ESPE2022 Poster Category 1 Fat, Metabolism and Obesity (73 abstracts)
1Department of Pediatrics and Pediatric Endocrinology, Faculty of Medical Sciences, Medical University of Silesia, Katowice, Poland; 2Biobank Lab, Department of Molecular Biophysics, Faculty of Biology and Environmental Protection, University of Lodz, Lodz, Poland; 3Bioinformatics Knowledge Unit, Lorry I. Lokey Interdisciplinary Center for Life Sciences and Engineering, Technion-Israel Institute of Technology, Haifa, Israel; 4Division of Pediatric Endocrinology, Marmara University, School of Medicine, Istanbul, Turkey; 5Department of Human Pathology of Adulthood and Childhood University of MessinaDepartment of Human Pathology of Adulthood and Childhood University of Messina, Messina, Italy; 6Division of Pediatric Endocrinology, Marmara University, School of Medicine, Istanbul, Poland; 7Steroid Research and Mass Spectrometry Unit, Division of Pediatric Endocrinology and Diabetology, Center of Child and Adolescent Medicine, Justus Liebig University, Giessen, Germany; 8Faculty of Medicine, Technion- Israel Institute of Technology, Haifa, Israel
Context: The response to lifestyle modification (LSM) in children with obesity is variable and difficult to predict.
Aim: A systematic search for identifying common single nucleotide polymorphisms (SNPs) to predict positive outcomes of LSM in pediatric obesity management, defined as decrease in BMI z-score (based on IOTF).
Patients/Methods: Out of 240 children with obesity (BMI>97%) recruited to a prospective ‘multi-OMICS’ study granted by ESPE Research Unit, 159 subjects (age 8-17 yrs, median 12.8 yrs; 45% females) finished twelve-months (V12) of LSM obesity management at three centers in Poland, Turkey and Italy. A genome wide association study was performed with Infinium Global Screenig Aarray+MultiDisease Early ACC Kit (Illumina). The filtered genotyping data was exported to gds format in R. Subsequently, kinship was estimated by means of the KING robust method via the snpgdsIBDKING function in package SNPRelate. The genetic relatedness matrix was used to estimate the principal components via the PCAiR method in package GENESIS. In what follows, the linear mixed model with one dependent variable (delta BMI z-score) and two independent variables: age and sex was used to estimate the fixed effects (via the function fitNullModel in package GENESIS). The random effect was associated with the individual participant of the study and the correlation matrix between random effects was set as the genetic relatedness matrix. The effect of individual SNPS was estimated by means of the Score test with the aid of the assocTestSingle function in package GENESIS.
The results: for SNP with MAF>0.05 and with Score P-value<1*10-5 were reported. The obtained result emerged one SNP rs10425933 (chr 19, 9010208) with genome-wide significant threshold, which was associated with reduction in BMI z-score (P<1.63*10-8). With suggestive significance, we observed SNPs which were also associated with BMI z-score reduction in tested group of children: rs76751343 (chr 5, 166326168, P=2.95*10-6); rs60674472 (AP001122.1, P=4.50*10-6); rs339065 (FAM71F1, P=6.39*10-6); rs78233922 (chr 17, 55738405, P=6.49*10-6); rs75642418 (C16orf95, P=9.86*10-6).
Conclusion: Our findings suggests that weight reduction as response to LSM in childhood obesity may be modified by common genetic variants. We identified a novel loci presumably associated with the change in BMI z scores but it should be further investigated.