New findings for phenotype–genotype correlations in a large European series of holoprosencephaly cases. Issue 11 (22nd September 2011)

• Record Type: Journal Article
• Authors: Mercier, Sandra; Dubourg, Christèle; Garcelon, Nicolas; Campillo-Gimenez, Boris; Gicquel, Isabelle; Belleguic, Marion; Ratié, Leslie; Pasquier, Laurent; Loget, Philippe; Bendavid, Claude; Jaillard, Sylvie; Rochard, Lucie; Quélin, Chloé; Dupé, Valérie; David, Véronique; Odent, Sylvie
• Is Part Of: Journal of medical genetics. Volume 48:Issue 11(2011)
• Page Start: 752
• Page End: 760
• Publication Date: 2011-09-22
• Subjects: Genetics -- cytogenetics -- molecular genetics -- genetic screening/counselling -- clinical genetics -- developmental -- diagnosis -- guidelines; Medical genetics -- Periodicals; 616.042
• DOI: 10.1136/jmedgenet-2011-100339
• Languages: English
• ISSNs: 1468-6244

Abstract

Abstract : Background: Holoprosencephaly (HPE) is the most common forebrain defect in humans. It results from incomplete midline cleavage of the prosencephalon. Methods: A large European series of 645 HPE probands (and 699 relatives), consisting of 51% fetuses and 49% liveborn children, is reported. Results: Mutations in the four main genes involved in HPE ( SHH, ZIC2, SIX3, TGIF ) were identified in 25% of cases. The SHH, SIX3, and TGIF mutations were inherited in more than 70% of these cases, whereas 70% of the mutations in ZIC2 occurred de novo . Moreover, rearrangements were detected in 22% of the 260 patients screened by array comparative genomic hybridisation. 15 probands had two mutations providing additional support for the 'multiple-hit process' in HPE. There was a positive correlation between the severity of the brain malformation and facial features for SHH, SIX3, and TGIF, but no such correlation was found for ZIC2 mutations. The most severe HPE types were associated with SIX3 and ZIC2 mutations, whereas microforms were associated with SHH mutations. The study focused on the associated brain malformations, including neuronal migration defects, which predominated in individuals with ZIC2 mutations, and neural tube defects, which were frequently associated with ZIC2 (rachischisis) and TGIF mutations. Extracraniofacial features were observed in 27% of the individuals in this series (up to 40% of those with ZIC2 mutations) and a significant correlation was found between renal/urinary defects and mutations of SHH and ZIC2 . Conclusions: An algorithm is proposed based on these new phenotype–genotype correlations, to facilitate molecular analysis and genetic counselling for HPE.