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Colmant L, Boyer E, Gerard T, Sleegers K, Lhommel R, Ivanoiu A, Lefèvre P, Kienlen-Campard P, Hanseeuw B. Definition of a Threshold for the Plasma Aβ42/Aβ40 Ratio Measured by Single-Molecule Array to Predict the Amyloid Status of Individuals without Dementia. Int J Mol Sci 2024; 25:1173. [PMID: 38256246 PMCID: PMC10816992 DOI: 10.3390/ijms25021173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 01/15/2024] [Accepted: 01/16/2024] [Indexed: 01/24/2024] Open
Abstract
Alzheimer's disease (AD) is characterized by amyloid beta (Aβ) plaques and hyperphosphorylated tau in the brain. Aβ plaques precede cognitive impairments and can be detected through amyloid-positron emission tomography (PET) or in cerebrospinal fluid (CSF). Assessing the plasma Aβ42/Aβ40 ratio seems promising for non-invasive and cost-effective detection of brain Aβ accumulation. This approach involves some challenges, including the accuracy of blood-based biomarker measurements and the establishment of clear, standardized thresholds to categorize the risk of developing brain amyloid pathology. Plasma Aβ42/Aβ40 ratio was measured in 277 volunteers without dementia, 70 AD patients and 18 non-AD patients using single-molecule array. Patients (n = 88) and some volunteers (n = 66) were subject to evaluation of amyloid status by CSF Aβ quantification or PET analysis. Thresholds of plasma Aβ42/Aβ40 ratio were determined based on a Gaussian mixture model, a decision tree, and the Youden's index. The 0.0472 threshold, the one with the highest sensitivity, was retained for general population without dementia screening, and the 0.0450 threshold was retained for research and clinical trials recruitment, aiming to minimize the need for CSF or PET analyses to identify amyloid-positive individuals. These findings offer a promising step towards a cost-effective method for identifying individuals at risk of developing AD.
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Affiliation(s)
- Lise Colmant
- Institute of Neuroscience, UCLouvain, 1200 Brussels, Belgium; (L.C.); (E.B.); (T.G.); (P.L.); (P.K.-C.)
- Neurology Department, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium;
- Institute of Information and Communication Technologies, Electronics and Applied Mathematics, UCLouvain, 1348 Louvain-la-Neuve, Belgium
| | - Emilien Boyer
- Institute of Neuroscience, UCLouvain, 1200 Brussels, Belgium; (L.C.); (E.B.); (T.G.); (P.L.); (P.K.-C.)
- Neurology Department, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium;
| | - Thomas Gerard
- Institute of Neuroscience, UCLouvain, 1200 Brussels, Belgium; (L.C.); (E.B.); (T.G.); (P.L.); (P.K.-C.)
- Neurology Department, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium;
| | - Kristel Sleegers
- Complex Genetics of Alzheimer’s Disease Group, VIB-UAntwerp Center for Molecular Neurology, University of Antwerp, 2000 Antwerpen, Belgium;
| | - Renaud Lhommel
- Neurology Department, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium;
| | - Adrian Ivanoiu
- Institute of Neuroscience, UCLouvain, 1200 Brussels, Belgium; (L.C.); (E.B.); (T.G.); (P.L.); (P.K.-C.)
- Neurology Department, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium;
| | - Philippe Lefèvre
- Institute of Neuroscience, UCLouvain, 1200 Brussels, Belgium; (L.C.); (E.B.); (T.G.); (P.L.); (P.K.-C.)
- Institute of Information and Communication Technologies, Electronics and Applied Mathematics, UCLouvain, 1348 Louvain-la-Neuve, Belgium
| | - Pascal Kienlen-Campard
- Institute of Neuroscience, UCLouvain, 1200 Brussels, Belgium; (L.C.); (E.B.); (T.G.); (P.L.); (P.K.-C.)
| | - Bernard Hanseeuw
- Institute of Neuroscience, UCLouvain, 1200 Brussels, Belgium; (L.C.); (E.B.); (T.G.); (P.L.); (P.K.-C.)
- Neurology Department, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium;
- WELBIO Department, WEL Research Institute, Avenue Pasteur, 6, 1300 Wavre, Belgium
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Tanaka T, Ruifen JC, Nai YH, Tan CH, Lim CZJ, Zhang Y, Stephenson MC, Hilal S, Saridin FN, Gyanwali B, Villaraza S, Robins EG, Ihara M, Schöll M, Zetterberg H, Blennow K, Ashton NJ, Shao H, Reilhac A, Chen C. Head-to-head comparison of amplified plasmonic exosome Aβ42 platform and single-molecule array immunoassay in a memory clinic cohort. Eur J Neurol 2021; 28:1479-1489. [PMID: 33370497 DOI: 10.1111/ene.14704] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Accepted: 12/20/2020] [Indexed: 12/16/2022]
Abstract
BACKGROUND AND PURPOSE Various blood biomarkers reflecting brain amyloid-β (Aβ) load have recently been proposed with promising results. However, to date, no comparative study amongst blood biomarkers has been reported. Our objective was to examine the diagnostic performance and cost effectiveness of three blood biomarkers on the same cohort. METHODS Using the same cohort (n = 68), the performances of the single-molecule array (Simoa) Aβ40, Aβ42, Aβ42/Aβ40 and the amplified plasmonic exosome (APEX) Aβ42 blood biomarkers were compared using amyloid positron emission tomography (PET) as the reference standard. The extent to which these blood tests can reduce the recruitment cost of clinical trials was also determined by identifying amyloid positive (Aβ+) participants. RESULTS Compared to Simoa biomarkers, APEX-Aβ42 showed significantly higher correlations with amyloid PET retention values and excellent diagnostic performance (sensitivity 100%, specificity 93.3%, area under the curve 0.995). When utilized for clinical trial recruitment, our simulation showed that pre-screening with blood biomarkers followed by a confirmatory amyloid PET imaging would roughly half the cost (56.8% reduction for APEX-Aβ42 and 48.6% for Simoa-Aβ42/Aβ40) compared to the situation where only PET imaging is used. Moreover, with 100% sensitivity, APEX-Aβ42 pre-screening does not increase the required number of initial participants. CONCLUSIONS With its high diagnostic performance, APEX is an ideal candidate for Aβ+ subject identification, monitoring and primary care screening, and could efficiently enrich clinical trials with Aβ+ participants whilst halving recruitment costs.
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Affiliation(s)
- Tomotaka Tanaka
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.,Clinical Imaging Research Centre, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.,Department of Neurology, National Cerebral and Cardiovascular Center, Osaka, Japan
| | - Joyce Chong Ruifen
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Ying-Hwey Nai
- Clinical Imaging Research Centre, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Chin Hong Tan
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.,Division of Psychology, Nanyang Technological University, Singapore, Singapore
| | - Carine Z J Lim
- Department of Biomedical Engineering, Faculty of Engineering, National University of Singapore, Singapore, Singapore.,Institute for Health Innovation and Technology, National University of Singapore, Singapore, Singapore
| | - Yan Zhang
- Department of Biomedical Engineering, Faculty of Engineering, National University of Singapore, Singapore, Singapore
| | - Mary C Stephenson
- Clinical Imaging Research Centre, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Saima Hilal
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.,Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Francis N Saridin
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Bibek Gyanwali
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Steven Villaraza
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Edward G Robins
- Clinical Imaging Research Centre, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.,Singapore Bioimaging Consortium, Agency for Science, A*Star, Singapore, Singapore
| | - Masafumi Ihara
- Department of Neurology, National Cerebral and Cardiovascular Center, Osaka, Japan
| | - Michael Schöll
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, 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
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.,Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden.,Maurice Wohl Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,NIHR Biomedical Research Centre for Mental Health, Biomedical Research Unit for Dementia at South London, and Maudsley NHS Foundation, London, UK
| | - Huilin Shao
- Department of Biomedical Engineering, Faculty of Engineering, National University of Singapore, Singapore, Singapore.,Institute for Health Innovation and Technology, National University of Singapore, Singapore, Singapore
| | - Anthonin Reilhac
- Clinical Imaging Research Centre, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Christopher Chen
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
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