Evaluating the contribution of rare variants to type 2 diabetes and related traits using pedigrees.

A major challenge in evaluating the contribution of rare variants to complex disease is identifying enough copies of the rare alleles to permit informative statistical analysis. To investigate the contribution of rare variants to the risk of type 2 diabetes (T2D) and related traits, we performed deep whole-genome analysis of 1,034 members of 20 large Mexican-American families with high prevalence of T2D. If rare variants of large effect accounted for much of the diabetes risk in these families, our experiment was powered to detect association. Using gene expression data on 21,677 transcripts for 643 pedigree members, we identified evidence for large-effect rare-variant cis-expression quantitative trait loci that could not be detected in population studies, validating our approach. However, we did not identify any rare variants of large effect associated with T2D, or the related traits of fasting glucose and insulin, suggesting that large-effect rare variants account for only a modest fraction of the genetic risk of these traits in this sample of families. Reliable identification of large-effect rare variants will require larger samples of extended pedigrees or different study designs that further enrich for such variants.

Evaluating and improving power in whole-genome association studies using fixed marker sets.

Emerging technologies make it possible for the first time to genotype hundreds of thousands of SNPs simultaneously, enabling whole-genome association studies. Using empirical genotype data from the International HapMap Project, we evaluate the extent to which the sets of SNPs contained on three whole-genome genotyping arrays capture common SNPs across the genome, and we find that the majority of common SNPs are well captured by these products either directly or through linkage disequilibrium. We explore analytical strategies that use HapMap data to improve power of association studies conducted with these fixed sets of markers and show that limited inclusion of specific haplotype tests in association analysis can increase the fraction of common variants captured by 25-100%. Finally, we introduce a Bayesian approach to association analysis by weighting the likelihood of each statistical test to reflect the number of putative causal alleles to which it is correlated.

Common variation in three genes, including a noncoding variant in CFH, strongly influences risk of age-related macular degeneration.

Age-related macular degeneration (AMD) is a common, late-onset disease with seemingly typical complexity: recurrence ratios for siblings of an affected individual are three- to sixfold higher than in the general population, and family-based analysis has resulted in only modestly significant evidence for linkage. In a case-control study drawn from a US-based population of European descent, we have identified a previously unrecognized common, noncoding variant in CFH, the gene encoding complement factor H, that substantially increases the influence of this locus on AMD, and we have strongly replicated the associations of four other previously reported common alleles in three genes (P values ranging from 10(-6) to 10(-70)). Despite excellent power to detect epistasis, we observed purely additive accumulation of risk from alleles at these genes. We found no differences in association of these loci with major phenotypic categories of advanced AMD. Genotypes at these five common SNPs define a broad spectrum of interindividual disease risk and explain about half of the classical sibling risk of AMD in our study population.

Systematic haplotype analysis resolves a complex plasma plant sterol locus on the Micronesian Island of Kosrae.

Pinpointing culprit causal variants along signal peaks of genome-wide association studies (GWAS) is challenging. To overcome confounding effects of multiple independent variants at such a locus and narrow the interval for causal allele capture, we developed an approach that maps local shared haplotypes harboring a putative causal variant. We demonstrate our method in an extreme isolate founder population, the pacific Island of Kosrae. We analyzed plasma plant sterol (PPS) levels, a surrogate measure of cholesterol absorption from the intestine, where previous studies have implicated 2p21 mutations in the ATP binding cassette subfamily G members 5 or 8 (ABCG5 or ABCG8) genes. We have previously reported that 11.1% of the islanders are carriers of a frameshift ABCG8 mutation increasing PPS levels in carriers by 50%. GWAS adjusted for this mutation revealed genomewide significant signals along 11 Mb around it. To fine-map this signal, we detected pairwise identity-by-descent haplotypes using our tool GERMLINE and implemented a clustering algorithm to identify haplotypes shared across multiple samples with their unique shared boundaries. A single 526-kb haplotype mapped strongly to PPS levels, dramatically refining the mapped interval. This haplotype spans the ABCG5/ABCG8 genes, is carried by 1.8% of the islanders, and results in a striking 100% increase of PPS in carriers. Resequencing of ABCG5 in these carriers found a D450H missense mutation along the associated haplotype. These findings exemplify the power of haplotype analysis for mapping mutations in isolated populations and specifically for dissecting effects of multiple variants of the same locus.

Genome-wide association studies in an isolated founder population from the Pacific Island of Kosrae.

It has been argued that the limited genetic diversity and reduced allelic heterogeneity observed in isolated founder populations facilitates discovery of loci contributing to both Mendelian and complex disease. A strong founder effect, severe isolation, and substantial inbreeding have dramatically reduced genetic diversity in natives from the island of Kosrae, Federated States of Micronesia, who exhibit a high prevalence of obesity and other metabolic disorders. We hypothesized that genetic drift and possibly natural selection on Kosrae might have increased the frequency of previously rare genetic variants with relatively large effects, making these alleles readily detectable in genome-wide association analysis. However, mapping in large, inbred cohorts introduces analytic challenges, as extensive relatedness between subjects violates the assumptions of independence upon which traditional association test statistics are based. We performed genome-wide association analysis for 15 quantitative traits in 2,906 members of the Kosrae population, using novel approaches to manage the extreme relatedness in the sample. As positive controls, we observe association to known loci for plasma cholesterol, triglycerides, and C-reactive protein and to a compelling candidate loci for thyroid stimulating hormone and fasting plasma glucose. We show that our study is well powered to detect common alleles explaining >/=5% phenotypic variance. However, no such large effects were observed with genome-wide significance, arguing that even in such a severely inbred population, common alleles typically have modest effects. Finally, we show that a majority of common variants discovered in Caucasians have indistinguishable effect sizes on Kosrae, despite the major differences in population genetics and environment.

Evoker: a visualization tool for genotype intensity data.

SUMMARY: Genome-wide association studies (GWAS), which produce huge volumes of data, are now being carried out by many groups around the world, creating a need for user-friendly tools for data quality control (QC) and analysis. One critical aspect of GWAS QC is evaluating genotype cluster plots to verify sensible genotype calling in putatively associated single nucleotide polymorphisms (SNPs). Evoker is a tool for visualizing genotype cluster plots, and provides a solution to the computational and storage problems related to working with such large datasets. AVAILABILITY: http://www.sanger.ac.uk/resources/software/evoker/

Common SNPs in HMGCR in micronesians and whites associated with LDL-cholesterol levels affect alternative splicing of exon13.

UNLABELLED: Background- Variation in LDL-cholesterol (LDL-C) among individuals is a complex genetic trait involving multiple genes and gene-environment interactions. METHODS AND RESULTS: In a genome-wide association study (GWAS) to identify genetic variants influencing LDL-C in an isolated population from Kosrae, we observed associations for SNPs in the gene encoding 3hydroxy-3-methylglutaryl (HMG)-coenzyme A (CoA) reductase (HMGCR). Three of these SNPs (rs7703051, rs12654264, and rs3846663) met the statistical threshold of genome-wide significance when combined with data from the Diabetes Genetics Initiative GWAS. We followed up the association results and identified a functional SNP in intron13 (rs3846662), which was in linkage disequilibrium with the SNPs of genome-wide significance and affected alternative splicing of HMGCR mRNA. In vitro studies in human lymphoblastoid cells demonstrated that homozygosity for the rs3846662 minor allele was associated with up to 2.2-fold lower expression of alternatively spliced HMGCR mRNA lacking exon13, and minigene transfection assays confirmed that allele status at rs3846662 directly modulated alternative splicing of HMGCR exon13 (42.9+/-3.9 versus 63.7+/-1.0%Deltaexon13/total HMGCR mRNA, P=0.02). Further, the alternative splice variant could not restore HMGCR activity when expressed in HMGCR deficient UT-2 cells. CONCLUSIONS: We identified variants in HMGCR that are associated with LDL-C across populations and affect alternative splicing of HMGCR exon13.

Autism spectrum disorder and attention deficit hyperactivity disorder have a similar burden of rare protein-truncating variants.

The exome sequences of approximately 8,000 children with autism spectrum disorder (ASD) and/or attention deficit hyperactivity disorder (ADHD) and 5,000 controls were analyzed, finding that individuals with ASD and individuals with ADHD had a similar burden of rare protein-truncating variants in evolutionarily constrained genes, both significantly higher than controls. This motivated a combined analysis across ASD and ADHD, identifying microtubule-associated protein 1A (MAP1A) as a new exome-wide significant gene conferring risk for childhood psychiatric disorders.

Identification of common genetic risk variants for autism spectrum disorder.

Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample-size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 individuals with ASD and 27,969 controls that identified five genome-wide-significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), we identified seven additional loci shared with other traits at equally strict significance levels. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis, and establish that GWAS performed at scale will be much more productive in the near term in ASD.

Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder.

Attention deficit/hyperactivity disorder (ADHD) is a highly heritable childhood behavioral disorder affecting 5% of children and 2.5% of adults. Common genetic variants contribute substantially to ADHD susceptibility, but no variants have been robustly associated with ADHD. We report a genome-wide association meta-analysis of 20,183 individuals diagnosed with ADHD and 35,191 controls that identifies variants surpassing genome-wide significance in 12 independent loci, finding important new information about the underlying biology of ADHD. Associations are enriched in evolutionarily constrained genomic regions and loss-of-function intolerant genes and around brain-expressed regulatory marks. Analyses of three replication studies: a cohort of individuals diagnosed with ADHD, a self-reported ADHD sample and a meta-analysis of quantitative measures of ADHD symptoms in the population, support these findings while highlighting study-specific differences on genetic overlap with educational attainment. Strong concordance with GWAS of quantitative population measures of ADHD symptoms supports that clinical diagnosis of ADHD is an extreme expression of continuous heritable traits.

Genome-wide association scan of quantitative traits for attention deficit hyperactivity disorder identifies novel associations and confirms candidate gene associations.

Attention deficit hyperactivity disorder (ADHD) is a complex condition with environmental and genetic etiologies. Up to this point, research has identified genetic associations with candidate genes from known biological pathways. In order to identify novel ADHD susceptibility genes, 600,000 SNPs were genotyped in 958 ADHD proband-parent trios. After applying data cleaning procedures we examined 429,981 autosomal SNPs in 909 family trios. We generated six quantitative phenotypes from 18 ADHD symptoms to be used in genome-wide association analyses. With the PBAT screening algorithm, we identified 2 SNPs, rs6565113 and rs552655 that met the criteria for significance within a specified phenotype. These SNPs are located in intronic regions of genes CDH13 and GFOD1, respectively. CDH13 has been implicated previously in substance use disorders. We also evaluated the association of SNPs from a list of 37 ADHD candidate genes that was specified a priori. These findings, along with association P-values with a magnitude less than 10(-5), are discussed in this manuscript. Seventeen of these candidate genes had association P-values lower then 0.01: SLC6A1, SLC9A9, HES1, ADRB2, HTR1E, DDC, ADRA1A, DBH, DRD2, BDNF, TPH2, HTR2A, SLC6A2, PER1, CHRNA4, SNAP25, and COMT. Among the candidate genes, SLC9A9 had the strongest overall associations with 58 association test P-values lower than 0.01 and multiple association P-values at a magnitude of 10(-5) in this gene. In sum, these findings identify novel genetic associations at viable ADHD candidate genes and provide confirmatory evidence for associations at previous candidate genes. Replication of these results is necessary in order to confirm the proposed genetic variants for ADHD.

Genome-wide association scan of attention deficit hyperactivity disorder.

Results of behavioral genetic and molecular genetic studies have converged to suggest that genes substantially contribute to the development of attention deficit/hyperactivity disorder (ADHD), a common disorder with an onset in childhood. Yet, despite numerous linkage and candidate gene studies, strongly consistent and replicable association has eluded detection. To search for ADHD susceptibility genes, we genotyped approximately 600,000 SNPs in 958 ADHD affected family trios. After cleaning the data, we analyzed 438,784 SNPs in 2,803 individuals comprising 909 complete trios using ADHD diagnosis as phenotype. We present the initial TDT findings as well as considerations for cleaning family-based TDT data. None of the SNP association tests achieved genome-wide significance, indicating that larger samples may be required to identify risk loci for ADHD. We additionally identify a systemic bias in family-based association, and suggest that variable missing genotype rates may be the source of this bias.

Genome-wide association scan of the time to onset of attention deficit hyperactivity disorder.

A time-to-onset analysis for family-based samples was performed on the genomewide association (GWAS) data for attention deficit hyperactivity disorder (ADHD) to determine if associations exist with the age at onset of ADHD. The initial dataset consisted of 958 parent-offspring trios that were genotyped on the Perlegen 600,000 SNP array. After data cleaning procedures, 429,981 autosomal SNPs and 930 parent-offspring trios were used found suitable for use and a family-based logrank analysis was performed using that age at first ADHD symptoms as the quantitative trait of interest. No SNP achieved genome-wide significance, and the lowest P-values had a magnitude of 10(-7). Several SNPs among a pre-specified list of candidate genes had nominal associations including SLC9A9, DRD1, ADRB2, SLC6A3, NFIL3, ADRB1, SYT1, HTR2A, ARRB2, and CHRNA4. Of these findings SLC9A9 stood out as a promising candidate, with nominally significant SNPs in six distinct regions of the gene.

High-Quality Exome Sequencing of Whole-Genome Amplified Neonatal Dried Blood Spot DNA.

Stored neonatal dried blood spot (DBS) samples from neonatal screening programmes are a valuable diagnostic and research resource. Combined with information from national health registries they can be used in population-based studies of genetic diseases. DNA extracted from neonatal DBSs can be amplified to obtain micrograms of an otherwise limited resource, referred to as whole-genome amplified DNA (wgaDNA). Here we investigate the robustness of exome sequencing of wgaDNA of neonatal DBS samples. We conducted three pilot studies of seven, eight and seven subjects, respectively. For each subject we analysed a neonatal DBS sample and corresponding adult whole-blood (WB) reference sample. Different DNA sample types were prepared for each of the subjects. Pilot 1: wgaDNA of 2x3.2mm neonatal DBSs (DBS_2x3.2) and raw DNA extract of the WB reference sample (WB_ref). Pilot 2: DBS_2x3.2, WB_ref and a WB_ref replica sharing DNA extract with the WB_ref sample. Pilot 3: DBS_2x3.2, WB_ref, wgaDNA of 2x1.6 mm neonatal DBSs and wgaDNA of the WB reference sample. Following sequencing and data analysis, we compared pairwise variant calls to obtain a measure of similarity--the concordance rate. Concordance rates were slightly lower when comparing DBS vs WB sample types than for any two WB sample types of the same subject before filtering of the variant calls. The overall concordance rates were dependent on the variant type, with SNPs performing best. Post-filtering, the comparisons of DBS vs WB and WB vs WB sample types yielded similar concordance rates, with values close to 100%. WgaDNA of neonatal DBS samples performs with great accuracy and efficiency in exome sequencing. The wgaDNA performed similarly to matched high-quality reference--whole-blood DNA--based on concordance rates calculated from variant calls. No differences were observed substituting 2x3.2 with 2x1.6 mm discs, allowing for additional reduction of sample material in future projects.

Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population.

Almost all genetic risk factors for autism spectrum disorders (ASDs) can be found in the general population, but the effects of this risk are unclear in people not ascertained for neuropsychiatric symptoms. Using several large ASD consortium and population-based resources (total n > 38,000), we find genome-wide genetic links between ASDs and typical variation in social behavior and adaptive functioning. This finding is evidenced through both LD score correlation and de novo variant analysis, indicating that multiple types of genetic risk for ASDs influence a continuum of behavioral and developmental traits, the severe tail of which can result in diagnosis with an ASD or other neuropsychiatric disorder. A continuum model should inform the design and interpretation of studies of neuropsychiatric disease biology.

Human genomics. Effect of predicted protein-truncating genetic variants on the human transcriptome.

Accurate prediction of the functional effect of genetic variation is critical for clinical genome interpretation. We systematically characterized the transcriptome effects of protein-truncating variants, a class of variants expected to have profound effects on gene function, using data from the Genotype-Tissue Expression (GTEx) and Geuvadis projects. We quantitated tissue-specific and positional effects on nonsense-mediated transcript decay and present an improved predictive model for this decay. We directly measured the effect of variants both proximal and distal to splice junctions. Furthermore, we found that robustness to heterozygous gene inactivation is not due to dosage compensation. Our results illustrate the value of transcriptome data in the functional interpretation of genetic variants.

A fine-scale chimpanzee genetic map from population sequencing.

To study the evolution of recombination rates in apes, we developed methodology to construct a fine-scale genetic map from high-throughput sequence data from 10 Western chimpanzees, Pan troglodytes verus. Compared to the human genetic map, broad-scale recombination rates tend to be conserved, but with exceptions, particularly in regions of chromosomal rearrangements and around the site of ancestral fusion in human chromosome 2. At fine scales, chimpanzee recombination is dominated by hotspots, which show no overlap with those of humans even though rates are similarly elevated around CpG islands and decreased within genes. The hotspot-specifying protein PRDM9 shows extensive variation among Western chimpanzees, and there is little evidence that any sequence motifs are enriched in hotspots. The contrasting locations of hotspots provide a natural experiment, which demonstrates the impact of recombination on base composition.

Bayesian refinement of association signals for 14 loci in 3 common diseases.

To further investigate susceptibility loci identified by genome-wide association studies, we genotyped 5,500 SNPs across 14 associated regions in 8,000 samples from a control group and 3 diseases: type 2 diabetes (T2D), coronary artery disease (CAD) and Graves' disease. We defined, using Bayes theorem, credible sets of SNPs that were 95% likely, based on posterior probability, to contain the causal disease-associated SNPs. In 3 of the 14 regions, TCF7L2 (T2D), CTLA4 (Graves' disease) and CDKN2A-CDKN2B (T2D), much of the posterior probability rested on a single SNP, and, in 4 other regions (CDKN2A-CDKN2B (CAD) and CDKAL1, FTO and HHEX (T2D)), the 95% sets were small, thereby excluding most SNPs as potentially causal. Very few SNPs in our credible sets had annotated functions, illustrating the limitations in understanding the mechanisms underlying susceptibility to common diseases. Our results also show the value of more detailed mapping to target sequences for functional studies.

Genetic profile for five common variants associated with age-related macular degeneration in densely affected families: a novel analytic approach.

About 40% of the genetic variance of age-related macular degeneration (AMD) can be explained by a common variation at five common single-nucleotide polymorphisms (SNPs). We evaluated the degree to which these known variants explain the clustering of AMD in a group of densely affected families. We sought to determine whether the actual number of risk alleles at the five variants in densely affected families matched the expected number. Using data from 322 families with AMD, we used a simulation strategy to generate comparison groups of families and determined whether their genetic profile at the known AMD risk loci differed from the observed genetic profile, given the density of disease observed. Overall, the genotypic loads for the five SNPs in the families did not deviate significantly from the genotypic loads predicted by the simulation. However, for a subset of densely affected families, the mean genotypic load in the families was significantly lower than the expected load determined from the simulation. Given that these densely affected families may harbor rare, more penetrant variants for AMD, linkage analyses and resequencing targeting these families may be an effective approach to finding additional implicated genes.

Prediction model for prevalence and incidence of advanced age-related macular degeneration based on genetic, demographic, and environmental variables.

PURPOSE: The joint effects of genetic, ocular, and environmental variables were evaluated and predictive models for prevalence and incidence of AMD were assessed. METHODS: Participants in the multicenter Age-Related Eye Disease Study (AREDS) were included in a prospective evaluation of 1446 individuals, of which 279 progressed to advanced AMD (geographic atrophy or neovascular disease) and 1167 did not progress during 6.3 years of follow-up. For prevalent AMD, 509 advanced cases were compared with 222 controls. Covariates for the incidence analysis included age, sex, education, smoking, body mass index (BMI), baseline AMD grade, and the AREDS vitamin-mineral treatment assignment. DNA specimens were evaluated for six variants in five genes related to AMD. Unconditional logistic regression analyses were performed for prevalent and incident advanced AMD. An algorithm was developed and receiver operating characteristic curves and C statistics were calculated to assess the predictive ability of risk scores to discriminate progressors from nonprogressors. RESULTS: All genetic polymorphisms were independently related to prevalence of advanced AMD, controlling for genetic factors, smoking, BMI, and AREDS treatment. Multivariate odds ratios (ORs) were 3.5 (95% confidence interval [CI], 1.7-7.1) for CFH Y402H; 3.7 (95% CI, 1.6-8.4) for CFH rs1410996; 25.4 (95% CI, 8.6-75.1) for LOC387715 A69S (ARMS2); 0.3 (95% CI, 0.1-0.7) for C2 E318D; 0.3 (95% CI, 0.1-0.5) for CFB; and 3.6 (95% CI, 1.4-9.4) for C3 R102G, comparing the homozygous risk/protective genotypes to the referent genotypes. For incident AMD, all these variants except CFB were significantly related to progression to advanced AMD, after controlling for baseline AMD grade and other factors, with ORs from 1.8 to 4.0 for presence of two risk alleles and 0.4 for the protective allele. An interaction was seen between CFH402H and treatment, after controlling for all genotypes. Smoking was independently related to AMD, with a multiplicative joint effect with genotype on AMD risk. The C statistic for the full model with all variables was 0.831 for progression to advanced AMD. CONCLUSIONS: Factors reflective of nature and nurture are independently related to prevalence and incidence of advanced AMD, with excellent predictive power.