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◆ The Journal of Clinical Endocrinology & Metabolism2026-02-06· Medicine

Determinants of hyperinsulinism severity in children with Beckwith-Wiedemann syndrome

Andrew M. George, A. C. Viswanathan, Jonathan Sussman, Evan R. Hathaway, Abigail Casalnova, Salima Nesbitt, Kara E. Boodhansingh, Nicole Stewart, Heather McKnight, Katherine Lord, Diva D De León, Charles A. Stanley, N Scott Adzick, Arupa Ganguly, Jennifer M. Kalish

原始摘要(英文原文)· Original abstract
CONTEXT: Congenital hyperinsulinism (HI) is a serious clinical feature of Beckwith-Wiedemann syndrome (BWS) causing severe hypoglycemia. The relationship between BWS genotypes and HI severity is not well understood. OBJECTIVE: Investigate the relationship between molecular determinants of patients with BWS and HI with measures of HI severity. METHODS: This retrospective cohort study included 85 children from 2009-2024, all patients evaluated at single, tertiary care center. BWS genotype frequency included 41 children with pUPD11, 24 with IC2 LOM, 8 with 11p15 chromosomal anomalies, 6 with GWpUPD, 4 with IC1 GOM, and 2 with CDKN1C. Retrospectively reviewed interventions included maximum glucose infusion rate (max GIR), diazoxide responsiveness, and surgery. Primary outcome was association between BWS genotypes and measures of HI severity. Secondary outcomes included the relationship between pUPD11 length and presence of KATP variants with diazoxide responsiveness and surgical need. RESULTS: Significant differences presented among genotypes in max GIR (P = .004), enteral dextrose requirements (P = .029), and pancreatectomy (P = .012). Most patients with IC2 LOM, IC1 GOM or CDKN1C were diazoxide responsive and did not require surgery. Patients with pUPD11 were more likely to be diazoxide unresponsive and to require surgery, especially if pUPD11 length extended into the KATP gene region and if a pathogenic variant in the ABCC8 or KCNJ11 was present. CONCLUSION: Patients with pUPD11 experience more severe HI, while patients with IC2 LOM, IC1 GOM, and CDKN1C exhibit milder disease. Based on our findings, we designed a genetic testing algorithm to guide clinical management.
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