Qiao-Xin Li1, Victor L Villemagne1,2, James D Doecke3, Alan Rembach1, Shannon Sarros1, Shiji Varghese1, Amelia McGlade1, Katrina M Laughton1, Kelly K Pertile1, Christopher J Fowler1, Rebecca L Rumble1, Brett O Trounson1, Kevin Taddei4,5, Stephanie R Rainey-Smith4,5, Simon M Laws4,5, Joanne S Robertson1, Lisbeth A Evered6, Brendan Silbert6, Kathryn A Ellis1,7, Christopher C Rowe1,2, S Lance Macaulay8, David Darby1, Ralph N Martins4,5,9, David Ames7,10, Colin L Masters1, Steven Collins1,11. 1. Florey Institute of Neuroscience and Mental Health, The University of Melbourne, VIC, Australia. 2. Department of Nuclear Medicine and Centre for PET, Austin Health, Heidelberg, VIC, Australia. 3. CSIRO Digital Productivity/Australian e-Health Research Centre and Cooperative Research Centre for Mental Health, Brisbane, QLD, Australia. 4. Centre of Excellence for Alzheimer's Disease Research & Care, School of Medical Sciences, Edith Cowan University, Joondalup, Western Australia, Australia. 5. Sir James McCusker Alzheimer's Disease Research Unit (Hollywood Private Hospital), Perth, WA, Australia. 6. Centre for Anaesthesia and Cognitive Function, Department of Anaesthesia, and Department of Surgery, St. Vincent's Hospital, The University of Melbourne, VIC, Australia. 7. The University of Melbourne Academic Unit for Psychiatry of Old Age, St George's Hospital, Kew, VIC, Australia. 8. CSIRO Food and Nutrition Flagship, Parkville, VIC, Australia. 9. School of Psychiatry and Clinical Neurosciences, University of Western Australia, Perth, Western Australia, Australia. 10. National Ageing Research Institute, Parkville, VIC, Australia. 11. Department of Pathology, The University of Melbourne, Parkville, Australia.
Abstract
BACKGROUND: The cerebrospinal fluid (CSF) amyloid-β (Aβ)(1-42), total-tau (T-tau), and phosphorylated-tau (P-tau181P) profile has been established as a valuable biomarker for Alzheimer's disease (AD). OBJECTIVE: The current study aimed to determine CSF biomarker cut-points using positron emission tomography (PET) Aβ imaging screened subjects from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging, as well as correlate CSF analyte cut-points across a range of PET Aβ amyloid ligands. METHODS: Aβ pathology was determined by PET imaging, utilizing ¹¹C-Pittsburgh Compound B, ¹⁸F-flutemetamol, or ¹⁸F-florbetapir, in 157 AIBL participants who also underwent CSF collection. Using an INNOTEST assay, cut-points were established (Aβ(1-42) >544 ng/L, T-tau <407 ng/L, and P-tau181P <78 ng/L) employing a rank based method to define a "positive" CSF in the sub-cohort of amyloid-PET negative healthy participants (n = 97), and compared with the presence of PET demonstrated AD pathology. RESULTS: CSF Aβ(1-42) was the strongest individual biomarker, detecting cognitively impaired PET positive mild cognitive impairment (MCI)/AD with 85% sensitivity and 91% specificity. The ratio of P-tau181P or T-tau to Aβ(1-42) provided greater accuracy, predicting MCI/AD with Aβ pathology with ≥92% sensitivity and specificity. Cross-validated accuracy, using all three biomarkers or the ratio of P-tau or T-tau to Aβ(1-42) to predict MCI/AD, reached ≥92% sensitivity and specificity. CONCLUSIONS: CSF Aβ(1-42) levels and analyte combination ratios demonstrated very high correlation with PET Aβ imaging. Our study offers additional support for CSF biomarkers in the early and accurate detection of AD pathology, including enrichment of patient cohorts for treatment trials even at the pre-symptomatic stage.
BACKGROUND: The cerebrospinal fluid (CSF) amyloid-β (Aβ)(1-42), total-tau (T-tau), and phosphorylated-tau (P-tau181P) profile has been established as a valuable biomarker for Alzheimer's disease (AD). OBJECTIVE: The current study aimed to determine CSF biomarker cut-points using positron emission tomography (PET) Aβ imaging screened subjects from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging, as well as correlate CSF analyte cut-points across a range of PET Aβ amyloid ligands. METHODS: Aβ pathology was determined by PET imaging, utilizing ¹¹C-Pittsburgh Compound B, ¹⁸F-flutemetamol, or ¹⁸F-florbetapir, in 157 AIBL participants who also underwent CSF collection. Using an INNOTEST assay, cut-points were established (Aβ(1-42) >544 ng/L, T-tau <407 ng/L, and P-tau181P <78 ng/L) employing a rank based method to define a "positive" CSF in the sub-cohort of amyloid-PET negative healthy participants (n = 97), and compared with the presence of PET demonstrated AD pathology. RESULTS: CSF Aβ(1-42) was the strongest individual biomarker, detecting cognitively impaired PET positive mild cognitive impairment (MCI)/AD with 85% sensitivity and 91% specificity. The ratio of P-tau181P or T-tau to Aβ(1-42) provided greater accuracy, predicting MCI/AD with Aβ pathology with ≥92% sensitivity and specificity. Cross-validated accuracy, using all three biomarkers or the ratio of P-tau or T-tau to Aβ(1-42) to predict MCI/AD, reached ≥92% sensitivity and specificity. CONCLUSIONS: CSF Aβ(1-42) levels and analyte combination ratios demonstrated very high correlation with PET Aβ imaging. Our study offers additional support for CSF biomarkers in the early and accurate detection of AD pathology, including enrichment of patient cohorts for treatment trials even at the pre-symptomatic stage.
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Authors: Christopher Fowler; Stephanie R Rainey-Smith; Sabine Bird; Julia Bomke; Pierrick Bourgeat; Belinda M Brown; Samantha C Burnham; Ashley I Bush; Carolyn Chadunow; Steven Collins; James Doecke; Vincent Doré; Kathryn A Ellis; Lis Evered; Amir Fazlollahi; Jurgen Fripp; Samantha L Gardener; Simon Gibson; Robert Grenfell; Elise Harrison; Richard Head; Liang Jin; Adrian Kamer; Fiona Lamb; Nicola T Lautenschlager; Simon M Laws; Qiao-Xin Li; Lucy Lim; Yen Ying Lim; Andrea Louey; S Lance Macaulay; Lucy Mackintosh; Ralph N Martins; Paul Maruff; Colin L Masters; Simon McBride; Lidija Milicic; Madeline Peretti; Kelly Pertile; Tenielle Porter; Morgan Radler; Alan Rembach; Joanne Robertson; Mark Rodrigues; Christopher C Rowe; Rebecca Rumble; Olivier Salvado; Greg Savage; Brendan Silbert; Magdalene Soh; Hamid R Sohrabi; Kevin Taddei; Tania Taddei; Christine Thai; Brett Trounson; Regan Tyrrell; Michael Vacher; Shiji Varghese; Victor L Villemagne; Michael Weinborn; Michael Woodward; Ying Xia; David Ames Journal: J Alzheimers Dis Rep Date: 2021-06-03
Authors: Min Soo Byun; Song E Kim; Jinsick Park; Dahyun Yi; Young Min Choe; Bo Kyung Sohn; Hyo Jung Choi; Hyewon Baek; Ji Young Han; Jong Inn Woo; Dong Young Lee Journal: PLoS One Date: 2015-11-30 Impact factor: 3.240