1
|
Denkinger M, Baker S, Inglis B, Kobayashi S, Juarez A, Mason S, Jagust W. Associations between regional blood-brain barrier permeability, aging, and Alzheimer's disease biomarkers in cognitively normal older adults. PLoS One 2024; 19:e0299764. [PMID: 38837947 PMCID: PMC11152304 DOI: 10.1371/journal.pone.0299764] [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: 02/20/2024] [Accepted: 05/05/2024] [Indexed: 06/07/2024] Open
Abstract
BACKGROUND Increased blood-brain barrier permeability (BBBp) has been hypothesized as a feature of aging that may lead to the development of Alzheimer's disease (AD). We sought to identify the brain regions most vulnerable to greater BBBp during aging and examine their regional relationship with neuroimaging biomarkers of AD. METHODS We studied 31 cognitively normal older adults (OA) and 10 young adults (YA) from the Berkeley Aging Cohort Study (BACS). Both OA and YA received dynamic contrast-enhanced MRI (DCE-MRI) to quantify Ktrans values, as a measure of BBBp, in 37 brain regions across the cortex. The OA also received Pittsburgh compound B (PiB)-PET to create distribution volume ratios (DVR) images and flortaucipir (FTP)- PET to create partial volume corrected standardized uptake volume ratios (SUVR) images. Repeated measures ANOVA assessed the brain regions where OA showed greater BBBp than YA. In OA, Ktrans values were compared based on sex, Aβ positivity status, and APOE4 carrier status within a composite region across the areas susceptible to aging. We used linear models and sparse canonical correlation analysis (SCCA) to examine the relationship between Ktrans and AD biomarkers. RESULTS OA showed greater BBBp than YA predominately in the temporal lobe, with some involvement of parietal, occipital and frontal lobes. Within an averaged ROI of affected regions, there was no difference in Ktrans values based on sex or Aβ positivity, but OA who were APOE4 carriers had significantly higher Ktrans values. There was no direct relationship between averaged Ktrans and global Aβ pathology, but there was a trend for an Ab status by tau interaction on Ktrans in this region. SCCA showed increased Ktrans was associated with increased PiB DVR, mainly in temporal and parietal brain regions. There was not a significant relationship between Ktrans and FTP SUVR. DISCUSSION Our findings indicate that the BBB shows regional vulnerability during normal aging that overlaps considerably with the pattern of AD pathology. Greater BBBp in brain regions affected in aging is related to APOE genotype and may also be related to the pathological accumulation of Aβ.
Collapse
Affiliation(s)
- Marisa Denkinger
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, California, United States of America
| | - Suzanne Baker
- Lawrence Berkeley National Laboratory, Berkeley, California, United States of America
| | - Ben Inglis
- Henry H. Wheeler Jr. Brain Imaging Center, University of California, Berkeley, Berkeley, California, United States of America
| | - Sarah Kobayashi
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, California, United States of America
| | - Alexis Juarez
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, California, United States of America
| | - Suzanne Mason
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, California, United States of America
| | - William Jagust
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, California, United States of America
- Lawrence Berkeley National Laboratory, Berkeley, California, United States of America
| |
Collapse
|
2
|
Zhou L, Butler TA, Wang XH, Xi K, Tanzi EB, Glodzik L, Chiang GC, de Leon MJ, Li Y. Multimodal assessment of brain fluid clearance is associated with amyloid-beta deposition in humans. J Neuroradiol 2024; 51:101164. [PMID: 37907155 PMCID: PMC11058119 DOI: 10.1016/j.neurad.2023.10.009] [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: 06/20/2023] [Revised: 10/09/2023] [Accepted: 10/28/2023] [Indexed: 11/02/2023]
Abstract
PURPOSE The present study investigates a multimodal imaging assessment of glymphatic function and its association with brain amyloid-beta deposition. METHODS Two brain CSF clearance measures (vCSF and DTI-ALPS) were derived from dynamic PET and MR diffusion tensor imaging (DTI) for 50 subjects, 24/50 were Aβ positive (Aβ+). T1W, T2W, DTI, T2FLAIR, and 11C-PiB and 18F-MK-6240 PET were acquired. Multivariate linear regression models were assessed with both vCSF and DTI-ALPS as independent variables and brain Aβ as the dependent variable. Three types of models were evaluated, including the vCSF-only model, the ALPS-only model and the vCSF+ALPS combined model. Models were applied to the whole group, and Aβ subgroups. All analyses were controlled for age, gender, and intracranial volume. RESULTS Sample demographics (N=50) include 20 males and 30 females with a mean age of 69.30 (sd=8.55). Our results show that the combination of vCSF and ALPS associates with Aβ deposition (p < 0.05, R2 = 0.575) better than either vCSF (p < 0.05, R2 = 0.431) or ALPS (p < 0.05, R2 = 0.372) alone in the Aβ+ group. We observed similar results in whole-group analyses (combined model: p < 0.05, R2 = 0.287; vCSF model: p <0.05, R2 = 0.175; ALPS model: p < 0.05, R2 = 0.196) with less significance. Our data also showed that vCSF has higher correlation (r = -0.548) in subjects with mild Aβ deposition and DTI-ALPS has higher correlation (r=-0.451) with severe Aβ deposition subjects. CONCLUSION The regression model with both vCSF and DTI-ALPS is better associated with brain Aβ deposition. These two independent brain clearance measures may better explain the variation in Aβ deposition than either term individually. Our results suggest that vCSF and DTI-ALPS reflect complementary aspects of brain clearance functions.
Collapse
Affiliation(s)
- Liangdong Zhou
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, 407 E 61st St, Feil 2, New York, NY 10065, United States
| | - Tracy A Butler
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, 407 E 61st St, Feil 2, New York, NY 10065, United States
| | - Xiuyuan H Wang
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, 407 E 61st St, Feil 2, New York, NY 10065, United States
| | - Ke Xi
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, 407 E 61st St, Feil 2, New York, NY 10065, United States
| | - Emily B Tanzi
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, 407 E 61st St, Feil 2, New York, NY 10065, United States
| | - Lidia Glodzik
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, 407 E 61st St, Feil 2, New York, NY 10065, United States
| | - Gloria C Chiang
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, 407 E 61st St, Feil 2, New York, NY 10065, United States
| | - Mony J de Leon
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, 407 E 61st St, Feil 2, New York, NY 10065, United States
| | - Yi Li
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, 407 E 61st St, Feil 2, New York, NY 10065, United States.
| |
Collapse
|
3
|
Rudolph MD, Sutphen CL, Register TC, Whitlow CT, Solingapuram Sai KK, Hughes TM, Bateman JR, Dage JL, Russ KA, Mielke MM, Craft S, Lockhart SN. Associations among plasma, MRI, and amyloid PET biomarkers of Alzheimer's disease and related dementias and the impact of health-related comorbidities in a community-dwelling cohort. Alzheimers Dement 2024; 20:4159-4173. [PMID: 38747525 DOI: 10.1002/alz.13835] [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: 11/08/2023] [Revised: 03/18/2024] [Accepted: 03/19/2024] [Indexed: 06/05/2024]
Abstract
INTRODUCTION We evaluated associations between plasma and neuroimaging-derived biomarkers of Alzheimer's disease and related dementias and the impact of health-related comorbidities. METHODS We examined plasma biomarkers (neurofilament light chain, glial fibrillary acidic protein, amyloid beta [Aβ] 42/40, phosphorylated tau 181) and neuroimaging measures of amyloid deposition (Aβ-positron emission tomography [PET]), total brain volume, white matter hyperintensity volume, diffusion-weighted fractional anisotropy, and neurite orientation dispersion and density imaging free water. Participants were adjudicated as cognitively unimpaired (CU; N = 299), mild cognitive impairment (MCI; N = 192), or dementia (DEM; N = 65). Biomarkers were compared across groups stratified by diagnosis, sex, race, and APOE ε4 carrier status. General linear models examined plasma-imaging associations before and after adjusting for demographics (age, sex, race, education), APOE ε4 status, medications, diagnosis, and other factors (estimated glomerular filtration rate [eGFR], body mass index [BMI]). RESULTS Plasma biomarkers differed across diagnostic groups (DEM > MCI > CU), were altered in Aβ-PET-positive individuals, and were associated with poorer brain health and kidney function. DISCUSSION eGFR and BMI did not substantially impact associations between plasma and neuroimaging biomarkers. HIGHLIGHTS Plasma biomarkers differ across diagnostic groups (DEM > MCI > CU) and are altered in Aβ-PET-positive individuals. Altered plasma biomarker levels are associated with poorer brain health and kidney function. Plasma and neuroimaging biomarker associations are largely independent of comorbidities.
Collapse
Affiliation(s)
- Marc D Rudolph
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| | - Courtney L Sutphen
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| | - Thomas C Register
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| | - Christopher T Whitlow
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| | - Kiran K Solingapuram Sai
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| | - Timothy M Hughes
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| | - James R Bateman
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| | - Jeffrey L Dage
- Department Of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Kristen A Russ
- Department Of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Michelle M Mielke
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| | - Suzanne Craft
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| | - Samuel N Lockhart
- Department of Internal Medicine, Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| |
Collapse
|
4
|
Robertson C, Rezaii N, Hochberg D, Quimby M, Wolff P, Dickerson BC. Using explainable artificial intelligence to identify linguistic biomarkers of amyloid pathology in primary progressive aphasia. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.02.24306657. [PMID: 38746086 PMCID: PMC11092708 DOI: 10.1101/2024.05.02.24306657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Introduction Recent success has been achieved in Alzheimer's disease (AD) clinical trials targeting amyloid beta (β), demonstrating a reduction in the rate of cognitive decline. However, testing methods for amyloid-β positivity are currently costly or invasive, motivating the development of accessible screening approaches to steer patients toward appropriate diagnostic tests. Here, we employ a pre-trained language model (Distil-RoBERTa) to identify amyloid-β positivity from a short, connected speech sample. We further use explainable AI (XAI) methods to extract interpretable linguistic features that can be employed in clinical practice. Methods We obtained language samples from 74 patients with primary progressive aphasia (PPA) across its three variants. Amyloid-β positivity was established through the analysis of cerebrospinal fluid, amyloid PET, or autopsy. 51% of the sample was amyloid-positive. We trained Distil-RoBERTa for 16 epochs with a batch size of 6 and a learning rate of 5e-5, and used the LIME algorithm to train interpretation models to interpret the trained classifier's inference conditions. Results Over ten runs of 10-fold cross-validation, the classifier achieved a mean accuracy of 92%, SD = 0.01. Interpretation models were able to capture the classifier's behavior well, achieving an accuracy of 97% against classifier predictions, and uncovering several novel speech patterns that may characterize amyloid-β positivity. Discussion Our work improves previous research which indicates connected speech is a useful diagnostic input for prediction of the presence of amyloid-β in patients with PPA. Further, we leverage XAI techniques to reveal novel linguistic features that can be tested in clinical practice in the appropriate subspecialty setting. Computational linguistic analysis of connected speech shows great promise as a novel assessment method in patients with AD and related disorders.
Collapse
|
5
|
Iaccarino L, Llibre-Guerra JJ, McDade E, Edwards L, Gordon B, Benzinger T, Hassenstab J, Kramer JH, Li Y, Miller BL, Miller Z, Morris JC, Mundada N, Perrin RJ, Rosen HJ, Soleimani-Meigooni D, Strom A, Tsoy E, Wang G, Xiong C, Allegri R, Chrem P, Vazquez S, Berman SB, Chhatwal J, Masters CL, Farlow MR, Jucker M, Levin J, Salloway S, Fox NC, Day GS, Gorno-Tempini ML, Boxer AL, La Joie R, Bateman R, Rabinovici GD. Molecular neuroimaging in dominantly inherited versus sporadic early-onset Alzheimer's disease. Brain Commun 2024; 6:fcae159. [PMID: 38784820 PMCID: PMC11114609 DOI: 10.1093/braincomms/fcae159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 03/14/2024] [Accepted: 05/01/2024] [Indexed: 05/25/2024] Open
Abstract
Approximately 5% of Alzheimer's disease patients develop symptoms before age 65 (early-onset Alzheimer's disease), with either sporadic (sporadic early-onset Alzheimer's disease) or dominantly inherited (dominantly inherited Alzheimer's disease) presentations. Both sporadic early-onset Alzheimer's disease and dominantly inherited Alzheimer's disease are characterized by brain amyloid-β accumulation, tau tangles, hypometabolism and neurodegeneration, but differences in topography and magnitude of these pathological changes are not fully elucidated. In this study, we directly compared patterns of amyloid-β plaque deposition and glucose hypometabolism in sporadic early-onset Alzheimer's disease and dominantly inherited Alzheimer's disease individuals. Our analysis included 134 symptomatic sporadic early-onset Alzheimer's disease amyloid-Positron Emission Tomography (PET)-positive cases from the University of California, San Francisco, Alzheimer's Disease Research Center (mean ± SD age 59.7 ± 5.6 years), 89 symptomatic dominantly inherited Alzheimer's disease cases (age 45.8 ± 9.3 years) and 102 cognitively unimpaired non-mutation carriers from the Dominantly Inherited Alzheimer Network study (age 44.9 ± 9.2). Each group underwent clinical and cognitive examinations, 11C-labelled Pittsburgh Compound B-PET and structural MRI. 18F-Fluorodeoxyglucose-PET was also available for most participants. Positron Emission Tomography scans from both studies were uniformly processed to obtain a standardized uptake value ratio (PIB50-70 cerebellar grey reference and FDG30-60 pons reference) images. Statistical analyses included pairwise global and voxelwise group comparisons and group-independent component analyses. Analyses were performed also adjusting for covariates including age, sex, Mini-Mental State Examination, apolipoprotein ε4 status and average composite cortical of standardized uptake value ratio. Compared with dominantly inherited Alzheimer's disease, sporadic early-onset Alzheimer's disease participants were older at age of onset (mean ± SD, 54.8 ± 8.2 versus 41.9 ± 8.2, Cohen's d = 1.91), with more years of education (16.4 ± 2.8 versus 13.5 ± 3.2, d = 1) and more likely to be apolipoprotein ε4 carriers (54.6% ε4 versus 28.1%, Cramer's V = 0.26), but similar Mini-Mental State Examination (20.6 ± 6.1 versus 21.2 ± 7.4, d = 0.08). Sporadic early-onset Alzheimer's disease had higher global cortical Pittsburgh Compound B-PET binding (mean ± SD standardized uptake value ratio, 1.92 ± 0.29 versus 1.58 ± 0.44, d = 0.96) and greater global cortical 18F-fluorodeoxyglucose-PET hypometabolism (mean ± SD standardized uptake value ratio, 1.32 ± 0.1 versus 1.39 ± 0.19, d = 0.48) compared with dominantly inherited Alzheimer's disease. Fully adjusted comparisons demonstrated relatively higher Pittsburgh Compound B-PET standardized uptake value ratio in the medial occipital, thalami, basal ganglia and medial/dorsal frontal regions in dominantly inherited Alzheimer's disease versus sporadic early-onset Alzheimer's disease. Sporadic early-onset Alzheimer's disease showed relatively greater 18F-fluorodeoxyglucose-PET hypometabolism in Alzheimer's disease signature temporoparietal regions and caudate nuclei, whereas dominantly inherited Alzheimer's disease showed relatively greater hypometabolism in frontal white matter and pericentral regions. Independent component analyses largely replicated these findings by highlighting common and unique Pittsburgh Compound B-PET and 18F-fluorodeoxyglucose-PET binding patterns. In summary, our findings suggest both common and distinct patterns of amyloid and glucose hypometabolism in sporadic and dominantly inherited early-onset Alzheimer's disease.
Collapse
Affiliation(s)
- Leonardo Iaccarino
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Jorge J Llibre-Guerra
- The Dominantly Inherited Alzheimer Network (DIAN), St Louis, MO 63108, USA
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Eric McDade
- The Dominantly Inherited Alzheimer Network (DIAN), St Louis, MO 63108, USA
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Lauren Edwards
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Brian Gordon
- Department of Radiology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Tammie Benzinger
- Department of Radiology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Jason Hassenstab
- The Dominantly Inherited Alzheimer Network (DIAN), St Louis, MO 63108, USA
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Joel H Kramer
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Yan Li
- Department of Biostatistics, Washington University in St Louis, St Louis, MO 63110, USA
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Zachary Miller
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - John C Morris
- The Dominantly Inherited Alzheimer Network (DIAN), St Louis, MO 63108, USA
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Nidhi Mundada
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Richard J Perrin
- Department of Pathology and Immunology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Howard J Rosen
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - David Soleimani-Meigooni
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Amelia Strom
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Elena Tsoy
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Guoqiao Wang
- Department of Biostatistics, Washington University in St Louis, St Louis, MO 63110, USA
| | - Chengjie Xiong
- Department of Biostatistics, Washington University in St Louis, St Louis, MO 63110, USA
| | - Ricardo Allegri
- Department of Cognitive Neurology, Institute for Neurological Research Fleni, Buenos Aires 1428, Argentina
| | - Patricio Chrem
- Department of Cognitive Neurology, Institute for Neurological Research Fleni, Buenos Aires 1428, Argentina
| | - Silvia Vazquez
- Department of Cognitive Neurology, Institute for Neurological Research Fleni, Buenos Aires 1428, Argentina
| | - Sarah B Berman
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Jasmeer Chhatwal
- Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Colin L Masters
- Department of Neuroscience, Florey Institute, The University of Melbourne, Melbourne 3052, Australia
| | - Martin R Farlow
- Neuroscience Center, Indiana University School of Medicine at Indianapolis, Indiana, IN 46202, USA
| | - Mathias Jucker
- DZNE-German Center for Neurodegenerative Diseases, Tübingen 72076, Germany
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-University, Munich 80539, Germany
- German Center for Neurodegenerative Diseases, Munich 81377, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich 81377, Germany
| | - Stephen Salloway
- Memory & Aging Program, Butler Hospital, Brown University in Providence, RI 02906, USA
| | - Nick C Fox
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London Institute of Neurology, London WC1N 3BG, UK
| | - Gregory S Day
- Department of Neurology, Mayo Clinic Florida, Jacksonville, FL 33224, USA
| | - Maria Luisa Gorno-Tempini
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Adam L Boxer
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
| | - Randall Bateman
- The Dominantly Inherited Alzheimer Network (DIAN), St Louis, MO 63108, USA
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA 94158, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA 94143, USA
| |
Collapse
|
6
|
Huang S, Zhang Y, Guo Y, Du J, Ren P, Wu B, Feng J, Cheng W, Yu J. Glymphatic system dysfunction predicts amyloid deposition, neurodegeneration, and clinical progression in Alzheimer's disease. Alzheimers Dement 2024; 20:3251-3269. [PMID: 38501315 PMCID: PMC11095446 DOI: 10.1002/alz.13789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 02/08/2024] [Accepted: 02/15/2024] [Indexed: 03/20/2024]
Abstract
INTRODUCTION Although glymphatic function is involved in Alzheimer's disease (AD), its potential for predicting the pathological and clinical progression of AD and its sequential association with core AD biomarkers is poorly understood. METHODS Whole-brain glymphatic activity was measured by diffusion tensor image analysis along the perivascular space (DTI-ALPS) in participants with AD dementia (n = 47), mild cognitive impairment (MCI; n = 137), and normal controls (n = 235) from the Alzheimer's Disease Neuroimaging Initiative. RESULTS ALPS index was significantly lower in AD dementia than in MCI or controls. Lower ALPS index was significantly associated with faster changes in amyloid positron emission tomography (PET) burden and AD signature region of interest volume, higher risk of amyloid-positive transition and clinical progression, and faster rates of amyloid- and neurodegeneration-related cognitive decline. Furthermore, the associations of the ALPS index with cognitive decline were fully mediated by amyloid PET and brain atrophy. DISCUSSION Glymphatic failure may precede amyloid pathology, and predicts amyloid deposition, neurodegeneration, and clinical progression in AD. HIGHLIGHTS The analysis along the perivascular space (ALPS) index is reduced in patients with Alzheimer's disease (AD) dementia, prodromal AD, and preclinical AD. Lower ALPS index predicted accelerated amyloid beta (Aβ) positron emission tomography (PET) burden and Aβ-positive transition. The decrease in the ALPS index occurs before cerebrospinal fluid Aβ42 reaches the positive threshold. ALPS index predicted brain atrophy, clinical progression, and cognitive decline. Aβ PET and brain atrophy mediated the link of ALPS index with cognitive decline.
Collapse
Affiliation(s)
- Shu‐Yi Huang
- Department of Neurology and National Center for Neurological DisordersHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceShanghai Medical CollegeFudan UniversityShanghaiChina
| | - Ya‐Ru Zhang
- Department of Neurology and National Center for Neurological DisordersHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceShanghai Medical CollegeFudan UniversityShanghaiChina
| | - Yu Guo
- Department of Neurology and National Center for Neurological DisordersHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceShanghai Medical CollegeFudan UniversityShanghaiChina
| | - Jing Du
- Centre for Healthy Brain Ageing (CHeBA)Discipline of Psychiatry and Mental HealthSchool of Clinical MedicineUNSWSydneyNew South WalesAustralia
| | - Peng Ren
- Institute of Science and Technology for Brain‐Inspired IntelligenceFudan UniversityShanghaiChina
| | - Bang‐Sheng Wu
- Department of Neurology and National Center for Neurological DisordersHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceShanghai Medical CollegeFudan UniversityShanghaiChina
| | - Jian‐Feng Feng
- Institute of Science and Technology for Brain‐Inspired IntelligenceFudan UniversityShanghaiChina
- Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence (Fudan University), Ministry of EducationShanghaiChina
- Fudan ISTBI—ZJNU Algorithm Centre for Brain‐Inspired IntelligenceZhejiang Normal UniversityJinhuaChina
| | | | - Wei Cheng
- Department of Neurology and National Center for Neurological DisordersHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceShanghai Medical CollegeFudan UniversityShanghaiChina
- Institute of Science and Technology for Brain‐Inspired IntelligenceFudan UniversityShanghaiChina
- Key Laboratory of Computational Neuroscience and Brain‐Inspired Intelligence (Fudan University), Ministry of EducationShanghaiChina
- Fudan ISTBI—ZJNU Algorithm Centre for Brain‐Inspired IntelligenceZhejiang Normal UniversityJinhuaChina
- Shanghai Medical College and Zhongshan Hospital Immunotherapy Technology Transfer CenterFudan UniversityShanghaiChina
| | - Jin‐Tai Yu
- Department of Neurology and National Center for Neurological DisordersHuashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceShanghai Medical CollegeFudan UniversityShanghaiChina
| |
Collapse
|
7
|
Lee S, Byun MS, Yi D, Ahn H, Jung G, Jung JH, Chang YY, Kim K, Choi H, Choi J, Lee JY, Kang KM, Sohn CH, Lee YS, Kim YK, Lee DY. Plasma Leptin and Alzheimer Protein Pathologies Among Older Adults. JAMA Netw Open 2024; 7:e249539. [PMID: 38700863 PMCID: PMC11069086 DOI: 10.1001/jamanetworkopen.2024.9539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Accepted: 03/01/2024] [Indexed: 05/06/2024] Open
Abstract
Importance Many epidemiologic studies have suggested that low levels of plasma leptin, a major adipokine, are associated with increased risk of Alzheimer disease (AD) dementia and cognitive decline. Nevertheless, the mechanistic pathway linking plasma leptin and AD-related cognitive decline is not yet fully understood. Objective To examine the association of plasma leptin levels with in vivo AD pathologies, including amyloid-beta (Aβ) and tau deposition, through both cross-sectional and longitudinal approaches among cognitively unimpaired older adults. Design, Setting, and Participants This was a longitudinal cohort study from the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer Disease. Data were collected from January 1, 2014, to December 31, 2020, and data were analyzed from July 11 to September 6, 2022. The study included a total of 208 cognitively unimpaired participants who underwent baseline positron emission tomography (PET) scans for brain Aβ deposition. For longitudinal analyses, 192 participants who completed both baseline and 2-year follow-up PET scans for brain Aβ deposition were included. Exposure Plasma leptin levels as assessed by enzyme-linked immunosorbent assay. Main Outcomes and Measures Baseline levels and longitudinal changes of global Aβ and AD-signature region tau deposition measured by PET scans. Results Among the 208 participants, the mean (SD) age was 66.0 (11.3) years, 114 were women (54.8%), and 37 were apolipoprotein E ε4 carriers (17.8%). Lower plasma leptin levels had a significant cross-sectional association with greater brain Aβ deposition (β = -0.04; 95% CI, -0.09 to 0.00; P = .046), while there was no significant association between plasma leptin levels and tau deposition (β = -0.02; 95% CI, -0.05 to 0.02; P = .41). In contrast, longitudinal analyses revealed that there was a significant association between lower baseline leptin levels and greater increase of tau deposition over 2 years (β = -0.06; 95% CI, -0.11 to -0.01; P = .03), whereas plasma leptin levels did not have a significant association with longitudinal change of Aβ deposition (β = 0.006; 95% CI, 0.00-0.02; P = .27). Conclusions and Relevance The present findings suggest that plasma leptin may be protective for the development or progression of AD pathology, including both Aβ and tau deposition.
Collapse
Affiliation(s)
- Seunghoon Lee
- Department of Psychiatry, Myongji Hospital, Hanyang University College of Medicine, Goyang, Republic of Korea
| | - Min Soo Byun
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Dahyun Yi
- Institute of Human Behavioral Medicine, Medical Research Center, Seoul National University, Seoul, Republic of Korea
| | - Hyejin Ahn
- Interdisciplinary Program of Cognitive Science, Seoul National University College of Humanities, Seoul, Republic of Korea
| | - Gijung Jung
- Institute of Human Behavioral Medicine, Medical Research Center, Seoul National University, Seoul, Republic of Korea
| | - Joon Hyung Jung
- Department of Psychiatry, Chungbuk National University Hospital, Cheongju, Republic of Korea
| | - Yoon Young Chang
- Department of Psychiatry, Inje University, Sanggye Paik Hospital, Seoul, Republic of Korea
| | - Kyungtae Kim
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Hyeji Choi
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Jeongmin Choi
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Jun-Young Lee
- Department of Neuropsychiatry, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea
| | - Koung Mi Kang
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Chul-Ho Sohn
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Yun-Sang Lee
- Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Yu Kyeong Kim
- Department of Nuclear Medicine, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea
| | - Dong Young Lee
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
- Institute of Human Behavioral Medicine, Medical Research Center, Seoul National University, Seoul, Republic of Korea
- Interdisciplinary Program of Cognitive Science, Seoul National University College of Humanities, Seoul, Republic of Korea
| |
Collapse
|
8
|
Bao YW, Wang ZJ, Guo LL, Bai GJ, Feng Y, Zhao GD. Expression of regional brain amyloid-β deposition with [18F]Flutemetamol in Centiloid scale -a multi-site study. Neuroradiology 2024:10.1007/s00234-024-03364-5. [PMID: 38676749 DOI: 10.1007/s00234-024-03364-5] [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: 12/12/2023] [Accepted: 04/19/2024] [Indexed: 04/29/2024]
Abstract
PURPOSE The Centiloid project helps calibrate the quantitative amyloid-β (Aβ) load into a unified Centiloid (CL) scale that allows data comparison across multi-site. How the smaller regional amyloid converted into CL has not been attempted. We first aimed to express regional Aβ deposition in CL using [18F]Flutemetamol and evaluate regional Aβ deposition in CL with that in standardized uptake value ratio (SUVr). Second, we aimed to determine the presence or absence of focal Aβ deposition by measuring regional CL in equivocal cases showing negative global CL. METHODS Following the Centiloid project pipeline, Level-1 replication, Level-2 calibration, and quality control were completed to generate corresponding Centiloid conversion equations to convert SUVr into Centiloid at regional levels. In equivocal cases, the regional CL was compared with visual inspection to evaluate regional Aβ positivity. RESULTS 14 out of 16 regional conversions from [18F]Flutemetamol SUVr to Centiloid successfully passed the quality control, showing good reliability and relative variance, especially precuneus/posterior cingulate and prefrontal regions with good stability for Centiloid scaling. The absence of focal Aβ deposition could be detected by measuring regional CL, showing a high agreement rate with visual inspection. The regional Aβ positivity in the bilateral anterior cingulate cortex was most prevalent in equivocal cases. CONCLUSION The expression of regional brain Aβ deposition in CL with [18F]Flutemetamol has been attempted in this study. Equivocal cases had focal Aβ deposition that can be detected by measuring regional CL.
Collapse
Affiliation(s)
- Yi-Wen Bao
- Department of Medical Imaging Center, The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University, 1 Huanghe West Road, Huaiyin District, 223300, Huai'an, Jiangsu, China.
| | - Zuo-Jun Wang
- Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Li-Li Guo
- Department of Medical Imaging Center, The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University, 1 Huanghe West Road, Huaiyin District, 223300, Huai'an, Jiangsu, China
| | - Gen-Ji Bai
- Department of Medical Imaging Center, The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University, 1 Huanghe West Road, Huaiyin District, 223300, Huai'an, Jiangsu, China
| | - Yun Feng
- Department of Medical Imaging Center, The Affiliated Huaian No.1 People's Hospital of Nanjing Medical University, 1 Huanghe West Road, Huaiyin District, 223300, Huai'an, Jiangsu, China
| | - Guo-Dong Zhao
- Department of General Surgery, Lianshui County People's Hospital, 223400, Huai'an, Jiang Su, China
| |
Collapse
|
9
|
Katsumi Y, Howe IA, Eckbo R, Wong B, Quimby M, Hochberg D, McGinnis SM, Putcha D, Wolk DA, Touroutoglou A, Dickerson BC. Default mode network tau predicts future clinical decline in atypical early Alzheimer's disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.17.24305620. [PMID: 38699357 PMCID: PMC11065041 DOI: 10.1101/2024.04.17.24305620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
Identifying individuals with early stage Alzheimer's disease (AD) at greater risk of steeper clinical decline would allow professionals and loved ones to make better-informed medical, support, and life planning decisions. Despite accumulating evidence on the clinical prognostic value of tau PET in typical late-onset amnestic AD, its utility in predicting clinical decline in individuals with atypical forms of AD remains unclear. In this study, we examined the relationship between baseline tau PET signal and the rate of subsequent clinical decline in a sample of 48 A+/T+/N+ patients with mild cognitive impairment or mild dementia due to AD with atypical clinical phenotypes (Posterior Cortical Atrophy, logopenic variant Primary Progressive Aphasia, and amnestic syndrome with multi-domain impairment and age of onset < 65 years). All patients underwent structural magnetic resonance imaging (MRI), tau (18F-Flortaucipir) PET, and amyloid (either 18F-Florbetaben or 11C-Pittsburgh Compound B) PET scans at baseline. Each patient's longitudinal clinical decline was assessed by calculating the annualized change in the Clinical Dementia Rating Sum-of-Boxes (CDR-SB) scores from baseline to follow-up (mean time interval = 14.55 ± 3.97 months). Our sample of early atypical AD patients showed an increase in CDR-SB by 1.18 ± 1.25 points per year: t(47) = 6.56, p < .001, d = 0.95. These AD patients showed prominent baseline tau burden in posterior cortical regions including the major nodes of the default mode network, including the angular gyrus, posterior cingulate cortex/precuneus, and lateral temporal cortex. Greater baseline tau in the broader default mode network predicted faster clinical decline. Tau in the default mode network was the strongest predictor of clinical decline, outperforming baseline clinical impairment, tau in other functional networks, and the magnitude of cortical atrophy and amyloid burden in the default mode network. Overall, these findings point to the contribution of baseline tau burden within the default mode network of the cerebral cortex to predicting the magnitude of clinical decline in a sample of atypical early AD patients one year later. This simple measure based on a tau PET scan could aid the development of a personalized prognostic, monitoring, and treatment plan tailored to each individual patient, which would help clinicians not only predict the natural evolution of the disease but also estimate the effect of disease-modifying therapies on slowing subsequent clinical decline given the patient's tau burden while still early in the disease course.
Collapse
Affiliation(s)
- Yuta Katsumi
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Inola A Howe
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Ryan Eckbo
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Bonnie Wong
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Megan Quimby
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Daisy Hochberg
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Scott M McGinnis
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Center for Brain Mind Medicine, Department of Neurology, Brigham & Women's Hospital, Boston, MA 02115, USA
| | - Deepti Putcha
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Center for Brain Mind Medicine, Department of Neurology, Brigham & Women's Hospital, Boston, MA 02115, USA
| | - David A Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Alexandra Touroutoglou
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Alzheimer's Disease Research Center, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Bradford C Dickerson
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Alzheimer's Disease Research Center, Massachusetts General Hospital, Charlestown, MA 02129, USA
| |
Collapse
|
10
|
Fonseca CS, Baker SL, Dobyns L, Janabi M, Jagust WJ, Harrison TM. Tau accumulation and atrophy predict amyloid independent cognitive decline in aging. Alzheimers Dement 2024; 20:2526-2537. [PMID: 38334195 PMCID: PMC11032527 DOI: 10.1002/alz.13654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 11/15/2023] [Accepted: 11/30/2023] [Indexed: 02/10/2024]
Abstract
INTRODUCTION Amyloid beta (Aβ) and tau pathology are cross-sectionally associated with atrophy and cognitive decline in aging and Alzheimer's disease (AD). METHODS We investigated relationships between concurrent longitudinal measures of Aβ (Pittsburgh compound B [PiB] positron emission tomography [PET]), tau (flortaucipir [FTP] PET), atrophy (structural magnetic resonance imaging), episodic memory (EM), and non-memory (NM) in 78 cognitively healthy older adults (OA). RESULTS Entorhinal FTP change was correlated with EM decline regardless of Aβ, but meta-temporal FTP and global PiB change were only associated with EM and NM decline in Aβ+ OA. Voxel-wise analyses revealed significant associations between temporal lobe FTP change and EM decline in all groups. PiB and FTP change were not associated with structural change, suggesting a functional or microstructural mechanism linking these measures to cognitive decline. DISCUSSION Our results show that longitudinal Aβ is linked to cognitive decline only in the presence of elevated Aβ, but longitudinal temporal lobe tau is associated with memory decline regardless of Aβ status. HIGHLIGHTS Entorhinal tau change was associated with memory decline in older adults (OA), regardless of amyloid beta (Aβ). Greater meta-region of interest (ROI) tau change correlated with memory decline in Aβ+ OA. Voxel-wise temporal tau change correlated with memory decline, regardless of Aβ. Meta-ROI tau and global amyloid change correlated with non-memory change in Aβ+ OA. Tau and amyloid accumulation were not associated with structural change in OA.
Collapse
Affiliation(s)
- Corrina S. Fonseca
- Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
| | | | - Lindsey Dobyns
- Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
| | - Mustafa Janabi
- Lawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA
| | - William J. Jagust
- Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
- Lawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA
| | - Theresa M. Harrison
- Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
| |
Collapse
|
11
|
Giorgio J, Adams JN, Maass A, Jagust WJ, Breakspear M. Amyloid induced hyperexcitability in default mode network drives medial temporal hyperactivity and early tau accumulation. Neuron 2024; 112:676-686.e4. [PMID: 38096815 PMCID: PMC10922797 DOI: 10.1016/j.neuron.2023.11.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 09/01/2023] [Accepted: 11/14/2023] [Indexed: 02/24/2024]
Abstract
In early Alzheimer's disease (AD) β-amyloid (Aβ) deposits throughout association cortex and tau appears in the entorhinal cortex (EC). Why these initially appear in disparate locations is not understood. Using task-based fMRI and multimodal PET imaging, we assess the impact of local AD pathology on network-to-network interactions. We show that AD pathologies flip interactions between the default mode network (DMN) and the medial temporal lobe (MTL) from inhibitory to excitatory. The DMN is hyperexcited with increasing levels of Aβ, which drives hyperexcitability within the MTL and this directed hyperexcitation of the MTL by the DMN predicts the rate of tau accumulation within the EC. Our results support a model whereby Aβ induces disruptions to local excitatory-inhibitory balance in the DMN, driving hyperexcitability in the MTL, leading to tau accumulation. We propose that Aβ-induced disruptions to excitatory-inhibitory balance is a candidate causal route between Aβ and remote EC-tau accumulation.
Collapse
Affiliation(s)
- Joseph Giorgio
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA; School of Psychological Sciences, College of Engineering, Science, and the Environment, University of Newcastle, Newcastle, NSW 2305, Australia.
| | - Jenna N Adams
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA 92697, USA
| | - Anne Maass
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg 39120, Germany
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - Michael Breakspear
- School of Psychological Sciences, College of Engineering, Science, and the Environment, University of Newcastle, Newcastle, NSW 2305, Australia; Discipline of Psychiatry, College of Health, Medicine, and Wellbeing, The University of Newcastle, Newcastle, NSW 2305, Australia
| |
Collapse
|
12
|
Rezaii N, Hochberg D, Quimby M, Wong B, McGinnis S, Dickerson BC, Putcha D. Language uncovers visuospatial dysfunction in posterior cortical atrophy: a natural language processing approach. Front Neurosci 2024; 18:1342909. [PMID: 38379764 PMCID: PMC10876777 DOI: 10.3389/fnins.2024.1342909] [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: 11/22/2023] [Accepted: 01/18/2024] [Indexed: 02/22/2024] Open
Abstract
Introduction Posterior Cortical Atrophy (PCA) is a syndrome characterized by a progressive decline in higher-order visuospatial processing, leading to symptoms such as space perception deficit, simultanagnosia, and object perception impairment. While PCA is primarily known for its impact on visuospatial abilities, recent studies have documented language abnormalities in PCA patients. This study aims to delineate the nature and origin of language impairments in PCA, hypothesizing that language deficits reflect the visuospatial processing impairments of the disease. Methods We compared the language samples of 25 patients with PCA with age-matched cognitively normal (CN) individuals across two distinct tasks: a visually-dependent picture description and a visually-independent job description task. We extracted word frequency, word utterance latency, and spatial relational words for this comparison. We then conducted an in-depth analysis of the language used in the picture description task to identify specific linguistic indicators that reflect the visuospatial processing deficits of PCA. Results Patients with PCA showed significant language deficits in the visually-dependent task, characterized by higher word frequency, prolonged utterance latency, and fewer spatial relational words, but not in the visually-independent task. An in-depth analysis of the picture description task further showed that PCA patients struggled to identify certain visual elements as well as the overall theme of the picture. A predictive model based on these language features distinguished PCA patients from CN individuals with high classification accuracy. Discussion The findings indicate that language is a sensitive behavioral construct to detect visuospatial processing abnormalities of PCA. These insights offer theoretical and clinical avenues for understanding and managing PCA, underscoring language as a crucial marker for the visuospatial deficits of this atypical variant of Alzheimer's disease.
Collapse
Affiliation(s)
- Neguine Rezaii
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Daisy Hochberg
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Megan Quimby
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Bonnie Wong
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Scott McGinnis
- Center for Brain Mind Medicine, Department of Neurology, Brigham and Women’s Hospital, Boston, MA, United States
| | - Bradford C. Dickerson
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States
- Alzheimer’s Disease Research Center, Massachusetts General Hospital, Charlestown, MA, United States
| | - Deepti Putcha
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| |
Collapse
|
13
|
Lesman-Segev OH, Golan Shekhtman S, Springer RR, Livny A, Lin HM, Yuxia O, Zadok M, Ganmore I, Heymann A, Hoffmann C, Domachevsky L, Schnaider Beeri M. Amyloid deposition and small vessel disease are associated with cognitive function in older adults with type 2 diabetes. Sci Rep 2024; 14:2741. [PMID: 38302529 PMCID: PMC10834442 DOI: 10.1038/s41598-024-53043-x] [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: 09/20/2023] [Accepted: 01/27/2024] [Indexed: 02/03/2024] Open
Abstract
Diabetes is associated with cognitive decline, but the underlying mechanisms are complex and their relationship with Alzheimer's Disease biomarkers is not fully understood. We assessed the association of small vessel disease (SVD) and amyloid burden with cognitive functioning in 47 non-demented older adults with type-2 diabetes from the Israel Diabetes and Cognitive Decline Study (mean age 78Y, 64% females). FLAIR-MRI, Vizamyl amyloid-PET, and T1W-MRI quantified white matter hyperintensities as a measure of SVD, amyloid burden, and gray matter (GM) volume, respectively. Mean hemoglobin A1c levels and duration of type-2 diabetes were used as measures of diabetic control. Cholesterol level and blood pressure were used as measures of cardiovascular risk. A broad neuropsychological battery assessed cognition. Linear regression models revealed that both higher SVD and amyloid burden were associated with lower cognitive functioning. Additional adjustments for type-2 diabetes-related characteristics, GM volume, and cardiovascular risk did not alter the results. The association of amyloid with cognition remained unchanged after further adjustment for SVD, and the association of SVD with cognition remained unchanged after further adjustment for amyloid burden. Our findings suggest that SVD and amyloid pathology may independently contribute to lower cognitive functioning in non-demented older adults with type-2 diabetes, supporting a multimodal approach for diagnosing, preventing, and treating cognitive decline in this population.
Collapse
Affiliation(s)
- Orit H Lesman-Segev
- Department of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Israel.
- The Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel.
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
| | - Sapir Golan Shekhtman
- The Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Ramit Ravona Springer
- The Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Memory Clinic, Sheba Medical Center, Tel Hashomer, Israel
| | - Abigail Livny
- Department of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Israel
- The Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel
| | - Hung-Mo Lin
- Department of Population Health Science and Policy, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ouyang Yuxia
- Department of Population Health Science and Policy, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Maya Zadok
- The Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel
| | - Ithamar Ganmore
- The Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Memory Clinic, Sheba Medical Center, Tel Hashomer, Israel
| | - Anthony Heymann
- Maccabi Healthcare Services, Tel Aviv, Israel
- Department of Family Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Chen Hoffmann
- Department of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Israel
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Liran Domachevsky
- Department of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Israel
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Michal Schnaider Beeri
- The Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel
- Department of Psychiatry, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
| |
Collapse
|
14
|
Putcha D, Eustace A, Carvalho N, Wong B, Quimby M, Dickerson BC. Auditory naming is impaired in posterior cortical atrophy and early-onset Alzheimer's disease. Front Neurosci 2024; 18:1342928. [PMID: 38327846 PMCID: PMC10847232 DOI: 10.3389/fnins.2024.1342928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 01/05/2024] [Indexed: 02/09/2024] Open
Abstract
Introduction Visual naming ability reflects semantic memory retrieval and is a hallmark deficit of Alzheimer's disease (AD). Naming impairment is most prominently observed in the late-onset amnestic and logopenic variant Primary Progressive Aphasia (lvPPA) syndromes. However, little is known about how other patients across the atypical AD syndromic spectrum perform on tests of auditory naming, particularly those with primary visuospatial deficits (Posterior Cortical Atrophy; PCA) and early onset (EOAD) syndromes. Auditory naming tests may be of particular relevance to more accurately measuring anomia in PCA syndrome and in others with visual perceptual deficits. Methods Forty-six patients with biomarker-confirmed AD (16 PCA, 12 lvPPA, 18 multi-domain EOAD), at the stage of mild cognitive impairment or mild dementia, were administered the Auditory Naming Test (ANT). Performance differences between groups were evaluated using one-way ANOVA and post-hoc t-tests. Correlation analyses were used to examine ANT performance in relation to measures of working memory and word retrieval to elucidate cognitive mechanisms underlying word retrieval deficits. Whole-cortex general linear models were generated to determine the relationship between ANT performance and cortical atrophy. Results Based on published cutoffs, out of a total possible score of 50 on the ANT, 56% of PCA patients (mean score = 45.3), 83% of EOAD patients (mean = 39.2), and 83% of lvPPA patients (mean = 29.8) were impaired. Total uncued ANT performance differed across groups, with lvPPA performing most poorly, followed by EOAD, and then PCA. ANT performance was still impaired in lvPPA and EOAD after cuing, while performance in PCA patients improved to the normal range with phonemic cues. ANT performance was also directly correlated with measures of verbal fluency and working memory, and was associated with cortical atrophy in a circumscribed semantic language network. Discussion Auditory confrontation naming is impaired across the syndromic spectrum of AD including in PCA and EOAD, and is likely related to auditory-verbal working memory and verbal fluency which represent the nexus of language and executive functions. The left-lateralized semantic language network was implicated in ANT performance. Auditory naming, in the absence of a visual perceptual demand, may be particularly sensitive to measuring naming deficits in PCA.
Collapse
Affiliation(s)
- Deepti Putcha
- Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Departments of Psychiatry and Neurology, Massachusetts General Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Ana Eustace
- Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Departments of Psychiatry and Neurology, Massachusetts General Hospital, Boston, MA, United States
| | - Nicole Carvalho
- Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Departments of Psychiatry and Neurology, Massachusetts General Hospital, Boston, MA, United States
| | - Bonnie Wong
- Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Departments of Psychiatry and Neurology, Massachusetts General Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Megan Quimby
- Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Departments of Psychiatry and Neurology, Massachusetts General Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| | - Bradford C. Dickerson
- Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Departments of Psychiatry and Neurology, Massachusetts General Hospital, Boston, MA, United States
- Harvard Medical School, Boston, MA, United States
| |
Collapse
|
15
|
Zhang L, Qu J, Ma H, Chen T, Liu T, Zhu D. Exploring Alzheimer's disease: a comprehensive brain connectome-based survey. PSYCHORADIOLOGY 2024; 4:kkad033. [PMID: 38333558 PMCID: PMC10848159 DOI: 10.1093/psyrad/kkad033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 12/21/2023] [Accepted: 01/03/2024] [Indexed: 02/10/2024]
Abstract
Dementia is an escalating global health challenge, with Alzheimer's disease (AD) at its forefront. Substantial evidence highlights the accumulation of AD-related pathological proteins in specific brain regions and their subsequent dissemination throughout the broader area along the brain network, leading to disruptions in both individual brain regions and their interconnections. Although a comprehensive understanding of the neurodegeneration-brain network link is lacking, it is undeniable that brain networks play a pivotal role in the development and progression of AD. To thoroughly elucidate the intricate network of elements and connections constituting the human brain, the concept of the brain connectome was introduced. Research based on the connectome holds immense potential for revealing the mechanisms underlying disease development, and it has become a prominent topic that has attracted the attention of numerous researchers. In this review, we aim to systematically summarize studies on brain networks within the context of AD, critically analyze the strengths and weaknesses of existing methodologies, and offer novel perspectives and insights, intending to serve as inspiration for future research.
Collapse
Affiliation(s)
- Lu Zhang
- Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA
| | - Junqi Qu
- Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA
| | - Haotian Ma
- Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA
| | - Tong Chen
- Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA
| | - Tianming Liu
- Department of Computer Science, The University of Georgia, Athens, GA 30602, USA
| | - Dajiang Zhu
- Department of Computer Science and Engineering, The University of Texas at Arlington, Arlington, TX 76019, USA
| |
Collapse
|
16
|
Hojjati SH, Chiang GC, Butler TA, de Leon M, Gupta A, Li Y, Sabuncu MR, Feiz F, Nayak S, Shteingart J, Ozoria S, Gholipour Picha S, Stern Y, Luchsinger JA, Devanand DP, Razlighi QR. Remote Associations Between Tau and Cortical Amyloid-β Are Stage-Dependent. J Alzheimers Dis 2024; 98:1467-1482. [PMID: 38552116 DOI: 10.3233/jad-231362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/20/2024]
Abstract
Background Histopathologic studies of Alzheimer's disease (AD) suggest that extracellular amyloid-β (Aβ) plaques promote the spread of neurofibrillary tau tangles. However, these two proteinopathies initiate in spatially distinct brain regions, so how they interact during AD progression is unclear. Objective In this study, we utilized Aβ and tau positron emission tomography (PET) scans from 572 older subjects (476 healthy controls (HC), 14 with mild cognitive impairment (MCI), 82 with mild AD), at varying stages of the disease, to investigate to what degree tau is associated with cortical Aβ deposition. Methods Using multiple linear regression models and a pseudo-longitudinal ordering technique, we investigated remote tau-Aβ associations in four pathologic phases of AD progression based on tau spread: 1) no-tau, 2) pre-acceleration, 3) acceleration, and 4) post-acceleration. Results No significant tau-Aβ association was detected in the no-tau phase. In the pre-acceleration phase, the earliest stage of tau deposition, associations emerged between regional tau in medial temporal lobe (MTL) (i.e., entorhinal cortex, parahippocampal gyrus) and cortical Aβ in lateral temporal lobe regions. The strongest tau-Aβ associations were found in the acceleration phase, in which tau in MTL regions was strongly associated with cortical Aβ (i.e., temporal and frontal lobes regions). Strikingly, in the post-acceleration phase, including 96% of symptomatic subjects, tau-Aβ associations were no longer significant. Conclusions The results indicate that associations between tau and Aβ are stage-dependent, which could have important implications for understanding the interplay between these two proteinopathies during the progressive stages of AD.
Collapse
Affiliation(s)
- Seyed Hani Hojjati
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, NY, USA
| | - Gloria C Chiang
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, NY, USA
| | - Tracy A Butler
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, NY, USA
| | - Mony de Leon
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, NY, USA
| | - Ajay Gupta
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
| | - Yi Li
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, NY, USA
| | - Mert R Sabuncu
- Department of Radiology, Weill Cornell Medicine, New York, NY, USA
- Department of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA
| | - Farnia Feiz
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, NY, USA
| | - Siddharth Nayak
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, NY, USA
| | - Jacob Shteingart
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, NY, USA
| | - Sindy Ozoria
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, NY, USA
| | - Saman Gholipour Picha
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, NY, USA
- Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Yaakov Stern
- Departments of Neurology, Psychiatry, GH Sergievsky Center, The Taub Institute for the Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - José A Luchsinger
- Departments of Medicine and Epidemiology, Columbia University Irving Medical Center, New York, NY, USA
| | - Davangere P Devanand
- Division of Geriatric Psychiatry, New York State Psychiatric Institute, Columbia University Irving Medical Center, New York, NY, USA
- Department of Neurology, Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
- Department of Psychiatry, New York State Psychiatric Institute, Columbia University Irving Medical Center, New York, NY, USA
| | - Qolamreza R Razlighi
- Department of Radiology, Brain Health Imaging Institute, Weill Cornell Medicine, New York, NY, USA
| |
Collapse
|
17
|
Mattsson P, Cselényi Z, Forsberg Morén A, Freund-Levi Y, Wahlund LO, Halldin C, Farde L. High Contrast PET Imaging of Subcortical and Allocortical Amyloid-β in Early Alzheimer's Disease Using [11C]AZD2184. J Alzheimers Dis 2024; 98:1391-1401. [PMID: 38552111 DOI: 10.3233/jad-231013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/20/2024]
Abstract
Background Deposits of amyloid-β (Aβ) appear early in Alzheimer's disease (AD). Objective The aim of the present study was to compare the presence of cortical and subcortical Aβ in early AD using positron emission tomography (PET). Methods Eight cognitively unimpaired (CU) subjects, 8 with mild cognitive impairment (MCI) and 8 with mild AD were examined with PET and [11C]AZD2184. A data driven cut-point for Aβ positivity was defined by Gaussian mixture model of isocortex binding potential (BPND) values. Results Sixteen subjects (3 CU, 5 MCI and 8 AD) were Aβ-positive. BPND was lower in subcortical and allocortical regions compared to isocortex. Fifteen of the 16 Aβ-positive subjects displayed Aβ binding in striatum, 14 in thalamus and 10 in allocortical regions. Conclusions Aβ deposits appear to be widespread in early AD. It cannot be excluded that deposits appear simultaneously throughout the whole brain which has implications for improved diagnostics and disease monitoring.
Collapse
Affiliation(s)
- Patrik Mattsson
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet and Stockholm Health Care Services, Stockholm, Sweden
| | - Zsolt Cselényi
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet and Stockholm Health Care Services, Stockholm, Sweden
- PET Science Centre, Personalized Medicine and Biosamples, R&D, AstraZeneca, Stockholm, Sweden
| | - Anton Forsberg Morén
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet and Stockholm Health Care Services, Stockholm, Sweden
| | - Yvonne Freund-Levi
- Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden
- School of Medicine, Örebro University, Örebro, Sweden
- Department of Geriatrics, Örebro University Hospital, Örebro and Södertälje Hospital, Södertälje, Sweden
| | - Lars-Olof Wahlund
- Department of Neurobiology, Care Sciences and Society, Division of Clinical Geriatrics, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden
| | - Christer Halldin
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet and Stockholm Health Care Services, Stockholm, Sweden
| | - Lars Farde
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet and Stockholm Health Care Services, Stockholm, Sweden
| |
Collapse
|
18
|
Pezzoli S, Giorgio J, Martersteck A, Dobyns L, Harrison TM, Jagust WJ. Successful cognitive aging is associated with thicker anterior cingulate cortex and lower tau deposition compared to typical aging. Alzheimers Dement 2024; 20:341-355. [PMID: 37614157 PMCID: PMC10916939 DOI: 10.1002/alz.13438] [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: 04/12/2023] [Revised: 06/30/2023] [Accepted: 08/01/2023] [Indexed: 08/25/2023]
Abstract
INTRODUCTION There is no consensus on either the definition of successful cognitive aging (SA) or the underlying neural mechanisms. METHODS We examined the agreement between new and existing definitions using: (1) a novel measure, the cognitive age gap (SA-CAG, cognitive-predicted age minus chronological age), (2) composite scores for episodic memory (SA-EM), (3) non-memory cognition (SA-NM), and (4) the California Verbal Learning Test (SA-CVLT). RESULTS Fair to moderate strength of agreement was found between the four definitions. Most SA groups showed greater cortical thickness compared to typical aging (TA), especially in the anterior cingulate and midcingulate cortices and medial temporal lobes. Greater hippocampal volume was found in all SA groups except SA-NM. Lower entorhinal 18 F-Flortaucipir (FTP) uptake was found in all SA groups. DISCUSSION These findings suggest that a feature of SA, regardless of its exact definition, is resistance to tau pathology and preserved cortical integrity, especially in the anterior cingulate and midcingulate cortices. HIGHLIGHTS Different approaches have been used to define successful cognitive aging (SA). Regardless of definition, different SA groups have similar brain features. SA individuals have greater anterior cingulate thickness and hippocampal volume. Lower entorhinal tau deposition, but not amyloid beta is related to SA. A combination of cortical integrity and resistance to tau may be features of SA.
Collapse
Affiliation(s)
- Stefania Pezzoli
- Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
- Lawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA
| | - Joseph Giorgio
- Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
- University of NewcastleNewcastleNSWAustralia
| | - Adam Martersteck
- Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
| | - Lindsey Dobyns
- Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
| | - Theresa M. Harrison
- Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
| | - William J. Jagust
- Helen Wills Neuroscience InstituteUniversity of CaliforniaBerkeleyCaliforniaUSA
- Lawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA
| |
Collapse
|
19
|
Kamal F, Morrison C, Dadar M. Investigating the relationship between sleep disturbances and white matter hyperintensities in older adults on the Alzheimer's disease spectrum. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2024; 16:e12553. [PMID: 38476639 PMCID: PMC10927930 DOI: 10.1002/dad2.12553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 12/15/2023] [Accepted: 01/19/2024] [Indexed: 03/14/2024]
Abstract
INTRODUCTION While studies report that sleep disturbance can have negative effects on brain vasculature, its impact on cerebrovascular diseases such as white matter hyperintensities (WMHs) in beta-amyloid-positive older adults remains unexplored. METHODS Sleep disturbance, WMH burden, and cognition in normal controls (NCs), and individuals with mild cognitive impairment (MCI) and Alzheimer's disease (AD), were examined at baseline and longitudinally. A total of 912 amyloid-positive participants were included (198 NC, 504 MCI, and 210 AD). RESULTS Individuals with AD reported more sleep disturbances than NC and MCI participants. Those with sleep disturbances had more WMHs than those without sleep disturbances in the AD group. Mediation analysis revealed an effect of regional WMH burden on the relationship between sleep disturbance and future cognition. DISCUSSION These results suggest that WMH burden and sleep disturbance increase from aging to AD. Sleep disturbance decreases cognition through increases in WMH burden. Improved sleep could mitigate the impact of WMH accumulation and cognitive decline.
Collapse
Affiliation(s)
- Farooq Kamal
- Department of PsychiatryMcGill UniversityMontrealQuebecCanada
- Douglas Mental Health University InstituteMontrealQuebecCanada
| | | | - Mahsa Dadar
- Department of PsychiatryMcGill UniversityMontrealQuebecCanada
- Douglas Mental Health University InstituteMontrealQuebecCanada
| |
Collapse
|
20
|
Mitsunaga S, Fujito N, Nakaoka H, Imazeki R, Nagata E, Inoue I. Detection of APP gene recombinant in human blood plasma. Sci Rep 2023; 13:21703. [PMID: 38066066 PMCID: PMC10709617 DOI: 10.1038/s41598-023-48993-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 12/02/2023] [Indexed: 12/18/2023] Open
Abstract
The pathogenesis of Alzheimer's disease (AD) is believed to involve the accumulation of amyloid-β in the brain, which is produced by the sequential cleavage of amyloid precursor protein (APP) by β-secretase and γ-secretase. Recently, analysis of genomic DNA and mRNA from postmortem brain neurons has revealed intra-exonic recombinants of APP (gencDNA), which have been implicated in the accumulation of amyloid-β. In this study, we computationally analyzed publicly available sequence data (SRA) using probe sequences we constructed to screen APP gencDNAs. APP gencDNAs were detected in SRAs constructed from both genomic DNA and RNA obtained from the postmortem brain and in the SRA constructed from plasma cell-free mRNA (cf-mRNA). The SRA constructed from plasma cf-mRNA showed a significant difference in the number of APP gencDNA reads between SAD and NCI: the p-value from the Mann-Whitney U test was 5.14 × 10-6. The transcripts were also found in circulating nucleic acids (CNA) from our plasma samples with NGS analysis. These data indicate that transcripts of APP gencDNA can be detected in blood plasma and suggest the possibility of using them as blood biomarkers for Alzheimer's disease.
Collapse
Affiliation(s)
- Shigeki Mitsunaga
- Laboratory of Human Genetics, National Institute of Genetics, 1111 Yata, Mishima, Shizuoka, 411-8540, Japan.
| | - Naoko Fujito
- Laboratory of Human Genetics, National Institute of Genetics, 1111 Yata, Mishima, Shizuoka, 411-8540, Japan
- Department of Genetics, The Graduate University for Advanced Studies (SOKENDAI), Mishima, 411-8540, Japan
| | - Hirofumi Nakaoka
- Department of Cancer Genome Research, Sasaki Institute, Sasaki Foundation, Chiyoda-ku, Tokyo, 101-0062, Japan
| | - Ryoko Imazeki
- Department of Neurology, Tokai University School of Medicine, Isehara, Japan
| | - Eiichiro Nagata
- Department of Neurology, Tokai University School of Medicine, Isehara, Japan
| | - Ituro Inoue
- Laboratory of Human Genetics, National Institute of Genetics, 1111 Yata, Mishima, Shizuoka, 411-8540, Japan.
| |
Collapse
|
21
|
Yakoub Y, Ashton NJ, Strikwerda-Brown C, Montoliu-Gaya L, Karikari TK, Kac PR, Gonzalez-Ortiz F, Gallego-Rudolf J, Meyer PF, St-Onge F, Schöll M, Soucy JP, Breitner JCS, Zetterberg H, Blennow K, Poirier J, Villeneuve S. Longitudinal blood biomarker trajectories in preclinical Alzheimer's disease. Alzheimers Dement 2023; 19:5620-5631. [PMID: 37294682 DOI: 10.1002/alz.13318] [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: 12/26/2022] [Revised: 04/03/2023] [Accepted: 05/11/2023] [Indexed: 06/11/2023]
Abstract
INTRODUCTION Plasma biomarkers are altered years prior to Alzheimer's disease (AD) clinical onset. METHODS We measured longitudinal changes in plasma amyloid-beta (Aβ)42/40 ratio, pTau181, pTau231, neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP) in a cohort of older adults at risk of AD (n = 373 total, n = 229 with Aβ and tau positron emission tomography [PET] scans) considering genetic and demographic factors as possible modifiers of these markers' progression. RESULTS Aβ42/40 ratio concentrations decreased, while NfL and GFAP values increased over the 4-year follow-up. Apolipoprotein E (APOE) ε4 carriers showed faster increase in plasma pTau181 than non-carriers. Older individuals showed a faster increase in plasma NfL, and females showed a faster increase in plasma GFAP values. In the PET subsample, individuals both Aβ-PET and tau-PET positive showed faster plasma pTau181 and GFAP increase compared to PET-negative individuals. DISCUSSION Plasma markers can track biological change over time, with plasma pTau181 and GFAP markers showing longitudinal change in individuals with preclinical AD. HIGHLIGHTS Longitudinal increase of plasma pTau181 and glial fibrillary acidic protein (GFAP) can be measured in the preclinical phase of AD. Apolipoprotein E ε4 carriers experience faster increase in plasma pTau181 over time than non-carriers. Female sex showed accelerated increase in plasma GFAP over time compared to males. Aβ42/40 and pTau231 values are already abnormal at baseline in individuals with both amyloid and tau PET burden.
Collapse
Affiliation(s)
- Yara Yakoub
- Douglas Mental Health University Institute, Centre for Studies on the Prevention of Alzheimer's Disease (StoP-AD), Montreal, Quebec, Canada
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
- King's College London, Institute of Psychiatry, Psychology & Neuroscience, Maurice Wohl Clinical Neuroscience Institute, London, UK
- NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London & Maudsley NHS Foundation, London, UK
| | - Cherie Strikwerda-Brown
- Douglas Mental Health University Institute, Centre for Studies on the Prevention of Alzheimer's Disease (StoP-AD), Montreal, Quebec, Canada
| | - Laia Montoliu-Gaya
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Przemysław R Kac
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Fernando Gonzalez-Ortiz
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Jonathan Gallego-Rudolf
- Douglas Mental Health University Institute, Centre for Studies on the Prevention of Alzheimer's Disease (StoP-AD), Montreal, Quebec, Canada
| | - Pierre-François Meyer
- Douglas Mental Health University Institute, Centre for Studies on the Prevention of Alzheimer's Disease (StoP-AD), Montreal, Quebec, Canada
| | - Frédéric St-Onge
- Douglas Mental Health University Institute, Centre for Studies on the Prevention of Alzheimer's Disease (StoP-AD), Montreal, Quebec, Canada
| | - Michael Schöll
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Jean-Paul Soucy
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - John C S Breitner
- Douglas Mental Health University Institute, Centre for Studies on the Prevention of Alzheimer's Disease (StoP-AD), Montreal, Quebec, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada
- McGill Centre for Integrative Neuroscience, McGill University, Montreal, Quebec, Canada
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- UW Department of Medicine, School of Medicine and Public Health, Madison, WI, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Judes Poirier
- Douglas Mental Health University Institute, Centre for Studies on the Prevention of Alzheimer's Disease (StoP-AD), Montreal, Quebec, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Sylvia Villeneuve
- Douglas Mental Health University Institute, Centre for Studies on the Prevention of Alzheimer's Disease (StoP-AD), Montreal, Quebec, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| |
Collapse
|
22
|
Rezaii N, Hochberg D, Quimby M, Wong B, McGinnis S, Dickerson BC, Putcha D. Language Uncovers Visuospatial Dysfunction in Posterior Cortical Atrophy: A Natural Language Processing Approach. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.21.23298864. [PMID: 38045263 PMCID: PMC10690359 DOI: 10.1101/2023.11.21.23298864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
Introduction Posterior Cortical Atrophy (PCA) is a syndrome characterized by a progressive decline in higher-order visuospatial processing, leading to symptoms such as space perception deficit, simultanagnosia, and object perception impairment. While PCA is primarily known for its impact on visuospatial abilities, recent studies have documented language abnormalities in PCA patients. This study aims to delineate the nature and origin of language impairments in PCA, hypothesizing that language deficits reflect the visuospatial processing impairments of the disease. Methods We compared the language samples of 25 patients with PCA with age-matched cognitively normal (CN) individuals across two distinct tasks: a visually-dependent picture description and a visually-independent job description task. We extracted word frequency, word utterance latency, and spatial relational words for this comparison. We then conducted an in-depth analysis of the language used in the picture description task to identify specific linguistic indicators that reflect the visuospatial processing deficits of PCA. Results Patients with PCA showed significant language deficits in the visually-dependent task, characterized by higher word frequency, prolonged utterance latency, and fewer spatial relational words, but not in the visually-independent task. An in-depth analysis of the picture description task further showed that PCA patients struggled to identify certain visual elements as well as the overall theme of the picture. A predictive model based on these language features distinguished PCA patients from CN individuals with high classification accuracy. Discussion The findings indicate that language is a sensitive behavioral construct to detect visuospatial processing abnormalities of PCA. These insights offer theoretical and clinical avenues for understanding and managing PCA, underscoring language as a crucial marker for the visuospatial deficits of this atypical variant of Alzheimer's disease.
Collapse
Affiliation(s)
- Neguine Rezaii
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114
| | - Daisy Hochberg
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114
| | - Megan Quimby
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114
| | - Bonnie Wong
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114
| | - Scott McGinnis
- Center for Brain Mind Medicine, Department of Neurology, Brigham & Women’s Hospital, Boston, MA 02115
| | - Bradford C Dickerson
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129
- Alzheimer’s Disease Research Center, Massachusetts General Hospital, Charlestown, MA 02129
| | - Deepti Putcha
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114
| |
Collapse
|
23
|
Cho H, Mundada NS, Apostolova LG, Carrillo MC, Shankar R, Amuiri AN, Zeltzer E, Windon CC, Soleimani-Meigooni DN, Tanner JA, Heath CL, Lesman-Segev OH, Aisen P, Eloyan A, Lee HS, Hammers DB, Kirby K, Dage JL, Fagan A, Foroud T, Grinberg LT, Jack CR, Kramer J, Kukull WA, Murray ME, Nudelman K, Toga A, Vemuri P, Atri A, Day GS, Duara R, Graff-Radford NR, Honig LS, Jones DT, Masdeu J, Mendez M, Musiek E, Onyike CU, Riddle M, Rogalski EJ, Salloway S, Sha S, Turner RS, Wingo TS, Wolk DA, Koeppe R, Iaccarino L, Dickerson BC, La Joie R, Rabinovici GD. Amyloid and tau-PET in early-onset AD: Baseline data from the Longitudinal Early-onset Alzheimer's Disease Study (LEADS). Alzheimers Dement 2023; 19 Suppl 9:S98-S114. [PMID: 37690109 PMCID: PMC10807231 DOI: 10.1002/alz.13453] [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: 04/14/2023] [Revised: 08/07/2023] [Accepted: 08/08/2023] [Indexed: 09/12/2023]
Abstract
INTRODUCTION We aimed to describe baseline amyloid-beta (Aβ) and tau-positron emission tomograrphy (PET) from Longitudinal Early-onset Alzheimer's Disease Study (LEADS), a prospective multi-site observational study of sporadic early-onset Alzheimer's disease (EOAD). METHODS We analyzed baseline [18F]Florbetaben (Aβ) and [18F]Flortaucipir (tau)-PET from cognitively impaired participants with a clinical diagnosis of mild cognitive impairment (MCI) or AD dementia aged < 65 years. Florbetaben scans were used to distinguish cognitively impaired participants with EOAD (Aβ+) from EOnonAD (Aβ-) based on the combination of visual read by expert reader and image quantification. RESULTS 243/321 (75.7%) of participants were assigned to the EOAD group based on amyloid-PET; 231 (95.1%) of them were tau-PET positive (A+T+). Tau-PET signal was elevated across cortical regions with a parietal-predominant pattern, and higher burden was observed in younger and female EOAD participants. DISCUSSION LEADS data emphasizes the importance of biomarkers to enhance diagnostic accuracy in EOAD. The advanced tau-PET binding at baseline might have implications for therapeutic strategies in patients with EOAD. HIGHLIGHTS 72% of patients with clinical EOAD were positive on both amyloid- and tau-PET. Amyloid-positive patients with EOAD had high tau-PET signal across cortical regions. In EOAD, tau-PET mediated the relationship between amyloid-PET and MMSE. Among EOAD patients, younger onset and female sex were associated with higher tau-PET.
Collapse
Affiliation(s)
- Hanna Cho
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
- Global Brain Health Institute, University of California, San Francisco, California, USA
| | - Nidhi S Mundada
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Liana G Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine Indianapolis, Indianapolis, Indiana, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Maria C Carrillo
- Medical & Scientific Relations Division, Alzheimer's Association, Chicago, Illinois, USA
| | - Ranjani Shankar
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Alinda N Amuiri
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Ehud Zeltzer
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Charles C Windon
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - David N Soleimani-Meigooni
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Jeremy A Tanner
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Courtney Lawhn Heath
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Orit H Lesman-Segev
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
- Department of Diagnostic Imaging, Sheba Medical Center, Tel HaShomer, Israel
| | - Paul Aisen
- Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, California, USA
| | - Ani Eloyan
- Department of Biostatistics, Center for Statistical Sciences, Brown University, Rhode Island, USA
| | - Hye Sun Lee
- Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Dustin B Hammers
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Kala Kirby
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Jeffrey L Dage
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Anne Fagan
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Lea T Grinberg
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
- Department of Pathology, University of California - San Francisco, San Francisco, California, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Joel Kramer
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Walter A Kukull
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Melissa E Murray
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA
| | - Kelly Nudelman
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Arthur Toga
- Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Los Angeles, California, USA
| | | | - Alireza Atri
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Gregory S Day
- Department of Neurology, Mayo Clinic, Jacksonville, Florida, USA
| | - Ranjan Duara
- Wien Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami, Florida, USA
| | | | - Lawrence S Honig
- Taub Institute and Department of Neurology, Columbia University Irving Medical Center, New York, New York, USA
| | - David T Jones
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Joseph Masdeu
- Nantz National Alzheimer Center, Houston Methodist and Weill Cornell Medicine, Houston, Texas, USA
| | - Mario Mendez
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Erik Musiek
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Chiadi U Onyike
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Meghan Riddle
- Department of Neurology, Alpert Medical School, Brown University, Rhode Island, USA
| | - Emily J Rogalski
- Department of Psychiatry and Behavioral Sciences, Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Stephen Salloway
- Department of Neurology, Alpert Medical School, Brown University, Rhode Island, USA
| | - Sharon Sha
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, California, USA
| | | | - Thomas S Wingo
- Department of Neurology and Human Genetics, Emory University School of Medicine, Atlanta, Georgia, USA
| | - David A Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Robert Koeppe
- Division of Nuclear Medicine, Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Leonardo Iaccarino
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Bradford C Dickerson
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Renaud La Joie
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
| | - Gil D Rabinovici
- Memory and Aging Center, UCSF Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, California, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| |
Collapse
|
24
|
Touroutoglou A, Katsumi Y, Brickhouse M, Zaitsev A, Eckbo R, Aisen P, Beckett L, Dage JL, Eloyan A, Foroud T, Ghetti B, Griffin P, Hammers D, Jack CR, Kramer JH, Iaccarino L, Joie RL, Mundada NS, Koeppe R, Kukull WA, Murray ME, Nudelman K, Polsinelli AJ, Rumbaugh M, Soleimani-Meigooni DN, Toga A, Vemuri P, Atri A, Day GS, Duara R, Graff-Radford NR, Honig LS, Jones DT, Masdeu JC, Mendez MF, Musiek E, Onyike CU, Riddle M, Rogalski E, Salloway S, Sha S, Turner RS, Wingo TS, Wolk DA, Womack K, Carrillo MC, Rabinovici GD, Apostolova LG, Dickerson BC. The Sporadic Early-onset Alzheimer's Disease Signature Of Atrophy: Preliminary Findings From The Longitudinal Early-onset Alzheimer's Disease Study (LEADS) Cohort. Alzheimers Dement 2023; 19 Suppl 9:S74-S88. [PMID: 37850549 PMCID: PMC10829523 DOI: 10.1002/alz.13466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 07/13/2023] [Accepted: 07/18/2023] [Indexed: 10/19/2023]
Abstract
INTRODUCTION Magnetic resonance imaging (MRI) research has advanced our understanding of neurodegeneration in sporadic early-onset Alzheimer's disease (EOAD) but studies include small samples, mostly amnestic EOAD, and have not focused on developing an MRI biomarker. METHODS We analyzed MRI scans to define the sporadic EOAD-signature atrophy in a small sample (n = 25) of Massachusetts General Hospital (MGH) EOAD patients, investigated its reproducibility in the large longitudinal early-onset Alzheimer's disease study (LEADS) sample (n = 211), and investigated the relationship of the magnitude of atrophy with cognitive impairment. RESULTS The EOAD-signature atrophy was replicated across the two cohorts, with prominent atrophy in the caudal lateral temporal cortex, inferior parietal lobule, and posterior cingulate and precuneus cortices, and with relative sparing of the medial temporal lobe. The magnitude of EOAD-signature atrophy was associated with the severity of cognitive impairment. DISCUSSION The EOAD-signature atrophy is a reliable and clinically valid biomarker of AD-related neurodegeneration that could be used in clinical trials for EOAD. HIGHLIGHTS We developed an early-onset Alzheimer's disease (EOAD)-signature of atrophy based on magnetic resonance imaging (MRI) scans. EOAD signature was robustly reproducible across two independent patient cohorts. EOAD signature included prominent atrophy in parietal and posterior temporal cortex. The EOAD-signature atrophy was associated with the severity of cognitive impairment. EOAD signature is a reliable and clinically valid biomarker of neurodegeneration.
Collapse
Affiliation(s)
- Alexandra Touroutoglou
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Yuta Katsumi
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Michael Brickhouse
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Alexander Zaitsev
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Ryan Eckbo
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Paul Aisen
- Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, California, USA
| | - Laurel Beckett
- Department of Public Health Sciences, University of California - Davis, Davis, California, USA
| | - Jeffrey L Dage
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Ani Eloyan
- Department of Biostatistics, Center for Statistical Sciences, Brown University, Providence, Rhode Island, USA
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Bernardino Ghetti
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Percy Griffin
- Medical & Scientific Relations Division, Alzheimer's Association, Chicago, Illinois, USA
| | - Dustin Hammers
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Joel H Kramer
- Department of Neurology, University of California - San Francisco, San Francisco, California, USA
| | - Leonardo Iaccarino
- Department of Neurology, University of California - San Francisco, San Francisco, California, USA
| | - Renaud La Joie
- Department of Neurology, University of California - San Francisco, San Francisco, California, USA
| | - Nidhi S Mundada
- Department of Neurology, University of California - San Francisco, San Francisco, California, USA
| | - Robert Koeppe
- Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Walter A Kukull
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Melissa E Murray
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA
| | - Kelly Nudelman
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Angelina J Polsinelli
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Malia Rumbaugh
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | | | - Arthur Toga
- Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Los Angeles, California, USA
| | | | - Alireza Atri
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | - Gregory S Day
- Department of Neurology, Mayo Clinic in Florida, Jacksonville, Florida, USA
| | - Ranjan Duara
- Wien Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami, Florida, USA
| | | | - Lawrence S Honig
- Taub Institute and Department of Neurology, Columbia University Irving Medical Center, New York, New York, USA
| | - David T Jones
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Joseph C Masdeu
- Nantz National Alzheimer Center, Houston Methodist and Weill Cornell Medicine, Houston, Texas, USA
| | - Mario F Mendez
- Department of Neurology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Erik Musiek
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Chiadi U Onyike
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Meghan Riddle
- Department of Neurology, Alpert Medical School, Brown University, Providence, Rhode Island, USA
| | - Emily Rogalski
- Department of Psychiatry and Behavioral Sciences, Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Stephen Salloway
- Department of Neurology, Alpert Medical School, Brown University, Providence, Rhode Island, USA
| | - Sharon Sha
- Department of Neurology & Neurological Sciences, Stanford University, Palo Alto, California, USA
| | - R Scott Turner
- Department of Neurology, Georgetown University, Washington, D.C., USA
| | - Thomas S Wingo
- Department of Neurology and Human Genetics, Emory University School of Medicine, Atlanta, Georgia, USA
| | - David A Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Kyle Womack
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Maria C Carrillo
- Medical & Scientific Relations Division, Alzheimer's Association, Chicago, Illinois, USA
| | - Gil D Rabinovici
- Department of Neurology, University of California - San Francisco, San Francisco, California, USA
| | - Liana G Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Department of Radiology and Imaging Sciences, Center for Neuroimaging, Indiana University School of Medicine Indianapolis, Indianapolis, Indiana, USA
| | - Bradford C Dickerson
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| |
Collapse
|
25
|
Perosa V, Auger CA, Zanon Zotin MC, Oltmer J, Frosch MP, Viswanathan A, Greenberg SM, van Veluw SJ. Histopathological Correlates of Lobar Microbleeds in False-Positive Cerebral Amyloid Angiopathy Cases. Ann Neurol 2023; 94:856-870. [PMID: 37548609 DOI: 10.1002/ana.26761] [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: 03/16/2023] [Revised: 07/05/2023] [Accepted: 07/31/2023] [Indexed: 08/08/2023]
Abstract
OBJECTIVE A definite diagnosis of cerebral amyloid angiopathy (CAA), characterized by the accumulation of amyloid β in walls of cerebral small vessels, can only be obtained through pathological examination. A diagnosis of probable CAA during life relies on the presence of hemorrhagic markers, including lobar cerebral microbleeds (CMBs). The aim of this project was to study the histopathological correlates of lobar CMBs in false-positive CAA cases. METHODS In 3 patients who met criteria for probable CAA during life, but showed no CAA upon neuropathological examination, lobar CMBs were counted on ex vivo 3T magnetic resonance imaging (MRI) and on ex vivo 7T MRI. Areas with lobar CMBs were next sampled and cut into serial sections, on which the CMBs were then identified. RESULTS Collectively, there were 25 lobar CMBs on in vivo MRI and 22 on ex vivo 3T MRI of the analyzed hemispheres. On ex vivo MRI, we targeted 12 CMBs for sampling, and definite histopathological correlates were retrieved for 9 of them, of which 7 were true CMBs. No CAA was found on any of the serial sections. The "culprit vessels" associated with the true CMBs instead showed moderate to severe arteriolosclerosis. Furthermore, CMBs in false-positive CAA cases tended to be located more often in the juxtacortical or subcortical white matter than in the cortical ribbon. INTERPRETATION These findings suggest that arteriolosclerosis can generate lobar CMBs and that more detailed investigations into the exact localization of CMBs with respect to the cortical ribbon could potentially aid the diagnosis of CAA during life. ANN NEUROL 2023;94:856-870.
Collapse
Affiliation(s)
- Valentina Perosa
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Corinne A Auger
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Maria Clara Zanon Zotin
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Center for Imaging Sciences and Medical Physics, Department of Medical Imaging, Hematology, and Clinical Oncology, Ribeirão Preto Medical School, University of São Paulo, São Paulo, Brazil
| | - Jan Oltmer
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Matthew P Frosch
- Department of Neuropathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Anand Viswanathan
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Steven M Greenberg
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Susanne J van Veluw
- J. Philip Kistler Stroke Research Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- MassGeneral Institute for Neurodegenerative Disease, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| |
Collapse
|
26
|
Sun Y, Qiao Y, Guo J, Hou W, Chen Y, Peng D. The preservation of right cingulum fibers in subjective cognitive decline of preclinical phase of Alzheimer's disease. Front Aging Neurosci 2023; 15:1223697. [PMID: 37965494 PMCID: PMC10642356 DOI: 10.3389/fnagi.2023.1223697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 10/13/2023] [Indexed: 11/16/2023] Open
Abstract
Introduction Subjective cognitive decline (SCD) with a positive amyloid burden has been recognized as the earliest clinical symptom of the preclinical phase of Alzheimers disease (AD), providing invaluable opportunities to improve our understanding of the natural history of AD and determine strategies for early therapeutic interventions. Methods The microstructure of white matter in patients showing SCD in the preclinical phase of AD (SCD of pre-AD) was evaluated using diffusion images, and voxel-wise fractional anisotropy (FA), mean diffusivity (MD), and axial and radial diffusivities were assessed and compared among participant groups. Significant clusters in the tracts were extracted to determine their associations with alterations in the cognitive domains. Results We found that individuals with SCD of pre-AD may have subclinical episodic memory impairment associated with the global amyloid burden. Meanwhile, we found significantly reduced FA and λ1 in the right cingulum (cingulate and hippocampus) in AD dementia, while significantly increased FA and decreased MD as well as λ23 in the SCD of pre-AD group in comparison with the HC group. Discussion In conclusion, increased white matter microstructural integrity in the right cingulum (cingulate and hippocampus) may indicate compensation for short-term episodic memory in individuals with SCD of pre-AD in comparison with individuals with AD and healthy elderly individuals.
Collapse
Affiliation(s)
- Yu Sun
- Department of Neurology, China-Japan Friendship Hospital, Beijing, China
| | - Yanan Qiao
- Department of Neurology, China-Japan Friendship Hospital, Beijing, China
| | - Jing Guo
- Department of Neurology, China-Japan Friendship Hospital, Beijing, China
| | - Wenjie Hou
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Yaojing Chen
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Dantao Peng
- Department of Neurology, China-Japan Friendship Hospital, Beijing, China
| |
Collapse
|
27
|
Mantyh WG, Cochran JN, Taylor JW, Broce IJ, Geier EG, Bonham LW, Anderson AG, Sirkis DW, Joie RL, Iaccarino L, Chaudhary K, Edwards L, Strom A, Grant H, Allen IE, Miller ZA, Gorno‐Tempini ML, Kramer JH, Miller BL, Desikan RS, Rabinovici GD, Yokoyama JS. Early-onset Alzheimer's disease explained by polygenic risk of late-onset disease? ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12482. [PMID: 37780862 PMCID: PMC10535074 DOI: 10.1002/dad2.12482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 08/28/2023] [Accepted: 09/01/2023] [Indexed: 10/03/2023]
Abstract
Early-onset Alzheimer's disease (AD) is highly heritable, yet only 10% of cases are associated with known pathogenic mutations. For early-onset AD patients without an identified autosomal dominant cause, we hypothesized that their early-onset disease reflects further enrichment of the common risk-conferring single nucleotide polymorphisms associated with late-onset AD. We applied a previously validated polygenic hazard score for late-onset AD to 193 consecutive patients diagnosed at our tertiary dementia referral center with symptomatic early-onset AD. For comparison, we included 179 participants with late-onset AD and 70 healthy controls. Polygenic hazard scores were similar in early- versus late-onset AD. The polygenic hazard score was not associated with age-of-onset or disease biomarkers within early-onset AD. Early-onset AD does not represent an extreme enrichment of the common single nucleotide polymorphisms associated with late-onset AD. Further exploration of novel genetic risk factors of this highly heritable disease is warranted.Highlights: There is a unique genetic architecture of early- versus late-onset Alzheimer's disease (AD).Late-onset AD polygenic risk is not an explanation for early-onset AD.Polygenic risk of late-onset AD does not predict early-onset AD biology.Unique genetic architecture of early- versus late-onset AD parallels AD heterogeneity.
Collapse
Affiliation(s)
- William G. Mantyh
- Department of NeurologyUniversity of MinnesotaMinneapolisMinnesotaUSA
| | | | | | - Iris J. Broce
- Memory and Aging CenterDepartment of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Ethan G. Geier
- Memory and Aging CenterDepartment of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Luke W. Bonham
- Memory and Aging CenterDepartment of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | | | - Daniel W. Sirkis
- Memory and Aging CenterDepartment of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Renaud La Joie
- Memory and Aging CenterDepartment of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Leonardo Iaccarino
- Memory and Aging CenterDepartment of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Kiran Chaudhary
- Memory and Aging CenterDepartment of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Lauren Edwards
- Memory and Aging CenterDepartment of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Amelia Strom
- Memory and Aging CenterDepartment of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Harli Grant
- Memory and Aging CenterDepartment of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Isabel E. Allen
- Department of Epidemiology and BiostatisticsUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Zachary A. Miller
- Memory and Aging CenterDepartment of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Marilu L. Gorno‐Tempini
- Memory and Aging CenterDepartment of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Joel H. Kramer
- Memory and Aging CenterDepartment of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Bruce L. Miller
- Memory and Aging CenterDepartment of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Rahul S. Desikan
- Memory and Aging CenterDepartment of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| | - Gil D. Rabinovici
- Memory and Aging CenterDepartment of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of California San FranciscoSan FranciscoCaliforniaUSA
- Life Sciences DivisionLawrence Berkeley National LaboratoryBerkeleyCaliforniaUSA
| | - Jennifer S. Yokoyama
- Memory and Aging CenterDepartment of NeurologyUniversity of California San FranciscoSan FranciscoCaliforniaUSA
| |
Collapse
|
28
|
Vogel JW, Corriveau-Lecavalier N, Franzmeier N, Pereira JB, Brown JA, Maass A, Botha H, Seeley WW, Bassett DS, Jones DT, Ewers M. Connectome-based modelling of neurodegenerative diseases: towards precision medicine and mechanistic insight. Nat Rev Neurosci 2023; 24:620-639. [PMID: 37620599 DOI: 10.1038/s41583-023-00731-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/26/2023] [Indexed: 08/26/2023]
Abstract
Neurodegenerative diseases are the most common cause of dementia. Although their underlying molecular pathologies have been identified, there is substantial heterogeneity in the patterns of progressive brain alterations across and within these diseases. Recent advances in neuroimaging methods have revealed that pathological proteins accumulate along specific macroscale brain networks, implicating the network architecture of the brain in the system-level pathophysiology of neurodegenerative diseases. However, the extent to which 'network-based neurodegeneration' applies across the wide range of neurodegenerative disorders remains unclear. Here, we discuss the state-of-the-art of neuroimaging-based connectomics for the mapping and prediction of neurodegenerative processes. We review findings supporting brain networks as passive conduits through which pathological proteins spread. As an alternative view, we also discuss complementary work suggesting that network alterations actively modulate the spreading of pathological proteins between connected brain regions. We conclude this Perspective by proposing an integrative framework in which connectome-based models can be advanced along three dimensions of innovation: incorporating parameters that modulate propagation behaviour on the basis of measurable biological features; building patient-tailored models that use individual-level information and allowing model parameters to interact dynamically over time. We discuss promises and pitfalls of these strategies for improving disease insights and moving towards precision medicine.
Collapse
Affiliation(s)
- Jacob W Vogel
- Department of Clinical Sciences, SciLifeLab, Lund University, Lund, Sweden.
| | - Nick Corriveau-Lecavalier
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN, USA
| | - Nicolai Franzmeier
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Acadamy, University of Gothenburg, Mölndal and Gothenburg, Sweden
| | - Joana B Pereira
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
- Neuro Division, Department of Clinical Neurosciences, Karolinska Institute, Stockholm, Sweden
| | - Jesse A Brown
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Anne Maass
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - William W Seeley
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
- Department of Pathology, University of California, San Francisco, CA, USA
| | - Dani S Bassett
- Departments of Bioengineering, Electrical and Systems Engineering, Physics and Astronomy, Neurology and Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Santa Fe Institute, Santa Fe, NM, USA
| | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Michael Ewers
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany.
| |
Collapse
|
29
|
Markova TZ, Ciampa CJ, Parent JH, LaPoint MR, D'Esposito M, Jagust WJ, Berry AS. Poorer aging trajectories are associated with elevated serotonin synthesis capacity. Mol Psychiatry 2023; 28:4390-4398. [PMID: 37460847 PMCID: PMC10792105 DOI: 10.1038/s41380-023-02177-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 06/28/2023] [Accepted: 06/30/2023] [Indexed: 01/18/2024]
Abstract
The dorsal raphe nucleus (DRN) is one of the earliest targets of Alzheimer's disease-related tau pathology and is a major source of brain serotonin. We used [18F]Fluoro-m-tyrosine ([18F]FMT) PET imaging to measure serotonin synthesis capacity in the DRN in 111 healthy adults (18-85 years-old). Similar to reports in catecholamine systems, we found elevated serotonin synthesis capacity in older adults relative to young. To establish the structural and functional context within which serotonin synthesis capacity is elevated in aging, we examined relationships among DRN [18F]FMT net tracer influx (Ki) and longitudinal changes in cortical thickness using magnetic resonance imaging, longitudinal changes in self-reported depression symptoms, and AD-related tau and β-amyloid (Aβ) pathology using cross-sectional [18F]Flortaucipir and [11C]Pittsburgh compound-B PET respectively. Together, our findings point to elevated DRN [18F]FMT Ki as a marker of poorer aging trajectories. Older adults with highest serotonin synthesis capacity showed greatest temporal lobe cortical atrophy. Cortical atrophy was associated with increasing depression symptoms over time, and these effects appeared to be strongest in individuals with highest serotonin synthesis capacity. We did not find direct relationships between serotonin synthesis capacity and AD-related pathology. Exploratory analyses revealed nuanced effects of sex within the older adult group. Older adult females showed the highest DRN synthesis capacity and exhibited the strongest relationships between entorhinal cortex tau pathology and increasing depression symptoms. Together these findings reveal PET measurement of the serotonin system to be a promising marker of aging trajectories relevant to both AD and affective changes in older age.
Collapse
Affiliation(s)
| | | | | | - Molly R LaPoint
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, 94720, USA
| | - Mark D'Esposito
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, 94720, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, 94720, USA
- Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | | |
Collapse
|
30
|
Lesman-Segev OH, Golan S, Springer RR, Livny A, Lin HM, Yuxia O, Zadok M, Ganmore I, Heymann A, Hoffmann C, Domachevsky L, Beeri MS. Amyloid deposition and small vessel disease are associated with cognitive function in older adults with type 2 diabetes. RESEARCH SQUARE 2023:rs.3.rs-3373943. [PMID: 37841857 PMCID: PMC10571611 DOI: 10.21203/rs.3.rs-3373943/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/17/2023]
Abstract
Diabetes is associated with cognitive decline, but the underlying mechanisms are complex and their relationship with Alzheimer's Disease biomarkers is not fully understood. We assessed the association of small vessel disease (SVD) and amyloid burden with cognitive functioning in 47 non-demented older adults with type-2 diabetes from the Israel Diabetes and Cognitive Decline Study (mean age 78Y, 64% females). FLAIR-MRI, Vizamyl amyloid-PET, and T1W-MRI quantified white matter hyperintensities as a measure of SVD, amyloid burden, and gray matter (GM) volume, respectively. Mean hemoglobin A1c levels and duration of type-2 diabetes were used as measures of diabetic control. Cholesterol level and blood pressure were used as measures of cardiovascular risk. A broad neuropsychological battery assessed cognition. Linear regression models revealed that both higher SVD and amyloid burden were associated with lower cognitive functioning. Additional adjustments for type-2 diabetes-related characteristics, GM volume, and cardiovascular risk did not alter the results. The association of amyloid with cognition remained unchanged after further adjustment for SVD. Our findings suggest that SVD and amyloid pathology may independently contribute to lower cognitive functioning in non-demented older adults with type-2 diabetes, supporting a multimodal approach for diagnosing, preventing, and treating cognitive decline in this population.
Collapse
|
31
|
Grayson JM, Short SM, Lee CJ, Park N, Marsac C, Sette A, Lindestam Arlehamn CS, Leng XI, Lockhart SN, Craft S. T cell exhaustion is associated with cognitive status and amyloid accumulation in Alzheimer's disease. Sci Rep 2023; 13:15779. [PMID: 37737298 PMCID: PMC10516910 DOI: 10.1038/s41598-023-42708-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 09/13/2023] [Indexed: 09/23/2023] Open
Abstract
Studies over the last 100 years have suggested a link between inflammation, infectious disease, and Alzheimer's Disease (AD). Understanding how the immune system changes during the development of AD may facilitate new treatments. Here, we studied an aging cohort who had been assessed for AD pathology with amyloid positron emission tomography and cognitive testing, and conducted high dimensional flow cytometry on peripheral blood mononuclear and cerebrospinal fluid cells. Participants were assigned a classification of being amyloid negative cognitively normal, amyloid positive cognitively normal (APCN), or amyloid positive mild cognitive impairment (APMCI), an early stage of AD. We observed major alterations in the peripheral innate immune system including increased myeloid and plasmacytoid dendritic cells in the blood of APMCI participants. When the adaptive immune system was examined, amyloid positive participants, regardless of cognitive status, had increased CD3+ T cells. Further analyses of CD4+ and CD8+ T cells revealed that APMCI participants had an increase in more differentiated phenotype T cells, such as effector memory and effector memory CD45RA expressing (TEMRA), compared to those with normal cognition. When T cell function was measured, we observed that T cells from APCN participants had increased IFNγ+GzB- producing cells compared to the other participants. In contrast, we demonstrate that APMCI participants had a major increase in T cells that lacked cytokine production following restimulation and expressed increased levels of PD-1 and Tox, suggesting these are exhausted cells. Rejuvenation of these cells may provide a potential treatment for AD.
Collapse
Affiliation(s)
- Jason M Grayson
- Department of Microbiology and Immunology, Wake Forest University School of Medicine, 525 Wake Forest Biotech Place, 525 Patterson Avenue Room 2N051, Winston-Salem, NC, 27101, USA.
| | - Samantha M Short
- Department of Microbiology and Immunology, Wake Forest University School of Medicine, 525 Wake Forest Biotech Place, 525 Patterson Avenue Room 2N051, Winston-Salem, NC, 27101, USA
| | - C Jiah Lee
- Department of Microbiology and Immunology, Wake Forest University School of Medicine, 525 Wake Forest Biotech Place, 525 Patterson Avenue Room 2N051, Winston-Salem, NC, 27101, USA
| | - Nuri Park
- Department of Microbiology and Immunology, Wake Forest University School of Medicine, 525 Wake Forest Biotech Place, 525 Patterson Avenue Room 2N051, Winston-Salem, NC, 27101, USA
| | - Caitlyn Marsac
- Department of Microbiology and Immunology, Wake Forest University School of Medicine, 525 Wake Forest Biotech Place, 525 Patterson Avenue Room 2N051, Winston-Salem, NC, 27101, USA
| | - Alessandro Sette
- La Jolla Institute for Immunology, 9420 Athena Circle, La Jolla, CA, 92037, USA
| | | | - Xiaoyan I Leng
- Department of Biostatistics and Data Science, One Medical Center Boulevard, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA
| | - Samuel N Lockhart
- Department of Internal Medicine-Geriatrics, One Medical Center Boulevard, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA
| | - Suzanne Craft
- Department of Internal Medicine-Geriatrics, One Medical Center Boulevard, Wake Forest University School of Medicine, Winston-Salem, NC, 27157, USA
| |
Collapse
|
32
|
Cassady KE, Chen X, Adams JN, Harrison TM, Zhuang K, Maass A, Baker S, Jagust W. Effect of Alzheimer's Pathology on Task-Related Brain Network Reconfiguration in Aging. J Neurosci 2023; 43:6553-6563. [PMID: 37604690 PMCID: PMC10513069 DOI: 10.1523/jneurosci.0023-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 08/02/2023] [Accepted: 08/06/2023] [Indexed: 08/23/2023] Open
Abstract
Large-scale brain networks undergo widespread changes with older age and in neurodegenerative diseases such as Alzheimer's disease (AD). Research in young adults (YA) suggest that the underlying functional architecture of brain networks remains relatively consistent between rest and task states. However, it remains unclear whether the same is true in aging and to what extent any changes may be related to accumulation of AD pathology such as β-amyloid (Aβ) and tau. Here, we examined age-related differences in functional connectivity (FC) between rest and an object-scene mnemonic discrimination task using fMRI in young and older adults (OA; both females and males). We used an a priori episodic memory network (EMN) parcellation scheme associated with object and scene processing, that included anterior-temporal regions and posterior-medial regions. We also used positron emission topography to measure Aβ and tau in older adults. The correlation between rest and task FC (i.e., FC similarity) was reduced in older compared with younger adults. Older adults with lower FC similarity in EMN had higher levels of tau in the same EMN regions and performed worse during object, but not scene, trials during the fMRI task. These findings link AD pathology, particularly tau, to a less stable functional architecture in memory networks. They also suggest that smaller changes in FC organization between rest and task states may facilitate better performance in older age. Interpretations are limited by methodological factors related to different acquisition directions and durations between rest and task scans.SIGNIFICANCE STATEMENT The brain's large-scale network organization is relatively consistent between rest and task states in young adults (YA). We found that memory networks in older adults (OA) were less correlated between rest and (memory) task states compared with young adults. Older adults with less correlated brain networks also had higher levels of Alzheimer's disease (AD) pathology in the same regions, suggesting that a less stable network architecture may reflect the early evolution of AD. Older adults with less correlated brain networks also performed worse during the memory task suggesting that more similar network organization between rest and task states may facilitate better performance in older age.
Collapse
Affiliation(s)
- Kaitlin E Cassady
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, California 94720
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California 94720
| | - Xi Chen
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, California 94720
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California 94720
| | - Jenna N Adams
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California 94720
| | - Theresa M Harrison
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California 94720
| | - Kailin Zhuang
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California 94720
| | - Anne Maass
- German Center for Neurodegenerative Disease, 39120 Magdeburg, Germany
| | - Suzanne Baker
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - William Jagust
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, California 94720
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, California 94720
| |
Collapse
|
33
|
Yue J, Han S, Li A, Wei Z, Cao D, Gao S, Li X, Yang G, Zhang Q. Multimodal magnetic resonance imaging on brain structure and function changes in subjective cognitive decline: a mini-review. Front Aging Neurosci 2023; 15:1259190. [PMID: 37790282 PMCID: PMC10543888 DOI: 10.3389/fnagi.2023.1259190] [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: 07/15/2023] [Accepted: 08/28/2023] [Indexed: 10/05/2023] Open
Abstract
Subjective cognitive decline (SCD) is the initial stage of Alzheimer's disease (AD). Early identification of SCD and its risk factors is of great importance for targeted interventions and for delaying the onset of AD. We reviewed the relevant literature on structural magnetic resonance imaging (sMRI), diffusion tensor imaging (DTI), functional magnetic resonance imaging (fMRI), and other techniques regarding SCD research in recent years. This study applied sMRI and fMRI techniques to explore abnormal brain structures and functions, which may help provide a basis for SCD diagnosis.
Collapse
Affiliation(s)
- Jinhuan Yue
- Shenzhen Frontiers in Chinese Medicine Research Co., Ltd., Shenzhen, China
- Department of Acupuncture and Moxibustion, Vitality University, Hayward, CA, United States
| | - Shengwang Han
- Third Ward of Rehabilitation Department, Second Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Ang Li
- Servier (Beijing) Pharmaceutical Research & Development CO., Ltd., Beijing, China
| | - Zeyi Wei
- Graduate School of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Danna Cao
- Division of CT and MRI, First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Shenglan Gao
- Graduate School of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Xiaoling Li
- Division of CT and MRI, First Affiliated Hospital of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Guanhu Yang
- Department of Specialty Medicine, Ohio University, Athens, OH, United States
| | - Qinhong Zhang
- Shenzhen Frontiers in Chinese Medicine Research Co., Ltd., Shenzhen, China
- Heilongjiang University of Chinese Medicine, Harbin, China
| |
Collapse
|
34
|
Mandelli ML, Lorca‐Puls DL, Lukic S, Montembeault M, Gajardo‐Vidal A, Licata A, Scheffler A, Battistella G, Grasso SM, Bogley R, Ratnasiri BM, La Joie R, Mundada NS, Europa E, Rabinovici G, Miller BL, De Leon J, Henry ML, Miller Z, Gorno‐Tempini ML. Network anatomy in logopenic variant of primary progressive aphasia. Hum Brain Mapp 2023; 44:4390-4406. [PMID: 37306089 PMCID: PMC10318204 DOI: 10.1002/hbm.26388] [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: 12/22/2022] [Revised: 04/21/2023] [Accepted: 05/17/2023] [Indexed: 06/13/2023] Open
Abstract
The logopenic variant of primary progressive aphasia (lvPPA) is a neurodegenerative syndrome characterized linguistically by gradual loss of repetition and naming skills resulting from left posterior temporal and inferior parietal atrophy. Here, we sought to identify which specific cortical loci are initially targeted by the disease (epicenters) and investigate whether atrophy spreads through predetermined networks. First, we used cross-sectional structural MRI data from individuals with lvPPA to define putative disease epicenters using a surface-based approach paired with an anatomically fine-grained parcellation of the cortical surface (i.e., HCP-MMP1.0 atlas). Second, we combined cross-sectional functional MRI data from healthy controls and longitudinal structural MRI data from individuals with lvPPA to derive the epicenter-seeded resting-state networks most relevant to lvPPA symptomatology and ascertain whether functional connectivity in these networks predicts longitudinal atrophy spread in lvPPA. Our results show that two partially distinct brain networks anchored to the left anterior angular and posterior superior temporal gyri epicenters were preferentially associated with sentence repetition and naming skills in lvPPA. Critically, the strength of connectivity within these two networks in the neurologically-intact brain significantly predicted longitudinal atrophy progression in lvPPA. Taken together, our findings indicate that atrophy progression in lvPPA, starting from inferior parietal and temporoparietal junction regions, predominantly follows at least two partially nonoverlapping pathways, which may influence the heterogeneity in clinical presentation and prognosis.
Collapse
Affiliation(s)
- Maria Luisa Mandelli
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Diego L. Lorca‐Puls
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Sección de Neurología, Departamento de Especialidades, Facultad de MedicinaUniversidad de ConcepciónConcepciónChile
| | - Sladjana Lukic
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of Communication Sciences and DisordersAdelphi UniversityGarden CityNew YorkUSA
| | - Maxime Montembeault
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of PsychiatryDouglas Mental Health University Institute, McGill UniversityMontréalCanada
| | - Andrea Gajardo‐Vidal
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Faculty of Health SciencesUniversidad del DesarrolloConcepciónChile
| | - Abigail Licata
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Aaron Scheffler
- Department of Epidemiology and BiostatisticsUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Giovanni Battistella
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of OtolaryngologyHead and Neck Surgery, Massachusetts Eye and Ear and Harvard Medical SchoolBostonMassachusettsUSA
| | - Stephanie M. Grasso
- Department of Speech, Language, and Hearing SciencesUniversity of TexasAustinTexasUSA
| | - Rian Bogley
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Buddhika M. Ratnasiri
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Renaud La Joie
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Nidhi S. Mundada
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Eduardo Europa
- Department of Communicative Disorders and SciencesSan Jose State UniversitySan JoseCaliforniaUSA
| | - Gil Rabinovici
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Bruce L. Miller
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Jessica De Leon
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | - Maya L. Henry
- Department of Speech, Language, and Hearing SciencesUniversity of TexasAustinTexasUSA
| | - Zachary Miller
- Memory and Aging Center, Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
| | | |
Collapse
|
35
|
Aslanyan V, Ortega N, Fenton L, Harrison TM, Raman R, Mack WJ, Pa J. Protective effects of sleep duration and physical activity on cognitive performance are influenced by β-amyloid and brain volume but not tau burden among cognitively unimpaired older adults. Neuroimage Clin 2023; 39:103460. [PMID: 37379733 PMCID: PMC10316126 DOI: 10.1016/j.nicl.2023.103460] [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: 03/07/2023] [Revised: 06/21/2023] [Accepted: 06/21/2023] [Indexed: 06/30/2023]
Abstract
BACKGROUND AND OBJECTIVES Sleep and physical activity have gained traction as modifiable risk factors for Alzheimer's disease. Sleep duration is linked to amyloid-β clearance while physical activity is associated with brain volume maintenance. We investigate how sleep duration and physical activity are associated with cognition by testing if the associations between sleep duration or physical activity to cognition are explained by amyloid-β burden and brain volume, respectively. Additionally, we explore the mediating role of tau deposition in sleep duration-cognition and physical activity-cognition relationships. METHODS This cross-sectional study obtained data from participants in the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4) study, a randomized clinical trial. In trial screening, cognitively unimpaired participants (age 65-85 years) underwent amyloid PET and brain MRI; APOE genotype and lifestyle questionnaire data were obtained. Cognitive performance was assessed using the Preclinical Alzheimer Cognitive Composite (PACC). Self-reported nightly sleep duration and weekly physical activity were the primary predictors. Regional Aβ and tau pathologies and volumes were the proposed variables influencing relationships between sleep duration or physical activity and cognition. RESULTS Aβ data were obtained from 4322 participants (1208 with MRI, 59% female, 29% amyloid positive). Sleep duration was associated with a Aβ composite score (β = -0.005, CI: (-0.01, -0.001)) and Aβ burden in the anterior cingulate (ACC) (β = -0.012, CI: (-0.017, -0.006)) and medial orbitofrontal cortices (MOC) (β = -0.009, CI: (-0.014, -0.005)). Composite (β = -1.54, 95% CI:(-1.93, -1.15)), ACC (β = -1.22, CI:(-1.54, -0.90)) and MOC (β = -1.44, CI:(-1.86, -1.02)) Aβ deposition was associated with PACC. Sleep duration-PACC association was explained by Aβ burden in path analyses. Physical activity was associated with hippocampal (β = 10.57, CI: (1.06, 20.08)), parahippocampal (β = 9.3, CI: (1.69, 16.91)), entorhinal (β = 14.68, CI: (1.75, 27.61), and fusiform gyral (β = 38.38, CI: (5.57, 71.18)) volumes, which were positively associated with PACC (p < 0.02 for hippocampus, entorhinal cortex and fusiform gyrus). Physical activity-cognition relationship was explained by regional volumes. PET tau imaging was available for 443 participants. No direct sleep duration-tau burden, physical activity by tau burden, or mediation by regional tau was observed in sleep duration-cognition or physical activity-cognition relationships. DISCUSSION Sleep duration and physical activity are associated with cognition through independent paths of brain Aβ and brain volume, respectively. These findings implicate neural and pathological mechanisms for the relationships between sleep duration and physical activity on cognition. Dementia risk reduction approaches that emphasize the adequate sleep duration and a physically active lifestyle may benefit those with risk for Alzheimer's disease.
Collapse
Affiliation(s)
- Vahan Aslanyan
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA
| | - Nancy Ortega
- Alzheimer's Disease Cooperative Study (ADCS), Department of Neurosciences, University of California, San Diego, CA 92121, USA
| | - Laura Fenton
- Department of Psychology, USC Dornsife College of Letters, Arts, and Sciences, Los Angeles, CA 90089, USA
| | - Theresa M Harrison
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA 94720, USA
| | - Rema Raman
- Alzheimer Therapeutic Research Institute, Keck School of Medicine, University of Southern California, San Diego, CA 92093, USA
| | - Wendy J Mack
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA
| | - Judy Pa
- Alzheimer's Disease Cooperative Study (ADCS), Department of Neurosciences, University of California, San Diego, CA 92121, USA.
| |
Collapse
|
36
|
Ferreiro AL, Choi J, Ryou J, Newcomer EP, Thompson R, Bollinger RM, Hall-Moore C, Ndao IM, Sax L, Benzinger TLS, Stark SL, Holtzman DM, Fagan AM, Schindler SE, Cruchaga C, Butt OH, Morris JC, Tarr PI, Ances BM, Dantas G. Gut microbiome composition may be an indicator of preclinical Alzheimer's disease. Sci Transl Med 2023; 15:eabo2984. [PMID: 37315112 PMCID: PMC10680783 DOI: 10.1126/scitranslmed.abo2984] [Citation(s) in RCA: 38] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 05/26/2023] [Indexed: 06/16/2023]
Abstract
Alzheimer's disease (AD) pathology is thought to progress from normal cognition through preclinical disease and ultimately to symptomatic AD with cognitive impairment. Recent work suggests that the gut microbiome of symptomatic patients with AD has an altered taxonomic composition compared with that of healthy, cognitively normal control individuals. However, knowledge about changes in the gut microbiome before the onset of symptomatic AD is limited. In this cross-sectional study that accounted for clinical covariates and dietary intake, we compared the taxonomic composition and gut microbial function in a cohort of 164 cognitively normal individuals, 49 of whom showed biomarker evidence of early preclinical AD. Gut microbial taxonomic profiles of individuals with preclinical AD were distinct from those of individuals without evidence of preclinical AD. The change in gut microbiome composition correlated with β-amyloid (Aβ) and tau pathological biomarkers but not with biomarkers of neurodegeneration, suggesting that the gut microbiome may change early in the disease process. We identified specific gut bacterial taxa associated with preclinical AD. Inclusion of these microbiome features improved the accuracy, sensitivity, and specificity of machine learning classifiers for predicting preclinical AD status when tested on a subset of the cohort (65 of the 164 participants). Gut microbiome correlates of preclinical AD neuropathology may improve our understanding of AD etiology and may help to identify gut-derived markers of AD risk.
Collapse
Affiliation(s)
- Aura L. Ferreiro
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA
- Department of Pathology and Immunology, Division of Laboratory and Genomic Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - JooHee Choi
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Jian Ryou
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Erin P. Newcomer
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Regina Thompson
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Rebecca M. Bollinger
- Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Carla Hall-Moore
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - I. Malick Ndao
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Laurie Sax
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Tammie L. S. Benzinger
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Charles F. and Joanne Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Susan L. Stark
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Program in Occupational Therapy, Washington University School of Medicine, St. Louis, MO 63110, USA
- Charles F. and Joanne Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - David M. Holtzman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Charles F. and Joanne Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Anne M. Fagan
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Charles F. and Joanne Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Suzanne E. Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Charles F. and Joanne Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Carlos Cruchaga
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Omar H. Butt
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - John C. Morris
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Charles F. and Joanne Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Phillip I. Tarr
- Division of Gastroenterology, Hepatology, and Nutrition, Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Beau M. Ances
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Radiology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Charles F. and Joanne Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Gautam Dantas
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA
- Department of Pathology and Immunology, Division of Laboratory and Genomic Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Pediatrics, Washington University School of Medicine, St. Louis, MO 63110, USA
| |
Collapse
|
37
|
Lee S, Byun MS, Yi D, Kim MJ, Jung JH, Kong N, Jung G, Ahn H, Lee JY, Kang KM, Sohn CH, Lee YS, Kim YK, Lee DY. Body mass index and two-year change of in vivo Alzheimer's disease pathologies in cognitively normal older adults. Alzheimers Res Ther 2023; 15:108. [PMID: 37312229 DOI: 10.1186/s13195-023-01259-w] [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: 08/10/2022] [Accepted: 06/01/2023] [Indexed: 06/15/2023]
Abstract
BACKGROUND Low body mass index (BMI) or underweight status in late life is associated with an increased risk of dementia or Alzheimer's disease (AD). However, the relationship between late-life BMI and prospective longitudinal changes of in-vivo AD pathology has not been investigated. METHODS This prospective longitudinal study was conducted as part of the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer's Disease (KBASE). A total of 194 cognitive normal older adults were included in the analysis. BMI at baseline was measured, and two-year changes in brain Aβ and tau deposition on PET imaging were used as the main outcomes. Linear mixed-effects (LME) models were used to examine the relationships between late-life BMI and longitudinal change in AD neuropathological biomarkers. RESULTS A lower BMI at baseline was significantly associated with a greater increase in tau deposition in AD-signature region over 2 years (β, -0.018; 95% CI, -0.028 to -0.004; p = .008), In contrast, BMI was not related to two-year changes in global Aβ deposition (β, 0.0002; 95% CI, -0.003 to 0.002, p = .671). An additional exploratory analysis for each sex showed lower baseline BMI was associated with greater increases in tau deposition in males (β, -0.027; 95% CI, -0.046 to -0.009; p = 0.007), but not in females. DISCUSSION The findings suggest that lower BMI in late-life may predict or contribute to the progression of tau pathology over the subsequent years in cognitively unimpaired older adults.
Collapse
Affiliation(s)
- Seunghoon Lee
- Department of Psychiatry, Myongji Hospital, Hanyang University College of Medicine, Goyang, 10475, Republic of Korea
| | - Min Soo Byun
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, 03080, Republic of Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, 03080, Republic of Korea
| | - Dahyun Yi
- Institute of Human Behavioral Medicine, Medical Research Center, Seoul National University, 101 Daehak-Ro, Jongno-Gu, Seoul, 03080, Republic of Korea
| | - Min Jung Kim
- Department of Neuropsychiatry, Nowon Eulji University Hospital, Seoul, 01830, Republic of Korea
| | - Joon Hyung Jung
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, 03080, Republic of Korea
| | - Nayeong Kong
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, 03080, Republic of Korea
| | - Gijung Jung
- Institute of Human Behavioral Medicine, Medical Research Center, Seoul National University, 101 Daehak-Ro, Jongno-Gu, Seoul, 03080, Republic of Korea
| | - Hyejin Ahn
- Institute of Human Behavioral Medicine, Medical Research Center, Seoul National University, 101 Daehak-Ro, Jongno-Gu, Seoul, 03080, Republic of Korea
| | - Jun-Young Lee
- Department of Neuropsychiatry, SMG-SNU Boramae Medical Center, Seoul, 07061, Republic of Korea
| | - Koung Mi Kang
- Department of Radiology, Seoul National University Hospital, Seoul, 03080, Republic of Korea
| | - Chul-Ho Sohn
- Department of Radiology, Seoul National University Hospital, Seoul, 03080, Republic of Korea
| | - Yun-Sang Lee
- Department of Nuclear Medicine, Seoul National University College of Medicine, Seoul, 03080, Republic of Korea
| | - Yu Kyeong Kim
- Department of Nuclear Medicine, SMG-SNU Boramae Medical Center, Seoul, 07061, Republic of Korea
| | - Dong Young Lee
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, 03080, Republic of Korea.
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, 03080, Republic of Korea.
- Institute of Human Behavioral Medicine, Medical Research Center, Seoul National University, 101 Daehak-Ro, Jongno-Gu, Seoul, 03080, Republic of Korea.
| |
Collapse
|
38
|
Mandelli ML, Lorca-Puls DL, Lukic S, Montembeault M, Gajardo-Vidal A, Licata A, Scheffler A, Battistella G, Grasso SM, Bogley R, Ratnasiri BM, La Joie R, Mundada NS, Europa E, Rabinovici G, Miller BL, De Leon J, Henry ML, Miller Z, Gorno-Tempini ML. Network anatomy in logopenic variant of primary progressive aphasia. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.15.23289065. [PMID: 37292690 PMCID: PMC10246009 DOI: 10.1101/2023.05.15.23289065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
The logopenic variant of primary progressive aphasia (lvPPA) is a neurodegenerative syndrome characterized linguistically by gradual loss of repetition and naming skills, resulting from left posterior temporal and inferior parietal atrophy. Here, we sought to identify which specific cortical loci are initially targeted by the disease (epicenters) and investigate whether atrophy spreads through pre-determined networks. First, we used cross-sectional structural MRI data from individuals with lvPPA to define putative disease epicenters using a surface-based approach paired with an anatomically-fine-grained parcellation of the cortical surface (i.e., HCP-MMP1.0 atlas). Second, we combined cross-sectional functional MRI data from healthy controls and longitudinal structural MRI data from individuals with lvPPA to derive the epicenter-seeded resting-state networks most relevant to lvPPA symptomatology and ascertain whether functional connectivity in these networks predicts longitudinal atrophy spread in lvPPA. Our results show that two partially distinct brain networks anchored to the left anterior angular and posterior superior temporal gyri epicenters were preferentially associated with sentence repetition and naming skills in lvPPA. Critically, the strength of connectivity within these two networks in the neurologically-intact brain significantly predicted longitudinal atrophy progression in lvPPA. Taken together, our findings indicate that atrophy progression in lvPPA, starting from inferior parietal and temporo-parietal junction regions, predominantly follows at least two partially non-overlapping pathways, which may influence the heterogeneity in clinical presentation and prognosis.
Collapse
|
39
|
Alchera N, Garibotto V, Tomczyk S, Treyer V, Hock C, Gietl AF, Lövblad KO, Scheffler M, Chincarini A, Frisoni GB, Ribaldi F. Patterns of amyloid accumulation in amyloid-negative cases. Neurobiol Aging 2023; 129:99-108. [PMID: 37279618 DOI: 10.1016/j.neurobiolaging.2023.05.006] [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: 10/25/2022] [Revised: 05/03/2023] [Accepted: 05/03/2023] [Indexed: 06/08/2023]
Abstract
Amyloid staging models showed that regional abnormality occurs before global positivity. Several studies assumed that the trajectory of amyloid spread is homogeneous, but clinical evidence suggests that it is highly heterogeneous. We tested whether different amyloid-β (Aβ) patterns exist by applying clustering on negative scans and investigating their demographics, clinical, cognitive, and biomarkers correlates, and cognitive trajectories. 151 individuals from Geneva and Zurich cohorts with T1-MRI, negative Aβ positron emission tomography (PET,centiloid<12) and clinical assessment were included. N=123 underwent tau PET, and N=65 follow-up neuropsychological assessment. We performed k-means clustering using 33 Aβ regional Standardized Uptake Vales ratio. Demographics, clinical, cognitive, and biomarkers differences were investigated. Longitudinal cognitive changes by baseline cluster status were estimated using a linear mixed model. The cluster analysis identified two clusters: temporal predominant (TP) and cingulate predominant (CP). TP tau deposition was higher than CP. A trend for a higher cognitive decline in TP compared to CP was observed. This study suggests the existence of two Aβ deposition patterns in the earliest phases of Aβ accumulation, differently prone to tau pathology and cognitive decline.
Collapse
Affiliation(s)
- Nicola Alchera
- Istituto Nazionale di Fisica Nucleare (INFN), Genova, University of Genoa, Genoa, Italy
| | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular Imaging, Diagnostic Department, Geneva University Hospitals, Geneva, Switzerland; Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland; Center for Biomedical imaging (CIBM), Geneva, Switzerland
| | - Szymon Tomczyk
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
| | - Valerie Treyer
- Department of Nuclear Medicine, University Hospital of Zurich, University of Zurich, Zurich, Switzerland; Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | - Christoph Hock
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland; Neurimmune, Schlieren, Switzerland
| | - Anton F Gietl
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland; Department for Geriatric Psychiatry, University Hospital for Psychiatry Zurich, Zurich, Switzerland
| | - Karl-Olof Lövblad
- Division of Radiology, Geneva University Hospitals, Geneva, Switzerland
| | - Max Scheffler
- Division of Radiology, Geneva University Hospitals, Geneva, Switzerland
| | | | - Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland; Geneva Memory Center, Department of Rehabilitation and Geriatrics, Geneva University Hospitals, Geneva, Switzerland
| | - Federica Ribaldi
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland; Geneva Memory Center, Department of Rehabilitation and Geriatrics, Geneva University Hospitals, Geneva, Switzerland.
| |
Collapse
|
40
|
Zavecz Z, Shah VD, Murillo OG, Vallat R, Mander BA, Winer JR, Jagust WJ, Walker MP. NREM sleep as a novel protective cognitive reserve factor in the face of Alzheimer's disease pathology. BMC Med 2023; 21:156. [PMID: 37138290 PMCID: PMC10155344 DOI: 10.1186/s12916-023-02811-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 02/28/2023] [Indexed: 05/05/2023] Open
Abstract
BACKGROUND Alzheimer's disease (AD) pathology impairs cognitive function. Yet some individuals with high amounts of AD pathology suffer marked memory impairment, while others with the same degree of pathology burden show little impairment. Why is this? One proposed explanation is cognitive reserve i.e., factors that confer resilience against, or compensation for the effects of AD pathology. Deep NREM slow wave sleep (SWS) is recognized to enhance functions of learning and memory in healthy older adults. However, that the quality of NREM SWS (NREM slow wave activity, SWA) represents a novel cognitive reserve factor in older adults with AD pathology, thereby providing compensation against memory dysfunction otherwise caused by high AD pathology burden, remains unknown. METHODS Here, we tested this hypothesis in cognitively normal older adults (N = 62) by combining 11C-PiB (Pittsburgh compound B) positron emission tomography (PET) scanning for the quantification of β-amyloid (Aβ) with sleep electroencephalography (EEG) recordings to quantify NREM SWA and a hippocampal-dependent face-name learning task. RESULTS We demonstrated that NREM SWA significantly moderates the effect of Aβ status on memory function. Specifically, NREM SWA selectively supported superior memory function in individuals suffering high Aβ burden, i.e., those most in need of cognitive reserve (B = 2.694, p = 0.019). In contrast, those without significant Aβ pathological burden, and thus without the same need for cognitive reserve, did not similarly benefit from the presence of NREM SWA (B = -0.115, p = 0.876). This interaction between NREM SWA and Aβ status predicting memory function was significant after correcting for age, sex, Body Mass Index, gray matter atrophy, and previously identified cognitive reserve factors, such as education and physical activity (p = 0.042). CONCLUSIONS These findings indicate that NREM SWA is a novel cognitive reserve factor providing resilience against the memory impairment otherwise caused by high AD pathology burden. Furthermore, this cognitive reserve function of NREM SWA remained significant when accounting both for covariates, and factors previously linked to resilience, suggesting that sleep might be an independent cognitive reserve resource. Beyond such mechanistic insights are potential therapeutic implications. Unlike many other cognitive reserve factors (e.g., years of education, prior job complexity), sleep is a modifiable factor. As such, it represents an intervention possibility that may aid the preservation of cognitive function in the face of AD pathology, both present moment and longitudinally.
Collapse
Affiliation(s)
- Zsófia Zavecz
- Department of Psychology, Center for Human Sleep Science, University of California Berkeley, Berkeley, CA, 94720, USA.
| | - Vyoma D Shah
- Department of Psychology, Center for Human Sleep Science, University of California Berkeley, Berkeley, CA, 94720, USA
| | - Olivia G Murillo
- Department of Psychology, Center for Human Sleep Science, University of California Berkeley, Berkeley, CA, 94720, USA
| | - Raphael Vallat
- Department of Psychology, Center for Human Sleep Science, University of California Berkeley, Berkeley, CA, 94720, USA
| | - Bryce A Mander
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, 92617, USA
| | - Joseph R Winer
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, 94304, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, 94720, USA
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, 94720, USA
| | - Matthew P Walker
- Department of Psychology, Center for Human Sleep Science, University of California Berkeley, Berkeley, CA, 94720, USA.
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, 94720, USA.
| |
Collapse
|
41
|
Hani Hojjati S, Butler TA, Chiang GC, Habeck C, RoyChoudhury A, Feiz F, Shteingart J, Nayak S, Ozoria S, Fernández A, Stern Y, Luchsinger JA, Devanand DP, Razlighi QR. Distinct and joint effects of low and high levels of Aβ and tau deposition on cortical thickness. Neuroimage Clin 2023; 38:103409. [PMID: 37104927 PMCID: PMC10165160 DOI: 10.1016/j.nicl.2023.103409] [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: 01/31/2023] [Revised: 04/11/2023] [Accepted: 04/14/2023] [Indexed: 04/29/2023]
Abstract
Alzheimer's disease (AD) is defined by the presence of Amyloid-β (Aβ),tau, and neurodegeneration (ATN framework) in the human cerebral cortex. Yet, prior studies have suggested that Aβ deposition can be associated with both cortical thinning and thickening. These contradictory results are attributed to small sample sizes, the presence versus absence of tau, and limited detectability in the earliest phase of protein deposition, which may begin in young adulthood and cannot be captured in studies enrolling only older subjects. In this study, we aimed to find the distinct and joint effects of Aβ andtau on neurodegeneration during the progression from normal to abnormal stages of pathologies that remain elusive. We used18F-MK6240 and 18F-Florbetaben/18F-Florbetapir positron emission tomography (PET) and magnetic resonance imaging (MRI) to quantify tau, Aβ, and cortical thickness in 590 participants ranging in age from 20 to 90. We performed multiple regression analyses to assess the distinct and joint effects of Aβ and tau on cortical thickness using 590 healthy control (HC) and mild cognitive impairment (MCI) participants (141 young, 394 HC elderlies, 52 MCI). We showed thatin participants with normal levels of global Aβdeposition, Aβ uptakewassignificantly associated with increasedcortical thickness regardless of tau (e.g., left entorhinal cortex with t > 3.241, p < 0.0013). The relationship between tau deposition and neurodegeneration was more complex: in participants with abnormal levels of global tau, tau uptake was associated with cortical thinning in several regions of the brain (e.g., left entorhinal with t < -2.80, p < 0.0096 and left insula with t-value < -4.284, p < 0.0001), as reported on prior neuroimaging and neuropathological studies. Surprisingly, in participants with normal levels of global tau, tau was found to be associated with cortical thickening. Moreover, in participants with abnormal levels of global Aβandtau, theresonancebetween them, defined as their correlation throughout the cortex, wasassociated strongly with cortical thinning even when controlling for a direct linear effect. We confirm prior findings of an association between Aβ deposition and cortical thickening and suggest this may also be the case in the earliest stages of deposition in normal aging. We also illustrate that resonance between high levels of Aβ and tau uptake is strongly associated with cortical thinning, emphasizing the effects of Aβ/tau synergy inAD pathogenesis.
Collapse
Affiliation(s)
- Seyed Hani Hojjati
- Quantitative Neuroimaging Laboratory, Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, NY, United States.
| | - Tracy A Butler
- Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Gloria C Chiang
- Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Christian Habeck
- Department of Neurology and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, United States
| | - Arindam RoyChoudhury
- Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, United States
| | - Farnia Feiz
- Quantitative Neuroimaging Laboratory, Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Jacob Shteingart
- Quantitative Neuroimaging Laboratory, Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Siddharth Nayak
- Quantitative Neuroimaging Laboratory, Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Sindy Ozoria
- Quantitative Neuroimaging Laboratory, Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Antonio Fernández
- Quantitative Neuroimaging Laboratory, Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| | - Yaakov Stern
- Departments of Neurology, Psychiatry, GH Sergievsky Center, the Taub Institute for the Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, United States
| | - José A Luchsinger
- Departments of Medicine and Epidemiology, Columbia University Irving Medical Center, New York, NY, United States
| | - Davangere P Devanand
- Division of Geriatric Psychiatry, New York State Psychiatric Institute, Columbia University Irving Medical Center, New York, NY, United States; Department of Neurology, Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, United States; Department of Psychiatry, New York State Psychiatric Institute, Columbia University Irving Medical Center, New York, NY, United States
| | - Qolamreza R Razlighi
- Quantitative Neuroimaging Laboratory, Brain Health Imaging Institute, Department of Radiology, Weill Cornell Medicine, New York, NY, United States
| |
Collapse
|
42
|
Kamal F, Morrison C, Dadar M. Investigating the relationship between sleep disturbances and white matter hyperintensities in older adults on the Alzheimer's disease spectrum. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.13.23288544. [PMID: 37131746 PMCID: PMC10153314 DOI: 10.1101/2023.04.13.23288544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Background While studies report that sleep disturbance can have negative effects on brain vasculature, its impact on cerebrovascular disease such as white matter hyperintensities (WMHs) in beta-amyloid positive older adults remains unexplored. Methods Linear regressions, mixed effects models, and mediation analysis examined the crosssectional and longitudinal associations between sleep disturbance, cognition, and WMH burden, and cognition in normal controls (NCs), mild cognitive impairment (MCI), and Alzheimer's disease (AD) at baseline and longitudinally. Results People with AD reported more sleep disturbance than NC and MCI. AD with sleep disturbance had more WMHs than AD without sleep disturbances. Mediation analysis revealed an effect of regional WMH burden on the relationship between sleep disturbance and future cognition. Conclusion These results suggest that WMH burden and sleep disturbance increases from aging to AD. Sleep disturbance decreases cognition through increases in WMH burden. Improved sleep could mitigate the impact of WMH accumulation and cognitive decline.
Collapse
Affiliation(s)
- Farooq Kamal
- Department of Psychiatry, McGill University, Montreal, Quebec, H3A 1A1, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, H4H 1R3, Canada
| | - Cassandra Morrison
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, H3A 2B4, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, H3A 2B4, Canada
| | - Mahsa Dadar
- Department of Psychiatry, McGill University, Montreal, Quebec, H3A 1A1, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, H4H 1R3, Canada
| |
Collapse
|
43
|
Yesantharao L, Cai Y, Schrack JA, Gross AL, Wang H, Bilgel M, Dougherty R, Simonsick EM, Ferrucci L, Resnick SM, Agrawal Y. Sensory impairment and beta-amyloid deposition in the Baltimore longitudinal study of aging. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12407. [PMID: 37139098 PMCID: PMC10150164 DOI: 10.1002/dad2.12407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 12/19/2022] [Accepted: 01/19/2023] [Indexed: 05/05/2023]
Abstract
Introduction Beta-amyloid (Aβ) plaque deposition is a biomarker of preclinical Alzheimer's disease (AD). Impairments in sensory function are associated with cognitive decline. We sought to investigate the relationship between PET-indicated Aβ deposition and sensory impairment. Methods Using data from 174 participants ≥55 years in the Baltimore Longitudinal Study of Aging, we analyzed associations between sensory impairments and Aβ deposition measured by PET and Pittsburgh Compound B (PiB) mean cortical distribution volume ratio (cDVR). Results The combinations of hearing and proprioceptive impairment and hearing, vision, and proprioceptive impairment, were positively correlated with cDVR (β = 0.087 and p = 0.036, β = 0.110 and p = 0.018, respectively). In stratified analyses of PiB+ participants, combinations of two, three, and four sensory impairments (all involving proprioception) were associated with higher cDVR. Discussion Our findings suggest a relationship between multi-sensory impairment (notably proprioceptive impairment) and Aβ deposition, which could reflect sensory impairment as an indicator or potentially a risk factor for Aβ deposition.
Collapse
Affiliation(s)
- Lekha Yesantharao
- Department of Otolaryngology ‐ Head and Neck SurgeryJohns Hopkins School of MedicineBaltimoreMarylandUSA
| | - Yurun Cai
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
| | - Jennifer A. Schrack
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
- Center on Aging and HealthJohns Hopkins School of MedicineBaltimoreMarylandUSA
| | - Alden L. Gross
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
- Center on Aging and HealthJohns Hopkins School of MedicineBaltimoreMarylandUSA
| | - Hang Wang
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
| | - Murat Bilgel
- Intramural Research ProgramNational Institute on AgingBaltimoreMarylandUSA
| | - Ryan Dougherty
- Department of EpidemiologyJohns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
| | | | - Luigi Ferrucci
- Intramural Research ProgramNational Institute on AgingBaltimoreMarylandUSA
| | - Susan M. Resnick
- Intramural Research ProgramNational Institute on AgingBaltimoreMarylandUSA
| | - Yuri Agrawal
- Department of Otolaryngology ‐ Head and Neck SurgeryJohns Hopkins School of MedicineBaltimoreMarylandUSA
| |
Collapse
|
44
|
Moon SW, Byun MS, Yi D, Kim MJ, Jung JH, Kong N, Jung G, Ahn H, Lee JY, Kang KM, Sohn CH, Kim YK, Lee DY. Low Ankle-Brachial Index Relates to Alzheimer-Signature Cerebral Glucose Metabolism in Cognitively Impaired Older Adults. J Alzheimers Dis 2023; 93:87-95. [PMID: 36938732 DOI: 10.3233/jad-220911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/16/2023]
Abstract
BACKGROUND Ankle-brachial index (ABI), an indicator of atherosclerosis or arterial stiffness, has been associated with Alzheimer's disease (AD) dementia and related cognitive impairment. Nevertheless, only limited information is available regarding its contribution to brain alterations leading to cognitive decline in late-life. OBJECTIVE We aimed to investigate the relationship of ABI with in vivo AD pathologies and cerebrovascular injury in cognitively impaired older adults. METHODS Total 127 cognitively impaired (70 mild cognitive impairment and 57 AD dementia) individuals, who participated in an ongoing prospective cohort study, were included. All participants underwent comprehensive clinical and neuropsychological assessment, ABI measurement, apolipoprotein E (APOE) ɛ4 genotyping, and multi-modal brain imaging including [11C] Pittsburgh Compound B (PiB)-positron emission tomography (PET) and [18F] fludeoxyglucose (FDG)-PET, and MRI. RESULTS General linear model analysis showed significant relationship between ABI strata (low ABI: <1.00, normal ABI: 1.00-1.29, and high ABI: ≥1.30) and AD-signature region cerebral glucose metabolism (AD-CM), even after controlling age, sex, clinical dementia rating-sum of box, and APOE ɛ4 positivity (p = 0.029). Post hoc comparison revealed that low ABI had significantly lower AD-CM than middle and high ABI, while no difference of AD-CM was found between middle and high ABI. There was no significant difference of global Aβ deposition, AD-signature region cortical thickness, and white matter hyperintensity volume between the three ABI strata. CONCLUSION Our findings suggest that lower ABI, likely related to atherosclerosis, may contribute to the aggravation of AD-related regional neurodegeneration in cognitively impaired older adults.
Collapse
Affiliation(s)
- Seok Woo Moon
- Department of Neuropsychiatry & Research Institute of Medical Science, Konkuk University School of Medicine, Chungju, Republic of Korea
| | - Min Soo Byun
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea.,Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Dahyun Yi
- Institute of Human Behavioral Medicine, Medical Research Center Seoul National University, Seoul, Republic of Korea
| | - Min Jung Kim
- Department of Psychiatry, Eulji University Nowon Eulji Medical Center, Seoul, Republic of Korea
| | - Joon Hyung Jung
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Nayeong Kong
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Gijung Jung
- Institute of Human Behavioral Medicine, Medical Research Center Seoul National University, Seoul, Republic of Korea
| | - Hyejin Ahn
- Institute of Human Behavioral Medicine, Medical Research Center Seoul National University, Seoul, Republic of Korea
| | - Jun-Young Lee
- Department of Neuropsychiatry, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea
| | - Koung Mi Kang
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Chul-Ho Sohn
- Department of Radiology, Seoul National University Hospital, Seoul, Republic of Korea
| | - Yu Kyeong Kim
- Department of Nuclear Medicine, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea
| | - Dong Young Lee
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea.,Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea.,Institute of Human Behavioral Medicine, Medical Research Center Seoul National University, Seoul, Republic of Korea
| | | |
Collapse
|
45
|
Dai WZ, Liu L, Zhu MZ, Lu J, Ni JM, Li R, Ma T, Zhu XC. Morphological and Structural Network Analysis of Sporadic Alzheimer's Disease Brains Based on the APOE4 Gene. J Alzheimers Dis 2023; 91:1035-1048. [PMID: 36530087 DOI: 10.3233/jad-220877] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
BACKGROUND Alzheimer's disease (AD) is an increasingly common type of dementia. Apolipoprotein E (APOE) gene is a strong risk factor for AD. OBJECTIVE Here, we explored alterations in grey matter structure (GMV) and networks in AD, as well as the effects of the APOEɛ4 allele on neuroimaging regions based on structural magnetic resonance imaging (sMRI). METHODS All subjects underwent an sMRI scan. GMV and cortical thickness were calculated using voxel-based morphological analysis, and structural networks were constructed based on graph theory analysis to compare differences between AD and normal controls. RESULTS The volumes of grey matter in the bilateral inferior temporal gyrus, right middle temporal gyrus, right inferior parietal lobule, right limbic lobe, right frontal lobe, left anterior cingulate gyrus, and bilateral olfactory cortex of patients with AD were significantly decreased. The cortical thickness in patients with AD was significantly reduced in the left lateral occipital lobe, inferior parietal lobe, orbitofrontal region, precuneus, superior parietal gyrus, right precentral gyrus, middle temporal gyrus, pars opercularis gyrus, insular gyrus, superior marginal gyrus, bilateral fusiform gyrus, and superior frontal gyrus. In terms of local properties, there were significant differences between the AD and control groups in these areas, including the right bank, right temporalis pole, bilateral middle temporal gyrus, right transverse temporal gyrus, left postcentral gyrus, and left parahippocampal gyrus. CONCLUSION There were significant differences in the morphological and structural covariate networks between AD patients and healthy controls under APOEɛ4 allele effects.
Collapse
Affiliation(s)
- Wen-Zhuo Dai
- Department of Neurology, Affiliated Wuxi Clinical College of Nantong University, Wuxi, Jiangsu Province, China.,Department of Neurology, The Affiliated Wuxi No. 2 People's Hospital of Nanjing Medical University, Wuxi, Jiangsu Province, China.,Department of Neurology, Affiliated Wuxi No. 2 Hospital of Jiangnan University, Wuxi, Jiangsu Province, China
| | - Lu Liu
- Department of Neurology, The Affiliated Wuxi No. 2 People's Hospital of Nanjing Medical University, Wuxi, Jiangsu Province, China
| | - Meng-Zhuo Zhu
- Department of Neurology, Affiliated Wuxi Clinical College of Nantong University, Wuxi, Jiangsu Province, China
| | - Jing Lu
- Department of Neurology, The Affiliated Wuxi No. 2 People's Hospital of Nanjing Medical University, Wuxi, Jiangsu Province, China
| | - Jian-Ming Ni
- Radiology Department, Nanjing Medical University, Wuxi, Jiangsu Province, China
| | - Rong Li
- Department of Pharmacy, The Affiliated Wuxi No. 2 People's Hospital of Nanjing Medical University, Wuxi, Jiangsu Province, China
| | - Tao Ma
- Department of Neurology, Affiliated Wuxi Clinical College of Nantong University, Wuxi, Jiangsu Province, China.,Department of Neurology, The Affiliated Wuxi No. 2 People's Hospital of Nanjing Medical University, Wuxi, Jiangsu Province, China.,Department of Neurology, Affiliated Wuxi No. 2 Hospital of Jiangnan University, Wuxi, Jiangsu Province, China
| | - Xi-Chen Zhu
- Department of Neurology, Affiliated Wuxi Clinical College of Nantong University, Wuxi, Jiangsu Province, China.,Department of Neurology, The Affiliated Wuxi No. 2 People's Hospital of Nanjing Medical University, Wuxi, Jiangsu Province, China.,Department of Neurology, Affiliated Wuxi No. 2 Hospital of Jiangnan University, Wuxi, Jiangsu Province, China
| |
Collapse
|
46
|
Sun Y, Zhao Y, Hu K, Wang M, Liu Y, Liu B. Distinct spatiotemporal subtypes of amyloid deposition are associated with diverging disease profiles in cognitively normal and mild cognitive impairment individuals. Transl Psychiatry 2023; 13:35. [PMID: 36732496 PMCID: PMC9895066 DOI: 10.1038/s41398-023-02328-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 01/04/2023] [Accepted: 01/19/2023] [Indexed: 02/04/2023] Open
Abstract
We aimed to investigate the relationship between spatiotemporal changes of amyloid deposition and Alzheimer's disease (AD) profiles in cognitively normal (CN) and those with mild cognitive impairment (MCI). Using a data-driven method and amyloid-PET data, we identified and validated two subtypes in two independent datasets (discovery dataset: N = 548, age = 72.4 ± 6.78, 49% female; validation dataset: N = 348, age = 74.9 ± 8.16, 47% female) from the Alzheimer's Disease Neuroimaging Initiative across a range of individuals who were CN or had MCI. The two subtypes showed distinct regional progression patterns and presented distinct genetic, clinical and biomarker characteristics. The cortex-priority subtype was more likely to show typical clinical syndromes of symptomatic AD and vice versa. Furthermore, the regional progression patterns were associated with clinical and biomarker profiles. In sum, our findings suggest that the spatiotemporal variants of amyloid depositions are in close association with disease trajectories; these findings may provide insight into the disease monitoring and enrollment of therapeutic trials in AD.
Collapse
Affiliation(s)
- Yuqing Sun
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
| | - Yuxin Zhao
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
| | - Ke Hu
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
| | - Meng Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
| | - Yong Liu
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, 100876, China.
| | - Bing Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875, China.
- Chinese Institute for Brain Research, Beijing, 102206, China.
| |
Collapse
|
47
|
Dobyns L, Zhuang K, Baker SL, Mungas D, Jagust WJ, Harrison TM. An empirical measure of resilience explains individual differences in the effect of tau pathology on memory change in aging. NATURE AGING 2023; 3:229-237. [PMID: 37118122 PMCID: PMC10148952 DOI: 10.1038/s43587-022-00353-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 12/19/2022] [Indexed: 04/30/2023]
Abstract
Accurately measuring resilience to preclinical Alzheimer's disease (AD) pathology is essential to understanding an important source of variability in cognitive aging. In a cohort of cognitively normal older adults (n = 123, age 76.75 ± 6.15 yr), we built a multifactorial measure of resilience which moderated the effect of AD pathology on longitudinal cognitive change. Linear residuals-based measures of resilience, along with other proxy measures (education and vocabulary), were entered into a hierarchical partial least-squares path model defining a putative consolidated resilience latent factor (model goodness of fit = 0.77). In a set of validation analyses using linear mixed models predicting longitudinal cognitive change, there was a significant three-way interaction among consolidated resilience, tau and time on episodic memory change (P = 0.001) such that higher resilience blunted the effect of tau pathology on episodic memory decline. Interactions between consolidated resilience and amyloid pathology on non-memory cognition decline suggested that resilience moderates pathology-specific effects on different cognitive domains.
Collapse
Affiliation(s)
- Lindsey Dobyns
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Kailin Zhuang
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | | | - Dan Mungas
- Department of Neurology, University of California, Davis, Sacramento, CA, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
- Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Theresa M Harrison
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA.
| |
Collapse
|
48
|
Kamal F, Morrison C, Maranzano J, Zeighami Y, Dadar M. Topographical differences in white matter hyperintensity burden and cognition in aging, MCI, and AD. GeroScience 2023; 45:1-16. [PMID: 36229760 PMCID: PMC9886779 DOI: 10.1007/s11357-022-00665-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 09/17/2022] [Indexed: 02/03/2023] Open
Abstract
White matter hyperintensities (WMHs) are pathological changes that occur with increased age and are associated with cognitive decline. Most WMH research has not examined regional differences and focuses on a whole-brain approach. This study examined regional WMHs between normal controls (NCs), people with mild cognitive impairment (MCI), and Alzheimer's disease (AD). We also examined whether WMHs were associated with cognitive decline. Participants from the Alzheimer's Disease Neuroimaging Initiative were included if they had at least one WMH measurement and cognitive scores examining global cognition, executive functioning, and memory. Only amyloid-positive MCI and AD participants were included. A total of 1573 participants with 7381 timepoints over a maximum period of 13 years were included. Linear mixed-effects models examined group differences in WMH burden and associations between WMH burden and cognition. People with MCI and AD had increased total and regional WMHs compared to NCs. An association between WMHs and cognition was observed for global cognition, executive functioning, and memory in NCs in all regions. A steeper decline (stronger association between WMH and cognition) was observed in MCI compared to NCs for all cognitive domains in all regions. A steeper decline was observed in AD compared to NCs for global cognition in only the temporal region. A strong association is observed between all cognitive domains of interest and WMH burden in healthy aging and MCI, while those with AD only had a few associations between WMH and global cognition. These findings suggest that the WMH burden is associated with changes in cognition in healthy aging and early cognitive decline.
Collapse
Affiliation(s)
- Farooq Kamal
- Department of Psychiatry, McGill University, Montreal, QC, Canada.
- Douglas Mental Health University Institute, Montreal, QC, H4H 1R3, Canada.
| | - Cassandra Morrison
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Josefina Maranzano
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, QC, Canada
- Department of Anatomy, University of Quebec in Trois-Rivières, Trois-Rivières, QC, Canada
| | - Yashar Zeighami
- Department of Psychiatry, McGill University, Montreal, QC, Canada
- Douglas Mental Health University Institute, Montreal, QC, H4H 1R3, Canada
| | - Mahsa Dadar
- Department of Psychiatry, McGill University, Montreal, QC, Canada.
- Douglas Mental Health University Institute, Montreal, QC, H4H 1R3, Canada.
| |
Collapse
|
49
|
Katsumi Y, Quimby M, Hochberg D, Jones A, Brickhouse M, Eldaief MC, Dickerson BC, Touroutoglou A. Association of Regional Cortical Network Atrophy With Progression to Dementia in Patients With Primary Progressive Aphasia. Neurology 2023; 100:e286-e296. [PMID: 36192173 PMCID: PMC9869757 DOI: 10.1212/wnl.0000000000201403] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 08/30/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Patients with primary progressive aphasia (PPA) have gradually progressive language deficits during the initial phase of the illness. As the underlying neurodegenerative disease progresses, patients with PPA start losing independent functioning due to the development of nonlanguage cognitive or behavioral symptoms. The timeline of this progression from the mild cognitive impairment stage to the dementia stage of PPA is variable across patients. In this study, in a sample of patients with PPA, we measured the magnitude of cortical atrophy within functional networks believed to subserve diverse cognitive and affective functions. The objective of the study was to evaluate the utility of this measure as a predictor of time to subsequent progression to dementia in PPA. METHODS Patients with PPA with largely independent daily function were recruited through the Massachusetts General Hospital Frontotemporal Disorders Unit. All patients underwent an MRI scan at baseline. Cortical atrophy was then estimated relative to a group of amyloid-negative cognitively normal control participants. For each patient, we measured the time between the baseline visit and the subsequent visit at which dementia progression was documented or last observation. Simple and multivariable Cox regression models were used to examine the relationship between cortical atrophy and the likelihood of progression to dementia. RESULTS Forty-nine patients with PPA (mean age = 66.39 ± 8.36 years, 59.2% females) and 25 controls (mean age = 67.43 ± 4.84 years, 48% females) were included in the data analysis. Greater baseline atrophy in not only the left language network (hazard ratio = 1.47, 95% CI = 1.17-1.84) but also in the frontoparietal control (1.75, 1.25-2.44), salience (1.63, 1.25-2.13), default mode (1.55, 1.19-2.01), and ventral frontotemporal (1.41, 1.16-1.71) networks was associated with a higher risk of progression to dementia. A multivariable model identified contributions of the left frontoparietal control (1.94, 1.09-3.48) and ventral frontotemporal (1.61, 1.09-2.39) networks in predicting dementia progression, with no additional variance explained by the language network (0.75, 0.43-1.31). DISCUSSION These results suggest that baseline atrophy in cortical networks subserving nonlanguage cognitive and affective functions is an important predictor of progression to dementia in PPA. This measure should be included in precision medicine models of prognosis in PPA.
Collapse
Affiliation(s)
- Yuta Katsumi
- *These authors contributed equally as co-first authors.
- These authors contributed equally as co-senior authors.
- From the Frontotemporal Disorders Unit (Y.K., M.Q., D.H., A.J., M.B., M.C.E., B.C.D., A.T.), the Departments of Neurology (Y.K., M.Q., D.H., A.J., M.B., M.C.E., B.C.D., A.T.), and Psychiatry (M.C.E., B.C.D., A.T.), the Massachusetts Alzheimer's Disease Research Center (M.C.E., B.C.D., A.T.), and the Athinoula A. Martinos Center for Biomedical Imaging (B.C.D.), Massachusetts General Hospital and Harvard Medical School, Boston, MA.
| | - Megan Quimby
- *These authors contributed equally as co-first authors
- These authors contributed equally as co-senior authors
- From the Frontotemporal Disorders Unit (Y.K., M.Q., D.H., A.J., M.B., M.C.E., B.C.D., A.T.), the Departments of Neurology (Y.K., M.Q., D.H., A.J., M.B., M.C.E., B.C.D., A.T.), and Psychiatry (M.C.E., B.C.D., A.T.), the Massachusetts Alzheimer's Disease Research Center (M.C.E., B.C.D., A.T.), and the Athinoula A. Martinos Center for Biomedical Imaging (B.C.D.), Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Daisy Hochberg
- *These authors contributed equally as co-first authors
- These authors contributed equally as co-senior authors
- From the Frontotemporal Disorders Unit (Y.K., M.Q., D.H., A.J., M.B., M.C.E., B.C.D., A.T.), the Departments of Neurology (Y.K., M.Q., D.H., A.J., M.B., M.C.E., B.C.D., A.T.), and Psychiatry (M.C.E., B.C.D., A.T.), the Massachusetts Alzheimer's Disease Research Center (M.C.E., B.C.D., A.T.), and the Athinoula A. Martinos Center for Biomedical Imaging (B.C.D.), Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Amelia Jones
- *These authors contributed equally as co-first authors
- These authors contributed equally as co-senior authors
- From the Frontotemporal Disorders Unit (Y.K., M.Q., D.H., A.J., M.B., M.C.E., B.C.D., A.T.), the Departments of Neurology (Y.K., M.Q., D.H., A.J., M.B., M.C.E., B.C.D., A.T.), and Psychiatry (M.C.E., B.C.D., A.T.), the Massachusetts Alzheimer's Disease Research Center (M.C.E., B.C.D., A.T.), and the Athinoula A. Martinos Center for Biomedical Imaging (B.C.D.), Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Michael Brickhouse
- *These authors contributed equally as co-first authors
- These authors contributed equally as co-senior authors
- From the Frontotemporal Disorders Unit (Y.K., M.Q., D.H., A.J., M.B., M.C.E., B.C.D., A.T.), the Departments of Neurology (Y.K., M.Q., D.H., A.J., M.B., M.C.E., B.C.D., A.T.), and Psychiatry (M.C.E., B.C.D., A.T.), the Massachusetts Alzheimer's Disease Research Center (M.C.E., B.C.D., A.T.), and the Athinoula A. Martinos Center for Biomedical Imaging (B.C.D.), Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Mark C Eldaief
- *These authors contributed equally as co-first authors
- These authors contributed equally as co-senior authors
- From the Frontotemporal Disorders Unit (Y.K., M.Q., D.H., A.J., M.B., M.C.E., B.C.D., A.T.), the Departments of Neurology (Y.K., M.Q., D.H., A.J., M.B., M.C.E., B.C.D., A.T.), and Psychiatry (M.C.E., B.C.D., A.T.), the Massachusetts Alzheimer's Disease Research Center (M.C.E., B.C.D., A.T.), and the Athinoula A. Martinos Center for Biomedical Imaging (B.C.D.), Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Bradford C Dickerson
- *These authors contributed equally as co-first authors
- These authors contributed equally as co-senior authors
- From the Frontotemporal Disorders Unit (Y.K., M.Q., D.H., A.J., M.B., M.C.E., B.C.D., A.T.), the Departments of Neurology (Y.K., M.Q., D.H., A.J., M.B., M.C.E., B.C.D., A.T.), and Psychiatry (M.C.E., B.C.D., A.T.), the Massachusetts Alzheimer's Disease Research Center (M.C.E., B.C.D., A.T.), and the Athinoula A. Martinos Center for Biomedical Imaging (B.C.D.), Massachusetts General Hospital and Harvard Medical School, Boston, MA
| | - Alexandra Touroutoglou
- *These authors contributed equally as co-first authors
- These authors contributed equally as co-senior authors
- From the Frontotemporal Disorders Unit (Y.K., M.Q., D.H., A.J., M.B., M.C.E., B.C.D., A.T.), the Departments of Neurology (Y.K., M.Q., D.H., A.J., M.B., M.C.E., B.C.D., A.T.), and Psychiatry (M.C.E., B.C.D., A.T.), the Massachusetts Alzheimer's Disease Research Center (M.C.E., B.C.D., A.T.), and the Athinoula A. Martinos Center for Biomedical Imaging (B.C.D.), Massachusetts General Hospital and Harvard Medical School, Boston, MA
| |
Collapse
|
50
|
Katsumi Y, Putcha D, Eckbo R, Wong B, Quimby M, McGinnis S, Touroutoglou A, Dickerson BC. Anterior dorsal attention network tau drives visual attention deficits in posterior cortical atrophy. Brain 2023; 146:295-306. [PMID: 36237170 DOI: 10.1093/brain/awac245] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 05/16/2022] [Accepted: 06/21/2022] [Indexed: 01/11/2023] Open
Abstract
Posterior cortical atrophy (PCA), usually an atypical clinical syndrome of Alzheimer's disease, has well-characterized patterns of cortical atrophy and tau deposition that are distinct from typical amnestic presentations of Alzheimer's disease. However, the mechanisms underlying the cortical spread of tau in PCA remain unclear. Here, in a sample of 17 biomarker-confirmed (A+/T+/N+) individuals with PCA, we sought to identify functional networks with heightened vulnerability to tau pathology by examining the cortical distribution of elevated tau as measured by 18F-flortaucipir (FTP) PET. We then assessed the relationship between network-specific FTP uptake and visuospatial cognitive task performance. As predicted, we found consistent and prominent localization of tau pathology in the dorsal attention network and visual network of the cerebral cortex. Elevated FTP uptake within the dorsal attention network (particularly the ratio of FTP uptake between the anterior and posterior nodes) was associated with poorer visuospatial attention in PCA; associations were also identified in other functional networks, although to a weaker degree. Furthermore, using functional MRI data collected from each patient at wakeful rest, we found that a greater anterior-to-posterior ratio in FTP uptake was associated with stronger intrinsic functional connectivity between anterior and posterior nodes of the dorsal attention network. Taken together, we conclude that our cross-sectional marker of anterior-to-posterior FTP ratio could indicate tau propagation from posterior to anterior dorsal attention network nodes, and that this anterior progression occurs in relation to intrinsic functional connectivity within this network critical for visuospatial attention. Our findings help to clarify the spatiotemporal pattern of tau propagation in relation to visuospatial cognitive decline and highlight the key role of the dorsal attention network in the disease progression of PCA.
Collapse
Affiliation(s)
- Yuta Katsumi
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.,Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Deepti Putcha
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.,Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Ryan Eckbo
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Bonnie Wong
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.,Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Megan Quimby
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Scott McGinnis
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.,Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Alexandra Touroutoglou
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.,Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Bradford C Dickerson
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.,Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.,Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.,Alzheimer's Disease Research Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| |
Collapse
|