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  • Result 31-33 of 33
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31.
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32.
  • Tosun, Duygu, et al. (author)
  • Detection of β-amyloid positivity in Alzheimer's Disease Neuroimaging Initiative participants with demographics, cognition, MRI and plasma biomarkers.
  • 2021
  • In: Brain communications. - : Oxford University Press (OUP). - 2632-1297. ; 3:2
  • Journal article (peer-reviewed)abstract
    • In vivo gold standard for the ante-mortem assessment of brain β-amyloid pathology is currently β-amyloid positron emission tomography or cerebrospinal fluid measures of β-amyloid42 or the β-amyloid42/β-amyloid40 ratio. The widespread acceptance of a biomarker classification scheme for the Alzheimer's disease continuum has ignited interest in more affordable and accessible approaches to detect Alzheimer's disease β-amyloid pathology, a process that often slows down the recruitment into, and adds to the cost of, clinical trials. Recently, there has been considerable excitement concerning the value of blood biomarkers. Leveraging multidisciplinary data from cognitively unimpaired participants and participants with mild cognitive impairment recruited by the multisite biomarker study of Alzheimer's Disease Neuroimaging Initiative, here we assessed to what extent plasma β-amyloid42/β-amyloid40, neurofilament light and phosphorylated-tau at threonine-181 biomarkers detect the presence of β-amyloid pathology, and to what extent the addition of clinical information such as demographic data, APOE genotype, cognitive assessments and MRI can assist plasma biomarkers in detecting β-amyloid-positivity. Our results confirm plasma β-amyloid42/β-amyloid40 as a robust biomarker of brain β-amyloid-positivity (area under curve, 0.80-0.87). Plasma phosphorylated-tau at threonine-181 detected β-amyloid-positivity only in the cognitively impaired with a moderate area under curve of 0.67, whereas plasma neurofilament light did not detect β-amyloid-positivity in either group of participants. Clinical information as well as MRI-score independently detected positron emission tomography β-amyloid-positivity in both cognitively unimpaired and impaired (area under curve, 0.69-0.81). Clinical information, particularly APOE ε4 status, enhanced the performance of plasma biomarkers in the detection of positron emission tomography β-amyloid-positivity by 0.06-0.14 units of area under curve for cognitively unimpaired, and by 0.21-0.25 units for cognitively impaired; and further enhancement of these models with an MRI-score of β-amyloid-positivity yielded an additional improvement of 0.04-0.11 units of area under curve for cognitively unimpaired and 0.05-0.09 units for cognitively impaired. Taken together, these multi-disciplinary results suggest that when combined with clinical information, plasma phosphorylated-tau at threonine-181 and neurofilament light biomarkers, and an MRI-score could effectively identify β-amyloid+ cognitively unimpaired and impaired (area under curve, 0.80-0.90). Yet, when the MRI-score is considered in combination with clinical information, plasma phosphorylated-tau at threonine-181 and plasma neurofilament light have minimal added value for detecting β-amyloid-positivity. Our systematic comparison of β-amyloid-positivity detection models identified effective combinations of demographics, APOE, global cognition, MRI and plasma biomarkers. Promising minimally invasive and low-cost predictors such as plasma biomarkers of β-amyloid42/β-amyloid40 may be improved by age and APOE genotype.
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33.
  • Young, Peter N.E., et al. (author)
  • Imaging biomarkers in neurodegeneration : Current and future practices
  • 2020
  • In: Alzheimer's Research and Therapy. - : Springer Science and Business Media LLC. - 1758-9193. ; 12:1
  • Research review (peer-reviewed)abstract
    • There is an increasing role for biological markers (biomarkers) in the understanding and diagnosis of neurodegenerative disorders. The application of imaging biomarkers specifically for the in vivo investigation of neurodegenerative disorders has increased substantially over the past decades and continues to provide further benefits both to the diagnosis and understanding of these diseases. This review forms part of a series of articles which stem from the University College London/University of Gothenburg course "Biomarkers in neurodegenerative diseases". In this review, we focus on neuroimaging, specifically positron emission tomography (PET) and magnetic resonance imaging (MRI), giving an overview of the current established practices clinically and in research as well as new techniques being developed. We will also discuss the use of machine learning (ML) techniques within these fields to provide additional insights to early diagnosis and multimodal analysis.
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  • Result 31-33 of 33
Type of publication
journal article (21)
conference paper (8)
research review (4)
Type of content
peer-reviewed (32)
other academic/artistic (1)
Author/Editor
Jagust, William J. (24)
Ossenkoppele, Rik (16)
Rabinovici, Gil D (15)
Blennow, Kaj, 1958 (12)
Schöll, Michael, 198 ... (11)
Zetterberg, Henrik, ... (9)
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Hansson, Oskar (9)
Baker, Suzanne L. (7)
Scheltens, Philip (7)
Mattsson, Niklas (7)
Stomrud, Erik (6)
van der Flier, Wiesj ... (6)
Molinuevo, José Luis (6)
Fagan, Anne M (6)
Shaw, Leslie M (6)
Trojanowski, John Q (6)
Frisoni, Giovanni B. (6)
Rowe, Christopher C (6)
Hampel, Harald (6)
Aarsland, Dag (5)
Tsolaki, Magda (5)
Van Laere, Koen (5)
Vandenberghe, Rik (5)
Marcusson, Jan (5)
Chen, Kewei (5)
Teunissen, Charlotte ... (5)
Rinne, Juha O. (5)
Alcolea, Daniel (5)
Fortea, Juan (5)
Lleó, Alberto (5)
Morris, John C (5)
Rami, Lorena (5)
Kornhuber, Johannes (5)
Nordberg, Agneta (5)
Grimmer, Timo (5)
Drzezga, Alexander (5)
Wiltfang, Jens (5)
Fladby, Tormod (5)
Engelborghs, Sebasti ... (5)
Mroczko, Barbara (5)
Verbeek, Marcel M (5)
Waldemar, Gunhild (5)
Visser, Pieter Jelle (5)
Cohen, Ann D (5)
Roe, Catherine M (5)
Peters, Oliver (5)
Maier, Wolfgang (5)
Sánchez-Juan, Pascua ... (5)
Petersen, Ronald C. (5)
Santana, Isabel (5)
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University
University of Gothenburg (25)
Lund University (16)
Karolinska Institutet (7)
Örebro University (4)
Linköping University (1)
Language
English (33)
Research subject (UKÄ/SCB)
Medical and Health Sciences (33)

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