Facilitating the validation of novel protein biomarkers for dementia: an optimal workflow for the development of sandwich immunoassays

Different neurodegenerative disorders, such as Alzheimer's disease (AD) and frontotemporal dementia (FTD), lead to dementia syndromes. Dementia will pose a huge impact on society and thus it is essential to develop novel tools that are able to detect the earliest, most sensitive, discriminative, and dynamic biomarkers for each of the disorders. To date, the most common assays used in large-scale protein biomarker analysis are enzyme-linked immunosorbent assays (ELISA), such as the sandwich immunoassays, which are sensitive, practical, and easily implemented. However, due to the novelty of many candidate biomarkers identified during proteomics screening, such assays or the antibodies that specifically recognize the desired marker are often not available. The development and optimization of a new ELISA should be carried out with considerable caution since a poor planning can be costly, ineffective, time consuming, and it may lead to a misinterpretation of the findings. Previous guidelines described either the overall biomarker development in more general terms (i.e., the process from biomarker discovery to validation) or the specific steps of performing an ELISA procedure. However, a workflow describing and guiding the main issues in the development of a novel ELISA is missing. Here, we describe a specific and detailed workflow to develop and validate new ELISA for a successful and reliable validation of novel dementia biomarkers. The proposed workflow highlights the main issues in the development of an ELISA and covers several critical aspects, including production, screening, and selection of specific antibodies until optimal fine-tuning of the assay. Although these recommendations are designed to analyze novel biomarkers for dementia in cerebrospinal fluid, they are generally applicable for the development of immunoassays for biomarkers in other human body fluids or tissues. This workflow is designed to maximize the quality of the developed ELISA using a time- and cost-efficient strategy. This will facilitate the validation of the dementia biomarker candidates ultimately allowing accurate diagnostic conclusions

Quantification of amyloid-beta 40 in cerebrospinal fluid

Background: Truncated forms and full-length forms of the amyloid-beta 40 (Aβ40) are key molecules in the pathogenesis of dementia, and are detectable in CSF. Reliable methods to detect these biomarkers in CSF are of great importance for understanding the disease mechanisms and for diagnostic purposes. Methods: VU-α-Aβ40, a monoclonal antibody (mAb) specifically detecting Aβ40, was generated and characterized by solid and fluid phase ELISA, surface plasmon resonance spectroscopy (SPRS), immunoprecipitation (IP), immunohistochemical and Western blot (WB) analysis. In addition, an ELISA with VU-α-Aβ40 as catching and 6E10 as detecting mAbs was set up and validated. This ELISA was used to measure Aβ40 in CSF of controls (N = 27), patients with Alzheimer's disease (AD; N = 20), frontotemporal lobe dementia (FTLD; N = 14), noninflammatory (N = 15) and inflammatory (N = 15) neurological conditions. Results: VU-α-Aβ40 specifically recognizes Aβ40 with high affinity (

Neurofilament ELISA validation

Contains fulltext : 89601.pdf (publisher's version ) (Closed access)BACKGROUND: Neurofilament proteins (Nf) are highly specific biomarkers for neuronal death and axonal degeneration. As these markers become more widely used, an inter-laboratory validation study is required to identify assay criteria for high quality performance. METHODS: The UmanDiagnostics NF-light (R)enzyme-linked immunoabsorbent assays (ELISA) for the neurofilament light chain (NfL, 68kDa) was used to test the intra-assay and inter-laboratory coefficient of variation (CV) between 35 laboratories worldwide on 15 cerebrospinal fluid (CSF) samples. Critical factors, such as sample transport and storage, analytical delays, reaction temperature and time, the laboratories' accuracy and preparation of standards were documented and used for the statistical analyses. RESULTS: The intra-laboratory CV averaged 3.3% and the inter-laboratory CV 59%. The results from the test laboratories correlated with those from the reference laboratory (R=0.60, p<0.0001). Correcting for critical factors improved the strength of the correlation. Differences in the accuracy of standard preparation were identified as the most critical factor. Correcting for the error introduced by variation in the protein standards improved the correlation to R=0.98, p<0.0001 with an averaged inter-laboratory CV of 14%. The corrected overall inter-rater agreement was subtantial (0.6) according to Fleiss' multi-rater kappa and Gwet's AC1 statistics. CONCLUSION: This multi-center validation study identified the lack of preparation of accurate and consistent protein standards as the main reason for a poor inter-laboratory CV. This issue is also relevant to other protein biomarkers based on this type of assay and will need to be solved in order to achieve an acceptable level of analytical accuracy. The raw data of this study is available online

Neurofilament ELISA validation

Background: Neurofilament proteins (Nf) are highly specific biomarkers for neuronal death and axonal degeneration. As these markers become more widely used, an inter-laboratory validation study is required to identify assay criteria for high quality performance. Methods: The UmanDiagnostics NF-light ®enzyme-linked immunoabsorbent assays (ELISA) for the neurofilament light chain (NfL, 68 kDa) was used to test the intra-assay and inter-laboratory coefficient of variation (CV) between 35 laboratories worldwide on 15 cerebrospinal fluid (CSF) samples. Critical factors, such as sample transport and storage, analytical delays, reaction temperature and time, the laboratories&apos; accuracy and preparation of standards were documented and used for the statistical analyses. Results: The intra-laboratory CV averaged 3.3% and the inter-laboratory CV 59%. The results from the test laboratories correlated with those from the reference laboratory (R = 0.60, p &lt; 0.0001). Correcting for critical factors improved the strength of the correlation. Differences in the accuracy of standard preparation were identified as the most critical factor. Correcting for the error introduced by variation in the protein standards improved the correlation to R = 0.98, p &lt; 0.0001 with an averaged inter-laboratory CV of 14%. The corrected overall inter-rater agreement was subtantial (0.6) according to Fleiss&apos; multi-rater kappa and Gwet&apos;s AC1 statistics. Conclusion: This multi-center validation study identified the lack of preparation of accurate and consistent protein standards as the main reason for a poor inter-laboratory CV. This issue is also relevant to other protein biomarkers based on this type of assay and will need to be solved in order to achieve an acceptable level of analytical accuracy. The raw data of this study is available online. © 2009 Elsevier B.V