Studies in animal models and in cultured cells have shown that fatty acids can induce alterations in the DNA methylation of specific genes. There have been no studies of the effects of fatty acid supp Show more
Studies in animal models and in cultured cells have shown that fatty acids can induce alterations in the DNA methylation of specific genes. There have been no studies of the effects of fatty acid supplementation on the epigenetic regulation of genes in adult humans. We investigated the effect of supplementing renal patients with 4 g daily of either n-3 long-chain polyunsaturated fatty acids (n-3 LCPUFA) or olive oil (OO) for 8 weeks on the methylation status of individual CpG loci in the 5' regulatory region of genes involved in PUFA biosynthesis in peripheral blood mononuclear cells from men and women (aged 53 to 63 years). OO and n-3 LCPUFA each altered (>10% difference in methylation) 2/22 fatty acid desaturase (FADS)-2 CpGs, while n-3 LCPUFA, but not OO, altered (>10%) 1/12 ELOVL5 CpGs in men. OO altered (>6%) 8/22 FADS2 CpGs and (>3%) 3/12 elongase (ELOVL)-5 CpGs, while n-3 LCPUFA altered (>5%) 3/22 FADS2 CpGs and 2/12 (>3%) ELOVL5 CpGs in women. FADS1 or ELOVL2 methylation was unchanged. The n-3 PUFA supplementation findings were replicated in blood DNA from healthy adults (aged 23 to 30 years). The methylation status of the altered CpGs in FADS2 and ELOVL5 was associated negatively with the level of their transcripts. These findings show that modest fatty acid supplementation can induce altered methylation of specific CpG loci in adult humans, contingent on the nature of the supplement and on sex. This has implications for understanding the effect of fatty acids on PUFA metabolism and cell function. Show less
The timing of associations between common genetic variants and changes in growth patterns over childhood may provide insight into the development of obesity in later life. To address this question, it Show more
The timing of associations between common genetic variants and changes in growth patterns over childhood may provide insight into the development of obesity in later life. To address this question, it is important to define appropriate statistical models to allow for the detection of genetic effects influencing longitudinal childhood growth. Children from The Western Australian Pregnancy Cohort (Raine; n=1,506) Study were genotyped at 17 genetic loci shown to be associated with childhood obesity (FTO, MC4R, TMEM18, GNPDA2, KCTD15, NEGR1, BDNF, ETV5, SEC16B, LYPLAL1, TFAP2B, MTCH2, BCDIN3D, NRXN3, SH2B1, MRSA) and an obesity-risk-allele-score was calculated as the total number of 'risk alleles' possessed by each individual. To determine the statistical method that fits these data and has the ability to detect genetic differences in BMI growth profile, four methods were investigated: linear mixed effects model, linear mixed effects model with skew-t random errors, semi-parametric linear mixed models and a non-linear mixed effects model. Of the four methods, the semi-parametric linear mixed model method was the most efficient for modelling childhood growth to detect modest genetic effects in this cohort. Using this method, three of the 17 loci were significantly associated with BMI intercept or trajectory in females and four in males. Additionally, the obesity-risk-allele score was associated with increased average BMI (female: β=0.0049, P=0.0181; male: β=0.0071, P=0.0001) and rate of growth (female: β=0.0012, P=0.0006; male: β=0.0008, P=0.0068) throughout childhood. Using statistical models appropriate to detect genetic variants, variations in adult obesity genes were associated with childhood growth. There were also differences between males and females. This study provides evidence of genetic effects that may identify individuals early in life that are more likely to rapidly increase their BMI through childhood, which provides some insight into the biology of childhood growth. Show less