Biological, clinical and population relevance of 95 loci for blood lipids.

Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.

Common variants in mendelian kidney disease genes and their association with renal function.

Many common genetic variants identified by genome-wide association studies for complex traits map to genes previously linked to rare inherited Mendelian disorders. A systematic analysis of common single-nucleotide polymorphisms (SNPs) in genes responsible for Mendelian diseases with kidney phenotypes has not been performed. We thus developed a comprehensive database of genes for Mendelian kidney conditions and evaluated the association between common genetic variants within these genes and kidney function in the general population. Using the Online Mendelian Inheritance in Man database, we identified 731 unique disease entries related to specific renal search terms and confirmed a kidney phenotype in 218 of these entries, corresponding to mutations in 258 genes. We interrogated common SNPs (minor allele frequency >5%) within these genes for association with the estimated GFR in 74,354 European-ancestry participants from the CKDGen Consortium. However, the top four candidate SNPs (rs6433115 at LRP2, rs1050700 at TSC1, rs249942 at PALB2, and rs9827843 at ROBO2) did not achieve significance in a stage 2 meta-analysis performed in 56,246 additional independent individuals, indicating that these common SNPs are not associated with estimated GFR. The effect of less common or rare variants in these genes on kidney function in the general population and disease-specific cohorts requires further research.

Tejada et al. Reply

A Reply to the Comment by M. Hanson, C. Johansson, and S. Mørup.

Sauvon kirkon lehterinkaidemaalaukset vuodelta 1695 : Johannes Gezelius nuoremman kuvaohjelma

Zusammenfassung: Die Malereien am Geländer der Empore in der Kirche von Sauvo aus dem Jahre 1695 : das Bildprogramm Johannes Gezelius, des Jüngeren

Update of the BIPM comparison BIPM.RI(II)-K1.Ho-166m activity measurements to include the IRA and the NPL and a re-evaluation of the degrees of equivalence for the APMP.RI(II)-K2.Ho-166m comparison

The IRA and the NPL have submitted ampoules of 166Hom to the International Reference System (SIR) for activity comparison at the Bureau International des Poids et Mesures, thus becoming the third and fourth participants since 1989. The five samples of known activity of 166Hom now recorded in the SIR have activities between about 70 kBq and 500 kBq. The new results have enabled a re-evaluation of the key comparison reference value, and the degrees of equivalence between each equivalent activity measured in the SIR and the key comparison reference value (KCRV) have been calculated. The results are given in the form of a matrix for these four NMIs together with the recalculated degrees of equivalence of an APMP regional comparison held in 2000, comparison identifier APMP.RI(II)-K2.Ho-166m for six other NMIs. A graphical presentation is also given.

Hundreds of variants clustered in genomic loci and biological pathways affect human height.

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 identified more than 600 variants associated with human traits, 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. 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.