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Shao Z, Gao X, Cen S, Tang X, Gong J, Ding W. Unveiling the link between glymphatic function and cortical microstructures in post-traumatic stress disorder. J Affect Disord 2024; 365:341-350. [PMID: 39178958 DOI: 10.1016/j.jad.2024.08.094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 08/16/2024] [Accepted: 08/17/2024] [Indexed: 08/26/2024]
Abstract
PURPOSE The discovery of the glymphatic system, crucial for cerebrospinal and interstitial fluid exchange, has enhanced our grasp of brain protein balance and its potential role in neurodegenerative disease prevention and therapy. Detecting early neurodegenerative shifts via noninvasive biomarkers could be key in identifying at-risk individuals for Alzheimer's disease (AD). Our research explores a diffusion tensor imaging (DTI) method that measures cortical mean diffusivity (cMD), potentially a more sensitive indicator of neurodegeneration than traditional macrostructural methods. MATERIALS AND METHODS We analyzed 67 post-traumatic stress disorder (PTSD)-diagnosed veterans from the Alzheimer's Disease Neuroimaging Initiative database. Participants underwent structural MRI, DTI, Aβ PET imaging, and cognitive testing. We focused on the DTI-ALPS technique to assess glymphatic function and its relation to cMD, cortical Aβ accumulation, and thickness, accounting for age and APOE ε4 allele variations. RESULTS The cohort, all male with an average age of 68.1 (SD 3.4), showed a strong inverse correlation between DTI-ALPS and cMD in AD-affected regions, especially in the entorhinal, parahippocampal, and fusiform areas. Higher DTI-ALPS readings were consistently linked with greater cortical thickness, independent of Aβ deposits and genetic risk factors. Age and cMD emerged as inversely proportional predictors of DTI-ALPS, indicating a complex interaction with age. CONCLUSION The study confirms a meaningful association between glymphatic efficiency and cMD in AD-sensitive zones, accentuating cortical microstructural alterations in PTSD. It positions DTI-ALPS as a viable biomarker for assessing glymphatic function in PTSD, implicating changes in DTI-ALPS as indicative of glymphatic impairment.
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Affiliation(s)
- Zhiding Shao
- Department of Neurology, The Second Affiliated Hospital of Wannan Medical College, Wuhu, China
| | - Xue Gao
- Department of Neurology, The Second Affiliated Hospital of Wannan Medical College, Wuhu, China
| | - Si Cen
- Department of Neurology, The Second Affiliated Hospital of Wannan Medical College, Wuhu, China
| | - Xiaolei Tang
- Translational Medicine Center, The Second Affiliated Hospital of Wannan Medical College, Wuhu, China
| | - Juanyu Gong
- Department of Neurology, The Second Affiliated Hospital of Wannan Medical College, Wuhu, China.
| | - Wencai Ding
- Department of Neurology, The Second Affiliated Hospital of Wannan Medical College, Wuhu, China.
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Naveed K, Rashidi-Ranjbar N, Kumar S, Zomorrodi R, Blumberger DM, Fischer CE, Sanches M, Mulsant BH, Pollock BG, Voineskos AN, Rajji TK. Effect of dorsolateral prefrontal cortex structural measures on neuroplasticity and response to paired-associative stimulation in Alzheimer's dementia. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230233. [PMID: 38853564 PMCID: PMC11343312 DOI: 10.1098/rstb.2023.0233] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 12/04/2023] [Accepted: 01/15/2024] [Indexed: 06/11/2024] Open
Abstract
Long-term potentiation (LTP)-like activity can be induced by stimulation protocols such as paired associative stimulation (PAS). We aimed to determine whether PAS-induced LTP-like activity (PAS-LTP) of the dorsolateral prefrontal cortex (DLPFC) is associated with cortical thickness and other structural measures impaired in Alzheimer's dementia (AD). We also explored longitudinal relationships between these brain structures and PAS-LTP response after a repetitive PAS (rPAS) intervention. Mediation and regression analyses were conducted using data from randomized controlled trials with AD and healthy control participants. PAS-electroencephalography assessed DLPFC PAS-LTP. DLPFC thickness and surface area were acquired from T1-weighted magnetic resonance imaging. Fractional anisotropy and mean diffusivity (MD) of the superior longitudinal fasciculus (SLF)-a tract important to induce PAS-LTP-were measured with diffusion-weighted imaging. AD participants exhibited reduced DLPFC thickness and increased SLF MD. There was also some evidence that reduction in DLPFC thickness mediates DLPFC PAS-LTP impairment. Longitudinal analyses showed preliminary evidence that SLF MD, and to a lesser extent DLPFC thickness, is associated with DLPFC PAS-LTP response to active rPAS. This study expands our understanding of the relationships between brain structural changes and neuroplasticity. It provides promising evidence for a structural predictor to improving neuroplasticity in AD with neurostimulation. This article is part of a discussion meeting issue 'Long-term potentiation: 50 years on'.
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Affiliation(s)
- K. Naveed
- Temerty Faculty of Medicine, University of Toronto, 1 King’s College Cir, Toronto, OntarioM5S 1A8, Canada
- Toronto Dementia Research Alliance, University of Toronto, 250 College Street, Toronto, OntarioM5T 1R8, Canada
| | - N. Rashidi-Ranjbar
- Temerty Faculty of Medicine, University of Toronto, 1 King’s College Cir, Toronto, OntarioM5S 1A8, Canada
- Toronto Dementia Research Alliance, University of Toronto, 250 College Street, Toronto, OntarioM5T 1R8, Canada
- Keenan Research Centre for Biomedical Science, Li Ka Shing Knowledge Institute, 209 Victoria Street, Toronto, OntarioM5B 1T8, Canada
| | - S. Kumar
- Temerty Faculty of Medicine, University of Toronto, 1 King’s College Cir, Toronto, OntarioM5S 1A8, Canada
- Toronto Dementia Research Alliance, University of Toronto, 250 College Street, Toronto, OntarioM5T 1R8, Canada
- Campbell Family Mental Health Research Institute, CAMH, 479 Spadina Avenue, Toronto, OntarioM5S 2S1, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, 250 College Street, Toronto, OntarioM5T 1R8, Canada
| | - R. Zomorrodi
- Temerty Faculty of Medicine, University of Toronto, 1 King’s College Cir, Toronto, OntarioM5S 1A8, Canada
- Campbell Family Mental Health Research Institute, CAMH, 479 Spadina Avenue, Toronto, OntarioM5S 2S1, Canada
| | - D. M. Blumberger
- Temerty Faculty of Medicine, University of Toronto, 1 King’s College Cir, Toronto, OntarioM5S 1A8, Canada
- Campbell Family Mental Health Research Institute, CAMH, 479 Spadina Avenue, Toronto, OntarioM5S 2S1, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, 250 College Street, Toronto, OntarioM5T 1R8, Canada
| | - C. E. Fischer
- Temerty Faculty of Medicine, University of Toronto, 1 King’s College Cir, Toronto, OntarioM5S 1A8, Canada
- Toronto Dementia Research Alliance, University of Toronto, 250 College Street, Toronto, OntarioM5T 1R8, Canada
- Keenan Research Centre for Biomedical Science, Li Ka Shing Knowledge Institute, 209 Victoria Street, Toronto, OntarioM5B 1T8, Canada
| | - M. Sanches
- Biostatistics Core, Centre for Addiction and Mental Health, 60 White Squirrel Way, Toronto, OntarioM6J 1H4, Canada
| | - B. H. Mulsant
- Temerty Faculty of Medicine, University of Toronto, 1 King’s College Cir, Toronto, OntarioM5S 1A8, Canada
- Toronto Dementia Research Alliance, University of Toronto, 250 College Street, Toronto, OntarioM5T 1R8, Canada
- Campbell Family Mental Health Research Institute, CAMH, 479 Spadina Avenue, Toronto, OntarioM5S 2S1, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, 250 College Street, Toronto, OntarioM5T 1R8, Canada
| | - B. G. Pollock
- Temerty Faculty of Medicine, University of Toronto, 1 King’s College Cir, Toronto, OntarioM5S 1A8, Canada
- Campbell Family Mental Health Research Institute, CAMH, 479 Spadina Avenue, Toronto, OntarioM5S 2S1, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, 250 College Street, Toronto, OntarioM5T 1R8, Canada
| | - A. N. Voineskos
- Temerty Faculty of Medicine, University of Toronto, 1 King’s College Cir, Toronto, OntarioM5S 1A8, Canada
- Campbell Family Mental Health Research Institute, CAMH, 479 Spadina Avenue, Toronto, OntarioM5S 2S1, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, 250 College Street, Toronto, OntarioM5T 1R8, Canada
| | - T. K. Rajji
- Temerty Faculty of Medicine, University of Toronto, 1 King’s College Cir, Toronto, OntarioM5S 1A8, Canada
- Toronto Dementia Research Alliance, University of Toronto, 250 College Street, Toronto, OntarioM5T 1R8, Canada
- Campbell Family Mental Health Research Institute, CAMH, 479 Spadina Avenue, Toronto, OntarioM5S 2S1, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, 250 College Street, Toronto, OntarioM5T 1R8, Canada
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da S Senra Filho AC, Murta Junior LO, Monteiro Paschoal A. Assessing biological self-organization patterns using statistical complexity characteristics: a tool for diffusion tensor imaging analysis. MAGMA (NEW YORK, N.Y.) 2024:10.1007/s10334-024-01185-4. [PMID: 39068635 DOI: 10.1007/s10334-024-01185-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Revised: 06/24/2024] [Accepted: 06/28/2024] [Indexed: 07/30/2024]
Abstract
OBJECT Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) are well-known and powerful imaging techniques for MRI. Although DTI evaluation has evolved continually in recent years, there are still struggles regarding quantitative measurements that can benefit brain areas that are consistently difficult to measure via diffusion-based methods, e.g., gray matter (GM). The present study proposes a new image processing technique based on diffusion distribution evaluation of López-Ruiz, Mancini and Calbet (LMC) complexity called diffusion complexity (DC). MATERIALS AND METHODS The OASIS-3 and TractoInferno open-science databases for healthy individuals were used, and all the codes are provided as open-source materials. RESULTS The DC map showed relevant signal characterization in brain tissues and structures, achieving contrast-to-noise ratio (CNR) gains of approximately 39% and 93%, respectively, compared to those of the FA and ADC maps. DISCUSSION In the special case of GM tissue, the DC map obtains its maximum signal level, showing the possibility of studying cortical and subcortical structures challenging for classical DTI quantitative formalism. The ability to apply the DC technique, which requires the same imaging acquisition for DTI and its potential to provide complementary information to study the brain's GM structures, can be a rich source of information for further neuroscience research and clinical practice.
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Ji F, Wei JLK, Leng S, Zhong L, Tan RS, Gao F, Ng KK, Leong RLF, Pasternak O, Chee MWL, Koh WP, Zhou JH, Koh AS. Heart-brain mapping: Cardiac atrial function is associated with distinct cerebral regions with high free water in older adults. J Cereb Blood Flow Metab 2024; 44:1218-1230. [PMID: 38295860 PMCID: PMC11179607 DOI: 10.1177/0271678x241229581] [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: 08/30/2023] [Revised: 12/01/2023] [Accepted: 12/21/2023] [Indexed: 06/13/2024]
Abstract
Left atrial (LA) dysfunction has been linked to cognitive impairment and cerebrovascular dysfunction. Higher brain free-water (FW) derived from diffusion-MRI was associated with early and subtle cerebrovascular dysfunction and more severe cognitive impairment. We hypothesized that LA dysfunction would correlate with higher brain free-water (FW) among healthy older adults. 56 community older adults (73.13 ± 3.56 years; 24 female) with normal cognition and without known cardiovascular disease who had undergone cardiac-MRI, brain-MRI, and neuropsychological assessments were included. Whole-brain voxel-level general linear models were constructed to correlate brain FW measures with LA indices. We found lower scores in LA function measures were related to higher grey matter (GM) FW in regions including orbital frontal and right temporal regions (p < 0.01, family-wise error corrected). In parallel, LA dysfunction was associated with higher FW in white matter (WM) fibres including superior longitudinal fasciculus, internal capsule, and superior corona radiata. However, LA dysfunction was not related to WM tissue reduction and GM cortical thinning. Moreover, these cardiac-related higher brain FW were associated with lower executive function and higher serum B-type natriuretic peptide (p < 0.05, Holm-Bonferroni corrected). These findings may have implications for anti-ageing preventive strategies targeting cardiac and cerebral vascular functions to improve heart and brain outcomes.
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Affiliation(s)
- Fang Ji
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Joseph Lim Kai Wei
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Shuang Leng
- National Heart Centre Singapore, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Liang Zhong
- National Heart Centre Singapore, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Ru San Tan
- National Heart Centre Singapore, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Fei Gao
- National Heart Centre Singapore, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
| | - Kwun Kei Ng
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Ruth LF Leong
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Ofer Pasternak
- Departments of Psychiatry and Radiology, Brigham and Women’s Hospital, Harvard Medical School, USA
| | - Michael WL Chee
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Woon-Puay Koh
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Juan Helen Zhou
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
| | - Angela S Koh
- National Heart Centre Singapore, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
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Deantoni M, Reyt M, Dourte M, de Haan S, Lesoinne A, Vandewalle G, Phillips C, Berthomier C, Maquet P, Muto V, Hammad G, Schmidt C, Baillet M. Circadian rapid eye movement sleep expression is associated with brain microstructural integrity in older adults. Commun Biol 2024; 7:758. [PMID: 38909162 PMCID: PMC11193799 DOI: 10.1038/s42003-024-06415-y] [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: 12/06/2023] [Accepted: 06/05/2024] [Indexed: 06/24/2024] Open
Abstract
Rapid eye movement sleep (REMS) is increasingly suggested as a discriminant sleep state for subtle signs of age-related neurodegeneration. While REMS expression is under strong circadian control and circadian dysregulation increases with age, the association between brain aging and circadian REMS regulation has not yet been assessed. Here, we measure the circadian amplitude of REMS through a 40-h in-lab multiple nap protocol in controlled laboratory conditions, and brain microstructural integrity with quantitative multi-parameter mapping (MPM) imaging in 86 older individuals. We show that reduced circadian REMS amplitude is related to lower magnetization transfer saturation (MTsat), longitudinal relaxation rate (R1) and effective transverse relaxation rate (R2*) values in several white matter regions mostly located around the lateral ventricles, and with lower R1 values in grey matter clusters encompassing the hippocampus, parahippocampus, thalamus and hypothalamus. Our results further highlight the importance of considering circadian regulation for understanding the association between sleep and brain structure in older individuals.
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Affiliation(s)
| | - Mathilde Reyt
- GIGA-CRC Human Imaging, University of Liège, Liège, Belgium
- Psychology and Neuroscience of Cognition Research Unit (PsyNCog), Faculty of Psychology and Educational Sciences, University of Liège, Liège, Belgium
| | - Marine Dourte
- GIGA-CRC Human Imaging, University of Liège, Liège, Belgium
- Psychology and Neuroscience of Cognition Research Unit (PsyNCog), Faculty of Psychology and Educational Sciences, University of Liège, Liège, Belgium
| | - Stella de Haan
- GIGA-CRC Human Imaging, University of Liège, Liège, Belgium
| | | | | | - Christophe Phillips
- GIGA-CRC Human Imaging, University of Liège, Liège, Belgium
- GIGA-In Silico Medicine, University of Liège, Liège, Belgium
| | | | - Pierre Maquet
- GIGA-CRC Human Imaging, University of Liège, Liège, Belgium
- Department of Neurology, University Hospital of Liège, University of Liège, Liège, Belgium
| | - Vincenzo Muto
- GIGA-CRC Human Imaging, University of Liège, Liège, Belgium
| | - Grégory Hammad
- GIGA-CRC Human Imaging, University of Liège, Liège, Belgium
- Human Chronobiology and Sleep, University of Surrey, Guildford, England
| | - Christina Schmidt
- GIGA-CRC Human Imaging, University of Liège, Liège, Belgium.
- Psychology and Neuroscience of Cognition Research Unit (PsyNCog), Faculty of Psychology and Educational Sciences, University of Liège, Liège, Belgium.
| | - Marion Baillet
- GIGA-CRC Human Imaging, University of Liège, Liège, Belgium.
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Tang R, Franz CE, Hauger RL, Dale AM, Dorros SM, Eyler LT, Fennema-Notestine C, Hagler DJ, Lyons MJ, Panizzon MS, Puckett OK, Williams ME, Elman JA, Kremen WS. Early Cortical Microstructural Changes in Aging Are Linked to Vulnerability to Alzheimer's Disease Pathology. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024:S2451-9022(24)00158-7. [PMID: 38878863 DOI: 10.1016/j.bpsc.2024.05.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 05/09/2024] [Accepted: 05/29/2024] [Indexed: 08/15/2024]
Abstract
BACKGROUND Early identification of Alzheimer's disease (AD) risk is critical for improving treatment success. Cortical thickness is a macrostructural measure used to assess neurodegeneration in AD. However, cortical microstructural changes appear to precede macrostructural atrophy and may improve early risk identification. Currently, whether cortical microstructural changes in aging are linked to vulnerability to AD pathophysiology remains unclear in nonclinical populations, who are precisely the target for early risk identification. METHODS In 194 adults, we calculated magnetic resonance imaging-derived maps of changes in cortical mean diffusivity (microstructure) and cortical thickness (macrostructure) over 5 to 6 years (mean age: time 1 = 61.82 years; time 2 = 67.48 years). Episodic memory was assessed using 3 well-established tests. We obtained positron emission tomography-derived maps of AD pathology deposition (amyloid-β, tau) and neurotransmitter receptors (cholinergic, glutamatergic) implicated in AD pathophysiology. Spatial correlational analyses were used to compare pattern similarity among maps. RESULTS Spatial patterns of cortical macrostructural changes resembled patterns of cortical organization sensitive to age-related processes (r = -0.31, p < .05), whereas microstructural changes resembled the patterns of tau deposition in AD (r = 0.39, p = .038). Individuals with patterns of microstructural changes that more closely resembled stereotypical tau deposition exhibited greater memory decline (β = 0.22, p = .029). Microstructural changes and AD pathology deposition were enriched in areas with greater densities of cholinergic and glutamatergic receptors (ps < .05). CONCLUSIONS Patterns of cortical microstructural changes were more AD-like than patterns of macrostructural changes, which appeared to reflect more general aging processes. Microstructural changes may better inform early risk prediction efforts as a sensitive measure of vulnerability to pathological processes prior to overt atrophy and cognitive decline.
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Affiliation(s)
- Rongxiang Tang
- Department of Psychiatry, University of California San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California.
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California
| | - Richard L Hauger
- Department of Psychiatry, University of California San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California; Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, San Diego, California
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, California; Department of Neurosciences, University of California San Diego, La Jolla, California
| | - Stephen M Dorros
- Department of Radiology, University of California San Diego, La Jolla, California
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, La Jolla, California; Desert Pacific Mental Illness Research Education and Clinical Center, Veterans Affairs San Diego Healthcare System, San Diego, California
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, La Jolla, California; Department of Radiology, University of California San Diego, La Jolla, California
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, La Jolla, California
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California
| | - Olivia K Puckett
- Department of Psychiatry, University of California San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California
| | - McKenna E Williams
- Department of Psychiatry, University of California San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California; Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California San Diego, San Diego, California
| | - Jeremy A Elman
- Department of Psychiatry, University of California San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, California; Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California
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7
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Cho KIK, Zhang F, Penzel N, Seitz-Holland J, Tang Y, Zhang T, Xu L, Li H, Keshavan M, Whitfield-Gabrieli S, Niznikiewicz M, Stone WS, Wang J, Shenton ME, Pasternak O. Excessive interstitial free-water in cortical gray matter preceding accelerated volume changes in individuals at clinical high risk for psychosis. Mol Psychiatry 2024:10.1038/s41380-024-02597-3. [PMID: 38830974 DOI: 10.1038/s41380-024-02597-3] [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: 07/17/2023] [Revised: 05/01/2024] [Accepted: 05/03/2024] [Indexed: 06/05/2024]
Abstract
Recent studies show that accelerated cortical gray matter (GM) volume reduction seen in anatomical MRI can help distinguish between individuals at clinical high risk (CHR) for psychosis who will develop psychosis and those who will not. This reduction is suggested to represent atypical developmental or degenerative changes accompanying an accumulation of microstructural changes, such as decreased spine density and dendritic arborization. Detecting the microstructural sources of these changes before they accumulate into volume loss is crucial. Our study aimed to detect these microstructural GM alterations using diffusion MRI (dMRI). We tested for baseline and longitudinal group differences in anatomical and dMRI data from 160 individuals at CHR and 96 healthy controls (HC) acquired in a single imaging site. Of the CHR individuals, 33 developed psychosis (CHR-P), while 127 did not (CHR-NP). Among all participants, longitudinal data was available for 45 HCs, 17 CHR-P, and 66 CHR-NP. Eight cortical lobes were examined for GM volume and GM microstructure. A novel dMRI measure, interstitial free water (iFW), was used to quantify GM microstructure by eliminating cerebrospinal fluid contribution. Additionally, we assessed whether these measures differentiated the CHR-P from the CHR-NP. In addition, for completeness, we also investigated changes in cortical thickness and in white matter (WM) microstructure. At baseline the CHR group had significantly higher iFW than HC in the prefrontal, temporal, parietal, and occipital lobes, while volume was reduced only in the temporal lobe. Neither iFW nor volume differentiated between the CHR-P and CHR-NP groups at baseline. However, in many brain areas, the CHR-P group demonstrated significantly accelerated changes (iFW increase and volume reduction) with time than the CHR-NP group. Cortical thickness provided similar results as volume, and there were no significant changes in WM microstructure. Our results demonstrate that microstructural GM changes in individuals at CHR have a wider extent than volumetric changes or microstructural WM changes, and they predate the acceleration of brain changes that occur around psychosis onset. Microstructural GM changes, as reflected by the increased iFW, are thus an early pathology at the prodromal stage of psychosis that may be useful for a better mechanistic understanding of psychosis development.
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Affiliation(s)
- Kang Ik K Cho
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Fan Zhang
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Nora Penzel
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Johanna Seitz-Holland
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Yingying Tang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, China
| | - Tianhong Zhang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lihua Xu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, China
| | - Huijun Li
- Department of Psychology, Florida A&M University, Tallahassee, FL, USA
| | - Matcheri Keshavan
- The Massachusetts Mental Health Center, Public Psychiatry Division, Beth Israel Deaconess Medical Center, and Harvard Medical School, Boston, MA, USA
| | - Susan Whitfield-Gabrieli
- Department of Psychology, Northeastern University, Boston, MA, USA
- The McGovern Institute for Brain Research and the Poitras Center for Affective Disorders Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Margaret Niznikiewicz
- The Department of Psychiatry, Veterans Affairs Boston Healthcare System, Brockton Division, Brockton, MA, USA
| | - William S Stone
- The Massachusetts Mental Health Center, Public Psychiatry Division, Beth Israel Deaconess Medical Center, and Harvard Medical School, Boston, MA, USA
| | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Brain Science and Technology Research Center, Shanghai Jiao Tong University, Shanghai, China.
| | - Martha E Shenton
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Ofer Pasternak
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
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8
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Krijnen EA, Broeders TAA, Noteboom S, van Dam M, Bajrami A, Bouman PM, Barkhof F, Uitdehaag BMJ, Klawiter EC, Koubiyr I, Schoonheim MM. The cognitive relevance of non-lesional damage to cortical networks in people with multiple sclerosis. J Neurol 2024; 271:3203-3214. [PMID: 38441612 PMCID: PMC11136718 DOI: 10.1007/s00415-024-12240-4] [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: 12/08/2023] [Revised: 02/01/2024] [Accepted: 02/05/2024] [Indexed: 05/30/2024]
Abstract
BACKGROUND Cognitive impairment, a common and debilitating symptom in people with multiple sclerosis (MS), is especially related to cortical damage. However, the impact of regional cortical damage remains poorly understood. Our aim was to evaluate structural (network) integrity in lesional and non-lesional cortex in people with MS, and its relationship with cognitive dysfunction. METHODS In this cross-sectional study, 176 people with MS and 48 healthy controls underwent MRI, including double inversion recovery and diffusion-weighted scans, and neuropsychological assessment. Cortical integrity was assessed based on fractional anisotropy (FA) and mean diffusivity (MD) within 212 regions split into lesional or non-lesional cortex, and grouped into seven cortical networks. Integrity was compared between people with MS and controls, and across cognitive groups: cognitively-impaired (CI; ≥ two domains at Z ≤ - 2 below controls), mildly CI (≥ two at - 2 < Z ≤ - 1.5), or cognitively-preserved (CP). RESULTS Cortical lesions were observed in 87.5% of people with MS, mainly in ventral attention network, followed by limbic and default mode networks. Compared to controls, in non-lesional cortex, MD was increased in people with MS, but mean FA did not differ. Within the same individual, MD and FA were increased in lesional compared to non-lesional cortex. CI-MS exhibited higher MD than CP-MS in non-lesional cortex of default mode, frontoparietal and sensorimotor networks, of which the default mode network could best explain cognitive performance. CONCLUSION Diffusion differences in lesional cortex were more severe than in non-lesional cortex. However, while most people with MS had cortical lesions, diffusion differences in CI-MS were more prominent in non-lesional cortex than lesional cortex, especially within default mode, frontoparietal and sensorimotor networks.
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Affiliation(s)
- Eva A Krijnen
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, 1007 MB, Amsterdam, The Netherlands.
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA.
- , De Boelelaan 1108, 1081 HZ, Amsterdam, The Netherlands.
| | - Tommy A A Broeders
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, 1007 MB, Amsterdam, The Netherlands
| | - Samantha Noteboom
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, 1007 MB, Amsterdam, The Netherlands
| | - Maureen van Dam
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, 1007 MB, Amsterdam, The Netherlands
| | - Albulena Bajrami
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, 1007 MB, Amsterdam, The Netherlands
- Division of Neurology, Emergency Department, "S. Chiara" Hospital, Azienda Provinciale per i Servizi Sanitari (APSS), 38122, Trento, Italy
| | - Piet M Bouman
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, 1007 MB, Amsterdam, The Netherlands
| | - Frederik Barkhof
- MS Center Amsterdam, Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, 1081 BT, Amsterdam, The Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, WC1E 6BT, UK
| | - Bernard M J Uitdehaag
- MS Center Amsterdam, Neurology, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, 1081 HV, Amsterdam, The Netherlands
| | - Eric C Klawiter
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02114, USA
| | - Ismail Koubiyr
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, 1007 MB, Amsterdam, The Netherlands
| | - Menno M Schoonheim
- MS Center Amsterdam, Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, 1007 MB, Amsterdam, The Netherlands
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9
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Hanycz SA, Noorani A, Hung PSP, Walker MR, Zhang AB, Latypov TH, Hodaie M. Hippocampus diffusivity abnormalities in classical trigeminal neuralgia. Pain Rep 2024; 9:e1159. [PMID: 38655236 PMCID: PMC11037743 DOI: 10.1097/pr9.0000000000001159] [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: 03/08/2023] [Revised: 02/16/2024] [Accepted: 02/24/2024] [Indexed: 04/26/2024] Open
Abstract
Introduction Patients with chronic pain frequently report cognitive symptoms that affect memory and attention, which are functions attributed to the hippocampus. Trigeminal neuralgia (TN) is a chronic neuropathic pain disorder characterized by paroxysmal attacks of unilateral orofacial pain. Given the stereotypical nature of TN pain and lack of negative symptoms including sensory loss, TN provides a unique model to investigate the hippocampal implications of chronic pain. Recent evidence demonstrated that TN is associated with macrostructural hippocampal abnormalities indicated by reduced subfield volumes; however, there is a paucity in our understanding of hippocampal microstructural abnormalities associated with TN. Objectives To explore diffusivity metrics within the hippocampus, along with its functional and structural subfields, in patients with TN. Methods To examine hippocampal microstructure, we utilized diffusion tensor imaging in 31 patients with TN and 21 controls. T1-weighted magnetic resonance images were segmented into hippocampal subfields and registered into diffusion-weighted imaging space. Fractional anisotropy (FA) and mean diffusivity were extracted for hippocampal subfields and longitudinal axis segmentations. Results Patients with TN demonstrated reduced FA in bilateral whole hippocampi and hippocampal body and contralateral subregions CA2/3 and CA4, indicating microstructural hippocampal abnormalities. Notably, patients with TN showed significant correlation between age and hippocampal FA, while controls did not exhibit this correlation. These effects were driven chiefly by female patients with TN. Conclusion This study demonstrates that TN is associated with microstructural hippocampal abnormalities, which may precede and potentially be temporally linked to volumetric hippocampal alterations demonstrated previously. These findings provide further evidence for the role of the hippocampus in chronic pain and suggest the potential for targeted interventions to mitigate cognitive symptoms in patients with chronic pain.
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Affiliation(s)
- Shaun Andrew Hanycz
- Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada
- Division of Brain, Imaging, and Behaviour—Systems Neuroscience, Krembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
- Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Alborz Noorani
- Division of Brain, Imaging, and Behaviour—Systems Neuroscience, Krembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
- Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Peter Shih-Ping Hung
- Division of Brain, Imaging, and Behaviour—Systems Neuroscience, Krembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
- Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Matthew R. Walker
- Division of Brain, Imaging, and Behaviour—Systems Neuroscience, Krembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Ashley B. Zhang
- MD Program, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA, USA
| | - Timur H. Latypov
- Division of Brain, Imaging, and Behaviour—Systems Neuroscience, Krembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
- Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Mojgan Hodaie
- Division of Brain, Imaging, and Behaviour—Systems Neuroscience, Krembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
- Institute of Medical Science, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Division of Neurosurgery, Krembil Brain Institute, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
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10
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Hong S, Choi Y, Lee MB, Rhee HY, Park S, Ryu CW, Cho AR, Kwon OI, Jahng GH. Increased extra-neurite conductivity of brain in patients with Alzheimer's disease: A pilot study. Psychiatry Res Neuroimaging 2024; 340:111807. [PMID: 38520873 DOI: 10.1016/j.pscychresns.2024.111807] [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: 09/14/2023] [Revised: 01/31/2024] [Accepted: 03/03/2024] [Indexed: 03/25/2024]
Abstract
The objectives of this study were to investigate how the extra-neurite conductivity (EC) and intra-neurite conductivity (IC) were reflected in Alzheimer's disease (AD) patients compared with old cognitively normal (CN) people and patients with amnestic mild cognitive impairment (MCI) and to evaluate the association between those conductivity values and cognitive decline. To do this, high-frequency conductivity (HFC) at the Larmor frequency was obtained using MRI-based electrical property tomography (MREPT) and was decomposed into EC and IC using information of multi-shell multi-gradient direction diffusion tensor images. This prospective single-center study included 20 patients with mild or moderate AD, 25 patients with amnestic MCI, and 21 old CN participants. After decomposing EC and IC from HFC for all participants, we performed voxel-based and regions-of-interest analyses to compare conductivity between the three participant groups and to evaluate the association with either age or the Mini-Mental State Examination (MMSE) scores. We found increased EC in AD compared to CN and MCI. EC was significantly negatively associated with MMSE scores in the insula, and middle temporal gyrus. EC might be used as an imaging biomarker for helping to monitor cognitive function.
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Affiliation(s)
- Seowon Hong
- Department of Radiology, Kyung Hee University Hospital at Gangdong, 892 Dongnam-ro, Gangdong-Gu, Seoul 05278, Republic of Korea
| | - Yunjeong Choi
- Department of Biomedical Engineering, Undergraduate School, College of Electronics and Information, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Yongin-si, Gyeonggi-do 17104, Republic of Korea
| | - Mun Bae Lee
- Department of Mathematics, College of Basic Science, Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul 05029, Republic of Korea
| | - Hak Young Rhee
- Department of Neurology, Kyung Hee University Hospital at Gangdong, 892 Dongnam-ro, Gangdong-Gu, Seoul 05278, Republic of Korea; Department of Medicine, Kyung Hee University College of Medicine, 26 Kyung Hee Dae-ro, Dongdaemun-gu, Seoul 02447, Republic of Korea
| | - Soonchan Park
- Department of Radiology, Kyung Hee University Hospital at Gangdong, 892 Dongnam-ro, Gangdong-Gu, Seoul 05278, Republic of Korea; Department of Medicine, Kyung Hee University College of Medicine, 26 Kyung Hee Dae-ro, Dongdaemun-gu, Seoul 02447, Republic of Korea
| | - Chang-Woo Ryu
- Department of Radiology, Kyung Hee University Hospital at Gangdong, 892 Dongnam-ro, Gangdong-Gu, Seoul 05278, Republic of Korea; Department of Medicine, Kyung Hee University College of Medicine, 26 Kyung Hee Dae-ro, Dongdaemun-gu, Seoul 02447, Republic of Korea
| | - Ah Rang Cho
- Department of Medicine, Kyung Hee University College of Medicine, 26 Kyung Hee Dae-ro, Dongdaemun-gu, Seoul 02447, Republic of Korea; Department of Psychiatry, Kyung Hee University Hospital at Gangdong, 892 Dongnam-ro, Gangdong-Gu, Seoul 05278, Republic of Korea
| | - Oh In Kwon
- Department of Mathematics, College of Basic Science, Konkuk University, 120 Neungdong-ro, Gwangjin-gu, Seoul 05029, Republic of Korea.
| | - Geon-Ho Jahng
- Department of Radiology, Kyung Hee University Hospital at Gangdong, 892 Dongnam-ro, Gangdong-Gu, Seoul 05278, Republic of Korea; Department of Medicine, Kyung Hee University College of Medicine, 26 Kyung Hee Dae-ro, Dongdaemun-gu, Seoul 02447, Republic of Korea.
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11
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Pardo J, Montal V, Campabadal A, Oltra J, Uribe C, Roura I, Bargalló N, Martí MJ, Compta Y, Iranzo A, Fortea J, Junqué C, Segura B. Cortical Macro- and Microstructural Changes in Parkinson's Disease with Probable Rapid Eye Movement Sleep Behavior Disorder. Mov Disord 2024; 39:814-824. [PMID: 38456361 DOI: 10.1002/mds.29761] [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: 09/18/2023] [Revised: 01/17/2024] [Accepted: 02/16/2024] [Indexed: 03/09/2024] Open
Abstract
BACKGROUND Evidence regarding cortical atrophy patterns in Parkinson's disease (PD) with probable rapid eye movement sleep behavior disorder (RBD) (PD-pRBD) remains scarce. Cortical mean diffusivity (cMD), as a novel imaging biomarker highly sensitive to detecting cortical microstructural changes in different neurodegenerative diseases, has not been investigated in PD-pRBD yet. OBJECTIVES The aim was to investigate cMD as a sensitive measure to identify subtle cortical microstructural changes in PD-pRBD and its relationship with cortical thickness (CTh). METHODS Twenty-two PD-pRBD, 31 PD without probable RBD (PD-nonpRBD), and 28 healthy controls (HC) were assessed using 3D T1-weighted and diffusion-weighted magnetic resonance imaging on a 3-T scanner and neuropsychological testing. Measures of cortical brain changes were obtained through cMD and CTh. Two-class group comparisons of a general linear model were performed (P < 0.05). Cohen's d effect size for both approaches was computed. RESULTS PD-pRBD patients showed higher cMD than PD-nonpRBD patients in the left superior temporal, superior frontal, and precentral gyri, precuneus cortex, as well as in the right middle frontal and postcentral gyri and paracentral lobule (d > 0.8), whereas CTh did not detect significant differences. PD-pRBD patients also showed increased bilateral posterior cMD in comparison with HCs (d > 0.8). These results partially overlapped with CTh results (0.5 < d < 0.8). PD-nonpRBD patients showed no differences in cMD when compared with HCs but showed cortical thinning in the left fusiform gyrus and lateral occipital cortex bilaterally (d > 0.5). CONCLUSIONS cMD may be more sensitive than CTh displaying significant cortico-structural differences between PD subgroups, indicating this imaging biomarker's utility in studying early cortical changes in PD. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Grants
- PID2020-114640GB-I00/AEI/10.13039/501100011033 Ministerio de Economía y Competitividad
- H2020-SC1-BHC-2018-2020/GA 965422 European Union's Horizon 2020, "MES-CoBraD"
- FI18/00275 Instituto de Salud Carlos III
- IIBSP-DOW-2020-151 Departament de Salut, Generalitat de Catalunya, Fundación Tatiana Pérez de Guzmán el Bueno
- PRE2018-086675 Ministerio de Ciencia, Innovación y Universidades
- PI20/01473 Fondo de Investigaciones Sanitario, Carlos III Health Institute
- SGR 2021SGR00801 Generalitat de Catalunya
- 1R01AG056850-01A1 CIBERNED Program 1, National Institutes of Health (NIH) grants
- 3RF1AG056850-01S1 CIBERNED Program 1, National Institutes of Health (NIH) grants
- AG056850 CIBERNED Program 1, National Institutes of Health (NIH) grants
- R01AG061566 CIBERNED Program 1, National Institutes of Health (NIH) grants
- R21AG056974 CIBERNED Program 1, National Institutes of Health (NIH) grants
- 888692 H2020 Marie Skłodowska-Curie Actions
- LCF/BQ/DR22/11950012 'la Caixa' Foundation
- PRE2021-099689 Ministerio de Ciencia e Innovación
- CEX2021-001159-M María de Maeztu Unit of Excellence (Institute of Neurosciences, University of Barcelona), Ministry of Science and Innovation
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Affiliation(s)
- Jèssica Pardo
- Medical Psychology Unit, Department of Medicine, Institute of Neurosciences, University of Barcelona, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Victor Montal
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Department of Life Sciences, Barcelona Supercomputing Center, Barcelona, Spain
| | - Anna Campabadal
- Medical Psychology Unit, Department of Medicine, Institute of Neurosciences, University of Barcelona, Barcelona, Spain
- Neurology Service, Consorci Corporació Sanitària Parc Taulí de Sabadell, Barcelona, Spain
| | - Javier Oltra
- Medical Psychology Unit, Department of Medicine, Institute of Neurosciences, University of Barcelona, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Carme Uribe
- Medical Psychology Unit, Department of Medicine, Institute of Neurosciences, University of Barcelona, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Brain Health Imaging Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada
| | - Ignacio Roura
- Medical Psychology Unit, Department of Medicine, Institute of Neurosciences, University of Barcelona, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Núria Bargalló
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Imaging Diagnostic Center (CDI), Hospital Clínic Universitari de Barcelona, Barcelona, Spain
| | - Maria J Martí
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Barcelona, Spain
- Parkinson's Disease and Movement Disorders Unit, Hospital Clínic Universitari de Barcelona, UBNeuro Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | - Yaroslau Compta
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Barcelona, Spain
- Parkinson's Disease and Movement Disorders Unit, Hospital Clínic Universitari de Barcelona, UBNeuro Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | - Alex Iranzo
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Barcelona, Spain
- Sleep Disorders Center, Neurology Service, Hospital Clínic Universitari de Barcelona, University of Barcelona, Barcelona, Spain
| | - Juan Fortea
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Barcelona, Spain
- Barcelona Down Medical Center, Fundació Catalana de Síndrome de Down, Barcelona, Spain
| | - Carme Junqué
- Medical Psychology Unit, Department of Medicine, Institute of Neurosciences, University of Barcelona, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Barcelona, Spain
| | - Bàrbara Segura
- Medical Psychology Unit, Department of Medicine, Institute of Neurosciences, University of Barcelona, Barcelona, Spain
- Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Barcelona, Spain
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12
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Tang R, Buchholz E, Dale AM, Rissman RA, Fennema-Notestine C, Gillespie NA, Hagler DJ, Lyons MJ, Neale MC, Panizzon MS, Puckett OK, Reynolds CA, Franz CE, Kremen WS, Elman JA. Associations of plasma neurofilament light chain with cognition and neuroimaging measures in community-dwelling early old age men. Alzheimers Res Ther 2024; 16:90. [PMID: 38664843 PMCID: PMC11044425 DOI: 10.1186/s13195-024-01464-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 04/21/2024] [Indexed: 04/28/2024]
Abstract
BACKGROUND Plasma neurofilament light chain (NfL) is a promising biomarker of neurodegeneration with potential clinical utility in monitoring the progression of neurodegenerative diseases. However, the cross-sectional associations of plasma NfL with measures of cognition and brain have been inconsistent in community-dwelling populations. METHODS We examined these associations in a large community-dwelling sample of early old age men (N = 969, mean age = 67.57 years, range = 61-73 years), who are either cognitively unimpaired (CU) or with mild cognitive impairment (MCI). Specifically, we investigated five cognitive domains (executive function, episodic memory, verbal fluency, processing speed, visual-spatial ability), as well as neuroimaging measures of gray and white matter. RESULTS After adjusting for age, health status, and young adult general cognitive ability, plasma NfL level was only significantly associated with processing speed and white matter hyperintensity (WMH) volume, but not with other cognitive or neuroimaging measures. The association with processing speed was driven by individuals with MCI, as it was not detected in CU individuals. CONCLUSIONS These results suggest that in early old age men without dementia, plasma NfL does not appear to be sensitive to cross-sectional individual differences in most domains of cognition or neuroimaging measures of gray and white matter. The revealed plasma NfL associations were limited to WMH for all participants and processing speed only within the MCI cohort. Importantly, considering cognitive status in community-based samples will better inform the interpretation of the relationships of plasma NfL with cognition and brain and may help resolve mixed findings in the literature.
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Affiliation(s)
- Rongxiang Tang
- Department of Psychiatry, University of California San Diego, La Jolla, 92093, USA.
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, 92093, USA.
| | - Erik Buchholz
- Department of Psychiatry, University of California San Diego, La Jolla, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, 92093, USA
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, 92093, USA
- Department of Neurosciences, University of California San Diego, La Jolla, 92093, USA
| | - Robert A Rissman
- Department of Neurosciences, University of California San Diego, La Jolla, 92093, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, La Jolla, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, 92093, USA
- Department of Radiology, University of California San Diego, La Jolla, 92093, USA
| | - Nathan A Gillespie
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, VA, 23284, USA
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Donald J Hagler
- Department of Neurosciences, University of California San Diego, La Jolla, 92093, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, 02215, USA
| | - Michael C Neale
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, VA, 23284, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, 92093, USA
| | - Olivia K Puckett
- Department of Psychiatry, University of California San Diego, La Jolla, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, 92093, USA
| | - Chandra A Reynolds
- Department of Psychology and Neurosciences, University of Colorado Boulder, Boulder, 80309, USA
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, La Jolla, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, 92093, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, 92093, USA
| | - Jeremy A Elman
- Department of Psychiatry, University of California San Diego, La Jolla, 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, 92093, USA
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13
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Takahashi H, Takami Y, Takeda S, Hayakawa N, Nakajima T, Takeya Y, Matsuo-Hagiyama C, Arisawa A, Rakugi H, Tomiyama N. Imaging Biomarker for Early-Stage Alzheimer Disease: Utility of Hippocampal Histogram Analysis of Diffusion Metrics. AJNR Am J Neuroradiol 2024; 45:320-327. [PMID: 38331963 DOI: 10.3174/ajnr.a8106] [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: 06/01/2023] [Accepted: 11/17/2023] [Indexed: 02/10/2024]
Abstract
BACKGROUND AND PURPOSE Biomarkers have been required for diagnosing early Alzheimer disease. We assessed the utility of hippocampal diffusion parameters for diagnosing Alzheimer disease pathology in mild cognitive impairment. MATERIALS AND METHODS Sixty-nine patients with mild cognitive impairment underwent both CSF measurement and multi-shell diffusion imaging at 3T. Based on the CSF biomarker level, patients were classified according to the presence (Alzheimer disease group, n = 35) or absence (non-Alzheimer disease group, n = 34) of Alzheimer disease pathology. Neurite orientation dispersion and density imaging and diffusion tensor imaging parametric maps were generated. Two observers independently created the hippocampal region of interest for calculating histogram features. Interobserver correlations were calculated. The statistical significance of intergroup differences was tested by using the Mann-Whitney U test. Logistic regression analyses, using both the clinical scale and the image data, were used to predict intergroup differences, after which group discriminations were performed. RESULTS Most intraclass correlation coefficient values were between 0.59 and 0.91. In the regions of interest of both observers, there were statistically significant intergroup differences for the left-side neurite orientation dispersion and density imaging-derived intracellular volume fraction, right-side diffusion tensor imaging-derived mean diffusivity, left-side diffusion tensor imaging-derived mean diffusivity, axial diffusivity, and radial diffusivity (P < .05). Logistic regression models revealed that diffusion parameters contributed the most to discriminating between the groups. The areas under the receiver operating characteristic curve for the regions of interest of observers A/B were 0.69/0.68, 0.69/0.68, 0.73/0.68, 0.71/0.68, and 0.68/0.68 for the left-side intracellular volume fraction (mean), right-side mean diffusivity (mean), left-side mean diffusivity (10th percentile), axial diffusivity (10th percentile), and radial diffusivity (mean). CONCLUSIONS Hippocampal diffusion parameters might be useful for the early diagnosis of Alzheimer disease.
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Affiliation(s)
- Hiroto Takahashi
- From the Department of Diagnostic and Interventional Radiology (H.T., C.M.-H., A.A., N.T.), Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Yoichi Takami
- Department of Geriatric and General Medicine (Y. Takami, N.H., T.N., Y. Takeya, H.R.), Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Shuko Takeda
- Department of Clinical Gene Therapy, Graduate School of Medicine (S.T.), Osaka University, Suita, Osaka, Japan
- Osaka Psychiatric Research Center (S.T.), Osaka Psychiatric Medical Center, Hirakata, Osaka, Japan
| | - Naoki Hayakawa
- Department of Geriatric and General Medicine (Y. Takami, N.H., T.N., Y. Takeya, H.R.), Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Tsuneo Nakajima
- Department of Geriatric and General Medicine (Y. Takami, N.H., T.N., Y. Takeya, H.R.), Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Yasushi Takeya
- Department of Geriatric and General Medicine (Y. Takami, N.H., T.N., Y. Takeya, H.R.), Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Chisato Matsuo-Hagiyama
- From the Department of Diagnostic and Interventional Radiology (H.T., C.M.-H., A.A., N.T.), Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Atsuko Arisawa
- From the Department of Diagnostic and Interventional Radiology (H.T., C.M.-H., A.A., N.T.), Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Hiromi Rakugi
- Department of Geriatric and General Medicine (Y. Takami, N.H., T.N., Y. Takeya, H.R.), Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Noriyuki Tomiyama
- From the Department of Diagnostic and Interventional Radiology (H.T., C.M.-H., A.A., N.T.), Osaka University Graduate School of Medicine, Suita, Osaka, Japan
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14
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Du L, Roy S, Wang P, Li Z, Qiu X, Zhang Y, Yuan J, Guo B. Unveiling the future: Advancements in MRI imaging for neurodegenerative disorders. Ageing Res Rev 2024; 95:102230. [PMID: 38364912 DOI: 10.1016/j.arr.2024.102230] [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: 01/11/2024] [Revised: 02/11/2024] [Accepted: 02/11/2024] [Indexed: 02/18/2024]
Abstract
Neurodegenerative disorders represent a significant and growing global health challenge, necessitating continuous advancements in diagnostic tools for accurate and early detection. This work explores the recent progress in Magnetic Resonance Imaging (MRI) techniques and their application in the realm of neurodegenerative disorders. The introductory section provides a comprehensive overview of the study's background, significance, and objectives. Recognizing the current challenges associated with conventional MRI, the manuscript delves into advanced imaging techniques such as high-resolution structural imaging (HR-MRI), functional MRI (fMRI), diffusion tensor imaging (DTI), and positron emission tomography-MRI (PET-MRI) fusion. Each technique is critically examined regarding its potential to address theranostic limitations and contribute to a more nuanced understanding of the underlying pathology. A substantial portion of the work is dedicated to exploring the applications of advanced MRI in specific neurodegenerative disorders, including Parkinson's disease, Alzheimer's disease, Huntington's disease, and Amyotrophic Lateral Sclerosis (ALS). In addressing the future landscape, the manuscript examines technological advances, including the integration of machine learning and artificial intelligence in neuroimaging. The conclusion summarizes key findings, outlines implications for future research, and underscores the importance of these advancements in reshaping our understanding and approach to neurodegenerative disorders.
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Affiliation(s)
- Lixin Du
- Department of Medical Imaging, Shenzhen Longhua District Central Hospital, Shenzhen Longhua District Key Laboratory of Neuroimaging, Shenzhen 518110, China.
| | - Shubham Roy
- School of Science, Shenzhen Key Laboratory of Flexible Printed Electronics Technology, Shenzhen Key Laboratory of Advanced Functional Carbon Materials Research and Comprehensive Application, Harbin Institute of Technology, Shenzhen 518055, China
| | - Pan Wang
- Department of Medical Imaging, Shenzhen Longhua District Central Hospital, Shenzhen Longhua District Key Laboratory of Neuroimaging, Shenzhen 518110, China
| | - Zhigang Li
- Department of Medical Imaging, Shenzhen Longhua District Central Hospital, Shenzhen Longhua District Key Laboratory of Neuroimaging, Shenzhen 518110, China
| | - Xiaoting Qiu
- Department of Medical Imaging, Shenzhen Longhua District Central Hospital, Shenzhen Longhua District Key Laboratory of Neuroimaging, Shenzhen 518110, China
| | - Yinghe Zhang
- School of Science, Shenzhen Key Laboratory of Flexible Printed Electronics Technology, Shenzhen Key Laboratory of Advanced Functional Carbon Materials Research and Comprehensive Application, Harbin Institute of Technology, Shenzhen 518055, China
| | - Jianpeng Yuan
- Department of Radiology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen 518107, China.
| | - Bing Guo
- School of Science, Shenzhen Key Laboratory of Flexible Printed Electronics Technology, Shenzhen Key Laboratory of Advanced Functional Carbon Materials Research and Comprehensive Application, Harbin Institute of Technology, Shenzhen 518055, China.
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15
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Mak E, Dounavi ME, Operto G, Ziukelis ET, Jones PS, Low A, Swann P, Newton C, Muniz Terrera G, Malhotra P, Koychev I, Falcon C, Mackay C, Lawlor B, Naci L, Wells K, Ritchie C, Ritchie K, Su L, Gispert JD, O’Brien JT. APOE ɛ4 exacerbates age-dependent deficits in cortical microstructure. Brain Commun 2024; 6:fcad351. [PMID: 38384997 PMCID: PMC10881196 DOI: 10.1093/braincomms/fcad351] [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: 05/30/2023] [Revised: 10/20/2023] [Accepted: 02/09/2024] [Indexed: 02/23/2024] Open
Abstract
The apolipoprotein E ɛ4 allele is the primary genetic risk factor for the sporadic type of Alzheimer's disease. However, the mechanisms by which apolipoprotein E ɛ4 are associated with neurodegeneration are still poorly understood. We applied the Neurite Orientation Dispersion Model to characterize the effects of apolipoprotein ɛ4 and its interactions with age and education on cortical microstructure in cognitively normal individuals. Data from 1954 participants were included from the PREVENT-Dementia and ALFA (ALzheimer and FAmilies) studies (mean age = 57, 1197 non-carriers and 757 apolipoprotein E ɛ4 carriers). Structural MRI datasets were processed with FreeSurfer v7.2. The Microstructure Diffusion Toolbox was used to derive Orientation Dispersion Index maps from diffusion MRI datasets. Primary analyses were focused on (i) the main effects of apolipoprotein E ɛ4, and (ii) the interactions of apolipoprotein E ɛ4 with age and education on lobar and vertex-wise Orientation Dispersion Index and implemented using Permutation Analysis of Linear Models. There were apolipoprotein E ɛ4 × age interactions in the temporo-parietal and frontal lobes, indicating steeper age-dependent Orientation Dispersion Index changes in apolipoprotein E ɛ4 carriers. Steeper age-related Orientation Dispersion Index declines were observed among apolipoprotein E ɛ4 carriers with lower years of education. We demonstrated that apolipoprotein E ɛ4 worsened age-related Orientation Dispersion Index decreases in brain regions typically associated with atrophy patterns of Alzheimer's disease. This finding also suggests that apolipoprotein E ɛ4 may hasten the onset age of dementia by accelerating age-dependent reductions in cortical Orientation Dispersion Index.
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Affiliation(s)
- Elijah Mak
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Maria-Eleni Dounavi
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Grégory Operto
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona 08005, Spain
| | - Elina T Ziukelis
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Peter Simon Jones
- Department of Clinical Neurosciences, University of Cambridge, Cambridge CB2 0SZ, UK
| | - Audrey Low
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Peter Swann
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Coco Newton
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | | | - Paresh Malhotra
- Department of Brain Sciences, Imperial College, London W12 0NN, UK
| | - Ivan Koychev
- Department of Psychiatry, Oxford University, Oxford OX3 7JX, UK
| | - Carles Falcon
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona 08005, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona 08003, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid 28029, Spain
| | - Clare Mackay
- Department of Psychiatry, Oxford University, Oxford OX3 7JX, UK
| | - Brian Lawlor
- Institute of Neuroscience, Trinity College Dublin, University of Dublin, Dublin D02 PX31, Ireland
| | - Lorina Naci
- Institute of Neuroscience, Trinity College Dublin, University of Dublin, Dublin D02 PX31, Ireland
| | - Katie Wells
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Craig Ritchie
- Centre for Dementia Prevention, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Karen Ritchie
- Institut National de la Santé et de la Recherche Médicale, U1061 Neuropsychiatrie, Montpellier 34093, France
- Faculty of Medicine, University of Montpellier, Montpellier 34093, France
| | - Li Su
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona 08005, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona 08003, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Madrid 28029, Spain
| | - John T O’Brien
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
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16
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Chen A, Li Q, Huang Y, Li Y, Chuang YN, Hu X, Guo S, Wu Y, Guo Y, Bian J. Feasibility of Identifying Factors Related to Alzheimer's Disease and Related Dementia in Real-World Data. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.10.24302621. [PMID: 38405723 PMCID: PMC10889002 DOI: 10.1101/2024.02.10.24302621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
A comprehensive view of factors associated with AD/ADRD will significantly aid in studies to develop new treatments for AD/ADRD and identify high-risk populations and patients for prevention efforts. In our study, we summarized the risk factors for AD/ADRD by reviewing existing meta-analyses and review articles on risk and preventive factors for AD/ADRD. In total, we extracted 477 risk factors in 10 categories from 537 studies. We constructed an interactive knowledge map to disseminate our study results. Most of the risk factors are accessible from structured Electronic Health Records (EHRs), and clinical narratives show promise as information sources. However, evaluating genomic risk factors using RWD remains a challenge, as genetic testing for AD/ADRD is still not a common practice and is poorly documented in both structured and unstructured EHRs. Considering the constantly evolving research on AD/ADRD risk factors, literature mining via NLP methods offers a solution to automatically update our knowledge map.
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Affiliation(s)
- Aokun Chen
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, 1889 Museum Rd, Suite 7000, Gainesville, FL 32610
| | - Qian Li
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, 1889 Museum Rd, Suite 7000, Gainesville, FL 32610
| | - Yu Huang
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, 1889 Museum Rd, Suite 7000, Gainesville, FL 32610
| | - Yongqiu Li
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, 1889 Museum Rd, Suite 7000, Gainesville, FL 32610
| | - Yu-Neng Chuang
- Department of Computer Science, George R. Brown School of Engineering, Rice University, 6100 Main St., Houston, TX 77005
| | - Xia Hu
- Department of Computer Science, George R. Brown School of Engineering, Rice University, 6100 Main St., Houston, TX 77005
| | - Serena Guo
- Department of Pharmaceutical Outcomes & Policy, College of Pharmacy, University of Florida, 1225 Center Drive, Gainesville, FL 32610
| | - Yonghui Wu
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, 1889 Museum Rd, Suite 7000, Gainesville, FL 32610
| | - Yi Guo
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, 1889 Museum Rd, Suite 7000, Gainesville, FL 32610
| | - Jiang Bian
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, 1889 Museum Rd, Suite 7000, Gainesville, FL 32610
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17
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Nir TM, Villalón-Reina JE, Salminen LE, Haddad E, Zheng H, Thomopoulos SI, Jack CR, Weiner MW, Thompson PM, Jahanshad N. Cortical microstructural associations with CSF amyloid and pTau. Mol Psychiatry 2024; 29:257-268. [PMID: 38092890 PMCID: PMC11116103 DOI: 10.1038/s41380-023-02321-7] [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: 02/13/2023] [Revised: 10/25/2023] [Accepted: 11/07/2023] [Indexed: 12/26/2023]
Abstract
Diffusion MRI (dMRI) can be used to probe microstructural properties of brain tissue and holds great promise as a means to non-invasively map Alzheimer's disease (AD) pathology. Few studies have evaluated multi-shell dMRI models such as neurite orientation dispersion and density imaging (NODDI) and mean apparent propagator (MAP)-MRI in cortical gray matter where many of the earliest histopathological changes occur in AD. Here, we investigated the relationship between CSF pTau181 and Aβ1-42 burden and regional cortical NODDI and MAP-MRI indices in 46 cognitively unimpaired individuals, 18 with mild cognitive impairment, and two with dementia (mean age: 71.8 ± 6.2 years) from the Alzheimer's Disease Neuroimaging Initiative. We compared findings to more conventional cortical thickness measures. Lower CSF Aβ1-42 and higher pTau181 were associated with cortical dMRI measures reflecting less hindered or restricted diffusion and greater diffusivity. Cortical dMRI measures, but not cortical thickness measures, were more widely associated with Aβ1-42 than pTau181 and better distinguished Aβ+ from Aβ- participants than pTau+ from pTau- participants. dMRI associations mediated the relationship between CSF markers and delayed logical memory performance, commonly impaired in early AD. dMRI metrics sensitive to early AD pathogenesis and microstructural damage may be better measures of subtle neurodegeneration in comparison to standard cortical thickness and help to elucidate mechanisms underlying cognitive decline.
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Affiliation(s)
- Talia M Nir
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA.
| | - Julio E Villalón-Reina
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Lauren E Salminen
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Elizabeth Haddad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Hong Zheng
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Sophia I Thomopoulos
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | | | - Michael W Weiner
- Department of Radiology, School of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, USA
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18
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Morrissey ZD, Gao J, Shetti A, Li W, Zhan L, Li W, Fortel I, Saido T, Saito T, Ajilore O, Cologna SM, Lazarov O, Leow AD. Temporal Alterations in White Matter in An App Knock-In Mouse Model of Alzheimer's Disease. eNeuro 2024; 11:ENEURO.0496-23.2024. [PMID: 38290851 PMCID: PMC10897532 DOI: 10.1523/eneuro.0496-23.2024] [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: 11/27/2023] [Revised: 01/05/2024] [Accepted: 01/17/2024] [Indexed: 02/01/2024] Open
Abstract
Alzheimer's disease (AD) is the most common form of dementia and results in neurodegeneration and cognitive impairment. White matter (WM) is affected in AD and has implications for neural circuitry and cognitive function. The trajectory of these changes across age, however, is still not well understood, especially at earlier stages in life. To address this, we used the AppNL-G-F/NL-G-F knock-in (APPKI) mouse model that harbors a single copy knock-in of the human amyloid precursor protein (APP) gene with three familial AD mutations. We performed in vivo diffusion tensor imaging (DTI) to study how the structural properties of the brain change across age in the context of AD. In late age APPKI mice, we observed reduced fractional anisotropy (FA), a proxy of WM integrity, in multiple brain regions, including the hippocampus, anterior commissure (AC), neocortex, and hypothalamus. At the cellular level, we observed greater numbers of oligodendrocytes in middle age (prior to observations in DTI) in both the AC, a major interhemispheric WM tract, and the hippocampus, which is involved in memory and heavily affected in AD, prior to observations in DTI. Proteomics analysis of the hippocampus also revealed altered expression of oligodendrocyte-related proteins with age and in APPKI mice. Together, these results help to improve our understanding of the development of AD pathology with age, and imply that middle age may be an important temporal window for potential therapeutic intervention.
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Affiliation(s)
- Zachery D Morrissey
- Graduate Program in Neuroscience, University of Illinois Chicago, Chicago, Illinois 60612
- Department of Psychiatry, University of Illinois Chicago, Chicago, Illinois 60612
- Department of Anatomy & Cell Biology, University of Illinois Chicago, Chicago, Illinois 60612
| | - Jin Gao
- Department of Electrical & Computer Engineering, University of Illinois Chicago, Chicago, Illinois 60607
- Preclinical Imaging Core, University of Illinois Chicago, Chicago, Illinois 60612
| | - Aashutosh Shetti
- Department of Anatomy & Cell Biology, University of Illinois Chicago, Chicago, Illinois 60612
| | - Wenping Li
- Department of Chemistry, University of Illinois Chicago, Chicago, Illinois 60607
| | - Liang Zhan
- Department of Electrical & Computer Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania 15261
| | - Weiguo Li
- Preclinical Imaging Core, University of Illinois Chicago, Chicago, Illinois 60612
- Department of Bioengineering, University of Illinois Chicago, Chicago, Illinois 60607
- Department of Radiology, Northwestern University, Chicago, Illinois 60611
| | - Igor Fortel
- Department of Bioengineering, University of Illinois Chicago, Chicago, Illinois 60607
| | - Takaomi Saido
- Laboratory for Proteolytic Neuroscience, RIKEN Center for Brain Science, Wako 351-0198, Japan
| | - Takashi Saito
- Department of Neurocognitive Science, Institute of Brain Science, Nagoya City University, Nagoya 467-8601, Japan
| | - Olusola Ajilore
- Department of Psychiatry, University of Illinois Chicago, Chicago, Illinois 60612
| | - Stephanie M Cologna
- Department of Chemistry, University of Illinois Chicago, Chicago, Illinois 60607
| | - Orly Lazarov
- Department of Anatomy & Cell Biology, University of Illinois Chicago, Chicago, Illinois 60612
| | - Alex D Leow
- Department of Psychiatry, University of Illinois Chicago, Chicago, Illinois 60612
- Department of Bioengineering, University of Illinois Chicago, Chicago, Illinois 60607
- Department of Computer Science, University of Illinois Chicago, Chicago, Illinois 60607
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19
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Silva-Rudberg JA, Salardini E, O'Dell RS, Chen MK, Ra J, Georgelos JK, Morehouse MR, Melino KP, Varma P, Toyonaga T, Nabulsi NB, Huang Y, Carson RE, van Dyck CH, Mecca AP. Assessment of Gray Matter Microstructure and Synaptic Density in Alzheimer's Disease: A Multimodal Imaging Study With DTI and SV2A PET. Am J Geriatr Psychiatry 2024; 32:17-28. [PMID: 37673749 PMCID: PMC10840732 DOI: 10.1016/j.jagp.2023.08.002] [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: 05/25/2023] [Revised: 07/19/2023] [Accepted: 08/05/2023] [Indexed: 09/08/2023]
Abstract
OBJECTIVE Multimodal imaging techniques have furthered our understanding of how different aspects of Alzheimer's disease (AD) pathology relate to one another. Diffusion tensor imaging (DTI) measures such as mean diffusivity (MD) may be a surrogate measure of the changes in gray matter structure associated with AD. Positron emission tomography (PET) imaging of synaptic vesicle glycoprotein 2A (SV2A) has been used to quantify synaptic loss, which is the major pathological correlate of cognitive impairment in AD. In this study, we investigated the relationship between gray matter microstructure and synaptic density. METHODS DTI was used to measure MD and [11C]UCB-J PET to measure synaptic density in 33 amyloid-positive participants with AD and 17 amyloid-negative cognitively normal (CN) participants aged 50-83. Univariate regression analyses were used to assess the association between synaptic density and MD in both the AD and CN groups. RESULTS Hippocampal MD was inversely associated with hippocampal synaptic density in participants with AD (r = -0.55, p <0.001, df = 31) but not CN (r = 0.13, p = 0.62, df = 15). Exploratory analyses across other regions known to be affected in AD suggested widespread inverse associations between synaptic density and MD in the AD group. CONCLUSION In the setting of AD, an increase in gray matter MD is inversely associated with synaptic density. These co-occurring changes may suggest a link between synaptic loss and gray matter microstructural changes in AD. Imaging studies of gray matter microstructure and synaptic density may allow important insights into AD-related neuropathology.
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Affiliation(s)
- Jason A Silva-Rudberg
- Alzheimer's Disease Research Unit (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT; Department of Psychiatry (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT.
| | - Elaheh Salardini
- Alzheimer's Disease Research Unit (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT; Department of Psychiatry (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT
| | - Ryan S O'Dell
- Alzheimer's Disease Research Unit (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT; Department of Psychiatry (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT
| | - Ming-Kai Chen
- Department of Radiology and Biomedical Imaging (M-KC, PV, TT, NBN, YH, REC), Yale University School of Medicine, New Haven, CT
| | - Jocelyn Ra
- Alzheimer's Disease Research Unit (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT; Department of Psychiatry (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT
| | - Jamie K Georgelos
- Alzheimer's Disease Research Unit (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT; Department of Psychiatry (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT
| | - Mackenzie R Morehouse
- Alzheimer's Disease Research Unit (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT; Department of Psychiatry (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT
| | - Kaitlyn P Melino
- Alzheimer's Disease Research Unit (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT; Department of Psychiatry (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT
| | - Pradeep Varma
- Department of Radiology and Biomedical Imaging (M-KC, PV, TT, NBN, YH, REC), Yale University School of Medicine, New Haven, CT
| | - Takuya Toyonaga
- Department of Radiology and Biomedical Imaging (M-KC, PV, TT, NBN, YH, REC), Yale University School of Medicine, New Haven, CT
| | - Nabeel B Nabulsi
- Department of Radiology and Biomedical Imaging (M-KC, PV, TT, NBN, YH, REC), Yale University School of Medicine, New Haven, CT
| | - Yiyun Huang
- Department of Radiology and Biomedical Imaging (M-KC, PV, TT, NBN, YH, REC), Yale University School of Medicine, New Haven, CT
| | - Richard E Carson
- Department of Radiology and Biomedical Imaging (M-KC, PV, TT, NBN, YH, REC), Yale University School of Medicine, New Haven, CT
| | - Christopher H van Dyck
- Alzheimer's Disease Research Unit (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT; Department of Psychiatry (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT; Department of Neuroscience (CHvD), Yale University School of Medicine, New Haven, CT; Department of Neurology (CHvD), Yale University School of Medicine, New Haven, CT
| | - Adam P Mecca
- Alzheimer's Disease Research Unit (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT; Department of Psychiatry (JAS-R, ES, RSO, JR, JKG, MRM, KPM, CHvD, APM), Yale University School of Medicine, New Haven, CT.
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20
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Tang R, Elman JA, Dale AM, Dorros SM, Eyler LT, Fennema-Notestine C, Gustavson DE, Hagler DJ, Lyons MJ, Panizzon MS, Puckett OK, Reynolds CA, Franz CE, Kremen WS. Childhood Disadvantage Moderates Late Midlife Default Mode Network Cortical Microstructure and Visual Memory Association. J Gerontol A Biol Sci Med Sci 2024; 79:glad114. [PMID: 37096346 DOI: 10.1093/gerona/glad114] [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: 09/20/2022] [Indexed: 04/26/2023] Open
Abstract
BACKGROUND Childhood disadvantage is a prominent risk factor for cognitive and brain aging. Childhood disadvantage is associated with poorer episodic memory in late midlife and functional and structural brain abnormalities in the default mode network (DMN). Although age-related changes in DMN are associated with episodic memory declines in older adults, it remains unclear if childhood disadvantage has an enduring impact on this later-life brain-cognition relationship earlier in the aging process. Here, within the DMN, we examined whether its cortical microstructural integrity-an early marker of structural vulnerability that increases the risk for future cognitive decline and neurodegeneration-is associated with episodic memory in adults at ages 56-66, and whether childhood disadvantage moderates this association. METHODS Cortical mean diffusivity (MD) obtained from diffusion magnetic resonance imaging was used to measure microstructural integrity in 350 community-dwelling men. We examined both visual and verbal episodic memory in relation to DMN MD and divided participants into disadvantaged and nondisadvantaged groups based on parental education and occupation. RESULTS Higher DMN MD was associated with poorer visual memory but not verbal memory (β = -0.11, p = .040 vs β = -0.04, p = .535). This association was moderated by childhood disadvantage and was significant only in the disadvantaged group (β = -0.26, p = .002 vs β = -0.00, p = .957). CONCLUSIONS Lower DMN cortical microstructural integrity may reflect visual memory vulnerability in cognitively normal adults earlier in the aging process. Individuals who experienced childhood disadvantage manifested greater vulnerability to cortical microstructure-related visual memory dysfunction than their nondisadvantaged counterparts who exhibited resilience in the face of low cortical microstructural integrity.
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Affiliation(s)
- Rongxiang Tang
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - Jeremy A Elman
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, California, USA
- Department of Neurosciences, University of California San Diego, La Jolla, California, USA
| | - Stephen M Dorros
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, California, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Daniel E Gustavson
- Institute for Behavior Genetics, University of Colorado Boulder, Boulder, Colorado, USA
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, La Jolla, California, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - Olivia K Puckett
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - Chandra A Reynolds
- Department of Psychology, University of California Riverside, Riverside, California, USA
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, California, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, California, USA
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21
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Feng Y, Murphy MC, Hojo E, Li F, Roberts N. Magnetic Resonance Elastography in the Study of Neurodegenerative Diseases. J Magn Reson Imaging 2024; 59:82-96. [PMID: 37084171 DOI: 10.1002/jmri.28747] [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: 02/16/2023] [Revised: 04/03/2023] [Accepted: 04/04/2023] [Indexed: 04/22/2023] Open
Abstract
Neurodegenerative diseases such as Alzheimer's disease (AD) and Parkinson's disease (PD) present a major health burden to society. Changes in brain structure and cognition are generally only observed at the late stage of the disease. Although advanced magnetic resonance imaging (MRI) techniques such as diffusion imaging may allow identification of biomarkers at earlier stages of neurodegeneration, early diagnosis is still challenging. Magnetic resonance elastography (MRE) is a noninvasive MRI technique for studying the mechanical properties of tissues by measuring the wave propagation induced in the tissues using a purpose-built actuator. Here, we present a systematic review of preclinical and clinical studies in which MRE has been applied to study neurodegenerative diseases. Actuator systems for data acquisition, inversion algorithms for data analysis, and sample demographics are described and tissue stiffness measures obtained for the whole brain and internal structures are summarized. A total of six animal studies and eight human studies have been published. The animal studies refer to 123 experimental animals (68 AD and 55 PD) and 121 wild-type animals, while the human studies refer to 142 patients with neurodegenerative disease (including 56 AD and 17 PD) and 166 controls. The animal studies are consistent in the reporting of decreased stiffness of the hippocampal region in AD mice. However, in terms of disease progression, although consistent decreases in either storage modulus or shear modulus magnitude are reported for whole brain, there is variation in the results reported for the hippocampal region. The clinical studies are consistent in reports of a significant decrease in either whole brain storage modulus or shear modulus magnitude, in both AD and PD and with different brain structures affected in different neurodegenerative diseases. MRE studies of neurodegenerative diseases are still in their infancy, and in future it will be interesting to investigate potential relationships between brain mechanical properties and clinical measures, which may help elucidate the mechanisms underlying onset and progression of neurodegenerative diseases. EVIDENCE LEVEL: 1. TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Yuan Feng
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
- Department of Radiology, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China
- National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy (NERC-AMRT), Shanghai Jiao Tong University, Shanghai, China
| | - Matthew C Murphy
- Department of Radiology, Mayo Clinic College of Medicine and Science, Rochester, Minnesota, USA
| | - Emi Hojo
- Centre for Reproductive Health (CRH), School of Clinical Sciences, University of Edinburgh, Edinburgh, UK
| | - Fei Li
- Department of Radiology and Huaxi MR Research Center (HMRRC), Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, Sichuan Province, China
| | - Neil Roberts
- Centre for Reproductive Health (CRH), School of Clinical Sciences, University of Edinburgh, Edinburgh, UK
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22
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Kang K, Fleming K, Sathe A, Muller J, Harrop J, Middleton D, Heller J, Sharan A, Mohamed F, Krisa L, Alizadeh M. Microstructural alterations of major thalamic nuclei in the chronic pediatric spinal cord injured population. World Neurosurg X 2024; 21:100268. [PMID: 38187507 PMCID: PMC10767188 DOI: 10.1016/j.wnsx.2023.100268] [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: 01/21/2023] [Revised: 07/12/2023] [Accepted: 11/28/2023] [Indexed: 01/09/2024] Open
Abstract
Background The brain undergoes reorganization following spinal cord injury (SCI), but little is known about how the thalamus is affected in pediatric SCIs. Purpose To characterize microstructural alterations in the thalamus after SCI with diffusion tensor imaging (DTI) metrics. Methods 18 pediatric participants with chronic SCI (8-20 years) were stratified using the American Spinal Injury Association Impairment Scale (AIS) into groups: A, B, and C/D. DTI of the brain used a 3 T Siemens Verio MRI using the parameters: 20 directions, number of averages = 3, b = 1000 s/mm2, voxel size = 1.8 mm × 1.8 mm, slice thickness = 5 mm, TE = 95 ms, TR = 4300 ms, 30 slices, FOV = 230 × 230 mm2, matrix = 128 × 128, acquisition time = 4:45 min. Diffusion data was processed to generate DTI metrics FA, MD, AD, and RD. Data analysis DTI metrics were acquired by superimposing the AAL3 thalamic atlas onto participant diffusion images registered to MNI152 space. We utilized a multiple Mann-Whitney U-test to compare between AIS groups, considering values of p ≤ 0.05 as significant. Results FA, AD, RD, and MD significantly differed in thalamic nuclei between AIS groups A vs B and B vs C/D. Significant nuclei include the right ventral anterior, left intralaminar, bilateral lateral pulvinar, and right lateral geniculate. Conclusion Our findings suggest the presence of microstructural alterations based on SCI severity in pediatric patients. These results are encouraging and warrant further study.
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Affiliation(s)
- K. Kang
- Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, 909 Walnut St., Philadelphia, PA, 19107, USA
| | - K. Fleming
- Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, 909 Walnut St., Philadelphia, PA, 19107, USA
| | - A. Sathe
- Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, 909 Walnut St., Philadelphia, PA, 19107, USA
| | - J. Muller
- Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, 909 Walnut St., Philadelphia, PA, 19107, USA
| | - J. Harrop
- Department of Neurosurgery, Thomas Jefferson University, 909 Walnut Street, 2nd Floor, Philadelphia, PA, 19107, USA
| | - D. Middleton
- Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, 909 Walnut St., Philadelphia, PA, 19107, USA
| | - J.E. Heller
- Department of Neurosurgery, Thomas Jefferson University, 909 Walnut Street, 2nd Floor, Philadelphia, PA, 19107, USA
| | - A. Sharan
- Department of Neurosurgery, Thomas Jefferson University, 909 Walnut Street, 2nd Floor, Philadelphia, PA, 19107, USA
| | - F. Mohamed
- Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, 909 Walnut St., Philadelphia, PA, 19107, USA
| | - L. Krisa
- Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, 909 Walnut St., Philadelphia, PA, 19107, USA
| | - M. Alizadeh
- Department of Neurosurgery, Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, 909 Walnut St., Philadelphia, PA, 19107, USA
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23
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Wang X, Luo X, Pan H, Wang X, Xu S, Li H, Lin Z. Performance of hippocampal radiomics models based on T2-FLAIR images in mesial temporal lobe epilepsy with hippocampal sclerosis. Eur J Radiol 2023; 167:111082. [PMID: 37708677 DOI: 10.1016/j.ejrad.2023.111082] [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: 02/11/2023] [Revised: 07/14/2023] [Accepted: 09/04/2023] [Indexed: 09/16/2023]
Abstract
PURPOSE Preoperative identification of hippocampal sclerosis (HS) is crucial to successful surgery for mesial temporal lobe epilepsy (MTLE). We aimed to investigate the diagnostic performance of hippocampal radiomics models based on T2 fluid-attenuated inversion recovery (FLAIR) images in MTLE with HS. METHODS We analysed 210 cases, including 172 HS pathology-confirmed cases (100 magnetic resonance imaging [MRI]-positive cases [MRI + HS], 72 MRI-negative HS cases [MRI - HS]), and 38 healthy controls (HC). The hippocampus was delineated slice by slice on an oblique coronal plane by a T2-FLAIR sequence, perpendicular to the hippocampus's long axis, to obtain a three-dimensional region of interest. Radiomics were processed using Artificial Intelligence Kit software; logistic regression radiomics models were constructed. The model evaluation indexes included the area under the curve (AUC), accuracy, sensitivity, and specificity. RESULTS The respective AUC, accuracy, sensitivity, and specificity were 0.863, 81.4%, 78.0%, and 84.6% between the MRI - HS and HC groups in the training set and 0.855, 75.0%, 68.2%, and 81.8% in the test set; 0.975, 95.0%, 92.9%, and 98.0% between the MRI + HS and HC groups in the training set and 0.954, 88.7%, 90.0%, and 87.0% in the test set; and 0.912, 84.3%, 83.3%, and 86.5% between the MTLE and HC groups in the training set and 0.854, 79.7%, 80.8%, and 77.3% in the test set. The AUC values of the comparative radiomics models were > 0.85, indicating good diagnostic efficiency. CONCLUSION The hippocampal radiomics models based on T2-FLAIR images can help diagnose MTLE with HS. They can be used as biological markers for MTLE diagnosis.
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Affiliation(s)
- Xiaoyu Wang
- Fuzong Clinical Medical College of Fujian Medical University, Fuzhou, Fujian Province, China; Department of Radiology, 900TH Hospital of Joint Logistics Support Force, Fuzhou, Fujian Province, China
| | - Xiaoting Luo
- Department of Radiology, the First Affiliated Hospital of Xiamen University, Xiamen, Fujian Province, China
| | - Haitao Pan
- Department of Radiology, Cangshan Branch of 900TH Hospital of Joint Logistics Support Force, Fuzhou, Fujian Province, China
| | - Xiaoyang Wang
- Fuzong Clinical Medical College of Fujian Medical University, Fuzhou, Fujian Province, China; Department of Radiology, 900TH Hospital of Joint Logistics Support Force, Fuzhou, Fujian Province, China
| | - Shangwen Xu
- Fuzong Clinical Medical College of Fujian Medical University, Fuzhou, Fujian Province, China; Department of Radiology, 900TH Hospital of Joint Logistics Support Force, Fuzhou, Fujian Province, China.
| | - Hui Li
- Fuzong Clinical Medical College of Fujian Medical University, Fuzhou, Fujian Province, China; Department of Radiology, 900TH Hospital of Joint Logistics Support Force, Fuzhou, Fujian Province, China
| | - Zhiping Lin
- GE Healthcare, Guangzhou, Guangdong Province, China
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24
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Grimaldi S, Guye M, Bianciardi M, Eusebio A. Brain MRI Biomarkers in Isolated Rapid Eye Movement Sleep Behavior Disorder: Where Are We? A Systematic Review. Brain Sci 2023; 13:1398. [PMID: 37891767 PMCID: PMC10604962 DOI: 10.3390/brainsci13101398] [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: 08/27/2023] [Revised: 09/22/2023] [Accepted: 09/28/2023] [Indexed: 10/29/2023] Open
Abstract
The increasing number of MRI studies focused on prodromal Parkinson's Disease (PD) demonstrates a strong interest in identifying early biomarkers capable of monitoring neurodegeneration. In this systematic review, we present the latest information regarding the most promising MRI markers of neurodegeneration in relation to the most specific prodromal symptoms of PD, namely isolated rapid eye movement (REM) sleep behavior disorder (iRBD). We reviewed structural, diffusion, functional, iron-sensitive, neuro-melanin-sensitive MRI, and proton magnetic resonance spectroscopy studies conducted between 2000 and 2023, which yielded a total of 77 relevant papers. Among these markers, iron and neuromelanin emerged as the most robust and promising indicators for early neurodegenerative processes in iRBD. Atrophy was observed in several regions, including the frontal and temporal cortices, limbic cortices, and basal ganglia, suggesting that neurodegenerative processes had been underway for some time. Diffusion and functional MRI produced heterogeneous yet intriguing results. Additionally, reduced glymphatic clearance function was reported. Technological advancements, such as the development of ultra-high field MRI, have enabled the exploration of minute anatomical structures and the detection of previously undetectable anomalies. The race to achieve early detection of neurodegeneration is well underway.
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Affiliation(s)
- Stephan Grimaldi
- Department of Neurology and Movement Disorders, APHM, Hôpital Universitaire Timone, 265 rue Saint-Pierre, 13005 Marseille, France
- Centre d’Exploration Métabolique par Résonnance Magnétique, Assistance Publique des Hôpitaux de Marseille, Hôpital Universitaire Timone, 265 rue Saint-Pierre, 13005 Marseille, France
- Center for Magnetic Resonance in Biology and Medicine, Aix Marseille University, Centre National de la Recherche Scientifique, 27 Bd Jean Moulin, 13385 Marseille, France
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, 149 13th St., Charlestown, MA 02129, USA
| | - Maxime Guye
- Centre d’Exploration Métabolique par Résonnance Magnétique, Assistance Publique des Hôpitaux de Marseille, Hôpital Universitaire Timone, 265 rue Saint-Pierre, 13005 Marseille, France
- Center for Magnetic Resonance in Biology and Medicine, Aix Marseille University, Centre National de la Recherche Scientifique, 27 Bd Jean Moulin, 13385 Marseille, France
| | - Marta Bianciardi
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, 149 13th St., Charlestown, MA 02129, USA
- Division of Sleep Medicine, Harvard University, Boston, MA 02114, USA
| | - Alexandre Eusebio
- Department of Neurology and Movement Disorders, APHM, Hôpital Universitaire Timone, 265 rue Saint-Pierre, 13005 Marseille, France
- Institut de Neurosciences de la Timone, Aix Marseille University, Centre National de la Recherche Scientifique, 27 Bd Jean Moulin, 13385 Marseille, France
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Kang IC, Pasternak O, Zhang F, Penzel N, Seitz-Holland J, Tang Y, Zhang T, Xu L, Li H, Keshavan M, Whitfield-Gabrielli S, Niznikiewicz M, Stone W, Wang J, Shenton M. Microstructural Cortical Gray Matter Changes Preceding Accelerated Volume Changes in Individuals at Clinical High Risk for Psychosis. RESEARCH SQUARE 2023:rs.3.rs-3179575. [PMID: 37841868 PMCID: PMC10571628 DOI: 10.21203/rs.3.rs-3179575/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: 10/17/2023]
Abstract
Recent studies show that accelerated cortical gray matter (GM) volume reduction seen in anatomical MRI can help distinguish between individuals at clinical high risk (CHR) for psychosis who will develop psychosis and those who will not. This reduction is thought to result from an accumulation of microstructural changes, such as decreased spine density and dendritic arborization. Detecting the microstructural sources of these changes before they accumulate is crucial, as volume reduction likely indicates an underlying neurodegenerative process. Our study aimed to detect these microstructural GM alterations using diffusion MRI (dMRI). We tested for baseline and longitudinal group differences in anatomical and dMRI data from 160 individuals at CHR and 96 healthy controls (HC) acquired in a single imaging site. Eight cortical lobes were examined for GM volume and GM microstructure. A novel dMRI measure, interstitial free water (iFW), was used to quantify GM microstructure by eliminating cerebrospinal fluid contribution. Additionally, we assessed whether these measures differentiated the 33 individuals at CHR who developed psychosis (CHR-P) from the 127 individuals at CHR who did not (CHR-NP). At baseline the CHR group had significantly higher iFW than HC in the prefrontal, temporal, parietal, and occipital lobes, while volume was reduced only in the temporal lobe. Neither iFW nor volume differentiated between the CHR-P and CHR-NP groups at baseline. However, in most brain areas, the CHR-P group demonstrated significantly accelerated iFW increase and volume reduction with time than the CHR-NP group. Our results demonstrate that microstructural GM changes in individuals at CHR have a wider extent than volumetric changes and they predate the acceleration of brain changes that occur around psychosis onset. Microstructural GM changes are thus an early pathology at the prodromal stage of psychosis that may be useful for early detection and a better mechanistic understanding of psychosis development.
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Affiliation(s)
| | | | | | | | - Johanna Seitz-Holland
- Brigham and Women's Hospital and Massachusetts General Hospital, Harvard Medical School
| | - Yingying Tang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine
| | - Tianhong Zhang
- Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai Key Laboratory of Psychotic Disorders, Shanghai 200030, PR China
| | | | | | | | | | | | | | - Jijun Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine
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26
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Shrestha S, Zhu X, Sullivan KJ, Blackshear C, Deal JA, Sharrett AR, Kamath V, Schneider ALC, Jack CR, Huang J, Palta P, Reid RI, Knopman DS, Gottesman RF, Chen H, Windham BG, Griswold ME, Mosley TH. Association of Olfaction and Microstructural Integrity of Brain Tissue in Community-Dwelling Adults: Atherosclerosis Risk in Communities Neurocognitive Study. Neurology 2023; 101:e1328-e1340. [PMID: 37541841 PMCID: PMC10558165 DOI: 10.1212/wnl.0000000000207636] [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: 01/09/2023] [Accepted: 05/30/2023] [Indexed: 08/06/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Research on olfaction and brain neuropathology may help understand brain regions associated with normal olfaction and dementia pathophysiology. To identify early regional brain structures affected in poor olfaction, we examined cross-sectional associations of microstructural integrity of the brain with olfaction in the Atherosclerosis Risk in Communities Neurocognitive Study. METHODS Participants were selected from a prospective cohort study of community-dwelling adults; selection criteria included the following: evidence of cognitive impairment, participation in a previous MRI study, and a random sample of cognitively normal participants. Microstructural integrity was measured by 2 diffusion tensor imaging (DTI) measures, fractional anisotropy (FA) and mean diffusivity (MD), and olfaction by a 12-item odor identification test at the same visit. Higher FA and MD values indicate better and worse microstructural integrity, respectively, and higher odor identification scores indicate better olfaction. We used brain region-specific linear regression models to examine associations between DTI measures and olfaction, adjusting for potential confounders. RESULTS Among 1,418 participants (mean age 76 ± 5 years, 41% male, 21% Black race, 59% with normal cognition), the mean olfaction score was 9 ± 2.3. Relevant to olfaction, higher MD in the medial temporal lobe (MTL) regions, namely the hippocampus (β -0.79 [95% CI -0.94 to -0.65] units lower olfaction score per 1 SD higher MD), amygdala, entorhinal area, and some white matter (WM) tracts connecting to these regions, was associated with olfaction. We also observed associations with MD and WM FA in multiple atlas regions that were not previously implicated in olfaction. The associations between MD and olfaction were particularly stronger in the MTL regions among individuals with mild cognitive impairment (MCI) compared with those with normal cognition (e.g., βhippocampus -0.75 [95% CI -1.02 to -0.49] and -0.44 [95% CI -0.63 to -0.26] for MCI and normal cognition, respectively, p interaction = 0.004). DISCUSSION Neuronal microstructural integrity in multiple brain regions, particularly the MTL (the regions known to be affected in early Alzheimer disease), is associated with odor identification ability. Differential associations in the MTL regions among cognitively normal individuals compared with those with MCI may reflect the earlier vs later effects of the dementia pathogenesis. It is likely that some of the associated regions may not have any functional relevance to olfaction.
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Affiliation(s)
- Srishti Shrestha
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing.
| | - Xiaoqian Zhu
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Kevin J Sullivan
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Chad Blackshear
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Jennifer A Deal
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - A Richey Sharrett
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Vidyulata Kamath
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Andrea L C Schneider
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Clifford R Jack
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Juebin Huang
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Priya Palta
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Robert I Reid
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - David S Knopman
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Rebecca F Gottesman
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Honglei Chen
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - B Gwen Windham
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Michael E Griswold
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
| | - Thomas H Mosley
- From the The Memory Impairment and Neurodegenerative Dementia (MIND) Center (S.S., X.Z., K.J.S., C.B., J.H., B.G.W., M.E.G., T.H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (J.A.D., A.R.S.), Johns Hopkins University Bloomberg School of Public Health; Department of Psychiatry and Behavioral Sciences (V.K.), Johns Hopkins University School of Medicine, Baltimore, MD; Department of Neurology (A.L.C.S.), and Department of Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Perelman School of Medicine, Philadelphia; Department of Radiology (C.R.J., R.I.R.), Mayo Clinic, Rochester, MN; Department of Neurology (J.H.), University of Mississippi Medical Center, Jackson; Department of Neurology (P.P.), University of North Carolina at Chapel Hill; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD; and Department of Epidemiology and Biostatistics (H.C.), Michigan State University, East Lansing
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Williams ME, Elman JA, Bell TR, Dale AM, Eyler LT, Fennema-Notestine C, Franz CE, Gillespie NA, Hagler DJ, Lyons MJ, McEvoy LK, Neale MC, Panizzon MS, Reynolds CA, Sanderson-Cimino M, Kremen WS. Higher cortical thickness/volume in Alzheimer's-related regions: protective factor or risk factor? Neurobiol Aging 2023; 129:185-194. [PMID: 37343448 PMCID: PMC10676195 DOI: 10.1016/j.neurobiolaging.2023.05.004] [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: 11/03/2022] [Revised: 04/18/2023] [Accepted: 05/03/2023] [Indexed: 06/23/2023]
Abstract
Some evidence suggests a biphasic pattern of changes in cortical thickness wherein higher, rather than lower, thickness is associated with very early Alzheimer's disease (AD) pathology. We examined whether integrating information from AD brain signatures based on mean diffusivity (MD) can aid in the interpretation of cortical thickness/volume as a risk factor for future AD-related changes. Participants were 572 men in the Vietnam Era Twin Study of Aging who were cognitively unimpaired at baseline (mean age = 56 years; range = 51-60). Individuals with both high thickness/volume signatures and high MD signatures at baseline had lower cortical thickness/volume in AD signature regions and lower episodic memory performance 12 years later compared to those with high thickness/volume and low MD signatures at baseline. Groups did not differ in level of young adult cognitive reserve. Our findings are in line with a biphasic model in which increased cortical thickness may precede future decline and establish the value of examining cortical MD alongside cortical thickness to identify subgroups with differential risk for poorer brain and cognitive outcomes.
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Affiliation(s)
- McKenna E Williams
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California, San Diego, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA.
| | - Jeremy A Elman
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Tyler R Bell
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, CA, USA; Department of Neuroscience, University of California San Diego, La Jolla, CA, USA
| | - Lisa T Eyler
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, CA, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA; Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Carol E Franz
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Linda K McEvoy
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, VA, USA
| | - Matthew S Panizzon
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Chandra A Reynolds
- Department of Psychology, University of California Riverside, Riverside, CA, USA
| | - Mark Sanderson-Cimino
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California, San Diego, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - William S Kremen
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA, USA; Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
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Williams ME, Gillespie NA, Bell TR, Dale AM, Elman JA, Eyler LT, Fennema-Notestine C, Franz CE, Hagler DJ, Lyons MJ, McEvoy LK, Neale MC, Panizzon MS, Reynolds CA, Sanderson-Cimino M, Kremen WS. Genetic and Environmental Influences on Structural and Diffusion-Based Alzheimer's Disease Neuroimaging Signatures Across Midlife and Early Old Age. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:918-927. [PMID: 35738479 PMCID: PMC9827615 DOI: 10.1016/j.bpsc.2022.06.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 05/04/2022] [Accepted: 06/07/2022] [Indexed: 01/27/2023]
Abstract
BACKGROUND Composite scores of magnetic resonance imaging-derived metrics in brain regions associated with Alzheimer's disease (AD), commonly termed AD signatures, have been developed to distinguish early AD-related atrophy from normal age-associated changes. Diffusion-based gray matter signatures may be more sensitive to early AD-related changes compared with thickness/volume-based signatures, demonstrating their potential clinical utility. The timing of early (i.e., midlife) changes in AD signatures from different modalities and whether diffusion- and thickness/volume-based signatures each capture unique AD-related phenotypic or genetic information remains unknown. METHODS Our validated thickness/volume signature, our novel mean diffusivity (MD) signature, and a magnetic resonance imaging-derived measure of brain age were used in biometrical analyses to examine genetic and environmental influences on the measures as well as phenotypic and genetic relationships between measures over 12 years. Participants were 736 men from 3 waves of the Vietnam Era Twin Study of Aging (VETSA) (baseline/wave 1: mean age [years] = 56.1, SD = 2.6, range = 51.1-60.2). Subsequent waves occurred at approximately 5.7-year intervals. RESULTS MD and thickness/volume signatures were highly heritable (56%-72%). Baseline MD signatures predicted thickness/volume signatures over a decade later, but baseline thickness/volume signatures showed a significantly weaker relationship with future MD signatures. AD signatures and brain age were correlated, but each measure captured unique phenotypic and genetic variance. CONCLUSIONS Cortical MD and thickness/volume AD signatures are heritable, and each signature captures unique variance that is also not explained by brain age. Moreover, results are in line with changes in MD emerging before changes in cortical thickness, underscoring the utility of MD as a very early predictor of AD risk.
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Affiliation(s)
- McKenna E Williams
- Center for Behavior Genetics of Aging, University of California San Diego, San Diego, California; Department of Psychiatry, University of California San Diego, San Diego, California; Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California San Diego, San Diego, California.
| | - Nathan A Gillespie
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, Virginia
| | - Tyler R Bell
- Center for Behavior Genetics of Aging, University of California San Diego, San Diego, California; Department of Psychiatry, University of California San Diego, San Diego, California
| | - Anders M Dale
- Department of Radiology, University of California San Diego, San Diego, California; Department of Neuroscience, University of California San Diego, San Diego, California
| | - Jeremy A Elman
- Center for Behavior Genetics of Aging, University of California San Diego, San Diego, California; Department of Psychiatry, University of California San Diego, San Diego, California
| | - Lisa T Eyler
- Desert Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare System, San Diego, California
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, San Diego, California; Department of Radiology, University of California San Diego, San Diego, California
| | - Carol E Franz
- Center for Behavior Genetics of Aging, University of California San Diego, San Diego, California; Department of Psychiatry, University of California San Diego, San Diego, California
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, San Diego, California
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts
| | - Linda K McEvoy
- Department of Radiology, University of California San Diego, San Diego, California
| | - Michael C Neale
- Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, Richmond, Virginia
| | - Matthew S Panizzon
- Center for Behavior Genetics of Aging, University of California San Diego, San Diego, California; Department of Psychiatry, University of California San Diego, San Diego, California
| | - Chandra A Reynolds
- Department of Psychology, University of California Riverside, Riverside, California
| | - Mark Sanderson-Cimino
- Center for Behavior Genetics of Aging, University of California San Diego, San Diego, California; Department of Psychiatry, University of California San Diego, San Diego, California; Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California San Diego, San Diego, California
| | - William S Kremen
- Center for Behavior Genetics of Aging, University of California San Diego, San Diego, California; Department of Psychiatry, University of California San Diego, San Diego, California
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29
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Wang L, Zhou C, Zhang W, Zhang M, Cheng W, Feng J. Association of Cortical and Subcortical Microstructure With Clinical Progression and Fluid Biomarkers in Patients With Parkinson Disease. Neurology 2023; 101:e300-e310. [PMID: 37202161 PMCID: PMC10382272 DOI: 10.1212/wnl.0000000000207408] [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: 08/09/2022] [Accepted: 03/28/2023] [Indexed: 05/20/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Mean diffusivity (MD) of diffusion MRI (dMRI) has been used to measure cortical and subcortical microstructural properties. This study investigated relationships of cortical and subcortical MD, clinical progression, and fluid biomarkers in Parkinson disease (PD). METHODS This longitudinal study using data from the Parkinson's Progression Markers Initiative was collected from April 2011 to July 2022. Clinical symptoms were assessed with Movement Disorder Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (UPDRS) and Montreal Cognitive Assessment (MoCA) scores. Clinical assessments were followed up to 5 years. Linear mixed-effects (LME) models were performed to examine associations of MD and the annual rate of changes in clinical scores. Partial correlation analysis was conducted to examine the associations of MD and fluid biomarker levels. RESULTS A total of 174 patients with PD (age 61.9 ± 9.7 years, 63% male) with baseline dMRI and at least 2 years of clinical follow-up were included. Results of LME models revealed a significant association between MD values, predominantly in subcortical regions, temporal lobe, occipital lobe, and frontal lobe, and annual rate of changes in clinical scores (UPDRS-Part-I, standardized β > 2.35; UPDRS-Part-II, standardized β > 2.34; postural instability and gait disorder score, standardized β > 2.47; MoCA, standardized β < -2.42; all p < 0.05, false discovery rate [FDR] corrected). In addition, MD was associated with the levels of neurofilament light chain in serum (r > 0.22) and α-synuclein (right putamen r = 0.31), β-amyloid 1-42 (left hippocampus r = -0.30), phosphorylated tau at 181 threonine position (r > 0.26), and total tau (r > 0.23) in CSF at baseline (all p < 0.05, FDR corrected). Furthermore, the β coefficients derived from MD and annual rate of changes in the clinical score recapitulated the spatial distribution of dopamine (DAT, D1, and D2), glutamate (mGluR5 and NMDA), serotonin (5-HT1a and 5-HT2a), cannabinoid (CB1), and γ-amino butyric acid A receptor neurotransmitter receptors/transporters (p < 0.05, FDR corrected) derived from PET scans in the brain of healthy volunteers. DISCUSSION In this cohort study, cortical and subcortical MD values at baseline were associated with clinical progression and baseline fluid biomarkers, suggesting that microstructural properties could be useful for stratification of patients with fast clinical progression.
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Affiliation(s)
- Linbo Wang
- From the Institute of Science and Technology for Brain-Inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; MOE Frontiers Center for Brain Science (L.W., W.Z., W.C., J.F.), Fudan University; Zhangjiang Fudan International Innovation Center (L.W., W.Z., W.C., J.F.), Shanghai; Department of Radiology (C.Z., M.Z.), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou; Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C.), Zhejiang Normal University, Jinhua, China; and Department of Computer Science (J.F.), University of Warwick, Coventry, United Kingdom
| | - Cheng Zhou
- From the Institute of Science and Technology for Brain-Inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; MOE Frontiers Center for Brain Science (L.W., W.Z., W.C., J.F.), Fudan University; Zhangjiang Fudan International Innovation Center (L.W., W.Z., W.C., J.F.), Shanghai; Department of Radiology (C.Z., M.Z.), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou; Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C.), Zhejiang Normal University, Jinhua, China; and Department of Computer Science (J.F.), University of Warwick, Coventry, United Kingdom
| | - Wei Zhang
- From the Institute of Science and Technology for Brain-Inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; MOE Frontiers Center for Brain Science (L.W., W.Z., W.C., J.F.), Fudan University; Zhangjiang Fudan International Innovation Center (L.W., W.Z., W.C., J.F.), Shanghai; Department of Radiology (C.Z., M.Z.), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou; Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C.), Zhejiang Normal University, Jinhua, China; and Department of Computer Science (J.F.), University of Warwick, Coventry, United Kingdom
| | - Minming Zhang
- From the Institute of Science and Technology for Brain-Inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; MOE Frontiers Center for Brain Science (L.W., W.Z., W.C., J.F.), Fudan University; Zhangjiang Fudan International Innovation Center (L.W., W.Z., W.C., J.F.), Shanghai; Department of Radiology (C.Z., M.Z.), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou; Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C.), Zhejiang Normal University, Jinhua, China; and Department of Computer Science (J.F.), University of Warwick, Coventry, United Kingdom
| | - Wei Cheng
- From the Institute of Science and Technology for Brain-Inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; MOE Frontiers Center for Brain Science (L.W., W.Z., W.C., J.F.), Fudan University; Zhangjiang Fudan International Innovation Center (L.W., W.Z., W.C., J.F.), Shanghai; Department of Radiology (C.Z., M.Z.), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou; Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C.), Zhejiang Normal University, Jinhua, China; and Department of Computer Science (J.F.), University of Warwick, Coventry, United Kingdom
| | - Jianfeng Feng
- From the Institute of Science and Technology for Brain-Inspired Intelligence (L.W., W.Z., W.C., J.F.), Fudan University; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University) (L.W., W.Z., W.C., J.F.), Ministry of Education; MOE Frontiers Center for Brain Science (L.W., W.Z., W.C., J.F.), Fudan University; Zhangjiang Fudan International Innovation Center (L.W., W.Z., W.C., J.F.), Shanghai; Department of Radiology (C.Z., M.Z.), The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou; Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence (W.C.), Zhejiang Normal University, Jinhua, China; and Department of Computer Science (J.F.), University of Warwick, Coventry, United Kingdom.
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Weston PSJ, Coath W, Harris MJ, Malone IB, Dickson J, Aigbirhio FI, Cash DM, Zhang H, Schott JM. Cortical tau is associated with microstructural imaging biomarkers of neurite density and dendritic complexity in Alzheimer's disease. Alzheimers Dement 2023; 19:2750-2754. [PMID: 36932979 PMCID: PMC10614698 DOI: 10.1002/alz.13011] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Revised: 01/20/2023] [Accepted: 01/24/2023] [Indexed: 03/19/2023]
Abstract
INTRODUCTION In Alzheimer's disease (AD), hyperphosphorylated tau is closely associated with focal neurodegeneration, but the mechanism remains uncertain. METHODS We quantified cortical microstructure using neurite orientation dispersion and density imaging in 14 individuals with young onset AD. Diffusion tensor imaging measured mean diffusivity (MD). Amyloid beta and tau positron emission tomography were acquired and associations with microstructural measures were assessed. RESULTS When regional volume was adjusted for, in the medial temporal lobe there was a significant negative association between neurite density and tau (partial R2 = 0.56, p = 0.008) and between orientation dispersion and tau (partial R2 = 0.66, p = 0.002), but not between MD and tau. In a wider cortical composite, there was an association between orientation dispersion and tau (partial R2 = 0.43, p = 0.030), but not between other measures and tau. DISCUSSION Our findings are consistent with tau causing first dendritic pruning (reducing dispersion/complexity) followed by neuronal loss. Advanced magnetic resonance imaging (MRI) microstructural measures have the potential to provide information relating to underlying tau deposition.
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Affiliation(s)
- Philip S. J. Weston
- The Dementia Research Centre, Department of Neurodegenerative DiseaseUCL Queen Square Institute of NeurologyLondonUK
- UK Dementia Research Institute at UCLUniversity College LondonLondonUK
| | - William Coath
- The Dementia Research Centre, Department of Neurodegenerative DiseaseUCL Queen Square Institute of NeurologyLondonUK
| | - Matthew J. Harris
- The Dementia Research Centre, Department of Neurodegenerative DiseaseUCL Queen Square Institute of NeurologyLondonUK
| | - Ian B. Malone
- The Dementia Research Centre, Department of Neurodegenerative DiseaseUCL Queen Square Institute of NeurologyLondonUK
| | - John Dickson
- Institute of Nuclear MedicineUniversity College London HospitalsLondonUK
| | - Franklin I. Aigbirhio
- Department of Clinical NeurosciencesUniversity of CambridgeCambridgeUK
- Wolfson Brain Imaging CentreUniversity of CambridgeCambridgeUK
| | - David M. Cash
- The Dementia Research Centre, Department of Neurodegenerative DiseaseUCL Queen Square Institute of NeurologyLondonUK
| | - Hui Zhang
- Department of Computer Science and Centre for Medical Image ComputingUniversity College LondonLondonUK
| | - Jonathan M. Schott
- The Dementia Research Centre, Department of Neurodegenerative DiseaseUCL Queen Square Institute of NeurologyLondonUK
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Nir TM, Villalón-Reina JE, Salminen L, Haddad E, Zheng H, Thomopoulos SI, Jack CR, Weiner MW, Thompson PM, Jahanshad N. Cortical microstructural associations with CSF amyloid and pTau. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.10.23288366. [PMID: 37090601 PMCID: PMC10120803 DOI: 10.1101/2023.04.10.23288366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Diffusion MRI (dMRI) can be used to probe microstructural properties of brain tissue and holds great promise as a means to non-invasively map Alzheimer's disease (AD) pathology. Few studies have evaluated multi-shell dMRI models, such as neurite orientation dispersion and density imaging (NODDI) and mean apparent propagator (MAP)-MRI, in cortical gray matter where many of the earliest histopathological changes occur in AD. Here, we investigated the relationship between CSF pTau181 and Aβ1-42 burden and regional cortical NODDI and MAP-MRI indices in 46 cognitively unimpaired individuals, 18 with mild cognitive impairment, and two with dementia (mean age: 71.8±6.2 years) from the Alzheimer's Disease Neuroimaging Initiative. We compared findings to more conventional cortical thickness measures. Lower CSF Aβ1-42 and higher pTau181 were associated with cortical dMRI measures reflecting less hindered or restricted diffusion and greater diffusivity. Cortical dMRI measures were more widely associated with Aβ1-42 than pTau181 and better distinguished Aβ+ from Aβ- participants than pTau+/- participants. Conversely, cortical thickness was more tightly linked with pTau181. dMRI associations mediated the relationship between CSF markers and delayed logical memory performance, commonly impaired in early AD. dMRI measures sensitive to early AD pathogenesis and microstructural damage may elucidate mechanisms underlying cognitive decline.
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Affiliation(s)
- Talia M. Nir
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Julio E. Villalón-Reina
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Lauren Salminen
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Elizabeth Haddad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Hong Zheng
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Sophia I. Thomopoulos
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Clifford R. Jack
- Department of Radiology, Mayo Clinic, Rochester, MN, United States
| | - Michael W. Weiner
- Department of Radiology, School of Medicine, University of California, San Francisco, San Francisco, CA, United States
| | - Paul M. Thompson
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Neda Jahanshad
- Imaging Genetics Center, Mark & Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
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32
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Sagnier S, Catheline G, Dilharreguy B, Linck PA, Coupé P, Munsch F, Bigourdan A, Poli M, Debruxelles S, Renou P, Olindo S, Rouanet F, Dousset V, Tourdias T, Sibon I. Microstructural Gray Matter Integrity Deteriorates After an Ischemic Stroke and Is Associated with Processing Speed. Transl Stroke Res 2023; 14:185-192. [PMID: 35437660 DOI: 10.1007/s12975-022-01020-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 03/25/2022] [Accepted: 04/04/2022] [Indexed: 11/26/2022]
Abstract
Microstructural changes after an ischemic stroke (IS) have mainly been described in white matter. Data evaluating microstructural changes in gray matter (GM) remain scarce. The aim of the present study was to evaluate the integrity of GM on longitudinal data using mean diffusivity (MD), and its influence on post-IS cognitive performances. A prospective study was conducted, including supra-tentorial IS patients without pre-stroke disability. A cognitive assessment was performed at baseline and 1 year, including a Montreal Cognitive Assessment, an Isaacs set test, and a Zazzo cancelation task (ZCT): completion time and number of errors. A 3-T brain MRI was performed at the same two time-points, including diffusion tensor imaging for the assessment of GM MD. GM volume was also computed, and changes in GM volume and GM MD were evaluated, followed by the assessment of the relationship between these structural changes and changes in cognitive performances. One hundred and four patients were included (age 68.5 ± 21.5, 38.5% female). While no GM volume loss was observed, GM MD increased between baseline and 1 year. The increase of GM MD in left fronto-temporal regions (dorsolateral prefrontal cortex, superior and medial temporal gyrus, p < 0.05, Threshold-Free Cluster Enhancement, 5000 permutations) was associated with an increase time to complete ZCT, regardless of demographic confounders, IS volume and location, GM, and white matter hyperintensity volume. GM integrity deterioration was thus associated with processing speed slowdown, and appears to be a biomarker of cognitive frailty. This broadens the knowledge of post-IS cognitive impairment mechanisms.
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Affiliation(s)
- Sharmila Sagnier
- UMR-5287, CNRS, Université de Bordeaux, EPHE PSL Research University, Bordeaux, France.
- Unité Neuro-Vasculaire, CHU de Bordeaux, Bordeaux, France.
- INCIA Université, Bordeaux 2, 146 rue Léo Saignat Zone Nord, Bâtiment 2A, 2e étage, 33076, Bordeaux, France.
| | - Gwenaëlle Catheline
- UMR-5287, CNRS, Université de Bordeaux, EPHE PSL Research University, Bordeaux, France
| | - Bixente Dilharreguy
- UMR-5287, CNRS, Université de Bordeaux, EPHE PSL Research University, Bordeaux, France
| | | | - Pierrick Coupé
- UMR 5800, Univ. Bordeaux, CNRS, INP, LaBRI, 33400, Talence, Bordeaux, France
| | - Fanny Munsch
- Beth Israel Deaconess Medical Center, Harvard University, Boston, USA
| | | | - Mathilde Poli
- Unité Neuro-Vasculaire, CHU de Bordeaux, Bordeaux, France
| | | | - Pauline Renou
- Unité Neuro-Vasculaire, CHU de Bordeaux, Bordeaux, France
| | | | | | - Vincent Dousset
- Neuroradiologie, CHU de Bordeaux, Bordeaux, France
- INSERM-U862, Neurocentre Magendie, Bordeaux, France
| | - Thomas Tourdias
- Neuroradiologie, CHU de Bordeaux, Bordeaux, France
- INSERM-U862, Neurocentre Magendie, Bordeaux, France
| | - Igor Sibon
- UMR-5287, CNRS, Université de Bordeaux, EPHE PSL Research University, Bordeaux, France
- Unité Neuro-Vasculaire, CHU de Bordeaux, Bordeaux, France
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Ding W, Ren P, Yi L, Si Y, Yang F, Li Z, Bao H, Yan S, Zhang X, Li S, Liang X, Yao L. Association of cortical and subcortical microstructure with disease severity: impact on cognitive decline and language impairments in frontotemporal lobar degeneration. Alzheimers Res Ther 2023; 15:58. [PMID: 36941645 PMCID: PMC10029187 DOI: 10.1186/s13195-023-01208-7] [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: 07/18/2022] [Accepted: 03/13/2023] [Indexed: 03/23/2023]
Abstract
BACKGROUND Cortical and subcortical microstructural modifications are critical to understanding the pathogenic changes in frontotemporal lobar degeneration (FTLD) subtypes. In this study, we investigated cortical and subcortical microstructure underlying cognitive and language impairments across behavioral variant of frontotemporal dementia (bvFTD), semantic variant of primary progressive aphasia (svPPA), and nonfluent variant of primary progressive aphasia (nfvPPA) subtypes. METHODS The current study characterized 170 individuals with 3 T MRI structural and diffusion-weighted imaging sequences as portion of the Frontotemporal Lobar Degeneration Neuroimaging Initiative study: 41 bvFTD, 35 nfvPPA, 34 svPPA, and 60 age-matched cognitively unimpaired controls. To determine the severity of the disease, clinical dementia rating plus national Alzheimer's coordinating center behavior and language domains sum of boxes scores were used; other clinical measures, including the Boston naming test and verbal fluency test, were also evaluated. We computed surface-based cortical thickness and cortical and subcortical microstructural metrics using tract-based spatial statistics and explored their relationships with clinical and cognitive assessments. RESULTS Compared with controls, those with FTLD showed substantial cortical mean diffusivity alterations extending outside the regions with cortical thinning. Tract-based spatial statistics revealed that anomalies in subcortical white matter diffusion were widely distributed across the frontotemporal and parietal areas. Patients with bvFTD, nfvPPA, and svPPA exhibited distinct patterns of cortical and subcortical microstructural abnormalities, which appeared to correlate with disease severity, and separate dimensions of language functions. CONCLUSIONS Our findings imply that cortical and subcortical microstructures may serve as sensitive biomarkers for the investigation of neurodegeneration-associated microstructural alterations in FTLD subtypes. Flowchart of the study design (see materials and methods for detailed description).
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Affiliation(s)
- Wencai Ding
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China
| | - Peng Ren
- Laboratory for Space Environment and Physical Science, Harbin Institute of Technology, Harbin, 150001, China
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, 150001, China
| | - Liye Yi
- Department of Neurosurgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, 150001, China
| | - Yao Si
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China
| | - Fan Yang
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China
| | - Zhipeng Li
- Laboratory for Space Environment and Physical Science, Harbin Institute of Technology, Harbin, 150001, China
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, 150001, China
| | - Hongbo Bao
- Department of Neurosurgery, Harbin Medical University Cancer Hospital, Harbin, 150001, China
| | - Shi Yan
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China
| | - Xinyu Zhang
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China
| | - Siyang Li
- Laboratory for Space Environment and Physical Science, Harbin Institute of Technology, Harbin, 150001, China
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, 150001, China
| | - Xia Liang
- Laboratory for Space Environment and Physical Science, Harbin Institute of Technology, Harbin, 150001, China.
- School of Life Science and Technology, Harbin Institute of Technology, Harbin, 150001, China.
| | - Lifen Yao
- Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, 150001, China.
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Malakshan SR, Daneshvarfard F, Abrishami Moghaddam H. A correlational study between microstructural, macrostructural and functional age-related changes in the human visual cortex. PLoS One 2023; 18:e0266206. [PMID: 36662780 PMCID: PMC9858032 DOI: 10.1371/journal.pone.0266206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 12/27/2022] [Indexed: 01/21/2023] Open
Abstract
Age-related changes in the human brain can be investigated from either structural or functional perspectives. Analysis of structural and functional age-related changes throughout the lifespan may help to understand the normal brain development process and monitor the structural and functional pathology of the brain. This study, combining dedicated electroencephalography (EEG) and magnetic resonance imaging (MRI) approaches in adults (20-78 years), highlights the complex relationship between micro/macrostructural properties and the functional responses to visual stimuli. Here, we aimed to relate age-related changes of the latency of visual evoked potentials (VEPs) to micro/macrostructural indexes and find any correlation between micro/macrostructural features, as well. We studied age-related structural changes in the brain, by using the MRI and diffusion-weighted imaging (DWI) as preferred imaging methods for extracting brain macrostructural parameters such as the cortical thickness, surface area, folding and curvature index, gray matter volume, and microstructural parameters such as mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD). All the mentioned features were significantly correlated with age in V1 and V2 regions of the visual cortex. Furthermore, we highlighted, negative correlations between structural features extracted from T1-weighted images and DWI. The latency and amplitude of the three dominants peaks (C1, P1, N1) of the VEP were considered as the brain functional features to be examined for correlation with age and structural features of the corresponding age. We observed significant correlations between mean C1 latency and GM volume averaged in V1 and V2. In hierarchical regression analysis, the structural index did not contribute to significant variance in the C1 latency after regressing out the effect of age. However, the age explained significant variance in the model after regressing out the effect of structural feature.
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Affiliation(s)
- Sahar Rahimi Malakshan
- Faculty of Electrical Engineering, Department of Biomedical Engineering, K.N. Toosi University of Technology, Tehran, Iran
| | - Farveh Daneshvarfard
- Faculty of Electrical Engineering, Department of Biomedical Engineering, K.N. Toosi University of Technology, Tehran, Iran
- INSERM U1105, Université de Picardie, CURS, Amiens, France
| | - Hamid Abrishami Moghaddam
- Faculty of Electrical Engineering, Department of Biomedical Engineering, K.N. Toosi University of Technology, Tehran, Iran
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Giraldo DL, Smith RE, Struyfs H, Niemantsverdriet E, De Roeck E, Bjerke M, Engelborghs S, Romero E, Sijbers J, Jeurissen B. Investigating Tissue-Specific Abnormalities in Alzheimer's Disease with Multi-Shell Diffusion MRI. J Alzheimers Dis 2022; 90:1771-1791. [PMID: 36336929 PMCID: PMC9789487 DOI: 10.3233/jad-220551] [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] [Indexed: 12/12/2022]
Abstract
BACKGROUND Most studies using diffusion-weighted MRI (DW-MRI) in Alzheimer's disease (AD) have focused their analyses on white matter (WM) microstructural changes using the diffusion (kurtosis) tensor model. Although recent works have addressed some limitations of the tensor model, such as the representation of crossing fibers and partial volume effects with cerebrospinal fluid (CSF), the focus remains in modeling and analyzing the WM. OBJECTIVE In this work, we present a brain analysis approach for DW-MRI that disentangles multiple tissue compartments as well as micro- and macroscopic effects to investigate differences between groups of subjects in the AD continuum and controls. METHODS By means of the multi-tissue constrained spherical deconvolution of multi-shell DW-MRI, underlying brain tissue is modeled with a WM fiber orientation distribution function along with the contributions of gray matter (GM) and CSF to the diffusion signal. From this multi-tissue model, a set of measures capturing tissue diffusivity properties and morphology are extracted. Group differences were interrogated following fixel-, voxel-, and tensor-based morphometry approaches while including strong FWE control across multiple comparisons. RESULTS Abnormalities related to AD stages were detected in WM tracts including the splenium, cingulum, longitudinal fasciculi, and corticospinal tract. Changes in tissue composition were identified, particularly in the medial temporal lobe and superior longitudinal fasciculus. CONCLUSION This analysis framework constitutes a comprehensive approach allowing simultaneous macro and microscopic assessment of WM, GM, and CSF, from a single DW-MRI dataset.
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Affiliation(s)
- Diana L. Giraldo
- Computer Imaging and Medical Applications Laboratory - Cim@Lab, Universidad Nacional de Colombia, Bogotá, Colombia,imec-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium,μNEURO Research Center of Excellence, University of Antwerp, Antwerp, Belgium
| | - Robert E. Smith
- The Florey Institute of Neuroscience and Mental Health, Heidelberg, VIC, Australia,The Florey Department of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, Australia
| | - Hanne Struyfs
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Ellis Niemantsverdriet
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Ellen De Roeck
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium,Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium
| | - Maria Bjerke
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium,Laboratory of Neurochemistry, Department of Clinical Chemistry, and Center for Neurosciences (C4N), Universitair Ziekenhuis Brussel, Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium,Department of Neurology, and Center for Neurosciences (C4N), Universitair Ziekenhuis Brussel, Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Eduardo Romero
- Computer Imaging and Medical Applications Laboratory - Cim@Lab, Universidad Nacional de Colombia, Bogotá, Colombia
| | - Jan Sijbers
- imec-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium,μNEURO Research Center of Excellence, University of Antwerp, Antwerp, Belgium
| | - Ben Jeurissen
- imec-Vision Lab, Department of Physics, University of Antwerp, Antwerp, Belgium,μNEURO Research Center of Excellence, University of Antwerp, Antwerp, Belgium,Lab for Equilibrium Investigations and Aerospace, Department of Physics, University of Antwerp, Antwerp, Belgium,Correspondence to: Ben Jeurissen, PhD, imec - Vision Lab, Department of Physics, University of Antwerp (CDE), Universiteitsplein 1, Building N, 2610 Antwerp, Belgium. Tel.: +32 3 265 24 77; E-mail:
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36
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Sampedro F, Puig-Davi A, Martinez-Horta S, Pagonabarraga J, Horta-Barba A, Aracil-Bolaños I, Kulisevsky J. Cortical macro and microstructural correlates of cognitive and neuropsychiatric symptoms in Parkinson's disease. Clin Neurol Neurosurg 2022; 224:107531. [PMID: 36455303 DOI: 10.1016/j.clineuro.2022.107531] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Accepted: 11/17/2022] [Indexed: 11/22/2022]
Abstract
BACKGROUND Cognitive and neuropsychiatric disturbances in Parkinson's disease are as common and as disabling as its well-known motor symptoms. Even though several neural substrates for these symptoms have been suggested, to which extent these symptoms reflect cortical neurodegeneration in Parkinson's disease remains to be fully elucidated. METHODS In a representative sample of 44 Parkinson's disease patients, the data about the following symptoms was recorded: cognitive performance, apathy, depression and anxiety. Surface-based vertexwise multiple regression analyses were performed to investigate the cortical macro (cortical thinning) and microstructural (increased intracortical diffusivity) correlates of each symptom. A group of 18 healthy controls with similar sociodemographics was also included to assess the disease specificity of the neuroimaging results. RESULTS Compared to healthy controls, Parkinson's disease patients showed significantly increased scores in all the considered non-motor scales (p < 0.01). Within the Parkinson's disease group, increased scores in these scales were associated with cortical macro- and microstructural neurodegeneration (p < 0.05 corrected). Each of the considered non-motor scales was associated with a specific pattern of cortical degeneration. When observing both neuroimaging techniques, intracortical diffusivity revealed similar but extensive patterns of cortical compromise than cortical thickness for each symptom, with the exception of anxiety. CONCLUSIONS Cognitive and neuropsychiatric symptoms in Parkinson's disease reflect cortical degeneration. Increases in intracortical diffusivity were able to detect symptom-specific cortical microstructural damage in the absence of cortical thinning. A better understanding of this association may contribute to characterize the brain circuitry and the neurotransmitter pathways underlying these highly prevalent and debilitating symptoms in Parkinson's disease.
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Affiliation(s)
- Frederic Sampedro
- Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain; Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain; Centro de Investigación en Red-Enfermedades Neurodegenerativas (CIBERNED), Spain; Radiology Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - Arnau Puig-Davi
- Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain; Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain; Centro de Investigación en Red-Enfermedades Neurodegenerativas (CIBERNED), Spain; Institute of Neurosciences, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain
| | - Saul Martinez-Horta
- Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain; Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain; Centro de Investigación en Red-Enfermedades Neurodegenerativas (CIBERNED), Spain
| | - Javier Pagonabarraga
- Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain; Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain; Centro de Investigación en Red-Enfermedades Neurodegenerativas (CIBERNED), Spain
| | - Andrea Horta-Barba
- Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain; Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain; Centro de Investigación en Red-Enfermedades Neurodegenerativas (CIBERNED), Spain; Department of Medicine, Universitat Autònoma de Barcelona (UAB), Barcelona, Spain; Faculty of Health Sciences, Universitat Oberta de Catalunya (UOC), Barcelona, Spain
| | - Ignacio Aracil-Bolaños
- Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain; Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain; Centro de Investigación en Red-Enfermedades Neurodegenerativas (CIBERNED), Spain
| | - Jaime Kulisevsky
- Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain; Biomedical Research Institute (IIB-Sant Pau), Barcelona, Spain; Centro de Investigación en Red-Enfermedades Neurodegenerativas (CIBERNED), Spain.
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Wang WE, Chen R, Mayrand RP, Adjouadi M, Fang R, DeKosky ST, Duara R, Coombes SA, Vaillancourt DE. Association of Longitudinal Cognitive Decline with Diffusion MRI in Gray Matter, Amyloid, and Tau Deposition. Neurobiol Aging 2022; 121:166-178. [DOI: 10.1016/j.neurobiolaging.2022.10.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Revised: 10/21/2022] [Accepted: 10/25/2022] [Indexed: 11/06/2022]
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38
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Nakaya M, Sato N, Matsuda H, Maikusa N, Shigemoto Y, Sone D, Yamao T, Ogawa M, Kimura Y, Chiba E, Ohnishi M, Kato K, Okita K, Tsukamoto T, Yokoi Y, Sakata M, Abe O. Free water derived by multi-shell diffusion MRI reflects tau/neuroinflammatory pathology in Alzheimer's disease. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2022; 8:e12356. [PMID: 36304723 PMCID: PMC9594557 DOI: 10.1002/trc2.12356] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 08/03/2022] [Accepted: 08/20/2022] [Indexed: 11/23/2022]
Abstract
INTRODUCTION Free-water (FW) imaging, a new analysis method for diffusion magnetic resonance imaging (MRI), can indicate neuroinflammation and degeneration. We evaluated FW in Alzheimer's disease (AD) using tau/inflammatory and amyloid positron emission tomography (PET). METHODS Seventy-one participants underwent multi-shell diffusion MRI, 18F-THK5351 PET, 11C-Pittsburgh compound B PET, and neuropsychological assessments. They were categorized into two groups: healthy controls (HCs) (n = 40) and AD-spectrum group (AD-S) (n = 31) using the Centiloid scale with amyloid PET and cognitive function. We analyzed group comparisons in FW and PET, correlations between FW and PET, and correlation analysis with neuropsychological scores. RESULTS In AD-S group, there was a significant positive correlation between FW and 18F-THK5351 in the temporal lobes. In addition, there were negative correlations between FW and cognitive function in the temporal lobe and cingulate gyrus, and negative correlations between 18F-THK5351 and cognitive function in the same regions. DISCUSSION FW imaging could be a biomarker for tau in AD alongside clinical correlations.
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Affiliation(s)
- Moto Nakaya
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan,Department of RadiologyGraduate School of MedicineUniversity of TokyoHongoBunkyo‐kuTokyoJapan
| | - Noriko Sato
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Hiroshi Matsuda
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan,Drug Discovery and Cyclotron Research CenterSouthern TOHOKU Research Institute for NeuroscienceKoriyamaJapan
| | - Norihide Maikusa
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Yoko Shigemoto
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Daichi Sone
- Department of PsychiatryThe Jikei University School of MedicineTokyoJapan,Integrative Brain Imaging CenterNational Center of Neurology and PsychiatryTokyoJapan
| | - Tensho Yamao
- Department of Radiological SciencesSchool of Health SciencesFukushima Medical UniversityFukushimaJapan
| | - Masayo Ogawa
- Integrative Brain Imaging CenterNational Center of Neurology and PsychiatryTokyoJapan
| | - Yukio Kimura
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Emiko Chiba
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Masahiro Ohnishi
- Departmentof RadiologyNational Center Hospital of Neurology and PsychiatryOgawa‐HigashiKodairaTokyoJapan
| | - Koichi Kato
- Integrative Brain Imaging CenterNational Center of Neurology and PsychiatryTokyoJapan
| | - Kyoji Okita
- Integrative Brain Imaging CenterNational Center of Neurology and PsychiatryTokyoJapan
| | - Tadashi Tsukamoto
- Department of NeurologyNational Center of Neurology and PsychiatryKodairaTokyoJapan
| | - Yuma Yokoi
- Department of PsychiatryNational Center of Neurology and PsychiatryKodairaTokyoJapan
| | - Masuhiro Sakata
- Department of PsychiatryNational Center of Neurology and PsychiatryKodairaTokyoJapan
| | - Osamu Abe
- Department of RadiologyGraduate School of MedicineUniversity of TokyoHongoBunkyo‐kuTokyoJapan
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Elman JA, Puckett OK, Hagler DJ, Pearce RC, Fennema-Notestine C, Hatton SN, Lyons MJ, McEvoy LK, Panizzon MS, Reas ET, Dale AM, Franz CE, Kremen WS. Associations between MRI-assessed locus coeruleus integrity and cortical gray matter microstructure. Cereb Cortex 2022; 32:4191-4203. [PMID: 34969072 PMCID: PMC9528780 DOI: 10.1093/cercor/bhab475] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Revised: 11/17/2021] [Accepted: 11/22/2021] [Indexed: 01/27/2023] Open
Abstract
The locus coeruleus (LC) is one of the earliest sites of tau pathology, making it a key structure in early Alzheimer's disease (AD) progression. As the primary source of norepinephrine for the brain, reduced LC integrity may have negative consequences for brain health, yet macrostructural brain measures (e.g. cortical thickness) may not be sensitive to early stages of neurodegeneration. We therefore examined whether LC integrity was associated with differences in cortical gray matter microstructure among 435 men (mean age = 67.5; range = 62-71.7). LC structural integrity was indexed by contrast-to-noise ratio (LCCNR) from a neuromelanin-sensitive MRI scan. Restriction spectrum imaging (RSI), an advanced multi-shell diffusion technique, was used to characterize cortical microstructure, modeling total diffusion in restricted, hindered, and free water compartments. Higher LCCNR (greater integrity) was associated with higher hindered and lower free water diffusion in multiple cortical regions. In contrast, no associations between LCCNR and cortical thickness survived correction. Results suggest lower LC integrity is associated with patterns of cortical microstructure that may reflect a reduction in cytoarchitectural barriers due to broader neurodegenerative processes. These findings highlight the potential utility for LC imaging and advanced diffusion measures of cortical microstructure in assessing brain health and early identification of neurodegenerative processes.
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Affiliation(s)
- Jeremy A Elman
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
| | - Olivia K Puckett
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
| | - Donald J Hagler
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
| | - Rahul C Pearce
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
| | - Christine Fennema-Notestine
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
| | - Sean N Hatton
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Department of Neurosciences, University of California San Diego, La Jolla, CA 92093, USA
| | - Michael J Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA 02215, USA
| | - Linda K McEvoy
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA 92093, USA
| | - Matthew S Panizzon
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
| | - Emilie T Reas
- Department of Neurosciences, University of California San Diego, La Jolla, CA 92093, USA
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, CA 92093, USA
- Department of Neurosciences, University of California San Diego, La Jolla, CA 92093, USA
| | - Carol E Franz
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
| | - William S Kremen
- Department of Psychiatry, University of California San Diego, La Jolla, CA 92093, USA
- Center for Behavior Genetics of Aging, University of California San Diego, La Jolla, CA 92093, USA
- Center of Excellence for Stress and Mental Health, VA San Diego Health Care System, La Jolla, CA 92161, USA
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40
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Longitudinal associations of absolute versus relative moderate-to-vigorous physical activity with brain microstructural decline in aging. Neurobiol Aging 2022; 116:25-31. [PMID: 35544996 PMCID: PMC9177705 DOI: 10.1016/j.neurobiolaging.2022.04.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Revised: 04/08/2022] [Accepted: 04/09/2022] [Indexed: 11/21/2022]
Abstract
Higher moderate-to-vigorous intensity (MVPA) may preserve brain structural integrity, but evidence is mostly cross-sectional and relies on absolute PA measures. We examined longitudinal associations of absolute MVPA using population-level activity count thresholds and relative MVPA using individual heart rate reserve (HRR) via Actiheart with subsequent changes in brain diffusion tensor imaging (DTI) over average of 3.8 years in 248 initially cognitively normal individuals (56-91 years). DTI markers included areas important for memory (temporal areas), executive (prefrontal cortex, superior longitudinal fasciculus), and motor function (precentral gyrus, putamen, caudate, body of corpus callosum). Associations of MVPA with changes in DTI markers were examined using linear mixed-effects models, adjusted for demographics and apolipoprotein e4 carrier status. Each additional 22 min of relative MVPA per day was significantly associated with less decline in fractional anisotropy of uncinate fasciculus and cingulum-hippocampal part and with less increase in mean diffusivity of entorhinal cortex and parahippocampal gyrus. Absolute MVPA was not associated with DTI changes. More time spent in relative MVPA by HRR may prevent brain microstructural decline in selected temporal areas.
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41
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Wei L, Ding M, Zhang Y, Wang H. Decoding transcriptional signatures of the association between free water and macroscale organizations in healthy adolescents. Neuroimage 2022; 261:119514. [PMID: 35901916 DOI: 10.1016/j.neuroimage.2022.119514] [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: 01/04/2022] [Revised: 07/11/2022] [Accepted: 07/22/2022] [Indexed: 11/16/2022] Open
Abstract
We leveraged a novel index of diffusion MRI to investigate the relationships among cortical free water, macro-organizations and gene expression in healthy adults. Few research has been conducted to investigate the role of free water in the healthy adults due to it can easily be affected also by aging diseases. High quality data of 350 subjects from Human Connectome Project were used in our study. Cortical free water was estimated by using a bi-tensor model. The free water was high in the limbic, insular and somatosensory cortex, while being lower in motor and association cortex. The negative correlation between the free water and cortical thickness has been consistently identified in almost all the cortical regions. Negative correlation between the cortical free water and structural covariance (rho=-0.38, pspin=0.005) revealed the free water was sensitive to cortical heterogeneity. Using human gene expression dataset, we found the gene expression pattern of the relationship between the free water and cortical thickness spatially coupled with primary gradient of structural covariance network (rho=0.40, pspin=0.004). Our findings indicated the free water was sensitive to the cortical cellular status. The relationship between free water and macroscale organization also reflected hierarchal structures of cerebral cortex.
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Affiliation(s)
- Lei Wei
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China.
| | - Ming Ding
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China
| | - Yuwen Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China
| | - He Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, PR China; Human Phenome Institute, Fudan University, Shanghai, PR China; Department of Neurology, Zhongshan Hospital, Fudan University, Shanghai, PR China.
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42
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Kim H, Devanand DP, Carlson S, Goldberg TE. Apolipoprotein E Genotype e2: Neuroprotection and Its Limits. Front Aging Neurosci 2022; 14:919712. [PMID: 35912085 PMCID: PMC9329577 DOI: 10.3389/fnagi.2022.919712] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 06/09/2022] [Indexed: 11/21/2022] Open
Abstract
In this review, we comprehensively, qualitatively, and critically synthesized several features of APOE-e2, a known APOE protective variant, including its associations with longevity, cognition, and neuroimaging, and neuropathology, all in humans. If e2’s protective effects—and their limits—could be elucidated, it could offer therapeutic windows for Alzheimer’s disease (AD) prevention or amelioration. Literature examining e2 within the years 1994–2021 were considered for this review. Studies on human subjects were selectively reviewed and were excluded if observation of e2 was not specified. Effects of e2 were compared with e3 and e4, separately and as a combined non-e2 group. Our examination of existing literature indicated that the most robust protective role of e2 is in longevity and AD neuropathologies, but e2’s effect on cognition and other AD imaging markers (brain structure, function, and metabolism) were inconsistent, thus inconclusive. Notably, e2 was associated with greater risk of non-AD proteinopathies and a disadvantageous cerebrovascular profile. We identified multiple methodological shortcomings of the literature on brain function and cognition that could have contributed to inconsistent and potentially misleading findings. We make careful interpretations of existing findings and provide directions for research strategies that could effectively examine the independent and unbiased effect of e2 on AD risk.
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Affiliation(s)
- Hyun Kim
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, United States
- Department of Geriatric Psychiatry, New York State Psychiatric Institute, New York, NY, United States
| | - Davangere P. Devanand
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, United States
- Department of Geriatric Psychiatry, New York State Psychiatric Institute, New York, NY, United States
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, United States
| | - Scott Carlson
- Department of Geriatric Psychiatry, New York State Psychiatric Institute, New York, NY, United States
| | - Terry E. Goldberg
- Department of Psychiatry, Columbia University Irving Medical Center, New York, NY, United States
- Department of Geriatric Psychiatry, New York State Psychiatric Institute, New York, NY, United States
- Department of Anesthesiology, Columbia University Irving Medical Center, New York, NY, United States
- *Correspondence: Terry E. Goldberg,
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43
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Shahid SS, Wen Q, Risacher SL, Farlow MR, Unverzagt FW, Apostolova LG, Foroud TM, Zetterberg H, Blennow K, Saykin AJ, Wu YC. Hippocampal-subfield microstructures and their relation to plasma biomarkers in Alzheimer's disease. Brain 2022; 145:2149-2160. [PMID: 35411392 PMCID: PMC9630875 DOI: 10.1093/brain/awac138] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 03/24/2022] [Accepted: 03/29/2022] [Indexed: 11/14/2022] Open
Abstract
Hippocampal subfields exhibit differential vulnerabilities to Alzheimer's disease-associated pathology including abnormal accumulation of amyloid-β deposition and neurofibrillary tangles. These pathological processes extensively impact on the structural and functional interconnectivities of the subfields and may explain the association between hippocampal dysfunction and cognitive deficits. In this study, we investigated the degree of alterations in the microstructure of hippocampal subfields across the clinical continuum of Alzheimer's disease. We applied a grey matter-specific multi-compartment diffusion model (Cortical-Neurite orientation dispersion and density imaging) to understand the differential effects of Alzheimer's disease pathology on the hippocampal subfield microstructure. A total of 119 participants were included in this cross-sectional study. Participants were stratified into three categories, cognitively normal (n = 47), mild cognitive impairment (n = 52), and Alzheimer's disease (n = 19). Diffusion MRI, plasma biomarkers and neuropsychological test scores were used to determine the association between the microstructural integrity and Alzheimer's disease-associated molecular indicators and cognition. For Alzheimer's disease-related plasma biomarkers, we studied amyloid-β, total tau and neurofilament light; for Alzheimer's disease-related neuropsychological tests, we included the Trail Making Test, Rey Auditory Verbal Learning Test, Digit Span and Montreal Cognitive Assessment. Comparisons between cognitively normal subjects and those with mild cognitive impairment showed significant microstructural alterations in the hippocampal cornu ammonis (CA) 4 and dentate gyrus region, whereas CA 1-3 was the most sensitive region for the later stages in the Alzheimer's disease clinical continuum. Among imaging metrics for microstructures, the volume fraction of isotropic diffusion for interstitial free water demonstrated the largest effect size in between-group comparisons. Regarding the plasma biomarkers, neurofilament light appeared to be the most sensitive biomarker for associations with microstructural imaging findings in CA4-dentate gyrus. CA 1-3 was the subfield which had stronger correlations between cognitive performance and microstructural metrics. Particularly, poor performance on the Rey Auditory Verbal Learning Test and Montreal Cognitive Assessment was associated with decreased intracellular volume fraction. Overall, our findings support the value of tissue-specific microstructural imaging for providing pathologically relevant information manifesting in the plasma biomarkers and neuropsychological outcomes across various stages of Alzheimer's disease.
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Affiliation(s)
- Syed Salman Shahid
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Qiuting Wen
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Shannon L Risacher
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Stark Neuroscience Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Martin R Farlow
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Stark Neuroscience Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Frederick W Unverzagt
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Liana G Apostolova
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Stark Neuroscience Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Tatiana M Foroud
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Stark Neuroscience Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Andrew J Saykin
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Stark Neuroscience Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Yu Chien Wu
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Stark Neuroscience Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
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Illán-Gala I, Montal V, Borrego-Écija S, Mandelli ML, Falgàs N, Welch AE, Pegueroles J, Santos-Santos M, Bejanin A, Alcolea D, Dols-Icardo O, Belbin O, Sánchez-Saudinós MB, Bargalló N, González-Ortiz S, Lladó A, Blesa R, Dickerson BC, Rosen HJ, Miller BL, Lleó A, Gorno-Tempini ML, Sánchez-Valle R, Fortea J. Cortical microstructure in primary progressive aphasia: a multicenter study. Alzheimers Res Ther 2022; 14:27. [PMID: 35139897 PMCID: PMC8830043 DOI: 10.1186/s13195-022-00974-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 02/02/2022] [Indexed: 02/06/2023]
Abstract
BACKGROUND Cortical mean diffusivity is a novel imaging metric sensitive to early changes in neurodegenerative syndromes. Higher cortical mean diffusivity values reflect microstructural disorganization and have been proposed as a sensitive biomarker that might antedate macroscopic cortical changes. We aimed to test the hypothesis that cortical mean diffusivity is more sensitive than cortical thickness to detect cortical changes in primary progressive aphasia (PPA). METHODS In this multicenter, case-control study, we recruited 120 patients with PPA (52 non-fluent, 31 semantic, and 32 logopenic variants; and 5 GRN-related PPA) as well as 89 controls from three centers. The 3-Tesla MRI protocol included structural and diffusion-weighted sequences. Disease severity was assessed with the Clinical Dementia Rating scale. Cortical thickness and cortical mean diffusivity were computed using a surface-based approach. RESULTS The comparison between each PPA variant and controls revealed cortical mean diffusivity increases and cortical thinning in overlapping regions, reflecting the canonical loci of neurodegeneration of each variant. Importantly, cortical mean diffusivity increases also expanded to other PPA-related areas and correlated with disease severity in all PPA groups. Cortical mean diffusivity was also increased in patients with very mild PPA when only minimal cortical thinning was observed and showed a good correlation with measures of disease severity. CONCLUSIONS Cortical mean diffusivity shows promise as a sensitive biomarker for the study of the neurodegeneration-related microstructural changes in PPA.
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Affiliation(s)
- Ignacio Illán-Gala
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Sant Antoni Maria Claret, 167, 08025, Barcelona, Spain.
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Barcelona, Spain.
- Atlantic Fellow for Equity in Brain Health at the University of California San Francisco, San Francisco, CA, 94115, USA.
| | - Victor Montal
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Sant Antoni Maria Claret, 167, 08025, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Barcelona, Spain
| | - Sergi Borrego-Écija
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Barcelona, Spain
- Alzheimer's Disease and Other Cognitive Disorders Unit, Service of Neurology, Hospital Clínic de Barcelona, Institut d'Investigació Biomèdica August Pi i Sunyer, University of Barcelona, 08036, Barcelona, Spain
| | - Maria Luisa Mandelli
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, 94115, USA
| | - Neus Falgàs
- Atlantic Fellow for Equity in Brain Health at the University of California San Francisco, San Francisco, CA, 94115, USA
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, 94115, USA
| | - Ariane E Welch
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, 94115, USA
| | - Jordi Pegueroles
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Sant Antoni Maria Claret, 167, 08025, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Barcelona, Spain
| | - Miguel Santos-Santos
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Sant Antoni Maria Claret, 167, 08025, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Barcelona, Spain
| | - Alexandre Bejanin
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Sant Antoni Maria Claret, 167, 08025, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Barcelona, Spain
| | - Daniel Alcolea
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Sant Antoni Maria Claret, 167, 08025, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Barcelona, Spain
| | - Oriol Dols-Icardo
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Sant Antoni Maria Claret, 167, 08025, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Barcelona, Spain
| | - Olivia Belbin
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Sant Antoni Maria Claret, 167, 08025, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Barcelona, Spain
| | - Mª Belén Sánchez-Saudinós
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Sant Antoni Maria Claret, 167, 08025, Barcelona, Spain
| | - Nuria Bargalló
- Radiology Department, Hospital Clinic Barcelona and Magnetic Resonance Image Core facility, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | | | - Albert Lladó
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Barcelona, Spain
- Alzheimer's Disease and Other Cognitive Disorders Unit, Service of Neurology, Hospital Clínic de Barcelona, Institut d'Investigació Biomèdica August Pi i Sunyer, University of Barcelona, 08036, Barcelona, Spain
| | - Rafael Blesa
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Sant Antoni Maria Claret, 167, 08025, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Barcelona, Spain
| | - Bradford C Dickerson
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Massachusetts Alzheimer's Disease Research Center, Boston, MA, USA
| | - Howard J Rosen
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, 94115, USA
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, 94115, USA
| | - Alberto Lleó
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Sant Antoni Maria Claret, 167, 08025, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Barcelona, Spain
| | - Maria Luisa Gorno-Tempini
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, 94115, USA
| | - Raquel Sánchez-Valle
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Barcelona, Spain
- Alzheimer's Disease and Other Cognitive Disorders Unit, Service of Neurology, Hospital Clínic de Barcelona, Institut d'Investigació Biomèdica August Pi i Sunyer, University of Barcelona, 08036, Barcelona, Spain
| | - Juan Fortea
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Sant Antoni Maria Claret, 167, 08025, Barcelona, Spain.
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Barcelona, Spain.
- Barcelona Down Medical Center. Fundació Catalana de Síndrome de Down, Barcelona, Spain.
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Porat S, Sibilia F, Yoon J, Shi Y, Dahl MJ, Werkle-Bergner M, Düzel S, Bodammer N, Lindenberger U, Kühn S, Mather M. Age Differences in Diffusivity in the Locus Coeruleus and its Ascending Noradrenergic Tract. Neuroimage 2022; 251:119022. [PMID: 35192943 PMCID: PMC9183949 DOI: 10.1016/j.neuroimage.2022.119022] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 02/16/2022] [Accepted: 02/17/2022] [Indexed: 12/11/2022] Open
Abstract
The noradrenergic locus coeruleus (LC) is a small brainstem nucleus that promotes arousal and attention. Recent studies have examined the microstructural properties of the LC using diffusion-weighted magnetic resonance imaging and found unexpected age-related differences in fractional anisotropy - a measure of white matter integrity. Here, we used two datasets (Berlin Aging Study-II, N = 301, the Leipzig Study for Mind-Body-Emotion Interactions, N = 220), to replicate published findings and expand them by investigating diffusivity in the LC’s ascending noradrenergic bundle. In younger adults, LC fractional anisotropy was significantly lower, compared to older adults. However, in the LC’s ascending noradrenergic bundle, we observed significantly higher fractional anisotropy in younger adults, relative to older adults. These findings indicate that diffusivity in the LC versus the ascending noradrenergic bundle are both susceptible to structural changes in aging that have opposing effects on fractional anisotropy.
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Reyes-Leiva D, Dols-Icardo O, Sirisi S, Cortés-Vicente E, Turon-Sans J, de Luna N, Blesa R, Belbin O, Montal V, Alcolea D, Fortea J, Lleó A, Rojas-García R, Illán-Gala I. Pathophysiological Underpinnings of Extra-Motor Neurodegeneration in Amyotrophic Lateral Sclerosis: New Insights From Biomarker Studies. Front Neurol 2022; 12:750543. [PMID: 35115992 PMCID: PMC8804092 DOI: 10.3389/fneur.2021.750543] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 12/09/2021] [Indexed: 11/13/2022] Open
Abstract
Amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) lie at opposing ends of a clinical, genetic, and neuropathological continuum. In the last decade, it has become clear that cognitive and behavioral changes in patients with ALS are more frequent than previously recognized. Significantly, these non-motor features can impact the diagnosis, prognosis, and management of ALS. Partially overlapping neuropathological staging systems have been proposed to describe the distribution of TAR DNA-binding protein 43 (TDP-43) aggregates outside the corticospinal tract. However, the relationship between TDP-43 inclusions and neurodegeneration is not absolute and other pathophysiological processes, such as neuroinflammation (with a prominent role of microglia), cortical hyperexcitability, and synaptic dysfunction also play a central role in ALS pathophysiology. In the last decade, imaging and biofluid biomarker studies have revealed important insights into the pathophysiological underpinnings of extra-motor neurodegeneration in the ALS-FTLD continuum. In this review, we first summarize the clinical and pathophysiological correlates of extra-motor neurodegeneration in ALS. Next, we discuss the diagnostic and prognostic value of biomarkers in ALS and their potential to characterize extra-motor neurodegeneration. Finally, we debate about how biomarkers could improve the diagnosis and classification of ALS. Emerging imaging biomarkers of extra-motor neurodegeneration that enable the monitoring of disease progression are particularly promising. In addition, a growing arsenal of biofluid biomarkers linked to neurodegeneration and neuroinflammation are improving the diagnostic accuracy and identification of patients with a faster progression rate. The development and validation of biomarkers that detect the pathological aggregates of TDP-43 in vivo are notably expected to further elucidate the pathophysiological underpinnings of extra-motor neurodegeneration in ALS. Novel biomarkers tracking the different aspects of ALS pathophysiology are paving the way to precision medicine approaches in the ALS-FTLD continuum. These are essential steps to improve the diagnosis and staging of ALS and the design of clinical trials testing novel disease-modifying treatments.
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Affiliation(s)
- David Reyes-Leiva
- Neuromuscular Diseases Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras, CIBERER, Valencia, Spain
| | - Oriol Dols-Icardo
- Sant Pau Memory Unit, Department of Neurology, Biomedical Research Institute Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Sonia Sirisi
- Sant Pau Memory Unit, Department of Neurology, Biomedical Research Institute Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Elena Cortés-Vicente
- Neuromuscular Diseases Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras, CIBERER, Valencia, Spain
| | - Janina Turon-Sans
- Neuromuscular Diseases Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras, CIBERER, Valencia, Spain
| | - Noemi de Luna
- Neuromuscular Diseases Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras, CIBERER, Valencia, Spain
| | - Rafael Blesa
- Sant Pau Memory Unit, Department of Neurology, Biomedical Research Institute Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Olivia Belbin
- Sant Pau Memory Unit, Department of Neurology, Biomedical Research Institute Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Victor Montal
- Sant Pau Memory Unit, Department of Neurology, Biomedical Research Institute Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Daniel Alcolea
- Sant Pau Memory Unit, Department of Neurology, Biomedical Research Institute Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Juan Fortea
- Sant Pau Memory Unit, Department of Neurology, Biomedical Research Institute Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Alberto Lleó
- Sant Pau Memory Unit, Department of Neurology, Biomedical Research Institute Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Ricard Rojas-García
- Neuromuscular Diseases Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras, CIBERER, Valencia, Spain
| | - Ignacio Illán-Gala
- Sant Pau Memory Unit, Department of Neurology, Biomedical Research Institute Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
- *Correspondence: Ignacio Illán-Gala
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Ochi R, Plitman E, Patel R, Tarumi R, Iwata Y, Tsugawa S, Kim J, Honda S, Noda Y, Uchida H, Devenyi GA, Mimura M, Graff-Guerrero A, Chakravarty MM, Nakajima S. Investigating structural subdivisions of the anterior cingulate cortex in schizophrenia, with implications for treatment resistance and glutamatergic levels. J Psychiatry Neurosci 2022; 47:E1-E10. [PMID: 35027443 PMCID: PMC8842685 DOI: 10.1503/jpn.210113] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 09/24/2021] [Accepted: 10/25/2021] [Indexed: 11/01/2022] Open
Abstract
BACKGROUND Abnormalities in the anterior cingulate cortex (ACC) are thought to play an important role in the pathophysiology of schizophrenia. Given regional variations in ACC structure, the present study aimed to examine ACC structural subdivisions and their relationships to treatment resistance and glutamatergic levels in schizophrenia. METHODS This study included 100 patients with schizophrenia and 52 healthy controls from 2 cohorts. We applied non-negative matrix factorization to identify accurate and stable spatial components of ACC structure. Between groups, we compared ACC structural indices in each spatial component based on treatment resistance or response and tested relationships with ACC glutamate + glutamine levels. RESULTS We detected reductions in cortical thickness and increases in mean diffusivity in the spatial components on the surface of the cingulate sulcus, especially in patients with treatment-resistant and clozapine-resistant schizophrenia. Notably, mean diffusivity in these components was higher in patients who did not respond to clozapine compared to those who did. Furthermore, these ACC structural alterations were related to elevated ACC glutamate + glutamine levels but not related to symptomatology or antipsychotic dose. LIMITATIONS Sample sizes, cross-sectional findings and mixed antipsychotic status were limitations of this study. CONCLUSION This study identified reproducible abnormalities in ACC structures in patients with treatment-resistant and clozapine-resistant schizophrenia. Given that these spatial components play a role in inhibitory control, the present study strengthens the notion that glutamate-related disinhibition is a common biological feature of treatment resistance in schizophrenia.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | - Shinichiro Nakajima
- From the Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan (Ochi, Tarumi, Tsugawa, Honda, Noda, Uchida, Mimura, Nakajima); the Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Que., Canada (Plitman, Patel, Devenyi, Chakravarty); the Department of Psychiatry, McGill University, Montreal, Que., Canada (Plitman, Devenyi, Chakravarty); the Department of Biological and Biomedical Engineering, McGill University, Montreal, Que., Canada (Patel, Chakravarty); the Multimodal Imaging Group, Research Imaging Centre, Centre for Addiction and Mental Health, Toronto, Ont., Canada (Iwata, Kim, Graff-Guerrero, Nakajima); and the Institute of Medical Science, University of Toronto, Toronto, Ont., Canada (Kim, Graff-Guerrero)
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48
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Vogt NM, Hunt JFV, Adluru N, Ma Y, Van Hulle CA, Dean DC, Kecskemeti SR, Chin NA, Carlsson CM, Asthana S, Johnson SC, Kollmorgen G, Batrla R, Wild N, Buck K, Zetterberg H, Alexander AL, Blennow K, Bendlin BB. Interaction of amyloid and tau on cortical microstructure in cognitively unimpaired adults. Alzheimers Dement 2022; 18:65-76. [PMID: 33984184 PMCID: PMC8589921 DOI: 10.1002/alz.12364] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 03/31/2021] [Accepted: 04/12/2021] [Indexed: 01/03/2023]
Abstract
INTRODUCTION Neurite orientation dispersion and density imaging (NODDI), a multi-compartment diffusion-weighted imaging (DWI) model, may be useful for detecting early cortical microstructural alterations in Alzheimer's disease prior to cognitive impairment. METHODS Using neuroimaging (NODDI and T1-weighted magnetic resonance imaging [MRI]) and cerebrospinal fluid (CSF) biomarker data (measured using Elecsys® CSF immunoassays) from 219 cognitively unimpaired participants, we tested the main and interactive effects of CSF amyloid beta (Aβ)42 /Aβ40 and phosphorylated tau (p-tau) on cortical NODDI metrics and cortical thickness, controlling for age, sex, and apolipoprotein E ε4. RESULTS We observed a significant CSF Aβ42 /Aβ40 × p-tau interaction on cortical neurite density index (NDI), but not orientation dispersion index or cortical thickness. The directionality of these interactive effects indicated: (1) among individuals with lower CSF p-tau, greater amyloid burden was associated with higher cortical NDI; and (2) individuals with greater amyloid and p-tau burden had lower cortical NDI, consistent with cortical neurodegenerative changes. DISCUSSION NDI is a particularly sensitive marker for early cortical changes that occur prior to gross atrophy or development of cognitive impairment.
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Affiliation(s)
- Nicholas M. Vogt
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Jack F. V. Hunt
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Nagesh Adluru
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Yue Ma
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Carol A. Van Hulle
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Douglas C. Dean
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Pediatrics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Steven R. Kecskemeti
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Nathaniel A. Chin
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Cynthia M. Carlsson
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Sanjay Asthana
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Sterling C. Johnson
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | | | - Richard Batrla
- Roche Diagnostics International AG, Rotkreuz, Switzerland
| | | | | | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at University College London, London, UK
| | - Andrew L. Alexander
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Barbara B. Bendlin
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
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Felix C, Chahine LM, Hengenius J, Chen H, Rosso AL, Zhu X, Cao Z, Rosano C. Diffusion Tensor Imaging of the Olfactory System in Older Adults With and Without Hyposmia. Front Aging Neurosci 2021; 13:648598. [PMID: 34744681 PMCID: PMC8569942 DOI: 10.3389/fnagi.2021.648598] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Accepted: 06/21/2021] [Indexed: 11/15/2022] Open
Abstract
Objectives: To compare gray matter microstructural characteristics of higher-order olfactory regions among older adults with and without hyposmia. Methods: Data from the Brief Smell Identification Test (BSIT) were obtained in 1998–99 for 265 dementia-free adults from the Health, Aging, and Body Composition study (age at BSIT: 74.9 ± 2.7; 62% White; 43% male) who received 3T diffusion tensor imaging in 2006–08 [Interval of time: mean (SD): 8.01 years (0.50)], Apolipoprotein (ApoEε4) genotypes, and repeated 3MS assessments until 2011–12. Cognitive status (mild cognitive impairment, dementia, normal cognition) was adjudicated in 2011–12. Hyposmia was defined as BSIT ≤ 8. Microstructural integrity was quantified by mean diffusivity (MD) in regions of the primary olfactory cortex amygdala, orbitofrontal cortex (including olfactory cortex, gyrus rectus, the orbital parts of the superior, middle, and inferior frontal gyri, medial orbital part of the superior frontal gyrus), and hippocampus. Multivariable regression models were adjusted for total brain atrophy, demographics, cognitive status, and ApoEε4 genotype. Results: Hyposmia in 1998–99 (n = 57, 21.59%) was significantly associated with greater MD in 2006–08, specifically in the orbital part of the middle frontal gyrus, and amygdala, on the right [adjusted beta (p value): 0.414 (0.01); 0.527 (0.01); respectively]. Conclusion: Older adults with higher mean diffusivity in regions important for olfaction are more likely to have hyposmia up to ten years prior. Future studies should address whether hyposmia can serve as an early biomarker of brain microstructural abnormalities for older adults with a range of cognitive functions, including those with normal cognition.
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Affiliation(s)
- Cynthia Felix
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Lana M Chahine
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, United States
| | - James Hengenius
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Honglei Chen
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI, United States
| | - Andrea L Rosso
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Xiaonan Zhu
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, United States
| | - Zichun Cao
- Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, MI, United States
| | - Caterina Rosano
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, United States
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50
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Hippocampal and non-hippocampal correlates of physically active lifestyle and their relation to episodic memory in older adults. Neurobiol Aging 2021; 109:100-112. [PMID: 34706317 DOI: 10.1016/j.neurobiolaging.2021.08.017] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 08/24/2021] [Accepted: 08/25/2021] [Indexed: 11/21/2022]
Abstract
Aging is associated with compromised neurocognition. While aerobic exercise has been linked with cognitive resilience, findings regarding its relationship with brain morphology are inconsistent. Furthermore, the biological underpinnings of the relationship between aerobic activity and memory in the aging human brain are unclear. To investigate these issues, we examined hippocampal and non-hippocampal structural correlates of aerobically active lifestyle and cardiorespiratory fitness in older adults. We then examined structural pathways which may potentially mediate the association between active lifestyle and memory. Fifty participants (aged 65-80) underwent structural and diffusion MRI, memory evaluation, were examined for active lifestyle and cardiorespiratory fitness. Morphological features of the hippocampus and fornix, white matter lesions, and brain atrophy were assessed. Active lifestyle and cardiorespiratory fitness correlated with all neurocognitive measures. An exploratory mediation analysis revealed hippocampal and white matter lesions pathways linking active lifestyle and cardiorespiratory fitness with memory. Our results support a neuroprotective role of aerobic exercise on the aging brain and suggest plausible morphological pathways that may underlie the relationship between aerobic exercise and memory.
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