Molecular Diagnostic Algorithm of Syndromic Craniosynostosis


Karaman V., Toksoy G., Avcı Ş., Karaman B., Altunoğlu U., Başaran S., ...Daha Fazla

European Human Genetics. Conference 2014, Milan, İtalya, 31 Mayıs - 03 Haziran 2014, cilt.22, sa.1, ss.215

  • Yayın Türü: Bildiri / Özet Bildiri
  • Cilt numarası: 22
  • Basıldığı Şehir: Milan
  • Basıldığı Ülke: İtalya
  • Sayfa Sayıları: ss.215
  • İstanbul Üniversitesi Adresli: Evet

Özet

Craniosynostosis(CS) is a birth defect, with a prevalence of 1/2100-1/2500,

caused by the premature fusion of one or more cranial sutures leading to

speci􀏐ic cranial base and vault abnormalities. It is a highly heterogeneous

group of disorders occurring both in syndromic and non-syndromic forms,

associated with approximately 180 different syndromes. The identi􀏐ication

of the responsible gene largely depends on the fact if it is syndromic

or non-syndromic. Although 85% of the cases are reported to be non-syndromic

with unknown etiology, syndromic forms arise from chromosomal

anormalies or single gene defects of Mendelian inheritance, both together

comprising the etiopathogenesis only in 40% of the cases and single gene

defects contributing to three/fourth. Noteworthy genes in this group are

FGFR1, FGFR2, FGFR3, TWIST1, EFNB1, MSX2, RAB23 and FREM1. EFNB1

can be excluded from this group due to its association with Craniofrontonasal

Syndrome. Thirty syndromic CS patients with normal karyotype were

included in the study cohort. Stepwise screening algorithm was applied, initial

step being the sequencing of FGFR2, FGFR3 and FGFR1, followed by full

gene sequencing of FGFR2 and FGFR3. Samples with unidenti􀏐ied etiology

were further screened for deletion/duplication by craniofrontonasal MLPA

kit (P080). The last step consisted of sequencing of FGFR1, MSX2, TWIST1,

RAB23 and FREM1 genes, when the cases showed distinct related clinical

phenotype.

We highly suggest that our ongoing research will lead to better insight for

the clinical diagnosis, molecular diagnostic 􀏐low charts in CS and will contribute

to the genotype-phenotype correlation.