Ivan Iossifov

The contribution of de novo coding mutations to autism spectrum disorder

Whole exome sequencing has proven to be a powerful tool for understanding the genetic architecture of human disease. Here we apply it to more than 2,500 simplex families, each having a child with an autistic spectrum disorder. By comparing affected to unaffected siblings, we show that 13% of de novo missense mutations and 43% of de novo likely gene-disrupting (LGD) mutations contribute to 12% and 9% of diagnoses, respectively. Including copy number variants, coding de novo mutations contribute to about 30% of all simplex and 45% of female diagnoses. Almost all LGD mutations occur opposite wild-type alleles. LGD targets in affected females significantly overlap the targets in males of lower intelligence quotient (IQ), but neither overlaps significantly with targets in males of higher IQ. We estimate that LGD mutation in about 400 genes can contribute to the joint class of affected females and males of lower IQ, with an overlapping and similar number of genes vulnerable to contributory missense mutation. LGD targets in the joint class overlap with published targets for intellectual disability and schizophrenia, and are enriched for chromatin modifiers, FMRP-associated genes and embryonically expressed genes. Most of the significance for the latter comes from affected females.

Rare De Novo Variants Associated with Autism Implicate a Large Functional Network of Genes Involved in Formation and Function of Synapses

Identification of complex molecular networks underlying common human phenotypes is a major challenge of modern genetics. In this study, we develop a method for network-based analysis of genetic associations (NETBAG). We use NETBAG to identify a large biological network of genes affected by rare de novo CNVs in autism. The genes forming the network are primarily related to synapse development, axon targeting, and neuron motility. The identified network is strongly related to genes previously implicated in autism and intellectual disability phenotypes. Our results are also consistent with the hypothesis that significantly stronger functional perturbations are required to trigger the autistic phenotype in females compared to males. Overall, the presented analysis of de novo variants supports the hypothesis that perturbed synaptogenesis is at the heart of autism. More generally, our study provides proof of the principle that networks underlying complex human phenotypes can be identified by a network-based functional analysis of rare genetic variants.

GeneWays: a system for extracting, analyzing, visualizing, and integrating molecular pathway data

The immense growth in the volume of research literature and experimental data in the field of molecular biology calls for efficient automatic methods to capture and store information. In recent years, several groups have worked on specific problems in this area, such as automated selection of articles pertinent to molecular biology, or automated extraction of information using natural-language processing, information visualization, and generation of specialized knowledge bases for molecular biology. GeneWays is an integrated system that combines several such subtasks. It analyzes interactions between molecular substances, drawing on multiple sources of information to infer a consensus view of molecular networks. GeneWays is designed as an open platform, allowing researchers to query, review, and critique stored information.

The role of de novo mutations in the genetics of autism spectrum disorders.

The identification of the genetic components of autism spectrum disorders (ASDs) has advanced rapidly in recent years, particularly with the demonstration of de novo mutations as an important source of causality. We review these developments in light of genetic models for ASDs. We consider the number of genetic loci that underlie ASDs and the relative contributions from different mutational classes, and we discuss possible mechanisms by which these mutations might lead to dysfunction. We update the two-class risk genetic model for autism, especially in regard to children with high intelligence quotients.

De novo mutations in congenital heart disease with neurodevelopmental and other congenital anomalies

Putting both heart and brain at risk For reasons that are unclear, newborns with congenital heart disease (CHD) have a high risk of neurodevelopmental disabilities. Homsy et al. performed exome sequence analysis of 1200 CHD patients and their parents to identify spontaneously arising (de novo) mutations. Patients with both CHD and neurodevelopmental disorders had a much higher burden of damaging de novo mutations, particularly in genes with likely roles in both heart and brain development. Thus, clinical genotyping of patients with CHD may help to identify those at greatest risk of neurodevelopmental disabilities, allowing surveillance and early intervention. Science, this issue p. 1262 Genotyping of children with congenital heart disease may identify those at high risk of neurodevelopmental disorders. Congenital heart disease (CHD) patients have an increased prevalence of extracardiac congenital anomalies (CAs) and risk of neurodevelopmental disabilities (NDDs). Exome sequencing of 1213 CHD parent-offspring trios identified an excess of protein-damaging de novo mutations, especially in genes highly expressed in the developing heart and brain. These mutations accounted for 20% of patients with CHD, NDD, and CA but only 2% of patients with isolated CHD. Mutations altered genes involved in morphogenesis, chromatin modification, and transcriptional regulation, including multiple mutations in RBFOX2, a regulator of mRNA splicing. Genes mutated in other cohorts examined for NDD were enriched in CHD cases, particularly those with coexisting NDD. These findings reveal shared genetic contributions to CHD, NDD, and CA and provide opportunities for improved prognostic assessment and early therapeutic intervention in CHD patients.

Genome-wide linkage scan in a large bipolar disorder sample from the National Institute of Mental Health genetics initiative suggests putative loci for bipolar disorder, psychosis, suicide, and panic disorder

We conducted a 9-cM genome scan in a large bipolar pedigree sample from the National Institute of Mental Health genetics initiative (1060 individuals from 154 multiplex families). We performed parametric and nonparametric analyses using both standard diagnostic models and comorbid conditions thought to identify phenotypic subtypes: psychosis, suicidal behavior, and panic disorder. Our strongest linkage signals (genome-wide significance) were observed on chromosomes 10q25, 10p12, 16q24, 16p13, and 16p12 using standard diagnostic models, and on 6q25 (suicidal behavior), 7q21 (panic disorder) and 16p12 (psychosis) using phenotypic subtypes. Several other regions were suggestive of linkage, including 1p13 (psychosis), 1p21 (psychosis), 1q44, 2q24 (suicidal behavior), 2p25 (psychosis), 4p16 (psychosis, suicidal behavior), 5p15, 6p25 (psychosis), 8p22 (psychosis), 8q24, 10q21, 10q25 (suicidal behavior), 10p11 (psychosis), 13q32 and 19p13 (psychosis). Over half the implicated regions were identified using phenotypic subtypes. Several regions – 1p, 1q, 6q, 8p, 13q and 16p – have been previously reported to be linked to bipolar disorder. Our results suggest that dissection of the disease phenotype can enrich the harvest of linkage signals and expedite the search for susceptibility genes. This is the first large-scale linkage scan of bipolar disorder to analyze simultaneously bipolar disorder, psychosis, suicidal behavior, and panic disorder.

accurate de novo and transmitted indel detection in exome-capture data using microassembly

We present an open-source algorithm, Scalpel (http://scalpel.sourceforge.net/), which combines mapping and assembly for sensitive and specific discovery of insertions and deletions (indels) in exome-capture data. A detailed repeat analysis coupled with a self-tuning k-mer strategy allows Scalpel to outperform other state-of-the-art approaches for indel discovery, particularly in regions containing near-perfect repeats. We analyzed 593 families from the Simons Simplex Collection and demonstrated Scalpels power to detect long (≥30 bp) transmitted events and enrichment for de novo likely gene-disrupting indels in autistic children.

A comparative analysis of exome capture

BackgroundHuman exome resequencing using commercial target capture kits has been and is being used for sequencing large numbers of individuals to search for variants associated with various human diseases. We rigorously evaluated the capabilities of two solution exome capture kits. These analyses help clarify the strengths and limitations of those data as well as systematically identify variables that should be considered in the use of those data.ResultsEach exome kit performed well at capturing the targets they were designed to capture, which mainly corresponds to the consensus coding sequences (CCDS) annotations of the human genome. In addition, based on their respective targets, each capture kit coupled with high coverage Illumina sequencing produced highly accurate nucleotide calls. However, other databases, such as the Reference Sequence collection (RefSeq), define the exome more broadly, and so not surprisingly, the exome kits did not capture these additional regions.ConclusionsCommercial exome capture kits provide a very efficient way to sequence select areas of the genome at very high accuracy. Here we provide the data to help guide critical analyses of sequencing data derived from these products.

Analysis of Drosophila segmentation network identifies a JNK pathway factor overexpressed in kidney cancer

We constructed a large-scale functional network model in Drosophila melanogaster built around two key transcription factors involved in the process of embryonic segmentation. Analysis of the model allowed the identification of a new role for the ubiquitin E3 ligase complex factor SPOP. In Drosophila, the gene encoding SPOP is a target of segmentation transcription factors. Drosophila SPOP mediates degradation of the Jun kinase phosphatase Puckered, thereby inducing tumor necrosis factor (TNF)/Eiger–dependent apoptosis. In humans, we found that SPOP plays a conserved role in TNF-mediated JNK signaling and was highly expressed in 99% of clear cell renal cell carcinomas (RCCs), the most prevalent form of kidney cancer. SPOP expression distinguished histological subtypes of RCC and facilitated identification of clear cell RCC as the primary tumor for metastatic lesions.

Increased Frequency of De Novo Copy Number Variants in Congenital Heart Disease by Integrative Analysis of Single Nucleotide Polymorphism Array and Exome Sequence Data

Rationale: Congenital heart disease (CHD) is among the most common birth defects. Most cases are of unknown pathogenesis. Objective: To determine the contribution of de novo copy number variants (CNVs) in the pathogenesis of sporadic CHD. Methods and Results: We studied 538 CHD trios using genome-wide dense single nucleotide polymorphism arrays and whole exome sequencing. Results were experimentally validated using digital droplet polymerase chain reaction. We compared validated CNVs in CHD cases with CNVs in 1301 healthy control trios. The 2 complementary high-resolution technologies identified 63 validated de novo CNVs in 51 CHD cases. A significant increase in CNV burden was observed when comparing CHD trios with healthy trios, using either single nucleotide polymorphism array (P=7×10−5; odds ratio, 4.6) or whole exome sequencing data (P=6×10−4; odds ratio, 3.5) and remained after removing 16% of de novo CNV loci previously reported as pathogenic (P=0.02; odds ratio, 2.7). We observed recurrent de novo CNVs on 15q11.2 encompassing CYFIP1, NIPA1, and NIPA2 and single de novo CNVs encompassing DUSP1, JUN, JUP, MED15, MED9, PTPRE SREBF1, TOP2A, and ZEB2, genes that interact with established CHD proteins NKX2-5 and GATA4. Integrating de novo variants in whole exome sequencing and CNV data suggests that ETS1 is the pathogenic gene altered by 11q24.2-q25 deletions in Jacobsen syndrome and that CTBP2 is the pathogenic gene in 10q subtelomeric deletions. Conclusions: We demonstrate a significantly increased frequency of rare de novo CNVs in CHD patients compared with healthy controls and suggest several novel genetic loci for CHD.