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Systematic Assessment of Immune Marker Variation in Type 1 Diabetes: A Prospective Longitudinal Study

Immune analytes have been widely tested in efforts to understand the heterogeneity of disease progression, risk, and therapeutic responses in type 1 diabetes (T1D). The future clinical utility of such analytes as biomarkers depends on their technical and biological variability, as well as their corr...

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Autores principales: Speake, Cate, Bahnson, Henry T., Wesley, Johnna D., Perdue, Nikole, Friedrich, David, Pham, Minh N., Lanxon-Cookson, Erinn, Kwok, William W., Sehested Hansen, Birgit, von Herrath, Matthias, Greenbaum, Carla J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6753618/
https://www.ncbi.nlm.nih.gov/pubmed/31572352
http://dx.doi.org/10.3389/fimmu.2019.02023
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author Speake, Cate
Bahnson, Henry T.
Wesley, Johnna D.
Perdue, Nikole
Friedrich, David
Pham, Minh N.
Lanxon-Cookson, Erinn
Kwok, William W.
Sehested Hansen, Birgit
von Herrath, Matthias
Greenbaum, Carla J.
author_facet Speake, Cate
Bahnson, Henry T.
Wesley, Johnna D.
Perdue, Nikole
Friedrich, David
Pham, Minh N.
Lanxon-Cookson, Erinn
Kwok, William W.
Sehested Hansen, Birgit
von Herrath, Matthias
Greenbaum, Carla J.
author_sort Speake, Cate
collection PubMed
description Immune analytes have been widely tested in efforts to understand the heterogeneity of disease progression, risk, and therapeutic responses in type 1 diabetes (T1D). The future clinical utility of such analytes as biomarkers depends on their technical and biological variability, as well as their correlation with clinical outcomes. To assess the variability of a panel of 91 immune analytes, we conducted a prospective study of adults with T1D (<3 years from diagnosis), at 9–10 visits over 1 year. Autoantibodies and frequencies of T-cell, natural killer cell, and myeloid subsets were evaluated; autoreactive T-cell frequencies and function were also measured. We calculated an intraclass correlation coefficient (ICC) for each marker, which is a relative measure of between- and within-subject variability. Of the 91 analytes tested, we identified 35 with high between- and low within-subject variability, indicating their potential ability to be used to stratify subjects. We also provide extensive data regarding technical variability for 64 of the 91 analytes. To pilot the concept that ICC can be used to identify analytes that reflect biological outcomes, the association between each immune analyte and C-peptide was also evaluated using partial least squares modeling. CD8 effector memory T-cell (CD8 EM) frequency exhibited a high ICC and a positive correlation with C-peptide, which was also seen in an independent dataset of recent-onset T1D subjects. More work is needed to better understand the mechanisms underlying this relationship. Here we find that there are a limited number of technically reproducible immune analytes that also have a high ICC. We propose the use of ICC to define within- and between-subject variability and measurement of technical variability for future biomarker identification studies. Employing such a method is critical for selection of analytes to be tested in the context of future clinical trials aiming to understand heterogeneity in disease progression and response to therapy.
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spelling pubmed-67536182019-09-30 Systematic Assessment of Immune Marker Variation in Type 1 Diabetes: A Prospective Longitudinal Study Speake, Cate Bahnson, Henry T. Wesley, Johnna D. Perdue, Nikole Friedrich, David Pham, Minh N. Lanxon-Cookson, Erinn Kwok, William W. Sehested Hansen, Birgit von Herrath, Matthias Greenbaum, Carla J. Front Immunol Immunology Immune analytes have been widely tested in efforts to understand the heterogeneity of disease progression, risk, and therapeutic responses in type 1 diabetes (T1D). The future clinical utility of such analytes as biomarkers depends on their technical and biological variability, as well as their correlation with clinical outcomes. To assess the variability of a panel of 91 immune analytes, we conducted a prospective study of adults with T1D (<3 years from diagnosis), at 9–10 visits over 1 year. Autoantibodies and frequencies of T-cell, natural killer cell, and myeloid subsets were evaluated; autoreactive T-cell frequencies and function were also measured. We calculated an intraclass correlation coefficient (ICC) for each marker, which is a relative measure of between- and within-subject variability. Of the 91 analytes tested, we identified 35 with high between- and low within-subject variability, indicating their potential ability to be used to stratify subjects. We also provide extensive data regarding technical variability for 64 of the 91 analytes. To pilot the concept that ICC can be used to identify analytes that reflect biological outcomes, the association between each immune analyte and C-peptide was also evaluated using partial least squares modeling. CD8 effector memory T-cell (CD8 EM) frequency exhibited a high ICC and a positive correlation with C-peptide, which was also seen in an independent dataset of recent-onset T1D subjects. More work is needed to better understand the mechanisms underlying this relationship. Here we find that there are a limited number of technically reproducible immune analytes that also have a high ICC. We propose the use of ICC to define within- and between-subject variability and measurement of technical variability for future biomarker identification studies. Employing such a method is critical for selection of analytes to be tested in the context of future clinical trials aiming to understand heterogeneity in disease progression and response to therapy. Frontiers Media S.A. 2019-09-13 /pmc/articles/PMC6753618/ /pubmed/31572352 http://dx.doi.org/10.3389/fimmu.2019.02023 Text en Copyright © 2019 Speake, Bahnson, Wesley, Perdue, Friedrich, Pham, Lanxon-Cookson, Kwok, Sehested Hansen, von Herrath and Greenbaum. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Immunology
Speake, Cate
Bahnson, Henry T.
Wesley, Johnna D.
Perdue, Nikole
Friedrich, David
Pham, Minh N.
Lanxon-Cookson, Erinn
Kwok, William W.
Sehested Hansen, Birgit
von Herrath, Matthias
Greenbaum, Carla J.
Systematic Assessment of Immune Marker Variation in Type 1 Diabetes: A Prospective Longitudinal Study
title Systematic Assessment of Immune Marker Variation in Type 1 Diabetes: A Prospective Longitudinal Study
title_full Systematic Assessment of Immune Marker Variation in Type 1 Diabetes: A Prospective Longitudinal Study
title_fullStr Systematic Assessment of Immune Marker Variation in Type 1 Diabetes: A Prospective Longitudinal Study
title_full_unstemmed Systematic Assessment of Immune Marker Variation in Type 1 Diabetes: A Prospective Longitudinal Study
title_short Systematic Assessment of Immune Marker Variation in Type 1 Diabetes: A Prospective Longitudinal Study
title_sort systematic assessment of immune marker variation in type 1 diabetes: a prospective longitudinal study
topic Immunology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6753618/
https://www.ncbi.nlm.nih.gov/pubmed/31572352
http://dx.doi.org/10.3389/fimmu.2019.02023
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