Endocrine Abstracts

Short stature (SS), defined as height ≤−2 SDS for a given population, comprises ~50% of new patient referrals to paediatric endocrine clinics. Since >80% SS children in the UK do not receive a clear diagnosis, enhanced genetic testing and stratification is a fundamental need. Whole-genome sequencing (WGS) was offered to rare disease patients recruited to the 100 000 Genomes Project (100KGP), leading to new clinical diagnoses in ~25% of participants. The 100KGP analysis pipeline uses disease-specific virtual gene panels, with focus on coding regions and canonical splice sites. Genes outside the panel, intronic variants impacting non-canonical splice sites and copy number variations (CNVs) remain uninvestigated. Our study aimed to identify molecular causes of SS in unsolved individuals recruited to the 100KGP. From 72 947 participants recruited to the rare disease cohort, 1996 SS probands were identified, of which 1602(80%) remained unsolved. WGS data from unsolved cases were interrogated to investigate coding/intronic variants affecting non-canonical splice sites in our wider gene panel, CNV and uniparental disomy (UPD). Burden analysis was used to investigate the effects of rare damaging coding variants on SS. In unsolved probands, 509 previously unreported coding (83 splice site, 41 frameshift, 35 stop gain, 350 missense) and 217 intronic predicted highly pathogenic variants were identified, respectively. This included a novel deep intronic variant in HMGA2 predicted to create a cryptic donor site and possible pseudoexon inclusion in a Silver–Russell Syndrome patient. CNV analysis identified variants predicted pathogenic at both previously established (1q21, 22q11.2) and novel regions. Burden analysis revealed statistically significant associations with genes implicated in growth. 100KGP has made a significant contribution to the healthcare community through its unprecedented scale of testing and depth of information it has generated. This study shows that WGS has clear advantages in its ability to simultaneously detect coding and deep intronic SNV, CNV and UPD, and its potential to improve diagnostic rate. This work is particularly relevant to those investigating endocrine diseases with heterogenous molecular origin. Application of WGS in a clinical setting could improve diagnosis/clinical care for patients/families and discovery of new candidate genes for targeted clinical treatments.