Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence phenotype. Genome-wide association (GWA) studies have identified >600 variants associated with human traits1, but these typically explain small fractions of phenotypic variation, raising questions about the utility 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 trait2,3. 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 amongst variants that alter amino acid structure of proteins and expression levels of nearby genes. Our data explain ∼10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to ∼16% of phenotypic variation (∼20% of heritable variation). Although additional approaches are needed to fully dissect the genetic architecture of polygenic human traits, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.
Oxidation of lipoproteins is important for the initiation and propagation of the atherosclerotic lesion and may involve secondary oxidants derived from nitric oxide. Nitric oxide (NO) reacts at near diffusion limited rates with superoxide (O2-.) to form the strong oxidant, peroxynitrite (ONOO-). Nitration on the ortho position of tyrosine is a major product of peroxynitrite attack on proteins. Nitrotyrosine was detected in atherosclerotic lesions of formalin-fixed human coronary arteries with polyclonal and monoclonal antibodies. Binding was pronounced in and around foamy macrophages within the atheroma deposits. Nitration was also observed in early subintimal fatty streaks. Antibody binding was completely blocked by co-incubation with 10mM nitrotyrosine, but not by equivalent concentrations of aminotyrosine or phosphotyrosine. The presence of nitrotyrosine indicates that oxidants derived from nitric oxide such as peroxynitrite are generated in human atherosclerosis and may be involved in its pathogenesis.
Elevated serum uric acid levels cause gout and are a risk factor for cardiovascular disease and diabetes. To investigate the polygenetic basis of serum uric acid levels, we conducted a meta-analysis of genome-wide association scans from 14 studies totalling 28,141 participants of European descent, resulting in identification of 954 SNPs distributed across nine loci that exceeded the threshold of genome-wide significance, five of which are novel. Overall, the common variants associated with serum uric acid levels fall in the following nine regions: SLC2A9 (p = 5.2×10−201), ABCG2 (p = 3.1×10−26), SLC17A1 (p = 3.0×10−14), SLC22A11 (p = 6.7×10−14), SLC22A12 (p = 2.0×10−9), SLC16A9 (p = 1.1×10−8), GCKR (p = 1.4×10−9), LRRC16A (p = 8.5×10−9), and near PDZK1 (p = 2.7×10−9). Identified variants were analyzed for gender differences. We found that the minor allele for rs734553 in SLC2A9 has greater influence in lowering uric acid levels in women and the minor allele of rs2231142 in ABCG2 elevates uric acid levels more strongly in men compared to women. To further characterize the identified variants, we analyzed their association with a panel of metabolites. rs12356193 within SLC16A9 was associated with DL-carnitine (p = 4.0×10−26) and propionyl-L-carnitine (p = 5.0×10−8) concentrations, which in turn were associated with serum UA levels (p = 1.4×10−57 and p = 8.1×10−54, respectively), forming a triangle between SNP, metabolites, and UA levels. Taken together, these associations highlight additional pathways that are important in the regulation of serum uric acid levels and point toward novel potential targets for pharmacological intervention to prevent or treat hyperuricemia. In addition, these findings strongly support the hypothesis that transport proteins are key in regulating serum uric acid levels.
Adult height is a model polygenic trait, but there has been limited success in identifying the genes underlying its normal variation. To identify genetic variants influencing adult human height, we used genome-wide association data from 13,665 individuals and genotyped 39 variants in an additional 16,482 samples. We identified 20 variants associated with adult height (P < 5 x 10(-7), with 10 reaching P < 1 x 10(-10)). Combined, the 20 SNPs explain approximately 3% of height variation, with a approximately 5 cm difference between the 6.2% of people with 17 or fewer 'tall' alleles compared to the 5.5% with 27 or more 'tall' alleles. The loci we identified implicate genes in Hedgehog signaling (IHH, HHIP, PTCH1), extracellular matrix (EFEMP1, ADAMTSL3, ACAN) and cancer (CDK6, HMGA2, DLEU7) pathways, and provide new insights into human growth and developmental processes. Finally, our results provide insights into the genetic architecture of a classic quantitative trait.
The human genome is thought to harbor 50,000 to 100,000 genes, of which about half have been sampled to date in the form of expressed sequence tags. An international consortium was organized to develop and map gene-based sequence tagged site markers on a set of two radiation hybrid panels and a yeast artificial chromosome library. More than 16,000 human genes have been mapped relative to a framework map that contains about 1000 polymorphic genetic markers. The gene map unifies the existing genetic and physical maps with the nucleotide and protein sequence databases in a fashion that should speed the discovery of genes underlying inherited human disease. The integrated resource is available through a site on the World Wide Web at http://www.ncbi.nlm.nih.gov/SCIENCE96/.
Both underweight and obesity have been associated with increased mortality1,2. Underweight, defined as body mass index (BMI) ≤ 18,5 kg/m2 in adults 3 and ≤ −2 standard deviations (SD) in children4,5, is the main sign of a series of heterogeneous clinical conditions such as failure to thrive (FTT) 6–8, feeding and eating disorder and/or anorexia nervosa9,10. In contrast to obesity, few genetic variants underlying these clinical conditions have been reported 11, 12. We previously demonstrated that hemizygosity of a ~600 kb region on the short arm of chromosome 16 (chr16:29.5–30.1Mb), causes a highly-penetrant form of obesity often associated with hyperphagia and intellectual disabilities13. Here we show that the corresponding reciprocal duplication is associated with underweight. We identified 138 (132 novel cases) duplication carriers (108 unrelated carriers) from over 95,000 individuals clinically-referred for developmental or intellectual disabilities (DD/ID), psychiatric disorders or recruited from population-based cohorts. These carriers show significantly reduced postnatal weight (mean Z-score −0.6; p=4.4×10−4) and BMI (mean Z-score −0.5; p=2.0×10−3). In particular, half of the boys younger than 5 years are underweight with a probable diagnosis of FTT, while adult duplication carriers have an 8.7-fold (p=5.9×10−11; CI_95=[4.5–16.6]) increased risk of being clinically underweight. We observe a significant trend towards increased severity in males, as well as a depletion of male carriers among non-medically ascertained cases. These features are associated with an unusually high frequency of selective and restrictive feeding behaviours and a significant reduction in head circumference (mean Z-score −0.9; p=7.8×10−6). Each of the observed phenotypes is the converse of one reported in carriers of deletions at this locus, correlating with changes in transcript levels for genes mapping within the duplication but not within flanking regions. The reciprocal impact of these 16p11.2 copy number variants suggests that severe obesity and being underweight can have mirror etiologies, possibly through contrasting effects on eating behaviour.
Mutations in glucokinase are the primary cause of hyperglycemia in a substantial fraction of French patients with maturity-onset diabetes of the young and result in a relatively mild form of NIDDM that can be diagnosed in childhood.
Scavenger receptor BI (SR-BI) is the major receptor for high-density lipoprotein (HDL) cholesterol (HDL-C). In humans, high amounts of HDL-C in plasma are associated with a lower risk of coronary heart disease (CHD). Mice that have depleted Scarb1 (SR-BI knockout mice) have markedly elevated HDL-C levels but, paradoxically, increased atherosclerosis. The impact of SR-BI on HDL metabolism and CHD risk in humans remains unclear. Through targeted sequencing of coding regions of lipid-modifying genes in 328 individuals with extremely high plasma HDL-C levels, we identified a homozygote for a loss-of-function variant, in which leucine replaces proline 376 (P376L), in SCARB1, the gene encoding SR-BI. The P376L variant impairs posttranslational processing of SR-BI and abrogates selective HDL cholesterol uptake in transfected cells, in hepatocyte-like cells derived from induced pluripotent stem cells from the homozygous subject, and in mice. Large population-based studies revealed that subjects who are heterozygous carriers of the P376L variant have significantly increased levels of plasma HDL-C. P376L carriers have a profound HDL-related phenotype and an increased risk of CHD (odds ratio = 1.79, which is statistically significant).
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