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Zhao L, Qiu Q, Zhang S, Yan F, Li X. Tau pathology mediated the plasma biomarkers and cognitive function in patients with mild cognitive impairment. Exp Gerontol 2024; 195:112535. [PMID: 39128687 DOI: 10.1016/j.exger.2024.112535] [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: 05/05/2024] [Revised: 07/27/2024] [Accepted: 07/31/2024] [Indexed: 08/13/2024]
Abstract
Glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) are putative non-amyloid biomarkers indicative of ongoing inflammatory and neurodegenerative disease processes. Hence, this study aimed to demonstrate the relationship between plasma biomarkers (GFAP and NfL) and 18F-AV-1451 tau PET images, and to explore their effects on cognitive function. Ninety-one participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database and 20 participants from the Shanghai Action of Prevention Dementia for the Elderly (SHAPE) cohort underwent plasma biomarker testing, 18F-AV-1451 tau PET scans and cognitive function assessments. Within the ADNI, there were 42 cognitively normal (CN) individuals and 49 with mild cognitive impairment (MCI). Similarly, in the SHAPE, we had 10 CN and 10 MCI participants. We calculated the standardized uptake value ratios (SUVRs) for the regions of interest (ROIs) in the 18F-AV-1451 PET scans. Using plasma biomarkers and regional SUVRs, we trained machine learning models to differentiate between MCI and CN subjects with ADNI database and validated in SHAPE. Results showed that eight selected variables (including left amygdala SUVR, right amygdala SUVR, left entorhinal cortex SUVR, age, education, plasma NfL, plasma GFAP, plasma GFAP/ NfL) identified by LASSO could differentiate between the MCI and CN individuals, with AUC ranging from 0.783 to 0.926. Additionally, cognitive function was negatively associated with the plasma biomarkers and tau deposition in amygdala and left entorhinal cortex. Increased tau deposition in amygdala and left entorhinal cortex were related to increased plasma biomarkers. Moreover, tau pathology mediated the effect of plasma biomarkers level on the cognitive decline. The present study provides valuable insights into the association among plasma markers (GFAP and NfL), regional tau deposition and cognitive function. This study reports the mediation effect of brain regions tau deposition on the plasma biomarkers level and cognitive function, indicating the significance of tau pathology in the MCI patients.
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Affiliation(s)
- Lu Zhao
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University of Medicine, Shanghai, China
| | - Qi Qiu
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University of Medicine, Shanghai, China
| | - Shaowei Zhang
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University of Medicine, Shanghai, China
| | - Feng Yan
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University of Medicine, Shanghai, China.
| | - Xia Li
- Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University of Medicine, Shanghai, China.
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Leuzy A, Raket LL, Villemagne VL, Klein G, Tonietto M, Olafson E, Baker S, Saad ZS, Bullich S, Lopresti B, Bohorquez SS, Boada M, Betthauser TJ, Charil A, Collins EC, Collins JA, Cullen N, Gunn RN, Higuchi M, Hostetler E, Hutchison RM, Iaccarino L, Insel PS, Irizarry MC, Jack CR, Jagust WJ, Johnson KA, Johnson SC, Karten Y, Marquié M, Mathotaarachchi S, Mintun MA, Ossenkoppele R, Pappas I, Petersen RC, Rabinovici GD, Rosa-Neto P, Schwarz CG, Smith R, Stephens AW, Whittington A, Carrillo MC, Pontecorvo MJ, Haeberlein SB, Dunn B, Kolb HC, Sivakumaran S, Rowe CC, Hansson O, Doré V. Harmonizing tau positron emission tomography in Alzheimer's disease: The CenTauR scale and the joint propagation model. Alzheimers Dement 2024. [PMID: 39041435 DOI: 10.1002/alz.13908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 03/15/2024] [Accepted: 03/18/2024] [Indexed: 07/24/2024]
Abstract
INTRODUCTION Tau-positron emission tomography (PET) outcome data of patients with Alzheimer's disease (AD) cannot currently be meaningfully compared or combined when different tracers are used due to differences in tracer properties, instrumentation, and methods of analysis. METHODS Using head-to-head data from five cohorts with tau PET radiotracers designed to target tau deposition in AD, we tested a joint propagation model (JPM) to harmonize quantification (units termed "CenTauR" [CTR]). JPM is a statistical model that simultaneously models the relationships between head-to-head and anchor point data. JPM was compared to a linear regression approach analogous to the one used in the amyloid PET Centiloid scale. RESULTS A strong linear relationship was observed between CTR values across brain regions. Using the JPM approach, CTR estimates were similar to, but more accurate than, those derived using the linear regression approach. DISCUSSION Preliminary findings using the JPM support the development and adoption of a universal scale for tau-PET quantification. HIGHLIGHTS Tested a novel joint propagation model (JPM) to harmonize quantification of tau PET. Units of common scale are termed "CenTauRs". Tested a Centiloid-like linear regression approach. Using five cohorts with head-to-head tau PET, JPM outperformed linearregressionbased approach. Strong linear relationship was observed between CenTauRs values across brain regions.
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Affiliation(s)
- Antoine Leuzy
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden
- Critical Path for Alzheimer's Disease (CPAD) Consortium, Critical Path Institute, Tucson, Arizona, USA
- Enigma Biomedical Group, Knoxville, Tennessee, USA
| | - Lars Lau Raket
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden
- Eli Lilly and Company, Indianapolis, Indiana, USA
| | - Victor L Villemagne
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
- Florey Department of Neuroscience, University of Melbourne, Parkville, Victoria, Australia
- Department of Molecular Imaging & Therapy, Austin Health, Heidelberg, Victoria, Australia
| | | | | | - Emily Olafson
- Clinical Imaging Group, Genentech, Inc., South San Francisco, California, USA
| | - Suzanne Baker
- Lawrence Berkeley National Laboratory, Berkeley, California, USA
| | - Ziad S Saad
- Janssen Research & Development, Merryfield Row San Diego, California, USA
| | | | - Brian Lopresti
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | | | - Mercè Boada
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
- Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Av. de Monforte de Lemos, Madrid, Spain
| | - Tobey J Betthauser
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wisconsin, USA
- Department of Medicine Division of Geriatrics, University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wisconsin, USA
| | | | | | | | - Nicholas Cullen
- Critical Path for Alzheimer's Disease (CPAD) Consortium, Critical Path Institute, Tucson, Arizona, USA
| | - Roger N Gunn
- Invicro, Hammersmith Hospital, London, UK
- Brain Sciences, Imperial College London, Hammersmith Hospital, London, UK
| | - Makoto Higuchi
- Department of Functional Brain Imaging, Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Inage-ku, Chiba-shi, Chiba, Japan
| | | | | | | | - Philip S Insel
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, California, USA
| | - Michael C Irizarry
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Clifford R Jack
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - William J Jagust
- University of California Berkeley, Lawrence Berkeley National Laboratory, Berkeley, California, USA
| | - Keith A Johnson
- Harvard Medical School, Department of Radiology, Boston, Minnesota, USA
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Boston, Minnesota, USA
| | - Sterling C Johnson
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wisconsin, USA
- Department of Medicine Division of Geriatrics, University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Yashmin Karten
- Critical Path for Alzheimer's Disease (CPAD) Consortium, Critical Path Institute, Tucson, Arizona, USA
| | - Marta Marquié
- Department of Medicine Division of Geriatrics, University of Wisconsin-Madison School of Medicine and Public Health, Madison, Wisconsin, USA
- Department of Medical Physics, University of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wisconsin, USA
| | | | | | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden
- Amsterdam University Medical Center, Neuroscience Campus Amsterdam, Alzheimercenter, HZ Amsterdam, the Netherlands
| | - Ioannis Pappas
- Department of Psychology, Helen Wills Neuroscience Institute, University of California, Berkeley, California, USA
- Department of Neurology, VA Northern California Health Care System, Martinez, California, USA
| | | | - Gil D Rabinovici
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, California, USA
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, California, USA
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, Department of Neurology and Neurosurgery, Faculty of Medicine, The McGill University Research Centre for Studies in Aging, McGill University, Verdun, Quebec, Canada
- Montreal Neurological Institute, McGill University, Montréal, Québec, Canada
| | | | - Ruben Smith
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund, Sweden
| | | | | | | | | | | | - Billy Dunn
- Senior advisor to CPAD Consortium, Critical Path Institute, Tucson, Arizona, USA
| | | | - Sudhir Sivakumaran
- Critical Path for Alzheimer's Disease (CPAD) Consortium, Critical Path Institute, Tucson, Arizona, USA
| | - Christopher C Rowe
- Florey Department of Neuroscience, University of Melbourne, Parkville, Victoria, Australia
- Department of Molecular Imaging & Therapy, Austin Health, Heidelberg, Victoria, Australia
- The Australian Dementia Network (ADNeT), The University of Melbourne, Parkville, Victoria, Australia
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Vincent Doré
- Department of Molecular Imaging & Therapy, Austin Health, Heidelberg, Victoria, Australia
- Health and Biosecurity Flagship, The Australian eHealth Research Centre, CSIRO, Parkville, Victoria, Australia
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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.
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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
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4
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Park K, Kong CH, Kang WC, Jeon M, Lee WH, Lee J, Kim SC, Jung SY, Ryu JH. LPC20K modified from krill oil ameliorates the scopolamine-induced cognitive impairment. Behav Brain Res 2024; 461:114836. [PMID: 38145873 DOI: 10.1016/j.bbr.2023.114836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 12/22/2023] [Accepted: 12/22/2023] [Indexed: 12/27/2023]
Abstract
Alzheimer's disease (AD) is characterized by cognitive impairment. It is common in the elderly. Etiologically, dysfunction of cholinergic neurotransmitter system is prominent in AD. However, disease modifying drug for AD is still unavailable. We hypothesized that krill oil and modified krill oil containing 20 % lysophosphatidylcholine-docosahexaenoic acid (LPC-DHA, LPC20K) could play a crucial role in AD by improving cognitive functions measured by several behavioral tests. We found that LPC20K could ameliorate short-term, long-term, spatial, and object recognition memory under cholinergic hypofunction states. To find the underlying mechanism involved in the effect of LPC20K on cognitive function, we investigated changes of signaling molecules using Western blotting. Expression levels of protein kinase C zeta (PKCζ) and postsynaptic density protein 95 (PSD-95), and phosphorylation levels of extracellular signal-regulated kinase (ERK), Ca2+/calmodulin-dependent protein kinase Ⅱ (CaMKⅡ), and cAMP response element-binding protein (CREB) were significantly increased in LPC20K-administered group compared to those in the memory impairment group. Moreover, the expression levels of BDNF were temporally increased especially 6 or 9 h after administration of LPC20K compared with the control group. These results suggest that LPC20K could ameliorate memory impairment caused by hypocholinergic state by enhancing the expression levels of PKCζ and PSD-95, and phosphorylation levels of ERK, CaMKⅡ and CREB and increasing BDNF expression levels. Therefore, LPC20K could be used as a dietary supplement against cognitive impairment observed in diseases such as AD with a hypocholinergic state.
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Affiliation(s)
- Keontae Park
- Department of Biomedical and Pharmaceutical Science, Kyung Hee University, Seoul 02447, the Republic of Korea
| | - Chang Hyeon Kong
- Department of Biomedical and Pharmaceutical Science, Kyung Hee University, Seoul 02447, the Republic of Korea
| | - Woo Chang Kang
- Department of Biomedical and Pharmaceutical Science, Kyung Hee University, Seoul 02447, the Republic of Korea
| | - Mijin Jeon
- Department of Biomedical and Pharmaceutical Science, Kyung Hee University, Seoul 02447, the Republic of Korea
| | - Won Hyung Lee
- Department of Biomedical and Pharmaceutical Science, Kyung Hee University, Seoul 02447, the Republic of Korea
| | - Juyeon Lee
- Croda Korea Ltd., Seongnam-si, Gyeonggi-do 13636, the Republic of Korea
| | - Sang Chul Kim
- Croda Korea Ltd., Seongnam-si, Gyeonggi-do 13636, the Republic of Korea
| | - Seo Yun Jung
- Department of Biomedical and Pharmaceutical Science, Kyung Hee University, Seoul 02447, the Republic of Korea
| | - Jong Hoon Ryu
- Department of Biomedical and Pharmaceutical Science, Kyung Hee University, Seoul 02447, the Republic of Korea; Department of Oriental Pharmaceutical Science, Kyung Hee University, Seoul 02447, the Republic of Korea.
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5
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Lorca-Puls DL, Gajardo-Vidal A, Mandelli ML, Illán-Gala I, Ezzes Z, Wauters LD, Battistella G, Bogley R, Ratnasiri B, Licata AE, Battista P, García AM, Tee BL, Lukic S, Boxer AL, Rosen HJ, Seeley WW, Grinberg LT, Spina S, Miller BL, Miller ZA, Henry ML, Dronkers NF, Gorno-Tempini ML. Neural basis of speech and grammar symptoms in non-fluent variant primary progressive aphasia spectrum. Brain 2024; 147:607-626. [PMID: 37769652 PMCID: PMC10834255 DOI: 10.1093/brain/awad327] [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: 12/14/2022] [Revised: 07/28/2023] [Accepted: 08/29/2023] [Indexed: 10/03/2023] Open
Abstract
The non-fluent/agrammatic variant of primary progressive aphasia (nfvPPA) is a neurodegenerative syndrome primarily defined by the presence of apraxia of speech (AoS) and/or expressive agrammatism. In addition, many patients exhibit dysarthria and/or receptive agrammatism. This leads to substantial phenotypic variation within the speech-language domain across individuals and time, in terms of both the specific combination of symptoms as well as their severity. How to resolve such phenotypic heterogeneity in nfvPPA is a matter of debate. 'Splitting' views propose separate clinical entities: 'primary progressive apraxia of speech' when AoS occurs in the absence of expressive agrammatism, 'progressive agrammatic aphasia' (PAA) in the opposite case, and 'AOS + PAA' when mixed motor speech and language symptoms are clearly present. While therapeutic interventions typically vary depending on the predominant symptom (e.g. AoS versus expressive agrammatism), the existence of behavioural, anatomical and pathological overlap across these phenotypes argues against drawing such clear-cut boundaries. In the current study, we contribute to this debate by mapping behaviour to brain in a large, prospective cohort of well characterized patients with nfvPPA (n = 104). We sought to advance scientific understanding of nfvPPA and the neural basis of speech-language by uncovering where in the brain the degree of MRI-based atrophy is associated with inter-patient variability in the presence and severity of AoS, dysarthria, expressive agrammatism or receptive agrammatism. Our cross-sectional examination of brain-behaviour relationships revealed three main observations. First, we found that the neural correlates of AoS and expressive agrammatism in nfvPPA lie side by side in the left posterior inferior frontal lobe, explaining their behavioural dissociation/association in previous reports. Second, we identified a 'left-right' and 'ventral-dorsal' neuroanatomical distinction between AoS versus dysarthria, highlighting (i) that dysarthria, but not AoS, is significantly influenced by tissue loss in right-hemisphere motor-speech regions; and (ii) that, within the left hemisphere, dysarthria and AoS map onto dorsally versus ventrally located motor-speech regions, respectively. Third, we confirmed that, within the large-scale grammar network, left frontal tissue loss is preferentially involved in expressive agrammatism and left temporal tissue loss in receptive agrammatism. Our findings thus contribute to define the function and location of the epicentres within the large-scale neural networks vulnerable to neurodegenerative changes in nfvPPA. We propose that nfvPPA be redefined as an umbrella term subsuming a spectrum of speech and/or language phenotypes that are closely linked by the underlying neuroanatomy and neuropathology.
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Affiliation(s)
- Diego L Lorca-Puls
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, SanFrancisco, CA 94158, USA
- Sección de Neurología, Departamento de Especialidades, Facultad de Medicina, Universidad de Concepción, Concepción, 4070105, Chile
| | - Andrea Gajardo-Vidal
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, SanFrancisco, CA 94158, USA
- Centro de Investigación en Complejidad Social (CICS), Facultad de Gobierno, Universidad del Desarrollo, Santiago, 7590943, Chile
- Dirección de Investigación y Doctorados, Vicerrectoría de Investigación y Doctorados, Universidad del Desarrollo, Concepción, 4070001, Chile
| | - Maria Luisa Mandelli
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, SanFrancisco, CA 94158, USA
| | - Ignacio Illán-Gala
- Sant Pau Memory Unit, Department of Neurology, Biomedical Research Institute Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, 08025, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Madrid, 28029, Spain
- Global Brain Health Institute, University of California, San Francisco, CA 94143, USA
| | - Zoe Ezzes
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, SanFrancisco, CA 94158, USA
| | - Lisa D Wauters
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, SanFrancisco, CA 94158, USA
- Department of Speech, Language and Hearing Sciences, University of Texas, Austin, TX 78712-0114, USA
| | - Giovanni Battistella
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, SanFrancisco, CA 94158, USA
- Department of Otolaryngology, Head and Neck Surgery, Massachusetts Eye and Ear and Harvard Medical School, Boston, MA 02114, USA
| | - Rian Bogley
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, SanFrancisco, CA 94158, USA
| | - Buddhika Ratnasiri
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, SanFrancisco, CA 94158, USA
| | - Abigail E Licata
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, SanFrancisco, CA 94158, USA
| | - Petronilla Battista
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, SanFrancisco, CA 94158, USA
- Global Brain Health Institute, University of California, San Francisco, CA 94143, USA
- Laboratory of Neuropsychology, Istituti Clinici Scientifici Maugeri IRCCS, Bari, 70124, Italy
| | - Adolfo M García
- Global Brain Health Institute, University of California, San Francisco, CA 94143, USA
- Centro de Neurociencias Cognitivas, Universidad de San Andrés, Buenos Aires, B1644BID, Argentina
- Departamento de Lingüística y Literatura, Facultad de Humanidades, Universidad de Santiago de Chile, Santiago, 9160000, Chile
| | - Boon Lead Tee
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, SanFrancisco, CA 94158, USA
- Global Brain Health Institute, University of California, San Francisco, CA 94143, USA
| | - Sladjana Lukic
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, SanFrancisco, CA 94158, USA
- Department of Communication Sciences and Disorders, Ruth S. Ammon College of Education and Health Sciences, Adelphi University, Garden City, NY 11530-0701, USA
| | - Adam L Boxer
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, SanFrancisco, CA 94158, USA
| | - Howard J Rosen
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, SanFrancisco, CA 94158, USA
| | - William W Seeley
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, SanFrancisco, CA 94158, USA
- Department of Pathology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Lea T Grinberg
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, SanFrancisco, CA 94158, USA
- Global Brain Health Institute, University of California, San Francisco, CA 94143, USA
- Department of Pathology, University of California San Francisco, San Francisco, CA 94143, USA
| | - Salvatore Spina
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, SanFrancisco, CA 94158, USA
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, SanFrancisco, CA 94158, USA
- Global Brain Health Institute, University of California, San Francisco, CA 94143, USA
| | - Zachary A Miller
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, SanFrancisco, CA 94158, USA
| | - Maya L Henry
- Department of Speech, Language and Hearing Sciences, University of Texas, Austin, TX 78712-0114, USA
- Department of Neurology, Dell Medical School, University of Texas, Austin, TX 78712, USA
| | - Nina F Dronkers
- Department of Psychology, University of California, Berkeley, CA 94720, USA
- Department of Neurology, University of California, Davis, CA 95817, USA
| | - Maria Luisa Gorno-Tempini
- Memory and Aging Center, Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, SanFrancisco, CA 94158, USA
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6
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Boccalini C, Ribaldi F, Hristovska I, Arnone A, Peretti DE, Mu L, Scheffler M, Perani D, Frisoni GB, Garibotto V. The impact of tau deposition and hypometabolism on cognitive impairment and longitudinal cognitive decline. Alzheimers Dement 2024; 20:221-233. [PMID: 37555516 PMCID: PMC10916991 DOI: 10.1002/alz.13355] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 05/09/2023] [Accepted: 05/29/2023] [Indexed: 08/10/2023]
Abstract
INTRODUCTION Tau and neurodegeneration strongly correlate with cognitive impairment, as compared to amyloid. However, their contribution in explaining cognition and predicting cognitive decline in memory clinics remains unclarified. METHODS We included 94 participants with Mini-Mental State Examination (MMSE), tau positron emission tomography (PET), amyloid PET, fluorodeoxyglucose (FDG) PET, and MRI scans from Geneva Memory Center. Linear regression and mediation analyses tested the independent and combined association between biomarkers, cognitive performance, and decline. Linear mixed-effects and Cox proportional hazards models assessed biomarkers' prognostic values. RESULTS Metabolism had the strongest association with cognition (r = 0.712; p < 0.001), followed by tau (r = -0.682; p < 0.001). Neocortical tau showed the strongest association with cognitive decline (r = -0.677; p < 0.001). Metabolism mediated the association between tau and cognition and marginally mediated the one with decline. Tau positivity represented the strongest risk factor for decline (hazard ratio = 32). DISCUSSION Tau and neurodegeneration synergistically contribute to global cognitive impairment while tau drives decline. The tau PET superior prognostic value supports its implementation in memory clinics. HIGHLIGHTS Hypometabolism has the strongest association with concurrent cognitive impairment. Neocortical tau pathology is the main determinant of cognitive decline over time. FDG-PET has a superior value compared to MRI as a measure of neurodegeneration. The prognostic value of tau-PET exceeded all other neuroimaging modalities.
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Affiliation(s)
- Cecilia Boccalini
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of MedicineUniversity of GenevaGenevaSwitzerland
- Vita‐Salute San Raffaele UniversityMilanItaly
- In Vivo Human Molecular and Structural Neuroimaging Unit, Division of NeuroscienceIRCCS San Raffaele Scientific InstituteMilanItaly
| | - Federica Ribaldi
- Geneva Memory CenterGeneva University HospitalsGenevaSwitzerland
- Laboratory of Neuroimaging of Aging (LANVIE)University of GenevaGenevaSwitzerland
| | - Ines Hristovska
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of MedicineUniversity of GenevaGenevaSwitzerland
| | - Annachiara Arnone
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of MedicineUniversity of GenevaGenevaSwitzerland
| | - Débora Elisa Peretti
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of MedicineUniversity of GenevaGenevaSwitzerland
| | - Linjing Mu
- Institute of Pharmaceutical SciencesETH ZurichZurichSwitzerland
| | - Max Scheffler
- Division of RadiologyGeneva University HospitalsGenevaSwitzerland
| | - Daniela Perani
- Vita‐Salute San Raffaele UniversityMilanItaly
- In Vivo Human Molecular and Structural Neuroimaging Unit, Division of NeuroscienceIRCCS San Raffaele Scientific InstituteMilanItaly
- Nuclear Medicine UnitSan Raffaele HospitalMilanItaly
| | - Giovanni B. Frisoni
- Geneva Memory CenterGeneva University HospitalsGenevaSwitzerland
- Laboratory of Neuroimaging of Aging (LANVIE)University of GenevaGenevaSwitzerland
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of MedicineUniversity of GenevaGenevaSwitzerland
- Division of Nuclear Medicine and Molecular ImagingGeneva University HospitalsGenevaSwitzerland
- CIBM Center for Biomedical ImagingGeneva University HospitalsGenevaSwitzerland
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7
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Burnham SC, Iaccarino L, Pontecorvo MJ, Fleisher AS, Lu M, Collins EC, Devous MD. A review of the flortaucipir literature for positron emission tomography imaging of tau neurofibrillary tangles. Brain Commun 2023; 6:fcad305. [PMID: 38187878 PMCID: PMC10768888 DOI: 10.1093/braincomms/fcad305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 09/13/2023] [Accepted: 11/14/2023] [Indexed: 01/09/2024] Open
Abstract
Alzheimer's disease is defined by the presence of β-amyloid plaques and neurofibrillary tau tangles potentially preceding clinical symptoms by many years. Previously only detectable post-mortem, these pathological hallmarks are now identifiable using biomarkers, permitting an in vivo definitive diagnosis of Alzheimer's disease. 18F-flortaucipir (previously known as 18F-T807; 18F-AV-1451) was the first tau positron emission tomography tracer to be introduced and is the only Food and Drug Administration-approved tau positron emission tomography tracer (Tauvid™). It has been widely adopted and validated in a number of independent research and clinical settings. In this review, we present an overview of the published literature on flortaucipir for positron emission tomography imaging of neurofibrillary tau tangles. We considered all accessible peer-reviewed literature pertaining to flortaucipir through 30 April 2022. We found 474 relevant peer-reviewed publications, which were organized into the following categories based on their primary focus: typical Alzheimer's disease, mild cognitive impairment and pre-symptomatic populations; atypical Alzheimer's disease; non-Alzheimer's disease neurodegenerative conditions; head-to-head comparisons with other Tau positron emission tomography tracers; and technical considerations. The available flortaucipir literature provides substantial evidence for the use of this positron emission tomography tracer in assessing neurofibrillary tau tangles in Alzheimer's disease and limited support for its use in other neurodegenerative disorders. Visual interpretation and quantitation approaches, although heterogeneous, mostly converge and demonstrate the high diagnostic and prognostic value of flortaucipir in Alzheimer's disease.
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Affiliation(s)
| | | | | | | | - Ming Lu
- Avid, Eli Lilly and Company, Philadelphia, PA 19104, USA
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8
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Carbonell F, McNicoll C, Zijdenbos AP, Bedell BJ. Spatial association between distributed β-amyloid and tau varies with cognition. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.27.559737. [PMID: 37808643 PMCID: PMC10557646 DOI: 10.1101/2023.09.27.559737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Several PET studies have explored the relationship between β-amyloid load and tau uptake at the early stages of Alzheimer's disease (AD) progression. Most of these studies have focused on the linear relationship between β-amyloid and tau at the local level and their synergistic effect on different AD biomarkers. We hypothesize that patterns of spatial association between β-amyloid and tau might be uncovered using alternative association metrics that account for linear as well as more complex, possible nonlinear dependencies. In the present study, we propose a new Canonical Distance Correlation Analysis (CDCA) to generate distinctive spatial patterns of the cross-correlation structure between tau, as measured by [18F]flortaucipir PET, and β-amyloid, as measured by [18F]florbetapir PET, from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. We found that the CDCA-based β-amyloid scores were not only maximally distance-correlated to tau in cognitively normal (CN) controls and mild cognitive impairment (MCI), but also differentiated between low and high levels of β-amyloid uptake. The most distinctive spatial association pattern was characterized by a spread of β-amyloid covering large areas of the cortex and localized tau in the entorhinal cortex. More importantly, this spatial dependency varies according to cognition, which cannot be explained by the uptake differences in β-amyloid or tau between CN and MCI subjects. Hence, the CDCA-based scores might be more accurate than the amyloid or tau SUVR for the enrollment in clinical trials of those individuals on the path of cognitive deterioration.
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9
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Chow FC, Mundada NS, Abohashem S, La Joie R, Iaccarino L, Arechiga VM, Swaminathan S, Rabinovici GD, Epel ES, Tawakol A, Hsue PY. Psychological stress is associated with arterial inflammation in people living with treated HIV infection. Brain Behav Immun 2023; 113:21-28. [PMID: 37369339 DOI: 10.1016/j.bbi.2023.06.019] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 06/05/2023] [Accepted: 06/22/2023] [Indexed: 06/29/2023] Open
Abstract
Stress and depression are increasingly recognized as cerebrovascular risk factors, including among high stress populations such as people living with HIV infection (PLWH). Stress may contribute to stroke risk through activation of neural inflammatory pathways. In this cross-sectional study, we examined the relationships between stress, systemic and arterial inflammation, and metabolic activity in stress-related brain regions on 18F-fluorodeoxyglucose (FDG)-PET in PLWH. Participants were recruited from a parent trial evaluating the impact of alirocumab on radiologic markers of cardiovascular risk in people with treated HIV infection. We administered a stress battery to assess different forms of psychological stress, specifying the Perceived Stress Scale as the primary stress measure, and quantified plasma markers of inflammation and immune activation. Participants underwent FDG-PET of the brain, neck, and chest. Age- and sex-matched control participants without HIV infection were selected for brain FDG-PET comparisons. Among PLWH, we used nonparametric pairwise correlations, partial correlations, and linear regression to investigate the association between stress and 1) systemic inflammation; 2) atherosclerotic inflammation on FDG-PET; and metabolic activity in 3) brain regions in which glucose metabolism differed significantly by HIV serostatus; and 4) in a priori defined stress-responsive regions of interest (ROI) and stress-related neural network activity (i.e., ratio of amygdala to ventromedial prefrontal cortex or temporal lobe activity). We studied 37 PLWH (mean age 60 years, 97% men) and 29 control participants without HIV (mean age 62 years, 97% men). Among PLWH, stress was significantly correlated with systemic inflammation (r = 0.33, p = 0.041) and arterial inflammation in the carotid (r = 0.41, p = 0.023) independent of age, race/ethnicity, traditional vascular risk factors and health-related behaviors. In voxel-wise analyses, metabolic activity in a cluster corresponding to the anterior medial temporal lobes, including the bilateral amygdalae, was significantly lower in PLWH compared with controls. However, we did not find a significant positive relationship between stress and this cluster of decreased metabolic activity in PLWH, a priori defined stress-responsive ROI, or stress-related neural network activity. In conclusion, psychological stress was associated with systemic and carotid arterial inflammation in this group of PLWH with treated infection. These data provide preliminary evidence for a link between psychological stress, inflammation, and atherosclerosis as potential drivers of excess cerebrovascular risk among PLWH.
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Affiliation(s)
- Felicia C Chow
- Departments of Neurology and Medicine (Infectious Diseases) and Weill Institute for Neurosciences, University of California, San Francisco, USA.
| | - Nidhi S Mundada
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, USA
| | - Shady Abohashem
- Cardiovascular Imaging Research Center, Massachusetts General Hospital and Harvard Medical School, Boston, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, USA
| | - Leonardo Iaccarino
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, USA
| | - Victor M Arechiga
- Department of Medicine (Cardiology), University of California, San Francisco, USA
| | - Shreya Swaminathan
- Department of Medicine (Cardiology), University of California, San Francisco, USA
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, USA; Department of Radiology and Biomedical Imaging, University of California, San Francisco, USA
| | - Elissa S Epel
- Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California, San Francisco, USA
| | - Ahmed Tawakol
- Cardiovascular Imaging Research Center, Massachusetts General Hospital and Harvard Medical School, Boston, USA; Department of Medicine (Cardiology), Massachusetts General Hospital and Harvard Medical School, Boston, USA
| | - Priscilla Y Hsue
- Department of Medicine (Cardiology), University of California, San Francisco, USA
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10
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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.
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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.
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11
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Giannini LA, Mol MO, Rajicic A, van Buuren R, Sarkar L, Arezoumandan S, Ohm DT, Irwin DJ, Rozemuller AJ, van Swieten JC, Seelaar H. Presymptomatic and early pathological features of MAPT-associated frontotemporal lobar degeneration. Acta Neuropathol Commun 2023; 11:126. [PMID: 37533060 PMCID: PMC10394953 DOI: 10.1186/s40478-023-01588-9] [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: 05/23/2023] [Accepted: 05/24/2023] [Indexed: 08/04/2023] Open
Abstract
Early pathological features of frontotemporal lobar degeneration (FTLD) due to MAPT pathogenic variants (FTLD-MAPT) are understudied, since early-stage tissue is rarely available. Here, we report unique pathological data from three presymptomatic/early-stage MAPT variant carriers (FTLD Clinical Dementia Rating [FTLD-CDR] = 0-1). We examined neuronal degeneration semi-quantitatively and digitally quantified tau burden in 18 grey matter (9 cortical, 9 subcortical) and 13 white matter (9 cortical, 4 subcortical) regions. We compared presymptomatic/early-stage pathology to an intermediate/end-stage cohort (FTLD-CDR = 2-3) with the same variants (2 L315R, 10 P301L, 6 G272V), and developed a clinicopathological staging model for P301L and G272V variants. The 68-year-old presymptomatic L315R carrier (FTLD-CDR = 0) had limited tau burden morphologically similar to L315R end-stage carriers in middle frontal, antero-inferior temporal, amygdala, (para-)hippocampus and striatum, along with age-related Alzheimer's disease neuropathological change. The 59-year-old prodromal P301L carrier (FTLD-CDR = 0.5) had highest tau burden in anterior cingulate, anterior temporal, middle/superior frontal, and fronto-insular cortex, and amygdala. The 45-year-old early-stage G272V carrier (FTLD-CDR = 1) had highest tau burden in superior frontal and anterior cingulate cortex, subiculum and CA1. The severity and distribution of tau burden showed some regional variability between variants at presymptomatic/early-stage, while neuronal degeneration, mild-to-moderate, was similarly distributed in frontotemporal regions. Early-stage tau burden and neuronal degeneration were both less severe than in intermediate-/end-stage cases. In a subset of regions (10 GM, 8 WM) used for clinicopathological staging, clinical severity correlated strongly with neuronal degeneration (rho = 0.72, p < 0.001), less strongly with GM tau burden (rho = 0.57, p = 0.006), and did not with WM tau burden (p = 0.9). Clinicopathological staging showed variant-specific patterns of early tau pathology and progression across stages. These unique data demonstrate that tau pathology and neuronal degeneration are present already at the presymptomatic/early-stage of FTLD-MAPT, though less severely compared to intermediate/end-stage disease. Moreover, early pathological patterns, especially of tau burden, differ partly between specific MAPT variants.
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Affiliation(s)
- Lucia Aa Giannini
- Department of Neurology and Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, 3015 GD, The Netherlands
| | - Merel O Mol
- Department of Neurology and Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, 3015 GD, The Netherlands
| | - Ana Rajicic
- Department of Neurology and Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, 3015 GD, The Netherlands
| | - Renee van Buuren
- Department of Neurology and Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, 3015 GD, The Netherlands
| | - Lana Sarkar
- Department of Neurology and Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, 3015 GD, The Netherlands
| | - Sanaz Arezoumandan
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Daniel T Ohm
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - David J Irwin
- Digital Neuropathology Laboratory, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Annemieke Jm Rozemuller
- Department of Pathology, Amsterdam Neuroscience, Amsterdam University Medical Center, location VUmc, Amsterdam, 1081 HZ, The Netherlands
| | - John C van Swieten
- Department of Neurology and Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, 3015 GD, The Netherlands
| | - Harro Seelaar
- Department of Neurology and Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam, 3015 GD, The Netherlands.
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12
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Shi Y, Ghetti B, Goedert M, Scheres SHW. Cryo-EM Structures of Chronic Traumatic Encephalopathy Tau Filaments with PET Ligand Flortaucipir. J Mol Biol 2023; 435:168025. [PMID: 37330290 PMCID: PMC7615338 DOI: 10.1016/j.jmb.2023.168025] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 02/20/2023] [Accepted: 02/20/2023] [Indexed: 06/19/2023]
Abstract
Positron emission tomography (PET) imaging allows monitoring the progression of amyloid aggregation in the living brain. [18F]-Flortaucipir is the only approved PET tracer compound for the visualisation of tau aggregation. Here, we describe cryo-EM experiments on tau filaments in the presence and absence of flortaucipir. We used tau filaments isolated from the brain of an individual with Alzheimer's disease (AD), and from the brain of an individual with primary age-related tauopathy (PART) with a co-pathology of chronic traumatic encephalopathy (CTE). Unexpectedly, we were unable to visualise additional cryo-EM density for flortaucipir for AD paired helical or straight filaments (PHFs or SFs), but we did observe density for flortaucipir binding to CTE Type I filaments from the case with PART. In the latter, flortaucipir binds in a 1:1 molecular stoichiometry with tau, adjacent to lysine 353 and aspartate 358. By adopting a tilted geometry with respect to the helical axis, the 4.7 Å distance between neighbouring tau monomers is reconciled with the 3.5 Å distance consistent with π-π-stacking between neighbouring molecules of flortaucipir.
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Affiliation(s)
- Yang Shi
- Medical Research Council Laboratory of Molecular Biology, Cambridge, UK.
| | - Bernardino Ghetti
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA. https://twitter.com/GhettiBernardi1
| | - Michel Goedert
- Medical Research Council Laboratory of Molecular Biology, Cambridge, UK.
| | - Sjors H W Scheres
- Medical Research Council Laboratory of Molecular Biology, Cambridge, UK.
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13
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Stocks J, Heywood A, Popuri K, Beg MF, Rosen H, Wang L. Longitudinal Spatial Relationships Between Atrophy and Hypometabolism Across the Alzheimer's Disease Continuum. J Alzheimers Dis 2023; 92:513-527. [PMID: 36776061 DOI: 10.3233/jad-220975] [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: 02/10/2023]
Abstract
BACKGROUND The A/T/N framework allows for the assessment of pathology-specific markers of MRI-derived structural atrophy and hypometabolism on 18FDG-PET. However, how these measures relate to each other locally and distantly across pathology-defined A/T/N groups is currently unclear. OBJECTIVE To determine the regions of association between atrophy and hypometabolism in A/T/N groups both within and across time points. METHODS We examined multivariate multimodal neuroimaging relationships between MRI and 18FDG-PET among suspected non-Alzheimer's disease pathology (SNAP) (A-T/N+; n = 14), Amyloid Only (A+T-N-; n = 24) and Probable AD (A+T+N+; n = 77) groups. Sparse canonical correlation analyses were employed to model spatially disjointed regions of association between MRI and 18FDG-PET data. These relationships were assessed at three combinations of time points -cross-sectionally, between baseline visits and between month 12 (M-12) follow-up visits, as well as longitudinally between baseline and M-12 follow-up. RESULTS In the SNAP group, spatially overlapping relationships between atrophy and hypometabolism were apparent in the bilateral temporal lobes when both modalities were assessed at the M-12 timepoint. Amyloid-Only subjects showed spatially discordant distributed atrophy-hypometabolism relationships at all time points assessed. In Probable AD subjects, local correlations were evident in the bilateral temporal lobes when both modalities were assessed at baseline and at M-12. Across groups, hypometabolism at baseline correlated with non-local, or distant, atrophy at M-12. CONCLUSION These results support the view that local concordance of atrophy and hypometabolism is the result of a tau-mediated process driving neurodegeneration.
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Affiliation(s)
- Jane Stocks
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Ashley Heywood
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Karteek Popuri
- School of Engineering Science, Simon Fraser University, Canada.,Memorial University of Newfoundland, Department of Computer Science, St. John's, NL, Canada
| | | | - Howie Rosen
- School of Medicine, University of California, San Francisco, CA, USA
| | - Lei Wang
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.,Department of Psychiatry and Behavioral Health, Ohio State University Wexner Medical Center, Columbus, OH, USA
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14
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Dang M, Chen Q, Zhao X, Chen K, Li X, Zhang J, Lu J, Ai L, Chen Y, Zhang Z. Tau as a biomarker of cognitive impairment and neuropsychiatric symptom in Alzheimer's disease. Hum Brain Mapp 2023; 44:327-340. [PMID: 36647262 PMCID: PMC9842886 DOI: 10.1002/hbm.26043] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 06/28/2022] [Accepted: 07/28/2022] [Indexed: 01/25/2023] Open
Abstract
The A/T/N research framework has been proposed for the diagnosis and prognosis of Alzheimer's disease (AD). However, the spatial distribution of ATN biomarkers and their relationship with cognitive impairment and neuropsychiatric symptoms (NPS) need further clarification in patients with AD. We scanned 83 AD patients and 38 cognitively normal controls who independently completed the mini-mental state examination and Neuropsychiatric Inventory scales. Tau, Aβ, and hypometabolism spatial patterns were characterized using Statistical Parametric Mapping together with [18F]flortaucipir, [18F]florbetapir, and [18F]FDG positron emission tomography. Piecewise linear regression, two-sample t-tests, and support vector machine algorithms were used to explore the relationship between tau, Aβ, and hypometabolism and cognition, NPS, and AD diagnosis. The results showed that regions with tau deposition are region-specific and mainly occurred in inferior temporal lobes in AD, which extensively overlaps with the hypometabolic regions. While the deposition regions of Aβ were unique and the regions affected by hypometabolism were widely distributed. Unlike Aβ, tau and hypometabolism build up monotonically with increasing cognitive impairment in the late stages of AD. In addition, NPS in AD were associated with tau deposition closely, followed by hypometabolism, but not with Aβ. Finally, hypometabolism and tau had higher accuracy in differentiating the AD patients from controls (accuracy = 0.88, accuracy = 0.85) than Aβ (accuracy = 0.81), and the combined three were the highest (accuracy = 0.95). These findings suggest tau pathology is superior over Aβ and glucose metabolism to identify cognitive impairment and NPS. Its results support tau accumulation can be used as a biomarker of clinical impairment in AD.
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Affiliation(s)
- Mingxi Dang
- State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijingChina
- BABRI CentreBeijing Normal UniversityBeijingChina
| | - Qian Chen
- Department of Nuclear Medicine, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Xiaobin Zhao
- Department of Nuclear Medicine, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Kewei Chen
- Banner Alzheimer's InstitutePhoenixArizonaUSA
| | - Xin Li
- State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijingChina
- BABRI CentreBeijing Normal UniversityBeijingChina
| | - Junying Zhang
- Institute of Basic Research in Clinical MedicineChina Academy of Chinese Medical SciencesBeijingChina
| | - Jie Lu
- Department of RadiologyXuanwu Hospital of Capital Medical UniversityBeijingChina
| | - Lin Ai
- Department of Nuclear Medicine, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Yaojing Chen
- State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijingChina
- BABRI CentreBeijing Normal UniversityBeijingChina
| | - Zhanjun Zhang
- State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijingChina
- BABRI CentreBeijing Normal UniversityBeijingChina
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15
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Asken BM, Tanner JA, VandeVrede L, Casaletto KB, Staffaroni AM, Mundada N, Fonseca C, Iaccarino L, La Joie R, Tsuei T, Mladinov M, Grant H, Shankar R, Wang KKW, Xu H, Cobigo Y, Rosen H, Gardner RC, Perry DC, Miller BL, Spina S, Seeley WW, Kramer JH, Grinberg LT, Rabinovici GD. Multi-Modal Biomarkers of Repetitive Head Impacts and Traumatic Encephalopathy Syndrome: A Clinicopathological Case Series. J Neurotrauma 2022; 39:1195-1213. [PMID: 35481808 PMCID: PMC9422800 DOI: 10.1089/neu.2022.0060] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
Traumatic encephalopathy syndrome (TES) criteria were developed to aid diagnosis of chronic traumatic encephalopathy (CTE) pathology during life. Interpreting clinical and biomarker findings in patients with TES during life necessitates autopsy-based determination of the neuropathological profile. We report a clinicopathological series of nine patients with previous repetitive head impacts (RHI) classified retrospectively using the recent TES research framework (100% male and white/Caucasian, age at death 49-84) who completed antemortem neuropsychological evaluations, T1-weighted magnetic resonance imaging, diffusion tensor imaging (n = 6), (18)F-fluorodeoxyglucose-positron emission tomography (n = 5), and plasma measurement of neurofilament light (NfL), glial fibrillary acidic protein (GFAP), and total tau (n = 8). Autopsies were performed on all patients. Cognitively, low test scores and longitudinal decline were relatively consistent for memory and executive function. Medial temporal lobe atrophy was observed in all nine patients. Poor white matter integrity was consistently found in the fornix. Glucose hypometabolism was most common in the medial temporal lobe and thalamus. Most patients had elevated plasma GFAP, NfL, and total tau at their initial visit and a subset showed longitudinally increasing concentrations. Neuropathologically, five of the nine patients had CTE pathology (n = 4 "High CTE"/McKee Stage III-IV, n = 1 "Low CTE"/McKee Stage I). Primary neuropathological diagnoses (i.e., the disease considered most responsible for observed symptoms) were frontotemporal lobar degeneration (n = 2 FTLD-TDP, n = 1 FTLD-tau), Alzheimer disease (n = 3), CTE (n = 2), and primary age-related tauopathy (n = 1). In addition, hippocampal sclerosis was a common neuropathological comorbidity (n = 5) and associated with limbic-predominant TDP-43 proteinopathy (n = 4) or FTLD-TDP (n = 1). Memory and executive function decline, limbic system brain changes (atrophy, decreased white matter integrity, hypometabolism), and plasma biomarker alterations are common in RHI and TES but may reflect multiple neuropathologies. In particular, the neuropathological differential for patients with RHI or TES presenting with medial temporal atrophy and memory loss should include limbic TDP-43. Researchers and clinicians should be cautious in attributing cognitive, neuroimaging, or other biomarker changes solely to CTE tau pathology based on previous RHI or a TES diagnosis alone.
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Affiliation(s)
- Breton M. Asken
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Jeremy A. Tanner
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Lawren VandeVrede
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Kaitlin B. Casaletto
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Adam M. Staffaroni
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Nidhi Mundada
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Corrina Fonseca
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Leonardo Iaccarino
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Renaud La Joie
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Torie Tsuei
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Miho Mladinov
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Harli Grant
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Ranjani Shankar
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Kevin K. W. Wang
- Program for Neurotrauma, Neuroproteomics & Biomarkers Research, Department of Emergency Medicine, Neuroscience, Psychiatry and Chemistry, McKnight Brain Institute, University of Florida, Gainesville, Florida, USA
- Brain Rehabilitation Research Center, Malcom Randall VA Medical Center, North Florida/South Georgia Veterans Health System, Gainesville, Florida, USA
| | - Haiyan Xu
- Program for Neurotrauma, Neuroproteomics & Biomarkers Research, Department of Emergency Medicine, Neuroscience, Psychiatry and Chemistry, McKnight Brain Institute, University of Florida, Gainesville, Florida, USA
- Brain Rehabilitation Research Center, Malcom Randall VA Medical Center, North Florida/South Georgia Veterans Health System, Gainesville, Florida, USA
| | - Yann Cobigo
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Howie Rosen
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Raquel C. Gardner
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
- San Francisco Veterans Affairs Medical Center, San Francisco, California, USA
| | - David C. Perry
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Bruce L. Miller
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Salvatore Spina
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - William W. Seeley
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Joel H. Kramer
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Lea T. Grinberg
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
| | - Gil D. Rabinovici
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
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16
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Shared pathophysiology: Understanding stroke and Alzheimer’s disease. Clin Neurol Neurosurg 2022; 218:107306. [PMID: 35636382 DOI: 10.1016/j.clineuro.2022.107306] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 05/03/2022] [Accepted: 05/19/2022] [Indexed: 12/17/2022]
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17
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Malpetti M, Joie RL, Rabinovici GD. Tau Beats Amyloid in Predicting Brain Atrophy in Alzheimer Disease: Implications for Prognosis and Clinical Trials. J Nucl Med 2022; 63:830-832. [PMID: 35649659 PMCID: PMC9157718 DOI: 10.2967/jnumed.121.263694] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Revised: 03/10/2022] [Indexed: 11/16/2022] Open
Affiliation(s)
- Maura Malpetti
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California; .,Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom; and
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California.,Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California
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18
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Qiao Z, Wang G, Zhao X, Wang K, Fan D, Chen Q, Ai L. Neuropsychological Performance Is Correlated With Tau Protein Deposition and Glucose Metabolism in Patients With Alzheimer’s Disease. Front Aging Neurosci 2022; 14:841942. [PMID: 35663582 PMCID: PMC9158435 DOI: 10.3389/fnagi.2022.841942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Accepted: 03/07/2022] [Indexed: 11/13/2022] Open
Abstract
Objective This study characterizes glucose metabolism and tau protein deposition distribution in patients with Alzheimer’s disease (AD) and to evaluate the relationships between neuropsychological performance and tau protein deposition or glucose metabolism using 18F-FDG and 18F-AV1451 positron emission tomography/computed tomography (PET/CT). Methods Sixty-four patients with β-amyloid-positive (Aβ+) AD and twenty-five healthy participants were enrolled in this study. All participants underwent 18F-FDG and 18F-AV1451 PET/CT. Clinical data and neuropsychological scores were collected. Patients with AD were divided into mild, moderate, and severe groups according to mini-mental state examination (MMSE) scores. The standardized uptake value ratios (SUVRs) for both FDG and AV1451 PET images were calculated using the cerebellar vermis as reference. The SUVRs of the whole cerebral cortex and each brain region were calculated. The volume of interest (VOI) was obtained using automated anatomical atlas (AAL) and Brodmann regions. Student’s t-test was used to perform intergroup comparisons of SUVR. The partial correlation coefficient between SUVR and neuropsychological scores was computed in an inter-subject manner using age and education as covariates. Results The mild subgroup showed a reduction in glucose metabolism and aggregation of tau protein in the temporoparietal cortex. With a decline in neuropsychiatric performance, the SUVR on FDG PET decreased and SUVR on tau PET increased gradually. The areas of glucose metabolism reduction and tau protein deposition appeared first in the parietal cortex, followed by the temporal and frontal cortex, successively. Both FDG and tau SUVRs significantly correlated with MMSE, Montreal cognitive assessment (MOCA), auditory verbal learning test (AVLT), Boston naming test (BNT), clock drawing task (CDT), and verbal fluency test (VFT) (p < 0.05). The SUVR on FDG PET significantly correlated with activities of daily living (ADL) and the Hamilton depression scale (HAMD). There was no significant correlation between the tau SUVRs and ADL or HAMD. Conclusion The extension of tau protein deposition was similar but not exactly consistent with the area of glucose metabolism reduction. Both tau and FDG SUVRs correlated with cognitive function in domain-specific patterns, and the results of FDG PET more closely correlated with neuropsychological function than tau PET results did.
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Affiliation(s)
- Zhen Qiao
- Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Guihong Wang
- Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Guihong Wang,
| | - Xiaobin Zhao
- Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Kai Wang
- Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Di Fan
- Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Qian Chen
- Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Lin Ai
- Department of Nuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- *Correspondence: Lin Ai,
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19
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Probing individual-level structural atrophy in frontal glioma patients. Neurosurg Rev 2022; 45:2845-2855. [PMID: 35508819 DOI: 10.1007/s10143-022-01800-9] [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: 02/14/2022] [Revised: 04/15/2022] [Accepted: 04/25/2022] [Indexed: 10/18/2022]
Abstract
Although every glioma patient varies in tumor size, location, histological grade and molecular biomarkers, non-tumoral morphological abnormalities are commonly detected by a statistical comparison among patient groups, missing the information of individual morphological alterations. In this study, we introduced an individual-level structural abnormality detection method for glioma patients and proposed several abnormality indexes to depict individual atrophy patterns. Forty-five patients with a glioma in the frontal lobe and fifty-one age-matched healthy controls participated in the study. Individual structural abnormality maps (SAM) were generated using patients' preoperative T1 images, by calculating the degree of deviation of voxel volume in each patient with the normative model built from healthy controls. Based on SAM, a series of individual abnormality indexes were computed, and their relationship with glioma characteristics was explored. The results demonstrated that glioma patients showed unique non-tumoral atrophy patterns with overlapping atrophy regions mainly located at hippocampus, parahippocampus, amygdala, insula, middle temporal gyrus and inferior temporal gyrus, which are closely related to the human cognitive functions. The abnormality indexes were associated with several molecular biomarkers including isocitrate dehydrogenase (IDH) mutation, 1p/19q co-deletion and telomerase reverse transcriptase (TERT) promoter mutation. Our study provides an effective way to access the individual-level non-tumoral structural abnormalities in glioma patients, which has the potential to significantly improve individualized precision medicine.
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20
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Lagarde J, Olivieri P, Tonietto M, Tissot C, Rivals I, Gervais P, Caillé F, Moussion M, Bottlaender M, Sarazin M. Tau-PET imaging predicts cognitive decline and brain atrophy progression in early Alzheimer's disease. J Neurol Neurosurg Psychiatry 2022; 93:459-467. [PMID: 35228270 DOI: 10.1136/jnnp-2021-328623] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Accepted: 01/31/2022] [Indexed: 11/04/2022]
Abstract
OBJECTIVES To explore whether regional tau binding measured at baseline is associated with the rapidity of Alzheimer's disease (AD) progression over 2 years, as assessed by the decline in specified cognitive domains, and the progression of regional brain atrophy, in comparison with amyloid-positron emission tomography (PET), MRI and cerebrospinal fluid (CSF) biomarkers. METHODS Thirty-six patients with AD (positive CSF biomarkers and amyloid-PET) and 15 controls underwent a complete neuropsychological assessment, 3T brain MRI, [11C]-PiB and [18F]-flortaucipir PET imaging, and were monitored annually over 2 years, with a second brain MRI after 2 years. We used mixed effects models to explore the relations between tau-PET, amyloid-PET, CSF biomarkers and MRI at baseline and cognitive decline and the progression of brain atrophy over 2 years in patients with AD. RESULTS Baseline tau-PET was strongly associated with the subsequent cognitive decline in regions that are usually associated with each cognitive domain. No significant relationship was observed between the cognitive decline and initial amyloid load, regional cortical atrophy or CSF biomarkers. Baseline tau tracer binding in the superior temporal gyrus was associated with subsequent atrophy in an inferomedial temporal volume of interest, as was the voxelwise tau tracer binding with subsequent cortical atrophy in the superior temporal, parietal and frontal association cortices. CONCLUSIONS These results suggest that tau tracer binding is predictive of cognitive decline in AD in domain-specific brain areas, which provides important insights into the interaction between tau burden and neurodegeneration, and is of the utmost importance to develop new prognostic markers that will help improve the design of therapeutic trials.
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Affiliation(s)
- Julien Lagarde
- Department of Neurology of Memory and Language, GHU Paris Psychiatrie & Neurosciences, Hôpital Sainte-Anne, Paris, France .,Université de Paris, Paris, France.,Université Paris-Saclay, BioMaps, Service Hospitalier Frédéric Joliot CEA, CNRS, Inserm, Orsay, France
| | - Pauline Olivieri
- Department of Neurology of Memory and Language, GHU Paris Psychiatrie & Neurosciences, Hôpital Sainte-Anne, Paris, France.,Université de Paris, Paris, France.,Université Paris-Saclay, BioMaps, Service Hospitalier Frédéric Joliot CEA, CNRS, Inserm, Orsay, France
| | - Matteo Tonietto
- Université Paris-Saclay, BioMaps, Service Hospitalier Frédéric Joliot CEA, CNRS, Inserm, Orsay, France
| | - Cecile Tissot
- McGill University Research Centre for Studies in Aging, Montreal, Quebec, Canada
| | - Isabelle Rivals
- Equipe de Statistique Appliquée, ESPCI Paris, PSL Research University, INSERM, UMRS 1158 Neurophysiologie Respiratoire Expérimentale et Clinique, 10 rue Vauquelin, Paris, France
| | - Philippe Gervais
- Université Paris-Saclay, BioMaps, Service Hospitalier Frédéric Joliot CEA, CNRS, Inserm, Orsay, France
| | - Fabien Caillé
- Université Paris-Saclay, BioMaps, Service Hospitalier Frédéric Joliot CEA, CNRS, Inserm, Orsay, France
| | - Martin Moussion
- Department of Neurology of Memory and Language, GHU Paris Psychiatrie & Neurosciences, Hôpital Sainte-Anne, Paris, France.,Centre d'évaluation Troubles Psychiques et Vieillissement, GHU Paris Psychiatrie & Neurosciences, Hôpital Sainte-Anne, Paris, France
| | - Michel Bottlaender
- Université Paris-Saclay, BioMaps, Service Hospitalier Frédéric Joliot CEA, CNRS, Inserm, Orsay, France.,Université Paris-Saclay, UNIACT, Neurospin, Joliot Institute, CEA, Gif sur Yvette, France
| | - Marie Sarazin
- Department of Neurology of Memory and Language, GHU Paris Psychiatrie & Neurosciences, Hôpital Sainte-Anne, Paris, France.,Université de Paris, Paris, France.,Université Paris-Saclay, BioMaps, Service Hospitalier Frédéric Joliot CEA, CNRS, Inserm, Orsay, France
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21
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Concordance of Alzheimer’s Disease Subtypes Produced from Different Representative Morphological Measures: A Comparative Study. Brain Sci 2022; 12:brainsci12020187. [PMID: 35203950 PMCID: PMC8869952 DOI: 10.3390/brainsci12020187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 01/20/2022] [Accepted: 01/25/2022] [Indexed: 11/17/2022] Open
Abstract
Background: Gray matter (GM) density and cortical thickness (CT) obtained from structural magnetic resonance imaging are representative GM morphological measures that have been commonly used in Alzheimer’s disease (AD) subtype research. However, how the two measures affect the definition of AD subtypes remains unclear. Methods: A total of 180 AD patients from the ADNI database were used to identify AD subgroups. The subtypes were identified via a data-driven strategy based on the density features and CT features, respectively. Then, the similarity between the two features in AD subtype definition was analyzed. Results: Four distinct subtypes were discovered by both density and CT features: diffuse atrophy AD, minimal atrophy AD (MAD), left temporal dominant atrophy AD (LTAD), and occipital sparing AD. The matched subtypes exhibited relatively high similarity in atrophy patterns and neuropsychological and neuropathological characteristics. They differed only in MAD and LTAD regarding the carrying of apolipoprotein E ε2. Conclusions: The results verified that different representative morphological GM measurement methods could produce similar AD subtypes. Meanwhile, the influences of apolipoprotein E genotype, asymmetric disease progression, and their interactions should be considered and included in the AD subtype definition. This study provides a valuable reference for selecting features in future studies of AD subtypes.
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22
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Differential associations between neocortical tau pathology and blood flow with cognitive deficits in early-onset vs late-onset Alzheimer's disease. Eur J Nucl Med Mol Imaging 2022; 49:1951-1963. [PMID: 34997294 PMCID: PMC9016024 DOI: 10.1007/s00259-021-05669-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 12/20/2021] [Indexed: 12/23/2022]
Abstract
Purpose Early-onset Alzheimer’s disease (EOAD) and late-onset Alzheimer’s disease (LOAD) differ in neuropathological burden and type of cognitive deficits. Assessing tau pathology and relative cerebral blood flow (rCBF) measured with [18F]flortaucipir PET in relation to cognition may help explain these differences between EOAD and LOAD. Methods Seventy-nine amyloid-positive individuals with a clinical diagnosis of AD (EOAD: n = 35, age-at-PET = 59 ± 5, MMSE = 23 ± 4; LOAD: n = 44, age-at-PET = 71 ± 5, MMSE = 23 ± 4) underwent a 130-min dynamic [18F]flortaucipir PET scan and extensive neuropsychological assessment. We extracted binding potentials (BPND) and R1 (proxy of rCBF) from parametric images using receptor parametric mapping, in medial and lateral temporal, parietal, occipital, and frontal regions-of-interest and used nine neuropsychological tests covering memory, attention, language, and executive functioning. We first examined differences between EOAD and LOAD in BPND or R1 using ANOVA (region-of-interest analysis) and voxel-wise contrasts. Next, we performed linear regression models to test for potential interaction effects between age-at-onset and BPND/R1 on cognition. Results Both region-of-interest and voxel-wise contrasts showed higher [18F]flortaucipir BPND values across all neocortical regions in EOAD. By contrast, LOAD patients had lower R1 values (indicative of more reduced rCBF) in medial temporal regions. For both tau and flow in lateral temporal, and occipitoparietal regions, associations with cognitive impairment were stronger in EOAD than in LOAD (EOAD BPND − 0.76 ≤ stβ ≤ − 0.48 vs LOAD − 0.18 ≤ stβ ≤ − 0.02; EOAD R1 0.37 ≤ stβ ≤ 0.84 vs LOAD − 0.25 ≤ stβ ≤ 0.16). Conclusions Compared to LOAD, the degree of lateral temporal and occipitoparietal tau pathology and relative cerebral blood-flow is more strongly associated with cognition in EOAD. Supplementary Information The online version contains supplementary material available at 10.1007/s00259-021-05669-6.
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23
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Leuzy A, Smith R, Cullen NC, Strandberg O, Vogel JW, Binette AP, Borroni E, Janelidze S, Ohlsson T, Jögi J, Ossenkoppele R, Palmqvist S, Mattsson-Carlgren N, Klein G, Stomrud E, Hansson O. Biomarker-Based Prediction of Longitudinal Tau Positron Emission Tomography in Alzheimer Disease. JAMA Neurol 2021; 79:149-158. [PMID: 34928318 PMCID: PMC8689441 DOI: 10.1001/jamaneurol.2021.4654] [Citation(s) in RCA: 71] [Impact Index Per Article: 23.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Question Which biomarkers best predict longitudinal tau accumulation at different clinical stages of Alzheimer disease? Findings In this cohort study of 343 participants including amyloid-β–positive individuals who were cognitively unimpaired or had mild cognitive impairment, the largest annual increase in [18F]RO948 tau positron emission tomography (PET) was seen across the entorhinal cortex, hippocampus, and amygdala and in temporal cortical regions, respectively. In a power analysis, plasma phosphorylated tau217 with tau PET at baseline in stage I and II, respectively, resulted in sample size reductions. Meaning In trials using tau PET as a main outcome, plasma phosphorylated tau217 with tau PET may prove optimal for enrichment in both preclinical and prodromal Alzheimer disease. Importance There is currently no consensus as to which biomarkers best predict longitudinal tau accumulation at different clinical stages of Alzheimer disease (AD). Objective To describe longitudinal [18F]RO948 tau positron emission tomography (PET) findings across the clinical continuum of AD and determine which biomarker combinations showed the strongest associations with longitudinal tau PET and best optimized clinical trial enrichment. Design, Setting, and Participants This longitudinal cohort study consecutively enrolled amyloid-β (Aβ)–negative cognitively unimpaired (CU) participants, Aβ-positive CU individuals, Aβ-positive individuals with mild cognitive impairment (MCI), and individuals with AD dementia between September 2017 and November 2020 from the Swedish BioFINDER-2 (discovery cohort) and BioFINDER-1 (validation cohort) studies. Exposures Baseline plasma and cerebrospinal fluid Aβ42/Aβ40, tau phosphorylated at threonine-217 (p-tau217), p-tau181 and neurofilament light, magnetic resonance imaging, amyloid PET ([18F]flutemetamol), and tau PET ([18F]RO948 in the BioFINDER-2 study; [18F]flortaucipir in the BioFINDER-1 study). Main Outcomes and Measures Baseline tau PET standardized uptake value ratio (SUVR) and annual percent change in tau PET SUVR across regions of interest derived using a data-driven approach combining clustering and event-based modeling. Regression models were used to examine associations between individual biomarkers and longitudinal tau PET and to identify which combinations best predicted longitudinal tau PET. These combinations were then entered in a power analysis to examine how their use as an enrichment strategy would affect sample size in a simulated clinical trial. Results Of 343 participants, the mean (SD) age was 72.56 (7.24) years, and 157 (51.1%) were female. The clustering/event-based modeling–based approach identified 5 regions of interest (stages). In Aβ-positive CU individuals, the largest annual increase in tau PET SUVR was seen in stage I (entorhinal cortex, hippocampus, and amygdala; 4.04% [95% CI, 2.67%-5.32%]). In Aβ-positive individuals with MCI and with AD dementia, the greatest increases were seen in stages II (temporal cortical regions; 4.45% [95% CI, 3.41%-5.49%]) and IV (certain frontal regions; 5.22% [95% CI, 3.95%-6.49%]), respectively. In Aβ-negative CU individuals and those with MCI, modest change was seen in stage I (1.38% [95% CI, 0.78%-1.99%] and 1.80% [95% CI, 0.76%-2.84%], respectively). When looking at individual predictors and longitudinal tau PET in the stages that showed most change, plasma p-tau217 (R2 = 0.27, P < .005), tau PET (stage I baseline SUVR; R2 = 0.13, P < .05) and amyloid PET (R2 = 0.10, P < .05) were significantly associated with longitudinal tau PET in stage I in Aβ-positive CU individuals. In Aβ-positive individuals with MCI, plasma p-tau217 (R2 = 0.24, P < .005) and tau PET (stage II baseline SUVR; R2 = 0.44, P < .001) were significantly associated with longitudinal tau PET in stage II. Findings were replicated in BioFINDER-1 using longitudinal [18F]flortaucipir. For the power analysis component, plasma p-tau217 with tau PET resulted in sample size reductions of 43% (95% CI, 34%-46%; P < .005) in Aβ-positive CU individuals and of 68% (95% CI, 61%-73%; P < .001) in Aβ-positive individuals with MCI. Conclusions and Relevance In trials using tau PET as the outcome, plasma p-tau217 with tau PET may prove optimal for enrichment in preclinical and prodromal AD. However, plasma p-tau217 was most important in preclinical AD, while tau PET was more important in prodromal AD.
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Affiliation(s)
- Antoine Leuzy
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Ruben Smith
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden.,Department of Neurology, Skåne University Hospital, Lund, Sweden
| | - Nicholas C Cullen
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Olof Strandberg
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Jacob W Vogel
- Penn/CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia.,Department of Psychiatry, University of Pennsylvania, Philadelphia
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | | | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Tomas Ohlsson
- Department of Radiation Physics, Skåne University Hospital, Lund, Sweden
| | - Jonas Jögi
- Department of Clinical Physiology and Nuclear Medicine, Skåne University Hospital, Lund, Sweden
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden.,VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden.,Memory Clinic, Skåne University Hospital, Lund, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden.,Department of Neurology, Skåne University Hospital, Lund, Sweden.,Wallenberg Centre for Molecular Medicine, Lund University, Lund, Sweden
| | | | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden.,VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden.,Memory Clinic, Skåne University Hospital, Lund, Sweden
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Jellinger KA. Recent update on the heterogeneity of the Alzheimer’s disease spectrum. J Neural Transm (Vienna) 2021; 129:1-24. [DOI: 10.1007/s00702-021-02449-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 11/25/2021] [Indexed: 02/03/2023]
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Iaccarino L, La Joie R, Koeppe R, Siegel BA, Hillner BE, Gatsonis C, Whitmer RA, Carrillo MC, Apgar C, Camacho MR, Nosheny R, Rabinovici GD. rPOP: Robust PET-only processing of community acquired heterogeneous amyloid-PET data. Neuroimage 2021; 246:118775. [PMID: 34890793 DOI: 10.1016/j.neuroimage.2021.118775] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 11/12/2021] [Accepted: 11/30/2021] [Indexed: 11/17/2022] Open
Abstract
The reference standard for amyloid-PET quantification requires structural MRI (sMRI) for preprocessing in both multi-site research studies and clinical trials. Here we describe rPOP (robust PET-Only Processing), a MATLAB-based MRI-free pipeline implementing non-linear warping and differential smoothing of amyloid-PET scans performed with any of the FDA-approved radiotracers (18F-florbetapir/FBP, 18F-florbetaben/FBB or 18F-flutemetamol/FLUTE). Each image undergoes spatial normalization based on weighted PET templates and data-driven differential smoothing, then allowing users to perform their quantification of choice. Prior to normalization, users can choose whether to automatically reset the origin of the image to the center of mass or proceed with the pipeline with the image as it is. We validate rPOP with n = 740 (514 FBP, 182 FBB, 44 FLUTE) amyloid-PET scans from the Imaging Dementia-Evidence for Amyloid Scanning - Brain Health Registry sub-study (IDEAS-BHR) and n = 1,518 scans from the Alzheimer's Disease Neuroimaging Initiative (n = 1,249 FBP, n = 269 FBB), including heterogeneous acquisition and reconstruction protocols. After running rPOP, a standard quantification to extract Standardized Uptake Value ratios and the respective Centiloids conversion was performed. rPOP-based amyloid status (using an independent pathology-based threshold of ≥24.4 Centiloid units) was compared with either local visual reads (IDEAS-BHR, n = 663 with complete valid data and reads available) or with amyloid status derived from an MRI-based PET processing pipeline (ADNI, thresholds of >20/>18 Centiloids for FBP/FBB). Finally, within the ADNI dataset, we tested the linear associations between rPOP- and MRI-based Centiloid values. rPOP achieved accurate warping for N = 2,233/2,258 (98.9%) in the first pass. Of the N = 25 warping failures, 24 were rescued with manual reorientation and origin reset prior to warping. We observed high concordance between rPOP-based amyloid status and both visual reads (IDEAS-BHR, Cohen's k = 0.72 [0.7-0.74], ∼86% concordance) or MRI-pipeline based amyloid status (ADNI, k = 0.88 [0.87-0.89], ∼94% concordance). rPOP- and MRI-pipeline based Centiloids were strongly linearly related (R2:0.95, p<0.001), with this association being significantly modulated by estimated PET resolution (β= -0.016, p<0.001). rPOP provides reliable MRI-free amyloid-PET warping and quantification, leveraging widely available software and only requiring an attenuation-corrected amyloid-PET image as input. The rPOP pipeline enables the comparison and merging of heterogeneous datasets and is publicly available at https://github.com/leoiacca/rPOP.
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Affiliation(s)
- Leonardo Iaccarino
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States
| | - Robert Koeppe
- Department of Radiology, University of Michigan, Ann Arbor, MI, United States
| | - Barry A Siegel
- Edward Mallinckrodt Institute of Radiology, Washington University School of Medicine in St Louis, St Louis, MO, United States
| | - Bruce E Hillner
- Department of Medicine, Virginia Commonwealth University, Richmond, VA, United States
| | - Constantine Gatsonis
- Center for Statistical Sciences, Brown University School of Public Health, Providence, RI, United States; Department of Biostatistics, Brown University School of Public Health, Providence, RI, United States
| | - Rachel A Whitmer
- Division of Research, Kaiser Permanente, Oakland, CA, United States; Department of Public Health Sciences, University of California Davis, Davis, CA, United States
| | - Maria C Carrillo
- Medical and Scientific Relations Division, Alzheimer's Association, Chicago, IL, United States
| | - Charles Apgar
- American College of Radiology, Reston, VA, United States
| | - Monica R Camacho
- San Francisco VA Medical Center, San Francisco, CA, United States; Northern California Institute for Research and Education (NCIRE), San Francisco, CA, United States
| | - Rachel Nosheny
- San Francisco VA Medical Center, San Francisco, CA, United States; Department of Psychiatry, University of California San Francisco, San Francisco, CA, United States
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, United States; Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, United States.
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Yu M, Sporns O, Saykin AJ. The human connectome in Alzheimer disease - relationship to biomarkers and genetics. Nat Rev Neurol 2021; 17:545-563. [PMID: 34285392 PMCID: PMC8403643 DOI: 10.1038/s41582-021-00529-1] [Citation(s) in RCA: 87] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/10/2021] [Indexed: 02/06/2023]
Abstract
The pathology of Alzheimer disease (AD) damages structural and functional brain networks, resulting in cognitive impairment. The results of recent connectomics studies have now linked changes in structural and functional network organization in AD to the patterns of amyloid-β and tau accumulation and spread, providing insights into the neurobiological mechanisms of the disease. In addition, the detection of gene-related connectome changes might aid in the early diagnosis of AD and facilitate the development of personalized therapeutic strategies that are effective at earlier stages of the disease spectrum. In this article, we review studies of the associations between connectome changes and amyloid-β and tau pathologies as well as molecular genetics in different subtypes and stages of AD. We also highlight the utility of connectome-derived computational models for replicating empirical findings and for tracking and predicting the progression of biomarker-indicated AD pathophysiology.
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Affiliation(s)
- Meichen Yu
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana University Network Science Institute, Bloomington, IN, USA
| | - Olaf Sporns
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana University Network Science Institute, Bloomington, IN, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
| | - Andrew J Saykin
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA.
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA.
- Indiana University Network Science Institute, Bloomington, IN, USA.
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Strom A, Iaccarino L, Edwards L, Lesman-Segev OH, Soleimani-Meigooni DN, Pham J, Baker SL, Landau S, Jagust WJ, Miller BL, Rosen HJ, Gorno-Tempini ML, Rabinovici GD, La Joie R. Cortical hypometabolism reflects local atrophy and tau pathology in symptomatic Alzheimer's disease. Brain 2021; 145:713-728. [PMID: 34373896 PMCID: PMC9014741 DOI: 10.1093/brain/awab294] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 07/09/2021] [Accepted: 07/21/2021] [Indexed: 11/14/2022] Open
Abstract
Posterior cortical hypometabolism measured with [18F]-Fluorodeoxyglucose (FDG)-PET is a well-known marker of Alzheimer's disease-related neurodegeneration, but its associations with underlying neuropathological processes are unclear. We assessed cross-sectionally the relative contributions of three potential mechanisms causing hypometabolism in the retrosplenial and inferior parietal cortices: local molecular (amyloid and tau) pathology and atrophy, distant factors including contributions from the degenerating medial temporal lobe or molecular pathology in functionally connected regions, and the presence of the apolipoprotein E (APOE) ε4 allele. Two hundred and thirty-two amyloid-positive cognitively impaired patients from two cohorts (University of California, San Francisco, UCSF, and Alzheimer's Disease Neuroimaging Initiative, ADNI) underwent MRI and PET with FDG, amyloid-PET using [11C]-Pittsburgh Compound B, [18F]-Florbetapir, or [18F]-Florbetaben, and [18F]-Flortaucipir tau-PET within one year. Standard uptake value ratios (SUVR) were calculated using tracer-specific reference regions. Regression analyses were run within cohorts to identify variables associated with retrosplenial or inferior parietal FDG SUVR. On average, ADNI patients were older and were less impaired than UCSF patients. Regional patterns of hypometabolism were similar between cohorts, though there were cohort differences in regional gray matter atrophy. Local cortical thickness and tau-PET (but not amyloid-PET) were independently associated with both retrosplenial and inferior parietal FDG SUVR (ΔR2 = .09 to .21) across cohorts in models that also included age and disease severity (local model). Including medial temporal lobe volume improved the retrosplenial FDG model in ADNI (ΔR2 = .04, p = .008) but not UCSF (ΔR2 < .01, p = .52), and did not improve the inferior parietal models (ΔR2s < .01, ps > .37). Interaction analyses revealed that medial temporal volume was more strongly associated with retrosplenial FDG SUVR at earlier disease stages (p = .06 in UCSF, p = .046 in ADNI). Exploratory analyses across the cortex confirmed overall associations between hypometabolism and local tau pathology and thickness and revealed associations between medial temporal degeneration and hypometabolism in retrosplenial, orbitofrontal, and anterior cingulate cortices. Finally, our data did not support hypotheses of a detrimental effect of pathology in connected regions or of an effect of the APOE ε4 allele in impaired participants. Overall, in two independent groups of patients at symptomatic stages of Alzheimer's disease, cortical hypometabolism mainly reflected structural neurodegeneration and tau, but not amyloid, pathology.
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Affiliation(s)
- Amelia Strom
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Leonardo Iaccarino
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Lauren Edwards
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Orit H Lesman-Segev
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.,Department of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel
| | - David N Soleimani-Meigooni
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Julie Pham
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Suzanne L Baker
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Susan Landau
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - William J Jagust
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.,Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Howard J Rosen
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Maria Luisa Gorno-Tempini
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.,Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.,Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA.,Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
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Ossenkoppele R, Smith R, Mattsson-Carlgren N, Groot C, Leuzy A, Strandberg O, Palmqvist S, Olsson T, Jögi J, Stormrud E, Cho H, Ryu YH, Choi JY, Boxer AL, Gorno-Tempini ML, Miller BL, Soleimani-Meigooni D, Iaccarino L, La Joie R, Baker S, Borroni E, Klein G, Pontecorvo MJ, Devous MD, Jagust WJ, Lyoo CH, Rabinovici GD, Hansson O. Accuracy of Tau Positron Emission Tomography as a Prognostic Marker in Preclinical and Prodromal Alzheimer Disease: A Head-to-Head Comparison Against Amyloid Positron Emission Tomography and Magnetic Resonance Imaging. JAMA Neurol 2021; 78:961-971. [PMID: 34180956 PMCID: PMC8240013 DOI: 10.1001/jamaneurol.2021.1858] [Citation(s) in RCA: 138] [Impact Index Per Article: 46.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Question What is the prognostic value of tau positron emission tomography (PET) for predicting cognitive decline across the clinical spectrum of Alzheimer disease? Findings In this longitudinal, multicenter prognostic study including 1431 participants, baseline tau PET predicted change in Mini-Mental State Examination scores during a mean (SD) follow-up of 1.9 (0.8) years. Moreover, tau PET outperformed established volumetric magnetic resonance imaging and amyloid PET markers in head-to-head comparisons, especially in participants with mild cognitive impairment and cognitively normal individuals who were positive for amyloid-β. Meaning These findings suggest that tau PET is a promising prognostic tool for predicting cognitive decline in preclinical and prodromal stages of Alzheimer disease. Importance Tau positron emission tomography (PET) tracers have proven useful for the differential diagnosis of dementia, but their utility for predicting cognitive change is unclear. Objective To examine the prognostic accuracy of baseline fluorine 18 (18F)–flortaucipir and [18F]RO948 (tau) PET in individuals across the Alzheimer disease (AD) clinical spectrum and to perform a head-to-head comparison against established magnetic resonance imaging (MRI) and amyloid PET markers. Design, Setting, and Participants This prognostic study collected data from 8 cohorts in South Korea, Sweden, and the US from June 1, 2014, to February 28, 2021, with a mean (SD) follow-up of 1.9 (0.8) years. A total of 1431 participants were recruited from memory clinics, clinical trials, or cohort studies; 673 were cognitively unimpaired (CU group; 253 [37.6%] positive for amyloid-β [Aβ]), 443 had mild cognitive impairment (MCI group; 271 [61.2%] positive for Aβ), and 315 had a clinical diagnosis of AD dementia (315 [100%] positive for Aβ). Exposures [18F]Flortaucipir PET in the discovery cohort (n = 1135) or [18F]RO948 PET in the replication cohort (n = 296), T1-weighted MRI (n = 1431), and amyloid PET (n = 1329) at baseline and repeated Mini-Mental State Examination (MMSE) evaluation. Main Outcomes and Measures Baseline [18F]flortaucipir/[18F]RO948 PET retention within a temporal region of interest, MRI-based AD-signature cortical thickness, and amyloid PET Centiloids were used to predict changes in MMSE using linear mixed-effects models adjusted for age, sex, education, and cohort. Mediation/interaction analyses tested whether associations between baseline tau PET and cognitive change were mediated by baseline MRI measures and whether age, sex, and APOE genotype modified these associations. Results Among 1431 participants, the mean (SD) age was 71.2 (8.8) years; 751 (52.5%) were male. Findings for [18F]flortaucipir PET predicted longitudinal changes in MMSE, and effect sizes were stronger than for AD-signature cortical thickness and amyloid PET across all participants (R2, 0.35 [tau PET] vs 0.24 [MRI] vs 0.17 [amyloid PET]; P < .001, bootstrapped for difference) in the Aβ-positive MCI group (R2, 0.25 [tau PET] vs 0.15 [MRI] vs 0.07 [amyloid PET]; P < .001, bootstrapped for difference) and in the Aβ-positive CU group (R2, 0.16 [tau PET] vs 0.08 [MRI] vs 0.08 [amyloid PET]; P < .001, bootstrapped for difference). These findings were replicated in the [18F]RO948 PET cohort. MRI mediated the association between [18F]flortaucipir PET and MMSE in the groups with AD dementia (33.4% [95% CI, 15.5%-60.0%] of the total effect) and Aβ-positive MCI (13.6% [95% CI, 0.0%-28.0%] of the total effect), but not the Aβ-positive CU group (3.7% [95% CI, −17.5% to 39.0%]; P = .71). Age (t = −2.28; P = .02), but not sex (t = 0.92; P = .36) or APOE genotype (t = 1.06; P = .29) modified the association between baseline [18F]flortaucipir PET and cognitive change, such that older individuals showed faster cognitive decline at similar tau PET levels. Conclusions and Relevance The findings of this prognostic study suggest that tau PET is a promising tool for predicting cognitive change that is superior to amyloid PET and MRI and may support the prognostic process in preclinical and prodromal stages of AD.
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Affiliation(s)
- Rik Ossenkoppele
- Clinical Memory Research Unit, Lund University, Malmö, Sweden.,Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Ruben Smith
- Clinical Memory Research Unit, Lund University, Malmö, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Lund University, Malmö, Sweden.,Department of Neurology, Skåne University Hospital, Lund, Sweden.,Wallenberg Centre for Molecular Medicine, Lund University, Lund, Sweden
| | - Colin Groot
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam University Medical Center, Amsterdam, the Netherlands
| | - Antoine Leuzy
- Clinical Memory Research Unit, Lund University, Malmö, Sweden
| | - Olof Strandberg
- Clinical Memory Research Unit, Lund University, Malmö, Sweden
| | | | - Tomas Olsson
- Department of Radiation Physics, Skåne University Hospital, Lund, Sweden
| | - Jonas Jögi
- Department of Clinical Physiology and Nuclear Medicine, Skåne University Hospital, Lund, Sweden
| | - Erik Stormrud
- Clinical Memory Research Unit, Lund University, Malmö, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Hanna Cho
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Young Hoon Ryu
- Department of Nuclear Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Jae Yong Choi
- Department of Nuclear Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea.,Division of Applied Radiological Imaging, Korea Institute Radiological and Medical Sciences, Seoul, South Korea
| | - Adam L Boxer
- Department of Neurology, Memory and Aging Center, University of California, San Francisco
| | - Maria L Gorno-Tempini
- Department of Neurology, Memory and Aging Center, University of California, San Francisco
| | - Bruce L Miller
- Department of Neurology, Memory and Aging Center, University of California, San Francisco
| | | | - Leonardo Iaccarino
- Department of Neurology, Memory and Aging Center, University of California, San Francisco
| | - Renaud La Joie
- Department of Neurology, Memory and Aging Center, University of California, San Francisco
| | - Suzanne Baker
- Lawrence Berkeley National Laboratory, Berkeley, California
| | | | | | | | | | - William J Jagust
- Lawrence Berkeley National Laboratory, Berkeley, California.,Helen Wills Neuroscience Institute, University of California, Berkeley
| | - Chul Hyoung Lyoo
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Gil D Rabinovici
- Department of Neurology, Memory and Aging Center, University of California, San Francisco.,Department of Radiology and Biomedical Imaging, University of California, San Francisco.,Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, California.,Associate Editor, JAMA Neurology
| | - Oskar Hansson
- Clinical Memory Research Unit, Lund University, Malmö, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
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Ossenkoppele R, Hansson O. Towards clinical application of tau PET tracers for diagnosing dementia due to Alzheimer's disease. Alzheimers Dement 2021; 17:1998-2008. [PMID: 33984177 DOI: 10.1002/alz.12356] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 03/22/2021] [Accepted: 03/28/2021] [Indexed: 11/07/2022]
Abstract
The recent development of several tau positron emission tomography (PET) tracers represents a major milestone for the Alzheimer's disease (AD) field. These tau PET tracers bind tau neurofibrillary tangles, a key neuropathological characteristic of AD that is tightly linked to synaptic loss, brain atrophy, and cognitive decline. It is notable that these tau PET tracers show low uptake in most non-AD tauopathies and other neurodegenerative disorders, resulting in a diagnostic specificity that is superior to that of amyloid beta (Aβ) PET and biofluid markers, especially at an older age when incidental Aβ pathology is common. Furthermore, tau PET tracers diagnostically outperform widely used MRI markers. Given its excellent diagnostic performance due to the combination of high sensitivity and specificity for detecting tau pathology in AD dementia, we hypothesize that tau PET can become an important diagnostic tool in specialized clinics for the differential diagnosis of dementia syndromes where AD is among the major possible underlying diseases.
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Affiliation(s)
- Rik Ossenkoppele
- Lund University, Clinical Memory Research Unit, Lund, Sweden.,Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Oskar Hansson
- Lund University, Clinical Memory Research Unit, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
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Buckley RF. Recent Advances in Imaging of Preclinical, Sporadic, and Autosomal Dominant Alzheimer's Disease. Neurotherapeutics 2021; 18:709-727. [PMID: 33782864 PMCID: PMC8423933 DOI: 10.1007/s13311-021-01026-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/15/2021] [Indexed: 12/25/2022] Open
Abstract
Observing Alzheimer's disease (AD) pathological changes in vivo with neuroimaging provides invaluable opportunities to understand and predict the course of disease. Neuroimaging AD biomarkers also allow for real-time tracking of disease-modifying treatment in clinical trials. With recent neuroimaging advances, along with the burgeoning availability of longitudinal neuroimaging data and big-data harmonization approaches, a more comprehensive evaluation of the disease has shed light on the topographical staging and temporal sequencing of the disease. Multimodal imaging approaches have also promoted the development of data-driven models of AD-associated pathological propagation of tau proteinopathies. Studies of autosomal dominant, early sporadic, and late sporadic courses of the disease have shed unique insights into the AD pathological cascade, particularly with regard to genetic vulnerabilities and the identification of potential drug targets. Further, neuroimaging markers of b-amyloid, tau, and neurodegeneration have provided a powerful tool for validation of novel fluid cerebrospinal and plasma markers. This review highlights some of the latest advances in the field of human neuroimaging in AD across these topics, particularly with respect to positron emission tomography and structural and functional magnetic resonance imaging.
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Affiliation(s)
- Rachel F Buckley
- Department of Neurology, Massachusetts General Hospital & Brigham and Women's, Harvard Medical School, Boston, MA, USA.
- Melbourne School of Psychological Sciences and Florey Institutes, University of Melbourne, Melbourne, VIC, Australia.
- Department of Neurology, Massachusetts General Hospital, 149 13th St, Charlestown, MA, 02129, USA.
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