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Chromosomal Microarray Analysis in 466 Patients With Autism Spectrum Disorder: Diagnostic Yield and Clinical Correlates

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  • a-CGH diagnostic yield was 4.7% (22/466), marginally below the reported 5.4%–14% range.
  • a-CGH positivity was significantly higher in females (p = 0.029) and in individuals with growth disorders (p = 0.003); no link with epilepsy or intellectual disability.
  • a-CGH detects clinically significant CNVs even in isolated ASD, supporting its use beyond syndromic cases and revealing established and candidate risk loci.
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Am J Med Genet B Neuropsychiatr Genet. 2026 Nov 5. doi: 10.1002/ajmg.b.70043. Online ahead of print.

ABSTRACT

Autism spectrum disorder (ASD) has a strong genetic component. Chromosomal microarray analysis is recommended as a first-tier genetic test for individuals with ASD, with a reported diagnostic yield of 5.4%-14%. We performed a-CGH analysis in ASD patients to evaluate diagnostic yield and genotype-phenotype correlations. Clinical features were collected and analyzed to assess associations with pathogenic/likely pathogenic (P/LP) CNVs. Segregation analysis was performed when feasible. A total of 466 patients were included (22.1% female; age range 3-59 years). Twenty-two patients (4.7%) carried at least one P/LP CNV, 129 (27.7%) had a variant of uncertain significance (VUS), and 315 (67.6%) tested negative. No significant associations were observed between a positive a-CGH result and age, family history, autism severity, perinatal distress, epilepsy, intellectual disability, congenital malformations, micro-/macrocephaly, or facial dysmorphisms. In contrast, positivity was significantly higher in females (p = 0.029) and in individuals with growth disorders (p = 0.003). a-CGH showed a diagnostic yield of 4.7%, slightly below the lower range reported in the literature. Clinically significant CNVs were also identified in individuals with isolated ASD, supporting the use of a-CGH beyond syndromic presentations. Overall, a-CGH analysis in ASD plays a dual role: identifying established risk loci and uncovering emerging candidate genes.

PMID:42988749 | DOI:10.1002/ajmg.b.70043

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