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Dolatshahi M, Commean PK, Rahmani F, Liu J, Lloyd L, Nguyen C, Hantler N, Ly M, Yu G, Ippolito JE, Sirlin C, Morris JC, Benzinger TL, Raji CA. Alzheimer Disease Pathology and Neurodegeneration in Midlife Obesity: A Pilot Study. Aging Dis 2024; 15:1843-1854. [PMID: 37548931 PMCID: PMC11272197 DOI: 10.14336/ad.2023.0707] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Accepted: 07/07/2023] [Indexed: 08/08/2023] Open
Abstract
Obesity and excess adiposity at midlife are risk factors for Alzheimer disease (AD). Visceral fat is known to be associated with insulin resistance and a pro-inflammatory state, the two mechanisms involved in AD pathology. We assessed the association of obesity, MRI-determined abdominal adipose tissue volumes, and insulin resistance with PET-determined amyloid and tau uptake in default mode network areas, and MRI-determined brain volume and cortical thickness in AD cortical signature in the cognitively normal midlife population. Thirty-two middle-aged (age: 51.27±6.12 years, 15 males, body mass index (BMI): 32.28±6.39 kg/m2) cognitively normal participants, underwent bloodwork, brain and abdominal MRI, and amyloid and tau PET scan. Visceral and subcutaneous adipose tissue (VAT, SAT) were semi-automatically segmented using VOXel Analysis Suite (Voxa). FreeSurfer was used to automatically segment brain regions using a probabilistic atlas. PET scans were acquired using [11C]PiB and AV-1451 tracers and were analyzed using PET unified pipeline. The association of brain volumes, cortical thicknesses, and PiB and AV-1451 standardized uptake value ratios (SUVRs) with BMI, VAT/SAT ratio, and insulin resistance were assessed using Spearman's partial correlation. VAT/SAT ratio was associated significantly with PiB SUVRs in the right precuneus cortex (p=0.034) overall, controlling for sex. This association was significant only in males (p=0.044), not females (p=0.166). Higher VAT/SAT ratio and PiB SUVRs in the right precuneus cortex were associated with lower cortical thickness in AD-signature areas predominantly including bilateral temporal cortices, parahippocampal, medial orbitofrontal, and cingulate cortices, with age and sex as covariates. Also, higher BMI and insulin resistance were associated with lower cortical thickness in bilateral temporal poles. In midlife cognitively normal adults, we demonstrated higher amyloid pathology in the right precuneus cortex in individuals with a higher VAT/SAT ratio, a marker of visceral obesity, along with a lower cortical thickness in AD-signature areas associated with higher visceral obesity, insulin resistance, and amyloid pathology.
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Affiliation(s)
- Mahsa Dolatshahi
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA.
| | - Paul K Commean
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA.
| | - Farzaneh Rahmani
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA.
| | - Jingxia Liu
- Washington University School of Medicine, Division of Public Health Sciences, Department of Surgery, St. Louis, Missouri, USA.
| | - LaKisha Lloyd
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA.
| | - Caitlyn Nguyen
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA.
| | - Nancy Hantler
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA.
| | - Maria Ly
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA.
| | - Gary Yu
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA.
| | - Joseph E Ippolito
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA.
- Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, Missouri, USA.
| | - Claude Sirlin
- Liver Imaging Group, Department of Radiology, University of California, San Diego, La Jolla, California, USA.
| | - John C Morris
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri, USA.
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, Saint Louis, Missouri, USA.
| | - Tammie L.S Benzinger
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA.
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, Saint Louis, Missouri, USA.
- Department of Neurosurgery, Washington University School of Medicine, St Louis, Missouri, USA.
| | - Cyrus A Raji
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, Missouri, USA.
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri, USA.
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, Saint Louis, Missouri, USA.
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McKay NS, Millar PR, Nicosia J, Aschenbrenner AJ, Gordon BA, Benzinger TLS, Cruchaga CC, Schindler SE, Morris JC, Hassenstab J. Pick a PACC: Comparing domain-specific and general cognitive composites in Alzheimer disease research. Neuropsychology 2024; 38:443-464. [PMID: 38602816 PMCID: PMC11176005 DOI: 10.1037/neu0000949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/13/2024] Open
Abstract
OBJECTIVE We aimed to illustrate how complex cognitive data can be used to create domain-specific and general cognitive composites relevant to Alzheimer disease research. METHOD Using equipercentile equating, we combined data from the Charles F. and Joanne Knight Alzheimer Disease Research Center that spanned multiple iterations of the Uniform Data Set. Exploratory factor analyses revealed four domain-specific composites representing episodic memory, semantic memory, working memory, and attention/processing speed. The previously defined preclinical Alzheimer disease cognitive composite (PACC) and a novel alternative, the Knight-PACC, were also computed alongside a global composite comprising all available tests. These three composites allowed us to compare the usefulness of domain and general composites in the context of predicting common Alzheimer disease biomarkers. RESULTS General composites slightly outperformed domain-specific metrics in predicting imaging-derived amyloid, tau, and neurodegeneration burden. Power analyses revealed that the global, Knight-PACC, and attention and processing speed composites would require the smallest sample sizes to detect cognitive change in a clinical trial, while the Alzheimer Disease Cooperative Study-PACC required two to three times as many participants. CONCLUSIONS Analyses of cognition with the Knight-PACC and our domain-specific composites offer researchers flexibility by providing validated outcome assessments that can equate across test versions to answer a wide range of questions regarding cognitive decline in normal aging and neurodegenerative disease. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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Teipel S, Grazia A, Dyrba M, Grothe MJ, Pomara N. Basal forebrain volume and metabolism in carriers of the Colombian mutation for autosomal dominant Alzheimer's disease. Sci Rep 2024; 14:11268. [PMID: 38760448 PMCID: PMC11101449 DOI: 10.1038/s41598-024-60799-9] [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: 01/03/2024] [Accepted: 04/26/2024] [Indexed: 05/19/2024] Open
Abstract
We aimed to study atrophy and glucose metabolism of the cholinergic basal forebrain in non-demented mutation carriers for autosomal dominant Alzheimer's disease (ADAD). We determined the level of evidence for or against atrophy and impaired metabolism of the basal forebrain in 167 non-demented carriers of the Colombian PSEN1 E280A mutation and 75 age- and sex-matched non-mutation carriers of the same kindred using a Bayesian analysis framework. We analyzed baseline MRI, amyloid PET, and FDG-PET scans of the Alzheimer's Prevention Initiative ADAD Colombia Trial. We found moderate evidence against an association of carrier status with basal forebrain volume (Bayes factor (BF10) = 0.182). We found moderate evidence against a difference of basal forebrain metabolism (BF10 = 0.167). There was only inconclusive evidence for an association between basal forebrain volume and delayed memory and attention (BF10 = 0.884 and 0.184, respectively), and between basal forebrain volume and global amyloid load (BF10 = 2.1). Our results distinguish PSEN1 E280A mutation carriers from sporadic AD cases in which cholinergic involvement of the basal forebrain is already detectable in the preclinical and prodromal stages. This indicates an important difference between ADAD and sporadic AD in terms of pathogenesis and potential treatment targets.
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Affiliation(s)
- Stefan Teipel
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Gehlsheimer Str. 20, 18147, Rostock, Germany.
- Department of Psychosomatic Medicine, University Medicine Rostock, Gehlsheimer Str. 20, 18147, Rostock, Germany.
| | - Alice Grazia
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Gehlsheimer Str. 20, 18147, Rostock, Germany
| | - Martin Dyrba
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Gehlsheimer Str. 20, 18147, Rostock, Germany
| | - Michel J Grothe
- CIEN Foundation/Queen Sofia Foundation Alzheimer Center, Madrid, Spain
| | - Nunzio Pomara
- Geriatric Psychiatry Division, Nathan Kline Institute/Department of Psychiatry and Pathology, NYU Grossman School of Medicine, Orangeburg, NY, USA
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Flaherty R, Sui YV, Masurkar AV, Betensky RA, Rusinek H, Lazar M. Diffusion imaging markers of accelerated aging of the lower cingulum in subjective cognitive decline. Front Neurol 2024; 15:1360273. [PMID: 38784911 PMCID: PMC11111894 DOI: 10.3389/fneur.2024.1360273] [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: 12/22/2023] [Accepted: 04/29/2024] [Indexed: 05/25/2024] Open
Abstract
Introduction Alzheimer's Disease (AD) typically starts in the medial temporal lobe, then develops into a neurodegenerative cascade which spreads to other brain regions. People with subjective cognitive decline (SCD) are more likely to develop dementia, especially in the presence of amyloid pathology. Thus, we were interested in the white matter microstructure of the medial temporal lobe in SCD, specifically the lower cingulum bundle that leads into the hippocampus. Diffusion tensor imaging (DTI) has been shown to differentiate SCD participants who will progress to mild cognitive impairment from those who will not. However, the biology underlying these DTI metrics is unclear, and results in the medial temporal lobe have been inconsistent. Methods To better characterize the microstructure of this region, we applied DTI to cognitively normal participants in the Cam-CAN database over the age of 55 with cognitive testing and diffusion MRI available (N = 325, 127 SCD). Diffusion MRI was processed to generate regional and voxel-wise diffusion tensor values in bilateral lower cingulum white matter, while T1-weighted MRI was processed to generate regional volume and cortical thickness in the medial temporal lobe white matter, entorhinal cortex, temporal pole, and hippocampus. Results SCD participants had thinner cortex in bilateral entorhinal cortex and right temporal pole. No between-group differences were noted for any of the microstructural metrics of the lower cingulum. However, correlations with delayed story recall were significant for all diffusion microstructure metrics in the right lower cingulum in SCD, but not in controls, with a significant interaction effect. Additionally, the SCD group showed an accelerated aging effect in bilateral lower cingulum with MD, AxD, and RD. Discussion The diffusion profiles observed in both interaction effects are suggestive of a mixed neuroinflammatory and neurodegenerative pathology. Left entorhinal cortical thinning correlated with decreased FA and increased RD, suggestive of demyelination. However, right entorhinal cortical thinning also correlated with increased AxD, suggestive of a mixed pathology. This may reflect combined pathologies implicated in early AD. DTI was more sensitive than cortical thickness to the associations between SCD, memory, and age. The combined effects of mixed pathology may increase the sensitivity of DTI metrics to variations with age and cognition.
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Affiliation(s)
- Ryn Flaherty
- Center for Advanced Imaging Innovation and Research, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States
- Vilcek Institute of Graduate Biomedical Sciences, New York University Grossman School of Medicine, New York, NY, United States
| | - Yu Veronica Sui
- Center for Advanced Imaging Innovation and Research, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States
| | - Arjun V. Masurkar
- Department of Neurology, New York University Grossman School of Medicine, New York, NY, United States
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, United States
| | - Rebecca A. Betensky
- Department of Biostatistics, New York University School of Global Public Health, New York, NY, United States
| | - Henry Rusinek
- Center for Advanced Imaging Innovation and Research, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, United States
| | - Mariana Lazar
- Center for Advanced Imaging Innovation and Research, Department of Radiology, New York University Grossman School of Medicine, New York, NY, United States
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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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Meeker KL, Luckett PH, Barthélemy NR, Hobbs DA, Chen C, Bollinger J, Ovod V, Flores S, Keefe S, Henson RL, Herries EM, McDade E, Hassenstab JJ, Xiong C, Cruchaga C, Benzinger TLS, Holtzman DM, Schindler SE, Bateman RJ, Morris JC, Gordon BA, Ances BM. Comparison of cerebrospinal fluid, plasma and neuroimaging biomarker utility in Alzheimer's disease. Brain Commun 2024; 6:fcae081. [PMID: 38505230 PMCID: PMC10950051 DOI: 10.1093/braincomms/fcae081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 02/01/2024] [Accepted: 03/14/2024] [Indexed: 03/21/2024] Open
Abstract
Alzheimer's disease biomarkers are crucial to understanding disease pathophysiology, aiding accurate diagnosis and identifying target treatments. Although the number of biomarkers continues to grow, the relative utility and uniqueness of each is poorly understood as prior work has typically calculated serial pairwise relationships on only a handful of markers at a time. The present study assessed the cross-sectional relationships among 27 Alzheimer's disease biomarkers simultaneously and determined their ability to predict meaningful clinical outcomes using machine learning. Data were obtained from 527 community-dwelling volunteers enrolled in studies at the Charles F. and Joanne Knight Alzheimer Disease Research Center at Washington University in St Louis. We used hierarchical clustering to group 27 imaging, CSF and plasma measures of amyloid beta, tau [phosphorylated tau (p-tau), total tau t-tau)], neuronal injury and inflammation drawn from MRI, PET, mass-spectrometry assays and immunoassays. Neuropsychological and genetic measures were also included. Random forest-based feature selection identified the strongest predictors of amyloid PET positivity across the entire cohort. Models also predicted cognitive impairment across the entire cohort and in amyloid PET-positive individuals. Four clusters emerged reflecting: core Alzheimer's disease pathology (amyloid and tau), neurodegeneration, AT8 antibody-associated phosphorylated tau sites and neuronal dysfunction. In the entire cohort, CSF p-tau181/Aβ40lumi and Aβ42/Aβ40lumi and mass spectrometry measurements for CSF pT217/T217, pT111/T111, pT231/T231 were the strongest predictors of amyloid PET status. Given their ability to denote individuals on an Alzheimer's disease pathological trajectory, these same markers (CSF pT217/T217, pT111/T111, p-tau/Aβ40lumi and t-tau/Aβ40lumi) were largely the best predictors of worse cognition in the entire cohort. When restricting analyses to amyloid-positive individuals, the strongest predictors of impaired cognition were tau PET, CSF t-tau/Aβ40lumi, p-tau181/Aβ40lumi, CSF pT217/217 and pT205/T205. Non-specific CSF measures of neuronal dysfunction and inflammation were poor predictors of amyloid PET and cognitive status. The current work utilized machine learning to understand the interrelationship structure and utility of a large number of biomarkers. The results demonstrate that, although the number of biomarkers has rapidly expanded, many are interrelated and few strongly predict clinical outcomes. Examining the entire corpus of available biomarkers simultaneously provides a meaningful framework to understand Alzheimer's disease pathobiological change as well as insight into which biomarkers may be most useful in Alzheimer's disease clinical practice and trials.
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Affiliation(s)
- Karin L Meeker
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Patrick H Luckett
- Department of Neurosurgery, Washington University in St Louis, St Louis, MO 63110, USA
| | - Nicolas R Barthélemy
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Diana A Hobbs
- Department of Radiology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Charles Chen
- Department of Radiology, Washington University in St Louis, St Louis, MO 63110, USA
| | - James Bollinger
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Vitaliy Ovod
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Shaney Flores
- Department of Radiology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Sarah Keefe
- Department of Radiology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Rachel L Henson
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Elizabeth M Herries
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Eric McDade
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
| | - Jason J Hassenstab
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Chengjie Xiong
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, USA
- Division of Biostatistics, Washington University in St Louis, St Louis, MO 63110, USA
| | - Carlos Cruchaga
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, USA
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Tammie L S Benzinger
- Department of Radiology, Washington University in St Louis, St Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, USA
| | - David M Holtzman
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Suzanne E Schindler
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Randall J Bateman
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
| | - John C Morris
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Brian A Gordon
- Department of Radiology, Washington University in St Louis, St Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, USA
| | - Beau M Ances
- Department of Neurology, Washington University in St Louis, St Louis, MO 63110, USA
- Department of Radiology, Washington University in St Louis, St Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St Louis, MO 63110, USA
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7
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Wagemann O, Li Y, Hassenstab J, Aschenbrenner AJ, McKay NS, Gordon BA, Benzinger TLS, Xiong C, Cruchaga C, Renton AE, Perrin RJ, Berman SB, Chhatwal JP, Farlow MR, Day GS, Ikeuchi T, Jucker M, Lopera F, Mori H, Noble JM, Sánchez‐Valle R, Schofield PR, Morris JC, Daniels A, Levin J, Bateman RJ, McDade E, Llibre‐Guerra JJ. Investigation of sex differences in mutation carriers of the Dominantly Inherited Alzheimer Network. Alzheimers Dement 2024; 20:47-62. [PMID: 37740921 PMCID: PMC10841236 DOI: 10.1002/alz.13460] [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: 05/16/2023] [Revised: 08/10/2023] [Accepted: 08/13/2023] [Indexed: 09/25/2023]
Abstract
INTRODUCTION Studies suggest distinct differences in the development, presentation, progression, and response to treatment of Alzheimer's disease (AD) between females and males. We investigated sex differences in cognition, neuroimaging, and fluid biomarkers in dominantly inherited AD (DIAD). METHODS Three hundred twenty-five mutation carriers (55% female) and one hundred eighty-six non-carriers (58% female) of the Dominantly Inherited Alzheimer Network Observational Study were analyzed. Linear mixed models and Spearman's correlation explored cross-sectional sex differences in cognition, cerebrospinal fluid (CSF) biomarkers, Pittsburgh compound B positron emission tomography (11 C-PiB PET) and structural magnetic resonance imaging (MRI). RESULTS Female carriers performed better than males on delayed recall and processing speed despite similar hippocampal volumes. As the disease progressed, symptomatic females revealed higher increases in MRI markers of neurodegeneration and memory impairment. PiB PET and established CSF AD markers revealed no sex differences. DISCUSSION Our findings suggest an initial cognitive reserve in female carriers followed by a pronounced increase in neurodegeneration coupled with worse performance on delayed recall at later stages of DIAD.
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Affiliation(s)
- Olivia Wagemann
- Department of NeurologyWashington University St. LouisSt. LouisMissouriUSA
- Department of NeurologyLudwig‐Maximilians‐Universität MünchenMunichGermany
| | - Yan Li
- Department of BiostatisticsWashington University St. LouisSt. LouisMissouriUSA
| | - Jason Hassenstab
- Department of NeurologyWashington University St. LouisSt. LouisMissouriUSA
| | | | - Nicole S. McKay
- Department of RadiologyWashington University St. LouisSt. LouisMissouriUSA
| | - Brian A. Gordon
- Department of RadiologyWashington University St. LouisSt. LouisMissouriUSA
| | | | - Chengjie Xiong
- Department of BiostatisticsWashington University St. LouisSt. LouisMissouriUSA
| | - Carlos Cruchaga
- Department of PsychiatryWashington University St. LouisSt. LouisMissouriUSA
| | - Alan E. Renton
- Department of NeuroscienceIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Richard J. Perrin
- Department of NeurologyWashington University St. LouisSt. LouisMissouriUSA
- Department of Pathology and ImmunologyWashington University St. LouisSt. LouisMissouriUSA
| | - Sarah B. Berman
- Department of NeurologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Jasmeer P. Chhatwal
- Department of NeurologyMassachusetts General and Brigham & Female's HospitalsHarvard Medical SchoolBostonMassachusettsUSA
| | - Martin R. Farlow
- Department of NeurologyIndiana University School of MedicineIndianapolisIndianaUSA
| | - Gregory S. Day
- Department of NeurologyMayo Clinic FloridaJacksonvilleFloridaUSA
| | - Takeshi Ikeuchi
- Department of Molecular GeneticsBrain Research InstituteNiigata UniversityNiigataJapan
| | - Mathias Jucker
- Hertie Institute for Clinical Brain ResearchUniversity of TübingenTübingenGermany
- German Center for Neurodegenerative Diseases (DZNE)TübingenGermany
| | - Francisco Lopera
- Grupo de Neurociencias de Antioquia (GNA)Universidad de AntioquiaMedellinColombia
| | - Hiroshi Mori
- Department of Clinical NeuroscienceOsaka Metropolitan University Medical SchoolNagaoka Sutoku UniversityOsakaJapan
| | - James M. Noble
- Department of NeurologyColumbia University Irving Medical CenterNew YorkNew YorkUSA
| | - Raquel Sánchez‐Valle
- Department of NeurologyHospital Clínic de Barcelona (IDIBAPS)University of BarcelonaBarcelonaSpain
| | - Peter R. Schofield
- Neuroscience Research AustraliaSydneyNew South WalesAustralia
- School of Biomedical SciencesUniversity of New South WalesSydneyNew South WalesAustralia
| | - John C. Morris
- Department of NeurologyWashington University St. LouisSt. LouisMissouriUSA
| | - Alisha Daniels
- Department of NeurologyWashington University St. LouisSt. LouisMissouriUSA
| | - Johannes Levin
- Department of NeurologyLudwig‐Maximilians‐Universität MünchenMunichGermany
- German Center for Neurodegenerative Diseases (DZNE)MunichGermany
- Munich Cluster for Systems Neurology (SyNergy)MunichGermany
| | - Randall J. Bateman
- Department of NeurologyWashington University St. LouisSt. LouisMissouriUSA
| | - Eric McDade
- Department of NeurologyWashington University St. LouisSt. LouisMissouriUSA
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8
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Millar PR, Gordon BA, Wisch JK, Schultz SA, Benzinger TL, Cruchaga C, Hassenstab JJ, Ibanez L, Karch C, Llibre-Guerra JJ, Morris JC, Perrin RJ, Supnet-Bell C, Xiong C, Allegri RF, Berman SB, Chhatwal JP, Chrem Mendez PA, Day GS, Hofmann A, Ikeuchi T, Jucker M, Lee JH, Levin J, Lopera F, Niimi Y, Sánchez-González VJ, Schofield PR, Sosa-Ortiz AL, Vöglein J, Bateman RJ, Ances BM, McDade EM. Advanced structural brain aging in preclinical autosomal dominant Alzheimer disease. Mol Neurodegener 2023; 18:98. [PMID: 38111006 PMCID: PMC10729487 DOI: 10.1186/s13024-023-00688-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 11/28/2023] [Indexed: 12/20/2023] Open
Abstract
BACKGROUND "Brain-predicted age" estimates biological age from complex, nonlinear features in neuroimaging scans. The brain age gap (BAG) between predicted and chronological age is elevated in sporadic Alzheimer disease (AD), but is underexplored in autosomal dominant AD (ADAD), in which AD progression is highly predictable with minimal confounding age-related co-pathology. METHODS We modeled BAG in 257 deeply-phenotyped ADAD mutation-carriers and 179 non-carriers from the Dominantly Inherited Alzheimer Network using minimally-processed structural MRI scans. We then tested whether BAG differed as a function of mutation and cognitive status, or estimated years until symptom onset, and whether it was associated with established markers of amyloid (PiB PET, CSF amyloid-β-42/40), phosphorylated tau (CSF and plasma pTau-181), neurodegeneration (CSF and plasma neurofilament-light-chain [NfL]), and cognition (global neuropsychological composite and CDR-sum of boxes). We compared BAG to other MRI measures, and examined heterogeneity in BAG as a function of ADAD mutation variants, APOE ε4 carrier status, sex, and education. RESULTS Advanced brain aging was observed in mutation-carriers approximately 7 years before expected symptom onset, in line with other established structural indicators of atrophy. BAG was moderately associated with amyloid PET and strongly associated with pTau-181, NfL, and cognition in mutation-carriers. Mutation variants, sex, and years of education contributed to variability in BAG. CONCLUSIONS We extend prior work using BAG from sporadic AD to ADAD, noting consistent results. BAG associates well with markers of pTau, neurodegeneration, and cognition, but to a lesser extent, amyloid, in ADAD. BAG may capture similar signal to established MRI measures. However, BAG offers unique benefits in simplicity of data processing and interpretation. Thus, results in this unique ADAD cohort with few age-related confounds suggest that brain aging attributable to AD neuropathology can be accurately quantified from minimally-processed MRI.
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Affiliation(s)
- Peter R Millar
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA.
| | - Brian A Gordon
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Julie K Wisch
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Stephanie A Schultz
- Department of Neurology, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Tammie Ls Benzinger
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | - Jason J Hassenstab
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Laura Ibanez
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
- NeuroGenomics & Informatics Center, Washington University in St. Louis, St. Louis, MO, USA
| | - Celeste Karch
- Department of Psychiatry, Washington University in St. Louis, St. Louis, MO, USA
| | | | - John C Morris
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Richard J Perrin
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Pathology & Immunology, Washington University in St. Louis, St. Louis, MO, USA
| | | | - Chengjie Xiong
- Department of Biostatistics, Washington University in St. Louis, St. Louis, MO, USA
| | | | - Sarah B Berman
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jasmeer P Chhatwal
- Department of Neurology, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | | | - Gregory S Day
- Department of Neurology, Mayo Clinic, Jacksonville, FL, USA
| | - Anna Hofmann
- German Center for Neurodegenerative Diseases (DZNE), 72076, Tübingen, Germany
- Department of Cellular Neurology, Hertie Institute for Clinical Brain Research, University of Tübingen, 72076, Tübingen, Germany
| | - Takeshi Ikeuchi
- Department of Molecular Genetics, Brain Research Institute, Niigata University, Niigata, Japan
| | - Mathias Jucker
- German Center for Neurodegenerative Diseases (DZNE), 72076, Tübingen, Germany
- Department of Cellular Neurology, Hertie Institute for Clinical Brain Research, University of Tübingen, 72076, Tübingen, Germany
| | - Jae-Hong Lee
- Department of Neurology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
- German Center for Neurodegenerative Diseases, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | | | - Yoshiki Niimi
- Unit for Early and Exploratory Clinical Development, The University of Tokyo Hospital, Bunkyo-Ku, Tokyo, Japan
| | - Victor J Sánchez-González
- Departamento de Clínicas, CUALTOS, Universidad de Guadalajara, Tepatitlán de Morelos, Jalisco, México
| | - Peter R Schofield
- Neuroscience Research Australia, Sydney, NSW, Australia
- School of Biomedical Sciences, University of New South Wales, Sydney, NSW, Australia
| | - Ana Luisa Sosa-Ortiz
- Instituto Nacional de Neurologia y Neurocirugía MVS, CDMX, Ciudad de México, Mexico
| | - Jonathan Vöglein
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
- German Center for Neurodegenerative Diseases, Munich, Germany
| | - Randall J Bateman
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Beau M Ances
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
- Mallinckrodt Institute of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Eric M McDade
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
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9
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Rahmani F, Brier MR, Gordon BA, McKay N, Flores S, Keefe S, Hornbeck R, Ances B, Joseph‐Mathurin N, Xiong C, Wang G, Raji CA, Libre‐Guerra JJ, Perrin RJ, McDade E, Daniels A, Karch C, Day GS, Brickman AM, Fulham M, Jack CR, la La Fougère C, Reischl G, Schofield PR, Oh H, Levin J, Vöglein J, Cash DM, Yakushev I, Ikeuchi T, Klunk WE, Morris JC, Bateman RJ, Benzinger TLS. T1 and FLAIR signal intensities are related to tau pathology in dominantly inherited Alzheimer disease. Hum Brain Mapp 2023; 44:6375-6387. [PMID: 37867465 PMCID: PMC10681640 DOI: 10.1002/hbm.26514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 09/17/2023] [Accepted: 09/27/2023] [Indexed: 10/24/2023] Open
Abstract
Carriers of mutations responsible for dominantly inherited Alzheimer disease provide a unique opportunity to study potential imaging biomarkers. Biomarkers based on routinely acquired clinical MR images, could supplement the extant invasive or logistically challenging) biomarker studies. We used 1104 longitudinal MR, 324 amyloid beta, and 87 tau positron emission tomography imaging sessions from 525 participants enrolled in the Dominantly Inherited Alzheimer Network Observational Study to extract novel imaging metrics representing the mean (μ) and standard deviation (σ) of standardized image intensities of T1-weighted and Fluid attenuated inversion recovery (FLAIR) MR scans. There was an exponential decrease in FLAIR-μ in mutation carriers and an increase in FLAIR and T1 signal heterogeneity (T1-σ and FLAIR-σ) as participants approached the symptom onset in both supramarginal, the right postcentral and right superior temporal gyri as well as both caudate nuclei, putamina, thalami, and amygdalae. After controlling for the effect of regional atrophy, FLAIR-μ decreased and T1-σ and FLAIR-σ increased with increasing amyloid beta and tau deposition in numerous cortical regions. In symptomatic mutation carriers and independent of the effect of regional atrophy, tau pathology demonstrated a stronger relationship with image intensity metrics, compared with amyloid pathology. We propose novel MR imaging intensity-based metrics using standard clinical T1 and FLAIR images which strongly associates with the progression of pathology in dominantly inherited Alzheimer disease. We suggest that tau pathology may be a key driver of the observed changes in this cohort of patients.
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Affiliation(s)
| | | | - Brian A. Gordon
- Washington University School of MedicineSt. LouisMissouriUSA
| | - Nicole McKay
- Washington University School of MedicineSt. LouisMissouriUSA
| | - Shaney Flores
- Washington University School of MedicineSt. LouisMissouriUSA
| | - Sarah Keefe
- Washington University School of MedicineSt. LouisMissouriUSA
| | - Russ Hornbeck
- Washington University School of MedicineSt. LouisMissouriUSA
| | - Beau Ances
- Washington University School of MedicineSt. LouisMissouriUSA
| | | | - Chengjie Xiong
- Washington University School of MedicineSt. LouisMissouriUSA
| | - Guoqiao Wang
- Washington University School of MedicineSt. LouisMissouriUSA
| | - Cyrus A. Raji
- Washington University School of MedicineSt. LouisMissouriUSA
| | | | | | - Eric McDade
- Washington University School of MedicineSt. LouisMissouriUSA
| | - Alisha Daniels
- Washington University School of MedicineSt. LouisMissouriUSA
| | - Celeste Karch
- Washington University School of MedicineSt. LouisMissouriUSA
| | - Gregory S. Day
- Mayo Clinic, Department of NeurologyJacksonvilleFloridaUSA
| | - Adam M. Brickman
- Taub Institute for Research on Alzheimer's Disease & the Aging Brain, and Department of Neurology College of Physicians and SurgeonsColumbia UniversityNew YorkNew YorkUSA
| | | | | | - Christian la La Fougère
- Department of Nuclear Medicine and Clinical Molecular ImagingUniversity Hospital TuebingenTübingenGermany
- German Center for Neurodegenerative Diseases (DZNE) TuebingenTübingenGermany
- Department of Preclinical Imaging and RadiopharmacyEberhard Karls University TübingenTübingenGermany
| | - Gerald Reischl
- Department of Nuclear Medicine and Clinical Molecular ImagingUniversity Hospital TuebingenTübingenGermany
- German Center for Neurodegenerative Diseases (DZNE) TuebingenTübingenGermany
- Department of Preclinical Imaging and RadiopharmacyEberhard Karls University TübingenTübingenGermany
| | - Peter R. Schofield
- Neuroscience Research AustraliaSydneyNew South WalesAustralia
- School of Biomedical SciencesUniversity of New South WalesSydneyNew South WalesAustralia
| | - Hwamee Oh
- Brown UniversityProvidenceRhode IslandUSA
| | - Johannes Levin
- Department of NeurologyLudwig‐Maximilians‐Universität MünchenMunichGermany
- German Center for Neurodegenerative Diseases (DZNE), site MunichMunichGermany
- Munich Cluster for Systems Neurology (SyNergy)MunichGermany
| | - Jonathan Vöglein
- Department of NeurologyLudwig‐Maximilians‐Universität MünchenMunichGermany
- German Center for Neurodegenerative Diseases (DZNE), site MunichMunichGermany
- Munich Cluster for Systems Neurology (SyNergy)MunichGermany
| | - David M. Cash
- UK Dementia Research Institute at University College LondonLondonUK
- Dementia Research CentreUCL Queen Square Institute of NeurologyLondonUK
| | - Igor Yakushev
- Department of NeurologyLudwig‐Maximilians‐Universität MünchenMunichGermany
- German Center for Neurodegenerative Diseases (DZNE), site MunichMunichGermany
- Munich Cluster for Systems Neurology (SyNergy)MunichGermany
| | | | | | - John C. Morris
- Washington University School of MedicineSt. LouisMissouriUSA
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10
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Lamar M, Arfanakis K, Yu L, Kapasi A, Duke Han S, Fleischman DA, Bennett DA, Boyle P. The Relationship of MRI-Derived Alzheimer's and Cerebrovascular-Related Signatures With Level of and Change in Health and Financial Literacy. Am J Geriatr Psychiatry 2023; 31:1129-1139. [PMID: 37541932 PMCID: PMC10800641 DOI: 10.1016/j.jagp.2023.07.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 07/13/2023] [Accepted: 07/14/2023] [Indexed: 08/06/2023]
Abstract
OBJECTIVE The cortical thickness "signature" of Alzheimer's disease (AD-CT) and white matter hyperintensity (WMH) burden have each been associated with cognitive aging and incident AD and related dementias. Less is known about how these structural neuroimaging markers associate with other critical behaviors. We investigated associations of AD-CT and WMH volumes with a composite index of health and financial literacy given that the ability to access, understand, and utilize health and financial information significantly influences older adults' health outcomes. DESIGN, SETTING, PARTICIPANTS Participants were 303 adults without dementia (age∼80 years; 74% women) from the Rush Memory and Aging Project. MEASUREMENTS Baseline 3T MRI T1-weighted structural and T2-weighted FLAIR data were used to assess AD-CT and WMH volumes, respectively. Literacy was measured using questions designed to assess comprehension of health and financial information and concepts, yielding a total literacy score. Multivariable linear mixed effects regression models determined the relationship of each neuroimaging marker, first separately and then combined, with the level of and change in literacy. RESULTS Reduced AD-CT and higher WMH at baseline were each associated with lower levels of literacy; only AD-CT was associated with the rate of decline in literacy over time. The association of AD-CT with change in literacy persisted when both neuroimaging markers were included in the same model. CONCLUSIONS The cortical thickness signature of AD predicts changes in health and financial literacy in nondemented older adults suggesting that the multidimensional construct of health and financial literacy relies on specific brain networks implicated in AD.
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Affiliation(s)
- Melissa Lamar
- Rush Alzheimer's Disease Center (ML, KA, LY, AK, SDH, DAF, DAB, PB), Rush University Medical Center, Chicago, IL; Department of Psychiatry and Behavioral Sciences (ML, DAF, PB), Rush University Medical Center, Chicago, IL.
| | - Konstantinos Arfanakis
- Rush Alzheimer's Disease Center (ML, KA, LY, AK, SDH, DAF, DAB, PB), Rush University Medical Center, Chicago, IL; Department of Diagnostic Radiology and Nuclear Medicine (KA, AK), Rush University Medical Center, Chicago, IL; Department of Biomedical Engineering (KA), Illinois Institute of Technology, Chicago, IL
| | - Lei Yu
- Rush Alzheimer's Disease Center (ML, KA, LY, AK, SDH, DAF, DAB, PB), Rush University Medical Center, Chicago, IL; Department of Neurological Sciences (LY, DAF, DAB), Rush University Medical Center, Chicago, IL
| | - Alifiya Kapasi
- Rush Alzheimer's Disease Center (ML, KA, LY, AK, SDH, DAF, DAB, PB), Rush University Medical Center, Chicago, IL; Department of Diagnostic Radiology and Nuclear Medicine (KA, AK), Rush University Medical Center, Chicago, IL
| | - S Duke Han
- Rush Alzheimer's Disease Center (ML, KA, LY, AK, SDH, DAF, DAB, PB), Rush University Medical Center, Chicago, IL; Department of Family Medicine (SDH), Keck School of Medicine of University of Southern California, Los Angeles, CA
| | - Debra A Fleischman
- Rush Alzheimer's Disease Center (ML, KA, LY, AK, SDH, DAF, DAB, PB), Rush University Medical Center, Chicago, IL; Department of Psychiatry and Behavioral Sciences (ML, DAF, PB), Rush University Medical Center, Chicago, IL; Department of Neurological Sciences (LY, DAF, DAB), Rush University Medical Center, Chicago, IL
| | - David A Bennett
- Rush Alzheimer's Disease Center (ML, KA, LY, AK, SDH, DAF, DAB, PB), Rush University Medical Center, Chicago, IL; Department of Neurological Sciences (LY, DAF, DAB), Rush University Medical Center, Chicago, IL
| | - Patricia Boyle
- Rush Alzheimer's Disease Center (ML, KA, LY, AK, SDH, DAF, DAB, PB), Rush University Medical Center, Chicago, IL; Department of Psychiatry and Behavioral Sciences (ML, DAF, PB), Rush University Medical Center, Chicago, IL
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11
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Eldaief MC, Brickhouse M, Katsumi Y, Rosen H, Carvalho N, Touroutoglou A, Dickerson BC. Atrophy in behavioural variant frontotemporal dementia spans multiple large-scale prefrontal and temporal networks. Brain 2023; 146:4476-4485. [PMID: 37201288 PMCID: PMC10629759 DOI: 10.1093/brain/awad167] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 04/10/2023] [Accepted: 04/16/2023] [Indexed: 05/20/2023] Open
Abstract
The identification of a neurodegenerative disorder's distributed pattern of atrophy-or atrophy 'signature'-can lend insights into the cortical networks that degenerate in individuals with specific constellations of symptoms. In addition, this signature can be used as a biomarker to support early diagnoses and to potentially reveal pathological changes associated with said disorder. Here, we characterized the cortical atrophy signature of behavioural variant frontotemporal dementia (bvFTD). We used a data-driven approach to estimate cortical thickness using surface-based analyses in two independent, sporadic bvFTD samples (n = 30 and n = 71, total n = 101), using age- and gender-matched cognitively and behaviourally normal individuals. We found highly similar patterns of cortical atrophy across the two independent samples, supporting the reliability of our bvFTD signature. Next, we investigated whether our bvFTD signature targets specific large-scale cortical networks, as is the case for other neurodegenerative disorders. We specifically asked whether the bvFTD signature topographically overlaps with the salience network, as previous reports have suggested. We hypothesized that because phenotypic presentations of bvFTD are diverse, this would not be the case, and that the signature would cross canonical network boundaries. Consistent with our hypothesis, the bvFTD signature spanned rostral portions of multiple networks, including the default mode, limbic, frontoparietal control and salience networks. We then tested whether the signature comprised multiple anatomical subtypes, which themselves overlapped with specific networks. To explore this, we performed a hierarchical clustering analysis. This yielded three clusters, only one of which extensively overlapped with a canonical network (the limbic network). Taken together, these findings argue against the hypothesis that the salience network is preferentially affected in bvFTD, but rather suggest that-at least in patients who meet diagnostic criteria for the full-blown syndrome-neurodegeneration in bvFTD encompasses a distributed set of prefrontal, insular and anterior temporal nodes of multiple large-scale brain networks, in keeping with the phenotypic diversity of this disorder.
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Affiliation(s)
- Mark C Eldaief
- Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Center for Brain Sciences, Harvard University, Cambridge, MA 02138, USA
| | - Michael Brickhouse
- Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Yuta Katsumi
- Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Howard Rosen
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Nicole Carvalho
- Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Alexandra Touroutoglou
- Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Bradford C Dickerson
- Frontotemporal Disorders Unit and Alzheimer’s Disease Research Center, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
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12
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Llibre-Guerra JJ, Iaccarino L, Coble D, Edwards L, Li Y, McDade E, Strom A, Gordon B, Mundada N, Schindler SE, Tsoy E, Ma Y, Lu R, Fagan AM, Benzinger TLS, Soleimani-Meigooni D, Aschenbrenner AJ, Miller Z, Wang G, Kramer JH, Hassenstab J, Rosen HJ, Morris JC, Miller BL, Xiong C, Perrin RJ, Allegri R, Chrem P, Surace E, Berman SB, Chhatwal J, Masters CL, Farlow MR, Jucker M, Levin J, Fox NC, Day G, Gorno-Tempini ML, Boxer AL, La Joie R, Rabinovici GD, Bateman R. Longitudinal clinical, cognitive and biomarker profiles in dominantly inherited versus sporadic early-onset Alzheimer's disease. Brain Commun 2023; 5:fcad280. [PMID: 37942088 PMCID: PMC10629466 DOI: 10.1093/braincomms/fcad280] [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: 06/01/2023] [Revised: 10/02/2023] [Accepted: 10/17/2023] [Indexed: 11/10/2023] Open
Abstract
Approximately 5% of Alzheimer's disease cases have an early age at onset (<65 years), with 5-10% of these cases attributed to dominantly inherited mutations and the remainder considered as sporadic. The extent to which dominantly inherited and sporadic early-onset Alzheimer's disease overlap is unknown. In this study, we explored the clinical, cognitive and biomarker profiles of early-onset Alzheimer's disease, focusing on commonalities and distinctions between dominantly inherited and sporadic cases. Our analysis included 117 participants with dominantly inherited Alzheimer's disease enrolled in the Dominantly Inherited Alzheimer Network and 118 individuals with sporadic early-onset Alzheimer's disease enrolled at the University of California San Francisco Alzheimer's Disease Research Center. Baseline differences in clinical and biomarker profiles between both groups were compared using t-tests. Differences in the rates of decline were compared using linear mixed-effects models. Individuals with dominantly inherited Alzheimer's disease exhibited an earlier age-at-symptom onset compared with the sporadic group [43.4 (SD ± 8.5) years versus 54.8 (SD ± 5.0) years, respectively, P < 0.001]. Sporadic cases showed a higher frequency of atypical clinical presentations relative to dominantly inherited (56.8% versus 8.5%, respectively) and a higher frequency of APOE-ε4 (50.0% versus 28.2%, P = 0.001). Compared with sporadic early onset, motor manifestations were higher in the dominantly inherited cohort [32.5% versus 16.9% at baseline (P = 0.006) and 46.1% versus 25.4% at last visit (P = 0.001)]. At baseline, the sporadic early-onset group performed worse on category fluency (P < 0.001), Trail Making Test Part B (P < 0.001) and digit span (P < 0.001). Longitudinally, both groups demonstrated similar rates of cognitive and functional decline in the early stages. After 10 years from symptom onset, dominantly inherited participants experienced a greater decline as measured by Clinical Dementia Rating Sum of Boxes [3.63 versus 1.82 points (P = 0.035)]. CSF amyloid beta-42 levels were comparable [244 (SD ± 39.3) pg/ml dominantly inherited versus 296 (SD ± 24.8) pg/ml sporadic early onset, P = 0.06]. CSF phosphorylated tau at threonine 181 levels were higher in the dominantly inherited Alzheimer's disease cohort (87.3 versus 59.7 pg/ml, P = 0.005), but no significant differences were found for t-tau levels (P = 0.35). In summary, sporadic and inherited Alzheimer's disease differed in baseline profiles; sporadic early onset is best distinguished from dominantly inherited by later age at onset, high frequency of atypical clinical presentations and worse executive performance at baseline. Despite these differences, shared pathways in longitudinal clinical decline and CSF biomarkers suggest potential common therapeutic targets for both populations, offering valuable insights for future research and clinical trial design.
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Affiliation(s)
| | - Leonardo Iaccarino
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Dean Coble
- Division of Biostatistics, Washington University in St Louis, St Louis, MO 63108, USA
| | - Lauren Edwards
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Yan Li
- Division of Biostatistics, Washington University in St Louis, St Louis, MO 63108, USA
| | - Eric McDade
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Amelia Strom
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Brian Gordon
- Malinckrodt Institute of Radiology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Nidhi Mundada
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Suzanne E Schindler
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Elena Tsoy
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Yinjiao Ma
- Division of Biostatistics, Washington University in St Louis, St Louis, MO 63108, USA
| | - Ruijin Lu
- Division of Biostatistics, Washington University in St Louis, St Louis, MO 63108, USA
| | - Anne M Fagan
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Tammie L S Benzinger
- Malinckrodt Institute of Radiology, Washington University in St Louis, St Louis, MO 63108, USA
| | - David Soleimani-Meigooni
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | | | - Zachary Miller
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Guoqiao Wang
- Division of Biostatistics, Washington University in St Louis, St Louis, MO 63108, USA
| | - Joel H Kramer
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Jason Hassenstab
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Howard J Rosen
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - John C Morris
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
| | - Bruce L Miller
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Chengjie Xiong
- Division of Biostatistics, Washington University in St Louis, St Louis, MO 63108, USA
| | - Richard J Perrin
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
- Department of Pathology and Immunology, Washington University in St Louis, St. Louis, MO 63108, USA
| | - Ricardo Allegri
- Department of Cognitive Neurology, Institute for Neurological Research Fleni, Buenos Aires, Argentina
| | - Patricio Chrem
- Department of Cognitive Neurology, Institute for Neurological Research Fleni, Buenos Aires, Argentina
| | - Ezequiel Surace
- Department of Cognitive Neurology, Institute for Neurological Research Fleni, Buenos Aires, 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
- Florey Institute, The University of Melbourne, Melbourne 3052, Australia
| | - Martin R Farlow
- Neuroscience Center, Indiana University School of Medicine at Indianapolis, IN 46202, USA
| | - Mathias Jucker
- DZNE-German Center for Neurodegenerative Diseases, Tübingen 72076, Germany
- Hertie-Institute for Clinical Brain Research, University of Tübingen, 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
| | - Nick C Fox
- Dementia Research Centre, Department of Neurodegenerative Disease, University College London Institute of Neurology, London WC1N 3BG, UK
| | - Gregory Day
- Department of Neurology, Mayo Clinic Florida, Jacksonville, FL 33224, USA
| | - Maria Luisa Gorno-Tempini
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Adam L Boxer
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Renaud La Joie
- Department of Neurology, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Gil D Rabinovici
- Department of Neurology, UCSF 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, San Francisco, CA 94158, USA
| | - Randall Bateman
- Department of Neurology, Washington University in St Louis, St Louis, MO 63108, USA
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Luo J, Ma Y, Agboola FJ, Grant E, Morris JC, McDade E, Fagan AM, Benzinger TLS, Hassenstab J, Bateman RJ, Perrin RJ, Gordon BA, Goyal M, Strain JF, Yakushev I, Day GS, Xiong C. Longitudinal Relationships of White Matter Hyperintensities and Alzheimer Disease Biomarkers Across the Adult Life Span. Neurology 2023; 101:e164-e177. [PMID: 37202169 PMCID: PMC10351551 DOI: 10.1212/wnl.0000000000207378] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 03/20/2023] [Indexed: 05/20/2023] Open
Abstract
BACKGROUND AND OBJECTIVES White matter hyperintensities (WMH) correlate with Alzheimer disease (AD) biomarkers cross-sectionally and modulate AD pathogenesis. Longitudinal changes have been reported for AD biomarkers, including concentrations of CSF β-amyloid (Aβ) 42, Aβ40, total tau and phosphorylated tau181, standardized uptake value ratio from the molecular imaging of cerebral fibrillar Aβ with PET using [11C] Pittsburgh Compound-B, MRI-based hippocampal volume, and cortical thickness. Correlations between established AD biomarkers and the longitudinal change for WMH have not been fully evaluated, especially among cognitively normal individuals across the adult life span. METHODS We jointly analyzed the longitudinal data of WMH volume and each of the established AD biomarkers and cognition from 371 cognitively normal individuals whose baseline age spanned from 19.6 to 88.20 years from 4 longitudinal studies of aging and AD. A 2-stage algorithm was applied to identify the inflection point of baseline age whereby older participants had an accelerated longitudinal change in WMH volume, in comparison with the younger participants. The longitudinal correlations between WMH volume and AD biomarkers were estimated from the bivariate linear mixed-effects models. RESULTS A longitudinal increase in WMH volume was associated with a longitudinal increase in PET amyloid uptake and a decrease in MRI hippocampal volume, cortical thickness, and cognition. The inflection point of baseline age in WMH volume was identified at 60.46 (95% CI 56.43-64.49) years, with the annual increase for the older participants (83.12 [SE = 10.19] mm3 per year) more than 13 times faster (p < 0.0001) than that for the younger participants (6.35 [SE = 5.63] mm3 per year). Accelerated rates of change among the older participants were similarly observed in almost all the AD biomarkers. Longitudinal correlations of WMH volume with MRI, PET amyloid biomarkers, and cognition seemed to be numerically stronger for the younger participants, but not significantly different from those for the older participants. Carrying APOE ε4 alleles did not alter the longitudinal correlations between WMH and AD biomarkers. DISCUSSION Longitudinal increases in WMH volume started to accelerate around a baseline age of 60.46 years and correlated with the longitudinal change in PET amyloid uptake, MRI structural outcomes, and cognition.
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Affiliation(s)
- Jingqin Luo
- From the Division of Public Health Sciences (J.L.), Department of Surgery, Siteman Cancer Center Biostatistics Core (J.L.), Division of Biostatistics (J.L., Y.M., F.J.A., E.G., C.X.), Knight Alzheimer Disease Research Center (Y.M., F.J.A., E.G., J.C.M., A.M.F., T.L.S.B., J.H., R.J.B., R.J.P., B.A.G., C.X.), Department of Neurology (J.C.M., E.M., A.M.F., J.H., R.J.B., R.J.P., M.G., J.F.S.), Department of Pathology and Immunology (J.C.M., R.J.P.), and Department of Radiology (T.L.S.B., B.A.G., M.G.), Washington University School of Medicine, St. Louis, MO; Department of Nuclear Medicine (I.Y.), and Klinikum rechts der Isar (I.Y.), School of Medicine, Neuroimaging Center (TUM-NIC), Technical University of Munich, Germany; and Department of Neurology (G.S.D.), Mayo Clinic, Jacksonville, FL
| | - Yinjiao Ma
- From the Division of Public Health Sciences (J.L.), Department of Surgery, Siteman Cancer Center Biostatistics Core (J.L.), Division of Biostatistics (J.L., Y.M., F.J.A., E.G., C.X.), Knight Alzheimer Disease Research Center (Y.M., F.J.A., E.G., J.C.M., A.M.F., T.L.S.B., J.H., R.J.B., R.J.P., B.A.G., C.X.), Department of Neurology (J.C.M., E.M., A.M.F., J.H., R.J.B., R.J.P., M.G., J.F.S.), Department of Pathology and Immunology (J.C.M., R.J.P.), and Department of Radiology (T.L.S.B., B.A.G., M.G.), Washington University School of Medicine, St. Louis, MO; Department of Nuclear Medicine (I.Y.), and Klinikum rechts der Isar (I.Y.), School of Medicine, Neuroimaging Center (TUM-NIC), Technical University of Munich, Germany; and Department of Neurology (G.S.D.), Mayo Clinic, Jacksonville, FL
| | - Folasade Jane Agboola
- From the Division of Public Health Sciences (J.L.), Department of Surgery, Siteman Cancer Center Biostatistics Core (J.L.), Division of Biostatistics (J.L., Y.M., F.J.A., E.G., C.X.), Knight Alzheimer Disease Research Center (Y.M., F.J.A., E.G., J.C.M., A.M.F., T.L.S.B., J.H., R.J.B., R.J.P., B.A.G., C.X.), Department of Neurology (J.C.M., E.M., A.M.F., J.H., R.J.B., R.J.P., M.G., J.F.S.), Department of Pathology and Immunology (J.C.M., R.J.P.), and Department of Radiology (T.L.S.B., B.A.G., M.G.), Washington University School of Medicine, St. Louis, MO; Department of Nuclear Medicine (I.Y.), and Klinikum rechts der Isar (I.Y.), School of Medicine, Neuroimaging Center (TUM-NIC), Technical University of Munich, Germany; and Department of Neurology (G.S.D.), Mayo Clinic, Jacksonville, FL
| | - Elizabeth Grant
- From the Division of Public Health Sciences (J.L.), Department of Surgery, Siteman Cancer Center Biostatistics Core (J.L.), Division of Biostatistics (J.L., Y.M., F.J.A., E.G., C.X.), Knight Alzheimer Disease Research Center (Y.M., F.J.A., E.G., J.C.M., A.M.F., T.L.S.B., J.H., R.J.B., R.J.P., B.A.G., C.X.), Department of Neurology (J.C.M., E.M., A.M.F., J.H., R.J.B., R.J.P., M.G., J.F.S.), Department of Pathology and Immunology (J.C.M., R.J.P.), and Department of Radiology (T.L.S.B., B.A.G., M.G.), Washington University School of Medicine, St. Louis, MO; Department of Nuclear Medicine (I.Y.), and Klinikum rechts der Isar (I.Y.), School of Medicine, Neuroimaging Center (TUM-NIC), Technical University of Munich, Germany; and Department of Neurology (G.S.D.), Mayo Clinic, Jacksonville, FL
| | - John C Morris
- From the Division of Public Health Sciences (J.L.), Department of Surgery, Siteman Cancer Center Biostatistics Core (J.L.), Division of Biostatistics (J.L., Y.M., F.J.A., E.G., C.X.), Knight Alzheimer Disease Research Center (Y.M., F.J.A., E.G., J.C.M., A.M.F., T.L.S.B., J.H., R.J.B., R.J.P., B.A.G., C.X.), Department of Neurology (J.C.M., E.M., A.M.F., J.H., R.J.B., R.J.P., M.G., J.F.S.), Department of Pathology and Immunology (J.C.M., R.J.P.), and Department of Radiology (T.L.S.B., B.A.G., M.G.), Washington University School of Medicine, St. Louis, MO; Department of Nuclear Medicine (I.Y.), and Klinikum rechts der Isar (I.Y.), School of Medicine, Neuroimaging Center (TUM-NIC), Technical University of Munich, Germany; and Department of Neurology (G.S.D.), Mayo Clinic, Jacksonville, FL
| | - Eric McDade
- From the Division of Public Health Sciences (J.L.), Department of Surgery, Siteman Cancer Center Biostatistics Core (J.L.), Division of Biostatistics (J.L., Y.M., F.J.A., E.G., C.X.), Knight Alzheimer Disease Research Center (Y.M., F.J.A., E.G., J.C.M., A.M.F., T.L.S.B., J.H., R.J.B., R.J.P., B.A.G., C.X.), Department of Neurology (J.C.M., E.M., A.M.F., J.H., R.J.B., R.J.P., M.G., J.F.S.), Department of Pathology and Immunology (J.C.M., R.J.P.), and Department of Radiology (T.L.S.B., B.A.G., M.G.), Washington University School of Medicine, St. Louis, MO; Department of Nuclear Medicine (I.Y.), and Klinikum rechts der Isar (I.Y.), School of Medicine, Neuroimaging Center (TUM-NIC), Technical University of Munich, Germany; and Department of Neurology (G.S.D.), Mayo Clinic, Jacksonville, FL
| | - Anne M Fagan
- From the Division of Public Health Sciences (J.L.), Department of Surgery, Siteman Cancer Center Biostatistics Core (J.L.), Division of Biostatistics (J.L., Y.M., F.J.A., E.G., C.X.), Knight Alzheimer Disease Research Center (Y.M., F.J.A., E.G., J.C.M., A.M.F., T.L.S.B., J.H., R.J.B., R.J.P., B.A.G., C.X.), Department of Neurology (J.C.M., E.M., A.M.F., J.H., R.J.B., R.J.P., M.G., J.F.S.), Department of Pathology and Immunology (J.C.M., R.J.P.), and Department of Radiology (T.L.S.B., B.A.G., M.G.), Washington University School of Medicine, St. Louis, MO; Department of Nuclear Medicine (I.Y.), and Klinikum rechts der Isar (I.Y.), School of Medicine, Neuroimaging Center (TUM-NIC), Technical University of Munich, Germany; and Department of Neurology (G.S.D.), Mayo Clinic, Jacksonville, FL
| | - Tammie L S Benzinger
- From the Division of Public Health Sciences (J.L.), Department of Surgery, Siteman Cancer Center Biostatistics Core (J.L.), Division of Biostatistics (J.L., Y.M., F.J.A., E.G., C.X.), Knight Alzheimer Disease Research Center (Y.M., F.J.A., E.G., J.C.M., A.M.F., T.L.S.B., J.H., R.J.B., R.J.P., B.A.G., C.X.), Department of Neurology (J.C.M., E.M., A.M.F., J.H., R.J.B., R.J.P., M.G., J.F.S.), Department of Pathology and Immunology (J.C.M., R.J.P.), and Department of Radiology (T.L.S.B., B.A.G., M.G.), Washington University School of Medicine, St. Louis, MO; Department of Nuclear Medicine (I.Y.), and Klinikum rechts der Isar (I.Y.), School of Medicine, Neuroimaging Center (TUM-NIC), Technical University of Munich, Germany; and Department of Neurology (G.S.D.), Mayo Clinic, Jacksonville, FL
| | - Jason Hassenstab
- From the Division of Public Health Sciences (J.L.), Department of Surgery, Siteman Cancer Center Biostatistics Core (J.L.), Division of Biostatistics (J.L., Y.M., F.J.A., E.G., C.X.), Knight Alzheimer Disease Research Center (Y.M., F.J.A., E.G., J.C.M., A.M.F., T.L.S.B., J.H., R.J.B., R.J.P., B.A.G., C.X.), Department of Neurology (J.C.M., E.M., A.M.F., J.H., R.J.B., R.J.P., M.G., J.F.S.), Department of Pathology and Immunology (J.C.M., R.J.P.), and Department of Radiology (T.L.S.B., B.A.G., M.G.), Washington University School of Medicine, St. Louis, MO; Department of Nuclear Medicine (I.Y.), and Klinikum rechts der Isar (I.Y.), School of Medicine, Neuroimaging Center (TUM-NIC), Technical University of Munich, Germany; and Department of Neurology (G.S.D.), Mayo Clinic, Jacksonville, FL
| | - Randall J Bateman
- From the Division of Public Health Sciences (J.L.), Department of Surgery, Siteman Cancer Center Biostatistics Core (J.L.), Division of Biostatistics (J.L., Y.M., F.J.A., E.G., C.X.), Knight Alzheimer Disease Research Center (Y.M., F.J.A., E.G., J.C.M., A.M.F., T.L.S.B., J.H., R.J.B., R.J.P., B.A.G., C.X.), Department of Neurology (J.C.M., E.M., A.M.F., J.H., R.J.B., R.J.P., M.G., J.F.S.), Department of Pathology and Immunology (J.C.M., R.J.P.), and Department of Radiology (T.L.S.B., B.A.G., M.G.), Washington University School of Medicine, St. Louis, MO; Department of Nuclear Medicine (I.Y.), and Klinikum rechts der Isar (I.Y.), School of Medicine, Neuroimaging Center (TUM-NIC), Technical University of Munich, Germany; and Department of Neurology (G.S.D.), Mayo Clinic, Jacksonville, FL
| | - Richard J Perrin
- From the Division of Public Health Sciences (J.L.), Department of Surgery, Siteman Cancer Center Biostatistics Core (J.L.), Division of Biostatistics (J.L., Y.M., F.J.A., E.G., C.X.), Knight Alzheimer Disease Research Center (Y.M., F.J.A., E.G., J.C.M., A.M.F., T.L.S.B., J.H., R.J.B., R.J.P., B.A.G., C.X.), Department of Neurology (J.C.M., E.M., A.M.F., J.H., R.J.B., R.J.P., M.G., J.F.S.), Department of Pathology and Immunology (J.C.M., R.J.P.), and Department of Radiology (T.L.S.B., B.A.G., M.G.), Washington University School of Medicine, St. Louis, MO; Department of Nuclear Medicine (I.Y.), and Klinikum rechts der Isar (I.Y.), School of Medicine, Neuroimaging Center (TUM-NIC), Technical University of Munich, Germany; and Department of Neurology (G.S.D.), Mayo Clinic, Jacksonville, FL
| | - Brian A Gordon
- From the Division of Public Health Sciences (J.L.), Department of Surgery, Siteman Cancer Center Biostatistics Core (J.L.), Division of Biostatistics (J.L., Y.M., F.J.A., E.G., C.X.), Knight Alzheimer Disease Research Center (Y.M., F.J.A., E.G., J.C.M., A.M.F., T.L.S.B., J.H., R.J.B., R.J.P., B.A.G., C.X.), Department of Neurology (J.C.M., E.M., A.M.F., J.H., R.J.B., R.J.P., M.G., J.F.S.), Department of Pathology and Immunology (J.C.M., R.J.P.), and Department of Radiology (T.L.S.B., B.A.G., M.G.), Washington University School of Medicine, St. Louis, MO; Department of Nuclear Medicine (I.Y.), and Klinikum rechts der Isar (I.Y.), School of Medicine, Neuroimaging Center (TUM-NIC), Technical University of Munich, Germany; and Department of Neurology (G.S.D.), Mayo Clinic, Jacksonville, FL
| | - Manu Goyal
- From the Division of Public Health Sciences (J.L.), Department of Surgery, Siteman Cancer Center Biostatistics Core (J.L.), Division of Biostatistics (J.L., Y.M., F.J.A., E.G., C.X.), Knight Alzheimer Disease Research Center (Y.M., F.J.A., E.G., J.C.M., A.M.F., T.L.S.B., J.H., R.J.B., R.J.P., B.A.G., C.X.), Department of Neurology (J.C.M., E.M., A.M.F., J.H., R.J.B., R.J.P., M.G., J.F.S.), Department of Pathology and Immunology (J.C.M., R.J.P.), and Department of Radiology (T.L.S.B., B.A.G., M.G.), Washington University School of Medicine, St. Louis, MO; Department of Nuclear Medicine (I.Y.), and Klinikum rechts der Isar (I.Y.), School of Medicine, Neuroimaging Center (TUM-NIC), Technical University of Munich, Germany; and Department of Neurology (G.S.D.), Mayo Clinic, Jacksonville, FL
| | - Jeremy F Strain
- From the Division of Public Health Sciences (J.L.), Department of Surgery, Siteman Cancer Center Biostatistics Core (J.L.), Division of Biostatistics (J.L., Y.M., F.J.A., E.G., C.X.), Knight Alzheimer Disease Research Center (Y.M., F.J.A., E.G., J.C.M., A.M.F., T.L.S.B., J.H., R.J.B., R.J.P., B.A.G., C.X.), Department of Neurology (J.C.M., E.M., A.M.F., J.H., R.J.B., R.J.P., M.G., J.F.S.), Department of Pathology and Immunology (J.C.M., R.J.P.), and Department of Radiology (T.L.S.B., B.A.G., M.G.), Washington University School of Medicine, St. Louis, MO; Department of Nuclear Medicine (I.Y.), and Klinikum rechts der Isar (I.Y.), School of Medicine, Neuroimaging Center (TUM-NIC), Technical University of Munich, Germany; and Department of Neurology (G.S.D.), Mayo Clinic, Jacksonville, FL
| | - Igor Yakushev
- From the Division of Public Health Sciences (J.L.), Department of Surgery, Siteman Cancer Center Biostatistics Core (J.L.), Division of Biostatistics (J.L., Y.M., F.J.A., E.G., C.X.), Knight Alzheimer Disease Research Center (Y.M., F.J.A., E.G., J.C.M., A.M.F., T.L.S.B., J.H., R.J.B., R.J.P., B.A.G., C.X.), Department of Neurology (J.C.M., E.M., A.M.F., J.H., R.J.B., R.J.P., M.G., J.F.S.), Department of Pathology and Immunology (J.C.M., R.J.P.), and Department of Radiology (T.L.S.B., B.A.G., M.G.), Washington University School of Medicine, St. Louis, MO; Department of Nuclear Medicine (I.Y.), and Klinikum rechts der Isar (I.Y.), School of Medicine, Neuroimaging Center (TUM-NIC), Technical University of Munich, Germany; and Department of Neurology (G.S.D.), Mayo Clinic, Jacksonville, FL
| | - Gregory S Day
- From the Division of Public Health Sciences (J.L.), Department of Surgery, Siteman Cancer Center Biostatistics Core (J.L.), Division of Biostatistics (J.L., Y.M., F.J.A., E.G., C.X.), Knight Alzheimer Disease Research Center (Y.M., F.J.A., E.G., J.C.M., A.M.F., T.L.S.B., J.H., R.J.B., R.J.P., B.A.G., C.X.), Department of Neurology (J.C.M., E.M., A.M.F., J.H., R.J.B., R.J.P., M.G., J.F.S.), Department of Pathology and Immunology (J.C.M., R.J.P.), and Department of Radiology (T.L.S.B., B.A.G., M.G.), Washington University School of Medicine, St. Louis, MO; Department of Nuclear Medicine (I.Y.), and Klinikum rechts der Isar (I.Y.), School of Medicine, Neuroimaging Center (TUM-NIC), Technical University of Munich, Germany; and Department of Neurology (G.S.D.), Mayo Clinic, Jacksonville, FL
| | - Chengjie Xiong
- From the Division of Public Health Sciences (J.L.), Department of Surgery, Siteman Cancer Center Biostatistics Core (J.L.), Division of Biostatistics (J.L., Y.M., F.J.A., E.G., C.X.), Knight Alzheimer Disease Research Center (Y.M., F.J.A., E.G., J.C.M., A.M.F., T.L.S.B., J.H., R.J.B., R.J.P., B.A.G., C.X.), Department of Neurology (J.C.M., E.M., A.M.F., J.H., R.J.B., R.J.P., M.G., J.F.S.), Department of Pathology and Immunology (J.C.M., R.J.P.), and Department of Radiology (T.L.S.B., B.A.G., M.G.), Washington University School of Medicine, St. Louis, MO; Department of Nuclear Medicine (I.Y.), and Klinikum rechts der Isar (I.Y.), School of Medicine, Neuroimaging Center (TUM-NIC), Technical University of Munich, Germany; and Department of Neurology (G.S.D.), Mayo Clinic, Jacksonville, FL.
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14
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Wisch JK, Butt OH, Gordon BA, Schindler SE, Fagan AM, Henson RL, Yang C, Boerwinkle AH, Benzinger TLS, Holtzman DM, Morris JC, Cruchaga C, Ances BM. Proteomic clusters underlie heterogeneity in preclinical Alzheimer's disease progression. Brain 2023; 146:2944-2956. [PMID: 36542469 PMCID: PMC10316757 DOI: 10.1093/brain/awac484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 11/21/2022] [Accepted: 11/30/2022] [Indexed: 12/24/2022] Open
Abstract
Heterogeneity in progression to Alzheimer's disease (AD) poses challenges for both clinical prognosis and clinical trial implementation. Multiple AD-related subtypes have previously been identified, suggesting differences in receptivity to drug interventions. We identified early differences in preclinical AD biomarkers, assessed patterns for developing preclinical AD across the amyloid-tau-(neurodegeneration) [AT(N)] framework, and considered potential sources of difference by analysing the CSF proteome. Participants (n = 10) enrolled in longitudinal studies at the Knight Alzheimer Disease Research Center completed four or more lumbar punctures. These individuals were cognitively normal at baseline. Cerebrospinal fluid measures of amyloid-β (Aβ)42, phosphorylated tau (pTau181), and neurofilament light chain (NfL) as well as proteomics values were evaluated. Imaging biomarkers, including PET amyloid and tau, and structural MRI, were repeatedly obtained when available. Individuals were staged according to the amyloid-tau-(neurodegeneration) framework. Growth mixture modelling, an unsupervised clustering technique, identified three patterns of biomarker progression as measured by CSF pTau181 and Aβ42. Two groups (AD Biomarker Positive and Intermediate AD Biomarker) showed distinct progression from normal biomarker status to having biomarkers consistent with preclinical AD. A third group (AD Biomarker Negative) did not develop abnormal AD biomarkers over time. Participants grouped by CSF trajectories were re-classified using only proteomic profiles (AUCAD Biomarker Positive versus AD Biomarker Negative = 0.857, AUCAD Biomarker Positive versus Intermediate AD Biomarkers = 0.525, AUCIntermediate AD Biomarkers versus AD Biomarker Negative = 0.952). We highlight heterogeneity in the development of AD biomarkers in cognitively normal individuals. We identified some individuals who became amyloid positive before the age of 50 years. A second group, Intermediate AD Biomarkers, developed elevated CSF ptau181 significantly before becoming amyloid positive. A third group were AD Biomarker Negative over repeated testing. Our results could influence the selection of participants for specific treatments (e.g. amyloid-reducing versus other agents) in clinical trials. CSF proteome analysis highlighted additional non-AT(N) biomarkers for potential therapies, including blood-brain barrier-, vascular-, immune-, and neuroinflammatory-related targets.
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Affiliation(s)
- Julie K Wisch
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Omar H Butt
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Brian A Gordon
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA
- Hope Center, Washington University in Saint Louis, St. Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Suzanne E Schindler
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Anne M Fagan
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Rachel L Henson
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Chengran Yang
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Anna H Boerwinkle
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Tammie L S Benzinger
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - David M Holtzman
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA
- Hope Center, Washington University in Saint Louis, St. Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - John C Morris
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Carlos Cruchaga
- Hope Center, Washington University in Saint Louis, St. Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Beau M Ances
- Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA
- Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA
- Hope Center, Washington University in Saint Louis, St. Louis, MO 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO 63110, USA
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15
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Luckett PH, Chen C, Gordon BA, Wisch J, Berman SB, Chhatwal JP, Cruchaga C, Fagan AM, Farlow MR, Fox NC, Jucker M, Levin J, Masters CL, Mori H, Noble JM, Salloway S, Schofield PR, Brickman AM, Brooks WS, Cash DM, Fulham MJ, Ghetti B, Jack CR, Vöglein J, Klunk WE, Koeppe R, Su Y, Weiner M, Wang Q, Marcus D, Koudelis D, Mathurin NJ, Cash L, Hornbeck R, Xiong C, Perrin RJ, Karch CM, Hassenstab J, McDade E, Morris JC, Benzinger TL, Bateman RJ, Ances BM. Biomarker clustering in autosomal dominant Alzheimer's disease. Alzheimers Dement 2023; 19:274-284. [PMID: 35362200 PMCID: PMC9525451 DOI: 10.1002/alz.12661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 02/20/2022] [Accepted: 02/22/2022] [Indexed: 01/18/2023]
Abstract
INTRODUCTION As the number of biomarkers used to study Alzheimer's disease (AD) continues to increase, it is important to understand the utility of any given biomarker, as well as what additional information a biomarker provides when compared to others. METHODS We used hierarchical clustering to group 19 cross-sectional biomarkers in autosomal dominant AD. Feature selection identified biomarkers that were the strongest predictors of mutation status and estimated years from symptom onset (EYO). Biomarkers identified included clinical assessments, neuroimaging, cerebrospinal fluid amyloid, and tau, and emerging biomarkers of neuronal integrity and inflammation. RESULTS Three primary clusters were identified: neurodegeneration, amyloid/tau, and emerging biomarkers. Feature selection identified amyloid and tau measures as the primary predictors of mutation status and EYO. Emerging biomarkers of neuronal integrity and inflammation were relatively weak predictors. DISCUSSION These results provide novel insight into our understanding of the relationships among biomarkers and the staging of biomarkers based on disease progression.
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Affiliation(s)
| | - Charlie Chen
- Washington University in St. Louis, St. Louis, Missouri, USA
| | - Brian A. Gordon
- Washington University in St. Louis, St. Louis, Missouri, USA
| | - Julie Wisch
- Washington University in St. Louis, St. Louis, Missouri, USA
| | | | - Jasmeer P. Chhatwal
- Brigham and Women’s Hospital, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Carlos Cruchaga
- Washington University in St. Louis, St. Louis, Missouri, USA
| | - Anne M. Fagan
- Washington University in St. Louis, St. Louis, Missouri, USA
| | | | - Nick C. Fox
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Mathias Jucker
- German Center for Neurodegenerative Disease, Tübingen, Germany
- Hertie-Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
- German Center for Neurodegenerative Diseases, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Colin L. Masters
- Florey Institute, The University of Melbourne, Parkville, Victoria, Australia
| | - Hiroshi Mori
- Osaka City University Medical School, Nagaoka Sutoku University, Abenoku, Osaka, Japan
| | - James M. Noble
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, G.H. Sergievsky Center, and Department of Neurology, Columbia University Irving Medical Center, New York, New York, USA
| | - Stephen Salloway
- Butler Hospital and Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Peter R. Schofield
- Neuroscience Research Australia, Randwick, New South Wales, Australia
- School of Medical Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - Adam M. Brickman
- Department of Molecular Imaging, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia
- The University of Sydney, Sydney, New South Wales, Australia
| | - William S. Brooks
- Neuroscience Research Australia, Randwick, New South Wales, Australia
- School of Medical Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - David M. Cash
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Michael J. Fulham
- Department of Molecular Imaging, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia
- The University of Sydney, Sydney, New South Wales, Australia
| | | | | | - Jonathan Vöglein
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | | | | | - Yi Su
- Banner Alzheimer Institute, Phoenix, Arizona, USA
| | - Michael Weiner
- University of California San Francisco, San Francisco, California, USA
- San Francisco Veterans Affairs Medical Center, San Francisco, California, USA
| | - Qing Wang
- Washington University in St. Louis, St. Louis, Missouri, USA
| | - Daniel Marcus
- Washington University in St. Louis, St. Louis, Missouri, USA
| | | | | | - Lisa Cash
- Washington University in St. Louis, St. Louis, Missouri, USA
| | - Russ Hornbeck
- Washington University in St. Louis, St. Louis, Missouri, USA
| | - Chengjie Xiong
- Washington University in St. Louis, St. Louis, Missouri, USA
| | | | | | | | - Eric McDade
- Washington University in St. Louis, St. Louis, Missouri, USA
| | - John C. Morris
- Washington University in St. Louis, St. Louis, Missouri, USA
| | | | | | - Beau M. Ances
- Washington University in St. Louis, St. Louis, Missouri, USA
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16
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Rahmani F, Ghezzi L, Tosti V, Liu J, Song SK, Wu AT, Rajamanickam J, Obert KA, Benzinger TL, Mittendorfer B, Piccio L, Raji CA. Twelve Weeks of Intermittent Caloric Restriction Diet Mitigates Neuroinflammation in Midlife Individuals with Multiple Sclerosis: A Pilot Study with Implications for Prevention of Alzheimer's Disease. J Alzheimers Dis 2023; 93:263-273. [PMID: 37005885 PMCID: PMC10460547 DOI: 10.3233/jad-221007] [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] [Indexed: 03/30/2023]
Abstract
BACKGROUND Multiple sclerosis (MS) is a prototype neuroinflammatory disorder with increasingly recognized role for neurodegeneration. Most first-line treatments cannot prevent the progression of neurodegeneration and the resultant disability. Interventions can improve symptoms of MS and might provide insights into the underlying pathology. OBJECTIVE To investigate the effect of intermittent caloric restriction on neuroimaging markers of MS. METHODS We randomized ten participants with relapsing remitting MS to either a 12-week intermittent calorie restriction (iCR) diet (n = 5) or control (n = 5). Cortical thickness and volumes were measured through FreeSurfer, cortical perfusion was measured by arterial spin labeling and neuroinflammation through diffusion basis spectrum imaging. RESULTS After 12 weeks of iCR, brain volume increased in the left superior and inferior parietal gyri (p: 0.050 and 0.049, respectively) and the banks of the superior temporal sulcus (p: 0.01). Similarly in the iCR group, cortical thickness improved in the bilateral medial orbitofrontal gyri (p: 0.04 and 0.05 in right and left, respectively), the left superior temporal gyrus (p: 0.03), and the frontal pole (p: 0.008) among others. Cerebral perfusion decreased in the bilateral fusiform gyri (p: 0.047 and 0.02 in right and left, respectively) and increased in the bilateral deep anterior white matter (p: 0.03 and 0.013 in right and left, respectively). Neuroinflammation, demonstrated through hindered and restricted water fractions (HF and RF), decreased in the left optic tract (HF p: 0.02), and the right extreme capsule (RF p: 0.007 and HF p: 0.003). CONCLUSION These pilot data suggest therapeutic effects of iCR in improving cortical volume and thickness and mitigating neuroinflammation in midlife adults with MS.
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Affiliation(s)
- Farzaneh Rahmani
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Laura Ghezzi
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Valeria Tosti
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Jingxia Liu
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA
- Department of Surgery, Division of Public Health Sciences, Washington University in St. Louis, St. Louis, MO, USA
| | - Sheng-Kwei Song
- Department of Physics, Washington University in St. Louis, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA
| | - Anthony T. Wu
- Department of Physics, Washington University in St. Louis, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA
| | - Jayashree Rajamanickam
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Kathleen A. Obert
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Tammie L.S. Benzinger
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University in St Louis, St. Louis, MO, USA
| | - Bettina Mittendorfer
- Department of Medicine, Division of Geriatrics and Nutritional Science, Washington University in St. Louis, St. Louis, MO, USA
| | - Laura Piccio
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA
- Brain and Mind Centre, School of Medical Sciences, The University of Sydney, NSW, Australia
- Charles Perkin Centre, The University of Sydney NSW, Australia
| | - Cyrus A. Raji
- Mallinckrodt Institute of Radiology, Division of Neuroradiology, Washington University in St. Louis, St. Louis, MO, USA
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University in St Louis, St. Louis, MO, USA
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17
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Strain JF, Brier MR, Tanenbaum A, Gordon BA, McCarthy JE, Dincer A, Marcus DS, Chhatwal JP, Graff-Radford NR, Day GS, la Fougère C, Perrin RJ, Salloway S, Schofield PR, Yakushev I, Ikeuchi T, Vöglein J, Morris JC, Benzinger TLS, Bateman RJ, Ances BM, Snyder AZ. Covariance-based vs. correlation-based functional connectivity dissociates healthy aging from Alzheimer disease. Neuroimage 2022; 261:119511. [PMID: 35914670 PMCID: PMC9750733 DOI: 10.1016/j.neuroimage.2022.119511] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 07/04/2022] [Accepted: 07/22/2022] [Indexed: 01/05/2023] Open
Abstract
Prior studies of aging and Alzheimer disease have evaluated resting state functional connectivity (FC) using either seed-based correlation (SBC) or independent component analysis (ICA), with a focus on particular functional systems. SBC and ICA both are insensitive to differences in signal amplitude. At the same time, accumulating evidence indicates that the amplitude of spontaneous BOLD signal fluctuations is physiologically meaningful. We systematically compared covariance-based FC, which is sensitive to amplitude, vs. correlation-based FC, which is not, in affected individuals and controls drawn from two cohorts of participants including autosomal dominant Alzheimer disease (ADAD), late onset Alzheimer disease (LOAD), and age-matched controls. Functional connectivity was computed over 222 regions of interest and group differences were evaluated in terms of components projected onto a space of lower dimension. Our principal observations are: (1) Aging is associated with global loss of resting state fMRI signal amplitude that is approximately uniform across resting state networks. (2) Thus, covariance FC measures decrease with age whereas correlation FC is relatively preserved in healthy aging. (3) In contrast, symptomatic ADAD and LOAD both lead to loss of spontaneous activity amplitude as well as severely degraded correlation structure. These results demonstrate a double dissociation between age vs. Alzheimer disease and the amplitude vs. correlation structure of resting state BOLD signals. Modeling results suggest that the AD-associated loss of correlation structure is attributable to a relative increase in the fraction of locally restricted as opposed to widely shared variance.
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Affiliation(s)
- Jeremy F Strain
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO 63110, USA
| | - Matthew R Brier
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO 63110, USA
| | - Aaron Tanenbaum
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO 63110, USA
| | - Brian A Gordon
- Department of Radiology, Washington University in Saint Louis, Box 8225, 660 South Euclid Ave, St. Louis, MO 63110, USA; Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA; Department of Psychological & Brain Sciences, Washington University, St. Louis, MO, USA
| | - John E McCarthy
- Department of Mathematics and Statistics, Washington University, St. Louis, MO 63130, USA
| | - Aylin Dincer
- Department of Radiology, Washington University in Saint Louis, Box 8225, 660 South Euclid Ave, St. Louis, MO 63110, USA
| | - Daniel S Marcus
- Department of Radiology, Washington University in Saint Louis, Box 8225, 660 South Euclid Ave, St. Louis, MO 63110, USA; Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Jasmeer P Chhatwal
- Martinos Center, Massachusetts General Hospital, 149 13th St Room 2662, Charlestown, MA 02129, USA
| | - Neill R Graff-Radford
- Department of Neurology, Mayo Clinic Florida, 4500 San Pablo Road, Jacksonville, Fl 32224, USA
| | - Gregory S Day
- Department of Neurology, Mayo Clinic Florida, 4500 San Pablo Road, Jacksonville, Fl 32224, USA
| | - Christian la Fougère
- Department of Nuclear Medicine and Clinical Molecular Imaging, Universityhospital Tübingen, Tübingen, Germany; German Center for Neurodegenerative Diseases (DZNE) Tübingen, Germany
| | - Richard J Perrin
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO 63110, USA; Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA; Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO 63110, USA; Department of Pathology and Immunology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Stephen Salloway
- Alpert Medical School of Brown University, 345 Blackstone Boulevard, Providence, RI 02906, USA
| | - Peter R Schofield
- Neuroscience Research Australia, Sydney, NSW 2131, Australia; School of Medical Sciences, University of New South Wales, Sydney, NSW 2052, Australia
| | - Igor Yakushev
- Department of Nuclear Medicine, Klinikum Rechts der Isar, School of Medicine, Technical University of Munich, Ismaninger Str. 22, Munich 81675, Germany
| | - Takeshi Ikeuchi
- Department of Molecular Genetics, Brain Research Institute, Niigata University, Japan
| | - Jonathan Vöglein
- Department of Neurology, Ludwig-Maximilians-Universität Munich, Germany
| | - John C Morris
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO 63110, USA; Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Tammie L S Benzinger
- Department of Radiology, Washington University in Saint Louis, Box 8225, 660 South Euclid Ave, St. Louis, MO 63110, USA; Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Randall J Bateman
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO 63110, USA; Knight Alzheimer Disease Research Center, Washington University in St. Louis, St. Louis, MO 63110, USA; Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Beau M Ances
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO 63110, USA; Department of Radiology, Washington University in Saint Louis, Box 8225, 660 South Euclid Ave, St. Louis, MO 63110, USA; Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Abraham Z Snyder
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO 63110, USA; Department of Radiology, Washington University in Saint Louis, Box 8225, 660 South Euclid Ave, St. Louis, MO 63110, USA.
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18
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Morris JC, Weiner M, Xiong C, Beckett L, Coble D, Saito N, Aisen PS, Allegri R, Benzinger TLS, Berman SB, Cairns NJ, Carrillo MC, Chui HC, Chhatwal JP, Cruchaga C, Fagan AM, Farlow M, Fox NC, Ghetti B, Goate AM, Gordon BA, Graff-Radford N, Day GS, Hassenstab J, Ikeuchi T, Jack CR, Jagust WJ, Jucker M, Levin J, Massoumzadeh P, Masters CL, Martins R, McDade E, Mori H, Noble JM, Petersen RC, Ringman JM, Salloway S, Saykin AJ, Schofield PR, Shaw LM, Toga AW, Trojanowski JQ, Vöglein J, Weninger S, Bateman RJ, Buckles VD. Autosomal dominant and sporadic late onset Alzheimer's disease share a common in vivo pathophysiology. Brain 2022; 145:3594-3607. [PMID: 35580594 PMCID: PMC9989348 DOI: 10.1093/brain/awac181] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 04/12/2022] [Accepted: 04/27/2022] [Indexed: 11/13/2022] Open
Abstract
The extent to which the pathophysiology of autosomal dominant Alzheimer's disease corresponds to the pathophysiology of 'sporadic' late onset Alzheimer's disease is unknown, thus limiting the extrapolation of study findings and clinical trial results in autosomal dominant Alzheimer's disease to late onset Alzheimer's disease. We compared brain MRI and amyloid PET data, as well as CSF concentrations of amyloid-β42, amyloid-β40, tau and tau phosphorylated at position 181, in 292 carriers of pathogenic variants for Alzheimer's disease from the Dominantly Inherited Alzheimer Network, with corresponding data from 559 participants from the Alzheimer's Disease Neuroimaging Initiative. Imaging data and CSF samples were reprocessed as appropriate to guarantee uniform pipelines and assays. Data analyses yielded rates of change before and after symptomatic onset of Alzheimer's disease, allowing the alignment of the ∼30-year age difference between the cohorts on a clinically meaningful anchor point, namely the participant age at symptomatic onset. Biomarker profiles were similar for both autosomal dominant Alzheimer's disease and late onset Alzheimer's disease. Both groups demonstrated accelerated rates of decline in cognitive performance and in regional brain volume loss after symptomatic onset. Although amyloid burden accumulation as determined by PET was greater after symptomatic onset in autosomal dominant Alzheimer's disease than in late onset Alzheimer's disease participants, CSF assays of amyloid-β42, amyloid-β40, tau and p-tau181 were largely overlapping in both groups. Rates of change in cognitive performance and hippocampal volume loss after symptomatic onset were more aggressive for autosomal dominant Alzheimer's disease participants. These findings suggest a similar pathophysiology of autosomal dominant Alzheimer's disease and late onset Alzheimer's disease, supporting a shared pathobiological construct.
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Affiliation(s)
- John C Morris
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Michael Weiner
- Department of Radiology, University of California at San Francisco, San Francisco, CA, USA
| | - Chengjie Xiong
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Laurel Beckett
- Department of Public Health Sciences, School of Medicine, University of California; Davis, Davis, CA, USA
| | - Dean Coble
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Naomi Saito
- Department of Public Health Sciences, School of Medicine, University of California; Davis, Davis, CA, USA
| | - Paul S Aisen
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Ricardo Allegri
- Department of Cognitive Neurology, Neuropsychology and Neuropsychiatry, Institute for Neurological Research (FLENI), Buenos Aires, Argentina
| | - Tammie L S Benzinger
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Sarah B Berman
- Department of Neurology and Clinical and Translational Science, University of Pittsburgh, Pittsburgh, PA, USA
| | - Nigel J Cairns
- College of Medicine and Health and the Living Systems Institute, University of Exeter, Exeter, UK
| | | | - Helena C Chui
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jasmeer P Chhatwal
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Anne M Fagan
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Martin Farlow
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Nick C Fox
- Department of Neurodegenerative Disease and UK Dementia Research Institute, UCL Institute of Neurology, London, UK
| | - Bernardino Ghetti
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Alison M Goate
- Ronald M. Loeb Center for Alzheimer’s Disease, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Brian A Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Gregory S Day
- Department of Neurology, Mayo Clinic, Jacksonville, FL, USA
| | - Jason Hassenstab
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Takeshi Ikeuchi
- Department of Molecular Genetics, Brain Research Institute, Niigata University, Niigata, Japan
| | | | - William J Jagust
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - Mathias Jucker
- Cell Biology of Neurological Diseases Group, German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Johannes Levin
- DZNE Munich, Munich Cluster of Systems Neurology (SyNergy) and Ludwig-Maximilians-Universität, Munich, Germany
| | - Parinaz Massoumzadeh
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Colin L Masters
- Florey Institute, University of Melbourne, Melbourne, Australia
| | - Ralph Martins
- Sir James McCusker Alzheimer’s Disease Research Unit, Edith Cowan University, Nedlands, Australia
| | - Eric McDade
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Hiroshi Mori
- Department of Neuroscience, Osaka City University Medical School, Osaka City, Japan
| | - James M Noble
- Department of Neurology, Taub Institute for Research on Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | | | - John M Ringman
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Stephen Salloway
- Department of Neurology, Butler Hospital and Alpert Medical School of Brown University, Providence, RI, 02906, USA
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences and the Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Peter R Schofield
- Neuroscience Research Australia and School of Medical Sciences, University of New South Wales, Sydney, Australia
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Arthur W Toga
- Laboratory of Neuro Imaging, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - John Q Trojanowski
- Center for Neurodegenerative Disease Research, Institute on Aging, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jonathan Vöglein
- German Center for Neurodegenerative Diseases (DZNE) and Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
| | | | - Randall J Bateman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Virginia D Buckles
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
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19
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Gong X, Zhang H, Liu X, Liu Y, Liu J, Fapohunda FO, Lü P, Wang K, Tang M. Is liquid biopsy mature enough for the diagnosis of Alzheimer’s disease? Front Aging Neurosci 2022; 14:977999. [PMID: 35992602 PMCID: PMC9389010 DOI: 10.3389/fnagi.2022.977999] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2022] [Accepted: 07/18/2022] [Indexed: 01/10/2023] Open
Abstract
The preclinical diagnosis and clinical practice for Alzheimer’s disease (AD) based on liquid biopsy have made great progress in recent years. As liquid biopsy is a fast, low-cost, and easy way to get the phase of AD, continual efforts from intense multidisciplinary studies have been made to move the research tools to routine clinical diagnostics. On one hand, technological breakthroughs have brought new detection methods to the outputs of liquid biopsy to stratify AD cases, resulting in higher accuracy and efficiency of diagnosis. On the other hand, diversiform biofluid biomarkers derived from cerebrospinal fluid (CSF), blood, urine, Saliva, and exosome were screened out and biologically verified. As a result, more detailed knowledge about the molecular pathogenesis of AD was discovered and elucidated. However, to date, how to weigh the reports derived from liquid biopsy for preclinical AD diagnosis is an ongoing question. In this review, we briefly introduce liquid biopsy and the role it plays in research and clinical practice. Then, we summarize the established fluid-based assays of the current state for AD diagnostic such as ELISA, single-molecule array (Simoa), Immunoprecipitation–Mass Spectrometry (IP–MS), liquid chromatography–MS, immunomagnetic reduction (IMR), multimer detection system (MDS). In addition, we give an updated list of fluid biomarkers in the AD research field. Lastly, the current outstanding challenges and the feasibility to use a stand-alone biomarker in the joint diagnostic strategy are discussed.
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Affiliation(s)
- Xun Gong
- Department of Rheumatology and Immunology, Affiliated Hospital of Jiangsu University, Zhenjiang, China
| | - Hantao Zhang
- School of Life Sciences, Jiangsu University, Zhenjiang, China
| | - Xiaoyan Liu
- School of Life Sciences, Jiangsu University, Zhenjiang, China
| | - Yi Liu
- School of Life Sciences, Jiangsu University, Zhenjiang, China
- Institute of Animal Husbandry, Jiangsu Academy of Agricultural Sciences, Nanjing, China
| | - Junlin Liu
- School of Life Sciences, Jiangsu University, Zhenjiang, China
| | | | - Peng Lü
- School of Life Sciences, Jiangsu University, Zhenjiang, China
| | - Kun Wang
- Children’s Center, The Affiliated Taian City Central Hospital of Qingdao University, Taian, China
- *Correspondence: Kun Wang,
| | - Min Tang
- School of Life Sciences, Jiangsu University, Zhenjiang, China
- Min Tang,
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20
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Random walk diffusion simulations in semi-permeable layered media with varying diffusivity. Sci Rep 2022; 12:10759. [PMID: 35750717 PMCID: PMC9232609 DOI: 10.1038/s41598-022-14541-y] [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: 03/02/2022] [Accepted: 06/08/2022] [Indexed: 11/09/2022] Open
Abstract
In this paper we present random walk based solutions to diffusion in semi-permeable layered media with varying diffusivity. We propose a novel transit model for solving the interaction of random walkers with a membrane. This hybrid model is based on treating the membrane permeability and the step change in diffusion coefficient as two interactions separated by an infinitesimally small layer. By conducting an extensive analytical flux analysis, the performance of our hybrid model is compared with a commonly used membrane transit model (reference model). Numerical simulations demonstrate the limitations of the reference model in dealing with step changes in diffusivity and show the capability of the hybrid model to overcome this limitation and to offer substantial gains in computational efficiency. The suitability of both random walk transit models for the application to simulations of diffusion tensor cardiovascular magnetic resonance (DT-CMR) imaging is assessed in a histology-based domain relevant to DT-CMR. In order to demonstrate the usefulness of the new hybrid model for other possible applications, we also consider a larger range of permeabilities beyond those commonly found in biological tissues.
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21
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Rahmani F, Nguyen M, Chen CD, McKay N, Dincer A, Joseph-Mathurin N, Chen G, Liu J, Orlowski HLP, Morris JC, Benzinger TLS. Intracranial internal carotid artery calcification is not predictive of future cognitive decline. Alzheimers Res Ther 2022; 14:32. [PMID: 35148796 PMCID: PMC8832765 DOI: 10.1186/s13195-022-00972-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 01/31/2022] [Indexed: 12/26/2022]
Abstract
Background Intracranial internal carotid artery (ICA) calcification is a common incidental finding in non-contrast head CT. We evaluated the predictive value of ICAC (ICAC) for future risk of cognitive decline and compared the results with conventional imaging biomarkers of dementia. Methods In a retrospective observational cohort, we included 230 participants with a PET-CT scan within 18 months of a baseline clinical assessment and longitudinal imaging assessments. Intracranial ICAC was quantified on baseline CT scans using the Agatson calcium score, and the association between baseline ICA calcium scores and the risk of conversion from a CDR of zero in baseline to a persistent CDR > 0 at any follow-up visit, as well as longitudinal changes in cognitive scores, were evaluated through linear and mixed regression models. We also evaluated the association of conventional imaging biomarkers of dementia with longitudinal changes in cognitive scores and a potential indirect effect of ICAC on cognition through these biomarkers. Results Baseline ICA calcium score could not distinguish participants who converted to CDR > 0. ICA calcium score was also unable to predict longitudinal changes in cognitive scores, imaging biomarkers of small vessel disease such as white matter hyperintensities (WMH) volume, or AD such as hippocampal volume, AD cortical signature thickness, and amyloid burden. Severity of intracranial ICAC increased with age and in men. Higher WMH volume and amyloid burden as well as lower hippocampal volume and AD cortical signature thickness at baseline predicted lower Mini-Mental State Exam scores at longitudinal follow-up. Baseline ICAC was indirectly associated with longitudinal cognitive decline, fully mediated through WMH volume. Conclusions In elderly and preclinical AD populations, atherosclerosis of large intracranial vessels as demonstrated through ICAC is not directly associated with a future risk of cognitive impairment, or progression of imaging biomarkers of AD or small vessel disease.
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Affiliation(s)
- Farzaneh Rahmani
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, 510 South Kingshighway Boulevard, Campus Box 8131, St. Louis, MO, 63110, USA.,Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC), Washington University, St. Louis, MO, USA
| | - Marina Nguyen
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, 510 South Kingshighway Boulevard, Campus Box 8131, St. Louis, MO, 63110, USA.,Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC), Washington University, St. Louis, MO, USA
| | - Charles D Chen
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, 510 South Kingshighway Boulevard, Campus Box 8131, St. Louis, MO, 63110, USA.,Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC), Washington University, St. Louis, MO, USA
| | - Nicole McKay
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, 510 South Kingshighway Boulevard, Campus Box 8131, St. Louis, MO, 63110, USA.,Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC), Washington University, St. Louis, MO, USA
| | - Aylin Dincer
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, 510 South Kingshighway Boulevard, Campus Box 8131, St. Louis, MO, 63110, USA.,Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC), Washington University, St. Louis, MO, USA
| | - Nelly Joseph-Mathurin
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, 510 South Kingshighway Boulevard, Campus Box 8131, St. Louis, MO, 63110, USA.,Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC), Washington University, St. Louis, MO, USA
| | - Gengsheng Chen
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, 510 South Kingshighway Boulevard, Campus Box 8131, St. Louis, MO, 63110, USA.,Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC), Washington University, St. Louis, MO, USA
| | - Jingxia Liu
- Department of Neurology, Washington University in Saint Louis, St. Louis, MO, USA.,Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine (WUSM), St. Louis, MO, USA
| | - Hilary L P Orlowski
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, 510 South Kingshighway Boulevard, Campus Box 8131, St. Louis, MO, 63110, USA
| | - John C Morris
- Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC), Washington University, St. Louis, MO, USA.,Department of Neurology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Tammie L S Benzinger
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, 510 South Kingshighway Boulevard, Campus Box 8131, St. Louis, MO, 63110, USA. .,Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC), Washington University, St. Louis, MO, USA.
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22
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Sturchio A, Dwivedi AK, Malm T, Wood MJ, Cilia R, Sharma JS, Hill EJ, Schneider LS, Graff-Radford NR, Mori H, Nübling G, El Andaloussi S, Svenningsson P, Ezzat K, Espay AJ. High Soluble Amyloid-β42 Predicts Normal Cognition in Amyloid-Positive Individuals with Alzheimer's Disease-Causing Mutations. J Alzheimers Dis 2022; 90:333-348. [PMID: 36120786 PMCID: PMC9661329 DOI: 10.3233/jad-220808] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/15/2022] [Indexed: 12/18/2022]
Abstract
BACKGROUND In amyloid-positive individuals at risk for Alzheimer's disease (AD), high soluble 42-amino acid amyloid-β (Aβ42) levels are associated with normal cognition. It is unknown if this relationship applies longitudinally in a genetic cohort. OBJECTIVE To test the hypothesis that high Aβ42 preserves normal cognition in amyloid-positive individuals with Alzheimer's disease (AD)-causing mutations (APP, PSEN1, or PSEN2) to a greater extent than lower levels of brain amyloid, cerebrospinal fluid (CSF) phosphorylated tau (p-tau), or total tau (t-tau). METHODS Cognitive progression was defined as any increase in Clinical Dementia Rating (CDR = 0, normal cognition; 0.5, very mild dementia; 1, mild dementia) over 3 years. Amyloid-positivity was defined as a standard uptake value ratio (SUVR) ≥1.42 by Pittsburgh compound-B positron emission tomography (PiB-PET). We used modified Poisson regression models to estimate relative risk (RR), adjusted for age at onset, sex, education, APOE4 status, and duration of follow-up. The results were confirmed with multiple sensitivity analyses, including Cox regression. RESULTS Of 232 mutation carriers, 108 were PiB-PET-positive at baseline, with 43 (39.8%) meeting criteria for progression after 3.3±2.0 years. Soluble Aβ42 levels were higher among CDR non-progressors than CDR progressors. Higher Aβ42 predicted a lower risk of progression (adjusted RR, 0.36; 95% confidence interval [CI], 0.19-0.67; p = 0.002) better than lower SUVR (RR, 0.81; 95% CI, 0.68-0.96; p = 0.018). CSF Aβ42 levels predicting lower risk of progression increased with higher SUVR levels. CONCLUSION High CSF Aβ42 levels predict normal cognition in amyloid-positive individuals with AD-causing genetic mutations.
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Affiliation(s)
- Andrea Sturchio
- Department of Neurology, James J. and Joan A. Gardner Family Center for Parkinson’s Disease and Movement Disorders, University of Cincinnati, Cincinnati, OH, USA
- Department of Clinical Neuroscience, Neuro Svenningsson, Karolinska Institutet, Stockholm, Sweden
| | - Alok K. Dwivedi
- Department of Molecular and Translational Medicine, Division of Biostatistics & Epidemiology, Texas Tech University Health Sciences Center, El Paso, TX, USA
| | - Tarja Malm
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Matthew J.A. Wood
- Department of Paediatrics, University of Oxford, Oxford, UK
- MDUK Oxford Neuromuscular Centre, University of Oxford, Oxford, UK
| | - Roberto Cilia
- Department of Clinical Neurosciences, Fondazione IRCCS Istituto Neurologico Carlo Besta, Parkinson and Movement Disorders Unit, Milan, Italy
| | - Jennifer S. Sharma
- Department of Neurology, James J. and Joan A. Gardner Family Center for Parkinson’s Disease and Movement Disorders, University of Cincinnati, Cincinnati, OH, USA
| | - Emily J. Hill
- Department of Neurology, James J. and Joan A. Gardner Family Center for Parkinson’s Disease and Movement Disorders, University of Cincinnati, Cincinnati, OH, USA
| | - Lon S. Schneider
- University of Southern California Keck School of Medicine, Los Angeles, CA, USA
| | | | - Hiroshi Mori
- Department of Clinical Neuroscience, Medical School, Osaka City University, Sutoku University, Abenoku, Osaka, Nagaoka, Japan
| | - Georg Nübling
- German Center for Neurodegenerative Diseases, Site Munich, Germany
- Department of Neurology, Ludwig-Maximilians University Munich, Germany
| | - Samir El Andaloussi
- Department of Laboratory Medicine, Biomolecular and Cellular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Per Svenningsson
- Department of Clinical Neuroscience, Neuro Svenningsson, Karolinska Institutet, Stockholm, Sweden
| | - Kariem Ezzat
- Department of Laboratory Medicine, Biomolecular and Cellular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Alberto J. Espay
- Department of Neurology, James J. and Joan A. Gardner Family Center for Parkinson’s Disease and Movement Disorders, University of Cincinnati, Cincinnati, OH, USA
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