The role of neuromedin U in adiposity regulation. Haplotype analysis in European children from the IDEFICS Cohort

Background and aimsNeuromedin U (NMU) is a hypothalamic neuropeptide with important roles in several metabolic processes, recently suggested as potential therapeutic target for obesity. We analysed the associations between NMU gene variants and haplotypes and body mass index (BMI) in a large sample of European children.Methods and resultsFrom a large European multi-center study on childhood obesity, 4,528 children (2.0–9.9 years, mean age 6.0±1.8 SD; boys 52.2%) were randomly selected, stratifying by age, sex and country, and genotyped for tag single nucleotide polymorphisms (SNPs; rs6827359, T:C; rs12500837, T:C; rs9999653,C:T) of NMU gene, then haplotypes were inferred. Regression models were applied to estimate the associations between SNPs or haplotypes and BMI as well as other anthropometric measures. BMI was associated with all NMU SNPs (pz-score, beta = -0.08, 95%CI:-0.14,-0.01, p = 0.019) and decreased risk of overweight/obesity (OR = 0.81, 95%CI:0.68,0.97, p = 0.020) when compared to the most prevalent haplotype (codominant model). Similar significant associations were also observed using the same variables collected after two years’ time (BMI, beta = -0.25, 95%CI:-0.41,-0.08, p = 0.004; z-score, beta = -0.10, 95%CI:-0.18,-0.03, p = 0.009; overweight/obesity OR = 0.81, 95%CI:0.66,0.99, p = 0.036). The association was age-dependent in girls (interaction between CCT haplotypes and age, p = 0.008), more evident between 7 and 9 years of age. The CCT haplotype was consistently associated with lower levels of fat mass, skinfold thickness, hip and arm circumferences both at T0 and at T1, after adjustment for multiple testing (FDR-adjusted pConclusionsThis study shows an association between a NMU haplotype and anthropometric indices, mainly linked to fat mass, which appears to be age- and sex-specific in children. Genetic variations within or in linkage with this haplotype should be investigated to identify functional variants responsible for the observed phenotypic variation.