Literature DB >> 27625836

Risk assessment models in genetics clinic for array comparative genomic hybridization: Clinical information can be used to predict the likelihood of an abnormal result in patients.

Rachel M Marano1, Laura Mercurio1, Rebecca Kanter2, Richard Doyle3, Dianne Abuelo1, Eric M Morrow4, Natasha Shur2.   

Abstract

Array comparative genomic hybridization (aCGH) testing can diagnose chromosomal microdeletions and duplications too small to be detected by conventional cytogenetic techniques. We need to consider which patients are more likely to receive a diagnosis from aCGH testing versus patients that have lower likelihood and may benefit from broader genome wide scanning. We retrospectively reviewed charts of a population of 200 patients, 117 boys and 83 girls, who underwent aCGH testing in Genetics Clinic at Rhode Island hospital between 1 January/2008 and 31 December 2010. Data collected included sex, age at initial clinical presentation, aCGH result, history of seizures, autism, dysmorphic features, global developmental delay/intellectual disability, hypotonia and failure to thrive. aCGH analysis revealed abnormal results in 34 (17%) and variants of unknown significance in 24 (12%). Patients with three or more clinical diagnoses had a 25.0% incidence of abnormal aCGH findings, while patients with two or fewer clinical diagnoses had a 12.5% incidence of abnormal aCGH findings. Currently, we provide families with a range of 10-30% of a diagnosis with aCGH testing. With increased clinical complexity, patients have an increased probability of having an abnormal aCGH result. With this, we can provide individualized risk estimates for each patient.

Entities:  

Keywords:  aCGH testing; genetic diagnosis; genetic testing; medical management; micro-array

Year:  2013        PMID: 27625836      PMCID: PMC5020955          DOI: 10.3233/PGE-13044

Source DB:  PubMed          Journal:  J Pediatr Genet        ISSN: 2146-460X


  1 in total

1.  Identification of Developmental and Behavioral Markers Associated With Genetic Abnormalities in Autism Spectrum Disorder.

Authors:  Somer L Bishop; Cristan Farmer; Vanessa Bal; Elise B Robinson; A Jeremy Willsey; Donna M Werling; Karoline Alexandra Havdahl; Stephan J Sanders; Audrey Thurm
Journal:  Am J Psychiatry       Date:  2017-03-03       Impact factor: 18.112

  1 in total

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