Background

Using the genome-wide association approach in individuals of European ancestry, we and others recently identified single nucleotide polymorphisms (SNPs) at 19 loci as associated with blood lipids; eight of these loci were novel. Whether these same SNPs associate with lipids in a broader range of ethnicities is unknown.

Methods and Results

We genotyped index SNPs at 19 loci in the Third United States National Health and Nutrition Examination Survey (n=7159), a population-based probability sample of the U.S. comprised primarily of non-Hispanic blacks, Mexican Americans, and non-Hispanic whites. We constructed ethnic-specific residual blood lipid levels after adjusting for age and gender. Ethnic-specific linear regression was used to test the association of genotype with blood lipids. To summarize the statistical evidence across three racial groups, we conducted a fixed-effects variance-weighted meta-analysis.

After exclusions, there were 1627 non-Hispanic blacks, 1659 Mexican Americans, and 2230 non-Hispanic whites. At five loci (1p13 near CELSR2/PSRC1/SORT1, HMGCR, CETP, LPL, and APOA5), the index SNP was associated with low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, or triglycerides in all three ethnic groups. At the remaining loci, there was mixed evidence by ethnic group. In meta-analysis, we found that, at 14 of the 19 loci, SNPs exceeded a nominal P < 0.05.

Conclusions

At five loci including the recently-discovered region on 1p13 near CELSR2/PSRC1/SORT1, the same SNP discovered in whites associates with blood lipids in non-Hispanic blacks and Mexican Americans. For the remaining loci, fine-mapping and resequencing will be required to definitively evaluate the relevance of each locus in individuals of African and Hispanic ancestries.

We examined the association of common variants at the NPPA-NPPB locus with circulating concentrations of the natriuretic peptides, which have blood pressure–lowering properties. We genotyped SNPs at the NPPA-NPPB locus in 14,743 individuals of European ancestry, and identified associations of plasma atrial natriuretic peptide with rs5068 (P = 8 × 10−70), rs198358 (P = 8 × 10−30) and rs632793 (P = 2 × 10−10), and of plasma B-type natriuretic peptide with rs5068 (P = 3 × 10−12), rs198358 (P = 1 × 10−25) and rs632793 (P = 2 × 10−68). In 29,717 individuals, the alleles of rs5068 and rs198358 that showed association with increased circulating natriuretic peptide concentrations were also found to be associated with lower systolic (P = 2 × 10−6 and 6 × 10−5, respectively) and diastolic blood pressure (P = 1 × 10−6 and 5 × 10−5), as well as reduced odds of hypertension (OR = 0.85, 95% CI = 0.79–0.92, P = 4 × 10−5; OR = 0.90, 95% CI = 0.85–0.95, P = 2 × 10−4, respectively). Common genetic variants at the NPPA-NPPB locus found to be associated with circulating natriuretic peptide concentrations contribute to interindividual variation in blood pressure and hypertension.

Abstract Three founder mutations in BRCA1 and BRCA2 contribute to the risk of hereditary breast and ovarian cancer in Ashkenazi Jews (AJ). They are observed at increased frequency in the AJ compared to other BRCA mutations in Caucasian non-Jews (CNJ). Several authors have proposed that elevated allele frequencies in the surrounding genomic regions reflect adaptive or balancing selection. Such proposals predict long-range linkage dis-equilibrium (LD) resulting from a selective sweep, although genetic drift in a founder population may also act to create long-distance LD. To date, few studies have used the tools of statistical genomics to examine the likelihood of long-range LD at a deleterious locus in a population that faced a genetic bottleneck. We studied the genotypes of hundreds of women from a large international consortium of BRCA1 and BRCA2 mutation carriers and found that AJ women exhibited long-range haplotypes compared to CNJ women. More than 50% of the AJ chromosomes with the BRCA1 185delAG mutation share an identical 2.1 Mb haplotype and nearly 16% of AJ chromosomes carrying the BRCA2 6174delT mutation share a 1.4 Mb haplotype. Simulations based on the best inference of Ashkenazi population demography indicate that long-range haplotypes are expected in the context of a genome-wide survey. Our results are consistent with the hypothesis that a local bottleneck effect from population size constriction events could by chance have resulted in the large haplotype blocks observed at high frequency in the BRCA1 and BRCA2 regions of Ashkenazi Jews.

Genome-wide genotyping of a cohort using pools rather than individual samples has long been proposed as a cost-saving alternative for performing genome-wide association (GWA) studies. However, successful disease gene mapping using pooled genotyping has thus far been limited to detecting common variants with large effect sizes, which tend not to exist for many complex common diseases or traits. Therefore, for DNA pooling to be a viable strategy for conducting GWA studies, it is important to determine whether commonly used genome-wide SNP array platforms such as the Affymetrix 6.0 array can reliably detect common variants of small effect sizes using pooled DNA. Taking obesity and age at menarche as examples of human complex traits, we assessed the feasibility of genome-wide genotyping of pooled DNA as a single-stage design for phenotype association. By individually genotyping the top associations identified by pooling, we obtained a 14- to 16-fold enrichment of SNPs nominally associated with the phenotype, but we likely missed the top true associations. In addition, we assessed whether genotyping pooled DNA can serve as an inexpensive screen as the second stage of a multi-stage design with a large number of samples by comparing the most cost-effective 3-stage designs with 80% power to detect common variants with genotypic relative risk of 1.1, with and without pooling. Given the current state of the specific technology we employed and the associated genotyping costs, we showed through simulation that a design involving pooling would be 1.07 times more expensive than a design without pooling. Thus, while a significant amount of information exists within the data from pooled DNA, our analysis does not support genotyping pooled DNA as a means to efficiently identify common variants contributing small effects to phenotypes of interest. While our conclusions were based on the specific technology and study design we employed, the approach presented here will be useful for evaluating the utility of other or future genome-wide genotyping platforms in pooled DNA studies.

Head and neck squamous cell carcinoma (HNSCC) is a common, morbid, and frequently lethal malignancy. To uncover its mutational spectrum, we analyzed whole-exome sequencing data from 74 tumor-normal pairs. The majority exhibited a mutational profile consistent with tobacco exposure; human papilloma virus was detectable by sequencing of DNA from infected tumors. In addition to identifying previously known HNSCC genes (TP53, CDKN2A, PTEN, PIK3CA, and HRAS), the analysis revealed many genes not previously implicated in this malignancy. At least 30% of cases harbored mutations in genes that regulate squamous differentiation (e.g., NOTCH1, IRF6, and TP63), implicating its dysregulation as a major driver of HNSCC carcinogenesis. More generally, the results indicate the ability of large-scale sequencing to reveal fundamental tumorigenic mechanisms.

Genome-wide association studies have identified 32 loci associated with body mass index (BMI), a measure that does not allow distinguishing lean from fat mass. To identify adiposity loci, we meta-analyzed associations between ~2.5 million SNPs and body fat percentage from 36,626 individuals, and followed up the 14 most significant (P<10−6) independent loci in 39,576 individuals. We confirmed the previously established adiposity locus in FTO (P=3×10−26), and identified two new loci associated with body fat percentage, one near IRS1 (P=4×10−11) and one near SPRY2 (P=3×10−8). Both loci harbour genes with a potential link to adipocyte physiology, of which the locus near IRS1 shows an intriguing association pattern. The body-fat-decreasing allele associates with decreased IRS1 expression and with an impaired metabolic profile, including decreased subcutaneous-to-visceral fat ratio, increased insulin resistance, dyslipidemia, risk of diabetes and coronary artery disease, and decreased adiponectin levels. Our findings provide new insights into adiposity and insulin resistance.

Infectious and inflammatory diseases have repeatedly shown strong genetic associations within the major histocompatibility complex (MHC); however, the basis for these associations remains elusive. To define host genetic effects on the outcome of a chronic viral infection, we performed genome-wide association analysis in a multiethnic cohort of HIV-1 controllers and progressors, and we analyzed the effects of individual amino acids within the classical human leukocyte antigen (HLA) proteins. We identified >300 genome-wide significant single-nucleotide polymorphisms (SNPs) within the MHC and none elsewhere. Specific amino acids in the HLA-B peptide binding groove, as well as an independent HLA-C effect, explain the SNP associations and reconcile both protective and risk HLA alleles. These results implicate the nature of the HLA–viral peptide interaction as the major factor modulating durable control of HIV infection.

Background

Genome-wide association studies in cohorts of European descent have identified novel genomic regions as associated with lipids, but their relevance in African Americans remains unclear.

Methods and Results

We genotyped 8 index SNPs and 488 tagging SNPs across 8 novel lipid loci in the Jackson Heart Study, a community-based cohort of 4605 African Americans. For each trait, we calculated residuals adjusted for age, sex, and global ancestry and performed multivariable linear regression to detect genotype-phenotype association with adjustment for local ancestry. To explore admixture effects, we conducted stratified analyses in individuals with a high probability of 2 African ancestral alleles or at least 1 European allele at each locus. We confirmed 2 index SNPs as associated with lipid traits in African Americans, with suggestive association for 3 more. However, the effect sizes for 4 of the 5 associated SNPs were larger in the European local ancestry subgroup compared to the African local ancestry subgroup, suggesting that the replication is driven by European ancestry segments. Through fine-mapping, we discovered 3 new SNPs with significant associations, two with consistent effect on triglyceride levels across ancestral groups: rs636523 near DOCK7/ANGPTL3 and rs780093 in GCKR. African LD patterns did not assist in narrowing association signals.

Conclusions

We confirm that 5 genetic regions associated with lipid traits in European-derived populations are relevant in African Americans. To further evaluate these loci, fine-mapping in larger African American cohorts and/or resequencing will be required.

To discover novel RA risk loci, we systematically examined 370 SNPs from 179 independent loci with p<0.001 in a published meta-analysis of RA GWAS of 3,393 cases and 12,462 controls1. We used GRAIL2, a computational method that applies statistical text mining to PubMed abstracts, to score these 179 loci for functional relationships to genes in 16 established RA disease loci1,3-11. We identified 22 loci with a significant degree of functional connectivity. We genotyped 22 representative SNPs in an independent set of 7,957 cases and 11,958 matched controls. Three validate convincingly: CD2/CD58 (rs11586238, p=1×10−6 replication, p=1×10−9 overall), and CD28 (rs1980422, p=5×10−6 replication, p=1×10−9 overall), PRDM1 (rs548234, p=1×10−5 replication, p=2×10−8 overall). An additional four replicate (p<0.0023): TAGAP (rs394581, p=0.0002 replication, p=4×10−7 overall), PTPRC (rs10919563, p=0.0003 replication, p=7×10−7 overall), TRAF6/RAG1 (rs540386, p=0.0008 replication, p=4×10−6 overall), and FCGR2A (rs12746613, p=0.0022 replication, p=2×10−5 overall). Many of these loci are also associated to other immunologic diseases.

Genome-wide association (GWA) studies have identified common variants that are associated with a variety of traits and diseases, but most studies have been performed in European-derived populations. Here, we describe the first genome-wide analyses of imputed genotype and copy number variants (CNVs) for anthropometric measures in African-derived populations: 1188 Nigerians from Igbo-Ora and Ibadan, Nigeria, and 743 African-Americans from Maywood, IL. To improve the reach of our study, we used imputation to estimate genotypes at ∼2.1 million single-nucleotide polymorphisms (SNPs) and also tested CNVs for association. No SNPs or common CNVs reached a genome-wide significance level for association with height or body mass index (BMI), and the best signals from a meta-analysis of the two cohorts did not replicate in ∼3700 African-Americans and Jamaicans. However, several loci previously confirmed in European populations showed evidence of replication in our GWA panel of African-derived populations, including variants near IHH and DLEU7 for height and MC4R for BMI. Analysis of global burden of rare CNVs suggested that lean individuals possess greater total burden of CNVs, but this finding was not supported in an independent European population. Our results suggest that there are not multiple loci with strong effects on anthropometric traits in African-derived populations and that sample sizes comparable to those needed in European GWA studies will be required to identify replicable associations. Meta-analysis of this data set with additional studies in African-ancestry populations will be helpful to improve power to detect novel associations.

SUMMARY

We sequenced all protein-coding regions of the genome (the “exome”) in two family members with combined hypolipidemia, marked by extremely low plasma levels of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, and triglycerides. These two participants were compound heterozygotes for two distinct nonsense mutations in ANGPTL3 (encoding the angiopoietin-like 3 protein). ANGPTL3 has been reported to inhibit lipoprotein lipase and endothelial lipase, thereby increasing plasma triglyceride and HDL cholesterol levels in rodents. Our finding of ANGPTL3 mutations highlights a role for the gene in LDL cholesterol metabolism in humans and shows the usefulness of exome sequencing for identification of novel genetic causes of inherited disorders. (Funded by the National Human Genome Research Institute and others.)

Human height is a classic, highly heritable quantitative trait. To begin to identify genetic variants influencing height, we examined genome-wide association data from 4,921 individuals. Common variants in the HMGA2 oncogene, exemplified by rs1042725, were associated with height (P = 4 × 10−8). HMGA2 is also a strong biological candidate for height, as rare, severe mutations in this gene alter body size in mice and humans, so we tested rs1042725 in additional samples. We confirmed the association in 19,064 adults from four further studies (P = 3 × 10−11, overall P = 4 × 10−16, including the genome-wide association data). We also observed the association in children (P = 1 × 10−6, N = 6,827) and a tall/short case-control study (P = 4 × 10−6, N = 3,207). We estimate that rs1042725 explains ~0.3% of population variation in height (~0.4 cm increased adult height per C allele). There are few examples of common genetic variants reproducibly associated with human quantitative traits; these results represent, to our knowledge, the first consistently replicated association with adult and childhood height.

Discovering the molecular basis of mitochondrial respiratory chain disease is challenging given the large number of both mitochondrial and nuclear genes involved. We report a strategy of focused candidate gene prediction, high-throughput sequencing, and experimental validation to uncover the molecular basis of mitochondrial complex I (CI) disorders. We created five pools of DNA from a cohort of 103 patients and then performed deep sequencing of 103 candidate genes to spotlight 151 rare variants predicted to impact protein function. We used confirmatory experiments to establish genetic diagnoses in 22% of previously unsolved cases, and discovered that defects in NUBPL and FOXRED1 can cause CI deficiency. Our study illustrates how large-scale sequencing, coupled with functional prediction and experimental validation, can reveal novel disease-causing mutations in individual patients.

The considerable uncertainty regarding cancer risks associated with inherited mutations of BRCA2 is due to unknown factors. To investigate whether common genetic variants modify penetrance for BRCA2 mutation carriers, we undertook a two-staged genome-wide association study in BRCA2 mutation carriers. In stage 1 using the Affymetrix 6.0 platform, 592,163 filtered SNPs genotyped were available on 899 young (<40 years) affected and 804 unaffected carriers of European ancestry. Associations were evaluated using a survival-based score test adjusted for familial correlations and stratified by country of the study and BRCA2*6174delT mutation status. The genomic inflation factor (λ) was 1.011. The stage 1 association analysis revealed multiple variants associated with breast cancer risk: 3 SNPs had p-values<10−5 and 39 SNPs had p-values<10−4. These variants included several previously associated with sporadic breast cancer risk and two novel loci on chromosome 20 (rs311499) and chromosome 10 (rs16917302). The chromosome 10 locus was in ZNF365, which contains another variant that has recently been associated with breast cancer in an independent study of unselected cases. In stage 2, the top 85 loci from stage 1 were genotyped in 1,264 cases and 1,222 controls. Hazard ratios (HR) and 95% confidence intervals (CI) for stage 1 and 2 were combined and estimated using a retrospective likelihood approach, stratified by country of residence and the most common mutation, BRCA2*6174delT. The combined per allele HR of the minor allele for the novel loci rs16917302 was 0.75 (95% CI 0.66–0.86, ) and for rs311499 was 0.72 (95% CI 0.61–0.85, ). FGFR2 rs2981575 had the strongest association with breast cancer risk (per allele HR = 1.28, 95% CI 1.18–1.39, ). These results indicate that SNPs that modify BRCA2 penetrance identified by an agnostic approach thus far are limited to variants that also modify risk of sporadic BRCA2 wild-type breast cancer.

Author Summary

The risk of breast cancer associated with BRCA2 mutations varies widely. To determine whether common genetic variants modify the penetrance of BRCA2 mutations, we conducted the first genome-wide association study of breast cancer among women with BRCA2 mutations using a two-stage approach. The major finding of the study is that only those loci known to be associated with breast cancer risk in the general population, including FGFR2 (rs2981575), modified BRCA2-associated risk in our high-risk population. Two novel loci, on chromosomes 10 in ZNF365 (rs16917302) and chromosome 20 (rs311499), were shown to modify risk in BRCA2 mutation carriers, although not at a genome-wide level of significance. However, the ZNF365 locus has recently independently been associated with breast cancer risk in sporadic tumors, highlighting the potential significance of this zinc finger-containing gene in breast cancer pathogenesis. Our results indicate that it is unlikely that other common variants have a strong modifying effect on BRCA2 penetrance.

Summary

Background

Comparison of patients with coronary heart disease and controls in genome-wide association studies has revealed several single nucleotide polymorphisms (SNPs) associated with coronary heart disease. We aimed to establish the external validity of these findings and to obtain more precise risk estimates using a prospective cohort design.

Methods

We tested 13 recently discovered SNPs for association with coronary heart disease in a case-control design including participants differing from those in the discovery samples (3829 participants with prevalent coronary heart disease and 48 897 controls free of the disease) and a prospective cohort design including 30 725 participants free of cardiovascular disease from Finland and Sweden. We modelled the 13 SNPs as a multilocus genetic risk score and used Cox proportional hazards models to estimate the association of genetic risk score with incident coronary heart disease. For case-control analyses we analysed associations between individual SNPs and quintiles of genetic risk score using logistic regression.

Findings

In prospective cohort analyses, 1264 participants had a first coronary heart disease event during a median 10·7 years' follow-up (IQR 6·7–13·6). Genetic risk score was associated with a first coronary heart disease event. When compared with the bottom quintile of genetic risk score, participants in the top quintile were at 1·66-times increased risk of coronary heart disease in a model adjusting for traditional risk factors (95% CI 1·35–2·04, p value for linear trend=7·3×10−10). Adjustment for family history did not change these estimates. Genetic risk score did not improve C index over traditional risk factors and family history (p=0·19), nor did it have a significant effect on net reclassification improvement (2·2%, p=0·18); however, it did have a small effect on integrated discrimination index (0·004, p=0·0006). Results of the case-control analyses were similar to those of the prospective cohort analyses.

Interpretation

Using a genetic risk score based on 13 SNPs associated with coronary heart disease, we can identify the 20% of individuals of European ancestry who are at roughly 70% increased risk of a first coronary heart disease event. The potential clinical use of this panel of SNPs remains to be defined.

Funding

The Wellcome Trust; Academy of Finland Center of Excellence for Complex Disease Genetics; US National Institutes of Health; the Donovan Family Foundation.

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.

As we move forward from the current generation of genome-wide association (GWA) studies, additional cohorts of different ancestries will be studied to increase power, fine map association signals, and generalize association results to additional populations. Knowledge of genetic ancestry as well as population substructure will become increasingly important for GWA studies in populations of unknown ancestry. Here we propose genotyping pooled DNA samples using genome-wide SNP arrays as a viable option to efficiently and inexpensively estimate admixture proportion and identify ancestry informative markers (AIMs) in populations of unknown origin. We constructed DNA pools from African American, Native Hawaiian, Latina, and Jamaican samples and genotyped them using the Affymetrix 6.0 array. Aided by individual genotype data from the African American cohort, we established quality control filters to remove poorly performing SNPs and estimated allele frequencies for the remaining SNPs in each panel. We then applied a regression-based method to estimate the proportion of admixture in each cohort using the allele frequencies estimated from pooling and populations from the International HapMap Consortium as reference panels, and identified AIMs unique to each population. In this study, we demonstrated that genotyping pooled DNA samples yields estimates of admixture proportion that are both consistent with our knowledge of population history and similar to those obtained by genotyping known AIMs. Furthermore, through validation by individual genotyping, we demonstrated that pooling is quite effective for identifying SNPs with large allele frequency differences (i.e., AIMs) and that these AIMs are able to differentiate two closely related populations (HapMap JPT and CHB).

Author Summary

Many association studies have been published looking for genetic variants contributing to a variety of human traits such as obesity, diabetes, and height. Because the frequency of genetic variants can differ across populations, it is important to have estimates of genetic ancestry in the individuals being studied. In this study, we were able to measure genetic ancestry in populations of mixed ancestry by genotyping pooled, rather than individual, DNA samples. This represents a rapid and inexpensive means for modeling genetic ancestry and thus could facilitate future association or population-genetic studies in populations of unknown ancestry for which whole-genome data do not already exist.

SLE is an autoimmune disease influenced by genetic and environmental components. We performed a genome-wide association scan (GWAS) and observed novel association evidence with a variant inTNFAIP3(rs5029939, P = 2.89×10−12, OR = 2.29). We also found evidence of two independent signals of association to SLE risk, including one described in Rheumatoid Arthritis. These results establish that genetic variation inTNFAIP3contributes to differential risk for SLE and RA.

OBJECTIVE—Using the genome-wide association approach, we recently identified the glucokinase regulatory protein gene (GCKR, rs780094) region as a novel quantitative trait locus for plasma triglyceride concentration in Europeans. Here, we sought to study the association of GCKR variants with metabolic phenotypes, including measures of glucose homeostasis, to evaluate the GCKR locus in samples of non-European ancestry and to fine- map across the associated genomic interval.

RESEARCH DESIGN AND METHODS—We performed association studies in 12 independent cohorts comprising >45,000 individuals representing several ancestral groups (whites from Northern and Southern Europe, whites from the U.S., African Americans from the U.S., Hispanics of Caribbean origin, and Chinese, Malays, and Asian Indians from Singapore). We conducted genetic fine-mapping across the ∼417-kb region of linkage disequilibrium spanning GCKR and 16 other genes on chromosome 2p23 by imputing untyped HapMap single nucleotide polymorphisms (SNPs) and genotyping 104 SNPs across the associated genomic interval.

RESULTS—We provide comprehensive evidence that GCKR rs780094 is associated with opposite effects on fasting plasma triglyceride (Pmeta = 3 × 10−56) and glucose (Pmeta = 1 × 10−13) concentrations. In addition, we confirmed recent reports that the same SNP is associated with C-reactive protein (CRP) level (P = 5 × 10−5). Both fine-mapping approaches revealed a common missense GCKR variant (rs1260326, Pro446Leu, 34% frequency, r2 = 0.93 with rs780094) as the strongest association signal in the region.

CONCLUSIONS—These findings point to a molecular mechanism in humans by which higher triglycerides and CRP can be coupled with lower plasma glucose concentrations and position GCKR in central pathways regulating both hepatic triglyceride and glucose metabolism.

To identify rheumatoid arthritis risk loci in European populations, we conducted a meta-analysis of two published genome-wide association (GWA) studies totaling 3,393 cases and 12,462 controls1,2. We genotyped 31 top-ranked SNPs not previously associated with rheumatoid arthritis in an independent replication of 3,929 autoantibody-positive rheumatoid arthritis cases and 5,807 matched controls from eight separate collections. We identified a common variant at the CD40 gene locus (rs4810485, P = 0.0032 replication, P = 8.2 × 10−9 overall, OR = 0.87). Along with other associations near TRAF1 (refs. 2,3) and TNFAIP3 (refs. 4,5), this implies a central role for the CD40 signaling pathway in rheumatoid arthritis pathogenesis. We also identified association at the CCL21 gene locus (rs2812378, P = 0.00097 replication, P = 2.8 × 10−7 overall), a gene involved in lymphocyte trafficking. Finally, we identified evidence of association at four additional gene loci: MMEL1-TNFRSF14 (rs3890745, P = 0.0035 replication, P = 1.1 × 10−7 overall), CDK6 (rs42041, P = 0.010 replication, P = 4.0 × 10−6 overall), PRKCQ (rs4750316, P = 0.0078 replication, P = 4.4 × 10−6 overall), and KIF5A-PIP4K2C (rs1678542, P = 0.0026 replication, P = 8.8 × 10−8 overall).

Blood pressure is a heritable trait, but no common genetic variants contributing to blood pressure in humans have been definitively established. Natriuretic peptides (NP) have blood pressure-lowering properties. Genotyping SNPs at the NPPA/NPPB locus in 14,743 individuals of European ancestry identified associations of plasma atrial natriuretic peptide with rs5068 (P=8×10−70), rs198358 (P=8×10−30), and rs632793 (P=2×10−10), and of plasma B-type natriuretic peptide with rs5068 (P=3×10−12), rs198358 (P=1×10−25), and rs632793 (P=2×10−68). In 29,717 individuals, the alleles of rs5068 and rs198358 related to increased circulating NP concentrations were associated with lower systolic (P=2×10−6 and 6×10−5, respectively) and diastolic blood pressure (P=1×10−6 and 5×10−5), and reduced odds of hypertension (odds ratio 0.85, 95% confidence interval, 0.79–0.92, P=4×10−5; odds ratio 0.90, 95% confidence interval, 0.85–0.95, P=2×10−4, respectively). Common genetic variants related to circulating NP concentrations contribute to inter-individual variation in blood pressure and hypertension.

Height is a classic polygenic trait, reflecting the combined influence of multiple as-yet-undiscovered genetic factors. We carried out a meta-analysis of genome-wide association study data of height from 15,821 individuals at 2.2 million SNPs, and followed up the strongest findings in >10,000 subjects. Ten newly identified and two previously reported loci were strongly associated with variation in height (P values from 4 × 10-7 to 8 × 10-22). Together, these 12 loci account for ~2% of the population variation in height. Individuals with ≤8 height-increasing alleles and ≥16 height-increasing alleles differ in height by ~3.5 cm. The newly identified loci, along with several additional loci with strongly suggestive associations, encompass both strong biological candidates and unexpected genes, and highlight several pathways (let-7 targets, chromatin remodeling proteins and Hedgehog signaling) as important regulators of human stature. These results expand the picture of the biological regulation of human height and of the genetic architecture of this classical complex trait.

Blood concentrations of lipoproteins and lipids are heritable1 risk factors for cardiovascular disease2,3. Using genome-wide association data from three studies (n = 8,816 that included 2,758 individuals from the Diabetes Genetics Initiative specific to the current paper as well as 1,874 individuals from the FUSION study of type 2 diabetes and 4,184 individuals from the SardiNIA study of aging-associated variables reported in a companion paper in this issue4) and targeted replication association analyses in up to 18,554 independent participants, we show that common SNPs at 18 loci are reproducibly associated with concentrations of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, and/or triglycerides. Six of these loci are new (P < 5 × 10−8 for each new locus). Of the six newly identified chromosomal regions, two were associated with LDL cholesterol (1p13 near CELSR2, PSRC1 and SORT1 and 19p13 near CILP2 and PBX4), one with HDL cholesterol (1q42 in GALNT2) and five with triglycerides (7q11 near TBL2 and MLXIPL, 8q24 near TRIB1, 1q42 in GALNT2, 19p13 near CILP2 and PBX4 and 1p31 near ANGPTL3). At 1p13, the LDL-associated SNP was also strongly correlated with CELSR2, PSRC1, and SORT1 transcript levels in human liver, and a proxy for this SNP was recently shown to affect risk for coronary artery disease5. Understanding the molecular, cellular and clinical consequences of the newly identified loci may inform therapy and clinical care.