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Effects of Perilipin (PLIN) Gene Variation on Metabolic Syndrome Risk and Weight Loss in Obese Children and Adolescents

Laboratory of Human Nutrition and Metabolic Disease (S.D., C.Y.N., I.G., A.H., S.M.V.), Laboratório de Investigação Médica 25, Faculdade de Medicina da Universidade de São Paulo (FMUSP), and Children Obesity’s Outpatient Clinic, Hospital das Clínicas of the University of São Paulo Medical School, University of São Paulo Medical School, São Paulo, Brazil CEP 01246-903; Reina Sofia University Hospital (P.P.-M.), Lipids and Atherosclerosis Research Unit, University of Cordoba,CIBER Fisiopatologia de la Obesidad y Nutricion (CIBEROBN), 14071 Cordoba, Spain; Endocrine Service and Heart Institute of the Hospital das Clinicas FMUSP (B.L.W.), 05403-000 São Paulo, Brazil; and Nutrition and Genomics Laboratory (J.M.O.), Jean Mayer U.S. Department of Agriculture Human Nutrition Research Center on Aging at Tufts University, Boston, Massachusetts 02111

Address all correspondence and requests for reprints to: Sophie Deram, Laboratory of Human Nutrition and Metabolic Disease—LIM-25 of HC-FMUSP, Avenida Doutor Arnaldo, 455, Room 4305, São Paulo-SP, Brazil, CEP 01246-903. E-mail: sophiederam{at}usp.br.

Context: Genetic polymorphisms at the perilipin (PLIN) locus have been investigated for their potential utility as markers for obesity and metabolic syndrome (MS). We examined in obese children and adolescents (OCA) aged 7–14 yr the association of single-nucleotide polymorphisms (SNP) at the PLIN locus with anthropometric, metabolic traits, and weight loss after 20-wk multidisciplinary behavioral and nutritional treatment without medication.

Design: A total of 234 OCA [body mass index (BMI = 30.4 ± 4.4 kg/m²; BMI Z-score = 2.31 ± 0.4) were evaluated at baseline and after intervention. We genotyped four SNPs (PLIN1 6209TC, PLIN4 11482GA, PLIN5 13041AG, and PLIN6 14995AT).

Results: Allele frequencies were similar to other populations, PLIN1 and PLIN4 were in linkage disequilibrium (D' = 0.999; P < 0.001). At baseline, no anthropometric differences were observed, but minor allele A at PLIN4 was associated with higher triglycerides (111 ± 49 vs. 94 ± 42 mg/dl; P = 0.003), lower high-density lipoprotein cholesterol (40 ± 9 vs. 44 ± 10 mg/dl; P = 0.003) and higher homeostasis model assessment for insulin resistance (4.0 ± 2.3 vs. 3.5 ± 2.1; P = 0.015). Minor allele A at PLIN4 was associated with MS risk (age and sex adjusted) hazard ratio 2.4 (95% confidence interval = 1.1–4.9) for genotype GA and 3.5 (95% confidence interval = 1.2–9.9) for AA. After intervention, subjects carrying minor allele T at PLIN6 had increased weight loss (3.3 ± 3.7 vs. 1.9 ± 3.4 kg; P = 0.002) and increased loss of the BMI Z-score (0.23 ± 0.18 vs. 0.18 ± 0.15; P = 0.003). Due to group size, risk of by-chance findings cannot be excluded.

Conclusion: The minor A allele at PLIN4 was associated with higher risk of MS at baseline, whereas the PLIN6 SNP was associated with better weight loss, suggesting that these polymorphisms may predict outcome strategies based on multidisciplinary treatment for OCA.