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Peripheral blood transcriptomic clusters uncovered immune phenotypes of asthma

BACKGROUND: Transcriptomic analysis has been used to elucidate the complex pathogenesis of heterogeneous disease and may also contribute to identify potential therapeutic targets by delineating the hub genes. This study aimed to investigate whether blood transcriptomic clustering can distinguish cli...

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Autores principales: Lee, Hyun Woo, Baek, Min-gyung, Choi, Sungmi, Ahn, Yoon Hae, Bang, Ji-Young, Sohn, Kyoung-Hee, Kang, Min-Gyu, Jung, Jae-Woo, Choi, Jeong-Hee, Cho, Sang-Heon, Yi, Hana, Kang, Hye-Ryun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9461267/
https://www.ncbi.nlm.nih.gov/pubmed/36076228
http://dx.doi.org/10.1186/s12931-022-02156-w
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author Lee, Hyun Woo
Baek, Min-gyung
Choi, Sungmi
Ahn, Yoon Hae
Bang, Ji-Young
Sohn, Kyoung-Hee
Kang, Min-Gyu
Jung, Jae-Woo
Choi, Jeong-Hee
Cho, Sang-Heon
Yi, Hana
Kang, Hye-Ryun
author_facet Lee, Hyun Woo
Baek, Min-gyung
Choi, Sungmi
Ahn, Yoon Hae
Bang, Ji-Young
Sohn, Kyoung-Hee
Kang, Min-Gyu
Jung, Jae-Woo
Choi, Jeong-Hee
Cho, Sang-Heon
Yi, Hana
Kang, Hye-Ryun
author_sort Lee, Hyun Woo
collection PubMed
description BACKGROUND: Transcriptomic analysis has been used to elucidate the complex pathogenesis of heterogeneous disease and may also contribute to identify potential therapeutic targets by delineating the hub genes. This study aimed to investigate whether blood transcriptomic clustering can distinguish clinical and immune phenotypes of asthmatics, and microbiome in asthmatics. METHODS: Transcriptomic expression of peripheral blood mononuclear cells (PBMCs) from 47 asthmatics and 21 non-asthmatics was measured using RNA sequencing. A hierarchical clustering algorithm was used to classify asthmatics. Differentially expressed genes, clinical phenotypes, immune phenotypes, and microbiome of each transcriptomic cluster were assessed. RESULTS: In asthmatics, three distinct transcriptomic clusters with numerously different transcriptomic expressions were identified. The proportion of severe asthmatics was highest in cluster 3 as 73.3%, followed by cluster 2 (45.5%) and cluster 1 (28.6%). While cluster 1 represented clinically non-severe T2 asthma, cluster 3 tended to include severe non-T2 asthma. Cluster 2 had features of both T2 and non-T2 asthmatics characterized by the highest serum IgE level and neutrophil-dominant sputum cell population. Compared to non-asthmatics, cluster 1 showed higher CCL23 and IL1RL1 expression while the expression of TREML4 was suppressed in cluster 3. CTSD and ALDH2 showed a significant positive linear relationship across three clusters in the order of cluster 1 to 3. No significant differences in the diversities of lung and gut microbiomes were observed among transcriptomic clusters of asthmatics and non-asthmatics. However, our study has limitations in that small sample size data were analyzed with unmeasured confounding factors and causal relationships or function pathways were not verified. CONCLUSIONS: Genetic clustering based on the blood transcriptome may provide novel immunological insight, which can be biomarkers of asthma immune phenotypes. Trial registration Retrospectively registered SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12931-022-02156-w.
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spelling pubmed-94612672022-09-10 Peripheral blood transcriptomic clusters uncovered immune phenotypes of asthma Lee, Hyun Woo Baek, Min-gyung Choi, Sungmi Ahn, Yoon Hae Bang, Ji-Young Sohn, Kyoung-Hee Kang, Min-Gyu Jung, Jae-Woo Choi, Jeong-Hee Cho, Sang-Heon Yi, Hana Kang, Hye-Ryun Respir Res Research BACKGROUND: Transcriptomic analysis has been used to elucidate the complex pathogenesis of heterogeneous disease and may also contribute to identify potential therapeutic targets by delineating the hub genes. This study aimed to investigate whether blood transcriptomic clustering can distinguish clinical and immune phenotypes of asthmatics, and microbiome in asthmatics. METHODS: Transcriptomic expression of peripheral blood mononuclear cells (PBMCs) from 47 asthmatics and 21 non-asthmatics was measured using RNA sequencing. A hierarchical clustering algorithm was used to classify asthmatics. Differentially expressed genes, clinical phenotypes, immune phenotypes, and microbiome of each transcriptomic cluster were assessed. RESULTS: In asthmatics, three distinct transcriptomic clusters with numerously different transcriptomic expressions were identified. The proportion of severe asthmatics was highest in cluster 3 as 73.3%, followed by cluster 2 (45.5%) and cluster 1 (28.6%). While cluster 1 represented clinically non-severe T2 asthma, cluster 3 tended to include severe non-T2 asthma. Cluster 2 had features of both T2 and non-T2 asthmatics characterized by the highest serum IgE level and neutrophil-dominant sputum cell population. Compared to non-asthmatics, cluster 1 showed higher CCL23 and IL1RL1 expression while the expression of TREML4 was suppressed in cluster 3. CTSD and ALDH2 showed a significant positive linear relationship across three clusters in the order of cluster 1 to 3. No significant differences in the diversities of lung and gut microbiomes were observed among transcriptomic clusters of asthmatics and non-asthmatics. However, our study has limitations in that small sample size data were analyzed with unmeasured confounding factors and causal relationships or function pathways were not verified. CONCLUSIONS: Genetic clustering based on the blood transcriptome may provide novel immunological insight, which can be biomarkers of asthma immune phenotypes. Trial registration Retrospectively registered SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12931-022-02156-w. BioMed Central 2022-09-08 2022 /pmc/articles/PMC9461267/ /pubmed/36076228 http://dx.doi.org/10.1186/s12931-022-02156-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Lee, Hyun Woo
Baek, Min-gyung
Choi, Sungmi
Ahn, Yoon Hae
Bang, Ji-Young
Sohn, Kyoung-Hee
Kang, Min-Gyu
Jung, Jae-Woo
Choi, Jeong-Hee
Cho, Sang-Heon
Yi, Hana
Kang, Hye-Ryun
Peripheral blood transcriptomic clusters uncovered immune phenotypes of asthma
title Peripheral blood transcriptomic clusters uncovered immune phenotypes of asthma
title_full Peripheral blood transcriptomic clusters uncovered immune phenotypes of asthma
title_fullStr Peripheral blood transcriptomic clusters uncovered immune phenotypes of asthma
title_full_unstemmed Peripheral blood transcriptomic clusters uncovered immune phenotypes of asthma
title_short Peripheral blood transcriptomic clusters uncovered immune phenotypes of asthma
title_sort peripheral blood transcriptomic clusters uncovered immune phenotypes of asthma
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9461267/
https://www.ncbi.nlm.nih.gov/pubmed/36076228
http://dx.doi.org/10.1186/s12931-022-02156-w
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