A cross-disorder dosage sensitivity map of the human genome.

Rare copy-number variants (rCNVs) include deletions and duplications that occur infrequently in the global human population and can confer substantial risk for disease. In this study, we aimed to quantify the properties of haploinsufficiency (i.e., deletion intolerance) and triplosensitivity (i.e., duplication intolerance) throughout the human genome. We harmonized and meta-analyzed rCNVs from nearly one million individuals to construct a genome-wide catalog of dosage sensitivity across 54 disorders, which defined 163 dosage sensitive segments associated with at least one disorder. These segments were typically gene dense and often harbored dominant dosage sensitive driver genes, which we were able to prioritize using statistical fine-mapping. Finally, we designed an ensemble machine-learning model to predict probabilities of dosage sensitivity (pHaplo & pTriplo) for all autosomal genes, which identified 2,987 haploinsufficient and 1,559 triplosensitive genes, including 648 that were uniquely triplosensitive. This dosage sensitivity resource will provide broad utility for human disease research and clinical genetics.

Rare coding variants in ten genes confer substantial risk for schizophrenia.

Rare coding variation has historically provided the most direct connections between gene function and disease pathogenesis. By meta-analysing the whole exomes of 24,248 schizophrenia cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in 10 genes as conferring substantial risk for schizophrenia (odds ratios of 3-50, P < 2.14 × 10-6) and 32 genes at a false discovery rate of <5%. These genes have the greatest expression in central nervous system neurons and have diverse molecular functions that include the formation, structure and function of the synapse. The associations of the NMDA (N-methyl-D-aspartate) receptor subunit GRIN2A and AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid) receptor subunit GRIA3 provide support for dysfunction of the glutamatergic system as a mechanistic hypothesis in the pathogenesis of schizophrenia. We observe an overlap of rare variant risk among schizophrenia, autism spectrum disorders1, epilepsy and severe neurodevelopmental disorders2, although different mutation types are implicated in some shared genes. Most genes described here, however, are not implicated in neurodevelopment. We demonstrate that genes prioritized from common variant analyses of schizophrenia are enriched in rare variant risk3, suggesting that common and rare genetic risk factors converge at least partially on the same underlying pathogenic biological processes. Even after excluding significantly associated genes, schizophrenia cases still carry a substantial excess of URVs, which indicates that more risk genes await discovery using this approach.

Whole exome sequencing study identifies novel rare and common Alzheimer's-Associated variants involved in immune response and transcriptional regulation.

The Alzheimer's Disease Sequencing Project (ADSP) undertook whole exome sequencing in 5,740 late-onset Alzheimer disease (AD) cases and 5,096 cognitively normal controls primarily of European ancestry (EA), among whom 218 cases and 177 controls were Caribbean Hispanic (CH). An age-, sex- and APOE based risk score and family history were used to select cases most likely to harbor novel AD risk variants and controls least likely to develop AD by age 85 years. We tested ~1.5 million single nucleotide variants (SNVs) and 50,000 insertion-deletion polymorphisms (indels) for association to AD, using multiple models considering individual variants as well as gene-based tests aggregating rare, predicted functional, and loss of function variants. Sixteen single variants and 19 genes that met criteria for significant or suggestive associations after multiple-testing correction were evaluated for replication in four independent samples; three with whole exome sequencing (2,778 cases, 7,262 controls) and one with genome-wide genotyping imputed to the Haplotype Reference Consortium panel (9,343 cases, 11,527 controls). The top findings in the discovery sample were also followed-up in the ADSP whole-genome sequenced family-based dataset (197 members of 42 EA families and 501 members of 157 CH families). We identified novel and predicted functional genetic variants in genes previously associated with AD. We also detected associations in three novel genes: IGHG3 (p = 9.8 × 10-7), an immunoglobulin gene whose antibodies interact with ß-amyloid, a long non-coding RNA AC099552.4 (p = 1.2 × 10-7), and a zinc-finger protein ZNF655 (gene-based p = 5.0 × 10-6). The latter two suggest an important role for transcriptional regulation in AD pathogenesis.

Correction: Whole exome sequencing study identifies novel rare and common Alzheimer's-Associated variants involved in immune response and transcriptional regulation.

A correction to this paper has been published and can be accessed via a link at the top of the paper.

Epilepsy subtype-specific copy number burden observed in a genome-wide study of 17 458 subjects.

Cytogenic testing is routinely applied in most neurological centres for severe paediatric epilepsies. However, which characteristics of copy number variants (CNVs) confer most epilepsy risk and which epilepsy subtypes carry the most CNV burden, have not been explored on a genome-wide scale. Here, we present the largest CNV investigation in epilepsy to date with 10 712 European epilepsy cases and 6746 ancestry-matched controls. Patients with genetic generalized epilepsy, lesional focal epilepsy, non-acquired focal epilepsy, and developmental and epileptic encephalopathy were included. All samples were processed with the same technology and analysis pipeline. All investigated epilepsy types, including lesional focal epilepsy patients, showed an increase in CNV burden in at least one tested category compared to controls. However, we observed striking differences in CNV burden across epilepsy types and investigated CNV categories. Genetic generalized epilepsy patients have the highest CNV burden in all categories tested, followed by developmental and epileptic encephalopathy patients. Both epilepsy types also show association for deletions covering genes intolerant for truncating variants. Genome-wide CNV breakpoint association showed not only significant loci for genetic generalized and developmental and epileptic encephalopathy patients but also for lesional focal epilepsy patients. With a 34-fold risk for developing genetic generalized epilepsy, we show for the first time that the established epilepsy-associated 15q13.3 deletion represents the strongest risk CNV for genetic generalized epilepsy across the whole genome. Using the human interactome, we examined the largest connected component of the genes overlapped by CNVs in the four epilepsy types. We observed that genetic generalized epilepsy and non-acquired focal epilepsy formed disease modules. In summary, we show that in all common epilepsy types, 1.5-3% of patients carry epilepsy-associated CNVs. The characteristics of risk CNVs vary tremendously across and within epilepsy types. Thus, we advocate genome-wide genomic testing to identify all disease-associated types of CNVs.

No Reliable Association between Runs of Homozygosity and Schizophrenia in a Well-Powered Replication Study.

It is well known that inbreeding increases the risk of recessive monogenic diseases, but it is less certain whether it contributes to the etiology of complex diseases such as schizophrenia. One way to estimate the effects of inbreeding is to examine the association between disease diagnosis and genome-wide autozygosity estimated using runs of homozygosity (ROH) in genome-wide single nucleotide polymorphism arrays. Using data for schizophrenia from the Psychiatric Genomics Consortium (n = 21,868), Keller et al. (2012) estimated that the odds of developing schizophrenia increased by approximately 17% for every additional percent of the genome that is autozygous (ß = 16.1, CI(ß) = [6.93, 25.7], Z = 3.44, p = 0.0006). Here we describe replication results from 22 independent schizophrenia case-control datasets from the Psychiatric Genomics Consortium (n = 39,830). Using the same ROH calling thresholds and procedures as Keller et al. (2012), we were unable to replicate the significant association between ROH burden and schizophrenia in the independent PGC phase II data, although the effect was in the predicted direction, and the combined (original + replication) dataset yielded an attenuated but significant relationship between Froh and schizophrenia (ß = 4.86,CI(ß) = [0.90,8.83],Z = 2.40,p = 0.02). Since Keller et al. (2012), several studies reported inconsistent association of ROH burden with complex traits, particularly in case-control data. These conflicting results might suggest that the effects of autozygosity are confounded by various factors, such as socioeconomic status, education, urbanicity, and religiosity, which may be associated with both real inbreeding and the outcome measures of interest.

Heterogeneous contribution of microdeletions in the development of common generalised and focal epilepsies.

BACKGROUND: Microdeletions are known to confer risk to epilepsy, particularly at genomic rearrangement 'hotspot' loci. However, microdeletion burden not overlapping these regions or within different epilepsy subtypes has not been ascertained. OBJECTIVE: To decipher the role of microdeletions outside hotspots loci and risk assessment by epilepsy subtype. METHODS: We assessed the burden, frequency and genomic content of rare, large microdeletions found in a previously published cohort of 1366 patients with genetic generalised epilepsy (GGE) in addition to two sets of additional unpublished genome-wide microdeletions found in 281 patients with rolandic epilepsy (RE) and 807 patients with adult focal epilepsy (AFE), totalling 2454 cases. Microdeletions were assessed in a combined and subtype-specific approaches against 6746 controls. RESULTS: When hotspots are considered, we detected an enrichment of microdeletions in the combined epilepsy analysis (adjusted p=1.06×10-6,OR 1.89, 95% CI 1.51 to 2.35). Epilepsy subtype-specific analyses showed that hotspot microdeletions in the GGE subgroup contribute most of the overall signal (adjusted p=9.79×10-12, OR 7.45, 95% CI 4.20-13.5). Outside hotspots , microdeletions were enriched in the GGE cohort for neurodevelopmental genes (adjusted p=9.13×10-3,OR 2.85, 95% CI 1.62-4.94). No additional signal was observed for RE and AFE. Still, gene-content analysis identified known (NRXN1, RBFOX1 and PCDH7) and novel (LOC102723362) candidate genes across epilepsy subtypes that were not deleted in controls. CONCLUSIONS: Our results show a heterogeneous effect of recurrent and non-recurrent microdeletions as part of the genetic architecture of GGE and a minor contribution in the aetiology of RE and AFE.

Genome-Wide Association Study of Behavioral Disinhibition in a Selected Adolescent Sample.

Behavioral disinhibition (BD) is a quantitative measure designed to capture the heritable variation encompassing risky and impulsive behaviors. As a result, BD represents an ideal target for discovering genetic loci that predispose individuals to a wide range of antisocial behaviors and substance misuse that together represent a large cost to society as a whole. Published genome-wide association studies (GWAS) have examined specific phenotypes that fall under the umbrella of BD (e.g. alcohol dependence, conduct disorder); however no GWAS has specifically examined the overall BD construct. We conducted a GWAS of BD using a sample of 1,901 adolescents over-selected for characteristics that define high BD, such as substance and antisocial behavior problems, finding no individual locus that surpassed genome-wide significance. Although no single SNP was significantly associated with BD, restricted maximum likelihood analysis estimated that 49.3 % of the variance in BD within the Caucasian sub-sample was accounted for by the genotyped SNPs (p = 0.06). Gene-based tests identified seven genes associated with BD (p ≤ 2.0 × 10(-6)). Although the current study was unable to identify specific SNPs or pathways with replicable effects on BD, the substantial sample variance that could be explained by all genotyped SNPs suggests that larger studies could successfully identify common variants associated with BD.

Runs of homozygosity implicate autozygosity as a schizophrenia risk factor.

Autozygosity occurs when two chromosomal segments that are identical from a common ancestor are inherited from each parent. This occurs at high rates in the offspring of mates who are closely related (inbreeding), but also occurs at lower levels among the offspring of distantly related mates. Here, we use runs of homozygosity in genome-wide SNP data to estimate the proportion of the autosome that exists in autozygous tracts in 9,388 cases with schizophrenia and 12,456 controls. We estimate that the odds of schizophrenia increase by ~17% for every 1% increase in genome-wide autozygosity. This association is not due to one or a few regions, but results from many autozygous segments spread throughout the genome, and is consistent with a role for multiple recessive or partially recessive alleles in the etiology of schizophrenia. Such a bias towards recessivity suggests that alleles that increase the risk of schizophrenia have been selected against over evolutionary time.

Principled distillation of UK Biobank phenotype data reveals underlying structure in human variation.

Data within biobanks capture broad yet detailed indices of human variation, but biobank-wide insights can be difficult to extract due to complexity and scale. Here, using large-scale factor analysis, we distill hundreds of variables (diagnoses, assessments and survey items) into 35 latent constructs, using data from unrelated individuals with predominantly estimated European genetic ancestry in UK Biobank. These factors recapitulate known disease classifications, disentangle elements of socioeconomic status, highlight the relevance of psychiatric constructs to health and improve measurement of pro-health behaviours. We go on to demonstrate the power of this approach to clarify genetic signal, enhance discovery and identify associations between underlying phenotypic structure and health outcomes. In building a deeper understanding of ways in which constructs such as socioeconomic status, trauma, or physical activity are structured in the dataset, we emphasize the importance of considering the interwoven nature of the human phenome when evaluating public health patterns.

Exome sequencing in bipolar disorder identifies AKAP11 as a risk gene shared with schizophrenia.

We report results from the Bipolar Exome (BipEx) collaboration analysis of whole-exome sequencing of 13,933 patients with bipolar disorder (BD) matched with 14,422 controls. We find an excess of ultra-rare protein-truncating variants (PTVs) in patients with BD among genes under strong evolutionary constraint in both major BD subtypes. We find enrichment of ultra-rare PTVs within genes implicated from a recent schizophrenia exome meta-analysis (SCHEMA; 24,248 cases and 97,322 controls) and among binding targets of CHD8. Genes implicated from genome-wide association studies (GWASs) of BD, however, are not significantly enriched for ultra-rare PTVs. Combining gene-level results with SCHEMA, AKAP11 emerges as a definitive risk gene (odds ratio (OR) = 7.06, P = 2.83 × 10-9). At the protein level, AKAP-11 interacts with GSK3B, the hypothesized target of lithium, a primary treatment for BD. Our results lend support to BD's polygenicity, demonstrating a role for rare coding variation as a significant risk factor in BD etiology.

Systematic single-variant and gene-based association testing of thousands of phenotypes in 394,841 UK Biobank exomes.

Genome-wide association studies have successfully discovered thousands of common variants associated with human diseases and traits, but the landscape of rare variations in human disease has not been explored at scale. Exome-sequencing studies of population biobanks provide an opportunity to systematically evaluate the impact of rare coding variations across a wide range of phenotypes to discover genes and allelic series relevant to human health and disease. Here, we present results from systematic association analyses of 4,529 phenotypes using single-variant and gene tests of 394,841 individuals in the UK Biobank with exome-sequence data. We find that the discovery of genetic associations is tightly linked to frequency and is correlated with metrics of deleteriousness and natural selection. We highlight biological findings elucidated by these data and release the dataset as a public resource alongside the Genebass browser for rapidly exploring rare-variant association results.

Detecting autozygosity through runs of homozygosity: a comparison of three autozygosity detection algorithms.

BACKGROUND: A central aim for studying runs of homozygosity (ROHs) in genome-wide SNP data is to detect the effects of autozygosity (stretches of the two homologous chromosomes within the same individual that are identical by descent) on phenotypes. However, it is unknown which current ROH detection program, and which set of parameters within a given program, is optimal for differentiating ROHs that are truly autozygous from ROHs that are homozygous at the marker level but vary at unmeasured variants between the markers. METHOD: We simulated 120 Mb of sequence data in order to know the true state of autozygosity. We then extracted common variants from this sequence to mimic the properties of SNP platforms and performed ROH analyses using three popular ROH detection programs, PLINK, GERMLINE, and BEAGLE. We varied detection thresholds for each program (e.g., prior probabilities, lengths of ROHs) to understand their effects on detecting known autozygosity. RESULTS: Within the optimal thresholds for each program, PLINK outperformed GERMLINE and BEAGLE in detecting autozygosity from distant common ancestors. PLINK's sliding window algorithm worked best when using SNP data pruned for linkage disequilibrium (LD). CONCLUSION: Our results provide both general and specific recommendations for maximizing autozygosity detection in genome-wide SNP data, and should apply equally well to research on whole-genome autozygosity burden or to research on whether specific autozygous regions are predictive using association mapping methods.

Exome sequencing in schizophrenia-affected parent-offspring trios reveals risk conferred by protein-coding de novo mutations.

Protein-coding de novo mutations (DNMs) are significant risk factors in many neurodevelopmental disorders, whereas schizophrenia (SCZ) risk associated with DNMs has thus far been shown to be modest. We analyzed DNMs from 1,695 SCZ-affected trios and 1,077 published SCZ-affected trios to better understand the contribution to SCZ risk. Among 2,772 SCZ probands, exome-wide DNM burden remained modest. Gene set analyses revealed that SCZ DNMs were significantly concentrated in genes that were highly expressed in the brain, that were under strong evolutionary constraint and/or overlapped with genes identified in other neurodevelopmental disorders. No single gene surpassed exome-wide significance; however, 16 genes were recurrently hit by protein-truncating DNMs, corresponding to a 3.15-fold higher rate than the mutation model expectation (permuted 95% confidence interval: 1-10 genes; permuted P = 3 × 10-5). Overall, DNMs explain a small fraction of SCZ risk, and larger samples are needed to identify individual risk genes, as coding variation across many genes confers risk for SCZ in the population.

Publisher Correction: Exome sequencing in amyotrophic lateral sclerosis implicates a novel gene, DNAJC7, encoding a heat-shock protein.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Paternal-age-related de novo mutations and risk for five disorders.

There are established associations between advanced paternal age and offspring risk for psychiatric and developmental disorders. These are commonly attributed to genetic mutations, especially de novo single nucleotide variants (dnSNVs), that accumulate with increasing paternal age. However, the actual magnitude of risk from such mutations in the male germline is unknown. Quantifying this risk would clarify the clinical significance of delayed paternity. Using parent-child trio whole-exome-sequencing data, we estimate the relationship between paternal-age-related dnSNVs and risk for five disorders: autism spectrum disorder (ASD), congenital heart disease, neurodevelopmental disorders with epilepsy, intellectual disability and schizophrenia (SCZ). Using Danish registry data, we investigate whether epidemiologic associations between each disorder and older fatherhood are consistent with the estimated role of dnSNVs. We find that paternal-age-related dnSNVs confer a small amount of risk for these disorders. For ASD and SCZ, epidemiologic associations with delayed paternity reflect factors that may not increase with age.

Exome sequencing in amyotrophic lateral sclerosis implicates a novel gene, DNAJC7, encoding a heat-shock protein.

To discover novel genes underlying amyotrophic lateral sclerosis (ALS), we aggregated exomes from 3,864 cases and 7,839 ancestry-matched controls. We observed a significant excess of rare protein-truncating variants among ALS cases, and these variants were concentrated in constrained genes. Through gene level analyses, we replicated known ALS genes including SOD1, NEK1 and FUS. We also observed multiple distinct protein-truncating variants in a highly constrained gene, DNAJC7. The signal in DNAJC7 exceeded genome-wide significance, and immunoblotting assays showed depletion of DNAJC7 protein in fibroblasts in a patient with ALS carrying the p.Arg156Ter variant. DNAJC7 encodes a member of the heat-shock protein family, HSP40, which, along with HSP70 proteins, facilitates protein homeostasis, including folding of newly synthesized polypeptides and clearance of degraded proteins. When these processes are not regulated, misfolding and accumulation of aberrant proteins can occur and lead to protein aggregation, which is a pathological hallmark of neurodegeneration. Our results highlight DNAJC7 as a novel gene for ALS.

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.

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.

SynGO: An Evidence-Based, Expert-Curated Knowledge Base for the Synapse.

Synapses are fundamental information-processing units of the brain, and synaptic dysregulation is central to many brain disorders ("synaptopathies"). However, systematic annotation of synaptic genes and ontology of synaptic processes are currently lacking. We established SynGO, an interactive knowledge base that accumulates available research about synapse biology using Gene Ontology (GO) annotations to novel ontology terms: 87 synaptic locations and 179 synaptic processes. SynGO annotations are exclusively based on published, expert-curated evidence. Using 2,922 annotations for 1,112 genes, we show that synaptic genes are exceptionally well conserved and less tolerant to mutations than other genes. Many SynGO terms are significantly overrepresented among gene variations associated with intelligence, educational attainment, ADHD, autism, and bipolar disorder and among de novo variants associated with neurodevelopmental disorders, including schizophrenia. SynGO is a public, universal reference for synapse research and an online analysis platform for interpretation of large-scale -omics data (https://syngoportal.org and http://geneontology.org).