Therapies for Renal Ciliopathies

纤毛疾病是一大组罕见而严重的遗传性疾病，由初级纤毛功能障碍引起，初级纤毛是一种基于微管的细胞表面天线，控制着发育和组织内稳所需的关键信号输出。纤毛功能障碍导致复杂的疾病，具有高度的遗传异质性和重叠的表型。尽管临床范围很广，但慢性肾脏病(CKD)导致终末期肾病(ESKD)是纤毛疾病发病率的常见原因。目前，慢性肾脏病唯一可用的治疗标准是基于透析和移植。肾脏纤毛疾病是儿童ESKD的主要原因，尽管已确定了40多个致病基因，但仍难以预测疾病的严重程度以及出现的风险(如果在诊断时不存在)和肾衰竭的进展率。因此，RaCil的目标是：(1)改善高危儿童肾脏纤毛病患者的诊断和预后；(2)实施治疗方法，旨在针对共同的病理途径，通过反义寡核苷酸修饰致病基因或修饰基因的mRNA靶标，以及通过改变现有分子的用途。这些目标将通过我们在欧洲各地提供的独特的儿童肾脏纤毛病病例数据库的联合来实现，这将允许更好地对患者进行分层，识别疾病进展的修饰基因和标记。生物信息学方法将用于整合患者的生物和遗传数据，以及来自患者样本和临床前模型的多组学和功能分析。这些分析应该导致确定共同的靶向病理途径以及有资格接受已确定的新治疗方法的患者，这些新治疗方法将在强大的临床前模型中进行评估。

Ciliopathies are a large group of rare and severe genetic diseases caused by dysfunction of the primary cilium, a microtubule-based cell surface antenna that controls key signaling output required during development and tissue homeostasis. Cilium dysfunction leads to complex disorders with high genetic heterogeneity and overlapping phenotypes. Despite the broad clinical spectrum, chronic kidney disease (CKD) leading to end stage kidney disease (ESKD) is a common cause of morbidity across ciliopathies. Currently, the only available standard of care for CKD is based on dialysis and transplantation. Renal ciliopathies represent a main cause of ESKD during childhood and despite the identification of more than 40 causative genes, it remains difficult to predict the severity of the disease as well as the risk of appearance (if not present at diagnosis) and the rate of progression of renal failure. TheRaCil therefore aims: (1) to improve diagnosis and prognosis of at risk pediatric renal ciliopathy patients, and (2) to implement therapeutic approaches aimed at targeting shared pathological pathways, at modifying mRNA targets of the causative or modifier genes by antisense oligonucleotides and by the repurposing of available molecules. These goals will be achieved through the federation of our unique databases of pediatric renal ciliopathies cases available across Europe, which will allow a better stratification of patients, the identification of modifier genes and markers of disease progression. Bioinformatics approaches will be used to integrate patients’ biological and genetic data as well as multi-omics and functional analyses from patients samples and preclinical models. These analyses should lead to the identification of shared targetable pathological pathways as well as of patients eligible for the identified new therapeutic approaches which will be evaluated in robust preclinical models.