Repurposing antihypertensive drugs for the prevention of Alzheimer’s disease: A mendelian randomization study
Open accessPublished version of a preprint
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.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
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)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Bowden, J., Davey Smith, G., & Burgess, S. (2015) · International Journal of Epidemiology · doi:10.1093/ije/dyv080 · Cited by 9,816 · see citing works
Davey Smith, G., & Ebrahim, S. (2003) · International Journal of Epidemiology · doi:10.1093/ije/dyg070 · Cited by 5,882 · see citing works
Meta-Analysis of 74,046 Individuals Identifies 11 New Susceptibility Loci for Alzheimer’s Disease
(EADI), E. A. D. I., Lambert, J.-C., (GERAD), G. A. E. R. I. A. D., Alzheimer's Disease Genetic Consortium (ADGC), (CHARGE), C. F. H. A. A. R. I. G. E., Ibrahim-Verbaas, C. A., Harold, D., Naj, A. C., Sims, R., Bellenguez, C., et al. (2013) · Nature Genetics · doi:10.1038/ng.2802 · Cited by 4,336 · see citing works
Triangulation in aetiological epidemiology
Lawlor, D. A., Tilling, K., & Davey Smith, G. (2017) · International Journal of Epidemiology · doi:10.1093/ije/dyw314 · Cited by 1,129 · see citing works
Østergaard, S. D., Mukherjee, S., Sharp, S. J., Proitsi, P., Lotta, L. A., Day, F., Perry, J. R. B., Boehme, K. L., Walter, S., Kauwe, J. S., et al. (2015) · PLOS Medicine · doi:10.1371/journal.pmed.1001841 · Cited by 203 · see citing works
Nilvadipine in mild to moderate Alzheimer disease: A randomised controlled trial
Lawlor, B., Segurado, R., Kennelly, S., Olde Rikkert, M. G. M., Howard, R., Pasquier, F., Börjesson-Hanson, A., Tsolaki, M., Lucca, U., Molloy, D. W., et al. (2018) · PLOS Medicine · doi:10.1371/journal.pmed.1002660 · Cited by 193 · see citing works
Flagged first, then by citations
Research works printed but not linked: 30
- [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]Corbett A, Pickett J, Burns A et al Drug repositioning for Alzheimer’s disease. Nat Rev Drug Discov 2012; 11: 833– 46. 23123941
- [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]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]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
- [7]Davey Smith G, Ebrahim S. Mendelian randomization: prospects, potentials, and limitations. Int J Epidemiol 2004; 33: 30– 42. 15075143
- [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
- [9]Lawlor DA. Commentary: Two-sample Mendelian randomization: opportunities and challenges. Int J Epidemiol 2016; 45: 908– 15. 27427429 PMC5005949
- [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
- [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
- [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
- [15]Kehoe PG, Miners S, Love S. Angiotensins in Alzheimer’s disease—friend or foe? Trends Neurosci 2009; 32: 619– 28. 19796831
- [16]Wright JW, Harding JW. Brain renin-angiotensin—a new look at an old system. Prog Neurobiol 2011; 95: 49– 67. 21777652
- [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
- [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
- [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
- [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
- [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
- [26]The 1000 Genomes Project Consortium. A global reference for human genetic variation. Nature 2015; 526: 68– 74. 26432245 PMC4750478
- [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
- [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.
- [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
- [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
- [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
- [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
- [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
- [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
- [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
- [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
- [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
Cited by
Sorted by citations
Sproviero, W., Winchester, L., Newby, D., Fernandes, M., Shi, L., Goodday, S. M., Prats-Uribe, A., Alhambra, D. P., Buckley, N. J., & Nevado-Holgado, A. J. (2021) · Biological Psychiatry · doi:10.1016/j.biopsych.2020.12.015 · Cited by 86 · see citing works
Korologou-Linden, R., Bhatta, L., Brumpton, B. M., Howe, L. D., Millard, L. A. C., Kolaric, K., Ben-Shlomo, Y., Williams, D. M., Smith, G. D., Anderson, E. L., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-32183-6 · Cited by 71 · see citing works
Self-citationDrug repurposing for Alzheimer’s disease from 2012–2022—a 10-year literature review
Grabowska, M. E., Huang, A., Wen, Z., Li, B., & Wei, W.-Q. (2023) · Frontiers in Pharmacology · doi:10.3389/fphar.2023.1257700 · Cited by 55 · see citing works
“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…”
BackgroundProgram, T. V. M. V., Bone, W. P., Siewert, K. M., Jha, A., Klarin, D., Damrauer, S. M., Chang, K.-M., Tsao, P. S., Assimes, T. L., Ritchie, M. D., et al. (2021) · Alzheimer's Research & Therapy · doi:10.1186/s13195-021-00773-z · Cited by 41 · see citing works
“In recent years, the relationship between ACE inhibitors and AD has been an active field of study and has resulted in two leading hypotheses of how ACE inhibitors may alter AD risk [34, 39].”
Background
- 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
- Publisher
- Oxford University Press (OUP)
- Published
- 2019-07-23
- Volume
- 49
- Issue
- 4
- Pages
- 1132-1140
- ISSN
- 0300-5771 (ISSN-L)
- 1464-3685
- PMC
- PMC7751008
- 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
- hybrid
- doi.org
- Licence
- 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review