严重哮喘气道具有与 WNT 信号相关的独特昼夜节律钟基因表达模式。

IF 4.6 2区 医学 Q2 ALLERGY
Nguyen Quoc Vuong Tran, Minh Khang Le, Yuki Nakamura, Atsuhito Nakao
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This study analyzed the expression profiles of circadian clock genes and their potential significance in asthmatic airways using a public database of patients with asthma.</p><p>Gene expression data from bronchial epithelial brushing samples of patients with mild/moderate and severe asthma and healthy subjects were obtained from five publicly available NCBI-GEO datasets (GSE41861, GSE43696, GSE63142, GSE67472, and GSE89809). Two bronchial epithelial brushing sample datasets of COPD patients (GSE20257 and GSE37147) and two peripheral blood sample datasets of patients with asthma (GSE69683 and GSE207751) were used as controls. Information of datasets analyzed in this study was summarized in Table S1.</p><p>Differential gene expression analysis of 34 circadian clock genes showed that <i>NR1D2</i>, <i>PER2</i>, and <i>PER3</i> are downregulated in bronchial epithelial samples from patients with asthma, apparently in those from severe asthma in four of the five datasets (4/5) compared with normal subjects (Figure 1A,B, Figure S1A, Table S2). Considering the lack of information on the timing of sampling, we conducted a sensitivity analysis for gene expression using relative amplitude data for <i>NR1D2</i>, <i>PER2</i>, and <i>PER3</i> from CircaDB, a database of circadian gene expression profile.<span><sup>4</sup></span> Even after accounting for diurnal variations, the differences in <i>PER2</i> expression remained significant in 3/5 datasets, while for <i>NR1D2</i> and <i>PER3</i>, significance was observed in only 2/5 datasets (Figure 1C, Figure S1B). Corroborating our findings, a previous study using time-matched bronchial brushing samples showed that the expression of <i>NR1D2</i> and <i>PER2</i> was reduced in asthma patients, as determined by Real-time PCR.<span><sup>5</sup></span></p><p>Importantly, in bronchial epithelial tissue, dimension reduction by principal component analysis and t-distributed stochastic neighbor embedding using the expression of <i>NR1D2</i>, <i>PER2</i>, and <i>PER3</i> showed distinct clustering between healthy subjects and patients with severe asthma (Figure 1D, Figure S1C). For comparison, we performed the same exploration on two peripheral blood sample datasets of patients with asthma and two bronchial epithelial brushing sample datasets of COPD patients. The distinct cluster was not seen in blood sample analyses from asthma patients despite the significantly downregulation of NR1D2, PER2, and PER3 (GSE69683, GSE207751) (Figure 1E, Figure S2) or in COPD (GSE20257, GSE37147) (Figure 1F, Figure S3). Thus, the alterations in <i>NR1D2</i>, <i>PER2</i>, and <i>PER3</i> may be specific to the severe asthmatic airways. Furthermore, a logistic regression model using these three genes successfully distinguishing healthy subjects from patients with severe asthma with high accuracy (0.8, 95% CI: 0.66–0.9, AUC: 0.81) (Figure 1G).</p><p>To explore possible pathophysiological significance of the alterations in three clock gene expression in severe asthmatic airways, we identified 41 genes correlated with <i>NR1D2</i>, <i>PER2</i>, or <i>PER3</i> that were differentially expressed in healthy subjects and patients with severe asthma (Table S3 and S4). Network analysis with STRING identified interactions between these circadian genes and a node centered around Catenin Beta 1 (<i>CTNNB1</i>), a key component of WNT signaling pathway (Figure 2A). Pathway analysis showed significant reduced activity of WNT and also NOTCH signaling pathways in severe asthma in 3/4 applicable datasets (Figure 2B).</p><p>Patients with mild/moderate asthma were interspersed among both healthy controls and severe asthma patients in the dimension reduction analysis (Figure 2C), suggesting that their circadian gene expression patterns may align with either the healthy-like or severe-like circadian type. To explore this further, the logistic regression model (Figure 1E) was used to categorize patients with mild/moderate asthma into either the healthy-like or severe-like circadian type. Pathway analysis showed significant reduced WNT and also NOTCH signaling activity in patients with the severe-like circadian type in 3/5 datasets (Figure 2D) as well as in severe asthma patients (Figure 2B).</p><p>Further analysis revealed changes in WNT signaling genes in severe asthma: <i>WNT5B</i> and <i>WNT7B</i> were downregulated, while <i>WNT11</i> was upregulated. Downstream, genes of canonical WNT signaling (<i>AXIN2</i>, <i>CCND1</i>, <i>GSK3B</i>) trended toward downregulation, whereas non-canonical signaling genes (<i>ROR1</i>, <i>ROR2</i>) showed potential upregulation (Figure 2E, Figure S4). Interestingly, this pattern, especially <i>WNT11</i> upregulation and canonical signaling genes downregulation, was also seen in the severe-like circadian phenotype (Figure 2F, Figure S5). WNT11 is known to induce non-canonical WNT signaling and contributed to airway remodeling in asthma.<span><sup>6, 7</sup></span> Conversely, canonical WNT signaling is reported to protect against allergic airway disease.<span><sup>8</sup></span> Collectively, these findings strongly support the idea that altered expression of <i>NR1D2</i>, <i>PER2</i>, and <i>PER3</i> in severe asthmatic airways is associated with altered activity of WNT and NOTCH signaling possibly via <i>CTNNB1</i>. Recently, the interaction between circadian clock and WNT signaling plays important role in lung regeneration,<span><sup>9</sup></span> which may be important for airway remodeling in asthma. Future research using single-cell RNA sequencing of asthma airways could reveal the complex relationships between the circadian clock, WNT signaling, and asthma pathology.</p><p>This study has several limitations. Firstly, the lack of information on specific sampling times restricted our analysis although bronchial epithelial brushing samples are likely collected during regular operation hours and we have considered diurnal variations in our analysis (Figure 1C). Secondly, we cannot exclude potential influence of asthma treatment including corticosteroid,<span><sup>10</sup></span> since most patients in the datasets, except for GSE67472, were on asthma medication. Thirdly, the causal link between the altered expression of these genes and reduced WNT signaling activity in severe asthma remains uncertain. Considering the bidirectional interaction of the circadian clock with key signaling pathways, these factors might jointly contribute to severe asthma development.<span><sup>11</sup></span> Further experimental and clinical studies is necessary to overcome these limitations.</p><p>In summary, we show that severe asthmatic airways have distinct circadian clock gene expression patterns associated with WNT signaling, a crucial pathway for airway remodeling in asthma. Thus, disturbance of airway circadian clock activity may be one of the determining features of severe asthma.</p><p><b>Nguyen Quoc Vuong Tran</b>: Conceptualization; data curation; formal analysis; writing—original draft. <b>Minh Khang Le</b>: Data curation; formal analysis; writing—original draft. <b>Yuki Nakamura</b>: Formal analysis; writing—original draft; <b>Atsuhito Nakao</b>: Conceptualization; formal analysis; funding acquisition; writing—original draft.</p><p>The authors declare no conflicts of interest.</p>","PeriodicalId":10334,"journal":{"name":"Clinical and Translational Allergy","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11213687/pdf/","citationCount":"0","resultStr":"{\"title\":\"Severe asthmatic airways have distinct circadian clock gene expression pattern associated with WNT signaling\",\"authors\":\"Nguyen Quoc Vuong Tran,&nbsp;Minh Khang Le,&nbsp;Yuki Nakamura,&nbsp;Atsuhito Nakao\",\"doi\":\"10.1002/clt2.12379\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>To the Editor,</p><p>The circadian clock, which consists of a network of approximately 30 clock genes, enables organisms to coordinate physiological processes including airway function in synchrony with the changing 24-h environment.<span><sup>1</sup></span> Asthma is characterized by a marked day–night variation in symptoms and laboratory parameters in the airways, suggesting that the airway circadian clock underpins the pathology of asthma.<span><sup>2, 3</sup></span> However, the basic question, “do asthmatic airways have normal or altered circadian clock activity?” remains unanswered. This study analyzed the expression profiles of circadian clock genes and their potential significance in asthmatic airways using a public database of patients with asthma.</p><p>Gene expression data from bronchial epithelial brushing samples of patients with mild/moderate and severe asthma and healthy subjects were obtained from five publicly available NCBI-GEO datasets (GSE41861, GSE43696, GSE63142, GSE67472, and GSE89809). Two bronchial epithelial brushing sample datasets of COPD patients (GSE20257 and GSE37147) and two peripheral blood sample datasets of patients with asthma (GSE69683 and GSE207751) were used as controls. Information of datasets analyzed in this study was summarized in Table S1.</p><p>Differential gene expression analysis of 34 circadian clock genes showed that <i>NR1D2</i>, <i>PER2</i>, and <i>PER3</i> are downregulated in bronchial epithelial samples from patients with asthma, apparently in those from severe asthma in four of the five datasets (4/5) compared with normal subjects (Figure 1A,B, Figure S1A, Table S2). Considering the lack of information on the timing of sampling, we conducted a sensitivity analysis for gene expression using relative amplitude data for <i>NR1D2</i>, <i>PER2</i>, and <i>PER3</i> from CircaDB, a database of circadian gene expression profile.<span><sup>4</sup></span> Even after accounting for diurnal variations, the differences in <i>PER2</i> expression remained significant in 3/5 datasets, while for <i>NR1D2</i> and <i>PER3</i>, significance was observed in only 2/5 datasets (Figure 1C, Figure S1B). Corroborating our findings, a previous study using time-matched bronchial brushing samples showed that the expression of <i>NR1D2</i> and <i>PER2</i> was reduced in asthma patients, as determined by Real-time PCR.<span><sup>5</sup></span></p><p>Importantly, in bronchial epithelial tissue, dimension reduction by principal component analysis and t-distributed stochastic neighbor embedding using the expression of <i>NR1D2</i>, <i>PER2</i>, and <i>PER3</i> showed distinct clustering between healthy subjects and patients with severe asthma (Figure 1D, Figure S1C). For comparison, we performed the same exploration on two peripheral blood sample datasets of patients with asthma and two bronchial epithelial brushing sample datasets of COPD patients. The distinct cluster was not seen in blood sample analyses from asthma patients despite the significantly downregulation of NR1D2, PER2, and PER3 (GSE69683, GSE207751) (Figure 1E, Figure S2) or in COPD (GSE20257, GSE37147) (Figure 1F, Figure S3). Thus, the alterations in <i>NR1D2</i>, <i>PER2</i>, and <i>PER3</i> may be specific to the severe asthmatic airways. Furthermore, a logistic regression model using these three genes successfully distinguishing healthy subjects from patients with severe asthma with high accuracy (0.8, 95% CI: 0.66–0.9, AUC: 0.81) (Figure 1G).</p><p>To explore possible pathophysiological significance of the alterations in three clock gene expression in severe asthmatic airways, we identified 41 genes correlated with <i>NR1D2</i>, <i>PER2</i>, or <i>PER3</i> that were differentially expressed in healthy subjects and patients with severe asthma (Table S3 and S4). Network analysis with STRING identified interactions between these circadian genes and a node centered around Catenin Beta 1 (<i>CTNNB1</i>), a key component of WNT signaling pathway (Figure 2A). Pathway analysis showed significant reduced activity of WNT and also NOTCH signaling pathways in severe asthma in 3/4 applicable datasets (Figure 2B).</p><p>Patients with mild/moderate asthma were interspersed among both healthy controls and severe asthma patients in the dimension reduction analysis (Figure 2C), suggesting that their circadian gene expression patterns may align with either the healthy-like or severe-like circadian type. To explore this further, the logistic regression model (Figure 1E) was used to categorize patients with mild/moderate asthma into either the healthy-like or severe-like circadian type. 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WNT11 is known to induce non-canonical WNT signaling and contributed to airway remodeling in asthma.<span><sup>6, 7</sup></span> Conversely, canonical WNT signaling is reported to protect against allergic airway disease.<span><sup>8</sup></span> Collectively, these findings strongly support the idea that altered expression of <i>NR1D2</i>, <i>PER2</i>, and <i>PER3</i> in severe asthmatic airways is associated with altered activity of WNT and NOTCH signaling possibly via <i>CTNNB1</i>. Recently, the interaction between circadian clock and WNT signaling plays important role in lung regeneration,<span><sup>9</sup></span> which may be important for airway remodeling in asthma. Future research using single-cell RNA sequencing of asthma airways could reveal the complex relationships between the circadian clock, WNT signaling, and asthma pathology.</p><p>This study has several limitations. 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引用次数: 0

摘要

致编辑:昼夜节律时钟由大约 30 个时钟基因组成,它使生物体能够随着 24 小时环境的变化同步协调包括气道功能在内的生理过程。1 哮喘的特点是气道中的症状和实验室参数昼夜变化明显,这表明气道昼夜节律时钟是哮喘病理学的基础。本研究利用哮喘患者公共数据库分析了昼夜节律钟基因的表达谱及其在哮喘气道中的潜在意义。研究人员从五个公开的 NCBI-GEO 数据集(GSE41861、GSE43696、GSE63142、GSE67472 和 GSE89809)中获得了轻度/中度和重度哮喘患者以及健康受试者支气管上皮刷洗样本的基因表达数据。两个 COPD 患者的支气管上皮刷毛样本数据集(GSE20257 和 GSE37147)和两个哮喘患者的外周血样本数据集(GSE69683 和 GSE207751)被用作对照。对 34 个昼夜节律时钟基因的差异基因表达分析表明,与正常人相比,哮喘患者支气管上皮样本中的 NR1D2、PER2 和 PER3 下调,与正常人相比,5 个数据集中的 4 个数据集(4/5)中的重症哮喘患者支气管上皮样本中的 NR1D2、PER2 和 PER3 下调(图 1A、B,图 S1A,表 S2)。考虑到缺乏取样时间的信息,我们使用昼夜节律基因表达谱数据库 CircaDB 中 NR1D2、PER2 和 PER3 的相对振幅数据进行了基因表达的敏感性分析。5 重要的是,在支气管上皮组织中,利用 NR1D2、PER2 和 PER3 的表达通过主成分分析和 t 分布随机邻接嵌入进行降维显示,健康受试者和严重哮喘患者之间存在明显的聚类(图 1D,图 S1C)。为了进行比较,我们对哮喘患者的两个外周血样本数据集和慢性阻塞性肺病患者的两个支气管上皮刷洗样本数据集进行了同样的探索。尽管 NR1D2、PER2 和 PER3 显著下调(GSE69683、GSE207751)(图 1E、图 S2),但在哮喘患者的血液样本分析中(GSE20257、GSE37147)或在 COPD 患者的血液样本分析中(图 1F、图 S3)并没有发现明显的集群。因此,NR1D2、PER2 和 PER3 的改变可能是严重哮喘气道所特有的。此外,利用这三个基因建立的逻辑回归模型成功地将健康受试者与重症哮喘患者区分开来,准确率很高(0.8,95% CI:0.66-0.9,AUC:0.81)(图 1G)。为了探索三个时钟基因表达的改变在重症哮喘气道中可能具有的病理生理学意义,我们发现了 41 个与 NR1D2、PER2 或 PER3 相关的基因在健康受试者和重症哮喘患者中表达不同(表 S3 和 S4)。利用 STRING 进行的网络分析发现了这些昼夜节律基因与以 Catenin Beta 1(CTNNB1)为中心的节点之间的相互作用,CTNNB1 是 WNT 信号通路的关键组成部分(图 2A)。在维度缩减分析中,轻度/中度哮喘患者夹杂在健康对照组和重度哮喘患者中(图 2C),这表明他们的昼夜节律基因表达模式可能与健康样或重度样昼夜节律类型一致。为了进一步探讨这一问题,我们使用逻辑回归模型(图 1E)将轻度/中度哮喘患者分为健康样或重度样昼夜节律类型。通路分析表明,在 3/5 个数据集(图 2D)和重症哮喘患者(图 2B)中,重症类昼夜节律型患者的 WNT 和 NOTCH 信号活性显著降低:进一步分析发现,重症哮喘患者的 WNT 信号基因发生了变化:WNT5B 和 WNT7B 下调,而 WNT11 上调。下游的典型 WNT 信号转导基因(AXIN2、CCND1、GSK3B)呈下调趋势,而非典型信号转导基因(ROR1、ROR2)则有可能上调(图 2E,图 S4)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Severe asthmatic airways have distinct circadian clock gene expression pattern associated with WNT signaling

Severe asthmatic airways have distinct circadian clock gene expression pattern associated with WNT signaling

To the Editor,

The circadian clock, which consists of a network of approximately 30 clock genes, enables organisms to coordinate physiological processes including airway function in synchrony with the changing 24-h environment.1 Asthma is characterized by a marked day–night variation in symptoms and laboratory parameters in the airways, suggesting that the airway circadian clock underpins the pathology of asthma.2, 3 However, the basic question, “do asthmatic airways have normal or altered circadian clock activity?” remains unanswered. This study analyzed the expression profiles of circadian clock genes and their potential significance in asthmatic airways using a public database of patients with asthma.

Gene expression data from bronchial epithelial brushing samples of patients with mild/moderate and severe asthma and healthy subjects were obtained from five publicly available NCBI-GEO datasets (GSE41861, GSE43696, GSE63142, GSE67472, and GSE89809). Two bronchial epithelial brushing sample datasets of COPD patients (GSE20257 and GSE37147) and two peripheral blood sample datasets of patients with asthma (GSE69683 and GSE207751) were used as controls. Information of datasets analyzed in this study was summarized in Table S1.

Differential gene expression analysis of 34 circadian clock genes showed that NR1D2, PER2, and PER3 are downregulated in bronchial epithelial samples from patients with asthma, apparently in those from severe asthma in four of the five datasets (4/5) compared with normal subjects (Figure 1A,B, Figure S1A, Table S2). Considering the lack of information on the timing of sampling, we conducted a sensitivity analysis for gene expression using relative amplitude data for NR1D2, PER2, and PER3 from CircaDB, a database of circadian gene expression profile.4 Even after accounting for diurnal variations, the differences in PER2 expression remained significant in 3/5 datasets, while for NR1D2 and PER3, significance was observed in only 2/5 datasets (Figure 1C, Figure S1B). Corroborating our findings, a previous study using time-matched bronchial brushing samples showed that the expression of NR1D2 and PER2 was reduced in asthma patients, as determined by Real-time PCR.5

Importantly, in bronchial epithelial tissue, dimension reduction by principal component analysis and t-distributed stochastic neighbor embedding using the expression of NR1D2, PER2, and PER3 showed distinct clustering between healthy subjects and patients with severe asthma (Figure 1D, Figure S1C). For comparison, we performed the same exploration on two peripheral blood sample datasets of patients with asthma and two bronchial epithelial brushing sample datasets of COPD patients. The distinct cluster was not seen in blood sample analyses from asthma patients despite the significantly downregulation of NR1D2, PER2, and PER3 (GSE69683, GSE207751) (Figure 1E, Figure S2) or in COPD (GSE20257, GSE37147) (Figure 1F, Figure S3). Thus, the alterations in NR1D2, PER2, and PER3 may be specific to the severe asthmatic airways. Furthermore, a logistic regression model using these three genes successfully distinguishing healthy subjects from patients with severe asthma with high accuracy (0.8, 95% CI: 0.66–0.9, AUC: 0.81) (Figure 1G).

To explore possible pathophysiological significance of the alterations in three clock gene expression in severe asthmatic airways, we identified 41 genes correlated with NR1D2, PER2, or PER3 that were differentially expressed in healthy subjects and patients with severe asthma (Table S3 and S4). Network analysis with STRING identified interactions between these circadian genes and a node centered around Catenin Beta 1 (CTNNB1), a key component of WNT signaling pathway (Figure 2A). Pathway analysis showed significant reduced activity of WNT and also NOTCH signaling pathways in severe asthma in 3/4 applicable datasets (Figure 2B).

Patients with mild/moderate asthma were interspersed among both healthy controls and severe asthma patients in the dimension reduction analysis (Figure 2C), suggesting that their circadian gene expression patterns may align with either the healthy-like or severe-like circadian type. To explore this further, the logistic regression model (Figure 1E) was used to categorize patients with mild/moderate asthma into either the healthy-like or severe-like circadian type. Pathway analysis showed significant reduced WNT and also NOTCH signaling activity in patients with the severe-like circadian type in 3/5 datasets (Figure 2D) as well as in severe asthma patients (Figure 2B).

Further analysis revealed changes in WNT signaling genes in severe asthma: WNT5B and WNT7B were downregulated, while WNT11 was upregulated. Downstream, genes of canonical WNT signaling (AXIN2, CCND1, GSK3B) trended toward downregulation, whereas non-canonical signaling genes (ROR1, ROR2) showed potential upregulation (Figure 2E, Figure S4). Interestingly, this pattern, especially WNT11 upregulation and canonical signaling genes downregulation, was also seen in the severe-like circadian phenotype (Figure 2F, Figure S5). WNT11 is known to induce non-canonical WNT signaling and contributed to airway remodeling in asthma.6, 7 Conversely, canonical WNT signaling is reported to protect against allergic airway disease.8 Collectively, these findings strongly support the idea that altered expression of NR1D2, PER2, and PER3 in severe asthmatic airways is associated with altered activity of WNT and NOTCH signaling possibly via CTNNB1. Recently, the interaction between circadian clock and WNT signaling plays important role in lung regeneration,9 which may be important for airway remodeling in asthma. Future research using single-cell RNA sequencing of asthma airways could reveal the complex relationships between the circadian clock, WNT signaling, and asthma pathology.

This study has several limitations. Firstly, the lack of information on specific sampling times restricted our analysis although bronchial epithelial brushing samples are likely collected during regular operation hours and we have considered diurnal variations in our analysis (Figure 1C). Secondly, we cannot exclude potential influence of asthma treatment including corticosteroid,10 since most patients in the datasets, except for GSE67472, were on asthma medication. Thirdly, the causal link between the altered expression of these genes and reduced WNT signaling activity in severe asthma remains uncertain. Considering the bidirectional interaction of the circadian clock with key signaling pathways, these factors might jointly contribute to severe asthma development.11 Further experimental and clinical studies is necessary to overcome these limitations.

In summary, we show that severe asthmatic airways have distinct circadian clock gene expression patterns associated with WNT signaling, a crucial pathway for airway remodeling in asthma. Thus, disturbance of airway circadian clock activity may be one of the determining features of severe asthma.

Nguyen Quoc Vuong Tran: Conceptualization; data curation; formal analysis; writing—original draft. Minh Khang Le: Data curation; formal analysis; writing—original draft. Yuki Nakamura: Formal analysis; writing—original draft; Atsuhito Nakao: Conceptualization; formal analysis; funding acquisition; writing—original draft.

The authors declare no conflicts of interest.

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来源期刊
Clinical and Translational Allergy
Clinical and Translational Allergy Immunology and Microbiology-Immunology
CiteScore
7.50
自引率
4.50%
发文量
117
审稿时长
12 weeks
期刊介绍: Clinical and Translational Allergy, one of several journals in the portfolio of the European Academy of Allergy and Clinical Immunology, provides a platform for the dissemination of allergy research and reviews, as well as EAACI position papers, task force reports and guidelines, amongst an international scientific audience. Clinical and Translational Allergy accepts clinical and translational research in the following areas and other related topics: asthma, rhinitis, rhinosinusitis, drug hypersensitivity, allergic conjunctivitis, allergic skin diseases, atopic eczema, urticaria, angioedema, venom hypersensitivity, anaphylaxis, food allergy, immunotherapy, immune modulators and biologics, animal models of allergic disease, immune mechanisms, or any other topic related to allergic disease.
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