Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands.
Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.
Eur J Hum Genet. 2021 Nov;29(11):1677-1689. doi: 10.1038/s41431-021-00907-9. Epub 2021 May 27.
Skeletal ciliopathies are a group of disorders caused by dysfunction of the cilium, a small signaling organelle present on nearly every vertebrate cell. This group of disorders is marked by genetic and clinical heterogeneity, which complicates accurate diagnosis. In this study, we developed a robust, standardized immunofluorescence approach to accurately diagnose a subset of these disorders. Hereto we determined and compared the cilium phenotype of healthy individuals to patients from three different ciliopathy subgroups, using skin-derived fibroblasts. The cilium phenotype assay consists of three parameters; (1) ciliogenesis, based on the presence or absence of cilium markers, (2) cilium length, measured by the combined signal of an axonemal and a cilium membrane marker, and (3) retrograde intraflagellar transport (IFT), quantified by the area of the ciliary tip. Analysis of the cilium phenotypic data yielded comparable and reproducible results and in addition, displayed identifiable clusters for healthy individuals and two ciliopathy subgroups, i.e. ATD and CED. Our results illustrate that standardized analysis of the cilium phenotype can be used to discriminate between ciliopathy subgroups. Therefore, we believe that standardization of functional assays analyzing cilium phenotypic data can provide additional proof for conclusive diagnosis of ciliopathies, which is essential for routine diagnostic care.
骨骼纤毛病是一组由纤毛功能障碍引起的疾病,纤毛是一种存在于几乎所有脊椎动物细胞上的小型信号细胞器。该疾病组的特点是遗传和临床异质性,这增加了准确诊断的难度。在这项研究中,我们开发了一种强大的、标准化的免疫荧光方法,以准确诊断其中的一部分疾病。为此,我们使用皮肤衍生的成纤维细胞,确定并比较了健康个体与来自三个不同纤毛病亚组的患者的纤毛表型。纤毛表型检测包括三个参数;(1)纤毛发生,基于纤毛标记物的存在与否,(2)纤毛长度,通过轴丝和纤毛膜标记物的联合信号测量,和 (3)逆行纤毛内运输 (IFT),通过纤毛尖端的面积定量。对纤毛表型数据的分析产生了可比且可重复的结果,并且还显示了健康个体和两个纤毛病亚组(即 ATD 和 CED)的可识别聚类。我们的结果表明,标准化的纤毛表型分析可用于区分纤毛病亚组。因此,我们认为,分析纤毛表型数据的功能检测的标准化可以为纤毛病的明确诊断提供额外的证据,这对于常规诊断护理至关重要。