Cited by 96Dementia and Cognitive Impairment ResearchGenetic Associations and EpidemiologyAlzheimer's disease research and treatments

Repurposing antihypertensive drugs for the prevention of Alzheimer’s disease: A mendelian randomization study

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Walker, Venexia M, Kehoe, Patrick G, Martin, Richard M, Davies, Neil M·2020·International Journal of Epidemiology

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Abstract

Background: Evidence concerning the potential repurposing of antihypertensives for Alzheimer’s disease prevention is inconclusive. We used Mendelian randomization, which can be more robust to confounding by indication and patient characteristics, to investigate the effects of lowering systolic blood pressure, via the protein targets of different antihypertensive drug classes, on Alzheimer’s disease. Methods: We used summary statistics from genome-wide association studies of systolic blood pressure and Alzheimer’s disease in a two-sample Mendelian randomization analysis. We identified single-nucleotide polymorphisms (SNPs) that mimic the action of antihypertensive protein targets and estimated the effect of lowering systolic blood pressure on Alzheimer’s disease in three ways: (i) combining the protein targets of antihypertensive drug classes, (ii) combining all protein targets and (iii) without consideration of the protein targets. Results: There was limited evidence that lowering systolic blood pressure, via the protein targets of antihypertensive drug classes, affected Alzheimer’s disease risk. For example, the protein targets of calcium channel blockers had an odds ratio (OR) per 10 mmHg lower systolic blood pressure of 1.53 [95% confidence interval (CI): 0.94 to 2.49; p = 0.09; SNPs = 17]. We also found limited evidence for an effect when combining all protein targets (OR per 10 mmHg lower systolic blood pressure: 1.14; 95% CI: 0.83 to 1.56; p = 0.41; SNPs = 59) and without consideration of the protein targets (OR per 10 mmHg lower systolic blood pressure: 1.04; 95% CI: 0.95 to 1.13; p = 0.45; SNPs = 153). Conclusions: Mendelian randomization suggests that lowering systolic blood pressure via the protein targets of antihypertensive drugs is unlikely to affect the risk of developing Alzheimer’s disease. Consequently, if specific antihypertensive drug classes do affect the risk of Alzheimer’s disease, they may not do so via systolic blood pressure.

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  • The drugs with evidence of little to no effect on AD risk included lipid-lowering agents (ezetimibe, mipomersen, and statins), antihypertensives, dimethyl fumarate, and drugs commonly used in treatment of rheumatoid arthritis (tofacitinib, tocilizumab, and TNF inhibitors).

    “These drugs included lipid-lowering agents (ezetimibe, mipomersen, and statins) (Williams et al., 2020), antihypertensives (Walker et al., 2020), dimethyl fumarate (approved for the treatment of multiple sclerosis) (Möhle et al., 2021), and drugs commonly used in treatment of rheumatoid arthritis (tofacitinib, tocilizumab, and TNF inhibitors) (Desai et al., 2022).”

    From Drug repurposing for Alzheimer’s disease from 2012–2022—a 10-year literature review (2023) · cites this paper as Walker et al., 2020

    The Results (‘Antihypertensive drug effect’) report little evidence for an overall effect on Alzheimer’s disease risk when the protein targets of antihypertensives were combined. But the ‘Drug class effects’ results identify exceptions, and the study’s limited evidence of an effect does not establish that antihypertensive drugs have little to no effect on risk. (LLM, conf=0.82)

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  1. [1]Calcoen D, Elias L, Yu X. What does it take to produce a breakthrough drug? Nat Rev Drug Discov 2015; 14: 161– 62. 25722234
  2. [2]Corbett A, Pickett J, Burns A et al Drug repositioning for Alzheimer’s disease. Nat Rev Drug Discov 2012; 11: 833– 46. 23123941
  3. [3]Appleby BS, Cummings JL. Discovering new treatments for Alzheimer’s disease by repurposing approved medications. Curr Top Med Chem 2013; 13: 2306– 27. 24059463
  4. [4]Larsson SC, Markus HS. Does treating vascular risk factors prevent dementia and Alzheimer’s disease? A systematic review and meta-analysis. JAD 2018; 64: 657– 68. 29914039
  5. [5]Walker VM, Davey Smith G, Davies NM, Martin RM. Mendelian randomization: a novel approach for the prediction of adverse drug events and drug repurposing opportunities. Int J Epidemiol 2017; 46: 2078– 89. 29040597 PMC5837479
  6. [7]Davey Smith G, Ebrahim S. Mendelian randomization: prospects, potentials, and limitations. Int J Epidemiol 2004; 33: 30– 42. 15075143
  7. [8]Davey Smith G, Hemani G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Hum Mol Genet 2014; 23: R89– 98. 25064373 PMC4170722
  8. [9]Lawlor DA. Commentary: Two-sample Mendelian randomization: opportunities and challenges. Int J Epidemiol 2016; 45: 908– 15. 27427429 PMC5005949
  9. [11]Larsson SC, Traylor M, Malik R, Dichgans M, Burgess S, Markus HS. Modifiable pathways in Alzheimer’s disease: Mendelian randomisation analysis. BMJ 2017; 359: j5375. 29212772 PMC5717765
  10. [12]Gill D, Georgakis MK, Koskeridis F et al Use of genetic variants related to antihypertensive drugs to inform on efficacy and side effects. Circulation 2019; CIRCULATIONAHA.118.038814. PMC6687408 31234639
  11. [14]Kehoe PG, Passmore PA. The renin-angiotensin system and antihypertensive drugs in Alzheimer’s disease: current standing of the angiotensin hypothesis? JAD 2012; 30(Suppl 2): S251– 68. 22330821
  12. [15]Kehoe PG, Miners S, Love S. Angiotensins in Alzheimer’s disease—friend or foe? Trends Neurosci 2009; 32: 619– 28. 19796831
  13. [16]Wright JW, Harding JW. Brain renin-angiotensin—a new look at an old system. Prog Neurobiol 2011; 95: 49– 67. 21777652
  14. [19]Allen NE, Sudlow C, Peakman T, Collins R, Biobank UK. UK Biobank data: come and get it. Sci Transl Med 2014; 6: 224ed4. 24553384
  15. [20]Fry A, Littlejohns TJ, Sudlow C et al Comparison of sociodemographic and health-related characteristics of UK Biobank participants with those of the general population. Am J Epidemiol 2017; 186: 1026– 34. 28641372 PMC5860371
  16. [23]Wishart DS, Feunang YD, Guo AC et al DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res 2018; 46: D1074– 82. 29126136 PMC5753335
  17. [24]GTEx Consortium, Analysts L, Laboratory DA & CC (LDACC), Management N program, Collection B, Pathology et al Genetic effects on gene expression across human tissues. Nature 2017; 550: 204– 13. 29022597 PMC5776756
  18. [25]Hemani G, Zheng J, Elsworth B et al The MR-Base platform supports systematic causal inference across the human phenome. eLife 2018; 7: e34408. 29846171 PMC5976434
  19. [26]The 1000 Genomes Project Consortium. A global reference for human genetic variation. Nature 2015; 526: 68– 74. 26432245 PMC4750478
  20. [27]Lawlor DA, Harbord RM, Sterne JAC, Timpson N, Davey Smith G. Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Statist Med 2008; 27: 1133– 63. 17886233
  21. [28]Burgess S, Bowden J, Integrating summarized data from multiple genetic variants in Mendelian randomization: bias and coverage properties of inverse-variance weighted methods. arXiv 2015: 04486.
  22. [29]Burgess S, Butterworth A, Thompson SG. Mendelian randomization analysis with multiple genetic variants using summarized data. Genet Epidemiol 2013; 37: 658– 65. 24114802 PMC4377079
  23. [30]Law MR, Wald NJ, Morris JK, Jordan RE. Value of low dose combination treatment with blood pressure lowering drugs: analysis of 354 randomised trials. BMJ 2003; 326: 1427. 12829555 PMC162261
  24. [31]Swerdlow DI, Kuchenbaecker KB, Shah S et al Selecting instruments for Mendelian randomization in the wake of genome-wide association studies. Int J Epidemiol 2016; 45: 1600– 16. 27342221 PMC5100611
  25. [34]Yasar S, Xia J, Yao W et al Antihypertensive drugs decrease risk of Alzheimer disease: Ginkgo Evaluation of Memory Study. Neurology 2013; 81: 896– 903. 23911756 PMC3885216
  26. [35]Rollin-Sillaire A, Breuilh L, Salleron J et al Reasons that prevent the inclusion of Alzheimer’s disease patients in clinical trials. Br J Clin Pharmacol 2013; 75: 1089– 97. 22891847 PMC3612727
  27. [36]Schneider LS. The potential and limits for clinical trials for early Alzheimer’s disease and some recommendations. J Nutr Health Aging 2010; 14: 295– 98. 20305999 PMC3923577
  28. [38]The SPRINT MIND Investigators for the SPRINT Research Group, Williamson JD, Pajewski NM, Auchus AP, Bryan RN, Chelune G et al Effect of intensive vs standard blood pressure control on probable dementia: a randomized clinical trial. JAMA 2019; 321: 553. 30688979 PMC6439590
  29. [39]Holmes MV, Ala-Korpela M, Davey Smith G. Mendelian randomization in cardiometabolic disease: challenges in evaluating causality. Nat Rev Cardiol 2017; 14: 577– 90. 28569269 PMC5600813
  30. [40]Hospers GP, Smulders YM, Maier AB, Deeg DJ, Muller M. Relation between blood pressure and mortality risk in an older population: role of chronological and biological age. J Intern Med 2015; 277: 488– 97. 25041041

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Authors
Walker, V. M., Kehoe, P. G., Martin, R. M., & Davies, N. M.
Affiliations
University of Bristol (GB)
Corresponding author
Walker, Venexia M
Venue
International Journal of Epidemiology
Published
2019-07-23
Volume
49
Issue
4
Pages
1132-1140
ISSN
  • 0300-5771 (ISSN-L)
  • 1464-3685
OpenAlex
W2951397190
Cited by
96
References
6
Citations by year
2026: 7 · 2025: 14 · 2024: 23 · 2023: 14 · 2022: 11 · 2021: 18 · 2020: 7 · 2019: 2
FWCI
7.45
Type
journal article
Language
en
Open access
Locations
  • International Journal of Epidemiology (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Bristol Research (University of Bristol) (publishedVersion, cc-by)
  • Explore Bristol Research (submittedVersion, cc-by)
Funders
  • Perros Trust
  • Integrative Epidemiology Unit
  • The Integrative Epidemiology Unit
  • Medical Research Council
  • University of Bristol (MC_UU_00011/1, MC_UU_00011/3)
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
Keywords
Alzheimer's disease, antihypertensive drugs, drug repurposing, systolic blood pressure, blood pressure reduction, calcium channel blockers, protein targets, Alzheimer's disease prevention, Mendelian randomization
MeSH terms
Alzheimer Disease, Antihypertensive Agents, Blood Pressure, Humans, Hypertension, Genome-Wide Association Study, Mendelian Randomization Analysis, Drug Repositioning

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