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Development and Implementation of an Internal Quality Control Sample to Standardize Oligomer-Based Diagnostics of Alzheimer’s Disease
Protein misfolding and aggregation are pathological hallmarks of various neurodegenerative diseases. In Alzheimer’s disease (AD), soluble and toxic amyloid-β (Aβ) oligomers are biomarker candidates for diagnostics and drug development. However, accurate quantification of Aβ oligomers in bodily fluid...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10217173/ https://www.ncbi.nlm.nih.gov/pubmed/37238187 http://dx.doi.org/10.3390/diagnostics13101702 |
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author | Pils, Marlene Dybala, Alexandra Rehn, Fabian Blömeke, Lara Bujnicki, Tuyen Kraemer-Schulien, Victoria Hoyer, Wolfgang Riesner, Detlev Willbold, Dieter Bannach, Oliver |
author_facet | Pils, Marlene Dybala, Alexandra Rehn, Fabian Blömeke, Lara Bujnicki, Tuyen Kraemer-Schulien, Victoria Hoyer, Wolfgang Riesner, Detlev Willbold, Dieter Bannach, Oliver |
author_sort | Pils, Marlene |
collection | PubMed |
description | Protein misfolding and aggregation are pathological hallmarks of various neurodegenerative diseases. In Alzheimer’s disease (AD), soluble and toxic amyloid-β (Aβ) oligomers are biomarker candidates for diagnostics and drug development. However, accurate quantification of Aβ oligomers in bodily fluids is challenging because extreme sensitivity and specificity are required. We previously introduced surface-based fluorescence intensity distribution analysis (sFIDA) with single-particle sensitivity. In this report, a preparation protocol for a synthetic Aβ oligomer sample was developed. This sample was used for internal quality control (IQC) to improve standardization, quality assurance, and routine application of oligomer-based diagnostic methods. We established an aggregation protocol for Aβ1–42, characterized the oligomers by atomic force microscopy (AFM), and assessed their application in sFIDA. Globular-shaped oligomers with a median size of 2.67 nm were detected by AFM, and sFIDA analysis of the Aβ1–42 oligomers yielded a femtomolar detection limit with high assay selectivity and dilution linearity over 5 log units. Lastly, we implemented a Shewhart chart for monitoring IQC performance over time, which is another important step toward quality assurance of oligomer-based diagnostic methods. |
format | Online Article Text |
id | pubmed-10217173 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102171732023-05-27 Development and Implementation of an Internal Quality Control Sample to Standardize Oligomer-Based Diagnostics of Alzheimer’s Disease Pils, Marlene Dybala, Alexandra Rehn, Fabian Blömeke, Lara Bujnicki, Tuyen Kraemer-Schulien, Victoria Hoyer, Wolfgang Riesner, Detlev Willbold, Dieter Bannach, Oliver Diagnostics (Basel) Article Protein misfolding and aggregation are pathological hallmarks of various neurodegenerative diseases. In Alzheimer’s disease (AD), soluble and toxic amyloid-β (Aβ) oligomers are biomarker candidates for diagnostics and drug development. However, accurate quantification of Aβ oligomers in bodily fluids is challenging because extreme sensitivity and specificity are required. We previously introduced surface-based fluorescence intensity distribution analysis (sFIDA) with single-particle sensitivity. In this report, a preparation protocol for a synthetic Aβ oligomer sample was developed. This sample was used for internal quality control (IQC) to improve standardization, quality assurance, and routine application of oligomer-based diagnostic methods. We established an aggregation protocol for Aβ1–42, characterized the oligomers by atomic force microscopy (AFM), and assessed their application in sFIDA. Globular-shaped oligomers with a median size of 2.67 nm were detected by AFM, and sFIDA analysis of the Aβ1–42 oligomers yielded a femtomolar detection limit with high assay selectivity and dilution linearity over 5 log units. Lastly, we implemented a Shewhart chart for monitoring IQC performance over time, which is another important step toward quality assurance of oligomer-based diagnostic methods. MDPI 2023-05-11 /pmc/articles/PMC10217173/ /pubmed/37238187 http://dx.doi.org/10.3390/diagnostics13101702 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Pils, Marlene Dybala, Alexandra Rehn, Fabian Blömeke, Lara Bujnicki, Tuyen Kraemer-Schulien, Victoria Hoyer, Wolfgang Riesner, Detlev Willbold, Dieter Bannach, Oliver Development and Implementation of an Internal Quality Control Sample to Standardize Oligomer-Based Diagnostics of Alzheimer’s Disease |
title | Development and Implementation of an Internal Quality Control Sample to Standardize Oligomer-Based Diagnostics of Alzheimer’s Disease |
title_full | Development and Implementation of an Internal Quality Control Sample to Standardize Oligomer-Based Diagnostics of Alzheimer’s Disease |
title_fullStr | Development and Implementation of an Internal Quality Control Sample to Standardize Oligomer-Based Diagnostics of Alzheimer’s Disease |
title_full_unstemmed | Development and Implementation of an Internal Quality Control Sample to Standardize Oligomer-Based Diagnostics of Alzheimer’s Disease |
title_short | Development and Implementation of an Internal Quality Control Sample to Standardize Oligomer-Based Diagnostics of Alzheimer’s Disease |
title_sort | development and implementation of an internal quality control sample to standardize oligomer-based diagnostics of alzheimer’s disease |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10217173/ https://www.ncbi.nlm.nih.gov/pubmed/37238187 http://dx.doi.org/10.3390/diagnostics13101702 |
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