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.

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.

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.

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.

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/

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.

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 study of electrocardiographic conduction measures in an isolated founder population: Kosrae.

BACKGROUND: Cardiac conduction, as assessed by electrocardiographic PR interval and QRS duration, is an important electrophysiological trait and a determinant of arrhythmia risk. OBJECTIVE: We sought to identify common genetic determinants of these measures. METHODS: We examined 1604 individuals from the island of Kosrae, Federated States of Micronesia, an isolated founder population. We adjusted for covariates and estimated the heritability of quantitative electrocardiographic QRS duration and PR interval and, secondarily, its subcomponents, P-wave duration and PR segment. Finally, we performed a genome-wide association study (GWAS) in a subset of 1262 individuals genotyped using the Affymetrix GeneChip Human Mapping 500K microarray. RESULTS: The heritability of PR interval was 34% (standard error [SE] 5%, P = 4 x 10(-18)); of PR segment, 31% (SE 6%, P = 3.2 x 10(-13)); and of P-wave duration, 17% (SE 5%, P = 5.8 x 10(-6)), but the heritablility of QRS duration was only 3% (SE 4%, P = .20). Hence, GWAS was performed only for the PR interval and its subcomponents. A total of 338,049 single nucleotide polymorphisms (SNPs) passed quality filters. For the PR interval, the most significantly associated SNPs were located in and downstream of the alpha-subunit of the cardiac voltage-gated sodium channel gene SCN5A, with a 4.8 ms (SE 1.0) or 0.23 standard deviation increase in adjusted PR interval for each minor allele copy of rs7638909 (P = 1.6 x 10(-6), minor allele frequency 0.40). These SNPs were also associated with P-wave duration (P = 1.5 x 10(-4)) and PR segment (P = .01) but not with QRS duration (P > or =.22). CONCLUSIONS: The PR interval and its subcomponents showed substantial heritability in a South Pacific islander population and were associated with common genetic variation in SCN5A.

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.

Variation near complement factor I is associated with risk of advanced AMD.

A case-control association study for advanced age-related macular degeneration was conducted to explore several regions of interest identified by linkage. This analysis identified a single nucleotide polymorphism just 3' of complement factor I on chromosome 4 showing significant association (P<10(-7)). Sequencing was performed on coding exons in linkage disequilibrium with the detected association. No obvious functional variation was discovered that could be the proximate cause of the association, suggesting a noncoding regulatory mechanism.

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.

Integrated detection and population-genetic analysis of SNPs and copy number variation.

Dissecting the genetic basis of disease risk requires measuring all forms of genetic variation, including SNPs and copy number variants (CNVs), and is enabled by accurate maps of their locations, frequencies and population-genetic properties. We designed a hybrid genotyping array (Affymetrix SNP 6.0) to simultaneously measure 906,600 SNPs and copy number at 1.8 million genomic locations. By characterizing 270 HapMap samples, we developed a map of human CNV (at 2-kb breakpoint resolution) informed by integer genotypes for 1,320 copy number polymorphisms (CNPs) that segregate at an allele frequency >1%. More than 80% of the sequence in previously reported CNV regions fell outside our estimated CNV boundaries, indicating that large (>100 kb) CNVs affect much less of the genome than initially reported. Approximately 80% of observed copy number differences between pairs of individuals were due to common CNPs with an allele frequency >5%, and more than 99% derived from inheritance rather than new mutation. Most common, diallelic CNPs were in strong linkage disequilibrium with SNPs, and most low-frequency CNVs segregated on specific SNP haplotypes.

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.

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.

Variation in complement factor 3 is associated with risk of age-related macular degeneration.

The association of variants in complement factors H and B with age-related macular degeneration has led to more intense genetic and functional analysis of the complement pathway. We identify a nonsynonymous coding change in complement factor 3 that is strongly associated with risk of age-related macular degeneration in a large case-control sample.