Inherited lifetime exposure to higher SBP is associated with lower AD risk. These findings suggest that higher blood pressure—or some environmental exposure associated with higher blood pressure, such as use of antihypertensive medications—may reduce AD risk.

Copyright information:

© 2015 Østergaard et al.

This is an Open Access work distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).
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