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Na H, Shin KY, Lee D, Yoon C, Han SH, Park JC, Mook-Jung I, Jang J, Kwon S. The QPLEX™ Plus Assay Kit for the Early Clinical Diagnosis of Alzheimer's Disease. Int J Mol Sci 2023; 24:11119. [PMID: 37446296 DOI: 10.3390/ijms241311119] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 07/02/2023] [Accepted: 07/03/2023] [Indexed: 07/15/2023] Open
Abstract
We recently developed a multiplex diagnostic kit, QPLEX™ Alz plus assay kit, which captures amyloid-β1-40, galectin-3 binding protein, angiotensin-converting enzyme, and periostin simultaneously using microliters of peripheral blood and utilizes an optimized algorithm for screening Alzheimer's disease (AD) by correlating with cerebral amyloid deposition. Owing to the demand for early AD detection, we investigate the potential of our kit for the early clinical diagnosis of AD. A total of 1395 participants were recruited, and their blood samples were analyzed with the QPLEX™ kit. The average of QPLEX™ algorithm values in each group increased gradually in the order of the clinical progression continuum of AD: cognitively normal (0.382 ± 0.150), subjective cognitive decline (0.452 ± 0.130), mild cognitive impairment (0.484 ± 0.129), and AD (0.513 ± 0.136). The algorithm values between each group showed statistically significant differences among groups divided by Mini-Mental State Examination and Clinical Dementia Rating. The QPLEX™ algorithm values could be used to distinguish the clinical continuum of AD or cognitive function. Because blood-based diagnosis is more accessible, convenient, and cost- and time-effective than cerebral spinal fluid or positron emission tomography imaging-based diagnosis, the QPLEX™ kit can potentially be used for health checkups and the early clinical diagnosis of AD.
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Affiliation(s)
- Hunjong Na
- Department of Electrical and Computer Engineering, Seoul National University, Seoul 08826, Republic of Korea
- QuantaMatrix Inc., Seoul 08506, Republic of Korea
| | - Ki Young Shin
- Bio-MAX Institute, Seoul National University, Seoul 08826, Republic of Korea
| | - Dokyung Lee
- QuantaMatrix Inc., Seoul 08506, Republic of Korea
| | | | - Sun-Ho Han
- Department of Biochemistry and Biomedical Sciences, College of Medicine, Seoul National University, Seoul 03080, Republic of Korea
- Neuroscience Research Institute, Medical Research Center, College of Medicine, Seoul National University, Seoul 03080, Republic of Korea
- SNU Dementia Research Center, College of Medicine, Seoul National University, Seoul 03080, Republic of Korea
| | - Jong-Chan Park
- Department of Biochemistry and Biomedical Sciences, College of Medicine, Seoul National University, Seoul 03080, Republic of Korea
- Neuroscience Research Institute, Medical Research Center, College of Medicine, Seoul National University, Seoul 03080, Republic of Korea
- SNU Dementia Research Center, College of Medicine, Seoul National University, Seoul 03080, Republic of Korea
| | - Inhee Mook-Jung
- Department of Biochemistry and Biomedical Sciences, College of Medicine, Seoul National University, Seoul 03080, Republic of Korea
- Neuroscience Research Institute, Medical Research Center, College of Medicine, Seoul National University, Seoul 03080, Republic of Korea
- SNU Dementia Research Center, College of Medicine, Seoul National University, Seoul 03080, Republic of Korea
| | - Jisung Jang
- QuantaMatrix Inc., Seoul 08506, Republic of Korea
| | - Sunghoon Kwon
- Department of Electrical and Computer Engineering, Seoul National University, Seoul 08826, Republic of Korea
- QuantaMatrix Inc., Seoul 08506, Republic of Korea
- Bio-MAX Institute, Seoul National University, Seoul 08826, Republic of Korea
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Abdelnour C, Agosta F, Bozzali M, Fougère B, Iwata A, Nilforooshan R, Takada LT, Viñuela F, Traber M. Perspectives and challenges in patient stratification in Alzheimer’s disease. Alzheimers Res Ther 2022; 14:112. [PMID: 35964143 PMCID: PMC9375274 DOI: 10.1186/s13195-022-01055-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 07/27/2022] [Indexed: 12/14/2022]
Abstract
Background Patient stratification is the division of a patient population into distinct subgroups based on the presence or absence of particular disease characteristics. As patient stratification can be used to account for the underlying pathology of a disease, it can help physicians to tailor therapeutic interventions to individuals and optimize their care management and treatment regime. Alzheimer’s disease, the most common form of dementia, is a heterogeneous disease and its management benefits from patient stratification in clinical trials, and the development of personalized care and treatment strategies for people living with the disease. Main body In this review, we discuss the importance of the stratification of people living with Alzheimer’s disease, the challenges associated with early diagnosis and patient stratification, and the evolution of patient stratification once disease-modifying therapies become widely available. Conclusion Patient stratification plays an important role in drug development in clinical trials and may play an even larger role in clinical practice. A timely diagnosis and stratification of people living with Alzheimer’s disease is paramount in determining people who are at risk of progressing from mild cognitive impairment to Alzheimer’s dementia. There are key issues associated with stratifying patients which include the heterogeneity and complex neurobiology behind Alzheimer’s disease, our inadequately prepared healthcare systems, and the cultural perceptions of Alzheimer’s disease. Stratifying people living with Alzheimer’s disease may be the key in establishing precision and personalized medicine in the field, optimizing disease prevention and pharmaceutical treatment to slow or stop cognitive decline, while minimizing adverse effects.
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Lee D, Park J, Jung KS, Kim J, Jang JS, Kwon S, Byun MS, Yi D, Byeon G, Jung G, Kim YK, Lee DY, Han S, Mook-jung I. Application of QPLEXTM biomarkers in cognitively normal individuals across a broad age range and diverse regions with cerebral amyloid deposition. Exp Mol Med. [PMID: 35058557 PMCID: PMC8814000 DOI: 10.1038/s12276-021-00719-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 10/28/2021] [Accepted: 11/10/2021] [Indexed: 11/29/2022] Open
Abstract
The deposition of beta-amyloid (Aβ) in the brain precedes the onset of symptoms such as cognitive impairment in Alzheimer’s disease (AD); therefore, the early detection of Aβ accumulation is crucial. We previously reported the applicability of the QPLEXTM Alz plus assay kit for the prescreening of Aβ accumulation. Here, we tested the specific application of the kit in a large cohort of cognitively normal (CN) individuals of varying ages for the early detection of Aβ accumulation. We included a total of 221 CN participants with or without brain Aβ. The QPLEXTM biomarkers were characterized based on age groups (1st–3rd tertile) and across various brain regions with cerebral amyloid deposition. The 3rd tertile group (>65 years) was found to be the most suitable age group for the application of our assay kit. Receiver operating characteristic curve analysis showed that the area under the curve (AUC, discrimination power) was 0.878 with 69.7% sensitivity and 98.4% specificity in the 3rd tertile group. Additionally, specific correlations between biomarkers and cerebral amyloid deposition in four different brain regions revealed an overall correlation with general amyloid deposition, consistent with previous findings. Furthermore, the combinational panel with plasma Aβ1–42 levels maximized the discrimination efficiency and achieved an AUC of 0.921 with 95.7% sensitivity and 67.3% specificity. Thus, we suggest that the QPLEXTM Alz plus assay is useful for prescreening brain Aβ levels in CN individuals, especially those aged >65 years, to prevent disease progression via the early detection of disease initiation. A novel assay kit called QPLEXTM Alz plus assay offers a convenient method for assessing brain levels of the beta-amyloid proteins implicated in Alzheimer’s disease in people with normal cognitive abilities, especially those aged over 65. South Korean researchers led by Inhee Mook-Jung at Seoul National University assessed the efficacy of blood tests using the QPLEXTM kit on 221 participants in the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer’s Disease (KBASE). The researchers developed the assay to identify several circulating biomarkers of brain beta-amyloid accumulation. They found the test can distinguish between people known to either have or not have beta-amyloid deposits in their brain. This suggests QPLEXTM Alz plus assay could offer an improved procedure for easy and early diagnosis of Alzheimer’s, increasing the opportunities for effective early treatment.
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Kim HJ, Park JC, Jung KS, Kim J, Jang JS, Kwon S, Byun MS, Yi D, Byeon G, Jung G, Kim YK, Lee DY, Han SH, Mook-Jung I. The clinical use of blood-test factors for Alzheimer's disease: improving the prediction of cerebral amyloid deposition by the QPLEX TM Alz plus assay kit. Exp Mol Med 2021; 53:1046-1054. [PMID: 34108650 PMCID: PMC8257730 DOI: 10.1038/s12276-021-00638-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 04/12/2021] [Accepted: 04/13/2021] [Indexed: 02/05/2023] Open
Abstract
Alzheimer's disease (AD) is the leading cause of dementia, and many studies have focused on finding effective blood biomarkers for the accurate diagnosis of this disease. Predicting cerebral amyloid deposition is considered the key for AD diagnosis because a cerebral amyloid deposition is the hallmark of AD pathogenesis. Previously, blood biomarkers were discovered to predict cerebral amyloid deposition, and further efforts have been made to increase their sensitivity and specificity. In this study, we analyzed blood-test factors (BTFs) that can be commonly measured in medical health check-ups from 149 participants with cognitively normal, 87 patients with mild cognitive impairment, and 64 patients with clinically diagnosed AD dementia with brain amyloid imaging data available. We demonstrated that four factors among regular health check-up blood tests, cortisol, triglyceride/high-density lipoprotein cholesterol ratio, alanine aminotransferase, and free triiodothyronine, showed either a significant difference by or correlation with cerebral amyloid deposition. Furthermore, we made a prediction model for Pittsburgh compound B-positron emission tomography positivity, using BTFs and the previously discovered blood biomarkers, the QPLEXTM Alz plus assay kit biomarker panel, and the area under the curve was significantly increased up to 0.845% with 69.4% sensitivity and 90.6% specificity. These results show that BTFs could be used as co-biomarkers and that a highly advanced prediction model for amyloid plaque deposition could be achieved by the combinational use of diverse biomarkers.
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Affiliation(s)
- Haeng Jun Kim
- Department of Biochemistry and Biomedical Sciences, College of Medicine, Seoul National University, Seoul, 03080, Republic of Korea
- SNU Dementia Research Center, College of Medicine, Seoul National University, Seoul, 03080, Republic of Korea
- Neuroscience Research Institute, Medical Research Center, College of Medicine, Seoul National University, Seoul, 03080, Republic of Korea
| | - Jong-Chan Park
- Department of Biochemistry and Biomedical Sciences, College of Medicine, Seoul National University, Seoul, 03080, Republic of Korea
- SNU Dementia Research Center, College of Medicine, Seoul National University, Seoul, 03080, Republic of Korea
- Neuroscience Research Institute, Medical Research Center, College of Medicine, Seoul National University, Seoul, 03080, Republic of Korea
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, WC1E 6BT, UK
| | | | - Jiyeong Kim
- QuantaMatrix Inc, Seoul, 03080, Republic of Korea
| | - Ji Sung Jang
- QuantaMatrix Inc, Seoul, 03080, Republic of Korea
| | | | - Min Soo Byun
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, 13620, Republic of Korea
| | - Dahyun Yi
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, 03080, Republic of Korea
| | - Gihwan Byeon
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, 03080, Republic of Korea
| | - Gijung Jung
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, 03080, Republic of Korea
| | - Yu Kyeong Kim
- Department of Nuclear Medicine, SMG-SNU Boramae Medical Center, Seoul, 07061, Republic of Korea
| | - Dong Young Lee
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, 03080, Republic of Korea.
- Department of Psychiatry, College of Medicine, Seoul National University, Seoul, 03080, Republic of Korea.
- Institute of Human Behavioral Medicine, Medical Research Center, Seoul National University, Seoul, 03080, Korea.
| | - Sun-Ho Han
- Department of Biochemistry and Biomedical Sciences, College of Medicine, Seoul National University, Seoul, 03080, Republic of Korea.
- SNU Dementia Research Center, College of Medicine, Seoul National University, Seoul, 03080, Republic of Korea.
- Neuroscience Research Institute, Medical Research Center, College of Medicine, Seoul National University, Seoul, 03080, Republic of Korea.
| | - Inhee Mook-Jung
- Department of Biochemistry and Biomedical Sciences, College of Medicine, Seoul National University, Seoul, 03080, Republic of Korea.
- SNU Dementia Research Center, College of Medicine, Seoul National University, Seoul, 03080, Republic of Korea.
- Neuroscience Research Institute, Medical Research Center, College of Medicine, Seoul National University, Seoul, 03080, Republic of Korea.
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