Genome-wide association studies (GWAS) for plasma lipid levels have mapped numerous genomic loci, with each region often containing many protein-coding genes. Targeted re-sequencing of exons is a strategy to pinpoint causal variants and genes.

We conducted a genome-wide association study (GWAS) on multiple sclerosis (MS) susceptibility in German cohorts with 4888 cases and 10,395 controls. In addition to associations within the major histocompatibility complex (MHC) region, 15 non-MHC loci reached genome-wide significance. Four of these loci are novel MS susceptibility loci. They map to the genes L3MBTL3, MAZ, ERG, and SHMT1. The lead variant at SHMT1 was replicated in an independent Sardinian cohort. Products of the genes L3MBTL3, MAZ, and ERG play important roles in immune cell regulation. SHMT1 encodes a serine hydroxymethyltransferase catalyzing the transfer of a carbon unit to the folate cycle. This reaction is required for regulation of methylation homeostasis, which is important for establishment and maintenance of epigenetic signatures. Our GWAS approach in a defined population with limited genetic substructure detected associations not found in larger, more heterogeneous cohorts, thus providing new clues regarding MS pathogenesis.

The analysis of next-generation sequencing data is computationally and statistically challenging because of the massive volume of data and imperfect data quality. We present GotCloud, a pipeline for efficiently detecting and genotyping high-quality variants from large-scale sequencing data. GotCloud automates sequence alignment, sample-level quality control, variant calling, filtering of likely artifacts using machine-learning techniques, and genotype refinement using haplotype information. The pipeline can process thousands of samples in parallel and requires less computational resources than current alternatives. Experiments with whole-genome and exome-targeted sequence data generated by the 1000 Genomes Project show that the pipeline provides effective filtering against false positive variants and high power to detect true variants. Our pipeline has already contributed to variant detection and genotyping in several large-scale sequencing projects, including the 1000 Genomes Project and the NHLBI Exome Sequencing Project. We hope it will now prove useful to many medical sequencing studies.

Sequencing studies of exonic regions aim to identify rare variants contributing to complex traits. With high coverage and large sample size, these studies tend to apply simple variant calling algorithms. However, coverage is often heterogeneous; sites with insufficient coverage may benefit from sophisticated calling algorithms used in low-coverage sequencing studies. We evaluate the potential benefits of different calling strategies by performing a comparative analysis of variant calling methods on exonic data from 202 genes sequenced at 24x in 7,842 individuals. We call variants using individual-based, population-based and linkage disequilibrium (LD)-aware methods with stringent quality control. We measure genotype accuracy by the concordance with on-target GWAS genotypes and between 80 pairs of sequencing replicates. We validate selected singleton variants using capillary sequencing.

DNA sequencing identifies common and rare genetic variants for association studies, but studies typically focus on variants in nuclear DNA and ignore the mitochondrial genome. In fact, analyzing variants in mitochondrial DNA (mtDNA) sequences presents special problems, which we resolve here with a general solution for the analysis of mtDNA in next-generation sequencing studies. The new program package comprises 1) an algorithm designed to identify mtDNA variants (i.e., homoplasmies and heteroplasmies), incorporating sequencing error rates at each base in a likelihood calculation and allowing allele fractions at a variant site to differ across individuals; and 2) an estimation of mtDNA copy number in a cell directly from whole-genome sequencing data. We also apply the methods to DNA sequence from lymphocytes of ~2,000 SardiNIA Project participants. As expected, mothers and offspring share all homoplasmies but a lesser proportion of heteroplasmies. Both homoplasmies and heteroplasmies show 5-fold higher transition/transversion ratios than variants in nuclear DNA. Also, heteroplasmy increases with age, though on average only ~1 heteroplasmy reaches the 4% level between ages 20 and 90. In addition, we find that mtDNA copy number averages ~110 copies/lymphocyte and is ~54% heritable, implying substantial genetic regulation of the level of mtDNA. Copy numbers also decrease modestly but significantly with age, and females on average have significantly more copies than males. The mtDNA copy numbers are significantly associated with waist circumference (p-value = 0.0031) and waist-hip ratio (p-value = 2.4×10-5), but not with body mass index, indicating an association with central fat distribution. To our knowledge, this is the largest population analysis to date of mtDNA dynamics, revealing the age-imposed increase in heteroplasmy, the relatively high heritability of copy number, and the association of copy number with metabolic traits.

Genome-wide association studies (GWAS) have identified genetic variants at 34 loci contributing to age-related macular degeneration (AMD)1-3. We generated transcriptional profiles of postmortem retinas from 453 controls and cases at distinct stages of AMD and integrated retinal transcriptomes, covering 13,662 protein-coding and 1,462 noncoding genes, with genotypes at more than 9 million common SNPs for expression quantitative trait loci (eQTL) analysis of a tissue not included in Genotype-Tissue Expression (GTEx) and other large datasets4,5. Cis-eQTL analysis identified 10,474 genes under genetic regulation, including 4,541 eQTLs detected only in the retina. Integrated analysis of AMD-GWAS with eQTLs ascertained likely target genes at six reported loci. Using transcriptome-wide association analysis (TWAS), we identified three additional genes, RLBP1, HIC1 and PARP12, after Bonferroni correction. Our studies expand the genetic landscape of AMD and establish the Eye Genotype Expression (EyeGEx) database as a resource for post-GWAS interpretation of multifactorial ocular traits.

The population of the Mediterranean island of Sardinia has made important contributions to genome-wide association studies of complex disease traits and, based on ancient DNA studies of mainland Europe, Sardinia is hypothesized to be a unique refuge for early Neolithic ancestry. To provide new insights on the genetic history of this flagship population, we analyzed 3,514 whole-genome sequenced individuals from Sardinia. Sardinian samples show elevated levels of shared ancestry with Basque individuals, especially samples from the more historically isolated regions of Sardinia. Our analysis also uniquely illuminates how levels of genetic similarity with mainland ancient DNA samples varies subtly across the island. Together, our results indicate that within-island substructure and sex-biased processes have substantially impacted the genetic history of Sardinia. These results give new insight into the demography of ancestral Sardinians and help further the understanding of sharing of disease risk alleles between Sardinia and mainland populations.

Estimates of the ancestry of specific chromosomal regions in admixed individuals are useful for studies of human evolutionary history and for genetic association studies. Previously, this ancestry inference relied on high-quality genotypes from genome-wide association study (GWAS) arrays. These high-quality genotypes are not always available when samples are exome sequenced, and exome sequencing is the strategy of choice for many ongoing genetic studies. Here we show that off-target reads generated during exome-sequencing experiments can be combined with on-target reads to accurately estimate the ancestry of each chromosomal segment in an admixed individual. To reconstruct local ancestry, our method SEQMIX models aligned bases directly instead of relying on hard genotype calls. We evaluate the accuracy of our method through simulations and analysis of samples sequenced by the 1000 Genomes Project and the NHLBI Grand Opportunity Exome Sequencing Project. In African Americans, we show that local-ancestry estimates derived by our method are very similar to those derived with Illumina's Omni 2.5M genotyping array and much improved in relation to estimates that use only exome genotypes and ignore off-target sequencing reads. Software implementing this method, SEQMIX, can be applied to analysis of human population history or used for genetic association studies in admixed individuals.

Blood lipid levels are heritable, treatable risk factors for cardiovascular disease. We systematically assessed genome-wide coding variation to identify new genes influencing lipid traits, fine map known lipid loci and evaluate whether low-frequency variants with large effects exist for these traits. Using an exome array, we genotyped 80,137 coding variants in 5,643 Norwegians. We followed up 18 variants in 4,666 Norwegians and identified ten loci with coding variants associated with a lipid trait (P < 5 × 10(-8)). One variant in TM6SF2 (encoding p.Glu167Lys), residing in a known genome-wide association study locus for lipid traits, influences total cholesterol levels and is associated with myocardial infarction. Transient TM6SF2 overexpression or knockdown of Tm6sf2 in mice alters serum lipid profiles, consistent with the association observed in humans, identifying TM6SF2 as a functional gene within a locus previously known as NCAN-CILP2-PBX4 or 19p13. This study demonstrates that systematic assessment of coding variation can quickly point to a candidate causal gene.

Psoriasis vulgaris (PsV) risk is strongly associated with variation within the major histocompatibility complex (MHC) region, but its genetic architecture has yet to be fully elucidated. Here, we conducted a large-scale fine-mapping study of PsV risk in the MHC region in 9,247 PsV-affected individuals and 13,589 controls of European descent by imputing class I and II human leukocyte antigen (HLA) genes from SNP genotype data. In addition, we imputed sequence variants for MICA, an MHC HLA-like gene that has been associated with PsV, to evaluate association at that locus as well. We observed that HLA-C(∗)06:02 demonstrated the lowest p value for overall PsV risk (p = 1.7 × 10(-364)). Stepwise analysis revealed multiple HLA-C(∗)06:02-independent risk variants in both class I and class II HLA genes for PsV susceptibility (HLA-C(∗)12:03, HLA-B amino acid positions 67 and 9, HLA-A amino acid position 95, and HLA-DQα1 amino acid position 53; p < 5.0 × 10(-8)), but no apparent risk conferred by MICA. We further evaluated risk of two major clinical subtypes of PsV, psoriatic arthritis (PsA; n = 3,038) and cutaneous psoriasis (PsC; n = 3,098). We found that risk heterogeneity between PsA and PsC might be driven by HLA-B amino acid position 45 (Pomnibus = 2.2 × 10(-11)), indicating that different genetic factors underlie the overall risk of PsV and the risk of specific PsV subphenotypes. Our study illustrates the value of high-resolution HLA and MICA imputation for fine mapping causal variants in the MHC.

Substance use is heritable, but few common genetic variants have been associated with these behaviors. Rare nonsynonymous exonic variants can now be efficiently genotyped, allowing exome-wide association tests. We identified and tested 111,592 nonsynonymous exonic variants for association with behavioral disinhibition and the use/misuse of nicotine, alcohol, and illicit drugs.

Deep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader allelic architecture of 12 anthropometric traits associated with height, body mass, and fat distribution in up to 267,616 individuals. We report 106 genome-wide significant signals that have not been previously identified, including 9 low-frequency variants pointing to functional candidates. Of the 106 signals, 6 are in genomic regions that have not been implicated with related traits before, 28 are independent signals at previously reported regions, and 72 represent previously reported signals for a different anthropometric trait. 71% of signals reside within genes and fine mapping resolves 23 signals to one or two likely causal variants. We confirm genetic overlap between human monogenic and polygenic anthropometric traits and find signal enrichment in cis expression QTLs in relevant tissues. Our results highlight the potential of WGS strategies to enhance biologically relevant discoveries across the frequency spectrum.

Psoriasis is a complex disease of skin with a prevalence of about 2%. We conducted the largest meta-analysis of genome-wide association studies (GWAS) for psoriasis to date, including data from eight different Caucasian cohorts, with a combined effective sample size >39,000 individuals. We identified 16 additional psoriasis susceptibility loci achieving genome-wide significance, increasing the number of identified loci to 63 for European-origin individuals. Functional analysis highlighted the roles of interferon signalling and the NFκB cascade, and we showed that the psoriasis signals are enriched in regulatory elements from different T cells (CD8+ T-cells and CD4+ T-cells including TH0, TH1 and TH17). The identified loci explain ∼28% of the genetic heritability and generate a discriminatory genetic risk score (AUC=0.76 in our sample) that is significantly correlated with age at onset (p=2 × 10-89). This study provides a comprehensive layout for the genetic architecture of common variants for psoriasis.

Age-related macular degeneration (AMD) is a common cause of blindness in older individuals. To accelerate the understanding of AMD biology and help design new therapies, we executed a collaborative genome-wide association study, including >17,100 advanced AMD cases and >60,000 controls of European and Asian ancestry. We identified 19 loci associated at P < 5 × 10(-8). These loci show enrichment for genes involved in the regulation of complement activity, lipid metabolism, extracellular matrix remodeling and angiogenesis. Our results include seven loci with associations reaching P < 5 × 10(-8) for the first time, near the genes COL8A1-FILIP1L, IER3-DDR1, SLC16A8, TGFBR1, RAD51B, ADAMTS9 and B3GALTL. A genetic risk score combining SNP genotypes from all loci showed similar ability to distinguish cases and controls in all samples examined. Our findings provide new directions for biological, genetic and therapeutic studies of AMD.

Economic variables such as income, education, and occupation are known to affect mortality and morbidity, such as cardiovascular disease, and have also been shown to be partly heritable. However, very little is known about which genes influence economic variables, although these genes may have both a direct and an indirect effect on health. We report results from the first large-scale collaboration that studies the molecular genetic architecture of an economic variable-entrepreneurship-that was operationalized using self-employment, a widely-available proxy. Our results suggest that common SNPs when considered jointly explain about half of the narrow-sense heritability of self-employment estimated in twin data (σ(g)(2)/σ(P)(2) = 25%, h(2) = 55%). However, a meta-analysis of genome-wide association studies across sixteen studies comprising 50,627 participants did not identify genome-wide significant SNPs. 58 SNPs with p<10(-5) were tested in a replication sample (n = 3,271), but none replicated. Furthermore, a gene-based test shows that none of the genes that were previously suggested in the literature to influence entrepreneurship reveal significant associations. Finally, SNP-based genetic scores that use results from the meta-analysis capture less than 0.2% of the variance in self-employment in an independent sample (p≥0.039). Our results are consistent with a highly polygenic molecular genetic architecture of self-employment, with many genetic variants of small effect. Although self-employment is a multi-faceted, heavily environmentally influenced, and biologically distal trait, our results are similar to those for other genetically complex and biologically more proximate outcomes, such as height, intelligence, personality, and several diseases.

Raised blood pressure (BP) is a major risk factor for cardiovascular disease. Previous studies have identified 47 distinct genetic variants robustly associated with BP, but collectively these explain only a few percent of the heritability for BP phenotypes. To find additional BP loci, we used a bespoke gene-centric array to genotype an independent discovery sample of 25,118 individuals that combined hypertensive case-control and general population samples. We followed up four SNPs associated with BP at our p < 8.56 × 10(-7) study-specific significance threshold and six suggestively associated SNPs in a further 59,349 individuals. We identified and replicated a SNP at LSP1/TNNT3, a SNP at MTHFR-NPPB independent (r(2) = 0.33) of previous reports, and replicated SNPs at AGT and ATP2B1 reported previously. An analysis of combined discovery and follow-up data identified SNPs significantly associated with BP at p < 8.56 × 10(-7) at four further loci (NPR3, HFE, NOS3, and SOX6). The high number of discoveries made with modest genotyping effort can be attributed to using a large-scale yet targeted genotyping array and to the development of a weighting scheme that maximized power when meta-analyzing results from samples ascertained with extreme phenotypes, in combination with results from nonascertained or population samples. Chromatin immunoprecipitation and transcript expression data highlight potential gene regulatory mechanisms at the MTHFR and NOS3 loci. These results provide candidates for further study to help dissect mechanisms affecting BP and highlight the utility of studying SNPs and samples that are independent of those studied previously even when the sample size is smaller than that in previous studies.

Identifying the genes that influence levels of pro-inflammatory molecules can help to elucidate the mechanisms underlying this process. We first conducted a two-stage genome-wide association scan (GWAS) for the key inflammatory biomarkers Interleukin-6 (IL-6), the general measure of inflammation erythrocyte sedimentation rate (ESR), monocyte chemotactic protein-1 (MCP-1), and high-sensitivity C-reactive protein (hsCRP) in a large cohort of individuals from the founder population of Sardinia. By analysing 731,213 autosomal or X chromosome SNPs and an additional ∼1.9 million imputed variants in 4,694 individuals, we identified several SNPs associated with the selected quantitative trait loci (QTLs) and replicated all the top signals in an independent sample of 1,392 individuals from the same population. Next, to increase power to detect and resolve associations, we further genotyped the whole cohort (6,145 individuals) for 293,875 variants included on the ImmunoChip and MetaboChip custom arrays. Overall, our combined approach led to the identification of 9 genome-wide significant novel independent signals-5 of which were identified only with the custom arrays-and provided confirmatory evidence for an additional 7. Novel signals include: for IL-6, in the ABO gene (rs657152, p = 2.13×10(-29)); for ESR, at the HBB (rs4910472, p = 2.31×10(-11)) and UCN119B/SPPL3 (rs11829037, p = 8.91×10(-10)) loci; for MCP-1, near its receptor CCR2 (rs17141006, p = 7.53×10(-13)) and in CADM3 (rs3026968, p = 7.63×10(-13)); for hsCRP, within the CRP gene (rs3093077, p = 5.73×10(-21)), near DARC (rs3845624, p = 1.43×10(-10)), UNC119B/SPPL3 (rs11829037, p = 1.50×10(-14)), and ICOSLG/AIRE (rs113459440, p = 1.54×10(-08)) loci. Confirmatory evidence was found for IL-6 in the IL-6R gene (rs4129267); for ESR at CR1 (rs12567990) and TMEM57 (rs10903129); for MCP-1 at DARC (rs12075); and for hsCRP at CRP (rs1205), HNF1A (rs225918), and APOC-I (rs4420638). Our results improve the current knowledge of genetic variants underlying inflammation and provide novel clues for the understanding of the molecular mechanisms regulating this complex process.

Psoriasis, an immune-mediated, inflammatory disease of the skin and joints, provides an ideal system for expression quantitative trait locus (eQTL) analysis, because it has a strong genetic basis and disease-relevant tissue (skin) is readily accessible. To better understand the role of genetic variants regulating cutaneous gene expression, we identified 841 cis-acting eQTLs using RNA extracted from skin biopsies of 53 psoriatic individuals and 57 healthy controls. We found substantial overlap between cis-eQTLs of normal control, uninvolved psoriatic, and lesional psoriatic skin. Consistent with recent studies and with the idea that control of gene expression can mediate relationships between genetic variants and disease risk, we found that eQTL SNPs are more likely to be associated with psoriasis than are randomly selected SNPs. To explore the tissue specificity of these eQTLs and hence to quantify the benefits of studying eQTLs in different tissues, we developed a refined statistical method for estimating eQTL overlap and used it to compare skin eQTLs to a published panel of lymphoblastoid cell line (LCL) eQTLs. Our method accounts for the fact that most eQTL studies are likely to miss some true eQTLs as a result of power limitations and shows that ∼70% of cis-eQTLs in LCLs are shared with skin, as compared with the naive estimate of < 50% sharing. Our results provide a useful method for estimating the overlap between various eQTL studies and provide a catalog of cis-eQTLs in skin that can facilitate efforts to understand the functional impact of identified susceptibility variants on psoriasis and other skin traits.

We carried out a meta-analysis of two recent psoriasis genome-wide association studies with a combined discovery sample of 1,831 affected individuals (cases) and 2,546 controls. One hundred and two loci selected based on P value rankings were followed up in a three-stage replication study including 4,064 cases and 4,685 controls from Michigan, Toronto, Newfoundland and Germany. In the combined meta-analysis, we identified three new susceptibility loci, including one at NOS2 (rs4795067, combined P = 4 × 10⁻¹¹), one at FBXL19 (rs10782001, combined P = 9 × 10⁻¹⁰) and one near PSMA6-NFKBIA (rs12586317, combined P = 2 × 10⁻⁸). All three loci were also associated with psoriatic arthritis (rs4795067, combined P = 1 × 10⁻⁵; rs10782001, combined P = 4 × 10⁻⁸; and rs12586317, combined P = 6 × 1⁻⁵) and purely cutaneous psoriasis (rs4795067, combined P = 1 × 10⁻⁸; rs10782001, combined P = 2 × 10⁻⁶; and rs12586317, combined P = 1 × 10⁻⁶). We also replicated a recently identified association signal near RNF114 (rs495337, combined P = 2 × 10⁻⁷).

Genome-wide association studies (GWAS) have revealed hundreds of loci associated with common human genetic diseases and traits. We have developed a web-based plotting tool that provides fast visual display of GWAS results in a publication-ready format. LocusZoom visually displays regional information such as the strength and extent of the association signal relative to genomic position, local linkage disequilibrium (LD) and recombination patterns and the positions of genes in the region.