Vladimir Makarov

Patterns and rates of exonic de novo mutations in autism spectrum disorders

Autism spectrum disorders (ASD) are believed to have genetic and environmental origins, yet in only a modest fraction of individuals can specific causes be identified. To identify further genetic risk factors, here we assess the role of de novo mutations in ASD by sequencing the exomes of ASD cases and their parents (n = 175 trios). Fewer than half of the cases (46.3%) carry a missense or nonsense de novo variant, and the overall rate of mutation is only modestly higher than the expected rate. In contrast, the proteins encoded by genes that harboured de novo missense or nonsense mutations showed a higher degree of connectivity among themselves and to previous ASD genes as indexed by protein-protein interaction screens. The small increase in the rate of de novo events, when taken together with the protein interaction results, are consistent with an important but limited role for de novo point mutations in ASD, similar to that documented for de novo copy number variants. Genetic models incorporating these data indicate that most of the observed de novo events are unconnected to ASD; those that do confer risk are distributed across many genes and are incompletely penetrant (that is, not necessarily sufficient for disease). Our results support polygenic models in which spontaneous coding mutations in any of a large number of genes increases risk by 5- to 20-fold. Despite the challenge posed by such models, results from de novo events and a large parallel case–control study provide strong evidence in favour of CHD8 and KATNAL2 as genuine autism risk factors.

Microduplications of 16p11.2 are associated with schizophrenia.

Recurrent microdeletions and microduplications of a 600-kb genomic region of chromosome 16p11.2 have been implicated in childhood-onset developmental disorders. We report the association of 16p11.2 microduplications with schizophrenia in two large cohorts. The microduplication was detected in 12/1,906 (0.63%) cases and 1/3,971 (0.03%) controls (P = 1.2 × 10−5, OR = 25.8) from the initial cohort, and in 9/2,645 (0.34%) cases and 1/2,420 (0.04%) controls (P = 0.022, OR = 8.3) of the replication cohort. The 16p11.2 microduplication was associated with a 14.5-fold increased risk of schizophrenia (95% CI (3.3, 62)) in the combined sample. A meta-analysis of datasets for multiple psychiatric disorders showed a significant association of the microduplication with schizophrenia (P = 4.8 × 10−7), bipolar disorder (P = 0.017) and autism (P = 1.9 × 10−7). In contrast, the reciprocal microdeletion was associated only with autism and developmental disorders (P = 2.3 × 10−13). Head circumference was larger in patients with the microdeletion than in patients with the microduplication (P = 0.0007).

Sensitive and accurate detection of copy number variants using read depth of coverage

Methods for the direct detection of copy number variation (CNV) genome-wide have become effective instruments for identifying genetic risk factors for disease. The application of next-generation sequencing platforms to genetic studies promises to improve sensitivity to detect CNVs as well as inversions, indels, and SNPs. New computational approaches are needed to systematically detect these variants from genome sequence data. Existing sequence-based approaches for CNV detection are primarily based on paired-end read mapping (PEM) as reported previously by Tuzun et al. and Korbel et al. Due to limitations of the PEM approach, some classes of CNVs are difficult to ascertain, including large insertions and variants located within complex genomic regions. To overcome these limitations, we developed a method for CNV detection using read depth of coverage. Event-wise testing (EWT) is a method based on significance testing. In contrast to standard segmentation algorithms that typically operate by performing likelihood evaluation for every point in the genome, EWT works on intervals of data points, rapidly searching for specific classes of events. Overall false-positive rate is controlled by testing the significance of each possible event and adjusting for multiple testing. Deletions and duplications detected in an individual genome by EWT are examined across multiple genomes to identify polymorphism between individuals. We estimated error rates using simulations based on real data, and we applied EWT to the analysis of chromosome 1 from paired-end shotgun sequence data (30x) on five individuals. Our results suggest that analysis of read depth is an effective approach for the detection of CNVs, and it captures structural variants that are refractory to established PEM-based methods.

Duplications of the neuropeptide receptor gene VIPR2 confer significant risk for schizophrenia

Rare copy number variants (CNVs) have a prominent role in the aetiology of schizophrenia and other neuropsychiatric disorders. Substantial risk for schizophrenia is conferred by large (>500-kilobase) CNVs at several loci, including microdeletions at 1q21.1 (ref. 2), 3q29 (ref. 3), 15q13.3 (ref. 2) and 22q11.2 (ref. 4) and microduplication at 16p11.2 (ref. 5). However, these CNVs collectively account for a small fraction (2–4%) of cases, and the relevant genes and neurobiological mechanisms are not well understood. Here we performed a large two-stage genome-wide scan of rare CNVs and report the significant association of copy number gains at chromosome 7q36.3 with schizophrenia. Microduplications with variable breakpoints occurred within a 362-kilobase region and were detected in 29 of 8,290 (0.35%) patients versus 2 of 7,431 (0.03%) controls in the combined sample. All duplications overlapped or were located within 89 kilobases upstream of the vasoactive intestinal peptide receptor gene VIPR2. VIPR2 transcription and cyclic-AMP signalling were significantly increased in cultured lymphocytes from patients with microduplications of 7q36.3. These findings implicate altered vasoactive intestinal peptide signalling in the pathogenesis of schizophrenia and indicate the VPAC2 receptor as a potential target for the development of new antipsychotic drugs.

High Frequencies of De Novo CNVs in Bipolar Disorder and Schizophrenia

While it is known that rare copy-number variants (CNVs) contribute to risk for some neuropsychiatric disorders, the role of CNVs in bipolar disorder is unclear. Here, we reasoned that a contribution of CNVs to mood disorders might be most evident for de novo mutations. We performed a genome-wide analysis of de novo CNVs in a cohort of 788 trios. Diagnoses of offspring included bipolar disorder (nxa0= 185), schizophrenia (nxa0= 177), and healthy controls (nxa0= 426). Frequencies of de novo CNVs were significantly higher in bipolar disorder as compared with controls (ORxa0= 4.8 [1.4,16.0], pxa0= 0.009). De novo CNVs were particularly enriched among cases with an age at onset younger than 18 (ORxa0= 6.3 [1.7,22.6], pxa0= 0.006). We also confirmed a significant enrichment of de novo CNVs in schizophrenia (ORxa0= 5.0 [1.5,16.8], pxa0= 0.007). Our results suggest that rare spontaneous mutations are an important contributor to risk for bipolar disorder and other major neuropsychiatric diseases.

The Sac1 Domain of SYNJ1 Identified Mutated in a Family with Early-Onset Progressive Parkinsonism with Generalized Seizures

This study aimed to elucidate the genetic causes underlying early‐onset Parkinsonism (EOP) in a consanguineous Iranian family. To attain this, homozygosity mapping and whole‐exome sequencing were performed. As a result, a homozygous mutation (c.773G>A; p.Arg258Gln) lying within the NH2‐terminal Sac1‐like inositol phosphatase domain of polyphosphoinositide phosphatase synaptojanin 1 (SYNJ1), which has been implicated in the regulation of endocytic traffic at synapses, was identified as the disease‐segregating mutation. This mutation impaired the phosphatase activity of SYNJ1 against its Sac1 domain substrates in vitro. We concluded that the SYNJ1 mutation identified here is responsible for the EOP phenotype seen in our patients probably due to deficiencies in its phosphatase activity and consequent impairment of its synaptic functions. Our finding not only opens new avenues of investigation in the synaptic dysfunction mechanisms associated with Parkinsonism, but also suggests phosphoinositide metabolism as a novel therapeutic target for Parkinsonism.

Analysis of Rare, Exonic Variation amongst Subjects with Autism Spectrum Disorders and Population Controls

We report on results from whole-exome sequencing (WES) of 1,039 subjects diagnosed with autism spectrum disorders (ASD) and 870 controls selected from the NIMH repository to be of similar ancestry to cases. The WES data came from two centers using different methods to produce sequence and to call variants from it. Therefore, an initial goal was to ensure the distribution of rare variation was similar for data from different centers. This proved straightforward by filtering called variants by fraction of missing data, read depth, and balance of alternative to reference reads. Results were evaluated using seven samples sequenced at both centers and by results from the association study. Next we addressed how the data and/or results from the centers should be combined. Gene-based analyses of association was an obvious choice, but should statistics for association be combined across centers (meta-analysis) or should data be combined and then analyzed (mega-analysis)? Because of the nature of many gene-based tests, we showed by theory and simulations that mega-analysis has better power than meta-analysis. Finally, before analyzing the data for association, we explored the impact of population structure on rare variant analysis in these data. Like other recent studies, we found evidence that population structure can confound case-control studies by the clustering of rare variants in ancestry space; yet, unlike some recent studies, for these data we found that principal component-based analyses were sufficient to control for ancestry and produce test statistics with appropriate distributions. After using a variety of gene-based tests and both meta- and mega-analysis, we found no new risk genes for ASD in this sample. Our results suggest that standard gene-based tests will require much larger samples of cases and controls before being effective for gene discovery, even for a disorder like ASD.

Family-based association tests for sequence data, and comparisons with population-based association tests

Recent advances in high-throughput sequencing technologies make it increasingly more efficient to sequence large cohorts for many complex traits. We discuss here a class of sequence-based association tests for family-based designs that corresponds naturally to previously proposed population-based tests, including the classical Burden and variance-component tests. This framework allows for a direct comparison between the powers of sequence-based association tests with family- vs population-based designs. We show that for dichotomous traits using family-based controls results in similar power levels as the population-based design (although at an increased sequencing cost for the family-based design), while for continuous traits (in random samples, no ascertainment) the population-based design can be substantially more powerful. A possible disadvantage of population-based designs is that they can lead to increased false-positive rates in the presence of population stratification, while the family-based designs are robust to population stratification. We show also an application to a small exome-sequencing family-based study on autism spectrum disorders. The tests are implemented in publicly available software.

AnnTools: a comprehensive and versatile annotation toolkit for genomic variants

UNLABELLEDnAnnTools is a versatile bioinformatics application designed for comprehensive annotation of a full spectrum of human genome variation: novel and known single-nucleotide substitutions (SNP/SNV), short insertions/deletions (INDEL) and structural variants/copy number variation (SV/CNV). The variants are interpreted by interrogating data compiled from 15 constantly updated sources. In addition to detailed functional characterization of the coding variants, AnnTools searches for overlaps with regulatory elements, disease/trait associated loci, known segmental duplications and artifact prone regions, thereby offering an integrated and comprehensive analysis of genomic data. The tool conveniently accepts user-provided tracks for custom annotation and offers flexibility in input data formats. The output is generated in the universal Variant Call Format. High annotation speed makes AnnTools suitable for high-throughput sequencing facilities, while a low-memory footprint and modest CPU requirements allow it to operate on a personal computer. The application is freely available for public use; the package includes installation scripts and a set of helper tools.nnnAVAILABILITYnhttp://anntools.sourceforge.net/.nnnSUPPLEMENTARY INFORMATIONnSupplementary data are available at Bioinformatics online.

The ACMSD gene, involved in tryptophan metabolism, is mutated in a family with cortical myoclonus, epilepsy, and parkinsonism

Familial cortical myoclonic tremor and epilepsy is a phenotypically and genetically heterogeneous autosomal dominant disorder characterized by the presence of cortical myoclonic tremor and epilepsy that is often accompanied by additional neurological features. Despite the numerous familial studies performed and the number of loci identified, there is no gene associated with this syndrome. It is expected that through the application of novel genomic technologies, such as whole exome sequencing and whole genome sequencing, a substantial number of novel genes will come to light in the coming years. In this study, we describe the identification of two disease-segregating mutations in a large family featuring cortical myoclonic tremor with epilepsy and parkinsonism. Due to the previous association of ACMSD deficiency with the development of epileptic seizures, we concluded that the identified nonsense mutation in the ACMSD gene, which encodes for a critical enzyme of the kynurenine pathway of the tryptophan metabolism, is the disease-segregating mutation most likely to be responsible for the phenotype described in our family. This finding not only reveals the identification of the first gene associated with familial cortical myoclonic tremor and epilepsy but also discloses the kynurenine pathway as a potential therapeutic target for the treatment of this devastating syndrome.Key messageACMSD is mutated in a family with cortical myoclonus, epilepsy, and parkinsonism.ACMSD mutation contributes to the development of FCMTEQA accumulation is likely to play an important role in the pathogenesis of FCMTE.The kynurenine pathway as a potential drug target for the treatment of epilepsy.