Submicroscopic genomic alterations in Silver-Russell syndrome and Silver-Russell-like patients

Sara Bruce ^1*, Katariina Hannula-Jouppi ², Mari Puoskari ², Ingegerd Fransson ¹, Kalle OJ Simola ³, Marita Lipsanen-Nyman ⁴ and Juha Kere ¹

¹ Karolinska Institutet, Sweden
² University of Helsinki, Finland
³ Tampere University Hospital, Finland
⁴ The Hospital for Children and Adolescents, University of Helsinki, Finland

^* To whom correspondence should be addressed. E-mail: sara.bruce{at}ki.se.

Accepted 25 August 2009

Abstract

Background: Silver-Russell syndrome (SRS, OMIM# 180860) features fetal and postnatal growth restriction and variable dysmorphisms. Genetic and epigenetic aberrations on chromosomes 7 and 11 are commonly found in SRS. However, a large fraction of SRS remain with unknown genetic etiology.

Methods: We studied 22 patients diagnosed with SRS (ten with H19 hypomethylation and twelve of unknown molecular etiology) and their parents with the Affymetrix 250K Sty microarray. Several analytical approaches were used to identify genomic aberrations such as copy number changes (CNCs), loss of heterozygosity (LOH), and uniparental disomy (UPD). Selected CNCs were verified with quantitative real-time PCR.

Results: The largest unambiguous CNCs were found in previously molecularly unexplained SRS patients with relatively mild phenotypes: a heterozygous deletion of chromosome 15q26.3 including the IGF1R gene (2.6 Mb), an atypical, distal 22q11.2 deletion (1.1 Mb), and a pseudoautosomal region duplication (2.7 Mb) in a male patient. We also identified LOH regions of potential relevance to the SRS phenotype. Importantly, we did not identify any duplications or UPD of chromosomes 7 or 11.

Conclusion: In summary, we found unexpected submicroscopic genomic events with pathogenic potential in three molecularly unexplained patients with mild SRS. Our findings emphasize that SRS is heterogeneous in genetic etiology beyond the major groups of H19 hypomethylation and matUPD7 and that unbiased genome-scale screens may reveal novel genotype-phenotype correlations.