Warrington Nicole M, Howe Laura D, Paternoster Lavinia, Kaakinen Marika, Herrala Sauli, Huikari Ville, Wu Yan Yan, Kemp John P, Timpson Nicholas J, St Pourcain Beate, Davey Smith George, Tilling Kate, Jarvelin Marjo-Riitta, Pennell Craig E, Evans David M, Lawlor Debbie A, Briollais Laurent, Palmer Lyle J
School of Women's and Infants' Health, University of Western Australia, Perth, WA, Australia, University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, QLD, Australia, MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK, School of Social and Community Medicine, University of Bristol, Bristol, UK, Biocenter Oulu, and Institute of Health Sciences, University of Oulu, Oulu, Finland, Department of Genomics of Common Disease, School of Public Health, Imperial College London, London, UK, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada, Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland, Department of Epidemiology and Biostatistics, MRC-HPA Centre for Environment and Health, School of Public Health, Imperial College London, London, UK, Unit of Primary Care, Oulu University Hospital, Oulu, Finland and The Joanna Briggs Institute, The Robinson Research Institute, and School of Translational Health Science, University of Adelaide, Adelaide, SA, Australia School of Women's and Infants' Health, University of Western Australia, Perth, WA, Australia, University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, QLD, Australia, MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK, School of Social and Community Medicine, University of Bristol, Bristol, UK, Biocenter Oulu, and Institute of Health Sciences, University of Oulu, Oulu, Finland, Department of Genomics of Common Disease, School of Public Health, Imperial College London, London, UK, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada, Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland, Department of Epidemiology and Biostatistics, MRC-HPA Centre for Environment and Health, School of Public Health, Imperial College London, London, UK, Unit of Prim
School of Women's and Infants' Health, University of Western Australia, Perth, WA, Australia, University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, QLD, Australia, MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK, School of Social and Community Medicine, University of Bristol, Bristol, UK, Biocenter Oulu, and Institute of Health Sciences, University of Oulu, Oulu, Finland, Department of Genomics of Common Disease, School of Public Health, Imperial College London, London, UK, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON, Canada, Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland, Department of Epidemiology and Biostatistics, MRC-HPA Centre for Environment and Health, School of Public Health, Imperial College London, London, UK, Unit of Primary Care, Oulu University Hospital, Oulu, Finland and The Joanna Briggs Institute, The Robinson Research Institute, and School of Translational Health Science, University of Adelaide, Adelaide, SA, Australia.
Int J Epidemiol. 2015 Apr;44(2):700-12. doi: 10.1093/ije/dyv077. Epub 2015 May 7.
Several studies have investigated the effect of known adult body mass index (BMI) associated single nucleotide polymorphisms (SNPs) on BMI in childhood. There has been no genome-wide association study (GWAS) of BMI trajectories over childhood.
We conducted a GWAS meta-analysis of BMI trajectories from 1 to 17 years of age in 9377 children (77,967 measurements) from the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Western Australian Pregnancy Cohort (Raine) Study. Genome-wide significant loci were examined in a further 3918 individuals (48,530 measurements) from Northern Finland. Linear mixed effects models with smoothing splines were used in each cohort for longitudinal modelling of BMI.
A novel SNP, downstream from the FAM120AOS gene on chromosome 9, was detected in the meta-analysis of ALSPAC and Raine. This association was driven by a difference in BMI at 8 years (T allele of rs944990 increased BMI; PSNP = 1.52 × 10(-8)), with a modest association with change in BMI over time (PWald(Change) = 0.006). Three known adult BMI-associated loci (FTO, MC4R and ADCY3) and one childhood obesity locus (OLFM4) reached genome-wide significance (PWald < 1.13 × 10(-8)) with BMI at 8 years and/or change over time.
This GWAS of BMI trajectories over childhood identified a novel locus that warrants further investigation. We also observed genome-wide significance with previously established obesity loci, making the novel observation that these loci affected both the level and the rate of change in BMI. We have demonstrated that the use of repeated measures data can increase power to allow detection of genetic loci with smaller sample sizes.
多项研究调查了已知的与成人身体质量指数（BMI）相关的单核苷酸多态性（SNP）对儿童期BMI的影响。尚未有关于儿童期BMI轨迹的全基因组关联研究（GWAS）。
我们对来自阿冯父母与儿童纵向研究（ALSPAC）和西澳大利亚妊娠队列（Raine）研究的9377名儿童（77967次测量）从1岁到17岁的BMI轨迹进行了GWAS荟萃分析。在来自芬兰北部的另外3918名个体（48530次测量）中检查了全基因组显著位点。每个队列中使用带平滑样条的线性混合效应模型对BMI进行纵向建模。
在ALSPAC和Raine的荟萃分析中检测到一个位于9号染色体上FAM120AOS基因下游的新型SNP。这种关联是由8岁时BMI的差异驱动的（rs944990的T等位基因增加BMI；P SNP = 1.52×10⁻⁸），与BMI随时间的变化有适度关联（P Wald(变化) = 0.006）。三个已知的与成人BMI相关的位点（FTO、MC4R和ADCY3）以及一个儿童肥胖位点（OLFM4）在8岁时的BMI和/或随时间的变化达到了全基因组显著性（P Wald < 1.13×10⁻⁸）。
这项关于儿童期BMI轨迹的GWAS确定了一个值得进一步研究的新位点。我们还观察到与先前确定的肥胖位点具有全基因组显著性，从而有了这些位点影响BMI水平和变化率的新发现。我们已经证明，使用重复测量数据可以提高检测能力，从而能够在较小样本量的情况下检测到遗传位点。
