Jong-Chan Park1,2,3,4, Keum Sim Jung5, Jiyeong Kim5, Ji Sung Jang5, Sunghoon Kwon5, Min Soo Byun6, Dahyun Yi7, Gihwan Byeon7, Gijung Jung7, Yu Kyeong Kim8, Dong Young Lee9,10,11, Sun-Ho Han12,13,14, Inhee Mook-Jung15,16,17. 1. Department of Biochemistry and Biomedical Sciences, College of Medicine, Seoul National University, Seoul, 03080, Republic of Korea. 2. Department of Biochemistry & Biomedical Sciences, SNU Dementia Research Center, College of Medicine, Seoul National University, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. 3. Department of Biochemistry & Biomedical Sciences, Neuroscience Research Institute, Medical Research Center, College of Medicine, Seoul National University, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. 4. Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, WC1E 6BT, UK. 5. QuantaMatrix Inc., Seoul, 03080, Republic of Korea. 6. Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, 13620, Republic of Korea. 7. Department of Neuropsychiatry, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. 8. Department of Nuclear Medicine, SMG-SNU Boramae Medical Center, Seoul, 07061, Republic of Korea. 9. Department of Neuropsychiatry, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. selfpsy@snu.ac.kr. 10. Department of Psychiatry, College of medicine, Seoul National University, Seoul, 03080, Republic of Korea. selfpsy@snu.ac.kr. 11. Institute of Human Behavioral Medicine, Medical Research Center, Seoul National University, Seoul, 03080, Republic of Korea. selfpsy@snu.ac.kr. 12. Department of Biochemistry and Biomedical Sciences, College of Medicine, Seoul National University, Seoul, 03080, Republic of Korea. sunho@snu.ac.kr. 13. Department of Biochemistry & Biomedical Sciences, SNU Dementia Research Center, College of Medicine, Seoul National University, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. sunho@snu.ac.kr. 14. Department of Biochemistry & Biomedical Sciences, Neuroscience Research Institute, Medical Research Center, College of Medicine, Seoul National University, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. sunho@snu.ac.kr. 15. Department of Biochemistry and Biomedical Sciences, College of Medicine, Seoul National University, Seoul, 03080, Republic of Korea. inhee@snu.ac.kr. 16. Department of Biochemistry & Biomedical Sciences, SNU Dementia Research Center, College of Medicine, Seoul National University, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. inhee@snu.ac.kr. 17. Department of Biochemistry & Biomedical Sciences, Neuroscience Research Institute, Medical Research Center, College of Medicine, Seoul National University, 103 Daehak-ro, Jongno-gu, Seoul, 03080, Republic of Korea. inhee@snu.ac.kr.
Abstract
BACKGROUND: Alzheimer's disease (AD) is an irreversible neurodegenerative disease characterized by the hallmark finding of cerebral amyloid deposition. Many researchers have tried to predict the existence of cerebral amyloid deposition by using easily accessible blood plasma samples, but the effectiveness of such strategies remains controversial. METHODS: We developed a new multiplex kit, the QPLEX™ Alz plus assay kit, which uses proteomics-based blood biomarkers to prescreen for cerebral amyloid deposition. A total of 300 participants who underwent Pittsburgh compound B (PiB)-positron emission tomography (PET) which allows imaging of cerebral amyloid deposition were included in this study. We compared the levels of QPLEX™ biomarkers between patients who were classified as PiB-negative or PiB-positive, regardless of their cognitive function. Logistic regression analysis followed by receiver operating characteristic (ROC) curve analysis was performed. The kit accuracy was tested using a randomized sample selection method. RESULTS: The results obtained using our assay kit reached 89.1% area under curve (AUC) with 80.0% sensitivity and 83.0% specificity. Further validation of the QPLEX™ Alz plus assay kit using a randomized sample selection method showed an average accuracy of 81.5%. CONCLUSIONS: Our QPLEX™ Alz plus assay kit provides preliminary evidence that it can be used as blood marker to predict cerebral amyloid deposition but independent validation is needed.
BACKGROUND:Alzheimer's disease (AD) is an irreversible neurodegenerative disease characterized by the hallmark finding of cerebral amyloid deposition. Many researchers have tried to predict the existence of cerebral amyloid deposition by using easily accessible blood plasma samples, but the effectiveness of such strategies remains controversial. METHODS: We developed a new multiplex kit, the QPLEX™ Alz plus assay kit, which uses proteomics-based blood biomarkers to prescreen for cerebral amyloid deposition. A total of 300 participants who underwent Pittsburgh compound B (PiB)-positron emission tomography (PET) which allows imaging of cerebral amyloid deposition were included in this study. We compared the levels of QPLEX™ biomarkers between patients who were classified as PiB-negative or PiB-positive, regardless of their cognitive function. Logistic regression analysis followed by receiver operating characteristic (ROC) curve analysis was performed. The kit accuracy was tested using a randomized sample selection method. RESULTS: The results obtained using our assay kit reached 89.1% area under curve (AUC) with 80.0% sensitivity and 83.0% specificity. Further validation of the QPLEX™ Alz plus assay kit using a randomized sample selection method showed an average accuracy of 81.5%. CONCLUSIONS: Our QPLEX™ Alz plus assay kit provides preliminary evidence that it can be used as blood marker to predict cerebral amyloid deposition but independent validation is needed.
Authors: Michelle M Mielke; Clinton E Hagen; Jing Xu; Xiyun Chai; Prashanthi Vemuri; Val J Lowe; David C Airey; David S Knopman; Rosebud O Roberts; Mary M Machulda; Clifford R Jack; Ronald C Petersen; Jeffrey L Dage Journal: Alzheimers Dement Date: 2018-04-05 Impact factor: 21.566
Authors: Jong-Chan Park; Sun-Ho Han; Hyun Jin Cho; Min Soo Byun; Dahyun Yi; Young Min Choe; Seokjo Kang; Eun Sun Jung; Su Jin Won; Eun Hye Kim; Yu Kyeong Kim; Dong Young Lee; Inhee Mook-Jung Journal: Alzheimers Res Ther Date: 2017-03-22 Impact factor: 6.982
Authors: Andrea Vergallo; Lucile Mégret; Simone Lista; Enrica Cavedo; Henrik Zetterberg; Kaj Blennow; Eugeen Vanmechelen; Ann De Vos; Marie-Odile Habert; Marie-Claude Potier; Bruno Dubois; Christian Neri; Harald Hampel Journal: Alzheimers Dement Date: 2019-05-18 Impact factor: 21.566