Interpreting the role of de novo protein-coding mutations in neuropsychiatric disease

Graph Node Classification to Predict Autism Risk in Genes

This study explores the genetic risk associations with autism spectrum disorder (ASD) using graph neural networks (GNNs), leveraging the Sfari dataset and protein interaction network (PIN) data. We built a gene network with genes as nodes, chromosome band location as node features, and gene interactions as edges. Graph models were employed to classify the autism risk associated with newly introduced genes (test set). Three classification tasks were undertaken to test the ability of our models: binary risk association, multi-class risk association, and syndromic gene association. We tested graph convolutional networks, Graph Sage, graph transformer, and Multi-Layer Perceptron (Baseline) architectures on this problem. The Graph Sage model consistently outperformed the other models, showcasing its utility in classifying ASD-related genes. Our ablation studies show that the chromosome band location and protein interactions contain useful information for this problem. The models achieved 85.80% accuracy on the binary risk classification, 81.68% accuracy on the multi-class risk classification, and 90.22% on the syndromic classification.

Non-coding de novo mutations in chromatin interactions are implicated in autism spectrum disorder

Three-dimensional chromatin interactions regulate gene expressions. The significance of de novo mutations (DNMs) in chromatin interactions remains poorly understood for autism spectrum disorder (ASD). We generated 813 whole-genome sequences from 242 Korean simplex families to detect DNMs, and identified target genes which were putatively affected by non-coding DNMs in chromatin interactions. Non-coding DNMs in chromatin interactions were significantly involved in transcriptional dysregulations related to ASD risk. Correspondingly, target genes showed spatiotemporal expressions relevant to ASD in developing brains and enrichment in biological pathways implicated in ASD, such as histone modification. Regarding clinical features of ASD, non-coding DNMs in chromatin interactions particularly contributed to low intelligence quotient levels in ASD probands. We further validated our findings using two replication cohorts, Simons Simplex Collection (SSC) and MSSNG, and showed the consistent enrichment of non-coding DNM-disrupted chromatin interactions in ASD probands. Generating human induced pluripotent stem cells in two ASD families, we were able to demonstrate that non-coding DNMs in chromatin interactions alter the expression of target genes at the stage of early neural development. Taken together, our findings indicate that non-coding DNMs in ASD probands lead to early neurodevelopmental disruption implicated in ASD risk via chromatin interactions.

Retrospective analysis of a clinical exome sequencing cohort reveals the mutational spectrum and identifies candidate disease-associated loci for BAFopathies

PURPOSE

BRG1/BRM-associated factor (BAF) complex is a chromatin remodeling complex that plays a critical role in gene regulation. Defects in the genes encoding BAF subunits lead to BAFopathies, a group of neurodevelopmental disorders with extensive locus and phenotypic heterogeneity.

METHODS

We retrospectively analyzed data from 16,243 patients referred for clinical exome sequencing (ES) with a focus on the BAF complex. We applied a genotype-first approach, combining predicted genic constraints to propose candidate BAFopathy genes.

RESULTS

We identified 127 patients carrying pathogenic variants, likely pathogenic variants, or de novo variants of unknown clinical significance in 11 known BAFopathy genes. Those include 34 patients molecularly diagnosed using ES reanalysis with new gene-disease evidence (n = 21) or variant reclassifications in known BAFopathy genes (n = 13). We also identified de novo or predicted loss-of-function variants in 4 candidate BAFopathy genes, including ACTL6A, BICRA (implicated in Coffin-Siris syndrome during this study), PBRM1, and SMARCC1.

CONCLUSION

We report the mutational spectrum of BAFopathies in an ES cohort. A genotype-driven and pathway-based reanalysis of ES data identified new evidence for candidate genes involved in BAFopathies. Further mechanistic and phenotypic characterization of additional patients are warranted to confirm their roles in human disease and to delineate their associated phenotypic spectrums.

Autism-associated SHANK3 missense point mutations impact conformational fluctuations and protein turnover at synapses

Members of the SH3- and ankyrin repeat (SHANK) protein family are considered as master scaffolds of the postsynaptic density of glutamatergic synapses. Several missense mutations within the canonical SHANK3 isoform have been proposed as causative for the development of autism spectrum disorders (ASDs). However, there is a surprising paucity of data linking missense mutation-induced changes in protein structure and dynamics to the occurrence of ASD-related synaptic phenotypes. In this proof-of-principle study, we focus on two ASD-associated point mutations, both located within the same domain of SHANK3 and demonstrate that both mutant proteins indeed show distinct changes in secondary and tertiary structure as well as higher conformational fluctuations. Local and distal structural disturbances result in altered synaptic targeting and changes of protein turnover at synaptic sites in rat primary hippocampal neurons.

Voltage-Gated Ca2+-Channel α1-Subunit de novo Missense Mutations: Gain or Loss of Function - Implications for Potential Therapies

This review summarizes our current knowledge of human disease-relevant genetic variants within the family of voltage gated Ca2+ channels. Ca2+ channelopathies cover a wide spectrum of diseases including epilepsies, autism spectrum disorders, intellectual disabilities, developmental delay, cerebellar ataxias and degeneration, severe cardiac arrhythmias, sudden cardiac death, eye disease and endocrine disorders such as congential hyperinsulinism and hyperaldosteronism. A special focus will be on the rapidly increasing number of de novo missense mutations identified in the pore-forming α1-subunits with next generation sequencing studies of well-defined patient cohorts. In contrast to likely gene disrupting mutations these can not only cause a channel loss-of-function but can also induce typical functional changes permitting enhanced channel activity and Ca2+ signaling. Such gain-of-function mutations could represent therapeutic targets for mutation-specific therapy of Ca2+-channelopathies with existing or novel Ca2+-channel inhibitors. Moreover, many pathogenic mutations affect positive charges in the voltage sensors with the potential to form gating-pore currents through voltage sensors. If confirmed in functional studies, specific blockers of gating-pore currents could also be of therapeutic interest.

From Rare Copy Number Variants to Biological Processes in ADHD

OBJECTIVE

Attention deficit hyperactivity disorder (ADHD) is a highly heritable psychiatric disorder. The objective of this study was to define ADHD-associated candidate genes and their associated molecular modules and biological themes, based on the analysis of rare genetic variants.

METHODS

The authors combined data from 11 published copy number variation studies in 6,176 individuals with ADHD and 25,026 control subjects and prioritized genes by applying an integrative strategy based on criteria including recurrence in individuals with ADHD, absence in control subjects, complete coverage in copy number gains, and presence in the minimal region common to overlapping copy number variants (CNVs), as well as on protein-protein interactions and information from cross-species genotype-phenotype annotation.

RESULTS

The authors localized 2,241 eligible genes in the 1,532 reported CNVs, of which they classified 432 as high-priority ADHD candidate genes. The high-priority ADHD candidate genes were significantly coexpressed in the brain. A network of 66 genes was supported by ADHD-relevant phenotypes in the cross-species database. Four significantly interconnected protein modules were found among the high-priority ADHD genes. A total of 26 genes were observed across all applied bioinformatic methods. Lookup in the latest genome-wide association study for ADHD showed that among those 26 genes, POLR3C and RBFOX1 were also supported by common genetic variants.

CONCLUSIONS

Integration of a stringent filtering procedure in CNV studies with suitable bioinformatics approaches can identify ADHD candidate genes at increased levels of credibility. The authors' analytic pipeline provides additional insight into the molecular mechanisms underlying ADHD and allows prioritization of genes for functional validation in validated model organisms.

Stem Cells to Inform the Neurobiology of Mental Illness

The inception of human-induced pluripotent stem cell (hiPSCs) technology has provided an exciting platform upon which the modelling and treatment of human neurodevelopmental and neuropsychiatric disorders may be expedited. Although the genetic architecture of these disorders is far more complex than previously imagined, many key loci have at last been identified. This has allowed in vivo and in vitro technologies to be refined to model specific high-penetrant genetic loci involved in both disorders. Animal models of neurodevelopmental disorders, such as schizophrenia and autism spectrum disorders, show limitations in recapitulating the full complexity and heterogeneity of human neurodevelopmental disease states. Indeed, patient-derived hiPSCs offer distinct advantages over classical animal models in the study of human neuropathologies. Here we have discussed the current, relative translational merit of hiPSCs in investigating human neurodevelopmental and neuropsychiatric disorders with a specific emphasis on the utility of such systems to aid in the identification of biomarkers. We have highlighted the promises and pitfalls of reprogramming cell fate for the study of these disorders and provide recommendations for future directions in this field in order to overcome current limitations. Ultimately, this will aid in the development of effective clinical strategies for diverse patient populations affected by these disorders with the aim of also leading to biomarker identification.

De novo Mutations From Whole Exome Sequencing in Neurodevelopmental and Psychiatric Disorders: From Discovery to Application

Neurodevelopmental and psychiatric disorders are a highly disabling and heterogeneous group of developmental and mental disorders, resulting from complex interactions of genetic and environmental risk factors. The nature of multifactorial traits and the presence of comorbidity and polygenicity in these disorders present challenges in both disease risk identification and clinical diagnoses. The genetic component has been firmly established, but the identification of all the causative variants remains elusive. The development of next-generation sequencing, especially whole exome sequencing (WES), has greatly enriched our knowledge of the precise genetic alterations of human diseases, including brain-related disorders. In particular, the extensive usage of WES in research studies has uncovered the important contribution of de novo mutations (DNMs) to these disorders. Trio and quad familial WES are a particularly useful approach to discover DNMs. Here, we review the major WES studies in neurodevelopmental and psychiatric disorders and summarize how genes hit by discovered DNMs are shared among different disorders. Next, we discuss different integrative approaches utilized to interrogate DNMs and to identify biological pathways that may disrupt brain development and shed light on our understanding of the genetic architecture underlying these disorders. Lastly, we discuss the current state of the transition from WES research to its routine clinical application. This review will assist researchers and clinicians in the interpretation of variants obtained from WES studies, and highlights the need to develop consensus analytical protocols and validated lists of genes appropriate for clinical laboratory analysis, in order to reach the growing demands.

Overexpression of NEUROG2 and NEUROG1 in human embryonic stem cells produces a network of excitatory and inhibitory neurons

Overexpression of mouse neurogenin ( Neurog) 2 alone or in combination with mouse Neurog2/1 in human embryonic stem cells (hESCs) and human induced pluripotent stem cells (hiPSCs) can rapidly produce high-yield excitatory neurons. Here, we report a detailed characterization of human neuronal networks induced by the expression of human NEUROG2 together with human NEUROG2/1 in hESCs using molecular, cellular, and electrophysiological measurements over 60 d after induction. Both excitatory synaptic transmission and network firing activity increased over time. Strikingly, inhibitory synaptic transmission and GABAergic cells were identified from NEUROG2/1 induced neurons (iNs). To illustrate the application of such iNs, we demonstrated that the heterozygous knock out of SCN2A, whose loss-of-function mutation is strongly implicated in autism risk, led to a dramatic reduction in network activity in the NEUROG2/1 iNs. Our findings not only extend our understanding of the NEUROG2/1-induced human neuronal network but also substantiate NEUROG2/1 iNs as an in vitro system for modeling neuronal and functional deficits on a human genetic background.-Lu, C., Shi, X., Allen, A., Baez-Nieto, D., Nikish, A., Sanjana, N. E., Pan, J. Q. Overexpression of NEUROG2 and NEUROG1 in human embryonic stem cells produces a network of excitatory and inhibitory neurons.

Using mouse transgenic and human stem cell technologies to model genetic mutations associated with schizophrenia and autism

Solid progress has occurred over the last decade in our understanding of the molecular genetic basis of neurodevelopmental disorders, and of schizophrenia and autism in particular. Although the genetic architecture of both disorders is far more complex than previously imagined, many key loci have at last been identified. This has allowed in vivo and in vitro technologies to be refined to model specific high-penetrant genetic loci involved in both disorders. Using the DISC1/NDE1 and CYFIP1/EIF4E loci as exemplars, we explore the opportunities and challenges of using animal models and human-induced pluripotent stem cell technologies to further understand/treat and potentially reverse the worst consequences of these debilitating disorders.

This article is part of a discussion meeting issue ‘Of mice and mental health: facilitating dialogue between basic and clinical neuroscientists’.

Replication of a rare risk haplotype on 1p36.33 for autism spectrum disorder

Hundreds of genes have been implicated in autism spectrum disorders (ASDs). In genetically heterogeneous conditions, large families with multiple affected individuals provide strong evidence implicating a rare variant, and replication of the same variant in multiple families is unusual. We previously published linkage analyses and follow-up exome sequencing in seven large families with ASDs, implicating 14 rare exome variants. These included rs200195897, which was transmitted to four affected individuals in one family. We attempted replication of those variants in the MSSNG database. MSSNG is a unique resource for replication of ASD risk loci, containing whole genome sequence (WGS) on thousands of individuals diagnosed with ASDs and family members. For each exome variant, we obtained all carriers and their relatives in MSSNG, using a TDT test to quantify evidence for transmission and association. We replicated the transmission of rs200195897 to four affected individuals in three additional families. rs200195897 was also present in three singleton affected individuals, and no unaffected individuals other than transmitting parents. We identified two additional rare variants (rs566472488 and rs185038034) transmitted with rs200195897 on 1p36.33. Sanger sequencing confirmed the presence of these variants in the original family segregating rs200195897. To our knowledge, this is the first example of a rare haplotype being transmitted with ASD in multiple families. The candidate risk variants include a missense mutation in SAMD11, an intronic variant in NOC2L, and a regulatory region variant close to both genes. NOC2L is a transcription repressor, and several genes involved in transcription regulation have been previously associated with ASDs.

The Candidate Schizophrenia Risk Gene DGCR2 Regulates Early Steps of Corticogenesis

BACKGROUND

Alterations in early steps of cortical circuit assembly are thought to play a critical role in vulnerability to schizophrenia (SZ), but the pathogenic impact of SZ-risk mutations on corticogenesis remains to be determined. DiGeorge syndrome critical region 2 (DGCR2) is located in the 22q11.2 locus, whose deletion is a major risk factor for SZ. Moreover, exome sequencing of individuals with idiopathic SZ identified a rare missense mutation in DGCR2, further suggesting that DGCR2 is involved in SZ.

METHODS

Here we investigated the function of Dgcr2 and the pathogenic impact of the SZ-risk DGCR2 mutation in mouse corticogenesis using in utero electroporation targeted to projection neurons.

RESULTS

Dgcr2 knockdown impaired radial locomotion and final translocation of projection neurons, leading to persistent laminar positioning alterations. The DGCR2 missense SZ-risk mutation had a pathogenic impact on projection neuron laminar allocation by reducing protein expression. Mechanistically, we identified Dgcr2 as a novel member of the Reelin complex, regulating the phosphorylation of Reelin-dependent substrates and the expression of Reelin-dependent transcriptional targets.

CONCLUSIONS

Overall, this study provides biological evidence that the SZ-risk gene DGCR2 regulates critical steps of early corticogenesis possibly through a Reelin-dependent mechanism. Additionally, we found that the SZ-risk mutation in DGCR2 has a pathogenic impact on cortical formation by reducing protein expression level, suggesting a functional role for DGCR2 haploinsufficiency in the 22q11.2 deletion syndrome.

Identification of de novo germline mutations and causal genes for sporadic diseases using trio-based whole-exome/genome sequencing

Whole-genome or whole-exome sequencing (WGS/WES) of the affected proband together with normal parents (trio) is commonly adopted to identify de novo germline mutations (DNMs) underlying sporadic cases of various genetic disorders. However, our current knowledge of the occurrence and functional effects of DNMs remains limited and accurately identifying the disease-causing DNM from a group of irrelevant DNMs is complicated. Herein, we provide a general-purpose discussion of important issues related to pathogenic gene identification based on trio-based WGS/WES data. Specifically, the relevance of DNMs to human sporadic diseases, current knowledge of DNM biogenesis mechanisms, and common strategies or software tools used for DNM detection are reviewed, followed by a discussion of pathogenic gene prioritization. In addition, several key factors that may affect DNM identification accuracy and causal gene prioritization are reviewed. Based on recent major advances, this review both sheds light on how trio-based WGS/WES technologies can play a significant role in the identification of DNMs and causal genes for sporadic diseases, and also discusses existing challenges.

Shifting the focus toward rare variants in schizophrenia to close the gap from genotype to phenotype

Schizophrenia (SZ) is a disorder with a high heritability and a complex architecture. Several dozen genetic variants have been identified as risk factors through genome-wide association studies including large population-based samples. However, the bulk of the risk cannot be accounted for by the genes associated to date. Rare mutations have been historically seen as relevant only for some infrequent, Mendelian forms of psychosis. Recent findings, however, show that the subset of patients that present a mutation with major effect is larger than expected. We discuss some of the molecular findings of these studies. SZ is clinically and genetically heterogeneous. To identify the genetic variation underlying the disorder, research should be focused on features that are more likely a product of genetic heterogeneity. Based on the phenotypical correlations with rare variants, cognition emerges as a relevant domain to study. Cognitive disturbances could be useful in selecting cases that have a higher probability of carrying deleterious mutations, as well as on the correct ascertainment of sporadic cases for the identification of de novo variants.

A Cell Type-Specific Expression Signature Predicts Haploinsufficient Autism-Susceptibility Genes

Recent studies have identified many genes with rare de novo mutations in autism, but a limited number of these have been conclusively established as disease-susceptibility genes due to the lack of recurrence and confounding background mutations. Such extreme genetic heterogeneity severely limits recurrence-based statistical power even in studies with a large sample size. Here, we use cell-type specific expression profiles to differentiate mutations in autism patients from those in unaffected siblings. We report a gene expression signature in different neuronal cell types shared by genes with likely gene-disrupting (LGD) mutations in autism cases. This signature reflects haploinsufficiency of risk genes enriched in transcriptional and post-transcriptional regulators, with the strongest positive associations with specific types of neurons in different brain regions, including cortical neurons, cerebellar granule cells, and striatal medium spiny neurons. When used to prioritize genes with a single LGD mutation in cases, a D-score derived from the signature achieved a precision of 40% as compared with the 15% baseline with a minimal loss in sensitivity. An ensemble model combining D-score with mutation intolerance metrics from Exome Aggregation Consortium further improved the precision to 60%, resulting in 117 high-priority candidates. These prioritized lists can facilitate identification of additional autism-susceptibility genes.

Functional and Genomic Features of Human Genes Mutated in Neuropsychiatric Disorders

Background:

In recent years, a large number of studies around the world have led to the identification of causal genes for hereditary types of common and rare neurological and psychiatric disorders.

Objective:

To explore the functional and genomic features of known human genes mutated in neuropsychiatric disorders.

Methods:

A systematic search was used to develop a comprehensive catalog of genes mutated in neuropsychiatric disorders (NPD). Functional enrichment and protein-protein interaction analyses were carried out. A false discovery rate approach was used for correction for multiple testing.

Results:

We found several functional categories that are enriched among NPD genes, such as gene ontologies, protein domains, tissue expression, signaling pathways and regulation by brain-expressed miRNAs and transcription factors. Sixty six of those NPD genes are known to be druggable. Several topographic parameters of protein-protein interaction networks and the degree of conservation between orthologous genes were identified as significant among NPD genes.

Conclusion:

These results represent one of the first analyses of enrichment of functional categories of genes known to harbor mutations for NPD. These findings could be useful for a future creation of computational tools for prioritization of novel candidate genes for NPD.

Resetting the bar: Statistical significance in whole-genome sequencing-based association studies of global populations

Genome-wide association studies (GWAS) of common disease have been hugely successful in implicating loci that modify disease risk. The bulk of these associations have proven robust and reproducible, in part due to community adoption of statistical criteria for claiming significant genotype-phenotype associations. As the cost of sequencing continues to drop, assembling large samples in global populations is becoming increasingly feasible. Sequencing studies interrogate not only common variants, as was true for genotyping-based GWAS, but variation across the full allele frequency spectrum, yielding many more (independent) statistical tests. We sought to empirically determine genome-wide significance thresholds for various analysis scenarios. Using whole-genome sequence data, we simulated sequencing-based disease studies of varying sample size and ancestry. We determined that future sequencing efforts in >2,000 samples of European, Asian, or admixed ancestry should set genome-wide significance at approximately P = 5 × 10^-9 , and studies of African samples should apply a more stringent genome-wide significance threshold of P = 1 × 10^-9 . Adoption of a revised multiple test correction will be crucial in avoiding irreproducible claims of association.

Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism

Autism spectrum disorder (ASD) involves substantial genetic contributions. These contributions are profoundly heterogeneous but may converge on common pathways that are not yet well understood. Here, through post-mortem genome-wide transcriptome analysis of the largest cohort of samples analysed so far, to our knowledge, we interrogate the noncoding transcriptome, alternative splicing, and upstream molecular regulators to broaden our understanding of molecular convergence in ASD. Our analysis reveals ASD-associated dysregulation of primate-specific long noncoding RNAs (lncRNAs), downregulation of the alternative splicing of activity-dependent neuron-specific exons, and attenuation of normal differences in gene expression between the frontal and temporal lobes. Our data suggest that SOX5, a transcription factor involved in neuron fate specification, contributes to this reduction in regional differences. We further demonstrate that a genetically defined subtype of ASD, chromosome 15q11.2-13.1 duplication syndrome (dup15q), shares the core transcriptomic signature observed in idiopathic ASD. Co-expression network analysis reveals that individuals with ASD show age-related changes in the trajectory of microglial and synaptic function over the first two decades, and suggests that genetic risk for ASD may influence changes in regional cortical gene expression. Our findings illustrate how diverse genetic perturbations can lead to phenotypic convergence at multiple biological levels in a complex neuropsychiatric disorder.

Advancing the understanding of autism disease mechanisms through genetics

Progress in understanding the genetic etiology of autism spectrum disorders (ASD) has fueled remarkable advances in our understanding of its potential neurobiological mechanisms. Yet, at the same time, these findings highlight extraordinary causal diversity and complexity at many levels ranging from molecules to circuits and emphasize the gaps in our current knowledge. Here we review current understanding of the genetic architecture of ASD and integrate genetic evidence, neuropathology and studies in model systems with how they inform mechanistic models of ASD pathophysiology. Despite the challenges, these advances provide a solid foundation for the development of rational, targeted molecular therapies.

Risk of psychiatric illness from advanced paternal age is not predominantly from de novo mutations

The offspring of older fathers have higher risk of psychiatric disorders such as schizophrenia and autism. Paternal-age-related de novo mutations are widely assumed to be the underlying causal mechanism, and, although such mutations must logically make some contribution, there are alternative explanations (for example, elevated liability to psychiatric illness may delay fatherhood). We used population genetic models based on empirical observations of key parameters (for example, mutation rate, prevalence, and heritability) to assess the genetic relationship between paternal age and risk of psychiatric illness. These models suggest that age-related mutations are unlikely to explain much of the increased risk of psychiatric disorders in children of older fathers. Conversely, a model incorporating a weak correlation between age at first child and liability to psychiatric illness matched epidemiological observations. Our results suggest that genetic risk factors shared by older fathers and their offspring are a credible alternative explanation to de novo mutations for risk to children of older fathers.

Depression as a risk factor for Alzheimer's disease: Genes, steroids, cytokines and neurogenesis - What do we need to know?

Depression (MDD) is prodromal to, and a component of, Alzheimer's disease (AD): it may also be a trigger for incipient AD. MDD is not a unitary disorder, so there may be particular subtypes of early life MDD that pose independent high risks for later AD, though the identification of these subtypes is problematical. There may either be a common pathological event underlying both MDD and AD, or MDD may sensitize the brain to a second event ('hit') that precipitates AD. MDD may also accelerate brain ageing, including altered DNA methylation, increased cortisol but decreasing DHEA and thus the risk for AD. So far, genes predicting AD (e.g. APOEε4) are not risk factors for MDD, and those implicated in MDD (e.g. SLC6A4) are not risks for AD, so a common genetic predisposition looks unlikely. There is as yet no strong indication that an epigenetic event occurs during some forms of MDD that predisposes to later AD, though the evidence is limited. Glucocorticoids (GCs) are disturbed in some cases of MDD and in AD. GCs have marked degenerative actions on the hippocampus, a site of early β-amyloid deposition, and rare genetic variants of GC-regulating enzymes (e.g. 11β-HSD) predispose to AD. GCs also inhibit hippocampal neurogenesis and plasticity, and thus episodic memory, a core symptom of AD. Disordered GCs in MDD may inhibit neurogenesis, but the contribution of diminished neurogenesis to the onset or progression of AD is still debated. GCs and cytokines also reduce BDNF, implicated in both MDD and AD and hippocampal neurogenesis, reinforcing the notion that those cases of MDD with disordered GCs may be a risk for AD. Cytokines, including IL1β, IL6 and TNFα, are increased in the blood in some cases of MDD. They also reduce hippocampal neurogenesis, and increased cytokines are a known risk for later AD. Inflammatory changes occur in both MDD and AD (e.g. raised CRP, TNFα). Both cytokines and GCs can have pro-inflammatory actions in the brain. Inflammation (e.g. microglial activation) may be a common link, but this has not been systematically investigated. We lack substantial, rigorous and comprehensive follow-up studies to better identify possible subtypes of MDD that may represent a major predictor for later AD. This would enable specific interventions during critical episodes of these subtypes of MDD that should reduce this substantial risk.

RELN Mutations in Autism Spectrum Disorder

RELN encodes a large, secreted glycoprotein integral to proper neuronal positioning during development and regulation of synaptic function postnatally. Rare, homozygous, null mutations lead to lissencephaly with cerebellar hypoplasia (LCH), accompanied by developmental delay and epilepsy. Until recently, little was known about the frequency or consequences of heterozygous mutations. Several lines of evidence from multiple studies now implicate heterozygous mutations in RELN in autism spectrum disorders (ASD). RELN maps to the AUTS1 locus on 7q22, and at this time over 40 distinct mutations have been identified that would alter the protein sequence, four of which are de novo. The RELN mutations that are most clearly consequential are those that are predicted to inactivate the signaling function of the encoded protein and those that fall in a highly conserved RXR motif found at the core of the 16 Reelin subrepeats. Despite the growing evidence of RELN dysfunction in ASD, it appears that these mutations in isolation are insufficient and that secondary genetic or environmental factors are likely required for a diagnosis.

Disease and Polygenic Architecture: Avoid Trio Design and Appropriately Account for Unscreened Control Subjects for Common Disease

Genome-wide association studies (GWASs) are an optimal design for discovery of disease risk loci for diseases whose underlying genetic architecture includes many common causal loci of small effect (a polygenic architecture). We consider two designs that deserve careful consideration if the true underlying genetic architecture of the trait is polygenic: parent-offspring trios and unscreened control subjects. We assess these designs in terms of quantification of the total contribution of genome-wide genetic markers to disease risk (SNP heritability) and power to detect an associated risk allele. First, we show that trio designs should be avoided when: (1) the disease has a lifetime risk > 1%; (2) trio probands are ascertained from families with more than one affected sibling under which scenario the SNP heritability can drop by more than 50% and power can drop as much as from 0.9 to 0.15 for a sample of 20,000 subjects; or (3) assortative mating occurs (spouse correlation of the underlying liability to the disorder), which decreases the SNP heritability but not the power to detect a single locus in the trio design. Some studies use unscreened rather than screened control subjects because these can be easier to collect; we show that the estimated SNP heritability should then be scaled by dividing by (1 - K × u)(2) for disorders with population prevalence K and proportion of unscreened control subjects u. When omitting to scale appropriately, the SNP heritability of, for example, major depressive disorder (K = 0.15) would be underestimated by 28% when none of the control subjects are screened.

Genes with de novo mutations are shared by four neuropsychiatric disorders discovered from NPdenovo database

Currently, many studies on neuropsychiatric disorders have utilized massive trio-based whole-exome sequencing (WES) and whole-genome sequencing (WGS) to identify numerous de novo mutations (DNMs). Here, we retrieved 17,104 DNMs from 3555 trios across four neuropsychiatric disorders: autism spectrum disorder, epileptic encephalopathy, intellectual disability and schizophrenia, in addition to unaffected siblings (control), from 36 studies by WES/WGS. After eliminating non-exonic variants, we focused on 3334 exonic DNMs for evaluation of their association with these diseases. Our results revealed a higher prevalence of DNMs in the probands of all four disorders compared with the one in the controls (P<1.3 × 10(-7)). The elevated DNM frequency is dominated by loss-of-function/deleterious single-nucleotide variants and frameshift indels (that is, extreme mutations, P<4.5 × 10(-5)). With extensive annotation of these 'extreme' mutations, we prioritized 764 candidate genes in these four disorders. A combined analysis of Gene Ontology, microRNA targets and transcription factor targets revealed shared biological process and non-coding regulatory elements of candidate genes in the pathology of neuropsychiatric disorders. In addition, weighted gene co-expression network analysis of human laminar-specific neocortical expression data showed that candidate genes are convergent on eight shared modules with specific layer enrichment and biological process features. Furthermore, we identified that 53 candidate genes are associated with more than one disorder (P<0.000001), suggesting a possibly shared genetic etiology underlying these disorders. Particularly, DNMs of the SCN2A gene are frequently occurred across all four disorders. Finally, we constructed a freely available NPdenovo database, which provides a comprehensive catalog of the DNMs identified in neuropsychiatric disorders.

Genetic studies in intellectual disability and related disorders

Genetic factors play a major part in intellectual disability (ID), but genetic studies have been complicated for a long time by the extreme clinical and genetic heterogeneity. Recently, progress has been made using different next-generation sequencing approaches in combination with new functional readout systems. This approach has provided novel insights into the biological pathways underlying ID, improved the diagnostic process and offered new targets for therapy. In this Review, we highlight the insights obtained from recent studies on the role of genetics in ID and its impact on diagnosis, prognosis and therapy. We also discuss the future directions of genetics research for ID and related neurodevelopmental disorders.

Whole exome sequencing in extended families with autism spectrum disorder implicates four candidate genes

Autism spectrum disorders (ASDs) are a group of neurodevelopmental disorders, characterized by impairment in communication and social interactions, and by repetitive behaviors. ASDs are highly heritable, and estimates of the number of risk loci range from hundreds to >1000. We considered 7 extended families (size 12-47 individuals), each with ≥3 individuals affected by ASD. All individuals were genotyped with dense SNP panels. A small subset of each family was typed with whole exome sequence (WES). We used a 3-step approach for variant identification. First, we used family-specific parametric linkage analysis of the SNP data to identify regions of interest. Second, we filtered variants in these regions based on frequency and function, obtaining exactly 200 candidates. Third, we compared two approaches to narrowing this list further. We used information from the SNP data to impute exome variant dosages into those without WES. We regressed affected status on variant allele dosage, using pedigree-based kinship matrices to account for relationships. The p value for the test of the null hypothesis that variant allele dosage is unrelated to phenotype was used to indicate strength of evidence supporting the variant. A cutoff of p = 0.05 gave 28 variants. As an alternative third filter, we required Mendelian inheritance in those with WES, resulting in 70 variants. The imputation- and association-based approach was effective. We identified four strong candidate genes for ASD (SEZ6L, HISPPD1, FEZF1, SAMD11), all of which have been previously implicated in other studies, or have a strong biological argument for their relevance.

De novo deleterious genetic variations target a biological network centered on Aβ peptide in early-onset Alzheimer disease

We hypothesized that de novo variants (DNV) might participate in the genetic determinism of sporadic early-onset Alzheimer disease (EOAD, onset before 65 years). We investigated 14 sporadic EOAD trios first by array-comparative genomic hybridization. Two patients carried a de novo copy number variation (CNV). We then performed whole-exome sequencing in the 12 remaining trios and identified 12 non-synonymous DNVs in six patients. The two de novo CNVs (an amyloid precursor protein (APP) duplication and a BACE2 intronic deletion) and 3/12 non-synonymous DNVs (in PSEN1, VPS35 and MARK4) targeted genes from a biological network centered on the Amyloid beta (Aβ) peptide. We showed that this a priori-defined genetic network was significantly enriched in amino acid-altering DNV, compared with the rest of the exome. The causality of the APP de novo duplication (which is the first reported one) was obvious. In addition, we provided evidence of the functional impact of the following three non-synonymous DNVs targeting this network: the novel PSEN1 variant resulted in exon 9 skipping in patient's RNA, leading to a pathogenic missense at exons 8-10 junction; the VPS35 missense variant led to partial loss of retromer function, which may impact neuronal APP trafficking and Aβ secretion; and the MARK4 multiple nucleotide variant resulted into increased Tau phosphorylation, which may trigger enhanced Aβ-induced toxicity. Despite the difficulty to recruit Alzheimer disease (AD) trios owing to age structures of the pedigrees and the genetic heterogeneity of the disease, this strategy allowed us to highlight the role of de novo pathogenic events, the putative involvement of new genes in AD genetics and the key role of Aβ network alteration in AD.

Genome-wide patterns and properties of de novo mutations in humans

Mutations create variation in the population, fuel evolution, and cause genetic diseases. Current knowledge about de novo mutations is incomplete and mostly indirect ^1–10. Here, we analyze 11,020 de novo mutations from whole-genomes of 250 families. We show that de novo mutations in offspring of older fathers are not only more numerous ^11–13 but also occur more frequently in early-replicating, genic regions. Functional regions exhibit higher mutation rates due to CpG dinucleotides and reveal signatures of transcription-coupled repair, while mutation clusters with a unique signature point to a novel mutational mechanism. Mutation and recombination rates independently associate with nucleotide diversity, and regional variation in human-chimpanzee divergence is only partly explained by mutation rate heterogeneity. Finally, we provide a genome-wide mutation rate map for medical and population genetics applications. Our results reveal novel insights and refine long-standing hypotheses about human mutagenesis.

Genetic causes of amyotrophic lateral sclerosis: new genetic analysis methodologies entailing new opportunities and challenges

The genetic architecture of amyotrophic lateral sclerosis (ALS) is being increasingly understood. In this far-reaching review, we examine what is currently known about ALS genetics and how these genes were initially identified. We also discuss the various types of mutations that might underlie this fatal neurodegenerative condition and outline some of the strategies that might be useful in untangling them. These include expansions of short repeat sequences, common and low-frequency genetic variations, de novo mutations, epigenetic changes, somatic mutations, epistasis, oligogenic and polygenic hypotheses. This article is part of a Special Issue entitled ALS complex pathogenesis.

A novel approach for identifying causal models of complex diseases from family data

Causal models including genetic factors are important for understanding the presentation mechanisms of complex diseases. Familial aggregation and segregation analyses based on polygenic threshold models have been the primary approach to fitting genetic models to the family data of complex diseases. In the current study, an advanced approach to obtaining appropriate causal models for complex diseases based on the sufficient component cause (SCC) model involving combinations of traditional genetics principles was proposed. The probabilities for the entire population, i.e., normal-normal, normal-disease, and disease-disease, were considered for each model for the appropriate handling of common complex diseases. The causal model in the current study included the genetic effects from single genes involving epistasis, complementary gene interactions, gene-environment interactions, and environmental effects. Bayesian inference using a Markov chain Monte Carlo algorithm (MCMC) was used to assess of the proportions of each component for a given population lifetime incidence. This approach is flexible, allowing both common and rare variants within a gene and across multiple genes. An application to schizophrenia data confirmed the complexity of the causal factors. An analysis of diabetes data demonstrated that environmental factors and gene-environment interactions are the main causal factors for type II diabetes. The proposed method is effective and useful for identifying causal models, which can accelerate the development of efficient strategies for identifying causal factors of complex diseases.

Patterns of variation influencing antipsychotic treatment outcomes in South African first-episode schizophrenia patients

AIM

Many antipsychotic pharmacogenetics studies have been performed examining candidate genes or known variation; however, our understanding of the genetic factors involved in antipsychotic pharmacogenetic traits remains limited.

MATERIALS & METHODS

A well-characterized cohort of first-episode schizophrenia (FES) patients was used to identify a subset of nonresponders and responders to antipsychotic treatment for exome sequencing (n = 11). The variation observed in the responders and nonresponders was subsequently compared and a prioritization strategy was employed to identify variants for genotyping in the entire FES cohort (n = 103) as well as an additional Xhosa schizophrenia cohort (n = 222).

RESULTS

Examination of coding variation revealed a potential role for rare loss-of-function variants in treatment response outcomes. One variant, rs11368509, was found to be weakly associated with better treatment outcomes in the FES cohort (p = 0.057) and the Xhosa schizophrenia cohort (p = 0.016). In addition, the majority of the loss-of-function variation that was considered likely to be involved in antipsychotic treatment response was either novel or rare in Asian and European populations.

CONCLUSION

This pilot study has highlighted the importance of exome sequencing for antipsychotic pharmacogenomics studies, particularly in African individuals. Furthermore, the results emphasize once again the complexity of antipsychotic pharmacogenomics and the need for future research.

mirTrios: an integrated pipeline for detection of de novo and rare inherited mutations from trios-based next-generation sequencing

OBJECTIVES

Recently, several studies documented that de novo mutations (DNMs) play important roles in the aetiology of sporadic diseases. Next-generation sequencing (NGS) enables variant calling at single-base resolution on a genome-wide scale. However, accurate identification of DNMs from NGS data still remains a major challenge. We developed mirTrios, a web server, to accurately detect DNMs and rare inherited mutations from NGS data in sporadic diseases.

METHODS

The expectation-maximisation (EM) model was adopted to accurately identify DNMs from variant call files of a trio generated by GATK (Genome Analysis Toolkit). The GATK results, which contain certain basic properties (such as PL, PRT and PART), are iteratively integrated into the EM model to strike a threshold for DNMs detection. Training sets of true and false positive DNMs in the EM model were built from whole genome sequencing data of 64 trios.

RESULTS

With our in-house whole exome sequencing datasets from 20 trios, mirTrios totally identified 27 DNMs in the coding region, 25 of which (92.6%) are validated as true positives. In addition, to facilitate the interpretation of diverse mutations, mirTrios can also be employed in the identification of rare inherited mutations. Embedded with abundant annotation of DNMs and rare inherited mutations, mirTrios also supports known diagnostic variants and causative gene identification, as well as the prioritisation of novel and promising candidate genes.

CONCLUSIONS

mirTrios provides an intuitive interface for the general geneticist and clinician, and can be widely used for detection of DNMs and rare inherited mutations, and annotation in sporadic diseases. mirTrios is freely available at http://centre.bioinformatics.zj.cn/mirTrios/.

De novo FUS mutations in 2 Korean patients with sporadic amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is an adult-onset neurodegenerative disorder. Approximately 5% of ALS patients are familial (fALS) cases, and the remaining 95% are apparently sporadic (sALS) cases. To date, a number of genes have been discovered as associated with ALS, but the genetic background of sALS is not yet fully understood. The occurrence of de novo mutations in ALS genes might be an explanation for sALS, but reduced penetrance could be an alternative theory. Previously, we screened mutations in 5 ALS genes including SOD1 and FUS in 9 fALS and 249 sALS patients and found a total of 15 patients with either SOD1 (7 fALS and 3 sALS) or FUS (1 fALS and 4 sALS) mutations. Interestingly, only 1 fALS patient had the FUS mutation, whereas 4 sALS patients had mutations in this gene. To determine if the FUS mutations in sALS were de novo, we performed genetic analysis on 2 sALS patients with living parents. Genetic analysis confirmed that 2 FUS mutations, including the c.1483C>T (p.Arg495*) and the c.1509_1510delAG (p.Gly504Trpfs*12) mutations, were found only in the patients and not in their parents, confirming the de novo occurrence of these mutations. These findings support the notion that de novo mutations are responsible for a certain proportion of sALS.

Exon resequencing of H3K9 methyltransferase complex genes, EHMT1, EHTM2 and WIZ, in Japanese autism subjects

Background

Histone H3 methylation at lysine 9 (H3K9) is a conserved epigenetic signal, mediating heterochromatin formation by trimethylation, and transcriptional silencing by dimethylation. Defective GLP (Ehmt1) and G9a (Ehmt2) histone lysine methyltransferases, involved in mono and dimethylation of H3K9, confer autistic phenotypes and behavioral abnormalities in animal models. Moreover, EHMT1 loss of function results in Kleefstra syndrome, characterized by severe intellectual disability, developmental delays and psychiatric disorders. We examined the possible role of histone methyltransferases in the etiology of autism spectrum disorders (ASD) and suggest that rare functional variants in these genes that regulate H3K9 methylation may be associated with ASD.

Methods

Since G9a-GLP-Wiz forms a heteromeric methyltransferase complex, all the protein-coding regions and exon/intron boundaries of EHMT1, EHMT2 and WIZ were sequenced in Japanese ASD subjects. The detected variants were prioritized based on novelty and functionality. The expression levels of these genes were tested in blood cells and postmortem brain samples from ASD and control subjects. Expression of EHMT1 and EHMT2 isoforms were determined by digital PCR.

Results

We identified six nonsynonymous variants: three in EHMT1, two in EHMT2 and one in WIZ. Two variants, the EHMT1 ankyrin repeat domain (Lys968Arg) and EHMT2 SET domain (Thr961Ile) variants were present exclusively in cases, but showed no statistically significant association with ASD. The EHMT2 transcript expression was significantly elevated in the peripheral blood cells of ASD when compared with control samples; but not for EHMT1 and WIZ. Gene expression levels of EHMT1, EHMT2 and WIZ in Brodmann area (BA) 9, BA21, BA40 and the dorsal raphe nucleus (DoRN) regions from postmortem brain samples showed no significant changes between ASD and control subjects. Nor did expression levels of EHMT1 and EHMT2 isoforms in the prefrontal cortex differ significantly between ASD and control groups.

Conclusions

We identified two novel rare missense variants in the EHMT1 and EHMT2 genes of ASD patients. We surmise that these variants alone may not be sufficient to exert a significant effect on ASD pathogenesis. The elevated expression of EHMT2 in the peripheral blood cells may support the notion of a restrictive chromatin state in ASD, similar to schizophrenia.

Electronic supplementary material

The online version of this article (doi:10.1186/2040-2392-5-49) contains supplementary material, which is available to authorized users.

Research review: Polygenic methods and their application to psychiatric traits

BACKGROUND

Despite evidence from twin and family studies for an important contribution of genetic factors to both childhood and adult onset psychiatric disorders, identifying robustly associated specific DNA variants has proved challenging. In the pregenomics era the genetic architecture (number, frequency and effect size of risk variants) of complex genetic disorders was unknown. Empirical evidence for the genetic architecture of psychiatric disorders is emerging from the genetic studies of the last 5 years.

METHODS AND SCOPE

We review the methods investigating the polygenic nature of complex disorders. We provide mini-guides to genomic profile (or polygenic) risk scoring and to estimation of variance (or heritability) from common SNPs; a glossary of key terms is also provided. We review results of applications of the methods to psychiatric disorders and related traits and consider how these methods inform on missing heritability, hidden heritability and still-missing heritability.

FINDINGS

Genome-wide genotyping and sequencing studies are providing evidence that psychiatric disorders are truly polygenic, that is they have a genetic architecture of many genetic variants, including risk variants that are both common and rare in the population. Sample sizes published to date are mostly underpowered to detect effect sizes of the magnitude presented by nature, and these effect sizes may be constrained by the biological validity of the diagnostic constructs.

CONCLUSIONS

Increasing the sample size for genome wide association studies of psychiatric disorders will lead to the identification of more associated genetic variants, as already found for schizophrenia. These loci provide the starting point of functional analyses that might eventually lead to new prevention and treatment options and to improved biological validity of diagnostic constructs. Polygenic analyses will contribute further to our understanding of complex genetic traits as sample sizes increase and as sample resources become richer in phenotypic descriptors, both in terms of clinical symptoms and of nongenetic risk factors.

Managing the ethical challenges of next-generation sequencing in genomic medicine

INTRODUCTION

Next-generation sequencing (NGS) is transforming the conduct of genetic research and diagnostic investigation. This creates new challenges as it generates additional information, including unsought and unwanted information. Nevertheless, this information must be deliberately managed-interpreted, disclosed and then either stored or destroyed.

AREAS OF AGREEMENT

Handling the process of consent to exome or genome sequencing should include discussion about the possible detection of variants of uncertain significance (VUSs) or incidental findings (IFs) that the patient may prefer not to hear about. A plan should be drawn up that specifies whether and how the patient would be recontacted in the future with new interpretations.

AREAS OF CONTROVERSY

There is an active debate about which IFs or VUSs should be disclosed to the patient when an exome or genome sequence has been performed, or whether all findings of any possible relevance should always be disclosed. How this is managed has important implications for the initial explanation of the test to the patient and the process of consent. The assumption is often made that all sequence information should be stored, but this may not be sustainable or useful.

GROWING POINTS

Efforts are being made to build a consensus on what 'incidental' information should be disclosed. These policy questions are being addressed in many centres and practices are evolving rapidly.

AREAS TIMELY FOR DEVELOPING RESEARCH

Those interested in genetics, public health, bioethics and medical ethics may wish to debate these issues and influence future practice in both genetic research and genetic diagnostic services.

Advances in Genetic Discovery and Implications for Counseling of Patients and Families with Autism Spectrum Disorders

The prevalence of autism spectrum disorders (ASD) continues to increase. Genetic factors play an important role in the etiology of ASD, although specific genetic causes are identified in only a minority of cases. Recent advances have accelerated the discovery of genes implicated in ASD through convergent genomic analysis of genome-wide association studies, chromosomal microarray, exome sequencing, genome sequencing, and gene networks. Hundreds of candidate genes for ASD have been reported, yet only a handful have proven causative. Symptoms are complex and highly variable, and most cases are likely due to cumulative genetic factors, the interactions among them, as well as environmental factors. Here we summarize recent findings in genomic research regarding discovery of candidate genes, describe the major molecular processes in neural development that may be disrupted in ASD, and discuss the implication of research findings in clinical genetic diagnostic testing and counseling. Continued advances in genetic research will eventually translate into innovative approaches to prevention and treatment of ASD.

Autism and attention-deficit/hyperactivity disorder among individuals with a family history of alcohol use disorders

Recent studies suggest de novo mutations may involve the pathogenesis of autism and attention-deficit/hyperactivity disorder (ADHD). Based on the evidence that excessive alcohol consumption may be associated with an increased rate of de novo mutations in germ cells (sperms or eggs), we examine here whether the risks of autism and ADHD are increased among individuals with a family history of alcohol use disorders (AUDs). The standardized incidence ratios (SIRs) of autism and ADHD among individuals with a biological parental history of AUDs were 1.39 (95% CI 1.34–1.44) and 2.19 (95% CI 2.15–2.23), respectively, compared to individuals without an affected parent. Among offspring whose parents were diagnosed with AUDs before their birth, the corresponding risks were 1.46 (95% CI 1.36–1.58) and 2.70 (95% CI 2.59–2.81), respectively. Our study calls for extra surveillance for children with a family history of AUDs, and further studies examining the underlying mechanisms are needed.

DOI:http://dx.doi.org/10.7554/eLife.02917.001

Children learn to talk, manage their emotions, and control their behavior in a period when the brain is developing rapidly. The first signs of several developmental disorders, such as autism and attention-deficit/hyperactivity disorder (ADHD), may also emerge during this period. Children with autism may have difficulties with social interactions and communication, while those with attention-deficit/hyperactivity disorder may struggle to pay attention to a task and may be more active than other children.

Autism or ADHD are diagnosed based on the child's behavior because the underlying causes of the disorders are not well understood. Both genes and the environment have been linked to the conditions; and it was recently suggested that certain common genetic mutations are more common in children with ADHD or autism. However, as some of the mutations linked to autism are not found in the genes of the affected children's parents, it is likely that they occurred in either of the sperm or the egg cell from the parents.

Exposure to harmful substances in the environment can cause mutations in egg or sperm cells, or alter the expression of genes without changing the gene sequence. Excessive alcohol consumption is one environmental factor that can mutate genes or alter gene expression. Here, Sundquist et al. have looked to see if there is a relationship between a child having a parent with an alcohol use problem and the child's risk of developing autism or ADHD.

Examining national medical registries identified 24,157 people with autism and 49,348 with ADHD in Sweden between 1987 and 2010. Sundquist et al. discovered that autism and ADHD were more common in individuals who had a parent with a history of an alcohol use disorder than in those whose parents had no history of an alcohol use disorder. There was also an even greater risk of either condition if the parent had been diagnosed with an alcohol use problem before the birth of the child.

Adopted children who had a biological parent with an alcohol use disorder were at a greater risk of autism and ADHD than those whose adoptive parent had an alcohol use disorder. However, as very few adopted parents were diagnosed with an alcohol use problem, it is important to be cautious about drawing firm conclusions from this observation.

Sundquist et al. estimate that around 4% of autism cases and 11% of ADHD cases could be avoided if parents abstained from heavy alcohol consumption. Though these findings are consistent with parents with an alcohol use disorder being more likely to pass on mutations to their children, there are also other possible explanations. As such, further research examining the underlying cause is still needed.

DOI:http://dx.doi.org/10.7554/eLife.02917.002

Using familial information for variant filtering in high-throughput sequencing studies

High-throughput sequencing studies (HTS) have been highly successful in identifying the genetic causes of human disease, particularly those following Mendelian inheritance. Many HTS studies to date have been performed without utilizing available family relationships between samples. Here, we discuss the many merits and occasional pitfalls of using identity by descent information in conjunction with HTS studies. These methods are not only applicable to family studies but are also useful in cohorts of apparently unrelated, ‘sporadic’ cases and small families underpowered for linkage and allow inference of relationships between individuals. Incorporating familial/pedigree information not only provides powerful filtering options for the extensive variant lists that are usually produced by HTS but also allows valuable quality control checks, insights into the genetic model and the genotypic status of individuals of interest. In particular, these methods are valuable for challenging discovery scenarios in HTS analysis, such as in the study of populations poorly represented in variant databases typically used for filtering, and in the case of poor-quality HTS data.

Common DNA methylation alterations in multiple brain regions in autism

Autism spectrum disorders (ASD) are increasingly common neurodevelopmental disorders defined clinically by a triad of features including impairment in social interaction, impairment in communication in social situations and restricted and repetitive patterns of behavior and interests, with considerable phenotypic heterogeneity among individuals. Although heritability estimates for ASD are high, conventional genetic-based efforts to identify genes involved in ASD have yielded only few reproducible candidate genes that account for only a small proportion of ASDs. There is mounting evidence to suggest environmental and epigenetic factors play a stronger role in the etiology of ASD than previously thought. To begin to understand the contribution of epigenetics to ASD, we have examined DNA methylation (DNAm) in a pilot study of postmortem brain tissue from 19 autism cases and 21 unrelated controls, among three brain regions including dorsolateral prefrontal cortex, temporal cortex and cerebellum. We measured over 485,000 CpG loci across a diverse set of functionally relevant genomic regions using the Infinium HumanMethylation450 BeadChip and identified four genome-wide significant differentially methylated regions (DMRs) using a bump hunting approach and a permutation-based multiple testing correction method. We replicated 3/4 DMRs identified in our genome-wide screen in a different set of samples and across different brain regions. The DMRs identified in this study represent suggestive evidence for commonly altered methylation sites in ASD and provide several promising new candidate genes.

Whole-genome sequence variation, population structure and demographic history of the Dutch population

Whole-genome sequencing enables complete characterization of genetic variation, but geographic clustering of rare alleles demands many diverse populations be studied. Here we describe the Genome of the Netherlands (GoNL) Project, in which we sequenced the whole genomes of 250 Dutch parent-offspring families and constructed a haplotype map of 20.4 million single-nucleotide variants and 1.2 million insertions and deletions. The intermediate coverage (∼13×) and trio design enabled extensive characterization of structural variation, including midsize events (30-500 bp) previously poorly catalogued and de novo mutations. We demonstrate that the quality of the haplotypes boosts imputation accuracy in independent samples, especially for lower frequency alleles. Population genetic analyses demonstrate fine-scale structure across the country and support multiple ancient migrations, consistent with historical changes in sea level and flooding. The GoNL Project illustrates how single-population whole-genome sequencing can provide detailed characterization of genetic variation and may guide the design of future population studies.

Missense dopamine transporter mutations associate with adult parkinsonism and ADHD

Parkinsonism and attention deficit hyperactivity disorder (ADHD) are widespread brain disorders that involve disturbances of dopaminergic signaling. The sodium-coupled dopamine transporter (DAT) controls dopamine homeostasis, but its contribution to disease remains poorly understood. Here, we analyzed a cohort of patients with atypical movement disorder and identified 2 DAT coding variants, DAT-Ile312Phe and a presumed de novo mutant DAT-Asp421Asn, in an adult male with early-onset parkinsonism and ADHD. According to DAT single-photon emission computed tomography (DAT-SPECT) scans and a fluoro-deoxy-glucose-PET/MRI (FDG-PET/MRI) scan, the patient suffered from progressive dopaminergic neurodegeneration. In heterologous cells, both DAT variants exhibited markedly reduced dopamine uptake capacity but preserved membrane targeting, consistent with impaired catalytic activity. Computational simulations and uptake experiments suggested that the disrupted function of the DAT-Asp421Asn mutant is the result of compromised sodium binding, in agreement with Asp421 coordinating sodium at the second sodium site. For DAT-Asp421Asn, substrate efflux experiments revealed a constitutive, anomalous efflux of dopamine, and electrophysiological analyses identified a large cation leak that might further perturb dopaminergic neurotransmission. Our results link specific DAT missense mutations to neurodegenerative early-onset parkinsonism. Moreover, the neuropsychiatric comorbidity provides additional support for the idea that DAT missense mutations are an ADHD risk factor and suggests that complex DAT genotype and phenotype correlations contribute to different dopaminergic pathologies.

Large-scale genomics unveils the genetic architecture of psychiatric disorders

Family study results are consistent with genetic effects making substantial contributions to risk of psychiatric disorders such as schizophrenia, yet robust identification of specific genetic variants that explain variation in population risk had been disappointing until the advent of technologies that assay the entire genome in large samples. We highlight recent progress that has led to a better understanding of the number of risk variants in the population and the interaction of allele frequency and effect size. The emerging genetic architecture implies a large number of contributing loci (that is, a high genome-wide mutational target) and suggests that genetic risk of psychiatric disorders involves the combined effects of many common variants of small effect, as well as rare and de novo variants of large effect. The capture of a substantial proportion of genetic risk facilitates new study designs to investigate the combined effects of genes and the environment.

Brain-expressed exons under purifying selection are enriched for de novo mutations in autism spectrum disorder

A universal challenge in genetic studies of autism spectrum disorders (ASDs) is determining whether a given DNA sequence alteration will manifest as disease. Among different population controls, we observed, for specific exons, an inverse correlation between exon expression level in brain and burden of rare missense mutations. For genes that harbor de novo mutations predicted to be deleterious, we found that specific critical exons were significantly enriched in individuals with ASD relative to their siblings without ASD (P < 1.13 × 10(-38); odds ratio (OR) = 2.40). Furthermore, our analysis of genes with high exonic expression in brain and low burden of rare mutations demonstrated enrichment for known ASD-associated genes (P < 3.40 × 10(-11); OR = 6.08) and ASD-relevant fragile-X protein targets (P < 2.91 × 10(-157); OR = 9.52). Our results suggest that brain-expressed exons under purifying selection should be prioritized in genotype-phenotype studies for ASD and related neurodevelopmental conditions.

The total burden of rare, non-synonymous exome genetic variants is not associated with childhood or late-life cognitive ability

Human cognitive ability shows consistent, positive associations with fitness components across the life-course. Underlying genetic variation should therefore be depleted by selection, which is not observed. Genetic variation in general cognitive ability (intelligence) could be maintained by a mutation-selection balance, with rare variants contributing to its genetic architecture. This study examines the association between the total number of rare stop-gain/loss, splice and missense exonic variants and cognitive ability in childhood and old age in the same individuals. Exome array data were obtained in the Lothian Birth Cohorts of 1921 and 1936 (combined N = 1596). General cognitive ability was assessed at age 11 years and in late life (79 and 70 years, respectively) and was modelled against the total number of stop-gain/loss, splice, and missense exonic variants, with minor allele frequency less than or equal to 0.01, using linear regression adjusted for age and sex. In both cohorts and in both the childhood and late-life models, there were no significant associations between rare variant burden in the exome and cognitive ability that survived correction for multiple testing. Contrary to our a priori hypothesis, we observed no evidence for an association between the total number of rare exonic variants and either childhood cognitive ability or late-life cognitive ability.

Reading and language disorders: the importance of both quantity and quality

Reading and language disorders are common childhood conditions that often co-occur with each other and with other neurodevelopmental impairments. There is strong evidence that disorders, such as dyslexia and Specific Language Impairment (SLI), have a genetic basis, but we expect the contributing genetic factors to be complex in nature. To date, only a few genes have been implicated in these traits. Their functional characterization has provided novel insight into the biology of neurodevelopmental disorders. However, the lack of biological markers and clear diagnostic criteria have prevented the collection of the large sample sizes required for well-powered genome-wide screens. One of the main challenges of the field will be to combine careful clinical assessment with high throughput genetic technologies within multidisciplinary collaborations.

Explaining additional genetic variation in complex traits

Genome-wide association studies (GWAS) have provided valuable insights into the genetic basis of complex traits, discovering >6000 variants associated with >500 quantitative traits and common complex diseases in humans. The associations identified so far represent only a fraction of those that influence phenotype, because there are likely to be many variants across the entire frequency spectrum, each of which influences multiple traits, with only a small average contribution to the phenotypic variance. This presents a considerable challenge to further dissection of the remaining unexplained genetic variance within populations, which limits our ability to predict disease risk, identify new drug targets, improve and maintain food sources, and understand natural diversity. This challenge will be met within the current framework through larger sample size, better phenotyping, including recording of nongenetic risk factors, focused study designs, and an integration of multiple sources of phenotypic and genetic information. The current evidence supports the application of quantitative genetic approaches, and we argue that one should retain simpler theories until simplicity can be traded for greater explanatory power.