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Waury K. Decision Tree for Protein Biomarker Selection for Clinical Applications. Methods Mol Biol 2025; 2884:355-368. [PMID: 39716013 DOI: 10.1007/978-1-0716-4298-6_21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2024]
Abstract
Discovery of novel protein biomarkers for clinical applications is an active research field across a manifold of diseases. Despite some successes and progress, the biomarker development pipeline still frequently ends in failure. Biomarker candidates that are discovered by appropriate technologies such as unbiased mass spectrometry cannot be validated or translated to immunoassays in many cases. Selection of strong disease biomarker candidates that further constitute suitable targets for antibody binding in immunoassays is thus important to allow routine clinical use. This essential selection step can be supported and rationalized using bioinformatics tools such as protein databases. Here, we present a workflow in the form of decision trees to computationally investigate biomarker candidates and their available affinity reagents in depth. This analysis can identify the most promising biomarker candidates for assay development, while minimal time and effort are required.
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Affiliation(s)
- Katharina Waury
- Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
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2
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Pei J, Palanisamy CP, Jayaraman S, Natarajan PM, Umapathy VR, Roy JR, Thalamati D, Ahalliya RM, Kanniappan GV, Mironescu M. Proteomics profiling of extracellular vesicle for identification of potential biomarkers in Alzheimer's disease: A comprehensive review. Ageing Res Rev 2024; 99:102359. [PMID: 38821418 DOI: 10.1016/j.arr.2024.102359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2024] [Revised: 05/28/2024] [Accepted: 05/28/2024] [Indexed: 06/02/2024]
Abstract
The intricate origins and diverse symptoms of Alzheimer's disease (AD) pose significant challenges for both diagnosis and treatment. Exosomes and microvesicles, which carry disease-specific cargo from a variety of central nervous system cell types, have emerged as promising reservoirs of biomarkers for AD. Research on the screening of possible biomarkers in Alzheimer's disease using proteomic profiling of EVs is systematically reviewed in this comprehensive review. We highlight key methodologies employed in EV isolation, characterization, and proteomic analysis, elucidating their advantages and limitations. Furthermore, we summarize the evolving landscape of EV-associated biomarkers implicated in AD pathogenesis, including proteins involved in amyloid-beta metabolism, tau phosphorylation, neuroinflammation, synaptic dysfunction, and neuronal injury. The literature review highlights the necessity for robust validation strategies and standardized protocols to effectively transition EV-based biomarkers into clinical use. In the concluding section, this review delves into potential future avenues and technological advancements pivotal in crafting EV-derived biomarkers applicable to AD diagnostics and prognostics. This review contributes to our comprehension of AD pathology and the advancement of precision medicine in neurodegenerative diseases, hinting at a promising era in AD precision medicine.
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Affiliation(s)
- JinJin Pei
- Qinba State Key Laboratory of Biological Resources and Ecological Environment, 2011 QinLing-Bashan Mountains Bioresources Comprehensive Development C. I. C, Shaanxi Province Key Laboratory of Bio-Resources, College of Bioscience and Bioengineering, Shaanxi University of Technology, Hanzhong 723001, China
| | - Chella Perumal Palanisamy
- Department of Chemical Technology, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand.
| | - Selvaraj Jayaraman
- Centre of Molecular Medicine and Diagnostics (COMManD), Department of Biochemistry, Saveetha Dental College & Hospital, Saveetha Institute of Medical & Technical Sciences, Saveetha University, Chennai 600077, India
| | - Prabhu Manickam Natarajan
- Department of Clinical Sciences, Center of Medical and Bio-allied Health Sciences and Research, College of Dentistry, Ajman University, Ajman, United Arab Emirates
| | - Vidhya Rekha Umapathy
- Department of Public Health Dentistry, Thai Moogambigai Dental College and Hospital, Dr. MGR Educational and Research Institute, Chennai 600 107, Tamil Nadu, India
| | - Jeane Rebecca Roy
- Department of Anatomy, Bhaarath Medical College and hospital, Bharath Institute of Higher Education and Research (BIHER), Chennai, Tamil Nadu 600073, India
| | | | - Rathi Muthaiyan Ahalliya
- Department of Biochemistry, FASCM, Karpagam Academy of Higher Education, Coimbatore, Tamil Nadu 641021, India
| | | | - Monica Mironescu
- Faculty of Agricultural Sciences, Food Industry and Environmental Protection, Research Center in Biotechnology and Food Engineering, Lucian Blaga University of Sibiu, 7-9 Ioan Ratiu Street, Sibiu 550024, Romania.
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3
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Gogishvili D, Illes-Toth E, Harris MJ, Hopley C, Teunissen CE, Abeln S. Structural flexibility and heterogeneity of recombinant human glial fibrillary acidic protein (GFAP). Proteins 2024; 92:649-664. [PMID: 38149328 DOI: 10.1002/prot.26656] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 12/07/2023] [Accepted: 12/12/2023] [Indexed: 12/28/2023]
Abstract
Glial fibrillary acidic protein (GFAP) is a promising biomarker for brain and spinal cord disorders. Recent studies have highlighted the differences in the reliability of GFAP measurements in different biological matrices. The reason for these discrepancies is poorly understood as our knowledge of the protein's 3-dimensional conformation, proteoforms, and aggregation remains limited. Here, we investigate the structural properties of GFAP under different conditions. For this, we characterized recombinant GFAP proteins from various suppliers and applied hydrogen-deuterium exchange mass spectrometry (HDX-MS) to provide a snapshot of the conformational dynamics of GFAP in artificial cerebrospinal fluid (aCSF) compared to the phosphate buffer. Our findings indicate that recombinant GFAP exists in various conformational species. Furthermore, we show that GFAP dimers remained intact under denaturing conditions. HDX-MS experiments show an overall decrease in H-bonding and an increase in solvent accessibility of GFAP in aCSF compared to the phosphate buffer, with clear indications of mixed EX2 and EX1 kinetics. To understand possible structural interface regions and the evolutionary conservation profiles, we combined HDX-MS results with the predicted GFAP-dimer structure by AlphaFold-Multimer. We found that deprotected regions with high structural flexibility in aCSF overlap with predicted conserved dimeric 1B and 2B domain interfaces. Structural property predictions combined with the HDX data show an overall deprotection and signatures of aggregation in aCSF. We anticipate that the outcomes of this research will contribute to a deeper understanding of the structural flexibility of GFAP and ultimately shed light on its behavior in different biological matrices.
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Affiliation(s)
- Dea Gogishvili
- Bioinformatics, Computer Science Department, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- AI Technology for Life, Department of Computing and Information Sciences, Department of Biology, Utrecht University, Utrecht, The Netherlands
| | - Eva Illes-Toth
- National Measurement Laboratory at Laboratory of the Government Chemist (LGC), Teddington, UK
| | - Matthew J Harris
- National Measurement Laboratory at Laboratory of the Government Chemist (LGC), Teddington, UK
| | - Christopher Hopley
- National Measurement Laboratory at Laboratory of the Government Chemist (LGC), Teddington, UK
| | - Charlotte E Teunissen
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Sanne Abeln
- Bioinformatics, Computer Science Department, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- AI Technology for Life, Department of Computing and Information Sciences, Department of Biology, Utrecht University, Utrecht, The Netherlands
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4
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Cheng HP, Yang TH, Wang JC, Chuang HS. Recent Trends and Innovations in Bead-Based Biosensors for Cancer Detection. SENSORS (BASEL, SWITZERLAND) 2024; 24:2904. [PMID: 38733011 PMCID: PMC11086254 DOI: 10.3390/s24092904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Revised: 04/29/2024] [Accepted: 04/30/2024] [Indexed: 05/13/2024]
Abstract
Demand is strong for sensitive, reliable, and cost-effective diagnostic tools for cancer detection. Accordingly, bead-based biosensors have emerged in recent years as promising diagnostic platforms based on wide-ranging cancer biomarkers owing to the versatility, high sensitivity, and flexibility to perform the multiplexing of beads. This comprehensive review highlights recent trends and innovations in the development of bead-based biosensors for cancer-biomarker detection. We introduce various types of bead-based biosensors such as optical, electrochemical, and magnetic biosensors, along with their respective advantages and limitations. Moreover, the review summarizes the latest advancements, including fabrication techniques, signal-amplification strategies, and integration with microfluidics and nanotechnology. Additionally, the challenges and future perspectives in the field of bead-based biosensors for cancer-biomarker detection are discussed. Understanding these innovations in bead-based biosensors can greatly contribute to improvements in cancer diagnostics, thereby facilitating early detection and personalized treatments.
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Affiliation(s)
- Hui-Pin Cheng
- Department of Biomedical Engineering, National Cheng Kung University, Tainan 701, Taiwan (T.-H.Y.)
| | - Tai-Hua Yang
- Department of Biomedical Engineering, National Cheng Kung University, Tainan 701, Taiwan (T.-H.Y.)
- Department of Orthopedic Surgery, National Cheng Kung University Hospital, Tainan 704, Taiwan
- Medical Device Innovation Center, National Cheng Kung University, Tainan 701, Taiwan
| | - Jhih-Cheng Wang
- Department of Urology, Chimei Medical Center, Tainan 710, Taiwan
- Department of Electrical Engineering, Southern Taiwan University of Science and Technology, Tainan 710, Taiwan
- School of Medicine, College of Medicine, National Sun Yat-sen University, Kaohsiung 804, Taiwan
| | - Han-Sheng Chuang
- Department of Biomedical Engineering, National Cheng Kung University, Tainan 701, Taiwan (T.-H.Y.)
- Medical Device Innovation Center, National Cheng Kung University, Tainan 701, Taiwan
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Wojdała AL, Bellomo G, Gaetani L, Toja A, Chipi E, Shan D, Chiasserini D, Parnetti L. Trajectories of CSF and plasma biomarkers across Alzheimer's disease continuum: disease staging by NF-L, p-tau181, and GFAP. Neurobiol Dis 2023; 189:106356. [PMID: 37977432 DOI: 10.1016/j.nbd.2023.106356] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 10/02/2023] [Accepted: 11/14/2023] [Indexed: 11/19/2023] Open
Abstract
CSF-to-plasma transition will open new avenues for molecular phenotyping of Alzheimer's disease (AD). Here we evaluated a panel of AD biomarkers in matched CSF and plasma samples across the AD continuum, from preclinical AD to dementia. The aims were to: 1) compare diagnostic performance of the two biofluids, 2) evaluate trajectories of the biomarkers along AD progression. We analyzed CSF and plasma Aβ42/40, p-tau181, p-tau231, t-tau, NF-L, GFAP, UCHL-1 and CSF SNAP-25 in a cohort (n = 173) of preclinical AD, MCI-AD, AD dementia, frontotemporal dementia patients, and controls. We found a significant correlation between CSF and plasma levels of Aβ42/40, p-tau181, p-tau231, NF-L, and GFAP, while no CSF-plasma correlation was observed for t-tau and UCHL-1. Next to the core CSF biomarkers (Aβ42/40, p-tau181, t-tau), those providing the best discrimination between controls and preclinical AD were CSF p-tau231 and SNAP-25 and plasma Aβ42/40, p-tau231, and GFAP. Among plasma biomarkers, we found Aβ42/Aβ40, GFAP, and p-tau231 to show the largest rate of change at the CSF biomarker-defined cut-offs for amyloidosis and tauopathy. Finally, we identified GFAP, NF-L, and p-tau181 as the biomarkers most significantly associated with disease progression in both CSF and plasma. We suggest that a well-standardized and validated panel of selected plasma markers can facilitate early AD diagnosis, even at the asymptomatic disease stage. We propose that both CSF and plasma measurement of NF-L, p-tau181, and GFAP may play a significant role in disease staging and monitoring.
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Affiliation(s)
- Anna Lidia Wojdała
- Laboratory of Clinical Neurochemistry, Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia 06132, Italy
| | - Giovanni Bellomo
- Laboratory of Clinical Neurochemistry, Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia 06132, Italy
| | - Lorenzo Gaetani
- Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia 06132, Italy
| | - Andrea Toja
- Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia 06132, Italy
| | - Elena Chipi
- Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia 06132, Italy
| | - Dandan Shan
- Quanterix Corporation, Billerica, MA 01821, United States of America
| | - Davide Chiasserini
- Section of Physiology and Biochemistry, Department of Medicine and Surgery, University of Perugia, Perugia 06132, Italy.
| | - Lucilla Parnetti
- Laboratory of Clinical Neurochemistry, Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia 06132, Italy; Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia 06132, Italy.
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6
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Teunissen CE, Kimble L, Bayoumy S, Bolsewig K, Burtscher F, Coppens S, Das S, Gogishvili D, Fernandes Gomes B, Gómez de San José N, Mavrina E, Meda FJ, Mohaupt P, Mravinacová S, Waury K, Wojdała AL, Abeln S, Chiasserini D, Hirtz C, Gaetani L, Vermunt L, Bellomo G, Halbgebauer S, Lehmann S, Månberg A, Nilsson P, Otto M, Vanmechelen E, Verberk IMW, Willemse E, Zetterberg H. Methods to Discover and Validate Biofluid-Based Biomarkers in Neurodegenerative Dementias. Mol Cell Proteomics 2023; 22:100629. [PMID: 37557955 PMCID: PMC10594029 DOI: 10.1016/j.mcpro.2023.100629] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 07/24/2023] [Accepted: 07/31/2023] [Indexed: 08/11/2023] Open
Abstract
Neurodegenerative dementias are progressive diseases that cause neuronal network breakdown in different brain regions often because of accumulation of misfolded proteins in the brain extracellular matrix, such as amyloids or inside neurons or other cell types of the brain. Several diagnostic protein biomarkers in body fluids are being used and implemented, such as for Alzheimer's disease. However, there is still a lack of biomarkers for co-pathologies and other causes of dementia. Such biofluid-based biomarkers enable precision medicine approaches for diagnosis and treatment, allow to learn more about underlying disease processes, and facilitate the development of patient inclusion and evaluation tools in clinical trials. When designing studies to discover novel biofluid-based biomarkers, choice of technology is an important starting point. But there are so many technologies to choose among. To address this, we here review the technologies that are currently available in research settings and, in some cases, in clinical laboratory practice. This presents a form of lexicon on each technology addressing its use in research and clinics, its strengths and limitations, and a future perspective.
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Affiliation(s)
- Charlotte E Teunissen
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Neurochemistry Lab, Department of Laboratory Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands.
| | - Leighann Kimble
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; KIN Center for Digital Innovation, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Sherif Bayoumy
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Neurochemistry Lab, Department of Laboratory Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
| | - Katharina Bolsewig
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Neurochemistry Lab, Department of Laboratory Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
| | - Felicia Burtscher
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Salomé Coppens
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; National Measurement Laboratory at LGC, Teddington, United Kingdom
| | - Shreyasee Das
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; ADx NeuroSciences, Gent, Belgium
| | - Dea Gogishvili
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Bárbara Fernandes Gomes
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Nerea Gómez de San José
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Neurology, University of Ulm, Ulm, Germany
| | - Ekaterina Mavrina
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; KIN Center for Digital Innovation, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Francisco J Meda
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Pablo Mohaupt
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; LBPC-PPC, IRMB CHU Montpellier, INM INSERM, Université de Montpellier, Montpellier, France
| | - Sára Mravinacová
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Division of Affinity Proteomics, Department of Protein Science, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden
| | - Katharina Waury
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Anna Lidia Wojdała
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Sanne Abeln
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Davide Chiasserini
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Section of Physiology and Biochemistry, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Christophe Hirtz
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; LBPC-PPC, IRMB CHU Montpellier, INM INSERM, Université de Montpellier, Montpellier, France
| | - Lorenzo Gaetani
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Lisa Vermunt
- Neurochemistry Lab, Department of Laboratory Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
| | - Giovanni Bellomo
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Steffen Halbgebauer
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Neurology, University of Ulm, Ulm, Germany; German Center for Neurodegenerative Diseases (DZNE e.V.), Ulm, Germany
| | - Sylvain Lehmann
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; LBPC-PPC, IRMB CHU Montpellier, INM INSERM, Université de Montpellier, Montpellier, France
| | - Anna Månberg
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Division of Affinity Proteomics, Department of Protein Science, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden
| | - Peter Nilsson
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Division of Affinity Proteomics, Department of Protein Science, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden
| | - Markus Otto
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Neurology, University of Ulm, Ulm, Germany; Department of Neurology, Martin-Luther-University Halle-Wittenberg, Halle, Germany
| | - Eugeen Vanmechelen
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; ADx NeuroSciences, Gent, Belgium
| | - Inge M W Verberk
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Neurochemistry Lab, Department of Laboratory Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
| | - Eline Willemse
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Neurochemistry Lab, Department of Laboratory Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
| | - Henrik Zetterberg
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The 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; Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China; Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
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Coppens S, Lehmann S, Hopley C, Hirtz C. Neurofilament-Light, a Promising Biomarker: Analytical, Metrological and Clinical Challenges. Int J Mol Sci 2023; 24:11624. [PMID: 37511382 PMCID: PMC10380627 DOI: 10.3390/ijms241411624] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 07/13/2023] [Accepted: 07/15/2023] [Indexed: 07/30/2023] Open
Abstract
Neurofilament-light chain (Nf-L) is a non-specific early-stage biomarker widely studied in the context of neurodegenerative diseases (NDD) and traumatic brain injuries (TBI), which can be measured in biofluids after axonal damage. Originally measured by enzyme-linked immunosorbent assay (ELISA) in cerebrospinal fluid (CSF), Nf-L can now be quantified in blood with the emergence of ultrasensitive assays. However, to ensure successful clinical implementation, reliable clinical thresholds and reference measurement procedures (RMP) should be developed. This includes establishing and distributing certified reference materials (CRM). As a result of the complexity of Nf-L and the number of circulating forms, a clear definition of what is measured when immunoassays are used is also critical to achieving standardization to ensure the long-term success of those assays. The use of powerful tools such as mass spectrometry for developing RMP and defining the measurand is ongoing. Here, we summarize the current methods in use for quantification of Nf-L in biofluid showing potential for clinical implementation. The progress and challenges in developing RMP and defining the measurand for Nf-L standardization of diagnostic tests are addressed. Finally, we discuss the impact of pathophysiological factors on Nf-L levels and the establishment of a clinical cut-off.
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Affiliation(s)
- Salomé Coppens
- National Measurement Laboratory, LGC Limited, Teddington TW11 0LY, UK
- Univ. Montpellier, IRMB-PPC, INM, CHU Montpellier, INSERM CNRS, 34295 Montpellier, France
| | - Sylvain Lehmann
- Univ. Montpellier, IRMB-PPC, INM, CHU Montpellier, INSERM CNRS, 34295 Montpellier, France
| | | | - Christophe Hirtz
- Univ. Montpellier, IRMB-PPC, INM, CHU Montpellier, INSERM CNRS, 34295 Montpellier, France
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8
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Hok‐A‐Hin YS, Bolsewig K, Ruiters DN, Lleó A, Alcolea D, Lemstra AW, van der Flier WM, Teunissen CE, del Campo M. Thimet oligopeptidase as a potential CSF biomarker for Alzheimer's disease: A cross-platform validation study. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12456. [PMID: 37502019 PMCID: PMC10369371 DOI: 10.1002/dad2.12456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 06/14/2023] [Accepted: 06/16/2023] [Indexed: 07/29/2023]
Abstract
INTRODUCTION Our previous antibody-based cerebrospinal fluid (CSF) proteomics study showed that Thimet oligopeptidase (THOP1), an amyloid beta (Aβ) neuropeptidase, was increased in mild cognitive impairment with amyloid pathology (MCI-Aβ+) and Alzheimer's disease (AD) dementia compared with controls and dementia with Lewy bodies (DLB), highlighting the potential of CSF THOP1 as an early specific biomarker for AD. We aimed to develop THOP1 immunoassays for large-scale analysis and validate our proteomics findings in two independent cohorts. METHODS We developed in-house CSF THOP1 immunoassays on automated Ella and Simoa platforms. The performance of the different assays were compared using Passing-Bablok regression analysis in a subset of CSF samples from the discovery cohort (n = 72). Clinical validation was performed in two independent cohorts (cohort 1: n = 200; cohort 2: n = 165) using the Ella platform. RESULTS THOP1 concentrations moderately correlated between proteomics analysis and our novel assays (Rho > 0.580). In both validation cohorts, CSF THOP1 was increased in MCI-Aβ+ (>1.3-fold) and AD (>1.2-fold) compared with controls; and between MCI-Aβ+ and DLB (>1.2-fold). Higher THOP1 concentrations were detected in AD compared with DLB only when both cohorts were analyzed together. In both cohorts, THOP1 correlated with CSF total tau (t-tau), phosphorylated tau (p-tau), and Aβ40 (Rho > 0.540) but not Aβ42. DISCUSSION Validation of our proteomics findings underpins the potential of CSF THOP1 as an early specific biomarker associated with AD pathology. The use of antibody-based platforms in both the discovery and validation phases facilitated the translation of proteomics findings, providing an additional workflow that may accelerate the development of biofluid-based biomarkers.
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Affiliation(s)
- Yanaika S. Hok‐A‐Hin
- Neurochemistry Laboratory, Department of Laboratory Medicine, Amsterdam NeuroscienceVU University Medical Center, Amsterdam UMCAmsterdamThe Netherlands
| | - Katharina Bolsewig
- Neurochemistry Laboratory, Department of Laboratory Medicine, Amsterdam NeuroscienceVU University Medical Center, Amsterdam UMCAmsterdamThe Netherlands
| | - Daimy N. Ruiters
- Neurochemistry Laboratory, Department of Laboratory Medicine, Amsterdam NeuroscienceVU University Medical Center, Amsterdam UMCAmsterdamThe Netherlands
| | - Alberto Lleó
- Department of Neurology, Institut d'Investigacions Biomèdiques Sant Pau ‐ Hospital de Sant PauUniversitat Autònoma de Barcelona, Hospital de la Santa Creu i Sant PauBarcelonaSpain
| | - Daniel Alcolea
- Department of Neurology, Institut d'Investigacions Biomèdiques Sant Pau ‐ Hospital de Sant PauUniversitat Autònoma de Barcelona, Hospital de la Santa Creu i Sant PauBarcelonaSpain
| | - Afina W. Lemstra
- Alzheimer Center Amsterdam, Department of NeurologyAmsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMCAmsterdamThe Netherlands
| | - Wiesje M. van der Flier
- Alzheimer Center Amsterdam, Department of NeurologyAmsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMCAmsterdamThe Netherlands
- Department of Epidemiology and Data ScienceVU University Medical CentersAmsterdamThe Netherlands
| | - Charlotte E. Teunissen
- Neurochemistry Laboratory, Department of Laboratory Medicine, Amsterdam NeuroscienceVU University Medical Center, Amsterdam UMCAmsterdamThe Netherlands
| | - Marta del Campo
- Neurochemistry Laboratory, Department of Laboratory Medicine, Amsterdam NeuroscienceVU University Medical Center, Amsterdam UMCAmsterdamThe Netherlands
- Departamento de Ciencias Farmacéuticas y de la Salud, Facultad de FarmaciaUniversidad San Pablo‐CEU, CEU UniversitiesMadridSpain
- Bareclonaβeta Brain Research Center (BBRC)Pasqual Maragall FoundationBarcelonaSpain
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Giangrande C, Delatour V, Andreasson U, Blennow K, Gobom J, Zetterberg H. Harmonization and standardization of biofluid-based biomarker measurements for AT(N) classification in Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12465. [PMID: 37600860 PMCID: PMC10432775 DOI: 10.1002/dad2.12465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 05/31/2023] [Accepted: 07/05/2023] [Indexed: 08/22/2023]
Abstract
Fluid biomarkers are currently measured in cerebrospinal fluid and blood for Alzheimer's disease diagnosis and are promising targets for drug development and for patients' follow-up in clinical trials. These biomarkers have been grouped in an unbiased research framework, the amyloid (Aβ), tau, and neurodegeneration (AT[N]) biomarker system to aid patients' early diagnosis and stratification. Metrological approaches relying on mass spectrometry have been used for the development of reference materials and reference measurement procedures. Despite their excellent performances as clinical tools, fluid biomarkers often present an important between-laboratory variation. Standardization efforts were carried out on the biomarkers currently included in the AT(N) classification system, involving the collaboration of national metrology institutes, clinicians, researchers, and in vitro diagnostic providers. This article provides an overview of current activities towards standardization. These reference methods and reference materials may be used for recalibration of immunoassays and the establishment of standardized cutoff values allowing a better stratification of Alzheimer's disease patients. Highlights The AT(N) biomarker system allows stratifying AD patients on the basis of biomarker profiles.Fluid biomarker measurements often present an important between-laboratory variation preventing the establishment of standardized cutoff values.Overview on the standardization initiatives involving the fluid biomarkers currently included in the AT(N) framework.
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Affiliation(s)
- Chiara Giangrande
- Laboratoire National de Métrologie et d'Essais (LNE)Department of BioanalysesParis, Cedex 15France
| | - Vincent Delatour
- Laboratoire National de Métrologie et d'Essais (LNE)Department of BioanalysesParis, Cedex 15France
| | - Ulf Andreasson
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and Physiologythe Sahlgrenska Academy at the University of Gothenburg, MölndalGothenburgSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
| | - Kaj Blennow
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and Physiologythe Sahlgrenska Academy at the University of Gothenburg, MölndalGothenburgSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
| | - Johan Gobom
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and Physiologythe Sahlgrenska Academy at the University of Gothenburg, MölndalGothenburgSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
| | - Henrik Zetterberg
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and Physiologythe Sahlgrenska Academy at the University of Gothenburg, MölndalGothenburgSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Department of Neurodegenerative DiseaseUCL Institute of NeurologyQueen SquareLondonUK
- UK Dementia Research Institute at UCLLondonUK
- Hong Kong Center for Neurodegenerative DiseasesClear Water BayHong KongChina
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public HealthUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
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Srivastava P, Tiwari A, Ahmad K, Srivastava N, Garg P. Editorial: An insight into multi-omics analysis of dementia disorders. Front Genet 2023; 14:1206530. [PMID: 37260774 PMCID: PMC10227556 DOI: 10.3389/fgene.2023.1206530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2023] [Accepted: 05/04/2023] [Indexed: 06/02/2023] Open
Affiliation(s)
- Prachi Srivastava
- Amity Institute of Biotechnology, Amity University Uttar Pradesh, Lucknow Campus, Uttar Pradesh, India
| | - Anshul Tiwari
- Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN, United States
| | - Khurshid Ahmad
- Department of Medical Biotechnology, Yeungnam University, Gyeongsan, Republic of Korea
| | | | - Prekshi Garg
- Amity Institute of Biotechnology, Amity University Uttar Pradesh, Lucknow Campus, Uttar Pradesh, India
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β-Synuclein as a candidate blood biomarker for synaptic degeneration in Alzheimer's disease. Alzheimers Res Ther 2022; 14:179. [PMID: 36451155 PMCID: PMC9710176 DOI: 10.1186/s13195-022-01125-1] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 11/17/2022] [Indexed: 12/03/2022]
Abstract
Synaptic degeneration is an early event closely associated with the course of Alzheimer's disease (AD). The identification of synaptic blood biomarkers is, therefore, of great interest and clinical relevance. The levels of most synaptic proteins are increased in the cerebrospinal fluid (CSF) of patients with AD, but their detection in blood is hitherto either unavailable or not very informative. This paradigm is related to their low concentration, their peripheral origin, or the presence of highly abundant blood proteins that hinder detection. In recent years, significant progress has been made in detecting the presynaptic protein β-synuclein. This mini-review summarizes the results that highlight the role of β-synuclein as a candidate blood marker for synaptic degeneration in AD.
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Waury K, Willemse EAJ, Vanmechelen E, Zetterberg H, Teunissen CE, Abeln S. Bioinformatics tools and data resources for assay development of fluid protein biomarkers. Biomark Res 2022; 10:83. [DOI: 10.1186/s40364-022-00425-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Accepted: 10/25/2022] [Indexed: 11/16/2022] Open
Abstract
AbstractFluid protein biomarkers are important tools in clinical research and health care to support diagnosis and to monitor patients. Especially within the field of dementia, novel biomarkers could address the current challenges of providing an early diagnosis and of selecting trial participants. While the great potential of fluid biomarkers is recognized, their implementation in routine clinical use has been slow. One major obstacle is the often unsuccessful translation of biomarker candidates from explorative high-throughput techniques to sensitive antibody-based immunoassays. In this review, we propose the incorporation of bioinformatics into the workflow of novel immunoassay development to overcome this bottleneck and thus facilitate the development of novel biomarkers towards clinical laboratory practice. Due to the rapid progress within the field of bioinformatics many freely available and easy-to-use tools and data resources exist which can aid the researcher at various stages. Current prediction methods and databases can support the selection of suitable biomarker candidates, as well as the choice of appropriate commercial affinity reagents. Additionally, we examine methods that can determine or predict the epitope - an antibody’s binding region on its antigen - and can help to make an informed choice on the immunogenic peptide used for novel antibody production. Selected use cases for biomarker candidates help illustrate the application and interpretation of the introduced tools.
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