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Vanderlinden G, Vandenberghe R, Vandenbulcke M, Van Laere K. The Current Role of Tau PET Imaging in Neurodegeneration. Semin Nucl Med 2025:S0001-2998(25)00031-5. [PMID: 40263023 DOI: 10.1053/j.semnuclmed.2025.03.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2025] [Accepted: 03/19/2025] [Indexed: 04/24/2025]
Abstract
Neurodegenerative tauopathies are characterized by the pathological hyperphosphorylation of tau proteins that subsequently form aggregates. Tau PET tracers with affinity to bind these pathological tau aggregates have been developed to measure disease progression and to support therapeutic drug development. In this review, we summarize the pathophysiology of tau throughout the range of neurodegenerative tauopathies. We outline the available first- and second-generation tau PET tracers, with a focus on new tau PET tracer developments, and discuss the quantification of tau PET images. Next, we summarize how tau PET relates to cerebrospinal fluid and plasma tau biomarkers. Finally, we review the current recommendations on the clinical use of tau PET versus fluid tau biomarkers in diagnosis, prognosis and treatment development.
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Affiliation(s)
- Greet Vanderlinden
- Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - Rik Vandenberghe
- Department of Neurology, University Hospitals UZ Leuven, Leuven, Belgium; Laboratory for Cognitive Neurology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - Mathieu Vandenbulcke
- Research Group Psychiatry, Leuven Brain Institute, KU Leuven, Leuven, Belgium; Department of Geriatric Psychiatry, University Hospitals UZ Leuven, Leuven, Belgium
| | - Koen Van Laere
- Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, Leuven Brain Institute, KU Leuven, Leuven, Belgium; Division of Nuclear Medicine, University Hospitals UZ Leuven, Leuven, Belgium.
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Boccalini C, Peretti DE, Scheffler M, Mu L, Griffa A, Testart N, Allali G, Prior JO, Ashton NJ, Zetterberg H, Blennow K, Frisoni GB, Garibotto V. Sex differences in the association of Alzheimer's disease biomarkers and cognition in a multicenter memory clinic study. Alzheimers Res Ther 2025; 17:46. [PMID: 39966925 PMCID: PMC11837373 DOI: 10.1186/s13195-025-01684-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2024] [Accepted: 01/25/2025] [Indexed: 02/20/2025]
Abstract
BACKGROUND This study investigated sex differences in the associations between Alzheimer's disease (AD) biomarkers, cognitive performance, and decline in memory clinic settings. METHODS 249 participants (females/males:123/126), who underwent tau-PET, amyloid-PET, structural MRI, and plasma glial fibrillary acidic protein (GFAP) measurement were included from Geneva and Lausanne Memory Clinics. Mann-Whitney U tests investigated sex differences in clinical and biomarker data. Linear regression models estimated the moderating effect of sex on the relationship between biomarkers and cognitive performance and decline. Sex differences in cognitive decline were further evaluated using longitudinal linear mixed-effect models with three-way interaction effects. RESULTS Women and men present similar clinical features, amyloid, and neurodegeneration. Women had higher tau load and plasma levels of GFAP than men (p < 0.05). Tau associations with amyloid (standardized β = 0.54,p < 0.001), neurodegeneration (standardized β=-0.44,p < 0.001), and cognition (standardized β=-0.48,p < 0.001) were moderated by a significant interaction with sex. Specifically, the association between amyloid and tau was stronger among women than men (standardized β=-0.19,p = 0.047), whereas the associations between tau and cognition and between tau and neurodegeneration were stronger among men than in women (standardized β=-0.76,p = 0.001 and standardized β=-0.56,p = 0.044). Women exhibited faster cognitive decline than men in the presence of severe cortical thinning (p < 0.001). CONCLUSION Women showed higher tau load and stronger association between amyloid and tau than men. In individuals with high tau burden, men exhibited greater neurodegeneration and cognitive impairment than women. These findings support that sex differences may impact tau deposition through an upstream interplay with amyloid, leading to downstream effects on neurodegeneration and cognitive outcomes.
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Affiliation(s)
- Cecilia Boccalini
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Faculty of Medicine, Geneva University Neurocenter, University of Geneva, Rue Gabrielle-Perret-Gentil 4, Geneva, CH-1205, Switzerland
| | - Debora Elisa Peretti
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Faculty of Medicine, Geneva University Neurocenter, University of Geneva, Rue Gabrielle-Perret-Gentil 4, Geneva, CH-1205, Switzerland
| | - Max Scheffler
- Division of Radiology, Geneva University Hospitals, Rue Gabrielle-Perret-Gentil 4, Geneva, CH-1205, Switzerland
| | - Linjing Mu
- Institute of Pharmaceutical Sciences, ETH Zurich, Vladimir-Prelog-Weg 1-5/10, Zurich, 8049, Switzerland
| | - Alessandra Griffa
- Leenaards Memory Center, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Chem. de Mont-Paisible 16, Lausanne, 1011, Switzerland
- Medical Image Processing Laboratory, Neuro-X Institute, École Polytechnique Fédérale De Lausanne- EPFL, Campus Biotech H4 Chemin des Mines 9, Geneva, CH-1202, Switzerland
| | - Nathalie Testart
- Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Rue du Bugnon 46, Lausanne, 1005, Switzerland
| | - Gilles Allali
- Leenaards Memory Center, Department of Clinical Neurosciences, Lausanne University Hospital and University of Lausanne, Chem. de Mont-Paisible 16, Lausanne, 1011, Switzerland
| | - John O Prior
- Nuclear Medicine and Molecular Imaging, Lausanne University Hospital, Rue du Bugnon 46, Lausanne, 1005, Switzerland
| | - Nicholas J Ashton
- Centre for Age-Related Medicine, Stavanger University Hospital, Armauer Hansens vei 30, Stavanger, 4011, Norway
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Wallinsgatan 6, Mölndal, S-431 80, Sweden
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, Maurice Wohl Clinical Neuroscience Institute, London, SE5 9RX, UK
- UK NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London & Maudsley NHS Foundation, London, SE5 8AF, UK
| | - Henrik Zetterberg
- UK NIHR Biomedical Research Centre for Mental Health & Biomedical Research Unit for Dementia at South London & Maudsley NHS Foundation, London, SE5 8AF, UK
- UK Dementia Research Institute at UCL, London, WC1E 6BT, UK
- UK Department of Neurodegenerative Disease, UCL Institute of Neurology, London, WC1N 3BG, UK
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Klin Neurokemi Lab Hus V3, SU/Mölndals sjukhus, Mölndal S-431 80, Gothenburg, Sweden
- Hong Kong Centre for Neurodegenerative Diseases, Clear Water Bay, Hong Kong Units, Hong Kong, 1501-1502, 1512-1518, China
- Wisconsin Alzheimer's Disease Research Centre, University of Wisconsin, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Wallinsgatan 6, Mölndal, S-431 80, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Klin Neurokemi Lab Hus V3, SU/Mölndals sjukhus, Mölndal S-431 80, Gothenburg, Sweden
- Pitié Salpêtrière Hospital, Paris Brain Institute, ICM, Sorbonne University, 47 Bd de l'Hôpital, Paris, 75013, France
- Neurodegenerative Disorder Research Centre, Division of Life Sciences and Medicine, Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei, 230001, China
| | - Giovanni B Frisoni
- Geneva Memory Center, Geneva University Hospitals, Rue Gabrielle-Perret-Gentil 4, Geneva, CH-1205, Switzerland
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Faculty of Medicine, Geneva University Neurocenter, University of Geneva, Rue Gabrielle-Perret-Gentil 4, Geneva, CH-1205, Switzerland.
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Rue Gabrielle-Perret-Gentil 4, Geneva, CH-1205, Switzerland.
- CIBM Center for Biomedical Imaging, EPFL AVP CP CIBM Station 6, Lausanne, 1015, Switzerland.
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Cacciaglia R, Falcón C, Benavides GS, Brugulat‐Serrat A, Alomà MM, Calvet MS, Molinuevo JL, Fauria K, Minguillón C, Kollmorgen G, Quijano‐Rubio C, Blennow K, Zetterberg H, Lorenzini L, Wink AM, Ingala S, Barkhof F, Ritchie CW, Gispert JD. Soluble Aβ pathology predicts neurodegeneration and cognitive decline independently on p-tau in the earliest Alzheimer's continuum: Evidence across two independent cohorts. Alzheimers Dement 2025; 21:e14415. [PMID: 39898436 PMCID: PMC11848178 DOI: 10.1002/alz.14415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Revised: 10/07/2024] [Accepted: 10/27/2024] [Indexed: 02/04/2025]
Abstract
INTRODUCTION Identifying the link between early Alzheimer's disease (AD) pathological changes and neurodegeneration in asymptomatic individuals may lead to the discovery of preventive strategies. We assessed longitudinal brain atrophy and cognitive decline as a function of cerebrospinal fluid (CSF) AD biomarkers in two independent cohorts of cognitively unimpaired (CU) individuals. METHODS We used longitudinal voxel-based morphometry (VBM) in combination with hippocampal subfield segmentation. Changes in neuroimaging and cognitive variables were inspected using general linear models (GLMs) adjusting by age, sex, apolipoprotein E (APOE) status, follow-up time, and years of education. RESULTS In both cohorts, baseline CSF amyloid beta (Aβ) biomarkers significantly predicted medial temporal lobe (MTL) atrophy rates and episodic memory (EM) decline independently of CSF phosphorylated tau (p-tau). DISCUSSION Our data suggest that soluble Aβ dyshomeostasis triggers MTL longitudinal atrophy and EM decline independently of CSF p-tau. Our data underscore the need for secondary preventive strategies at the earliest stages of the AD pathological cascade. HIGHLIGHTS We assessed brain atrophy and cognitive decline in asymptomatic individuals. Aβ biomarkers predicted MTL atrophy independently of p-tau. Our results underscore the importance of undertaking Alzheimer's preclinical trials.
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Grants
- #ALFGBG-715986 the Swedish state under the agreement between the Swedish government and the County Councils, the Avtal om Läkarutbildning och Forskning (ALF)-agreement
- #RDAPB-201809-2016615 the Alzheimer Drug Discovery Foundation (ADDF), USA
- #AF-968270 the Swedish Alzheimer Foundation
- JPND2021-00694 the European Union Joint Programme - Neurodegenerative Disease Research
- Project "PI19/00155" European Union's Horizon 2020 Research and Innovation Programme (Grant agreement No. 948677)
- No. 101053962 the European Union's Horizon Europe Research and Innovation Programme under Grant Agreement
- #FO2017-0243 Hjärnfonden, Sweden
- ZEN-21-848495 the Alzheimer's Association 2021 Zenith Award
- #2018-02532 HZ is a Wallenberg Scholar supported by grants from the Swedish Research Council
- MSC receives funding from the European Research Council (ERC)
- #ALZ2022-0006 Hjärnfonden, Sweden
- #AF-939721 the Swedish Alzheimer Foundation
- the European Union Next Generation EU/Plan de Recuperación
- #ADSF-21-831377-C the AD Strategic Fund and the Alzheimer's Association
- MCIN/AEI/10.13039/501100011033/FEDER RC receives funding from "Ministerio de Ciencia, Innovación y Universidades - Agencia Estatal de Investigación"
- PID2021-125433OA-100 RC receives funding from "Ministerio de Ciencia, Innovación y Universidades - Agencia Estatal de Investigación"
- Transformación y Resiliencia (PRTR)
- LCF/BQ/PR21/11840004 the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 847648
- the Bluefield Project, the Olav Thon Foundation
- SG-23-1038904 QC the Alzheimer's Association 2022-2025
- R01 AG068398 NIA NIH HHS
- MCIN/AEI/10.13039/501100011033 RC receives funding from "Ministerio de Ciencia, Innovación y Universidades - Agencia Estatal de Investigación"
- #ALFGBG-965240 the Swedish state under the agreement between the Swedish government and the County Councils, the Avtal om Läkarutbildning och Forskning (ALF)-agreement
- #FO2022-0270 the Erling-Persson Family Foundation, Stiftelsen för Gamla Tjänarinnor, Hjärnfonden, Sweden
- the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 860197 (MIRIADE)
- JPND2019-466-236 the European Union Joint Program for Neurodegenerative Disorders
- #1R01AG068398-01 the National Institute of Health (NIH), USA
- UKDRI-1003 the UK Dementia Research Institute at University College London (UCL)
- #ALFGBG-71320 Swedish State Support for Clinical Research
- #201809-2016862 the Alzheimer Drug Discovery Foundation (ADDF), USA
- #ADSF-21-831376-C the AD Strategic Fund and the Alzheimer's Association
- #AF-930351 the Swedish Alzheimer Foundation
- #2017-00915 KB is supported by the Swedish Research Council
- ID 100010434 Instituto de Salud Carlos III (ISCIII) and co-funded by the European Union, and from a fellowship from "la Caixa" Foundation
- #ADSF-21-831381-C the AD Strategic Fund and the Alzheimer's Association
- RYC2021-031128-I RC receives funding from "Ministerio de Ciencia, Innovación y Universidades - Agencia Estatal de Investigación"
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Affiliation(s)
- Raffaele Cacciaglia
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall FoundationBarcelonaSpain
- Hospital del Mar Research InstituteBarcelonaSpain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES)MadridSpain
| | - Carles Falcón
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall FoundationBarcelonaSpain
- Hospital del Mar Research InstituteBarcelonaSpain
- Centro de Investigación Biomédica en Red de BioingenieríaBiomateriales y Nanomedicina (CIBERBBN)MadridSpain
| | - Gonzalo Sánchez Benavides
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall FoundationBarcelonaSpain
- Hospital del Mar Research InstituteBarcelonaSpain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES)MadridSpain
| | - Anna Brugulat‐Serrat
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall FoundationBarcelonaSpain
- Hospital del Mar Research InstituteBarcelonaSpain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES)MadridSpain
- Global Brain Health InstituteSan FranciscoCaliforniaUSA
| | - Marta Milà Alomà
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall FoundationBarcelonaSpain
- Northern California Institute for Research and EducationSan FranciscoCaliforniaUSA
| | - Marc Suárez Calvet
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall FoundationBarcelonaSpain
- Hospital del Mar Research InstituteBarcelonaSpain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES)MadridSpain
- Servei de NeurologiaHospital del MarBarcelonaSpain
| | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall FoundationBarcelonaSpain
- Present address:
Ottiliavej 9, 2500KøbenhavnDenmark
| | - Karine Fauria
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall FoundationBarcelonaSpain
- Hospital del Mar Research InstituteBarcelonaSpain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES)MadridSpain
| | - Carolina Minguillón
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall FoundationBarcelonaSpain
- Hospital del Mar Research InstituteBarcelonaSpain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES)MadridSpain
| | | | | | - Kaj Blennow
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologyThe Sahlgrenska Academy at the University of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
| | - Henrik Zetterberg
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologyThe Sahlgrenska Academy at the University of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- UK Dementia Research Institute at UCLLondonUK
- Department of Neurodegenerative DiseaseUCL Institute of NeurologyLondonUK
- Hong Kong Center for Neurodegenerative DiseasesHong KongChina
- Wisconsin Alzheimer's Disease Research CenterUniversity of Wisconsin School of Medicine and Public HealthUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Luigi Lorenzini
- Department of Radiology & Nuclear MedicineAmsterdam UMC, Vrije UniversiteitAmsterdamthe Netherlands
| | - Alle Meije Wink
- Department of Radiology & Nuclear MedicineAmsterdam UMC, Vrije UniversiteitAmsterdamthe Netherlands
| | - Silvia Ingala
- Department of Radiology & Nuclear MedicineAmsterdam UMC, Vrije UniversiteitAmsterdamthe Netherlands
| | - Frederik Barkhof
- Department of Radiology & Nuclear MedicineAmsterdam UMC, Vrije UniversiteitAmsterdamthe Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image ComputingUniversity College LondonLondonUK
| | - Craig W. Ritchie
- Edinburgh Dementia Prevention, Centre for Clinical Brain SciencesUniversity of EdinburghEdinburghScotlandUK
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall FoundationBarcelonaSpain
- Hospital del Mar Research InstituteBarcelonaSpain
- Centro de Investigación Biomédica en Red de BioingenieríaBiomateriales y Nanomedicina (CIBERBBN)MadridSpain
- Universitat Pompeu FabraBarcelonaSpain
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Pan F, Huang Q, Huang C, Lu Y, Cui L, Huang L, Guan Y, Xie F, Guo Q. Associations of hippocampal volumes, brain hypometabolism, and plasma NfL with amyloid, tau, and cognitive decline. Alzheimers Dement 2025; 21:e70005. [PMID: 39989286 PMCID: PMC11848211 DOI: 10.1002/alz.70005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2024] [Revised: 01/22/2025] [Accepted: 01/23/2025] [Indexed: 02/25/2025]
Abstract
INTRODUCTION Various indicators of neurodegeneration (N) are used in the assessment of neuronal injury in Alzheimer's disease (AD). The heterogeneity of such indicators is less clear. METHODS A total of 416 individuals with different cognitive statuses were recruited for this study. Differential associations of hippocampal volume (HV), 18F-fluorodeoxyglucose positron emission tomography (FDG PET) standardized uptake value ratios (SUVRs), and plasma neurofilament light chain (NfL) levels with amyloid beta (Aβ)-tau pathology and cognitive impairment were examined. RESULTS HV decreased early during the high Aβ burden but tau-negative stage. FDG PET SUVRs and plasma NfL levels notably changed at tau-positive stages. HV and plasma NfL correlated with cognitive scores in the early to middle stages, while FDG PET SUVRs aligned with cognitive decline from the middle to late stages. Hippocampal atrophy and inferior parietal hypometabolism increased the risk of cognitive impairment in A+T+, while adding NfL+ had no additional impact within the distinct A/T groups. DISCUSSION Different indicators of N have varying relationships to AD pathology and cognitive impairment. HIGHLIGHTS Hippocampal atrophy emerges early with a high amyloid beta burden and exacerbates during the tau-positive phase. Brain hypometabolism and elevated plasma neurofilament light chain (NfL) levels appear mainly in tau-positive stages. Hippocampal volume and plasma NfL levels correlate with cognitive decline in the early to middle stages, while 18F-fluorodeoxyglucose positron emission tomography standardized uptake value ratios in the middle to late stages. Hippocampal atrophy and inferior parietal hypometabolism raise the risk of cognitive impairment in amyloid/tau-positive individuals while adding NfL+ shows no additional effect.
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Affiliation(s)
- Feng‐Feng Pan
- Department of GerontologyShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Qi Huang
- PET CenterHuashan HospitalFudan UniversityShanghaiChina
| | - Chu‐Chung Huang
- Shanghai Key Laboratory of Brain Functional Genomics (Ministry of Education)Affiliated Mental Health Center (ECNU)School of Psychology and Cognitive ScienceEast China Normal UniversityShanghaiChina
| | - Yao Lu
- Department of GerontologyShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Liang Cui
- Department of GerontologyShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Lin Huang
- Department of GerontologyShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Yihui Guan
- PET CenterHuashan HospitalFudan UniversityShanghaiChina
| | - Fang Xie
- PET CenterHuashan HospitalFudan UniversityShanghaiChina
| | - Qi‐Hao Guo
- Department of GerontologyShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghaiChina
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Wisch JK, Petersen K, Millar PR, Abdelmoity O, Babulal GM, Meeker KL, Braskie MN, Yaffe K, Toga AW, O'Bryant S, Ances BM. Cross-Sectional Comparison of Structural MRI Markers of Impairment in a Diverse Cohort of Older Adults. Hum Brain Mapp 2025; 46:e70133. [PMID: 39868891 PMCID: PMC11770891 DOI: 10.1002/hbm.70133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2024] [Revised: 12/11/2024] [Accepted: 12/27/2024] [Indexed: 01/28/2025] Open
Abstract
Neurodegeneration is presumed to be the pathological process measure most proximal to clinical symptom onset in Alzheimer Disease (AD). Structural MRI is routinely collected in research and clinical trial settings. Several quantitative MRI-based measures of atrophy have been proposed, but their low correspondence with each other has been previously documented. The purpose of this study was to identify which commonly used structural MRI measure (hippocampal volume, cortical thickness in AD signature regions, or brain age gap [BAG]) had the best correspondence with the Clinical Dementia Rating (CDR) in an ethno-racially diverse sample. 2870 individuals recruited by the Healthy and Aging Brain Study-Health Disparities completed both structural MRI and CDR evaluation. Of these, 1887 individuals were matched on ethno-racial identity (Mexican American [MA], non-Hispanic Black [NHB], and non-Hispanic White [NHW]) and CDR (27% CDR > 0). We estimated brain age using two pipelines (DeepBrainNet, BrainAgeR) and then calculated BAG as the difference between the estimated brain age and chronological age. We also quantified their hippocampal volumes using HippoDeep and cortical thicknesses (both an AD-specific signature and average whole brain) using FreeSurfer. We used ordinal regression to evaluate associations between neuroimaging measures and CDR and to test whether these associations differed between ethno-racial groups. Higher BAG (pDeepBrainNet = 0.0002; pBrainAgeR = 0.00117) and lower hippocampal volume (p = 0.0015) and cortical thickness (p < 0.0001) were associated with worse clinical status (higher CDR). AD signature cortical thickness had the strongest relationship with CDR (AICDeepBrainNet = 2623, AICwhole cortex = 2588, AICBrainAgeR = 2533, AICHippocampus = 2293, AICSignature Cortical Thickness = 1903). The relationship between CDR and atrophy measures differed between ethno-racial groups for both BAG estimates and hippocampal volume, but not for cortical thickness. We interpret the lack of an interaction between ethno-racial identity and AD signature cortical thickness on CDR as evidence that cortical thickness effectively captures sources of disease-related atrophy that may differ across racial and ethnic groups. Cortical thickness had the strongest association with CDR. These results suggest that cortical thickness may be a more sensitive and generalizable marker of neurodegeneration than hippocampal volume or BAG in ethno-racially diverse cohorts.
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Affiliation(s)
- Julie K. Wisch
- Department of NeurologyWashington University in St. LouisSt. LouisMissouriUSA
| | - Kalen Petersen
- Department of NeurologyWashington University in St. LouisSt. LouisMissouriUSA
| | - Peter R. Millar
- Department of NeurologyWashington University in St. LouisSt. LouisMissouriUSA
| | - Omar Abdelmoity
- Danforth Undergraduate CampusWashington University in St. LouisSt. LouisMissouriUSA
| | - Ganesh M. Babulal
- Department of NeurologyWashington University in St. LouisSt. LouisMissouriUSA
| | - Karin L. Meeker
- Department of Family Medicine, Institute for Translational ResearchUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - Meredith N. Braskie
- Stevens Neuroimaging and Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Kristine Yaffe
- Weill Institute for NeurosciencesUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - Arthur W. Toga
- Stevens Neuroimaging and Informatics Institute, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Sid O'Bryant
- Department of Family Medicine, Institute for Translational ResearchUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - Beau M. Ances
- Department of NeurologyWashington University in St. LouisSt. LouisMissouriUSA
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Earnest T, Yang B, Kothapalli D, Sotiras A. Comprehensive evaluation of AT(N) imaging biomarkers for predicting cognition. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.11.25.24317943. [PMID: 39649612 PMCID: PMC11623732 DOI: 10.1101/2024.11.25.24317943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 12/11/2024]
Abstract
Background and Objectives Imaging biomarkers enable in vivo quantification of amyloid, tau, and neurogenerative pathologies that develop in Alzheimer's Disease (AD). Interest in imaging biomarkers has led to a wide variety of biomarker definitions, some of which potentially offer less predictive value than others. We aimed to assess how different operationalizations of AD imaging biomarkers affect prediction of cognition. Methods We included individuals from ADNI who underwent amyloid-PET ([18F]-Florbetapir), tau-PET ([18F]-Flortaucipir), and volumetric MRI imaging. We compiled a large collection of imaging biomarker definitions (42 in total) spanning different pathologies (amyloid, tau, neurodegeneration) and variable types (continuous, binary, non-binary categorical). Using cross-validation, we trained regression models to predict neuropsychological performance, both globally and across different subdomains (Phenotype Harmonization Consortium composites), using different combinations of biomarkers. We also compared these biomarker models to support vector machines (SVMs) trained to predict cognition directly from imaging regions of interest. In a subsample of individuals with CSF biomarker readouts, we repeated experiments comparing the accuracy of models using imaging and fluid biomarkers. Additional analyses tested the predictive strength of imaging biomarkers when limited to specific clinical stages of disease (cognitive unimpaired vs. impaired) and when modeling longitudinal cognitive change. Results Our sample included 490 people (247 female) with a mix of no impairment (n=288), mild impairment (n=163), and dementia (n=39). While almost all biomarkers tested were predictive of cognitive performance, we observed substantial variability in accuracy, even for measures of the same pathology. Tau biomarkers were the single most accurate single predictors, though combination of biomarkers spanning multiple pathologies were more accurate overall. SVM models were generally more accurate than models using traditional biomarkers. Incorporating continuous or non-binary categorical biomarkers was beneficial only for tau and neurodegeneration, but not amyloid. Patterns of results were largely consistent when considering different clinical stages of disease, neuropsychological domains, and longitudinal cognition. In the CSF subsample (n=246), imaging biomarkers strongly outperformed CSF versions for cognitive prediction. Discussion We demonstrated that different imaging biomarker definitions can lead to variability in downstream predictive tasks. Researchers should consider how their biomarker operationalizations may help or hinder the assessment of disease severity.
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Affiliation(s)
- Tom Earnest
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in St Louis; 4525 Scott Ave, Saint Louis, MO 63110
| | - Braden Yang
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in St Louis; 4525 Scott Ave, Saint Louis, MO 63110
| | - Deydeep Kothapalli
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in St Louis; 4525 Scott Ave, Saint Louis, MO 63110
| | - Aristeidis Sotiras
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in St Louis; 4525 Scott Ave, Saint Louis, MO 63110
- Institute for Informatics, Data Science & Biostatistics, Washington University School of Medicine in St Louis; 660 S. Euclid Ave, Campus Box 8132, Saint Louis, MO 63110
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Kovacech B, Cullen NC, Novak P, Hanes J, Kontsekova E, Katina S, Parrak V, Fresser M, Vanbrabant J, Feldman HH, Winblad B, Stoops E, Vanmechelen E, Zilka N. Post hoc analysis of ADAMANT, a phase 2 clinical trial of active tau immunotherapy with AADvac1 in patients with Alzheimer's disease, positive for plasma p-tau217. Alzheimers Res Ther 2024; 16:254. [PMID: 39580468 PMCID: PMC11585249 DOI: 10.1186/s13195-024-01620-7] [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: 09/13/2024] [Accepted: 11/11/2024] [Indexed: 11/25/2024]
Abstract
BACKGROUND The spread of tau pathology closely correlates with the disease course and cognitive decline in Alzheimer's disease (AD). Tau-targeting immunotherapies are being developed to stop the spread of tau pathology and thus halt disease progression. In this post hoc analysis of the ADAMANT clinical trial, we examined the performance of AADvac1, an active immunotherapy targeting the microtubule-binding region (MTBR) of tau, in a subgroup of participants with elevated plasma p-tau217, indicating AD-related neuropathological changes. METHODS ADAMANT was a 24-month, randomized, placebo-controlled, parallel-group, double-blinded, multicenter, phase 2 clinical trial in subjects with mild AD. The trial participants were randomized 3:2 to receive six doses of AADvac1 or placebo at 4-week intervals, followed by five booster doses at 14-week intervals. The primary outcome was safety. The secondary outcomes were the Clinical Dementia Rating-Sum of Boxes (CDR-SB), the Alzheimer's Disease Cooperative Study - Activities of Daily Living score for Mild Cognitive Impairment 18-item version (ADCS-ADL-MCI-18), and immunogenicity. Volumetric MRI, plasma neurofilament light (NfL), and glial fibrillary acidic protein (GFAP) were exploratory outcomes. The inclusion criterion for this post-hoc analysis was a baseline plasma p-tau217 level above the cutoff for AD. RESULTS Among 196 ADAMANT participants, 137 were positive for plasma p-tau217 (mean age 71.4 years, 59% women). AADvac1 was safe and well tolerated in this subgroup. AADvac1 reduced the rate of accumulation of log-plasma NfL by 56% and that of GFAP by 73%. The treatment differences in the CDR-SB and ADCS-ADL-MCI-18 scores favored AADvac1 but were not statistically significant. AADvac1 had no effect on whole-brain volume but nonsignificantly reduced the loss of brain cortical tissue in several regions. Importantly, the impact on the study outcomes was more pronounced in participants with higher anti-tau antibody levels. CONCLUSIONS These results suggest that AADvac1 tau immunotherapy can reduce plasma biomarkers of neurodegeneration and neuroinflammation. These findings and possible observations on brain atrophy and cognition are hypothesis-generating and warrant further evaluation in a larger clinical trial. TRIAL REGISTRATION EudraCT 2015-000630-30 (primary) and NCT02579252.
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Affiliation(s)
- Branislav Kovacech
- Axon Neuroscience R&D Services SE, Dvorakovo Nabr. 10, 81102, Bratislava, Slovakia.
| | - Nicholas C Cullen
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Clinical Research Centre, Jan Waldenströms Gata 35, 202 13, Malmö, Sweden
| | - Petr Novak
- Axon Neuroscience R&D Services SE, Dvorakovo Nabr. 10, 81102, Bratislava, Slovakia
| | - Jozef Hanes
- Axon Neuroscience R&D Services SE, Dvorakovo Nabr. 10, 81102, Bratislava, Slovakia
| | - Eva Kontsekova
- Axon Neuroscience R&D Services SE, Dvorakovo Nabr. 10, 81102 Bratislava, Slovakia and Institute of Neuroimmunology, Slovak Academy of Sciences, Dubravska Cesta 9, Bratislava, 84510, Slovakia
| | - Stanislav Katina
- Department of Mathematics and Statistics, Axon Neuroscience R&D Services SE, Bratislava, Slovakia, and (current) Masaryk University, Kotlářská 267/2, Brno, 611 37, Czech Republic
| | - Vojtech Parrak
- Axon Neuroscience R&D Services SE, Dvorakovo Nabr. 10, 81102, Bratislava, Slovakia
| | - Michal Fresser
- Axon Neuroscience SE, 4 Arch. Makariou & Kalogreon, 6016, Larnaca, Cyprus
| | | | - Howard H Feldman
- Department of Neurosciences, Alzheimer's Disease Cooperative Study, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA
| | - Bengt Winblad
- Division of Neurogeriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, BioClinicum, 171 64, Solna, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, 141 86, Stockholm, Sweden
| | - Erik Stoops
- ADx NeuroSciences NV, Technologiepark 6, 9052, Ghent, Belgium
| | | | - Norbert Zilka
- Axon Neuroscience R&D Services SE, Dvorakovo Nabr. 10, 81102, Bratislava, Slovakia.
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8
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Puig-Pijoan A, García-Escobar G, Fernández-Lebrero A, Manero-Borràs RM, Sánchez-Benavides G, Navalpotro-Gómez I, Cascales Lahoz D, Suárez-Calvet M, Grau-Rivera O, Boltes Alandí A, Pont-Sunyer MC, Ortiz-Gil J, Carrillo-Molina S, López-Villegas D, Abellán-Vidal MT, Martínez-Casamitjana MI, Hernández-Sánchez JJ, Peña-Casanova J, Roquer J, Padrós Fluvià A, Puente-Périz V. The CORCOBIA study: Cut-off points of Alzheimer's disease CSF biomarkers in a clinical cohort. Neurologia 2024; 39:756-765. [PMID: 35961506 DOI: 10.1016/j.nrleng.2022.05.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 05/24/2022] [Indexed: 10/15/2022] Open
Abstract
INTRODUCTION The analysis of the core biomarkers of Alzheimer's Disease (AD) in the cerebrospinal fluid (CSF) is recommended in the clinical units where it is available. Because of the absence of universal validated values, the determination of specific cut-off points for each center and its population is recommended. The main objective of the CORCOBIA study was to determine the cut-off points of core AD CSF biomarkers for several centers (Parc de Salut Mar, Barcelona and Hospital General de Granollers), which work with the same reference laboratory (Laboratori de Referència de Catalunya). METHODS Prospective study including cognitively unimpaired individuals (CU, n = 42), subjects with amnestic mild cognitive impairment (aMCI, n = 35) and patients with dementia due to Alzheimer's Disease (AD, n = 48), in whom clinical and neuropsychological assessment, neuroimaging, APOE genotyping and lumbar puncture to analyse amyloid beta peptides (Aβ42, Aβ40), total tau (tTau) and phosphorylated Tau (pTau181) using the Lumipulse G600II (Fujirebio) was performed. The values of sensitivity (SE), specificity (SP), predictive values and area under the curve (AUC) were calculated, determining the cut-off point according to the Youden index by comparing the CU and AD groups. RESULTS The resulting cut-offs and their AUC were the following: Aβ42 750 pg/mL (AUC 0.809); Aβ42/Aβ40 0.062 (AUC 0.78); pTau181 69.85 pg/mL (AUC 0.81); tTau 522.0 pg/mL (AUC 0.79); Aβ42/tTau 1.76 (AUC 0.86); Aβ42/pTau181 10.25 (AUC 0.86). CONCLUSIONS The determination of cut-off points of core AD CSF biomarkers for the participating centers allows a better diagnostic accuracy. The ratio CSF Aβ42/pTau181 shows the highest AUC and better balance between sensitivity and specificity.
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Affiliation(s)
- A Puig-Pijoan
- Unitat de Deteriorament Cognitiu i Transtorns del Moviment, Servei de Neurologia, Hospital del Mar, Parc de Salut Mar, Barcelona, Spain; Farmacologia Integrada i Neurociència de Sistemes, Programa de Neurociències, Institut Hospital del Mar d'Investigacions Mèdiques (IMIM), Barcelona, Spain.
| | - G García-Escobar
- Farmacologia Integrada i Neurociència de Sistemes, Programa de Neurociències, Institut Hospital del Mar d'Investigacions Mèdiques (IMIM), Barcelona, Spain
| | - A Fernández-Lebrero
- Unitat de Deteriorament Cognitiu i Transtorns del Moviment, Servei de Neurologia, Hospital del Mar, Parc de Salut Mar, Barcelona, Spain; Farmacologia Integrada i Neurociència de Sistemes, Programa de Neurociències, Institut Hospital del Mar d'Investigacions Mèdiques (IMIM), Barcelona, Spain; Barcelonaβeta Brain Research Center (BBRC), Fundació Pasqual Maragall, Barcelona, Spain
| | - R M Manero-Borràs
- Unitat de Deteriorament Cognitiu i Transtorns del Moviment, Servei de Neurologia, Hospital del Mar, Parc de Salut Mar, Barcelona, Spain; Farmacologia Integrada i Neurociència de Sistemes, Programa de Neurociències, Institut Hospital del Mar d'Investigacions Mèdiques (IMIM), Barcelona, Spain
| | - G Sánchez-Benavides
- Barcelonaβeta Brain Research Center (BBRC), Fundació Pasqual Maragall, Barcelona, Spain; Institut Hospital del Mar d'Investigacions Mèdiques (IMIM), Hospital del Mar, Barcelona, Spain
| | - I Navalpotro-Gómez
- Unitat de Deteriorament Cognitiu i Transtorns del Moviment, Servei de Neurologia, Hospital del Mar, Parc de Salut Mar, Barcelona, Spain; Farmacologia Integrada i Neurociència de Sistemes, Programa de Neurociències, Institut Hospital del Mar d'Investigacions Mèdiques (IMIM), Barcelona, Spain; Barcelonaβeta Brain Research Center (BBRC), Fundació Pasqual Maragall, Barcelona, Spain
| | - D Cascales Lahoz
- Unitat de Deteriorament Cognitiu i Transtorns del Moviment, Servei de Neurologia, Hospital del Mar, Parc de Salut Mar, Barcelona, Spain
| | - M Suárez-Calvet
- Unitat de Deteriorament Cognitiu i Transtorns del Moviment, Servei de Neurologia, Hospital del Mar, Parc de Salut Mar, Barcelona, Spain; Barcelonaβeta Brain Research Center (BBRC), Fundació Pasqual Maragall, Barcelona, Spain; Institut Hospital del Mar d'Investigacions Mèdiques (IMIM), Hospital del Mar, Barcelona, Spain; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - O Grau-Rivera
- Unitat de Deteriorament Cognitiu i Transtorns del Moviment, Servei de Neurologia, Hospital del Mar, Parc de Salut Mar, Barcelona, Spain; Barcelonaβeta Brain Research Center (BBRC), Fundació Pasqual Maragall, Barcelona, Spain; Institut Hospital del Mar d'Investigacions Mèdiques (IMIM), Hospital del Mar, Barcelona, Spain; Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - A Boltes Alandí
- Servei de Neurologia, Hospital General de Granollers, Granollers, Barcelona, Spain
| | - M C Pont-Sunyer
- Servei de Neurologia, Hospital General de Granollers, Granollers, Barcelona, Spain
| | - J Ortiz-Gil
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain; Unitat de Psicologia, Hospital General de Granollers, Granollers, Barcelona, Spain; Fundación para la Investigación y Docencia Maria Angustias Gimenez (FIDMAG), Sant Boi de Llobregat, Barcelona, Spain
| | - S Carrillo-Molina
- Servei de Neurologia, Hospital General de Granollers, Granollers, Barcelona, Spain; Unitat de Psicologia, Hospital General de Granollers, Granollers, Barcelona, Spain
| | - D López-Villegas
- Institut Hospital del Mar d'Investigacions Mèdiques (IMIM), Hospital del Mar, Barcelona, Spain; Centre Emili Mira, Institut de Neuropsiquiatria i Addiccions (INAD), Parc de Salut Mar, Santa Coloma de Gramenet, Barcelona, Spain
| | - M T Abellán-Vidal
- Centre Emili Mira, Institut de Neuropsiquiatria i Addiccions (INAD), Parc de Salut Mar, Santa Coloma de Gramenet, Barcelona, Spain
| | - M I Martínez-Casamitjana
- Centre Emili Mira, Institut de Neuropsiquiatria i Addiccions (INAD), Parc de Salut Mar, Santa Coloma de Gramenet, Barcelona, Spain
| | | | - J Peña-Casanova
- Farmacologia Integrada i Neurociència de Sistemes, Programa de Neurociències, Institut Hospital del Mar d'Investigacions Mèdiques (IMIM), Barcelona, Spain
| | - J Roquer
- Unitat de Deteriorament Cognitiu i Transtorns del Moviment, Servei de Neurologia, Hospital del Mar, Parc de Salut Mar, Barcelona, Spain; Institut Hospital del Mar d'Investigacions Mèdiques (IMIM), Hospital del Mar, Barcelona, Spain
| | - A Padrós Fluvià
- Laboratori de Referència de Catalunya, Sant Boi de Llobregat, Barcelona, Spain
| | - V Puente-Périz
- Unitat de Deteriorament Cognitiu i Transtorns del Moviment, Servei de Neurologia, Hospital del Mar, Parc de Salut Mar, Barcelona, Spain; Farmacologia Integrada i Neurociència de Sistemes, Programa de Neurociències, Institut Hospital del Mar d'Investigacions Mèdiques (IMIM), Barcelona, Spain.
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Khan AF, Iturria-Medina Y. Beyond the usual suspects: multi-factorial computational models in the search for neurodegenerative disease mechanisms. Transl Psychiatry 2024; 14:386. [PMID: 39313512 PMCID: PMC11420368 DOI: 10.1038/s41398-024-03073-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 08/20/2024] [Accepted: 08/27/2024] [Indexed: 09/25/2024] Open
Abstract
From Alzheimer's disease to amyotrophic lateral sclerosis, the molecular cascades underlying neurodegenerative disorders remain poorly understood. The clinical view of neurodegeneration is confounded by symptomatic heterogeneity and mixed pathology in almost every patient. While the underlying physiological alterations originate, proliferate, and propagate potentially decades before symptomatic onset, the complexity and inaccessibility of the living brain limit direct observation over a patient's lifespan. Consequently, there is a critical need for robust computational methods to support the search for causal mechanisms of neurodegeneration by distinguishing pathogenic processes from consequential alterations, and inter-individual variability from intra-individual progression. Recently, promising advances have been made by data-driven spatiotemporal modeling of the brain, based on in vivo neuroimaging and biospecimen markers. These methods include disease progression models comparing the temporal evolution of various biomarkers, causal models linking interacting biological processes, network propagation models reproducing the spatial spreading of pathology, and biophysical models spanning cellular- to network-scale phenomena. In this review, we discuss various computational approaches for integrating cross-sectional, longitudinal, and multi-modal data, primarily from large observational neuroimaging studies, to understand (i) the temporal ordering of physiological alterations, i(i) their spatial relationships to the brain's molecular and cellular architecture, (iii) mechanistic interactions between biological processes, and (iv) the macroscopic effects of microscopic factors. We consider the extents to which computational models can evaluate mechanistic hypotheses, explore applications such as improving treatment selection, and discuss how model-informed insights can lay the groundwork for a pathobiological redefinition of neurodegenerative disorders.
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Affiliation(s)
- Ahmed Faraz Khan
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, Canada
- Ludmer Centre for Neuroinformatics & Mental Health, Montreal, Canada
| | - Yasser Iturria-Medina
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada.
- McConnell Brain Imaging Center, Montreal Neurological Institute, Montreal, Canada.
- Ludmer Centre for Neuroinformatics & Mental Health, Montreal, Canada.
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10
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Vilkaite G, Vogel J, Mattsson-Carlgren N. Integrating amyloid and tau imaging with proteomics and genomics in Alzheimer's disease. Cell Rep Med 2024; 5:101735. [PMID: 39293391 PMCID: PMC11525023 DOI: 10.1016/j.xcrm.2024.101735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 07/28/2024] [Accepted: 08/20/2024] [Indexed: 09/20/2024]
Abstract
Alzheimer's disease (AD) is the most common neurodegenerative disease and is characterized by the aggregation of β-amyloid (Aβ) and tau in the brain. Breakthroughs in disease-modifying treatments targeting Aβ bring new hope for the management of AD. But to effectively modify and someday even prevent AD, a better understanding is needed of the biological mechanisms that underlie and link Aβ and tau in AD. Developments of high-throughput omics, including genomics, proteomics, and transcriptomics, together with molecular imaging of Aβ and tau with positron emission tomography (PET), allow us to discover and understand the biological pathways that regulate the aggregation and spread of Aβ and tau in living humans. The field of integrated omics and PET studies of Aβ and tau in AD is growing rapidly. We here provide an update of this field, both in terms of biological insights and in terms of future clinical implications of integrated omics-molecular imaging studies.
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Affiliation(s)
- Gabriele Vilkaite
- Department of Clinical Sciences Malmö, SciLifeLab, Lund University, Lund, Sweden
| | - Jacob Vogel
- Department of Clinical Sciences Malmö, SciLifeLab, Lund University, Lund, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden; Department of Neurology, Skåne University Hospital, Lund University, Lund, Sweden; Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden.
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11
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Yoshioka H, Jin R, Hisaka A, Suzuki H. Disease progression modeling with temporal realignment: An emerging approach to deepen knowledge on chronic diseases. Pharmacol Ther 2024; 259:108655. [PMID: 38710372 DOI: 10.1016/j.pharmthera.2024.108655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 04/22/2024] [Accepted: 05/01/2024] [Indexed: 05/08/2024]
Abstract
The recent development of the first disease-modifying drug for Alzheimer's disease represents a major advancement in dementia treatment. Behind this breakthrough is a quarter century of research efforts to understand the disease not by a particular symptom at a given moment, but by long-term sequential changes in multiple biomarkers. Disease progression modeling with temporal realignment (DPM-TR) is an emerging computational approach proposed with this biomarker-based disease concept. By integrating short-term clinical observations of multiple disease biomarkers in a data-driven manner, DPM-TR provides a way to understand the progression of chronic diseases over decades and predict individual disease stages more accurately. DPM-TR has been developed primarily in the area of neurodegenerative diseases but has recently been extended to non-neurodegenerative diseases, including chronic obstructive pulmonary, autoimmune, and ophthalmologic diseases. This review focuses on opportunities for DPM-TR in clinical practice and drug development and discusses its current status and challenges.
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Affiliation(s)
- Hideki Yoshioka
- Office of Regulatory Science Research, Pharmaceuticals and Medical Devices Agency, Tokyo, Japan; Laboratory of Clinical Pharmacology and Pharmacometrics, Graduate School of Pharmaceutical Sciences, Chiba University, Chiba, Japan
| | - Ryota Jin
- Laboratory of Clinical Pharmacology and Pharmacometrics, Graduate School of Pharmaceutical Sciences, Chiba University, Chiba, Japan
| | - Akihiro Hisaka
- Laboratory of Clinical Pharmacology and Pharmacometrics, Graduate School of Pharmaceutical Sciences, Chiba University, Chiba, Japan.
| | - Hiroshi Suzuki
- Executive Director, Pharmaceuticals and Medical Devices Agency, Tokyo, Japan; Department of Pharmacy, The University of Tokyo Hospital, Faculty of Medicine, The University of Tokyo, Tokyo, Japan
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12
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Arnold SE, Hendrix S, Nicodemus‐Johnson J, Knowlton N, Williams VJ, Burns JM, Crane M, McManus AJ, Vaishnavi SN, Arvanitakis Z, Neugroschl J, Bell K, Trombetta BA, Carlyle BC, Kivisäkk P, Dodge HH, Tanzi RE, Yeramian PD, Leslie K. Biological effects of sodium phenylbutyrate and taurursodiol in Alzheimer's disease. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2024; 10:e12487. [PMID: 39131742 PMCID: PMC11310855 DOI: 10.1002/trc2.12487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Revised: 03/25/2024] [Accepted: 05/13/2024] [Indexed: 08/13/2024]
Abstract
INTRODUCTION Sodium phenylbutyrate and taurursodiol (PB and TURSO) is hypothesized to mitigate endoplasmic reticulum stress and mitochondrial dysfunction, two of many mechanisms implicated in Alzheimer's disease (AD) pathophysiology. METHODS The first-in-indication phase 2a PEGASUS trial was designed to gain insight into PB and TURSO effects on mechanistic targets of engagement and disease biology in AD. The primary clinical efficacy outcome was a global statistical test combining three endpoints relevant to disease trajectory (cognition [Mild/Moderate Alzheimer's Disease Composite Score], function [Functional Activities Questionnaire], and total hippocampal volume on magnetic resonance imaging). Secondary clinical outcomes included various cognitive, functional, and neuropsychiatric assessments. Cerebrospinal fluid (CSF) biomarkers spanning multiple pathophysiological pathways in AD were evaluated in participants with both baseline and Week 24 samples (exploratory outcome). RESULTS PEGASUS enrolled 95 participants (intent-to-treat [ITT] cohort); cognitive assessments indicated significantly greater baseline cognitive impairment in the PB and TURSO (n = 51) versus placebo (n = 44) group. Clinical efficacy outcomes did not significantly differ between treatment groups in the ITT cohort. CSF interleukin-15 increased from baseline to Week 24 within the placebo group (n = 34). In the PB and TURSO group (n = 33), reductions were observed in core AD biomarkers phosphorylated tau-181 (p-tau181) and total tau; synaptic and neuronal degeneration biomarkers neurogranin and fatty acid binding protein-3 (FABP3); and gliosis biomarker chitinase 3-like protein 1 (YKL-40), while the oxidative stress marker 8-hydroxy-2-deoxyguanosine (8-OHdG) increased. Between-group differences were observed for the Aβ42/40 ratio, p-tau181, total tau, neurogranin, FABP3, YKL-40, interleukin-15, and 8-OHdG. Additional neurodegeneration, inflammation, and metabolic biomarkers showed no differences between groups. DISCUSSION While between-group differences in clinical outcomes were not observed, most likely due to the small sample size and relatively short treatment duration, exploratory biomarker analyses suggested that PB and TURSO engages multiple pathophysiologic pathways in AD. Highlights Proteostasis and mitochondrial stress play key roles in Alzheimer's disease (AD).Sodium phenylbutyrate and taurursodiol (PB and TURSO) targets these mechanisms.The PEGASUS trial was designed to assess PB and TURSO effects on biologic AD targets.PB and TURSO reduced exploratory biomarkers of AD and neurodegeneration.Supports further clinical development of PB and TURSO in neurodegenerative diseases.
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Affiliation(s)
- Steven E. Arnold
- Department of NeurologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | | | | | | | - Victoria J. Williams
- Department of MedicineUniversity of Wisconsin‐MadisonSchool of Medicine and Public HealthMadisonWisconsinUSA
| | - Jeffrey M. Burns
- University of Kansas Alzheimer's Disease Research CenterFairwayKansasUSA
| | - Monica Crane
- Genesis Neuroscience ClinicKnoxvilleTennesseeUSA
| | - Alison J. McManus
- Department of NeurologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Sanjeev N. Vaishnavi
- Department of NeurologyPenn Memory CenterPerelman School of Medicine at the University of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Zoe Arvanitakis
- Rush Alzheimer's Disease CenterRush University Medical CenterChicagoIllinoisUSA
| | - Judith Neugroschl
- Department of PsychiatryIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Karen Bell
- Department of NeurologyColumbia UniversityNew YorkNew YorkUSA
| | - Bianca A. Trombetta
- Department of NeurologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Becky C. Carlyle
- Department of PhysiologyAnatomy & Genetics and Kavli Institute for Nanoscience DiscoveryUniversity of OxfordOxfordUK
| | - Pia Kivisäkk
- Department of NeurologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Hiroko H. Dodge
- Department of NeurologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Rudolph E. Tanzi
- Department of NeurologyGenetics and Aging Research UnitMcCance Center for Brain HealthMassachusetts General HospitalHarvard UniversityBostonMassachusettsUSA
| | | | - Kent Leslie
- Amylyx Pharmaceuticals, Inc.CambridgeMassachusettsUSA
- Present address:
Division of Biology and Biological Engineering Graduate ProgramCalifornia Institute of TechnologyPasadenaCAUSA
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13
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Gonzalez-Ortiz F, Kirsebom BE, Contador J, Tanley JE, Selnes P, Gísladóttir B, Pålhaugen L, Suhr Hemminghyth M, Jarholm J, Skogseth R, Bråthen G, Grøndtvedt G, Bjørnerud A, Tecelao S, Waterloo K, Aarsland D, Fernández-Lebrero A, García-Escobar G, Navalpotro-Gómez I, Turton M, Hesthamar A, Kac PR, Nilsson J, Luchsinger J, Hayden KM, Harrison P, Puig-Pijoan A, Zetterberg H, Hughes TM, Suárez-Calvet M, Karikari TK, Fladby T, Blennow K. Plasma brain-derived tau is an amyloid-associated neurodegeneration biomarker in Alzheimer's disease. Nat Commun 2024; 15:2908. [PMID: 38575616 PMCID: PMC10995141 DOI: 10.1038/s41467-024-47286-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 03/26/2024] [Indexed: 04/06/2024] Open
Abstract
Staging amyloid-beta (Aβ) pathophysiology according to the intensity of neurodegeneration could identify individuals at risk for cognitive decline in Alzheimer's disease (AD). In blood, phosphorylated tau (p-tau) associates with Aβ pathophysiology but an AD-type neurodegeneration biomarker has been lacking. In this multicenter study (n = 1076), we show that brain-derived tau (BD-tau) in blood increases according to concomitant Aβ ("A") and neurodegeneration ("N") abnormalities (determined using cerebrospinal fluid biomarkers); We used blood-based A/N biomarkers to profile the participants in this study; individuals with blood-based p-tau+/BD-tau+ profiles had the fastest cognitive decline and atrophy rates, irrespective of the baseline cognitive status. Furthermore, BD-tau showed no or much weaker correlations with age, renal function, other comorbidities/risk factors and self-identified race/ethnicity, compared with other blood biomarkers. Here we show that blood-based BD-tau is a biomarker for identifying Aβ-positive individuals at risk of short-term cognitive decline and atrophy, with implications for clinical trials and implementation of anti-Aβ therapies.
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Affiliation(s)
- Fernando Gonzalez-Ortiz
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.
| | - Bjørn-Eivind Kirsebom
- Department of Neurology, University Hospital of North Norway, Tromsø, Norway
- Department of Psychology, Faculty of Health Sciences, The Arctic University of Norway, Tromsø, Norway
- Institute of Clinical Medicine, Campus Ahus, University of Oslo, Oslo, Norway
| | - José Contador
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Hospital del Mar Research Institute, Barcelona, Spain
- Cognitive Decline and Movement Disorders Unit, Neurology Department, Hospital del Mar, Barcelona, Spain
| | - Jordan E Tanley
- Department of Internal Medicine, Section on Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Per Selnes
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | | | - Lene Pålhaugen
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | - Mathilde Suhr Hemminghyth
- Research Group for Age-Related Medicine, Haugesund Hospital, Haugesund, Norway
- Department of Neuropsychology, Haugesund Hospital, Haugesund, Norway
- Department of Clinical Medicine (K1), University of Bergen, Bergen, Norway
| | - Jonas Jarholm
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | - Ragnhild Skogseth
- Department of Geriatric Medicine, Haraldsplass Deaconess Hospital, Bergen, Norway
- Department of Clinical Sciences, Faculty of Medicine, University of Bergen, Bergen, Norway
| | - Geir Bråthen
- Department of Neurology and Clinical Neurophysiology, University Hospital of Trondheim, Trondheim, Norway
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Gøril Grøndtvedt
- Department of Neurology and Clinical Neurophysiology, University Hospital of Trondheim, Trondheim, Norway
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Atle Bjørnerud
- Department of Physics, University of Oslo, Oslo, Norway
- Unit for Computational Radiology and Artificial Intelligence, Oslo University hospital, Oslo, Norway
- Department of Psychology, Faculty for Social Sciences, University of Oslo, Oslo, Norway
| | - Sandra Tecelao
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | - Knut Waterloo
- Department of Neurology, University Hospital of North Norway, Tromsø, Norway
- Department of Psychology, Faculty of Health Sciences, The Arctic University of Norway, Tromsø, Norway
| | - Dag Aarsland
- Department of Old Age Psychiatry. Institute of psychiatry, Psychology and Neuroscience King's College London, London, UK
- Centre for Age-Related Diseases, University Hospital Stavanger, Stavanger, Norway
| | - Aida Fernández-Lebrero
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Hospital del Mar Research Institute, Barcelona, Spain
- Cognitive Decline and Movement Disorders Unit, Neurology Department, Hospital del Mar, Barcelona, Spain
- Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, 08003, Spain
- ERA-Net on Cardiovascular Diseases (ERA-CVD) consortium, Barcelona, Spain
| | - Greta García-Escobar
- Hospital del Mar Research Institute, Barcelona, Spain
- ERA-Net on Cardiovascular Diseases (ERA-CVD) consortium, Barcelona, Spain
| | - Irene Navalpotro-Gómez
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Hospital del Mar Research Institute, Barcelona, Spain
- Cognitive Decline and Movement Disorders Unit, Neurology Department, Hospital del Mar, Barcelona, Spain
- ERA-Net on Cardiovascular Diseases (ERA-CVD) consortium, Barcelona, Spain
| | - Michael Turton
- Bioventix Plc, 7 Romans Business Park, East Street, Farnham, Surrey, GU9 7SX, UK
| | - Agnes Hesthamar
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Przemyslaw R Kac
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Johanna Nilsson
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Jose Luchsinger
- Department of Internal Medicine, Section on Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Kathleen M Hayden
- Department of Internal Medicine, Section on Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Peter Harrison
- Bioventix Plc, 7 Romans Business Park, East Street, Farnham, Surrey, GU9 7SX, UK
| | - Albert Puig-Pijoan
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Hospital del Mar Research Institute, Barcelona, Spain
- ERA-Net on Cardiovascular Diseases (ERA-CVD) consortium, Barcelona, Spain
- Department of Medicine, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, 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
| | - Timothy M Hughes
- Department of Internal Medicine, Section on Gerontology and Geriatric Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Marc Suárez-Calvet
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Hospital del Mar Research Institute, Barcelona, Spain
- Cognitive Decline and Movement Disorders Unit, Neurology Department, Hospital del Mar, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Tormod Fladby
- Institute of Clinical Medicine, Campus Ahus, University of Oslo, Oslo, Norway
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
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14
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Hung SM, Adams SW, Molloy C, Wu DA, Shimojo S, Arakaki X. Practice makes imperfect: stronger implicit interference with practice in individuals at high risk of developing Alzheimer's disease. GeroScience 2024; 46:2777-2786. [PMID: 37817004 PMCID: PMC10828369 DOI: 10.1007/s11357-023-00953-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 09/19/2023] [Indexed: 10/12/2023] Open
Abstract
Early screening to determine patient risk of developing Alzheimer's will allow better interventions and planning but necessitates accessible methods such as behavioral biomarkers. Previously, we showed that cognitively healthy older individuals whose cerebrospinal fluid amyloid/tau ratio indicates high risk of cognitive decline experienced implicit interference during a high-effort task, signaling early changes in attention. To further investigate attention's effect on implicit interference, we analyzed two experiments completed sequentially by the same high- and low-risk individuals. We hypothesized that if attention modulates interference, practice would affect the influence of implicit distractors. Indeed, while both groups experienced a strong practice effect, the association between practice and interference effects diverged between groups: stronger practice effects correlated with more implicit interference in high-risk participants, but less interference in low-risk individuals. Furthermore, low-risk individuals showed a positive correlation between implicit interference and EEG low-range alpha event-related desynchronization when switching from high- to low-load tasks. This suggests that lower attention on the task was correlated with stronger interference, a typical phenomenon in the younger population. These results demonstrate how attention impacts implicit interference and highlight early differences in perception between high- and low-risk individuals.
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Affiliation(s)
- Shao-Min Hung
- Waseda Institute for Advanced Study, Waseda University, Tokyo, Japan.
- Faculty of Science and Engineering, Waseda University, Tokyo, Japan.
- Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
| | - Sara W Adams
- Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Cathleen Molloy
- Cognition and Brain Integration Laboratory, Department of Neurosciences, Huntington Medical Research Institutes, Pasadena, CA, USA
| | - Daw-An Wu
- Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Shinsuke Shimojo
- Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
- Computation and Neural Systems, California Institute of Technology, Pasadena, CA, USA.
| | - Xianghong Arakaki
- Cognition and Brain Integration Laboratory, Department of Neurosciences, Huntington Medical Research Institutes, Pasadena, CA, USA.
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15
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Guo Z, Tian C, Shi Y, Song XR, Yin W, Tao QQ, Liu J, Peng GP, Wu ZY, Wang YJ, Zhang ZX, Zhang J. Blood-based CNS regionally and neuronally enriched extracellular vesicles carrying pTau217 for Alzheimer's disease diagnosis and differential diagnosis. Acta Neuropathol Commun 2024; 12:38. [PMID: 38444036 PMCID: PMC10913681 DOI: 10.1186/s40478-024-01727-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 12/21/2023] [Indexed: 03/07/2024] Open
Abstract
Accurate differential diagnosis among various dementias is crucial for effective treatment of Alzheimer's disease (AD). The study began with searching for novel blood-based neuronal extracellular vesicles (EVs) that are more enriched in the brain regions vulnerable to AD development and progression. With extensive proteomic profiling, GABRD and GPR162 were identified as novel brain regionally enriched plasma EVs markers. The performance of GABRD and GPR162, along with the AD molecule pTau217, was tested using the self-developed and optimized nanoflow cytometry-based technology, which not only detected the positive ratio of EVs but also concurrently presented the corresponding particle size of the EVs, in discovery (n = 310) and validation (n = 213) cohorts. Plasma GABRD+- or GPR162+-carrying pTau217-EVs were significantly reduced in AD compared with healthy control (HC). Additionally, the size distribution of GABRD+- and GPR162+-carrying pTau217-EVs were significantly different between AD and non-AD dementia (NAD). An integrative model, combining age, the number and corresponding size of the distribution of GABRD+- or GPR162+-carrying pTau217-EVs, accurately and sensitively discriminated AD from HC [discovery cohort, area under the curve (AUC) = 0.96; validation cohort, AUC = 0.93] and effectively differentiated AD from NAD (discovery cohort, AUC = 0.91; validation cohort, AUC = 0.90). This study showed that brain regionally enriched neuronal EVs carrying pTau217 in plasma may serve as a robust diagnostic and differential diagnostic tool in both clinical practice and trials for AD.
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Affiliation(s)
- Zhen Guo
- Department of Pathology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, China
| | - Chen Tian
- Department of Pathology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, China
| | - Yang Shi
- Department of Pathology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, China
- MOE Frontier Science Center for Brain Science and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Xue-Ru Song
- Department of Pathology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, China
| | - Wei Yin
- Core Facilities, Zhejiang University School of Medicine, Hangzhou, 310011, China
| | - Qing-Qing Tao
- Department of Neurology and Research Center of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, 310000, China
| | - Jie Liu
- Department of Neurology and Centre for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Guo-Ping Peng
- Department of Neurology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China
| | - Zhi-Ying Wu
- Department of Neurology and Research Center of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, 310000, China
| | - Yan-Jiang Wang
- Department of Neurology and Centre for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 400042, China
| | - Zhen-Xin Zhang
- Department of Neurology and Clinical Epidemiology Unit, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Jing Zhang
- Department of Pathology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, Zhejiang, China.
- National Health and Disease Human Brain Tissue Resource Center, Zhejiang University, Hangzhou, 310012, China.
- Liangzhu Laboratory, Zhejiang University, 311121, Hangzhou, China.
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16
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Ashton NJ, Brum WS, Di Molfetta G, Benedet AL, Arslan B, Jonaitis E, Langhough RE, Cody K, Wilson R, Carlsson CM, Vanmechelen E, Montoliu-Gaya L, Lantero-Rodriguez J, Rahmouni N, Tissot C, Stevenson J, Servaes S, Therriault J, Pascoal T, Lleó A, Alcolea D, Fortea J, Rosa-Neto P, Johnson S, Jeromin A, Blennow K, Zetterberg H. Diagnostic Accuracy of a Plasma Phosphorylated Tau 217 Immunoassay for Alzheimer Disease Pathology. JAMA Neurol 2024; 81:255-263. [PMID: 38252443 PMCID: PMC10804282 DOI: 10.1001/jamaneurol.2023.5319] [Citation(s) in RCA: 190] [Impact Index Per Article: 190.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 11/10/2023] [Indexed: 01/23/2024]
Abstract
Importance Phosphorylated tau (p-tau) is a specific blood biomarker for Alzheimer disease (AD) pathology, with p-tau217 considered to have the most utility. However, availability of p-tau217 tests for research and clinical use has been limited. Expanding access to this highly accurate AD biomarker is crucial for wider evaluation and implementation of AD blood tests. Objective To determine the utility of a novel and commercially available immunoassay for plasma p-tau217 to detect AD pathology and evaluate reference ranges for abnormal amyloid β (Aβ) and longitudinal change across 3 selected cohorts. Design, Setting, and Participants This cohort study examined data from 3 single-center observational cohorts: cross-sectional and longitudinal data from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort (visits October 2017-August 2021) and Wisconsin Registry for Alzheimer's Prevention (WRAP) cohort (visits February 2007-November 2020) and cross-sectional data from the Sant Pau Initiative on Neurodegeneration (SPIN) cohort (baseline visits March 2009-November 2021). Participants included individuals with and without cognitive impairment grouped by amyloid and tau (AT) status using PET or CSF biomarkers. Data were analyzed from February to June 2023. Exposures Magnetic resonance imaging, Aβ positron emission tomography (PET), tau PET, cerebrospinal fluid (CSF) biomarkers (Aβ42/40 and p-tau immunoassays), and plasma p-tau217 (ALZpath pTau217 assay). Main Outcomes and Measures Accuracy of plasma p-tau217 in detecting abnormal amyloid and tau pathology, longitudinal p-tau217 change according to baseline pathology status. Results The study included 786 participants (mean [SD] age, 66.3 [9.7] years; 504 females [64.1%] and 282 males [35.9%]). High accuracy was observed in identifying elevated Aβ (area under the curve [AUC], 0.92-0.96; 95% CI, 0.89-0.99) and tau pathology (AUC, 0.93-0.97; 95% CI, 0.84-0.99) across all cohorts. These accuracies were comparable with CSF biomarkers in determining abnormal PET signal. The detection of abnormal Aβ pathology using a 3-range reference yielded reproducible results and reduced confirmatory testing by approximately 80%. Longitudinally, plasma p-tau217 values showed an annual increase only in Aβ-positive individuals, with the highest increase observed in those with tau positivity. Conclusions and Relevance This study found that a commercially available plasma p-tau217 immunoassay accurately identified biological AD, comparable with results using CSF biomarkers, with reproducible cut-offs across cohorts. It detected longitudinal changes, including at the preclinical stage.
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Affiliation(s)
- Nicholas J. Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience Maurice Wohl Institute Clinical Neuroscience Institute, London, United Kingdom
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, United Kingdom
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Wagner S. Brum
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | - Guglielmo Di Molfetta
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Andrea L. Benedet
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Burak Arslan
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Erin Jonaitis
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
| | - Rebecca E. Langhough
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
| | - Karly Cody
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
| | - Rachael Wilson
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
| | - Cynthia M. Carlsson
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Department of Medicine, Division of Geriatrics and Gerontology, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Geriatric Research Education and Clinical Center of the Wm. S. Middleton Memorial Veterans Hospital, Madison, Wisconsin
| | | | - Laia Montoliu-Gaya
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Juan Lantero-Rodriguez
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - 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
| | - Cecile 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
| | - 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
| | - 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
| | - 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
| | - Tharick Pascoal
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Neurology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Alberto Lleó
- Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau, Hospital de Sant Pau, Universitat Autònoma de Barcelona, Hospital de la Santa Creu i Sant Pau, Barcelona, Catalunya
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Daniel Alcolea
- Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau, Hospital de Sant Pau, Universitat Autònoma de Barcelona, Hospital de la Santa Creu i Sant Pau, Barcelona, Catalunya
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Juan Fortea
- Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau, Hospital de Sant Pau, Universitat Autònoma de Barcelona, Hospital de la Santa Creu i Sant Pau, Barcelona, Catalunya
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - 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
| | - Sterling Johnson
- Wisconsin Alzheimer’s Institute, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
| | | | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Wisconsin Alzheimer’s Disease Research Center, School of Medicine and Public Health, University of Wisconsin–Madison, Madison
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, United Kingdom
- UK Dementia Research Institute at UCL, London, United Kingdom
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
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Hernández‐Lorenzo L, Gil‐Moreno MJ, Ortega‐Madueño I, Cárdenas MC, Diez‐Cirarda M, Delgado‐Álvarez A, Palacios‐Sarmiento M, Matias‐Guiu J, Corrochano S, Ayala JL, Matias‐Guiu JA. A data-driven approach to complement the A/T/(N) classification system using CSF biomarkers. CNS Neurosci Ther 2024; 30:e14382. [PMID: 37501389 PMCID: PMC10848077 DOI: 10.1111/cns.14382] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 07/13/2023] [Accepted: 07/15/2023] [Indexed: 07/29/2023] Open
Abstract
AIMS The AT(N) classification system not only improved the biological characterization of Alzheimer's disease (AD) but also raised challenges for its clinical application. Unbiased, data-driven techniques such as clustering may help optimize it, rendering informative categories on biomarkers' values. METHODS We compared the diagnostic and prognostic abilities of CSF biomarkers clustering results against their AT(N) classification. We studied clinical (patients from our center) and research (Alzheimer's Disease Neuroimaging Initiative) cohorts. The studied CSF biomarkers included Aβ(1-42), Aβ(1-42)/Aβ(1-40) ratio, tTau, and pTau. RESULTS The optimal solution yielded three clusters in both cohorts, significantly different in diagnosis, AT(N) classification, values distribution, and survival. We defined these three CSF groups as (i) non-defined or unrelated to AD, (ii) early stages and/or more delayed risk of conversion to dementia, and (iii) more severe cognitive impairment subjects with faster progression to dementia. CONCLUSION We propose this data-driven three-group classification as a meaningful and straightforward approach to evaluating the risk of conversion to dementia, complementary to the AT(N) system classification.
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Affiliation(s)
- Laura Hernández‐Lorenzo
- Department of NeurologySan Carlos Research Institute (IdSSC), Hospital Clínico San CarlosMadridSpain
- Department of Computer Architecture and Automation, Computer Science FacultyComplutense University of MadridMadridSpain
| | - Maria José Gil‐Moreno
- Department of NeurologySan Carlos Research Institute (IdSSC), Hospital Clínico San CarlosMadridSpain
| | - Isabel Ortega‐Madueño
- Department of Clinical Analysis, Institute of Laboratory MedicineIdSSC, Hospital Clínico San CarlosMadridSpain
| | - Maria Cruz Cárdenas
- Department of Clinical Analysis, Institute of Laboratory MedicineIdSSC, Hospital Clínico San CarlosMadridSpain
| | - Maria Diez‐Cirarda
- Department of NeurologySan Carlos Research Institute (IdSSC), Hospital Clínico San CarlosMadridSpain
| | - Alfonso Delgado‐Álvarez
- Department of NeurologySan Carlos Research Institute (IdSSC), Hospital Clínico San CarlosMadridSpain
| | - Marta Palacios‐Sarmiento
- Department of NeurologySan Carlos Research Institute (IdSSC), Hospital Clínico San CarlosMadridSpain
| | - Jorge Matias‐Guiu
- Department of NeurologySan Carlos Research Institute (IdSSC), Hospital Clínico San CarlosMadridSpain
| | - Silvia Corrochano
- Department of NeurologySan Carlos Research Institute (IdSSC), Hospital Clínico San CarlosMadridSpain
| | - José L. Ayala
- Department of Computer Architecture and Automation, Computer Science FacultyComplutense University of MadridMadridSpain
| | - Jordi A. Matias‐Guiu
- Department of NeurologySan Carlos Research Institute (IdSSC), Hospital Clínico San CarlosMadridSpain
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18
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Salimi Y, Domingo-Fernández D, Hofmann-Apitius M, Birkenbihl C. Data-Driven Thresholding Statistically Biases ATN Profiling across Cohort Datasets. J Prev Alzheimers Dis 2024; 11:185-195. [PMID: 38230732 PMCID: PMC10995057 DOI: 10.14283/jpad.2023.100] [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: 05/19/2023] [Accepted: 07/02/2023] [Indexed: 01/18/2024]
Abstract
BACKGROUND While the amyloid/tau/neurodegeneration (ATN) framework has found wide application in Alzheimer's disease research, it is unclear if thresholds obtained using distinct thresholding methods are concordant within the same dataset and interchangeable across cohorts. OBJECTIVES To investigate the robustness of data-driven thresholding methods and ATN profiling across cohort datasets. DESIGN AND SETTING We evaluated the impact of thresholding methods on ATN profiles by applying five commonly-used methodologies across cohort datasets. We assessed the generalizability of disease patterns discovered within ATN profiles by clustering individuals from different cohorts who were assigned to the same ATN profile. PARTICIPANTS AND MEASUREMENTS Participants with available CSF amyloid-β 1-42, phosphorylated tau, and total tau measurements were included from eleven AD cohort studies. RESULTS We observed high variability among obtained ATN thresholds, both across methods and datasets that impacted the resulting profile assignments of participants significantly. Clustering participants from different cohorts within the same ATN category indicated that identified disease patterns were comparable across most cohorts and biases introduced through distinct thresholding and data representations remained insignificant in most ATN profiles. CONLUSION Thresholding method selection is a decision of statistical relevance that will inevitably bias the resulting profiling and affect its sensitivity and specificity. Thresholds are likely not directly interchangeable between independent cohorts. To apply the ATN framework as an actionable and robust profiling scheme, a comprehensive understanding of the impact of used thresholding methods, their statistical implications, and a validation of results is crucial.
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Affiliation(s)
- Y. Salimi
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, 53757 Germany
- Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, 53115 Germany
- Schloß Birlinghoven, Sankt Augustin, 53757 Germany
| | - D. Domingo-Fernández
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, 53757 Germany
| | - M. Hofmann-Apitius
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, 53757 Germany
- Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, 53115 Germany
| | - C. Birkenbihl
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, 53757 Germany
- Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, 53115 Germany
- Schloß Birlinghoven, Sankt Augustin, 53757 Germany
| | - the Alzheimer’s Disease Neuroimaging Initiative
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, 53757 Germany
- Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, 53115 Germany
- Schloß Birlinghoven, Sankt Augustin, 53757 Germany
| | - the Japanese Alzheimer’s Disease Neuroimaging Initiative
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, 53757 Germany
- Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, 53115 Germany
- Schloß Birlinghoven, Sankt Augustin, 53757 Germany
| | - the Alzheimer’s Disease Repository Without Borders Investigators
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, 53757 Germany
- Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, 53115 Germany
- Schloß Birlinghoven, Sankt Augustin, 53757 Germany
| | - the European Prevention of Alzheimer’s Disease (EPAD) Consortium
- Department of Bioinformatics, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, 53757 Germany
- Bonn-Aachen International Center for IT, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, 53115 Germany
- Schloß Birlinghoven, Sankt Augustin, 53757 Germany
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Yoo HS, Kim HK, Lee JH, Chun JH, Lee HS, Grothe MJ, Teipel S, Cavedo E, Vergallo A, Hampel H, Ryu YH, Cho H, Lyoo CH. Association of Basal Forebrain Volume with Amyloid, Tau, and Cognition in Alzheimer's Disease. J Alzheimers Dis 2024; 99:145-159. [PMID: 38640150 DOI: 10.3233/jad-230975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/21/2024]
Abstract
Background Degeneration of cholinergic basal forebrain (BF) neurons characterizes Alzheimer's disease (AD). However, what role the BF plays in the dynamics of AD pathophysiology has not been investigated precisely. Objective To investigate the baseline and longitudinal roles of BF along with core neuropathologies in AD. Methods In this retrospective cohort study, we enrolled 113 subjects (38 amyloid [Aβ]-negative cognitively unimpaired, 6 Aβ-positive cognitively unimpaired, 39 with prodromal AD, and 30 with AD dementia) who performed brain MRI for BF volume and cortical thickness, 18F-florbetaben PET for Aβ, 18F-flortaucipir PET for tau, and detailed cognitive testing longitudinally. We investigated the baseline and longitudinal association of BF volume with Aβ and tau standardized uptake value ratio and cognition. Results Cross-sectionally, lower BF volume was not independently associated with higher cortical Aβ, but it was associated with tau burden. Tau burden in the orbitofrontal, insular, lateral temporal, inferior temporo-occipital, and anterior cingulate cortices were associated with progressive BF atrophy. Lower BF volume was associated with faster Aβ accumulation, mainly in the prefrontal, anterior temporal, cingulate, and medial occipital cortices. BF volume was associated with progressive decline in language and memory functions regardless of baseline Aβ and tau burden. Conclusions Tau deposition affected progressive BF atrophy, which in turn accelerated amyloid deposition, leading to a vicious cycle. Also, lower baseline BF volume independently predicted deterioration in cognitive function.
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Affiliation(s)
- Han Soo Yoo
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Han-Kyeol Kim
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Jae-Hoon Lee
- Department of Nuclear Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Joong-Hyun Chun
- Biostatistics Collaboration Unit, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Hye Sun Lee
- Department of Biostatistics, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Michel J Grothe
- Reina Sofia Alzheimer Center, CIEN Foundation-ISCIII, Madrid, Spain
| | - Stefan Teipel
- Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE)-Rostock/Greifswald, Rostock, Germany
- Department of Psychosomatic Medicine, University Medicine Rostock, Germany
| | - Enrica Cavedo
- Sorbonne University Alzheimer Precision Medicine, AP-HP, Pitié-Salpêtrière Hospital, Paris, France
| | - Andrea Vergallo
- Sorbonne University Alzheimer Precision Medicine, AP-HP, Pitié-Salpêtrière Hospital, Paris, France
| | - Harald Hampel
- Sorbonne University Alzheimer Precision Medicine, AP-HP, Pitié-Salpêtrière Hospital, Paris, France
| | - Young Hoon Ryu
- Department of Nuclear Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Hanna Cho
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Chul Hyoung Lyoo
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
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20
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Jain L, Khrestian M, Formica S, Tuason ED, Pillai JA, Rao S, Oguh O, Lippa CF, Lopez OL, Berman SB, Tsuang DW, Zabetian CP, Irwin DJ, Galasko DR, Litvan I, Marder KS, Honig LS, Fleisher JE, Galvin JE, Bozoki AC, Taylor AS, Sabbagh MN, Leverenz JB, Bekris LM. ATN cerebrospinal fluid biomarkers in dementia with Lewy bodies: Initial results from the United States Dementia with Lewy Bodies Consortium. Alzheimers Dement 2024; 20:549-562. [PMID: 37740924 PMCID: PMC10840643 DOI: 10.1002/alz.13398] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 06/09/2023] [Accepted: 06/19/2023] [Indexed: 09/25/2023]
Abstract
INTRODUCTION The National Institute on Aging - Alzheimer's Association (NIA-AA) ATN research framework proposes to use biomarkers for amyloid (A), tau (T), and neurodegeneration (N) to stage individuals with AD pathological features and track changes longitudinally. The overall aim was to utilize this framework to characterize pre-mortem ATN status longitudinally in a clinically diagnosed cohort of dementia with Lewy bodies (DLB) and to correlate it with the post mortem diagnosis. METHODS The cohort was subtyped by cerebrospinal fluid (CSF) ATN category. A subcohort had longitudinal data, and a subgroup was neuropathologically evaluated. RESULTS We observed a significant difference in Aβ42/40 after 12 months in the A+T- group. Post mortem neuropathologic analyses indicated that most of the p-Tau 181 positive (T+) cases also had a high Braak stage. DISCUSSION This suggests that DLB patients who are A+ but T- may need to be monitored to determine whether they remain A+ or ever progress to T positivity. HIGHLIGHTS Some A+T- DLB subjects transition from A+ to negative after 12-months. Clinically diagnosed DLB with LBP-AD (A+T+) maintain their positivity. Clinically diagnosed DLB with LBP-AD (A+T+) maintain their positivity. Monitoring of the A+T- sub-type of DLB may be necessary.
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Affiliation(s)
- Lavanya Jain
- Genomic Medicine InstituteCleveland ClinicClevelandOhioUSA
| | | | - Shane Formica
- Genomic Medicine InstituteCleveland ClinicClevelandOhioUSA
| | | | - Jagan A. Pillai
- Cleveland Clinic Lou Ruvo Center for Brain HealthCleveland ClinicClevelandOhioUSA
| | - Stephen Rao
- Cleveland Clinic Lou Ruvo Center for Brain HealthCleveland ClinicClevelandOhioUSA
| | - Odinachi Oguh
- Cleveland Clinic Lou Ruvo Center for Brain Health‐Las VegasCleveland ClinicLas VegasNevadaUSA
| | - Carol F. Lippa
- Cleveland Clinic Lou Ruvo Center for Brain Health‐Las VegasCleveland ClinicLas VegasNevadaUSA
| | - Oscar L. Lopez
- Cognitive Disorders & Comprehensive Alzheimer's Disease CenterThomas Jefferson UniversityPhiladelphiaPennsylvaniaUSA
| | - Sarah B. Berman
- Department of NeurologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Debby W. Tsuang
- Department of Psychiatry and Behavioral SciencesUniversity of Washington School of MedicineSeattleWashingtonUSA
- Geriatric Research, Education, and Clinical CenterVA Puget Sound Health Care SystemSeattleWashingtonUSA
| | - Cyrus P. Zabetian
- Geriatric Research, Education, and Clinical CenterVA Puget Sound Health Care SystemSeattleWashingtonUSA
- Department of NeurologyUniversity of Washington School of MedicineSeattleWashingtonUSA
| | - David J. Irwin
- Department of NeurologyUniversity of Pennsylvania Health SystemPhiladelphiaPennsylvaniaUSA
- Digital Neuropathology LaboratoryPhiladelphiaPennsylvaniaUSA
- Lewy Body Disease Research Center of ExcellencePhiladelphiaPennsylvaniaUSA
- Frontotemporal Degeneration CenterPhiladelphiaPennsylvaniaUSA
| | - Douglas R. Galasko
- Department of NeurosciencesUniversity of CaliforniaSan DiegoCaliforniaUSA
| | - Irene Litvan
- Department of NeurosciencesUniversity of CaliforniaSan DiegoCaliforniaUSA
| | - Karen S. Marder
- Columbia University Irving Medical CenterNew YorkNew YorkUSA
| | - Lawrence S. Honig
- Department of NeurosciencesUniversity of CaliforniaSan DiegoCaliforniaUSA
| | - Jori E. Fleisher
- Department of Neurological SciencesRush Medical CollegeChicagoIllinoisUSA
| | - James E. Galvin
- Department of NeurologyComprehensive Center for Brain HealthUniversity of Miami Miller School of MedicineMiamiFloridaUSA
| | - Andrea C. Bozoki
- Department of NeurologyUniversity of North CarolinaChapel HillNorth CarolinaUSA
| | | | - Marwan N. Sabbagh
- Department of NeurologyBarrow Neurological InstitutePhoenixArizonaUSA
| | - James B. Leverenz
- Cleveland Clinic Lou Ruvo Center for Brain HealthCleveland ClinicClevelandOhioUSA
| | - Lynn M. Bekris
- Genomic Medicine InstituteCleveland ClinicClevelandOhioUSA
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Boccalini C, Ribaldi F, Hristovska I, Arnone A, Peretti DE, Mu L, Scheffler M, Perani D, Frisoni GB, Garibotto V. The impact of tau deposition and hypometabolism on cognitive impairment and longitudinal cognitive decline. Alzheimers Dement 2024; 20:221-233. [PMID: 37555516 PMCID: PMC10916991 DOI: 10.1002/alz.13355] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 05/09/2023] [Accepted: 05/29/2023] [Indexed: 08/10/2023]
Abstract
INTRODUCTION Tau and neurodegeneration strongly correlate with cognitive impairment, as compared to amyloid. However, their contribution in explaining cognition and predicting cognitive decline in memory clinics remains unclarified. METHODS We included 94 participants with Mini-Mental State Examination (MMSE), tau positron emission tomography (PET), amyloid PET, fluorodeoxyglucose (FDG) PET, and MRI scans from Geneva Memory Center. Linear regression and mediation analyses tested the independent and combined association between biomarkers, cognitive performance, and decline. Linear mixed-effects and Cox proportional hazards models assessed biomarkers' prognostic values. RESULTS Metabolism had the strongest association with cognition (r = 0.712; p < 0.001), followed by tau (r = -0.682; p < 0.001). Neocortical tau showed the strongest association with cognitive decline (r = -0.677; p < 0.001). Metabolism mediated the association between tau and cognition and marginally mediated the one with decline. Tau positivity represented the strongest risk factor for decline (hazard ratio = 32). DISCUSSION Tau and neurodegeneration synergistically contribute to global cognitive impairment while tau drives decline. The tau PET superior prognostic value supports its implementation in memory clinics. HIGHLIGHTS Hypometabolism has the strongest association with concurrent cognitive impairment. Neocortical tau pathology is the main determinant of cognitive decline over time. FDG-PET has a superior value compared to MRI as a measure of neurodegeneration. The prognostic value of tau-PET exceeded all other neuroimaging modalities.
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Affiliation(s)
- Cecilia Boccalini
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of MedicineUniversity of GenevaGenevaSwitzerland
- Vita‐Salute San Raffaele UniversityMilanItaly
- In Vivo Human Molecular and Structural Neuroimaging Unit, Division of NeuroscienceIRCCS San Raffaele Scientific InstituteMilanItaly
| | - Federica Ribaldi
- Geneva Memory CenterGeneva University HospitalsGenevaSwitzerland
- Laboratory of Neuroimaging of Aging (LANVIE)University of GenevaGenevaSwitzerland
| | - Ines Hristovska
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of MedicineUniversity of GenevaGenevaSwitzerland
| | - Annachiara Arnone
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of MedicineUniversity of GenevaGenevaSwitzerland
| | - Débora Elisa Peretti
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of MedicineUniversity of GenevaGenevaSwitzerland
| | - Linjing Mu
- Institute of Pharmaceutical SciencesETH ZurichZurichSwitzerland
| | - Max Scheffler
- Division of RadiologyGeneva University HospitalsGenevaSwitzerland
| | - Daniela Perani
- Vita‐Salute San Raffaele UniversityMilanItaly
- In Vivo Human Molecular and Structural Neuroimaging Unit, Division of NeuroscienceIRCCS San Raffaele Scientific InstituteMilanItaly
- Nuclear Medicine UnitSan Raffaele HospitalMilanItaly
| | - Giovanni B. Frisoni
- Geneva Memory CenterGeneva University HospitalsGenevaSwitzerland
- Laboratory of Neuroimaging of Aging (LANVIE)University of GenevaGenevaSwitzerland
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of MedicineUniversity of GenevaGenevaSwitzerland
- Division of Nuclear Medicine and Molecular ImagingGeneva University HospitalsGenevaSwitzerland
- CIBM Center for Biomedical ImagingGeneva University HospitalsGenevaSwitzerland
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22
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Wang Y, Zhang Y, Yu E. Targeted examination of amyloid beta and tau protein accumulation via positron emission tomography for the differential diagnosis of Alzheimer's disease based on the A/T(N) research framework. Clin Neurol Neurosurg 2024; 236:108071. [PMID: 38043158 DOI: 10.1016/j.clineuro.2023.108071] [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: 06/08/2023] [Revised: 11/24/2023] [Accepted: 11/25/2023] [Indexed: 12/05/2023]
Abstract
Alzheimer's disease (AD) is one of the most common neurodegenerative diseases among the older population. Its main pathological features include the abnormal deposition of extracellular amyloid-β plaques and the intracellular neurofibrillary tangles of tau proteins. Its clinical presentation is complex. This review introduces the pathological processes in AD and other common neurodegenerative diseases. It then discusses the positron emission tomography (PET) probes that target amyloid-β plaques and tau proteins for diagnosing AD. According to the A/T(N) research framework, combined targeted amyloid-β and tau protein detection via PET to further improve the diagnostic accuracy of AD. In particular, the properties of the 18F-flortaucipir and 18F-MK6240 tracers-may be more beneficial in helping to differentiate AD from other common neurodegenerative diseases, such as dementia with Lewy bodies, Parkinson's disease dementia, and frontotemporal dementia. Furthermore, the A/T(N) research framework should be used as the clinical diagnosis model of AD in the future.
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Affiliation(s)
- Ye Wang
- The Second School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou 310053, China; Department of Psychiatry, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), 310022, China
| | - Yuhan Zhang
- The Second School of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou 310053, China
| | - Enyan Yu
- Department of Psychiatry, The Cancer Hospital of the University of Chinese Academy of Sciences (Zhejiang Cancer Hospital), 310022, China.
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23
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Yoon SH, Kim HK, Lee JH, Chun JH, Sohn YH, Lee PH, Ryu YH, Cho H, Yoo HS, Lyoo CH. Association of Sleep Disturbances With Brain Amyloid and Tau Burden, Cortical Atrophy, and Cognitive Dysfunction Across the AD Continuum. Neurology 2023; 101:e2162-e2171. [PMID: 37813585 PMCID: PMC10663023 DOI: 10.1212/wnl.0000000000207917] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Accepted: 08/24/2023] [Indexed: 10/14/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Patients with Alzheimer disease (AD) frequently suffer from various sleep disturbances. However, how sleep disturbance is associated with AD and its progression remains poorly investigated. We investigated the association of total sleep time with brain amyloid and tau burden, cortical atrophy, cognitive dysfunction, and their longitudinal changes in the AD spectrum. METHODS In this retrospective cohort study, we enrolled participants on the AD spectrum who were positive on 18F-florbetaben (FBB) PET. All participants underwent the Pittsburgh Sleep Quality Index, brain MRI, FBB PET, 18F-flortaucipir (FTP) PET, and detailed neuropsychological testing. In addition, a subset of participants completed follow-up assessments. We analyzed the association of total sleep time with the baseline and longitudinal FBB-standardized uptake value ratio (SUVR), FTP-SUVR, cortical thickness, and cognitive domain composite scores. RESULTS We examined 138 participants on the AD spectrum (15 with preclinical AD, 62 with prodromal AD, and 61 with AD dementia; mean age 73.4 ± 8.0 years; female 58.7%). Total sleep time was longer in the AD dementia group (7.4 ± 1.6 hours) compared with the preclinical (6.5 ± 1.4 hours; p = 0.026) and prodromal groups (6.6 ± 1.4 hours; p = 0.001), whereas other sleep parameters did not differ between groups. Longer total sleep time was not associated with amyloid accumulation but rather with tau accumulation, especially in the amygdala, hippocampus, basal forebrain, insular, cingulate, occipital, inferior temporal cortices, and precuneus. Longer total sleep time predicted faster tau accumulation in Braak regions V-VI (β = 0.016, p = 0.007) and disease progression to mild cognitive impairment or dementia (hazard ratio = 1.554, p = 0.024). Longer total sleep time was also associated with memory deficit (β = -0.19, p = 0.008). DISCUSSION Prolonged total sleep time was associated with tau accumulation in sleep-related cortical and subcortical areas as well as memory dysfunction. It also predicted faster disease progression with tau accumulation. Our study highlights the clinical importance of assessing total sleep time as a marker for disease severity and prognosis in the AD spectrum.
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Affiliation(s)
- So Hoon Yoon
- From the Department of Neurology (S.H.Y.), International St. Mary's Hospital, Catholic Kwandong University College of Medicine, Incheon; Departments of Neurology (H.-K.K., H.C., H.S.Y., C.H.L.) and Nuclear Medicine (J.-H.L., Y.H.R.), Gangnam Severance Hospital; Departments of Nuclear Medicine (J.-H.C.) and Neurology (Y.H.S., P.H.L.), Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Han-Kyeol Kim
- From the Department of Neurology (S.H.Y.), International St. Mary's Hospital, Catholic Kwandong University College of Medicine, Incheon; Departments of Neurology (H.-K.K., H.C., H.S.Y., C.H.L.) and Nuclear Medicine (J.-H.L., Y.H.R.), Gangnam Severance Hospital; Departments of Nuclear Medicine (J.-H.C.) and Neurology (Y.H.S., P.H.L.), Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jae-Hoon Lee
- From the Department of Neurology (S.H.Y.), International St. Mary's Hospital, Catholic Kwandong University College of Medicine, Incheon; Departments of Neurology (H.-K.K., H.C., H.S.Y., C.H.L.) and Nuclear Medicine (J.-H.L., Y.H.R.), Gangnam Severance Hospital; Departments of Nuclear Medicine (J.-H.C.) and Neurology (Y.H.S., P.H.L.), Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Joong-Hyun Chun
- From the Department of Neurology (S.H.Y.), International St. Mary's Hospital, Catholic Kwandong University College of Medicine, Incheon; Departments of Neurology (H.-K.K., H.C., H.S.Y., C.H.L.) and Nuclear Medicine (J.-H.L., Y.H.R.), Gangnam Severance Hospital; Departments of Nuclear Medicine (J.-H.C.) and Neurology (Y.H.S., P.H.L.), Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Young H Sohn
- From the Department of Neurology (S.H.Y.), International St. Mary's Hospital, Catholic Kwandong University College of Medicine, Incheon; Departments of Neurology (H.-K.K., H.C., H.S.Y., C.H.L.) and Nuclear Medicine (J.-H.L., Y.H.R.), Gangnam Severance Hospital; Departments of Nuclear Medicine (J.-H.C.) and Neurology (Y.H.S., P.H.L.), Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Phil Hyu Lee
- From the Department of Neurology (S.H.Y.), International St. Mary's Hospital, Catholic Kwandong University College of Medicine, Incheon; Departments of Neurology (H.-K.K., H.C., H.S.Y., C.H.L.) and Nuclear Medicine (J.-H.L., Y.H.R.), Gangnam Severance Hospital; Departments of Nuclear Medicine (J.-H.C.) and Neurology (Y.H.S., P.H.L.), Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Young Hoon Ryu
- From the Department of Neurology (S.H.Y.), International St. Mary's Hospital, Catholic Kwandong University College of Medicine, Incheon; Departments of Neurology (H.-K.K., H.C., H.S.Y., C.H.L.) and Nuclear Medicine (J.-H.L., Y.H.R.), Gangnam Severance Hospital; Departments of Nuclear Medicine (J.-H.C.) and Neurology (Y.H.S., P.H.L.), Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Hanna Cho
- From the Department of Neurology (S.H.Y.), International St. Mary's Hospital, Catholic Kwandong University College of Medicine, Incheon; Departments of Neurology (H.-K.K., H.C., H.S.Y., C.H.L.) and Nuclear Medicine (J.-H.L., Y.H.R.), Gangnam Severance Hospital; Departments of Nuclear Medicine (J.-H.C.) and Neurology (Y.H.S., P.H.L.), Yonsei University College of Medicine, Seoul, Republic of Korea.
| | - Han Soo Yoo
- From the Department of Neurology (S.H.Y.), International St. Mary's Hospital, Catholic Kwandong University College of Medicine, Incheon; Departments of Neurology (H.-K.K., H.C., H.S.Y., C.H.L.) and Nuclear Medicine (J.-H.L., Y.H.R.), Gangnam Severance Hospital; Departments of Nuclear Medicine (J.-H.C.) and Neurology (Y.H.S., P.H.L.), Yonsei University College of Medicine, Seoul, Republic of Korea.
| | - Chul Hyoung Lyoo
- From the Department of Neurology (S.H.Y.), International St. Mary's Hospital, Catholic Kwandong University College of Medicine, Incheon; Departments of Neurology (H.-K.K., H.C., H.S.Y., C.H.L.) and Nuclear Medicine (J.-H.L., Y.H.R.), Gangnam Severance Hospital; Departments of Nuclear Medicine (J.-H.C.) and Neurology (Y.H.S., P.H.L.), Yonsei University College of Medicine, Seoul, Republic of Korea
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24
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Burnham SC, Iaccarino L, Pontecorvo MJ, Fleisher AS, Lu M, Collins EC, Devous MD. A review of the flortaucipir literature for positron emission tomography imaging of tau neurofibrillary tangles. Brain Commun 2023; 6:fcad305. [PMID: 38187878 PMCID: PMC10768888 DOI: 10.1093/braincomms/fcad305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 09/13/2023] [Accepted: 11/14/2023] [Indexed: 01/09/2024] Open
Abstract
Alzheimer's disease is defined by the presence of β-amyloid plaques and neurofibrillary tau tangles potentially preceding clinical symptoms by many years. Previously only detectable post-mortem, these pathological hallmarks are now identifiable using biomarkers, permitting an in vivo definitive diagnosis of Alzheimer's disease. 18F-flortaucipir (previously known as 18F-T807; 18F-AV-1451) was the first tau positron emission tomography tracer to be introduced and is the only Food and Drug Administration-approved tau positron emission tomography tracer (Tauvid™). It has been widely adopted and validated in a number of independent research and clinical settings. In this review, we present an overview of the published literature on flortaucipir for positron emission tomography imaging of neurofibrillary tau tangles. We considered all accessible peer-reviewed literature pertaining to flortaucipir through 30 April 2022. We found 474 relevant peer-reviewed publications, which were organized into the following categories based on their primary focus: typical Alzheimer's disease, mild cognitive impairment and pre-symptomatic populations; atypical Alzheimer's disease; non-Alzheimer's disease neurodegenerative conditions; head-to-head comparisons with other Tau positron emission tomography tracers; and technical considerations. The available flortaucipir literature provides substantial evidence for the use of this positron emission tomography tracer in assessing neurofibrillary tau tangles in Alzheimer's disease and limited support for its use in other neurodegenerative disorders. Visual interpretation and quantitation approaches, although heterogeneous, mostly converge and demonstrate the high diagnostic and prognostic value of flortaucipir in Alzheimer's disease.
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Affiliation(s)
| | | | | | | | - Ming Lu
- Avid, Eli Lilly and Company, Philadelphia, PA 19104, USA
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25
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Wang ZB, Tan L, Gao PY, Ma YH, Fu Y, Sun Y, Yu JT. Associations of the A/T/N profiles in PET, CSF, and plasma biomarkers with Alzheimer's disease neuropathology at autopsy. Alzheimers Dement 2023; 19:4421-4435. [PMID: 37506291 DOI: 10.1002/alz.13413] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 07/03/2023] [Accepted: 07/10/2023] [Indexed: 07/30/2023]
Abstract
INTRODUCTION To examine the extent to which positron emission tomography (PET)-, cerebrospinal fluid (CSF)-, and plasma-related amyloid-β/tau/neurodegeneration (A/T/N) biomarkers are associated with Alzheimer's disease (AD) neuropathology at autopsy. METHODS A total of 100 participants who respectively underwent antemortem biomarker measurements and postmortem neuropathology were included in the Alzheimer's Disease Neuroimaging Initiative (ADNI). We examined the associations of PET-, CSF-, and plasma-related A/T/N biomarkers in combinations or alone with AD neuropathological changes (ADNC). RESULTS PET- and CSF-related A/T/N biomarkers in combination showed high concordance with the ADNC stage and alone showed high accuracy in discriminating autopsy-confirmed AD. However, the plasma-related A/T/N biomarkers alone showed better discriminative performance only when combined with apolipoprotein E (APO)E ε4 genotype. DISCUSSION This study supports that PET- and CSF-related A/T/N profiles can be used to predict accurately the stages of AD neuropathology. For diagnostic settings, PET-, CSF-, and plasma-related A/T/N biomarkers are all useful diagnostic tools to detect the presence of AD neuropathology. HIGHLIGHTS PET- and CSF-related A/T/N biomarkers in combination can accurately predict the specific stages of AD neuropathology. PET- and CSF-related A/T/N biomarkers alone may serve as a precise diagnostic tool for detecting AD neuropathology at autopsy. Plasma-related A/T/N biomarkers may need combined risk factors when used as a diagnostic tool. Aβ PET and CSF p-tau181/Aβ42 were most consistent with Aβ pathology, while tau PET and CSF p-tau181/Aβ42 were most consistent with tau pathology.
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Affiliation(s)
- Zhi-Bo Wang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Pei-Yang Gao
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Ya-Hui Ma
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yan Fu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yan Sun
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
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Coughlan G, DeSouza B, Zhukovsky P, Hornberger M, Grady C, Buckley RF. Spatial cognition is associated with levels of phosphorylated-tau and β-amyloid in clinically normal older adults. Neurobiol Aging 2023; 130:124-134. [PMID: 37506550 DOI: 10.1016/j.neurobiolaging.2023.06.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 06/23/2023] [Accepted: 06/24/2023] [Indexed: 07/30/2023]
Abstract
Spatial cognition is associated with Alzheimer's disease (AD) biomarkers in the symptomatic stages of the disease. We investigated whether cerebrospinal fluid (CSF) biomarkers (phosphorylated-tau [p-tau] and β-amyloid) are associated with poorer spatial cognition in clinically normal older adults. Participants were 1875 clinically normal adults (age 67.8 [8.5] years) from the European Prevention of Alzheimer's Dementia Consortium. Mixed effect models assessed the cross-sectional association between p-tau181, β-amyloid1-42 (Aβ1-42) and p-tau181/Aβ1-42 ratio and spatial cognition measured using semi-automated Supermarket Task and the 4 Mountains Task. Levels of p-tau181, Aβ1-42, and p-tau181/Aβ1-42 ratio were significantly associated with spatial cognition scores on both tasks. The p-tau181/Aβ1-42 ratio showed the largest effect sizes (β = -0.04/0.05, p < 0.001). Lower entorhinal cortical volume was associated with poorer outcomes on both tasks (β = 0.06, p < 0.002) and accounted for 18%-22% of the direct association between p-tau181 and spatial cognition scores. In conclusion, degeneration of the entorhinal cortex mediates a significant proportion of the association between p-tau181 and spatial assessments in cognitively normal adults. Future studies should focus on increasing the sensitivity of digital spatial assessments.
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Affiliation(s)
- Gillian Coughlan
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - Brennan DeSouza
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada
| | - Peter Zhukovsky
- Campbell Family Mental Health Research Institute, Centre for Mental Health and Addiction, Toronto, Ontario, Canada
| | - Michael Hornberger
- Norwich Medical School, University of East Anglia, Norwich, United Kingdom
| | - Cheryl Grady
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada; Departments of Psychiatry and Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Rachel F Buckley
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA; Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, Victoria, Australia.
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Buccellato FR, D’Anca M, Tartaglia GM, Del Fabbro M, Scarpini E, Galimberti D. Treatment of Alzheimer's Disease: Beyond Symptomatic Therapies. Int J Mol Sci 2023; 24:13900. [PMID: 37762203 PMCID: PMC10531090 DOI: 10.3390/ijms241813900] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 09/05/2023] [Accepted: 09/07/2023] [Indexed: 09/29/2023] Open
Abstract
In an ever-increasing aged world, Alzheimer's disease (AD) represents the first cause of dementia and one of the first chronic diseases in elderly people. With 55 million people affected, the WHO considers AD to be a disease with public priority. Unfortunately, there are no final cures for this pathology. Treatment strategies are aimed to mitigate symptoms, i.e., acetylcholinesterase inhibitors (AChEI) and the N-Methyl-D-aspartate (NMDA) antagonist Memantine. At present, the best approaches for managing the disease seem to combine pharmacological and non-pharmacological therapies to stimulate cognitive reserve. Over the last twenty years, a number of drugs have been discovered acting on the well-established biological hallmarks of AD, deposition of β-amyloid aggregates and accumulation of hyperphosphorylated tau protein in cells. Although previous efforts disappointed expectations, a new era in treating AD has been working its way recently. The Food and Drug Administration (FDA) gave conditional approval of the first disease-modifying therapy (DMT) for the treatment of AD, aducanumab, a monoclonal antibody (mAb) designed against Aβ plaques and oligomers in 2021, and in January 2023, the FDA granted accelerated approval for a second monoclonal antibody, Lecanemab. This review describes ongoing clinical trials with DMTs and non-pharmacological therapies. We will also present a future scenario based on new biomarkers that can detect AD in preclinical or prodromal stages, identify people at risk of developing AD, and allow an early and curative treatment.
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Affiliation(s)
- Francesca R. Buccellato
- Department of Biomedical, Surgical and Dental Sciences, University of Milan, 20122 Milan, Italy
- Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Marianna D’Anca
- Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Gianluca Martino Tartaglia
- Department of Biomedical, Surgical and Dental Sciences, University of Milan, 20122 Milan, Italy
- Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Massimo Del Fabbro
- Department of Biomedical, Surgical and Dental Sciences, University of Milan, 20122 Milan, Italy
- Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Elio Scarpini
- Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Daniela Galimberti
- Department of Biomedical, Surgical and Dental Sciences, University of Milan, 20122 Milan, Italy
- Fondazione IRCCS Ca’ Granda, Ospedale Maggiore Policlinico, 20122 Milan, Italy
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Peretti DE, Ribaldi F, Scheffler M, Chicherio C, Frisoni GB, Garibotto V. Prognostic value of imaging-based ATN profiles in a memory clinic cohort. Eur J Nucl Med Mol Imaging 2023; 50:3313-3323. [PMID: 37358619 PMCID: PMC10542279 DOI: 10.1007/s00259-023-06311-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Accepted: 06/17/2023] [Indexed: 06/27/2023]
Abstract
PURPOSE The ATN model represents a research framework used to classify subjects based on the presence or absence of Alzheimer's disease (AD) pathology through biomarkers for amyloid (A), tau (T), and neurodegeneration (N). The aim of this study was to assess the relationship between ATN profiles defined through imaging and cognitive decline in a memory clinic cohort. METHODS One hundred-eight patients from the memory clinic of Geneva University Hospitals underwent complete clinical and neuropsychological evaluation at baseline and 23 ± 5 months after inclusion, magnetic resonance imaging, amyloid and tau PET scans. ATN profiles were divided into four groups: normal, AD pathological change (AD-PC: A + T-N-, A + T-N +), AD pathology (AD-P: A + T + N-, A + T + N +), and suspected non-AD pathology (SNAP: A-T + N-, A-T-N + , A-T + N +). RESULTS Mini-Mental State Examination (MMSE) scores were significantly different among groups, both at baseline and follow-up, with the normal group having higher average MMSE scores than the other groups. MMSE scores changed significantly after 2 years only in AD-PC and AD-P groups. AD-P profile classification also had the largest number of decliners at follow-up (55%) and the steepest global cognitive decline compared to the normal group. Cox regression showed that participants within the AD-P group had a higher risk of cognitive decline (HR = 6.15, CI = 2.59-14.59), followed by AD-PC (HR = 3.16, CI = 1.17-8.52). CONCLUSION Of the different group classifications, AD-P was found to have the most significant effect on cognitive decline over a period of 2 years, highlighting the value of both amyloid and tau PET molecular imaging as prognostic imaging biomarkers in clinical practice.
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Affiliation(s)
- Débora E Peretti
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocentre and Faculty of Medicine, University of Geneva, Geneva, Switzerland.
| | - Federica Ribaldi
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Centre, Department of Rehabilitation and Geriatrics, Geneva University Hospitals, Geneva, Switzerland
| | - Max Scheffler
- Division of Radiology, Geneva University Hospitals, Geneva, Switzerland
| | - Christian Chicherio
- Geneva Memory Centre, Department of Rehabilitation and Geriatrics, Geneva University Hospitals, Geneva, Switzerland
- Centre for Interdisciplinary Study of Gerontology and Vulnerability (CIGEV), University of Geneva, Geneva, Switzerland
| | - Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Centre, Department of Rehabilitation and Geriatrics, Geneva University Hospitals, Geneva, Switzerland
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocentre and Faculty of Medicine, University of Geneva, Geneva, Switzerland
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland
- Centre for Biomedical Imaging, University of Geneva, Geneva, Switzerland
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Cozachenco D, Zimmer ER, Lourenco MV. Emerging concepts towards a translational framework in Alzheimer's disease. Neurosci Biobehav Rev 2023; 152:105246. [PMID: 37236385 DOI: 10.1016/j.neubiorev.2023.105246] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 05/20/2023] [Accepted: 05/22/2023] [Indexed: 05/28/2023]
Abstract
Over the past decades, significant efforts have been made to understand the precise mechanisms underlying the pathogenesis of Alzheimer's disease (AD), the most common cause of dementia. However, clinical trials targeting AD pathological hallmarks have consistently failed. Refinement of AD conceptualization, modeling, and assessment is key to developing successful therapies. Here, we review critical findings and discuss emerging ideas to integrate molecular mechanisms and clinical approaches in AD. We further propose a refined workflow for animal studies incorporating multimodal biomarkers used in clinical studies - delineating critical paths for drug discovery and translation. Addressing unresolved questions with the proposed conceptual and experimental framework may accelerate the development of effective disease-modifying strategies for AD.
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Affiliation(s)
- Danielle Cozachenco
- Institute of Medical Biochemistry Leopoldo de Meis, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | - Eduardo R Zimmer
- Department of Pharmacology, Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brazil; Graduate Program in Biological Sciences: Biochemistry (PPGBioq), UFRGS, Porto Alegre, RS, Brazil; Pharmacology and Therapeutics (PPGFT), UFRGS, Porto Alegre, RS, Brazil; McGill Centre for Studies in Aging, McGill University, Montreal, Canada; Brain Institute of Rio Grande do Sul, PUCRS, Porto Alegre, Brazil.
| | - Mychael V Lourenco
- Institute of Medical Biochemistry Leopoldo de Meis, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil.
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Erickson P, Simrén J, Brum WS, Ennis GE, Kollmorgen G, Suridjan I, Langhough R, Jonaitis EM, Van Hulle CA, Betthauser TJ, Carlsson CM, Asthana S, Ashton NJ, Johnson SC, Shaw LM, Blennow K, Andreasson U, Bendlin BB, Zetterberg H. Prevalence and Clinical Implications of a β-Amyloid-Negative, Tau-Positive Cerebrospinal Fluid Biomarker Profile in Alzheimer Disease. JAMA Neurol 2023; 80:2807607. [PMID: 37523162 PMCID: PMC10391361 DOI: 10.1001/jamaneurol.2023.2338] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Accepted: 05/05/2023] [Indexed: 08/01/2023]
Abstract
Importance Knowledge is lacking on the prevalence and prognosis of individuals with a β-amyloid-negative, tau-positive (A-T+) cerebrospinal fluid (CSF) biomarker profile. Objective To estimate the prevalence of a CSF A-T+ biomarker profile and investigate its clinical implications. Design, Setting, and Participants This was a retrospective cohort study of the cross-sectional multicenter University of Gothenburg (UGOT) cohort (November 2019-January 2021), the longitudinal multicenter Alzheimer Disease Neuroimaging Initiative (ADNI) cohort (individuals with mild cognitive impairment [MCI] and no cognitive impairment; September 2005-May 2022), and 2 Wisconsin cohorts, Wisconsin Alzheimer Disease Research Center and Wisconsin Registry for Alzheimer Prevention (WISC; individuals without cognitive impairment; February 2007-November 2020). This was a multicenter study, with data collected from referral centers in clinical routine (UGOT) and research settings (ADNI and WISC). Eligible individuals had 1 lumbar puncture (all cohorts), 2 or more cognitive assessments (ADNI and WISC), and imaging (ADNI only) performed on 2 separate occasions. Data were analyzed on August 2022 to April 2023. Exposures Baseline CSF Aβ42/40 and phosphorylated tau (p-tau)181; cognitive tests (ADNI: modified preclinical Alzheimer cognitive composite [mPACC]; WISC: modified 3-test PACC [PACC-3]). Exposures in the ADNI cohort included [18F]-florbetapir amyloid positron emission tomography (PET), magnetic resonance imaging (MRI), [18F]-fluorodeoxyglucose PET (FDG-PET), and cross-sectional tau-PET (ADNI: [18F]-flortaucipir, WISC: [18F]-MK6240). Main Outcomes and Measures Primary outcomes were the prevalence of CSF AT biomarker profiles and continuous longitudinal global cognitive outcome and imaging biomarker trajectories in A-T+ vs A-T- groups. Secondary outcomes included cross-sectional tau-PET. Results A total of 7679 individuals (mean [SD] age, 71.0 [8.4] years; 4101 male [53%]) were included in the UGOT cohort, 970 individuals (mean [SD] age, 73 [7.0] years; 526 male [54%]) were included in the ADNI cohort, and 519 individuals (mean [SD] age, 60 [7.3] years; 346 female [67%]) were included in the WISC cohort. The prevalence of an A-T+ profile in the UGOT cohort was 4.1% (95% CI, 3.7%-4.6%), being less common than the other patterns. Longitudinally, no significant differences in rates of worsening were observed between A-T+ and A-T- profiles for cognition or imaging biomarkers. Cross-sectionally, A-T+ had similar tau-PET uptake to individuals with an A-T- biomarker profile. Conclusion and Relevance Results suggest that the CSF A-T+ biomarker profile was found in approximately 5% of lumbar punctures and was not associated with a higher rate of cognitive decline or biomarker signs of disease progression compared with biomarker-negative individuals.
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Affiliation(s)
- Pontus Erickson
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Joel Simrén
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Wagner S. Brum
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Gilda E. Ennis
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison
| | | | | | - Rebecca Langhough
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison
| | - Erin M. Jonaitis
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison
| | - Carol A. Van Hulle
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison
| | - Tobey J. Betthauser
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison
| | - Cynthia M. Carlsson
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison
- Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison
- Geriatric Research Education and Clinical Center of the Wm. S. Middleton Memorial Veterans Hospital, Madison, Wisconsin
| | - Sanjay Asthana
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison
- Division of Geriatrics and Gerontology, Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison
- Geriatric Research Education and Clinical Center of the Wm. S. Middleton Memorial Veterans Hospital, Madison, Wisconsin
| | - Nicholas J. Ashton
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, King’s College London, London, England
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, England
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Sterling C. Johnson
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison
| | - Leslie M. Shaw
- Department of Pathology and Laboratory Medicine, University of Pennsylvania School of Medicine, Philadelphia
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Ulf Andreasson
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Barbara B. Bendlin
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
| | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Institute of Neurology, Department of Neurodegenerative Disease, University College London, London, England
- UK Dementia Research Institute, University College London, London, England
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
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Peretti DE, Ribaldi F, Scheffler M, Mu L, Treyer V, Gietl AF, Hock C, Frisoni GB, Garibotto V. ATN profile classification across two independent prospective cohorts. Front Med (Lausanne) 2023; 10:1168470. [PMID: 37559930 PMCID: PMC10407659 DOI: 10.3389/fmed.2023.1168470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 07/10/2023] [Indexed: 08/11/2023] Open
Abstract
Background The ATN model represents a research framework used to describe in subjects the presence or absence of Alzheimer's disease (AD) pathology through biomarkers. The aim of this study was to describe the prevalence of different ATN profiles using quantitative imaging biomarkers in two independent cohorts, and to evaluate the pertinence of ATN biomarkers to identify comparable populations across independent cohorts. Methods A total of 172 subjects from the Geneva Memory Clinic and 113 volunteers from a study on healthy aging at the University Hospital of Zurich underwent amyloid (A) and tau (T) PET, as well as T1-weigthed MRI scans using site-specific protocols. Subjects were classified by cognition (cognitively unimpaired, CU, or impaired, CI) based on clinical assessment by experts. Amyloid data converted into the standardized centiloid scale, tau PET data normalized to cerebellar uptake, and hippocampal volume expressed as a ratio over total intracranial volume ratio were considered as biomarkers for A, T, and neurodegeneration (N), respectively. Positivity for each biomarker was defined based on previously published thresholds. Subjects were then classified according to the ATN model. Differences among profiles were tested using Kruskal-Wallis ANOVA, and between cohorts using Wilcoxon tests. Results Twenty-nine percent of subjects from the Geneva cohorts were classified with a normal (A-T-N-) profile, while the Zurich cohort included 64% of subjects in the same category. Meanwhile, 63% of the Geneva and 16% of the Zurich cohort were classified within the AD continuum (being A+ regardless of other biomarkers' statuses). Within cohorts, ATN profiles were significantly different for age and mini-mental state examination scores, but not for years of education. Age was not significantly different between cohorts. In general, imaging A and T biomarkers were significantly different between cohorts, but they were no longer significantly different when stratifying the cohorts by ATN profile. N was not significantly different between cohorts. Conclusion Stratifying subjects into ATN profiles provides comparable groups of subjects even when individual recruitment followed different criteria.
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Affiliation(s)
- Débora E. Peretti
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Faculty of Medicine, Geneva University Neurocenter, University of Geneva, Geneva, Switzerland
| | - Federica Ribaldi
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
| | - Max Scheffler
- Division of Radiology, Geneva University Hospitals, Geneva, Switzerland
| | - Linjing Mu
- Department of Nuclear Medicine, University Hospital of Zurich, University of Zurich, Zurich, Switzerland
- Institute of Pharmaceutical Sciences, Zurich, Switzerland
| | - Valerie Treyer
- Department of Nuclear Medicine, University Hospital of Zurich, University of Zurich, Zurich, Switzerland
| | - Anton F. Gietl
- Department of Nuclear Medicine, University Hospital of Zurich, University of Zurich, Zurich, Switzerland
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | - Christoph Hock
- Department of Nuclear Medicine, University Hospital of Zurich, University of Zurich, Zurich, Switzerland
- Institute for Regenerative Medicine (IREM), University of Zurich, Zurich, Switzerland
| | - Giovanni B. Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Memory Clinic, Geneva University Hospitals, Geneva, Switzerland
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Faculty of Medicine, Geneva University Neurocenter, University of Geneva, Geneva, Switzerland
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland
- Center for Biomedical Imaging, University of Geneva, Geneva, Switzerland
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Lu J, Ma X, Zhang H, Xiao Z, Li M, Wu J, Ju Z, Chen L, Zheng L, Ge J, Liang X, Bao W, Wu P, Ding D, Yen TC, Guan Y, Zuo C, Zhao Q. Head-to-head comparison of plasma and PET imaging ATN markers in subjects with cognitive complaints. Transl Neurodegener 2023; 12:34. [PMID: 37381042 PMCID: PMC10308642 DOI: 10.1186/s40035-023-00365-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Accepted: 06/02/2023] [Indexed: 06/30/2023] Open
Abstract
BACKGROUND Gaining more information about the reciprocal associations between different biomarkers within the ATN (Amyloid/Tau/Neurodegeneration) framework across the Alzheimer's disease (AD) spectrum is clinically relevant. We aimed to conduct a comprehensive head-to-head comparison of plasma and positron emission tomography (PET) ATN biomarkers in subjects with cognitive complaints. METHODS A hospital-based cohort of subjects with cognitive complaints with a concurrent blood draw and ATN PET imaging (18F-florbetapir for A, 18F-Florzolotau for T, and 18F-fluorodeoxyglucose [18F-FDG] for N) was enrolled (n = 137). The β-amyloid (Aβ) status (positive versus negative) and the severity of cognitive impairment served as the main outcome measures for assessing biomarker performances. RESULTS Plasma phosphorylated tau 181 (p-tau181) level was found to be associated with PET imaging of ATN biomarkers in the entire cohort. Plasma p-tau181 level and PET standardized uptake value ratios of AT biomarkers showed a similarly excellent diagnostic performance for distinguishing between Aβ+ and Aβ- subjects. An increased tau burden and glucose hypometabolism were significantly associated with the severity of cognitive impairment in Aβ+ subjects. Additionally, glucose hypometabolism - along with elevated plasma neurofilament light chain level - was related to more severe cognitive impairment in Aβ- subjects. CONCLUSION Plasma p-tau181, as well as 18F-florbetapir and 18F-Florzolotau PET imaging can be considered as interchangeable biomarkers in the assessment of Aβ status in symptomatic stages of AD. 18F-Florzolotau and 18F-FDG PET imaging could serve as biomarkers for the severity of cognitive impairment. Our findings have implications for establishing a roadmap to identifying the most suitable ATN biomarkers for clinical use.
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Affiliation(s)
- Jiaying Lu
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
| | - Xiaoxi Ma
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Huiwei Zhang
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
| | - Zhenxu Xiao
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Ming Li
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Jie Wu
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Zizhao Ju
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
| | - Li Chen
- Department of Ultrasound, Huashan Hospital, Fudan University, Shanghai, China
| | - Li Zheng
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Jingjie Ge
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
| | - Xiaoniu Liang
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Weiqi Bao
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
| | - Ping Wu
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
| | - Ding Ding
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | | | - Yihui Guan
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China.
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China.
| | - Chuantao Zuo
- Department of Nuclear Medicine and PET Center, Huashan Hospital, Fudan University, Shanghai, China.
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China.
- Human Phenome Institute, Fudan University, Shanghai, China.
| | - Qianhua Zhao
- National Clinical Research Center for Aging and Medicine and National Center for Neurological Disorders, Huashan Hospital, Fudan University, Shanghai, China.
- Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China.
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China.
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Li B, Shi K, Ren C, Kong M, Ba M. Detection of Tau-PET Positivity in Clinically Diagnosed Mild Cognitive Impairment with Multidimensional Features. J Alzheimers Dis 2023:JAD230180. [PMID: 37334600 DOI: 10.3233/jad-230180] [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: 06/20/2023]
Abstract
BACKGROUND The way to evaluate brain tau pathology in vivo is tau positron emission tomography (tau-PET) or cerebrospinal fluid (CSF) analysis. In the clinically diagnosed mild cognitive impairment (MCI), a significant proportion of tau-PET are negative. Interest in less expensive and convenient ways to detect tau pathology in Alzheimer's disease has increased due to the high cost of tau-PET and the invasiveness of lumbar puncture, which typically slows down the cost and enrollment of clinical trials. OBJECTIVE We aimed to investigate one simple and effective method in predicting tau-PET status in MCI individuals. METHODS The sample included 154 individuals which were dichotomized into tau-PET (+) and tau-PET (-) using a cut-off of >1.33. We used stepwise regression to select the unitary or combination of variables that best predicted tau-PET. The receiver operating characteristic curve was used to assess the accuracy of single and multiple clinical markers. RESULTS The combined performance of three variables [Alzheimer's Disease Assessment Scale-Cognitive Subscale 13 (ADAS-Cog13), Mini-Mental State Examination (MMSE), ADNI-Memory summary score (ADNI-MEM)] in neurocognitive measures demonstrated good predictive accuracy of tau-PET status [accuracy = 85.7%, area under the curve (AUC) = 0.879]. The combination of clinical markers model (APOEɛ4, neurocognitive measures and structural MRI imaging of middle temporal) had the best discriminative power (AUC = 0.946). CONCLUSION As a noninvasive test, the combination of APOEɛ4, neurocognitive measures and structural MRI imaging of middle temporal accurately predicts tau-PET status. The finding may provide a non-invasive, cost-effective tool for clinical application in predicting tau pathology among MCI individuals.
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Affiliation(s)
- Bingyu Li
- Department of Neurology, Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, China
| | - Kening Shi
- Department of Neurology, Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, China
| | - Chao Ren
- Department of Neurology, Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, China
| | - Min Kong
- Department of Neurology, Yantaishan Hospital, Yantai, Shandong, China
| | - Maowen Ba
- Department of Neurology, Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai, China
- Yantai Regional Sub Center of National Center for Clinical Medical Research of Neurological Diseases, Shandong, China
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Hung SM, Adams SW, Molloy C, Wu DA, Shimojo S, Arakaki X. Practice makes imperfect: stronger implicit interference with practice in individuals at high risk of developing Alzheimer's disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.16.541059. [PMID: 37292951 PMCID: PMC10245765 DOI: 10.1101/2023.05.16.541059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Early screening to determine patient risk of developing Alzheimer's will allow better interventions and planning but necessitates accessible methods such as behavioral biomarkers. Previously, we showed that cognitively healthy older individuals whose cerebrospinal fluid amyloid / tau ratio indicates high risk of cognitive decline experienced implicit interference during a high-effort task, signaling early changes in attention. To further investigate attention's effect on implicit interference, we analyzed two experiments completed sequentially by the same high- and low-risk individuals. We hypothesized that if attention modulates interference, practice would affect the influence of implicit distractors. Indeed, while both groups experienced a strong practice effect, the association between practice and interference effects diverged between groups: stronger practice effects correlated with more implicit interference in high-risk participants, but less interference in low-risk individuals. Furthermore, low-risk individuals showed a positive correlation between implicit interference and EEG low-range alpha event-related desynchronization when switching from high- to low-load tasks. These results demonstrate how attention impacts implicit interference and highlight early differences in cognition between high- and low-risk individuals.
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Affiliation(s)
- Shao-Min Hung
- Waseda Institute for Advanced Study, Waseda University, Tokyo, Japan
- Faculty of Science and Engineering, Waseda University, Tokyo, Japan
- Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Sara W. Adams
- Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Cathleen Molloy
- Cognition and Brain Integration Laboratory, Department of Neurosciences, Huntington Medical Research Institutes, Pasadena, CA, USA
| | - Daw-An Wu
- Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Shinsuke Shimojo
- Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
- Computation and Neural Systems, California Institute of Technology, Pasadena, CA, USA
| | - Xianghong Arakaki
- Cognition and Brain Integration Laboratory, Department of Neurosciences, Huntington Medical Research Institutes, Pasadena, CA, USA
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Hansson O, Blennow K, Zetterberg H, Dage J. Blood biomarkers for Alzheimer's disease in clinical practice and trials. NATURE AGING 2023; 3:506-519. [PMID: 37202517 PMCID: PMC10979350 DOI: 10.1038/s43587-023-00403-3] [Citation(s) in RCA: 156] [Impact Index Per Article: 78.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 03/21/2023] [Indexed: 05/20/2023]
Abstract
Blood-based biomarkers hold great promise to revolutionize the diagnostic and prognostic work-up of Alzheimer's disease (AD) in clinical practice. This is very timely, considering the recent development of anti-amyloid-β (Aβ) immunotherapies. Several assays for measuring phosphorylated tau (p-tau) in plasma exhibit high diagnostic accuracy in distinguishing AD from all other neurodegenerative diseases in patients with cognitive impairment. Prognostic models based on plasma p-tau levels can also predict future development of AD dementia in patients with mild cognitive complaints. The use of such high-performing plasma p-tau assays in the clinical practice of specialist memory clinics would reduce the need for more costly investigations involving cerebrospinal fluid samples or positron emission tomography. Indeed, blood-based biomarkers already facilitate identification of individuals with pre-symptomatic AD in the context of clinical trials. Longitudinal measurements of such biomarkers will also improve the detection of relevant disease-modifying effects of new drugs or lifestyle interventions.
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Affiliation(s)
- Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden.
- Memory Clinic, Skåne University Hospital, Lund, Sweden.
| | - 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
| | - 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 Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for 27 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
| | - Jeffrey Dage
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
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36
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Heinzinger N, Maass A, Berron D, Yakupov R, Peters O, Fiebach J, Villringer K, Preis L, Priller J, Spruth EJ, Altenstein S, Schneider A, Fliessbach K, Wiltfang J, Bartels C, Jessen F, Maier F, Glanz W, Buerger K, Janowitz D, Perneczky R, Rauchmann BS, Teipel S, Killimann I, Göerß D, Laske C, Munk MH, Spottke A, Roy N, Heneka MT, Brosseron F, Dobisch L, Ewers M, Dechent P, Haynes JD, Scheffler K, Wolfsgruber S, Kleineidam L, Schmid M, Berger M, Düzel E, Ziegler G. Exploring the ATN classification system using brain morphology. Alzheimers Res Ther 2023; 15:50. [PMID: 36915139 PMCID: PMC10009950 DOI: 10.1186/s13195-023-01185-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 02/08/2023] [Indexed: 03/16/2023]
Abstract
BACKGROUND The NIA-AA proposed amyloid-tau-neurodegeneration (ATN) as a classification system for AD biomarkers. The amyloid cascade hypothesis (ACH) implies a sequence across ATN groups that patients might undergo during transition from healthy towards AD: A-T-N-➔A+T-N-➔A+T+N-➔A+T+N+. Here we assess the evidence for monotonic brain volume decline for this particular (amyloid-conversion first, tau-conversion second, N-conversion last) and alternative progressions using voxel-based morphometry (VBM) in a large cross-sectional MRI cohort. METHODS We used baseline data of the DELCODE cohort of 437 subjects (127 controls, 168 SCD, 87 MCI, 55 AD patients) which underwent lumbar puncture, MRI scanning, and neuropsychological assessment. ATN classification was performed using CSF-Aβ42/Aβ40 (A+/-), CSF phospho-tau (T+/-), and adjusted hippocampal volume or CSF total-tau (N+/-). We compared voxel-wise model evidence for monotonic decline of gray matter volume across various sequences over ATN groups using the Bayesian Information Criterion (including also ROIs of Braak stages). First, face validity of the ACH transition sequence A-T-N-➔A+T-N-➔A+T+N-➔A+T+N+ was compared against biologically less plausible (permuted) sequences among AD continuum ATN groups. Second, we evaluated evidence for 6 monotonic brain volume progressions from A-T-N- towards A+T+N+ including also non-AD continuum ATN groups. RESULTS The ACH-based progression A-T-N-➔A+T-N-➔A+T+N-➔A+T+N+ was consistent with cognitive decline and clinical diagnosis. Using hippocampal volume for operationalization of neurodegeneration (N), ACH was most evident in 9% of gray matter predominantly in the medial temporal lobe. Many cortical regions suggested alternative non-monotonic volume progressions over ACH progression groups, which is compatible with an early amyloid-related tissue expansion or sampling effects, e.g., due to brain reserve. Volume decline in 65% of gray matter was consistent with a progression where A status converts before T or N status (i.e., ACH/ANT) when compared to alternative sequences (TAN/TNA/NAT/NTA). Brain regions earlier affected by tau tangle deposition (Braak stage I-IV, MTL, limbic system) present stronger evidence for volume decline than late Braak stage ROIs (V/VI, cortical regions). Similar findings were observed when using CSF total-tau for N instead. CONCLUSION Using the ATN classification system, early amyloid status conversion (before tau and neurodegeneration) is associated with brain volume loss observed during AD progression. The ATN system and the ACH are compatible with monotonic progression of MTL atrophy. TRIAL REGISTRATION DRKS00007966, 04/05/2015, retrospectively registered.
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Affiliation(s)
- Nils Heinzinger
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany. .,Institute of Cognitive Neurology and Dementia Research (IKND), University Hospital Magdeburg, Otto-von-Guericke University, Leipziger Str. 44, 39120, Magdeburg, Germany.
| | - Anne Maass
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.,Institute of Cognitive Neurology and Dementia Research (IKND), University Hospital Magdeburg, Otto-von-Guericke University, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - David Berron
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.,Institute of Cognitive Neurology and Dementia Research (IKND), University Hospital Magdeburg, Otto-von-Guericke University, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Renat Yakupov
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.,Institute of Cognitive Neurology and Dementia Research (IKND), University Hospital Magdeburg, Otto-von-Guericke University, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Oliver Peters
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany.,Department of Psychiatry, Charité-Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
| | - Jochen Fiebach
- Center for Stroke Research Berlin, Charité-Universitätsmedizin, Berlin, Germany
| | - Kersten Villringer
- Center for Stroke Research Berlin, Charité-Universitätsmedizin, Berlin, Germany
| | - Lukas Preis
- Department of Psychiatry, Charité-Universitätsmedizin Berlin, Campus Benjamin Franklin, Berlin, Germany
| | - Josef Priller
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany.,Department of Psychiatry and Psychotherapy, Charité, Berlin, Germany.,Department of Psychiatry and Psychotherapy, School of Medicine, Technical University of Munich, Munich, Germany.,University of Edinburgh and UK DRI, Edinburgh, UK
| | - Eike Jacob Spruth
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany.,Department of Psychiatry and Psychotherapy, Charité, Berlin, Germany
| | - Slawek Altenstein
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany.,Department of Psychiatry and Psychotherapy, Charité, Berlin, Germany
| | - Anja Schneider
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Neurodegenerative Diseases and Geriatric Psychiatry/Psychiatry, University of Bonn Medical Center, Bonn, Germany
| | - Klaus Fliessbach
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Neurodegenerative Diseases and Geriatric Psychiatry/Psychiatry, University of Bonn Medical Center, Bonn, Germany
| | - Jens Wiltfang
- German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany.,Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, University of Göttingen, Göttingen, Germany.,Department of Medical Sciences, Neurosciences and Signaling Group, Institute of Biomedicine (iBiMED), University of Aveiro, Aveiro, Portugal
| | - Claudia Bartels
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, University of Göttingen, Göttingen, Germany
| | - Frank Jessen
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Psychiatry, Medical Faculty, University of Cologne, Cologne, Germany.,Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Franziska Maier
- Department of Psychiatry, Medical Faculty, University of Cologne, Cologne, Germany
| | - Wenzel Glanz
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Katharina Buerger
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Daniel Janowitz
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Robert Perneczky
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.,Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.,Ageing Epidemiology Research Unit (AGE), School of Public Health, Imperial College London, London, UK
| | - Boris-Stephan Rauchmann
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Stefan Teipel
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany.,Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
| | - Ingo Killimann
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany.,Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
| | - Doreen Göerß
- Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
| | - Christoph Laske
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany.,Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Matthias H Munk
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany.,Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Annika Spottke
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Neurology, University of Bonn, Bonn, Germany
| | - Nina Roy
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Michael T Heneka
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Neurodegenerative Diseases and Geriatric Psychiatry/Psychiatry, University of Bonn Medical Center, Bonn, Germany
| | - Frederic Brosseron
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Neurodegenerative Diseases and Geriatric Psychiatry/Psychiatry, University of Bonn Medical Center, Bonn, Germany
| | - Laura Dobisch
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Michael Ewers
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Peter Dechent
- MR-Research in Neurosciences, Department of Cognitive Neurology, Georg-August-University Göttingen, Göttingen, Germany
| | - John Dylan Haynes
- Bernstein Center for Computational Neuroscience, Charité-Universitätsmedizin, Berlin, Germany
| | - Klaus Scheffler
- Department for Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
| | - Steffen Wolfsgruber
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Department of Neurodegenerative Diseases and Geriatric Psychiatry/Psychiatry, University of Bonn Medical Center, Bonn, Germany
| | - Luca Kleineidam
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Matthias Schmid
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.,Institute for Medical Biometry, University Hospital Bonn, Bonn, Germany
| | - Moritz Berger
- Institute for Medical Biometry, University Hospital Bonn, Bonn, Germany
| | - Emrah Düzel
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.,Institute of Cognitive Neurology and Dementia Research (IKND), University Hospital Magdeburg, Otto-von-Guericke University, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Gabriel Ziegler
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.,Institute of Cognitive Neurology and Dementia Research (IKND), University Hospital Magdeburg, Otto-von-Guericke University, Leipziger Str. 44, 39120, Magdeburg, Germany
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Kasuga K, Tsukie T, Kikuchi M, Tokutake T, Washiyama K, Simizu S, Yoshizawa H, Kuroha Y, Yajima R, Mori H, Arakawa Y, Onda K, Miyashita A, Onodera O, Iwatsubo T, Ikeuchi T. The Clinical Application of Optimized AT(N) Classification in Alzheimer’s Clinical Syndrome (ACS) and non-ACS Conditions. Neurobiol Aging 2023; 127:23-32. [PMID: 37030016 DOI: 10.1016/j.neurobiolaging.2023.03.007] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 03/10/2023] [Accepted: 03/11/2023] [Indexed: 03/18/2023]
Abstract
We aimed to assess the utility of AT(N) classification in clinical practice. We measured the cerebrospinal fluid levels of amyloid-β (Aβ) 42, Aβ40, phosphorylated tau, total tau, and neurofilament light chain (NfL) in samples from 230 patients with Alzheimer's clinical syndrome (ACS) and 328 patients with non-ACS. The concordance of two A-markers (i.e., Aβ42 alone and the Aβ42/Aβ40 ratio) was not significantly different between the ACS (87.4%) and non-ACS (74.1%) groups. However, the frequency of discordant cases with AAβ42-alone+/AAβ-ratio- was significantly higher in the non-ACS (23.8%) than in the ACS group (7.4%). The concordance of two N-markers (i.e., total tau and NfL) was 40.4% in the ACS group and 24.4% in the non-ACS group. In the ACS samples, the frequency of biological Alzheimer's disease (i.e., A+T+) in Ntau+ cases was 95% while that in NNfL+ cases was 65%. Reflecting Aβ deposition and neurodegeneration more accurately, we recommend the use of AT(N) classification defined by cerebrospinal fluid AAβ-ratioTNNfL in clinical practice.
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Ayton S, Janelidze S, Kalinowski P, Palmqvist S, Belaidi AA, Stomrud E, Roberts A, Roberts B, Hansson O, Bush AI. CSF ferritin in the clinicopathological progression of Alzheimer's disease and associations with APOE and inflammation biomarkers. J Neurol Neurosurg Psychiatry 2023; 94:211-219. [PMID: 36357168 PMCID: PMC9992756 DOI: 10.1136/jnnp-2022-330052] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 10/23/2022] [Indexed: 11/12/2022]
Abstract
BACKGROUND A putative role for iron in driving Alzheimer's disease (AD) progression is complicated by previously reported associations with neuroinflammation, apolipoprotein E and AD proteinopathy. To establish how iron interacts with clinicopathological features of AD and at what disease stage iron influences cognitive outcomes, we investigated the association of cerebrospinal fluid (CSF) biomarkers of iron (ferritin), inflammation (acute phase response proteins) and apolipoproteins with pathological biomarkers (CSF Aβ42/t-tau, p-tau181), clinical staging and longitudinal cognitive deterioration in subjects from the BioFINDER cohort, with replication of key results in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. METHODS Ferritin, acute phase response proteins (n=9) and apolipoproteins (n=6) were measured in CSF samples from BioFINDER (n=1239; 4 years cognitive follow-up) participants stratified by cognitive status (cognitively unimpaired, mild cognitive impairment, AD) and for the presence of amyloid and tangle pathology using CSF Aβ42/t-tau (A+) and p-tau181 (T+). The ferritin and apolipoprotein E associations were replicated in the ADNI (n=264) cohort. RESULTS In both cohorts, ferritin and apoE were elevated in A-T+ and A+T+ subjects (16%-40%), but not clinical diagnosis. Other apolipoproteins and acute phase response proteins increased with clinical diagnosis, not pathology. CSF ferritin was positively associated with p-tau181, which was mediated by apolipoprotein E. An optimised threshold of ferritin predicted cognitive deterioration in mild cognitive impairment subjects in the BioFINDER cohort, especially those people classified as A-T- and A+T-. CONCLUSIONS CSF markers of iron and neuroinflammation have distinct associations with disease stages, while iron may be more intimately associated with apolipoprotein E and tau pathology.
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Affiliation(s)
- Scott Ayton
- Melbourne Dementia Research Centre, Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
| | - Pawel Kalinowski
- Melbourne Dementia Research Centre, Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Abdel A. Belaidi
- Melbourne Dementia Research Centre, Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Anne Roberts
- Department of Biochemistry, Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Blaine Roberts
- Department of Biochemistry, Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Ashley I. Bush
- Melbourne Dementia Research Centre, Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Australia
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Therriault J, Vermeiren M, Servaes S, Tissot C, Ashton NJ, Benedet AL, Karikari TK, Lantero-Rodriguez J, Brum WS, Lussier FZ, Bezgin G, Stevenson J, Rahmouni N, Kunach P, Wang YT, Fernandez-Arias J, Socualaya KQ, Macedo AC, Ferrari-Souza JP, Ferreira PCL, Bellaver B, Leffa DT, Zimmer ER, Vitali P, Soucy JP, Triana-Baltzer G, Kolb HC, Pascoal TA, Saha-Chaudhuri P, Gauthier S, Zetterberg H, Blennow K, Rosa-Neto P. Association of Phosphorylated Tau Biomarkers With Amyloid Positron Emission Tomography vs Tau Positron Emission Tomography. JAMA Neurol 2023; 80:188-199. [PMID: 36508198 PMCID: PMC9856704 DOI: 10.1001/jamaneurol.2022.4485] [Citation(s) in RCA: 98] [Impact Index Per Article: 49.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 10/13/2022] [Indexed: 12/14/2022]
Abstract
Importance The recent proliferation of phosphorylated tau (p-tau) biomarkers has raised questions about their preferential association with the hallmark pathologies of Alzheimer disease (AD): amyloid-β plaques and tau neurofibrillary tangles. Objective To determine whether cerebrospinal fluid (CSF) and plasma p-tau biomarkers preferentially reflect cerebral β-amyloidosis or neurofibrillary tangle aggregation measured with positron emission tomography (PET). Design, Setting, and Participants This was a cross-sectional study of 2 observational cohorts: the Translational Biomarkers in Aging and Dementia (TRIAD) study, with data collected between October 2017 and August 2021, and the Alzheimer's Disease Neuroimaging Initiative (ADNI), with data collected between September 2015 and November 2019. TRIAD was a single-center study, and ADNI was a multicenter study. Two independent subsamples were derived from TRIAD. The first TRIAD subsample comprised individuals assessed with CSF p-tau (p-tau181, p-tau217, p-tau231, p-tau235), [18F]AZD4694 amyloid PET, and [18F]MK6240 tau PET. The second TRIAD subsample included individuals assessed with plasma p-tau (p-tau181, p-tau217, p-tau231), [18F]AZD4694 amyloid PET, and [18F]MK6240 tau PET. An independent cohort from ADNI comprised individuals assessed with CSF p-tau181, [18F]florbetapir PET, and [18F]flortaucipir PET. Participants were included based on the availability of p-tau and PET biomarker assessments collected within 9 months of each other. Exclusion criteria were a history of head trauma or magnetic resonance imaging/PET safety contraindications. No participants who met eligibility criteria were excluded. Exposures Amyloid PET, tau PET, and CSF and plasma assessments of p-tau measured with single molecule array (Simoa) assay or enzyme-linked immunosorbent assay. Main Outcomes and Measures Associations between p-tau biomarkers with amyloid PET and tau PET. Results A total of 609 participants (mean [SD] age, 66.9 [13.6] years; 347 female [57%]; 262 male [43%]) were included in the study. For all 4 phosphorylation sites assessed in CSF, p-tau was significantly more closely associated with amyloid-PET values than tau-PET values (p-tau181 difference, 13%; 95% CI, 3%-22%; P = .006; p-tau217 difference, 11%; 95% CI, 3%-20%; P = .003; p-tau231 difference, 15%; 95% CI, 5%-22%; P < .001; p-tau235 difference, 9%; 95% CI, 1%-19%; P = .02) . These results were replicated with plasma p-tau181 (difference, 11%; 95% CI, 1%-22%; P = .02), p-tau217 (difference, 9%; 95% CI, 1%-19%; P = .02), p-tau231 (difference, 13%; 95% CI, 3%-24%; P = .009), and CSF p-tau181 (difference, 9%; 95% CI, 1%-21%; P = .02) in independent cohorts. Conclusions and Relevance Results of this cross-sectional study of 2 observational cohorts suggest that the p-tau abnormality as an early event in AD pathogenesis was associated with amyloid-β accumulation and highlights the need for careful interpretation of p-tau biomarkers in the context of the amyloid/tau/neurodegeneration, or A/T/(N), framework.
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Affiliation(s)
- Joseph Therriault
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Marie Vermeiren
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, Canada
- Erasmus Medical Center, Erasmus University Rotterdam, Rotterdam, the Netherlands
| | - Stijn Servaes
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Cécile Tissot
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, Canada
| | - Nicholas J. Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Wallenberg Centre for Molecular Medicine, University of Gothenburg, Gothenburg, Sweden
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, London, United Kingdom
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, United Kingdom
| | - Andréa Lessa Benedet
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Thomas K. Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Department of Neurology and Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Juan Lantero-Rodriguez
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Wagner S. Brum
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Department of Pharmacology, Graduate Program in Biological Sciences: Biochemistry and Pharmacology and Therapeutics, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Firoza Z. Lussier
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, Canada
- Department of Neurology and Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Gleb Bezgin
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Jenna Stevenson
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, Canada
| | - Nesrine Rahmouni
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, Canada
| | - Peter Kunach
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Yi-Ting Wang
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Jaime Fernandez-Arias
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Kely Quispialaya Socualaya
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Arthur C. Macedo
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - João Pedro Ferrari-Souza
- Department of Neurology and Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Pâmela C. L. Ferreira
- Department of Neurology and Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Bruna Bellaver
- Department of Neurology and Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Douglas T. Leffa
- Department of Neurology and Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | - Eduardo R. Zimmer
- Department of Pharmacology, Graduate Program in Biological Sciences: Biochemistry and Pharmacology and Therapeutics, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Paolo Vitali
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Jean-Paul Soucy
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | | | - Hartmuth C. Kolb
- Neuroscience Biomarkers, Janssen Research & Development, La Jolla, California
| | - Tharick A. Pascoal
- Department of Neurology and Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | | | - Serge Gauthier
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, United Kingdom
- UK Dementia Research Institute at UCL, London, United Kingdom
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
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Leuzy A, Mattsson-Carlgren N, Cullen NC, Stomrud E, Palmqvist S, La Joie R, Iaccarino L, Zetterberg H, Rabinovici G, Blennow K, Janelidze S, Hansson O. Robustness of CSF Aβ42/40 and Aβ42/P-tau181 measured using fully automated immunoassays to detect AD-related outcomes. Alzheimers Dement 2023. [PMID: 36681387 DOI: 10.1002/alz.12897] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 10/26/2022] [Accepted: 11/10/2022] [Indexed: 01/23/2023]
Abstract
INTRODUCTION This study investigated the comparability of cerebrospinal fluid (CSF) cutoffs for Elecsys immunoassays for amyloid beta (Aβ)42/Aβ40 or Aβ42/phosphorylated tau (p-tau)181 and the effects of measurement variability when predicting Alzheimer's disease (AD)-related outcomes (i.e., Aβ-positron emission tomography [PET] visual read and AD neuropathology). METHODS We studied 750 participants (BioFINDER study, Alzheimer's Disease Neuroimaging Initiative [ADNI], and University of California San Francisco [UCSF]). Youden's index was used to identify cutoffs and to calculate accuracy (Aβ-PET visual read as outcome). Using longitudinal variability in Aβ-negative controls, we identified a gray zone around cut-points where the risk of an inconsistent predicted outcome was >5%. RESULTS For Aβ42/Aβ40, cutoffs across cohorts were <0.059 (BioFINDER), <0.057 (ADNI), and <0.058 (UCSF). For Aβ42/p-tau181, cutoffs were <41.90 (BioFINDER), <39.20 (ADNI), and <46.02 (UCSF). Accuracy was ≈90% for both Aβ42/Aβ40 and Aβ42/p-tau181 using these cutoffs. Using Aβ-PET as an outcome, 8.7% of participants fell within a gray zone interval for Aβ42/Aβ40, compared to 4.5% for Aβ42/p-tau181. Similar findings were observed using a measure of overall AD neuropathologic change (7.7% vs. 3.3%). In a subset with CSF and plasma Aβ42/40, the number of individuals within the gray zone was ≈1.5 to 3 times greater when using plasma Aβ42/40. DISCUSSION CSF Aβ42/p-tau181 was more robust to the effects of measurement variability, suggesting that it may be the preferred Elecsys-based measure in clinical practice and trials.
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Affiliation(s)
- Antoine Leuzy
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden.,Department of Neurology, Skåne University Hospital, Lund, Sweden.,Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Nicholas C Cullen
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California, USA
| | - Leonardo Iaccarino
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California, USA
| | - 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 Institute of Neurology, London, UK.,UK Dementia Research Institute at UCL, London, UK.,Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Gil Rabinovici
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California, USA.,Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA.,Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, California, USA.,Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, 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
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
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41
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Na HK, Kim HK, Lee HS, Park M, Lee JH, Ryu YH, Cho H, Lyoo CH. Role of Enlarged Perivascular Space in the Temporal Lobe in Cerebral Amyloidosis. Ann Neurol 2023; 93:965-978. [PMID: 36651566 DOI: 10.1002/ana.26601] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Revised: 12/01/2022] [Accepted: 01/07/2023] [Indexed: 01/19/2023]
Abstract
OBJECTIVE Although growing evidence suggests that perivascular space (PVS) serves as a clearance route for amyloid and tau, the association between enlarged PVS (EPVS) and Alzheimer disease is highly inconsistent across studies. As the conventional visual rating systems for EPVS were insufficient to predict amyloid/tau/neurodegeneration (A/T/N) status, we developed a new rating scale for EPVS located in the temporal lobe (T-EPVS). METHODS EPVS located in the basal ganglia (BG-EPVS), centrum semiovale (CS-EPVS), and T-EPVS was visually rated in 272 individuals (healthy controls, n = 96; mild cognitive impairment, n = 106; dementia, n = 70) who underwent structural magnetic resonance imaging (MRI) and dual positron emission tomography scans (18 F-flortaucipir and 18 F-florbetaben). T-EPVS and BG-EPVS were defined as high degree when the counts in any hemisphere were >10, and the CS-EPVS cutoff was >20. Logistic regression models were constructed to investigate whether the regional EPVS burden was predictive of A/T/N status. The derived models were externally validated in a temporal validation cohort (n = 195) that underwent MRI studies using a different scanner. RESULTS Compared with those with low-degree T-EPVS (23/136, 16.9%), individuals with high-degree T-EPVS/CS-EPVS but low-degree BG-EPVS were more likely to exhibit amyloid positivity (46/56, 82.1%). High-degree T-EPVS burden (odds ratio [OR] = 7.251, 95% confidence interval [CI] = 3.296-15.952) and low-degree BG-EPVS (OR = 0.241, 95% CI = 0.109-0.530) were predictive of amyloid positivity. Although high-degree T-EPVS was associated with tau positivity, the association was no longer significant after adjusting for amyloid and neurodegeneration status. INTERPRETATION Investigating the burden and topographic distribution of EPVS including T-EPVS may be useful for predicting amyloid status, indicating that impaired perivascular drainage may contribute to cerebral amyloidosis. ANN NEUROL 2023.
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Affiliation(s)
- Han Kyu Na
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea.,Department of Neurology, Yonsei University College of Medicine, Seoul, South Korea
| | - Han-Kyeol Kim
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Hye Sun Lee
- Biostatics Collaboration Unit, Yonsei University College of Medicine, Seoul, South Korea
| | - Mina Park
- Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Jae Hoon Lee
- Department of Nuclear Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Young Hoon Ryu
- Department of Nuclear Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Hanna Cho
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Chul Hyoung Lyoo
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
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42
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Kawarabayashi T, Nakamura T, Miyashita K, Segawa T, Fukamachi I, Sugawara T, Oka H, Ishizawa K, Amari M, Kasahara H, Makioka K, Ikeda Y, Takatama M, Shoji M. Clinical Evaluation of Cerebrospinal Fluid p217tau and Neurofilament Light Chain Levels in Patients with Alzheimer's Disease or Other Neurological Diseases. J Alzheimers Dis 2023; 96:1623-1638. [PMID: 38007650 PMCID: PMC10741340 DOI: 10.3233/jad-230419] [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] [Accepted: 09/29/2023] [Indexed: 11/27/2023]
Abstract
BACKGROUND The cerebrospinal fluid (CSF) levels of tau phosphorylated at threonine 217 (p217tau) or 181 (p181tau), and neurofilament light chain (NfL) are definite biomarkers of tauopathy and neurodegeneration in Alzheimer's disease (AD). OBJECTIVE To validate their utility in excluding other neurological diseases and age-related changes in clinical settings. METHODS We developed monoclonal antibodies against p217tau and NfL, established novel ELISAs, and analyzed 170 CSF samples from patients with AD or other neurological diseases. RESULTS In AD, p217tau is a more specific and abundant CSF component than p181tau. However, CSF NfL levels increase age-dependently and to a greater extent in central and peripheral nervous diseases than in AD. CONCLUSIONS CSF p217tau correlates better with AD neurodegeneration than other tau-related biomarkers and the major phosphorylated tau species. The clinical usage of NfL as a neurodegeneration biomarker in AD requires exclusion of various central and peripheral neurological diseases.
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Affiliation(s)
- Takeshi Kawarabayashi
- Department of Neurology, Dementia Research Center, Geriatrics Research Institute and Hospital, Maebashi, Japan
- Department of Neurology, Gunma University Hospital, Maebashi, Japan
- Department of Social Medicine, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Takumi Nakamura
- Department of Neurology, Gunma University Hospital, Maebashi, Japan
- Department of Social Medicine, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | | | | | | | - Takashi Sugawara
- Department of Neurology, Dementia Research Center, Geriatrics Research Institute and Hospital, Maebashi, Japan
| | - Hironori Oka
- Department of Neurology, Dementia Research Center, Geriatrics Research Institute and Hospital, Maebashi, Japan
| | - Kunihiko Ishizawa
- Department of Neurology, Dementia Research Center, Geriatrics Research Institute and Hospital, Maebashi, Japan
| | - Masakuni Amari
- Department of Neurology, Dementia Research Center, Geriatrics Research Institute and Hospital, Maebashi, Japan
| | - Hiroo Kasahara
- Department of Neurology, Gunma University Hospital, Maebashi, Japan
| | - Kouki Makioka
- Department of Neurology, Gunma University Hospital, Maebashi, Japan
| | - Yoshio Ikeda
- Department of Neurology, Gunma University Hospital, Maebashi, Japan
| | - Masamitsu Takatama
- Department of Neurology, Dementia Research Center, Geriatrics Research Institute and Hospital, Maebashi, Japan
| | - Mikio Shoji
- Department of Neurology, Dementia Research Center, Geriatrics Research Institute and Hospital, Maebashi, Japan
- Department of Neurology, Gunma University Hospital, Maebashi, Japan
- Department of Social Medicine, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
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Pascoal TA, Leuzy A, Therriault J, Chamoun M, Lussier F, Tissot C, Strandberg O, Palmqvist S, Stomrud E, Ferreira PCL, Ferrari‐Souza JP, Smith R, Benedet AL, Gauthier S, Hansson O, Rosa‐Neto P. Discriminative accuracy of the A/T/N scheme to identify cognitive impairment due to Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12390. [PMID: 36733847 PMCID: PMC9886860 DOI: 10.1002/dad2.12390] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 11/09/2022] [Accepted: 11/29/2022] [Indexed: 02/03/2023]
Abstract
Introduction The optimal combination of amyloid-β/tau/neurodegeneration (A/T/N) biomarker profiles for the diagnosis of Alzheimer's disease (AD) dementia is unclear. Methods We examined the discriminative accuracy of A/T/N combinations assessed with neuroimaging biomarkers for the differentiation of AD from cognitively unimpaired (CU) elderly and non-AD neurodegenerative diseases in the TRIAD, BioFINDER-1 and BioFINDER-2 cohorts (total n = 832) using area under the receiver operating characteristic curves (AUC). Results For the diagnosis of AD dementia (vs. CU elderly), T biomarkers performed as well as the complete A/T/N system (AUC range: 0.90-0.99). A and T biomarkers in isolation performed as well as the complete A/T/N system in differentiating AD dementia from non-AD neurodegenerative diseases (AUC range; A biomarker: 0.84-1; T biomarker: 0.83-1). Discussion In diagnostic settings, the use of A or T neuroimaging biomarkers alone can reduce patient burden and medical costs compared with using their combination, without significantly compromising accuracy.
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Affiliation(s)
- Tharick A. Pascoal
- Department of PsychiatrySchool of MedicineUniversity of PittsburghPittsburghPennsylvaniaUSA
- Department of NeurologySchool of MedicineUniversity of PittsburghPittsburghPennsylvaniaUSA
- Translational Neuroimaging LaboratoryThe McGill University Research Centre for Studies in AgingDepartment of Neurology and NeurosurgeryFaculty of MedicineMcGill UniversityMontrealQuébecCanada
| | - Antoine Leuzy
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityLundSweden
| | - Joseph Therriault
- Translational Neuroimaging LaboratoryThe McGill University Research Centre for Studies in AgingDepartment of Neurology and NeurosurgeryFaculty of MedicineMcGill UniversityMontrealQuébecCanada
- Montreal Neurological InstituteMcGill UniversityMontrealQuébecCanada
| | - Mira Chamoun
- Translational Neuroimaging LaboratoryThe McGill University Research Centre for Studies in AgingDepartment of Neurology and NeurosurgeryFaculty of MedicineMcGill UniversityMontrealQuébecCanada
- Montreal Neurological InstituteMcGill UniversityMontrealQuébecCanada
| | - Firoza Lussier
- Department of PsychiatrySchool of MedicineUniversity of PittsburghPittsburghPennsylvaniaUSA
- Translational Neuroimaging LaboratoryThe McGill University Research Centre for Studies in AgingDepartment of Neurology and NeurosurgeryFaculty of MedicineMcGill UniversityMontrealQuébecCanada
| | - Cecile Tissot
- Department of NeurologySchool of MedicineUniversity of PittsburghPittsburghPennsylvaniaUSA
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityLundSweden
| | - Olof Strandberg
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityLundSweden
- Memory ClinicSkåne University HospitalLundSweden
| | - Sebastian Palmqvist
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityLundSweden
- Memory ClinicSkåne University HospitalLundSweden
| | - Erik Stomrud
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityLundSweden
- Memory ClinicSkåne University HospitalLundSweden
| | - Pamela C. L. Ferreira
- Department of PsychiatrySchool of MedicineUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - João Pedro Ferrari‐Souza
- Department of PsychiatrySchool of MedicineUniversity of PittsburghPittsburghPennsylvaniaUSA
- Graduate Program in Biological Sciences: BiochemistryUniversidade Federal do Rio Grande do SulPorto AlegreRSBrazil
| | - Ruben Smith
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityLundSweden
- Memory ClinicSkåne University HospitalLundSweden
| | - Andrea Lessa Benedet
- Translational Neuroimaging LaboratoryThe McGill University Research Centre for Studies in AgingDepartment of Neurology and NeurosurgeryFaculty of MedicineMcGill UniversityMontrealQuébecCanada
- Montreal Neurological InstituteMcGill UniversityMontrealQuébecCanada
| | - Serge Gauthier
- Translational Neuroimaging LaboratoryThe McGill University Research Centre for Studies in AgingDepartment of Neurology and NeurosurgeryFaculty of MedicineMcGill UniversityMontrealQuébecCanada
| | - Oskar Hansson
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityLundSweden
- Memory ClinicSkåne University HospitalLundSweden
| | - Pedro Rosa‐Neto
- Translational Neuroimaging LaboratoryThe McGill University Research Centre for Studies in AgingDepartment of Neurology and NeurosurgeryFaculty of MedicineMcGill UniversityMontrealQuébecCanada
- Montreal Neurological InstituteMcGill UniversityMontrealQuébecCanada
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García-Escobar G, Puig-Pijoan A, Puente-Periz V, Fernández-Lebrero A, María Manero R, Navalpotro-Gómez I, Suárez-Calvet M, Grau-Rivera O, Contador-Muñana J, Cascales-Lahoz D, Duran-Jordà X, Boltes N, Pont-Sunyer MC, Ortiz-Gil J, Carrillo-Molina S, López-Villegas MD, Abellán-Vidal MT, Martínez-Casamitjana MI, Hernández-Sánchez JJ, Padrós-Fluvià A, Peña-Casanova J, Sánchez-Benavides G. NEURONORMA Cognitive Battery Associations with Cerebrospinal Fluid Amyloid-β and Tau Levels in the Continuum of Alzheimer's Disease. J Alzheimers Dis 2023; 92:1303-1321. [PMID: 37038810 DOI: 10.3233/jad-220930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/12/2023]
Abstract
BACKGROUND Neuropsychological assessments are essential to define the cognitive profile and contribute to the diagnosis of Alzheimer's disease (AD). The progress in knowledge about the pathophysiological process of the disease has allowed conceptualizing AD through biomarkers as a biological continuum that encompasses different clinical stages. OBJECTIVE To explore the association between cerebrospinal fluid (CSF) biomarkers of AD and cognition using the NEURONORMA battery, in a sample of cognitively unimpaired (CU), mild cognitive impaired (MCI), and mild dementia of the Alzheimer type (DAT) subjects, and to characterize the cognitive profiles in MCI subjects classified by A/T/N system. METHODS 42 CU, 35 MCI, and 35 mild DAT were assessed using the NEURONORMA battery. Core AD biomarkers [amyloid-β42 (Aβ42) peptide, total tau (t-tau), and phosphorylated tau 181 (p-tau181)] proteins were measured in CSF. Correlation coefficients, multivariate regression, and effect sizes were calculated. We explored the age- and education-adjusted cognitive profiles by A/T/N variants within the MCI group. RESULTS Cognitive outcomes were directly associated with CSF Aβ42 and inversely with CSF tau measures. We found differences in both biomarkers and cognitive outcomes comparing all pairs except for CSF measures between cognitively impaired groups. The highest effect size was in memory tasks and biomarkers ratios. Lower performances were in memory and executive domains in MCI subjects with AD pathology (A+T+N±) compared to those with normal levels of AD biomarkers (A- T- N). CONCLUSION This study provides further evidence of the validity of Spanish NEURONORMA cognitive battery to characterize cognitive impairment in the AD pathological continuum.
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Affiliation(s)
- Greta García-Escobar
- Integrative Pharmacology and Systems Neurosciences Research Group, Neurosciences Research Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Albert Puig-Pijoan
- Integrative Pharmacology and Systems Neurosciences Research Group, Neurosciences Research Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Cognitive Impairment and Movement Disorders Unit, Neurology Department, Hospital del Mar, Parc de Salut Mar, Barcelona, Spain
| | - Víctor Puente-Periz
- Integrative Pharmacology and Systems Neurosciences Research Group, Neurosciences Research Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Cognitive Impairment and Movement Disorders Unit, Neurology Department, Hospital del Mar, Parc de Salut Mar, Barcelona, Spain
| | - Aida Fernández-Lebrero
- Integrative Pharmacology and Systems Neurosciences Research Group, Neurosciences Research Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Cognitive Impairment and Movement Disorders Unit, Neurology Department, Hospital del Mar, Parc de Salut Mar, Barcelona, Spain
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
| | - Rosa María Manero
- Integrative Pharmacology and Systems Neurosciences Research Group, Neurosciences Research Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Cognitive Impairment and Movement Disorders Unit, Neurology Department, Hospital del Mar, Parc de Salut Mar, Barcelona, Spain
| | - Irene Navalpotro-Gómez
- Integrative Pharmacology and Systems Neurosciences Research Group, Neurosciences Research Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Cognitive Impairment and Movement Disorders Unit, Neurology Department, Hospital del Mar, Parc de Salut Mar, Barcelona, Spain
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
| | - Marc Suárez-Calvet
- Cognitive Impairment and Movement Disorders Unit, Neurology Department, Hospital del Mar, Parc de Salut Mar, Barcelona, Spain
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Oriol Grau-Rivera
- Cognitive Impairment and Movement Disorders Unit, Neurology Department, Hospital del Mar, Parc de Salut Mar, Barcelona, Spain
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - José Contador-Muñana
- Integrative Pharmacology and Systems Neurosciences Research Group, Neurosciences Research Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
- Cognitive Impairment and Movement Disorders Unit, Neurology Department, Hospital del Mar, Parc de Salut Mar, Barcelona, Spain
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
| | - Diego Cascales-Lahoz
- Cognitive Impairment and Movement Disorders Unit, Neurology Department, Hospital del Mar, Parc de Salut Mar, Barcelona, Spain
| | | | - Núncia Boltes
- Neurology Department, Hospital General de Granollers, Granollers, Spain
| | | | - Jordi Ortiz-Gil
- Neurology Department, Hospital General de Granollers, Granollers, Spain
- Psychology Unit, Hospital General de Granollers, Granollers, Spain
- Maria Angustias Gimenez Research Foundation (FIDMAG), Sant Boi del Llobregat, Spain
| | - Sara Carrillo-Molina
- Neurology Department, Hospital General de Granollers, Granollers, Spain
- Psychology Unit, Hospital General de Granollers, Granollers, Spain
| | - María Dolores López-Villegas
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Centre Emili Mira, Institut de Neuropsiquiatria i Addiccions (INAD), Parc de Salut Mar, Santa Coloma de Gramenet, Spain
| | - María Teresa Abellán-Vidal
- Centre Emili Mira, Institut de Neuropsiquiatria i Addiccions (INAD), Parc de Salut Mar, Santa Coloma de Gramenet, Spain
| | | | | | | | - Jordi Peña-Casanova
- Integrative Pharmacology and Systems Neurosciences Research Group, Neurosciences Research Program, Hospital del Mar Medical Research Institute (IMIM), Barcelona, Spain
| | - Gonzalo Sánchez-Benavides
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
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Simrén J, Brum WS, Ashton NJ, Benedet AL, Karikari TK, Kvartsberg H, Sjons E, Lussier FZ, Chamoun M, Stevenson J, Hopewell R, Pallen V, Ye K, Pascoal TA, Zetterberg H, Rosa-Neto P, Blennow K. CSF tau368/total-tau ratio reflects cognitive performance and neocortical tau better compared to p-tau181 and p-tau217 in cognitively impaired individuals. Alzheimers Res Ther 2022; 14:192. [PMID: 36544221 PMCID: PMC9773470 DOI: 10.1186/s13195-022-01142-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 12/14/2022] [Indexed: 12/24/2022]
Abstract
INTRODUCTION Cerebrospinal fluid (CSF) tau biomarkers are reliable diagnostic markers for Alzheimer's disease (AD). However, their strong association with amyloid pathology may limit their reliability as specific markers of tau neurofibrillary tangles. A recent study showed evidence that a ratio of CSF C-terminally truncated tau (tau368, a tangle-enriched tau species), especially in ratio with total tau (t-tau), correlates strongly with tau PET tracer uptake. In this study, we set to evaluate the performance of the tau368/t-tau ratio in capturing tangle pathology, as indexed by a high-affinity tau PET tracer, as well as its association with severity of clinical symptoms. METHODS In total, 125 participants were evaluated cross-sectionally from the Translational Biomarkers of Aging and Dementia (TRIAD) cohort (21 young, 60 cognitively unimpaired [CU] elderly [15 Aβ+], 10 Aβ+ with mild cognitive impairment [MCI], 14 AD dementia patients, and 20 Aβ- individuals with non-AD cognitive disorders). All participants underwent amyloid and tau PET scanning, with [18F]-AZD4694 and [18F]-MK6240, respectively, and had CSF measurements of p-tau181, p-tau217, and t-tau. CSF concentrations of tau368 were quantified in all individuals with an in-house single molecule array assay. RESULTS CSF tau368 concentration was not significantly different across the diagnostic groups, although a modest increase was observed in all groups as compared with healthy young individuals (all P < 0.01). In contrast, the CSF tau368/t-tau ratio was the lowest in AD dementia, being significantly lower than in CU individuals (Aβ-, P < 0.001; Aβ+, P < 0.01), as well as compared to those with non-AD cognitive disorders (P < 0.001). Notably, in individuals with symptomatic AD, tau368/t-tau correlated more strongly with [18F]-MK6240 PET SUVR as compared to the other CSF tau biomarkers, with increasing associations being seen in brain regions associated with more advanced disease (isocortical regions > limbic regions > transentorhinal regions). Importantly, linear regression models indicated that these associations were not confounded by Aβ PET SUVr. CSF tau368/t-tau also tended to continue to become more abnormal with higher tau burden, whereas the other biomarkers plateaued after the limbic stage. Finally, the tau368/t-tau ratio correlated more strongly with cognitive performance in individuals with symptomatic AD as compared to t-tau, p-tau217 and p-tau181. CONCLUSION The tau368/t-tau ratio captures novel aspects of AD pathophysiology and disease severity in comparison to established CSF tau biomarkers, as it is more closely related to tau PET SUVR and cognitive performance in the symptomatic phase of the disease.
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Affiliation(s)
- Joel Simrén
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden.
| | - Wagner S Brum
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College, London, London, UK
| | - Andrea L Benedet
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- 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, McGill University, Montreal, Canada
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Hlin Kvartsberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Emma Sjons
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Firoza Z Lussier
- 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, McGill University, Montreal, Canada
- Montreal Neurological Institute, Montreal, QC, Canada
| | - Mira Chamoun
- 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, McGill University, Montreal, Canada
- Montreal Neurological Institute, Montreal, QC, 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, McGill University, Montreal, Canada
- Montreal Neurological Institute, Montreal, QC, Canada
| | - Robert Hopewell
- 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, McGill University, Montreal, Canada
- Montreal Neurological Institute, Montreal, QC, Canada
| | - Vanessa Pallen
- 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, McGill University, Montreal, Canada
- Montreal Neurological Institute, Montreal, QC, Canada
| | - Keqiang Ye
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Tharick A Pascoal
- Department of Neurology and Psychiatry, University of Pittsburgh, Pittsburgh, USA
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
- Department of Neurodegenerative Disease, Institute of Neurology, University College London, London, UK
- UK Dementia Research Institute, University College London, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - 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, McGill University, Montreal, Canada
- Montreal Neurological Institute, Montreal, QC, Canada
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
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Zhang F, Petersen M, Johnson L, Hall J, O’Bryant SE. Combination of Serum and Plasma Biomarkers Could Improve Prediction Performance for Alzheimer's Disease. Genes (Basel) 2022; 13:1738. [PMID: 36292623 PMCID: PMC9601501 DOI: 10.3390/genes13101738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 09/21/2022] [Accepted: 09/23/2022] [Indexed: 11/25/2022] Open
Abstract
Alzheimer's disease (AD) can be predicted either by serum or plasma biomarkers, and a combination may increase predictive power, but due to the high complexity of machine learning, it may also incur overfitting problems. In this paper, we investigated whether combining serum and plasma biomarkers with feature selection could improve prediction performance for AD. 150 D patients and 150 normal controls (NCs) were enrolled for a serum test, and 100 patients and 100 NCs were enrolled for the plasma test. Among these, 79 ADs and 65 NCs had serum and plasma samples in common. A 10 times repeated 5-fold cross-validation model and a feature selection method were used to overcome the overfitting problem when serum and plasma biomarkers were combined. First, we tested to see if simply adding serum and plasma biomarkers improved prediction performance but also caused overfitting. Then we employed a feature selection algorithm we developed to overcome the overfitting problem. Lastly, we tested the prediction performance in a 10 times repeated 5-fold cross validation model for training and testing sets. We found that the combined biomarkers improved AD prediction but also caused overfitting. A further feature selection based on the combination of serum and plasma biomarkers solved the problem and produced an even higher prediction performance than either serum or plasma biomarkers on their own. The combined feature-selected serum-plasma biomarkers may have critical implications for understanding the pathophysiology of AD and for developing preventative treatments.
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Affiliation(s)
- Fan Zhang
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, TX 76107, USA
- Department of Family Medicine, University of North Texas Health Science Center, Fort Worth, TX 76107, USA
| | - Melissa Petersen
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, TX 76107, USA
- Department of Family Medicine, University of North Texas Health Science Center, Fort Worth, TX 76107, USA
| | - Leigh Johnson
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, TX 76107, USA
- Department of Pharmacology and Neuroscience, University of North Texas Health Science Center, Fort Worth, TX 76107, USA
| | - James Hall
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, TX 76107, USA
- Department of Family Medicine, University of North Texas Health Science Center, Fort Worth, TX 76107, USA
| | - Sid E. O’Bryant
- Institute for Translational Research, University of North Texas Health Science Center, Fort Worth, TX 76107, USA
- Department of Family Medicine, University of North Texas Health Science Center, Fort Worth, TX 76107, USA
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Hung S, Wu D, Shimojo S, Arakaki X. Stronger implicit interference in cognitively healthy older participants with higher risk of Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2022; 14:e12340. [PMID: 36187196 PMCID: PMC9489163 DOI: 10.1002/dad2.12340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 06/05/2022] [Accepted: 06/10/2022] [Indexed: 01/09/2023]
Abstract
Introduction Abnormal cerebrospinal fluid amyloid beta (Aβ)42 and tau levels have been revealed decades before symptoms onset in Alzheimer's disease (AD); however, the examination is usually invasive and inaccessible to most people. We thus aimed to develop a non-invasive behavioral test that targets early potential cognitive changes to gauge cognitive decline. Specifically, we hypothesized that older cognitive healthy participants would exhibit comparable performance when the task was explicit and relied on conscious cognition. However, when the task was implicit, the performance of participants at high and low risks for AD would bifurcate. That is, early changes in unconscious cognition could be linked to cognitive health. Methods We measured implicit interference elicited by an imperceptible distractor in cognitively healthy elderly participants with normal (low risk) and pathological (high risk) Aβ42/total tau ratio. Participants were required to perform a Stroop task (word-naming or color-naming on an ink-semantics inconsistent word) with a visually masked distractor presented prior to the target task. Results We found that, under a high-effort task (i.e., color-naming in the Stroop task), high-risk participants suffered interference when the imperceptible distractor and the subsequent target were incongruent in the responses they triggered. Their reaction times were slowed down by approximately 4%. This implicit interference was not found in the low-risk participants. Discussion These findings indicate that weakened inhibition of distracting implicit information can be a potential behavioral biomarker of early identification of AD pathology. Our study thus offers a new experimental paradigm to reveal early pathological aging by assessing how individuals respond to subperceptual threshold visual stimuli.
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Affiliation(s)
- Shao‐Min Hung
- Biology and Biological EngineeringCalifornia Institute of TechnologyPasadenaCaliforniaUSA
- Faculty of Science and EngineeringWaseda UniversityTokyoJapan
| | - Daw‐An Wu
- Biology and Biological EngineeringCalifornia Institute of TechnologyPasadenaCaliforniaUSA
| | - Shinsuke Shimojo
- Biology and Biological EngineeringCalifornia Institute of TechnologyPasadenaCaliforniaUSA
- Computation and Neural SystemsCalifornia Institute of TechnologyPasadenaCaliforniaUSA
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Baldeiras I, Silva-Spínola A, Lima M, Leitão MJ, Durães J, Vieira D, Tbuas-Pereira M, Cruz VT, Rocha R, Alves L, Machado Á, Milheiro M, Santiago B, Santana I. Alzheimer’s Disease Diagnosis Based on the Amyloid, Tau, and Neurodegeneration Scheme (ATN) in a Real-Life Multicenter Cohort of General Neurological Centers. J Alzheimers Dis 2022; 90:419-432. [DOI: 10.3233/jad-220587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: The ATN scheme was proposed as an unbiased biological characterization of the Alzheimer’s disease (AD) spectrum, grouping biomarkers into three categories: brain Amyloidosis-A, Tauopathy-T, Neurodegeneration-N. Although this scheme was mainly recommended for research, it is relevant for diagnosis. Objective: To evaluate the ATN scheme performance in real-life cohorts reflecting the inflow of patients with cognitive complaints and different underlying disorders in general neurological centers. Methods: We included patients (n = 1,128) from six centers with their core cerebrospinal fluid-AD biomarkers analyzed centrally. A was assessed through Aβ 42/Aβ 40, T through pTau-181, and N through tTau. Association between demographic features, clinical diagnosis at baseline/follow-up and ATN profiles was assessed. Results: The prevalence of ATN categories was: A-T-N-: 28.3% ; AD continuum (A + T-/+N-/+): 47.8% ; non-AD (A- plus T or/and N+): 23.9% . ATN profiles prevalence was strongly influenced by age, showing differences according to gender, APOE genotype, and cognitive status. At baseline, 74.6% of patients classified as AD fell in the AD continuum, decreasing to 47.4% in mild cognitive impairment and 42.3% in other neurodegenerative conditions. At follow-up, 41% of patients changed diagnosis, and 92% of patients that changed to AD were classified within the AD continuum. A + was the best individual marker for predicting a final AD diagnosis, and the combinations A + T+(irrespective of N) and A + T+N+had the highest overall accuracy (83%). Conclusion: The ATN scheme is useful to guide AD diagnosis real-life neurological centers settings. However, it shows a lack of accuracy for patients with other types of dementia. In such cases, the inclusion of other markers specific for non-AD proteinopathies could be an important aid to the differential diagnosis.
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Affiliation(s)
- Inês Baldeiras
- Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
- Faculdade de Medicina, Universidade de Coimbra, Coimbra, Portugal
- Center for Neuroscience and Cell Biology; Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
| | - Anuschka Silva-Spínola
- Center for Neuroscience and Cell Biology; Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
| | - Marisa Lima
- Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
- Center for Neuroscience and Cell Biology; Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
- Center for Research in Neuropsychology and Cognitive Behavioral Intervention, Faculty of Psychology and Educational Sciences, University of Coimbra, Coimbra, Portugal
| | - Maria João Leitão
- Center for Neuroscience and Cell Biology; Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
| | - João Durães
- Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
- Faculdade de Medicina, Universidade de Coimbra, Coimbra, Portugal
- Center for Neuroscience and Cell Biology; Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
| | - Daniela Vieira
- Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Miguel Tbuas-Pereira
- Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
- Faculdade de Medicina, Universidade de Coimbra, Coimbra, Portugal
- Center for Neuroscience and Cell Biology; Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
| | | | - Raquel Rocha
- ULSM Unidade Local de Sáude de Matosinhos, Matosinhos, Portugal
| | - Luisa Alves
- Hospital Egas Moniz, Centro Hospitalar de Lisboa Ocidental, Lisboa, Portugal
| | | | | | | | - Isabel Santana
- Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
- Faculdade de Medicina, Universidade de Coimbra, Coimbra, Portugal
- Center for Neuroscience and Cell Biology; Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
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Kim SE, Kim HJ, Jang H, Weiner MW, DeCarli C, Na DL, Seo SW. Interaction between Alzheimer's Disease and Cerebral Small Vessel Disease: A Review Focused on Neuroimaging Markers. Int J Mol Sci 2022; 23:10490. [PMID: 36142419 PMCID: PMC9499680 DOI: 10.3390/ijms231810490] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 09/07/2022] [Accepted: 09/07/2022] [Indexed: 11/26/2022] Open
Abstract
Alzheimer's disease (AD) is characterized by the presence of β-amyloid (Aβ) and tau, and subcortical vascular cognitive impairment (SVCI) is characterized by cerebral small vessel disease (CSVD). They are the most common causes of cognitive impairment in the elderly population. Concurrent CSVD burden is more commonly observed in AD-type dementia than in other neurodegenerative diseases. Recent developments in Aβ and tau positron emission tomography (PET) have enabled the investigation of the relationship between AD biomarkers and CSVD in vivo. In this review, we focus on the interaction between AD and CSVD markers and the clinical effects of these two markers based on molecular imaging studies. First, we cover the frequency of AD imaging markers, including Aβ and tau, in patients with SVCI. Second, we discuss the relationship between AD and CSVD markers and the potential distinct pathobiology of AD markers in SVCI compared to AD-type dementia. Next, we discuss the clinical effects of AD and CSVD markers in SVCI, and hemorrhagic markers in cerebral amyloid angiopathy. Finally, this review provides both the current challenges and future perspectives for SVCI.
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Affiliation(s)
- Si Eun Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
- Neuroscience Center, Samsung Medical Center, Seoul 06351, Korea
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul 06351, Korea
- Department of Neurology, Inje University College of Medicine, Haeundae Paik Hospital, Busan 48108, Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
- Neuroscience Center, Samsung Medical Center, Seoul 06351, Korea
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul 06351, Korea
| | - Hyemin Jang
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
- Neuroscience Center, Samsung Medical Center, Seoul 06351, Korea
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul 06351, Korea
| | - Michael W. Weiner
- Center for Imaging of Neurodegenerative Diseases, University of California, San Francisco, CA 94121, USA
| | - Charles DeCarli
- Department of Neurology and Center for Neuroscience, University of California, Davis, CA 95616, USA
| | - Duk L. Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
- Neuroscience Center, Samsung Medical Center, Seoul 06351, Korea
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul 06351, Korea
- Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Seoul 06355, Korea
- Stem Cell and Regenerative Medicine Institute, Samsung Medical Center, Seoul 06351, Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Korea
- Neuroscience Center, Samsung Medical Center, Seoul 06351, Korea
- Samsung Alzheimer Research Center, Samsung Medical Center, Seoul 06351, Korea
- Department of Clinical Research Design and Evaluation, SAIHST, Sungkyunkwan University, Seoul 06355, Korea
- Center for Clinical Epidemiology, Samsung Medical Center, Seoul 06351, Korea
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50
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Kasuga K, Kikuchi M, Tsukie T, Suzuki K, Ihara R, Iwata A, Hara N, Miyashita A, Kuwano R, Iwatsubo T, Ikeuchi T. Different AT(N) profiles and clinical progression classified by two different N markers using total tau and neurofilament light chain in cerebrospinal fluid. BMJ Neurol Open 2022; 4:e000321. [PMID: 36046332 PMCID: PMC9379489 DOI: 10.1136/bmjno-2022-000321] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 06/29/2022] [Indexed: 12/12/2022] Open
Abstract
Background The AT(N) classification was proposed for categorising individuals according to biomarkers. However, AT(N) profiles may vary depending on the markers chosen and the target population. Methods We stratified 177 individuals who participated in the Japanese Alzheimer's Disease Neuroimaging Initiative by AT(N) classification according to cerebrospinal fluid (CSF) biomarkers. We compared the frequency of AT(N) profiles between the classification using total tau and neurofilament light chain (NfL) as N markers (AT(N)tau and AT(N)NfL). Baseline characteristics, and longitudinal biological and clinical changes were examined between AT(N) profiles. Results We found that 9% of cognitively unimpaired subjects, 49% of subjects with mild cognitive impairment, and 61% of patients with Alzheimer's disease (AD) dementia had the biological AD profile (ie, A+T+) in the cohort. The frequency of AT(N) profiles substantially differed between the AT(N)tau and AT(N)NfL classifications. When we used t-tau as the N marker (AT(N)tau), those who had T- were more frequently assigned to (N)-, whereas those who had T+were more frequently assigned to (N)+ than when we used NfL as the N marker (AT(N)NfL). During a follow-up, the AD continuum group progressed clinically and biologically compared with the normal biomarker group in both the AT(N)tau and AT(N)NfL classifications. More frequent conversion to dementia was observed in the non-AD pathological change group in the AT(N)tau classification, but not in the AT(N)NfL classification. Conclusions AT(N)tau and AT(N)NfL in CSF may capture different aspects of neurodegeneration and provide a different prognostic value. The AT(N) classification aids in understanding the AD continuum biology in various populations.
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Affiliation(s)
- Kensaku Kasuga
- Molecular Genetics, Niigata University Brain Research Institute, Niigata, Japan
| | - Masataka Kikuchi
- Genome Informatics, Graduate School of Medicine, Osaka University, Osaka, Japan.,Computational Biology and Medical Science, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan
| | - Tamao Tsukie
- Molecular Genetics, Niigata University Brain Research Institute, Niigata, Japan
| | - Kazushi Suzuki
- Neurology, National Defense Medical College, Tokorozawa, Japan
| | - Ryoko Ihara
- Neurology, Tokyo Metropolitan Geriatric Medical Center Hospital, Tokyo, Japan
| | - Atsushi Iwata
- Neurology, Tokyo Metropolitan Geriatric Medical Center Hospital, Tokyo, Japan
| | - Norikazu Hara
- Molecular Genetics, Niigata University Brain Research Institute, Niigata, Japan
| | - Akinori Miyashita
- Molecular Genetics, Niigata University Brain Research Institute, Niigata, Japan
| | | | - Takeshi Iwatsubo
- Neuropathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Takeshi Ikeuchi
- Molecular Genetics, Niigata University Brain Research Institute, Niigata, Japan
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