Narrowing critical regions and determining penetrance for selected 18q- phenotypes

Jannine D Cody1, Patricia L Heard, Analisa C Crandall

  • 1Department of Pediatrics, University of Texas Health Science Center at San Antonio, San Antonio, Texas 78229, USA. cody@uthscsa.edu

Insights

This study identifies critical genetic regions for 18q deletion phenotypes, aiding in predicting medical issues for affected children. Understanding these regions and their penetrance improves medical care for 18q- individuals.

Area of Science:

  • Genetics
  • Medical Genetics
  • Developmental Biology

Background:

  • 18q deletion syndrome presents complex medical challenges for affected children.
  • Accurate prediction of medical issues is crucial for optimizing care in 18q deletion cases.

Purpose of the Study:

  • To identify and narrow critical genetic regions associated with specific phenotypes in 18q deletion.
  • To determine the penetrance of these critical regions to enable genotype-based phenotype prediction.

Main Methods:

  • Oligo-array comparative genomic hybridization (CGH) and clinical assessments were performed on 151 individuals with 18q deletions.
  • Genotype-phenotype correlations were established to define or refine critical regions for key features.
  • Penetrance rates were calculated by comparing hemizygosity for critical regions with observed phenotypes.

Main Results:

  • Critical regions were identified within 18q22.3-q23 for kidney malformations, brain dysmyelination, growth hormone deficiency, and aural atresia.
  • The region for dysmyelination and growth hormone deficiency was narrowed to 1.62 Mb (5 genes); aural atresia to 2.3 Mb (3 additional genes); kidney malformations to 3.21 Mb (4 additional genes).
  • Penetrance rates were determined: kidney malformations (25%), dysmyelination (100%), growth hormone deficiency (90%), and aural atresia (78%).

Conclusions:

  • Identification of critical regions provides candidate genes for further study.
  • Penetrance data allows for the development of predictive phenotypic descriptions based on an individual's genotype.
  • This research enhances the ability to anticipate medical issues and optimize care for children with 18q deletions.