Blood pressure variability and medial temporal atrophy in apolipoprotein ϵ4 carriers
Tóm tắt
Blood pressure variability is an emerging risk factor for dementia but relationships with markers of neurodegeneration and Alzheimer’s disease risk are understudied. We investigated blood pressure variability over one year and follow-up medial temporal brain volume change in apolipoprotein ϵ4 carriers and non-carriers, and in those with and without Alzheimer’s disease biomarker abnormality. 1051 Alzheimer’s Disease Neuroimaging Initiative participants without history of dementia or stroke underwent 3–4 blood pressure measurements over 12 months and ≥ 1 MRI thereafter. A subset (n = 252) underwent lumbar puncture to determine Alzheimer’s disease cerebral spinal fluid amyloid-beta and phosphorylated tau biomarker abnormality. Blood pressure variability over 12 months was calculated as variability independent of mean. Longitudinal hippocampal and entorhinal cortex volume data were extracted from serial brain MRI scans obtained after the final blood pressure measurement. Apolipoprotein ϵ4 carrier status was defined as at least one ϵ4 allele. Bayesian growth modelling revealed a significant interaction of blood pressure variability by ϵ4 by time on hippocampal (ß: -2.61 [95% credible interval -3.02, -2.12]) and entorhinal cortex (ß: -1.47 [95% credible interval -1.71, -1.17]) volume decline. A similar pattern emerged in subsets with Alzheimer’s disease pathophysiology (i.e., abnormal levels of both amyloid-beta and phosphorylated tau). Findings suggest that elevated blood pressure variability is related to medial temporal volume loss specifically in ϵ4 carriers, and in those with Alzheimer’s disease biomarker abnormality. Findings could implicate blood pressure variability in medial temporal neurodegeneration observed in older ϵ4 carriers and those with prodromal Alzheimer’s disease.
Tài liệu tham khảo
Barnes, D. E., & Yaffe, K. (2011). The projected effect of risk factor reduction on Alzheimer’s disease prevalence. The Lancet Neurology, 10(9), 819–828. https://doi.org/10.1016/S1474-4422(11)70072-2
Bittner, T., Zetterberg, H., Teunissen, C. E., Ostlund, R. E., Militello, M., Andreasson, U., et al. (2016). Technical performance of a novel, fully automated electrochemiluminescence immunoassay for the quantitation of β-amyloid (1–42) in human cerebrospinal fluid. Alzheimer’s and Dementia. https://doi.org/10.1016/j.jalz.2015.09.009
Brickman, A. M., Reitz, C., Luchsinger, J. A., Manly, J. J., Schupf, N., Muraskin, J., et al. (2010). Long-term blood pressure fluctuation and cerebrovascular disease in an elderly cohort. Archives of Neurology, 67(5), 564–569. https://doi.org/10.1001/archneurol.2010.70
Brown, E. M., Pierce, M. E., Clark, D. C., Fischl, B. R., Iglesias, J. E., Milberg, W. P., et al. (2020). Test-retest reliability of FreeSurfer automated hippocampal subfield segmentation within and across scanners. NeuroImage, 210, 116563. https://doi.org/10.1016/j.neuroimage.2020.116563
Burggren, A. C., Zeineh, M. M., Ekstrom, A. D., Braskie, M. N., Thompson, P. M., Small, G. W., & Bookheimer, S. Y. (2008). Reduced cortical thickness in hippocampal sub-regions among cognitively normal apolipoprotein E e4 carriers. NeuroImage, 41(4), 1177–1183. https://doi.org/10.1016/j.neuroimage.2008.03.039.Reduced
Cho, N., Hoshide, S., Nishizawa, M., Fujiwara, T., & Kario, K. (2018). Relationship between blood pressure variability and cognitive function in elderly patients with good blood pressure control. American Journal of Hypertension, 31(3), 293–298. https://doi.org/10.1093/ajh/hpx155
Cohen, R. M., Small, C., Lalonde, F., Friz, J., & Sunderland, T. (2001). Effect of apolipoprotein E genotype on hippocampal volume loss in aging healthy women. Neurology, 57(12), 2223 LP – 2228. https://doi.org/10.1212/WNL.57.12.2223
Corder, E. H., Saunders, A. M., Strittmatter, W. J., Schmechel, D. E., Gaskell, P. C., Small, G. W., et al. (1993). Gene Dose of Apolipoprotein E Type 4 Allele and the Risk of Alzheimer ’ s Disease in Late Onset Families Published by : American Association for the Advancement of Science Stable URL : http://www.jstor.org/stable/2882127. Science, 261(5123), 921–923.
D’Agostino, R. B., Wolf, P. A., Belanger, A. J., & Kannel, W. B. (1994). Stroke risk profile: Adjustment for antihypertensive medication: The Framingham Study. Stroke, 25(1), 40–43. https://doi.org/10.1161/01.STR.25.1.40
de Heus, R. A. A., Olde Rikkert, M. G. M., Tully, P. J., Lawlor, B. A., & Claassen, J. A. H. R. (2019). Blood pressure variability and progression of clinical Alzheimer disease. Hypertension, 74, 1172–1180. https://doi.org/10.1161/HYPERTENSIONAHA.119.13664
Fischl, B. (2012). FreeSurfer. Neuroimage, 62(2), 774–781. https://doi.org/10.1016/j.neuroimage.2012.01.021
Hansson, O., Seibyl, J., Stomrud, E., Zetterberg, H., Trojanowski, J. Q., Bittner, T., et al. (2018). CSF biomarkers of Alzheimer’s disease concord with amyloid-β PET and predict clinical progression: A study of fully automated immunoassays in BioFINDER and ADNI cohorts. Alzheimer’s and Dementia, 14(11), 1470–1481. https://doi.org/10.1016/j.jalz.2018.01.010
Iadecola, C. (2004). Neurovascular regulation in the normal brain and in Alzheimer’s disease. Nature Reviews Neuroscience, 5(5), 347–360. https://doi.org/10.1038/nrn1387
Jack, C. R., Bennett, D. A., Blennow, K., Carrillo, M. C., Dunn, B., Haeberlein, S. B., et al. (2018). NIA-AA research framework: Toward a biological definition of Alzheimer’s disease. Alzheimer’s and Dementia, 14(4), 535–562. https://doi.org/10.1016/j.jalz.2018.02.018
Jak, A. J., Houston, W. S., Nagel, B. J., Corey-Bloom, J., & Bondi, M. W. (2007). Differential cross-sectional and longitudinal impact of APOE genotype on hippocampal volumes in nondemented older adults. Dementia and Geriatric Cognitive Disorders, 23(6), 382–389. https://doi.org/10.1159/000101340
Kitamura, J., Nagai, M., Ueno, H., Ohshita, T., Kikumoto, M., Toko, M., et al. (2020). The insular cortex, Alzheimer disease pathology, and their effects on blood pressure variability. Alzheimer Disease and Associated Disorders, 34(3), 282–291. https://doi.org/10.1097/WAD.0000000000000340
Lane, C. A., Barnes, J., Nicholas, J. M., Sudre, C. H., Cash, D. M., Parker, T. D., et al. (2019). Associations between blood pressure across adulthood and late-life brain structure and pathology in the neuroscience substudy of the 1946 British birth cohort (Insight 46): An epidemiological study. The Lancet Neurology, 18(10), 942–952. https://doi.org/10.1016/S1474-4422(19)30228-5
Lattanzi, S., Luzzi, S., Provinciali, L., & Silvestrini, M. (2014a). Blood pressure variability predicts cognitive decline in Alzheimer’s disease patients. Neurobiology of Aging, 35(10), 2282–2287. https://doi.org/10.1016/j.neurobiolaging.2014.04.023
Lattanzi, S., Luzzi, S., Provinciali, L., & Silvestrini, M. (2015). Blood pressure variability in alzheimer’s disease and frontotemporal dementia: The effect on the rate of cognitive decline. Journal of Alzheimer’s Disease, 45(2), 387–394. https://doi.org/10.3233/JAD-142532
Lattanzi, S., Vernieri, F., & Silvestrini, M. (2018). Blood pressure variability and neurocognitive functioning. Journal of Clinical Hypertension, 20(4), 645–647. https://doi.org/10.1111/jch.13232
Lattanzi, S., Viticchi, G., Falsetti, L., Buratti, L., Luzzi, S., Provinciali, L., & Silvestrini, M. (2014b). Visit-to-visit blood pressure variability in Alzheimer disease. Alzheimer Disease and Associated Disorders, 28(4), 347–351. https://doi.org/10.1097/WAD.0000000000000040
Ma, Y., Song, A., Viswanathan, A., Blacker, D., Vernooij, M. W., Hofman, A., & Papatheodorou, S. (2020a). Blood pressure variability and cerebral small vessel disease: A systematic review and meta-analysis of population-based cohorts. Stroke, 51(1), 82–89. https://doi.org/10.1161/STROKEAHA.119.026739
Ma, Y., Tully, P. J., Hofman, A., & Tzourio, C. (2020b). Blood pressure variability and dementia: A state-of-the art review. American Journal of Hypertension, 33(12), 1059–1066. https://doi.org/10.1093/ajh/hpaa119
Ma, Y., Yilmaz, P., Bos, D., Blacker, D., Viswanathan, A., Ikram, M. A., et al. (2020c). Blood pressure variation and subclinical brain disease. Journal of the American College of Cardiology, 75(19), 2387–2399. https://doi.org/10.1016/j.jacc.2020.03.043
Moffat, S. D., Szekely, C. A., Zonderman, A. B., Kabani, N. J., & Resnick, S. M. (2000). Longitudinal change in hippocampal volume as a function of apolipoprotein E genotype. Neurology, 55(1), 134 LP – 136. https://doi.org/10.1212/WNL.55.1.134
Montagne, A., Nation, D. A., Sagare, A. P., Barisano, G., Sweeney, M. D., Chakhoyan, A., et al. (2020). APOE4 leads to early blood-brain barrier dysfunction predicting human cognitive decline. Nature, 581(7806), 71–76. https://doi.org/10.1038/s41586-020-2247-3.APOE4
Nagai, M., Dote, K., Kato, M., Sasaki, S., Oda, N., Kagawa, E., et al. (2017). Visit-to-visit blood pressure variability and Alzheimer’s disease: Links and risks. Journal of Alzheimer’s Disease, 59(2), 515–526. https://doi.org/10.3233/JAD-161172
Nation, D. A., Edmonds, E. C., Bangen, K. J., Delano-Wood, L., Scanlon, B. K., Han, S. D., et al. (2015). Pulse pressure in relation to tau-mediated neurodegeneration, cerebral amyloidosis, and progression to dementia in very old adults. JAMA Neurology, 72(5), 546–553. https://doi.org/10.1001/jamaneurol.2014.4477
Nation, D. A., Sweeney, M. D., Montagne, A., Sagare, A. P., D’Orazio, L. M., Pachicano, M., et al. (2019). Blood-brain barrier breakdown is an early biomarker of human cognitive dysfunction. Nature Medicine, 25(2), 270–276. https://doi.org/10.1038/s41591-018-0297-y.Blood-brain
Palop, J. J., & Mucke, L. (2011). Amyloid-β induced neuronal dysfunction in Alzheimer’s disease: From synapses toward neural networks. Nature Neuroscience, 13(7), 812–818. https://doi.org/10.1038/nn.2583.Amyloid-
Petersen, R. C., Aisen, P. S., Beckett, L. A., Donohue, M. C., Gamst, A. C., Harvey, D. J., et al. (2010). Alzheimer’s disease neuroimaging initiative (ADNI): Clinical characterization. Neurology, 74(3), 201–209. https://doi.org/10.1212/WNL.0b013e3181cb3e25
R Core Team. (2018). R: A language and environment for statistical computing.
Reuter, M., Schmansky, N. J., Rosas, H. D., & Fischl, B. (2012). Within-subject template estimation for unbiased longitudinal image analysis. NeuroImage, 61(4), 1402–1418. https://doi.org/10.1016/j.neuroimage.2012.02.084
Rothwell, P. M., Howard, S. C., Dolan, E., O’Brien, E., Dobson, J. E., Dahlöf, B., et al. (2010). Prognostic significance of visit-to-visit variability, maximum systolic blood pressure, and episodic hypertension. The Lancet, 375(9718), 895–905. https://doi.org/10.1016/S0140-6736(10)60308-X
Rouch, L., Cestac, P., Sallerin, B., Piccoli, M., Benattar-Zibi, L., Bertin, P., et al. (2020). Visit-to-visit blood pressure variability is associated with cognitive decline and incident dementia: The S.AGES cohort. Hypertension, 76, 1280–1288. https://doi.org/10.1161/HYPERTENSIONAHA.119.14553
Sabayan, B., Wijsman, L. W., Foster-Dingley, J. C., Stott, D. J., Ford, I., Buckley, B. M., et al. (2013). Association of visit-to-visit variability in blood pressure with cognitive function in old age: Prospective cohort study. BMJ (Online), 347(7919). https://doi.org/10.1136/bmj.f4600
Saykin, A. J., Shen, L., Foroud, T. M., Potkin, S. G., Swaminathan, S., Kim, S., et al. (2010). Alzheimer’s disease neuroimaging Initiative biomarkers as quantitative phenotypes: Genetics core aims, progress, and plans. Alzheimer’s and Dementia, 6(3), 265–273. https://doi.org/10.1016/j.jalz.2010.03.013
Schneider, J. A., Arvanitakis, Z., Bang, W., & Bennett, D. A. (2007). Mixed brain pathologies account for most dementia cases in community-dwelling older persons. Neurology, 69, 2197–2204. https://doi.org/10.1212/01.wnl.0000307675.38908.39
Seibyl, J., Shaw, L. M., Blennow, K., Widmann, M., Corradini, V., Wahl, S., et al. (2017). Amyloid-PET concordance of Elecsys® CSF biomarker immunoassays for Alzheimer’s disease. Alzheimer’s & Dementia, 13(7), P199–P200. https://doi.org/10.1016/j.jalz.2017.07.062
Shaw, L. M., Fields, L., Korecka, M., Waligórska, T., Trojanowski, J. Q., Allegranza, D., et al. (2016). Method comparison of AB(1–42) measured in human cerebrospinal fluid samples by liquid chromatography-tandem mass spectrometry, the INNO-BIA AlzBio3 assay, and the Elecsys® B-Amyloid(1–42) assay. Alzheimer’s & Dementia, 12(7), P668. https://doi.org/10.1016/j.jalz.2016.06.1513
Shaw, L. M., Waligorska, T., Fields, L., Korecka, M., Figurski, M., Trojanowski, J. Q., et al. (2018). Derivation of cutoffs for the Elecsys® amyloid β (1–42) assay in Alzheimer’s disease. Alzheimer’s and Dementia: Diagnosis, Assessment and Disease Monitoring, 10, 698–705. https://doi.org/10.1016/j.dadm.2018.07.002
Sible, I. J., Bangen, K. J., Blanken, A. E., Ho, J. K., & Nation, D. A. (2021a). Antemortem visit-to-visit blood pressure variability predicts cerebrovascular lesion burden in autopsy-confirmed Alzheimer’s disease. Journal of Alzheimer’s Disease.
Sible, I. J., Nation, D. A., & Alzheimer’s Disease Neuroimaging Initiative. (2020). Long-term blood pressure variability across the clinical and biomarker spectrum of Alzheimer’s disease. Journal of Alzheimer’s Disease, 77(4), 1655–1669. https://doi.org/10.3233/JAD-200221
Sible, I. J., Yew, B., Dutt, S., Bangen, K. J., Li, Y., Nation, D. A., & Alzheimer’s Disease Neuroimaging Initiative. . (2021b). Visit-to-visit blood pressure variability and regional cerebral perfusion decline in older adults. Neurobiology of Aging, 105, 57–63. https://doi.org/10.1016/j.neurobiolaging.2021.04.009
Tully, P. J., Yano, Y., Launer, L. J., Kario, K., Nagai, M., Mooijaart, S. P., et al. (2020). Association between blood pressure variability and cerebral small-vessel disease: A systematic review and meta-analysis. Journal of the American Heart Association, 9(1). https://doi.org/10.1161/JAHA.119.013841
Vikner, T., Eklund, A., Karalija, N., Malm, J., Riklund, K., Lindenberger, U., et al. (2021). Cerebral arterial pulsatility is linked to hippocampal microvascular function and episodic memory in healthy older adults. Journal of Cerebral Blood Flow and Metabolism. https://doi.org/10.1177/0271678X20980652
Webb, A. J., Fischer, U., Mehta, Z., & Rothwell, P. M. (2010). Effects of antihypertensive-drug class on interindividual variation in blood pressure and risk of stroke: A systematic review and meta-analysis. The Lancet, 375(9718), 906–915. https://doi.org/10.1016/S0140-6736(10)60235-8
Winder, N. R., Reeve, E. H., & Walker, A. E. (2021). Large artery stiffness and brain health: Insights from animal models. American Journal of Physiology - Heart and Circulatory Physiology, 320(1), H424–H431. https://doi.org/10.1152/AJPHEART.00696.2020
Wright, J. T., Williamson, J. D., Whelton, P. K., Snyder, J. K., Sink, K. M., Rocco, M. V., et al. (2015). A randomized trial of intensive versus standard blood-pressure control. New England Journal of Medicine, 373(22), 2103–2116. https://doi.org/10.1056/NEJMoa1511939
Yaffe, K. (2019). Prevention of cognitive impairment with intensive systolic blood pressure control. JAMA, 321(6), 548–549.
Yano, Y. (2017). Visit-to-visit blood pressure variability - What is the current challenge? American Journal of Hypertension, 30(2), 112–114. https://doi.org/10.1093/ajh/hpw124
Yoo, J. E., Shin, D. W., Han, K., Kim, D., Lee, S. P., Jeong, S. M., et al. (2020). Blood pressure variability and the risk of dementia: A nationwide cohort study. Hypertension, 75(4), 982–990. https://doi.org/10.1161/HYPERTENSIONAHA.119.14033
Zlokovic, B. V. (2011). Neurovascular pathways to neurodegeneration in Alzheimer’s disease and other disorders. Nature Reviews Neuroscience, 12(12), 723–738. https://doi.org/10.1038/nrn3114