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Llamas Rodríguez J, van der Kouwe AJW, Oltmer J, Rosenblum E, Mercaldo N, Fischl B, Marshall M, Frosch MP, Augustinack JC. Entorhinal vessel density correlates with phosphorylated tau and TDP-43 pathology. Alzheimers Dement 2024. [PMID: 38877668 DOI: 10.1002/alz.13896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Revised: 04/23/2024] [Accepted: 04/23/2024] [Indexed: 06/16/2024]
Abstract
INTRODUCTION The entorhinal cortex (EC) and perirhinal cortex (PC) are vulnerable to Alzheimer's disease. A triggering factor may be the interaction of vascular dysfunction and tau pathology. METHODS We imaged post mortem human tissue at 100 μm3 with 7 T magnetic resonance imaging and manually labeled individual blood vessels (mean = 270 slices/case). Vessel density was quantified and compared per EC subfield, between EC and PC, and in relation to tau and TAR DNA-binding protein 43 (TDP-43) semiquantitative scores. RESULTS PC was more vascularized than EC and vessel densities were higher in posterior EC subfields. Tau and TDP-43 strongly correlated with vasculature density and subregions with severe tau at the preclinical stage had significantly greater vessel density than those with low tau burden. DISCUSSION These data impact cerebrovascular maps, quantification of subfield vasculature, and correlation of vasculature and pathology at early stages. The ordered association of vessel density, and tau or TDP-43 pathology, may be exploited in a predictive context. HIGHLIGHTS Vessel density correlates with phosphorylated tau (p-tau) burden in entorhinal and perirhinal cortices. Perirhinal area 35 and posterior entorhinal cortex showed greatest p-tau burden but also the highest vessel density in the preclinical phase of Alzheimer's disease. We combined an ex vivo magnetic resonance imaging model and histopathology to demonstrate the 3D reconstruction of intracortical vessels and its spatial relationship to the pathology.
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Affiliation(s)
- Josué Llamas Rodríguez
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - André J W van der Kouwe
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Jan Oltmer
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Digital Health & Innovation, Vivantes Netzwerk für Gesundheit GmbH, Berlin, Germany
| | - Emma Rosenblum
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Nathaniel Mercaldo
- Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
- MGH Institute for Technology Assessment, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Bruce Fischl
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Michael Marshall
- C.S. Kubik Laboratory for Neuropathology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Matthew P Frosch
- C.S. Kubik Laboratory for Neuropathology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Jean C Augustinack
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
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Tang R, Buchholz E, Dale AM, Rissman RA, Fennema-Notestine C, Gillespie NA, Hagler DJ, Lyons MJ, Neale MC, Panizzon MS, Puckett OK, Reynolds CA, Franz CE, Kremen WS, Elman JA. Associations of plasma neurofilament light chain with cognition and neuroimaging measures in community-dwelling early old age men. Alzheimers Res Ther 2024; 16:90. [PMID: 38664843 PMCID: PMC11044425 DOI: 10.1186/s13195-024-01464-1] [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] [Received: 10/31/2023] [Accepted: 04/21/2024] [Indexed: 04/28/2024]
Abstract
BACKGROUND Plasma neurofilament light chain (NfL) is a promising biomarker of neurodegeneration with potential clinical utility in monitoring the progression of neurodegenerative diseases. However, the cross-sectional associations of plasma NfL with measures of cognition and brain have been inconsistent in community-dwelling populations. METHODS We examined these associations in a large community-dwelling sample of early old age men (N = 969, mean age = 67.57 years, range = 61-73 years), who are either cognitively unimpaired (CU) or with mild cognitive impairment (MCI). Specifically, we investigated five cognitive domains (executive function, episodic memory, verbal fluency, processing speed, visual-spatial ability), as well as neuroimaging measures of gray and white matter. RESULTS After adjusting for age, health status, and young adult general cognitive ability, plasma NfL level was only significantly associated with processing speed and white matter hyperintensity (WMH) volume, but not with other cognitive or neuroimaging measures. The association with processing speed was driven by individuals with MCI, as it was not detected in CU individuals. CONCLUSIONS These results suggest that in early old age men without dementia, plasma NfL does not appear to be sensitive to cross-sectional individual differences in most domains of cognition or neuroimaging measures of gray and white matter. The revealed plasma NfL associations were limited to WMH for all participants and processing speed only within the MCI cohort. Importantly, considering cognitive status in community-based samples will better inform the interpretation of the relationships of plasma NfL with cognition and brain and may help resolve mixed findings in the literature.
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Affiliation(s)
- Rongxiang Tang
- Department of Psychiatry, University of California San Diego, La Jolla, 92093, USA.
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, 92093, USA.
| | - Erik Buchholz
- Department of Psychiatry, University of California San Diego, La Jolla, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, 92093, USA
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, 92093, USA
- Department of Neurosciences, University of California San Diego, La Jolla, 92093, USA
| | - Robert A Rissman
- Department of Neurosciences, University of California San Diego, La Jolla, 92093, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, La Jolla, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, 92093, USA
- Department of Radiology, University of California San Diego, La Jolla, 92093, USA
| | - Nathan A Gillespie
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, VA, 23284, USA
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Donald J Hagler
- Department of Neurosciences, University of California San Diego, La Jolla, 92093, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, 02215, USA
| | - Michael C Neale
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, VA, 23284, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, 92093, USA
| | - Olivia K Puckett
- Department of Psychiatry, University of California San Diego, La Jolla, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, 92093, USA
| | - Chandra A Reynolds
- Department of Psychology and Neurosciences, University of Colorado Boulder, Boulder, 80309, USA
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, La Jolla, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, 92093, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, 92093, USA
| | - Jeremy A Elman
- Department of Psychiatry, University of California San Diego, La Jolla, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, 92093, USA
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Li Z, Sang F, Zhang Z, Li X. Effect of the duration of hypertension on white matter structure and its link with cognition. J Cereb Blood Flow Metab 2024; 44:580-594. [PMID: 37950676 PMCID: PMC10981405 DOI: 10.1177/0271678x231214073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2023] [Revised: 09/22/2023] [Accepted: 10/21/2023] [Indexed: 11/13/2023]
Abstract
The relation between hypertension (HTN) and cognition has been reported inclusive results, which may be affected by disease duration. Our study aimed to examine the influence of HTN duration on cognition and its underlying white matter (WM) changes including macrostructural WM hyperintensities (WMH) and microstructural WM integrity. A total of 1218 patients aged ≥55 years with neuropsychological assessment and a subgroup of 233 people with imaging data were recruited and divided into 3 groups (short duration: <5 years, medium duration: 5-20 years, long duration: >20 years). We found that greater HTN duration was preferentially related to worse executive function (EF), processing speed (PS), and more severe WMH, which became more significant during long duration stage. The reductions in WM integrity were evident at the early stage especially in long-range association fibers and then scattered through the whole brain. Increasing WMH and decreasing integrity of specific tracts consistently undermined EF. Furthermore, free water imaging method greatly enhanced the sensitivity in detecting HTN-related WM alterations. These findings supported that the neurological damaging effects of HTN is cumulative and neuroimaging markers of WM at macro- and microstructural level underlie the progressive effect of HTN on cognition.
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Affiliation(s)
- Zilin Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Aging Brain Rejuvenation Initiative Centre, Beijing Normal University, Beijing, China
| | - Feng Sang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Aging Brain Rejuvenation Initiative Centre, Beijing Normal University, Beijing, China
| | - Zhanjun Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Aging Brain Rejuvenation Initiative Centre, Beijing Normal University, Beijing, China
| | - Xin Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Beijing Aging Brain Rejuvenation Initiative Centre, Beijing Normal University, Beijing, China
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Riggs PK, Anderson AM, Tang B, Rubin LH, Morgello S, Marra CM, Gelman BB, Clifford DB, Franklin D, Heaton RK, Ellis RJ, Fennema-Notestine C, Letendre SL. Elevated Plasma Protein Carbonyl Concentration Is Associated with More Abnormal White Matter in People with HIV. Viruses 2023; 15:2410. [PMID: 38140650 PMCID: PMC10747698 DOI: 10.3390/v15122410] [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] [Received: 08/17/2023] [Revised: 11/23/2023] [Accepted: 12/09/2023] [Indexed: 12/24/2023] Open
Abstract
Structural brain abnormalities, including those in white matter (WM), remain common in people with HIV (PWH). Their pathogenesis is uncertain and may reflect multiple etiologies. Oxidative stress is associated with inflammation, HIV, and its comorbidities. The post-translational carbonylation of proteins results from oxidative stress, and circulating protein carbonyls may reflect this. In this cross-sectional analysis, we evaluated the associations between protein carbonyls and a panel of soluble biomarkers of neuronal injury and inflammation in plasma (N = 45) and cerebrospinal fluid (CSF, n = 32) with structural brain MRI. The volume of abnormal WM was normalized for the total WM volume (nAWM). In this multisite project, all regression models were adjusted for the scanner. The candidate covariates included demographics, HIV disease characteristics, and comorbidities. Participants were PWH on virally suppressive antiretroviral therapy (ART) and were mostly white (64.4%) men (88.9%), with a mean age of 56.8 years. In unadjusted analyses, more nAWM was associated with higher plasma protein carbonyls (p = 0.002) and higher CCL2 (p = 0.045). In the adjusted regression models for nAWM, the association with plasma protein carbonyls remained significant (FDR p = 0.018). Protein carbonyls in plasma may be a valuable biomarker of oxidative stress and its associated adverse health effects, including within the central nervous system. If confirmed, these findings would support the hypothesis that reducing oxidative stress could treat or prevent WM injury in PWH.
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Affiliation(s)
- Patricia K. Riggs
- Division of Infectious Diseases and Global Public Health, Department of Medicine, University of California San Diego, San Diego, CA 92093, USA
| | - Albert M. Anderson
- Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Bin Tang
- Department of Psychiatry, University of California San Diego, San Diego, CA 92093, USA
| | - Leah H. Rubin
- Departments of Neurology, Psychiatry and Behavioral Sciences, and Epidemiology, The Johns Hopkins University, Baltimore, MD 21205, USA
| | - Susan Morgello
- Departments of Neurology, Neuroscience, and Pathology, Mt Sinai School of Medicine, New York, NY 10029, USA
| | - Christina M. Marra
- Department of Neurology, University of Washington, Seattle, WA 98195, USA
| | - Benjamin B. Gelman
- Departments of Pathology, and Neuroscience & Cell Biology, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - David B. Clifford
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Donald Franklin
- Department of Psychiatry, University of California San Diego, San Diego, CA 92093, USA
| | - Robert K. Heaton
- Department of Psychiatry, University of California San Diego, San Diego, CA 92093, USA
| | - Ronald J. Ellis
- Department of Psychiatry, University of California San Diego, San Diego, CA 92093, USA
- Department of Neurosciences, University of California San Diego, San Diego, CA 92093, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, San Diego, CA 92093, USA
- Department of Radiology, University of California San Diego, San Diego, CA 92093, USA
| | - Scott L. Letendre
- Division of Infectious Diseases and Global Public Health, Department of Medicine, University of California San Diego, San Diego, CA 92093, USA
- Department of Psychiatry, University of California San Diego, San Diego, CA 92093, USA
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Li Z, Wang W, Sang F, Zhang Z, Li X. White matter changes underlie hypertension-related cognitive decline in older adults. Neuroimage Clin 2023; 38:103389. [PMID: 37004321 PMCID: PMC10102561 DOI: 10.1016/j.nicl.2023.103389] [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: 02/03/2023] [Revised: 03/18/2023] [Accepted: 03/25/2023] [Indexed: 03/31/2023]
Abstract
Hypertension has been well recognized as a risk factor for cognitive impairment and dementia. Although the underlying mechanisms of hypertension-affected cognitive deterioration are not fully understood, white matter changes (WMCs) seem to play an important role. WMCs include low microstructural integrity and subsequent white matter macrostructural lesions, which are common on brain imaging in hypertensive patients and are critical for multiple cognitive domains. This article provides an overview of the impact of hypertension on white matter microstructural and macrostructural changes and its link to cognitive dysfunction. Hypertension may induce microstructural changes in white matter, especially for the long-range fibers such as anterior thalamic radiation (ATR) and inferior fronto-occipital fasciculus (IFOF), and then macrostructural abnormalities affecting different lobes, especially the periventricular area. Different regions' WMCs would further exert different effects to specific cognitive domains and accelerate brain aging. As a modifiable risk factor, hypertension might provide a new perspective for alleviating and delaying cognitive impairment.
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Affiliation(s)
- Zilin Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Aging Brain Rejuvenation Initiative Centre, Beijing Normal University, Beijing 100875, China
| | - Wenxiao Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Aging Brain Rejuvenation Initiative Centre, Beijing Normal University, Beijing 100875, China
| | - Feng Sang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Aging Brain Rejuvenation Initiative Centre, Beijing Normal University, Beijing 100875, China
| | - Zhanjun Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Aging Brain Rejuvenation Initiative Centre, Beijing Normal University, Beijing 100875, China
| | - Xin Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; Beijing Aging Brain Rejuvenation Initiative Centre, Beijing Normal University, Beijing 100875, China.
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Gustavson DE, Archer DB, Elman JA, Puckett OK, Fennema-Notestine C, Panizzon MS, Shashikumar N, Hohman TJ, Jefferson AL, Eyler LT, McEvoy LK, Lyons MJ, Franz CE, Kremen WS. Associations among executive function Abilities, free Water, and white matter microstructure in early old age. Neuroimage Clin 2022; 37:103279. [PMID: 36493704 PMCID: PMC9731853 DOI: 10.1016/j.nicl.2022.103279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 10/26/2022] [Accepted: 11/30/2022] [Indexed: 12/04/2022]
Abstract
BACKGROUND Studies have investigated white matter microstructure in relation to late-life cognitive impairments, with fractional anisotropy (FA) and mean diffusivity (MD) measures thought to capture demyelination and axonal degradation. However, new post-processing methods allow isolation of free water (FW), which captures extracellular fluid contributions such as atrophy and neuroinflammation, from tissue components. FW also appears to be highly relevant to late-life cognitive impairment. Here, we evaluated whether executive functions are associated with FW, and FA and MD corrected for FW (FAFWcorr and MDFWcorr). METHOD We examined 489 non-demented men in the Vietnam Era Twin Study of Aging (VETSA) at mean age 68. Two latent factors capturing 'common executive function' and 'working-memory specific' processes were estimated based on 6 tasks. Analyses focused on 11 cortical white matter tracts across three metrics: FW, FAFWcorr, and MDFWcorr. RESULTS Better 'common executive function' was associated with lower FW across 9 of the 11 tracts. There were no significant associations with intracellular metrics after false discovery rate correction. Effects also appeared driven by individuals with MCI (13.7% of the sample). Working memory-specific tasks showed some associations with FAFWcorr, including the triangularis portion of the inferior frontal gyrus. There was no evidence that cognitive reserve (i.e., general cognitive ability assessed in early adulthood) moderated these associations between executive function and FW or FA. DISCUSSION Executive function abilities in early old age are associated primarily with extracellular fluid (FW) as opposed to white matter (FAFWcorr or MDFWcorr). Moderation analyses suggested cognitive reserve does not play a strong role in these associations, at least in this sample of non-demented men.
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Affiliation(s)
- Daniel E Gustavson
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA; Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Derek B Archer
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jeremy A Elman
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA
| | - Olivia K Puckett
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA
| | - Christine Fennema-Notestine
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA
| | - Niranjana Shashikumar
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Timothy J Hohman
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Angela L Jefferson
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA
| | - Linda K McEvoy
- Department of Radiology, University of California San Diego, La Jolla, CA, USA; Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA
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Li X, Xu N, Meng X, Dai C, Qiu X, Ding H, Lv H, Zeng R, Xie J, Zhao P, Yang Z, Gong S, Wang Z. Transverse Sinus Stenosis in Venous Pulsatile Tinnitus Patients May Lead to Brain Perfusion and White Matter Changes. Front Neurosci 2021; 15:732113. [PMID: 34955710 PMCID: PMC8694213 DOI: 10.3389/fnins.2021.732113] [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: 06/28/2021] [Accepted: 11/19/2021] [Indexed: 11/23/2022] Open
Abstract
Objective: Transverse sinus stenosis (TSS) is associated with various symptoms, but whether it can lead to pathological brain changes is unclear. This study aimed to investigate brain changes in venous pulsatile tinnitus (PT) patients with TSS. Materials and Methods: In this study, fifty-five consecutive venous PT patients and fifty age- and gender-matched healthy controls (HCs) were investigated. In CT venography, the combined conduit score (CCS) was used to assess the degree of TSS in venous PT patients. Magnetic resonance venography was used to assess TSS in HCs. All the participants had undergone arterial spin labeling and structural MRI scans. Results: Two patients without TSS and ten HCs with TSS were excluded. Fifty-three venous PT patients with TSS and 40 HCs without TSS were included in this study. All the patients had unilateral cases: 16 on the left and 37 on the right. Based on the CCS, the patients were divided into high-degree TSS (a score of 1–2) (n = 30) and low-degree TSS groups (a score of 3–4) (n = 23). In the whole brain and gray matter, the patients with high-degree TSS showed decreased cerebral blood flow (CBF) compared with patients with low-degree TSS as well as HCs (P < 0.05), and no significant difference in CBF was found in patients with low-degree TSS and HCs (P > 0.05). In white matter (WM) regions, the patients with high-degree TSS exhibited decreased CBF relative to the HCs (P < 0.05). The incidence of cloud-like WM hyperintensity was significantly higher in the above two patient groups than in the HC group (P < 0.05). Conclusion: TSS in venous PT patients may lead to decreased CBF and cloud-like WM hyperintensity. These neuroimaging findings may provide new insights into pathological TSS in venous PT.
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Affiliation(s)
- Xiaoshuai Li
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Ning Xu
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Xuxu Meng
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Chihang Dai
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Xiaoyu Qiu
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Heyu Ding
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Han Lv
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Rong Zeng
- Department of Otolaryngology Head and Neck Surgery, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Jing Xie
- Department of Otolaryngology Head and Neck Surgery, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Pengfei Zhao
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Zhenghan Yang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Shusheng Gong
- Department of Otolaryngology Head and Neck Surgery, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Zhenchang Wang
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
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Franz CE, Hatton SN, Elman JA, Warren T, Gillespie NA, Whitsel NA, Puckett OK, Dale AM, Eyler LT, Fennema-Notestine C, Hagler DJ, Hauger RL, McKenzie R, Neale MC, Panizzon MS, Pearce RC, Reynolds CA, Sanderson-Cimino M, Toomey R, Tu XM, Williams M, Xian H, Lyons MJ, Kremen WS. Lifestyle and the aging brain: interactive effects of modifiable lifestyle behaviors and cognitive ability in men from midlife to old age. Neurobiol Aging 2021; 108:80-89. [PMID: 34547718 PMCID: PMC8862767 DOI: 10.1016/j.neurobiolaging.2021.08.007] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Revised: 07/23/2021] [Accepted: 08/12/2021] [Indexed: 01/18/2023]
Abstract
We examined the influence of lifestyle on brain aging after nearly 30 years, and tested the hypothesis that young adult general cognitive ability (GCA) would moderate these effects. In the community-dwelling Vietnam Era Twin Study of Aging (VETSA), 431 largely non-Hispanic white men completed a test of GCA at mean age 20. We created a modifiable lifestyle behavior composite from data collected at mean age 40. During VETSA, MRI-based measures at mean age 68 included predicted brain age difference (PBAD), Alzheimer's disease (AD) brain signature, and abnormal white matter scores. There were significant main effects of young adult GCA and lifestyle on PBAD and the AD signature (ps ≤ 0.012), and a GCA-by-lifestyle interaction on both (ps ≤ 0.006). Regardless of GCA level, having more favorable lifestyle behaviors predicted less advanced brain age and less AD-like brain aging. Unfavorable lifestyles predicted advanced brain aging in those with lower age 20 GCA, but did not affect brain aging in those with higher age 20 GCA. Targeting early lifestyle modification may promote dementia risk reduction, especially among lower reserve individuals.
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Affiliation(s)
- Carol E Franz
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA.
| | - Sean N Hatton
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Jeremy A Elman
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Teresa Warren
- Department of Psychology, San Diego State University, San Diego, CA, USA
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA; QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
| | - Nathan A Whitsel
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Olivia K Puckett
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Anders M Dale
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA; Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, San Diego, CA, USA
| | - Richard L Hauger
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
| | - Ruth McKenzie
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behavior Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Rahul C Pearce
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
| | - Chandra A Reynolds
- Department of Psychology, University of California Riverside, Riverside, CA, USA
| | - Mark Sanderson-Cimino
- San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA; Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
| | - Rosemary Toomey
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Xin M Tu
- Department of Family Medicine, University of California San Diego, San Diego, CA, USA
| | - McKenna Williams
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA; San Diego State University/University of California San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
| | - Hong Xian
- Department of Epidemiology & Biostatistics, St. Louis University, St. Louis, MO, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA; Center for Behavior Genetics of Aging, University of California San Diego, San Diego, CA, USA
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9
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Moyano LM, Montano SM, Vilchez Barreto P, Reto N, Larrauri L, Mori N, Cornejo-Olivas M, Guevara-Silva E, Urizar F, Najar E, Gamboa R, Azabache C, Herrer Ticse R, Bolivar-Herrada L, Doud A, Martinez P, Miranda JJ, Zunt JR, García HH. Prevalence of stroke survival in rural communities living in northern Peru. PLoS One 2021; 16:e0254440. [PMID: 34324513 PMCID: PMC8321101 DOI: 10.1371/journal.pone.0254440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Accepted: 06/27/2021] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND AND PURPOSE Stroke is the leading cause of neurological impairment in the South American Andean region. However, the epidemiology of stroke in the region has been poorly characterized. METHODS We conducted a staged three-phase population-based study applying a validated eight-question neurological survey in 80 rural villages in Tumbes, northern Peru, then confirmed presence or absence of stroke through a neurologist's examination to estimate the prevalence of stroke. RESULTS Our survey covered 90% of the population (22,278/24,854 individuals, mean age 30±21.28, 48.45% females), and prevalence of stroke was 7.05/1,000 inhabitants. After direct standardization to WHO's world standard population, adjusted prevalence of stroke was 6.94/1,000 inhabitants. Participants aged ≥85 years had higher stroke prevalence (>50/1000 inhabitants) compared to other stratified ages, and some unusual cases of stroke were found among individuals aged 25-34 years. The lowest age reported for a first stroke event was 16.8 years. High blood pressure (aPR 4.2 [2.7-6.4], p>0.001), and sedentary lifestyle (aPR 1.6 [1.0-2.6], p = 0.045) were more prevalent in people with stroke. CONCLUSIONS The age-standardized prevalence of stroke in this rural coastal Peruvian population was slightly higher than previously reported in studies from surrounding rural South American settings, but lower than in rural African and Asian regions. The death rate from stroke was much higher than in industrialized and middle-income countries.
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Affiliation(s)
- Luz M. Moyano
- Cysticercosis Elimination Program, Center for Global Health, Universidad Peruana Cayetano Heredia, Tumbes, Perú
| | - Silvia M. Montano
- Sección de Epidemiologia, Instituto de Medicina Tropical Daniel Alcides carrión Universidad Nacional Mayor de San Marcos, Lima, Perú
| | - Percy Vilchez Barreto
- Cysticercosis Elimination Program, Center for Global Health, Universidad Peruana Cayetano Heredia, Tumbes, Perú
| | - Narcisa Reto
- Cysticercosis Elimination Program, Center for Global Health, Universidad Peruana Cayetano Heredia, Tumbes, Perú
| | - Luis Larrauri
- Centro Basico de Investigación en Demencia y enfermedades desmielinizantes, Instituto Nacional de Ciencias Neurológicas, Lima, Perú
| | - Nicanor Mori
- Departamento de Medicina, Hospital Nacional Daniel Alcides Carriòn, Lima, Perú
| | - Mario Cornejo-Olivas
- Cysticercosis Elimination Program, Center for Global Health, Universidad Peruana Cayetano Heredia, Tumbes, Perú
- Neurogenetics Research center (MC), Instituto Nacional de Ciencias Neurológicas, Lima, Perú
| | - Erik Guevara-Silva
- Centro Basico de Investigación en Demencia y enfermedades desmielinizantes, Instituto Nacional de Ciencias Neurológicas, Lima, Perú
| | - Fernando Urizar
- Cysticercosis Elimination Program, Center for Global Health, Universidad Peruana Cayetano Heredia, Tumbes, Perú
| | - Enrique Najar
- Departamento de Medicina, Hospital Nacional Cayetano Heredia, Lima, Perú
| | - Ricardo Gamboa
- Cysticercosis Elimination Program, Center for Global Health, Universidad Peruana Cayetano Heredia, Tumbes, Perú
| | - Cintya Azabache
- Cysticercosis Elimination Program, Center for Global Health, Universidad Peruana Cayetano Heredia, Tumbes, Perú
| | - Raquel Herrer Ticse
- Cysticercosis Elimination Program, Center for Global Health, Universidad Peruana Cayetano Heredia, Tumbes, Perú
| | - Lucia Bolivar-Herrada
- Cysticercosis Elimination Program, Center for Global Health, Universidad Peruana Cayetano Heredia, Tumbes, Perú
| | - Alex Doud
- Departments of Neurology, Global Health, Medicine and Epidemiology, University of Washington, Seattle, WA, United State of America
| | - Peggy Martinez
- Departamento de Pediatría, Instituto Nacional del Niño, San Borja, Lima, Perú
| | - J. Jaime Miranda
- Cysticercosis Elimination Program, Center for Global Health, Universidad Peruana Cayetano Heredia, Tumbes, Perú
- CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Perú
| | - Joseph R. Zunt
- Departamento de Medicina, Hospital Nacional Cayetano Heredia, Lima, Perú
| | - Hector H. García
- Cysticercosis Elimination Program, Center for Global Health, Universidad Peruana Cayetano Heredia, Tumbes, Perú
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10
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Li J, Zhang Q, Che Y, Zhang N, Guo L. Iron Deposition Characteristics of Deep Gray Matter in Elderly Individuals in the Community Revealed by Quantitative Susceptibility Mapping and Multiple Factor Analysis. Front Aging Neurosci 2021; 13:611891. [PMID: 33935681 PMCID: PMC8079745 DOI: 10.3389/fnagi.2021.611891] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 03/15/2021] [Indexed: 12/23/2022] Open
Abstract
Purpose The objective of this study was to determine which factors influence brain iron concentrations in deep gray matter in elderly individuals and how these factors influence regional brain iron concentrations. Methods A total of 105 elderly individuals were enrolled in this study. All participants underwent detailed magnetic resonance imaging (MRI) examinations from October 2018 to August 2019. Among them, 44 individuals had undergone a previous MRI examination from July 2010 to August 2011. Quantitative susceptibility mapping (QSM) was utilized as an indirect quantitative marker of brain iron, and the susceptibility values of deep gray matter structures were obtained. Univariate analysis and multiple linear regression analysis were used to investigate 11 possible determinants for cerebral iron deposition. Results Our results showed no sex- or hemisphere-related differences in susceptibility values in any of the regions studied. Aging was significantly correlated with increased insusceptibility values in almost all analyzed brain regions (except for the thalamus) when we compared the susceptibility values at the two time points. In a cross-sectional analysis, the relationship between gray matter nucleus susceptibility values and age was conducted using Pearson’s linear regression. Aging was significantly correlated with the susceptibility values of the globus pallidus (GP), putamen (Put), and caudate nucleus (CN), with the Put having the strongest correlations. In multiple linear regression models, associations with increased susceptibility values were found in the CN, Put, red nucleus, and dentate nucleus for individuals with a history of type 2 diabetes mellitus (T2DM). However, the patients with hypertension showed significantly reduced susceptibility values in the red nucleus and dentate nucleus. Our data suggested that smokers had increased susceptibility values in the thalamus. No significant associations were found for individuals with a history of hypercholesterolemia and Apolipoprotein E4 carrier status. Conclusion Our data revealed that aging, T2DM, and smoking could increase iron deposition in some deep gray matter structures. However, hypertension had the opposite effects in the red nuclei and dentate nuclei. Brain iron metabolism could be influenced by many factors in different modes. In future studies, we should strictly control for confounding factors.
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Affiliation(s)
- Jing Li
- Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Qihao Zhang
- Department of Radiology, Weill Cornell Medical College, Cornell University, New York City, NY, United States
| | - Yena Che
- Department of Clinical Laboratory, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Nan Zhang
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Lingfei Guo
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
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11
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Sanderson-Cimino M, Panizzon MS, Elman JA, Tu X, Gustavson DE, Puckett O, Cross K, Notestine R, Hatton SN, Eyler LT, McEvoy LK, Hagler DJ, Neale MC, Gillespie NA, Lyons MJ, Franz CE, Fennema-Notestine C, Kremen WS. Periventricular and deep abnormal white matter differ in associations with cognitive performance at midlife. Neuropsychology 2021; 35:252-264. [PMID: 33970659 PMCID: PMC8500190 DOI: 10.1037/neu0000718] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
Objective: Abnormal white matter (AWM) on magnetic resonance imaging is associated with cognitive performance in older adults. We explored cognitive associations with AWM during late-midlife. Method: Participants were community-dwelling men (n = 242; M = 61.90 years; range = 56-66). Linear-mixed effects regression models examined associations of total, periventricular, and deep AWM with cognitive performance, controlling for multiple comparisons. Models considering specific cognitive domains controlled for current general cognitive ability (GCA). We hypothesized that total AWM would be associated with worse processing speed, executive function, and current GCA; deep AWM would correlate with GCA and periventricular AWM would relate to specific cognitive abilities. We also assessed the potential influence of cognitive reserve by examining a moderation effect of early life (mean age of 20) cognition. Results: Greater total and deep AWM were associated with poorer current GCA. Periventricular AWM was associated with worse executive function, working memory, and episodic memory. When periventricular and deep AWM were modeled simultaneously, both retained their respective significant associations with cognitive performance. Cognitive reserve did not moderate associations. Conclusions: Our findings suggest that AWM contributes to poorer cognitive function in late-midlife. Examining only total AWM may obscure the potential differential impact of regional AWM. Separating total AWM into subtypes while controlling for current GCA revealed a dissociation in relationships with cognitive performance; deep AWM was associated with nonspecific cognitive ability whereas periventricular AWM was associated with specific frontal-related abilities and memory. Management of vascular or other risk factors that may increase the risk of AWM should begin during or before early late-midlife. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
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Affiliation(s)
- Mark Sanderson-Cimino
- Joint Doctoral Program in Clinical Psychology, San Diego State/University of California
- Center for Behavior Genetics of Aging, University of California
| | - Matthew S. Panizzon
- Center for Behavior Genetics of Aging, University of California
- Department of Psychiatry University of California
| | - Jeremy A. Elman
- Center for Behavior Genetics of Aging, University of California
- Department of Psychiatry University of California
| | - Xin Tu
- Family Medicine and Public Health, University of California
| | - Daniel E. Gustavson
- Center for Behavior Genetics of Aging, University of California
- Department of Psychiatry University of California
- Department of Medicine, Vanderbilt University Medical Center
| | - Olivia Puckett
- Center for Behavior Genetics of Aging, University of California
- Department of Psychiatry University of California
| | | | - Randy Notestine
- Department of Psychiatry University of California
- Computational and Applied Statistics Laboratory (CASL) at the San Diego Supercomputer Center
| | - Sean N Hatton
- Center for Behavior Genetics of Aging, University of California
- Department of Psychiatry University of California
- Department of Neurosciences, University of California
| | - Lisa T. Eyler
- Department of Psychiatry University of California
- Mental Illness Research, Education, And Clinical Center, Veterans Affairs San Diego Healthcare System
| | - Linda K. McEvoy
- Department of Radiology, University of California, San Diego
| | | | - Michael C. Neale
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University
| | - Nathan A. Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University
| | - Michael J. Lyons
- Department of Psychological and Brain Sciences, Boston University
| | - Carol E. Franz
- Center for Behavior Genetics of Aging, University of California
- Department of Psychiatry University of California
| | - Christine Fennema-Notestine
- Center for Behavior Genetics of Aging, University of California
- Department of Psychiatry University of California
- Department of Radiology, University of California, San Diego
| | - William S. Kremen
- Center for Behavior Genetics of Aging, University of California
- Department of Psychiatry University of California
- Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System
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12
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Reas ET, Laughlin GA, Hagler DJ, Lee RR, Dale AM, McEvoy LK. Age and Sex Differences in the Associations of Pulse Pressure With White Matter and Subcortical Microstructure. Hypertension 2021; 77:938-947. [PMID: 33461315 DOI: 10.1161/hypertensionaha.120.16446] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Midlife vascular disease increases risk for dementia and effects of vascular dysfunction on brain health differ between men and women. Elevated pulse pressure, a surrogate for arterial stiffness, contributes to cerebrovascular pathology and white matter damage that may advance cognitive aging; however, it remains unclear how associations between pulse pressure and neural integrity differ by sex and age. This study used restriction spectrum imaging to examine associations between pulse pressure and brain microstructure in community-dwelling women (N=88) and men (N=55), aged 56 to 97 (mean, 76.3) years. Restricted isotropic (presumed intracellular), hindered isotropic (presumed extracellular), neurite density, and free water diffusion were computed in white matter tracts and subcortical regions. After adjustment for age and sex, higher pulse pressure correlated with lower restricted isotropic diffusion in global white matter, with more pronounced associations in parahippocampal cingulum, as well as in thalamus and hippocampus. Subgroup analyses demonstrated stronger correlations between pulse pressure and restricted isotropic diffusion in association fibers for participants ≤75 years than for older participants, with stronger effects for women than men of this age group. Microstructure in parahippocampal cingulum and thalamus differed by pulse pressure level regardless of antihypertensive treatment. Increased pulse pressure may lead to widespread injury to white matter and subcortical structures, with greatest vulnerability for women in late middle to early older age. Restriction spectrum imaging could be useful for monitoring microstructural changes indicative of neuronal loss or shrinkage, demyelination, or inflammation that accompany age-related cerebrovascular dysfunction.
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Affiliation(s)
- Emilie T Reas
- From the Department of Neurosciences (E.T.R., A.M.D.), University of California, San Diego
| | - Gail A Laughlin
- Department of Family Medicine and Public Health (G.A.L., L.K.M.), University of California, San Diego
| | - Donald J Hagler
- Department of Radiology (D.J.H., R.R.L., A.M.D., L.K.M.), University of California, San Diego
| | - Roland R Lee
- Department of Radiology (D.J.H., R.R.L., A.M.D., L.K.M.), University of California, San Diego.,Radiology Services, VA San Diego Healthcare System (R.R.L.)
| | - Anders M Dale
- From the Department of Neurosciences (E.T.R., A.M.D.), University of California, San Diego.,Department of Radiology (D.J.H., R.R.L., A.M.D., L.K.M.), University of California, San Diego
| | - Linda K McEvoy
- Department of Family Medicine and Public Health (G.A.L., L.K.M.), University of California, San Diego.,Department of Radiology (D.J.H., R.R.L., A.M.D., L.K.M.), University of California, San Diego
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13
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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: 6.5] [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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14
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Cardiometabolic determinants of early and advanced brain alterations: Insights from conventional and novel MRI techniques. Neurosci Biobehav Rev 2020; 115:308-320. [DOI: 10.1016/j.neubiorev.2020.04.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 02/21/2020] [Accepted: 04/02/2020] [Indexed: 12/11/2022]
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15
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Franz CE, Hatton SN, Hauger RL, Kredlow MA, Dale AM, Eyler L, McEvoy LK, Fennema-Notestine C, Hagler D, Jacobson KC, McKenzie RE, Panizzon MS, Gustavson DE, Xian H, Toomey R, Beck A, Stevens S, Tu X, Lyons MJ, Kremen WS. Posttraumatic stress symptom persistence across 24 years: association with brain structures. Brain Imaging Behav 2020; 14:1208-1220. [PMID: 30830577 PMCID: PMC6722032 DOI: 10.1007/s11682-019-00059-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
Posttraumatic stress disorder (PTSD) is known to persist, eliciting early medical co-morbidity, and accelerated aging. Although PTSD diagnosis has been found to be associated with smaller volume in multiple brain regions, posttraumatic stress (PTS) symptoms and their associations with brain morphometry are rarely assessed over long periods of time. We predicted that persistent PTS symptoms across ~24 years would be inversely associated with hippocampal, amygdala, anterior cingulate volumes, and hippocampal occupancy (HOC = hippocampal volume/[hippocampal volume + inferior lateral ventricle volume]) in late middle age. Exploratory analyses examined prefrontal regions. We assessed PTS symptoms in 247 men at average ages 38 (time 1) and 62 (time 2). All were trauma-exposed prior to time 1. Brain volumes were assessed at time 2 using 3 T structural magnetic resonance imaging. Symptoms were correlated over time (r = 0.46 p < .0001). Higher PTS symptoms averaged over time and symptoms at time 1 were both associated with lower hippocampal, amygdala, rostral middle frontal gyrus (MFG), and medial orbitofrontal cortex (OFC) volumes, and a lower HOC ratio at time 2. Increased PTS symptomatology from time 1 to time 2 was associated with smaller hippocampal volume. Results for hippocampal, rostral MFG and medial OFC remained significant after omitting individuals above the threshold for PTSD diagnosis. Even at sub-diagnostic threshold levels, PTS symptoms were present decades after trauma exposure in parallel with highly correlated structural deficits in brain regions regulating stress responsivity and adaptation.
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Affiliation(s)
- Carol E Franz
- Department of Psychiatry MC 0738, University of California San Diego, La Jolla, CA, 92093, USA.
| | - Sean N Hatton
- Department of Psychiatry MC 0738, University of California San Diego, La Jolla, CA, 92093, USA
- Department of Radiology, University of California San Diego, La Jolla, CA, 92093, USA
| | - Richard L Hauger
- Department of Psychiatry MC 0738, University of California San Diego, La Jolla, CA, 92093, USA
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, La Jolla, CA, 92093, USA
| | - M Alexandra Kredlow
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, 02215, USA
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, CA, 92093, USA
| | - Lisa Eyler
- Department of Psychiatry MC 0738, University of California San Diego, La Jolla, CA, 92093, USA
| | - Linda K McEvoy
- Department of Radiology, University of California San Diego, La Jolla, CA, 92093, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry MC 0738, University of California San Diego, La Jolla, CA, 92093, USA
- Department of Radiology, University of California San Diego, La Jolla, CA, 92093, USA
| | - Donald Hagler
- Department of Radiology, University of California San Diego, La Jolla, CA, 92093, USA
| | - Kristen C Jacobson
- Department of Psychiatry & Behavioral Neuroscience, University of Chicago, Chicago, IL, 60637, USA
| | - Ruth E McKenzie
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, 02215, USA
| | - Matthew S Panizzon
- Department of Psychiatry MC 0738, University of California San Diego, La Jolla, CA, 92093, USA
| | - Daniel E Gustavson
- Department of Psychiatry MC 0738, University of California San Diego, La Jolla, CA, 92093, USA
| | - Hong Xian
- Department of Epidemiology and Biostatistics, St Louis University, St Louis, MO, 60134, USA
| | - Rosemary Toomey
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, 02215, USA
| | - Asad Beck
- Department of Psychology, San Diego State University, San Diego, CA, 92182, USA
| | - Samantha Stevens
- Department of Psychiatry MC 0738, University of California San Diego, La Jolla, CA, 92093, USA
| | - Xin Tu
- Department of Family Medicine and Public Health, University of California San Diego, La Jolla, CA, 92093, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, 02215, USA
| | - William S Kremen
- Department of Psychiatry MC 0738, University of California San Diego, La Jolla, CA, 92093, USA
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, La Jolla, CA, 92093, USA
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16
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Armstrong NJ, Mather KA, Sargurupremraj M, Knol MJ, Malik R, Satizabal CL, Yanek LR, Wen W, Gudnason VG, Dueker ND, Elliott LT, Hofer E, Bis J, Jahanshad N, Li S, Logue MA, Luciano M, Scholz M, Smith AV, Trompet S, Vojinovic D, Xia R, Alfaro-Almagro F, Ames D, Amin N, Amouyel P, Beiser AS, Brodaty H, Deary IJ, Fennema-Notestine C, Gampawar PG, Gottesman R, Griffanti L, Jack CR, Jenkinson M, Jiang J, Kral BG, Kwok JB, Lampe L, C M Liewald D, Maillard P, Marchini J, Bastin ME, Mazoyer B, Pirpamer L, Rafael Romero J, Roshchupkin GV, Schofield PR, Schroeter ML, Stott DJ, Thalamuthu A, Trollor J, Tzourio C, van der Grond J, Vernooij MW, Witte VA, Wright MJ, Yang Q, Morris Z, Siggurdsson S, Psaty B, Villringer A, Schmidt H, Haberg AK, van Duijn CM, Jukema JW, Dichgans M, Sacco RL, Wright CB, Kremen WS, Becker LC, Thompson PM, Mosley TH, Wardlaw JM, Ikram MA, Adams HHH, Seshadri S, Sachdev PS, Smith SM, Launer L, Longstreth W, DeCarli C, Schmidt R, Fornage M, Debette S, Nyquist PA. Common Genetic Variation Indicates Separate Causes for Periventricular and Deep White Matter Hyperintensities. Stroke 2020; 51:2111-2121. [PMID: 32517579 DOI: 10.1161/strokeaha.119.027544] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
BACKGROUND AND PURPOSE Periventricular white matter hyperintensities (WMH; PVWMH) and deep WMH (DWMH) are regional classifications of WMH and reflect proposed differences in cause. In the first study, to date, we undertook genome-wide association analyses of DWMH and PVWMH to show that these phenotypes have different genetic underpinnings. METHODS Participants were aged 45 years and older, free of stroke and dementia. We conducted genome-wide association analyses of PVWMH and DWMH in 26,654 participants from CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology), ENIGMA (Enhancing Neuro-Imaging Genetics Through Meta-Analysis), and the UKB (UK Biobank). Regional correlations were investigated using the genome-wide association analyses -pairwise method. Cross-trait genetic correlations between PVWMH, DWMH, stroke, and dementia were estimated using LDSC. RESULTS In the discovery and replication analysis, for PVWMH only, we found associations on chromosomes 2 (NBEAL), 10q23.1 (TSPAN14/FAM231A), and 10q24.33 (SH3PXD2A). In the much larger combined meta-analysis of all cohorts, we identified ten significant regions for PVWMH: chromosomes 2 (3 regions), 6, 7, 10 (2 regions), 13, 16, and 17q23.1. New loci of interest include 7q36.1 (NOS3) and 16q24.2. In both the discovery/replication and combined analysis, we found genome-wide significant associations for the 17q25.1 locus for both DWMH and PVWMH. Using gene-based association analysis, 19 genes across all regions were identified for PVWMH only, including the new genes: CALCRL (2q32.1), KLHL24 (3q27.1), VCAN (5q27.1), and POLR2F (22q13.1). Thirteen genes in the 17q25.1 locus were significant for both phenotypes. More extensive genetic correlations were observed for PVWMH with small vessel ischemic stroke. There were no associations with dementia for either phenotype. CONCLUSIONS Our study confirms these phenotypes have distinct and also shared genetic architectures. Genetic analyses indicated PVWMH was more associated with ischemic stroke whilst DWMH loci were implicated in vascular, astrocyte, and neuronal function. Our study confirms these phenotypes are distinct neuroimaging classifications and identifies new candidate genes associated with PVWMH only.
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Affiliation(s)
- Nicola J Armstrong
- Mathematics and Statistics, Murdoch University, Perth, Australia (N.J.A.)
| | - Karen A Mather
- Centre for Healthy Brain Ageing, School of Psychiatry (K.A.M., W.W., H.B., J.J., A.T., J.T., P.S.S.), University of New South Wales, Sydney, Australia.,Neuroscience Research Australia, Sydney, Australia (K.A.M., P.R.S., A.T.)
| | | | - Maria J Knol
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands (M.J.K., D.V., N.A., G.V.R., M.W.V., C.M.v.D., M.A.I., H.H.H.A.)
| | - Rainer Malik
- Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig-Maximilians-Universität LMU Munich, Germany (R.M., M.D.)
| | - Claudia L Satizabal
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX (C.L.S., S.S.).,The Framingham Heart Study, MA (C.L.S., A.S.B., J.R.R., S.S.).,Department of Neurology (C.L.S., A.S.B., J.R.R., S.S.), Boston University School of Medicine, MA
| | - Lisa R Yanek
- GeneSTAR Research Program (L.R.Y., B.G.K., L.C.B., P.A.N.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Wei Wen
- Centre for Healthy Brain Ageing, School of Psychiatry (K.A.M., W.W., H.B., J.J., A.T., J.T., P.S.S.), University of New South Wales, Sydney, Australia
| | - Vilmundur G Gudnason
- Icelandic Heart Association, Kopavogur (V.G.G., S.S.).,University of Iceland, Reykjavik, Iceland (V.G.G., A.V.S.)
| | - Nicole D Dueker
- Dr. John T. Macdonald Foundation Department of Human Genetics (R.L.S.), University of Miami, FL
| | - Lloyd T Elliott
- Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, BC, Canada (L.T.E.).,Wellcome Centre for Integrative Neuroimaging (WIN FMRIB) (L.T.E., F.A.-A., L.G., M.J., S.M.S.), University of Oxford, United Kingdom
| | - Edith Hofer
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Austria (E.H., R.S.).,Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Austria (E.H.)
| | - Joshua Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA (J.B., B.P., W.L.)
| | - Neda Jahanshad
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Marina del Rey (N.J., P.M.T.)
| | - Shuo Li
- Department of Biostatistics, Boston University School of Public Health, Boston, MA (S.L., M.A.L., A.S.B., Q.Y.)
| | - Mark A Logue
- Department of Psychiatry and Biomedical Genetics Section (M.A.L.), Boston University School of Medicine, MA.,Department of Biostatistics, Boston University School of Public Health, Boston, MA (S.L., M.A.L., A.S.B., Q.Y.).,National Center for PTSD: Behavioral Science Division, VA Boston Healthcare System, Boston, MA (M.A.L.)
| | - Michelle Luciano
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, United Kingdom (M.L., I.J.D., D.C.M.L., M.E.B., J.M.W.)
| | - Markus Scholz
- Institute for Medical Informatics, Statistics and Epidemiology (M.S.)
| | - Albert V Smith
- University of Iceland, Reykjavik, Iceland (V.G.G., A.V.S.)
| | - Stella Trompet
- Department of Internal Medicine, Section of Gerontology and Geriatrics (S.T.), Leiden University Medical Center, the Netherlands.,Department of Cardiology (S.T.), Leiden University Medical Center, the Netherlands
| | - Dina Vojinovic
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands (M.J.K., D.V., N.A., G.V.R., M.W.V., C.M.v.D., M.A.I., H.H.H.A.)
| | - Rui Xia
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, TX (R.X., M.F.)
| | - Fidel Alfaro-Almagro
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB) (L.T.E., F.A.-A., L.G., M.J., S.M.S.), University of Oxford, United Kingdom
| | - David Ames
- National Ageing Research Institute, Parkville, Victoria, Australia (D.A.).,Academic Unit for Psychiatry of Old Age, University of Melbourne, St George's Hospital, Kew, Australia (D.A.)
| | - Najaf Amin
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands (M.J.K., D.V., N.A., G.V.R., M.W.V., C.M.v.D., M.A.I., H.H.H.A.)
| | - Philippe Amouyel
- Lille University, Inserm, Institut Pasteur de Lille, RID-AGE - Risk Factors and Molecular Determinants of Aging-Related Diseases and Labex Distalz, France (P.A.).,Lille University, Inserm, CHU Lille, Institut Pasteur de Lille, RID-AGE (P.A.)
| | - Alexa S Beiser
- The Framingham Heart Study, MA (C.L.S., A.S.B., J.R.R., S.S.).,Department of Neurology (C.L.S., A.S.B., J.R.R., S.S.), Boston University School of Medicine, MA.,Department of Biostatistics, Boston University School of Public Health, Boston, MA (S.L., M.A.L., A.S.B., Q.Y.)
| | - Henry Brodaty
- Centre for Healthy Brain Ageing, School of Psychiatry (K.A.M., W.W., H.B., J.J., A.T., J.T., P.S.S.), University of New South Wales, Sydney, Australia.,Dementia Centre for Research Collaboration (H.B.), University of New South Wales, Sydney, Australia
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, United Kingdom (M.L., I.J.D., D.C.M.L., M.E.B., J.M.W.)
| | - Christine Fennema-Notestine
- Department of Psychiatry (C.F.-N.), University of California, San Diego, La Jolla, CA.,Center for Behavior Genetics of Aging (C.F.-N.), University of California, San Diego, La Jolla, CA
| | - Piyush G Gampawar
- Gottfried Schatz Research Center (for Cell Signaling, Metabolism and Aging), Medical University of Graz, Austria (P.G.G., H.S.)
| | - Rebecca Gottesman
- Department of Neurology, Cerebrovascular and stroke Division (R.G.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Ludovica Griffanti
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB) (L.T.E., F.A.-A., L.G., M.J., S.M.S.), University of Oxford, United Kingdom
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN (C.R.J.J.)
| | - Mark Jenkinson
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB) (L.T.E., F.A.-A., L.G., M.J., S.M.S.), University of Oxford, United Kingdom
| | - Jiyang Jiang
- Centre for Healthy Brain Ageing, School of Psychiatry (K.A.M., W.W., H.B., J.J., A.T., J.T., P.S.S.), University of New South Wales, Sydney, Australia
| | - Brian G Kral
- GeneSTAR Research Program (L.R.Y., B.G.K., L.C.B., P.A.N.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - John B Kwok
- School of Medical Sciences (J.B.K., P.R.S.), University of New South Wales, Sydney, Australia.,Brain and Mind Centre - The University of Sydney, Camperdown, NSW, Australia (J.B.K.)
| | - Leonie Lampe
- Department of Neurology, Max-Planck-Institute for Human Cognitive and Brain Sciences, Leipzig, Germany (L.L., V.A.W.)
| | - David C M Liewald
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, United Kingdom (M.L., I.J.D., D.C.M.L., M.E.B., J.M.W.)
| | - Pauline Maillard
- Imaging of Dementia and Aging (IDeA) Laboratory, Department of Neurology, University of California-Davis, Davis, CA (P.M.)
| | - Jonathan Marchini
- Statistical Genetics and Methods at Regeneron Pharmaceuticals, Inc, New York, NY (J.M.)
| | - Mark E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, United Kingdom (M.L., I.J.D., D.C.M.L., M.E.B., J.M.W.).,Centre for Clinical Brain Sciences, Edinburgh Imaging, Centre for Cognitive Ageing, University of Edinburgh, United Kingdom (M.E.B., J.M.W.)
| | - Bernard Mazoyer
- Institut des Maladies Neurodégénératives, University of Bordeaux, France (B.M.)
| | - Lukas Pirpamer
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Austria (L.P.)
| | - José Rafael Romero
- The Framingham Heart Study, MA (C.L.S., A.S.B., J.R.R., S.S.).,Department of Neurology (C.L.S., A.S.B., J.R.R., S.S.), Boston University School of Medicine, MA
| | - Gennady V Roshchupkin
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands (M.J.K., D.V., N.A., G.V.R., M.W.V., C.M.v.D., M.A.I., H.H.H.A.).,Department of Radiology and Nuclear Medicine (G.V.R., M.W.V., H.H.H.A.)
| | - Peter R Schofield
- School of Medical Sciences (J.B.K., P.R.S.), University of New South Wales, Sydney, Australia.,Neuroscience Research Australia, Sydney, Australia (K.A.M., P.R.S., A.T.)
| | - Matthias L Schroeter
- LIFE Research Center for Civilization Disease, Leipzig, Germany (M.S.).,Department of Neurology, Max-Planck-Institute for Human Cognitive and Brain Sciences, Leipzig, Germany (M.L.S., A.V.).,Day Clinic for Cognitive Neurology, University Hospital Leipzig, Germany (M.L.S., A.V.)
| | - David J Stott
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, United Kingdom (D.J.S.)
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Ageing, School of Psychiatry (K.A.M., W.W., H.B., J.J., A.T., J.T., P.S.S.), University of New South Wales, Sydney, Australia.,Neuroscience Research Australia, Sydney, Australia (K.A.M., P.R.S., A.T.)
| | - Julian Trollor
- Centre for Healthy Brain Ageing, School of Psychiatry (K.A.M., W.W., H.B., J.J., A.T., J.T., P.S.S.), University of New South Wales, Sydney, Australia.,Department of Developmental Disability Neuropsychiatry, School of Psychiatry (J.T.), University of New South Wales, Sydney, Australia
| | - Christophe Tzourio
- University Bordeaux, Inserm, Bordeaux Population Health Research Center, France (M.S., C.T., S.D.).,CHU de Bordeaux, Public Health Department, Medical information Department, Bordeaux, France (C.T.)
| | - Jeroen van der Grond
- Department of Radiology (J.v.d.G.), Leiden University Medical Center, the Netherlands
| | - Meike W Vernooij
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands (M.J.K., D.V., N.A., G.V.R., M.W.V., C.M.v.D., M.A.I., H.H.H.A.).,Department of Radiology and Nuclear Medicine (G.V.R., M.W.V., H.H.H.A.)
| | - Veronica A Witte
- Collaborative Research Center 1052 Obesity Mechanisms, Faculty of Medicine, University of Leipzig, Germany (V.A.W).,Department of Neurology, Max-Planck-Institute for Human Cognitive and Brain Sciences, Leipzig, Germany (L.L., V.A.W.)
| | - Margaret J Wright
- Queensland Brain Institute (M.J.W.), The University of Queensland, St Lucia, QLD, Australia.,Centre for Advanced Imaging (M.J.W.), The University of Queensland, St Lucia, QLD, Australia
| | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA (S.L., M.A.L., A.S.B., Q.Y.)
| | - Zoe Morris
- Neuroradiology Department, Department of Clinical Neurosciences, Western General Hospital, Edinburgh, United Kingdom (Z.M.)
| | - Siggi Siggurdsson
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX (C.L.S., S.S.).,The Framingham Heart Study, MA (C.L.S., A.S.B., J.R.R., S.S.).,Department of Neurology (C.L.S., A.S.B., J.R.R., S.S.), Boston University School of Medicine, MA
| | - Bruce Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA (J.B., B.P., W.L.)
| | - Arno Villringer
- Department of Neurology, Max-Planck-Institute for Human Cognitive and Brain Sciences, Leipzig, Germany (M.L.S., A.V.).,Day Clinic for Cognitive Neurology, University Hospital Leipzig, Germany (M.L.S., A.V.)
| | - Helena Schmidt
- Gottfried Schatz Research Center (for Cell Signaling, Metabolism and Aging), Medical University of Graz, Austria (P.G.G., H.S.)
| | - Asta K Haberg
- Department of Neuromedicine and Movement Science (A.K.H.), Norwegian University of Science and Technology, Trondheim, Norway.,Department of Radiology and Nuclear Medicine (A.K.H.), Norwegian University of Science and Technology, Trondheim, Norway
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands (M.J.K., D.V., N.A., G.V.R., M.W.V., C.M.v.D., M.A.I., H.H.H.A.).,Nuffield Department of Population Health (C.M.v.D.), University of Oxford, United Kingdom
| | - J Wouter Jukema
- Department of Cardiology (J.W.J.), Leiden University Medical Center, the Netherlands.,Einthoven Laboratory for Experimental Vascular Medicine, LUMC, Leiden, the Netherlands (J.W.J.)
| | - Martin Dichgans
- Institute for Stroke and Dementia Research (ISD), University Hospital, Ludwig-Maximilians-Universität LMU Munich, Germany (R.M., M.D.).,German Center for Neurodegenerative Diseases, Munich, Germany (M.D.).,Munich Cluster for Systems Neurology (SyNergy), Germany (M.D.)
| | - Ralph L Sacco
- Department of Public Health Sciences, Miller School of Medicine (R.L.S.), University of Miami, FL.,Department of Neurology, Miller School of Medicine (R.L.S.), University of Miami, FL.,Evelyn F. McKnight Brain Institute, Department of Neurology (R.L.S.), University of Miami, FL
| | - Clinton B Wright
- National Institute of Neurological Disorders and Stroke (C.B.W.), National Institutes of Health, Bethesda, MD
| | - William S Kremen
- Center for Behavior Genetics of Aging (W.S.K.), University of California, San Diego, La Jolla, CA.,Department of Psychiatry (W.S.K.), University of California, San Diego, La Jolla, CA
| | - Lewis C Becker
- GeneSTAR Research Program (L.R.Y., B.G.K., L.C.B., P.A.N.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Paul M Thompson
- Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Marina del Rey (N.J., P.M.T.)
| | - Thomas H Mosley
- Department of Geriatric Medicine, Memory Impairment and Neurodegenerative Dementia (MIND) Center, University of Mississippi Medical Center, Jackson (T.H.M.)
| | - Joanna M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, United Kingdom (M.L., I.J.D., D.C.M.L., M.E.B., J.M.W.).,Centre for Clinical Brain Sciences, Edinburgh Imaging, Centre for Cognitive Ageing, University of Edinburgh, United Kingdom (M.E.B., J.M.W.)
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands (M.J.K., D.V., N.A., G.V.R., M.W.V., C.M.v.D., M.A.I., H.H.H.A.)
| | - Hieab H H Adams
- Department of Epidemiology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands (M.J.K., D.V., N.A., G.V.R., M.W.V., C.M.v.D., M.A.I., H.H.H.A.).,Department of Radiology and Nuclear Medicine (G.V.R., M.W.V., H.H.H.A.).,Department of Clinical Genetics, Erasmus MC, Rotterdam, the Netherlands (H.H.H.A.)
| | | | - Perminder S Sachdev
- Centre for Healthy Brain Ageing, School of Psychiatry (K.A.M., W.W., H.B., J.J., A.T., J.T., P.S.S.), University of New South Wales, Sydney, Australia.,Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, Australia (P.S.S.)
| | - Stephen M Smith
- Wellcome Centre for Integrative Neuroimaging (WIN FMRIB) (L.T.E., F.A.-A., L.G., M.J., S.M.S.), University of Oxford, United Kingdom
| | - Lenore Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Intramural Research Program (L.L.), National Institutes of Health, Bethesda, MD
| | - William Longstreth
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA (J.B., B.P., W.L.)
| | - Charles DeCarli
- Alzheimer's Disease Center and Imaging of Dementia and Aging (IDeA) Laboratory, Department of Neurology and Center for Neuroscience University of California at Davis (C.D.)
| | - Reinhold Schmidt
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, Austria (E.H., R.S.)
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, TX (R.X., M.F.).,Human Genetics Center, School of Public Health UT, Houston, TX (M.F.)
| | - Stephanie Debette
- University Bordeaux, Inserm, Bordeaux Population Health Research Center, France (M.S., C.T., S.D.).,Department of Neurology, CHU de Bordeaux (University Hospital), Bordeaux, France (S.D.)
| | - Paul A Nyquist
- GeneSTAR Research Program (L.R.Y., B.G.K., L.C.B., P.A.N.), Johns Hopkins University School of Medicine, Baltimore, MD.,Departments of Neurology, Critical Care Medicine, Neurosurgery (P.A.N.), Johns Hopkins University School of Medicine, Baltimore, MD.,Critical Care Medicine Department (P.A.N.), National Institutes of Health, Bethesda, MD
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17
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Franz CE, Xian H, Lew D, Hatton SN, Puckett O, Whitsel N, Beck A, Dale AM, Fang B, Fennema-Notestine C, Hauger RL, Jacobson KC, Lyons MJ, Reynolds CA, Kremen WS. Body mass trajectories and cortical thickness in middle-aged men: a 42-year longitudinal study starting in young adulthood. Neurobiol Aging 2019; 79:11-21. [PMID: 31026618 PMCID: PMC6591047 DOI: 10.1016/j.neurobiolaging.2019.03.003] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2018] [Revised: 03/01/2019] [Accepted: 03/05/2019] [Indexed: 01/30/2023]
Abstract
Evidence strongly suggests that being overweight or obese at midlife confers significantly higher risk for Alzheimer's disease and greater brain atrophy later in life. Few studies, however, examine associations between longitudinal changes in adiposity during early adulthood and later brain morphometry. Measures of body mass index (BMI) were collected in 373 men from the Vietnam Era Twin Study of Aging at average ages 20, 40, 56, and 62 years, yielding 2 BMI trajectories. We then examined associations between BMI phenotypes (trajectories, continuous BMI, obese/nonobese), cortical thickness, and white matter measures from structural magnetic resonance imaging at mean age 62 (time 4, range 56-66 years). Those on the obesity trajectory (N = 171) had a thinner cortex compared with the normal/lean trajectory (N = 202) in multiple frontal and temporal lobe bilateral regions of interest: superior, inferior, middle temporal gyri, temporal pole, fusiform gyrus, banks of the superior temporal sulcus, frontal pole, pars triangularis, caudal and rostral middle frontal gyri (all p < 0.05, false discovery rate corrected). Frontal lobe thinness tended to occur mainly in the right hemisphere. Results were similar for obese versus nonobese adults at age 62. There were no significant differences for white matter volume or abnormalities. Taken in the context of other research, these associations between brain structures and excess BMI at midlife suggest potential for increased risk for cognitive decline in later life.
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Affiliation(s)
- Carol E. Franz
- Department of Psychiatry & Center for Behavior Genetics of Aging, University of California San Diego, La Jolla CA, USA
| | - Hong Xian
- Department of Epidemiology & Biostatistics, St. Louis University, St. Louis, MO, USA
| | - Daphne Lew
- Department of Epidemiology & Biostatistics, St. Louis University, St. Louis, MO, USA
| | - Sean N. Hatton
- Department of Psychiatry & Center for Behavior Genetics of Aging, University of California San Diego, La Jolla CA, USA
| | - Olivia Puckett
- Department of Psychiatry & Center for Behavior Genetics of Aging, University of California San Diego, La Jolla CA, USA
| | - Nathan Whitsel
- Department of Psychiatry & Center for Behavior Genetics of Aging, University of California San Diego, La Jolla CA, USA
| | - Asad Beck
- Department of Psychology, San Diego State University, San Diego, CA, USA
| | - Anders M. Dale
- Department of Radiology, University of California San Diego, La Jolla CA, USA
| | - Bin Fang
- Department of Psychiatry & Center for Behavior Genetics of Aging, University of California San Diego, La Jolla CA, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry & Center for Behavior Genetics of Aging, University of California San Diego, La Jolla CA, USA,Department of Radiology, University of California San Diego, La Jolla CA, USA
| | - Richard L. Hauger
- Department of Psychiatry & Center for Behavior Genetics of Aging, University of California San Diego, La Jolla CA, USA,Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, USA
| | - Kristen C. Jacobson
- Department of Psychiatry & Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - Michael J. Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Chandra A. Reynolds
- Department of Psychology, University of California Riverside, Riverside, CA, USA
| | - William S. Kremen
- Department of Psychiatry & Center for Behavior Genetics of Aging, University of California San Diego, La Jolla CA, USA,Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, USA
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18
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Zhao Y, Ke Z, He W, Cai Z. Volume of white matter hyperintensities increases with blood pressure in patients with hypertension. J Int Med Res 2019; 47:3681-3689. [PMID: 31242795 PMCID: PMC6726811 DOI: 10.1177/0300060519858023] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Objective Hypertension is a risk factor for development of white matter hyperintensities (WMHs). However, the relationship between hypertension and WMHs remains obscure. We sought to clarify this relationship using clinical data from different regions of China. Methods We analyzed the data of 333 patients with WMHs in this study. All included patients underwent conventional magnetic resonance imaging (MRI) examination. A primary diagnosis of WMHs was made according to MRI findings. The volume burden of WMHs was investigated using the Fazekas scale, which is widely used to rate the degree of WMHs. We conducted retrospective clinical analysis of the data in this study. Results Our findings showed that WMHs in patients with hypertension were associated with diabetes, cardiovascular diseases, history of cerebral infarct, and plasma glucose and triglyceride levels. Fazekas scale scores for WMHs increased with increased blood pressure values in patients with hypertension. Conclusion This analysis indicates that hypertension is an independent contributor to the prevalence and severity of WMHs.
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Affiliation(s)
- Yu Zhao
- 1 Department of Neurology, the Fourth Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Zunyu Ke
- 2 Department of Neurology, Renmin Hospital, Hubei University of Medicine, Shiyan Renmin Hospital, Shiyan, Hubei Province, China
| | - Wenbo He
- 2 Department of Neurology, Renmin Hospital, Hubei University of Medicine, Shiyan Renmin Hospital, Shiyan, Hubei Province, China
| | - Zhiyou Cai
- 3 Department of Neurology, Chongqing General Hospital, University of Chinese Academy of Sciences, Chongqing, Chongqing, China.,4 Chongqing Key Laboratory of Neurodegenerative Diseases, Chongqing, Chongqing, China
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19
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Abstract
OBJECTIVE The influence of confounding neurocognitive comorbidities in people living with HIV (PLWH) on neuroimaging has not been systematically evaluated. We determined associations between comorbidity burden and brain integrity and examined the moderating effect of age on these relationships. DESIGN Observational, cross-sectional substudy of the CNS HIV Antiretroviral Therapy Effects Research cohort. METHODS A total of 288 PLWH (mean age = 44.2) underwent structural MRI and magnetic resonance spectroscopy as well as neurocognitive and neuromedical assessments. Consistent with Frascati criteria for HIV-associated neurocognitive disorders (HAND), neuromedical and neuropsychiatric comorbidity burden was classified as incidental (mild), contributing (moderate), or confounding (severe-exclusionary) to a diagnosis of HAND. Multiple regression modeling predicted neuroimaging outcomes as a function of comorbidity classification, age, and their interaction. RESULTS Comorbidity classifications were 176 incidental, 77 contributing, and 35 confounded; groups did not differ in HIV disease characteristics. Relative to incidental and contributing participants, confounded participants had less cortical gray matter and more abnormal white matter and ventricular cerebrospinal fluid, alongside more neuroinflammation (choline, myo-inositol) and less neuronal integrity (N-acetylaspartate). Older age exacerbated the impact of comorbidity burden: to a greater extent in the confounded group, older age was associated with more abnormal white matter (P = 0.017), less total white matter (P = 0.015), and less subcortical gray matter (P = 0.014). CONCLUSION Neuroimaging in PLWH reveals signatures associated with confounding neurocognitive conditions, emphasizing the importance of evaluating these among individuals with suspected HAND. Older age amplifies subcortical and white matter tissue injury, especially in PLWH with severe comorbidity burden, warranting increased attention to this population as it ages.
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20
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Konijnenberg E, Carter SF, Ten Kate M, den Braber A, Tomassen J, Amadi C, Wesselman L, Nguyen HT, van de Kreeke JA, Yaqub M, Demuru M, Mulder SD, Hillebrand A, Bouwman FH, Teunissen CE, Serné EH, Moll AC, Verbraak FD, Hinz R, Pendleton N, Lammertsma AA, van Berckel BNM, Barkhof F, Boomsma DI, Scheltens P, Herholz K, Visser PJ. The EMIF-AD PreclinAD study: study design and baseline cohort overview. ALZHEIMERS RESEARCH & THERAPY 2018; 10:75. [PMID: 30075734 PMCID: PMC6091034 DOI: 10.1186/s13195-018-0406-7] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Accepted: 07/12/2018] [Indexed: 12/26/2022]
Abstract
Background Amyloid pathology is the pathological hallmark in Alzheimer’s disease (AD) and can precede clinical dementia by decades. So far it remains unclear how amyloid pathology leads to cognitive impairment and dementia. To design AD prevention trials it is key to include cognitively normal subjects at high risk for amyloid pathology and to find predictors of cognitive decline in these subjects. These goals can be accomplished by targeting twins, with additional benefits to identify genetic and environmental pathways for amyloid pathology, other AD biomarkers, and cognitive decline. Methods From December 2014 to October 2017 we enrolled cognitively normal participants aged 60 years and older from the ongoing Manchester and Newcastle Age and Cognitive Performance Research Cohort and the Netherlands Twins Register. In Manchester we included single individuals, and in Amsterdam monozygotic twin pairs. At baseline, participants completed neuropsychological tests and questionnaires, and underwent physical examination, blood sampling, ultrasound of the carotid arteries, structural and resting state functional brain magnetic resonance imaging, and dynamic amyloid positron emission tomography (PET) scanning with [18F]flutemetamol. In addition, the twin cohort underwent lumbar puncture for cerebrospinal fluid collection, buccal cell collection, magnetoencephalography, optical coherence tomography, and retinal imaging. Results We included 285 participants, who were on average 74.8 ± 9.7 years old, 64% female. Fifty-eight participants (22%) had an abnormal amyloid PET scan. Conclusions A rich baseline dataset of cognitively normal elderly individuals has been established to estimate risk factors and biomarkers for amyloid pathology and future cognitive decline. Electronic supplementary material The online version of this article (10.1186/s13195-018-0406-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Elles Konijnenberg
- Alzheimer Center, Department of Neurology, VU University Medical Center, Neuroscience Amsterdam, PO Box 7057, 1007 MB, Amsterdam, The Netherlands.
| | - Stephen F Carter
- Wolfson Molecular Imaging Centre, Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK
| | - Mara Ten Kate
- Alzheimer Center, Department of Neurology, VU University Medical Center, Neuroscience Amsterdam, PO Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - Anouk den Braber
- Alzheimer Center, Department of Neurology, VU University Medical Center, Neuroscience Amsterdam, PO Box 7057, 1007 MB, Amsterdam, The Netherlands.,Department of Biological Psychology, VU University, Neuroscience Amsterdam, Amsterdam, The Netherlands
| | - Jori Tomassen
- Alzheimer Center, Department of Neurology, VU University Medical Center, Neuroscience Amsterdam, PO Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - Chinenye Amadi
- Wolfson Molecular Imaging Centre, Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK
| | - Linda Wesselman
- Alzheimer Center, Department of Neurology, VU University Medical Center, Neuroscience Amsterdam, PO Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - Hoang-Ton Nguyen
- Department of Ophthalmology, VU University Medical Center, Neuroscience Amsterdam, Amsterdam, The Netherlands
| | - Jacoba A van de Kreeke
- Department of Ophthalmology, VU University Medical Center, Neuroscience Amsterdam, Amsterdam, The Netherlands
| | - Maqsood Yaqub
- Department of Radiology & Nuclear Medicine, VU University Medical Center, Neuroscience Amsterdam, Amsterdam, The Netherlands
| | - Matteo Demuru
- Alzheimer Center, Department of Neurology, VU University Medical Center, Neuroscience Amsterdam, PO Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - Sandra D Mulder
- Neurochemistry Laboratory, Department of Clinical Chemistry, VU University Medical Center, Neuroscience Amsterdam, Amsterdam, The Netherlands
| | - Arjan Hillebrand
- Department of Clinical Neurophysiology, VU University Medical Center, Neuroscience Amsterdam, Amsterdam, The Netherlands
| | - Femke H Bouwman
- Alzheimer Center, Department of Neurology, VU University Medical Center, Neuroscience Amsterdam, PO Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, VU University Medical Center, Neuroscience Amsterdam, Amsterdam, The Netherlands
| | - Erik H Serné
- Department of Internal Medicine, VU University Medical Center, Neuroscience Amsterdam, Amsterdam, The Netherlands
| | - Annette C Moll
- Department of Ophthalmology, VU University Medical Center, Neuroscience Amsterdam, Amsterdam, The Netherlands
| | - Frank D Verbraak
- Department of Ophthalmology, VU University Medical Center, Neuroscience Amsterdam, Amsterdam, The Netherlands
| | - Rainer Hinz
- Wolfson Molecular Imaging Centre, Division of Informatics, Imaging and Data Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Neil Pendleton
- Wolfson Molecular Imaging Centre, Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK
| | - Adriaan A Lammertsma
- Department of Radiology & Nuclear Medicine, VU University Medical Center, Neuroscience Amsterdam, Amsterdam, The Netherlands
| | - Bart N M van Berckel
- Department of Radiology & Nuclear Medicine, VU University Medical Center, Neuroscience Amsterdam, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology & Nuclear Medicine, VU University Medical Center, Neuroscience Amsterdam, Amsterdam, The Netherlands.,Institutes of Neurology & Healthcare Engineering, UCL, London, UK
| | - Dorret I Boomsma
- Department of Biological Psychology, VU University, Neuroscience Amsterdam, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center, Department of Neurology, VU University Medical Center, Neuroscience Amsterdam, PO Box 7057, 1007 MB, Amsterdam, The Netherlands
| | - Karl Herholz
- Wolfson Molecular Imaging Centre, Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK
| | - Pieter Jelle Visser
- Alzheimer Center, Department of Neurology, VU University Medical Center, Neuroscience Amsterdam, PO Box 7057, 1007 MB, Amsterdam, The Netherlands.,Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, The Netherlands
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21
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Ten Kate M, Sudre CH, den Braber A, Konijnenberg E, Nivard MG, Cardoso MJ, Scheltens P, Ourselin S, Boomsma DI, Barkhof F, Visser PJ. White matter hyperintensities and vascular risk factors in monozygotic twins. Neurobiol Aging 2018; 66:40-48. [PMID: 29505954 DOI: 10.1016/j.neurobiolaging.2018.02.002] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2017] [Revised: 01/15/2018] [Accepted: 02/04/2018] [Indexed: 11/16/2022]
Abstract
Cerebral white matter hyperintensities (WMHs) have been associated with vascular risk factors, both of which are under genetic influence. We examined in a monozygotic twin sample whether the association between vascular risk and WMHs is influenced by overlapping genetic factors. We included 195 cognitively normal monozygotic twins (age = 70 ± 7 years), including 94 complete pairs. Regional WMH load was estimated using an automated algorithm. Vascular risk was summarized with the Framingham score. The within-twin pair correlation for total WMHs was 0.76 and for Framingham score was 0.77. Within participants, Framingham score was associated with total and periventricular WMHs (r = 0.32). Framingham score in 1 twin was also associated with total WMHs in the co-twin (r = 0.26). Up to 83% of the relation between both traits could be explained by shared genetic effects. In conclusion, monozygotic twins have highly similar vascular risk and WMH burden, confirming a genetic background for these traits. The association between both traits is largely driven by overlapping genetic factors.
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Affiliation(s)
- Mara Ten Kate
- Alzheimer Center, Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands.
| | - Carole H Sudre
- Translational Imaging Group, Centre for Medical Image Computing (CMIC), University College London, London, UK
| | - Anouk den Braber
- Alzheimer Center, Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands; Department of Biological Psychology, VU University Amsterdam, Amsterdam, the Netherlands
| | - Elles Konijnenberg
- Alzheimer Center, Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands
| | - Michel G Nivard
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, the Netherlands
| | - M Jorge Cardoso
- Translational Imaging Group, Centre for Medical Image Computing (CMIC), University College London, London, UK
| | - Philip Scheltens
- Alzheimer Center, Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands
| | - Sébastien Ourselin
- Translational Imaging Group, Centre for Medical Image Computing (CMIC), University College London, London, UK
| | - Dorret I Boomsma
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, the Netherlands
| | - Frederik Barkhof
- Translational Imaging Group, Centre for Medical Image Computing (CMIC), University College London, London, UK; Department of Radiology and Nuclear Medicine, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands
| | - Pieter Jelle Visser
- Alzheimer Center, Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands; Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, Maastricht, the Netherlands
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22
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Alcohol intake and brain white matter in middle aged men: Microscopic and macroscopic differences. NEUROIMAGE-CLINICAL 2018; 18:390-398. [PMID: 29487796 PMCID: PMC5816025 DOI: 10.1016/j.nicl.2018.02.006] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Revised: 01/29/2018] [Accepted: 02/05/2018] [Indexed: 11/22/2022]
Abstract
Heavy alcohol consumption is associated with deleterious changes in the brain but associations of moderate alcohol intake are not well understood. We examined the association of alcohol consumption with brain white matter health in 377 middle-aged men (56-66 years old; mean 61.8 ± 2.6 years) who were participants in the Vietnam Era Twin Study of Aging (VETSA). T1-, T2-, proton density-, and diffusion-weighted magnetic resonance images were obtained. Diffusion measures were quantified from 12 major white matter tracts. Global white matter lesion (WML) burden was also quantified. Mixed effects linear models examined differences in diffusivity and WMLs by amount of alcohol intake. Analyses adjusted for numerous demographic, health, and lifestyle variables. An inverted-U association was found between alcohol intake and fractional anisotropy (FA) in several tracts, including the inferior-frontal-occipital fasciculus, uncinate fasciculus, superior longitudinal fasciculus, the forceps minor and the anterior thalamic radiations. In these tracts, FA increased with increasing alcohol intake, peaking with moderate alcohol intake (9-28 drinks in 14 days), and declining with heavier intake. Associations remained significant after exclusion of individuals with diabetes or hypertension. There was a U-shaped association in WML burden with highest burden among never drinkers and heavy drinkers (>28 drinks in 14 days). This association was no longer significant after exclusion of individuals with hypertension, since WML burden among heavy drinkers no longer differed from that of other drinkers. This suggests that hypertension related to heavy alcohol intake may contribute to WML burden observed among heavy drinkers. Together, these correlational results suggest that among middle-aged men, moderate drinking may be associated with metrics of better white matter health, particularly microstructural measures, whereas drinking beyond recommended guidelines may be associated with both microstructural and macrostructural white matter damage.
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23
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Petkus AJ, Reynolds CA, Wetherell JL, Kremen WS, Gatz M. Temporal dynamics of cognitive performance and anxiety across older adulthood. Psychol Aging 2017; 32:278-292. [PMID: 28333502 PMCID: PMC5573587 DOI: 10.1037/pag0000164] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Cognitive decline and anxiety symptoms commonly co-occur in later life, but the temporal order of changes on these two attributes is unclear. Specifically, it is unknown if greater anxiety leads to subsequent declines in cognitive performance or if worse cognitive performance leads to increased anxiety. In this study, we sought to elucidate the temporal dynamics between anxiety symptoms and cognitive performance across old age-that is, the extent to which level and change in one variable influence subsequent changes in a second variable. We examined data from 721 nondemented participants from the Swedish Adoption/Twin Study of Aging. Participants completed as many as eight assessments of cognitive performance and anxiety over a 26-year period. Bivariate dual-change score models were fit to examine the dynamic association between anxiety and cognitive performance. Bidirectional associations between anxiety and cognitive performance were found among measures of processing speed, attention, and memory but not visuospatial abilities. Higher anxiety was associated with greater declines in processing speed over the duration of 6 years and worsening attention over a span of 3 years. The reverse direction was also significant in that slower processing speed, worse attention, and poorer nonverbal and working memory performance were associated with larger increases in anxiety 3 years later. These findings highlight that in cognitively intact older adults, the association between anxiety and worse cognitive performance is bidirectional and complex. (PsycINFO Database Record
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Affiliation(s)
- Andrew J. Petkus
- Department of Psychology, University of Southern California, Los Angeles, CA, 90089-1061
| | - Chandra A. Reynolds
- Department of Psychology, University of California, Riverside, Riverside, CA, 92521
| | - Julie Loebach Wetherell
- VA San Diego Healthcare System, San Diego, CA, 92093
- Department of Psychiatry, University of California, San Diego, San Diego, CA, 92093
| | - William S. Kremen
- Department of Psychiatry, University of California, San Diego, San Diego, CA, 92093
- VA Center of Excellence for Stress and Mental Health, San Diego, CA 92093
| | - Margaret Gatz
- Department of Psychology, University of Southern California, Los Angeles, CA, 90089-1061
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 171 77 Stockholm, Sweden
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