Peripheral blood transcriptomic clusters uncovered immune phenotypes of asthma

被引:6
|
作者
Lee, Hyun Woo [1 ]
Baek, Min-Gyung [2 ]
Choi, Sungmi [2 ]
Ahn, Yoon Hae [3 ]
Bang, Ji-Young [4 ]
Sohn, Kyoung-Hee [5 ]
Kang, Min-Gyu [6 ]
Jung, Jae-Woo [7 ]
Choi, Jeong-Hee [8 ]
Cho, Sang-Heon [3 ,9 ]
Yi, Hana [2 ,10 ]
Kang, Hye-Ryun [3 ,4 ,9 ]
机构
[1] Seoul Natl Univ, Dept Internal Med, Seoul Metropolitan Govt, Boramae Med Ctr, Seoul, South Korea
[2] Korea Univ, Interdisciplinary Program Precis Publ Hlth, Seoul, South Korea
[3] Seoul Natl Univ Hosp, Dept Internal Med, 101 Daehak Ro, Seoul 110744, South Korea
[4] Seoul Natl Univ, Dept Translat Med, Coll Med, Seoul, South Korea
[5] Kyung Hee Univ Hosp, Dept Internal Med, Seoul, South Korea
[6] Chungbuk Natl Univ, Chungbuk Natl Univ Hosp, Dept Internal Med, Coll Med, Cheongju, South Korea
[7] Chung Ang Univ, Dept Internal Med, Coll Med, Seoul, South Korea
[8] Hallym Univ, Allergy & Clin Immunol Res Ctr, Dept Pulmonol & Allergy, Coll Med, Chunchon, South Korea
[9] Seoul Natl Univ, Med Res Ctr, Inst Allergy & Clin Immunol, Coll Med, Seoul, South Korea
[10] Korea Univ, Sch Biosyst & Biomed Sci, 145 Anam Ro, Seoul 02841, South Korea
关键词
Asthma; Cluster analysis; Microbiome; RNA-Seq; Transcriptome; DOUBLE-BLIND; EXPRESSION; CCL23; INFLAMMATION; DEFINITION; CHEMOKINE; SEVERITY; PROTEIN; ADULTS; LUNG;
D O I
10.1186/s12931-022-02156-w
中图分类号
R56 [呼吸系及胸部疾病];
学科分类号
摘要
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
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页数:12
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