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Robinson AC, Bin Rizwan T, Davidson YS, Minshull J, Tinkler P, Payton A, Mann DMA, Roncaroli F. Self-Reported Late-Life Hypertension Is Associated with a Healthy Cognitive Status and Reduced Alzheimer's Disease Pathology Burden. J Alzheimers Dis 2024; 98:1457-1466. [PMID: 38552117 DOI: 10.3233/jad-231429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/20/2024]
Abstract
Background While mid-life hypertension represents a risk factor for the development of Alzheimer's disease (AD), the risk after the age of 65 is less certain. Establishing relationships between late life hypertension and the pathological changes of AD could be crucial in understanding the relevance of blood pressure as a risk factor for this disorder. Objective We investigated associations between self-reported late-life hypertension, cognitive status and AD pathology at death. The impact of antihypertensive medication was also examined. Methods Using the Cornell Medical Index questionnaire, we ascertained whether participants had ever reported hypertension. We also noted use of antihypertensive medication. The donated brains of 108 individuals were assessed for AD pathology using consensus guidelines. Statistical analysis aimed to elucidate relationships between hypertension and AD pathology. Results We found no associations between self-reported hypertension and cognitive impairment at death. However, those with hypertension were significantly more likely to exhibit lower levels of AD pathology as measured by Thal phase, Braak stage, CERAD score, and NIA-AA criteria-even after controlling for sex, level of education and presence of APOEɛ4 allele(s). No significant associations could be found when examining use of antihypertensive medications. Conclusions Our findings suggest that late-life hypertension is associated with less severe AD pathology. We postulate that AD pathology may be promoted by reduced cerebral blood flow.
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Affiliation(s)
- Andrew C Robinson
- Faculty of Biology, Medicine and Health, School of Biological Sciences, Division of Neuroscience, The University of Manchester, Salford Royal Hospital, Salford, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre (MAHSC), Manchester, UK
| | - Tawfique Bin Rizwan
- Faculty of Biology, Medicine and Health, School of Medical Sciences, School of Health Sciences, The University of Manchester, Manchester, UK
| | - Yvonne S Davidson
- Faculty of Biology, Medicine and Health, School of Biological Sciences, Division of Neuroscience, The University of Manchester, Salford Royal Hospital, Salford, UK
| | - James Minshull
- Faculty of Biology, Medicine and Health, School of Biological Sciences, Division of Neuroscience, The University of Manchester, Salford Royal Hospital, Salford, UK
| | - Phillip Tinkler
- Faculty of Biology, Medicine and Health, School of Biological Sciences, Division of Neuroscience, The University of Manchester, Salford Royal Hospital, Salford, UK
| | - Antony Payton
- Faculty of Biology, Medicine and Health, School of Health Sciences, Division of Informatics, Imaging and Data Sciences, The University of Manchester, Manchester, UK
| | - David M A Mann
- Faculty of Biology, Medicine and Health, School of Biological Sciences, Division of Neuroscience, The University of Manchester, Salford Royal Hospital, Salford, UK
| | - Federico Roncaroli
- Faculty of Biology, Medicine and Health, School of Biological Sciences, Division of Neuroscience, The University of Manchester, Salford Royal Hospital, Salford, UK
- Geoffrey Jefferson Brain Research Centre, Manchester Academic Health Science Centre (MAHSC), Manchester, UK
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Affleck AJ, Sachdev PS, Halliday GM. Past antihypertensive medication use is associated with lower levels of small vessel disease and lower Aβ plaque stage in the brains of older individuals. Neuropathol Appl Neurobiol 2023; 49:e12922. [PMID: 37431095 PMCID: PMC10947144 DOI: 10.1111/nan.12922] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 05/22/2023] [Accepted: 06/24/2023] [Indexed: 07/12/2023]
Abstract
AIMS This study assesses the association of antihypertensive medication use on the severities of neuropathological cerebrovascular disease (CVD excluding lobar infarction) in older individuals. METHODS Clinical and neuropathological data were retrieved for 149 autopsy cases >75 years old with or without CVD or Alzheimer's disease and no other neuropathological diagnoses. Clinical data included hypertension status, hypertension diagnosis, antihypertensive medication use, antihypertensive medication dose (where available) and clinical dementia rating (CDR). Neuropathological CVD severity was evaluated for differences with anti-hypertensive medication usage. RESULTS Antihypertensive medication use was associated with less severe white matter small vessel disease (SVD, mainly perivascular dilatation and rarefaction), with a 5.6-14.4 times greater likelihood of less severe SVD if medicated. No significant relationship was detected between infarction (presence, type, number and size), lacunes or cerebral amyloid angiopathy and antihypertensive medication use. Only increased white matter rarefaction/oedema and not perivascular dilation was associated with Alzheimer's pathology, with a 4.3 times greater likelihood of reduced Aβ progression through the brain if white matter rarefaction severity was none or mild. Antihypertensive medication use was associated with reduced Aβ progression but only in those with moderate to severe white matter SVD. CONCLUSIONS This histopathological study provides further evidence that antihypertensive medication use in older individuals is associated with white matter SVD and not with other CVD pathologies. This is mainly due to a reduction in white matter perivascular dilation and rarefaction/oedema. Even in those with moderate to severe white matter SVD, antihypertensive medication use reduced rarefaction and Aβ propagation through the brain.
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Affiliation(s)
- Andrew J. Affleck
- Neuroscience Research Australia (NeuRA)SydneyAustralia
- Centre for Health Brain Ageing (CHeBA), Discipline of Psychiatry and Mental Health, Faculty of MedicineUniversity of New South WalesSydneyAustralia
| | - Perminder S. Sachdev
- Centre for Health Brain Ageing (CHeBA), Discipline of Psychiatry and Mental Health, Faculty of MedicineUniversity of New South WalesSydneyAustralia
- Neuropsychiatric InstituteThe Prince of Wales HospitalSydneyAustralia
| | - Glenda M. Halliday
- Neuroscience Research Australia (NeuRA)SydneyAustralia
- School of Medical Sciences, Faculty of MedicineUniversity of New South WalesSydneyAustralia
- Brain and Mind Centre & Faculty of Medicine and Health School of Medical SciencesUniversity of SydneySydneyAustralia
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Upadhyaya P, Ling Y, Chen L, Kim Y, Jiang X. Inferring Personalized Treatment Effect of Antihypertensives on Alzheimer's Disease Using Deep Learning. IEEE INTERNATIONAL CONFERENCE ON HEALTHCARE INFORMATICS. IEEE INTERNATIONAL CONFERENCE ON HEALTHCARE INFORMATICS 2023; 2023:49-57. [PMID: 38516035 PMCID: PMC10956734 DOI: 10.1109/ichi57859.2023.00018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/23/2024]
Abstract
Alzheimer's disease (AD) is one of the leading causes of death in the United States, especially among the elderly. Recent studies have shown how hypertension is related to cognitive decline in elderly patients, which in turn leads to increased mortality as well as morbidity. There have been various studies that have looked at the effect of antihypertensive drugs in reducing cognitive decline, and their results have proved inconclusive. However, most of these studies assume the treatment effect is similar for all patients, thus considering only the average treatment effects of antihypertensive drugs. In this paper, we assume that the effect of antihypertensives on the onset of AD depends on patient characteristics. We develop a deep learning method called LASSO-Dragonnet to estimate the individualized treatment effects of each patient. We considered six antihypertensive drugs, and each of the six models considered one of the drugs as the treatment and the remaining as control. Our studies showed that although many antihypertensives have a positive impact in delaying AD onset on average, the impact varies from individual to individual, depending on their various characteristics. We also analyzed the importance of various covariates in such an estimation. Our results showed that the individualized treatment effects of each patient could be estimated accurately using a deep learning method, and that the importance of various covariates could be determined.
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Affiliation(s)
| | - Yaobin Ling
- School of Biomedical Informatics, UT Health, Houston, USA
| | - Luyao Chen
- School of Biomedical Informatics, UT Health, Houston, USA
| | - Yejin Kim
- School of Biomedical Informatics, UT Health, Houston, USA
| | - Xiaoqian Jiang
- School of Biomedical Informatics, UT Health, Houston, USA
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Scambray KA, Nguyen HL, Sajjadi SA. Association of vascular and degenerative brain pathologies and past medical history from the National Alzheimer's Coordinating Center Database. J Neuropathol Exp Neurol 2023; 82:390-401. [PMID: 36947583 PMCID: PMC10117154 DOI: 10.1093/jnen/nlad020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2023] Open
Abstract
The relationship between past medical histories (PMH) and dementia-related neuropathologies is not well understood. Using the National Alzheimer's Coordinating Center (NACC) database, we explored the relationship between patient-reported PMH and various vascular and degenerative neuropathologies. We examined the following PMH: transient ischemic attack (TIA), stroke, traumatic brain injury, seizures, hypertension, cardiovascular events, hypercholesterolemia, B12 deficiency, diabetes mellitus, and thyroid disease. We dichotomized the following neuropathologies: atherosclerosis, arteriolosclerosis, cerebral amyloid angiopathy (CAA), Alzheimer disease neuropathology (ADNP), Lewy bodies (LB), hippocampal sclerosis, frontotemporal lobar degeneration (FTLD), and TAR DNA-binding protein-43 (TDP-43). Separate logistic regression models assessed the relationship between the outcome of individual neuropathologies and all PMHs. Additional logistic regressions were stratified by sex to further examine these associations. Hypertension history was associated with an increased likelihood of atherosclerosis (OR = 1.7) and arteriolosclerosis (OR = 1.3), but decreased odds of ADNP (OR = 0.81), CAA (OR = 0.79), and LB (OR = 0.78). History of TIA was associated with an increased likelihood of atherosclerosis (OR = 1.3) and arteriolosclerosis (OR = 1.4) and lower odds of ADNP (OR = 0.72). Seizure history was associated with an increased likelihood of ADNP (OR = 1.9) and lower odds of FTLD (OR = 0.49). Hypertension history was associated with a greater likelihood of vascular pathologies yet a lower likelihood of ADNP and other neurodegenerative pathologies.
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Affiliation(s)
- Kiana A Scambray
- Department of Neurology, University of California, Irvine, Irvine, California, USA
| | - Hannah L Nguyen
- Department of Neurology, University of California, Irvine, Irvine, California, USA
| | - S Ahmad Sajjadi
- Department of Neurology, University of California, Irvine, Irvine, California, USA
- Department of Pathology, University of California, Irvine, Irvine, California, USA
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Abdulrahman H, van Dalen JW, den Brok M, Latimer CS, Larson EB, Richard E. Hypertension and Alzheimer's disease pathology at autopsy: A systematic review. Alzheimers Dement 2022; 18:2308-2326. [PMID: 35758526 PMCID: PMC9796086 DOI: 10.1002/alz.12707] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 02/27/2022] [Accepted: 04/27/2022] [Indexed: 01/31/2023]
Abstract
Hypertension is an important risk factor for Alzheimer's disease (AD) and all-cause dementia. The mechanisms underlying this association are unclear. Hypertension may be associated with AD neuropathological changes (ADNC), but reports are sparse and inconsistent. This systematic review included 15 autopsy studies (n = 5879) from observational cohorts. Studies were highly heterogeneous regarding populations, follow-up duration, hypertension operationalization, neuropathological methods, and statistical analyses. Hypertension seems associated with higher plaque and tangle burden, but results are inconsistent. Four studies (n = 3993/5879; 68%), reported clear associations between hypertension and ADNC. Another four suggested that antihypertensive medication may protect against ADNC. Larger studies with longer follow-up reported the strongest relationships. Our findings suggest a positive association between hypertension and ADNC, but effects may be modest, and possibly attenuate with higher hypertension age and antihypertensive medication use. Investigating interactions among plaques, tangles, cerebrovascular pathology, and dementia may be key in better understanding hypertension's role in dementia development.
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Affiliation(s)
- Herrer Abdulrahman
- Department of NeurologyAmsterdam University Medical CenterUniversity of AmsterdamAmsterdamthe Netherlands
- Department of NeurologyRadboud University Medical CenterDonders Institute for BrainCognition and BehaviorNijmegenthe Netherlands
| | - Jan Willem van Dalen
- Department of NeurologyAmsterdam University Medical CenterUniversity of AmsterdamAmsterdamthe Netherlands
- Department of NeurologyRadboud University Medical CenterDonders Institute for BrainCognition and BehaviorNijmegenthe Netherlands
| | - Melina den Brok
- Department of NeurologyAmsterdam University Medical CenterUniversity of AmsterdamAmsterdamthe Netherlands
- Department of NeurologyRadboud University Medical CenterDonders Institute for BrainCognition and BehaviorNijmegenthe Netherlands
| | - Caitlin S. Latimer
- Department of Laboratory Medicine and PathologyUniversity of WashingtonSeattleWashingtonUSA
| | - Eric B. Larson
- Kaiser Permanente Washington Health Research Institute SeattleSeattleWashingtonUSA
| | - Edo Richard
- Department of NeurologyRadboud University Medical CenterDonders Institute for BrainCognition and BehaviorNijmegenthe Netherlands
- Department of Public and Occupational HealthAmsterdam University Medical CenterUniversity of AmsterdamAmsterdamthe Netherlands
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6
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Lopes Alves I, Heeman F, Collij LE, Salvadó G, Tolboom N, Vilor-Tejedor N, Markiewicz P, Yaqub M, Cash D, Mormino EC, Insel PS, Boellaard R, van Berckel BNM, Lammertsma AA, Barkhof F, Gispert JD. Strategies to reduce sample sizes in Alzheimer's disease primary and secondary prevention trials using longitudinal amyloid PET imaging. Alzheimers Res Ther 2021; 13:82. [PMID: 33875021 PMCID: PMC8056524 DOI: 10.1186/s13195-021-00819-2] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Accepted: 03/26/2021] [Indexed: 01/07/2023]
Abstract
BACKGROUND Detecting subtle-to-moderate biomarker changes such as those in amyloid PET imaging becomes increasingly relevant in the context of primary and secondary prevention of Alzheimer's disease (AD). This work aimed to determine if and when distribution volume ratio (DVR; derived from dynamic imaging) and regional quantitative values could improve statistical power in AD prevention trials. METHODS Baseline and annualized % change in [11C]PIB SUVR and DVR were computed for a global (cortical) and regional (early) composite from scans of 237 cognitively unimpaired subjects from the OASIS-3 database ( www.oasis-brains.org ). Bland-Altman and correlation analyses were used to assess the relationship between SUVR and DVR. General linear models and linear mixed effects models were used to determine effects of age, sex, and APOE-ε4 carriership on baseline and longitudinal amyloid burden. Finally, differences in statistical power of SUVR and DVR (cortical or early composite) were assessed considering three anti-amyloid trial scenarios: secondary prevention trials including subjects with (1) intermediate-to-high (Centiloid > 20.1), or (2) intermediate (20.1 < Centiloid ≤ 49.4) amyloid burden, and (3) a primary prevention trial focusing on subjects with low amyloid burden (Centiloid ≤ 20.1). Trial scenarios were set to detect 20% reduction in accumulation rates across the whole population and in APOE-ε4 carriers only. RESULTS Although highly correlated to DVR (ρ = .96), cortical SUVR overestimated DVR cross-sectionally and in annual % change. In secondary prevention trials, DVR required 143 subjects per arm, compared with 176 for SUVR. Both restricting inclusion to individuals with intermediate amyloid burden levels or to APOE-ε4 carriers alone further reduced sample sizes. For primary prevention, SUVR required less subjects per arm (n = 855) compared with DVR (n = 1508) and the early composite also provided considerable sample size reductions (n = 855 to n = 509 for SUVR, n = 1508 to n = 734 for DVR). CONCLUSION Sample sizes in AD secondary prevention trials can be reduced by the acquisition of dynamic PET scans and/or by restricting inclusion to subjects with intermediate amyloid burden or to APOE-ε4 carriers only. Using a targeted early composite only leads to reductions of sample size requirements in primary prevention trials. These findings support strategies to enable smaller Proof-of-Concept Phase II clinical trials to better streamline drug development.
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Affiliation(s)
- Isadora Lopes Alves
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - Fiona Heeman
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Gemma Salvadó
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Nelleke Tolboom
- Imaging Division, Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Natàlia Vilor-Tejedor
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
- Centre for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona, Spain
- Department of Clinical Genetics, Erasmus MC University Medical Center Rotterdam, Rotterdam, The Netherlands
- Universitat Pompeu Fabra, Barcelona, Spain
| | - Pawel Markiewicz
- Centre for Medical Image Computing, Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Maqsood Yaqub
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - David Cash
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Elizabeth C Mormino
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Philip S Insel
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Department of Psychiatry, University of California, San Francisco, CA, USA
| | - Ronald Boellaard
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Bart N M van Berckel
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Adriaan A Lammertsma
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Centre for Medical Image Computing, Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain.
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain.
- Universitat Pompeu Fabra, Barcelona, Spain.
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, Madrid, Spain.
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