A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes(1). Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel(2)) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants

A saturated map of common genetic variants associated with human height.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries

Gender Differences in the Expression and Cellular Localization of Lipin 1 in the Hearts of Fructose-Fed Rats

To give new insight to alterations of cardiac lipid metabolism accompanied by a fructose-rich diet (FRD), rats of both sexes were exposed to 10 % fructose in drinking water during 9 weeks. The protein level and subcellular localization of the main regulators of cardiac lipid metabolism, such as lipin 1, peroxisome proliferator-activated receptor alpha (PPAR alpha), peroxisome proliferator-activated receptor gamma coactivator-1 alpha (PGC-1 alpha), carnitine palmitoyltransferase I (CPTI), and CD36 were studied. Caloric intake in fructose-fed rats (FFR) of both sexes was increased. Circulating triacylglyceroles (TAG) and non-esterified fatty acids were increased in male FFR, while females increased visceral adiposity and blood TAG. Total expression of lipin 1 in cardiac cell lysate and its cytosolic and microsomal level were increased in the hearts of male FFR. PPAR alpha and PGC-1 alpha content were decreased in the nuclear extract. In addition, cardiac deposition of TAG in male FFR was elevated, as well as inhibitory phosphorylation of insulin receptor substrate 1 (IRS-1). In contrast, in female FFR, lipin 1 level was increased in nuclear extract only, while overall CPTI expression and phosphorylation of IRS-1 at serine 307 were decreased. The results of our study suggest that fructose diet causes gender-dependent alterations in cardiac lipid metabolism. Potentially detrimental effects of FRD seem to be limited to male rats. Most of the observed changes might be a consequence of elevated expression and altered localization of lipin 1. Increased inhibitory phosphorylation of IRS-1 is possible link between cardiac lipid metabolism and insulin resistance in FFR