Department of Immunology and Infectious Diseases, Australian National University, Canberra, ACT, Australia.
Centre for Personalised Immunology, John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia.
Front Immunol. 2019 Sep 11;10:2134. doi: 10.3389/fimmu.2019.02134. eCollection 2019.
Genetic primary immunodeficiency diseases are increasingly recognized, with pathogenic mutations changing the composition of circulating leukocyte subsets measured by flow cytometry (FCM). Discerning changes in multiple subpopulations is challenging, and subtle trends might be missed if traditional reference ranges derived from a control population are applied. We developed an algorithm where centiles were allocated using non-parametric comparison to controls, generating multiparameter heat maps to simultaneously represent all leukocyte subpopulations for inspection of trends within a cohort or segregation with a putative genetic mutation. To illustrate this method, we analyzed patients with Primary Antibody Deficiency (PAD) and kindreds harboring mutations in (encoding TACI), , and . In PAD, loss of switched memory B cells (B-SM) was readily demonstrated, but as a continuous, not dichotomous, variable. Expansion of CXCR5+/CD45RA- CD4+ T cells (X5-Th cells) was a prominent feature in PAD, particularly in TACI mutants, and patients with expansion in CD21-lo B cells or transitional B cells were readily apparent. We observed differences between unaffected and affected TACI mutants (increased B cells and CD8+ T-effector memory cells, loss of B-SM cells and non-classical monocytes), cellular signatures that distinguished haploinsufficiency itself (expansion of plasmablasts, activated CD4+ T cells, regulatory T cells, and X5-Th cells) from its clinical expression (B-cell depletion), and those that were associated with gain-of-function mutation (decreased CD8+ T effector memory cells, B cells, CD21-lo B cells, B-SM cells, and NK cells). Co-efficients of variation exceeded 30% for 36/54 FCM parameters, but by comparing inter-assay variation with disease-related variation, we ranked each parameter in terms of laboratory precision vs. disease variability, identifying X5-Th cells (and derivatives), naïve, activated, and central memory CD8+ T cells, transitional B cells, memory and SM-B cells, plasmablasts, activated CD4 cells, and total T cells as the 10 most useful cellular parameters. Applying these to cluster analysis of our PAD cohort, we could detect subgroups with the potential to reflect underlying genotypes. Heat mapping of normalized FCM data reveals cellular trends missed by standard reference ranges, identifies changes associating with a phenotype or genotype, and could inform hypotheses regarding pathogenesis of genetic immunodeficiency.
遗传原发性免疫缺陷病的认识日益增多,致病突变改变了流式细胞术(FCM)检测到的循环白细胞亚群的组成。如果应用来自对照人群的传统参考范围,则难以辨别多个亚群的变化,细微的趋势可能会被忽略。我们开发了一种算法,其中使用非参数比较对照来分配百分位数,生成多参数热图,同时表示所有白细胞亚群,以检查队列内的趋势或与假定遗传突变的分离。为了说明这种方法,我们分析了原发性抗体缺陷(PAD)患者和携带 (编码 TACI)、 、和 突变的家系。在 PAD 中,容易证明转换记忆 B 细胞(B-SM)的缺失,但作为一个连续的,而不是二分的变量。CXCR5+/CD45RA-CD4+T 细胞(X5-Th 细胞)的扩增是 PAD 的一个突出特征,特别是在 TACI 突变体中,并且在 CD21-lo B 细胞或过渡 B 细胞中具有扩增的患者很容易被发现。我们观察到未受影响和受影响的 TACI 突变体之间的差异(B 细胞和 CD8+T 效应记忆细胞增加,B-SM 细胞和非经典单核细胞减少),这些差异区分了单倍不足本身(浆母细胞、活化的 CD4+T 细胞、调节性 T 细胞和 X5-Th 细胞的扩增)与其临床表达(B 细胞耗竭),以及与 TACI 获得功能突变相关的差异(CD8+T 效应记忆细胞、B 细胞、CD21-lo B 细胞、B-SM 细胞和 NK 细胞减少)。54 个 FCM 参数中有 36 个的变异系数超过 30%,但通过比较测定内变异与疾病相关变异,我们根据实验室精度与疾病变异性对每个参数进行了排序,确定了 X5-Th 细胞(及其衍生物)、幼稚、活化和中央记忆 CD8+T 细胞、过渡 B 细胞、记忆和 SM-B 细胞、浆母细胞、活化的 CD4 细胞和总 T 细胞为 10 个最有用的细胞参数。将这些参数应用于我们的 PAD 队列的聚类分析,可以检测到具有潜在反映潜在基因型的亚组。标准化 FCM 数据的热图揭示了标准参考范围错过的细胞趋势,确定了与表型或基因型相关的变化,并可以为遗传免疫缺陷的发病机制提供信息。