ESPE Abstracts

Background: Genetic factors play an important role in determining individual susceptibility to weight gain and obesity. In the last few years, several genetic variants have been identified as causative of monogenic/syndromic forms of obesity, mainly involved in the hypothalamic leptin-melanocortin pathways (LMP) that regulates food intake and energy homeostasis.

Methods: Pediatric patients (<18 years) with severe obesity (BMI ≥ 97°centile) underwent NGS genetic test (including 79 genes and 16p11.2 chromosomal region, known to be associated with obesity). Anamnestic, anthropometric, and biochemical data were collected for each patient. Patients’ parents also completed Hyperphagia Questionnaire (HQ) ed Epworth Sleepiness Scale (ESS) to investigate hunger and daytime sleepiness, respectively.

Results: The study included 50 patients (age 9,3 ± 4.26 SDS, Male 52%, BMI SDS 3.5 ± 0.92) of which 22 (44%) tested positive for genetic variants classified as pathogenic/likely pathogenic (n = 9, 18%) or uncertain VUS (n = 13, 26%). These gene variants predominantly related to LMP (LEPR n = 2, PCSK1 n = 3, MC4R n = 2, NRP2 n = 1, SEMA3F n = 1, SIM1 n = 1, POMC n = 1), or to syndromic obesity (IFT74, CEP290, BBS9 for Bardet-Biedl syndrome, VPS13B Cohen syndrome, RAI1 Smith-Magenis syndrome, DNMT3A Tatton-Brown-Rahman syndrome, EP300 and CREBBP Rubinstein-Taybi syndrome, ALMS1 Alström syndrome). These 22 patients showed BMI SDS 3.4 ± 0.99, cognitive impairment (n = 2), endocrinopathy (n = 1). None had dysmorphic features and all but 2 patients with pathogenic mutations developed obesity before the age of 5. Familial history of obesity was present in 59% of these cases, similarly to the whole cohort. When comparing patients with different patterns of genetic mutations (none, pathogenic, VUS), we found statistically significant differences in age (P = 0,0379), BMI (P = 0,0033), HbA1c (P = 0,0095) and triglycerides/HDL ratio (P = 0,0235). Mean HQ total score was higher in patients with pathogenic/VUS mutations than the whole cohort (24 ± 4,08 vs 21,62 ± 7,07), whereas no ESS showed pathological results. We explored the development of a “Genetic Obesity Risk Score” from logistic regression analysis by selecting HQ total score, age of obesity onset, and familiarity as variables, with low accuracy (AUC 0,6844) of final model, probably due to small sample size.

Conclusions: Genetic screening of our cohort of obese children revealed pathogenic variants in 18% of cases, with PCSK1 being the most frequently mutated gene. Identifying clinical, behavioral and metabolic features predictive of genetic obesity would improve early diagnosis and tailored treatment and management.