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

Significant lethality following liver resection in A20 heterozygous knockout mice uncovers a key role for A20 in liver regeneration

Hepatic expression of A20, including in hepatocytes, increases in response to injury, inflammation and resection. This increase likely serves a hepatoprotective purpose. The characteristic unfettered liver inflammation and necrosis in A20 knockout mice established physiologic upregulation of A20 as integral to the anti-inflammatory and anti-apoptotic armamentarium of hepatocytes. However, the implication of physiologic upregulation of A20 in modulating hepatocytes' proliferative responses following liver resection remains controversial. To resolve the impact of A20 on hepatocyte proliferation and the liver's regenerative capacity, we examined whether decreased A20 expression, as in A20 heterozygous knockout mice, affects outcome following two-third partial hepatectomy. A20 heterozygous mice do not demonstrate a striking liver phenotype, indicating that their A20 expression levels are still sufficient to contain inflammation and cell death at baseline. However, usually benign partial hepatectomy provoked a staggering lethality (>40%) in these mice, uncovering an unsuspected phenotype. Heightened lethality in A20 heterozygous mice following partial hepatectomy resulted from impaired hepatocyte proliferation due to heightened levels of cyclin-dependent kinase inhibitor, p21, and deficient upregulation of cyclins D1, E and A, in the context of worsened liver steatosis. A20 heterozygous knockout minimally affected baseline liver transcriptome, mostly circadian rhythm genes. Nevertheless, this caused differential expression of >1000 genes post hepatectomy, hindering lipid metabolism, bile acid biosynthesis, insulin signaling and cell cycle, all critical cellular processes for liver regeneration. These results demonstrate that mere reduction of A20 levels causes worse outcome post hepatectomy than full knockout of bona fide liver pro-regenerative players such as IL-6, clearly ascertaining A20's primordial role in enabling liver regeneration. Clinical implications of these data are of utmost importance as they caution safety of extensive hepatectomy for donation or tumor in carriers of A20/TNFAIP3 single nucleotide polymorphisms alleles that decrease A20 expression or function, and prompt the development of A20-based liver pro-regenerative therapies