Leslie M Shaw1, Oskar Hansson2, Ekaterina Manuilova3, Colin L Masters4, James D Doecke5, Qiao-Xin Li6, Sandra Rutz7, Monika Widmann8, Andreas Leinenbach9, Kaj Blennow10. 1. Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd, Philadelphia, PA 19104, USA. Electronic address: leslie.shaw2@uphs.upenn.edu. 2. Clinical Memory Research Unit, Lund University, VO Minnessjukdomar, Simrisbanv 14/4, 212 24 Malmö, Sweden; Memory Clinic, Skåne University Hospital, Inga Marie Nilssons gata 47, 214 21 Malmö, Sweden. Electronic address: oskar.hansson@med.lu.se. 3. Roche Diagnostics GmbH, Nonnenwald 2, 82377 Penzberg, Germany. Electronic address: ekaterina.manuilova@roche.com. 4. The Florey Institute of Neuroscience and Mental Health, University of Melbourne, 30 Royal Parade, Parkville, VIC 3052, Australia. Electronic address: c.masters@unimelb.edu.au. 5. The Commonwealth Scientific and Industrial Research Organisation/Australian E-Health Research Centre, Butterfield St & Bowen Bridge Rd, Herston, QLD 4029, Australia. Electronic address: james.doecke@csiro.au. 6. The Florey Institute of Neuroscience and Mental Health, University of Melbourne, 30 Royal Parade, Parkville, VIC 3052, Australia. Electronic address: q.li@unimelb.edu.au. 7. Roche Diagnostics GmbH, Nonnenwald 2, 82377 Penzberg, Germany. Electronic address: sandra.rutz@roche.com. 8. Roche Diagnostics GmbH, Sandhofer Str. 116, 68305 Mannheim, Germany. Electronic address: monika.widmann@roche.com. 9. Roche Diagnostics GmbH, Inselkammerstraße 8, 82008 Unterhaching, Munich, Germany. Electronic address: andreas.leinenbach@roche.com. 10. Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Göteborgsvägen 31, 431 80 Mölndal, Sweden; Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at University of Gothenburg, Wallinsgatan 6, 431 41 Mölndal, Sweden. Electronic address: kaj.blennow@neuro.gu.se.
Abstract
BACKGROUND: Alzheimer's disease (AD) biomarkers, such as cerebrospinal fluid (CSF) amyloid-β (1-42; Aβ42), can provide high diagnostic accuracy. Several immunoassays are available for Aβ42 quantitation, but standardisation across assays remains an issue. We compared the Elecsys® β-Amyloid (1-42) CSF assay with three assays and two liquid chromatography tandem mass spectrometry (LC-MS/MS) methods. METHODS: Three method comparison studies evaluated the correlation between the Elecsys® β-Amyloid (1-42) CSF assay versus: INNOTEST® β-AMYLOID(1-42) (860 samples) and the Roche Diagnostics-developed LC-MS/MS method (250 samples); INNO-BIA AlzBio3 and the University of Pennsylvania (UPenn)-developed LC-MS/MS method (250 samples); and ADx-EUROIMMUN Beta-Amyloid (1-42) enzyme-linked immunosorbent assay (ELISA) (49 samples). RESULTS: High correlation was demonstrated between Elecsys® β-Amyloid (1-42) CSF and comparator assays: INNOTEST® β-AMYLOID(1-42) (Spearman's ρ, 0.954); INNO-BIA AlzBio3 (Spearman's ρ, 0.864); ADx-EUROIMMUN Beta-Amyloid (1-42) ELISA (Pearson's r, 0.925). Elecsys® assay and LC-MS/MS measurements were highly correlated: Pearson's r, 0.949 (Roche Diagnostics-developed method) and 0.943 (UPenn-developed method). CONCLUSION: Findings from this multicentre evaluation further support use of the Elecsys® β-Amyloid (1-42) CSF assay to aid AD diagnosis. CSF-based certified reference materials should improve agreement across assays and mass spectrometry-based methods, which is essential to establish a global uniform CSF Aβ42 cut-off to detect amyloid pathology.
BACKGROUND:Alzheimer's disease (AD) biomarkers, such as cerebrospinal fluid (CSF) amyloid-β (1-42; Aβ42), can provide high diagnostic accuracy. Several immunoassays are available for Aβ42 quantitation, but standardisation across assays remains an issue. We compared the Elecsys® β-Amyloid (1-42) CSF assay with three assays and two liquid chromatography tandem mass spectrometry (LC-MS/MS) methods. METHODS: Three method comparison studies evaluated the correlation between the Elecsys® β-Amyloid (1-42) CSF assay versus: INNOTEST® β-AMYLOID(1-42) (860 samples) and the Roche Diagnostics-developed LC-MS/MS method (250 samples); INNO-BIA AlzBio3 and the University of Pennsylvania (UPenn)-developed LC-MS/MS method (250 samples); and ADx-EUROIMMUN Beta-Amyloid (1-42) enzyme-linked immunosorbent assay (ELISA) (49 samples). RESULTS: High correlation was demonstrated between Elecsys® β-Amyloid (1-42) CSF and comparator assays: INNOTEST® β-AMYLOID(1-42) (Spearman's ρ, 0.954); INNO-BIA AlzBio3 (Spearman's ρ, 0.864); ADx-EUROIMMUN Beta-Amyloid (1-42) ELISA (Pearson's r, 0.925). Elecsys® assay and LC-MS/MS measurements were highly correlated: Pearson's r, 0.949 (Roche Diagnostics-developed method) and 0.943 (UPenn-developed method). CONCLUSION: Findings from this multicentre evaluation further support use of the Elecsys® β-Amyloid (1-42) CSF assay to aid AD diagnosis. CSF-based certified reference materials should improve agreement across assays and mass spectrometry-based methods, which is essential to establish a global uniform CSF Aβ42 cut-off to detect amyloid pathology.
Authors: Michelle R Campbell; Susan Ashrafzadeh-Kian; Ronald C Petersen; Michelle M Mielke; Jeremy A Syrjanen; Argonde C van Harten; Val J Lowe; Clifford R Jack; Joshua A Bornhorst; Alicia Algeciras-Schimnich Journal: Alzheimers Dement (Amst) Date: 2021-05-18
Authors: Jagan A Pillai; Gurkan Bebek; Maria Khrestian; James Bena; Cornelia C Bergmann; William S Bush; James B Leverenz; Lynn M Bekris Journal: Front Aging Neurosci Date: 2021-02-25 Impact factor: 5.750
Authors: Jagan A Pillai; Maria Khrestian; James Bena; James B Leverenz; Lynn M Bekris Journal: Front Aging Neurosci Date: 2021-06-29 Impact factor: 5.750