Endocrine Abstracts

Introduction: Short stature (SS), defined as height more than 2 standard deviation scores (SDS) below the mean, affects ~2% of UK children and accounts for ~50% of referrals to paediatric endocrine clinics. Over 80% of children with SS remain undiagnosed, resulting in repeated investigations, delayed management, and significant anxiety for families and clinicians. This highlights the urgent need for advanced genetic diagnostics to enable early diagnosis, personalised management, and improved clinical outcomes. Height is a highly heritable trait (80-90%). Recent trans-ancestry genome-wide association studies have identified over 12,000 common variants accounting for ~40% of height variance. SS may be due to a rare monogenic disorder or a high burden of common variants associated with short height. Current diagnostic strategies target monogenic causes but cannot distinguish these from polygenic ones. We hypothesised that a polygenic prediction model could help discriminate monogenic from polygenic SS and improve diagnostic pathways.

Methods: We analysed a sub-cohort (n = 161) from our Genetic Research Analysing Short Patients (GRASP) study, including monogenic diagnoses (n = 81), variants of uncertain significance (VUS) (n = 23), and undiagnosed (n = 57) individuals. SNP array genotyping was performed, and polygenic scores for height were calculated using >12,000 trans-ancestry GWAS variants. These scores were regressed against measured height SDS using simulated reference data (n = 10,000). Deviation from genetically predicted height was defined as a residual >2 and Mahalanobis P < 0.001.

Results: Eighty individuals deviated significantly from their polygenic height prediction suggesting a likely monogenic cause. Of these, 48 had confirmed monogenic diagnoses, 11 had putative monogenic causes (VUS), and 21 were undiagnosed. The greatest deviations were found in the most severe SS individuals with known pathogenic variants in GHR (Laron syndrome), CCDC8 (3M syndrome), and BLM (Bloom syndrome), supporting the model’s ability to discriminate ‘true’ monogenic SS.

Conclusion: Our approach may prioritise cases for advanced sequencing, reduce unnecessary investigation in polygenic cases, and support earlier, equitable precision care in SS. Genome-wide SNP testing is also cost-effective (£30-40 per patient) compared to ~£2,000 for comprehensive NHS genetic testing. Integration of polygenic scores into diagnostics represents a clinically actionable advancement in paediatric endocrine genomics and contribute to broader implementation in precision medicine.