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Chen J, Li J, Wang X, Fu X, Ke J, Li J, Wen J, Cheng K, Li S, Shi Z. Heme Oxygenase-1 Gene (GT)n Polymorphism Linked to Deep White Matter Hyperintensities, Not Periventricular Hyperintensities. J Am Heart Assoc 2024; 13:e033981. [PMID: 38818928 DOI: 10.1161/jaha.123.033981] [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: 12/13/2023] [Accepted: 05/01/2024] [Indexed: 06/01/2024]
Abstract
BACKGROUND Oxidative stress plays a principal role in the pathogenesis of white matter hyperintensities (WMHs). The induction of heme oxygenase-1 (HO-1) gene in the brain represents 1 of the pivotal mechanisms to counteract the noxious effects of reactive oxygen species, and the transcriptional modulation of HO-1 induction depends on the length of a GT-repeat (GT)n in the promoter region. We investigated whether the HO-1 gene (GT)n polymorphism is associated with the risk of WMHs. METHODS AND RESULTS A total of 849 subjects from the memory clinic were consecutively enrolled, and the HO-1 (GT)n genotype was determined. WMHs were assessed with the Fazekas scale and further divided into periventricular WMHs and deep WMHs (DWMHs). Allelic HO-1 (GT)n polymorphisms were classified as short (≤24 (GT)n), median (25≤[GT]n<31), or long (31≤[GT]n). Multivariate logistic regression analysis was used to evaluate the effect of the HO-1 (GT)n variants on WMHs. The number of repetitions of the HO-1 gene (GT)n ranged from 15 to 39 with a bimodal distribution at lengths 23 and 30. The proportion of S/S genotypes was higher for moderate/severe DWMHs than none/mild DWMHs (22.22% versus 12.44%; P=0.001), but the association for periventricular WMHs was not statistically significant. Logistic regression suggested that the S/S genotype was significantly associated with moderate/severe DWMHs (S/S versus non-S/S: odds ratio, 2.001 [95% CI, 1.323-3.027]; P<0.001). The HO-1 gene (GT)n S/S genotype and aging synergistically contributed to the progression of DWMHs (relative excess risk attributable to interaction, 6.032 [95% CI, 0.149-11.915]). CONCLUSIONS Short (GT)n variants in the HO-1 gene may confer susceptibility to rather than protection from DWMHs, but not periventricular WMHs. REGISTRATION URL: https://www.chictr.org.cn; Unique identifier: ChiCTR2100045869.
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Affiliation(s)
- Junting Chen
- Department of Neurology and Memory Center The 10th Affiliate Hospital, Southern Medical University Dongguan China
- Postgraduate School Guangdong Medical University Zhanjiang Guangdong China
| | - Jinrui Li
- Department of Neurology and Memory Center The 10th Affiliate Hospital, Southern Medical University Dongguan China
- The 1st Clinical Medical School Southern Medical University Dongguan China
| | - Xiaomian Wang
- Postgraduate School Guangdong Medical University Zhanjiang Guangdong China
| | - Xiaoli Fu
- Department of Neurology and Memory Center The 10th Affiliate Hospital, Southern Medical University Dongguan China
| | - Jianxia Ke
- The 1st Clinical Medical School Southern Medical University Dongguan China
| | - Jintao Li
- The 1st Clinical Medical School Southern Medical University Dongguan China
| | - Jia Wen
- Postgraduate School Guangdong Medical University Zhanjiang Guangdong China
| | - Kailin Cheng
- Postgraduate School Guangdong Medical University Zhanjiang Guangdong China
| | - Shuen Li
- Department of Neurology and Memory Center The 10th Affiliate Hospital, Southern Medical University Dongguan China
| | - Zhu Shi
- Department of Neurology and Memory Center The 10th Affiliate Hospital, Southern Medical University Dongguan China
- Postgraduate School Guangdong Medical University Zhanjiang Guangdong China
- The 1st Clinical Medical School Southern Medical University Dongguan China
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Nyúl-Tóth Á, Patai R, Csiszar A, Ungvari A, Gulej R, Mukli P, Yabluchanskiy A, Benyo Z, Sotonyi P, Prodan CI, Liotta EM, Toth P, Elahi F, Barsi P, Maurovich-Horvat P, Sorond FA, Tarantini S, Ungvari Z. Linking peripheral atherosclerosis to blood-brain barrier disruption: elucidating its role as a manifestation of cerebral small vessel disease in vascular cognitive impairment. GeroScience 2024:10.1007/s11357-024-01194-0. [PMID: 38831182 DOI: 10.1007/s11357-024-01194-0] [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: 04/10/2024] [Accepted: 05/06/2024] [Indexed: 06/05/2024] Open
Abstract
Aging plays a pivotal role in the pathogenesis of cerebral small vessel disease (CSVD), contributing to the onset and progression of vascular cognitive impairment and dementia (VCID). In older adults, CSVD often leads to significant pathological outcomes, including blood-brain barrier (BBB) disruption, which in turn triggers neuroinflammation and white matter damage. This damage is frequently observed as white matter hyperintensities (WMHs) in neuroimaging studies. There is mounting evidence that older adults with atherosclerotic vascular diseases, such as peripheral artery disease, ischemic heart disease, and carotid artery stenosis, face a heightened risk of developing CSVD and VCID. This review explores the complex relationship between peripheral atherosclerosis, the pathogenesis of CSVD, and BBB disruption. It explores the continuum of vascular aging, emphasizing the shared pathomechanisms that underlie atherosclerosis in large arteries and BBB disruption in the cerebral microcirculation, exacerbating both CSVD and VCID. By reviewing current evidence, this paper discusses the impact of endothelial dysfunction, cellular senescence, inflammation, and oxidative stress on vascular and neurovascular health. This review aims to enhance understanding of these complex interactions and advocate for integrated approaches to manage vascular health, thereby mitigating the risk and progression of CSVD and VCID.
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Affiliation(s)
- Ádám Nyúl-Tóth
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Department of Public Health, Semmelweis University, Semmelweis University, Budapest, Hungary
| | - Roland Patai
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Anna Csiszar
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Stephenson Cancer Center, University of Oklahoma, Oklahoma City, OK, USA
| | - Anna Ungvari
- Department of Public Health, Semmelweis University, Semmelweis University, Budapest, Hungary.
| | - Rafal Gulej
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Peter Mukli
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Department of Public Health, Semmelweis University, Semmelweis University, Budapest, Hungary
| | - Andriy Yabluchanskiy
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Stephenson Cancer Center, University of Oklahoma, Oklahoma City, OK, USA
- Department of Health Promotion Sciences, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Doctoral College/Department of Public Health, International Training Program in Geroscience, Semmelweis University, Budapest, Hungary
| | - Zoltan Benyo
- Institute of Translational Medicine, Semmelweis University, 1094, Budapest, Hungary
- Cerebrovascular and Neurocognitive Disorders Research Group, HUN-REN, Semmelweis University, 1094, Budapest, Hungary
| | - Peter Sotonyi
- Department of Vascular and Endovascular Surgery, Heart and Vascular Centre, Semmelweis University, 1122, Budapest, Hungary
| | - Calin I Prodan
- Veterans Affairs Medical Center, Oklahoma City, OK, USA
- Department of Neurology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Eric M Liotta
- Doctoral College/Department of Public Health, International Training Program in Geroscience, Semmelweis University, Budapest, Hungary
- Department of Neurology, Division of Stroke and Neurocritical Care, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Peter Toth
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Department of Public Health, Semmelweis University, Semmelweis University, Budapest, Hungary
- Department of Neurosurgery, Medical School, University of Pecs, Pecs, Hungary
- Neurotrauma Research Group, Szentagothai Research Centre, University of Pecs, Pecs, Hungary
- ELKH-PTE Clinical Neuroscience MR Research Group, University of Pecs, Pecs, Hungary
| | - Fanny Elahi
- Departments of Neurology and Neuroscience Ronald M. Loeb Center for Alzheimer's Disease Friedman Brain Institute Icahn School of Medicine at Mount Sinai, New York, NY, USA
- James J. Peters VA Medical Center, Bronx, NY, USA
| | - Péter Barsi
- ELKH-SE Cardiovascular Imaging Research Group, Department of Radiology, Medical Imaging Centre, Semmelweis University, Budapest, Hungary
| | - Pál Maurovich-Horvat
- ELKH-SE Cardiovascular Imaging Research Group, Department of Radiology, Medical Imaging Centre, Semmelweis University, Budapest, Hungary
| | - Farzaneh A Sorond
- Department of Neurology, Division of Stroke and Neurocritical Care, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Stefano Tarantini
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Stephenson Cancer Center, University of Oklahoma, Oklahoma City, OK, USA
- Department of Health Promotion Sciences, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Doctoral College/Department of Public Health, International Training Program in Geroscience, Semmelweis University, Budapest, Hungary
| | - Zoltan Ungvari
- Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Stephenson Cancer Center, University of Oklahoma, Oklahoma City, OK, USA
- Department of Health Promotion Sciences, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
- Doctoral College/Department of Public Health, International Training Program in Geroscience, Semmelweis University, Budapest, Hungary
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Yong J, Song J. CaMKII activity and metabolic imbalance-related neurological diseases: Focus on vascular dysfunction, synaptic plasticity, amyloid beta accumulation, and lipid metabolism. Biomed Pharmacother 2024; 175:116688. [PMID: 38692060 DOI: 10.1016/j.biopha.2024.116688] [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: 02/01/2024] [Revised: 04/25/2024] [Accepted: 04/29/2024] [Indexed: 05/03/2024] Open
Abstract
Metabolic syndrome (MetS) is characterized by insulin resistance, hyperglycemia, excessive fat accumulation and dyslipidemia, and is known to be accompanied by neuropathological symptoms such as memory loss, anxiety, and depression. As the number of MetS patients is rapidly increasing globally, studies on the mechanisms of metabolic imbalance-related neuropathology are emerging as an important issue. Ca2+/calmodulin-dependent kinase II (CaMKII) is the main Ca2+ sensor and contributes to diverse intracellular signaling in peripheral organs and the central nervous system (CNS). CaMKII exerts diverse functions in cells, related to mechanisms such as RNA splicing, reactive oxygen species (ROS) generation, cytoskeleton, and protein-protein interactions. In the CNS, CaMKII regulates vascular function, neuronal circuits, neurotransmission, synaptic plasticity, amyloid beta toxicity, lipid metabolism, and mitochondrial function. Here, we review recent evidence for the role of CaMKII in neuropathologic issues associated with metabolic disorders.
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Affiliation(s)
- Jeongsik Yong
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota Twin Cities, Minneapolis, MN, USA
| | - Juhyun Song
- Department of Anatomy, Chonnam National University Medical School, Hwasun, Jeollanam-do, Republic of Korea.
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Le Grand Q, Tsuchida A, Koch A, Imtiaz MA, Aziz NA, Vigneron C, Zago L, Lathrop M, Dubrac A, Couffinhal T, Crivello F, Matthews PM, Mishra A, Breteler MMB, Tzourio C, Debette S. Diffusion imaging genomics provides novel insight into early mechanisms of cerebral small vessel disease. Mol Psychiatry 2024:10.1038/s41380-024-02604-7. [PMID: 38811690 DOI: 10.1038/s41380-024-02604-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 05/06/2024] [Accepted: 05/09/2024] [Indexed: 05/31/2024]
Abstract
Cerebral small vessel disease (cSVD) is a leading cause of stroke and dementia. Genetic risk loci for white matter hyperintensities (WMH), the most common MRI-marker of cSVD in older age, were recently shown to be significantly associated with white matter (WM) microstructure on diffusion tensor imaging (signal-based) in young adults. To provide new insights into these early changes in WM microstructure and their relation with cSVD, we sought to explore the genetic underpinnings of cutting-edge tissue-based diffusion imaging markers across the adult lifespan. We conducted a genome-wide association study of neurite orientation dispersion and density imaging (NODDI) markers in young adults (i-Share study: N = 1 758, (mean[range]) 22.1[18-35] years), with follow-up in young middle-aged (Rhineland Study: N = 714, 35.2[30-40] years) and late middle-aged to older individuals (UK Biobank: N = 33 224, 64.3[45-82] years). We identified 21 loci associated with NODDI markers across brain regions in young adults. The most robust association, replicated in both follow-up cohorts, was with Neurite Density Index (NDI) at chr5q14.3, a known WMH locus in VCAN. Two additional loci were replicated in UK Biobank, at chr17q21.2 with NDI, and chr19q13.12 with Orientation Dispersion Index (ODI). Transcriptome-wide association studies showed associations of STAT3 expression in arterial and adipose tissue (chr17q21.2) with NDI, and of several genes at chr19q13.12 with ODI. Genetic susceptibility to larger WMH volume, but not to vascular risk factors, was significantly associated with decreased NDI in young adults, especially in regions known to harbor WMH in older age. Individually, seven of 25 known WMH risk loci were associated with NDI in young adults. In conclusion, we identified multiple novel genetic risk loci associated with NODDI markers, particularly NDI, in early adulthood. These point to possible early-life mechanisms underlying cSVD and to processes involving remyelination, neurodevelopment and neurodegeneration, with a potential for novel approaches to prevention.
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Affiliation(s)
- Quentin Le Grand
- University of Bordeaux, INSERM, Bordeaux Population Health research center, UMR1219, F-33000, Bordeaux, France
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Ami Tsuchida
- University of Bordeaux, INSERM, Bordeaux Population Health research center, UMR1219, F-33000, Bordeaux, France
- University of Bordeaux, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
- CNRS, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
- CEA, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
| | - Alexandra Koch
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Mohammed-Aslam Imtiaz
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - N Ahmad Aziz
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Chloé Vigneron
- University of Bordeaux, INSERM, Bordeaux Population Health research center, UMR1219, F-33000, Bordeaux, France
| | - Laure Zago
- University of Bordeaux, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
- CNRS, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
- CEA, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
| | - Mark Lathrop
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada; Victor Phillip Dahdaleh Institute of Genomic Medicine at McGill University, Montreal, QC, H3A 0G1, Canada
| | - Alexandre Dubrac
- Centre de Recherche, CHU Sainte-Justine, Montréal, QC, Canada
- Département de Pathologie et Biologie Cellulaire, Université de Montréal, Montréal, QC, Canada
- Département d'Ophtalmologie, Université de Montréal, Montréal, QC, Canada
| | - Thierry Couffinhal
- University of Bordeaux, INSERM, Biologie des maladies cardiovasculaires, U1034, F-33600, Pessac, France
| | - Fabrice Crivello
- University of Bordeaux, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
- CNRS, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
- CEA, Institute of Neurodegenerative Diseases, UMR5293, Neurofunctional Imaging Group, F-33000, Bordeaux, France
| | - Paul M Matthews
- UK Dementia Research Institute and Department of Brain Sciences, Imperial College, London, UK
| | - Aniket Mishra
- University of Bordeaux, INSERM, Bordeaux Population Health research center, UMR1219, F-33000, Bordeaux, France
| | - Monique M B Breteler
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Christophe Tzourio
- University of Bordeaux, INSERM, Bordeaux Population Health research center, UMR1219, F-33000, Bordeaux, France
- Bordeaux University Hospital, Department of Medical Informatics, F-33000, Bordeaux, France
| | - Stéphanie Debette
- University of Bordeaux, INSERM, Bordeaux Population Health research center, UMR1219, F-33000, Bordeaux, France.
- Bordeaux University Hospital, Department of Neurology, Institute for Neurodegenerative Diseases, F-33000, Bordeaux, France.
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Torres-Simón L, Cuesta P, Del Cerro A, Doval S, Chino B, Hernández L, Marsh EB, Maestú F. The effects of white matter hyperintensities on MEG power spectra in cognitively healthy aging. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.15.24307438. [PMID: 38798609 PMCID: PMC11118657 DOI: 10.1101/2024.05.15.24307438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Objective This study sought to identify magnetoencephalography (MEG) power spectra patterns associated with cerebrovascular damage (white matter hyperintensities - WMH) and their relationship with cognitive performance and brain structure integrity in aging individuals without cognitive impairment. Methods We hypothesized a "slowness" pattern characterized by increased power in δ and θ bands and decreased power in the β band associated with the severity of vascular damage. MEG signals were analyzed in cognitively healthy older adults to investigate these associations. Results Contrary to expectations, we did not observe an increase in δ and θ power. However, we found a significant negative correlation between β band power and WMH volume. This β power reduction was linked to structural brain changes, such as larger lateral ventricles, reduced white matter volume, and decreased fractional anisotropy in critical white matter tracts, but not to cognitive performance. This suggests that β band power reduction may serve as an early marker of vascular damage before the onset of cognitive symptoms. Conclusion Our findings partially confirm our initial hypothesis by demonstrating a decrease in β band power with increased vascular damage but not the anticipated increase in slow band power. The lack of correlation between the βpow marker and cognitive performance suggests its potential utility in early identification of at-risk individuals for future cognitive impairment due to vascular origins. These results contribute to understanding the electrophysiological signatures of preclinical vascular damage and highlight the importance of MEG in detecting subtle brain changes associated with aging.
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Jiang K, Albert MS, Coresh J, Couper DJ, Gottesman RF, Hayden KM, Jack CR, Knopman DS, Mosley TH, Pankow JS, Pike JR, Reed NS, Sanchez VA, Sharrett AR, Lin FR, Deal JA. Cross-Sectional Associations of Peripheral Hearing, Brain Imaging, and Cognitive Performance With Speech-in-Noise Performance: The Aging and Cognitive Health Evaluation in Elders Brain Magnetic Resonance Imaging Ancillary Study. Am J Audiol 2024:1-12. [PMID: 38748919 DOI: 10.1044/2024_aja-23-00108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/25/2024] Open
Abstract
PURPOSE Population-based evidence in the interrelationships among hearing, brain structure, and cognition is limited. This study aims to investigate the cross-sectional associations of peripheral hearing, brain imaging measures, and cognitive function with speech-in-noise performance among older adults. METHOD We studied 602 participants in the Aging and Cognitive Health Evaluation in Elders (ACHIEVE) brain magnetic resonance imaging (MRI) ancillary study, including 427 ACHIEVE baseline (2018-2020) participants with hearing loss and 175 Atherosclerosis Risk in Communities Neurocognitive Study Visit 6/7 (2016-2017/2018-2019) participants with normal hearing. Speech-in-noise performance, as outcome of interest, was assessed by the Quick Speech-in-Noise (QuickSIN) test (range: 0-30; higher = better). Predictors of interest included (a) peripheral hearing assessed by pure-tone audiometry; (b) brain imaging measures: structural MRI measures, white matter hyperintensities, and diffusion tensor imaging measures; and (c) cognitive performance assessed by a battery of 10 cognitive tests. All predictors were standardized to z scores. We estimated the differences in QuickSIN associated with every standard deviation (SD) worse in each predictor (peripheral hearing, brain imaging, and cognition) using multivariable-adjusted linear regression, adjusting for demographic variables, lifestyle, and disease factors (Model 1), and, additionally, for other predictors to assess independent associations (Model 2). RESULTS Participants were aged 70-84 years, 56% female, and 17% Black. Every SD worse in better-ear 4-frequency pure-tone average was associated with worse QuickSIN (-4.89, 95% confidence interval, CI [-5.57, -4.21]) when participants had peripheral hearing loss, independent of other predictors. Smaller temporal lobe volume was associated with worse QuickSIN, but the association was not independent of other predictors (-0.30, 95% CI [-0.86, 0.26]). Every SD worse in global cognitive performance was independently associated with worse QuickSIN (-0.90, 95% CI [-1.30, -0.50]). CONCLUSIONS Peripheral hearing and cognitive performance are independently associated with speech-in-noise performance among dementia-free older adults. The ongoing ACHIEVE trial will elucidate the effect of a hearing intervention that includes amplification and auditory rehabilitation on speech-in-noise understanding in older adults. SUPPLEMENTAL MATERIAL https://doi.org/10.23641/asha.25733679.
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Affiliation(s)
- Kening Jiang
- Cochlear Center for Hearing and Public Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Marilyn S Albert
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - David J Couper
- Department of Biostatistics, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill
| | - Rebecca F Gottesman
- Stroke Branch, National Institute of Neurological Disorders and Stroke Intramural Research Program, National Institutes of Health, Bethesda, MD
| | - Kathleen M Hayden
- Department of Social Sciences and Health Policy, Wake Forest School of Medicine, Winston-Salem, NC
| | | | | | - Thomas H Mosley
- The MIND Center, University of Mississippi Medical Center, Jackson, MS
| | - James S Pankow
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis
| | - James R Pike
- Department of Biostatistics, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill
| | - Nicholas S Reed
- Cochlear Center for Hearing and Public Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
- Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins School of Medicine, Baltimore, MD
| | - Victoria A Sanchez
- Department of Otolaryngology, Morsani College of Medicine, University of South Florida, Tampa
| | - A Richey Sharrett
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Frank R Lin
- Cochlear Center for Hearing and Public Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
- Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins School of Medicine, Baltimore, MD
| | - Jennifer A Deal
- Cochlear Center for Hearing and Public Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
- Department of Otolaryngology-Head and Neck Surgery, Johns Hopkins School of Medicine, Baltimore, MD
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Torres-Simon L, Del Cerro-León A, Yus M, Bruña R, Gil-Martinez L, Marcos Dolado A, Maestú F, Arrazola-Garcia J, Cuesta P. Decoding the Best Automated Segmentation Tools for Vascular White Matter Hyperintensities in the Aging Brain: A Clinician's Guide to Precision and Purpose. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.03.30.23287946. [PMID: 38798616 PMCID: PMC11118558 DOI: 10.1101/2023.03.30.23287946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
Cerebrovascular damage from small vessel disease (SVD) occurs in healthy and pathological aging. SVD markers, such as white matter hyperintensities (WMH), are commonly found in individuals over 60 and increase in prevalence with age. WMHs are detectable on standard MRI by adhering to the STRIVE criteria. Currently, visual assessment scales are used in clinical and research scenarios but is time-consuming and has rater variability, limiting its practicality. Addressing this issue, our study aimed to determine the most precise WMH segmentation software, offering insights into methodology and usability to balance clinical precision with practical application. This study employed a dataset comprising T1, FLAIR, and DWI images from 300 cognitively healthy older adults. WMHs in this cohort were evaluated using four automated neuroimaging tools: Lesion Prediction Algorithm (LPA) and Lesion Growth Algorithm (LGA) from Lesion Segmentation Tool (LST), Sequence Adaptive Multimodal Segmentation (SAMSEG), and Brain Intensity Abnormalities Classification Algorithm (BIANCA). Additionally, clinicians manually segmented WMHs in a subsample of 45 participants to establish a gold standard. The study assessed correlations with the Fazekas scale, algorithm performance, and the influence of WMH volume on reliability. Results indicated that supervised algorithms were superior, particularly in detecting small WMHs, and can improve their consistency when used in parallel with unsupervised tools. The research also proposed a biomarker for moderate vascular damage, derived from the top 95th percentile of WMH volume in healthy individuals aged 50 to 60. This biomarker effectively differentiated subgroups within the cohort, correlating with variations in brain structure and behavior.
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Song J. BDNF Signaling in Vascular Dementia and Its Effects on Cerebrovascular Dysfunction, Synaptic Plasticity, and Cholinergic System Abnormality. J Lipid Atheroscler 2024; 13:122-138. [PMID: 38826183 PMCID: PMC11140249 DOI: 10.12997/jla.2024.13.2.122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 11/29/2023] [Accepted: 12/19/2023] [Indexed: 06/04/2024] Open
Abstract
Vascular dementia (VaD) is the second most common type of dementia and is characterized by memory impairment, blood-brain barrier disruption, neuronal cell loss, glia activation, impaired synaptic plasticity, and cholinergic system abnormalities. To effectively prevent and treat VaD a good understanding of the mechanisms underlying its neuropathology is needed. Brain-derived neurotrophic factor (BDNF) is an important neurotrophic factor with multiple functions in the systemic circulation and the central nervous system and is known to regulate neuronal cell survival, synaptic formation, glia activation, and cognitive decline. Recent studies indicate that when compared with normal subjects, patients with VaD have low serum BDNF levels and that BDNF deficiency in the serum and cerebrospinal fluid is an important indicator of VaD. Here, we review current knowledge on the role of BDNF signaling in the pathology of VaD, such as cerebrovascular dysfunction, synaptic dysfunction, and cholinergic system impairment.
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Affiliation(s)
- Juhyun Song
- Department of Anatomy, Chonnam National University Medical School, Hwasun, Korea
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Manelis A, Hu H, Miceli R, Satz S, Lau R, Iyengar S, Swartz HA. The relationship between the size and asymmetry of the lateral ventricles and cortical myelin content in individuals with mood disorders. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.30.24306621. [PMID: 38746112 PMCID: PMC11092679 DOI: 10.1101/2024.04.30.24306621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Background Although enlargement of the lateral ventricles was previously observed in individuals with mood disorders, the link between ventricular size and asymmetry with other indices of brain structure remains underexplored. In this study, we examined the association of lateral ventricular size and asymmetry with cortical myelin content in individuals with bipolar (BD) and depressive (DD) disorders compared to healthy controls (HC). Methods Magnetic resonance imaging (MRI) was used to obtain T1w and T2w images from 149 individuals (age=27.7 (SD=6.1) years, 78% female, BD=38, DD=57, HC=54). Cortical myelin content was calculated using the T1w/T2w ratio. Elastic net regularized regression identified brain regions whose myelin content was associated with ventricular size and asymmetry. A post-hoc linear regression examined how participants' diagnosis, illness duration, and current level of depression moderated the relationship between the size and asymmetry of the lateral ventricles and levels of cortical myelin in the selected brain regions. Results Individuals with mood disorders had larger lateral ventricles than HC. Larger ventricles and lower asymmetry were observed in individuals with BD who had longer lifetime illness duration and more severe current depressive symptoms. A greater left asymmetry was observed in participants with DD than in those with BD (p<0.01). Elastic net revealed that both ventricular enlargement and asymmetry were associated with altered myelin content in cingulate, frontal, and sensorimotor cortices. In BD, but not other groups, ventricular enlargement was related to altered myelin content in the right insular regions. Conclusions Lateral ventricular enlargement and asymmetry are linked to myelin content imbalance, thus, potentially leading to emotional and cognitive dysfunction in mood disorders.
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Andreatta Maduro P, Guimarães MP, de Sousa Rodrigues M, Pereira Rolim Coimbra Pinto AP, da Mota Junior AA, Lima Rocha AS, Matoso JMD, Bavaresco Gambassi B, Schwingel PA. Comparing the Efficacy of Two Cognitive Screening Tools in Identifying Gray and White Matter Brain Damage among Older Adults. J Aging Res 2024; 2024:5527225. [PMID: 38690079 PMCID: PMC11060871 DOI: 10.1155/2024/5527225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2024] [Revised: 03/19/2024] [Accepted: 04/12/2024] [Indexed: 05/02/2024] Open
Abstract
Background Ageing is associated with structural changes in brain regions and functional decline in cognitive domains. Noninvasive tools for identifying structural damage in the brains of older adults are relevant for early treatment. Aims This study aims to evaluate and compare the accuracy of the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA©) in identifying gray and white matter brain damage in older individuals with varying degrees of cognitive impairment. Methods Ninety older adults (62 women) with an average age of 69 ± 7 years were enrolled and categorized as having no cognitive impairment (NCI), mild cognitive impairment (MCI), or moderate cognitive impairment (MoCI). Magnetic resonance imaging (MRI) was utilized to assess the number, volume, and distribution of brain damage. The Fazekas and Scheltens scales were applied to the brain MRIs, and inferential statistics were employed to compare variables among the groups. Results Cognitive impairment was observed in 56.7% of the participants (95% confidence interval (CI): 46.4-66.4%), with thirty-six older adults (40%) classified as MCI and 15 (17%) as MoCI. Cognitive impairment and medial temporal lobe (MTL) atrophy were found to be associated (p=0.001), exhibiting higher mean volume scales of the MTL atrophied area in the MoCI group (p < 0.001). The MMSE accurately revealed MTL atrophy based on the Scheltens (p < 0.05) and Fazekas (p < 0.05) scales. At the same time, the MoCA accurately identified periventricular white matter (PWM) abnormalities according to the Fazekas scale (p < 0.05). Conclusions The MMSE and MoCA screening tools effectively identified gray and white matter brain damage in older adults with varying degrees of cognitive impairment. Lower MMSE scores are associated with MTL atrophy and lesions, and lower MoCA scores are related to PWM lesions. The concurrent use of MMSE and MoCA is recommended for assessing structural changes in distinct brain regions.
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Affiliation(s)
- Paula Andreatta Maduro
- Post-Graduation Program in Health Sciences (PPGCS), University of Pernambuco (UPE), Recife, PE 50100-130, Brazil
- Human Performance Research Laboratory (LAPEDH), UPE, Petrolina, PE 56328-900, Brazil
- University Hospital of the Federal University of Vale do São Francisco (HU-UNIVASF), Brazilian Hospital Services Company (EBSERH), Petrolina, PE 56304-205, Brazil
| | | | - Mateus de Sousa Rodrigues
- Human Performance Research Laboratory (LAPEDH), UPE, Petrolina, PE 56328-900, Brazil
- University Hospital of the Federal University of Vale do São Francisco (HU-UNIVASF), Brazilian Hospital Services Company (EBSERH), Petrolina, PE 56304-205, Brazil
| | - Ana Paula Pereira Rolim Coimbra Pinto
- University Hospital of the Federal University of Vale do São Francisco (HU-UNIVASF), Brazilian Hospital Services Company (EBSERH), Petrolina, PE 56304-205, Brazil
| | - Américo Alves da Mota Junior
- Human Performance Research Laboratory (LAPEDH), UPE, Petrolina, PE 56328-900, Brazil
- University Hospital of the Federal University of Vale do São Francisco (HU-UNIVASF), Brazilian Hospital Services Company (EBSERH), Petrolina, PE 56304-205, Brazil
| | - Alaine Souza Lima Rocha
- Post-Graduation Program in Health Sciences (PPGCS), University of Pernambuco (UPE), Recife, PE 50100-130, Brazil
- Human Performance Research Laboratory (LAPEDH), UPE, Petrolina, PE 56328-900, Brazil
- Department of Physical Therapy, Federal University of Ceará (UFC), Fortaleza, CE 60430-450, Brazil
| | - Juliana Magalhães Duarte Matoso
- Human Performance Research Laboratory (LAPEDH), UPE, Petrolina, PE 56328-900, Brazil
- Department of Clinical Medicine, Pedro Ernesto University Hospital, State University of Rio de Janeiro (UERJ), Rio de Janeiro, RJ 20551-030, Brazil
| | - Bruno Bavaresco Gambassi
- Human Performance Research Laboratory (LAPEDH), UPE, Petrolina, PE 56328-900, Brazil
- Post-Graduation Program in Management of Health Programs and Services (PPGGPSS), CEUMA University (UNICEUMA), São Luís, MA 65075-120, Brazil
| | - Paulo Adriano Schwingel
- Post-Graduation Program in Health Sciences (PPGCS), University of Pernambuco (UPE), Recife, PE 50100-130, Brazil
- Human Performance Research Laboratory (LAPEDH), UPE, Petrolina, PE 56328-900, Brazil
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Keller JA, Sigurdsson S, Schmitz Abecassis B, Kant IMJ, Van Buchem MA, Launer LJ, van Osch MJP, Gudnason V, de Bresser J. Identification of Distinct Brain MRI Phenotypes and Their Association With Long-Term Dementia Risk in Community-Dwelling Older Adults. Neurology 2024; 102:e209176. [PMID: 38471053 PMCID: PMC11033985 DOI: 10.1212/wnl.0000000000209176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 12/13/2023] [Indexed: 03/14/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Individual brain MRI markers only show at best a modest association with long-term occurrence of dementia. Therefore, it is challenging to accurately identify individuals at increased risk for dementia. We aimed to identify different brain MRI phenotypes by hierarchical clustering analysis based on combined neurovascular and neurodegenerative brain MRI markers and to determine the long-term dementia risk within the brain MRI phenotype subgroups. METHODS Hierarchical clustering analysis based on 32 combined neurovascular and neurodegenerative brain MRI markers in community-dwelling individuals of the Age-Gene/Environment Susceptibility Reykjavik Study was applied to identify brain MRI phenotypes. A Cox proportional hazards regression model was used to determine the long-term risk for dementia per subgroup. RESULTS We included 3,056 participants and identified 15 subgroups with distinct brain MRI phenotypes. The phenotypes ranged from limited burden, mostly irregular white matter hyperintensity (WMH) shape and cerebral atrophy, mostly irregularly WMHs and microbleeds, mostly cortical infarcts and atrophy, mostly irregularly shaped WMH and cerebral atrophy to multiburden subgroups. Each subgroup showed different long-term risks for dementia (min-max range hazard ratios [HRs] 1.01-6.18; mean time to follow-up 9.9 ± 2.6 years); especially the brain MRI phenotype with mainly WMHs and atrophy showed a large increased risk (HR 6.18, 95% CI 3.37-11.32). DISCUSSION Distinct brain MRI phenotypes can be identified in community-dwelling older adults. Our results indicate that distinct brain MRI phenotypes are related to varying long-term risks of developing dementia. Brain MRI phenotypes may in the future assist in an improved understanding of the structural correlates of dementia predisposition.
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Affiliation(s)
- Jasmin Annica Keller
- From the Department of Radiology (J.A.K., B.S.A., M.A.V.B., M.J.P.v.O., J.d.B.), Leiden University Medical Center, the Netherlands; Icelandic Heart Association (S.S., V.G.), Kópavogur, Iceland; Clinical Artificial Intelligence Implementation and Research Lab (CAIRELab) and Department of Information Technology & Digital Innovation, Department of Digital Health (I.M.J.K.), University Medical Center Utrecht, the Netherlands; Laboratory of Epidemiology and Population Science (L.J.L.), National Institute on Aging, Bethesda, MD; and Faculty of Medicine (V.G.), University of Iceland, Reykjavik
| | - Sigurdur Sigurdsson
- From the Department of Radiology (J.A.K., B.S.A., M.A.V.B., M.J.P.v.O., J.d.B.), Leiden University Medical Center, the Netherlands; Icelandic Heart Association (S.S., V.G.), Kópavogur, Iceland; Clinical Artificial Intelligence Implementation and Research Lab (CAIRELab) and Department of Information Technology & Digital Innovation, Department of Digital Health (I.M.J.K.), University Medical Center Utrecht, the Netherlands; Laboratory of Epidemiology and Population Science (L.J.L.), National Institute on Aging, Bethesda, MD; and Faculty of Medicine (V.G.), University of Iceland, Reykjavik
| | - Bárbara Schmitz Abecassis
- From the Department of Radiology (J.A.K., B.S.A., M.A.V.B., M.J.P.v.O., J.d.B.), Leiden University Medical Center, the Netherlands; Icelandic Heart Association (S.S., V.G.), Kópavogur, Iceland; Clinical Artificial Intelligence Implementation and Research Lab (CAIRELab) and Department of Information Technology & Digital Innovation, Department of Digital Health (I.M.J.K.), University Medical Center Utrecht, the Netherlands; Laboratory of Epidemiology and Population Science (L.J.L.), National Institute on Aging, Bethesda, MD; and Faculty of Medicine (V.G.), University of Iceland, Reykjavik
| | - Ilse M J Kant
- From the Department of Radiology (J.A.K., B.S.A., M.A.V.B., M.J.P.v.O., J.d.B.), Leiden University Medical Center, the Netherlands; Icelandic Heart Association (S.S., V.G.), Kópavogur, Iceland; Clinical Artificial Intelligence Implementation and Research Lab (CAIRELab) and Department of Information Technology & Digital Innovation, Department of Digital Health (I.M.J.K.), University Medical Center Utrecht, the Netherlands; Laboratory of Epidemiology and Population Science (L.J.L.), National Institute on Aging, Bethesda, MD; and Faculty of Medicine (V.G.), University of Iceland, Reykjavik
| | - Mark A Van Buchem
- From the Department of Radiology (J.A.K., B.S.A., M.A.V.B., M.J.P.v.O., J.d.B.), Leiden University Medical Center, the Netherlands; Icelandic Heart Association (S.S., V.G.), Kópavogur, Iceland; Clinical Artificial Intelligence Implementation and Research Lab (CAIRELab) and Department of Information Technology & Digital Innovation, Department of Digital Health (I.M.J.K.), University Medical Center Utrecht, the Netherlands; Laboratory of Epidemiology and Population Science (L.J.L.), National Institute on Aging, Bethesda, MD; and Faculty of Medicine (V.G.), University of Iceland, Reykjavik
| | - Lenore J Launer
- From the Department of Radiology (J.A.K., B.S.A., M.A.V.B., M.J.P.v.O., J.d.B.), Leiden University Medical Center, the Netherlands; Icelandic Heart Association (S.S., V.G.), Kópavogur, Iceland; Clinical Artificial Intelligence Implementation and Research Lab (CAIRELab) and Department of Information Technology & Digital Innovation, Department of Digital Health (I.M.J.K.), University Medical Center Utrecht, the Netherlands; Laboratory of Epidemiology and Population Science (L.J.L.), National Institute on Aging, Bethesda, MD; and Faculty of Medicine (V.G.), University of Iceland, Reykjavik
| | - Matthias J P van Osch
- From the Department of Radiology (J.A.K., B.S.A., M.A.V.B., M.J.P.v.O., J.d.B.), Leiden University Medical Center, the Netherlands; Icelandic Heart Association (S.S., V.G.), Kópavogur, Iceland; Clinical Artificial Intelligence Implementation and Research Lab (CAIRELab) and Department of Information Technology & Digital Innovation, Department of Digital Health (I.M.J.K.), University Medical Center Utrecht, the Netherlands; Laboratory of Epidemiology and Population Science (L.J.L.), National Institute on Aging, Bethesda, MD; and Faculty of Medicine (V.G.), University of Iceland, Reykjavik
| | - Vilmundur Gudnason
- From the Department of Radiology (J.A.K., B.S.A., M.A.V.B., M.J.P.v.O., J.d.B.), Leiden University Medical Center, the Netherlands; Icelandic Heart Association (S.S., V.G.), Kópavogur, Iceland; Clinical Artificial Intelligence Implementation and Research Lab (CAIRELab) and Department of Information Technology & Digital Innovation, Department of Digital Health (I.M.J.K.), University Medical Center Utrecht, the Netherlands; Laboratory of Epidemiology and Population Science (L.J.L.), National Institute on Aging, Bethesda, MD; and Faculty of Medicine (V.G.), University of Iceland, Reykjavik
| | - Jeroen de Bresser
- From the Department of Radiology (J.A.K., B.S.A., M.A.V.B., M.J.P.v.O., J.d.B.), Leiden University Medical Center, the Netherlands; Icelandic Heart Association (S.S., V.G.), Kópavogur, Iceland; Clinical Artificial Intelligence Implementation and Research Lab (CAIRELab) and Department of Information Technology & Digital Innovation, Department of Digital Health (I.M.J.K.), University Medical Center Utrecht, the Netherlands; Laboratory of Epidemiology and Population Science (L.J.L.), National Institute on Aging, Bethesda, MD; and Faculty of Medicine (V.G.), University of Iceland, Reykjavik
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Chong JR, Chai YL, Yam ATY, Hilal S, Vrooman H, Venketasubramanian N, Blennow K, Zetterberg H, Ashton NJ, Chen CP, Lai MKP. Association of plasma GFAP with elevated brain amyloid is dependent on severity of white matter lesions in an Asian cognitively impaired cohort. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2024; 16:e12576. [PMID: 38605996 PMCID: PMC11007806 DOI: 10.1002/dad2.12576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 02/25/2024] [Accepted: 03/01/2024] [Indexed: 04/13/2024]
Abstract
INTRODUCTION While elevated blood glial fibrillary acidic protein (GFAP) has been associated with brain amyloid pathology, whether this association occurs in populations with high cerebral small vessel disease (CSVD) concomitance remains unclear. METHODS Using a Singapore-based cohort of cognitively impaired subjects, we assessed associations between plasma GFAP and neuroimaging measures of brain amyloid and CSVD, including white matter hyperintensities (WMH). We also examined the diagnostic performance of plasma GFAP in detecting brain amyloid beta positivity (Aβ+). RESULTS When stratified by WMH status, elevated brain amyloid was associated with higher plasma GFAP only in the WMH- group (β = 0.383; P < 0.001). The diagnostic performance of plasma GFAP in identifying Aβ+ was significantly higher in the WMH- group (area under the curve [AUC] = 0.896) than in the WMH+ group (AUC = 0.712, P = 0.008). DISCUSSION The biomarker utility of plasma GFAP in detecting brain amyloid pathology is dependent on the severity of concomitant WMH. Highlight Glial fibrillary acidic protein (GFAP)'s association with brain amyloid is unclear in populations with high cerebral small vessel disease (CSVD).Plasma GFAP was measured in a cohort with CSVD and brain amyloid.Plasma GFAP was better in detecting amyloid in patients with low CSVD versus high CSVD.Biomarker utility of GFAP in detecting brain amyloid depends on the severity of CSVD.
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Affiliation(s)
- Joyce R. Chong
- Department of PharmacologyYong Loo Lin School of MedicineNational University of SingaporeKent RidgeSingapore
- Memory, Aging and Cognition CentreNational University Health SystemsKent RidgeSingapore
| | - Yuek Ling Chai
- Department of PharmacologyYong Loo Lin School of MedicineNational University of SingaporeKent RidgeSingapore
- Memory, Aging and Cognition CentreNational University Health SystemsKent RidgeSingapore
| | - Amelia T. Y. Yam
- Department of PharmacologyYong Loo Lin School of MedicineNational University of SingaporeKent RidgeSingapore
- Memory, Aging and Cognition CentreNational University Health SystemsKent RidgeSingapore
| | - Saima Hilal
- Department of PharmacologyYong Loo Lin School of MedicineNational University of SingaporeKent RidgeSingapore
- Memory, Aging and Cognition CentreNational University Health SystemsKent RidgeSingapore
- Saw Swee Hock School of Public HealthNational University of Singapore and National University Health SystemKent RidgeSingapore
- Department of Radiology and Nuclear MedicineErasmus Medical CenterRotterdamthe Netherlands
| | - Henri Vrooman
- Department of Radiology and Nuclear MedicineErasmus Medical CenterRotterdamthe Netherlands
| | | | - Kaj Blennow
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologySahlgrenska AcademyUniversity of GothenburgGöteborgSweden
| | - Henrik Zetterberg
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologySahlgrenska AcademyUniversity of GothenburgGöteborgSweden
- Department of Neurodegenerative DiseaseThe UCL Queen Square Institute of NeurologyLondonUK
| | - Nicholas J. Ashton
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologySahlgrenska AcademyUniversity of GothenburgGöteborgSweden
| | - Christopher P. Chen
- Department of PharmacologyYong Loo Lin School of MedicineNational University of SingaporeKent RidgeSingapore
- Memory, Aging and Cognition CentreNational University Health SystemsKent RidgeSingapore
| | - Mitchell K. P. Lai
- Department of PharmacologyYong Loo Lin School of MedicineNational University of SingaporeKent RidgeSingapore
- Memory, Aging and Cognition CentreNational University Health SystemsKent RidgeSingapore
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Bachmann D, von Rickenbach B, Buchmann A, Hüllner M, Zuber I, Studer S, Saake A, Rauen K, Gruber E, Nitsch RM, Hock C, Treyer V, Gietl A. White matter hyperintensity patterns: associations with comorbidities, amyloid, and cognition. Alzheimers Res Ther 2024; 16:67. [PMID: 38561806 PMCID: PMC10983708 DOI: 10.1186/s13195-024-01435-6] [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: 10/27/2023] [Accepted: 03/23/2024] [Indexed: 04/04/2024]
Abstract
BACKGROUND White matter hyperintensities (WMHs) are often measured globally, but spatial patterns of WMHs could underlie different risk factors and neuropathological and clinical correlates. We investigated the spatial heterogeneity of WMHs and their association with comorbidities, Alzheimer's disease (AD) risk factors, and cognition. METHODS In this cross-sectional study, we studied 171 cognitively unimpaired (CU; median age: 65 years, range: 50 to 89) and 51 mildly cognitively impaired (MCI; median age: 72, range: 53 to 89) individuals with available amyloid (18F-flutementamol) PET and FLAIR-weighted images. Comorbidities were assessed using the Cumulative Illness Rating Scale (CIRS). Each participant's white matter was segmented into 38 parcels, and WMH volume was calculated in each parcel. Correlated principal component analysis was applied to the parceled WMH data to determine patterns of WMH covariation. Adjusted and unadjusted linear regression models were used to investigate associations of component scores with comorbidities and AD-related factors. Using multiple linear regression, we tested whether WMH component scores predicted cognitive performance. RESULTS Principal component analysis identified four WMH components that broadly describe FLAIR signal hyperintensities in posterior, periventricular, and deep white matter regions, as well as basal ganglia and thalamic structures. In CU individuals, hypertension was associated with all patterns except the periventricular component. MCI individuals showed more diverse associations. The posterior and deep components were associated with renal disorders, the periventricular component was associated with increased amyloid, and the subcortical gray matter structures was associated with sleep disorders, endocrine/metabolic disorders, and increased amyloid. In the combined sample (CU + MCI), the main effects of WMH components were not associated with cognition but predicted poorer episodic memory performance in the presence of increased amyloid. No interaction between hypertension and the number of comorbidities on component scores was observed. CONCLUSION Our study underscores the significance of understanding the regional distribution patterns of WMHs and the valuable insights that risk factors can offer regarding their underlying causes. Moreover, patterns of hyperintensities in periventricular regions and deep gray matter structures may have more pronounced cognitive implications, especially when amyloid pathology is also present.
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Affiliation(s)
- Dario Bachmann
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland.
- Department of Health Sciences and Technology, ETH Zürich, 8093, Zurich, Switzerland.
| | | | - Andreas Buchmann
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
| | - Martin Hüllner
- Department of Nuclear Medicine, University Hospital of Zurich, University of Zurich, 8091, Zurich, Switzerland
| | - Isabelle Zuber
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
| | - Sandro Studer
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
| | - Antje Saake
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
| | - Katrin Rauen
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
- Department of Geriatric Psychiatry, Psychiatric Hospital Zurich, 8032, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich, 8057, Zurich, Switzerland
| | - Esmeralda Gruber
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
| | - Roger M Nitsch
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
- Neurimmune AG, 8952, Zurich, Schlieren, Switzerland
| | - Christoph Hock
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
- Neurimmune AG, 8952, Zurich, Schlieren, Switzerland
| | - Valerie Treyer
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
- Department of Nuclear Medicine, University Hospital of Zurich, University of Zurich, 8091, Zurich, Switzerland
| | - Anton Gietl
- Institute for Regenerative Medicine, University of Zurich, Campus Schlieren, Wagistrasse 12, 8952, Zurich, Schlieren, Switzerland
- Department of Geriatric Psychiatry, Psychiatric Hospital Zurich, 8032, Zurich, Switzerland
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Pradeep A, Raghavan S, Przybelski SA, Preboske G, Schwarz CG, Lowe VJ, Knopman DS, Petersen RC, Jack CR, Graff-Radford J, Cogswell PM, Vemuri P. Can white matter hyperintensities based Fazekas visual assessment scales inform about Alzheimer's disease pathology in the population? RESEARCH SQUARE 2024:rs.3.rs-4017874. [PMID: 38558965 PMCID: PMC10980106 DOI: 10.21203/rs.3.rs-4017874/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Background White matter hyperintensities (WMH) are considered hallmark features of cerebral small vessel disease and have recently been linked to Alzheimer's disease pathology. Their distinct spatial distributions, namely periventricular versus deep WMH, may differ by underlying age-related and pathobiological processes contributing to cognitive decline. We aimed to identify the spatial patterns of WMH using the 4-scale Fazekas visual assessment and explore their differential association with age, vascular health, Alzheimer's imaging markers, namely amyloid and tau burden, and cognition. Because our study consisted of scans from GE and Siemens scanners with different resolutions, we also investigated inter-scanner reproducibility and combinability of WMH measurements on imaging. Methods We identified 1144 participants from the Mayo Clinic Study of Aging consisting of older adults from Olmsted County, Minnesota with available structural magnetic resonance imaging (MRI), amyloid, and tau positron emission tomography (PET). WMH distribution patterns were assessed on FLAIR-MRI, both 2D axial and 3D, using Fazekas ratings of periventricular and deep WMH severity. We compared the association of periventricular and deep WMH scales with vascular risk factors, amyloid-PET and tau-PET standardized uptake value ratio, WMH volume, and cognition using Pearson partial correlation after adjusting for age. We also evaluated vendor compatibility and reproducibility of the Fazekas scales using intraclass correlations (ICC). Results Periventricular and deep WMH measurements showed similar correlations with age, cardiometabolic conditions score (vascular risk), and cognition, (p < 0.001). Both periventricular WMH and deep WMH showed weak associations with amyloidosis (R = 0.07, p = < 0.001), and none with tau burden. We found substantial agreement between data from the two scanners for Fazekas measurements (ICC = 0.78). The automated WMH volume had high discriminating power for identifying participants with Fazekas ≥ 2 (area under curve = 0.97). Conclusion Our study investigates risk factors underlying WMH spatial patterns and their impact on global cognition, with no discernible differences between periventricular and deep WMH. We observed minimal impact of amyloidosis on WMH severity. These findings, coupled with enhanced inter-scanner reproducibility of WMH data, suggest the combinability of inter-scanner data assessed by harmonized protocols in the context of vascular contributions to cognitive impairment and dementia biomarker research.
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Bhuiyan MIH, Habib K, Sultan MT, Chen F, Jahan I, Weng Z, Rahman MS, Islam R, Foley LM, Hitchens TK, Deng X, Canna SW, Sun D, Cao G. SPAK inhibitor ZT-1a attenuates reactive astrogliosis and oligodendrocyte degeneration in a mouse model of vascular dementia. CNS Neurosci Ther 2024; 30:e14654. [PMID: 38433018 PMCID: PMC10909630 DOI: 10.1111/cns.14654] [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: 08/16/2023] [Revised: 01/08/2024] [Accepted: 01/28/2024] [Indexed: 03/05/2024] Open
Abstract
BACKGROUND Astrogliosis and white matter lesions (WML) are key characteristics of vascular contributions to cognitive impairment and dementia (VCID). However, the molecular mechanisms underlying VCID remain poorly understood. Stimulation of Na-K-Cl cotransport 1 (NKCC1) and its upstream kinases WNK (with no lysine) and SPAK (the STE20/SPS1-related proline/alanine-rich kinase) play a role in astrocytic intracellular Na+ overload, hypertrophy, and swelling. Therefore, in this study, we assessed the effect of SPAK inhibitor ZT-1a on pathogenesis and cognitive function in a mouse model of VCID induced by bilateral carotid artery stenosis (BCAS). METHODS Following sham or BCAS surgery, mice were randomly assigned to receive either vehicle (DMSO) or SPAK inhibitor ZT-1a treatment regimen (days 14-35 post-surgery). Mice were then evaluated for cognitive functions by Morris water maze, WML by ex vivo MRI-DTI analysis, and astrogliosis/demyelination by immunofluorescence and immunoblotting. RESULTS Compared to sham control mice, BCAS-Veh mice exhibited chronic cerebral hypoperfusion and memory impairments, accompanied by significant MRI DTI-detected WML and oligodendrocyte (OL) death. Increased activation of WNK-SPAK-NKCC1-signaling proteins was detected in white matter tissues and in C3d+ GFAP+ cytotoxic astrocytes but not in S100A10+ GFAP+ homeostatic astrocytes in BCAS-Veh mice. In contrast, ZT-1a-treated BCAS mice displayed reduced expression and phosphorylation of NKCC1, decreased astrogliosis, OL death, and WML, along with improved memory functions. CONCLUSION BCAS-induced upregulation of WNK-SPAK-NKCC1 signaling contributes to white matter-reactive astrogliosis, OL death, and memory impairment. Pharmacological inhibition of the SPAK activity has therapeutic potential for alleviating pathogenesis and memory impairment in VCID.
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Affiliation(s)
- Mohammad Iqbal H. Bhuiyan
- Department of Pharmaceutical Sciences, School of PharmacyUniversity of Texas at El PasoEl PasoTexasUSA
- Department of NeurologyUniversity of PittsburghPittsburghPennsylvaniaUSA
- Pittsburgh Institute for Neurodegenerative DisordersUniversity of PittsburghPittsburghPennsylvaniaUSA
- Veterans Affairs Pittsburgh Health Care System Pittsburgh Healthcare SystemGeriatric Research Education and Clinical CenterPittsburghPennsylvaniaUSA
| | - Khadija Habib
- Department of Pharmaceutical Sciences, School of PharmacyUniversity of Texas at El PasoEl PasoTexasUSA
| | - Md Tipu Sultan
- Department of Pharmaceutical Sciences, School of PharmacyUniversity of Texas at El PasoEl PasoTexasUSA
| | - Fenghua Chen
- Department of NeurologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Israt Jahan
- Department of Pharmaceutical Sciences, School of PharmacyUniversity of Texas at El PasoEl PasoTexasUSA
- Department of NeurologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Zhongfang Weng
- Department of NeurologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Md Shamim Rahman
- Department of Pharmaceutical Sciences, School of PharmacyUniversity of Texas at El PasoEl PasoTexasUSA
| | | | - Lesley M. Foley
- Animal Imaging CenterUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - T. Kevin Hitchens
- Animal Imaging CenterUniversity of PittsburghPittsburghPennsylvaniaUSA
- Department of NeurobiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Xianming Deng
- State Key Laboratory of Cellular Stress Biology, School of Life SciencesXiamen UniversityXiamenFujianChina
| | - Scott W. Canna
- Department of Pediatric RheumatologyThe Children's Hospital of PhiladelphiaPhiladelphiaPennsylvaniaUSA
| | - Dandan Sun
- Department of NeurologyUniversity of PittsburghPittsburghPennsylvaniaUSA
- Pittsburgh Institute for Neurodegenerative DisordersUniversity of PittsburghPittsburghPennsylvaniaUSA
- Veterans Affairs Pittsburgh Health Care System Pittsburgh Healthcare SystemGeriatric Research Education and Clinical CenterPittsburghPennsylvaniaUSA
| | - Guodong Cao
- Department of NeurologyUniversity of PittsburghPittsburghPennsylvaniaUSA
- Veterans Affairs Pittsburgh Health Care System Pittsburgh Healthcare SystemGeriatric Research Education and Clinical CenterPittsburghPennsylvaniaUSA
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16
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Raghavan S, Przybelski SA, Lesnick TG, Fought AJ, Reid RI, Gebre RK, Windham BG, Algeciras‐Schimnich A, Machulda MM, Vassilaki M, Knopman DS, Jack CR, Petersen RC, Graff‐Radford J, Vemuri P. Vascular risk, gait, behavioral, and plasma indicators of VCID. Alzheimers Dement 2024; 20:1201-1213. [PMID: 37932910 PMCID: PMC10916988 DOI: 10.1002/alz.13540] [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: 07/11/2023] [Revised: 10/06/2023] [Accepted: 10/11/2023] [Indexed: 11/08/2023]
Abstract
INTRODUCTION Cost-effective screening tools for vascular contributions to cognitive impairment and dementia (VCID) has significant implications. We evaluated non-imaging indicators of VCID using magnetic resonance imaging (MRI)-measured white matter (WM) damage and hypothesized that these indicators differ based on age. METHODS In 745 participants from the Mayo Clinic Study of Aging (≥50 years of age) with serial WM assessments from diffusion MRI and fluid-attenuated inversion recovery (FLAIR)-MRI, we examined associations between baseline non-imaging indicators (demographics, vascular risk factors [VRFs], gait, behavioral, plasma glial fibrillary acidic protein [GFAP], and plasma neurofilament light chain [NfL]) and WM damage across three age tertiles. RESULTS VRFs and gait were associated with diffusion changes even in low age strata. All measures (VRFs, gait, behavioral, plasma GFAP, plasma NfL) were associated with white matter hyperintensities (WMHs) but mainly in intermediate and high age strata. DISCUSSION Non-imaging indicators of VCID were related to WM damage and may aid in screening participants and assessing outcomes for VCID. HIGHLIGHTS Non-imaging indicators of VCID can aid in prediction of MRI-measured WM damage but their importance differed by age. Vascular risk and gait measures were associated with early VCID changes measured using diffusion MRI. Plasma markers explained variability in WMH across age strata. Most non-imaging measures explained variability in WMH and vascular WM scores in intermediate and older age groups. The framework developed here can be used to evaluate new non-imaging VCID indicators proposed in the future.
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Affiliation(s)
| | | | - Timothy G. Lesnick
- Department of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
| | - Angela J. Fought
- Department of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
| | - Robert I. Reid
- Department of Information TechnologyMayo ClinicRochesterMinnesotaUSA
| | | | - B. Gwen Windham
- Department of MedicineUniversity of Mississippi Medical CenterJacksonUSA
| | | | | | - Maria Vassilaki
- Department of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
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17
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Dhabalia R, Kashikar SV, Parihar PS, Mishra GV. Unveiling the Intricacies: A Comprehensive Review of Magnetic Resonance Imaging (MRI) Assessment of T2-Weighted Hyperintensities in the Neuroimaging Landscape. Cureus 2024; 16:e54808. [PMID: 38529430 PMCID: PMC10961652 DOI: 10.7759/cureus.54808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 02/24/2024] [Indexed: 03/27/2024] Open
Abstract
T2-weighted hyperintensities in neuroimaging represent areas of heightened signal intensity on magnetic resonance imaging (MRI) scans, holding crucial importance in neuroimaging. This comprehensive review explores the T2-weighted hyperintensities, providing insights into their definition, characteristics, clinical relevance, and underlying causes. It highlights the significance of these hyperintensities as sensitive markers for neurological disorders, including multiple sclerosis, vascular dementia, and brain tumors. The review also delves into advanced neuroimaging techniques, such as susceptibility-weighted and diffusion tensor imaging, and the application of artificial intelligence and machine learning in hyperintensities analysis. Furthermore, it outlines the challenges and pitfalls associated with their assessment and emphasizes the importance of standardized protocols and a multidisciplinary approach. The review discusses future directions for research and clinical practice, including the development of biomarkers, personalized medicine, and enhanced imaging techniques. Ultimately, the review underscores the profound impact of T2-weighted hyperintensities in shaping the landscape of neurological diagnosis, prognosis, and treatment, contributing to a deeper understanding of complex neurological conditions and guiding more informed and effective patient care.
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Affiliation(s)
- Rishabh Dhabalia
- Radiodiagnosis, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education & Research, Wardha, IND
| | - Shivali V Kashikar
- Radiodiagnosis, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education & Research, Wardha, IND
| | - Pratap S Parihar
- Radiodiagnosis, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education & Research, Wardha, IND
| | - Gaurav V Mishra
- Radiodiagnosis, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education & Research, Wardha, IND
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18
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Iandolo R, Avci E, Bommarito G, Sandvig I, Rohweder G, Sandvig A. Characterizing upper extremity fine motor function in the presence of white matter hyperintensities: A 7 T MRI cross-sectional study in older adults. Neuroimage Clin 2024; 41:103569. [PMID: 38281363 PMCID: PMC10839532 DOI: 10.1016/j.nicl.2024.103569] [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: 07/10/2023] [Revised: 01/19/2024] [Accepted: 01/21/2024] [Indexed: 01/30/2024]
Abstract
BACKGROUND White matter hyperintensities (WMH) are a prevalent radiographic finding in the aging brain studies. Research on WMH association with motor impairment is mostly focused on the lower-extremity function and further investigation on the upper-extremity is needed. How different degrees of WMH burden impact the network of activation recruited during upper limb motor performance could provide further insight on the complex mechanisms of WMH pathophysiology and its interaction with aging and neurological disease processes. METHODS 40 healthy elderly subjects without a neurological/psychiatric diagnosis were included in the study (16F, mean age 69.3 years). All subjects underwent ultra-high field 7 T MRI including structural and finger tapping task-fMRI. First, we quantified the WMH lesion load and its spatial distribution. Secondly, we performed a data-driven stratification of the subjects according to their periventricular and deep WMH burdens. Thirdly, we investigated the distribution of neural recruitment and the corresponding activity assessed through BOLD signal changes among different brain regions for groups of subjects. We clustered the degree of WMH based on location, numbers, and volume into three categories; ranging from mild, moderate, and severe. Finally, we explored how the spatial distribution of WMH, and activity elicited during task-fMRI relate to motor function, measured with the 9-Hole Peg Test. RESULTS Within our population, we found three subgroups of subjects, partitioned according to their periventricular and deep WMH lesion load. We found decreased activity in several frontal and cingulate cortex areas in subjects with a severe WMH burden. No statistically significant associations were found when performing the brain-behavior statistical analysis for structural or functional data. CONCLUSION WMH burden has an effect on brain activity during fine motor control and the activity changes are associated with varying degrees of the total burden and distributions of WMH lesions. Collectively, our results shed new light on the potential impact of WMH on motor function in the context of aging and neurodegeneration.
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Affiliation(s)
- Riccardo Iandolo
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
| | - Esin Avci
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
| | - Giulia Bommarito
- Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Ioanna Sandvig
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Gitta Rohweder
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway; Stroke Unit, Department of Medicine, St Olav's University Hospital, Trondheim, Norway
| | - Axel Sandvig
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway; Department of Neurology and Clinical Neurophysiology, St. Olav's University Hospital, Trondheim, Norway; Department of Clinical Neurosciences, Division of Neuro, Head and Neck, Umeå University Hospital, Umeå, Sweden; Department of Community Medicine and Rehabilitation, Umeå University Hospital, Umeå, Sweden.
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19
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Carey C, Mulcahy E, McCarthy FP, Jennings E, Kublickiene K, Khashan A, Barrett P. Hypertensive disorders of pregnancy and the risk of maternal dementia: a systematic review and meta-analysis. Am J Obstet Gynecol 2024:S0002-9378(24)00043-7. [PMID: 38278201 DOI: 10.1016/j.ajog.2024.01.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 01/05/2024] [Accepted: 01/17/2024] [Indexed: 01/28/2024]
Abstract
OBJECTIVE Hypertensive disorders of pregnancy, including preeclampsia, are associated with an increased risk for maternal cardiovascular disease, stroke, and chronic kidney disease. However, their association with subsequent maternal dementia or cognitive impairment is less well understood. This study aimed to review and synthesize the published literature on hypertensive disorders of pregnancy and the subsequent risk for maternal dementia or cognitive impairment. DATA SOURCES PubMed, Web of Science, Pyschinfo, and CINAHL were searched from database inception until July 31, 2022, for observational studies of hypertensive disorders of pregnancy and maternal dementia or cognitive impairment. STUDY ELIGIBILITY CRITERIA Selected studies included the following: a population of pregnant women, exposure to a hypertensive disorder of pregnancy of interest, and at least 1 primary outcome (dementia) or secondary outcome (cognitive impairment). Two reviewers were involved in study selection. METHODS We followed the Meta-analyses of Observational Studies in Epidemiology guidelines throughout. Random-effects meta-analyses were used to calculate the overall pooled estimates. Bias was assessed using an adapted version of the validated Newcastle-Ottawa Quality Assessment tool. RESULTS A total of 25 eligible studies were identified and included 2,501,673 women. Preeclampsia was associated with a significantly increased risk for vascular dementia (adjusted hazard ratio, 1.89; 95% confidence interval, 1.47-2.43), whereas no clear association was noted between preeclampsia and Alzheimer's disease (adjusted hazard ratio, 1.27; 95% confidence interval, 0.95-1.70), nor between preeclampsia and any (undifferentiated) dementia (adjusted hazard ratio, 1.18; 95% confidence interval, 0.95-1.47). However, in an analysis restricted to women aged 65 years and older, preeclampsia was associated with an increased risk for Alzheimer's disease (adjusted hazard ratio, 1.92; 95% confidence interval, 1.35-2.73) and any dementia (adjusted hazard ratio, 1.87; 95% confidence interval, 1.21-2.91). CONCLUSION Women whose pregnancies were complicated by preeclampsia seem to be at a substantially increased future risk for vascular dementia. The longer-term risks among these women with regards to Alzheimer's disease and other forms of dementia are less clear.
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Affiliation(s)
- Cian Carey
- School of Public Health, University College Cork, Cork, Ireland
| | - Emily Mulcahy
- School of Public Health, University College Cork, Cork, Ireland
| | - Fergus P McCarthy
- Irish Centre for Maternal and Child Health Research, Cork University Maternity Hospital, University College Cork, Cork, Ireland; Department of Obstetrics and Gynaecology, Cork University Maternity Hospital, Cork, Ireland (Dr McCarthy)
| | - Emma Jennings
- School of Medicine, University College Cork, Cork, Ireland; Department of Geriatric Medicine, Cork University and Mallow General Hospital, Cork, Ireland
| | - Karolina Kublickiene
- Division of Renal Medicine, Department of Clinical Intervention, Science and Technology (CLINTEC), Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
| | - Ali Khashan
- School of Public Health, University College Cork, Cork, Ireland; Irish Centre for Maternal and Child Health Research, Cork University Maternity Hospital, University College Cork, Cork, Ireland
| | - Peter Barrett
- School of Public Health, University College Cork, Cork, Ireland; Department of Public Health Area D (Cork & Kerry), St. Finbarr's Hospital, Cork, Ireland.
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20
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Hayek D, Ziegler G, Kleineidam L, Brosseron F, Nemali A, Vockert N, Ravichandran KA, Betts MJ, Peters O, Schneider LS, Wang X, Priller J, Altenstein S, Schneider A, Fliessbach K, Wiltfang J, Bartels C, Rostamzadeh A, Glanz W, Buerger K, Janowitz D, Perneczky R, Rauchmann BS, Teipel S, Kilimann I, Laske C, Mengel D, Synofzik M, Munk MH, Spottke A, Roy N, Roeske S, Kuhn E, Ramirez A, Dobisch L, Schmid M, Berger M, Wolfsgruber S, Yakupov R, Hetzer S, Dechent P, Ewers M, Scheffler K, Schott BH, Schreiber S, Orellana A, de Rojas I, Marquié M, Boada M, Sotolongo O, González PG, Puerta R, Düzel E, Jessen F, Wagner M, Ruiz A, Heneka MT, Maass A. Different inflammatory signatures based on CSF biomarkers relate to preserved or diminished brain structure and cognition. Mol Psychiatry 2024:10.1038/s41380-023-02387-3. [PMID: 38216727 DOI: 10.1038/s41380-023-02387-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 12/07/2023] [Accepted: 12/15/2023] [Indexed: 01/14/2024]
Abstract
Neuroinflammation is a hallmark of Alzheimer's disease (AD) and both positive and negative associations of individual inflammation-related markers with brain structure and cognitive function have been described. We aimed to identify inflammatory signatures of CSF immune-related markers that relate to changes of brain structure and cognition across the clinical spectrum ranging from normal aging to AD. A panel of 16 inflammatory markers, Aβ42/40 and p-tau181 were measured in CSF at baseline in the DZNE DELCODE cohort (n = 295); a longitudinal observational study focusing on at-risk stages of AD. Volumetric maps of gray and white matter (GM/WM; n = 261) and white matter hyperintensities (WMHs, n = 249) were derived from baseline MRIs. Cognitive decline (n = 204) and the rate of change in GM volume was measured in subjects with at least 3 visits (n = 175). A principal component analysis on the CSF markers revealed four inflammatory components (PCs). Of these, the first component PC1 (highly loading on sTyro3, sAXL, sTREM2, YKL-40, and C1q) was associated with older age and higher p-tau levels, but with less pathological Aβ when controlling for p-tau. PC2 (highly loading on CRP, IL-18, complement factor F/H and C4) was related to male gender, higher body mass index and greater vascular risk. PC1 levels, adjusted for AD markers, were related to higher GM and WM volumes, less WMHs, better baseline memory, and to slower atrophy rates in AD-related areas and less cognitive decline. In contrast, PC2 related to less GM and WM volumes and worse memory at baseline. Similar inflammatory signatures and associations were identified in the independent F.ACE cohort. Our data suggest that there are beneficial and detrimental signatures of inflammatory CSF biomarkers. While higher levels of TAM receptors (sTyro/sAXL) or sTREM2 might reflect a protective glia response to degeneration related to phagocytic clearance, other markers might rather reflect proinflammatory states that have detrimental impact on brain integrity.
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Affiliation(s)
- Dayana Hayek
- German Center for Neurodegenerative Diseases (DZNE), Leipziger Straße 44, Magdeburg, 39120, Germany
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, Magdeburg, Germany
| | - Gabriel Ziegler
- German Center for Neurodegenerative Diseases (DZNE), Leipziger Straße 44, Magdeburg, 39120, Germany
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, Magdeburg, Germany
| | - Luca Kleineidam
- Department of Neurodegenerative Disease and Geriatric Psychiatry/Psychiatry, University of Bonn Medical Center, Venusberg-Campus 1, 53127, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Frederic Brosseron
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Neurodegenerative Disease and Geriatric Psychiatry/Neurology, University of Bonn Medical Center, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Aditya Nemali
- German Center for Neurodegenerative Diseases (DZNE), Leipziger Straße 44, Magdeburg, 39120, Germany
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, Magdeburg, Germany
| | - Niklas Vockert
- German Center for Neurodegenerative Diseases (DZNE), Leipziger Straße 44, Magdeburg, 39120, Germany
| | - Kishore A Ravichandran
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Neurodegenerative Disease and Geriatric Psychiatry/Neurology, University of Bonn Medical Center, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Matthew J Betts
- German Center for Neurodegenerative Diseases (DZNE), Leipziger Straße 44, Magdeburg, 39120, Germany
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, Magdeburg, Germany
| | - Oliver Peters
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Institute of Psychiatry and Neuroscience, Hindenburgdamm 30, 12203, Berlin, Germany
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
| | - Luisa-Sophie Schneider
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Institute of Psychiatry and Neuroscience, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Xiao Wang
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Institute of Psychiatry and Neuroscience, Hindenburgdamm 30, 12203, Berlin, Germany
| | - Josef Priller
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité, Charitéplatz 1, 10117, Berlin, Germany
- School of Medicine, Technical University of Munich; Department of Psychiatry and Psychotherapy, Munich, Germany
- University of Edinburgh and UK DRI, Edinburgh, UK
| | - Slawek Altenstein
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité, Charitéplatz 1, 10117, Berlin, Germany
| | - Anja Schneider
- Department of Neurodegenerative Disease and Geriatric Psychiatry/Psychiatry, University of Bonn Medical Center, Venusberg-Campus 1, 53127, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Klaus Fliessbach
- Department of Neurodegenerative Disease and Geriatric Psychiatry/Psychiatry, University of Bonn Medical Center, Venusberg-Campus 1, 53127, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Jens Wiltfang
- German Center for Neurodegenerative Diseases (DZNE), Von-Siebold-Str. 3a, Göttingen, 37075, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, University of Göttingen, Von-Siebold-Str. 5, 37075, Göttingen, Germany
- Neurosciences and Signaling Group, Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro, Aveiro, Portugal
| | - Claudia Bartels
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, University of Göttingen, Von-Siebold-Str. 5, 37075, Göttingen, Germany
| | - Ayda Rostamzadeh
- Department of Psychiatry, University of Cologne, Medical Faculty, Kerpener Strasse 62, 50924, Cologne, Germany
| | - Wenzel Glanz
- German Center for Neurodegenerative Diseases (DZNE), Leipziger Straße 44, Magdeburg, 39120, Germany
| | - Katharina Buerger
- German Center for Neurodegenerative Diseases (DZNE, Munich), Feodor-Lynen-Strasse 17, 81377, Munich, Germany
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Feodor-Lynen-Strasse 17, 81377, Munich, Germany
| | - Daniel Janowitz
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Feodor-Lynen-Strasse 17, 81377, Munich, Germany
| | - Robert Perneczky
- German Center for Neurodegenerative Diseases (DZNE, Munich), Feodor-Lynen-Strasse 17, 81377, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy) Munich, Munich, Germany
- Ageing Epidemiology Research Unit (AGE), School of Public Health, Imperial College London, London, UK
| | - Boris-Stephan Rauchmann
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
- Department of Neuroradiology, University Hospital LMU, Munich, Germany
| | - Stefan Teipel
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Center, Gehlsheimer Str. 20, 18147, Rostock, Germany
| | - Ingo Kilimann
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Center, Gehlsheimer Str. 20, 18147, Rostock, Germany
| | - Christoph Laske
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - David Mengel
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Division Translational Genomics of Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, Germany
| | - Matthis Synofzik
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Division Translational Genomics of Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, Germany
| | - Matthias H Munk
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Annika Spottke
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Neurology, University of Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Nina Roy
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Sandra Roeske
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Elizabeth Kuhn
- Department of Neurodegenerative Disease and Geriatric Psychiatry/Psychiatry, University of Bonn Medical Center, Venusberg-Campus 1, 53127, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Alfredo Ramirez
- Department of Neurodegenerative Disease and Geriatric Psychiatry/Psychiatry, University of Bonn Medical Center, Venusberg-Campus 1, 53127, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
- Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Joseph-Stelzmann-Strasse 26, 50931, Köln, Germany
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Department of Psychiatry & Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, San Antonio, TX, USA
| | - Laura Dobisch
- German Center for Neurodegenerative Diseases (DZNE), Leipziger Straße 44, Magdeburg, 39120, Germany
| | - Matthias Schmid
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
- Institute for Medical Biometry, University Hospital Bonn, Venusberg-Campus 1, D-53127, Bonn, Germany
| | - Moritz Berger
- Institute for Medical Biometry, University Hospital Bonn, Venusberg-Campus 1, D-53127, Bonn, Germany
| | - Steffen Wolfsgruber
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Renat Yakupov
- German Center for Neurodegenerative Diseases (DZNE), Leipziger Straße 44, Magdeburg, 39120, Germany
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, Magdeburg, Germany
| | - Stefan Hetzer
- Berlin Center for Advanced Neuroimaging, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Peter Dechent
- MR-Research in Neurosciences, Department of Cognitive Neurology, Georg-August-University Goettingen, Goettingen, Germany
| | - Michael Ewers
- German Center for Neurodegenerative Diseases (DZNE, Munich), Feodor-Lynen-Strasse 17, 81377, Munich, Germany
| | - Klaus Scheffler
- Department for Biomedical Magnetic Resonance, University of Tübingen, 72076, Tübingen, Germany
| | - Björn H Schott
- German Center for Neurodegenerative Diseases (DZNE), Von-Siebold-Str. 3a, Göttingen, 37075, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, University of Göttingen, Von-Siebold-Str. 5, 37075, Göttingen, Germany
- Leibniz Institute for Neurobiology, Brenneckestr. 6, 39118, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - Stefanie Schreiber
- German Center for Neurodegenerative Diseases (DZNE), Leipziger Straße 44, Magdeburg, 39120, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
- Department of Neurology, Otto-von-Guericke University Magdeburg, Leipziger Strasse 44, 39120, Magdeburg, Germany
| | - Adelina Orellana
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Itziar de Rojas
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Marta Marquié
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Mercè Boada
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Oscar Sotolongo
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Pablo García González
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Spain
| | - Raquel Puerta
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Spain
| | - Emrah Düzel
- German Center for Neurodegenerative Diseases (DZNE), Leipziger Straße 44, Magdeburg, 39120, Germany
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - Frank Jessen
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Psychiatry, University of Cologne, Medical Faculty, Kerpener Strasse 62, 50924, Cologne, Germany
- Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Joseph-Stelzmann-Strasse 26, 50931, Köln, Germany
| | - Michael Wagner
- Department of Neurodegenerative Disease and Geriatric Psychiatry/Psychiatry, University of Bonn Medical Center, Venusberg-Campus 1, 53127, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Augustín Ruiz
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Michael T Heneka
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Neurodegenerative Disease and Geriatric Psychiatry/Neurology, University of Bonn Medical Center, Venusberg-Campus 1, 53127, Bonn, Germany
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 7 avenue des Hauts Fourneaux, 4362, Esch-sur- Alzette, Luxembourg
- Department of Infectious Diseases and Immunology, University of Massachusetts Medical School, 55 Lake Avenue, North Worcester, MA, 01655, USA
| | - Anne Maass
- German Center for Neurodegenerative Diseases (DZNE), Leipziger Straße 44, Magdeburg, 39120, Germany.
- Center for Behavioral Brain Sciences, Magdeburg, Germany.
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Yeung SHS, Lee RHS, Cheng GWY, Ma IWT, Kofler J, Kent C, Ma F, Herrup K, Fornage M, Arai K, Tse KH. White matter hyperintensity genetic risk factor TRIM47 regulates autophagy in brain endothelial cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.18.566359. [PMID: 38187529 PMCID: PMC10769267 DOI: 10.1101/2023.12.18.566359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
White matter hyperintensity (WMH) is strongly correlated with age-related dementia and hypertension, but its pathogenesis remains obscure. GWAS identified TRIM47 at 17q25 locus as a top genetic risk factor for WMH formation. TRIM family is a class of E3 ubiquitin ligase with pivotal functions in autophagy, which is critical for brain endothelial cell (ECs) remodeling during hypertension. We hypothesize that TRIM47 regulates autophagy and its loss-of-function disturbs cerebrovasculature. Based on transcriptomics and immunohistochemistry, TRIM47 is found selectively expressed by brain ECs in human and mouse, and its transcription is upregulated by artificially-induced autophagy while downregulated in hypertension-like conditions. Using in silico simulation, immunocytochemistry and super-resolution microscopy, we identified the highly conserved binding site between TRIM47 and the LIR (LC3-interacting region) motif of LC3B. Importantly, pharmacological autophagy induction increased Trim47 expression on mouse ECs (b.End3) culture, while silencing Trim47 significantly increased autophagy with ULK1 phosphorylation induction, transcription and vacuole formation. Together, we confirm that TRIM47 is an endogenous inhibitor of autophagy in brain ECs, and such TRIM47-mediated regulation connects genetic and physiological risk factors for WMH formation but warrants further investigation. SUMMARY STATEMENT TRIM47, top genetic risk factor for white matter hyperintensity formation, is a negative regulator of autophagy in brain endothelial cells and implicates a novel cellular mechanism for age-related cerebrovascular changes.
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22
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Mu S, Lu W, Yu G, Zheng L, Qiu J. Deep learning-based grading of white matter hyperintensities enables identification of potential markers in multi-sequence MRI data. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 243:107904. [PMID: 37924768 DOI: 10.1016/j.cmpb.2023.107904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 10/06/2023] [Accepted: 10/27/2023] [Indexed: 11/06/2023]
Abstract
BACKGROUND White matter hyperintensities (WMHs) are widely-seen in the aging population, which are associated with cerebrovascular risk factors and age-related cognitive decline. At present, structural atrophy and functional alterations coexisted with WMHs lacks comprehensive investigation. This study developed a WMHs risk prediction model to evaluate WHMs according to Fazekas scales, and to locate potential regions with high risks across the entire brain. METHODS We developed a WMHs risk prediction model, which consisted of the following steps: T2 fluid attenuated inversion recovery (T2-FLAIR) image of each participant was firstly segmented into 1000 tiles with the size of 32 × 32 × 1, features from the tiles were extracted using the ResNet18-based feature extractor, and then a 1D convolutional neural network (CNN) was used to score all tiles based on the extracted features. Finally, a multi-layer perceptron (MLP) was constructed to predict the Fazekas scales based on the tile scores. The proposed model was trained using T2-FLAIR images, we selected tiles with abnormal scores in the test set after prediction, and evaluated their corresponding gray matter (GM) volume, white matter (WM) volume, fractional anisotropy (FA), mean diffusivity (MD), and cerebral blood flow (CBF) via longitudinal and multi-sequence Magnetic Resonance Imaging (MRI) data analysis. RESULTS The proposed WMHs risk prediction model could accurately predict the Fazekas ratings based on the tile scores from T2-FLAIR MRI images with accuracy of 0.656, 0.621 in training data set and test set, respectively. The longitudinal MRI validation revealed that most of the high-risk tiles predicted by the WMHs risk prediction model in the baseline images had WMHs in the corresponding positions in the longitudinal images. The validation on multi-sequence MRI demonstrated that WMHs were associated with GM and WM atrophies, WM micro-structural and perfusion alterations in high-risk tiles, and multi-modal MRI measures of most high-risk tiles showed significant associations with Mini Mental State Examination (MMSE) score. CONCLUSION Our proposed WMHs risk prediction model can not only accurately evaluate WMH severities according to Fazekas scales, but can also uncover potential markers of WMHs across modalities. The WMHs risk prediction model has the potential to be used for the early detection of WMH-related alterations in the entire brain and WMH-induced cognitive decline.
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Affiliation(s)
- Si Mu
- College of Mechanical and Electronic Engineering, Shandong Agricultural University, Tai'an, Shandong, 271000, China
| | - Weizhao Lu
- Department of Radiology, the Second Affiliated Hospital of Shandong First Medical University, Tai'an, Shandong, 271000, China
| | - Guanghui Yu
- Department of Radiology, the Second Affiliated Hospital of Shandong First Medical University, Tai'an, Shandong, 271000, China
| | - Lei Zheng
- Department of Radiology, Rushan Hospital of Chinese Medicine, Rushan, Shandong, 264500, China.
| | - Jianfeng Qiu
- School of Radiology, Shandong First Medical University & Shandong Academy of Medicine Sciences, Tai'an, Shandong, 271000, China; Science and Technology Innovation Center, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan, 250000, China.
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23
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Wang R, Deng Y, Zhang W, Ning J, Li H, Feng J, Cheng W, Yu J. Associations between adiposity and white matter hyperintensities: Cross-sectional and longitudinal analyses of 34,653 participants. Hum Brain Mapp 2024; 45:e26560. [PMID: 38224536 PMCID: PMC10789203 DOI: 10.1002/hbm.26560] [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: 06/04/2023] [Revised: 11/15/2023] [Accepted: 11/28/2023] [Indexed: 01/17/2024] Open
Abstract
OBJECTIVES White matter hyperintensities (WMH) increase the risk of stroke and cognitive impairment. This study aims to determine the cross-sectional and longitudinal associations between adiposity and WMH. METHODS Participants were enrolled from the UK Biobank cohort. Associations of concurrent, past, and changes in overall and central adiposity with WMH were investigated by linear and nonlinear regression models. The association of longitudinal adiposity and WMH volume changes was determined by a linear mixed model. Mediation analysis investigated the potential mediating effect of blood pressure. RESULTS In 34,653 participants with available adiposity measures and imaging data, the concurrent obese group had a 25.3% (β [95% CI] = 0.253 [0.222-0.284]) higher WMH volume than the ideal weight group. Increment in all adiposity measures was associated with a higher WMH volume. Among them, waist circumference demonstrated the strongest effect (β [95% CI] = 0.113 [0.101-0.125]). Past adiposity also demonstrated similar effects. Among the subset of 2664 participants with available WMH follow-up data, adiposity measures were predictive of WMH change. Regarding changes of adiposity, compared with ideal weight stable group, those who turned from ideal weight to overweight/obese had a 8.1% higher WMH volume (β [95% CI] = 0.081 [0.039-0.123]), while participants who turned from overweight/obese to ideal weight demonstrated no significant WMH volume change. Blood pressure partly meditates the associations between adiposity and WMH. CONCLUSIONS Both concurrent and past adiposity were associated with a higher WMH volume. The detrimental effects of adiposity on WMH occurred throughout midlife and in the elderly and may still exist after changes in obesity status.
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Affiliation(s)
- Rong‐Ze Wang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontier Center for Brain Science, Shanghai Medical CollegeFudan UniversityShanghaiChina
| | - Yue‐Ting Deng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontier Center for Brain Science, Shanghai Medical CollegeFudan UniversityShanghaiChina
| | - Wei Zhang
- Institute of Science and Technology for Brain‐Inspired IntelligenceFudan UniversityShanghaiChina
- Key Laboratory of Computational Neuroscience and Brain Inspired IntelligenceFudan University, Ministry of EducationShanghaiChina
| | - Jing Ning
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontier Center for Brain Science, Shanghai Medical CollegeFudan UniversityShanghaiChina
| | - Hong‐Qi Li
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontier Center for Brain Science, Shanghai Medical CollegeFudan UniversityShanghaiChina
| | - Jian‐Feng Feng
- Institute of Science and Technology for Brain‐Inspired IntelligenceFudan UniversityShanghaiChina
- Key Laboratory of Computational Neuroscience and Brain Inspired IntelligenceFudan University, Ministry of EducationShanghaiChina
| | - Wei Cheng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontier Center for Brain Science, Shanghai Medical CollegeFudan UniversityShanghaiChina
- Institute of Science and Technology for Brain‐Inspired IntelligenceFudan UniversityShanghaiChina
- Key Laboratory of Computational Neuroscience and Brain Inspired IntelligenceFudan University, Ministry of EducationShanghaiChina
| | - Jin‐Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontier Center for Brain Science, Shanghai Medical CollegeFudan UniversityShanghaiChina
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24
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Telpoukhovskaia MA, Murdy TJ, Marola OJ, Charland K, MacLean M, Luquez T, Lish AM, Neuner S, Dunn A, Onos KD, Wiley J, Archer D, Huentelman MJ, Arnold M, Menon V, Goate A, Van Eldik LJ, Territo PR, Howell GR, Carter GW, O'Connell KMS, Kaczorowski CC. New directions for Alzheimer's disease research from the Jackson Laboratory Center for Alzheimer's and Dementia Research 2022 workshop. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2024; 10:e12458. [PMID: 38469553 PMCID: PMC10925728 DOI: 10.1002/trc2.12458] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 01/30/2024] [Accepted: 02/01/2024] [Indexed: 03/13/2024]
Abstract
INTRODUCTION In September 2022, The Jackson Laboratory Center for Alzheimer's and Dementia Research (JAX CADR) hosted a workshop with leading researchers in the Alzheimer's disease and related dementias (ADRD) field. METHODS During the workshop, the participants brainstormed new directions to overcome current barriers to providing patients with effective ADRD therapeutics. The participants outlined specific areas of focus. Following the workshop, each group used standard literature search methods to provide background for each topic. RESULTS The team of invited experts identified four key areas that can be collectively addressed to make a significant impact in the field: (1) Prioritize the diversification of disease targets, (2) enhance factors promoting resilience, (3) de-risk clinical pipeline, and (4) centralize data management. DISCUSSION In this report, we review these four objectives and propose innovations to expedite ADRD therapeutic pipelines.
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Affiliation(s)
| | - Thomas J. Murdy
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
| | | | - Kevin Charland
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
| | - Michael MacLean
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
| | - Tain Luquez
- Center for Translational and Computational NeuroimmunologyDepartment of NeurologyColumbia University Irving Medical CenterNew YorkNew YorkUSA
| | - Alexandra M. Lish
- Ann Romney Center for Neurologic DiseasesDepartment of NeurologyBrigham and Women's Hospital and Harvard Medical SchoolBostonMassachusettsUSA
| | - Sarah Neuner
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Amy Dunn
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
| | - Kristen D. Onos
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
| | | | - Derek Archer
- Vanderbilt Memory and Alzheimer's CenterVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of NeurologyVanderbilt University Medical CenterNashvilleTennesseeUSA
- Vanderbilt Genetics InstituteVanderbilt University School of MedicineNashvilleTennesseeUSA
| | - Matthew J. Huentelman
- Neurogenomics DivisionTranslational Genomics Research Institute (TGen)PhoenixArizonaUSA
| | - Matthias Arnold
- Institute of Computational BiologyHelmholtz Zentrum München, German Research Center for Environmental HealthNeuherbergGermany
- Department of Psychiatry and Behavioral SciencesDuke UniversityDurhamNorth CarolinaUSA
| | - Vilas Menon
- Center for Translational and Computational NeuroimmunologyDepartment of NeurologyColumbia University Irving Medical CenterNew YorkNew YorkUSA
| | - Alison Goate
- Department of Genetics and Genomic SciencesIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | | | - Paul R. Territo
- Department of MedicineDivision of Clinical PharmacologyIndiana University School of MedicineIndianapolisIndianaUSA
- Stark Neuroscience Research InstituteIndiana University School of MedicineIndianapolisIndianaUSA
| | - Gareth R. Howell
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
- Graduate School of Biomedical Science and EngineeringUniversity of MaineOronoMaineUSA
- Neuroscience Program, Graduate School of Biomedical ScienceTufts University School of MedicineBostonMassachusettsUSA
- Genetics Program, Graduate School of Biomedical ScienceTufts University School of MedicineBostonMassachusettsUSA
| | - Gregory W. Carter
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
- Graduate School of Biomedical Science and EngineeringUniversity of MaineOronoMaineUSA
- Neuroscience Program, Graduate School of Biomedical ScienceTufts University School of MedicineBostonMassachusettsUSA
- Genetics Program, Graduate School of Biomedical ScienceTufts University School of MedicineBostonMassachusettsUSA
| | - Kristen M. S. O'Connell
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
- Graduate School of Biomedical Science and EngineeringUniversity of MaineOronoMaineUSA
- Neuroscience Program, Graduate School of Biomedical ScienceTufts University School of MedicineBostonMassachusettsUSA
- Genetics Program, Graduate School of Biomedical ScienceTufts University School of MedicineBostonMassachusettsUSA
| | - Catherine C. Kaczorowski
- The Jackson Laboratory for Mammalian GeneticsBar HarborMaineUSA
- Department of NeurologyUniversity of MichiganAnn ArborMichiganUSA
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25
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Lin K, Wen W, Lipnicki DM, Mewton L, Chen R, Du J, Wang D, Skoog I, Sterner TR, Najar J, Kim KW, Han JW, Kim JS, Ng TP, Ho R, Chua DQL, Anstey KJ, Cherbuin N, Mortby ME, Brodaty H, Kochan N, Sachdev PS, Jiang J. Risk factors and cognitive correlates of white matter hyperintensities in ethnically diverse populations without dementia: The COSMIC consortium. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2024; 16:e12567. [PMID: 38487075 PMCID: PMC10937819 DOI: 10.1002/dad2.12567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 01/18/2024] [Accepted: 02/06/2024] [Indexed: 03/17/2024]
Abstract
INTRODUCTION White matter hyperintensities (WMHs) are an important imaging marker for cerebral small vessel diseases, but their risk factors and cognitive associations have not been well documented in populations of different ethnicities and/or from different geographical regions. METHODS We investigated how WMHs were associated with vascular risk factors and cognition in both Whites and Asians, using data from five population-based cohorts of non-demented older individuals from Australia, Singapore, South Korea, and Sweden (N = 1946). WMH volumes (whole brain, periventricular, and deep) were quantified with UBO Detector and harmonized using the ComBat model. We also harmonized various vascular risk factors and scores for global cognition and individual cognitive domains. RESULTS Factors associated with larger whole brain WMH volumes included diabetes, hypertension, stroke, current smoking, body mass index, higher alcohol intake, and insufficient physical activity. Hypertension and stroke had stronger associations with WMH volumes in Whites than in Asians. No associations between WMH volumes and cognitive performance were found after correction for multiple testing. CONCLUSION The current study highlights ethnic differences in the contributions of vascular risk factors to WMHs.
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Affiliation(s)
- Keshuo Lin
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Wei Wen
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Darren M. Lipnicki
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Louise Mewton
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Rory Chen
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Jing Du
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Dadong Wang
- Quantitative Imaging Research TeamCSIRO Informatics and StatisticsNorth RydeNew South WalesAustralia
| | - Ingmar Skoog
- Neuropsychiatric Epidemiology UnitDepartment of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologySahlgrenska AcademyUniversity of GothenburgGothenburgSweden
- Centre for Ageing and Health (AGECAP)University of GothenburgGothenburgSweden
- Psychiatry, Cognition and Old Age Psychiatry ClinicSahlgrenska University HospitalGothenburgSweden
| | - Therese Rydberg Sterner
- Neuropsychiatric Epidemiology UnitDepartment of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologySahlgrenska AcademyUniversity of GothenburgGothenburgSweden
- Centre for Ageing and Health (AGECAP)University of GothenburgGothenburgSweden
- Aging Research CenterDepartment of NeurobiologyCare Sciences and SocietyKarolinska Institutet and Stockholm UniversityStockholmSweden
| | - Jenna Najar
- Neuropsychiatric Epidemiology UnitDepartment of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologySahlgrenska AcademyUniversity of GothenburgGothenburgSweden
- Centre for Ageing and Health (AGECAP)University of GothenburgGothenburgSweden
- Section Genomics of Neurodegenerative Diseases and AgingDepartment of Human GeneticsAmsterdam Universitair Medische CentraAmsterdamthe Netherlands
| | - Ki Woong Kim
- Department of NeuropsychiatrySeoul National University Bundang HospitalSeongnamSouth Korea
- Department of PsychiatrySeoul National University College of MedicineSeoulSouth Korea
- Department of Brain and Cognitive SciencesSeoul National University College of Natural SciencesSeoulSouth Korea
| | - Ji Won Han
- Department of NeuropsychiatrySeoul National University Bundang HospitalSeongnamSouth Korea
- Department of PsychiatrySeoul National University College of MedicineSeoulSouth Korea
| | - Jun Sung Kim
- Department of NeuropsychiatrySeoul National University Bundang HospitalSeongnamSouth Korea
| | - Tze Pin Ng
- Department of Psychological MedicineKhoo Teck Puat HospitalYishunSingapore
- Geriatric Education and Research InstituteMinistry of HealthSingaporeSingapore
| | - Roger Ho
- Institute for Health Innovation and Technology (iHealthtech)National University of SingaporeSingaporeSingapore
| | - Denise Qian Ling Chua
- Department of Psychological MedicineNational University of SingaporeSingaporeSingapore
| | - Kaarin J. Anstey
- School of PsychologyUniversity of New South WalesSydneyNew South WalesAustralia
- Department of NeurodegenerationNeuroscience Research AustraliaSydneyNew South WalesAustralia
- Ageing Futures InstituteUniversity of New South WalesSydneyNew South WalesAustralia
| | - Nicolas Cherbuin
- National Centre for Epidemiology and Population HealthCollege of Health and MedicineAustralian National UniversityCanberraAustralian Capital TerritoryAustralia
| | - Moyra E. Mortby
- School of PsychologyUniversity of New South WalesSydneyNew South WalesAustralia
- Department of NeurodegenerationNeuroscience Research AustraliaSydneyNew South WalesAustralia
- Ageing Futures InstituteUniversity of New South WalesSydneyNew South WalesAustralia
| | - Henry Brodaty
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Nicole Kochan
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
| | - Perminder S. Sachdev
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
- Neuropsychiatric InstituteThe Prince of Wales HospitalSydneyNew South WalesAustralia
| | - Jiyang Jiang
- Centre for Healthy Brain AgeingSchool of Clinical MedicineUniversity of New South WalesSydneyNew South WalesAustralia
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26
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Pajewski NM, Donohue MC, Raman R, Espeland MA. Ascertainment and Statistical Issues for Randomized Trials of Cardiovascular Interventions for Cognitive Impairment and Dementia. Hypertension 2024; 81:45-53. [PMID: 37732473 PMCID: PMC10840823 DOI: 10.1161/hypertensionaha.123.19941] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
There has been considerable progress in the prevention and treatment of cardiovascular disease, reducing the population burden of cardiovascular morbidity and mortality. Recently, some randomized trials, including the SPRINT (Systolic Blood Pressure Intervention Trial), have suggested that improvements in cardiovascular risk factors may also slow cognitive decline and reduce the eventual development of dementia. Unfortunately, the randomized trial template that has been used repeatedly to successfully demonstrate reductions in major adverse cardiac events faces several design and analytic obstacles when applied in the context of cognitive decline and dementia. Here, we review these obstacles, motivated by SPRINT and the context of selecting an appropriate cognitive end point for future preventive randomized trials. A few options are available, spanning neuropsychological test scores or composites reflecting specific domains of cognitive function, adjudicated cognitive impairment, or potentially physiological biomarkers. This choice entails considerations around statistical power, modes of ascertainment, the clinical relevance of treatment effects, a myriad of statistical issues (interval censoring, missing data, the competing risk of death, practice effects, etc), as well as ethical considerations around equipoise. Collectively, these considerations indicate that trials aiming to mitigate the cardiovascular contribution to cognitive decline and dementia will generally need to be large, inclusive of a wide age range of older adults, and with multiple years of follow-up.
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Affiliation(s)
- Nicholas M. Pajewski
- Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, NC
| | - Michael C. Donohue
- Alzheimer’s Therapeutic Research Institute, Keck School of Medicine of the University of Southern California, San Diego, CA
| | - Rema Raman
- Alzheimer’s Therapeutic Research Institute, Keck School of Medicine of the University of Southern California, San Diego, CA
| | - Mark A. Espeland
- Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, NC
- Section of Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston-Salem, NC
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27
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Schindler LS, Subramaniapillai S, Ambikairajah A, Barth C, Crestol A, Voldsbekk I, Beck D, Gurholt TP, Topiwala A, Suri S, Ebmeier KP, Andreassen OA, Draganski B, Westlye LT, de Lange AMG. Cardiometabolic health across menopausal years is linked to white matter hyperintensities up to a decade later. Front Glob Womens Health 2023; 4:1320640. [PMID: 38213741 PMCID: PMC10783171 DOI: 10.3389/fgwh.2023.1320640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 12/06/2023] [Indexed: 01/13/2024] Open
Abstract
Introduction The menopause transition is associated with several cardiometabolic risk factors. Poor cardiometabolic health is further linked to microvascular brain lesions, which can be detected as white matter hyperintensities (WMHs) using T2-FLAIR magnetic resonance imaging (MRI) scans. Females show higher risk for WMHs post-menopause, but it remains unclear whether changes in cardiometabolic risk factors underlie menopause-related increase in brain pathology. Methods In this study, we assessed whether cross-sectional measures of cardiometabolic health, including body mass index (BMI) and waist-to-hip ratio (WHR), blood lipids, blood pressure, and long-term blood glucose (HbA1c), as well as longitudinal changes in BMI and WHR, differed according to menopausal status at baseline in 9,882 UK Biobank females (age range 40-70 years, n premenopausal = 3,529, n postmenopausal = 6,353). Furthermore, we examined whether these cardiometabolic factors were associated with WMH outcomes at the follow-up assessment, on average 8.78 years after baseline. Results Postmenopausal females showed higher levels of baseline blood lipids (HDL β = 0.14, p < 0.001, LDL β = 0.20, p < 0.001, triglycerides β = 0.12, p < 0.001) and HbA1c (β = 0.24, p < 0.001) compared to premenopausal women, beyond the effects of age. Over time, BMI increased more in the premenopausal compared to the postmenopausal group (β = -0.08, p < 0.001), while WHR increased to a similar extent in both groups (β = -0.03, p = 0.102). The change in WHR was however driven by increased waist circumference only in the premenopausal group. While the group level changes in BMI and WHR were in general small, these findings point to distinct anthropometric changes in pre- and postmenopausal females over time. Higher baseline measures of BMI, WHR, triglycerides, blood pressure, and HbA1c, as well as longitudinal increases in BMI and WHR, were associated with larger WMH volumes (β range = 0.03-0.13, p ≤ 0.002). HDL showed a significant inverse relationship with WMH volume (β = -0.27, p < 0.001). Discussion Our findings emphasise the importance of monitoring cardiometabolic risk factors in females from midlife through the menopause transition and into the postmenopausal phase, to ensure improved cerebrovascular outcomes in later years.
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Affiliation(s)
- Louise S. Schindler
- LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
- Department of Psychology, University of Oslo, Oslo, Norway
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Sivaniya Subramaniapillai
- LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Ananthan Ambikairajah
- Discipline of Psychology, Faculty of Health, University of Canberra, Canberra, Australia
- National Centre for Epidemiology and Population Health, Australian National University, Canberra, Australia
| | - Claudia Barth
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Arielle Crestol
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Irene Voldsbekk
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dani Beck
- Department of Psychology, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Tiril P. Gurholt
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Anya Topiwala
- Nuffield Department Population Health, Big Data Institute, University of Oxford, Oxford, United Kingdom
| | - Sana Suri
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Klaus P. Ebmeier
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Ole A. Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Bogdan Draganski
- LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Lars T. Westlye
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Ann-Marie G. de Lange
- LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
- Department of Psychology, University of Oslo, Oslo, Norway
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
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Anzovino A, Canepa E, Alves M, Lemon NL, Carare RO, Fossati S. Amyloid Beta Oligomers Activate Death Receptors and Mitochondria-Mediated Apoptotic Pathways in Cerebral Vascular Smooth Muscle Cells; Protective Effects of Carbonic Anhydrase Inhibitors. Cells 2023; 12:2840. [PMID: 38132159 PMCID: PMC10741628 DOI: 10.3390/cells12242840] [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: 11/10/2023] [Revised: 12/08/2023] [Accepted: 12/11/2023] [Indexed: 12/23/2023] Open
Abstract
Amyloid beta (Aβ) deposition within the brain vasculature is an early hallmark of Alzheimer's disease (AD), which triggers loss of brain vascular smooth muscle cells (BVSMCs) in cerebral arteries, via poorly understood mechanisms, altering cerebral blood flow, brain waste clearance, and promoting cognitive impairment. We have previously shown that, in brain endothelial cells (ECs), vasculotropic Aβ species induce apoptosis through death receptors (DRs) DR4 and DR5 and mitochondria-mediated mechanisms, while FDA-approved carbonic anhydrase inhibitors (CAIs) prevent mitochondria-mediated EC apoptosis in vitro and in vivo. In this study, we analyzed Aβ-induced extrinsic and intrinsic (DR- and mitochondria-mediated) apoptotic pathways in BVSMC, aiming to unveil new therapeutic targets to prevent BVSMC stress and death. We show that both apoptotic pathways are activated in BVSMCs by oligomeric Aβ42 and Aβ40-Q22 (AβQ22) and mitochondrial respiration is severely impaired. Importantly, the CAIs methazolamide (MTZ) and acetazolamide (ATZ) prevent the pro-apoptotic effects in BVSMCs, while reducing caspase 3 activation and Aβ deposition in the arterial walls of TgSwDI animals, a murine model of cerebral amyloid angiopathy (CAA). This study reveals new molecular targets and a promising therapeutic strategy against BVSMC dysfunction in AD, CAA, and ARIA (amyloid-related imaging abnormalities) complications of recently FDA-approved anti-Aβ antibodies.
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Affiliation(s)
- Amy Anzovino
- Alzheimer’s Center at Temple, Department of Neural Sciences, Lewis Katz School of Medicine, Temple University, 3500 N Broad St, Philadelphia, PA 19140, USA; (A.A.); (E.C.); (M.A.); (N.L.L.)
| | - Elisa Canepa
- Alzheimer’s Center at Temple, Department of Neural Sciences, Lewis Katz School of Medicine, Temple University, 3500 N Broad St, Philadelphia, PA 19140, USA; (A.A.); (E.C.); (M.A.); (N.L.L.)
| | - Micaelly Alves
- Alzheimer’s Center at Temple, Department of Neural Sciences, Lewis Katz School of Medicine, Temple University, 3500 N Broad St, Philadelphia, PA 19140, USA; (A.A.); (E.C.); (M.A.); (N.L.L.)
| | - Nicole L. Lemon
- Alzheimer’s Center at Temple, Department of Neural Sciences, Lewis Katz School of Medicine, Temple University, 3500 N Broad St, Philadelphia, PA 19140, USA; (A.A.); (E.C.); (M.A.); (N.L.L.)
| | - Roxana O. Carare
- Faculty of Medicine, University of Southampton, Southampton SO16 6YD, UK;
| | - Silvia Fossati
- Alzheimer’s Center at Temple, Department of Neural Sciences, Lewis Katz School of Medicine, Temple University, 3500 N Broad St, Philadelphia, PA 19140, USA; (A.A.); (E.C.); (M.A.); (N.L.L.)
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Li Y, Kalpouzos G, Bäckman L, Qiu C, Laukka EJ. Association of white matter hyperintensity accumulation with domain-specific cognitive decline: a population-based cohort study. Neurobiol Aging 2023; 132:100-108. [PMID: 37776581 DOI: 10.1016/j.neurobiolaging.2023.08.011] [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: 02/12/2023] [Revised: 08/28/2023] [Accepted: 08/29/2023] [Indexed: 10/02/2023]
Abstract
We investigated the association of load and accumulation of white matter hyperintensities (WMHs) with rate of cognitive decline. This population-based study included 510 dementia-free people (age ≥60 years) who had repeated measures of global and regional (lobar, deep, periventricular) WMHs up to 6 years (from 2001-2003 to 2007-2010) and repeated measures of cognitive function (episodic memory, semantic memory, category fluency, letter fluency, executive function, perceptual speed) up to 15 years (from 2001-2004 to 2016-2019). We found that greater baseline loads of global and regional WMHs were associated with faster decline in letter fluency, perceptual speed, and global cognition. Furthermore, faster accumulation of global, deep, and periventricular WMHs was related to accelerated cognitive decline, primarily in perceptual speed. These data show that WMHs are associated with decline in perceptual speed rather than episodic or semantic memory and that cognitive change is more vulnerable to WMH accumulations in deep and periventricular regions.
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Affiliation(s)
- Yuanjing Li
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Grégoria Kalpouzos
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Lars Bäckman
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Chengxuan Qiu
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
| | - Erika J Laukka
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden; Stockholm Gerontology Research Center, Stockholm, Sweden.
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Keller JA, Sigurdsson S, Klaassen K, Hirschler L, van Buchem MA, Launer LJ, van Osch MJ, Gudnason V, de Bresser J. White matter hyperintensity shape is associated with long-term dementia risk. Alzheimers Dement 2023; 19:5632-5641. [PMID: 37303267 PMCID: PMC10713858 DOI: 10.1002/alz.13345] [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: 11/17/2022] [Revised: 04/11/2023] [Accepted: 05/05/2023] [Indexed: 06/13/2023]
Abstract
INTRODUCTION We aimed to investigate the association between white matter hyperintensity (WMH) shape and volume and the long-term dementia risk in community-dwelling older adults. METHODS Three thousand seventy-seven participants (mean age: 75.6 ± 5.2 years) of the Age Gene/Environment Susceptibility (AGES)-Reykjavik study underwent baseline 1.5T brain magnetic resonance imaging and were followed up for dementia (mean follow-up: 9.9 ± 2.6 years). RESULTS More irregular shape of periventricular/confluent WMH (lower solidity (hazard ratio (95% confidence interval) 1.34 (1.17 to 1.52), p < .001) and convexity 1.38 (1.28 to 1.49), p < .001); higher concavity index 1.43 (1.32 to 1.54), p < .001) and fractal dimension 1.45 (1.32 to 1.58), p < .001)), higher total WMH volume (1.68 (1.54 to 1.87), p < .001), higher periventricular/confluent WMH volume (1.71 (1.55 to 1.89), p < .001), and higher deep WMH volume (1.17 (1.08 to 1.27), p < .001) were associated with an increased long-term dementia risk. DISCUSSION WMH shape markers may in the future be useful in determining patient prognosis and may aid in patient selection for future preventive treatments in community-dwelling older adults.
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Affiliation(s)
- Jasmin A. Keller
- Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
| | | | - Kelly Klaassen
- Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
| | - Lydiane Hirschler
- Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
| | - Mark A. van Buchem
- Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
| | - Lenore J. Launer
- Laboratory of Epidemiology and Population Science, National Institute on Aging, Bethesda, MD 20898, United States
| | - Matthias J.P. van Osch
- Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
| | - Vilmundur Gudnason
- Icelandic Heart Association, 201 Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - Jeroen de Bresser
- Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
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Smith L, López Sánchez GF, Shin JI, Kostev K, Underwood BR, Oh H, Soysal P, Veronese N, Schuch F, Tully MA, Koyanagi A. Food insecurity and subjective cognitive complaints among adults aged ≥ 65 years from low- and middle-income countries. Eur J Nutr 2023; 62:3217-3226. [PMID: 37550594 PMCID: PMC10611875 DOI: 10.1007/s00394-023-03226-5] [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: 03/25/2023] [Accepted: 07/27/2023] [Indexed: 08/09/2023]
Abstract
PURPOSE To date, no study has investigated the association between food insecurity and subjective cognitive complaints (SCC). Thus, the aims of the present study were to examine this association among older adults in low- and middle-income countries (LMICs), and to identify the potential mediators in this association, given the importance of SCC in dementia risk among older people, and the projected particularly large increase in dementia in this setting. METHODS Cross-sectional, community-based, nationally representative data from the World Health Organization (WHO) Study on global AGEing and Adult Health (SAGE) collected between 2007 and 2010 were analyzed. Two questions on subjective memory and learning complaints in the past 30 days were used to create a SCC scale ranging from 0 (No SCC) to 100 (worse SCC). Past 12 month food insecurity was assessed with two questions on frequency of eating less and hunger due to lack of food. Multivariable linear regression and mediation (Karlson-Holm-Breen method) analyses were conducted to assess associations. RESULTS Data on 14,585 individuals aged ≥ 65 years [mean (SD) age 72.6 (11.5) years; 55.0% females] were analyzed. Severe food insecurity (vs. no food insecurity) was associated with 9.16 (95% CI = 6.95-11.37) points higher mean SCC score. Sleep/energy (mediated% 37.9%; P < 0.001), perceived stress (37.2%; P = 0.001), and depression (13.7%; P = 0.008) partially explained the association between severe food insecurity and SCC. CONCLUSION Food insecurity was associated with SCC among older adults in LMICs. Future studies should assess whether addressing food insecurity among older adults in LMICs can improve cognitive health.
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Affiliation(s)
- Lee Smith
- Centre for Health Performance and Wellbeing, Anglia Ruskin University, Cambridge, UK
| | - Guillermo F López Sánchez
- Division of Preventive Medicine and Public Health, Department of Public Health Sciences, School of Medicine, University of Murcia, Murcia, Spain.
| | - Jae Il Shin
- Department of Pediatrics, Yonsei University College of Medicine, Seoul, South Korea
- Severance Underwood Meta-research Center, Institute of Convergence Science, Yonsei University, Seoul, South Korea
| | | | - Benjamin R Underwood
- Cambridgeshire and Peterborough NHS Foundation Trust and Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Hans Oh
- Suzanne Dworak Peck School of Social Work, University of Southern California, Los Angeles, CA, USA
| | - Pinar Soysal
- Department of Geriatric Medicine, Faculty of Medicine, Bezmialem Vakif University, Istanbul, Turkey
| | - Nicola Veronese
- Department of Internal Medicine, Geriatrics Section, University of Palermo, Palermo, Italy
| | - Felipe Schuch
- Department of Sports Methods and Techniques, Federal University of Santa Maria, Santa Maria, Brazil
- Faculty of Health Sciences, Universidad Autónoma de Chile, Providencia, Chile
| | - Mark A Tully
- School of Medicine, Ulster University, Londonderry, Northern Ireland, UK
| | - Ai Koyanagi
- Research and Development Unit, Parc Sanitari Sant Joan de Déu, CIBERSAM, ISCIII, Dr. Antoni Pujadas, Sant Boi de Llobregat, Barcelona, Spain
- ICREA, Pg. Lluis Companys 23, 08010, Barcelona, Spain
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Marin MA, Gleichman AJ, Wei X, Whittaker DS, Mody I, Colwell CS, Carmichael ST. Motor Activity-Induced White Matter Repair in White Matter Stroke. J Neurosci 2023; 43:8126-8139. [PMID: 37821228 PMCID: PMC10697402 DOI: 10.1523/jneurosci.0631-23.2023] [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: 04/06/2023] [Revised: 08/22/2023] [Accepted: 09/13/2023] [Indexed: 10/13/2023] Open
Abstract
Subcortical white matter stroke (WMS) is a progressive disorder which is demarcated by the formation of small ischemic lesions along white matter tracts in the CNS. As lesions accumulate, patients begin to experience severe motor and cognitive decline. Despite its high rate of incidence in the human population, our understanding of the cause and outcome of WMS is extremely limited. As such, viable therapies for WMS remain to be seen. This study characterizes myelin recovery following stroke and motor learning-based rehabilitation in a mouse model of subcortical WMS. Following WMS, a transient increase in differentiating oligodendrocytes occurs within the peri-infarct in young male adult mice, which is completely abolished in male aged mice. Compound action potential recording demonstrates a decrease in conduction velocity of myelinated axons at the peri-infarct. Animals were then tested on one of three distinct motor learning-based rehabilitation strategies (skilled reach, restricted access to a complex running wheel, and unrestricted access to a complex running wheel) for their capacity to induce repair. These studies determined that unrestricted access to a complex running wheel alone increases the density of differentiating oligodendrocytes in infarcted white matter in young adult male mice, which is abolished in aged male mice. Unrestricted access to a complex running wheel was also able to enhance conduction velocity of myelinated axons at the peri-infarct to a speed comparable to naive controls suggesting functional recovery. However, there was no evidence of motor rehabilitation-induced remyelination or myelin protection.SIGNIFICANCE STATEMENT White matter stroke is a common disease with no medical therapy. A form of motor rehabilitation improves some aspects of white matter repair and recovery.
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Affiliation(s)
- Miguel A Marin
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California 90095
| | - Amy J Gleichman
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California 90095
| | - Xiaofei Wei
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California 90095
| | - Daniel S Whittaker
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California 90095
| | - Istvan Mody
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California 90095
| | - Christopher S Colwell
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California 90095
| | - S Thomas Carmichael
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California 90095
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Nerattini M, Rubino F, Jett S, Andy C, Boneu C, Zarate C, Carlton C, Loeb-Zeitlin S, Havryliuk Y, Pahlajani S, Williams S, Berti V, Christos P, Fink M, Dyke JP, Brinton RD, Mosconi L. Elevated gonadotropin levels are associated with increased biomarker risk of Alzheimer's disease in midlife women. FRONTIERS IN DEMENTIA 2023; 2:1303256. [PMID: 38774256 PMCID: PMC11108587 DOI: 10.3389/frdem.2023.1303256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/24/2024]
Abstract
Introduction In preclinical studies, menopausal elevations in pituitary gonadotropins, follicle-stimulating hormone (FSH) and luteinizing hormone (LH), trigger Alzheimer's disease (AD) pathology and synaptic loss in female animals. Herein, we took a translational approach to test whether gonadotropin elevations are linked to AD pathophysiology in women. Methods We examined 191 women ages 40-65 years, carrying risk factors for late-onset AD, including 45 premenopausal, 67 perimenopausal, and 79 postmenopausal participants with clinical, laboratory, cognitive exams, and volumetric MRI scans. Half of the cohort completed 11C-Pittsburgh Compound B (PiB) amyloid-β (Aβ) PET scans. Associations between serum FSH, LH and biomarkers were examined using voxel-based analysis, overall and stratified by menopause status. Associations with region-of-interest (ROI) hippocampal volume, plasma estradiol levels, APOE-4 status, and cognition were assessed in sensitivity analyses. Results FSH levels were positively associated with Aβ load in frontal cortex (multivariable adjusted P≤0.05, corrected for family wise type error, FWE), an effect that was driven by the postmenopausal group (multivariable adjusted PFWE ≤ 0.044). LH levels were also associated with Aβ load in frontal cortex, which did not survive multivariable adjustment. FSH and LH were negatively associated with gray matter volume (GMV) in frontal cortex, overall and in each menopausal group (multivariable adjusted PFWE ≤ 0.040), and FSH was marginally associated with ROI hippocampal volume (multivariable adjusted P = 0.058). Associations were independent of age, clinical confounders, menopause type, hormone therapy status, history of depression, APOE-4 status, and regional effects of estradiol. There were no significant associations with cognitive scores. Discussion Increasing serum gonadotropin levels, especially FSH, are associated with higher Aβ load and lower GMV in some AD-vulnerable regions of midlife women at risk for AD. These findings are consistent with preclinical work and provide exploratory hormonal targets for precision medicine strategies for AD risk reduction.
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Affiliation(s)
- Matilde Nerattini
- Department of Neurology, Weill Cornell Medicine, New York, NY, United States
- Department of Experimental and Clinical Biomedical Sciences, Nuclear Medicine Unit, University of Florence, Florence, Italy
| | - Federica Rubino
- Department of Neurology, Weill Cornell Medicine, New York, NY, United States
- Department of Experimental and Clinical Biomedical Sciences, Nuclear Medicine Unit, University of Florence, Florence, Italy
| | - Steven Jett
- Department of Neurology, Weill Cornell Medicine, New York, NY, United States
| | - Caroline Andy
- Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, United States
| | - Camila Boneu
- Department of Neurology, Weill Cornell Medicine, New York, NY, United States
| | - Camila Zarate
- Department of Neurology, Weill Cornell Medicine, New York, NY, United States
| | - Caroline Carlton
- Department of Neurology, Weill Cornell Medicine, New York, NY, United States
| | - Susan Loeb-Zeitlin
- Department of Obstetrics and Gynecology, Weill Cornell Medicine, New York, NY, United States
| | - Yelena Havryliuk
- Department of Obstetrics and Gynecology, Weill Cornell Medicine, New York, NY, United States
| | - Silky Pahlajani
- Department of Neurology, Weill Cornell Medicine, New York, NY, United States
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Schantel Williams
- Department of Neurology, Weill Cornell Medicine, New York, NY, United States
| | - Valentina Berti
- Department of Experimental and Clinical Biomedical Sciences, Nuclear Medicine Unit, University of Florence, Florence, Italy
| | - Paul Christos
- Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, United States
| | - Matthew Fink
- Department of Neurology, Weill Cornell Medicine, New York, NY, United States
| | - Jonathan P. Dyke
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Roberta Diaz Brinton
- Department of Neurology and Pharmacology, University of Arizona, Tucson, AZ, United States
| | - Lisa Mosconi
- Department of Neurology, Weill Cornell Medicine, New York, NY, United States
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States
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Wang R, Wu X, Zhang Z, Cao L, Kwapong WR, Wang H, Tao W, Ye C, Liu J, Wu B. Retinal ganglion cell-inner plexiform layer, white matter hyperintensities, and their interaction with cognition in older adults. Front Aging Neurosci 2023; 15:1240815. [PMID: 38035269 PMCID: PMC10685347 DOI: 10.3389/fnagi.2023.1240815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 10/11/2023] [Indexed: 12/02/2023] Open
Abstract
Purpose We explored the interaction of optical coherence tomography (OCT) parameters and white matter hyperintensities with cognitive measures in our older adult cohort. Methods This observational study enrolled participants who underwent a comprehensive neuropsychological battery, structural 3-T brain magnetic resonance imaging (MRI), visual acuity examination, and OCT imaging. Cerebral small vessel disease (CSVD) markers were read on MR images; lacune, cerebral microbleeds (CMB), white matter hyperintensities (WMH), and enlarged perivascular spaces (EPVS), were defined according to the STRIVE standards. Retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (GCIPL) thicknesses (μm) were measured on the OCT tool. Results Older adults with cognitive impairment (CI) showed lower RNFL (p = 0.001), GCIPL (p = 0.009) thicknesses, and lower hippocampal volume (p = 0.004) when compared to non-cognitively impaired (NCI). RNFL (p = 0.006) and GCIPL thicknesses (p = 0.032) correlated with MoCA scores. GCIPL thickness (p = 0.037), total WMH (p = 0.003), PWMH (p = 0.041), and DWMH (p = 0.001) correlated with hippocampal volume in our older adults after adjusting for covariates. With hippocampal volume as the outcome, a significant interaction (p < 0.05) between GCIPL and PWMH and total WMH was observed in our older adults. Conclusion Both GCIPL thinning and higher WMH burden (especially PWMH) are associated with hippocampal volume and older adults with both pathologies are more susceptible to subclinical cognitive decline.
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Affiliation(s)
- Ruilin Wang
- Ophthalmology Department, West China Hospital, Sichuan University, Chengdu, China
| | - Xinmao Wu
- Neurology Department, West China Hospital, Sichuan University, Chengdu, China
| | - Zengyi Zhang
- Neurology Department, West China Hospital, Sichuan University, Chengdu, China
| | - Le Cao
- Ophthalmology Department, West China Hospital, Sichuan University, Chengdu, China
| | | | - Hang Wang
- Neurology Department, West China Hospital, Sichuan University, Chengdu, China
| | - Wendan Tao
- Neurology Department, West China Hospital, Sichuan University, Chengdu, China
| | - Chen Ye
- Neurology Department, West China Hospital, Sichuan University, Chengdu, China
| | - Junfeng Liu
- Neurology Department, West China Hospital, Sichuan University, Chengdu, China
| | - Bo Wu
- Neurology Department, West China Hospital, Sichuan University, Chengdu, China
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Sokolovič L, Hofmann MJ, Mohammad N, Kukolja J. Neuropsychological differential diagnosis of Alzheimer's disease and vascular dementia: a systematic review with meta-regressions. Front Aging Neurosci 2023; 15:1267434. [PMID: 38020767 PMCID: PMC10657839 DOI: 10.3389/fnagi.2023.1267434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 10/16/2023] [Indexed: 12/01/2023] Open
Abstract
Introduction Diagnostic classification systems and guidelines posit distinguishing patterns of impairment in Alzheimer's (AD) and vascular dementia (VaD). In our study, we aim to identify which diagnostic instruments distinguish them. Methods We searched PubMed and PsychInfo for empirical studies published until December 2020, which investigated differences in cognitive, behavioral, psychiatric, and functional measures in patients older than 64 years and reported information on VaD subtype, age, education, dementia severity, and proportion of women. We systematically reviewed these studies and conducted Bayesian hierarchical meta-regressions to quantify the evidence for differences using the Bayes factor (BF). The risk of bias was assessed using the Newcastle-Ottawa-Scale and funnel plots. Results We identified 122 studies with 17,850 AD and 5,247 VaD patients. Methodological limitations of the included studies are low comparability of patient groups and an untransparent patient selection process. In the digit span backward task, AD patients were nine times more probable (BF = 9.38) to outperform VaD patients (β g = 0.33, 95% ETI = 0.12, 0.52). In the phonemic fluency task, AD patients outperformed subcortical VaD (sVaD) patients (β g = 0.51, 95% ETI = 0.22, 0.77, BF = 42.36). VaD patients, in contrast, outperformed AD patients in verbal (β g = -0.61, 95% ETI = -0.97, -0.26, BF = 22.71) and visual (β g = -0.85, 95% ETI = -1.29, -0.32, BF = 13.67) delayed recall. We found the greatest difference in verbal memory, showing that sVaD patients outperform AD patients (β g = -0.64, 95% ETI = -0.88, -0.36, BF = 72.97). Finally, AD patients performed worse than sVaD patients in recognition memory tasks (β g = -0.76, 95% ETI = -1.26, -0.26, BF = 11.50). Conclusion Our findings show inferior performance of AD in episodic memory and superior performance in working memory. We found little support for other differences proposed by diagnostic systems and diagnostic guidelines. The utility of cognitive, behavioral, psychiatric, and functional measures in differential diagnosis is limited and should be complemented by other information. Finally, we identify research areas and avenues, which could significantly improve the diagnostic value of cognitive measures.
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Affiliation(s)
- Leo Sokolovič
- Department of Neurology and Clinical Neurophysiology, Helios University Hospital Wuppertal, Wuppertal, Germany
- Faculty of Health, Witten/Herdecke University, Witten, Germany
- Department of General and Biological Psychology, University of Wuppertal, Wuppertal, Germany
| | - Markus J. Hofmann
- Department of General and Biological Psychology, University of Wuppertal, Wuppertal, Germany
| | - Nadia Mohammad
- Department of General and Biological Psychology, University of Wuppertal, Wuppertal, Germany
| | - Juraj Kukolja
- Department of Neurology and Clinical Neurophysiology, Helios University Hospital Wuppertal, Wuppertal, Germany
- Faculty of Health, Witten/Herdecke University, Witten, Germany
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Canepa E, Parodi-Rullan R, Vazquez-Torres R, Gamallo-Lana B, Guzman-Hernandez R, Lemon NL, Angiulli F, Debure L, Ilies MA, Østergaard L, Wisniewski T, Gutiérrez-Jiménez E, Mar AC, Fossati S. FDA-approved carbonic anhydrase inhibitors reduce amyloid β pathology and improve cognition, by ameliorating cerebrovascular health and glial fitness. Alzheimers Dement 2023; 19:5048-5073. [PMID: 37186121 PMCID: PMC10600328 DOI: 10.1002/alz.13063] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 03/09/2023] [Accepted: 03/09/2023] [Indexed: 05/17/2023]
Abstract
INTRODUCTION Cerebrovascular pathology is an early and causal hallmark of Alzheimer's disease (AD), in need of effective therapies. METHODS Based on the success of our previous in vitro studies, we tested for the first time in a model of AD and cerebral amyloid angiopathy (CAA), the carbonic anhydrase inhibitors (CAIs) methazolamide and acetazolamide, Food and Drug Administration-approved against glaucoma and high-altitude sickness. RESULTS Both CAIs reduced cerebral, vascular, and glial amyloid beta (Aβ) accumulation and caspase activation, diminished gliosis, and ameliorated cognition in TgSwDI mice. The CAIs also improved microvascular fitness and induced protective glial pro-clearance pathways, resulting in the reduction of Aβ deposition. Notably, we unveiled that the mitochondrial carbonic anhydrase-VB (CA-VB) is upregulated in TgSwDI brains, CAA and AD+CAA human subjects, and in endothelial cells upon Aβ treatment. Strikingly, CA-VB silencing specifically reduces Aβ-mediated endothelial apoptosis. DISCUSSION This work substantiates the potential application of CAIs in clinical trials for AD and CAA.
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Affiliation(s)
- Elisa Canepa
- Alzheimer’s Center at Temple, Department of Neural Sciences, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, 19140, USA
| | - Rebecca Parodi-Rullan
- Alzheimer’s Center at Temple, Department of Neural Sciences, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, 19140, USA
| | - Rafael Vazquez-Torres
- Alzheimer’s Center at Temple, Department of Neural Sciences, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, 19140, USA
| | - Begona Gamallo-Lana
- Department of Neuroscience and Physiology, Neuroscience Institute, NYU Grossman School of Medicine, New York, NY, 10016, USA
| | - Roberto Guzman-Hernandez
- Alzheimer’s Center at Temple, Department of Neural Sciences, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, 19140, USA
| | - Nicole L. Lemon
- Alzheimer’s Center at Temple, Department of Neural Sciences, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, 19140, USA
| | - Federica Angiulli
- Alzheimer’s Center at Temple, Department of Neural Sciences, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, 19140, USA
| | - Ludovic Debure
- Department on Neurology, Center for Cognitive Neurology, NYU Grossman School of Medicine, New York, NY, 10016, USA
| | - Marc A. Ilies
- Department of Pharmaceutical Sciences and Moulder Center for Drug Discovery Research, Temple University School of Pharmacy, Temple University, Philadelphia, PA, 19140, USA
| | - Leif Østergaard
- Center of Functionally Integrative Neuroscience (CFIN), Department of Clinical Medicine, Aarhus University, 8200 Aarhus, Denmark
| | - Thomas Wisniewski
- Department on Neurology, Center for Cognitive Neurology, NYU Grossman School of Medicine, New York, NY, 10016, USA
| | - Eugenio Gutiérrez-Jiménez
- Center of Functionally Integrative Neuroscience (CFIN), Department of Clinical Medicine, Aarhus University, 8200 Aarhus, Denmark
| | - Adam C. Mar
- Department of Neuroscience and Physiology, Neuroscience Institute, NYU Grossman School of Medicine, New York, NY, 10016, USA
| | - Silvia Fossati
- Alzheimer’s Center at Temple, Department of Neural Sciences, Lewis Katz School of Medicine, Temple University, Philadelphia, PA, 19140, USA
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Huang R, Zhang L, Deng L, Chen C. White matter hyperintensities combined with serum NLRP3 in diagnosis of cognitive impairment in patients with cerebral small vessel disease. Scand J Clin Lab Invest 2023; 83:448-454. [PMID: 37702579 DOI: 10.1080/00365513.2023.2255974] [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: 07/06/2023] [Accepted: 09/03/2023] [Indexed: 09/14/2023]
Abstract
Background: White matter hyperintensities (WMH) are widely used for the diagnosis of cerebral small vessel disease (CSVD). However, whether NLRP3 is correlated with cognitive impairment after CSVD is still not clear.Objective: This study aimed to investigate the diagnostic value of WMHs combined with NLRP3 for cognitive impairment after CSVD.Methods: This prospective observational study enrolled a total of 188 CSVD patients from September 2019 to May 2022. All patients received brain MRI assessment and WMH Fazekas score, as well as WMH volume, was recorded. Serum NLRP3 level was measured by ELISA. Patients' cognitive function was measured by MoCA after 6 months of diagnosis of CSVD. The serum levels of C reactive protein (CRP), interleukin (IL)-6, total cholesterol (TC), triglyceride (TG), high-density leptin cholesterol (HDL) and low-density leptin cholesterol (LDL) were recordedResults: CSVD patients with cognitive impairment had significantly higher Fazekas scores, WMH volumes, serum NLRP3 and IL-6 levels compared to patients without cognitive impairment. A positive correlation was found among Fazekas scores, WMH volumes and NLRP3 levels. The combination of WMH volume and NLRP3 could achieve a better specificity for the diagnosis of cognitive impairment. Coronary syndrome history, WMH volume and NLRP3 were found as independent risk factors for cognitive impairment after CSVD.Conclusion: Fazekas scores, WMH volume and serum NLRP3 levels are associated with cognitive impairment after CSVD and have the potential to be used as diagnostic biomarkers.
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Affiliation(s)
- Ronghui Huang
- Department of Medical Imaging, the Fourth Hospital of Changsha, Changsha, Hunan Province, P.R. China
| | - Lin Zhang
- Department of Emergency, the Fourth Hospital of Changsha, Changsha, Hunan Province, P.R. China
| | - Limeng Deng
- Department of Medical Imaging, the Fourth Hospital of Changsha, Changsha, Hunan Province, P.R. China
| | - Can Chen
- Department of Medical Imaging, the Fourth Hospital of Changsha, Changsha, Hunan Province, P.R. China
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Greco F, Quarta LG, Parizel PM, Zobel BB, Quattrocchi CC, Mallio CA. Relationship between chronic kidney disease and cerebral white matter hyperintensities: a systematic review. Quant Imaging Med Surg 2023; 13:7596-7606. [PMID: 37969631 PMCID: PMC10644141 DOI: 10.21037/qims-22-707] [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: 07/05/2022] [Accepted: 11/21/2022] [Indexed: 11/17/2023]
Abstract
Background This systematic review summarizes available evidence on the relationship between white matter hyperintensities (WMH) volumetric quantification on brain MRI scans and chronic kidney disease (CKD). Methods The literature search was performed in March 2022 using MEDLINE PubMed Central, Scopus and Web of Science - Publons as search engines. Relevant articles investigating, with a quantitative volumetric approach, the link between WMH and CKD patients were selected. Results The database search strategy found 987 articles, after excluding duplicates, the titles and abstracts of the remaining 320 articles were examined. Subsequently 276 articles were excluded as they were not relevant to the topic. Of the 44 articles evaluated for eligibility, 36 were excluded because the quantitative analysis of WMH was not volumetric. Finally, 8 articles were included in this systematic review. Conclusions Literature on this topic is extremely heterogeneous in terms of methodology and samples. However, evidence shows that there is a relationship between CKD and WMH volume of the brain. We recommend that quantifiable biomarkers such as estimated glomerular filtration rate (eGFR) and urine albumin to creatinine ratio (UACR) should be included in studies dealing with cerebrovascular disease. The biological and molecular mechanisms underlying cerebrovascular damage in patients with chronic renal failure deserve to be further explored.
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Affiliation(s)
- Federico Greco
- Diagnostica Per Immagini Territoriale Aziendale, Cittadella Della Salute Azienda Sanitaria Locale Di Lecce, Piazza Filippo Bottazzi, Lecce, Italy
| | - Luigi Giuseppe Quarta
- Diagnostica Per Immagini Territoriale Aziendale, Cittadella Della Salute Azienda Sanitaria Locale Di Lecce, Piazza Filippo Bottazzi, Lecce, Italy
| | - Paul M. Parizel
- David Hartley Chair of Radiology, Royal Perth Hospital & University of Western Australia, Perth, Western Australia, Australia
| | - Bruno Beomonte Zobel
- Unit of Diagnostic Imaging, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, Rome, Italy
| | - Carlo Cosimo Quattrocchi
- Unit of Diagnostic Imaging, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, Rome, Italy
| | - Carlo Augusto Mallio
- Unit of Diagnostic Imaging, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, Rome, Italy
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Zhang R, Peng L, Cai Q, Xu Y, Liu Z, Liu Y. Development and validation of a predictive model for white matter lesions in young- and middle-aged people. Front Neurol 2023; 14:1257795. [PMID: 37928162 PMCID: PMC10622790 DOI: 10.3389/fneur.2023.1257795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 10/02/2023] [Indexed: 11/07/2023] Open
Abstract
Background White matter lesion (WML) is an age-related disorder associated with stroke and cognitive impairment. This study aimed to investigate the risk factors and build a predictive model of WML in young- and middle-aged people. Methods We performed a second analysis of the data from the Dryad Digital Repository. We selected those people who are <60 years old and randomly divided them into the training group and the validation group. We investigated the risk factors of WML in the training group with logistic regression analysis and built a prediction nomogram based on multivariate logistic regression analysis; finally, the performance of the prediction nomogram was evaluated for discrimination, accuracy, and clinical utility. Results There were 308 people in the training group and 723 people in the validation group. Multivariate regression analysis showed that the age (OR = 1.49, 95% CI: 1.31-1.70), diastolic blood pressure (OR = 1.02, 95% CI: 1.00-1.03), carotid plaque score (OR = 1.31, 95% CI: 1.14-1.50), female gender (OR = 2.27, 95% CI: 1.56-3.30), and metabolic syndrome (OR = 2.12, 95% CI: 1.22-3.70) were significantly associated with white matter lesions. The area under the curve value (AUC) of the receiver operating curve (ROC) was 0.734 for the training group and 0.642 for the validation group. The calibration curve and clinical impact curve showed that the prediction nomogram has good accuracy and clinical application value. Conclusion Age, diastolic blood pressure, carotid plaque score, female gender, and metabolic syndrome were risk factors in young- and middle-aged people <60 years old with WML, and the nomogram based on these risk factors showed good discrimination, accuracy, and clinical utility.
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Affiliation(s)
- Renwei Zhang
- Department of Neurology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Li Peng
- Department of Cardiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Qi Cai
- Department of Neurology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Yao Xu
- Department of Neurology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Zhenxing Liu
- Department of Neurology, Yiling Hospital of Yichang, Yichang, China
| | - Yumin Liu
- Department of Neurology, Zhongnan Hospital of Wuhan University, Wuhan, China
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Wang Y, Liu Z. Research progress on the correlation between MRI and impairment caused by cerebral small vessel disease: A review. Medicine (Baltimore) 2023; 102:e35389. [PMID: 37800770 PMCID: PMC10553107 DOI: 10.1097/md.0000000000035389] [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: 04/13/2023] [Accepted: 09/05/2023] [Indexed: 10/07/2023] Open
Abstract
Cerebral small vessel disease (CSVD) is a chronic global brain disease mainly involving small blood vessels in the brain. The disease can be gradually aggravated with the increase of age, so it is the primary cause of brain dysfunction in the elderly. With the increasing aging of the world population and the high incidence of cerebrovascular risk factors, the incidence of CSVD is increasing day by day. CSVD is characterized by insidious onset, slow progression, diverse clinical manifestations, and difficult early diagnosis. CSVD can lead to cognitive impairment, gait impairment, affective impairment, and so on. however, it has not received enough attention from researchers in the past. In recent years, some studies have shown that CSVD patients have a high proportion of related impairment, which seriously affect patients daily life and social functions. Currently, no clear preventive measures or treatments exist to improve the condition. With the development of magnetic resonance imaging, CSVD has become more and more recognized and the detection rate has gradually improved. This paper reviews the research progress of magnetic resonance imaging and cognitive impairment, gait impairment, affective impairment, urination disorder, swallowing disorder, and other disorders to provide a useful reference for the early diagnosis and treatment of CSVD and expand new ideas.
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Affiliation(s)
- Yang Wang
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi’an, China
- Department of Neurology, 980th Hospital of PLA Joint Logistical Support Force (Bethune International Peace Hospital), Shijiazhuang, China
| | - Zhirong Liu
- Department of Neurology, Xijing Hospital, Fourth Military Medical University, Xi’an, China
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Ali DG, Bahrani AA, El Khouli RH, Gold BT, Jiang Y, Zachariou V, Wilcock DM, Jicha GA. White matter hyperintensities influence distal cortical β-amyloid accumulation in default mode network pathways. Brain Behav 2023; 13:e3209. [PMID: 37534614 PMCID: PMC10570488 DOI: 10.1002/brb3.3209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2023] [Revised: 07/19/2023] [Accepted: 07/22/2023] [Indexed: 08/04/2023] Open
Abstract
BACKGROUND AND PURPOSE Cerebral small vessel disease (SVD) has been suggested to contribute to the pathogenesis of Alzheimer's disease (AD). Yet, the role of SVD in potentially contributing to AD pathology is unclear. The main objective of this study was to test the hypothesis that WMHs influence amyloid β (Aβ) levels within connected default mode network (DMN) tracts and cortical regions in cognitively unimpaired older adults. METHODS Regional standard uptake value ratios (SUVr) from Aβ-PET and white matter hyperintensity (WMH) volumes from three-dimensional magnetic resonance imaging FLAIR images were analyzed across a sample of 72 clinically unimpaired (mini-mental state examination ≥26), older adults (mean age 74.96 and standard deviation 8.13) from the Alzheimer's Disease Neuroimaging Initiative (ADNI3). The association of WMH volumes in major fiber tracts projecting from cortical DMN regions and Aβ-PET SUVr in the connected cortical DMN regions was analyzed using linear regression models adjusted for age, sex, ApoE, and total brain volumes. RESULTS The regression analyses demonstrate that increased WMH volumes in the superior longitudinal fasciculus were associated with increased regional SUVr in the inferior parietal lobule (p = .011). CONCLUSION The findings suggest that the relation between Aβ in parietal cortex is associated with SVD in downstream white matter (WM) pathways in preclinical AD. The biological relationships and interplay between Aβ and WM microstructure alterations that precede overt WMH development across the continuum of AD progression warrant further study.
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Affiliation(s)
- Doaa G. Ali
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Behavioral Science, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Ahmed A. Bahrani
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Neurology, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Riham H. El Khouli
- Department of Radiology, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Brian T. Gold
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Neuroscience, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Yang Jiang
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Behavioral Science, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Valentinos Zachariou
- Department of Neuroscience, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Donna M. Wilcock
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Physiology, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Gregory A. Jicha
- Sanders‐Brown Center on Aging, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Behavioral Science, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
- Department of Neurology, College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
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Strain JF, Phuah CL, Adeyemo B, Cheng K, Womack KB, McCarthy J, Goyal M, Chen Y, Sotiras A, An H, Xiong C, Scharf A, Newsom-Stewart C, Morris JC, Benzinger TLS, Lee JM, Ances BM. White matter hyperintensity longitudinal morphometric analysis in association with Alzheimer disease. Alzheimers Dement 2023; 19:4488-4497. [PMID: 37563879 PMCID: PMC10592317 DOI: 10.1002/alz.13377] [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: 11/29/2022] [Revised: 05/30/2023] [Accepted: 06/02/2023] [Indexed: 08/12/2023]
Abstract
INTRODUCTION Vascular damage in Alzheimer's disease (AD) has shown conflicting findings particularly when analyzing longitudinal data. We introduce white matter hyperintensity (WMH) longitudinal morphometric analysis (WLMA) that quantifies WMH expansion as the distance from lesion voxels to a region of interest boundary. METHODS WMH segmentation maps were derived from 270 longitudinal fluid-attenuated inversion recovery (FLAIR) ADNI images. WLMA was performed on five data-driven WMH patterns with distinct spatial distributions. Amyloid accumulation was evaluated with WMH expansion across the five WMH patterns. RESULTS The preclinical group had significantly greater expansion in the posterior ventricular WM compared to controls. Amyloid significantly associated with frontal WMH expansion primarily within AD individuals. WLMA outperformed WMH volume changes for classifying AD from controls primarily in periventricular and posterior WMH. DISCUSSION These data support the concept that localized WMH expansion continues to proliferate with amyloid accumulation throughout the entirety of the disease in distinct spatial locations.
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Affiliation(s)
- Jeremy Fuller Strain
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Chia-Ling Phuah
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Babatunde Adeyemo
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Kathleen Cheng
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Kyle B Womack
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - John McCarthy
- Department of Mathematics, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Manu Goyal
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Yasheng Chen
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Aristeidis Sotiras
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
- Institute for Informatics, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Hongyu An
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Chengjie Xiong
- Division of Biostatics, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Andrea Scharf
- Department of Biological Sciences, Missouri University for Science and Technology, Rolla, Missouri, USA
| | - Catherine Newsom-Stewart
- Department of Developmental Biology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - John Carl Morris
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Knight Alzheimer Disease Research Center, St. Louis, Missouri, USA
| | - Tammie Lee Smith Benzinger
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
- Knight Alzheimer Disease Research Center, St. Louis, Missouri, USA
| | - Jin-Moo Lee
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Beau M Ances
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, Missouri, USA
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
- Knight Alzheimer Disease Research Center, St. Louis, Missouri, USA
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Caprihan A, Hillmer L, Erhardt EB, Adair JC, Knoefel JE, Prestopnik J, Rosenberg GA. A trichotomy method for defining homogeneous subgroups in a dementia population. Ann Clin Transl Neurol 2023; 10:1802-1815. [PMID: 37602520 PMCID: PMC10578887 DOI: 10.1002/acn3.51869] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 07/11/2023] [Accepted: 07/22/2023] [Indexed: 08/22/2023] Open
Abstract
INTRODUCTION Diagnosis of dementia in the aging brain is confounded by the presence of multiple pathologies. Mixed dementia (MX), a combination of Alzheimer's disease (AD) proteins with vascular disease (VD), is frequently found at autopsy, and has been difficult to diagnose during life. This report develops a method for separating the MX group and defining preclinical AD (presence of AD factors with normal cognition) and preclinical VD subgroups (presence of white matter damage with normal cognition). METHODS Clustering was based on three diagnostic axes: (1) AD factor (ADF) derived from cerebrospinal fluid proteins (Aβ42 and pTau), (2) VD factor (VDF) calculated from mean free water and peak width of skeletonized mean diffusivity in the white matter, and (3) Cognition (Cog) based on memory and executive function. The trichotomy method was applied to an Alzheimer's Disease Neuroimaging Initiative cohort (N = 538). RESULTS Eight biologically defined subgroups were identified which included the MX group with both high ADF and VDF (9.3%) and a preclinical VD group (3.9%), and a preclinical AD group (13.6%). Cog is significantly associated with both ADF and VDF, and the partial-correlation remains significant even when the effect of the other variable is removed (r(Cog, ADF/VDF removed) = 0.46, p < 10-28 and r(Cog, VDF/ADF removed) = 0.24, p < 10-7 ). DISCUSSION The trichotomy method creates eight biologically characterized patient groups, which includes MX, preclinical AD, and preclinical VD subgroups. Further longitudinal studies are needed to determine the utility of the 3-way clustering method with multimodal biological biomarkers.
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Affiliation(s)
| | - Laura Hillmer
- Center for Memory and AgingUniversity of New Mexico School of MedicineAlbuquerqueNew Mexico87106USA
| | - Erik Barry Erhardt
- Departments of Mathematics and StatisticsUniversity of New Mexico College of Arts and SciencesAlbuquerqueNew Mexico87106USA
| | - John C. Adair
- Center for Memory and AgingUniversity of New Mexico School of MedicineAlbuquerqueNew Mexico87106USA
- Department of NeurologyUniversity of New MexicoAlbuquerqueNew Mexico87106USA
| | - Janice E. Knoefel
- Center for Memory and AgingUniversity of New Mexico School of MedicineAlbuquerqueNew Mexico87106USA
- Department of NeurologyUniversity of New MexicoAlbuquerqueNew Mexico87106USA
| | - Jillian Prestopnik
- Center for Memory and AgingUniversity of New Mexico School of MedicineAlbuquerqueNew Mexico87106USA
| | - Gary A. Rosenberg
- Center for Memory and AgingUniversity of New Mexico School of MedicineAlbuquerqueNew Mexico87106USA
- Department of NeurologyUniversity of New MexicoAlbuquerqueNew Mexico87106USA
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Wang L, Chaudhari K, Winters A, Sun Y, Berry R, Tang C, Yang SH, Liu R. Recurrent Transient Ischemic Attack Induces Neural Cytoskeleton Modification and Gliosis in an Experimental Model. Transl Stroke Res 2023; 14:740-751. [PMID: 35867329 DOI: 10.1007/s12975-022-01068-7] [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: 06/08/2022] [Revised: 07/11/2022] [Accepted: 07/14/2022] [Indexed: 01/28/2023]
Abstract
Transient ischemic attack (TIA) presents a high risk for subsequent stroke, Alzheimer's disease (AD), and related dementia (ADRD). However, the neuropathophysiology of TIA has been rarely studied. By evaluating recurrent TIA-induced neuropathological changes, our study aimed to explore the potential mechanisms underlying the contribution of TIA to ADRD. In the current study, we established a recurrent TIA model by three times 10-min middle cerebral artery occlusion within a week in rat. Neither permanent neurological deficit nor apoptosis was observed following recurrent TIA. No increase of AD-related biomarkers was indicated after TIA, including increase of tau hyperphosphorylation and β-site APP cleaving enzyme 1 (BACE1). Neuronal cytoskeleton modification and neuroinflammation was found at 1, 3, and 7 days after recurrent TIA, evidenced by the reduction of microtubule-associated protein 2 (MAP2), elevation of neurofilament-light chain (NFL), and increase of glial fibrillary acidic protein (GFAP)-positive astrocytes and ionized calcium binding adaptor molecule 1 (Iba1)-positive microglia at the TIA-affected cerebral cortex and basal ganglion. Similar NFL, GFAP and Iba1 alteration was found in the white matter of corpus callosum. In summary, the current study demonstrated that recurrent TIA may trigger neuronal cytoskeleton change, astrogliosis, and microgliosis without induction of cell death at the acute and subacute stage. Our study indicates that TIA-induced neuronal cytoskeleton modification and neuroinflammation may be involved in the vascular contribution to cognitive impairment and dementia.
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Affiliation(s)
- Linshu Wang
- Departments of Pharmacology & Neuroscience, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107-2699, USA
| | - Kiran Chaudhari
- Departments of Pharmacology & Neuroscience, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107-2699, USA
| | - Ali Winters
- Departments of Pharmacology & Neuroscience, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107-2699, USA
| | - Yuanhong Sun
- Departments of Pharmacology & Neuroscience, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107-2699, USA
| | - Raymond Berry
- Departments of Pharmacology & Neuroscience, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107-2699, USA
| | - Christina Tang
- Departments of Pharmacology & Neuroscience, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107-2699, USA
| | - Shao-Hua Yang
- Departments of Pharmacology & Neuroscience, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107-2699, USA.
| | - Ran Liu
- Departments of Pharmacology & Neuroscience, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX, 76107-2699, USA.
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Terracciano A, Cenatus B, Zhu X, Karakose S, Stephan Y, Marcolini S, De Deyn PP, Luchetti M, Sutin AR. Neuroticism and white matter hyperintensities. J Psychiatr Res 2023; 165:174-179. [PMID: 37506413 PMCID: PMC10528519 DOI: 10.1016/j.jpsychires.2023.07.026] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Revised: 07/17/2023] [Accepted: 07/20/2023] [Indexed: 07/30/2023]
Abstract
Neuroticism is a major risk factor for neurodegenerative disorders, such as Alzheimer's disease and related dementias. This study investigates whether neuroticism is associated with white matter hyperintensities and whether this measure of brain integrity is a mediator between neuroticism and cognitive function. Middle-aged and older adults from the UK Biobank (N = 40,602; aged 45-82 years, M = 63.97, SD = 7.66) provided information on demographic and health covariates, completed measures of neuroticism and cognition, and underwent magnetic resonance imaging from which the volume of white matter hyperintensities was derived. Regression analyses that included age and sex as covariates found that participants who scored higher on neuroticism had more white matter hyperintensities (β = 0.024, 95% CI 0.015 to 0.032; p < .001), an association that was consistent across peri-ventricular and deep brain regions. The association was reduced by about 40% when accounting for vascular risk factors (smoking, obesity, diabetes, high blood pressure, heart attack, angina, and stroke). The association was not moderated by age, sex, college education, deprivation index, or APOE e4 genotype, and remained unchanged in sensitivity analyses that excluded individuals with dementia or those younger than 65. The mediation analysis revealed that white matter hyperintensities partly mediated the association between neuroticism and cognitive function. These findings identify white matter integrity as a potential neurobiological pathway that accounts for a small proportion of the association between neuroticism and cognitive health.
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Affiliation(s)
- Antonio Terracciano
- Department of Geriatrics, Florida State University College of Medicine, Tallahassee, FL, USA.
| | - Bertin Cenatus
- Department of Geriatrics, Florida State University College of Medicine, Tallahassee, FL, USA
| | - Xianghe Zhu
- Department of Psychology, School of Mental Health, Institute of Aging, Key Laboratory of Alzheimer's Disease of Zhejiang Province, Zhejiang Provincial Clinical Research Center for Mental Disorders, The Affiliated Kangning Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, 325035, China; Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Wenzhou, Zhejiang, 325000, China
| | - Selin Karakose
- Department of Geriatrics, Florida State University College of Medicine, Tallahassee, FL, USA
| | | | - Sofia Marcolini
- Department of Neurology and Alzheimer Center, University Medical Center Groningen, Groningen, the Netherlands
| | - Peter P De Deyn
- Department of Neurology and Alzheimer Center, University Medical Center Groningen, Groningen, the Netherlands; Laboratory of Neurochemistry and Behavior, Experimental Neurobiology Unit, University of Antwerp, Wilrijk, Antwerp, Belgium
| | - Martina Luchetti
- Department of Behavioral Sciences and Social Medicine, Florida State University College of Medicine, Tallahassee, FL, USA
| | - Angelina R Sutin
- Department of Behavioral Sciences and Social Medicine, Florida State University College of Medicine, Tallahassee, FL, USA
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Anzai Y, Ertl-Wagner B. Neuroradiology 2040: A Glimpse into the Future. Radiology 2023; 308:e231267. [PMID: 37750766 DOI: 10.1148/radiol.231267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/27/2023]
Affiliation(s)
- Yoshimi Anzai
- From the Department of Radiology and Imaging Sciences, University of Utah Health, Salth Lake City, Utah (Y.A.); Department of Diagnostic and Interventional Radiology, The Hospital for Sick Children, 555 University Ave, Toronto, ON, Canada M5G 1X8 (B.E.W.); and Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada (B.E.W.)
| | - Birgit Ertl-Wagner
- From the Department of Radiology and Imaging Sciences, University of Utah Health, Salth Lake City, Utah (Y.A.); Department of Diagnostic and Interventional Radiology, The Hospital for Sick Children, 555 University Ave, Toronto, ON, Canada M5G 1X8 (B.E.W.); and Department of Medical Imaging, University of Toronto, Toronto, Ontario, Canada (B.E.W.)
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VandeBunte AM, Fonseca C, Paolillo EW, Gontrum E, Lee SY, Kramer JH, Casaletto KB. Regional Vulnerability of the Corpus Callosum in the Context of Cardiovascular Risk. J Geriatr Psychiatry Neurol 2023; 36:397-406. [PMID: 36710073 PMCID: PMC10441555 DOI: 10.1177/08919887231154931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Many factors outside of cardiovascular health can impact the structure of white matter. Identification of reliable and clinically meaningful biomarkers of the neural effects of systemic and cardiovascular health are needed to refine etiologic predictions. We examined whether the corpus callosum demonstrates regional vulnerability to systemic cardiovascular risk factors. Three hundred and ninety-four older adults without dementia completed brain MRI, neurobehavioral evaluations, and blood draws. A subset (n = 126, n = 128) of individuals had blood plasma analyzed for inflammatory markers of interest (IL-6 and TNF-alpha). Considering diffusion tensor imaging (DTI) is a particularly reliable measure of white matter integrity, we utilized DTI to examine fractional anisotropy (FA) of anterior and posterior regions of the corpus callosum. Using multiple linear regression models, we simultaneously examined FA of the genu and the splenium to compare their associations with systemic and cardiovascular risk factors. Lower FA of the genu but not splenium was associated with greater systemic and cardiovascular risk, including higher systolic blood pressure (β = -0.17, p = .020), hemoglobin A1C (β = -0.21, p = .016) and IL-6 (β = -0.34, p = .005). FA of the genu was uniquely associated with cognitive processing speed (β = 0.20, p = .0015) and executive functioning (β = 0.15, p = .012), but not memory performances (β = 0.05, p = .357). Our results demonstrated differential vulnerability of the corpus callosum, such that frontal regions showed stronger, independent associations with biomarkers of systemic and cardiovascular health in comparison to posterior regions. Posterior white matter integrity may not reflect cardiovascular health. Clinically, these findings support the utility of examining the anterior corpus callosum as an indicator of cerebrovascular health.
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Affiliation(s)
- Anna M. VandeBunte
- Department of Neurology, University of California, San Francisco, Memory and Aging Center, San Francisco, CA, USA
- Palo Alto University, CA, USA
| | - Corrina Fonseca
- Department of Neurology, University of California, San Francisco, Memory and Aging Center, San Francisco, CA, USA
| | - Emily W. Paolillo
- Department of Neurology, University of California, San Francisco, Memory and Aging Center, San Francisco, CA, USA
| | - Eva Gontrum
- Department of Neurology, University of California, San Francisco, Memory and Aging Center, San Francisco, CA, USA
| | - Shannon Y. Lee
- Department of Neurology, University of California, San Francisco, Memory and Aging Center, San Francisco, CA, USA
| | - Joel H. Kramer
- Department of Neurology, University of California, San Francisco, Memory and Aging Center, San Francisco, CA, USA
| | - Kaitlin B. Casaletto
- Department of Neurology, University of California, San Francisco, Memory and Aging Center, San Francisco, CA, USA
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Lin K, Wen W, Lipnicki DM, Mewton L, Chen R, Du J, Wang D, Skoog I, Sterner TR, Najar J, Kim KW, Han JW, Kim JS, Ng TP, Ho R, Chua DQL, Anstey KJ, Cherbuin N, Mortby ME, Brodaty H, Kochan N, Sachdev PS, Jiang J. Risk factors and cognitive correlates of white matter hyperintensities in ethnically diverse populations without dementia: the COSMIC consortium. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.30.23294876. [PMID: 37693599 PMCID: PMC10491386 DOI: 10.1101/2023.08.30.23294876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
INTRODUCTION White matter hyperintensities (WMH) are an important imaging marker for cerebral small vessel diseases, but their risk factors and cognitive associations have not been well-documented in populations of different ethnicities and/or from different geographical regions. METHOD Magnetic resonance imaging data of five population-based cohorts of non-demented older individuals from Australia, Singapore, South Korea, and Sweden (N = 1,946) were examined for WMH and their associations with vascular risk factors and cognition. RESULT Factors associated with larger whole brain WMH volumes included diabetes, hypertension, stroke, current smoking, body mass index, higher alcohol intake and insufficient physical activity. Participants with moderate or higher physical activity had less WMH than those who never exercised, but the former two groups did not differ. Hypertension and stroke had stronger associations with WMH volumes in the White, compared to Asian subsample. DISCUSSION The current study highlighted the ethnic differences in the contributions of vascular risk factors to WMH.
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Affiliation(s)
- Keshuo Lin
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Wei Wen
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Darren M. Lipnicki
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Louise Mewton
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Rory Chen
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Jing Du
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Dadong Wang
- CSIRO Informatics and Statistics, Locked Bag 17, North Ryde, NSW 1670, Australia
| | - Ingmar Skoog
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, Box 100, 405 30, at the University of Gothenburg, Sweden
- Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Box 100, 405 30, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Box 100, Goeteborg, Vaestra Goetaland 405 30, Sweden
| | - Therese Rydberg Sterner
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, Box 100, 405 30, at the University of Gothenburg, Sweden
- Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Box 100, 405 30, Sweden
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Nobels väg 6, 171 77 Stockholm, Sweden
| | - Jenna Najar
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, Box 100, 405 30, at the University of Gothenburg, Sweden
- Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Box 100, 405 30, Sweden
- Section Genomics of Neurodegenerative Diseases and Aging, Department of Human Genetics, Amsterdam Universitair Medische Centra, PO Box 7057, 1007 MB, Amsterdam, the Netherlands
| | - Ki Woong Kim
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Gyeonggi-do 13620, Seongnam, Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul 03080, Korea
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul 03080, Korea
| | - Ji Won Han
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Gyeonggi-do 13620, Seongnam, Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul 03080, Korea
| | - Jun Sung Kim
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Gyeonggi-do 13620, Seongnam, Korea
| | - Tze Pin Ng
- Khoo Teck Puat Hospital, 768828, Singapore
- Geriatric Education and Research Institute, Ministry of Health, 768024, Singapore
| | - Roger Ho
- Institute for Health Innovation and Technology (iHealthtech), National University of Singapore, 119077, Singapore
| | - Denise Qian Ling Chua
- Department of Psychological Medicine, National University of Singapore, 119077, Singapore
| | - Kaarin J. Anstey
- School of Psychology, University of New South Wales, NSW 2052,Australia
- Neuroscience Research Australia, NSW 2031, Australia
- Ageing Futures Institute, University of New South Wales, NSW 2052,Australia
| | - Nicolas Cherbuin
- National Centre for Epidemiology and Population Health, College of Health and Medicine, Australian National University, ACT 2600, Canberra, Australia
| | - Moyra E. Mortby
- School of Psychology, University of New South Wales, NSW 2052,Australia
- Neuroscience Research Australia, NSW 2031, Australia
- Ageing Futures Institute, University of New South Wales, NSW 2052,Australia
| | - Henry Brodaty
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Nicole Kochan
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
| | - Perminder S. Sachdev
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
- Neuropsychiatric Institute, The Prince of Wales Hospital, Sydney, NSW 2031, Australia
| | - Jiyang Jiang
- Centre for Healthy Brain Ageing, School of Clinical Medicine, University of New South Wales, Sydney, NSW 2052, Australia
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Li M, Habes M, Grabe H, Kang Y, Qi S, Detre JA. Disconnectome associated with progressive white matter hyperintensities in aging: a virtual lesion study. Front Aging Neurosci 2023; 15:1237198. [PMID: 37719871 PMCID: PMC10500060 DOI: 10.3389/fnagi.2023.1237198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 08/04/2023] [Indexed: 09/19/2023] Open
Abstract
Objective White matter hyperintensities (WMH) are commonly seen on T2-weighted magnetic resonance imaging (MRI) in older adults and are associated with an increased risk of cognitive decline and dementia. This study aims to estimate changes in the structural connectome due to age-related WMH by using a virtual lesion approach. Methods High-quality diffusion-weighted imaging data of 30 healthy subjects were obtained from the Human Connectome Project (HCP) database. Diffusion tractography using q-space diffeomorphic reconstruction (QSDR) and whole brain fiber tracking with 107 seed points was conducted using diffusion spectrum imaging studio and the brainnetome atlas was used to parcellate a total of 246 cortical and subcortical nodes. Previously published WMH frequency maps across age ranges (50's, 60's, 70's, and 80's) were used to generate virtual lesion masks for each decade at three lesion frequency thresholds, and these virtual lesion masks were applied as regions of avoidance (ROA) in fiber tracking to estimate connectivity changes. Connections showing significant differences in fiber density with and without ROA were identified using paired tests with False Discovery Rate (FDR) correction. Results Disconnections appeared first from the striatum to middle frontal gyrus (MFG) in the 50's, then from the thalamus to MFG in the 60's and extending to the superior frontal gyrus in the 70's, and ultimately including much more widespread cortical and hippocampal nodes in the 80's. Conclusion Changes in the structural disconnectome due to age-related WMH can be estimated using the virtual lesion approach. The observed disconnections may contribute to the cognitive and sensorimotor deficits seen in aging.
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Affiliation(s)
- Meng Li
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Mohamad Habes
- Biggs Alzheimer’s Institute, University of Texas San Antonio, San Antonio, TX, United States
| | - Hans Grabe
- Department of Psychiatry and Psychotherapy, University of Greifswald, Stralsund, Germany
| | - Yan Kang
- College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, China
| | - Shouliang Qi
- College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, China
- Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Northeastern University, Shenyang, China
| | - John A. Detre
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
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50
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Fongang B, Satizabal C, Kautz TF, Wadop YN, Muhammad JAS, Vasquez E, Mathews J, Gireud-Goss M, Saklad AR, Himali J, Beiser A, Cavazos JE, Mahaney MC, Maestre G, DeCarli C, Shipp EL, Vasan RS, Seshadri S. Cerebral small vessel disease burden is associated with decreased abundance of gut Barnesiella intestinihominis bacterium in the Framingham Heart Study. Sci Rep 2023; 13:13622. [PMID: 37604954 PMCID: PMC10442369 DOI: 10.1038/s41598-023-40872-5] [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: 02/13/2023] [Accepted: 08/17/2023] [Indexed: 08/23/2023] Open
Abstract
A bidirectional communication exists between the brain and the gut, in which the gut microbiota influences cognitive function and vice-versa. Gut dysbiosis has been linked to several diseases, including Alzheimer's disease and related dementias (ADRD). However, the relationship between gut dysbiosis and markers of cerebral small vessel disease (cSVD), a major contributor to ADRD, is unknown. In this cross-sectional study, we examined the connection between the gut microbiome, cognitive, and neuroimaging markers of cSVD in the Framingham Heart Study (FHS). Markers of cSVD included white matter hyperintensities (WMH), peak width of skeletonized mean diffusivity (PSMD), and executive function (EF), estimated as the difference between the trail-making tests B and A. We included 972 FHS participants with MRI scans, neurocognitive measures, and stool samples and quantified the gut microbiota composition using 16S rRNA sequencing. We used multivariable association and differential abundance analyses adjusting for age, sex, BMI, and education level to estimate the association between gut microbiota and WMH, PSMD, and EF measures. Our results suggest an increased abundance of Pseudobutyrivibrio and Ruminococcus genera was associated with lower WMH and PSMD (p values < 0.001), as well as better executive function (p values < 0.01). In addition, in both differential and multivariable analyses, we found that the gram-negative bacterium Barnesiella intestinihominis was strongly associated with markers indicating a higher cSVD burden. Finally, functional analyses using PICRUSt implicated various KEGG pathways, including microbial quorum sensing, AMP/GMP-activated protein kinase, phenylpyruvate, and β-hydroxybutyrate production previously associated with cognitive performance and dementia. Our study provides important insights into the association between the gut microbiome and cSVD, but further studies are needed to replicate the findings.
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Affiliation(s)
- Bernard Fongang
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
- Department of Biochemistry and Structural Biology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
- Department of Population Health Sciences, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
| | - Claudia Satizabal
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- Department of Population Health Sciences, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Tiffany F Kautz
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- Department of Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Yannick N Wadop
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Jazmyn A S Muhammad
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Erin Vasquez
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Julia Mathews
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Monica Gireud-Goss
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Amy R Saklad
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Jayandra Himali
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- Department of Population Health Sciences, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Alexa Beiser
- Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Jose E Cavazos
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- Department of Neurology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Michael C Mahaney
- Department of Human Genetics, South Texas Diabetes and Obesity Institute, The University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Gladys Maestre
- Department of Neurosciences and Department of Human Genetics, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Charles DeCarli
- Department of Neurology, Alzheimer's Disease Center, University of California, Davis, Sacramento, CA, USA
| | - Eric L Shipp
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Ramachandran S Vasan
- Framingham Heart Study, Framingham, MA, USA
- Department of Medicine, Section of Cardiovascular Medicine, Boston Medical Center, Boston University School of Medicine, Boston, MA, USA
- Department of Medicine, Section of Preventive Medicine and Epidemiology, Boston University School of Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
- Boston University's Center for Computing and Data Sciences, Boston, MA, USA
- The University of Texas School of Public Health in San Antonio, San Antonio, TX, USA
- The Long School of Medicine, University of Texas Health Science Center, San Antonio, TX, USA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Department of Neurology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
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