There is increasing evidence that genome-wide association (GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study (using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined approximately 2,000 individuals for each of 7 major diseases and a shared set of approximately 3,000 controls. Case-control comparisons identified 24 independent association signals at

Circulating glucose levels are tightly regulated. To identify novel glycemic loci, we performed meta-analyses of 21 genome-wide associations studies informative for fasting glucose (FG), fasting insulin (FI) and indices of β-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 non-diabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with FG/HOMA-B and two associated with FI/HOMA-IR. These include nine new FG loci (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and FAM148B) and one influencing FI/HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB/TMEM195 with type 2 diabetes (T2D). Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify T2D risk loci, as well as loci that elevate FG modestly, but do not cause overt diabetes.

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.

To identify genetic variants influencing plasma lipid concentrations, we first used genotype imputation and meta-analysis to combine three genome-wide scans totaling 8,816 individuals and comprising 6,068 individuals specific to our study (1,874 individuals from the FUSION study of type 2 diabetes and 4,184 individuals from the SardiNIA study of aging-associated variables) and 2,758 individuals from the Diabetes Genetics Initiative, reported in a companion study in this issue. We subsequently examined promising signals in 11,569 additional individuals. Overall, we identify strongly associated variants in eleven loci previously implicated in lipid metabolism (ABCA1, the APOA5-APOA4-APOC3-APOA1 and APOE-APOC clusters, APOB, CETP, GCKR, LDLR, LPL, LIPC, LIPG and PCSK9) and also in several newly identified loci (near MVK-MMAB and GALNT2, with variants primarily associated with high-density lipoprotein (HDL) cholesterol; near SORT1, with variants primarily associated with low-density lipoprotein (LDL) cholesterol; near TRIB1, MLXIPL and ANGPTL3, with variants primarily associated with triglycerides; and a locus encompassing several genes near NCAN, with variants strongly associated with both triglycerides and LDL cholesterol). Notably, the 11 independent variants associated with increased LDL cholesterol concentrations in our study also showed increased frequency in a sample of coronary artery disease cases versus controls.

Asthma is caused by a combination of poorly understood genetic and environmental factors. We have systematically mapped the effects of single nucleotide polymorphisms (SNPs) on the presence of childhood onset asthma by genome-wide association. We characterized more than 317,000 SNPs in DNA from 994 patients with childhood onset asthma and 1,243 non-asthmatics, using family and case-referent panels. Here we show multiple markers on chromosome 17q21 to be strongly and reproducibly associated with childhood onset asthma in family and case-referent panels with a combined P value of P < 10(-12). In independent replication studies the 17q21 locus showed strong association with diagnosis of childhood asthma in 2,320 subjects from a cohort of German children (P = 0.0003) and in 3,301 subjects from the British 1958 Birth Cohort (P = 0.0005). We systematically evaluated the relationships between markers of the 17q21 locus and transcript levels of genes in Epstein-Barr virus (EBV)-transformed lymphoblastoid cell lines from children in the asthma family panel used in our association study. The SNPs associated with childhood asthma were consistently and strongly associated (P < 10(-22)) in cis with transcript levels of ORMDL3, a member of a gene family that encodes transmembrane proteins anchored in the endoplasmic reticulum. The results indicate that genetic variants regulating ORMDL3 expression are determinants of susceptibility to childhood asthma.

Blood low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol and triglyceride levels are risk factors for cardiovascular disease. To dissect the polygenic basis of these traits, we conducted genome-wide association screens in 19,840 individuals and replication in up to 20,623 individuals. We identified 30 distinct loci associated with lipoprotein concentrations (each with P < 5 × 10-8), including 11 loci that reached genome-wide significance for the first time. The 11 newly defined loci include common variants associated with LDL cholesterol near ABCG8, MAFB, HNF1A and TIMD4; with HDL cholesterol near ANGPTL4, FADS1-FADS2-FADS3, HNF4A, LCAT, PLTP and TTC39B; and with triglycerides near AMAC1L2, FADS1-FADS2-FADS3 and PLTP. The proportion of individuals exceeding clinical cut points for high LDL cholesterol, low HDL cholesterol and high triglycerides varied according to an allelic dosage score (P < 10-15 for each trend). These results suggest that the cumulative effect of multiple common variants contributes to polygenic dyslipidemia.

Psoriasis is a common immune mediated disorder that affects the skin, nails, and joints. To identify psoriasis susceptibility loci, we genotyped 438,670 SNPs in 1,409 European ancestry psoriasis cases and 1,436 controls. Twenty-one promising SNPs were followed-up in 5,048 psoriasis cases and 5,041 controls. Our results provide strong support for the association of at least seven genetic loci and psoriasis (each with p < 5×10−8 overall). Loci with confirmed association encode HLA-C, three genes involved in IL-23 signaling (IL23A, IL23R, IL12B), two genes that act downstream of TNF-α and regulate NF-κB signaling (TNIP1, TNFAIP3), and two genes involved in the modulation of Th2 immune responses (IL4, IL13). Although the proteins encoded in these loci are known to interact biologically, we found no evidence for epistasis between associated SNPs. Our results expand the catalog of genetic loci implicated in psoriasis susceptibility and suggest priority targets for study in other auto-immune disorders.

The increasing number of DNA polymorphisms characterized in humans will soon allow the construction of fine genetic maps of human chromosomes. This advance calls for a reexamination of current methodologies for linkage analysis by the family method. We Just as molecular hybridization has given a new power to methods for physical assignments (1), the new wealth of DNA polymorphisms (2, 3) will elicit the development of new strategies for linkage analysis by family methods. When only about 30 genetic markers were available at arbitrary locations, affording a very partial coverage of the human genome, a natural approach for the detection of linkage between a disease locus and a battery of markers consisted in the pairwise analysis of the disease phenotype and each marker in turn. Two-locus linkage analysis by the now classical method of lod-scores (4) or related techniques was originally restricted to simple Mendelian traits and nuclear families; later it was extended to complex phenotypes and general pedigrees through the development of appropriate algorithms and computer programs (5-7).More than 200 DNA polymorphisms have been defined in recent years (8), and there is no doubt that the number required to span the human genome (2, 9) will be reached soon.This inevitably raises questions regarding the relative merits of two-point and multipoint linkage analysis. Although the advantages of multipoint tests, as opposed to pairwise tests, seems generally intuitive (10), a systematic investigation is necessary before new approaches can be proposed.Need for a multilocus analysis is evident for the calculation of genetic risks when several linked markers are available; otherwise there would be no general way of combining pedigree calculations involving each marker singly. For detection of linkage, estimation of recombination, and construction of genetic maps, the merit of multipoint tests has yet to be established. Although Meyers et al. (11) considered three-point tests in restricted situations, most procedures for estimation of recombination and genetic mapping in humans have been based on the assumption that results from independent two-point linkage tests are combined (12)(13)(14).The determination of a genetic map from results of linkage analyses requires assumptions about the mathematical relationships between map distance, expressed in units of crossing-over, or morgans, and recombination frequency, thus defining a mapping function. This relation is complex because recombination results from an odd number of points of exchange between loci, and evidence points to their nonindependence-i.e., interference in crossing-over (15). Various mapping functions have been proposed embodying specific assumptions regarding interference (15). Statistical methods have been proposed that assume a mapping function or a specific process of chiasma formation (12)(13)(14) or that infer a genetic map solely from the rank-order constraints implied by pairwise recombination estimates (16).As the genetic map is developed, it is...