ESPE Abstracts

Background: Beckwith Wiedemann syndrome (BWS) is an overgrowth disorder with vari-able phenotype (hemihypertrophy, macroglossia, visceromegaly, malformations, and hypo-glycaemia in 30–50%) and predisposition for tumors, during the second part of pregnancy and first few years of life.

Objective and hypotheses: Molecular characterisation of a patient with BWS was perfor-med to ensure adequate clinical management. This analysis revealed the most common form of BWS due to loss of methylation in KvDMR1 in presence of a normal H19-DMR methylation.

Method: We present a 4-month-old boy with overgrowth and longitudinal hemihypertrophy of tongue and left cheek delivered with Elective Section Cesarean (ELSC) due to fetal macrosomia. His birth weight was 4600 g (+3.0 SDS), 98.6th percentile and birth length 53 cm (+1.25 SDS), 90th percentile. The boy had 9.9 kg (+3.5 SDS) and height 68 cm (+2.3 SDS) at 4 months, both at 99th percentile. There was a difference of 1 cm circumference between his left and right leg, but not in their length or in arms. Diagnostic assessment was achieved according to clinical features, ultrasound survey, biochemical, and molecular analysis.

Results: Performed tongue, cardiac, abdominal, and renal ultrasound scans (USS) showed: longitudinal left hemihypertrophy of tongue tissue, round heart shape with mild aortal valve stenosis, mild hypertrophy of liver and moderate hypertrophy of kidnies, especially left one. A brain ultrasound was uneventful, but on MRI were prominent both frontoparietal subarachnoideals more than 5 mm. Karyotype was normal male, 46,XY. No evidence of clinical or biochemical parameters for hypoglycemia. Molecular analysis revealed hypomethylation of KvDRM1 (LIT1) in chromosome 11p15 region and normal methylation pattern for H19 with estimated tumor risk of 1–5%.

Conclusion: We present a patient with BWS phenotype associated with molecular confirmation of loss of function in specific gene in the imprinting cluster and low risk of embryonal tumors. The overall estimation will predict his clinical management.