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Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
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Array-Based Comparative Genomic Hybridization Analysis in Children with Developmental Delay/Intellectual Disability.

A Türkyılmaz1, B B Geckinli2, E Tekin3

  • 1Department of Medical Genetics, Karadeniz Technical University Faculty of Medicine, Trabzon, Turkey.

Balkan Journal of Medical Genetics : BJMG
|October 17, 2022
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Summary

Array-based comparative genomic hybridization (aCGH) significantly improves the diagnosis rate for developmental delay (DD) and intellectual disability (ID). This genetic testing method identifies copy number variations (CNVs), aiding in genotype-phenotype correlation for these complex conditions.

Keywords:
Array-based comparative genomic hybridization (aCGH)Copy number variations (CNV)Developmental delayDysmorphic facial featuresGenotype-phenotype correlationIntellectual disability

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Area of Science:

  • Genetics
  • Developmental Biology
  • Medical Diagnostics

Background:

  • Developmental delay (DD) and intellectual disability (ID) are conditions affecting early childhood development, characterized by delayed milestones and impaired cognitive functions.
  • These conditions exhibit significant genetic heterogeneity, complicating diagnosis through conventional methods.
  • Array-based comparative genomic hybridization (aCGH) offers higher resolution for detecting genomic copy number variations (CNVs) compared to traditional cytogenetic techniques.

Purpose of the Study:

  • To evaluate the clinical utility of aCGH in diagnosing isolated and syndromic DD/ID cases.
  • To correlate identified genetic variations (CNVs) with observed clinical phenotypes.
  • To determine the diagnostic yield of aCGH as a first-tier test for DD/ID.

Main Methods:

  • Analysis of 139 pediatric cases (77 female, 62 male) diagnosed with DD/ID.
  • Application of aCGH to detect CNVs across the genome.
  • Clinical data collection for genotype-phenotype correlation.

Main Results:

  • aCGH identified 38 distinct CNVs in 35 cases.
  • Pathogenic CNVs were found in 13.6% of cases, and likely pathogenic CNVs in 3.5%, yielding an overall diagnostic rate of 17.1%.
  • The study detected rare microdeletion/microduplication syndromes, contributing to genotype-phenotype correlation data.

Conclusions:

  • aCGH is a highly effective first-tier diagnostic tool for DD/ID, significantly increasing diagnostic yields.
  • The identification of specific CNVs aids in understanding the genetic basis of DD/ID and refining genotype-phenotype correlations.
  • This approach facilitates the diagnosis of rare genetic syndromes, improving patient management and genetic counseling.