LAUSR

Ciliopathies are rare congenital disorders, caused by defects in the cilium, that cover a broad clinical spectrum. A subgroup of ciliopathies showing significant phenotypic overlap are known as skeletal ciliopathies and include Jeune asphyxiating thoracic dysplasia (JATD), Mainzer-Saldino syndrome (MZSDS), cranioectodermal dysplasia (CED), and short-rib polydactyly (SRP). Ciliopathies are heterogeneous disorders with >187 associated genes, of which some genes are described to cause more than one ciliopathy phenotype. Both the clinical and molecular overlap make accurate diagnosing of these disorders challenging. We describe two unrelated Polish patients presenting with a skeletal ciliopathy who share the same compound heterozygous variants in IFT140 (NM_014,714.4) r.2765_2768del; p.(Tyr923Leufs*28) and exon 27–30 duplication; p.(Tyr1152_Thr1394dup). Apart from overlapping clinical symptoms the patients also show phenotypic differences; patient 1 showed more resemblance to a Mainzer-Saldino syndrome (MZSDS) phenotype, while patient 2 was more similar to the phenotype of cranioectodermal dysplasia (CED). In addition, functional testing in patient-derived fibroblasts revealed a distinct cilium phenotyps for each patient, and strikingly, the cilium phenotype of CED-like patient 2 resembled that of known CED patients. Besides two variants in IFT140, in depth exome analysis of ciliopathy associated genes revealed a likely-pathogenic heterozygous variant in INTU for patient 2 that possibly affects the same IFT-A complex to which IFT140 belongs and thereby could add to the phenotype of patient 2. Taken together, by combining genetic data, functional test results, and clinical findings we were able to accurately diagnose patient 1 with “IFT140-related ciliopathy with MZSDS-like features” and patient 2 with “IFT140-related ciliopathy with CED-like features”. This study emphasizes that identical variants in one ciliopathy associated gene can lead to a variable ciliopathy phenotype and that an in depth and integrated analysis of clinical, molecular and functional data is necessary to accurately diagnose ciliopathy patients.