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2. Metabolic network alterations as a supportive biomarker in dementia with Lewy bodies with preserved dopamine transmission

Author

Stockbauer, Anna, Beyer, Leonie, Huber, Maria, Kreuzer, Annika, Palleis, Carla, Katzdobler, Sabrina, Rauchmann, Boris-Stephan, Morbelli, Silvia, Chincarini, Andrea, Bruffaerts, Rose, Vandenberghe, Rik, Kramberger, Milica G., Trost, Maja, Garibotto, Valentina, Nicastro, Nicolas, Lathuilière, Aurélien, Lemstra, Afina W., van Berckel, Bart N. M., Pilotto, Andrea, Padovani, Alessandro, Ochoa-Figueroa, Miguel A., Davidsson, Anette, Camacho, Valle, Peira, Enrico, Bauckneht, Matteo, Pardini, Matteo, Sambuceti, Gianmario, Aarsland, Dag, Nobili, Flavio, Gross, Mattes, Vöglein, Jonathan, Perneczky, Robert, Pogarell, Oliver, Buerger, Katharina, Franzmeier, Nicolai, Danek, Adrian, Levin, Johannes, Höglinger, Günter U., Bartenstein, Peter, Cumming, Paul, Rominger, Axel, and Brendel, Matthias

Published
2024
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3. Genome-wide analyses reveal a potential role for the MAPT, MOBP, and APOE loci in sporadic frontotemporal dementia

Author

Manzoni, Claudia, Kia, Demis A., Ferrari, Raffaele, Leonenko, Ganna, Costa, Beatrice, Saba, Valentina, Jabbari, Edwin, Tan, Manuela MX., Albani, Diego, Alvarez, Victoria, Alvarez, Ignacio, Andreassen, Ole A., Angiolillo, Antonella, Arighi, Andrea, Baker, Matt, Benussi, Luisa, Bessi, Valentina, Binetti, Giuliano, Blackburn, Daniel J., Boada, Merce, Boeve, Bradley F., Borrego-Ecija, Sergi, Borroni, Barbara, Bråthen, Geir, Brooks, William S., Bruni, Amalia C., Caroppo, Paola, Bandres-Ciga, Sara, Clarimon, Jordi, Colao, Rosanna, Cruchaga, Carlos, Danek, Adrian, de Boer, Sterre CM., de Rojas, Itziar, di Costanzo, Alfonso, Dickson, Dennis W., Diehl-Schmid, Janine, Dobson-Stone, Carol, Dols-Icardo, Oriol, Donizetti, Aldo, Dopper, Elise, Durante, Elisabetta, Ferrari, Camilla, Forloni, Gianluigi, Frangipane, Francesca, Fratiglioni, Laura, Kramberger, Milica G., Galimberti, Daniela, Gallucci, Maurizio, García-González, Pablo, Ghidoni, Roberta, Giaccone, Giorgio, Graff, Caroline, Graff-Radford, Neill R., Grafman, Jordan, Halliday, Glenda M., Hernandez, Dena G., Hjermind, Lena E., Hodges, John R., Holloway, Guy, Huey, Edward D., Illán-Gala, Ignacio, Josephs, Keith A., Knopman, David S., Kristiansen, Mark, Kwok, John B., Leber, Isabelle, Leonard, Hampton L., Libri, Ilenia, Lleo, Alberto, Mackenzie, Ian R., Madhan, Gaganjit K., Maletta, Raffaele, Marquié, Marta, Maver, Ales, Menendez-Gonzalez, Manuel, Milan, Graziella, Miller, Bruce L., Morris, Christopher M., Morris, Huw R., Nacmias, Benedetta, Newton, Judith, Nielsen, Jørgen E., Nilsson, Christer, Novelli, Valeria, Padovani, Alessandro, Pal, Suvankar, Pasquier, Florence, Pastor, Pau, Perneczky, Robert, Peterlin, Borut, Petersen, Ronald C., Piguet, Olivier, Pijnenburg, Yolande AL., Puca, Annibale A., Rademakers, Rosa, Rainero, Innocenzo, Reus, Lianne M., Richardson, Anna MT., Riemenschneider, Matthias, Rogaeva, Ekaterina, Rogelj, Boris, Rollinson, Sara, Rosen, Howard, Rossi, Giacomina, Rowe, James B., Rubino, Elisa, Ruiz, Agustin, Salvi, Erika, Sanchez-Valle, Raquel, Sando, Sigrid Botne, Santillo, Alexander F., Saxon, Jennifer A., Schlachetzki, Johannes CM., Scholz, Sonja W., Seelaar, Harro, Seeley, William W., Serpente, Maria, Sorbi, Sandro, Sordon, Sabrina, St George-Hyslop, Peter, Thompson, Jennifer C., Van Broeckhoven, Christine, Van Deerlin, Vivianna M., Van der Lee, Sven J., Van Swieten, John, Tagliavini, Fabrizio, van der Zee, Julie, Veronesi, Arianna, Vitale, Emilia, Waldo, Maria Landqvist, Yokoyama, Jennifer S., Nalls, Mike A., Momeni, Parastoo, Singleton, Andrew B., Hardy, John, and Escott-Price, Valentina

Published
2024
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4. Adopting transfer learning for neuroimaging: a comparative analysis with a custom 3D convolution neural network model

Author

Soliman, Amira, Chang, Jose R., Etminani, Kobra, Byttner, Stefan, Davidsson, Anette, Martínez-Sanchis, Begoña, Camacho, Valle, Bauckneht, Matteo, Stegeran, Roxana, Ressner, Marcus, Agudelo-Cifuentes, Marc, Chincarini, Andrea, Brendel, Matthias, Rominger, Axel, Bruffaerts, Rose, Vandenberghe, Rik, Kramberger, Milica G., Trost, Maja, Nicastro, Nicolas, Frisoni, Giovanni B., Lemstra, Afina W., Berckel, Bart N. M. van, Pilotto, Andrea, Padovani, Alessandro, Morbelli, Silvia, Aarsland, Dag, Nobili, Flavio, Garibotto, Valentina, and Ochoa-Figueroa, Miguel

Published
2023
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5. C9orf72, age at onset, and ancestry help discriminate behavioral from language variants in FTLD cohorts

Author

Costa, Beatrice, Manzoni, Claudia, Bernal-Quiros, Manuel, Kia, Demis A, Aguilar, Miquel, Alvarez, Ignacio, Alvarez, Victoria, Andreassen, Ole, Anfossi, Maria, Bagnoli, Silvia, Benussi, Luisa, Bernardi, Livia, Binetti, Giuliano, Blackburn, Daniel, Boada, Mercè, Borroni, Barbara, Bowns, Lucy, Bråthen, Geir, Bruni, Amalia C, Chiang, Huei-Hsin, Clarimon, Jordi, Colville, Shuna, Conidi, Maria E, Cope, Tom E, Cruchaga, Carlos, Cupidi, Chiara, Di Battista, Maria Elena, Diehl-Schmid, Janine, Diez-Fairen, Monica, Dols-Icardo, Oriol, Durante, Elisabetta, Flisar, Dušan, Frangipane, Francesca, Galimberti, Daniela, Gallo, Maura, Gallucci, Maurizio, Ghidoni, Roberta, Graff, Caroline, Grafman, Jordan H, Grossman, Murray, Hardy, John, Hernández, Isabel, Holloway, Guy JT, Huey, Edward D, Illán-Gala, Ignacio, Karydas, Anna, Khoshnood, Behzad, Kramberger, Milica G, Kristiansen, Mark, Lewis, Patrick A, Lleó, Alberto, Madhan, Gaganjit K, Maletta, Raffaele, Maver, Aleš, Menendez-Gonzalez, Manuel, Milan, Graziella, Miller, Bruce, Mol, Merel O, Momeni, Parastoo, Moreno-Grau, Sonia, Morris, Chris M, Nacmias, Benedetta, Nilsson, Christer, Novelli, Valeria, Öijerstedt, Linn, Padovani, Alessandro, Pal, Suvankar, Panchbhaya, Yasmin, Pastor, Pau, Peterlin, Borut, Piaceri, Irene, Pickering-Brown, Stuart, Pijnenburg, Yolande AL, Puca, Annibale A, Rainero, Innocenzo, Rendina, Antonella, Richardson, Anna MT, Rogaeva, Ekaterina, Rogelj, Boris, Rollinson, Sara, Rossi, Giacomina, Rossmeier, Carola, Rowe, James B, Rubino, Elisa, Ruiz, Agustín, Sanchez-Valle, Raquel, Sando, Sigrid B, Santillo, Alexander F, Saxon, Jennifer, Scarpini, Elio, Serpente, Maria, Smirne, Nicoletta, Sorbi, Sandro, Suh, EunRan, Tagliavini, Fabrizio, Thompson, Jennifer C, Trojanowski, John Q, Van Deerlin, Vivianna M, Van der Zee, Julie, and Van Broeckhoven, Christine

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Rare Diseases, Acquired Cognitive Impairment, Alzheimer's Disease Related Dementias (ADRD), Brain Disorders, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Neurodegenerative, Frontotemporal Dementia (FTD), Genetics, Clinical Research, Dementia, Neurological, Age of Onset, Aged, Aged, 80 and over, Aphasia, Primary Progressive, C9orf72 Protein, Cohort Studies, DNA Repeat Expansion, Europe, Female, Frontotemporal Dementia, Frontotemporal Lobar Degeneration, Geography, Humans, Male, Mediterranean Region, Middle Aged, Principal Component Analysis, Scandinavian and Nordic Countries, Syndrome, International FTD-Genetics Consortium, Cognitive Sciences, Neurology & Neurosurgery, Clinical sciences
Abstract

ObjectiveWe sought to characterize C9orf72 expansions in relation to genetic ancestry and age at onset (AAO) and to use these measures to discriminate the behavioral from the language variant syndrome in a large pan-European cohort of frontotemporal lobar degeneration (FTLD) cases.MethodsWe evaluated expansions frequency in the entire cohort (n = 1,396; behavioral variant frontotemporal dementia [bvFTD] [n = 800], primary progressive aphasia [PPA] [n = 495], and FTLD-motor neuron disease [MND] [n = 101]). We then focused on the bvFTD and PPA cases and tested for association between expansion status, syndromes, genetic ancestry, and AAO applying statistical tests comprising Fisher exact tests, analysis of variance with Tukey post hoc tests, and logistic and nonlinear mixed-effects model regressions.ResultsWe found C9orf72 pathogenic expansions in 4% of all cases (56/1,396). Expansion carriers differently distributed across syndromes: 12/101 FTLD-MND (11.9%), 40/800 bvFTD (5%), and 4/495 PPA (0.8%). While addressing population substructure through principal components analysis (PCA), we defined 2 patients groups with Central/Northern (n = 873) and Southern European (n = 523) ancestry. The proportion of expansion carriers was significantly higher in bvFTD compared to PPA (5% vs 0.8% [p = 2.17 × 10-5; odds ratio (OR) 6.4; confidence interval (CI) 2.31-24.99]), as well as in individuals with Central/Northern European compared to Southern European ancestry (4.4% vs 1.8% [p = 1.1 × 10-2; OR 2.5; CI 1.17-5.99]). Pathogenic expansions and Central/Northern European ancestry independently and inversely correlated with AAO. Our prediction model (based on expansions status, genetic ancestry, and AAO) predicted a diagnosis of bvFTD with 64% accuracy.ConclusionsOur results indicate correlation between pathogenic C9orf72 expansions, AAO, PCA-based Central/Northern European ancestry, and a diagnosis of bvFTD, implying complex genetic risk architectures differently underpinning the behavioral and language variant syndromes.

Published
2020

6. A 3D deep learning model to predict the diagnosis of dementia with Lewy bodies, Alzheimer’s disease, and mild cognitive impairment using brain 18F-FDG PET

Author

Etminani, Kobra, Soliman, Amira, Davidsson, Anette, Chang, Jose R., Martínez-Sanchis, Begoña, Byttner, Stefan, Camacho, Valle, Bauckneht, Matteo, Stegeran, Roxana, Ressner, Marcus, Agudelo-Cifuentes, Marc, Chincarini, Andrea, Brendel, Matthias, Rominger, Axel, Bruffaerts, Rose, Vandenberghe, Rik, Kramberger, Milica G., Trost, Maja, Nicastro, Nicolas, Frisoni, Giovanni B., Lemstra, Afina W., van Berckel, Bart N. M., Pilotto, Andrea, Padovani, Alessandro, Morbelli, Silvia, Aarsland, Dag, Nobili, Flavio, Garibotto, Valentina, and Ochoa-Figueroa, Miguel

Published
2022
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7. Association of Cerebral Amyloid-β Aggregation With Cognitive Functioning in Persons Without Dementia

Author

Jansen, Willemijn J, Ossenkoppele, Rik, Tijms, Betty M, Fagan, Anne M, Hansson, Oskar, Klunk, William E, van der Flier, Wiesje M, Villemagne, Victor L, Frisoni, Giovanni B, Fleisher, Adam S, Lleó, Alberto, Mintun, Mark A, Wallin, Anders, Engelborghs, Sebastiaan, Na, Duk L, Chételat, Gäel, Molinuevo, José Luis, Landau, Susan M, Mattsson, Niklas, Kornhuber, Johannes, Sabri, Osama, Rowe, Christopher C, Parnetti, Lucilla, Popp, Julius, Fladby, Tormod, Jagust, William J, Aalten, Pauline, Lee, Dong Young, Vandenberghe, Rik, de Oliveira, Catarina Resende, Kapaki, Elisabeth, Froelich, Lutz, Ivanoiu, Adrian, Gabryelewicz, Tomasz, Verbeek, Marcel M, Sanchez-Juan, Páscual, Hildebrandt, Helmut, Camus, Vincent, Zboch, Marzena, Brooks, David J, Drzezga, Alexander, Rinne, Juha O, Newberg, Andrew, de Mendonça, Alexandre, Sarazin, Marie, Rabinovici, Gil D, Madsen, Karine, Kramberger, Milica G, Nordberg, Agneta, Mok, Vincent, Mroczko, Barbara, Wolk, David A, Meyer, Philipp T, Tsolaki, Magda, Scheltens, Philip, Verhey, Frans RJ, Visser, Pieter Jelle, Aarsland, Dag, Alcolea, Daniel, Alexander, Myriam, Almdahl, Ina S, Arnold, Steven E, Baldeiras, Inês, Barthel, Henryk, van Berckel, Bart NM, Blennow, Kaj, van Buchem, Mark A, Cavedo, Enrica, Chen, Kewei, Chipi, Elena, Cohen, Ann D, Förster, Stefan, Fortea, Juan, Frederiksen, Kristian S, Freund-Levi, Yvonne, Gkatzima, Olymbia, Gordon, Mark Forrest, Grimmer, Timo, Hampel, Harald, Hausner, Lucrezia, Hellwig, Sabine, Herukka, Sanna-Kaisa, Johannsen, Peter, Klimkowicz-Mrowiec, Aleksandra, Köhler, Sebastian, Koglin, Norman, van Laere, Koen, de Leon, Mony, Lisetti, Viviana, Maier, Wolfgang, Marcusson, Jan, Meulenbroek, Olga, Møllergård, Hanne M, Morris, John C, Nordlund, Arto, Novak, Gerald P, Paraskevas, George P, Perera, Gayan, Peters, Oliver, and Ramakers, Inez HGB

Subjects
Health Services and Systems, Health Sciences, Acquired Cognitive Impairment, Alzheimer's Disease Related Dementias (ADRD), Neurosciences, Aging, Dementia, Brain Disorders, Behavioral and Social Science, Neurodegenerative, Alzheimer's Disease, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Clinical Research, Aetiology, 2.1 Biological and endogenous factors, Neurological, Mental health, Aged, Alzheimer Disease, Amyloid beta-Peptides, Brain, Cognition Disorders, Cognitive Dysfunction, Cross-Sectional Studies, Female, Humans, Male, Memory, Episodic, Mental Status and Dementia Tests, Middle Aged, Positron-Emission Tomography, Reference Values, Amyloid Biomarker Study Group, Other Medical and Health Sciences, Psychology, Cognitive Sciences, Clinical sciences, Clinical and health psychology
Abstract

ImportanceCerebral amyloid-β aggregation is an early event in Alzheimer disease (AD). Understanding the association between amyloid aggregation and cognitive manifestation in persons without dementia is important for a better understanding of the course of AD and for the design of prevention trials.ObjectiveTo investigate whether amyloid-β aggregation is associated with cognitive functioning in persons without dementia.Design, setting, and participantsThis cross-sectional study included 2908 participants with normal cognition and 4133 with mild cognitive impairment (MCI) from 53 studies in the multicenter Amyloid Biomarker Study. Normal cognition was defined as having no cognitive concerns for which medical help was sought and scores within the normal range on cognitive tests. Mild cognitive impairment was diagnosed according to published criteria. Study inclusion began in 2013 and is ongoing. Data analysis was performed in January 2017.Main outcomes and measuresGlobal cognitive performance as assessed by the Mini-Mental State Examination (MMSE) and episodic memory performance as assessed by a verbal word learning test. Amyloid aggregation was measured with positron emission tomography or cerebrospinal fluid biomarkers and dichotomized as negative (normal) or positive (abnormal) according to study-specific cutoffs. Generalized estimating equations were used to examine the association between amyloid aggregation and low cognitive scores (MMSE score ≤27 or memory z score≤-1.28) and to assess whether this association was moderated by age, sex, educational level, or apolipoprotein E genotype.ResultsAmong 2908 persons with normal cognition (mean [SD] age, 67.4 [12.8] years), amyloid positivity was associated with low memory scores after age 70 years (mean difference in amyloid positive vs negative, 4% [95% CI, 0%-7%] at 72 years and 21% [95% CI, 10%-33%] at 90 years) but was not associated with low MMSE scores (mean difference, 3% [95% CI, -1% to 6%], P = .16). Among 4133 patients with MCI (mean [SD] age, 70.2 [8.5] years), amyloid positivity was associated with low memory (mean difference, 16% [95% CI, 12%-20%], P

Published
2018

10. Association of Plasma Amyloid, P-Tau, GFAP, and NfL With CSF, Clinical, and Cognitive Features in Patients With Dementia With Lewy Bodies.

Author

Bolsewig, Katharina, van Unnik, Annemartijn A. J. M., Blujdea, Elena R., Gonzalez, Maria C., Ashton, Nicholas J., Aarsland, Dag, Zetterberg, Henrik, Padovani, Alessandro, Bonanni, Laura, Mollenhauer, Brit, Schade, Sebastian, Vandenberghe, Rik, Poesen, Koen, Kramberger, Milica G., Paquet, Claire, Bousiges, Olivier, Cretin, Benjamin, Willemse, Eline A. J., Teunissen, Charlotte E., and Lemstra, Afina W.

Published
2024
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11. Sex differences in brain atrophy in dementia with Lewy bodies

Author

Oltra, Javier, primary, Habich, Annegret, additional, Schwarz, Christopher G., additional, Nedelska, Zuzana, additional, Przybelski, Scott A., additional, Inguanzo, Anna, additional, Diaz‐Galvan, Patricia, additional, Lowe, Val J., additional, Oppedal, Ketil, additional, Gonzalez, Maria C., additional, Philippi, Nathalie, additional, Blanc, Frederic, additional, Barkhof, Frederik, additional, Lemstra, Afina W., additional, Hort, Jakub, additional, Padovani, Alessandro, additional, Rektorova, Irena, additional, Bonanni, Laura, additional, Massa, Federico, additional, Kramberger, Milica G., additional, Taylor, John‐Paul, additional, Snædal, Jon G., additional, Walker, Zuzana, additional, Antonini, Angelo, additional, Dierks, Thomas, additional, Segura, Barbara, additional, Junque, Carme, additional, Westman, Eric, additional, Boeve, Bradley F., additional, Aarsland, Dag, additional, Kantarci, Kejal, additional, and Ferreira, Daniel, additional

Published
2023
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12. Metabolic network alterations as a supportive biomarker in dementia with Lewy bodies with preserved dopamine transmission

Author

Stockbauer, Anna, primary, Beyer, Leonie, additional, Huber, Maria, additional, Kreuzer, Annika, additional, Palleis, Carla, additional, Katzdobler, Sabrina, additional, Rauchmann, Boris-Stephan, additional, Morbelli, Silvia, additional, Chincarini, Andrea, additional, Bruffaerts, Rose, additional, Vandenberghe, Rik, additional, Kramberger, Milica G., additional, Trost, Maja, additional, Garibotto, Valentina, additional, Nicastro, Nicolas, additional, Lathuilière, Aurélien, additional, Lemstra, Afina W., additional, van Berckel, Bart N. M., additional, Pilotto, Andrea, additional, Padovani, Alessandro, additional, Ochoa-Figueroa, Miguel A., additional, Davidsson, Anette, additional, Camacho, Valle, additional, Peira, Enrico, additional, Bauckneht, Matteo, additional, Pardini, Matteo, additional, Sambuceti, Gianmario, additional, Aarsland, Dag, additional, Nobili, Flavio, additional, Gross, Mattes, additional, Vöglein, Jonathan, additional, Perneczky, Robert, additional, Pogarell, Oliver, additional, Buerger, Katharina, additional, Franzmeier, Nicolai, additional, Danek, Adrian, additional, Levin, Johannes, additional, Höglinger, Günter U., additional, Bartenstein, Peter, additional, Cumming, Paul, additional, Rominger, Axel, additional, and Brendel, Matthias, additional

Published
2023
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13. Prevalence of Cerebral Amyloid Pathology in Persons Without Dementia: A Meta-analysis

Author

Jansen, Willemijn J, Ossenkoppele, Rik, Knol, Dirk L, Tijms, Betty M, Scheltens, Philip, Verhey, Frans RJ, Visser, Pieter Jelle, Aalten, Pauline, Aarsland, Dag, Alcolea, Daniel, Alexander, Myriam, Almdahl, Ina S, Arnold, Steven E, Baldeiras, Inês, Barthel, Henryk, van Berckel, Bart NM, Bibeau, Kristen, Blennow, Kaj, Brooks, David J, van Buchem, Mark A, Camus, Vincent, Cavedo, Enrica, Chen, Kewei, Chetelat, Gael, Cohen, Ann D, Drzezga, Alexander, Engelborghs, Sebastiaan, Fagan, Anne M, Fladby, Tormod, Fleisher, Adam S, van der Flier, Wiesje M, Ford, Lisa, Förster, Stefan, Fortea, Juan, Foskett, Nadia, Frederiksen, Kristian S, Freund-Levi, Yvonne, Frisoni, Giovanni B, Froelich, Lutz, Gabryelewicz, Tomasz, Gill, Kiran Dip, Gkatzima, Olymbia, Gómez-Tortosa, Estrella, Gordon, Mark Forrest, Grimmer, Timo, Hampel, Harald, Hausner, Lucrezia, Hellwig, Sabine, Herukka, Sanna-Kaisa, Hildebrandt, Helmut, Ishihara, Lianna, Ivanoiu, Adrian, Jagust, William J, Johannsen, Peter, Kandimalla, Ramesh, Kapaki, Elisabeth, Klimkowicz-Mrowiec, Aleksandra, Klunk, William E, Köhler, Sebastian, Koglin, Norman, Kornhuber, Johannes, Kramberger, Milica G, Van Laere, Koen, Landau, Susan M, Lee, Dong Young, de Leon, Mony, Lisetti, Viviana, Lleó, Alberto, Madsen, Karine, Maier, Wolfgang, Marcusson, Jan, Mattsson, Niklas, de Mendonça, Alexandre, Meulenbroek, Olga, Meyer, Philipp T, Mintun, Mark A, Mok, Vincent, Molinuevo, José Luis, Møllergård, Hanne M, Morris, John C, Mroczko, Barbara, Van der Mussele, Stefan, Na, Duk L, Newberg, Andrew, Nordberg, Agneta, Nordlund, Arto, Novak, Gerald P, Paraskevas, George P, Parnetti, Lucilla, Perera, Gayan, Peters, Oliver, Popp, Julius, Prabhakar, Sudesh, Rabinovici, Gil D, Ramakers, Inez HGB, Rami, Lorena, de Oliveira, Catarina Resende, Rinne, Juha O, Rodrigue, Karen M, and Rodríguez-Rodríguez, Eloy

Subjects
Health Services and Systems, Health Sciences, Clinical Research, Alzheimer's Disease, Vascular Cognitive Impairment/Dementia, Acquired Cognitive Impairment, Neurosciences, Alzheimer's Disease Related Dementias (ADRD), Brain Disorders, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Cerebrovascular, Neurodegenerative, Prevention, Dementia, Aging, 4.2 Evaluation of markers and technologies, Detection, screening and diagnosis, Aetiology, 2.1 Biological and endogenous factors, Neurological, Adult, Age Factors, Aged, Aged, 80 and over, Amyloid beta-Peptides, Apolipoprotein E4, Biomarkers, Brain, Cerebrospinal Fluid, Cognitive Dysfunction, Female, Genotype, Humans, Male, Middle Aged, Positron-Emission Tomography, Prevalence, Risk Factors, Amyloid Biomarker Study Group, Medical and Health Sciences, General & Internal Medicine, Biomedical and clinical sciences, Health sciences
Abstract

ImportanceCerebral amyloid-β aggregation is an early pathological event in Alzheimer disease (AD), starting decades before dementia onset. Estimates of the prevalence of amyloid pathology in persons without dementia are needed to understand the development of AD and to design prevention studies.ObjectiveTo use individual participant data meta-analysis to estimate the prevalence of amyloid pathology as measured with biomarkers in participants with normal cognition, subjective cognitive impairment (SCI), or mild cognitive impairment (MCI).Data sourcesRelevant biomarker studies identified by searching studies published before April 2015 using the MEDLINE and Web of Science databases and through personal communication with investigators.Study selectionStudies were included if they provided individual participant data for participants without dementia and used an a priori defined cutoff for amyloid positivity.Data extraction and synthesisIndividual records were provided for 2914 participants with normal cognition, 697 with SCI, and 3972 with MCI aged 18 to 100 years from 55 studies.Main outcomes and measuresPrevalence of amyloid pathology on positron emission tomography or in cerebrospinal fluid according to AD risk factors (age, apolipoprotein E [APOE] genotype, sex, and education) estimated by generalized estimating equations.ResultsThe prevalence of amyloid pathology increased from age 50 to 90 years from 10% (95% CI, 8%-13%) to 44% (95% CI, 37%-51%) among participants with normal cognition; from 12% (95% CI, 8%-18%) to 43% (95% CI, 32%-55%) among patients with SCI; and from 27% (95% CI, 23%-32%) to 71% (95% CI, 66%-76%) among patients with MCI. APOE-ε4 carriers had 2 to 3 times higher prevalence estimates than noncarriers. The age at which 15% of the participants with normal cognition were amyloid positive was approximately 40 years for APOE ε4ε4 carriers, 50 years for ε2ε4 carriers, 55 years for ε3ε4 carriers, 65 years for ε3ε3 carriers, and 95 years for ε2ε3 carriers. Amyloid positivity was more common in highly educated participants but not associated with sex or biomarker modality.Conclusions and relevanceAmong persons without dementia, the prevalence of cerebral amyloid pathology as determined by positron emission tomography or cerebrospinal fluid findings was associated with age, APOE genotype, and presence of cognitive impairment. These findings suggest a 20- to 30-year interval between first development of amyloid positivity and onset of dementia.

Published
2015

14. Sex differences in brain atrophy in dementia with Lewy bodies.

Author

Oltra, Javier, Habich, Annegret, Schwarz, Christopher G., Nedelska, Zuzana, Przybelski, Scott A., Inguanzo, Anna, Diaz‐Galvan, Patricia, Lowe, Val J., Oppedal, Ketil, Gonzalez, Maria C., Philippi, Nathalie, Blanc, Frederic, Barkhof, Frederik, Lemstra, Afina W., Hort, Jakub, Padovani, Alessandro, Rektorova, Irena, Bonanni, Laura, Massa, Federico, and Kramberger, Milica G.

Abstract

INTRODUCTION: Sex influences neurodegeneration, but it has been poorly investigated in dementia with Lewy bodies (DLB). We investigated sex differences in brain atrophy in DLB using magnetic resonance imaging (MRI). METHODS: We included 436 patients from the European‐DLB consortium and the Mayo Clinic. Sex differences and sex‐by‐age interactions were assessed through visual atrophy rating scales (n = 327; 73 ± 8 years, 62% males) and automated estimations of regional gray matter volume and cortical thickness (n = 165; 69 ± 9 years, 72% males). RESULTS: We found a higher likelihood of frontal atrophy and smaller volumes in six cortical regions in males and thinner olfactory cortices in females. There were significant sex‐by‐age interactions in volume (six regions) and cortical thickness (seven regions) across the entire cortex. DISCUSSION: We demonstrate that males have more widespread cortical atrophy at younger ages, but differences tend to disappear with increasing age, with males and females converging around the age of 75. Highlights: Male DLB patients had higher odds for frontal atrophy on radiological visual rating scales.Male DLB patients displayed a widespread pattern of cortical gray matter alterations on automated methods.Sex differences in gray matter measures in DLB tended to disappear with increasing age. [ABSTRACT FROM AUTHOR]

Published
2024
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16. C9orf72, AAO and ancestry help discriminating behavioural from language variants in FTLD cohorts

Author

Costa, Beatrice, Manzoni, Claudia, Bernal-Quiros, Manuel, Kia, Demis A, Aguilar, Miquel, Alvarez, Ignacio, Alvarez, Victoria, Andreassen, Ole, Anfossi, Maria, Bagnoli, Silvia, Benussi, Luisa, Bernardi, Livia, Binetti, Giuliano, Blackburn, Daniel, Boada, Mercè, Borroni, Barbara, Bowns, Lucy, Bråthen, Geir, Bruni, Amalia C, Chiang, Huei-Hsin, Clarimon, Jordi, Colville, Shuna, Conidi, Maria E, Cope, Tom E, Cruchaga, Carlos, Cupidi, Chiara, Di Battista, Maria Elena, Diehl-Schmid, Janine, Diez-Fairen, Monica, Dols-Icardo, Oriol, Durante, Elisabetta, Flisar, Dušan, Frangipane, Francesca, Galimberti, Daniela, Gallo, Maura, Gallucci, Maurizio, Ghidoni, Roberta, Graff, Caroline, Grafman, Jordan H, Grossman, Murray, Hardy, John, Hernández, Isabel, Holloway, Guy JT, Huey, Edward D, Illán-Gala, Ignacio, Karydas, Anna, Khoshnood, Behzad, Kramberger, Milica G, Kristiansen, Mark, Lewis, Patrick A, Lleó, Alberto, Madhan, Gaganjit K, Maletta, Raffaele, Maver, Aleš, Menendez-Gonzalez, Manuel, Milan, Graziella, Miller, Bruce, Mol, Merel O, Momeni, Parastoo, Moreno-Grau, Sonia, Morris, Chris M, Nacmias, Benedetta, Nilsson, Christer, Novelli, Valeria, Öijerstedt, Linn, Padovani, Alessandro, Pal, Suvankar, Panchbhaya, Yasmin, Pastor, Pau, Peterlin, Borut, Piaceri, Irene, Pickering-Brown, Stuart, Pijnenburg, Yolande AL, Puca, Annibale A, Rainero, Innocenzo, Rendina, Antonella, Richardson, Anna MT, Rogaeva, Ekaterina, Rogelj, Boris, Rollinson, Sara, Rossi, Giacomina, Rossmeier, Carola, Rowe, James B, Rubino, Elisa, Ruiz, Agustín, Sanchez-Valle, Raquel, Sando, Sigrid B, Santillo, Alexander F, Saxon, Jennifer, Scarpini, Elio, Serpente, Maria, Smirne, Nicoletta, Sorbi, Sandro, Suh, EunRan, Tagliavini, Fabrizio, Thompson, Jennifer C, Trojanowski, John Q, Van Deerlin, Vivianna M, Van der Zee, Julie, Van Broeckhoven, Christine, van Rooij, Jeroen, Van Swieten, John C, Veronesi, Arianna, Vitale, Emilia, Waldö, Maria L, Woodward, Cathy, Yokoyama, Jennifer, Escott-Price, Valentina, Polke, James M, and Ferrari, Raffaele

Published
2020
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17. β-Amyloid and tau biomarkers and clinical phenotype in dementia with Lewy bodies

Author

Ferreira, Daniel, Przybelski, Scott A., Lesnick, Timothy G., Lemstra, Afina W., Londos, Elisabet, Blanc, Frederic, Nedelska, Zuzana, Schwarz, Christopher G., Graff-Radford, Jonathan, Senjem, Matthew L., Fields, Julie A., Knopman, David S., Savica, Rodolfo, Ferman, Tanis J., Graff-Radford, Neill R., Lowe, Val J., Jack, Clifford R., Jr, Petersen, Ronald C., Mollenhauer, Brit, Garcia-Ptacek, Sara, Abdelnour, Carla, Hort, Jakub, Bonanni, Laura, Oppedal, Ketil, Kramberger, Milica G., Boeve, Bradley F., Aarsland, Dag, Westman, Eric, and Kantarci, Kejal

Published
2020
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18. The impact of automated hippocampal volumetry on diagnostic confidence in patients with suspected Alzheimer's disease: A European Alzheimer's Disease Consortium study

Author

Bosco, Paolo, Redolfi, Alberto, Bocchetta, Martina, Ferrari, Clarissa, Mega, Anna, Galluzzi, Samantha, Austin, Mark, Chincarini, Andrea, Collins, D. Louis, Duchesne, Simon, Maréchal, Bénédicte, Roche, Alexis, Sensi, Francesco, Wolz, Robin, Alegret, Montserrat, Assal, Frederic, Balasa, Mircea, Bastin, Christine, Bougea, Anastasia, Emek-Savaş, Derya Durusu, Engelborghs, Sebastiaan, Grimmer, Timo, Grosu, Galina, Kramberger, Milica G., Lawlor, Brian, Mandic Stojmenovic, Gorana, Marinescu, Mihaela, Mecocci, Patrizia, Molinuevo, José Luis, Morais, Ricardo, Niemantsverdriet, Ellis, Nobili, Flavio, Ntovas, Konstantinos, O'Dwyer, Sarah, Paraskevas, George P., Pelini, Luca, Picco, Agnese, Salmon, Eric, Santana, Isabel, Sotolongo-Grau, Oscar, Spiru, Luiza, Stefanova, Elka, Popovic, Katarina Surlan, Tsolaki, Magda, Yener, Görsev G., Zekry, Dina, and Frisoni, Giovanni B.

Published
2017
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20. Predicting progression to dementia in persons with mild cognitive impairment using cerebrospinal fluid markers

Author

Handels, Ron L.H., Vos, Stephanie J.B., Kramberger, Milica G., Jelic, Vesna, Blennow, Kaj, van Buchem, Mark, van der Flier, Wiesje, Freund-Levi, Yvonne, Hampel, Harald, Olde Rikkert, Marcel, Oleksik, Ania, Pirtosek, Zvezdan, Scheltens, Philip, Soininen, Hilkka, Teunissen, Charlotte, Tsolaki, Magda, Wallin, Asa K., Winblad, Bengt, Verhey, Frans R.J., and Visser, Pieter Jelle

Published
2017
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21. Recommendations for cerebrospinal fluid Alzheimer's disease biomarkers in the diagnostic evaluation of mild cognitive impairment

Author

Herukka, Sanna-Kaisa, Simonsen, Anja Hviid, Andreasen, Niels, Baldeiras, Ines, Bjerke, Maria, Blennow, Kaj, Engelborghs, Sebastiaan, Frisoni, Giovanni B., Gabryelewicz, Tomasz, Galluzzi, Samantha, Handels, Ron, Kramberger, Milica G., Kulczyńska, Agnieszka, Molinuevo, Jose Luis, Mroczko, Barbara, Nordberg, Agneta, Oliveira, Catarina Resende, Otto, Markus, Rinne, Juha O., Rot, Uroš, Saka, Esen, Soininen, Hilkka, Struyfs, Hanne, Suardi, Silvia, Visser, Pieter Jelle, Winblad, Bengt, Zetterberg, Henrik, and Waldemar, Gunhild

Published
2017
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22. Recommendations for CSF AD biomarkers in the diagnostic evaluation of dementia

Author

Simonsen, Anja Hviid, Herukka, Sanna-Kaisa, Andreasen, Niels, Baldeiras, Ines, Bjerke, Maria, Blennow, Kaj, Engelborghs, Sebastiaan, Frisoni, Giovanni B., Gabryelewicz, Tomasz, Galluzzi, Samantha, Handels, Ron, Kramberger, Milica G., Kulczyńska, Agnieszka, Molinuevo, Jose Luis, Mroczko, Barbara, Nordberg, Agneta, Oliveira, Catarina Resende, Otto, Markus, Rinne, Juha O., Rot, Uroš, Saka, Esen, Soininen, Hilkka, Struyfs, Hanne, Suardi, Silvia, Visser, Pieter Jelle, Winblad, Bengt, Zetterberg, Henrik, and Waldemar, Gunhild

Published
2017
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23. Precision medicine in neurodegeneration: the IHI-PROMINENT project.

Author

Tate, Ashley, Suárez-Calvet, Marc, Ekelund, Mats, Eriksson, Sven, Eriksdotter, Maria, Van Der Flier, Wiesje M., Georges, Jean, Kivipelto, Miia, Kramberger, Milica G., Lindgren, Peter, Gispert López, Juan Domingo, Lötjönen, Jyrki, Persson, Sofie, Pla, Sandra, Solomon, Alina, Thurfjell, Lennart, Wimo, Anders, Winblad, Bengt, and Jönsson, Linus

Subjects
INDIVIDUALIZED medicine, ALZHEIMER'S disease, DIGITAL technology, CLINICAL decision support systems, NEURODEGENERATION
Abstract

Neurodegenerative diseases are one of the most important contributors to morbidity and mortality in the elderly. In Europe, over 14 million people are currently living with dementia, at a cost of over 400 billion EUR annually. Recent advances in diagnostics and approval for new pharmaceutical treatments for Alzheimer's disease (AD), the most common etiology of dementia, heralds the beginning of precision medicine in this field. However, their implementation will challenge an already over-burdened healthcare systems. There is a need for innovative digital solutions that can drive the related clinical pathways and optimize and personalize care delivery. Public-private partnerships are ideal vehicles to tackle these challenges. Here we describe the Innovative Health Initiative (IHI) public-private partnership project PROMINENT that has been initiated by connecting leading dementia researchers, medical professionals, dementia patients and their care partners with the latest innovative health technologies using a precision medicine based digital platform. The project builds upon the knowledge and already implemented digital tools from several collaborative initiatives that address new models for early detection, diagnosis, and monitoring of AD and other neurodegenerative disorders. The project aims to provide support to improvement efforts to each aspect of the care pathway including diagnosis, prognosis, treatment, and data collection for real world evidence and cost effectiveness studies. Ultimately the PROMINENT project is expected to lead to cost-effective care and improved health outcomes. [ABSTRACT FROM AUTHOR]

Published
2023
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25. Adopting transfer learning for neuroimaging: a comparative analysis with a custom 3D convolution neural network model

Author

Soliman, Amira, Chang, Jose R, Etminani, Kobra, Byttner, Stefan, Davidsson, Anette, Martínez-Sanchis, Begoña, Camacho, Valle, Bauckneht, Matteo, Stegeran, Roxana, Ressner, Marcus, Agudelo-Cifuentes, Marc, Chincarini, Andrea, Brendel, Matthias, Rominger, Axel, Bruffaerts, Rose, Vandenberghe, Rik, Kramberger, Milica G, Trost, Maja, Nicastro, Nicolas, Frisoni, Giovanni B, Lemstra, Afina W, Berckel, Bart N M van, Pilotto, Andrea, Padovani, Alessandro, Morbelli, Silvia, Aarsland, Dag, Nobili, Flavio, Garibotto, Valentina, Ochoa-Figueroa, Miguel, Neurology, Amsterdam Neuroscience - Neurodegeneration, and Alzheimer’s Disease Neuroimaging Initiative

Subjects
Convolution Neural Networks, Transfer Learning, Brain Neurodegenerative Disorders, Medical Image Classification, Science & Technology, DEMENTIA, Health Policy, Health Informatics, 610 Medicine & health, DIAGNOSIS, LEWY BODIES, PREVALENCE, Computer Science Applications, Biomedicinsk laboratorievetenskap/teknologi, Biomedical Laboratory Science/Technology, Human medicine, BRAIN, 610 Medizin und Gesundheit, Life Sciences & Biomedicine, Biology, Medical Informatics
Abstract

Background: In recent years, neuroimaging with deep learning (DL) algorithms have made remarkable advances in the diagnosis of neurodegenerative disorders. However, applying DL in different medical domains is usually challenged by lack of labeled data. To address this challenge, transfer learning (TL) has been applied to use state-of-the-art convolution neural networks pre-trained on natural images. Yet, there are differences in characteristics between medical and natural images, also image classification and targeted medical diagnosis tasks. The purpose of this study is to investigate the performance of specialized and TL in the classification of neurodegenerative disorders using 3D volumes of 18F-FDG-PET brain scans. Results: Results show that TL models are suboptimal for classification of neurodegenerative disorders, especially when the objective is to separate more than two disorders. Additionally, specialized CNN model provides better interpretations of predicted diagnosis. Conclusions: TL can indeed lead to superior performance on binary classification in timely and data efficient manner, yet for detecting more than a single disorder, TL models do not perform well. Additionally, custom 3D model performs comparably to TL models for binary classification, and interestingly perform better for diagnosis of multiple disorders. The results confirm the superiority of the custom 3D-CNN in providing better explainable model compared to TL adopted ones. Funding Agencies|Center for Applied Intelligent System Research (CAISR) at Halmstad University, Sweden; Department of Clinical Physiology, Department of Radiology; Center for Medical Imaging Visualization (CMIV) at Linkoeping University Hospital, Sweden; European DLB consortium; Analytic Imaging Diagnostics Arena (AIDA) initiative; VINNOVA; Formas [2017-02447]; Swedish Energy Agency; Swiss National Science Foundation; Velux Foundation [320030_169876, 320030_185028]; Flanders Research Foundation [1123]; [FWO 12I2121N]

Published
2022

26. A Cost-Consequence Analysis of Different Screening Procedures in Alzheimer’s Disease: Results from the MOPEAD Project

Author

Wimo, Anders, Belger, Mark, Sannemann, Lena, Stoekenbroek, Malou, Gurruchaga Telleria, Miren, Valero, Sergi, Vermunt, Lisa, Waterink, Lisa, Winblad, Bengt, Visser, Peter Jelle, Zwan, Marissa, Boada, Mercè, Bon, Jaka, Collaborators, consortium, members of the MOPEAD, Escher, Claus, Müller, Theresa, Bogdanovic, Nenad, Andersen, Pia, Spulber, Gabriela, Sundström, Maria, Westman, Eric, Ferreira, Daniel, Jessen, Frank, Jelic, Vesna, Haglund, Anders, Stomrud, Erik, Nelvig, Anders, Saha, Samir, Petek, Davorina, Serné, Erik, Dumas, Annette, Kramberger, Milica G, Jamilis, Laura, Johansson, Gunilla, Rodrigo Salas, Adrián, Rodríguez Gómez, Octavio, Clinical chemistry, Neurology, and Amsterdam Neuroscience - Neurodegeneration

Subjects
medicine.medical_specialty, Referral, statistics & numerical data [Internet], Cost consequences, diagnosis, Cost-Benefit Analysis, Population, costs, Primary care, Disease, cost analysis, Alzheimer Disease, Diabetes mellitus, medicine, Diabetes Mellitus, Dementia, Humans, Mass Screening, ddc:610, education, Screening procedures, education.field_of_study, Internet, Primary Health Care, business.industry, General Neuroscience, economics [Primary Health Care], screening, diagnosis [Alzheimer Disease], General Medicine, medicine.disease, Europe, Psychiatry and Mental health, Clinical Psychology, Family medicine, cost-consequence analysis, statistics & numerical data [Primary Health Care], diagnostic work-up, Geriatrics and Gerontology, Patient Participation, business, economics [Internet], Alzheimer’s disease, Research Article, dementia
Abstract

Background: For care planning and support, under-detection and late diagnosis of Alzheimer’s disease (AD) is a great challenge. Models of Patient-Engagement for Alzheimer’s Disease (MOPEAD) is an EU-funded project aiming at testing different strategies to improve this situation. Objective: To make a cost-consequence analysis of MOPEAD. Methods: Four screening strategies were tested in five countries (Germany, the Netherlands, Slovenia, Spain, and Sweden): 1) a web-approach; 2) Open-House initiative; 3) in primary care; and 4) by diabetes specialists. Persons-at-risk of AD in all strategies were offered referral to a hospital-based specialist. The primary health-economic outcome was the cost per true-positive case (TP) of AD from the screened population. Results: Of 2,847 screened persons, 1,121 screened positive (39%), 402 were evaluated at memory clinics (14%), and 236 got an AD diagnosis (8%). The cost per TP of those screened was €3,115 with the web-approach, €2,722 with the Open-House, €1,530 in primary care, and €1,190 by diabetes specialists. Sensitivity analyses that more likely reflect the real-world situation confirmed the results. The number-needed-to-screen was 30 with the web-approach, 8 with the Open-House and primary care, and 6 with the diabetes specialists. There were country differences in terms of screening rates, referrals to memory clinics, staff-types involved, and costs per TP. Conclusion: In primary care and by the diabetes specialist, the costs per TP/screened population were lowest, but the capacity of such settings to identify cases with AD-risk must be discussed. Hence new diagnostic strategies such as web-solutions and Open-House initiatives may be valuable after modifications.

Published
2021

27. Stable cerebrospinal fluid neurogranin and β-site amyloid precursor protein cleaving enzyme 1 levels differentiate predementia Alzheimer’s disease patients

Author

Kirsebom, Bjørn Eivind, primary, Richter, Grit, additional, Nordengen, Kaja, additional, Aarsland, Dag, additional, Bråthen, Geir, additional, Tijms, Betty M, additional, Visser, Pieter Jelle, additional, Nilsson, Johanna, additional, Selnes, Per, additional, Kramberger, Milica G, additional, Winblad, Bengt, additional, Waterloo, Knut, additional, Gísladóttir, Berglind, additional, Blennow, Kaj, additional, and Fladby, Tormod, additional

Published
2022
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30. A study on 3D classical versus GAN-based augmentation for MRI brain image to predict the diagnosis of dementia with Lewy bodies and Alzheimer's disease in a European multi-center study

Author

Minne, Petter, Fernandez-Quilez, Alvaro, Aarsland, Dag, Ferreira, Daniel, Westman, Eric, Lemstra, Afina W., ten Kate, Mara, Padovani, Alessandro, Rektorova, Irene, Bonanni, Laura, Mariano Nobili, Flavio, Kramberger, Milica G., Taylor, John-Paul, Hort, Jakub, Snaedal, Jon, Blanc, Frederic, Antonini, Angelo, Oppedal, Ketil, Drukker, Karen, Iftekharuddin, Khan M., Drukker, Karen, Iftekharuddin, Khan M., Neurology, Amsterdam Neuroscience - Neurodegeneration, and Radiology and nuclear medicine

Abstract

Every year around 10 million people are diagnosed with dementia worldwide. Higher life expectancy and population growth could inflate this number even further in the near future. Alzheimer's disease (AD) is one of the primary and most frequently diagnosed dementia disease in elderly subjects. On the other hand, dementia with Lewy Bodies (DLB) is the third most common cause of dementia. A timely and accurate diagnosis of dementia is critical for patients' management and treatment. However, its diagnostic is often challenging due to overlapping symptoms between the different forms of thee disease. Deep learning (DL) combined with magnetic resonance imaging (MRI) has shown potential improving the diagnostic accuracy of several neurodegenerative diseases. In spite of it, DL methods heavily rely on the availability of annotated data. Classic augmentation techniques such as translation are commonly used to increase data availability. In addition, synthetic samples obtained through generative adversarial networks (GAN) are becoming an alternative to classic augmentation. Such techniques are well-known and explored for 2D images, but little is known about their effects in a 3D setting. In this work, we explore the effects of 3D classic augmentation and 3D GAN-based augmentation to classify between AD, DLB and control subjects.

Published
2022

32. Prevalence Estimates of Amyloid Abnormality Across the Alzheimer Disease Clinical Spectrum

Author

Jansen, Willemijn J, Janssen, Olin, von Arnim, Christine, Marquié, Marta, Martinez-Lage, Pablo, Maserejian, Nancy, Mattsson, Niklas, de Mendonça, Alexandre, Meyer, Philipp T, Miller, Bruce L, Minatani, Shinobu, Mintun, Mark A, Mok, Vincent C T, Baiardi, Simone, Molinuevo, Jose Luis, Morbelli, Silvia Daniela, Morris, John C, Mroczko, Barbara, Na, Duk L, Newberg, Andrew, Nobili, Flavio, Nordberg, Agneta, Olde Rikkert, Marcel G M, de Oliveira, Catarina Resende, Baldeiras, Ines, Olivieri, Pauline, Orellana, Adela, Paraskevas, George, Parchi, Piero, Pardini, Matteo, Parnetti, Lucilla, Peters, Oliver, Poirier, Judes, Popp, Julius, Prabhakar, Sudesh, Barthel, Henryk, Rabinovici, Gil D, Ramakers, Inez H, Rami, Lorena, Reiman, Eric M, Rinne, Juha O, Rodrigue, Karen M, Rodríguez-Rodriguez, Eloy, Roe, Catherine M, Rosa-Neto, Pedro, Rosen, Howard J, Bateman, Randall J, Rot, Uros, Rowe, Christopher C, Rüther, Eckart, Ruiz, Agustín, Sabri, Osama, Sakhardande, Jayant, Sánchez-Juan, Pascual, Sando, Sigrid Botne, Santana, Isabel, Sarazin, Marie, Van Berckel, Bart, Scheltens, Philip, Schröder, Johannes, Selnes, Per, Seo, Sang Won, Silva, Dina, Skoog, Ingmar, Snyder, Peter J, Soininen, Hilkka, Sollberger, Marc, Sperling, Reisa A, Binette, Alexa Pichet, Spiru, Luisa, Stern, Yaakov, Stomrud, Erik, Takeda, Akitoshi, Teichmann, Marc, Teunissen, Charlotte E, Thompson, Louisa I, Tomassen, Jori, Tsolaki, Magda, Vandenberghe, Rik, Blennow, Kaj, Verbeek, Marcel M, Verhey, Frans R J, Villemagne, Victor, Villeneuve, Sylvia, Vogelgsang, Jonathan, Waldemar, Gunhild, Wallin, Anders, Wallin, Åsa K, Wiltfang, Jens, Wolk, David A, Boada, Merce, Yen, Tzu-Chen, Zboch, Marzena, Zetterberg, Henrik, Boecker, Henning, Tijms, Betty M, Bottlaender, Michel, den Braber, Anouk, Brooks, David J, Van Buchem, Mark A, Camus, Vincent, Carill, Jose Manuel, Cerman, Jiri, Chen, Kewei, Chételat, Gaël, Chipi, Elena, Vos, Stephanie J B, Cohen, Ann D, Daniels, Alisha, Delarue, Marion, Didic, Mira, Drzezga, Alexander, Dubois, Bruno, Eckerström, Marie, Ekblad, Laura L, Engelborghs, Sebastiaan, Epelbaum, Stéphane, Ossenkoppele, Rik, Fagan, Anne M, Fan, Yong, Fladby, Tormod, Fleisher, Adam S, Van der Flier, Wiesje M, Förster, Stefan, Fortea, Juan, Frederiksen, Kristian Steen, Freund-Levi, Yvonne, Frings, Lars, Visser, Pieter Jelle, Frisoni, Giovanni B, Fröhlich, Lutz, Gabryelewicz, Tomasz, Gertz, Hermann-Josef, Gill, Kiran Dip, Gkatzima, Olymbia, Gómez-Tortosa, Estrella, Grimmer, Timo, Guedj, Eric, Habeck, Christian G, Group, Amyloid Biomarker Study, Hampel, Harald, Handels, Ron, Hansson, Oskar, Hausner, Lucrezia, Hellwig, Sabine, Heneka, Michael, Herukka, Sanna-Kaisa, Hildebrandt, Helmut, Hodges, John, Hort, Jakub, Aarsland, Dag, Huang, Chin-Chang, Iriondo, Ane Juaristi, Itoh, Yoshiaki, Ivanoiu, Adrian, Jagust, William J, Jessen, Frank, Johannsen, Peter, Johnson, Keith A, Kandimalla, Ramesh, Kapaki, Elisabeth N, Alcolea, Daniel, Kern, Silke, Kilander, Lena, Klimkowicz-Mrowiec, Aleksandra, Klunk, William E, Koglin, Norman, Kornhuber, Johannes, Kramberger, Milica G, Kuo, Hung-Chou, Van Laere, Koen, Landau, Susan M, Altomare, Daniele, Landeau, Brigitte, Lee, Dong Young, de Leon, Mony, Leyton, Cristian E, Lin, Kun-Ju, Lleó, Alberto, Löwenmark, Malin, Madsen, Karine, Maier, Wolfgang, Marcusson, Jan, Clinical sciences, Neuroprotection & Neuromodulation, Neurology, Amsterdam Neuroscience - Brain Imaging, Amsterdam Neuroscience - Neurodegeneration, Radiology and nuclear medicine, Laboratory Medicine, Amsterdam Neuroscience - Neuroinfection & -inflammation, APH - Personalized Medicine, APH - Methodology, RS: MHeNs - R1 - Cognitive Neuropsychiatry and Clinical Neuroscience, and Psychiatrie & Neuropsychologie

Subjects
Male, MILD COGNITIVE IMPAIRMENT, epidemiology [Cognitive Dysfunction], positron emission tomography, Alzheimer`s disease Donders Center for Medical Neuroscience [Radboudumc 1], epidemiology [Alzheimer Disease], Neuroscience(all), diagnostic imaging [Cognitive Dysfunction], Amyloidogenic Proteins, tau Proteins, cerebrospinal fluid [Amyloid beta-Peptides], DIAGNOSIS, cerebrospinal fluid, Apolipoproteins E, Alzheimer Disease, Prevalence, Humans, Amyloid, Alzheimer, PET, Cognitive Dysfunction, ddc:610, cerebrospinal fluid [Peptide Fragments], Aged, Amyloid beta-Peptides, neurology, DEMENTIA, Correction, ASSOCIATION, Amyloidosis, Middle Aged, Disorders of movement Donders Center for Medical Neuroscience [Radboudumc 3], health care planning, clinical trial design, Peptide Fragments, cerebrospinal fluid [Alzheimer Disease], PET, DRIFT, Cross-Sectional Studies, cerebrospinal fluid [Biomarkers], cerebrospinal fluid [tau Proteins], Radiology Nuclear Medicine and imaging, Positron-Emission Tomography, genetics [Apolipoproteins E], Female, Neurology (clinical), diagnostic imaging [Alzheimer Disease], cerebral amyloid aggregation, Biomarkers
Abstract

Importance: One characteristic histopathological event in Alzheimer disease (AD) is cerebral amyloid aggregation, which can be detected by biomarkers in cerebrospinal fluid (CSF) and on positron emission tomography (PET) scans. Prevalence estimates of amyloid pathology are important for health care planning and clinical trial design.Objective: To estimate the prevalence of amyloid abnormality in persons with normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia and to examine the potential implications of cutoff methods, biomarker modality (CSF or PET), age, sex, APOE genotype, educational level, geographical region, and dementia severity for these estimates.Design, Setting, and Participants: This cross-sectional, individual-participant pooled study included participants from 85 Amyloid Biomarker Study cohorts. Data collection was performed from January 1, 2013, to December 31, 2020. Participants had normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia. Normal cognition and subjective cognitive decline were defined by normal scores on cognitive tests, with the presence of cognitive complaints defining subjective cognitive decline. Mild cognitive impairment and clinical AD dementia were diagnosed according to published criteria.Exposures: Alzheimer disease biomarkers detected on PET or in CSF.Main Outcomes and Measures: Amyloid measurements were dichotomized as normal or abnormal using cohort-provided cutoffs for CSF or PET or by visual reading for PET. Adjusted data-driven cutoffs for abnormal amyloid were calculated using gaussian mixture modeling. Prevalence of amyloid abnormality was estimated according to age, sex, cognitive status, biomarker modality, APOE carrier status, educational level, geographical location, and dementia severity using generalized estimating equations.Results: Among the 19 097 participants (mean [SD] age, 69.1 [9.8] years; 10 148 women [53.1%]) included, 10 139 (53.1%) underwent an amyloid PET scan and 8958 (46.9%) had an amyloid CSF measurement. Using cohort-provided cutoffs, amyloid abnormality prevalences were similar to 2015 estimates for individuals without dementia and were similar across PET- and CSF-based estimates (24%; 95% CI, 21%-28%) in participants with normal cognition, 27% (95% CI, 21%-33%) in participants with subjective cognitive decline, and 51% (95% CI, 46%-56%) in participants with mild cognitive impairment, whereas for clinical AD dementia the estimates were higher for PET than CSF (87% vs 79%; mean difference, 8%; 95% CI, 0%-16%; P = .04). Gaussian mixture modeling-based cutoffs for amyloid measures on PET scans were similar to cohort-provided cutoffs and were not adjusted. Adjusted CSF cutoffs resulted in a 10% higher amyloid abnormality prevalence than PET-based estimates in persons with normal cognition (mean difference, 9%; 95% CI, 3%-15%; P = .004), subjective cognitive decline (9%; 95% CI, 3%-15%; P = .005), and mild cognitive impairment (10%; 95% CI, 3%-17%; P = .004), whereas the estimates were comparable in persons with clinical AD dementia (mean difference, 4%; 95% CI, -2% to 9%; P = .18).Conclusions and Relevance: This study found that CSF-based estimates using adjusted data-driven cutoffs were up to 10% higher than PET-based estimates in people without dementia, whereas the results were similar among people with dementia. This finding suggests that preclinical and prodromal AD may be more prevalent than previously estimated, which has important implications for clinical trial recruitment strategies and health care planning policies.

Published
2022

33. Association of Plasma p-tau181 and p-tau231 Concentrations with Cognitive Decline in Patients with Probable Dementia with Lewy Bodies

Author

Gonzalez, Maria C., Ashton, Nicholas J., Gomes, Bárbara Fernandes, Tovar-Rios, Diego Alejandro, Blanc, Frédéric, Karikari, Thomas K., Mollenhauer, Brit, Pilotto, Andrea, Lemstra, Afina W., Paquet, Claire, Abdelnour, Carla, Kramberger, Milica G., Bonanni, Laura, Vandenberghe, Rik, Hye, Abdul, Blennow, Kaj, Zetterberg, Henrik, Aarsland, Dag, Carrarini, Claudia, Russo, Mirella, Vrillon, Agathe, Cognat, Emmanuel, Dumurgier, Julien, Hourregue, Claire, Gaubert, Sinead, Porché, Maximilien, Lilamand, Matthieu, Teunissen, Charlotte E., Bolsewig, Katharina, Anthony, Pierre, Cretin, Benjamin, Demunyck, Catherine, Martin, Catherine, Muller, Candice, Philippi, Nathalie, Ravier, Alix, Botzung, Anne, Albasser, Timothée, Epp-Ehrhard, Emmanuelle, Jung, Guillaume, Merignac, Jeanne, Monjoin, Laetitia, Poesen, Koen, Cleynen, Isabelle, Boada, Mercè, Orellana, Adela, Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie (ICube), École Nationale du Génie de l'Eau et de l'Environnement de Strasbourg (ENGEES)-Université de Strasbourg (UNISTRA)-Institut National des Sciences Appliquées - Strasbourg (INSA Strasbourg), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Institut National de Recherche en Informatique et en Automatique (Inria)-Les Hôpitaux Universitaires de Strasbourg (HUS)-Centre National de la Recherche Scientifique (CNRS)-Matériaux et Nanosciences Grand-Est (MNGE), Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Réseau nanophotonique et optique, Université de Strasbourg (UNISTRA)-Université de Haute-Alsace (UHA) Mulhouse - Colmar (Université de Haute-Alsace (UHA))-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS), Neuropsychologie Cognitive et Physiopathologie de la Schizophrénie (NCPS), Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Hôpital Civil de Strasbourg, Neurology, and Amsterdam Neuroscience - Neurodegeneration

Subjects
Lewy Body Disease, Male, medicine.medical_specialty, tau Proteins, Disease, behavioral disciplines and activities, 03 medical and health sciences, 0302 clinical medicine, Cerebrospinal fluid, Internal medicine, mental disorders, medicine, Humans, Cognitive Dysfunction, Cognitive decline, Phosphorylation, 030304 developmental biology, Aged, 0303 health sciences, Mini–Mental State Examination, medicine.diagnostic_test, business.industry, Dementia with Lewy bodies, Correction, medicine.disease, 3. Good health, Cohort, Biomarker (medicine), Female, Lewy Bodies, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Neurology (clinical), Alzheimer's disease, business, 030217 neurology & neurosurgery
Abstract

Importance: Plasma phosphorylated tau (p-tau) has proven to be an accurate biomarker for Alzheimer disease (AD) pathologic characteristics, offering a less expensive and less invasive alternative to cerebrospinal fluid (CSF) and positron emission tomography biomarkers for amyloid-β and tau. Alzheimer disease comorbid pathologic characteristics are common and are associated with more rapid cognitive decline in patients with dementia with Lewy bodies (DLB); therefore, it is anticipated that plasma p-tau concentrations may have utility in assessing cognitive impairment in individuals with this disorder. Objective: To measure the concentrations of plasma p-tau (p-tau181 and p-tau231) and evaluate their associations with cognitive decline in individuals with probable DLB. Design, Setting, and Participants: This multicenter longitudinal cohort study included participants from the European-DLB (E-DLB) Consortium cohort enrolled at 10 centers with harmonized diagnostic procedures from January 1, 2002, to December 31, 2020, with up to 5 years of follow-up. A total of 1122 participants with plasma samples were available. Participants with acute delirium or terminal illness and patients with other previous major psychiatric or neurologic disorders were excluded, leaving a cohort of 987 clinically diagnosed participants with probable DLB (n = 371), Parkinson disease (n = 204), AD (n = 207), as well as healthy controls (HCs) (n = 205). Main Outcomes and Measures: The main outcome was plasma p-tau181 and p-tau231 levels measured with in-house single molecule array assays. The Mini-Mental State Examination (MMSE) was used to measure cognition. Results: Among this cohort of 987 patients (512 men [51.9%]; mean [SD] age, 70.0 [8.8] years), patients with DLB did not differ significantly regarding age, sex, or years of education from those in the AD group, but the DLB group was older than the HC group and included more men than the AD and HC groups. Baseline concentrations of plasma p-tau181 and p-tau231 in patients with DLB were significantly higher than those in the HC group but lower than in the AD group and similar to the Parkinson disease group. Higher plasma concentrations of both p-tau markers were found in a subgroup of patients with DLB with abnormal CSF amyloid-β42 levels compared with those with normal levels (difference in the groups in p-tau181, -3.61 pg/mL; 95% CI, -5.43 to -1.79 pg/mL; P =.049; difference in the groups in p-tau231, -2.51 pg/mL; 95% CI, -3.63 to -1.39 pg/mL; P =.02). There was no difference between p-tau181 level and p-tau231 level across confirmed AD pathologic characteristcs based on reduced Aβ42 level in CSF in individuals with DLB. In DLB, a significant association was found between higher plasma p-tau181 and p-tau231 levels and lower MMSE scores at baseline (for p-tau181, -0.092 MMSE points; 95% CI, -0.12 to -0.06 MMSE points; P =.001; for p-tau231, -0.16 MMSE points; 95% CI, -0.21 to -0.12 MMSE points; P

Published
2022

39. A 3D deep learning model to predict the diagnosis of dementia with Lewy bodies, Alzheimer’s disease, and mild cognitive impairment using brain 18F-FDG PET

Author

Etminani, Kobra, primary, Soliman, Amira, additional, Davidsson, Anette, additional, Chang, Jose R., additional, Martínez-Sanchis, Begoña, additional, Byttner, Stefan, additional, Camacho, Valle, additional, Bauckneht, Matteo, additional, Stegeran, Roxana, additional, Ressner, Marcus, additional, Agudelo-Cifuentes, Marc, additional, Chincarini, Andrea, additional, Brendel, Matthias, additional, Rominger, Axel, additional, Bruffaerts, Rose, additional, Vandenberghe, Rik, additional, Kramberger, Milica G., additional, Trost, Maja, additional, Nicastro, Nicolas, additional, Frisoni, Giovanni B., additional, Lemstra, Afina W., additional, van Berckel, Bart N. M., additional, Pilotto, Andrea, additional, Padovani, Alessandro, additional, Morbelli, Silvia, additional, Aarsland, Dag, additional, Nobili, Flavio, additional, Garibotto, Valentina, additional, and Ochoa-Figueroa, Miguel, additional

Published
2021
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40. EuroInf: A Multicenter Comparative Observational Study of Apomorphine and Levodopa Infusion in Parkinsonʼs Disease

Author

Martinez-Martin, Pablo, Reddy, Prashanth, Katzenschlager, Regina, Antonini, Angelo, Todorova, Antoniya, Odin, Per, Henriksen, Tove, Martin, Anne, Calandrella, Daniela, Rizos, Alexandra, Bryndum, Narissah, Glad, Arne, Dafsari, Haidar Salimi, Timmermann, Lars, Ebersbach, Georg, Kramberger, Milica G., Samuel, Michael, Wenzel, Karoline, Tomantschger, Volker, Storch, Alexander, Reichmann, Heinz, Pirtosek, Zvezdan, Trost, Maja, Svenningsson, Per, Palhagen, Sven, Volkmann, Jens, and Chaudhuri, Ray K.

Published
2015
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41. Complementary pre‐screening strategies to uncover hidden prodromal and mild Alzheimer's disease: Results from the MOPEAD project.

Author

Boada, Mercè, Rodrigo, Adrián, Jessen, Frank, Wimblad, Bengt, Kramberger, Milica G., Visser, Pieter Jelle, Simó, Rafael, Rodríguez‐Gomez, Octavio, Ciudin, Andreea, Georges, Jean, Dumas, Annete, Maguire, Peggy, Krivec, David, Wimo, Anders, Valero, Sergi, Alegret, Montserrat, Jamilis, Laura, Zwan, Marissa, Sannemann, Lena, and Arrufat, Jordi

Abstract

Introduction: The Models of Patient Engagement for Alzheimer's Disease (MOPEAD) project was conceived to explore innovative complementary strategies to uncover hidden prodromal and mild Alzheimer's disease (AD) dementia cases and to raise awareness both in the general public and among health professionals about the importance of early diagnosis. Methods: Four different strategies or RUNs were used: (a) a web‐based (WB) prescreening tool, (2) an open house initiative (OHI), (3) a primary care–based protocol for early detection of cognitive decline (PC), and (4) a tertiary care–based pre‐screening at diabetologist clinics (DC). Results: A total of 1129 patients at high risk of having prodromal AD or dementia were identified of 2847 pre‐screened individuals (39.7%). The corresponding proportion for the different initiatives were 36.8% (WB), 35.6% (OHI), 44.4% (PC), and 58.3% (DC). Conclusion: These four complementary pre‐screening strategies were useful for identifying individuals at high risk of having prodromal or mild AD. [ABSTRACT FROM AUTHOR]

Published
2022
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42. Associations among education, age, and the dementia with Lewy bodies (DLB) metabolic pattern: A European‐DLB consortium project

Author

Bauckneht, Matteo, primary, Chincarini, Andrea, additional, Brendel, Matthias, additional, Rominger, Axel, additional, Beyer, Leonie, additional, Bruffaerts, Rose, additional, Vandenberghe, Rik, additional, Kramberger, Milica G., additional, Trost, Maja, additional, Garibotto, Valentina, additional, Nicastro, Nicolas, additional, Frisoni, Giovanni B., additional, Lemstra, Afina W., additional, Berckel, Bart N. M., additional, Pilotto, Andrea, additional, Padovani, Alessandro, additional, Ochoa‐Figueroa, Miguel A., additional, Davidsson, Anette, additional, Camacho, Valle, additional, Peira, Enrico, additional, Arnaldi, Dario, additional, Pardini, Matteo, additional, Donegani, Maria Isabella, additional, Raffa, Stefano, additional, Miceli, Alberto, additional, Sambuceti, Gianmario, additional, Aarsland, Dag, additional, Nobili, Flavio, additional, and Morbelli, Silvia, additional

Published
2021
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44. Identifying relevant outcomes in the progression of Alzheimer's disease; what do patients and care partners want to know about prognosis?

Author

Mank, Arenda, primary, van Maurik, Ingrid S., additional, Bakker, Els D., additional, van de Glind, Esther M. M., additional, Jönsson, Linus, additional, Kramberger, Milica G., additional, Novak, Petr, additional, Diaz, Ana, additional, Gove, Dianne, additional, Scheltens, Philip, additional, van der Flier, Wiesje M., additional, and Visser, Leonie N. C., additional

Published
2021
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45. European Academy of Neurology/European Alzheimer’s Disease Consortium position statement on diagnostic disclosure, biomarker counseling, and management of patients with mild cognitive impairment

Author

Frederiksen, Kristian Steen, primary, Nielsen, T. Rune, additional, Winblad, Bengt, additional, Schmidt, Reinhold, additional, Kramberger, Milica G., additional, Jones, Roy W., additional, Hort, Jakub, additional, Grimmer, Timo, additional, Georges, Jean, additional, Frölich, Lutz, additional, Engelborghs, Sebastiaan, additional, Dubois, Bruno, additional, and Waldemar, Gunhild, additional

Published
2020
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46. The IMI‐EU H2020 project MOPEAD: Outcome of different screening methods to identify MCI/early AD

Author

Winblad, Bengt, primary, Jessen, Frank, additional, Kramberger, Milica G., additional, Visser, Pieter Jelle, additional, Rodrigo, Adrián, additional, Jamilis, Laura, additional, Rodriguez‐Gomez, Octavio, additional, Sannemann, Lena, additional, Zwan, Marissa D., additional, Bon, Jaka, additional, Johansson, Gunilla, additional, Nelvig, Anders, additional, Haglund, Anders, additional, Jelic, Vesna, additional, Campo, Laura, additional, Wimo, Anders, additional, Boada, Mercè, additional, and Consortium, MOPEAD, additional

Published
2020
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47. Data‐assisted differential diagnosis of dementia by deep neural networks using MRI: A study from the European DLB consortium

Author

Larsen, Simen Norrheim, primary, Oppedal, Ketil, additional, Eftestøl, Trygve, additional, Ferreira, Daniel, additional, Lemstra, Afina W., additional, Kate, Mara ten, additional, Padovani, Alessandro, additional, Rektorova, Irena, additional, Bonanni, Laura, additional, Nobili, Flavio Mariano, additional, Kramberger, Milica G., additional, Taylor, John‐Paul, additional, Hort, Jakub, additional, Snædal, Jón, additional, Blanc, Frédéric, additional, Antonini, Angelo, additional, Borda, Miguel German, additional, Aarsland, Dag, additional, and Westman, Eric, additional

Published
2020
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50. The reliability of a deep learning model in clinical out-of-distribution MRI data: A multicohort study

Author

Mårtensson, Gustav, primary, Ferreira, Daniel, additional, Granberg, Tobias, additional, Cavallin, Lena, additional, Oppedal, Ketil, additional, Padovani, Alessandro, additional, Rektorova, Irena, additional, Bonanni, Laura, additional, Pardini, Matteo, additional, Kramberger, Milica G, additional, Taylor, John-Paul, additional, Hort, Jakub, additional, Snædal, Jón, additional, Kulisevsky, Jaime, additional, Blanc, Frederic, additional, Antonini, Angelo, additional, Mecocci, Patrizia, additional, Vellas, Bruno, additional, Tsolaki, Magda, additional, Kłoszewska, Iwona, additional, Soininen, Hilkka, additional, Lovestone, Simon, additional, Simmons, Andrew, additional, Aarsland, Dag, additional, and Westman, Eric, additional

Published
2020
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