ScopeBody weight responds variably to the intake of dairy foods. Genetic variation may contribute to inter‐individual variability in associations between body weight and dairy consumption. Methods... Show moreScopeBody weight responds variably to the intake of dairy foods. Genetic variation may contribute to inter‐individual variability in associations between body weight and dairy consumption. Methods and resultsA genome‐wide interaction study to discover genetic variants that account for variation in BMI in the context of low‐fat, high‐fat and total dairy intake in cross‐sectional analysis was conducted. Data from nine discovery studies (up to 25 513 European descent individuals) were meta‐analyzed. Twenty‐six genetic variants reached the selected significance threshold (p‐interaction <10−7), and six independent variants (LINC01512‐rs7751666, PALM2/AKAP2‐rs914359, ACTA2‐rs1388, PPP1R12A‐rs7961195, LINC00333‐rs9635058, AC098847.1‐rs1791355) were evaluated meta‐analytically for replication of interaction in up to 17 675 individuals. Variant rs9635058 (128 kb 3’ of LINC00333) was replicated (p‐interaction = 0.004). In the discovery cohorts, rs9635058 interacted with dairy (p‐interaction = 7.36 × 10−8) such that each serving of low‐fat dairy was associated with 0.225 kg m−2 lower BMI per each additional copy of the effect allele (A). A second genetic variant (ACTA2‐rs1388) approached interaction replication significance for low‐fat dairy exposure. ConclusionBody weight responses to dairy intake may be modified by genotype, in that greater dairy intake may protect a genetic subgroup from higher body weight. Show less
Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have... Show moreMost common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits(1), but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait(2,3). The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P<0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways. Show less
