To the Editor,

Allergic asthma (AA) in childhood is characterized by a dominance of type 2 immunity driven by CD4⁺ T helper 2 (Th2) cells expressing the transcription factor (TF) GATA3 and inefficient counter-regulation by Tregs among other mechanisms.¹ However, a detailed analysis of T-cells associated with pediatric AA is still needed.

To explore T-cell phenotypes associating with pediatric AA, we applied a 42-antibody mass cytometry panel in combination with unsupervised computational analyses in a cohort of well-characterized 14 treatment naïve AA and 9 healthy children (HC) from the CLARA/CLAUS study (Table S1,S2 Figure S1A).² Integrating information from 12 lineage markers, we identified seven major T- and NK-cell populations within peripheral blood mononuclear cells (PBMC) (Figure S1B,C) of which CD8⁺ T-cell abundance was reduced with underrepresented memory compartment in AA vs HC (Figure 1A,S1D,E).

Accordingly, the CD4/CD8 T-cell ratio was elevated in AA vs HC and positively correlated with blood eosinophil frequencies, a determinant of AA severity,³ in AA but not in HC (Figure 1B,C,S1F). To address potential disease-associated changes within the CD4⁺ T-cell compartment, we selected 30 markers for subsequent clustering using FlowSOM algorithm. Two clusters, CD4_c6 and CD4_c30, were expanded in AA vs HC (Figure 1D,E,S1G,H). Cluster CD4_c6 represented Th2 cells (Figure 1F), since it expressed the Th2-specific TF GATA3 and chemokine receptors CRTH2 and CCR4.⁴ It uniquely co-expressed TIGIT and ICOS, which was not reported in AA before and could be specific for childhood, since TIGIT hypomethylation has been described only in pediatric AA.⁵ Manual gating confirmed higher abundance of ICOS⁺TIGIT⁺Th2-cells in AA vs HC (Figure S2A-C). This cell population was also characterized by CD161 expression, as described for Th2-cells restricted to atopic adults,⁶ thereby underpinning its probable pro-allergic nature. The frequency of the CD4_c6 cluster positively correlated with eosinophilia in AA with allergic comorbidities and also with CD4/CD8 T-cell ratio in asthmatics having intermittent disease symptoms, while inversely in stable disease (Figure 1G,H), suggesting its association with more symptomatic disease in relation to the CD4/CD8 T-cell ratio and allergic comorbidity in connection with eosinophilia.

Cluster CD4_c30 expressing markers characterizing naïve/resting Tregs (Figure S2D) matched the previously described CD45RA⁺FOXP3^low Treg fraction(Fr)-I,⁷ while effector (e)Tregs represented Fr-II (CD45RA⁻FOXP3^high) and Fr-III (CD45RA⁻FOXP3^low) (Figure 1I). Accordingly, the frequencies of Fr-I were enriched in AA vs HC, while Fr-II and Fr-III were similar (Figure S2E). Cluster CD4_c30 abundance tended to correlate inversely with lung function, and significantly with memory CD8⁺ T-cell frequencies (Figure 1J,S2F), indicating its partial connection to lung function and CD8⁺ T-cell alterations. The abundances of Fr-I vs Fr-II correlated inversely (Figure 1K), consistent with the linear developmental model,⁷ suggesting a differentiation block from Fr-I toward Fr-II, and a possible altered eTreg compartment.

Therefore, we next analyzed manually gated eTregs (Figure S1B), by FlowSOM clustering, which revealed an underrepresented eTreg_c2 and partially eTreg_c10 in AA (Figure 2A,B, Figure S2G). Considering a possible eTregs impairment and an overrepresentation of TIGIT⁺ICOS⁺Th2-cells (CD4_c6), we asked if the two phenomena are connected. Indeed, the CD4_c6/eTregs ratio tended to be higher in children with AA versus HC, but failed to associate with eosinophilia in AA and in HC, whereby eosinophilia was markedly lower in HC vs AA (Figure 2C,D, Figure S2H). In contrast, CD4_c6 ratio to eTreg_c2 and eTreg_c10 correlated significantly in AA but not in HC, suggesting a specific relation between eTreg_c2 and eTreg_c10 underrepresentation and TIGIT⁺ICOS⁺Th2-cell (CD4_c6)-associated eosinophilia in pediatric AA. Thus, eTregs (eTreg_c2 and eTreg_c10) and naïve/resting Tregs (CD4_c30) are involved in two different pathological features of AA, in the eosinophilia and in part in the lung function, respectively.

Next, we performed principal component analysis (PCA) based on significantly changed ratio and subset-frequencies, which separated AA from HC children at the first PC, indicating that the detected dysbalanced T-cell composition allows a discrimination between these two groups (Figure 2E). Additionally, ROC analyses revealed a relation of resting/naïve Tregs (CD4_c30), eTreg_c2 and eTreg_c10 to the pediatric AA phenotype (sensitivity, true positive rate) (Figure 2F), further supporting the relevant involvement of the Treg dysbalance in childhood AA.

Summarizing, despite an explorative character without multiple testing adjustment, our study identifies a unique T-cell signature of childhood AA and provides insights for pathophysiological involvement of dysbalanced Tregs, TIGIT⁺ICOS⁺ Th2 and memory CD8⁺ T-cells. This can be useful for immunomonitoring, immunomodulation, and for confirmatory larger studies in childhood AA.

致编辑，

^{儿童期过敏性哮喘 (AA) 的特征是由表达转录因子 (TF) GATA3 的 CD4 +} T 辅助 2 (Th2) 细胞驱动的 2 型免疫占主导地位，以及 Tregs 的低效反调节以及其他机制。¹然而，仍然需要对与儿科 AA 相关的 T 细胞进行详细分析。

为了探索与儿科 AA 相关的 T 细胞表型，我们在 CLARA/CLAUS 研究中明确表征的 14 名初治 AA 和 9 名健康儿童 (HC) 的队列中应用了 42 种抗体的大规模细胞计数组和无监督计算分析（表 S1，S2 图 S1A）。²整合来自 12 个谱系标记的信息，我们确定了外周血单核细胞 (PBMC) 内的 7 个主要 T 细胞和 NK 细胞群（图 S1B，C），其中 CD8 ⁺ T 细胞丰度降低，AA 与HC（图 1A、S1D、E）。

因此，AA 与 HC 中的 CD4/CD8 T 细胞比率升高，并与血嗜酸性粒细胞频率呈正相关，这是 AA 严重程度的决定因素，AA 中为³，但 HC 中没有（图 1B、C、S1F）。^{为了解决 CD4 +} T 细胞室内潜在的疾病相关变化，我们使用 FlowSOM 算法选择了 30 个标记用于随后的聚类。两个簇，CD4_c6 和 CD4_c30，在 AA 与 HC 中扩展（图 1D、E、S1G、H）。簇 CD4_c6 代表 Th2 细胞（图 1F），因为它表达 Th2 特异性 TF GATA3 和趋化因子受体 CRTH2 和 CCR4。⁴它独特地共同表达 TIGIT 和 ICOS，这在 AA 之前没有报道过，可能是儿童特有的，因为TIGIT仅在儿科 AA 中描述了低甲基化。⁵ 手动门控证实 AA 与 HC 相比，ICOS ⁺ TIGIT ⁺ Th2 细胞丰度更高（图 S2A-C）。该细胞群的特征还在于 CD161 表达，如针对仅限于特应性成人的 Th2 细胞所描述的，⁶从而支持其可能的促过敏性质。CD4_c6 簇的频率与伴有过敏性合并症的 AA 中的嗜酸性粒细胞增多以及具有间歇性疾病症状的哮喘患者的 CD4/CD8 T 细胞比率呈正相关，而在疾病稳定时则相反（图 1G，H），表明其与更多症状相关与 CD4/CD8 T 细胞比率和与嗜酸性粒细胞增多有关的过敏性合并症有关的疾病。

集群 CD4_c30 表达表征幼稚/静息 Treg 的标记（图 S2D）与先前描述的 CD45RA ⁺ FOXP3^低Treg 分数（Fr）-I, ⁷匹配，而效应器（e）Tregs 代表 Fr-II（CD45RA ^- FOXP3^高）和 Fr-III （CD45RA ^- FOXP3^低）（图 1I）。因此，Fr-I 的频率在 AA 与 HC 中富集，而 Fr-II 和 Fr-III 相似（图 S2E）。簇 CD4_c30 丰度与肺功能呈负相关，与记忆 CD8 ⁺ T 细胞频率显着相关（图 1J，S2F），表明其与肺功能和 CD8 ^{+部分相关}T细胞改变。Fr-I 与 Fr-II 的丰度呈负相关（图 1K），与线性发育模型一致，⁷表明从 Fr-I 向 Fr-II 的分化块，以及可能改变的 eTreg 隔室。

因此，我们接下来通过 FlowSOM 聚类分析了手动门控 eTregs（图 S1B），这揭示了 AA 中代表性不足的 eTreg_c2 和部分 eTreg_c10（图 2A，B，图 S2G）。考虑到可能的 eTregs 损伤和 TIGIT ⁺ ICOS ⁺ Th2 细胞 (CD4_c6) 的过度表达，我们询问这两种现象是否相关。事实上，AA 患儿的 CD4_c6/eTregs 比率往往高于 HC，但与 AA 和 HC 的嗜酸性粒细胞增多无关，因此 HC 与 AA 的嗜酸性粒细胞明显降低（图 2C、D，图 S2H）。相比之下，CD4_c6 与 eTreg_c2 和 eTreg_c10 的比率在 AA 中显着相关，但在 HC 中不相关，这表明 eTreg_c2 和 eTreg_c10 代表性不足与 TIGIT ⁺ ICOS ^{+之间存在特定关系}小儿 AA 中的 Th2 细胞 (CD4_c6) 相关嗜酸性粒细胞增多。因此，eTregs（eTreg_c2 和 eTreg_c10）和幼稚/静息 Tregs（CD4_c30）分别与 AA 的两种不同病理特征有关，即嗜酸性粒细胞增多和部分肺功能。

接下来，我们基于显着变化的比率和子集频率进行主成分分析 (PCA)，将 AA 与第一台 PC 的 HC 儿童分开，表明检测到的不平衡 T 细胞组成允许区分这两组（图 2E ）。此外，ROC 分析揭示了静息/幼稚 Tregs (CD4_c30)、eTreg_c2 和 eTreg_c10 与儿科 AA 表型（敏感性、真阳性率）的关系（图 2F），进一步支持 Treg 失衡与儿童 AA 相关。

总而言之，尽管没有多重测试调整的探索性特征，我们的研究确定了儿童 AA 的独特 T 细胞特征，并为失衡的 Treg、TIGIT ⁺ ICOS ⁺ Th2 和记忆 CD8 ⁺ T 细胞的病理生理学参与提供了见解。这可用于免疫监测、免疫调节和儿童 AA 的大型确证性研究。