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Genotype-Phenotype correlations in Joubert Syndrome in the Era of Next Generation Sequencing
© Bachmann-Gagescu et al. 2015
Published: 13 July 2015
To provide extensive genotype-phenotype correlations for Joubert syndrome (JS), a ciliopathy characterized by a distinctive hindbrain malformation ("the molar tooth sign"), ataxia and cognitive dysfunction.
Phenotypic data was collected from the University of Washington JS cohort and all known JS genes were sequenced in 429 individuals (364 families) using the MIPS capture technique and next-generation sequencing.
Core JS diagnostic features (hypotonia, ataxia, cognitive dysfunction, oculo-motor apraxia) were present in >80% of individuals, while abnormal breathing pattern was reported in 60%. Frequently associated features included retinal dystrophy (31.4%), renal disease (20.9%), coloboma (17.7%), polydactyly (15.3%), liver fibrosis (15.2%) and encephalocele (8%). Liver fibrosis and coloboma were strongly associated with each other (Odds Ratio 7.0, 95% Confidence Interval = 3.0-13.2), while retinal dystrophy and renal disease were weakly associated (O.R. 2.2, 95%C.I. = 1.7-5.6). Additional clinical features included other brain abnormalities (n = 73), seizures (n = 49), cleft palate (n = 16), hearing loss (n = 14) and psychiatric problems (n = 45). The genetic cause was identified in 60% of families, with 5 genes accounting for the majority of patients (C5ORF42, CEP290, CC2D2A, AHI1, TMEM67). Bi-allelic causal mutations in B9D2 and C2CD3 were identified in 2 families each. Bi-allelic mutations in 2 different genes were identified in 4 families and heterozygous mutations (in addition to the causal mutation) were present in 62 individuals. Significant (p<0.0001) genotype-phenotype correlations were observed: CEP290 with renal disease and retinal dystrophy; TMEM67 with liver fibrosis and coloboma.
This study provides a comprehensive description of the phenotypic spectrum, genetic makeup and genotype-phenotype correlations of a large JS cohort.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.