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Laporte JP, Akhonda MABS, Cortina LE, Faulkner ME, Gong Z, Guo A, Bae J, Fox NY, Zhang N, Bergeron CM, Ferrucci L, Egan JM, Bouhrara M. Investigating the association between human brainstem microstructural integrity and hypertension using magnetic resonance relaxometry. Hypertens Res 2025; 48:1564-1574. [PMID: 39849049 PMCID: PMC11972960 DOI: 10.1038/s41440-025-02114-1] [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] [Received: 03/21/2024] [Revised: 12/17/2024] [Accepted: 12/30/2024] [Indexed: 01/25/2025]
Abstract
The brainstem plays a vital role in regulating blood pressure, and disruptions to its neural pathways have been linked to hypertension. However, it remains unclear whether subtle microstructural changes in the brainstem are associated with an individual's blood pressure status. This exploratory, cross-sectional study investigated the relationship between brainstem microstructure, myelination, and hypertensive status in 116 cognitively unimpaired adults (aged 22-94 years). Advanced MRI techniques, including relaxometry (R1, R2) and myelin water fraction (MWF) analysis, were employed to assess microstructural integrity and myelin content in ten brainstem subregions. Our results revealed significant associations between higher microstructural damage or lower myelin content (indicated by lower R1, R2, or MWF values) and hypertensive status, particularly in the midbrain tegmentum. Notably, combining these MRI metrics yielded high classification accuracy (AUC > 0.85). Our findings suggest a potential link between disrupted brainstem tissue integrity, myelin content, and elevated blood pressure, warranting further longitudinal investigations to explore this relationship.
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Affiliation(s)
- John P Laporte
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224, MD, USA
| | - Mohammad A B S Akhonda
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224, MD, USA
| | - Luis E Cortina
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224, MD, USA
| | - Mary E Faulkner
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224, MD, USA
| | - Zhaoyuan Gong
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224, MD, USA
| | - Alex Guo
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224, MD, USA
| | - Jonghyun Bae
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224, MD, USA
| | - Noam Y Fox
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224, MD, USA
| | - Nathan Zhang
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224, MD, USA
| | - Christopher M Bergeron
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224, MD, USA
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, 21224, MD, USA
| | - Josephine M Egan
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224, MD, USA
| | - Mustapha Bouhrara
- Laboratory of Clinical Investigation, National Institute on Aging, National Institutes of Health, Baltimore, 21224, MD, USA.
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Cipolli GC, Ribeiro IC, Yasuda CL, Balthazar MLF, Fattori A, Yassuda MS. Frailty and brain changes in older adults without cognitive impairment: A scoping review. Arch Gerontol Geriatr 2024; 123:105395. [PMID: 38492289 DOI: 10.1016/j.archger.2024.105395] [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] [Received: 12/22/2023] [Revised: 02/11/2024] [Accepted: 03/02/2024] [Indexed: 03/18/2024]
Abstract
Little is known about changes in the brain associated with frailty, in particular, which brain areas could be related to frailty in older people without cognitive impairment. This scoping review mapped evidence on functional and/or structural brain changes in frail older adults without cognitive impairment. The methodology proposed by the JBI® was used in this study. The search in PubMed, PubMed PMC, BVS/BIREME, EBSCOHOST, Scopus, Web of Science, Embase, and PROQUEST was conducted up to January 2023. Studies included following the population, concepts, context and the screening and data extraction were performed by two independent reviewers. A total of 9,912 records were identified, 5,676 were duplicates and were excluded. The remaining articles were screened; 31 were read in full and 17 articles were included. The results showed that lesions in white matter hyperintensities, reduced volume of the hippocampus, cerebellum, middle frontal gyrus, low gray matter volume, cortical atrophy, decreased connectivity of the supplementary motor area, presence of amyloid-beta peptide (aβ) in the anterior and posterior putamen and precuneus regions were more frequently observed in frail older adults, compared with non-frail individuals. Studies have suggested that such findings may be of neurodegenerative or cerebrovascular origin. The identification of these brain alterations in frail older adults through neuroimaging studies contributes to our understanding of the underlying mechanisms of frailty. Such findings may have implications for the early detection of frailty and implementation of intervention strategies.
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Affiliation(s)
- Gabriela Cabett Cipolli
- Postgraduate Program in Gerontology, College of Medical Sciences, State University of Campinas, Campinas, Brazil
| | - Isadora Cristina Ribeiro
- Postgraduate Program in Medical Pathophysiology, Faculty of Medical Sciences, State University of Campinas, Campinas, Brazil
| | - Clarissa Lin Yasuda
- Faculty of Medical Sciences, Department of Neurology, State University of Campinas, Campinas, Brazil
| | | | - André Fattori
- Postgraduate Program in Gerontology, College of Medical Sciences, State University of Campinas, Campinas, Brazil; Faculty of Medical Sciences, Department of Internal Medicine, State University of Campinas, Campinas, Brazil
| | - Mônica Sanches Yassuda
- Postgraduate Program in Gerontology, College of Medical Sciences, State University of Campinas, Campinas, Brazil; Postgraduate Program in Gerontology, University of São Paulo, São Paulo, Brazil.
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Chen W, Deng S, Jiang H, Li H, Zhao Y, Yuan Y. Alterations of White Matter Connectivity in Adults with Essential Hypertension. Int J Gen Med 2024; 17:335-346. [PMID: 38314198 PMCID: PMC10838498 DOI: 10.2147/ijgm.s444384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 01/19/2024] [Indexed: 02/06/2024] Open
Abstract
Purpose To explore the topology of the white matter network in individuals with essential hypertension by graph theory. Patients and Methods T1-weighted image and diffusion tensor imaging (DTI) data from 43 patients diagnosed with essential hypertension (EHT) and 33 individuals with normotension (healthy controls, HCs) were incorporated in this cross-sectional study. Furthermore, structural networks were constructed by graph theory to calculate whole brain network characteristics and intracerebral node characteristics. Results Both EHT and HC groups displayed small-worldness in their structural networks. The area under the curve (AUC) of the small-worldness coefficient (σ) was higher in the EHT group compared to the HC group, whereas the AUC of assortativity was lower in the EHT group in contrast to the HC group. The nodal clustering coefficient (CP) and local efficiency (Eloc) of the EHT group decreased in the right dorsolateral superior frontal gyrus and the left medial superior frontal gyrus. These values increased in the left anterior cingulate and paracingulate gyrus. Furthermore, weight and body mass index (BMI) were positively correlated with σ. Conclusion The EHT group showed brain network separation and integration dysfunction. Weight and BMI were positively correlated with σ. The data acquired in this investigation implied that altered structural connectivity in the prefrontal region may be a potential neuroimaging marker in EHT patients.
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Affiliation(s)
- Weijie Chen
- Department of Cardiology, The Second School of Clinical Medicine, Southern Medical University, Guangdong, People's Republic of China
- Department of Cardiology, Dongguan Tung Wah Hospital, Guangdong, People's Republic of China
| | - Simin Deng
- Research Center, Dongguan Eighth People's Hospital, Guangdong, People's Republic of China
| | - Huali Jiang
- Department of Cardiology, Dongguan Tung Wah Hospital, Guangdong, People's Republic of China
| | - Heng Li
- Department of Cardiology, Dongguan Tung Wah Hospital, Guangdong, People's Republic of China
| | - Yu Zhao
- Department of Cardiology, Dongguan Tung Wah Hospital, Guangdong, People's Republic of China
| | - Yiqiang Yuan
- Department of Cardiology, The Second School of Clinical Medicine, Southern Medical University, The Seventh People's Hospital of Zhengzhou, Henan, People's Republic of China
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Lin K, Wen W, Lipnicki DM, Mewton L, Chen R, Du J, Wang D, Skoog I, Sterner TR, Najar J, Kim KW, Han JW, Kim JS, Ng TP, Ho R, Chua DQL, Anstey KJ, Cherbuin N, Mortby ME, Brodaty H, Kochan N, Sachdev PS, Jiang J. Risk factors and cognitive correlates of white matter hyperintensities in ethnically diverse populations without dementia: The COSMIC consortium. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2024; 16:e12567. [PMID: 38487075 PMCID: PMC10937819 DOI: 10.1002/dad2.12567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 01/18/2024] [Accepted: 02/06/2024] [Indexed: 03/17/2024]
Abstract
INTRODUCTION White matter hyperintensities (WMHs) are an important imaging marker for cerebral small vessel diseases, but their risk factors and cognitive associations have not been well documented in populations of different ethnicities and/or from different geographical regions. METHODS We investigated how WMHs were associated with vascular risk factors and cognition in both Whites and Asians, using data from five population-based cohorts of non-demented older individuals from Australia, Singapore, South Korea, and Sweden (N = 1946). WMH volumes (whole brain, periventricular, and deep) were quantified with UBO Detector and harmonized using the ComBat model. We also harmonized various vascular risk factors and scores for global cognition and individual cognitive domains. RESULTS Factors associated with larger whole brain WMH volumes included diabetes, hypertension, stroke, current smoking, body mass index, higher alcohol intake, and insufficient physical activity. Hypertension and stroke had stronger associations with WMH volumes in Whites than in Asians. No associations between WMH volumes and cognitive performance were found after correction for multiple testing. CONCLUSION The current study highlights ethnic differences in the contributions of vascular risk factors to WMHs.
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Affiliation(s)
- Keshuo Lin
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Wei Wen
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Darren M. Lipnicki
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Louise Mewton
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Rory Chen
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Jing Du
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Dadong Wang
- Quantitative Imaging Research TeamCSIRO Informatics and StatisticsNorth RydeNew South WalesAustralia
| | - Ingmar Skoog
- Neuropsychiatric Epidemiology UnitDepartment of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologySahlgrenska AcademyUniversity of GothenburgGothenburgSweden
- Centre for Ageing and Health (AGECAP)University of GothenburgGothenburgSweden
- Psychiatry, Cognition and Old Age Psychiatry ClinicSahlgrenska University HospitalGothenburgSweden
| | - Therese Rydberg Sterner
- Neuropsychiatric Epidemiology UnitDepartment of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologySahlgrenska AcademyUniversity of GothenburgGothenburgSweden
- Centre for Ageing and Health (AGECAP)University of GothenburgGothenburgSweden
- Aging Research CenterDepartment of NeurobiologyCare Sciences and SocietyKarolinska Institutet and Stockholm UniversityStockholmSweden
| | - Jenna Najar
- Neuropsychiatric Epidemiology UnitDepartment of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologySahlgrenska AcademyUniversity of GothenburgGothenburgSweden
- Centre for Ageing and Health (AGECAP)University of GothenburgGothenburgSweden
- Section Genomics of Neurodegenerative Diseases and AgingDepartment of Human GeneticsAmsterdam Universitair Medische CentraAmsterdamthe Netherlands
| | - Ki Woong Kim
- Department of NeuropsychiatrySeoul National University Bundang HospitalSeongnamSouth Korea
- Department of PsychiatrySeoul National University College of MedicineSeoulSouth Korea
- Department of Brain and Cognitive SciencesSeoul National University College of Natural SciencesSeoulSouth Korea
| | - Ji Won Han
- Department of NeuropsychiatrySeoul National University Bundang HospitalSeongnamSouth Korea
- Department of PsychiatrySeoul National University College of MedicineSeoulSouth Korea
| | - Jun Sung Kim
- Department of NeuropsychiatrySeoul National University Bundang HospitalSeongnamSouth Korea
| | - Tze Pin Ng
- Department of Psychological MedicineKhoo Teck Puat HospitalYishunSingapore
- Geriatric Education and Research InstituteMinistry of HealthSingaporeSingapore
| | - Roger Ho
- Institute for Health Innovation and Technology (iHealthtech)National University of SingaporeSingaporeSingapore
| | - Denise Qian Ling Chua
- Department of Psychological MedicineNational University of SingaporeSingaporeSingapore
| | - Kaarin J. Anstey
- School of PsychologyUniversity of New South WalesSydneyNew South WalesAustralia
- Department of NeurodegenerationNeuroscience Research AustraliaSydneyNew South WalesAustralia
- Ageing Futures InstituteUniversity of New South WalesSydneyNew South WalesAustralia
| | - Nicolas Cherbuin
- National Centre for Epidemiology and Population HealthCollege of Health and MedicineAustralian National UniversityCanberraAustralian Capital TerritoryAustralia
| | - Moyra E. Mortby
- School of PsychologyUniversity of New South WalesSydneyNew South WalesAustralia
- Department of NeurodegenerationNeuroscience Research AustraliaSydneyNew South WalesAustralia
- Ageing Futures InstituteUniversity of New South WalesSydneyNew South WalesAustralia
| | - Henry Brodaty
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Nicole Kochan
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Perminder S. Sachdev
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
- Neuropsychiatric InstituteThe Prince of Wales HospitalSydneyNew South WalesAustralia
| | - Jiyang Jiang
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
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Lin K, Wen W, Lipnicki DM, Mewton L, Chen R, Du J, Wang D, Skoog I, Sterner TR, Najar J, Kim KW, Han JW, Kim JS, Ng TP, Ho R, Chua DQL, Anstey KJ, Cherbuin N, Mortby ME, Brodaty H, Kochan N, Sachdev PS, Jiang J. Risk factors and cognitive correlates of white matter hyperintensities in ethnically diverse populations without dementia: the COSMIC consortium. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.30.23294876. [PMID: 37693599 PMCID: PMC10491386 DOI: 10.1101/2023.08.30.23294876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
INTRODUCTION White matter hyperintensities (WMH) are an important imaging marker for cerebral small vessel diseases, but their risk factors and cognitive associations have not been well-documented in populations of different ethnicities and/or from different geographical regions. METHOD Magnetic resonance imaging data of five population-based cohorts of non-demented older individuals from Australia, Singapore, South Korea, and Sweden (N = 1,946) were examined for WMH and their associations with vascular risk factors and cognition. RESULT Factors associated with larger whole brain WMH volumes included diabetes, hypertension, stroke, current smoking, body mass index, higher alcohol intake and insufficient physical activity. Participants with moderate or higher physical activity had less WMH than those who never exercised, but the former two groups did not differ. Hypertension and stroke had stronger associations with WMH volumes in the White, compared to Asian subsample. DISCUSSION The current study highlighted the ethnic differences in the contributions of vascular risk factors to WMH.
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Affiliation(s)
- Keshuo Lin
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Wei Wen
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Darren M. Lipnicki
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Louise Mewton
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Rory Chen
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Jing Du
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Dadong Wang
- CSIRO Informatics and Statistics, Locked Bag 17, North Ryde, NSW 1670, Australia
| | - Ingmar Skoog
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, Box 100, 405 30, at the University of Gothenburg, Sweden
- Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Box 100, 405 30, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Box 100, Goeteborg, Vaestra Goetaland 405 30, Sweden
| | - Therese Rydberg Sterner
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, Box 100, 405 30, at the University of Gothenburg, Sweden
- Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Box 100, 405 30, Sweden
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Nobels väg 6, 171 77 Stockholm, Sweden
| | - Jenna Najar
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, Box 100, 405 30, at the University of Gothenburg, Sweden
- Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Box 100, 405 30, Sweden
- Section Genomics of Neurodegenerative Diseases and Aging, Department of Human Genetics, Amsterdam Universitair Medische Centra, PO Box 7057, 1007 MB, Amsterdam, the Netherlands
| | - Ki Woong Kim
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Gyeonggi-do 13620, Seongnam, Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul 03080, Korea
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul 03080, Korea
| | - Ji Won Han
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Gyeonggi-do 13620, Seongnam, Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul 03080, Korea
| | - Jun Sung Kim
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Gyeonggi-do 13620, Seongnam, Korea
| | - Tze Pin Ng
- Khoo Teck Puat Hospital, 768828, Singapore
- Geriatric Education and Research Institute, Ministry of Health, 768024, Singapore
| | - Roger Ho
- Institute for Health Innovation and Technology (iHealthtech), National University of Singapore, 119077, Singapore
| | - Denise Qian Ling Chua
- Department of Psychological Medicine, National University of Singapore, 119077, Singapore
| | - Kaarin J. Anstey
- School of Psychology, University of New South Wales, NSW 2052,Australia
- Neuroscience Research Australia, NSW 2031, Australia
- Ageing Futures Institute, University of New South Wales, NSW 2052,Australia
| | - Nicolas Cherbuin
- National Centre for Epidemiology and Population Health, College of Health and Medicine, Australian National University, ACT 2600, Canberra, Australia
| | - Moyra E. Mortby
- School of Psychology, University of New South Wales, NSW 2052,Australia
- Neuroscience Research Australia, NSW 2031, Australia
- Ageing Futures Institute, University of New South Wales, NSW 2052,Australia
| | - Henry Brodaty
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Nicole Kochan
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Perminder S. Sachdev
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
- Neuropsychiatric Institute, The Prince of Wales Hospital, Sydney, NSW 2031, Australia
| | - Jiyang Jiang
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
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Laporte JP, Faulkner ME, Gong Z, Akhonda MA, Ferrucci L, Egan JM, Bouhrara M. Hypertensive Adults Exhibit Lower Myelin Content: A Multicomponent Relaxometry and Diffusion Magnetic Resonance Imaging Study. Hypertension 2023; 80:1728-1738. [PMID: 37283066 PMCID: PMC10355798 DOI: 10.1161/hypertensionaha.123.21012] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 05/11/2023] [Indexed: 06/08/2023]
Abstract
BACKGROUND It is unknown whether hypertension plays any role in cerebral myelination. To fill this knowledge gap, we studied 90 cognitively unimpaired adults, age range 40 to 94 years, who are participants in the Baltimore Longitudinal Study of Aging and the Genetic and Epigenetic Signatures of Translational Aging Laboratory Testing to look for potential associations between hypertension and cerebral myelin content across 14 white matter brain regions. METHODS Myelin content was probed using our advanced multicomponent magnetic resonance relaxometry method of myelin water fraction, a direct and specific magnetic resonance imaging measure of myelin content, and longitudinal and transverse relaxation rates (R1 and R2), 2 highly sensitive magnetic resonance imaging metrics of myelin content. We also applied diffusion tensor imaging magnetic resonance imaging to measure fractional anisotropy, mean diffusivity, radial diffusivity, and axial diffusivity values, which are metrics of cerebral microstructural tissue integrity, to provide context with previous magnetic resonance imaging findings. RESULTS After adjustment of age, sex, systolic blood pressure, smoking status, diabetes status, and cholesterol level, our results indicated that participants with hypertension exhibited lower myelin water fraction, fractional anisotropy, R1 and R2 values and higher mean diffusivity, radial diffusivity, and axial diffusivity values, indicating lower myelin content and higher impairment to the brain microstructure. These associations were significant across several white matter regions, particularly in the corpus callosum, fronto-occipital fasciculus, temporal lobes, internal capsules, and corona radiata. CONCLUSIONS These original findings suggest a direct association between myelin content and hypertension and form the basis for further investigations including longitudinal assessments of this relationship.
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Affiliation(s)
- John P. Laporte
- Laboratory of Clinical Investigation (J.P.L., M.E.F., Z.G., M.A.B.S.A., J.M.E., M.B.), National Institute on Aging, National Institutes of Health, Baltimore, MD
| | - Mary E. Faulkner
- Laboratory of Clinical Investigation (J.P.L., M.E.F., Z.G., M.A.B.S.A., J.M.E., M.B.), National Institute on Aging, National Institutes of Health, Baltimore, MD
| | - Zhaoyuan Gong
- Laboratory of Clinical Investigation (J.P.L., M.E.F., Z.G., M.A.B.S.A., J.M.E., M.B.), National Institute on Aging, National Institutes of Health, Baltimore, MD
| | - Mohammad A.B.S. Akhonda
- Laboratory of Clinical Investigation (J.P.L., M.E.F., Z.G., M.A.B.S.A., J.M.E., M.B.), National Institute on Aging, National Institutes of Health, Baltimore, MD
| | - Luigi Ferrucci
- Translational Gerontology Branch (L.F.), National Institute on Aging, National Institutes of Health, Baltimore, MD
| | - Josephine M. Egan
- Laboratory of Clinical Investigation (J.P.L., M.E.F., Z.G., M.A.B.S.A., J.M.E., M.B.), National Institute on Aging, National Institutes of Health, Baltimore, MD
| | - Mustapha Bouhrara
- Laboratory of Clinical Investigation (J.P.L., M.E.F., Z.G., M.A.B.S.A., J.M.E., M.B.), National Institute on Aging, National Institutes of Health, Baltimore, MD
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Rashid T, Li K, Toledo JB, Nasrallah I, Pajewski NM, Dolui S, Detre J, Wolk DA, Liu H, Heckbert SR, Bryan RN, Williamson J, Davatzikos C, Seshadri S, Launer LJ, Habes M. Association of Intensive vs Standard Blood Pressure Control With Regional Changes in Cerebral Small Vessel Disease Biomarkers: Post Hoc Secondary Analysis of the SPRINT MIND Randomized Clinical Trial. JAMA Netw Open 2023; 6:e231055. [PMID: 36857053 PMCID: PMC9978954 DOI: 10.1001/jamanetworkopen.2023.1055] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/02/2023] Open
Abstract
IMPORTANCE Little is known about the associations of strict blood pressure (BP) control with microstructural changes in small vessel disease markers. OBJECTIVE To investigate the regional associations of intensive vs standard BP control with small vessel disease biomarkers, such as white matter lesions (WMLs), fractional anisotropy (FA), mean diffusivity (MD), and cerebral blood flow (CBF). DESIGN, SETTING, AND PARTICIPANTS The Systolic Blood Pressure Intervention Trial (SPRINT) is a multicenter randomized clinical trial that compared intensive systolic BP (SBP) control (SBP target <120 mm Hg) vs standard control (SBP target <140 mm Hg) among participants aged 50 years or older with hypertension and without diabetes or a history of stroke. The study began randomization on November 8, 2010, and stopped July 1, 2016, with a follow-up duration of approximately 4 years. A total of 670 and 458 participants completed brain magnetic resonance imaging at baseline and follow-up, respectively, and comprise the cohort for this post hoc analysis. Statistical analyses for this post hoc analysis were performed between August 2020 and October 2022. INTERVENTIONS At baseline, 355 participants received intensive SBP treatment and 315 participants received standard SBP treatment. MAIN OUTCOMES AND MEASURES The main outcomes were regional changes in WMLs, FA, MD (in white matter regions of interest), and CBF (in gray matter regions of interest). RESULTS At baseline, 355 participants (mean [SD] age, 67.7 [8.0] years; 200 men [56.3%]) received intensive BP treatment and 315 participants (mean [SD] age, 67.0 [8.4] years; 199 men [63.2%]) received standard BP treatment. Intensive treatment was associated with smaller mean increases in WML volume compared with standard treatment (644.5 mm3 vs 1258.1 mm3). The smaller mean increases were observed specifically in the deep white matter regions of the left anterior corona radiata (intensive treatment, 30.3 mm3 [95% CI, 16.0-44.5 mm3]; standard treatment, 80.5 mm3 [95% CI, 53.8-107.2 mm3]), left tapetum (intensive treatment, 11.8 mm3 [95% CI, 4.4-19.2 mm3]; standard treatment, 27.2 mm3 [95% CI, 19.4-35.0 mm3]), left superior fronto-occipital fasciculus (intensive treatment, 3.2 mm3 [95% CI, 0.7-5.8 mm3]; standard treatment, 9.4 mm3 [95% CI, 5.5-13.4 mm3]), left posterior corona radiata (intensive treatment, 26.0 mm3 [95% CI, 12.9-39.1 mm3]; standard treatment, 52.3 mm3 [95% CI, 34.8-69.8 mm3]), left splenium of the corpus callosum (intensive treatment, 45.4 mm3 [95% CI, 25.1-65.7 mm3]; standard treatment, 83.0 mm3 [95% CI, 58.7-107.2 mm3]), left posterior thalamic radiation (intensive treatment, 53.0 mm3 [95% CI, 29.8-76.2 mm3]; standard treatment, 106.9 mm3 [95% CI, 73.4-140.3 mm3]), and right posterior thalamic radiation (intensive treatment, 49.5 mm3 [95% CI, 24.3-74.7 mm3]; standard treatment, 102.6 mm3 [95% CI, 71.0-134.2 mm3]). CONCLUSIONS AND RELEVANCE This study suggests that intensive BP treatment, compared with standard treatment, was associated with a slower increase of WMLs, improved diffusion tensor imaging, and FA and CBF changes in several brain regions that represent vulnerable areas that may benefit from more strict BP control. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT01206062.
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Affiliation(s)
- Tanweer Rashid
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio
| | - Karl Li
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio
| | - Jon B. Toledo
- Department of Neurology, University of Florida, Gainesville
- Department of Neurology, Houston Methodist Hospital, Houston, Texas
| | - Ilya Nasrallah
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| | - Nicholas M. Pajewski
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Sudipto Dolui
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia
| | - John Detre
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia
- Department of Neurology, University of Pennsylvania, Philadelphia
| | - David A. Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia
| | - Hangfan Liu
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| | | | - R. Nick Bryan
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia
| | - Jeff Williamson
- Section of Gerontology and Geriatric Medicine, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Christos Davatzikos
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| | - Sudha Seshadri
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio
| | - Lenore J. Launer
- Intramural Research Program, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Bethesda, Maryland
| | - Mohamad Habes
- Neuroimage Analytics Laboratory and the Biggs Institute Neuroimaging Core, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, University of Texas Health Science Center San Antonio, San Antonio
- Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia
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8
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Yang Y, Zhu Q, Wang L, Gao D, Wang Z, Geng Z. Effects of hypertension and aging on brain function in spontaneously hypertensive rats: a longitudinal resting-state functional magnetic resonance imaging study. Cereb Cortex 2022; 33:5493-5500. [PMID: 36408643 PMCID: PMC10152091 DOI: 10.1093/cercor/bhac436] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 10/07/2022] [Accepted: 10/09/2022] [Indexed: 11/22/2022] Open
Abstract
Abstract
To investigate the dynamic evolution of brain function under the comorbidities of hypertension and aging. Resting-state functional magnetic resonance imaging scans were longitudinally acquired at 10, 24, and 52 weeks in spontaneously hypertensive rats (SHRs) and Wistar-Kyoto rats. We computed the mean amplitude of low-frequency fluctuation (mALFF), mean regional homogeneity (mReHo), and functional connectivity (FC). There was no interaction between hypertension and aging on brain function. The main effect of aging reflects primarily the cumulative increase of brain activity, especially the increase of mALFF in amygdala and mReHo in cingulate cortex, accompanied by the decrease of brain activity. The main effect of hypertension reflects primarily decreased brain activity in default modal network, accompanied by increased brain activity. The main effect of aging shows reduced brain FC as early as 24 weeks, and the main effect of hypertension shows higher brain FC in SHRs. The novel discovery is that 1 brain FC network increased linearly with age in SHRs, in addition to the linearly decreasing FC. Hypertension and aging independently contribute to spatiotemporal alterations in brain function in SHRs following ongoing progression and compensation. This study provides new insight into the dynamic characteristics of brain function.
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Affiliation(s)
- Yingying Yang
- Hebei Medical University Medical Imaging Specialty, Graduate School, , Shijiazhuang 050000 , China
- The First Hospital of Qinhuangdao Department of Imaging, , Qinhuangdao 066000 , China
| | - Qingfeng Zhu
- The Second Hospital of Hebei Medical University Department of Medical Imaging, , Shijiazhuang 050000 , China
| | - Lixin Wang
- The Second Hospital of Hebei Medical University Department of Medical Imaging, , Shijiazhuang 050000 , China
| | - Duo Gao
- The Second Hospital of Hebei Medical University Department of Medical Imaging, , Shijiazhuang 050000 , China
| | - Zhanqiu Wang
- The First Hospital of Qinhuangdao Department of Imaging, , Qinhuangdao 066000 , China
| | - Zuojun Geng
- The Second Hospital of Hebei Medical University Department of Medical Imaging, , Shijiazhuang 050000 , China
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9
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Effects of the Mindfulness-Based Blood Pressure Reduction (MB-BP) program on depression and neural structural connectivity. J Affect Disord 2022; 311:31-39. [PMID: 35594968 DOI: 10.1016/j.jad.2022.05.059] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Revised: 05/05/2022] [Accepted: 05/12/2022] [Indexed: 11/17/2022]
Abstract
BACKGROUND Hypertension-related illnesses are a leading cause of disability and death in the United States, where hypertension prevalence in adults is 46%, with only half of those afflicted having it under control. Due to the significant challenges in long-term efficacy and adverse effects associated with pharmacological interventions, there is an eminent need for complimentary approaches for treating hypertension. Although initial studies of the Mindfulness-Based Blood Pressure Reduction program (MB-BP) indicate that this novel 8-week intervention is effective at inducing lasting decreases in blood pressure, the neural correlates are unknown. METHODS The objectives of this study were to identify structural neural correlates of MB-BP using diffusion tensor magnetic resonance imaging (DTI) and assess potential correlations with key clinical outcomes. RESULTS In a subset of participants (14 MB-BP, 22 controls) from a larger stage IIa randomized controlled trial, MB-BP participants exhibited increased interoception and decreased depressive symptoms compared to controls. Analyses of DTI data revealed significant group differences in multiple white matter neural tracts associated with the limbic system and/or blood pressure. Specific changes in neural structural connectivity were significantly associated with measures of interoception and depression. LIMITATIONS Limitations include small sample size (leading to insufficient power in the analysis of blood pressure) and the study duration (3 months). The main MRI limitation is suboptimal resolution in areas of extensive neural tract crossings. CONCLUSIONS It is concluded that MB-BP induces alterations in brain structural connectivity which could mediate beneficial changes in depression and interoceptive awareness in individuals with hypertension.
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10
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Different patterns of white matter lesions among patent foramen ovale, atherosclerotic cerebral small vessel disease and cerebral venous thrombosis. J Thromb Thrombolysis 2022; 53:911-925. [PMID: 34985685 DOI: 10.1007/s11239-021-02624-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/19/2021] [Indexed: 01/10/2023]
Abstract
None of studies are available on the predictive ability of white matter lesions (WMLs) among patent foramen ovale (PFO), atherosclerotic cerebral small vessel disease (aCSVD) and cerebral venous thrombosis (CVT). Herein, we aimed to uncover the difference of the WML patterns among the three disease entities in a real-world setting to provide clinical references for predicting probable WML etiologies. We retrospectively reviewed data from consecutive patients with imaging-confirmed PFO, aCSVD, or CVT enrolled from 2014 through 2020. WMLs presented on fluid-attenuated inversion recovery (FLAIR) maps were compared among the three groups based on visual evaluation, Fazekas and modified Scheltens scales. Propensity score matching (PSM) was implemented to correct age and hypertension differences among groups. A total of 401 patients were entered into final analysis, including PFO (n = 112, 46.5 ± 12.8 years), aCSVD (n = 177, 61.6 ± 11.8 years) and CVT (n = 112, 37.4 ± 11.4 years) groups. In this study, WMLs occurred in all of the involved patients in the three groups (100%), which were independent to age, symptom onset and disease durations. On visual evaluation, PFO-WMLs were multiple spots distributed asymmetrically around bilateral subcortex and peri-ventricles. aCSVD-WMLs were dots or sheets distributed symmetrically in subcortex and peri-ventricles, and often coexisted with lacunar infarctions. CVT-WMLs were cloud-like around bilateral peri-ventricles, and enabled to attenuate after recanalization. Fazekas and modified Scheltens scores of PFO-WML vs. aCSVD-WML were significantly different even after being matched by 1:2 PSM (all p < 0.05), meaning that the WML burden in aCSVD was considerably heavier than that in PFO. WML patterns induced by PFO, aCSVD and CVT were obviously different, and were therefore of great clinical significance to preliminarily predict and differentiate the three diseases entities.
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11
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Shao Y, Ruan J, Xu Y, Shu Z, He X. Comparing the Performance of Two Radiomic Models to Predict Progression and Progression Speed of White Matter Hyperintensities. Front Neuroinform 2021; 15:789295. [PMID: 34924990 PMCID: PMC8671609 DOI: 10.3389/fninf.2021.789295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 11/04/2021] [Indexed: 11/13/2022] Open
Abstract
Purpose: The aim of this study was to compare two radiomic models in predicting the progression of white matter hyperintensity (WMH) and the speed of progression from conventional magnetic resonance images. Methods: In this study, 232 people were retrospectively analyzed at Medical Center A (training and testing groups) and Medical Center B (external validation group). A visual rating scale was used to divide all patients into WMH progression and non-progression groups. Two regions of interest (ROIs)—ROI whole-brain white matter (WBWM) and ROI WMH penumbra (WMHp)—were segmented from the baseline image. For predicting WMH progression, logistic regression was applied to create radiomic models in the two ROIs. Then, age, sex, clinical course, vascular risk factors, and imaging factors were incorporated into a stepwise regression analysis to construct the combined diagnosis model. Finally, the presence of a correlation between radiomic findings and the speed of progression was analyzed. Results: The area under the curve (AUC) was higher for the WMHp-based radiomic model than the WBWM-based radiomic model in training, testing, and validation groups (0.791, 0.768, and 0.767 vs. 0.725, 0.693, and 0.691, respectively). The WBWM-based combined model was established by combining age, hypertension, and rad-score of the ROI WBWM. Also, the WMHp-based combined model is built by combining the age and rad-score of the ROI WMHp. Compared with the WBWM-based model (AUC = 0.779, 0.716, 0.673 in training, testing, and validation groups, respectively), the WMHp-based combined model has higher diagnostic efficiency and better generalization ability (AUC = 0.793, 0.774, 0.777 in training, testing, and validation groups, respectively). The speed of WMH progression was related to the rad-score from ROI WMHp (r = 0.49) but not from ROI WBWM. Conclusion: The heterogeneity of the penumbra could help identify the individuals at high risk of WMH progression and the rad-score of it was correlated with the speed of progression.
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Affiliation(s)
- Yuan Shao
- Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital of Hangzhou Medical College, Hangzhou, China
| | | | - Yuyun Xu
- Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital of Hangzhou Medical College, Hangzhou, China
| | - Zhenyu Shu
- Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital of Hangzhou Medical College, Hangzhou, China
| | - Xiaodong He
- Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital of Hangzhou Medical College, Hangzhou, China
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12
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Yang Y, Zhang Q, Ren J, Zhu Q, Wang L, Zhang Y, Geng Z. Evolution of Brain Morphology in Spontaneously Hypertensive and Wistar-Kyoto Rats From Early Adulthood to Aging: A Longitudinal Magnetic Resonance Imaging Study. Front Aging Neurosci 2021; 13:757808. [PMID: 34916922 PMCID: PMC8670306 DOI: 10.3389/fnagi.2021.757808] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 11/08/2021] [Indexed: 11/21/2022] Open
Abstract
The influence of hypertension and aging alone on brain structure has been described extensively. Our understanding of the interaction of hypertension with aging to brain morphology is still limited. We aimed to detect the synergistic effects of hypertension and aging on brain morphology and to describe the evolution patterns of cerebral atrophy from spatial and temporal perspectives. In 8 spontaneously hypertensive rats (SHRs) and 5 Wistar-Kyoto rats, high-resolution magnetic resonance imaging scans were longitudinally acquired at 10, 24, 52, and 80 weeks. We analyzed the tissue volumes of gray matter, white matter, cerebral spinal fluid, and total intracranial volume (TIV), and then evaluated gray matter volume in detail using voxel-based morphometry (VBM) and region of interest-based methods. There were interactive effects on hypertension and aging in tissue volumes of gray matter, white matter, and TIV, of which gray matter atrophy was most pronounced, especially in elderly SHRs. We identified the vulnerable gray matter volume with combined effects of hypertension and aging in the septal region, bilateral caudate putamen, hippocampus, primary somatosensory cortex, cerebellum, periaqueductal gray, right accumbens nucleus, and thalamus. We automatically extracted the septal region, anterior cingulate cortex, primary somatosensory cortex, caudate putamen, hippocampus, and accumbens nucleus and revealed an inverted-U trajectory of volume change in SHRs, with volume increase at the early phase and decline at the late phase. Hypertension interacts with aging to affect brain volume changes such as severe atrophy in elderly SHRs.
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Affiliation(s)
- Yingying Yang
- Graduate School, Hebei Medical University, Shijiazhuang, China.,Department of Imaging, The First Hospital of Qinhuangdao, Qinhuangdao, China
| | - Quan Zhang
- Tianjin Key Laboratory of Functional Imaging, Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | | | - Qingfeng Zhu
- Department of Medical Imaging, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Lixin Wang
- Department of Medical Imaging, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Yongzhi Zhang
- Graduate School, Hebei Medical University, Shijiazhuang, China
| | - Zuojun Geng
- Department of Medical Imaging, The Second Hospital of Hebei Medical University, Shijiazhuang, China
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13
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Zimmerman B, Rypma B, Gratton G, Fabiani M. Age-related changes in cerebrovascular health and their effects on neural function and cognition: A comprehensive review. Psychophysiology 2021; 58:e13796. [PMID: 33728712 PMCID: PMC8244108 DOI: 10.1111/psyp.13796] [Citation(s) in RCA: 68] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Revised: 01/11/2021] [Accepted: 02/08/2021] [Indexed: 12/11/2022]
Abstract
The process of aging includes changes in cellular biology that affect local interactions between cells and their environments and eventually propagate to systemic levels. In the brain, where neurons critically depend on an efficient and dynamic supply of oxygen and glucose, age-related changes in the complex interaction between the brain parenchyma and the cerebrovasculature have effects on health and functioning that negatively impact cognition and play a role in pathology. Thus, cerebrovascular health is considered one of the main mechanisms by which a healthy lifestyle, such as habitual cardiorespiratory exercise and a healthful diet, could lead to improved cognitive outcomes with aging. This review aims at detailing how the physiology of the cerebral vascular system changes with age and how these changes lead to differential trajectories of cognitive maintenance or decline. This provides a framework for generating specific mechanistic hypotheses about the efficacy of proposed interventions and lifestyle covariates that contribute to enhanced cognitive well-being. Finally, we discuss the methodological implications of age-related changes in the cerebral vasculature for human cognitive neuroscience research and propose directions for future experiments aimed at investigating age-related changes in the relationship between physiology and cognitive mechanisms.
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Affiliation(s)
- Benjamin Zimmerman
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Bart Rypma
- School of Behavioral and Brain Sciences, University of Texas at Dallas, Richardson, TX, USA
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Gabriele Gratton
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Psychology, University of Illinois at Urbana-Champaign, Champaign, IL, USA
- Neuroscience Program, University of Illinois at Urbana-Champaign, Champaign, IL, USA
| | - Monica Fabiani
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Psychology, University of Illinois at Urbana-Champaign, Champaign, IL, USA
- Neuroscience Program, University of Illinois at Urbana-Champaign, Champaign, IL, USA
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14
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Daugherty AM. Hypertension-related risk for dementia: A summary review with future directions. Semin Cell Dev Biol 2021; 116:82-89. [PMID: 33722505 DOI: 10.1016/j.semcdb.2021.03.002] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 03/01/2021] [Accepted: 03/06/2021] [Indexed: 02/07/2023]
Abstract
Chronic hypertension, or high blood pressure, is the most prevalent vascular risk factor that accelerates cognitive aging and increases risk for Alzheimer's disease and related dementia. Decades of observational and clinical trials have demonstrated that midlife hypertension is associated with greater gray matter atrophy, white matter damage commiserate with demyelination, and functional deficits as compared to normotension over the adult lifespan. Critically, hypertension is a modifiable dementia risk factor: successful blood pressure control with antihypertensive treatment improves outcomes as compared to uncontrolled hypertension, but does not completely negate the risk for dementia. This suggests that hypertension-related risk for neural and cognitive decline in aging cannot be due to elevations in blood pressure alone. This summary review describes three putative pathways for hypertension-related dementia risk: oxidative damage and metabolic dysfunction; systemic inflammation; and autonomic control of heart rate variability. The same processes contribute to pre-clinical hypertension, and therefore hypertension may be an early symptom of an aging nervous system that then exacerbates cumulative and progressive neurodegeneration. Current evidence is reviewed and future directions for research are outlined, including blood biomarkers and novel neuroimaging methods that may be sensitive to test the specific hypotheses.
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Affiliation(s)
- Ana M Daugherty
- Department of Psychology, Department of Psychiatry and Behavioral Neurosciences, Institute of Gerontology, Wayne State University, 5057 Woodward Ave., Detroit, MI, USA.
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15
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Common Brain Structural Alterations Associated with Cardiovascular Disease Risk Factors and Alzheimer's Dementia: Future Directions and Implications. Neuropsychol Rev 2020; 30:546-557. [PMID: 33011894 DOI: 10.1007/s11065-020-09460-6] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2019] [Accepted: 09/24/2020] [Indexed: 01/18/2023]
Abstract
Recent reports suggest declines in the age-specific risk of Alzheimer's dementia in higher income Western countries. At the same time, investigators believe that worldwide trends of increasing mid-life modifiable risk factors [e.g., cardiovascular disease (CVD) risk factors] coupled with the growth of the world's oldest age groups may nonetheless lead to an increase in Alzheimer's dementia. Thus, understanding the overlap in neuroanatomical profiles associated with CVD risk factors and AD may offer more relevant targets for investigating ways to reduce the growing dementia epidemic than current targets specific to isolated AD-related neuropathology. We hypothesized that a core group of common brain structural alterations exist between CVD risk factors and Alzheimer's dementia. Two co-authors conducted independent literature reviews in PubMed using search terms for CVD risk factor burden (separate searches for 'cardiovascular disease risk factors', 'hypertension', and 'Type 2 diabetes') and 'aging' or 'Alzheimer's dementia' with either 'grey matter volumes' or 'white matter'. Of studies that reported regionally localized results, we found support for our hypothesis, determining 23 regions commonly associated with both CVD risk factors and Alzheimer's dementia. Within this context, we outline future directions for research as well as larger cerebrovascular implications for these commonalities. Overall, this review supports previous as well as more recent calls for the consideration that both vascular and neurodegenerative factors contribute to the pathogenesis of dementia.
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16
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Taghdiri F, Multani N, Ozzoude M, Tarazi A, Khodadadi M, Wennberg R, Mikulis D, Green R, Colella B, Davis K, Blennow K, Zetterberg H, Tator C, Tartaglia M. Neurofilament‐light in former athletes: a potential biomarker of neurodegeneration and progression. Eur J Neurol 2020; 27:1170-1177. [DOI: 10.1111/ene.14251] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2020] [Accepted: 04/02/2020] [Indexed: 01/16/2023]
Affiliation(s)
- F. Taghdiri
- Tanz Centre for Research in Neurodegenerative Diseases University of Toronto OntarioTorontoCanada
| | - N. Multani
- Tanz Centre for Research in Neurodegenerative Diseases University of Toronto OntarioTorontoCanada
| | - M. Ozzoude
- Tanz Centre for Research in Neurodegenerative Diseases University of Toronto OntarioTorontoCanada
| | - A. Tarazi
- Division of Neurology Krembil Neuroscience Centre Toronto OntarioCanada
- Canadian Concussion Centre Toronto Western Hospital Krembil Brain Institute University Health Network TorontoCanada
| | - M. Khodadadi
- Canadian Concussion Centre Toronto Western Hospital Krembil Brain Institute University Health Network TorontoCanada
| | - R. Wennberg
- Division of Neurology Krembil Neuroscience Centre Toronto OntarioCanada
- Canadian Concussion Centre Toronto Western Hospital Krembil Brain Institute University Health Network TorontoCanada
- Institute of Medical Science University of Toronto Toronto OntarioCanada
| | - D. Mikulis
- Canadian Concussion Centre Toronto Western Hospital Krembil Brain Institute University Health Network TorontoCanada
- Institute of Medical Science University of Toronto Toronto OntarioCanada
- Division of Neuroradiology Joint Department of Medical Imaging University Health Network Toronto OntarioCanada
| | - R. Green
- Canadian Concussion Centre Toronto Western Hospital Krembil Brain Institute University Health Network TorontoCanada
- Department of Rehabilitation Sciences University of Toronto Toronto OntarioCanada
| | - B. Colella
- Canadian Concussion Centre Toronto Western Hospital Krembil Brain Institute University Health Network TorontoCanada
- Department of Rehabilitation Sciences University of Toronto Toronto OntarioCanada
| | - K.D. Davis
- Canadian Concussion Centre Toronto Western Hospital Krembil Brain Institute University Health Network TorontoCanada
- Institute of Medical Science University of Toronto Toronto OntarioCanada
- Department of Surgery University of Toronto Toronto OntarioCanada
- Division of Brain, Imaging and Behaviour‐systems Neuroscience Krembil Brain Institute University Health Network Toronto Ontario Canada
| | - K. Blennow
- Institute of Neuroscience and Physiology Department of Psychiatry and Neurochemistry The Sahlgrenska Academy at the University of Gothenburg MölndalSweden
- Clinical Neurochemistry Laboratory Sahlgrenska University Hospital Mölndal Sweden
| | - H. Zetterberg
- Institute of Neuroscience and Physiology Department of Psychiatry and Neurochemistry The Sahlgrenska Academy at the University of Gothenburg MölndalSweden
- Clinical Neurochemistry Laboratory Sahlgrenska University Hospital Mölndal Sweden
- Department of Neurodegenerative Disease UCL Institute of Neurology Queen Square LondonUK
- UK Dementia Research Institute at UCL University College London London UK
| | - C. Tator
- Canadian Concussion Centre Toronto Western Hospital Krembil Brain Institute University Health Network TorontoCanada
- Division of Neurosurgery Toronto Western Hospital Krembil Brain Institute University Health Network Toronto Canada
| | - M.C. Tartaglia
- Tanz Centre for Research in Neurodegenerative Diseases University of Toronto OntarioTorontoCanada
- Division of Neurology Krembil Neuroscience Centre Toronto OntarioCanada
- Canadian Concussion Centre Toronto Western Hospital Krembil Brain Institute University Health Network TorontoCanada
- Institute of Medical Science University of Toronto Toronto OntarioCanada
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17
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Wassenaar TM, Yaffe K, van der Werf YD, Sexton CE. Associations between modifiable risk factors and white matter of the aging brain: insights from diffusion tensor imaging studies. Neurobiol Aging 2019; 80:56-70. [PMID: 31103633 PMCID: PMC6683729 DOI: 10.1016/j.neurobiolaging.2019.04.006] [Citation(s) in RCA: 75] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2019] [Revised: 03/26/2019] [Accepted: 04/05/2019] [Indexed: 01/13/2023]
Abstract
There is increasing interest in factors that may modulate white matter (WM) breakdown and, consequentially, age-related cognitive and behavioral deficits. Recent diffusion tensor imaging studies have examined the relationship of such factors with WM microstructure. This review summarizes the evidence regarding the relationship between WM microstructure and recognized modifiable factors, including hearing loss, hypertension, diabetes, obesity, smoking, depressive symptoms, physical (in) activity, and social isolation, as well as sleep disturbances, diet, cognitive training, and meditation. Current cross-sectional evidence suggests a clear link between loss of WM integrity (lower fractional anisotropy and higher mean diffusivity) and hypertension, obesity, diabetes, and smoking; a relationship that seems to hold for hearing loss, social isolation, depressive symptoms, and sleep disturbances. Physical activity, cognitive training, diet, and meditation, on the other hand, may protect WM with aging. Preliminary evidence from cross-sectional studies of treated risk factors suggests that modification of factors could slow down negative effects on WM microstructure. Careful intervention studies are needed for this literature to contribute to public health initiatives going forward.
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Affiliation(s)
- Thomas M Wassenaar
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroscience, FMRIB Centre, University of Oxford, John Radcliffe Hospital, UK
| | - Kristine Yaffe
- Departments of Psychiatry, Neurology, and Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Ysbrand D van der Werf
- Department of Anatomy and Neurosciences, VU University Medical Center, MC, Amsterdam, the Netherlands
| | - Claire E Sexton
- Department of Neurology, Global Brain Health Institute, Memory and Aging Center, University of California San Francisco, San Francisco, CA, USA; Department of Psychiatry, Wellcome Centre for Integrative Neuroscience, Oxford Centre for Human Brain Activity, University of Oxford, John Radcliffe Hospital, UK.
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