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Gene expression signature predicts human islet integrity and transplant functionality in diabetic mice
There is growing evidence that transplantation of cadaveric human islets is an effective therapy for type 1 diabetes. However, gauging the suitability of islet samples for clinical use remains a challenge. We hypothesized that islet quality is reflected in the expression of specific genes. Therefore...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5624587/ https://www.ncbi.nlm.nih.gov/pubmed/28968432 http://dx.doi.org/10.1371/journal.pone.0185331 |
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author | Kurian, Sunil M. Ferreri, Kevin Wang, Chia-Hao Todorov, Ivan Al-Abdullah, Ismail H. Rawson, Jeffrey Mullen, Yoko Salomon, Daniel R. Kandeel, Fouad |
author_facet | Kurian, Sunil M. Ferreri, Kevin Wang, Chia-Hao Todorov, Ivan Al-Abdullah, Ismail H. Rawson, Jeffrey Mullen, Yoko Salomon, Daniel R. Kandeel, Fouad |
author_sort | Kurian, Sunil M. |
collection | PubMed |
description | There is growing evidence that transplantation of cadaveric human islets is an effective therapy for type 1 diabetes. However, gauging the suitability of islet samples for clinical use remains a challenge. We hypothesized that islet quality is reflected in the expression of specific genes. Therefore, gene expression in 59 human islet preparations was analyzed and correlated with diabetes reversal after transplantation in diabetic mice. Analysis yielded 262 differentially expressed probesets, which together predict islet quality with 83% accuracy. Pathway analysis revealed that failing islet preparations activated inflammatory pathways, while functional islets showed increased regeneration pathway gene expression. Gene expression associated with apoptosis and oxygen consumption showed little overlap with each other or with the 262 probeset classifier, indicating that the three tests are measuring different aspects of islet cell biology. A subset of 36 probesets surpassed the predictive accuracy of the entire set for reversal of diabetes, and was further reduced by logistic regression to sets of 14 and 5 without losing accuracy. These genes were further validated with an independent cohort of 16 samples. We believe this limited number of gene classifiers in combination with other tests may provide complementary verification of islet quality prior to their clinical use. |
format | Online Article Text |
id | pubmed-5624587 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-56245872017-10-17 Gene expression signature predicts human islet integrity and transplant functionality in diabetic mice Kurian, Sunil M. Ferreri, Kevin Wang, Chia-Hao Todorov, Ivan Al-Abdullah, Ismail H. Rawson, Jeffrey Mullen, Yoko Salomon, Daniel R. Kandeel, Fouad PLoS One Research Article There is growing evidence that transplantation of cadaveric human islets is an effective therapy for type 1 diabetes. However, gauging the suitability of islet samples for clinical use remains a challenge. We hypothesized that islet quality is reflected in the expression of specific genes. Therefore, gene expression in 59 human islet preparations was analyzed and correlated with diabetes reversal after transplantation in diabetic mice. Analysis yielded 262 differentially expressed probesets, which together predict islet quality with 83% accuracy. Pathway analysis revealed that failing islet preparations activated inflammatory pathways, while functional islets showed increased regeneration pathway gene expression. Gene expression associated with apoptosis and oxygen consumption showed little overlap with each other or with the 262 probeset classifier, indicating that the three tests are measuring different aspects of islet cell biology. A subset of 36 probesets surpassed the predictive accuracy of the entire set for reversal of diabetes, and was further reduced by logistic regression to sets of 14 and 5 without losing accuracy. These genes were further validated with an independent cohort of 16 samples. We believe this limited number of gene classifiers in combination with other tests may provide complementary verification of islet quality prior to their clinical use. Public Library of Science 2017-10-02 /pmc/articles/PMC5624587/ /pubmed/28968432 http://dx.doi.org/10.1371/journal.pone.0185331 Text en © 2017 Kurian et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Kurian, Sunil M. Ferreri, Kevin Wang, Chia-Hao Todorov, Ivan Al-Abdullah, Ismail H. Rawson, Jeffrey Mullen, Yoko Salomon, Daniel R. Kandeel, Fouad Gene expression signature predicts human islet integrity and transplant functionality in diabetic mice |
title | Gene expression signature predicts human islet integrity and transplant functionality in diabetic mice |
title_full | Gene expression signature predicts human islet integrity and transplant functionality in diabetic mice |
title_fullStr | Gene expression signature predicts human islet integrity and transplant functionality in diabetic mice |
title_full_unstemmed | Gene expression signature predicts human islet integrity and transplant functionality in diabetic mice |
title_short | Gene expression signature predicts human islet integrity and transplant functionality in diabetic mice |
title_sort | gene expression signature predicts human islet integrity and transplant functionality in diabetic mice |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5624587/ https://www.ncbi.nlm.nih.gov/pubmed/28968432 http://dx.doi.org/10.1371/journal.pone.0185331 |
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