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Kraynak TE, Karim HT, Banihashemi L, Tudorascu DL, Butters MA, Pascoal T, Lopresti B, Andreescu C. A preliminary investigation of worry, cortical amyloid burden, and stressor-evoked brain and cardiovascular reactivity in older adults. J Affect Disord 2024; 367:623-631. [PMID: 39151757 DOI: 10.1016/j.jad.2024.08.042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Revised: 07/31/2024] [Accepted: 08/11/2024] [Indexed: 08/19/2024]
Abstract
Worry is a transdiagnostic symptom common to many neurocognitive disorders of aging, including early stages of Alzheimer's disease and related dementias (ADRD). Severe worry is associated with amyloid burden in cognitively intact older adults, yet the mechanisms underlying this association are not well understood. We hypothesize that this relationship involves altered brain and cardiovascular reactivity to acute stressors, a brain-body phenotype that also increases risk for cardiovascular disease. Twenty cognitively normal older adults (age 60 to 80) with varying levels of worry severity underwent positron emission tomography using Pittsburgh Compound-B and functional magnetic resonance imaging. We examined associations of worry severity and amyloid burden with cardiovascular reactivity, brain activation, and brain connectivity using a cognitive stressor task. Worry severity was not associated with global amyloid burden, but was associated with greater resting levels of cardiovascular physiology and lower systolic blood pressure reactivity. Worry severity also was associated with altered stressor-evoked activation and effective connectivity in brain circuits implicated in stress processing, emotion perception, and physiological regulation. These associations showed small to medium effect sizes. These preliminary findings introduce key components of a model that may link severe worry to ADRD risk via stressor-evoked brain-body interactions.
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Affiliation(s)
- Thomas E Kraynak
- Department of Epidemiology, University of Pittsburgh, United States of America; Department of Psychiatry, University of Pittsburgh, United States of America
| | - Helmet T Karim
- Department of Psychiatry, University of Pittsburgh, United States of America; Department of Bioengineering, University of Pittsburgh, United States of America
| | - Layla Banihashemi
- Department of Psychiatry, University of Pittsburgh, United States of America; Department of Bioengineering, University of Pittsburgh, United States of America
| | - Dana L Tudorascu
- Department of Psychiatry, University of Pittsburgh, United States of America
| | - Meryl A Butters
- Department of Psychiatry, University of Pittsburgh, United States of America
| | - Tharick Pascoal
- Department of Psychiatry, University of Pittsburgh, United States of America; Department of Neurology, University of Pittsburgh, United States of America
| | - Brian Lopresti
- Department of Psychiatry, University of Pittsburgh, United States of America
| | - Carmen Andreescu
- Department of Psychiatry, University of Pittsburgh, United States of America.
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Gildengers A, Weinstein AM, Gujral S, Zeng X, Diaz JL, Lafferty TK, Cowie M, Emanuel JE, Lopez O, Royse SK, Lopresti B, Karikari TK. Where Do Plasma Biomarkers fit in With Current Alzheimer's Disease Detection? Am J Geriatr Psychiatry 2024:S1064-7481(24)00478-0. [PMID: 39448295 DOI: 10.1016/j.jagp.2024.09.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Revised: 09/11/2024] [Accepted: 09/23/2024] [Indexed: 10/26/2024]
Abstract
OBJECTIVES We examine the clinical utility of plasma-based detection for Alzheimer's disease (AD) pathophysiology in older adults with mild cognitive impairment (MCI) and whether cognitive screening can inform when to use plasma-based AD tests. METHODS Seventy-four community-dwelling older adults with MCI had testing with plasma phosphorylated tau (p-tau) 217 and 181, positron emission tomography (PET) imaging for amyloid beta (Aβ), and cognitive assessment. Receiver operating characteristic (ROC) analysis was used to assess the diagnostic value of plasma p-tau. RESULTS Plasma p-tau217 distinguished MCI participants who had PET imaging evidence of Aβ accumulation from those without (AUC of 0.92, specificity of 0.96, and sensitivity of 0.90), outperforming plasma p-tau181 (AUC of 0.76, specificity of 0.87 and sensitivity of 0.59) for the same purpose. Of the 60 MCI participants that were amnestic, 22 were Aβ+. The 14 participants that were nonamnestic were all Aβ-. CONCLUSIONS Our findings support the clinical use of plasma p-tau, particularly p-tau217, for patient detection of AD pathophysiology in older adults with amnestic MCI, but not in those who are nonamnestic.
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Affiliation(s)
- Ariel Gildengers
- Department of Psychiatry (AG, AMW, SG, XZ, TKL, MC, JEE, TKK), University of Pittsburgh School of Medicine, Pittsburgh, PA.
| | - Andrea M Weinstein
- Department of Psychiatry (AG, AMW, SG, XZ, TKL, MC, JEE, TKK), University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - Swathi Gujral
- Department of Psychiatry (AG, AMW, SG, XZ, TKL, MC, JEE, TKK), University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - Xuemei Zeng
- Department of Psychiatry (AG, AMW, SG, XZ, TKL, MC, JEE, TKK), University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - Jihui L Diaz
- Department of Psychiatry (AG, AMW, SG, XZ, TKL, MC, JEE, TKK), University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - Tara K Lafferty
- Department of Psychiatry (AG, AMW, SG, XZ, TKL, MC, JEE, TKK), University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - Matthew Cowie
- Department of Psychiatry (AG, AMW, SG, XZ, TKL, MC, JEE, TKK), University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - James E Emanuel
- Department of Psychiatry (AG, AMW, SG, XZ, TKL, MC, JEE, TKK), University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - Oscar Lopez
- Department of Neurology (OL), University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - Sarah K Royse
- Department of Radiology (SKR, BL), University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - Brian Lopresti
- Department of Radiology (SKR, BL), University of Pittsburgh School of Medicine, Pittsburgh, PA
| | - Thomas K Karikari
- Department of Psychiatry (AG, AMW, SG, XZ, TKL, MC, JEE, TKK), University of Pittsburgh School of Medicine, Pittsburgh, PA
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Royse SK, Snitz BE, Hill AV, Reese AC, Roush RE, Kamboh MI, Bertolet M, Saeed A, Lopresti BJ, Villemagne VL, Lopez OL, Reis SE, Becker JT, Cohen AD. Apolipoprotein E and Alzheimer's disease pathology in African American older adults. Neurobiol Aging 2024; 139:11-19. [PMID: 38582070 DOI: 10.1016/j.neurobiolaging.2024.03.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 03/07/2024] [Accepted: 03/22/2024] [Indexed: 04/08/2024]
Abstract
The apolipoprotein-E4 (APOE*4) and apolipoprotein-E2 (APOE*2) alleles are more common in African American versus non-Hispanic white populations, but relationships of both alleles with Alzheimer's disease (AD) pathology among African American individuals are unclear. We measured APOE allele and β-amyloid (Aβ) and tau using blood samples and positron emission tomography (PET) images, respectively. Individual regression models tested associations of each APOE allele with Aβ or tau PET overall, stratified by racialized group, and with a racialized group interaction. We included 358 older adults (42% African American) with Aβ PET, 134 (29% African American) of whom had tau PET. APOE*4 was associated with higher Aβ in non-Hispanic white (P < 0.0001), but not African American (P = 0.64) participants; racialized group modified the association between APOE*4 and Aβ (P < 0.0001). There were no other racialized group differences. These results suggest that the association of APOE*4 and Aβ differs between African American and non-Hispanic white populations. Other drivers of AD pathology in African American populations should be identified as potential therapeutic targets.
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Affiliation(s)
- Sarah K Royse
- University of Pittsburgh Department of Epidemiology, 130 De Soto Street, Pittsburgh, PA 15261, USA; University of Pittsburgh Department of Radiology, 200 Lothrop Street, Pittsburgh, PA 15213, USA.
| | - Beth E Snitz
- University of Pittsburgh Department of Neurology, 3471 Fifth Avenue, Pittsburgh, PA 15213, USA
| | - Ashley V Hill
- University of Pittsburgh Department of Epidemiology, 130 De Soto Street, Pittsburgh, PA 15261, USA
| | - Alexandria C Reese
- University of Pittsburgh Department of Radiology, 200 Lothrop Street, Pittsburgh, PA 15213, USA
| | - Rebecca E Roush
- University of Pittsburgh Department of Neurology, 3471 Fifth Avenue, Pittsburgh, PA 15213, USA
| | - M Ilyas Kamboh
- University of Pittsburgh Department of Epidemiology, 130 De Soto Street, Pittsburgh, PA 15261, USA; University of Pittsburgh Department of Psychiatry, 3811 O'Hara Street, Pittsburgh, PA 15213, USA; University of Pittsburgh Department of Human Genetics, 130 De Soto Street, Pittsburgh, PA 15213, USA
| | - Marnie Bertolet
- University of Pittsburgh Department of Epidemiology, 130 De Soto Street, Pittsburgh, PA 15261, USA; University of Pittsburgh Department of Biostatistics, 130 De Soto Street, Pittsburgh, PA 15213, USA
| | - Anum Saeed
- University of Pittsburgh Heart and Vascular Institute, University of Pittsburgh, 200 Lothrop Street, Pittsburgh, PA 15213, USA
| | - Brian J Lopresti
- University of Pittsburgh Department of Radiology, 200 Lothrop Street, Pittsburgh, PA 15213, USA
| | - Victor L Villemagne
- University of Pittsburgh Department of Psychiatry, 3811 O'Hara Street, Pittsburgh, PA 15213, USA
| | - Oscar L Lopez
- University of Pittsburgh Department of Neurology, 3471 Fifth Avenue, Pittsburgh, PA 15213, USA; University of Pittsburgh Department of Psychiatry, 3811 O'Hara Street, Pittsburgh, PA 15213, USA
| | - Steven E Reis
- University of Pittsburgh Heart and Vascular Institute, University of Pittsburgh, 200 Lothrop Street, Pittsburgh, PA 15213, USA
| | - James T Becker
- University of Pittsburgh Department of Neurology, 3471 Fifth Avenue, Pittsburgh, PA 15213, USA; University of Pittsburgh Department of Psychiatry, 3811 O'Hara Street, Pittsburgh, PA 15213, USA; University of Pittsburgh Department of Psychology, 210 South Bouquet Street, Pittsburgh, PA 15260, USA
| | - Ann D Cohen
- University of Pittsburgh Department of Psychiatry, 3811 O'Hara Street, Pittsburgh, PA 15213, USA
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Royse SK, Snitz BE, Hengenius JB, Huppert TJ, Roush RE, Ehrenkranz RE, Wilson JD, Bertolet M, Reese AC, Cisneros G, Potopenko K, Becker JT, Cohen AD, Shaaban CE. Unhealthy white matter connectivity, cognition, and racialization in older adults. Alzheimers Dement 2024; 20:1483-1496. [PMID: 37828730 PMCID: PMC10947965 DOI: 10.1002/alz.13494] [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] [Revised: 09/06/2023] [Accepted: 09/10/2023] [Indexed: 10/14/2023]
Abstract
INTRODUCTION White matter hyperintensities (WMH) may promote clinical Alzheimer's disease (AD) disparities between Black American (BA) and non-Hispanic White (nHW) populations. Using a novel measurement, unhealthy white matter connectivity (UWMC), we interrogated racialized group differences in associations between WMH in AD pathology-affected regions and cognition. METHODS UWMC is the proportion of white matter fibers that pass through WMH for every pair of brain regions. Individual regression models tested associations of UWMC in beta-amyloid (Aβ) or tau pathology-affected regions with cognition overall, stratified by racialized group, and with a racialized group interaction. RESULTS In 201 older adults ranging from cognitively unimpaired to AD, BA participants exhibited greater UWMC and worse cognition than nHW participants. UWMC was negatively associated with cognition in 17 and 5 Aβ- and tau-affected regions, respectively. Racialization did not modify these relationships. DISCUSSION Differential UWMC burden, not differential UWMC-and-cognition associations, may drive clinical AD disparities between racialized groups. HIGHLIGHTS Unhealthy white matter connectivity (UWMC) in Alzheimer's disease (AD) pathology-affected brain regions is associated with cognition. Relationships between UWMC and cognition are similar between Black American (BA) and non-Hispanic White (nHW) individuals. More UWMC may partially drive higher clinical AD burden in BA versus nHW populations. UWMC risk factors, particularly social and environmental, should be identified.
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Affiliation(s)
- Sarah K. Royse
- Department of EpidemiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
- Department of RadiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Beth E. Snitz
- Department of NeurologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - James B. Hengenius
- Department of EpidemiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Theodore J. Huppert
- Department of Electrical EngineeringUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Rebecca E. Roush
- Department of NeurologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | | | - James D. Wilson
- Department of Mathematics and StatisticsUniversity of San FranciscoSan FranciscoCaliforniaUSA
| | - Marnie Bertolet
- Department of EpidemiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
- Department of BiostatisticsUniversity of PittsburghPittsburghPennsylvaniaUSA
| | | | - Geraldine Cisneros
- Department of PsychologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Katey Potopenko
- Department of PsychologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - James T. Becker
- Department of NeurologyUniversity of PittsburghPittsburghPennsylvaniaUSA
- Department of BiostatisticsUniversity of PittsburghPittsburghPennsylvaniaUSA
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Ann D. Cohen
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
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Schweitzer N, Li J, Thurston RC, Lopresti B, Klunk WE, Snitz B, Tudorascu D, Cohen A, Kamboh MI, Halligan‐Eddy E, Iordanova B, Villemagne VL, Aizenstein H, Wu M. Sex-dependent alterations in hippocampal connectivity are linked to cerebrovascular and amyloid pathologies in normal aging. Alzheimers Dement 2024; 20:914-924. [PMID: 37817668 PMCID: PMC10916980 DOI: 10.1002/alz.13503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 08/29/2023] [Accepted: 09/19/2023] [Indexed: 10/12/2023]
Abstract
INTRODUCTION Compared to males, females have an accelerated trajectory of cognitive decline in Alzheimer's disease (AD). The neurobiological factors underlying the more rapid cognitive decline in AD in females remain unclear. This study explored how sex-dependent alterations in hippocampal connectivity over 2 years are associated with cerebrovascular and amyloid pathologies in normal aging. METHODS Thirty-three females and 21 males 65 to 93 years of age with no cognitive impairment performed a face-name associative memory functional magnetic resonance imaging (fMRI) task with a 2-year follow-up. We acquired baseline carbon 11-labeled Pittsburgh compound B ([11 C]PiB) positron emission tomography (PET) and T2-weighted fluid-attenuated inversion recovery (T2-FLAIR) MRI to quantify amyloid β (Aβ) burden and white matter hyperintensity (WMH) volume, respectively. RESULTS Males had increased hippocampal-prefrontal connectivity over 2 years, associated with greater Aβ burden. Females had increased bilateral hippocampal functional connectivity, associated with greater WMH volume. DISCUSSION These findings suggest sex-dependent compensatory mechanisms in the memory network in the presence of cerebrovascular and AD pathologies and may explain the accelerated trajectory of cognitive decline in females.
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Affiliation(s)
- Noah Schweitzer
- Department of BioengineeringUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Jinghang Li
- Department of BioengineeringUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Rebecca C. Thurston
- Department of PsychiatryUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Brian Lopresti
- Department of RadiologyUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - William E. Klunk
- Department of PsychiatryUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Beth Snitz
- Department of NeurologyUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Dana Tudorascu
- Department of PsychiatryUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Ann Cohen
- Department of PsychiatryUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - M. Ilyas Kamboh
- Department of Human GeneticsSchool of Public HealthUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Edythe Halligan‐Eddy
- Department of PsychiatryUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Bistra Iordanova
- Department of BioengineeringUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Victor L. Villemagne
- Department of PsychiatryUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Howard Aizenstein
- Department of PsychiatryUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Minjie Wu
- Department of PsychiatryUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
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6
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Bellaver B, Povala G, Ferreira PCL, Ferrari-Souza JP, Leffa DT, Lussier FZ, Benedet AL, Ashton NJ, Triana-Baltzer G, Kolb HC, Tissot C, Therriault J, Servaes S, Stevenson J, Rahmouni N, Lopez OL, Tudorascu DL, Villemagne VL, Ikonomovic MD, Gauthier S, Zimmer ER, Zetterberg H, Blennow K, Aizenstein HJ, Klunk WE, Snitz BE, Maki P, Thurston RC, Cohen AD, Ganguli M, Karikari TK, Rosa-Neto P, Pascoal TA. Astrocyte reactivity influences amyloid-β effects on tau pathology in preclinical Alzheimer's disease. Nat Med 2023:10.1038/s41591-023-02380-x. [PMID: 37248300 PMCID: PMC10353939 DOI: 10.1038/s41591-023-02380-x] [Citation(s) in RCA: 88] [Impact Index Per Article: 88.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Accepted: 05/01/2023] [Indexed: 05/31/2023]
Abstract
An unresolved question for the understanding of Alzheimer's disease (AD) pathophysiology is why a significant percentage of amyloid-β (Aβ)-positive cognitively unimpaired (CU) individuals do not develop detectable downstream tau pathology and, consequently, clinical deterioration. In vitro evidence suggests that reactive astrocytes unleash Aβ effects in pathological tau phosphorylation. Here, in a biomarker study across three cohorts (n = 1,016), we tested whether astrocyte reactivity modulates the association of Aβ with tau phosphorylation in CU individuals. We found that Aβ was associated with increased plasma phosphorylated tau only in individuals positive for astrocyte reactivity (Ast+). Cross-sectional and longitudinal tau-positron emission tomography analyses revealed an AD-like pattern of tau tangle accumulation as a function of Aβ only in CU Ast+ individuals. Our findings suggest astrocyte reactivity as an important upstream event linking Aβ with initial tau pathology, which may have implications for the biological definition of preclinical AD and for selecting CU individuals for clinical trials.
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Affiliation(s)
- Bruna Bellaver
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Graduate Program in Biological Sciences-Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Guilherme Povala
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - João Pedro Ferrari-Souza
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Graduate Program in Biological Sciences-Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Douglas T Leffa
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Firoza Z Lussier
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Andréa L Benedet
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | | | - Hartmuth C Kolb
- Neuroscience Biomarkers, Janssen Research and Development, La Jolla, CA, USA
| | - Cécile Tissot
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Joseph Therriault
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Stijn Servaes
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Jenna Stevenson
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Nesrine Rahmouni
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Oscar L Lopez
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Dana L Tudorascu
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Biostatistics, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Milos D Ikonomovic
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Geriatric Research Education and Clinical Center, VA Pittsburgh HS, Pittsburgh, PA, USA
| | - Serge Gauthier
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
| | - Eduardo R Zimmer
- Graduate Program in Biological Sciences-Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Department of Pharmacology, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Graduate Program in Biological Sciences: Pharmacology and Therapeutics, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Brain Institute, PUCRS, Porto Alegre, Brazil
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Howard J Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - William E Klunk
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beth E Snitz
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Pauline Maki
- Department of Psychiatry, University of Illinois, Chicago, IL, USA
| | - Rebecca C Thurston
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Epidemiology, University of Pittsburgh School of Public Health, Pittsburgh, PA, USA
| | - Ann D Cohen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Mary Ganguli
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Epidemiology, University of Pittsburgh School of Public Health, Pittsburgh, PA, USA
| | - Thomas K Karikari
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada
- Brain Imaging Centre, Montreal Neurological Institute-Hospital, Montreal, Quebec, Canada
| | - Tharick A Pascoal
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA.
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7
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Pascoal T, Bellaver B, Povala G, Ferreira P, Ferrari-Souza JP, Leffa D, Lussier F, Benedet A, Ashton N, Triana-Baltzerz G, Kolbzh H, Tissot C, Therriault J, Servaes S, Stevenson J, Rahmouni N, Lopez O, Tudorascu D, Villemagne V, Ikonomovic M, Gauthier S, Zimmer E, Zetterberg H, Blennow K, Aizenstein H, Klunk W, Snitz B, Maki P, Thurston R, Cohen A, Ganguli M, Karikari T, Rosa-Neto P. Astrocyte reactivity influences the association of amyloid-β and tau biomarkers in preclinical Alzheimer's disease. RESEARCH SQUARE 2023:rs.3.rs-2507179. [PMID: 36778243 PMCID: PMC9915798 DOI: 10.21203/rs.3.rs-2507179/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
An unresolved question for the understanding of Alzheimer's disease (AD) pathophysiology is why a significant percentage of amyloid β (Aβ)-positive cognitively unimpaired (CU) individuals do not develop detectable downstream tau pathology and, consequently, clinical deterioration. In vitro evidence suggests that reactive astrocytes are key to unleashing Aβ effects in pathological tau phosphorylation. In a large study ( n =1,016) across three cohorts, we tested whether astrocyte reactivity modulates the association of Aβ with plasma tau phosphorylation in CU people. We found that Aβ pathology was associated with increased plasma phosphorylated tau levels only in individuals positive for astrocyte reactivity (Ast+). Cross-sectional and longitudinal tau-PET analysis revealed that tau tangles accumulated as a function of Aβ burden only in CU Ast+ individuals with a topographic distribution compatible with early AD. Our findings suggest that increased astrocyte reactivity is an important upstream event linking Aβ burden with initial tau pathology which might have implications for the biological definition of preclinical AD and for selecting individuals for early preventive clinical trials.
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Affiliation(s)
| | | | | | | | | | | | | | - Andrea Benedet
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden
| | - Nicholas Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden
| | | | | | | | | | | | | | | | - Oscar Lopez
- Departments of Neurology and Psychiatry, University of Pittsburgh
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Wu M, Schweitzer N, Iordanova BE, Halligan-Eddy E, Tudorascu DL, Mathis CA, Lopresti BJ, Kamboh MI, Cohen AD, Snitz BE, Klunk WE, Aizenstein HJ. In Pre-Clinical AD Small Vessel Disease is Associated With Altered Hippocampal Connectivity and Atrophy. Am J Geriatr Psychiatry 2023; 31:112-123. [PMID: 36274019 PMCID: PMC10768933 DOI: 10.1016/j.jagp.2022.09.011] [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: 04/08/2022] [Revised: 09/16/2022] [Accepted: 09/20/2022] [Indexed: 01/25/2023]
Abstract
OBJECTIVE Small Vessel Disease (SVD) is known to be associated with higher AD risk, but its relationship to amyloidosis in the progression of AD is unclear. In this cross-sectional study of cognitively normal older adults, we explored the interactive effects of SVD and amyloid-beta (Aβ) pathology on hippocampal functional connectivity during an associative encoding task and on hippocampal volume. METHODS This study included 61 cognitively normal older adults (age range: 65-93 years, age mean ± standard deviation: 75.8 ± 6.4, 41 [67.2%] female). PiB PET, T2-weighted FLAIR, T1-weighted and face-name fMRI images were acquired on each participant to evaluate brain Aβ, white matter hyperintensities (WMH+/- status), gray matter density, and hippocampal functional connectivity. RESULTS We found that, in WMH (+) older adults greater Aβ burden was associated with greater hippocampal local connectivity (i.e., hippocampal-parahippocampal connectivity) and lower gray matter density in medial temporal lobe (MTL), whereas in WMH (-) older adults greater Aβ burden was associated with greater hippocampal distal connectivity (i.e., hippocampal-prefrontal connectivity) and no changes in MTL gray matter density. Moreover, greater hippocampal local connectivity was associated with MTL atrophy. CONCLUSION These observations support a hippocampal excitotoxicity model linking SVD to neurodegeneration in preclinical AD. This may explain how SVD may accelerate the progression from Aβ positivity to neurodegeneration, and subsequent AD.
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Affiliation(s)
- Minjie Wu
- Department of Psychiatry (MW, EHE, DLT, ADC, WEK, HJA), University of Pittsburgh, Pittsburgh, PA.
| | - Noah Schweitzer
- Department of Bioengineering (NS, BEI, HJA), University of Pittsburgh, Pittsburgh, PA
| | - Bistra E Iordanova
- Department of Bioengineering (NS, BEI, HJA), University of Pittsburgh, Pittsburgh, PA
| | - Edythe Halligan-Eddy
- Department of Psychiatry (MW, EHE, DLT, ADC, WEK, HJA), University of Pittsburgh, Pittsburgh, PA
| | - Dana L Tudorascu
- Department of Psychiatry (MW, EHE, DLT, ADC, WEK, HJA), University of Pittsburgh, Pittsburgh, PA; Departments of Medicine and Biostatistics (DLT), University of Pittsburgh, Pittsburgh, PA
| | - Chester A Mathis
- Department of Radiology (CAM, BJL), University of Pittsburgh, Pittsburgh, PA
| | - Brian J Lopresti
- Department of Radiology (CAM, BJL), University of Pittsburgh, Pittsburgh, PA
| | - M Ilyas Kamboh
- Department of Human Genetics (MIK), University of Pittsburgh, Pittsburgh, PA
| | - Ann D Cohen
- Department of Psychiatry (MW, EHE, DLT, ADC, WEK, HJA), University of Pittsburgh, Pittsburgh, PA
| | - Beth E Snitz
- Department of Neurology (BES), University of Pittsburgh, Pittsburgh, PA
| | - William E Klunk
- Department of Psychiatry (MW, EHE, DLT, ADC, WEK, HJA), University of Pittsburgh, Pittsburgh, PA
| | - Howard J Aizenstein
- Department of Psychiatry (MW, EHE, DLT, ADC, WEK, HJA), University of Pittsburgh, Pittsburgh, PA; Department of Bioengineering (NS, BEI, HJA), University of Pittsburgh, Pittsburgh, PA
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9
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Li J, Mountz EJ, Mizuno A, Shah AM, Weinstein A, Cohen AD, Klunk WE, Snitz BE, Aizenstein HJ, Karim HT. Functional Asymmetry During Working Memory and Its Association with Markers of Alzheimer's Disease in Cognitively Normal Older Adults. J Alzheimers Dis 2023; 95:1077-1089. [PMID: 37638440 DOI: 10.3233/jad-230379] [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: 08/29/2023]
Abstract
BACKGROUND Amyloid-β (Aβ) deposits asymmetrically early in Alzheimer's disease (AD). This process is variable and has been associated with asymmetric hypometabolism. OBJECTIVE We investigated whether neural asymmetry during working memory and executive function processing was associated with AD genetic risk and markers of AD as well as other brain neuropathology biomarkers, cognitive function, and cognitive reserve in cognitively normal older adults. METHODS We analyzed data from 77 cognitively healthy, older adults who completed functional magnetic resonance imaging, positron emission tomography, and cognitive testing. We identified regions of significant activation and asymmetry during the Digital Symbol Substitution Task (DSST). We examined associations between regions with significant hemispheric asymmetry (directional and absolute) and global cerebral Aβ, cerebral glucose metabolism, white matter hyperintensities, APOE ɛ4 allele status, DSST reaction time, age, sex, education, and cognitive function. RESULTS Asymmetry was not associated with several factors including cognitive function, Aβ, and white matter hyperintensities. The presence of at least one ɛ4 APOE allele in participants was associated with less asymmetric activation in the angular gyrus (right dominant activation). Greater education was associated with less asymmetric activation in mediodorsal thalamus (left dominant activation). CONCLUSIONS Genetic risk of AD was associated with lower asymmetry in angular gyrus activation, while greater education was associated with lower asymmetry in mediodorsal thalamus activation. Changes in asymmetry may reflect components of compensation or cognitive reserve. Asymmetric neural recruitment during working memory may be related to maintenance of cognitive function in cognitively normal older adults.
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Affiliation(s)
- Jinghang Li
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Elizabeth J Mountz
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Akiko Mizuno
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ashti M Shah
- Physician Scientist Training Program, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Andrea Weinstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ann D Cohen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - William E Klunk
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beth E Snitz
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Howard J Aizenstein
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Helmet T Karim
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
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10
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Hammers DB, Lin JH, Polsinelli AJ, Logan PE, Risacher SL, Schwarz AJ, Apostolova LG. Criterion Validation of Tau PET Staging Schemes in Relation to Cognitive Outcomes. J Alzheimers Dis 2023; 96:197-214. [PMID: 37742649 PMCID: PMC10825758 DOI: 10.3233/jad-230512] [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] [Accepted: 08/14/2023] [Indexed: 09/26/2023]
Abstract
BACKGROUND Utilization of NIA-AA Research Framework requires dichotomization of tau pathology. However, due to the novelty of tau-PET imaging, there is no consensus on methods to categorize scans into "positive" or "negative" (T+ or T-). In response, some tau topographical pathologic staging schemes have been developed. OBJECTIVE The aim of the current study is to establish criterion validity to support these recently-developed staging schemes. METHODS Tau-PET data from 465 participants from the Alzheimer's Disease Neuroimaging Initiative (aged 55 to 90) were classified as T+ or T- using decision rules for the Temporal-Occipital Classification (TOC), Simplified TOC (STOC), and Lobar Classification (LC) tau pathologic schemes of Schwarz, and Chen staging scheme. Subsequent dichotomization was analyzed in comparison to memory and learning slope performances, and diagnostic accuracy using actuarial diagnostic methods. RESULTS Tau positivity was associated with worse cognitive performance across all staging schemes. Cognitive measures were nearly all categorized as having "fair" sensitivity at classifying tau status using TOC, STOC, and LC schemes. Results were comparable between Schwarz schemes, though ease of use and better data fit preferred the STOC and LC schemes. While some evidence was supportive for Chen's scheme, validity lagged behind others-likely due to elevated false positive rates. CONCLUSIONS Tau-PET staging schemes appear to be valuable for Alzheimer's disease diagnosis, tracking, and screening for clinical trials. Their validation provides support as options for tau pathologic dichotomization, as necessary for use of NIA-AA Research Framework. Future research should consider other staging schemes and validation with other outcome benchmarks.
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Affiliation(s)
- Dustin B. Hammers
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Joshua H. Lin
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - Paige E. Logan
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Shannon L. Risacher
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Adam J. Schwarz
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Takeda Pharmaceuticals Ltd., Cambridge, MA, USA
| | - Liana G. Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
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11
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Pemberton HG, Collij LE, Heeman F, Bollack A, Shekari M, Salvadó G, Alves IL, Garcia DV, Battle M, Buckley C, Stephens AW, Bullich S, Garibotto V, Barkhof F, Gispert JD, Farrar G. Quantification of amyloid PET for future clinical use: a state-of-the-art review. Eur J Nucl Med Mol Imaging 2022; 49:3508-3528. [PMID: 35389071 PMCID: PMC9308604 DOI: 10.1007/s00259-022-05784-y] [Citation(s) in RCA: 60] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 03/25/2022] [Indexed: 12/15/2022]
Abstract
Amyloid-β (Aβ) pathology is one of the earliest detectable brain changes in Alzheimer's disease (AD) pathogenesis. The overall load and spatial distribution of brain Aβ can be determined in vivo using positron emission tomography (PET), for which three fluorine-18 labelled radiotracers have been approved for clinical use. In clinical practice, trained readers will categorise scans as either Aβ positive or negative, based on visual inspection. Diagnostic decisions are often based on these reads and patient selection for clinical trials is increasingly guided by amyloid status. However, tracer deposition in the grey matter as a function of amyloid load is an inherently continuous process, which is not sufficiently appreciated through binary cut-offs alone. State-of-the-art methods for amyloid PET quantification can generate tracer-independent measures of Aβ burden. Recent research has shown the ability of these quantitative measures to highlight pathological changes at the earliest stages of the AD continuum and generate more sensitive thresholds, as well as improving diagnostic confidence around established binary cut-offs. With the recent FDA approval of aducanumab and more candidate drugs on the horizon, early identification of amyloid burden using quantitative measures is critical for enrolling appropriate subjects to help establish the optimal window for therapeutic intervention and secondary prevention. In addition, quantitative amyloid measurements are used for treatment response monitoring in clinical trials. In clinical settings, large multi-centre studies have shown that amyloid PET results change both diagnosis and patient management and that quantification can accurately predict rates of cognitive decline. Whether these changes in management reflect an improvement in clinical outcomes is yet to be determined and further validation work is required to establish the utility of quantification for supporting treatment endpoint decisions. In this state-of-the-art review, several tools and measures available for amyloid PET quantification are summarised and discussed. Use of these methods is growing both clinically and in the research domain. Concurrently, there is a duty of care to the wider dementia community to increase visibility and understanding of these methods.
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Affiliation(s)
- Hugh G Pemberton
- GE Healthcare, Amersham, UK.
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK.
- UCL Queen Square Institute of Neurology, University College London, London, UK.
| | - Lyduine E Collij
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Fiona Heeman
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Ariane Bollack
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Isadora Lopes Alves
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Brain Research Center, Amsterdam, The Netherlands
| | - David Vallez Garcia
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Mark Battle
- GE Healthcare, Amersham, UK
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | | | | | | | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular Imaging, University Hospitals of Geneva, Geneva, Switzerland
- NIMTLab, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Frederik Barkhof
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, UK
- UCL Queen Square Institute of Neurology, University College London, London, UK
- Department of Radiology and Nuclear Medicine, Amsterdam Neurocience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, Madrid, Spain
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12
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Shaaban CE, Fan E, Klatt BN, Cohen AD, Snitz BE, Yu Z, Lopresti BJ, Villemagne VL, Klunk WE, Aizenstein HJ, Rosso AL. Brain health correlates of mobility-related confidence. Exp Gerontol 2022; 163:111776. [PMID: 35339632 PMCID: PMC9109136 DOI: 10.1016/j.exger.2022.111776] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Revised: 12/22/2021] [Accepted: 03/21/2022] [Indexed: 11/28/2022]
Abstract
BACKGROUND Mobility is important for independence in older age. While brain health correlates of objectively measured mobility-related features like gait and balance have been reported, we aimed to test neuroimaging and cognitive correlates of subjective measures of mobility-related confidence. METHODS We carried out a cross-sectional observational study comprised of N = 29 cognitively unimpaired older adult participants, mean age 75.8 ± 5.8, 52% female, 24% non-white. We measured cognition, hippocampal volume, white matter hyperintensities, cerebral amyloid-β (Aβ), and gait and balance confidence. We tested associations using unadjusted Spearman correlations and correlations partialling out covariates of interest one at a time. RESULTS Greater gait confidence was associated with better attention (unadjusted ρ = 0.37, p = 0.05; partially attenuated by adjustment for age, APOE4, anxiety, motivation, gait speed, or Aβ); executive performance (unadjusted ρ = 0.35, p = 0.06; partially attenuated by adjustment for age, APOE4, gait speed, or Aβ); and lower Aβ levels (unadjusted ρ = -0.40, p = 0.04; partially attenuated by adjustment for age, depressive symptoms, motivation, or gait speed). Greater balance confidence was associated with better global cognition (unadjusted ρ = 0.41, p = 0.03; partially attenuated by adjustment for APOE4, gait speed, or Aβ); attention (unadjusted ρ = 0.46, p = 0.01; robust to adjustment); and lower Aβ levels (unadjusted ρ = -0.35, p = 0.07; partially attenuated by adjustment for age, education, APOE4, depressive symptoms, anxiety, motivation, or gait speed). CONCLUSIONS Self-reported mobility-related confidence is associated with neuroimaging and cognitive measures and would be easy for providers to use in clinical evaluations. These associations should be further evaluated in larger samples, and longitudinal studies can help determine temporality of declines.
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Affiliation(s)
| | - Erica Fan
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Brooke N Klatt
- Department of Physical Therapy, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ann D Cohen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beth E Snitz
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Zheming Yu
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Brian J Lopresti
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - William E Klunk
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Andrea L Rosso
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA
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13
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Cohen AD, Bruña R, Chang YF, Cheng Y, Doman J, Huppert T, Kim T, Maestu F, Roush RE, Snitz BE, Becker JT. Connectomics in Brain Aging and Dementia - The Background and Design of a Study of a Connectome Related to Human Disease. Front Aging Neurosci 2021; 13:669490. [PMID: 34690734 PMCID: PMC8530182 DOI: 10.3389/fnagi.2021.669490] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 09/06/2021] [Indexed: 11/20/2022] Open
Abstract
The natural history of Alzheimer’s Disease (AD) includes significant alterations in the human connectome, and this disconnection results in the dementia of AD. The organizing principle of our research project is the idea that the expression of cognitive dysfunction in the elderly is the result of two independent processes — the neuropathology associated with AD, and second the neuropathological changes of cerebrovascular disease. Synaptic loss, senile plaques, and neurofibrillary tangles are the functional and diagnostic hallmarks of AD, but it is the structural changes as a consequence of vascular disease that reduce brain reserve and compensation, resulting in an earlier expression of the clinical dementia syndrome. This work is being completed under the auspices of the Human Connectome Project (HCP). We have achieved an equal representation of Black individuals (vs. White individuals) and enrolled 60% Women. Each of the participants contributes demographic, behavioral and laboratory data. We acquire data relative to vascular risk, and the participants also undergo in vivo amyloid imaging, and magnetoencephalography (MEG). All of the data are publicly available under the HCP guidelines using the Connectome Coordinating Facility and the NIMH Data Archive. Locally, we use these data to address specific questions related to structure, function, AD, aging and vascular disease in multi-modality studies leveraging the differential advantages of magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), MEG, and in vivo beta amyloid imaging.
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Affiliation(s)
- Ann D Cohen
- Department of Psychiatry, The University of Pittsburgh, Pittsburgh, PA, United States
| | - Ricardo Bruña
- Department of Experimental Psychology, Universidad Complutense de Madrid, Pozuelo de Alarcón, Madrid, Spain
| | - Yue-Fang Chang
- Department of Neurosurgery, The University of Pittsburgh, Pittsburgh, PA, United States
| | - Yu Cheng
- Department of Statistics, The University of Pittsburgh, Pittsburgh, PA, United States.,Department of Biostatistics, The University of Pittsburgh, Pittsburgh, PA, United States
| | - Jack Doman
- Department of Psychiatry, The University of Pittsburgh, Pittsburgh, PA, United States
| | - Ted Huppert
- Department of Electrical Engineering, The University of Pittsburgh, Pittsburgh, PA, United States
| | - Tae Kim
- Department of Radiology, The University of Pittsburgh, Pittsburgh, PA, United States
| | - Fernando Maestu
- Department of Experimental Psychology, Universidad Complutense de Madrid, Pozuelo de Alarcón, Madrid, Spain
| | - Rebecca E Roush
- Department of Neurology, The University of Pittsburgh, Pittsburgh, PA, United States
| | - Beth E Snitz
- Department of Neurology, The University of Pittsburgh, Pittsburgh, PA, United States
| | - James T Becker
- Department of Psychiatry, The University of Pittsburgh, Pittsburgh, PA, United States.,Department of Neurology, The University of Pittsburgh, Pittsburgh, PA, United States.,Department of Psychology, The University of Pittsburgh, Pittsburgh, PA, United States
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14
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Cui C, Higashiyama A, Lopresti BJ, Ihara M, Aizenstein HJ, Watanabe M, Chang Y, Kakuta C, Yu Z, Mathis CA, Kokubo Y, Fukuda T, Villemagne VL, Klunk WE, Lopez OL, Kuller LH, Miyamoto Y, Sekikawa A. Comparing Pathological Risk Factors for Dementia between Cognitively Normal Japanese and Americans. Brain Sci 2021; 11:1180. [PMID: 34573201 PMCID: PMC8469296 DOI: 10.3390/brainsci11091180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 08/28/2021] [Accepted: 08/30/2021] [Indexed: 11/16/2022] Open
Abstract
The Alzheimer's Disease Neuroimaging Initiative showed that Japanese had significantly lower brain Aβ burden than Americans among a cognitively normal population. This cross-sectional study aimed to compare vascular disease burden, Aβ burden, and neurodegeneration between cognitively normal elderly Japanese and Americans. Japanese and American participants were matched for age (±4-year-old), sex, and Apolipoprotein E (APOE) genotype. Brain vascular disease burden and brain Aβ burden were measured using white matter lesions (WMLs) and 11C-labeled Pittsburgh Compound B (PiB) retention, respectively. Neurodegeneration was measured using hippocampal volumes and cortical thickness. A total of 95 Japanese and 95 Americans were recruited (50.5% men, mean age = 82). Compared to Americans, Japanese participants had larger WMLs, and a similar global Aβ standardized uptake value ratio (SUVR), cortical thickness and hippocampal volumes. Japanese had significantly lower regional Aβ SUVR in the anterior ventral striatum, posterior cingulate cortex, and precuneus. Cognitively normal elderly Japanese and Americans had different profiles regarding vascular disease and Aβ burden. This suggests that multiple risk factors are likely to be involved in the development of dementia. Additionally, Japanese might have a lower risk of dementia due to lower Aβ burden than Americans. Longitudinal follow-up of these cohorts is warranted to ascertain the predictive accuracy of these findings.
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Affiliation(s)
- Chendi Cui
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA; (C.C.); (L.H.K.)
| | - Aya Higashiyama
- Department of Preventive Cardiology, National Cerebral and Cardiovascular Center, Suita 564-8565, Japan; (A.H.); (M.W.); (Y.K.); (Y.M.)
- Department of Hygiene, Wakayama Medical University, Wakayama 641-0011, Japan
| | - Brian J. Lopresti
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, USA; (B.J.L.); (Z.Y.); (C.A.M.)
| | - Masafumi Ihara
- Department of Neurology, National Cerebral and Cardiovascular Center, Suita 564-8565, Japan; (M.I.); (C.K.)
| | - Howard J. Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, USA; (H.J.A.); (V.L.V.); (W.E.K.)
| | - Makoto Watanabe
- Department of Preventive Cardiology, National Cerebral and Cardiovascular Center, Suita 564-8565, Japan; (A.H.); (M.W.); (Y.K.); (Y.M.)
| | - Yuefang Chang
- Department of Neurological Surgery, University of Pittsburgh, Pittsburgh, PA 15213, USA;
| | - Chikage Kakuta
- Department of Neurology, National Cerebral and Cardiovascular Center, Suita 564-8565, Japan; (M.I.); (C.K.)
| | - Zheming Yu
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, USA; (B.J.L.); (Z.Y.); (C.A.M.)
| | - Chester A. Mathis
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA 15213, USA; (B.J.L.); (Z.Y.); (C.A.M.)
| | - Yoshihiro Kokubo
- Department of Preventive Cardiology, National Cerebral and Cardiovascular Center, Suita 564-8565, Japan; (A.H.); (M.W.); (Y.K.); (Y.M.)
| | - Tetsuya Fukuda
- Department of Radiology, National Cerebral and Cardiovascular Center, Suita 564-8565, Japan;
| | - Victor L. Villemagne
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, USA; (H.J.A.); (V.L.V.); (W.E.K.)
| | - William E. Klunk
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, USA; (H.J.A.); (V.L.V.); (W.E.K.)
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA 15213, USA;
| | - Oscar L. Lopez
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA 15213, USA;
| | - Lewis H. Kuller
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA; (C.C.); (L.H.K.)
| | - Yoshihiro Miyamoto
- Department of Preventive Cardiology, National Cerebral and Cardiovascular Center, Suita 564-8565, Japan; (A.H.); (M.W.); (Y.K.); (Y.M.)
- Open Innovation Center, National Cerebral and Cardiovascular Center, Suita 564-8565, Japan
| | - Akira Sekikawa
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA; (C.C.); (L.H.K.)
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15
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Laymon CM, Minhas DS, Royse SK, Aizenstein HJ, Cohen AD, Tudorascu DL, Klunk WE. Characterization of point-spread function specification error on Geometric Transfer Matrix partial volume correction in [ 11C]PiB amyloid imaging. EJNMMI Phys 2021; 8:54. [PMID: 34283320 PMCID: PMC8292473 DOI: 10.1186/s40658-021-00403-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 07/05/2021] [Indexed: 11/29/2022] Open
Abstract
Purpose Partial-volume correction (PVC) using the Geometric Transfer Matrix (GTM) method is used in positron emission tomography (PET) to compensate for the effects of spatial resolution on quantitation. We evaluate the effect of misspecification of scanner point-spread function (PSF) on GTM results in amyloid imaging, including the effect on amyloid status classification (positive or negative). Methods Twenty-nine subjects with Pittsburgh Compound B ([11C]PiB) PET and structural T1 MR imaging were analyzed. FreeSurfer 5.3 (FS) was used to parcellate MR images into regions-of-interest (ROIs) that were used to extract radioactivity concentration values from the PET images. GTM PVC was performed using our “standard” PSF parameterization [3D Gaussian, full-width at half-maximum (w) of approximately 5 mm]. Additional GTM PVC was performed with “incorrect” parameterizations, taken around the correct value. The result is a set of regional activity values for each of the GTM applications. For each case, activity values from various ROIs were combined and normalized to produce standardized uptake value ratios (SUVRs) for nine standard [11C]PiB quantitation ROIs and a global region. GTM operating-point characteristics were determined from the slope of apparent SUVR versus w curves. Results Errors in specification of w on the order of 1 mm (3D) mainly produce only modest errors of up to a few percent. An exception was the anterior ventral striatum in which fractional errors of up to 0.29 per millimeter (3D) of error in w were observed. Conclusion While this study does not address all the issues regarding the quantitative strengths and weakness of GTM PVC, we find that with reasonable caution, the unavoidable inaccuracies associated with PSF specification do not preclude its use in amyloid quantitation. Supplementary Information The online version contains supplementary material available at 10.1186/s40658-021-00403-5.
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Affiliation(s)
- Charles M Laymon
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA. .,Department of Bioengineering, University of Pittsburgh, PET Center, PUH B930, 200 Lothrop St, Pittsburgh, PA, 15213, USA.
| | - Davneet S Minhas
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Sarah K Royse
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Howard J Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.,Department of Bioengineering, University of Pittsburgh, PET Center, PUH B930, 200 Lothrop St, Pittsburgh, PA, 15213, USA
| | - Ann D Cohen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Dana L Tudorascu
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - William E Klunk
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
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16
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Oberlin LE, Erickson KI, Mackey R, Klunk WE, Aizenstein H, Lopresti BJ, Kuller LH, Lopez OL, Snitz BE. Peripheral inflammatory biomarkers predict the deposition and progression of amyloid-β in cognitively unimpaired older adults. Brain Behav Immun 2021; 95:178-189. [PMID: 33737171 PMCID: PMC8647033 DOI: 10.1016/j.bbi.2021.03.015] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 02/23/2021] [Accepted: 03/10/2021] [Indexed: 12/28/2022] Open
Abstract
INTRODUCTION Systemic inflammation has been increasingly implicated in the pathogenesis of Alzheimer's disease (AD), yet the mechanistic and temporal specificity of this relationship is poorly understood. We aimed to characterize the cross-sectional and longitudinal associations between peripheral inflammatory biomarkers, cognition, and Aβ deposition in oldest-old cognitively unimpaired (CU) adults. METHODS A large sample of 139 CU older adults (mean age (range) = 85.4 (82-95)) underwent neuropsychological testing, Pittsburgh compound-B (PiB)-PET imaging and structural MRI. Hierarchical regression models examined associations between circulating inflammatory biomarkers (Interleukin-6 (IL-6), soluble Tumor Necrosis Factor receptors 1 and 2 (sTNFr1 and sTNFr2), soluble cluster of differentiation 14 (sCD14), C-reactive protein (CRP)), cognition, and global and regional Aβ deposition at baseline and over follow-up. Indices of preclinical disease, including pathologic Aβ status and hippocampal volume, were incorporated to assess conditional associations. RESULTS At baseline evaluation, higher concentrations of IL-6 and sTNFr2 were associated with greater global Aβ burden in those with lower hippocampal volume. In longitudinal models, IL-6 predicted subsequent conversion to MCI and both IL-6 and CRP predicted greater change in global and regional Aβ deposition specifically among participants PiB-positive at baseline. These relationships withstood adjustment for demographic factors, anti-hypertensive medication use, history of diabetes, heart disease, APOE ε4 carrier status, and white matter lesions. DISCUSSION In a large prospective sample of CU adults aged 80 and over, peripheral inflammatory biomarkers were associated with and predictive of the progression of Aβ deposition. This was specific to those with biomarker evidence of preclinical AD at baseline, supporting recent evidence of disease-state-dependent differences in inflammatory expression profiles. Chronic, low-level systemic inflammation may exacerbate the deposition of Aβ pathology among those with emerging disease processes, and place individuals at a higher risk of developing clinically significant cognitive impairment.
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Affiliation(s)
| | - Kirk I. Erickson
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA,Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA,College of Science, Health, Engineering and Education, Murdoch University, Perth, Australia
| | - Rachel Mackey
- Premier Applied Sciences, Premier Inc., Charlotte, North Carolina,Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA
| | - William E. Klunk
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA
| | | | | | - Lewis H. Kuller
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA
| | - Oscar L. Lopez
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA,Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA
| | - Beth E. Snitz
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA
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17
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Mizuno A, Karim HT, Ly MJ, Cohen AD, Lopresti BJ, Mathis CA, Klunk WE, Aizenstein HJ, Snitz BE. An Effect of Education on Memory-Encoding Activation in Subjective Cognitive Decline. J Alzheimers Dis 2021; 81:1065-1078. [PMID: 33843669 DOI: 10.3233/jad-201087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Subjective cognitive decline (SCD) may be an early manifestation of pre-clinical Alzheimer's disease. Elevated amyloid-β (Aβ) is a correlate of SCD symptoms in some individuals. The underlying neural correlates of SCD symptoms and their association with Aβ is unknown. SCD is a heterogeneous condition, and cognitive reserve may explain individual differences in its neural correlates. OBJECTIVE We investigated the association between brain activation during memory encoding and SCD symptoms, as well as with Aβ, among older individuals. We also tested the moderating role of education (an index of cognitive reserve) on the associations. METHODS We measured brain activation during the "face-name" memory-encoding fMRI task and Aβ deposition with Pittsburgh Compound-B (PiB)-PET among cognitively normal older individuals (n = 63, mean age 73.1 ± 7.4 years). We tested associations between activation and SCD symptoms by self-report measures, Aβ, and interactions with education. RESULTS Activation was not directly associated with SCD symptoms or Aβ. However, education moderated the association between activation and SCD symptoms in the executive control network, salience network, and subcortical regions. Greater SCD symptoms were associated with greater activation in those with higher education, but with lower activation in those with lower education. CONCLUSION SCD symptoms were associated with different patterns of brain activation in the extended memory system depending on level of cognitive reserve. Greater SCD symptoms may represent a saturation of neural compensation in individuals with greater cognitive reserve, while it may reflect diminishing neural resources in individuals with lower cognitive reserve.
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Affiliation(s)
- Akiko Mizuno
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Helmet T Karim
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Maria J Ly
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.,Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ann D Cohen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Brian J Lopresti
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Chester A Mathis
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - William E Klunk
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Howard J Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.,Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beth E Snitz
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
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18
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Flanigan MR, Royse SK, Cenkner DP, Kozinski KM, Stoughton CJ, Himes ML, Minhas DS, Lopresti B, Butters MA, Narendran R. Imaging beta-amyloid (Aβ) burden in the brains of middle-aged individuals with alcohol-use disorders: a [ 11C]PIB PET study. Transl Psychiatry 2021; 11:257. [PMID: 33934110 PMCID: PMC8088438 DOI: 10.1038/s41398-021-01374-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 03/13/2021] [Accepted: 04/07/2021] [Indexed: 02/03/2023] Open
Abstract
No in vivo human studies have examined the prevalence of Alzheimer's disease (AD) neuropathology in individuals with alcohol-use disorder (AUD), although recent research suggests that a relationship between the two exists. Therefore, this study used Pittsburgh Compound-B ([11C]PiB) PET imaging to test the hypothesis that AUD is associated with greater brain amyloid (Aβ) burden in middle-aged adults compared to healthy controls. Twenty healthy participants (14M and 6F) and 19 individuals with AUD (15M and 4F), all aged 40-65 years, underwent clinical assessment, MRI, neurocognitive testing, and positron emission tomography (PET) imaging. Global [11C]PiB standard uptake value ratios (SUVRs), cortical thickness, gray matter volumes (GMVs), and neurocognitive function in subjects with AUD were compared to healthy controls. These measures were selected because they are considered markers of risk for future AD and other types of neurocognitive dysfunction. The results of this study showed no significant differences in % global Aβ positivity or subthreshold Aβ loads between AUD and controls. However, relative to controls, we observed a significant 6.1% lower cortical thickness in both AD-signature regions and in regions not typically associated with AD, lower GMV in the hippocampus, and lower performance on tests of attention as well as immediate and delayed memory in individuals with AUD. This suggest that Aβ accumulation is not greater in middle-aged individuals with AUD. However, other markers of neurodegeneration, such as impaired memory, cortical thinning, and reduced hippocampal GMV, are present. Further studies are needed to elucidate the patterns and temporal staging of AUD-related pathophysiology and cognitive impairment. Imaging β-amyloid in middle age alcoholics as a mechanism that increases their risk for Alzheimer's disease; Registration Number: NCT03746366 .
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Affiliation(s)
- Margaret R. Flanigan
- grid.21925.3d0000 0004 1936 9000Department of Radiology, University of Pittsburgh, Pittsburgh, PA USA
| | - Sarah K. Royse
- grid.21925.3d0000 0004 1936 9000Department of Radiology, University of Pittsburgh, Pittsburgh, PA USA
| | - David P. Cenkner
- grid.21925.3d0000 0004 1936 9000Department of Radiology, University of Pittsburgh, Pittsburgh, PA USA
| | - Katelyn M. Kozinski
- grid.21925.3d0000 0004 1936 9000Department of Radiology, University of Pittsburgh, Pittsburgh, PA USA
| | - Clara J. Stoughton
- grid.21925.3d0000 0004 1936 9000Department of Radiology, University of Pittsburgh, Pittsburgh, PA USA
| | - Michael L. Himes
- grid.21925.3d0000 0004 1936 9000Department of Radiology, University of Pittsburgh, Pittsburgh, PA USA
| | - Davneet S. Minhas
- grid.21925.3d0000 0004 1936 9000Department of Radiology, University of Pittsburgh, Pittsburgh, PA USA
| | - Brian Lopresti
- grid.21925.3d0000 0004 1936 9000Department of Radiology, University of Pittsburgh, Pittsburgh, PA USA
| | - Meryl A. Butters
- grid.21925.3d0000 0004 1936 9000Department Psychiatry, University of Pittsburgh, Pittsburgh, PA USA
| | - Rajesh Narendran
- grid.21925.3d0000 0004 1936 9000Department of Radiology, University of Pittsburgh, Pittsburgh, PA USA ,grid.21925.3d0000 0004 1936 9000Department Psychiatry, University of Pittsburgh, Pittsburgh, PA USA
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19
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Gonzalez-Escamilla G, Miederer I, Grothe MJ, Schreckenberger M, Muthuraman M, Groppa S. Metabolic and amyloid PET network reorganization in Alzheimer's disease: differential patterns and partial volume effects. Brain Imaging Behav 2021; 15:190-204. [PMID: 32125613 PMCID: PMC7835313 DOI: 10.1007/s11682-019-00247-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Alzheimer’s disease (AD) is a neurodegenerative disorder, considered a disconnection syndrome with regional molecular pattern abnormalities quantifiable by the aid of PET imaging. Solutions for accurate quantification of network dysfunction are scarce. We evaluate the extent to which PET molecular markers reflect quantifiable network metrics derived through the graph theory framework and how partial volume effects (PVE)-correction (PVEc) affects these PET-derived metrics 75 AD patients and 126 cognitively normal older subjects (CN). Therefore our goal is twofold: 1) to evaluate the differential patterns of [18F]FDG- and [18F]AV45-PET data to depict AD pathology; and ii) to analyse the effects of PVEc on global uptake measures of [18F]FDG- and [18F]AV45-PET data and their derived covariance network reconstructions for differentiating between patients and normal older subjects. Network organization patterns were assessed using graph theory in terms of “degree”, “modularity”, and “efficiency”. PVEc evidenced effects on global uptake measures that are specific to either [18F]FDG- or [18F]AV45-PET, leading to increased statistical differences between the groups. PVEc was further shown to influence the topological characterization of PET-derived covariance brain networks, leading to an optimised characterization of network efficiency and modularisation. Partial-volume effects correction improves the interpretability of PET data in AD and leads to optimised characterization of network properties for organisation or disconnection.
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Affiliation(s)
- Gabriel Gonzalez-Escamilla
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstr. 1, 55131, Mainz, Germany.
| | - Isabelle Miederer
- Department of Nuclear Medicine, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Michel J Grothe
- German Center for Neurodegenerative Diseases (DZNE) - Rostock/Greifswald, Rostock, Germany
| | - Mathias Schreckenberger
- Department of Nuclear Medicine, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Muthuraman Muthuraman
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstr. 1, 55131, Mainz, Germany
| | - Sergiu Groppa
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Langenbeckstr. 1, 55131, Mainz, Germany
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20
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Yan Q, Nho K, Del-Aguila JL, Wang X, Risacher SL, Fan KH, Snitz BE, Aizenstein HJ, Mathis CA, Lopez OL, Demirci FY, Feingold E, Klunk WE, Saykin AJ, Cruchaga C, Kamboh MI. Genome-wide association study of brain amyloid deposition as measured by Pittsburgh Compound-B (PiB)-PET imaging. Mol Psychiatry 2021; 26:309-321. [PMID: 30361487 PMCID: PMC6219464 DOI: 10.1038/s41380-018-0246-7] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Accepted: 07/31/2018] [Indexed: 12/25/2022]
Abstract
Deposition of amyloid plaques in the brain is one of the two main pathological hallmarks of Alzheimer's disease (AD). Amyloid positron emission tomography (PET) is a neuroimaging tool that selectively detects in vivo amyloid deposition in the brain and is a reliable endophenotype for AD that complements cerebrospinal fluid biomarkers with regional information. We measured in vivo amyloid deposition in the brains of ~1000 subjects from three collaborative AD centers and ADNI using 11C-labeled Pittsburgh Compound-B (PiB)-PET imaging followed by meta-analysis of genome-wide association studies, first to our knowledge for PiB-PET, to identify novel genetic loci for this endophenotype. The APOE region showed the most significant association where several SNPs surpassed the genome-wide significant threshold, with APOE*4 being most significant (P-meta = 9.09E-30; β = 0.18). Interestingly, after conditioning on APOE*4, 14 SNPs remained significant at P < 0.05 in the APOE region that were not in linkage disequilibrium with APOE*4. Outside the APOE region, the meta-analysis revealed 15 non-APOE loci with P < 1E-05 on nine chromosomes, with two most significant SNPs on chromosomes 8 (P-meta = 4.87E-07) and 3 (P-meta = 9.69E-07). Functional analyses of these SNPs indicate their potential relevance with AD pathogenesis. Top 15 non-APOE SNPs along with APOE*4 explained 25-35% of the amyloid variance in different datasets, of which 14-17% was explained by APOE*4 alone. In conclusion, we have identified novel signals in APOE and non-APOE regions that affect amyloid deposition in the brain. Our data also highlights the presence of yet to be discovered variants that may be responsible for the unexplained genetic variance of amyloid deposition.
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Affiliation(s)
- Qi Yan
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Pediatrics, Children's Hospital of Pittsburgh of UPMC, University of Pittsburgh, Pittsburgh, PA, USA
| | - Kwangsik Nho
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Jorge L Del-Aguila
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Xingbin Wang
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Shannon L Risacher
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kang-Hsien Fan
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beth E Snitz
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
- Alzheimer Disease Research Center, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Chester A Mathis
- Alzheimer Disease Research Center, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Oscar L Lopez
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
- Alzheimer Disease Research Center, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - F Yesim Demirci
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Eleanor Feingold
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - William E Klunk
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
- Alzheimer Disease Research Center, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - M Ilyas Kamboh
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA.
- Alzheimer Disease Research Center, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
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21
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Farrell ME, Jiang S, Schultz AP, Properzi MJ, Price JC, Becker JA, Jacobs HIL, Hanseeuw BJ, Rentz DM, Villemagne VL, Papp KV, Mormino EC, Betensky RA, Johnson KA, Sperling RA, Buckley RF. Defining the Lowest Threshold for Amyloid-PET to Predict Future Cognitive Decline and Amyloid Accumulation. Neurology 2020; 96:e619-e631. [PMID: 33199430 DOI: 10.1212/wnl.0000000000011214] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Accepted: 09/21/2020] [Indexed: 12/22/2022] Open
Abstract
INTRODUCTION As clinical trials move toward earlier intervention, we sought to redefine the β-amyloid (Aβ)-PET threshold based on the lowest point in a baseline distribution that robustly predicts future Aβ accumulation and cognitive decline in 3 independent samples of clinically normal individuals. METHODS Sequential Aβ cutoffs were tested to identify the lowest cutoff associated with future change in cognition (Preclinical Alzheimer Cognitive Composite [PACC]) and Aβ-PET in clinically normal participants from the Harvard Aging Brain Study (n = 342), Australian Imaging, Biomarker and Lifestyle study of aging (n = 157), and Alzheimer's Disease Neuroimaging Initiative (n = 356). RESULTS Within samples, cutoffs derived from future Aβ-PET accumulation and PACC decline converged on the same inflection point, beyond which trajectories diverged from normal. Across samples, optimal cutoffs fell within a short range (Centiloid 15-18.5). DISCUSSION These optimized thresholds can help to inform future research and clinical trials targeting early Aβ. Threshold convergence raises the possibility of contemporaneous early changes in Aβ and cognition. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that among clinically normal individuals a specific Aβ-PET threshold is predictive of cognitive decline.
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Affiliation(s)
- Michelle E Farrell
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Shu Jiang
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Aaron P Schultz
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Michael J Properzi
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Julie C Price
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - J Alex Becker
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Heidi I L Jacobs
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Bernard J Hanseeuw
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Dorene M Rentz
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Victor L Villemagne
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Kathryn V Papp
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Elizabeth C Mormino
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Rebecca A Betensky
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Keith A Johnson
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Reisa A Sperling
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia
| | - Rachel F Buckley
- From the Departments of Neurology (M.E.F., S.J., A.P.S., M.J.P., D.M.R., K.V.P., R.A.B., K.A.J., R.A.S., R.F.B.) and Radiology (J.C.P., J.A.B., H.I.L.J., B.J.H., K.A.J.), Massachusetts General Hospital, Harvard Medical School; Department of Biostatistics (S.J., R.A.B.), Harvard T.H. Chan School of Public Health, Boston, MA; Division of Public Health Sciences (S.J.), Department of Surgery, Washington University School of Medicine in St. Louis, MO; Faculty of Health (H.I.L.J.), Medicine and Life Sciences, School for Mental Health and Neuroscience, Alzheimer Centre Limburg, Maastricht University, the Netherlands; Cliniques Universitaires Saint-Luc (B.J.H.), Université Catholique de Louvain, Brussels, Belgium; Center for Alzheimer Research and Treatment (D.M.R., K.V.P., R.A.S., R.F.B.), Brigham and Women's Hospital, Boston, MA; Department of Molecular Imaging & Therapy (V.L.V.), Austin Health, Melbourne, Australia; Department of Neuroscience (E.C.M.), Stanford University, Palo Alto, CA; Department of Biostatistics (R.A.B.), New York University School of Global Public Health, NY; Center for Alzheimer Research and Treatment, Brigham and Women's Hospital, Boston, MA; and Melbourne School of Psychological Sciences (R.F.B.), University of Melbourne, Australia.
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22
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Tudorascu DL, Laymon CM, Zammit M, Minhas DS, Anderson SJ, Ellison PA, Zaman S, Ances BM, Sabbagh M, Johnson SC, Mathis CA, Klunk WE, Handen BL, Christian BT, Cohen AD. Relationship of amyloid beta and neurofibrillary tau deposition in Neurodegeneration in Aging Down Syndrome (NiAD) study at baseline. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2020; 6:e12096. [PMID: 33163613 PMCID: PMC7602678 DOI: 10.1002/trc2.12096] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Accepted: 09/11/2020] [Indexed: 11/07/2022]
Abstract
IMPORTANCE Adults with Down syndrome (DS) are at high-risk of revealing Alzheimer's disease (AD) pathology, in part due to the triplication of chromosome 21 encoding the amyloid precursor protein. Adults with DS are uniformly affected by AD pathology by their 30's and have a 70% to 80% chance of clinical dementia by their 60's. Our previous studies have assessed longitudinal changes in amyloid beta (Aβ) accumulation in DS. OBJECTIVE The goal of the present study was to assess the presence of brain tau using [18F]AV-1451 positron emission tomography (PET) in DS and to assess the relationship of brain tau pathology to Aβ using Pittsburgh Compound B (PiB)-PET. DESIGN Cohort study. SETTING Multi-center study. PARTICIPANTS Participants consisted of a sample of individuals with DS and sibling controls recruited from the community; exclusion criteria included contraindications for magnetic resonance imaging (MRI) and/or a medical or psychiatric condition that impaired cognitive functioning. EXPOSURES PET brain scans to assess Aβ ([11C]PiB) and tau ([18F]AV-1451) burden. MAIN OUTCOMES AND MEASURES Multiple linear regression models (adjusted for chronological age, sex and performance site) were used to examine associations between regional [18F]AV-1451 standard uptake value ratio (SUVR) (based on regions associated with Braak stages 1-6) and global [11C]PiB SUVR (as both a continuous and dichotomous variable). RESULTS A cohort of 156 participants (mean age = 39.05, SD(8.4)) were examined. These results revealed a significant relationship between in vivo Aβ and tau pathology in DS. As a dichotomous variable, [18F]AV-1451 retention was higher in each Braak region in PiB(+) participants. We also found, based on our statistical models, starting with the Braak 3 region of interest (ROI), an acceleration of [18F]AV-1451 SUVR deposition with [11C]PiB SUVR increases.
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Affiliation(s)
- DL Tudorascu
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - CM Laymon
- Department of RadiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - M Zammit
- Department of Medical PhysicsUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - DS Minhas
- Department of RadiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - SJ Anderson
- Department of BiostatisticsUniversity of PittsburghPittsburghUSA
| | - PA Ellison
- Department of Medical PhysicsUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - S Zaman
- Department of PsychiatryUniversity of CambridgeCambridgeUK
| | - BM Ances
- Department of NeurologyWashington UniversitySt. LouisMissouriUSA
| | - M Sabbagh
- Cleveland Clinic Lou Ruvo Center for Brain HealthLas VegasNVUSA
| | - SC Johnson
- Department of MedicineUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - CA Mathis
- Department of RadiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - WE Klunk
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - BL Handen
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - BT Christian
- Department of Medical PhysicsUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - AD Cohen
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
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23
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Lopresti BJ, Campbell EM, Yu Z, Anderson SJ, Cohen AD, Minhas DS, Snitz BE, Royse SK, Becker CR, Aizenstein HJ, Mathis CA, Lopez OL, Klunk WE, Tudorascu DL. Influence of apolipoprotein-E genotype on brain amyloid load and longitudinal trajectories. Neurobiol Aging 2020; 94:111-120. [PMID: 32603776 PMCID: PMC7483397 DOI: 10.1016/j.neurobiolaging.2020.05.012] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 05/21/2020] [Accepted: 05/23/2020] [Indexed: 12/23/2022]
Abstract
To characterize the influence of apolipoprotein-E (APOE) genotype on cerebral Aβ load and longitudinal Aβ trajectories, [11C]Pittsburgh compound-B (PiB) positron emission tomography (PET) imaging was used to assess amyloid load in a clinically heterogeneous cohort of 428 elderly participants with known APOE genotype. Serial [11C]PiB data and a repeated measures model were used to model amyloid trajectories in a subset of 235 participants classified on the basis of APOE genotype. We found that APOE-ε4 was associated with increased Aβ burden and an earlier age of onset of Aβ positivity, whereas APOE-ε2 appeared to have modest protective effects against Aβ. APOE class did not predict rates of Aβ accumulation. The present study suggests that APOE modifies Alzheimer's disease risk through a direct influence on amyloidogenic processes, which manifests as an earlier age of onset of Aβ positivity, although it is likely that other genetic, environmental, and lifestyle factors are important.
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Affiliation(s)
- Brian J Lopresti
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
| | - Elizabeth M Campbell
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Zheming Yu
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Stewart J Anderson
- Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ann D Cohen
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Davneet S Minhas
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Beth E Snitz
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Sarah K Royse
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Carl R Becker
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Howard J Aizenstein
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Chester A Mathis
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Oscar L Lopez
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - William E Klunk
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Dana L Tudorascu
- Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA; Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
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24
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Hartley SL, Handen BL, Devenny D, Tudorascu D, Piro-Gambetti B, Zammit MD, Laymon CM, Klunk WE, Zaman S, Cohen A, Christian BT. Cognitive indicators of transition to preclinical and prodromal stages of Alzheimer's disease in Down syndrome. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2020; 12:e12096. [PMID: 32995465 PMCID: PMC7507534 DOI: 10.1002/dad2.12096] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/19/2019] [Revised: 07/30/2020] [Accepted: 07/30/2020] [Indexed: 11/09/2022]
Abstract
INTRODUCTION There is a critical need to identify measures of cognitive functioning sensitive to early Alzheimer's disease (AD) pathophysiology in Down syndrome to advance clinical trial research in this at-risk population. The objective of the study was to longitudinally track performance on cognitive measures in relation to neocortical and striatal amyloid beta (Aβ) in non-demented Down syndrome. METHODS The study included 118 non-demented adults with Down syndrome who participated in two to five points of data collection, spanning 1.5 to 8 years. Episodic memory, visual attention and executive functioning, and motor planning and coordination were assessed. Aβ was measured via [C-11] Pittsburgh Compound-B (PiB) PET. RESULTS PiB was associated with level and rate of decline in cognitive performance in episodic memory, visual attention, executive functioning, and visuospatial ability in models controlling for chronological age. DISCUSSION The Cued Recall Test emerged as a promising indicator of transition from preclinical to prodromal AD.
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Affiliation(s)
- Sigan L Hartley
- Waisman Center University of Wisconsin-Madison Madison Wisconsin USA
- Department of Human Development & Family Studies University of Wisconsin-Madison Madison Wisconsin USA
| | - Benjamin L Handen
- Department of Psychiatry University of Pittsburgh Pittsburgh Pennsylvania USA
| | - Darlynne Devenny
- New York State Institute for Basic Research in Developmental Disabilities Albany New York USA
| | - Dana Tudorascu
- Department of Psychiatry University of Pittsburgh Pittsburgh Pennsylvania USA
| | - Brianna Piro-Gambetti
- Waisman Center University of Wisconsin-Madison Madison Wisconsin USA
- Department of Human Development & Family Studies University of Wisconsin-Madison Madison Wisconsin USA
| | - Matthew D Zammit
- Waisman Center University of Wisconsin-Madison Madison Wisconsin USA
- Department of Medical Physics University of Wisconsin-Madison Madison Wisconsin USA
| | - Charles M Laymon
- Department of Psychiatry University of Pittsburgh Pittsburgh Pennsylvania USA
| | - William E Klunk
- Department of Psychiatry University of Pittsburgh Pittsburgh Pennsylvania USA
| | - Shahid Zaman
- Department of Psychiatry University of Cambridge Cambridge UK
| | - Annie Cohen
- Department of Psychiatry University of Pittsburgh Pittsburgh Pennsylvania USA
| | - Bradley T Christian
- Waisman Center University of Wisconsin-Madison Madison Wisconsin USA
- Department of Medical Physics University of Wisconsin-Madison Madison Wisconsin USA
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25
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Association of sleep with cognition and beta amyloid accumulation in adults with Down syndrome. Neurobiol Aging 2020; 93:44-51. [PMID: 32447011 PMCID: PMC7380565 DOI: 10.1016/j.neurobiolaging.2020.04.018] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2019] [Revised: 04/17/2020] [Accepted: 04/19/2020] [Indexed: 12/19/2022]
Abstract
Adults with Down syndrome have an increased risk for both disordered sleep and Alzheimer's disease (AD). In the general population, disrupted sleep has been linked to beta amyloid accumulation, an early pathophysiologic feature of AD. In this study, the association among sleep, beta amyloid, and measures of AD-related cognitive decline was examined in 47 non-demented adults with Down syndrome (aged 26-56 years). Sleep was measured using actigraphy over 7 nights. Pittsburgh Compound B positron emission tomography was used to assess global and striatal beta amyloid burden. Participants had the following clinical AD status: 7 (15%) mild cognitive impairment and 40 (85%) cognitively unaffected. Average length of night-time awakenings was significantly positively associated with striatal beta amyloid and decreased cognitive performance in executive functioning and motor planning and coordination. Findings suggest that disrupted sleep is associated with beta amyloid accumulation and cognitive features of preclinical AD in Down syndrome. Early identification and treatment of sleep problems could be a lifestyle intervention that may delay beta amyloid accumulation and cognitive decline in this AD vulnerable group.
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Snitz BE, Chang Y, Tudorascu DL, Lopez OL, Lopresti BJ, DeKosky ST, Carlson MC, Cohen AD, Kamboh MI, Aizenstein HJ, Klunk WE, Kuller LH. Predicting resistance to amyloid-beta deposition and cognitive resilience in the oldest-old. Neurology 2020; 95:e984-e994. [PMID: 32699143 PMCID: PMC7668550 DOI: 10.1212/wnl.0000000000010239] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2019] [Accepted: 02/20/2020] [Indexed: 01/05/2023] Open
Abstract
OBJECTIVE To explore long-term predictors of avoiding β-amyloid (Aβ) deposition and maintaining unimpaired cognition as outcomes in the oldest old. METHODS In a longitudinal observational cohort study, 100 former participants of the Ginkgo Evaluation of Memory Study (GEMS; 2000-2008) completed biannual Pittsburgh compound B-PET imaging and annual clinical-cognitive evaluations beginning in 2010. Most recent Aβ status and cognitive status were selected for each participant. Longitudinal outcomes included change in serial Aβ and cognitive tests. Baseline predictors from GEMS included neuropsychological tests, daily functioning, APOE genotype, lifestyle variables, occupational measures, health history, sleep, subjective memory, physical and cognitive activities, depressive symptoms, and physical performance and health indices, among others. RESULTS Mean age at the last cognitive evaluation was 92.0 (range 86-100) years. Mean follow-up time from baseline to last measured Aβ status was 12.3 (SD 1.9) years and to last cognitive evaluation was 14.1 (SD 1.9) years. The APOE*2 allele predicted last Aβ status (n = 34 Aβ negative vs n = 66 Aβ positive). Baseline cognition predicted cognitive status (n = 30 unimpaired vs n = 70 impaired). Predictors of cognitive status among Aβ-positive participants only (n = 14 normal cognition vs n = 52 impaired) were baseline cognitive test scores and smoking history. Baseline pulse pressure predicted longitudinal Aβ increase; paid work engagement and life satisfaction predicted less cognitive decline. CONCLUSIONS The APOE*2 allele and lower pulse pressure predict resistance to Aβ deposition in advanced aging. Cognitive test scores 14 years prior, likely reflecting premorbid abilities, predict cognitive status and maintenance of unimpaired cognition in the presence of Aβ. Several lifestyle factors appear protective.
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Affiliation(s)
- Beth E Snitz
- From the Departments of Neurology (B.E.S., O.L.L., W.E.K.), Neurological Surgery (Y.C.), Medicine (D.L.T.), Radiology (B.J.L.), Psychiatry (A.D.C., H.J.A., W.E.K.), Human Genetics (M.I.K.), and Epidemiology (L.H.K.), University of Pittsburgh, PA; Department of Neurology (S.T.D.), University of Florida, Gainesville; and Department of Mental Health (M.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
| | - Yuefang Chang
- From the Departments of Neurology (B.E.S., O.L.L., W.E.K.), Neurological Surgery (Y.C.), Medicine (D.L.T.), Radiology (B.J.L.), Psychiatry (A.D.C., H.J.A., W.E.K.), Human Genetics (M.I.K.), and Epidemiology (L.H.K.), University of Pittsburgh, PA; Department of Neurology (S.T.D.), University of Florida, Gainesville; and Department of Mental Health (M.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Dana L Tudorascu
- From the Departments of Neurology (B.E.S., O.L.L., W.E.K.), Neurological Surgery (Y.C.), Medicine (D.L.T.), Radiology (B.J.L.), Psychiatry (A.D.C., H.J.A., W.E.K.), Human Genetics (M.I.K.), and Epidemiology (L.H.K.), University of Pittsburgh, PA; Department of Neurology (S.T.D.), University of Florida, Gainesville; and Department of Mental Health (M.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Oscar L Lopez
- From the Departments of Neurology (B.E.S., O.L.L., W.E.K.), Neurological Surgery (Y.C.), Medicine (D.L.T.), Radiology (B.J.L.), Psychiatry (A.D.C., H.J.A., W.E.K.), Human Genetics (M.I.K.), and Epidemiology (L.H.K.), University of Pittsburgh, PA; Department of Neurology (S.T.D.), University of Florida, Gainesville; and Department of Mental Health (M.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Brian J Lopresti
- From the Departments of Neurology (B.E.S., O.L.L., W.E.K.), Neurological Surgery (Y.C.), Medicine (D.L.T.), Radiology (B.J.L.), Psychiatry (A.D.C., H.J.A., W.E.K.), Human Genetics (M.I.K.), and Epidemiology (L.H.K.), University of Pittsburgh, PA; Department of Neurology (S.T.D.), University of Florida, Gainesville; and Department of Mental Health (M.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Steven T DeKosky
- From the Departments of Neurology (B.E.S., O.L.L., W.E.K.), Neurological Surgery (Y.C.), Medicine (D.L.T.), Radiology (B.J.L.), Psychiatry (A.D.C., H.J.A., W.E.K.), Human Genetics (M.I.K.), and Epidemiology (L.H.K.), University of Pittsburgh, PA; Department of Neurology (S.T.D.), University of Florida, Gainesville; and Department of Mental Health (M.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Michelle C Carlson
- From the Departments of Neurology (B.E.S., O.L.L., W.E.K.), Neurological Surgery (Y.C.), Medicine (D.L.T.), Radiology (B.J.L.), Psychiatry (A.D.C., H.J.A., W.E.K.), Human Genetics (M.I.K.), and Epidemiology (L.H.K.), University of Pittsburgh, PA; Department of Neurology (S.T.D.), University of Florida, Gainesville; and Department of Mental Health (M.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Ann D Cohen
- From the Departments of Neurology (B.E.S., O.L.L., W.E.K.), Neurological Surgery (Y.C.), Medicine (D.L.T.), Radiology (B.J.L.), Psychiatry (A.D.C., H.J.A., W.E.K.), Human Genetics (M.I.K.), and Epidemiology (L.H.K.), University of Pittsburgh, PA; Department of Neurology (S.T.D.), University of Florida, Gainesville; and Department of Mental Health (M.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - M Ilyas Kamboh
- From the Departments of Neurology (B.E.S., O.L.L., W.E.K.), Neurological Surgery (Y.C.), Medicine (D.L.T.), Radiology (B.J.L.), Psychiatry (A.D.C., H.J.A., W.E.K.), Human Genetics (M.I.K.), and Epidemiology (L.H.K.), University of Pittsburgh, PA; Department of Neurology (S.T.D.), University of Florida, Gainesville; and Department of Mental Health (M.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Howard J Aizenstein
- From the Departments of Neurology (B.E.S., O.L.L., W.E.K.), Neurological Surgery (Y.C.), Medicine (D.L.T.), Radiology (B.J.L.), Psychiatry (A.D.C., H.J.A., W.E.K.), Human Genetics (M.I.K.), and Epidemiology (L.H.K.), University of Pittsburgh, PA; Department of Neurology (S.T.D.), University of Florida, Gainesville; and Department of Mental Health (M.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - William E Klunk
- From the Departments of Neurology (B.E.S., O.L.L., W.E.K.), Neurological Surgery (Y.C.), Medicine (D.L.T.), Radiology (B.J.L.), Psychiatry (A.D.C., H.J.A., W.E.K.), Human Genetics (M.I.K.), and Epidemiology (L.H.K.), University of Pittsburgh, PA; Department of Neurology (S.T.D.), University of Florida, Gainesville; and Department of Mental Health (M.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Lewis H Kuller
- From the Departments of Neurology (B.E.S., O.L.L., W.E.K.), Neurological Surgery (Y.C.), Medicine (D.L.T.), Radiology (B.J.L.), Psychiatry (A.D.C., H.J.A., W.E.K.), Human Genetics (M.I.K.), and Epidemiology (L.H.K.), University of Pittsburgh, PA; Department of Neurology (S.T.D.), University of Florida, Gainesville; and Department of Mental Health (M.C.C.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
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Sullivan KJ, Liu A, Chang CCH, Cohen AD, Lopresti BJ, Minhas DS, Laymon CM, Klunk WE, Aizenstein H, Nadkarni NK, Loewenstein D, Kamboh MI, Ganguli M, Snitz BE. Alzheimer's disease pathology in a community-based sample of older adults without dementia: The MYHAT neuroimaging study. Brain Imaging Behav 2020; 15:1355-1363. [PMID: 32748322 DOI: 10.1007/s11682-020-00334-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 05/07/2020] [Accepted: 05/25/2020] [Indexed: 12/12/2022]
Abstract
A true understanding of the distribution and functional correlates of Alzheimer's disease pathology in dementia-free older adults requires a population-based perspective. Here we report initial findings from a sample of 102 cognitively unimpaired participants (average age 77.2 years, 54.9% women, 13.7% APOE*4 carriers) recruited for neuroimaging from a larger representative population-based cohort participating in an ongoing longitudinal study of aging, the Monongahela-Youghiogheny Healthy Aging Team (MYHAT). All participants scored < 1.0 on the Clinical Dementia Rating (CDR) Scale, with 8 participants (7.8%) scoring CDR = 0.5. Participants completed a positron emission tomography scan using the tracers [C-11]Pittsburgh Compound-B (PiB) and [F-18]AV-1451 to estimate amyloid and tau deposition. PiB positivity was defined on a regional basis using established standardized uptake value ratio cutoffs (SUVR; cerebellar gray matter reference), with 39 participants (38.2%) determined to be PiB(+). Health history, lifestyle, and cognitive abilities were assessed cross-sectionally at the nearest annual parent MYHAT study visit. A series of adjusted regression analyses modeled cognitive performance as a function of global PiB SUVR and [F-18]AV-1451 SUVR in Braak associated regions 1, 3/4, and 5/6. In comparison to PiB(-) participants (n = 63), PiB(+) participants were older, less educated, and were more likely to be APOE*4 carriers. Global PiB SUVR was significantly correlated with [F-18]AV-1451 SUVR in all Braak-associated regions (r = .38-0.53, p < .05). In independent models, higher Global PiB SUVR and Braak 1 [F-18]AV-1451 SUVR were associated with worse performance on a semantic interference verbal memory test. Our findings suggest that brain amyloid is common in a community-based setting, and is associated with tau deposition, but both pathologies show few associations with concurrent cognitive performance in a dementia-free sample.
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Affiliation(s)
- Kevin J Sullivan
- Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA.
| | - Anran Liu
- Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Ann D Cohen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Brian J Lopresti
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Davneet S Minhas
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Charles M Laymon
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - William E Klunk
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Howard Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Neelesh K Nadkarni
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - David Loewenstein
- Department of Psychiatry and Behavioral Science, University of Miami, FL, Coral Gables, USA
| | - M Ilyas Kamboh
- Department of Human Genetics, University of Pittsburgh, PA, Pittsburgh, USA
| | - Mary Ganguli
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beth E Snitz
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
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28
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Nadkarni NK, Tudorascu D, Campbell E, Snitz BE, Cohen AD, Halligan E, Mathis CA, Aizenstein HJ, Klunk WE. Association Between Amyloid-β, Small-vessel Disease, and Neurodegeneration Biomarker Positivity, and Progression to Mild Cognitive Impairment in Cognitively Normal Individuals. J Gerontol A Biol Sci Med Sci 2020; 74:1753-1760. [PMID: 30957843 DOI: 10.1093/gerona/glz088] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND We estimated the prevalence and incidence of amyloid-β deposition (A), small-vessel disease (V), and neurodegeneration (N) biomarker positivity in community-dwelling cognitively normal individuals (CN). We determined the longitudinal association between the respective biomarker indices with progression to all-cause mild cognitive impairment (MCI) and its amnestic and nonamnestic subtypes. METHODS CN participants, recruited by advertising, underwent brain [C-11]Pittsburgh Compound-B (PiB)-positron emission tomography (PET), magnetic resonance imaging, and [F-18]fluoro-2-deoxy-glucose (FDG)-PET, and were designated as having high or low amyloid-β (A+/A-), greater or lower white matter hyperintensities burden (V+/V-) and diminished or normal cortical glucose metabolism (N+/N-). MCI was adjudicated using clinical assessments. We examined the association between A, V, and N biomarker positivity at study baseline and endpoint, with progression to MCI using linear regression, Cox proportional hazards and Kaplan-Meier analyses adjusted for age and APOE-ε4 carrier status. RESULTS In 98 CN individuals (average age 74 years, 65% female), A+, V+, and N+ prevalence was 26%, 33%, and 8%, respectively. At study endpoint (median: 5.5 years), an A+, but not a V+ or N+ scan, was associated with higher odds of all-cause MCI (Chi-square = 3.9, p = .048, odds ratio, 95% confidence interval = 2.6 [1.01-6.8]). Baseline A+, V+, or N+ were not associated with all-cause MCI, however, baseline A+ (p = .018) and A+N+ (p = .049), and endpoint A+N+ (p = .025) were associated with time to progression to amnestic, not nonamnestic, MCI. CONCLUSION Longitudinal assessments clarify the association between amyloid-β and progression to all-cause MCI in CN individuals. The association between biomarker positivity indices of amyloid-β and neurodegeneration, and amnestic MCI reflects the underlying pathology involved in the progression to prodromal Alzheimer's disease.
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Affiliation(s)
- Neelesh K Nadkarni
- Division of Geriatric Medicine, Department of Medicine, University of Pittsburgh, Pennsylvania.,Department of Neurology, University of Pittsburgh, Pennsylvania
| | - Dana Tudorascu
- Division of General Internal Medicine, Department of Medicine, University of Pittsburgh, Pennsylvania.,Department of Biostatistics, University of Pittsburgh, Pennsylvania.,Department of Psychiatry, University of Pittsburgh, Pennsylvania
| | | | - Beth E Snitz
- Department of Neurology, University of Pittsburgh, Pennsylvania
| | - Annie D Cohen
- Department of Psychiatry, University of Pittsburgh, Pennsylvania
| | - Edye Halligan
- Department of Psychiatry, University of Pittsburgh, Pennsylvania
| | | | | | - William E Klunk
- Department of Neurology, University of Pittsburgh, Pennsylvania.,Department of Psychiatry, University of Pittsburgh, Pennsylvania
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29
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Snitz BE, Tudorascu DL, Yu Z, Campbell E, Lopresti BJ, Laymon CM, Minhas DS, Nadkarni NK, Aizenstein HJ, Klunk WE, Weintraub S, Gershon RC, Cohen AD. Associations between NIH Toolbox Cognition Battery and in vivo brain amyloid and tau pathology in non-demented older adults. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2020; 12:e12018. [PMID: 32426450 PMCID: PMC7228102 DOI: 10.1002/dad2.12018] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/19/2019] [Revised: 01/13/2020] [Accepted: 01/23/2020] [Indexed: 12/04/2022]
Abstract
INTRODUCTION The National Institutes of Health (NIH) Toolbox Cognition Battery (NIHTB-CB) was developed to be a common assessment metric across a broad array of research studies. We investigated associations between NIHTB-CB and brain amyloid and tau deposition in cognitively unimpaired older adults. METHODS One hundred eighteen community-based volunteers completed magnetic resonance imaging (MRI), Pittsburgh compound B (PiB)-PET (positron emission tomography) and AV-1451-PET neuroimaging, a neuropsychological evaluation, NIHTB-CB, and the Clinical Dementia Rating (CDR) scale. Demographically adjusted regression models evaluated cognition-biomarker associations; standardized effect sizes allowed comparison of association strength across measures. RESULTS No NIHTB-CB measures were associated with amyloid deposition. NIHTB-CB measures of fluid cognition, including Pattern Comparison Processing Speed, Dimensional Change Card Sort, and Fluid Cognition Composite, were associated with tau deposition in higher Braak regions. Pattern Comparison Processing Speed was the most robust association with sensitivity analyses. DISCUSSION NIHTB-CB tasks of processing speed and executive functions may be sensitive to pathologic tau deposition on imaging in normal aging.
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Affiliation(s)
- Beth E. Snitz
- Department of NeurologyUniversity of PittsburghSchool of MedicinePittsburghPennsylvania
| | - Dana L. Tudorascu
- Department of MedicineUniversity of Pittsburgh School of MedicinePittsburghPennsylvania
| | - Zheming Yu
- Department of RadiologyUniversity of Pittsburgh School of MedicinePittsburghPennsylvania
| | - Elizabeth Campbell
- Department of RadiologyUniversity of Pittsburgh School of MedicinePittsburghPennsylvania
| | - Brian J. Lopresti
- Department of RadiologyUniversity of Pittsburgh School of MedicinePittsburghPennsylvania
| | - Charles M. Laymon
- Department of RadiologyUniversity of Pittsburgh School of MedicinePittsburghPennsylvania
- Department of BioengineeringUniversity of Pittsburgh School of EngineeringPittsburghPennsylvania
| | - Davneet S. Minhas
- Department of RadiologyUniversity of Pittsburgh School of MedicinePittsburghPennsylvania
| | - Neelesh K. Nadkarni
- Department of MedicineUniversity of Pittsburgh School of MedicinePittsburghPennsylvania
| | - Howard J. Aizenstein
- Department of BioengineeringUniversity of Pittsburgh School of EngineeringPittsburghPennsylvania
- Department of PsychiatryUniversity of Pittsburgh School of MedicinePittsburghPennsylvania
| | - William E. Klunk
- Department of PsychiatryUniversity of Pittsburgh School of MedicinePittsburghPennsylvania
| | - Sandra Weintraub
- Department of Psychiatry and Behavioral SciencesNorthwestern University Feinberg School of MedicineChicagoIllinois
| | - Richard C. Gershon
- Department of Medical Social SciencesNorthwestern University Feinberg School of MedicineChicagoIllinois
| | - Ann D. Cohen
- Department of PsychiatryUniversity of Pittsburgh School of MedicinePittsburghPennsylvania
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30
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Zammit MD, Laymon CM, Betthauser TJ, Cody KA, Tudorascu DL, Minhas DS, Sabbagh MN, Johnson SC, Zaman SH, Mathis CA, Klunk WE, Handen BL, Cohen AD, Christian BT. Amyloid accumulation in Down syndrome measured with amyloid load. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2020; 12:e12020. [PMID: 32435686 PMCID: PMC7233422 DOI: 10.1002/dad2.12020] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Revised: 12/18/2019] [Accepted: 12/20/2019] [Indexed: 12/03/2022]
Abstract
INTRODUCTION Individuals with Down syndrome (DS) show enhanced amyloid beta (Aβ) deposition in the brain. A new positron emission tomography (PET) index of amyloid load (AβL ) was recently developed as an alternative to standardized uptake value ratios (SUVrs) to quantify Aβ burden with high sensitivity for detecting and tracking Aβ change.1. METHODS AβL was calculated in a DS cohort (N = 169, mean age ± SD = 39.6 ± 8.7 years) using [C-11]Pittsburgh compound B (PiB) PET imaging. DS-specific PiB templates were created for Aβ carrying capacity (K) and non-specific binding (NS). RESULTS The highest values of Aβ carrying capacity were found in the striatum and precuneus. Longitudinal changes in AβL displayed less variability when compared to SUVrs. DISCUSSION These results highlight the utility of AβL for characterizing Aβ deposition in DS. Rates of Aβ accumulation in DS were found to be similar to that observed in late-onset Alzheimer's disease (AD; ≈3% to 4% per year), suggesting that AD progression in DS is of earlier onset but not accelerated.
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Affiliation(s)
| | - Charles M. Laymon
- Department of RadiologyUniversity of PittsburghPittsburghPennsylvania
| | - Tobey J. Betthauser
- Alzheimer's Disease Research CenterUniversity of Wisconsin‐MadisonMadisonWisconsin
| | - Karly A. Cody
- Alzheimer's Disease Research CenterUniversity of Wisconsin‐MadisonMadisonWisconsin
| | - Dana L. Tudorascu
- Department of Internal MedicineUniversity of PittsburghPittsburghPennsylvania
| | - Davneet S. Minhas
- Department of RadiologyUniversity of PittsburghPittsburghPennsylvania
| | | | - Sterling C. Johnson
- Alzheimer's Disease Research CenterUniversity of Wisconsin‐MadisonMadisonWisconsin
| | - Shahid H. Zaman
- Cambridge Intellectual Disability Research GroupUniversity of CambridgeCambridgeUK
| | - Chester A. Mathis
- Department of RadiologyUniversity of PittsburghPittsburghPennsylvania
| | - William E. Klunk
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvania
| | | | - Ann D. Cohen
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvania
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31
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Lin C, Ly M, Karim HT, Wei W, Snitz BE, Klunk WE, Aizenstein HJ. The effect of amyloid deposition on longitudinal resting-state functional connectivity in cognitively normal older adults. Alzheimers Res Ther 2020; 12:7. [PMID: 31907079 PMCID: PMC6945413 DOI: 10.1186/s13195-019-0573-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Accepted: 12/23/2019] [Indexed: 12/22/2022]
Abstract
BACKGROUND Pathological processes contributing to Alzheimer's disease begin decades prior to the onset of clinical symptoms. There is significant variation in cognitive changes in the presence of pathology, functional connectivity may be a marker of compensation to amyloid; however, this is not well understood. METHODS We recruited 64 cognitively normal older adults who underwent neuropsychological testing and biannual magnetic resonance imaging (MRI), amyloid imaging with Pittsburgh compound B (PiB)-PET, and glucose metabolism (FDG)-PET imaging for up to 6 years. Resting-state MRI was used to estimate connectivity of seven canonical neural networks using template-based rotation. Using voxel-wise paired t-tests, we identified neural networks that displayed significant changes in connectivity across time. We investigated associations among amyloid and longitudinal changes in connectivity and cognitive function by domains. RESULTS Left middle frontal gyrus connectivity within the memory encoding network increased over time, but the rate of change was lower with greater amyloid. This was no longer significant in an analysis where we limited the sample to only those with two time points. We found limited decline in cognitive domains overall. Greater functional connectivity was associated with better attention/processing speed and executive function (independent of time) in those with lower amyloid but was associated with worse function with greater amyloid. CONCLUSIONS Increased functional connectivity serves to preserve cognitive function in normal aging and may fail in the presence of pathology consistent with compensatory models.
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Affiliation(s)
- Chemin Lin
- Department of Psychiatry, Keelung Chang Chung Memorial Hospital, Keelung, Taiwan
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Maria Ly
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Helmet T Karim
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Wenjing Wei
- The Third Xiangya Hospital of Central South University, Changsha, Hunan, China
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Beth E Snitz
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - William E Klunk
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Howard J Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
- Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.
- Western Psychiatric Institute and Clinic, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA.
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32
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Lesot MJ, Vieira S, Reformat MZ, Carvalho JP, Wilbik A, Bouchon-Meunier B, Yager RR. Statistical Methods for Processing Neuroimaging Data from Two Different Sites with a Down Syndrome Population Application. INFORMATION PROCESSING AND MANAGEMENT OF UNCERTAINTY IN KNOWLEDGE-BASED SYSTEMS 2020. [PMCID: PMC7274647 DOI: 10.1007/978-3-030-50153-2_28] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Harmonization of magnetic resonance imaging (MRI) and positron emission tomography (PET) scans from multi-scanner and multi-site studies presents a challenging problem. We applied the Removal of Artificial Voxel Effect by Linear regression (RAVEL) method to normalize T1-MRI intensities collected on two different scanners across two different sites as part of the Neurodegeneration in Aging Down syndrome (NiAD) study. The effects on FreeSurfer regional cortical thickness and volume outcome measures, in addition to FreeSurfer-based regional quantification of amyloid PET standardized uptake value ratio (SUVR) outcomes, were evaluated. A neuroradiologist visually assessed the accuracy of FreeSurfer hippocampus segmentations with and without the application of RAVEL. Quantitative results demonstrated that the application of RAVEL intensity normalization prior to running FreeSurfer significantly impacted both FreeSurfer volume and cortical thickness outcome measures. Visual assessment demonstrated that the application of RAVEL significantly improved FreeSurfer hippocampal segmentation accuracy. The RAVEL intensity normalization had little impact on PET SUVR measures.
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Affiliation(s)
| | - Susana Vieira
- IDMEC, IST, Universidade de Lisboa, Lisbon, Portugal
| | | | | | - Anna Wilbik
- Eindhoven University of Technology, Eindhoven, The Netherlands
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Weigand AJ, Bangen KJ, Thomas KR, Delano-Wood L, Gilbert PE, Brickman AM, Bondi MW. Is tau in the absence of amyloid on the Alzheimer's continuum?: A study of discordant PET positivity. Brain Commun 2019; 2:fcz046. [PMID: 32051933 PMCID: PMC7001143 DOI: 10.1093/braincomms/fcz046] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Revised: 11/15/2019] [Accepted: 11/25/2019] [Indexed: 12/14/2022] Open
Abstract
The amyloid cascade model of Alzheimer’s disease posits the primacy of amyloid beta deposition preceding tau-mediated neurofibrillary tangle formation. The amyloid-tau-neurodegeneration biomarker-only diagnostic framework similarly requires the presence of amyloid beta for a diagnosis on the Alzheimer’s continuum. However, medial temporal lobe tau pathology in the absence of amyloid beta is frequently observed at autopsy in cognitively normal individuals, a phenomenon that may reflect a consequence of aging and has been labelled ‘primary age-related tauopathy’. Alternatively, others argue that this tauopathy reflects an early stage of the developmental continuum leading to Alzheimer’s disease. We used positron emission tomography imaging to investigate amyloid beta and tau positivity and associations with cognition to better inform the conceptualization of biomarker changes in Alzheimer’s pathogenesis. Five hundred twenty-three individuals from the Alzheimer’s Disease Neuroimaging Initiative who had undergone flortaucipir positron emission tomography imaging were selected to derive positron emission tomography positivity thresholds using conditional inference decision tree regression. A subsample of 301 individuals without dementia (i.e. those with normal cognition or mild cognitive impairment) had also undergone florbetapir positron emission tomography imaging within 12 months and were categorized into one of the four groups based on cortical amyloid and Braak stage I/II tau positivity: A−/T−, A+/T−, A−/T+, or A+/T+. Tau positivity in the absence of amyloid beta positivity (i.e. A−/T+) comprised the largest group, representing 45% of the sample. In contrast, only 6% of the sample was identified as A+/T−, and the remainder of the sample fell into A−/T− (22%) or A+/T+ (27%) categories. A−/T− and A+/T− groups had the best cognitive performances across memory, language and executive function; the A−/T+ group showed small-to-moderate relative decreases in cognition; and the A+/T+ group had the worst cognitive performances. Furthermore, there were negative associations between Braak stage I/II tau values and all cognitive domains only in the A−/T+ and A+/T+ groups, with strongest associations for the A+/T+ group. Among our sample of older adults across the Alzheimer’s pathological spectrum, 7-fold fewer individuals have positron emission tomography evidence of amyloid beta pathology in the absence of tau pathology than the converse, challenging prevailing models of amyloid beta’s primacy in Alzheimer’s pathogenesis. Given that cognitive performance in the A−/T+ group was poorer than in individuals without either pathology, our results suggest that medial temporal lobe tau without cortical amyloid beta may reflect an early stage on the Alzheimer’s pathological continuum.
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Affiliation(s)
- Alexandra J Weigand
- San Diego State University/University of California San Diego Joint Doctoral Program, San Diego, CA 92182, USA
| | - Katherine J Bangen
- VA San Diego Healthcare System, San Diego, CA 92161, USA.,Department of Psychiatry, University of California, San Diego, CA 92161, USA
| | - Kelsey R Thomas
- VA San Diego Healthcare System, San Diego, CA 92161, USA.,Department of Psychiatry, University of California, San Diego, CA 92161, USA
| | - Lisa Delano-Wood
- VA San Diego Healthcare System, San Diego, CA 92161, USA.,Department of Psychiatry, University of California, San Diego, CA 92161, USA
| | - Paul E Gilbert
- Department of Psychology, San Diego State University, San Diego, CA 92182, USA
| | - Adam M Brickman
- Department of Neurology, Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA
| | - Mark W Bondi
- VA San Diego Healthcare System, San Diego, CA 92161, USA.,Department of Psychiatry, University of California, San Diego, CA 92161, USA
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Fantoni E, Collij L, Lopes Alves I, Buckley C, Farrar G. The Spatial-Temporal Ordering of Amyloid Pathology and Opportunities for PET Imaging. J Nucl Med 2019; 61:166-171. [PMID: 31836683 DOI: 10.2967/jnumed.119.235879] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2019] [Accepted: 12/03/2019] [Indexed: 12/24/2022] Open
Abstract
Although clinical routine focuses on dichotomous and visual interpretation of amyloid PET, regional image assessment in research settings may yield additional opportunities. Understanding the regional-temporal evolution of amyloid pathology may enable earlier identification of subjects in the Alzheimer Disease pathologic continuum, as well as a finer-grained assessment of pathology beyond traditional dichotomous measures. This review summarizes current research in the detection of regional amyloid deposition patterns and its potential for staging amyloid pathology. Pathology studies, cross-sectional and longitudinal PET-only studies, and comparative PET and autopsy studies are included. Despite certain differences, cortical deposition generally precedes striatal pathology, and in PET-only studies, medial cortical regions are seen to accumulate amyloid earlier than lateral regions. Based on regional amyloid PET, multiple studies have developed and implemented models for staging amyloid pathology that could improve subject selection into secondary prevention trials and visual assessment in clinical routine.
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Affiliation(s)
- Enrico Fantoni
- Pharmaceutical Diagnostics, GE Healthcare, Chalfont St. Giles, Buckinghamshire, United Kingdom; and
| | - Lyduine Collij
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Isadora Lopes Alves
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Christopher Buckley
- Pharmaceutical Diagnostics, GE Healthcare, Chalfont St. Giles, Buckinghamshire, United Kingdom; and
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The clinical feasibility of deep learning-based classification of amyloid PET images in visually equivocal cases. Eur J Nucl Med Mol Imaging 2019; 47:332-341. [PMID: 31811343 DOI: 10.1007/s00259-019-04595-y] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2019] [Accepted: 11/04/2019] [Indexed: 10/25/2022]
Abstract
PURPOSE Although most deep learning (DL) studies have reported excellent classification accuracy, these studies usually target typical Alzheimer's disease (AD) and normal cognition (NC) for which conventional visual assessment performs well. A clinically relevant issue is the selection of high-risk subjects who need active surveillance among equivocal cases. We validated the clinical feasibility of DL compared with visual rating or quantitative measurement for assessing the diagnosis and prognosis of subjects with equivocal amyloid scans. METHODS 18F-florbetaben scans of 430 cases (85 NC, 233 mild cognitive impairment, and 112 AD) were assessed through visual rating-based, quantification-based, and DL-based methods. DL was trained using 280 two-dimensional PET images (80%) and tested by randomly assigning the remaining (70 cases, 20%) cases and a clinical validation set of 54 equivocal cases. In the equivocal cases, we assessed the agreement among the visual rating, quantification, and DL and compared the clinical outcome according to each modality-based amyloid status. RESULTS The visual reading was positive in 175 cases, equivocal in 54 cases, and negative in 201 cases. The composite SUVR cutoff value was 1.32 (AUC 0.99). The subject-level performance of DL using the test set was 100%. Among the 54 equivocal cases, 37 cases were classified as positive (Eq(deep+)) by DL, 40 cases were classified by a second-round visual assessment, and 40 cases were classified by quantification. The DL- and quantification-based classifications showed good agreement (83%, κ = 0.59). The composite SUVRs differed between Eq(deep+) (1.47 [0.13]) and Eq(deep-) (1.29 [0.10]; P < 0.001). DL, but not the visual rating, showed a significant difference in the Mini-Mental Status Examination score change during the follow-up between Eq(deep+) (- 4.21 [0.57]) and Eq(deep-) (- 1.74 [0.76]; P = 0.023) (mean duration, 1.76 years). CONCLUSIONS In visually equivocal scans, DL was more related to quantification than to visual assessment, and the negative cases selected by DL showed no decline in cognitive outcome. DL is useful for clinical diagnosis and prognosis assessment in subjects with visually equivocal amyloid scans.
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Karim HT, Tudorascu DL, Cohen A, Price JC, Lopresti B, Mathis C, Klunk W, Snitz BE, Aizenstein HJ. Relationships Between Executive Control Circuit Activity, Amyloid Burden, and Education in Cognitively Healthy Older Adults. Am J Geriatr Psychiatry 2019; 27:1360-1371. [PMID: 31402087 PMCID: PMC7047647 DOI: 10.1016/j.jagp.2019.07.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2018] [Revised: 07/01/2019] [Accepted: 07/15/2019] [Indexed: 11/30/2022]
Abstract
INTRODUCTION In cognitively healthy older adults, amyloid-beta (Aβ) burden is associated with greater activity on task-based functional magnetic resonance imaging. Higher levels of functional activation are associated with other factors along with amyloid and the authors investigated these relationships as well as how they relate to Aβ in cognitively healthy older adults. METHODS The authors recruited cognitive healthy older adults (N = 50) from the Pittsburgh community that underwent extensive cognitive batteries, activation during a working memory (digit symbol substitution task, DSST), positron emission tomography scan for Pittsburgh Compound B (PiB, measuring amyloid), and other demographic measures. The authors tested the association between DSST activation and global PiB, neurocognitive batteries, and education. RESULTS The authors found that the DSST robustly activated expected structures involved in working memory. The authors found that greater global Aβ deposition was associated with greater DSST activation in the right calcarine, precuneus, middle temporal as well as the left insula and inferior frontal gyrus. The authors also found that greater education was associated with lower DSST activation - however this was not significant after adjusting for Aβ. DISCUSSION Greater amyloid was associated with greater activation, which may represent compensatory activation. Greater education was associated with lower activation, which may represent more efficient activation (i.e., less activation for the same task). After adjusting for amyloid, education was not significantly associated with activation suggesting that during the preclinical stage amyloid is the primary determinant of activation. Further, activation was not associated with cognitive function. Compensatory activation in the preclinical stage may help maintain cognitive function.
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Affiliation(s)
| | | | - Ann Cohen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA
| | - Julie C. Price
- Department of Radiology, Massachusetts General Hospital, Boston, MA
| | - Brian Lopresti
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA
| | - Chester Mathis
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA
| | - William Klunk
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA,Department of Neurology, University of Pittsburgh, Pittsburgh, PA
| | - Beth E. Snitz
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA
| | - Howard J. Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA,Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA
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Okada Y, Kato T, Iwata K, Kimura Y, Nakamura A, Hattori H, Toyama H, Ishii K, Ishii K, Senda M, Ito K, Iwatsubo T. Evaluation of PiB visual interpretation with CSF Aβ and longitudinal SUVR in J-ADNI study. Ann Nucl Med 2019; 34:108-118. [PMID: 31749127 PMCID: PMC7026272 DOI: 10.1007/s12149-019-01420-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2019] [Accepted: 11/11/2019] [Indexed: 12/14/2022]
Abstract
Objective The objectives of the present study were to investigate (1) whether trinary visual interpretation of amyloid positron emission tomography (PET) imaging (negative/equivocal/positive) reflects quantitative amyloid measurements and the time course of 11C-Pittsburgh compound B (PiB) amyloid accumulation, and (2) whether visually equivocal scans represent an early stage of the Alzheimer’s disease (AD) continuum in terms of an intermediate state of quantitative amyloid measurements and the changes in amyloid accumulation over time. Methods From the National Bioscience Database Center Human Database of the Japanese Alzheimer’s Disease Neuroimaging Initiative, we selected 133 individuals for this study including 33 with Alzheimer’s disease dementia (ADD), 52 with late mild cognitive impairment (LMCI), and 48 cognitively normal (CN) subjects who underwent clinical assessment, PiB PET, and structural magnetic resonance imaging (MRI) with 2 or 3-years of follow-up. Sixty-eight of the 133 individuals underwent cerebrospinal fluid amyloid-β1-42 (CSF-Ab42) analysis at baseline. The standard uptake value ratio (SUVR) of PiB PET was calculated with a method using MRI at each visit. The cross-sectional values, longitudinal changes in SUVR, and baseline CSF-Ab42 were compared among groups, which were categorized based on trinary visual reads of amyloid PET (negative/equivocal/positive). Results From the trinary visual interpretation of the PiB PET images, 55 subjects were negative, 8 were equivocal, and 70 were positive. Negative interpretation was most frequent in the CN group (70.8/10.4/18.8%: negative/equivocal/positive), and positive was most frequent in the LMCI group (34.6/1.9/63.5%) and in the ADD group (9.1/6.1/84.8%). The baseline SUVRs were 1.08 ± 0.06 in the negative group, 1.23 ± 0.15 in the equivocal group, and 1.86 ± 0.31 in the positive group (F = 174.9, p < 0.001). The baseline CSF-Ab42 level was 463 ± 112 pg/mL in the negative group, 383 ± 125 pg/mL in the equivocal group, and 264 ± 69 pg/mL in the positive group (F = 37, p < 0.001). Over the 3-year follow-up, annual changes in SUVR were − 0.00 ± 0.02 in the negative group, 0.02 ± 0.02 in the equivocal group, and 0.04 ± 0.07 in the positive group (F = 8.4, p < 0.001). Conclusions Trinary visual interpretation (negative/equivocal/positive) of amyloid PET imaging reflects quantitative amyloid measurements evaluated with PET and the CSF amyloid test as well as the amyloid accumulation over time evaluated with PET over 3 years. Subjects in the early stage of the AD continuum could be identified with an equivocal scan, because they showed intermediate quantitative amyloid PET, CSF measurements, and the amyloid accumulation over time. Electronic supplementary material The online version of this article (10.1007/s12149-019-01420-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Yusuke Okada
- Department of Radiology, Fujita Health University, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, 470-1192, Aichi, Japan. .,Department of Psychiatry, National Center for Geriatrics and Gerontology, 7-430 Morioka-cho, Obu, 474-8511, Aichi, Japan. .,Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, 7-430 Morioka-cho, Obu, 474-8511, Aichi, Japan.
| | - Takashi Kato
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, 7-430 Morioka-cho, Obu, 474-8511, Aichi, Japan.,Department of Radiology, National Center for Geriatrics and Gerontology, 7-430 Morioka-cho, Obu, 474-8511, Aichi, Japan
| | - Kaori Iwata
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, 7-430 Morioka-cho, Obu, 474-8511, Aichi, Japan
| | - Yasuyuki Kimura
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, 7-430 Morioka-cho, Obu, 474-8511, Aichi, Japan
| | - Akinori Nakamura
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, 7-430 Morioka-cho, Obu, 474-8511, Aichi, Japan
| | - Hideyuki Hattori
- Department of Psychiatry, National Center for Geriatrics and Gerontology, 7-430 Morioka-cho, Obu, 474-8511, Aichi, Japan
| | - Hiroshi Toyama
- Department of Radiology, Fujita Health University, 1-98 Dengakugakubo, Kutsukake-cho, Toyoake, 470-1192, Aichi, Japan
| | - Kazunari Ishii
- Department of Radiology, Kindai University Faculty of Medicine, 377-2 Onohigashi, Osakasayama, 589-8511, Osaka, Japan
| | - Kenji Ishii
- Diagnostic Neuroimaging Research, Tokyo Metropolitan Institute of Gerontology, 35-2 Sakae-cho, Itabashi-ku, Tokyo, 173-0015, Japan
| | - Michio Senda
- Division of Molecular Imaging, Kobe City Medical Center General Hospital, 2-1-1, Minatojimaminamimachi, Chuo-ku, Kobe, 650-0047, Hyogo, Japan
| | - Kengo Ito
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, 7-430 Morioka-cho, Obu, 474-8511, Aichi, Japan.,Department of Radiology, National Center for Geriatrics and Gerontology, 7-430 Morioka-cho, Obu, 474-8511, Aichi, Japan
| | - Takeshi Iwatsubo
- Department of Neuropathology, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan
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Wu M, Thurston RC, Tudorascu DL, Karim HT, Mathis CA, Lopresti BJ, Kamboh MI, Cohen AD, Snitz BE, Klunk WE, Aizenstein HJ. Amyloid deposition is associated with different patterns of hippocampal connectivity in men versus women. Neurobiol Aging 2019; 76:141-150. [PMID: 30711677 PMCID: PMC6584958 DOI: 10.1016/j.neurobiolaging.2018.11.020] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2018] [Revised: 10/04/2018] [Accepted: 11/18/2018] [Indexed: 01/26/2023]
Abstract
Compared to men, women are disproportionally affected by Alzheimer's disease (AD) and have an accelerated trajectory of cognitive decline and disease progression. Neurobiological factors underlying gender differences in AD remain unclear. This study investigated brain beta-amyloid (Aβ)-related neural system differences in cognitively normal older men and women (N = 61; 41 females, 65-93 years old). We found that men and women showed different associations between Aβ load and hippocampal functional connectivity. During associative memory encoding, in men greater Aβ burden was accompanied by greater hippocampus-prefrontal connectivity (i.e., more synchronized activities), whereas in women hippocampal connectivity did not vary by Aβ burden. For resting-state data, the interaction of gender × Aβ on hippocampal connectivity did not survive multiple comparison in the whole-brain analyses. In the region of interest-based analyses, resting-state hippocampal-prefrontal connectivity was positively correlated with Aβ load in men and was negatively correlated with Aβ load in women. The observed Aβ-related neural differences may explain the accelerated trajectory of cognitive decline and AD progression in women.
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Affiliation(s)
- Minjie Wu
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Rebecca C Thurston
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA; Departments of Epidemiology and Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Dana L Tudorascu
- Departments of Medicine and Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Helmet T Karim
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Chester A Mathis
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Brian J Lopresti
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - M Ilyas Kamboh
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ann D Cohen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Beth E Snitz
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - William E Klunk
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Howard J Aizenstein
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA; Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA.
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La Joie R, Ayakta N, Seeley WW, Borys E, Boxer AL, DeCarli C, Doré V, Grinberg LT, Huang E, Hwang JH, Ikonomovic MD, Jack C, Jagust WJ, Jin LW, Klunk WE, Kofler J, Lesman-Segev OH, Lockhart SN, Lowe VJ, Masters CL, Mathis CA, McLean CL, Miller BL, Mungas D, O'Neil JP, Olichney JM, Parisi JE, Petersen RC, Rosen HJ, Rowe CC, Spina S, Vemuri P, Villemagne VL, Murray ME, Rabinovici GD. Multisite study of the relationships between antemortem [ 11C]PIB-PET Centiloid values and postmortem measures of Alzheimer's disease neuropathology. Alzheimers Dement 2019; 15:205-216. [PMID: 30347188 PMCID: PMC6368897 DOI: 10.1016/j.jalz.2018.09.001] [Citation(s) in RCA: 167] [Impact Index Per Article: 33.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2018] [Revised: 07/08/2018] [Accepted: 09/03/2018] [Indexed: 10/28/2022]
Abstract
INTRODUCTION We sought to establish the relationships between standard postmortem measures of AD neuropathology and antemortem [11C]PIB-positron emission tomography ([11C]PIB-PET) analyzed with the Centiloid (CL) method, a standardized scale for Aβ-PET quantification. METHODS Four centers contributed 179 participants encompassing a broad range of clinical diagnoses, PET data, and autopsy findings. RESULTS CL values increased with each CERAD neuritic plaque score increment (median -3 CL for no plaques and 92 CL for frequent plaques) and nonlinearly with Thal Aβ phases (increases were detected starting at phase 2) with overlap between scores/phases. PET-pathology associations were comparable across sites and unchanged when restricting the analyses to the 56 patients who died within 2 years of PET. A threshold of 12.2 CL detected CERAD moderate-to-frequent neuritic plaques (area under the curve = 0.910, sensitivity = 89.2%, specificity = 86.4%), whereas 24.4 CL identified intermediate-to-high AD neuropathological changes (area under the curve = 0.894, sensitivity = 84.1%, specificity = 87.9%). DISCUSSION Our study demonstrated the robustness of a multisite Centiloid [11C]PIB-PET study and established a range of pathology-based CL thresholds.
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Affiliation(s)
- Renaud La Joie
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA.
| | - Nagehan Ayakta
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA; Helen Wills Neuroscience Institute, University of California Berkeley, CA, USA
| | - William W Seeley
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Ewa Borys
- Department of Pathology, Stritch School of Medicine, Loyola University, Maywood, IL, USA
| | - Adam L Boxer
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Charles DeCarli
- Department of Neurology, University of California, Davis, CA, USA
| | - Vincent Doré
- Department of Molecular Imaging & Therapy, Centre for PET, Austin Health, Heidelberg, Victoria, Australia
| | - Lea T Grinberg
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Eric Huang
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Ji-Hye Hwang
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Milos D Ikonomovic
- Department of Neurology, University of Pittsburgh, PA, USA; Department of Psychiatry, University of Pittsburgh, PA, USA
| | - Clifford Jack
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California Berkeley, CA, USA
| | - Lee-Way Jin
- Alzheimer's Disease Center, Department of Pathology, University of California Davis, CA, USA
| | - William E Klunk
- Department of Neurology, University of Pittsburgh, PA, USA; Department of Psychiatry, University of Pittsburgh, PA, USA; Alzheimer's Disease Research Center, University of Pittsburgh, PA, USA
| | - Julia Kofler
- Department of Pathology, University of Pittsburgh, Pennsylvania, USA
| | - Orit H Lesman-Segev
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Samuel N Lockhart
- Helen Wills Neuroscience Institute, University of California Berkeley, CA, USA; Department of Internal Medicine, Division of Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Val J Lowe
- Department of Nuclear Medicine, Mayo Clinic, Rochester, MN, USA
| | - Colin L Masters
- The Florey Institute, The University of Melbourne, Melbourne, Victoria, Australia
| | | | - Catriona L McLean
- Department of Anatomical Pathology, Alfred Hospital, Melbourne, Australia
| | - Bruce L Miller
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Daniel Mungas
- Department of Neurology, University of California, Davis, CA, USA
| | - James P O'Neil
- Helen Wills Neuroscience Institute, University of California Berkeley, CA, USA; Biomedical Isotope Facility, MBIB Division, Lawrence Berkeley National Laboratory, CA, USA
| | - John M Olichney
- Department of Neurology, University of California, Davis, CA, USA
| | - Joseph E Parisi
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA; Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | - Howard J Rosen
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Christopher C Rowe
- Department of Molecular Imaging & Therapy, Centre for PET, Austin Health, Heidelberg, Victoria, Australia
| | - Salvatore Spina
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | | | - Victor L Villemagne
- Department of Molecular Imaging & Therapy, Centre for PET, Austin Health, Heidelberg, Victoria, Australia; The Florey Institute, The University of Melbourne, Melbourne, Victoria, Australia
| | | | - Gil D Rabinovici
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, CA, USA; Helen Wills Neuroscience Institute, University of California Berkeley, CA, USA
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Cognitive changes of older adults with an equivocal amyloid load. J Neurol 2019; 266:835-843. [DOI: 10.1007/s00415-019-09203-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2018] [Revised: 12/05/2018] [Accepted: 01/18/2019] [Indexed: 11/27/2022]
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Cohen AD, Landau SM, Snitz BE, Klunk WE, Blennow K, Zetterberg H. Fluid and PET biomarkers for amyloid pathology in Alzheimer's disease. Mol Cell Neurosci 2018; 97:3-17. [PMID: 30537535 DOI: 10.1016/j.mcn.2018.12.004] [Citation(s) in RCA: 63] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2018] [Accepted: 12/05/2018] [Indexed: 02/04/2023] Open
Abstract
Alzheimer's disease (AD) is characterized by amyloid plaques and tau pathology (neurofibrillary tangles and neuropil threads). Amyloid plaques are primarily composed of aggregated and oligomeric β-amyloid (Aβ) peptides ending at position 42 (Aβ42). The development of fluid and PET biomarkers for Alzheimer's disease (AD), has allowed for detection of Aβ pathology in vivo and marks a major advancement in understanding the role of Aβ in Alzheimer's disease (AD). In the recent National Institute on Aging and Alzheimer's Association (NIA-AA) Research Framework, AD is defined by the underlying pathology as measured in patients during life by biomarkers (Jack et al., 2018), while clinical symptoms are used for staging of the disease. Therefore, sensitive, specific and robust biomarkers to identify brain amyloidosis are central in AD research. Here, we discuss fluid and PET biomarkers for Aβ and their application.
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Affiliation(s)
- Ann D Cohen
- Department of Psychiatry, University of Pittsburgh School of Medicine, United States of America.
| | - Susan M Landau
- Neurology Helen Wills Neuroscience Institute, University of California, Berkeley, United States of America; Lawrence Berkeley National Laboratory, Molecular Biophysics and Integrated Bioimaging Functional Imaging Department, Life Sciences Division, United States of America
| | - Beth E Snitz
- Department of Neurology, University of Pittsburgh School of Medicine, United States of America
| | - William E Klunk
- Department of Psychiatry, University of Pittsburgh School of Medicine, United States of America
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Molndal, Sweden; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, University College, London, United Kingdom of Great Britain and Northern Ireland
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Molndal, Sweden; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, University College, London, United Kingdom of Great Britain and Northern Ireland; Department of Molecular Neuroscience, UCL Institute of Neurology, United Kingdom of Great Britain and Northern Ireland; UK Dementia Research Institute at UCL, United Kingdom of Great Britain and Northern Ireland
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Amyloid burden identifies neuropsychological phenotypes at increased risk of progression to Alzheimer's disease in mild cognitive impairment patients. Eur J Nucl Med Mol Imaging 2018; 46:288-296. [PMID: 30244387 PMCID: PMC6333718 DOI: 10.1007/s00259-018-4149-2] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Accepted: 08/26/2018] [Indexed: 02/06/2023]
Abstract
Purpose The extent of amyloid burden associated with cognitive impairment in amnestic mild cognitive impairment is unknown. The primary aim of the study was to determine the extent to which amyloid burden is associated to the cognitive impairment. The secondary objective was to test the relationship between amyloid accumulation and memory or cognitive impairment. Materials and methods In this prospective study 66 participants with amnestic mild cognitive impairment underwent clinical, neuropsychological and PET amyloid imaging tests. Composite scores assessing memory and non-memory domains were used to identify two clinical classes of neuropsychological phenotypes expressing different degree of cognitive impairment. Detection of amyloid status and definition of optimal amyloid ± cutoff for discrimination relied on unsupervised k-means clustering method. Results Threshold for identifying low and high amyloid retention groups was of SUVr = 1.3. Aß + participants showed poorer global cognitive and episodic memory performance than subjects with low amyloid deposition. Aß positivity significantly identified individuals with episodic memory impairment with a sensitivity and specificity of 80 and 79%, (χ2 = 21.48; P < 0.00001). Positive and negative predictive values were 82 and 76%, respectively. Amyloid deposition increased linearly as function of memory impairment with a rate of 0.13/ point of composite memory score (R = −44, P = 0.0003). Conclusion The amyloid burden of SUVr = 1.3 allows early identification of subjects with episodic memory impairment which might predict progression from MCI to Alzheimer’s disease. Trial registration EudraCT 2015-001184-39.
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The Relationship of Current Cognitive Activity to Brain Amyloid Burden and Glucose Metabolism. Am J Geriatr Psychiatry 2018; 26:977-984. [PMID: 29885987 PMCID: PMC6482956 DOI: 10.1016/j.jagp.2018.03.018] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2017] [Revised: 03/20/2018] [Accepted: 03/29/2018] [Indexed: 11/20/2022]
Abstract
Several studies have investigated how lifetime cognitive engagement affects levels of amyloid-beta (Aβ) deposition in the brain. However, there has been some disagreement, leaving the relationship of cognitive activity (CA) to Aβ a largely open question. The present study investigated the relationship between CA, Aβ deposition, and glucose metabolism. One hundred nine cognitively normal participants underwent Pittsburgh Compound-B (PiB) and [18F]fluorodeoxyglucose-positron emission tomography and completed a questionnaire designed to measure current CA. Statistical analyses revealed significant differences in PiB retention between those in the high and low CA groups. Linear regression models revealed a significant negative relationship between PiB retention and CA and a significant positive relationship between glucose metabolism and CA. These data suggest that CA may have a direct beneficial effect on the pathophysiology of AD or reflect another underlying process that results in both higher CA and lower AD pathophysiology.
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Wilckens KA, Tudorascu DL, Snitz BE, Price JC, Aizenstein HJ, Lopez OL, Erickson KI, Lopresti BJ, Laymon CM, Minhas D, Mathis CA, Buysse DJ, Klunk WE, Cohen AD. Sleep moderates the relationship between amyloid beta and memory recall. Neurobiol Aging 2018; 71:142-148. [PMID: 30138767 DOI: 10.1016/j.neurobiolaging.2018.07.011] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Revised: 06/18/2018] [Accepted: 07/17/2018] [Indexed: 12/21/2022]
Abstract
Amyloid-β (Aβ) accumulation is a hallmark of Alzheimer's disease, although Aβ alone may be insufficient to cause impairments. Modifiable health factors, including sleep, may mitigate functional symptoms of neurodegeneration. We assessed whether sleep moderated the relationship between Aβ and cognitive performance in 41 older adults, mean age 83 years. Sleep measures included actigraphy-assessed wake after sleep onset and total sleep time. Cognitive performance was assessed with memory recall, cognitive flexibility, and verbal fluency. Memory recall was assessed with the Rey-Osterrieth Complex Figure task, cognitive flexibility with the Trail Making test, and verbal fluency with FAS word generation. Aβ was assessed with a global measure of Pittsburgh Compound B. Wake after sleep onset moderated the relationship between Aβ and memory, with a stronger positive association for Aβ and forgetting in those with poorer sleep. These results suggest a possible protective role of sleep in preclinical Alzheimer's disease.
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Affiliation(s)
- Kristine A Wilckens
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
| | - Dana L Tudorascu
- Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Beth E Snitz
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Julie C Price
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Howard J Aizenstein
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Oscar L Lopez
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Kirk I Erickson
- Department of Psychology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Brian J Lopresti
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Charles M Laymon
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Bioengineering, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Davneet Minhas
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Chester A Mathis
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Daniel J Buysse
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - William E Klunk
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Ann D Cohen
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
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Cohen AD, McDade E, Christian B, Price J, Mathis C, Klunk W, Handen BL. Early striatal amyloid deposition distinguishes Down syndrome and autosomal dominant Alzheimer's disease from late-onset amyloid deposition. Alzheimers Dement 2018; 14:743-750. [PMID: 29477284 PMCID: PMC5994364 DOI: 10.1016/j.jalz.2018.01.002] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2017] [Revised: 09/23/2017] [Accepted: 01/08/2018] [Indexed: 01/19/2023]
Abstract
INTRODUCTION The objective of this study was to evaluate amyloid β (Aβ) deposition patterns in different groups of cerebral β amyloidosis: (1) nondemented with amyloid precursor protein overproduction (Down syndrome); (2) nondemented with abnormal processing of amyloid precursor protein (preclinical autosomal dominant Alzheimer disease); (3) presumed alteration in Aβ clearance with clinical symptoms (late-onset AD); and (4) presumed alterations in Aβ clearance (preclinical AD). METHODS We performed whole-brain voxelwise comparison of cerebral Aβ between 23 Down syndrome, 10 preclinical autosomal dominant Alzheimer disease, 17 late-onset AD, and 16 preclinical AD subjects, using Pittsburgh Compound B-positron emission tomography. RESULTS We found both Down syndrome and preclinical autosomal dominant Alzheimer disease shared a distinct pattern of increased bilateral striatal and thalamic Aβ deposition compared to late-onset AD and preclinical AD. CONCLUSION Disorders associated with early-life alterations in amyloid precursor protein production or processing are associated with a distinct pattern of early striatal fibrillary Aβ deposition before significant cognitive impairment. A better understanding of this unique pattern could identify important mechanisms of Aβ deposition and possibly important targets for early intervention.
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Affiliation(s)
- Ann D Cohen
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
| | - Eric McDade
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Brad Christian
- Department of Medical Physics, University of Wisconsin-Madison School of Medicine, Madison, WI, USA
| | - Julie Price
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; A. A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Cambridge, MA, USA
| | - Chester Mathis
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - William Klunk
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA; Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Benjamin L Handen
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
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46
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Mishra S, Blazey TM, Holtzman DM, Cruchaga C, Su Y, Morris JC, Benzinger TLS, Gordon BA. Longitudinal brain imaging in preclinical Alzheimer disease: impact of APOE ε4 genotype. Brain 2018; 141:1828-1839. [PMID: 29672664 PMCID: PMC5972633 DOI: 10.1093/brain/awy103] [Citation(s) in RCA: 104] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2017] [Revised: 01/29/2018] [Accepted: 02/17/2018] [Indexed: 02/07/2023] Open
Abstract
While prior work reliably demonstrates that the APOE ɛ4 allele has deleterious group level effects on Alzheimer disease pathology, the homogeneity of its influence across the lifespan and spatially in the brain remains unknown. Further it is unclear what combinations of factors at an individual level lead to observed group level effects of APOE genotype. To evaluate the impact of the APOE genotype on disease trajectories, we examined longitudinal MRI and PET imaging in a cohort of 497 cognitively normal middle and older aged participants. A whole-brain regional approach was used to evaluate the spatial effects of genotype on longitudinal change of amyloid-β pathology and cortical atrophy. Carriers of the ɛ4 allele had increased longitudinal accumulation of amyloid-β pathology diffusely through the cortex, but the emergence of this effect across the lifespan differed greatly by region (e.g. age 49 in precuneus, but 65 in the visual cortex) with the detrimental influence already being evident in some regions in middle age. This increased group level effect on accumulation was due to a greater proportion of ɛ4 carriers developing amyloid-β pathology, on average doing so at an earlier age, and having faster amyloid-β accumulation even after accounting for baseline amyloid-β levels. APOE ɛ4 carriers displayed faster rates of structural loss in primarily constrained to the medial temporal lobe structures at around 50 years, although this increase was modest and proportional to the elevated disease severity in APOE ɛ4 carriers. This work indicates that influence of the APOE gene on pathology can be detected starting in middle age.
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Affiliation(s)
- Shruti Mishra
- Department of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - Tyler M Blazey
- Department of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - David M Holtzman
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St Louis, MO, USA
| | - Carlos Cruchaga
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St Louis, MO, USA
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
| | - Yi Su
- Department of Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - John C Morris
- Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St Louis, MO, USA
| | - Tammie L S Benzinger
- Department of Radiology, Washington University School of Medicine, St Louis, MO, USA
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St Louis, MO, USA
| | - Brian A Gordon
- Department of Radiology, Washington University School of Medicine, St Louis, MO, USA
- Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St Louis, MO, USA
- Department of Psychological and Brain Sciences, Washington University School of Medicine, St Louis, MO, USA
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47
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Tudorascu DL, Minhas DS, Lao PJ, Betthauser TJ, Yu Z, Laymon CM, Lopresti BJ, Mathis CA, Klunk WE, Handen BL, Christian BT, Cohen AD. The use of Centiloids for applying [ 11C]PiB classification cutoffs across region-of-interest delineation methods. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2018; 10:332-339. [PMID: 30014032 PMCID: PMC6024172 DOI: 10.1016/j.dadm.2018.03.006] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Abstract
INTRODUCTION Centiloid standardization was developed to establish a quantitative outcome measure of amyloid burden that could accommodate the integration of different amyloid positron emission tomography radiotracers or different methods of quantifying the same tracer. The goal of this study was to examine the use of Centiloids for establishing amyloid classification cutoffs for differing region-of-interest (ROI) delineation schemes. METHODS Using ROIs from hand-drawn delineation in native space as the gold standard, we compared standard uptake value ratios obtained from the 6 hand-drawn ROIs that determine amyloid-positivity classification with standard uptake value ratio obtained from 3 different automated techniques (FreeSurfer, Statistical Parametric Mapping, and superimposed hand-drawn ROIs in Pittsburgh Compound B template space). We tested between-methods reliability using repeated measures models and intraclass correlation coefficients. RESULTS We found high reliability between the hand-drawn standard method and other methods for almost all the regions considered. However, small differences in standard uptake value ratio were found to lead to unreliable classifications when the hand-drawn native space-derived cutoffs were used across other ROI delineation methods. DISCUSSION The use of Centiloid standardization greatly improved the agreement of Pittsburgh Compound B classification across methods and may serve as an alternative method for applying cutoffs across methodologically different outcomes.
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Affiliation(s)
- Dana L. Tudorascu
- Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Davneet S. Minhas
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Patrick J. Lao
- Department of Medical Physics, University of Wisconsin–Madison, School of Medicine, Madison, WI, USA
- Waisman Center, University of Wisconsin–Madison, School of Medicine, Madison, WI, USA
| | - Tobey J. Betthauser
- Department of Medical Physics, University of Wisconsin–Madison, School of Medicine, Madison, WI, USA
- Waisman Center, University of Wisconsin–Madison, School of Medicine, Madison, WI, USA
| | - Zheming Yu
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Charles M. Laymon
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Brian J. Lopresti
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Chet A. Mathis
- Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - William E. Klunk
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Benjamin L. Handen
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Bradley T. Christian
- Department of Medical Physics, University of Wisconsin–Madison, School of Medicine, Madison, WI, USA
- Waisman Center, University of Wisconsin–Madison, School of Medicine, Madison, WI, USA
| | - Ann D. Cohen
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
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Sang S, Pan X, Chen Z, Zeng F, Pan S, Liu H, Jin L, Fei G, Wang C, Ren S, Jiao F, Bao W, Zhou W, Guan Y, Zhang Y, Shi H, Wang Y, Yu X, Wang Y, Zhong C. Thiamine diphosphate reduction strongly correlates with brain glucose hypometabolism in Alzheimer's disease, whereas amyloid deposition does not. ALZHEIMERS RESEARCH & THERAPY 2018; 10:26. [PMID: 29490669 PMCID: PMC5831864 DOI: 10.1186/s13195-018-0354-2] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2017] [Accepted: 02/05/2018] [Indexed: 01/08/2023]
Abstract
Background The underlying mechanism of brain glucose hypometabolism, an invariant neurodegenerative feature that tightly correlates with cognitive impairment and disease progression of Alzheimer’s disease (AD), remains elusive. Methods Positron emission tomography with 2-[18F]fluoro-2-deoxy-d-glucose (FDG-PET) was used to evaluate brain glucose metabolism, presented as the rate of 2-[18F]fluoro-2-deoxy-d-glucose standardized uptake value ratio (FDG SUVR) in patients with AD or control subjects and in mice with or without thiamine deficiency induced by a thiamine-deprived diet. Brain amyloid-β (Aβ) deposition in patients with clinically diagnosed AD was quantified by performing assays using 11C-Pittsburgh compound B PET. The levels of thiamine metabolites in blood samples of patients with AD and control subjects, as well as in blood and brain samples of mice, were detected by high-performance liquid chromatography with fluorescence detection. Results FDG SUVRs in frontal, temporal, and parietal cortices of patients with AD were closely correlated with the levels of blood thiamine diphosphate (TDP) and cognitive abilities, but not with brain Aβ deposition. Mice on a thiamine-deprived diet manifested a significant decline of FDG SUVRs in multiple brain regions as compared with those in control mice, with magnitudes highly correlating with both brain and blood TDP levels. There were no significant differences in the changes of FDG SUVRs in observed brain regions between amyloid precursor protein/presenilin-1 and wild-type mice following thiamine deficiency. Conclusions We demonstrate, for the first time to our knowledge, in vivo that TDP reduction strongly correlates with brain glucose hypometabolism, whereas amyloid deposition does not. Our study provides new insight into the pathogenesis and therapeutic strategy for AD. Electronic supplementary material The online version of this article (10.1186/s13195-018-0354-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Shaoming Sang
- Department of Neurology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.,Institutes of Brain Science & Collaborative Innovation Center for Brain Science, State Key Laboratory of Medical Neurobiology, Fudan University, Room 1105, Mingdao Building, 138 Yixueyuan Road, Shanghai, 200032, China
| | - Xiaoli Pan
- Department of Neurology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.,Institutes of Brain Science & Collaborative Innovation Center for Brain Science, State Key Laboratory of Medical Neurobiology, Fudan University, Room 1105, Mingdao Building, 138 Yixueyuan Road, Shanghai, 200032, China
| | - Zhichun Chen
- Department of Neurology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.,Institutes of Brain Science & Collaborative Innovation Center for Brain Science, State Key Laboratory of Medical Neurobiology, Fudan University, Room 1105, Mingdao Building, 138 Yixueyuan Road, Shanghai, 200032, China
| | - Fan Zeng
- Department of Neurology, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Shumei Pan
- Department of Neurology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.,Institutes of Brain Science & Collaborative Innovation Center for Brain Science, State Key Laboratory of Medical Neurobiology, Fudan University, Room 1105, Mingdao Building, 138 Yixueyuan Road, Shanghai, 200032, China
| | - Huimin Liu
- Department of Neurology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.,Institutes of Brain Science & Collaborative Innovation Center for Brain Science, State Key Laboratory of Medical Neurobiology, Fudan University, Room 1105, Mingdao Building, 138 Yixueyuan Road, Shanghai, 200032, China
| | - Lirong Jin
- Department of Neurology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.,Institutes of Brain Science & Collaborative Innovation Center for Brain Science, State Key Laboratory of Medical Neurobiology, Fudan University, Room 1105, Mingdao Building, 138 Yixueyuan Road, Shanghai, 200032, China
| | - Guoqiang Fei
- Department of Neurology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.,Institutes of Brain Science & Collaborative Innovation Center for Brain Science, State Key Laboratory of Medical Neurobiology, Fudan University, Room 1105, Mingdao Building, 138 Yixueyuan Road, Shanghai, 200032, China
| | - Changpeng Wang
- Department of Neurology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.,Institutes of Brain Science & Collaborative Innovation Center for Brain Science, State Key Laboratory of Medical Neurobiology, Fudan University, Room 1105, Mingdao Building, 138 Yixueyuan Road, Shanghai, 200032, China
| | - Shuhua Ren
- PET Center, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Fangyang Jiao
- PET Center, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Weiqi Bao
- PET Center, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Weiyan Zhou
- PET Center, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Yihui Guan
- PET Center, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Yiqiu Zhang
- Department of Nuclear Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Hongcheng Shi
- Department of Nuclear Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Yanjiang Wang
- Department of Neurology, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Xiang Yu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yun Wang
- Department of Neurology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China. .,Institutes of Brain Science & Collaborative Innovation Center for Brain Science, State Key Laboratory of Medical Neurobiology, Fudan University, Room 1105, Mingdao Building, 138 Yixueyuan Road, Shanghai, 200032, China.
| | - Chunjiu Zhong
- Department of Neurology, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Shanghai, 200032, China. .,Institutes of Brain Science & Collaborative Innovation Center for Brain Science, State Key Laboratory of Medical Neurobiology, Fudan University, Room 1105, Mingdao Building, 138 Yixueyuan Road, Shanghai, 200032, China.
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49
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Lao PJ, Handen BL, Betthauser TJ, Mihaila I, Hartley SL, Cohen AD, Tudorascu DL, Bulova PD, Lopresti BJ, Tumuluru RV, Murali D, Mathis CA, Barnhart TE, Stone CK, Price JC, Devenny DA, Johnson SC, Klunk WE, Christian BT. Alzheimer-Like Pattern of Hypometabolism Emerges with Elevated Amyloid-β Burden in Down Syndrome. J Alzheimers Dis 2018; 61:631-644. [PMID: 29254096 PMCID: PMC5994924 DOI: 10.3233/jad-170720] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
BACKGROUND The Down syndrome (DS) population is genetically predisposed to amyloid-β protein precursor overproduction and Alzheimer's disease (AD). OBJECTIVE The temporal ordering and spatial association between amyloid-β, glucose metabolism, and gray matter (GM) volume in the DS population can provide insight into those associations in the more common sporadic AD. METHODS Twenty-four adults (13 male, 11 female; 39±7 years) with DS underwent [11C]PiB, [18F]FDG, and volumetric MRI scans. Voxel-wise associations between PiB SUVR, FDG SUVR, and GM volume were investigated, with and without individual adjustments for variables of interest. RESULTS Positive associations of PiB and age were widespread throughout the neocortex and striatum. Negative associations of FDG and age (frontal, parietal, and temporal cortex) and of GM volume and age (frontal and insular cortex) were observed. PiB and FDG were negatively associated in parietal cortex, after adjustment for GM volume. CONCLUSIONS In adults with DS, early amyloid-β accumulation in the striatum is divergent from sporadic AD; however, despite the early striatal amyloid-β, glucose hypometabolism was confined to the typical AD-associated regions, which occurs similarly in autosomal dominant AD. Importantly, the glucose hypometabolism was not explained solely by increased partial volume effect due to GM volume reductions.
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Affiliation(s)
- Patrick J. Lao
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA
- University of Wisconsin-Madison, Waisman Center, Madison, WI, USA
| | - Ben L. Handen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Pediatrics, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Instruction and Learning, University of Pittsburgh, Pittsburgh, PA, USA
| | - Tobey J. Betthauser
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA
- University of Wisconsin-Madison, Waisman Center, Madison, WI, USA
| | - Iulia Mihaila
- University of Wisconsin-Madison, Waisman Center, Madison, WI, USA
- Department of Human Development and Family Studies, University of Wisconsin-Madison, Madison, WI, USA
| | - Sigan L. Hartley
- University of Wisconsin-Madison, Waisman Center, Madison, WI, USA
- Department of Human Development and Family Studies, University of Wisconsin-Madison, Madison, WI, USA
| | - Annie D. Cohen
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Dana L. Tudorascu
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Internal Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Biostatistics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Peter D. Bulova
- Department of Internal Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Brian J. Lopresti
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Dhanabalan Murali
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA
- University of Wisconsin-Madison, Waisman Center, Madison, WI, USA
| | - Chester A. Mathis
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Todd E. Barnhart
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA
| | - Charles K. Stone
- Department of Cardiovascular Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Julie C. Price
- Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
| | - Darlynne A. Devenny
- New York State Institute for Research in Developmental Disabilities, Staten Island, NY, USA
| | - Sterling C. Johnson
- Department of Medicine-Geriatrics, University of Wisconsin-Madison, Madison, WI, USA
| | - William E. Klunk
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Bradley T. Christian
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, USA
- University of Wisconsin-Madison, Waisman Center, Madison, WI, USA
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
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50
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Chen YJ, Nasrallah IM. Brain amyloid PET interpretation approaches: from visual assessment in the clinic to quantitative pharmacokinetic modeling. Clin Transl Imaging 2017. [DOI: 10.1007/s40336-017-0257-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
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