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Validation of diagnostic and predictive biomarkers for hereditary angioedema via plasma N‐glycomics
BACKGROUND: Hereditary angioedema (HAE) is a rare disease with heterogeneous clinical symptoms. It is vitally important to predict whether an HAE patient will develop severe symptoms in clinical practice, but there are currently no predictive biomarkers for HAE stratification. Plasma N‐glycomes are...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8712629/ https://www.ncbi.nlm.nih.gov/pubmed/34962719 http://dx.doi.org/10.1002/clt2.12090 |
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author | Zhang, Zejian Wang, Xue Gu, Jianqing Wu, Jianqiang Cao, Yang Xu, Yingyang Li, Lisha Guan, Kai Liu, Peng Yin, Jia Zhi, Yuxiang Zhang, Shuyang |
author_facet | Zhang, Zejian Wang, Xue Gu, Jianqing Wu, Jianqiang Cao, Yang Xu, Yingyang Li, Lisha Guan, Kai Liu, Peng Yin, Jia Zhi, Yuxiang Zhang, Shuyang |
author_sort | Zhang, Zejian |
collection | PubMed |
description | BACKGROUND: Hereditary angioedema (HAE) is a rare disease with heterogeneous clinical symptoms. It is vitally important to predict whether an HAE patient will develop severe symptoms in clinical practice, but there are currently no predictive biomarkers for HAE stratification. Plasma N‐glycomes are disease‐specific and have great potential for the discovery of non‐invasive biomarkers. In this study, we profiled the plasma N‐glycome of HAE patients from two independent cohorts to identify candidate biomarkers. METHODS: Linkage‐specific sialylation derivatization combined with matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry detection and automated data processing was employed to analyze the plasma N‐glycome of two independent type‐1 HAE cohorts. RESULTS: HAE patients had abnormal glycan complexity, galactosylation, and α2,3‐ and α2,6‐linked sialylation compared to healthy controls (HC). The classification models based on dysregulated glycan traits could successfully discriminate between HAE and HC with area under the curves (AUCs) being greater than 0.9. Some of the aberrant glycans showed response to therapy. Moreover, we identified a series of glycan traits with strong associations with the occurrence of laryngeal or gastrointestinal angioedema or disease severity score. Predictive models based on these traits could be used to predict disease severity (AUC > 0.9). These results were replicated in an independent cohort. CONCLUSIONS: We reported the full plasma N‐glycomic signature of HAE for the first time, and identified potential biomarkers. These findings may play a critical role in predicting disease severity and guide the treatment of HAE in clinical practice. Further protein‐specific and prospective studies are needed to validate our findings. |
format | Online Article Text |
id | pubmed-8712629 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87126292022-01-04 Validation of diagnostic and predictive biomarkers for hereditary angioedema via plasma N‐glycomics Zhang, Zejian Wang, Xue Gu, Jianqing Wu, Jianqiang Cao, Yang Xu, Yingyang Li, Lisha Guan, Kai Liu, Peng Yin, Jia Zhi, Yuxiang Zhang, Shuyang Clin Transl Allergy Original Article BACKGROUND: Hereditary angioedema (HAE) is a rare disease with heterogeneous clinical symptoms. It is vitally important to predict whether an HAE patient will develop severe symptoms in clinical practice, but there are currently no predictive biomarkers for HAE stratification. Plasma N‐glycomes are disease‐specific and have great potential for the discovery of non‐invasive biomarkers. In this study, we profiled the plasma N‐glycome of HAE patients from two independent cohorts to identify candidate biomarkers. METHODS: Linkage‐specific sialylation derivatization combined with matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry detection and automated data processing was employed to analyze the plasma N‐glycome of two independent type‐1 HAE cohorts. RESULTS: HAE patients had abnormal glycan complexity, galactosylation, and α2,3‐ and α2,6‐linked sialylation compared to healthy controls (HC). The classification models based on dysregulated glycan traits could successfully discriminate between HAE and HC with area under the curves (AUCs) being greater than 0.9. Some of the aberrant glycans showed response to therapy. Moreover, we identified a series of glycan traits with strong associations with the occurrence of laryngeal or gastrointestinal angioedema or disease severity score. Predictive models based on these traits could be used to predict disease severity (AUC > 0.9). These results were replicated in an independent cohort. CONCLUSIONS: We reported the full plasma N‐glycomic signature of HAE for the first time, and identified potential biomarkers. These findings may play a critical role in predicting disease severity and guide the treatment of HAE in clinical practice. Further protein‐specific and prospective studies are needed to validate our findings. John Wiley and Sons Inc. 2021-12-27 /pmc/articles/PMC8712629/ /pubmed/34962719 http://dx.doi.org/10.1002/clt2.12090 Text en © 2021 The Authors. Clinical and Translational Allergy published by John Wiley & Sons Ltd on behalf of European Academy of Allergy and Clinical Immunology. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Zhang, Zejian Wang, Xue Gu, Jianqing Wu, Jianqiang Cao, Yang Xu, Yingyang Li, Lisha Guan, Kai Liu, Peng Yin, Jia Zhi, Yuxiang Zhang, Shuyang Validation of diagnostic and predictive biomarkers for hereditary angioedema via plasma N‐glycomics |
title | Validation of diagnostic and predictive biomarkers for hereditary angioedema via plasma N‐glycomics |
title_full | Validation of diagnostic and predictive biomarkers for hereditary angioedema via plasma N‐glycomics |
title_fullStr | Validation of diagnostic and predictive biomarkers for hereditary angioedema via plasma N‐glycomics |
title_full_unstemmed | Validation of diagnostic and predictive biomarkers for hereditary angioedema via plasma N‐glycomics |
title_short | Validation of diagnostic and predictive biomarkers for hereditary angioedema via plasma N‐glycomics |
title_sort | validation of diagnostic and predictive biomarkers for hereditary angioedema via plasma n‐glycomics |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8712629/ https://www.ncbi.nlm.nih.gov/pubmed/34962719 http://dx.doi.org/10.1002/clt2.12090 |
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