Novel Mutations and Genes That Impact on Growth in Short Stature of Undefined Aetiology: The EPIGROW Study

Abstract

Background: Children with short stature of undefined aetiology (SS-UA) may have undiagnosed genetic conditions.

Purpose: To identify mutations causing short stature (SS) and genes related to SS, using candidate gene sequence data from the European EPIGROW study.

Methods: First, we selected exonic single nucleotide polymorphisms (SNPs), in cases and not controls, with minor allele frequency (MAF) < 2%, whose carriage fitted the mode of inheritance. Known mutations were identified using Ensembl and gene-specific databases. Variants were classified as pathogenic, likely pathogenic, or variant of uncertain significance using criteria from the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. If predicted by ≥ 5/10 algorithms (eg, Polyphen2) to be deleterious, this was considered supporting evidence of pathogenicity. Second, gene-based burden testing determined the difference in SNP frequencies between cases and controls across all and then rare SNPs. For genotype/phenotype relationships, we used PLINK, based on haplotype, MAF > 2%, genotype present in > 75%, and Hardy Weinberg equilibrium P > 10^-4.

Results: First, a diagnostic yield of 10% (27/263) was generated by 2 pathogenic (nonsense in ACAN) and a further 25 likely pathogenic mutations, including previously known missense mutations in FANCB, IGFIR, MMP13, NPR2, OBSL1, and PTPN11. Second, genes related to SS: all methods identified PEX2. Another 7 genes (BUB1B, FANCM, CUL7, FANCA, PTCH1, TEAD3, BCAS3) were identified by both gene-based approaches and 6 (A2M, EFEMP1, PRKCH, SOS2, RNF135, ZBTB38) were identified by gene-based testing for all SNPs and PLINK.

Conclusions: Such panels improve diagnosis in SS-UA, extending known disease phenotypes. Fourteen genes related to SS included some known to cause growth disorders as well as novel targets.

Keywords: growth; idiopathic short stature; short stature; short stature mutations; short stature of undefined aetiology; short stature syndrome.

Figure 1.

Overlaps between both gene-wide analyses and with genes containing variants associated with growth characteristics/IGF status. Results from both gene-based burden testing approaches are shown here, with overlap A illustrating genes that were identified by both methods. Orange boxes indicate genes where SNP frequency was greater in SS-UA cases and blue boxes represents genes where SNP frequency was lower in SS-UA cases compared with controls. Genes involved in an overlap are shown in bold. On the right, results of the PLINK analyses, linking specific variants to particular growth characteristics/biochemical measures of IGF status are shown. A P-value of ≤ 0.001 was considered significant. Overlap B highlights those genes that were identified by this method, as well as by one (all SNPs or rare SNPs alone) or both SNP burden testing approaches.