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The Origin-Adjusted Approach for Reliable Quantification of Endogenous Analytes in Mass Spectrometric Bioanalysis

[Image: see text] The reliably accurate and precise quantification of biomarkers is a priceless objective in the drug development and diagnostic arenas. To employ a technique that brings such reliability and furthermore involves a simpler, faster, and inexpensive regime would only underline the pote...

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Autores principales: MacNeill, Robert, Thomas, Samuel, Anand, Prachi, Koleto, Michael, Powers, Brendan, Ledvina, Aaron
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9774370/
https://www.ncbi.nlm.nih.gov/pubmed/36570202
http://dx.doi.org/10.1021/acsomega.2c06850
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author MacNeill, Robert
Thomas, Samuel
Anand, Prachi
Koleto, Michael
Powers, Brendan
Ledvina, Aaron
author_facet MacNeill, Robert
Thomas, Samuel
Anand, Prachi
Koleto, Michael
Powers, Brendan
Ledvina, Aaron
author_sort MacNeill, Robert
collection PubMed
description [Image: see text] The reliably accurate and precise quantification of biomarkers is a priceless objective in the drug development and diagnostic arenas. To employ a technique that brings such reliability and furthermore involves a simpler, faster, and inexpensive regime would only underline the potential importance of the concept and technique. To the existing established approaches for biomarker quantification in bioanalytical LC–MS, surrogate matrix (SUR-M) and surrogate analyte (SUR-A), in this Letter we present an approach that fulfills the aforementioned advantages. The concept builds on the historic method of standard addition (SA), in which one source of biological matrix is spiked with analyte to form a calibration curve. With the SA curve back-calculated, the heart of this procedure is the subsequent adjustment of the intercept to zero, the origin, and using only the slope of the curve for interpolation giving calculated sample concentrations. In SA, the concentration axis intercept indicates the endogenous analyte concentration, and our zeroing of this is equivalent to removing the endogenous level. This key shift of the calculated line to the origin unveils our novel origin-adjusted (OA) approach. It enables use akin to a regular xenobiotic method, with no need to ultimately account for the endogenous analyte level in the control matrix used for calibrants. We present a comparison of OA against the control approach of SUR-M in a representative application for kynurenine and tryptophan in human plasma by LC–MS. A numerical performance analysis performed is demonstrative of equivalence between the two approaches for both analytes.
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spelling pubmed-97743702022-12-23 The Origin-Adjusted Approach for Reliable Quantification of Endogenous Analytes in Mass Spectrometric Bioanalysis MacNeill, Robert Thomas, Samuel Anand, Prachi Koleto, Michael Powers, Brendan Ledvina, Aaron ACS Omega [Image: see text] The reliably accurate and precise quantification of biomarkers is a priceless objective in the drug development and diagnostic arenas. To employ a technique that brings such reliability and furthermore involves a simpler, faster, and inexpensive regime would only underline the potential importance of the concept and technique. To the existing established approaches for biomarker quantification in bioanalytical LC–MS, surrogate matrix (SUR-M) and surrogate analyte (SUR-A), in this Letter we present an approach that fulfills the aforementioned advantages. The concept builds on the historic method of standard addition (SA), in which one source of biological matrix is spiked with analyte to form a calibration curve. With the SA curve back-calculated, the heart of this procedure is the subsequent adjustment of the intercept to zero, the origin, and using only the slope of the curve for interpolation giving calculated sample concentrations. In SA, the concentration axis intercept indicates the endogenous analyte concentration, and our zeroing of this is equivalent to removing the endogenous level. This key shift of the calculated line to the origin unveils our novel origin-adjusted (OA) approach. It enables use akin to a regular xenobiotic method, with no need to ultimately account for the endogenous analyte level in the control matrix used for calibrants. We present a comparison of OA against the control approach of SUR-M in a representative application for kynurenine and tryptophan in human plasma by LC–MS. A numerical performance analysis performed is demonstrative of equivalence between the two approaches for both analytes. American Chemical Society 2022-12-09 /pmc/articles/PMC9774370/ /pubmed/36570202 http://dx.doi.org/10.1021/acsomega.2c06850 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle MacNeill, Robert
Thomas, Samuel
Anand, Prachi
Koleto, Michael
Powers, Brendan
Ledvina, Aaron
The Origin-Adjusted Approach for Reliable Quantification of Endogenous Analytes in Mass Spectrometric Bioanalysis
title The Origin-Adjusted Approach for Reliable Quantification of Endogenous Analytes in Mass Spectrometric Bioanalysis
title_full The Origin-Adjusted Approach for Reliable Quantification of Endogenous Analytes in Mass Spectrometric Bioanalysis
title_fullStr The Origin-Adjusted Approach for Reliable Quantification of Endogenous Analytes in Mass Spectrometric Bioanalysis
title_full_unstemmed The Origin-Adjusted Approach for Reliable Quantification of Endogenous Analytes in Mass Spectrometric Bioanalysis
title_short The Origin-Adjusted Approach for Reliable Quantification of Endogenous Analytes in Mass Spectrometric Bioanalysis
title_sort origin-adjusted approach for reliable quantification of endogenous analytes in mass spectrometric bioanalysis
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9774370/
https://www.ncbi.nlm.nih.gov/pubmed/36570202
http://dx.doi.org/10.1021/acsomega.2c06850
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