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Purpose: VEGF receptor (VEGFR) kinases are important drug targets in oncology that affect function of systemic endothelial cells. To discover genetic markers that affect VEGFR inhibitor pharmacodynamics, we performed a genome-wide association study of serum soluble vascular VEGFR2 concentrations [sVEGFR2], a pharmacodynamic biomarker for VEGFR2 inhibitors.Experimental Design: We conducted a genome-wide association study (GWAS) of [sVEGFR2] in 736 healthy Old Order Amish volunteers. Gene variants identified from the GWAS were genotyped serially in a cohort of 128 patients with advanced solid tumor with baseline [sVEGFR2] measurements, and in 121 patients with renal carcinoma with [sVEGFR2] measured before and during pazopanib therapy.Results: rs34231037 (C482R) in KDR, the gene encoding sVEGFR2 was found to be highly associated with [sVEGFR2], explaining 23% of the variance (P = 2.7 × 10−37). Association of rs34231037 with [sVEGFR2] was replicated in 128 patients with cancer with comparable effect size (P = 0.025). Furthermore, rs34231037 was a significant predictor of changes in [sVEGFR2] in response to pazopanib (P = 0.01).Conclusion: Our findings suggest that genome-wide analysis of phenotypes in healthy populations can expedite identification of candidate pharmacogenetic markers. Genotyping for germline variants in KDR may have clinical utility in identifying patients with cancer with unusual sensitivity to effects of VEGFR2 kinase inhibitors. Clin Cancer Res; 21(2); 365–72. ©2014 AACR.

Prioritizing genes for translation to therapeutics for common diseases has been challenging. Here, we propose an approach to identify drug targets with high probability of success by focusing on genes with both gain of function (GoF) and loss of function (LoF) mutations associated with opposing effects on phenotype (Bidirectional Effect Selected Targets, BEST). We find 98 BEST genes for a variety of indications. Drugs targeting those genes are 3.8-fold more likely to be approved than non-BEST genes. We focus on five genes (IGF1R, NPPC, NPR2, FGFR3, and SHOX) with evidence for bidirectional effects on stature. Rare protein-altering variants in those genes result in significantly increased risk for idiopathic short stature (ISS) (OR = 2.75, p = 3.99 × 10−8). Finally, using functional experiments, we demonstrate that adding an exogenous CNP analog (encoded by NPPC) rescues the phenotype, thus validating its potential as a therapeutic treatment for ISS. Our results show the value of looking for bidirectional effects to identify and validate drug targets., Prioritising genes as potential drug targets is challenging and often unsuccessful once testing efficacy in humans. Here, the authors propose an approach to identifying drug targets that uses evidence from gain- or loss-of-function mutations associated with bidirectional effects on phenotypes.

The UK Biobank is a prospective study of 502,543 individuals, combining extensive phenotypic and genotypic data with streamlined access for researchers around the world1. Here we describe the release of exome-sequence data for the first 49,960 study participants, revealing approximately 4 million coding variants (of which around 98.6% have a frequency of less than 1%). The data include 198,269 autosomal predicted loss-of-function (LOF) variants, a more than 14-fold increase compared to the imputed sequence. Nearly all genes (more than 97%) had at least one carrier with a LOF variant, and most genes (more than 69%) had at least ten carriers with a LOF variant. We illustrate the power of characterizing LOF variants in this population through association analyses across 1,730 phenotypes. In addition to replicating established associations, we found novel LOF variants with large effects on disease traits, including PIEZO1 on varicose veins, COL6A1 on corneal resistance, MEPE on bone density, and IQGAP2 and GMPR on blood cell traits. We further demonstrate the value of exome sequencing by surveying the prevalence of pathogenic variants of clinical importance, and show that 2% of this population has a medically actionable variant. Furthermore, we characterize the penetrance of cancer in carriers of pathogenic BRCA1 and BRCA2 variants. Exome sequences from the first 49,960 participants highlight the promise of genome sequencing in large population-based studies and are now accessible to the scientific community., Exome sequences from the first 49,960 participants in the UK Biobank highlight the promise of genome sequencing in large population-based studies and are now accessible to the scientific community.

While GWAS of common diseases has delivered thousands of novel genetic findings, prioritizing genes for translation to therapeutics has been challenging. Here, we propose an approach to resolve that issue by identifying genes that have both gain of function (GoF) and loss of function (LoF) mutations associated with opposing effects on phenotype (Bidirectional Effect Selected Targets, BEST). Bidirectionality is a desirable feature of the best targets because it implies both a causal role on the phenotype in one direction and that modulating the target activity might be safe and therapeutically beneficial in the other.We used height, a highly heritable trait and a model of complex diseases, to test our approach. Using 34,231 individuals with exome sequence data and height, we identified five genes (IGF1R, NPPC, NPR2, FGFR3, and SHOX) with evidence for bidirectional effects on stature. Rare protein-altering variants significantly increased risk for idiopathic short stature (ISS) (OR=2.75, p= 3.99×10−8). These genes are key members of the only two pathways successfully targeted for short stature: Growth Hormone/Insulin-like growth factor 1 axis and C-type Natriuretic peptide (CNP) for Achondroplasia, a monogenic form of dwarfism. We assayed a subset of NPR2 mutations and identified those with elevated (GoF) and diminished (LoF) activity and found that a polygenic score for height modulates the penetrance of pathogenic variants. We also demonstrated that adding exogenous CNP (encoded by NPPC) rescues the NPR2 haploinsufficiency molecular phenotype in a CRISPR-engineered cell line, thus validating its potential therapeutic treatment for inherited forms of short stature. Finally, we found that these BEST targets increase the probability of success in clinical trials above and beyond targets with other genetic evidence. Our results show the value of looking for bidirectional effects to identify and validate drug targets.

Support from human genetics increases the probability of success in drug development. However, few examples exist of successful genomically-driven drug repositioning. Given that a Mendelian form of severe enterocolitis is due to up-regulation of the interleukin-18 (IL18) signaling pathway, and pharmacologic inhibition of IL18 has been shown to reverse this enterocolitis, we undertook a Mendelian randomization study to test the causal effect of elevated IL18 levels on inflammatory bowel disease susceptibility (IBD) in 12,882 cases and 21,770 controls. Mendelian randomization is an established method to assess the role of biomarkers in disease etiology in a manner that minimizes confounding and prevents reverse causation. Using three SNPs that explained almost 7% of the variance in IL18 level, we found that each genetically predicted standard deviation increase in IL18 was associated with an increase in IBD susceptibility (odds ratio = 1.22, 95% CI = 1.11–1.34, P-value = 6 × 10−5). This association was further validated in 25,042 IBD cases and 34,915 controls (odds ratio = 1.13, 95% CI = 1.05–1.20). Recently, an anti-IL18 monoclonal antibody, which decreased free IL18 levels, was found to be safe, yet ineffective in a phase II trial for type 2 diabetes. Taken together, these genomic findings implicated IBD as an alternative indication for anti-IL18 therapy, which should be tested in randomized controlled trials.

SUMMARYThe UK Biobank is a prospective study of 502,543 individuals, combining extensive phenotypic and genotypic data with streamlined access for researchers around the world. Here we describe the first tranche of large-scale exome sequence data for 49,960 study participants, revealing approximately 4 million coding variants (of which ~98.4% have frequency < 1%). The data includes 231,631 predicted loss of function variants, a >10-fold increase compared to imputed sequence for the same participants. Nearly all genes (>97%) had ≥1 predicted loss of function carrier, and most genes (>69%) had ≥10 loss of function carriers. We illustrate the power of characterizing loss of function variation in this large population through association analyses across 1,741 phenotypes. In addition to replicating a range of established associations, we discover novel loss of function variants with large effects on disease traits, including PIEZO1 on varicose veins, COL6A1 on corneal resistance, MEPE on bone density, and IQGAP2 and GMPR on blood cell traits. We further demonstrate the value of exome sequencing by surveying the prevalence of pathogenic variants of clinical significance in this population, finding that 2% of the population has a medically actionable variant. Additionally, we leverage the phenotypic data to characterize the relationship between rare BRCA1 and BRCA2 pathogenic variants and cancer risk. Exomes from the first 49,960 participants are now made accessible to the scientific community and highlight the promise offered by genomic sequencing in large-scale population-based studies.

The hope for precision medicine has long been on the drug discovery horizon, well before the Human Genome Project gave it promise at the turn of the 21st century. In oncology, the concept has finally been realized and is now firmly embedded in ongoing drug discovery programs, and with many recent therapies involving some level of patient/disease stratification, including some highly personalized treatments. In addition, several drugs for rare diseases have been recently approved or are in late-stage clinical development, and new delivery modalities in cell and gene therapy and oligonucleotide approaches are yielding exciting new medicines for rare diseases of unmet need. For common complex diseases, however, the GWAS-driven advances in annotation of the genetic architecture over the past decade have not led to a concomitant shift in refined treatments. Similarly, attempts to disentangle treatment responders from non-responders via genetic predictors in pharmacogenetics studies have not met their anticipated success. It is possible that common diseases are simply lagging behind due to the inherent time lag with drug discovery, but it is also possible that their inherent multifactorial nature and their etiological and clinical heterogeneity will prove more resistant to refined treatment paradigms. The emergence of population-based resources in electronic health records, coupled with the rapid expansion of mobile devices and digital health may help to refine the measurement of phenotypic outcomes to match the exquisite detail emerging at the molecular level.

Supplemental Digital Content is available in the text., Objective Proteins involving absorption, distribution, metabolism, and excretion (ADME) play a critical role in drug pharmacokinetics. The type and frequency of genetic variation in the ADME genes differ among populations. The aim of this study was to systematically investigate common and rare ADME coding variation in diverse ethnic populations by exome sequencing. Materials and methods Data derived from commercial exome capture arrays and next-generation sequencing were used to characterize coding variation in 298 ADME genes in 251 Northeast Asians and 1181 individuals from the 1000 Genomes Project. Results Approximately 75% of the ADME coding sequence was captured at high quality across the joint samples harboring more than 8000 variants, with 49% of individuals carrying at least one ‘knockout’ allele. ADME genes carried 50% more nonsynonymous variation than non-ADME genes (P=8.2×10–13) and showed significantly greater levels of population differentiation (P=7.6×10–11). Out of the 2135 variants identified that were predicted to be deleterious, 633 were not on commercially available ADME or general-purpose genotyping arrays. Forty deleterious variants within important ADME genes, with frequencies of at least 2% in at least one population, were identified as candidates for future pharmacogenetic studies. Conclusion Exome sequencing was effective in accurately genotyping most ADME variants important for pharmacogenetic research, in addition to identifying rare or potentially de novo coding variants that may be clinically meaningful. Furthermore, as a class, ADME genes are more variable and less sensitive to purifying selection than non-ADME genes.

Ankylosing spondylitis (AS) is a common and highly heritable inflammatory arthropathy. Although the gene HLA-B27 is almost essential for the inheritance of the condition, it alone is not sufficient to explain the pattern of familial recurrence of the disease. We have previously demonstrated suggestive linkage of AS to chromosome 2q13, a region containing the interleukin 1 (IL-1) family gene cluster, which includes several strong candidates for involvement in the disease. In the current study, we describe strong association and transmission of IL-1 family gene cluster single-nucleotide polymorphisms and haplotypes with AS.

A substantial investment has been made in the generation of large public resources designed to enable the identification of tag SNP sets, but data establishing the adequacy of the sample sizes used are limited. Using large-scale empirical and simulated data sets, we found that the sample sizes used in the HapMap project are sufficient to capture common variation, but that performance declines substantially for variants with minor allele frequencies of

This protocol describes how to perform basic statistical analysis in a population-based genetic association case-control study. The steps described involve the (i) appropriate selection of measures of association and relevance of disease models; (ii) appropriate selection of tests of association; (iii) visualization and interpretation of results; (iv) consideration of appropriate methods to control for multiple testing; and (v) replication strategies. Assuming no previous experience with software such as PLINK, R or Haploview, we describe how to use these popular tools for handling single-nucleotide polymorphism data in order to carry out tests of association and visualize and interpret results. This protocol assumes that data quality assessment and control has been performed, as described in a previous protocol, so that samples and markers deemed to have the potential to introduce bias to the study have been identified and removed. Study design, marker selection and quality control of case-control studies have also been discussed in earlier protocols. The protocol should take ~1 h to complete.

This protocol details the data quality assessment and control steps that are typically carried out during case-control association studies. The steps described involve the identification and removal of DNA samples and markers that introduce bias to the study. These critical steps are paramount to the success of a case-control study and are necessary before statistically testing for association. We describe how to use PLINK, a tool for handling SNP data, to carry out assessments of failure rate per-individual and per-SNP and to assess the degree of relatedness between individuals. We also detail other quality control procedures, including the use of SMARTPCA for the identification of ancestral outliers. These platforms were selected because they are user-friendly, widely used, and computationally efficient. Steps needed to detect and establish a disease association using case-control data are not discussed, as these are provided in a further protocol in the series. Issues concerning the study design and marker selection in case-control studies have been discussed in our earlier protocols. The protocol should take approximately 8 hours to complete.

The age of onset of Huntington's disease (HD) is inversely correlated with the CAG length in the HD gene. The CAG repeat length accounts for 70% of the variability in HD age of onset. However, 90% of individuals worldwide with expanded alleles possess between 40 and 50 CAG repeat lengths in their HD gene. For these people, the size of their repeat only determines 44% of the variability in their age of onset. Once the effect of the CAG repeat has been accounted for, the residual variance in age of onset is a heritable trait. Targeted candidate gene studies and a genome scan have suggested some loci as potential modifiers of the age of onset of HD. We analyzed the large Venezuelan kindreds in which the HD gene was originally identified. These kindreds offer greater analytic power than standard sib-pair designs. We developed novel pedigree-member selection procedures to maximize power. Using a 5,858-single-nucleotide-polymorphism marker panel, we performed a genomewide linkage analysis. We discovered two novel loci on chromosome 2. Chromosome 2p25 (logarithm of the odds ratio (LOD)=4.29) and 2q35 (LOD=3.39) may contain genes that modify age of onset. A third linkage peak on chromosome 6q22 (LOD=2.48) may confirm the most promising locus from a previous genome scan. Two other candidate loci are suggestive on chromosome 5 (LOD=3.31 at 5p14 and LOD=3.14 at 5q32). All these regions harbor candidate genes that are potential HD modifier genes. Finding these modifier genes can reveal accessible and promising new therapeutic pathways and targets to ameliorate and cure HD. Genet. Epidemiol. 2008. © 2008 Wiley-Liss, Inc.

Chronic pelvic pain (CPP) is a common condition in women that is difficult to diagnose. Although heritability estimates have been published for some conditions potentially underlying pelvic pain, the heritability of CPP itself has never been investigated. Using data from 623 MZ and 377 DZ female twin pairs aged 29-50 from an Australian twin cohort, we found an increased CPP concordance among MZs compared to DZs, with tetrachoric correlations of 0.43 (95% CI: 0.26-0.58) and 0.11 (95% CI: -0.16-0.38), respectively. This corresponded to a heritability of 0.41 (95% CI: 0.25-0.56). Lack of correlations with environmental indicators suggested that violation of the equal environments assumption was not responsible for this effect. Multivariate Cholesky decomposition models incorporating CPP and significantly correlated phenotypes showed that the entire CPP heritability could be explained by genetic variance underlying endometriosis (38%), dysmenorrhoea (23%), fibroids (24%), and somatic distress (15%), the latter a possible indicator of increased nociception. CPP itself is unlikely to be a useful independent phenotype to conduct genetic aetiological studies; contributing conditions such as endometriosis and variation in nociception are likely to provide more useful phenotypes.

Several risk factors for Crohn's disease have been identified in recent genome-wide association studies. To advance gene discovery further, we combined data from three studies on Crohn's disease ( a total of 3,230 cases and 4,829 controls) and carried out replication in 3,664 independent cases with a mixture of population-based and family-based controls. The results strongly confirm 11 previously reported loci and provide genome-wide significant evidence for 21 additional loci, including the regions containing STAT3, JAK2, ICOSLG, CDKAL1 and ITLN1. The expanded molecular understanding of the basis of this disease offers promise for informed therapeutic development.

Family studies have long suggested a role for genetic factors in the aetiology of endometriosis. The influence of genes on disease development has mainly been researched independently of environmental factors, yet their interaction must play an important role. Greater exposure to retrograde menstruation and oestrogen is likely to increase the risk of endometriosis; toxic compounds such as dioxin may increase the risk, although the only direct evidence has come from primate studies. Previous association studies implicated GALT (a gene involved in galactose metabolism), and GSTM1 and NAT2 (genes encoding for the detoxification enzymes) as possible disease susceptibility genes. Recent findings have added to the evidence for the involvement of GSTM1 and NAT2, but have cast doubt on the role of GALT. However, the design of many genetic and epidemiological studies has been inadequate with respect to sample size, consistency in phenotype definition, and the choice of control populations. These features are likely to influence results, and could partly explain the lack of consistency in the findings. Future studies should use a consistent disease definition and be of appropriate epidemiological design.

Introduction Fetal haemoglobin (Hb F) and fetal cell (FC) levels in adults show considerable variation and the heritability of FC levels has been estimated to be 89% in the healthy European population; measured genotype analyses have shown the trait to be influenced by several genetic factors. In addition to the β-globin gene complex on chromosome 11p, linkage analyses have reported loci affecting FC levels on chromosomes Xp22.2–p22.3 and 6q23. Methods We have genotyped a sample of approximately 300 unselected, same sex, dizygotic twin pairs from the St. Thomas’ UK Adult Twin Register for markers in these three regions and carried out a linkage analysis of FC levels. We also used a new method to simultaneously test for linkage and allelic association, and association caused by population stratification or admixture. Results There was no evidence for linkage of FC levels to chromosomes Xp22.2–p22.3 and 6q23. However, the β-globin cluster was shown to be significantly linked and to be responsible for approximately one-third of the additive genetic variance in FC levels in the sample. Conclusions The report represents the first application of this method to a sample of nonsimulated data and demonstrates the effectiveness of the approach. Combined linkage and association analysis of the β-globin complex showed a strong association between the XmnI-Gγ site and FC levels and that the observed association is not an artifact of recent population admixture or stratification.

Background: A German genome-wide nonsynonymous single nucleotide polymorphism (nsSNP) association study identified ATG16L1 as a Crohn's disease (CD) susceptibility gene. The association appeared to be confined to the nsSNP rs2241880 and was confirmed in 2 German independent case-control collections (combined P = 4.0 × 10−8, odds ratio [OR] 1.45; 95% confidence interval [CI]: 1.21-1.74), a CD transmission disequilibrium test (TDT) collection, and an independent UK cohort. A weak statistical interaction with CARD15 was demonstrated. No association with ulcerative colitis (UC) was demonstrated. The aims of the study were to replicate the association with CD, examine subphenotype associations and statistical interactions with CARD15, IL23R, and the IBD5 risk haplotype, as well as explore the association with UC. Methods: The study included 645 CD and 676 UC rigorously phenotyped patients recruited from a single UK center. Unaffected controls comprised either spouses of patients (141) or individuals recruited from well-person clinics (1049). The nsSNP rs2241880 was genotyped using MassArray (Sequenom). Results: A strong association with CD was demonstrated (P = 2.33 × 10−7, OR 1.45 [1.25–1.67]), but no significant association was demonstrated with any subphenotype. We failed to replicate the reported interaction between rs2241880 and the CARD15 low-risk haplotypes dd and Dd. No significant statistical interaction with the 3 known CD susceptibility genes was seen. No association with UC susceptibility (P = 0.37, OR 1.06 [0.93-1.22]), or any UC subphenotype was identified. Conclusions: We confirmed the findings that ATG16L1 is a CD susceptibility gene and found no evidence of interaction with CARD15, IL23R, or IBD5. (Inflamm Bowel Dis 2007)

The goal of the International HapMap Project is to determine the common patterns of DNA sequence variation in the human genome and to make this information freely available in the public domain. An international consortium is developing a map of these patterns across the genome by determining the genotypes of one million or more sequence variants, their frequencies and the degree of association between them, in DNA samples from populations with ancestry from parts of Africa, Asia and Europe. The HapMap will allow the discovery of sequence variants that affect common disease, will facilitate development of diagnostic tools, and will enhance our ability to choose targets for therapeutic intervention. © 2003 Nature Publishing Group.

Genetic studies in inflammatory bowel disease have identified multiple susceptibility loci, whose relevance depends critically on verification in independent cohorts. Genetic variants associated with Crohn's disease have now been identified on chromosomes 5 (IBD5/5q31 risk haplotype) and 16 (IBD1 locus, CARD15/NOD2 mutations). Stratification of genome-wide linkage analyses by disease associated variants is now possible, offering both increased power for identification of other loci and improved understanding of genetic mechanisms. We performed a genome-wide scan of 137 Crohn's disease affected relative pairs from 112 families. Multipoint non-parametric linkage analyses were performed, with further stratification of affection status by common CARD15 mutations and the IBD5 haplotype. We verified linkage of Crohn's disease to regions on chromosome 3 (P=0.0009) and X (P=0.001) in our cohort. Linkage to chromosome 16 (IBD1) was observed in Crohn's disease pairs not possessing common CARD15 mutations (P=0.0007), approximately 25 cM q telomeric of CARD15. Evidence for linkage to chromosome 19 (IBD6) was observed in Crohn's disease pairs not possessing CARD15 mutations (P=0.0001), and in pairs possessing one or two copies of the IBD5 risk haplotype (P=0.0005), with significant evidence for genetic heterogeneity and epistasis, respectively. These analyses demonstrate the complex genetic basis to Crohn's disease, and show that the discovery of disease-causing variants may be used to aid identification of further susceptibility loci in complex disease.

Genome-wide association studies have identified hundreds of genetic variants associated with complex human diseases and traits, and have provided valuable insights into their genetic architecture. Most variants identified so far confer relatively small increments in risk, and explain only a small proportion of familial clustering, leading many to question how the remaining, ‘missing’ heritability can be explained. Here we examine potential sources of missing heritability and propose research strategies, including and extending beyond current genome-wide association approaches, to illuminate the genetics of complex diseases and enhance its potential to enable effective disease prevention or treatment.

The proteasome system is a proteolytic pathway that regulates the expression of genes involved in inflammation. Polymorphisms in the gene encoding subunit alpha type 6 (PSMA6)--in particular the rs1048990 exon 1-8C/G SNP--have been implicated with susceptibility to myocardial infarction (MI) in a Japanese study. We examined whether several polymorphisms in the PSMA6 gene were related to MI risk in 6946 nonfatal MI cases and 2720 unrelated controls in a UK population. The homozygous GG genotype for rs1048990 was much less frequent in this UK population than in the Japanese population (2.1 vs 8.9%), and was associated with an odds ratio (OR) for MI of 1.09 (95% confidence interval (CI): 0.98-1.21) per G allele in a co-dominant genetic model and 1.32 (95% CI: 0.90-1.93) in a recessive genetic model. Although not statistically significant, these results for this variant are still consistent with the Japanese hypothesis-generating study. Our findings, when taken together with four other studies (including the hypothesis-generating one), yielded a combined OR for MI of 1.15 (95% CI: 1.08-1.21) per G allele in a co-dominant model and 1.38 (95% CI: 1.22-1.57) for the GG genotype in a recessive model. Larger studies involving more than 10,000 disease cases would be required to further elucidate the role of this variant for susceptibility to MI. However, given the rarity of this variant in Caucasians, the attributable risk of rs1048990 for MI is unlikely to be great in western populations.

The first Crohn's disease (CD) susceptibility gene identified was CARD15, which is a member of the emerging NOD-like receptor (NLR) family. These function as intracellular cystosolic pattern recognition receptors (PRRs) and play a central role in the innate immune response. We studied other members of the NLR family using a gene-wide haplotype tagging approach in a well-characterised collection of 547 CD patients and 465 controls. Four single nucleotide polymorphisms (SNPs) in NLRP3 had P values < 0.05 and are in high linkage disequilibrium (LD) with each other (r(2) > 0.90 for all four SNPs). rs4925648 and rs10925019 were the most strongly associated with CD susceptibility (P = 0.001, odds ratio (OR) 1.62, 95% CI 1.2-2.18; and P = 6.5 x 10(-4), OR 1.65, 95% CI 1.23-2.19, respectively). rs1363758 located in NLRP11 was associated with CD susceptibility [P = 0.002 (1.64, 1.19-2.25)], which was weakly confirmed in an independent case-cohort collection on joint analysis [P = 0.05, (1.28, 1-1.64)]. On sub-phenotype analysis, an interesting association between NLRP1 and skin extra-intestinal manifestations and colonic, inflammatory CD was identified. None of these results was replicated in the Wellcome Trust Case Control Consortium study and therefore need replication in a further large cohort.

The International Haplotype Mapping Project (HapMap) aims to characterize the distribution and extent of linkage disequilibrium (LD) throughout the human genome, thereby facilitating genome-wide association analysis and the search for the genetic determinants of complex diseases. Implicit in the rationale behind the project is the expectation that hidden (unobserved) disease-causing variants will be in significant LD with surrounding typed markers and will thus be amenable to detection using association-based mapping approaches. In order to investigate the validity of this assumption, we examined more than 5,000 SNPs across a 10-MB region of chromosome 20 in a sample of 96 unrelated African-American and 96 unrelated Caucasian individuals. We treated observed loci as surrogates for hidden SNPs by pretending that individuals' genotypes were unknown. We then attempted to predict these genotypes at the surrogate hidden SNP by using information about LD in the region and genotypes at surrounding observed loci. Our method is based on finding the most likely genotype for each individual, given all possible haplotype pairs consistent with observed genotypes for that individual at surrounding loci, and given the frequencies of those haplotypes in an independent sample. Our method performs extremely well in predicting genotypes in areas of high LD. Furthermore, in areas of low LD, our method results in substantial gains in predictive accuracy as compared to pair-wise strategies. These results suggest that pair-wise tests of disease-marker association may be inferior to multipoint methods, which take advantage of the information contained within multi-locus haplotypes.

Tumour necrosis factor-alpha (TNF) expression is increased in inflammatory bowel disease (IBD), and TNF maps to the IBD3 susceptibility locus. Transmission disequilibrium and case-control analyses, in two independent Caucasian cohorts, showed a novel association of the TNF(-857C) promoter polymorphism with IBD (overall P=0.001 in 587 IBD families). Further genetic associations of TNF(-857C) with IBD sub-phenotypes were seen for ulcerative colitis and for Crohn's disease, but only in patients not carrying common NOD2 mutations. The genetic data suggest a recessive model of inheritance, and we observed ex vivo lipopolysaccharide-stimulated whole-blood TNF production to be higher in healthy TNF(-857C) homozygotes. We show the transcription factor OCT1 binds TNF(-857T) but not TNF(-857C), and interacts in vitro and in vivo with the pro-inflammatory NF(-kappa)B transcription factor p65 subunit at an adjacent binding site. Detailed functional analyses of these interactions in gut macrophages, in addition to further genetic mapping of this gene-dense region, will be critical to understand the significance of the observed association of TNF(-857C) with IBD.

A Deep Look Into Our Genes Recent debates have focused on the degree of genetic variation and its impact upon health at the genomic level in humans (see the Perspective by Casals and Bertranpetit ). Tennessen et al. (p. 64 , published online 17 May), looking at all of the protein-coding genes in the human genome, and Nelson et al. (p. 100 , published online 17 May), looking at genes that encode drug targets, address this question through deep sequencing efforts on samples from multiple individuals. The findings suggest that most human variation is rare, not shared between populations, and that rare variants are likely to play a role in human health.

Genetic variation in LRRK2 predisposes to Parkinson disease (PD), which underpins its development as a therapeutic target. Here, we aimed to identify novel genotype-phenotype associations that might support developing LRRK2 therapies for other conditions. We sequenced the 51 exons of LRRK2 in cases comprising 12 common diseases (n = 9,582), and in 4,420 population controls. We identified 739 single nucleotide variants (SNVs), 62% of which were observed in only one person, including 316 novel exonic variants. We found evidence of purifying selection for the LRRK2 gene and a trend suggesting that this is more pronounced in the central (ROC-COR-kinase) core protein domains of LRRK2 than the flanking domains. Population genetic analyses revealed that LRRK2 is not especially polymorphic or differentiated in comparison to 201 other drug target genes. Amongst Europeans, we identified 17 carriers (0.13%) of pathogenic LRRK2 mutations that were not significantly enriched within any disease or in those reporting a family history of PD. Analysis of pathogenic mutations within Europe reveals that the p.Arg1628Pro (c4883G>C) mutation arose independently in Europe and Asia. Taken together, these findings demonstrate how targeted deep sequencing can help to reveal fundamental characteristics of clinically important loci.

Malaria is a devastating infection caused by protozoa of the genus Plasmodium. Drug resistance is widespread, no new chemical class of antimalarials has been introduced into clinical practice since 1996 and there is a recent rise of parasite strains with reduced sensitivity to the newest drugs. We screened nearly 2 million compounds in GlaxoSmithKline's chemical library for inhibitors of P. falciparum, of which 13,533 were confirmed to inhibit parasite growth by at least 80% at 2 microM concentration. More than 8,000 also showed potent activity against the multidrug resistant strain Dd2. Most (82%) compounds originate from internal company projects and are new to the malaria community. Analyses using historic assay data suggest several novel mechanisms of antimalarial action, such as inhibition of protein kinases and host-pathogen interaction related targets. Chemical structures and associated data are hereby made public to encourage additional drug lead identification efforts and further research into this disease.

Association studies can focus on candidate gene(s), a particular genomic region, or adopt a genome-wide association approach, each of which has implications for marker selection. The strategy for marker selection will affect the statistical power of the study to detect a disease association and is a crucial element of study design. The abundant single nucleotide polymorphisms (SNPs) are the markers of choice in genetic case-control association studies. The genotypes of neighboring SNPs are often highly correlated ('in linkage disequilibrium', LD) within a population, which is utilized for selecting specific 'tagSNPs' to serve as proxies for other nearby SNPs in high LD. General guidelines for SNP selection in candidate genes/regions and genome-wide studies are provided in this protocol, along with illustrative examples. Publicly available web-based resources are utilized to browse and retrieve data, and software, such as Haploview and Goldsurfer2, is applied to investigate LD and to select tagSNPs.

The instability of the CAG repeat size of the HD gene when transmitted intergenerationally has critical implications for genetic counseling practices. In particular, CAG repeats between 27 and 35 have been the subject of debate based on small samples. To address this issue, we analyzed allelic instability in the Venezuelan HD kindreds, the largest and most informative families ascertained for HD. We identified 647 transmissions. Our results indicate that repeats in the 27-35 CAG range are highly stable. Out of 69 transmitted alleles in this range, none expand into any penetrant ranges. Contrastingly, 14% of alleles transmitted from the incompletely penetrant range (36-39 CAGs) expand into the completely penetrant range, characterized by alleles with 40 or more CAG repeats. At least 12 of the 534 transmissions from the completely penetrant range contract into the incompletely penetrant range of 36-39 CAG repeats. In these kindreds, none of the individuals with 27-39 CAGs were symptomatic, even though they ranged in age from 11 to 82 years. We expect these findings to be helpful in updating genetic counseling practices.

Association replication studies have a poor track record and, even when successful, often claim association with different markers, alleles, and phenotypes than those reported in the primary study. It is unknown whether these outcomes reflect genuine associations or false-positive results. A greater understanding of these observations is essential for genomewide association (GWA) studies, since they have the potential to identify multiple new associations that that will require external validation. Theoretically, a repeat association with precisely the same variant in an independent sample is the gold standard for replication, but testing additional variants is commonplace in replication studies. Finding different associated SNPs within the same gene or region as that originally identified is often reported as confirmatory evidence. Here, we compare the probability of replicating a gene or region under two commonly used marker-selection strategies: an “exact” approach that involves only the originally significant markers and a “local” approach that involves both the originally significant markers and others in the same region. When a region of high intermarker linkage disequilibrium is tested to replicate an initial finding that is only weak association with disease, the local approach is a good strategy. Otherwise, the most powerful and efficient strategy for replication involves testing only the initially identified variants. Association with a marker other than that originally identified can occur frequently, even in the presence of real effects in a low-powered replication study, and instances of such association increase as the number of included variants increases. Our results provide a basis for the design and interpretation of GWA replication studies and point to the importance of a clear distinction between fine mapping and replication after GWA.

What constitutes replication of a genotype–phenotype association, and how best can it be achieved?

Transmission distortion refers to deviation from the normal 50:50 transmission of alleles from parents to offspring. Identification of genomic regions which undergo distortion is necessary for the correct interpretation of linkage and association studies, since tests of linkage using affected relative pairs and family based tests of association will yield spurious results in the presence of transmission distortion. With the increasing availability of genome-wide high density SNP data (e.g. from the International HapMap project), identification of these loci is now a real possibility. Here we present an analytical formula which demonstrates that the power to detect transmission distortion is a simple function of the number of heterozygous parents in the sample and the level of distortion at the locus. Our results indicate that whilst it will be possible to identify loci undergoing major levels of distortion using tens or hundreds of trios, large sample sizes in the order of tens of thousands of trios will be necessary to detect minor levels of distortion with appreciable power. The corollary is that genome-wide searches are unlikely to identify loci where the level of distortion is small, although they may serve to identify interesting regions worthy of follow up.

In the search for common genetic variants that contribute to prevalent human diseases, patterns of linkage disequilibrium (LD) among linked markers should be considered when selecting SNPs. Genotyping efficiency can be increased by choosing tagging SNPs (tagSNPs) in LD with other SNPs. However, it remains to be seen whether tagSNPs defined in one population efficiently capture LD in other populations; that is, how portable tagSNPs are. Indeed, tagSNP portability is a challenge for the applicability of HapMap results. We analyzed 144 SNPs in a 1-Mb region of chromosome 22 in 1055 individuals from 38 worldwide populations, classified into seven continental groups. We measured tagSNP portability by choosing three reference populations (to approximate the three HapMap populations), defining tagSNPs, and applying them to other populations independently on the availability of information on the tagSNPs in the compared population. We found that tagSNPs are highly informative in other populations within each continental group. Moreover, tagSNPs defined in Europeans are often efficient for Middle Eastern and Central/South Asian populations. TagSNPs defined in the three reference populations are also efficient for more distant and differentiated populations (Oceania, Americas), in which the impact of their special demographic history on the genetic structure does not interfere with successfully detecting the most common haplotype variation. This high degree of portability lends promise to the search for disease association in different populations, once tagSNPs are defined in a few reference populations like those analyzed in the HapMap initiative.

As part of a recent high-density linkage disequilibrium (LD) study of chromosome 20, we obtained genotypes for ∼30,000 SNPs at a density of 1 SNP/2 kb on four different population samples (47 CEPH founders; 91 UK unrelateds [unrelated white individuals of western European ancestry]; 97 African Americans; 42 East Asians). We observed that ∼50% of SNPs had at least one genetically indistinguishable partner; i.e., for every individual considered, their genotype at the first locus was identical to their genotype at the second locus, or in LD terms, the SNPs were in “perfect” LD (r2 = 1.0). These “genetically indistinguishable SNPs” (giSNPs) formed into clusters of varying size. The larger the cluster, the greater the tendency to be located within genes and to overlap with giSNP clusters in other population samples. As might be expected for this map density, many giSNPs were located close to one another, thus reflecting local regions of undetected recombination or haplotype blocks. However, ∼1/3 of giSNP clusters had intermingled, non-indistinguishable SNPs with incomplete LD (D′ and r2

Inherited genetic variation has a critical but as yet largely uncharacterized role in human disease. Here we report a public database of common variation in the human genome: more than one million single nucleotide polymorphisms (SNPs) for which accurate and complete genotypes have been obtained in 269 DNA samples from four populations, including ten 500-kilobase regions in which essentially all information about common DNA variation has been extracted. These data document the generality of recombination hotspots, a block-like structure of linkage disequilibrium and low haplotype diversity, leading to substantial correlations of SNPs with many of their neighbours. We show how the HapMap resource can guide the design and analysis of genetic association studies, shed light on structural variation and recombination, and identify loci that may have been subject to natural selection during human evolution. © 2005 Nature Publishing Group., link_to_OA_fulltext

Recent large-scale studies of common genetic variation throughout the human genome are making it feasible to conduct whole genome studies of genotype–phenotype associations. Such studies have the potential to uncover novel contributors to common complex traits and thus lead to insights into the aetiology of multifactorial phenotypes. Despite this promise, it is important to recognize that the availability of genetic markers and the ability to assay them at realistic cost does not guarantee success of this approach. There are a number of practical issues that require close attention, some forms of allelic architecture are not readily amenable to the association approach with even the most rigorous design, and doubtless new hurdles will emerge as the studies begin. Here we discuss the promise and current challenges of the whole genome approach, and raise some issues to consider in interpreting the results of the first whole genome studies.

Autoimmune, inflammatory, and infectious diseases present a major burden to human health and are frequently associated with loci in the human major histocompatibility complex (MHC). Here, we report a high-resolution (1.9 kb) linkage-disequilibrium (LD) map of a 4.46-Mb fragment containing the MHC in U.S. pedigrees with northern and western European ancestry collected by the Centre d'Etude du Polymorphisme Humain (CEPH) and the first generation of haplotype tag single-nucleotide polymorphisms (tagSNPs) that provide up to a fivefold increase in genotyping efficiency for all future MHC-linked disease-association studies. The data confirm previously identified recombination hotspots in the class II region and allow the prediction of numerous novel hotspots in the class I and class III regions. The region of longest LD maps outside the classic MHC to the extended class I region spanning the MHC-linked olfactory-receptor gene cluster. The extended haplotype homozygosity analysis for recent positive selection shows that all 14 outlying haplotype variants map to a single extended haplotype, which most commonly bears HLA-DRB1*1501. The SNP data, haplotype blocks, and tagSNPs analysis reported here have been entered into a multidimensional Web-based database (GLOVAR), where they can be accessed and viewed in the context of relevant genome annotation. This LD map allowed us to give coordinates for the extremely variable LD structure underlying the MHC.

After nearly 10 years of intense academic and commercial research effort, large genome-wide association studies for common complex diseases are now imminent. Although these conditions involve a complex relationship between genotype and phenotype, including interactions between unlinked loci1, the prevailing strategies for analysis of such studies focus on the locus-by-locus paradigm. Here we consider analytical methods that explicitly look for statistical interactions between loci. We show first that they are computationally feasible, even for studies of hundreds of thousands of loci, and second that even with a conservative correction for multiple testing, they can be more powerful than traditional analyses under a range of models for interlocus interactions. We also show that plausible variations across populations in allele frequencies among interacting loci can markedly affect the power to detect their marginal effects, which may account in part for the well-known difficulties in replicating association results. These results suggest that searching for interactions among genetic loci can be fruitfully incorporated into analysis strategies for genome-wide association studies.

Genomewide linkage scans have traditionally employed panels of microsatellite markers spaced at intervals of approximately 10 cM across the genome. However, there is a growing realization that a map of closely spaced single-nucleotide polymorphisms (SNPs) may offer equal or superior power to detect linkage, compared with low-density microsatellite maps. We performed a series of simulations to calculate the information content associated with microsatellite and SNP maps across a range of different marker densities and heterozygosities for sib pairs (with and without parental genotypes), sib trios, and sib quads. In the case of microsatellite markers, we varied density across 11 levels (1 marker every 0.5, 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 cM) and marker heterozygosity across 6 levels (2, 3, 4, 5, 10, or 20 equally frequent alleles), whereas, in the case of SNPs, we varied marker density across 4 levels (1 marker every 0.1, 0.2, 0.5, or 1 cM) and minor-allele frequency across 7 levels (0.5, 0.4, 0.3, 0.2, 0.1, 0.05, and 0.01). When parental genotypes were available, a map consisting of microsatellites spaced every 2 cM or a relatively sparse map of SNPs (i.e., at least 1 SNP/cM) was sufficient to extract most of the inheritance information from the map (95% in most cases). However, when parental genotypes were unavailable, it was important to use as dense a map of markers as possible to extract the greatest amount of inheritance information. It is important to note that the information content associated with a traditional map of microsatellite markers (i.e., 1 marker every ~10 cM) was significantly lower than the information content associated with a dense map of SNPs or microsatellites. These results strongly suggest that previous linkage studies that employed sparse microsatellite maps could benefit substantially from reanalysis by use of a denser map of markers.

Haplotype tagging is a means of retaining most of the information in high density marker maps, while reducing genotyping requirements. Estimates of the numbers of tagging SNPs required to cover the human genome have varied widely, ranging from 100,000 to 1,000,000. Tagging has been applied to a number of gene-based datasets but has not been evaluated in contexts reflecting those of genome-wide association studies--large chromosome regions and multiple samples drawn from the same population. We analysed 5000 common markers across a 10 Mb segment of human chromosome 20 in three samples (UK Caucasian, CEPH Caucasian, African American) to evaluate tagging efficiency and consistency. Overall, the results indicate a high degree of efficiency, yielding 3-5-fold savings in Caucasians and 2-3-fold savings in African Americans. These levels varied according to linkage disequilibrium (LD) levels, tagging thresholds and allele frequencies, but in high LD regions they did not vary markedly due to marker density. However, a strong positive relationship between marker density and tagging was observed, relating to the fact that increasing marker density yields greater sequence coverage in high LD, thus requiring more tag SNPs to cover a greater fraction of the genome. Encouragingly, whatever the density employed, a high level of robustness was observed between UK and CEPH samples, as most of the htSNPs selected in one sample were also appropriate as tags in the other.

The design and feasibility of genetic studies of complex diseases are critically dependent on the extent and distribution of linkage disequilibrium (LD) across the genome and between different populations. We have examined genomewide and region-specific LD in a young genetically isolated population identified in the Netherlands by genotyping approximately 800 Short Tandem Repeat markers distributed genomewide across 58 individuals. Several regions were analyzed further using a denser marker map. The permutation-corrected measure of LD was used for analysis. A significant (P

Large-scale association studies hold substantial promise for unraveling the genetic basis of common human diseases. A well-known problem with such studies is the presence of undetected population structure, which can lead to both false positive results and failures to detect genuine associations. Here we examine approximately 15,000 genome-wide single-nucleotide polymorphisms typed in three population groups to assess the consequences of population structure on the coming generation of association studies. The consequences of population structure on association outcomes increase markedly with sample size. For the size of study needed to detect typical genetic effects in common diseases, even the modest levels of population structure within population groups cannot safely be ignored. We also examine one method for correcting for population structure (Genomic Control). Although it often performs well, it may not correct for structure if too few loci are used and may overcorrect in other settings, leading to substantial loss of power. The results of our analysis can guide the design of large-scale association studies.

BACKGROUND: Endometriosis occurs in several non-human primate species that have menstrual cycles. This study investigated the prevalence and familial aggregation of endometriosis in one of those species, the rhesus macaque. METHODS: Between 1978 and 2001, 142 animals with endometriosis were identified from necropsy and surgical records and through the use of magnetic resonance imaging (MRI) at the Wisconsin National Primate Research Center, Madison, USA. All cases were used to build one large multigenerational pedigree and nine nuclear families comprising 1602 females in total. By 2002, the pedigrees contained 124 cases diagnosed at necropsy; 17 at surgery and three at MRI. Female animals that had died aged > or = 10 years without endometriosis, had both ovaries until at least 1 year prior to death, and had a full necropsy, were considered unaffected. RESULTS: The prevalence of endometriosis among necropsied animals aged > or = 10 years in the colony was 31.4% [95% confidence interval (CI) 26.9-35.9%]; prevalence increased with rising age and calendar age at death. Familial aggregation of endometriosis was strongly suggested by a significantly higher average kinship coefficient among affecteds compared with unaffecteds (P < 0.001) and a higher recurrence risk for full sibs (0.75; 95% CI 0.45-1.0) compared with maternal half sibs (0.26; 95% CI 0.10-0.41) and paternal half sibs (0.18; 95% CI 0.02-0.34). The segregation ratio among affected mothers (44.2%) was not significantly higher compared with unaffected mothers (36.6%). CONCLUSIONS: The results support familial aggregation of endometriosis in the rhesus macaque, and indicate that this is a promising animal model for the investigation of mode of inheritance, the location of potential genetic susceptibility loci and the influence of environmental factors.

Linkage disequilibrium (LD) is a measure of the degree of association between alleles in a population. The detection of disease-causing variants by association with neighbouring single nucleotide polymorphisms (SNPs) depends on the existence of strong LD between them. Previous studies have indicated that the extent of LD is highly variable in different chromosome regions and different populations, demonstrating the importance of genome-wide accurate measurement of LD at high resolution throughout the human genome. A uniform feature of these studies has been the inability to detect LD in regions of low marker density. To investigate the dependence of LD patterns on marker selection we performed a high-resolution study in African-American, Asian and UK Caucasian populations. We selected over 5000 SNPs with an average spacing of approximately 1 SNP per 2 kb after validating ca 12 000 SNPs derived from a dense SNP collection (1 SNP per 0.3 kb on average). Applications of different statistical methods of LD assessment highlight similar areas of high and low LD. However, at high resolution, features such as overall sequence coverage in LD blocks and block boundaries vary substantially with respect to marker density. Model-based linkage disequilibrium unit (LDU) maps appear robust to marker density and consistently influenced by marker allele frequency. The results suggest that very dense marker sets will be required to yield stable views of fine-scale LD in the human genome.

Lipoprotein-associated phospholipase A2 (Lp-PLA2) produces the proinflammatory mediators lysophosphatidylcholine and oxidized free fatty acids through hydrolysis of oxidized phospholipids carried on low-density lipoproteins in atherosclerotic plaques. Although increased Lp-PLA2 activity has been associated with higher risks of occlusive vascular diseases, recent phase III trials of the Lp-PLA2 inhibitor darapladib, which reduces Lp-PLA2 activity by ∼60%, failed to establish a protective role of darapladib for prevention of major vascular events in patients with stable coronary heart disease (CHD) or acute coronary syndrome 1, 2.