ESPE Abstracts

Background: The etiology of short stature is heterogeneous, often encompassing complex genetic disorders of difficult diagnosis. Analysis of chromosomic copy number variants (CNVs) has been demonstrating the important role of these genomic imbalances in population diversity and human disease.

Objective and hypotheses: To analyze the frequency and describe novel submicroscopic chromosomal CNVs in a group of patients with short stature of unknown cause.

Method: We evaluated new 49 patients with short stature associated to other physical or developmental defects (dysmorphic features and/or intellectual disability), but without criteria for the diagnosis of known syndromes. All patients had normal G-banded karyotyping. Array-based comparative genomic hybridization (aCGH) or single nucleotide polymorphism array (aSNP) were performed with DNA from all patients. Detected CNVs were compared with CNV data from healthy control individuals and common copy number polymorphisms were excluded.

Results: We found 11 CNVs and 2 uniparental disomies in 12/49 patients (24%). According to established criteria for assessment of CNV pathogenicity, at least 7 CNVs in 6 patients were considered pathogenic as well as one maternal uniparental disomy (14%). In 3 patients we found deletions affecting the IGF1R gene (including a child born appropriate for gestational age), 2 patients with deletions consistent with Miller-Dieker lissencephaly syndrome (deletion involving 17p13.3) and a maternal uniparental disomy of chromosome 14 (Temple syndrome). Another patient has an interstitial de novo duplication of 7p14.3p12.1 (31.828.208-53.625.890) involving 125 genes, including IGFBP3 and GRB10. Taking together all previously published results and the present one, the frequency of pathogenic CNVs in children with short stature of unknown etiology is 13% (95% CI:10–16%, n=498).

Conclusion: Pathogenic NVs were common in the selected patients, suggesting that CNVs might contribute as a genetic cause of short stature. Genome-wide copy number analysis should be used as a diagnostic tool for evaluation of short stature.