Recent genome-wide association studies (GWAS) have implicated a range of genes from discrete biological pathways in the aetiology of autism. However, despite the strong influence of genetic factors, association studies have yet to identify statistically robust, replicated major effect genes or SNPs. We apply the principle of the SNP ratio test methodology described by O'Dushlaine et al to over 2100 families from the Autism Genome Project (AGP). Using a two-stage design we examine association enrichment in 5955 unique gene-ontology classifications across four groupings based on two phenotypic and two ancestral classifications. Based on estimates from simulation we identify excess of association enrichment across all analyses. We observe enrichment in association for sets of genes involved in diverse biological processes, including pyruvate metabolism, transcription factor activation, cell-signalling and cell-cycle regulation. Both genes and processes that show enrichment have previously been examined in autistic disorders and offer biologically plausibility to these findings.
autism; genome-wide association analysis; pathway analysis; family-based association test; gene ontology
As APOE locus variants contribute to both risk of late-onset Alzheimer disease and differences in age-at-onset, it is important to know if other established late-onset Alzheimer disease risk loci also affect age-at-onset in cases.
To investigate the effects of known Alzheimer disease risk loci in modifying age-at-onset, and to estimate their cumulative effect on age-at-onset variation, using data from genome-wide association studies in the Alzheimer’s Disease Genetics Consortium (ADGC).
Design, Setting and Participants
The ADGC comprises 14 case-control, prospective, and family-based datasets with data on 9,162 Caucasian participants with Alzheimer’s occurring after age 60 who also had complete age-at-onset information, gathered between 1989 and 2011 at multiple sites by participating studies. Data on genotyped or imputed single nucleotide polymorphisms (SNPs) most significantly associated with risk at ten confirmed LOAD loci were examined in linear modeling of AAO, and individual dataset results were combined using a random effects, inverse variance-weighted meta-analysis approach to determine if they contribute to variation in age-at-onset. Aggregate effects of all risk loci on AAO were examined in a burden analysis using genotype scores weighted by risk effect sizes.
Main Outcomes and Measures
Age at disease onset abstracted from medical records among participants with late-onset Alzheimer disease diagnosed per standard criteria.
Analysis confirmed association of APOE with age-at-onset (rs6857, P=3.30×10−96), with associations in CR1 (rs6701713, P=7.17×10−4), BIN1 (rs7561528, P=4.78×10−4), and PICALM (rs561655, P=2.23×10−3) reaching statistical significance (P<0.005). Risk alleles individually reduced age-at-onset by 3-6 months. Burden analyses demonstrated that APOE contributes to 3.9% of variation in age-at-onset (R2=0.220) over baseline (R2=0.189) whereas the other nine loci together contribute to 1.1% of variation (R2=0.198).
Conclusions and Relevance
We confirmed association of APOE variants with age-at-onset among late-onset Alzheimer disease cases and observed novel associations with age-at-onset in CR1, BIN1, and PICALM. In contrast to earlier hypothetical modeling, we show that the combined effects of Alzheimer disease risk variants on age-at-onset are on the scale of, but do not exceed, the APOE effect. While the aggregate effects of risk loci on age-at-onset may be significant, additional genetic contributions to age-at-onset are individually likely to be small.
Alzheimer Disease; Alzheimer Disease Genetics; Alzheimer’s Disease - Pathophysiology; Genetics of Alzheimer Disease; Aging
A key component of genetic architecture is the allelic spectrum influencing trait variability. For autism spectrum disorder (henceforth autism) the nature of its allelic spectrum is uncertain. Individual risk genes have been identified from rare variation, especially de novo mutations1–8. From this evidence one might conclude that rare variation dominates its allelic spectrum, yet recent studies show that common variation, individually of small effect, has substantial impact en masse9,10. At issue is how much of an impact relative to rare variation. Using a unique epidemiological sample from Sweden, novel methods that distinguish total narrow-sense heritability from that due to common variation, and by synthesizing results from other studies, we reach several conclusions about autism’s genetic architecture: its narrow-sense heritability is ≈54% and most traces to common variation; rare de novo mutations contribute substantially to individuals’ liability; still their contribution to variance in liability, 2.6%, is modest compared to heritable variation.
Attention deficit hyperactivity disorder (ADHD) is a common, heritable neuropsychiatric disorder of unknown etiology. We performed a whole-genome copy number variation (CNV) study on 1,013 cases with ADHD and 4,105 healthy children of European ancestry using 550,000 SNPs. We evaluated statistically significant findings in multiple independent cohorts, with a total of 2,493 cases with ADHD and 9,222 controls of European ancestry, using matched platforms. CNVs affecting metabotropic glutamate receptor genes were enriched across all cohorts (P = 2.1 × 10−9). We saw GRM5 (encoding glutamate receptor, metabotropic 5) deletions in ten cases and one control (P = 1.36 × 10−6). We saw GRM7 deletions in six cases, and we saw GRM8 deletions in eight cases and no controls. GRM1 was duplicated in eight cases. We experimentally validated the observed variants using quantitative RT-PCR. A gene network analysis showed that genes interacting with the genes in the GRM family are enriched for CNVs in ~10% of the cases (P = 4.38 × 10−10) after correction for occurrence in the controls. We identified rare recurrent CNVs affecting glutamatergic neurotransmission genes that were overrepresented in multiple ADHD cohorts.
Autism spectrum disorder (ASD) is now understood to have multiple genetic risk genes and one example is SHANK3. SHANK3 deletions and mutations disrupt synaptic function and result in Phelan-McDermid syndrome (PMS), which causes a monogenic form of ASD with a frequency of at least 0.5% of ASD cases. Recent evidence from preclinical studies with mouse and human neuronal models of SHANK3 deficiency suggest that insulin-like growth factor-1 (IGF-1) can reverse synaptic plasticity and motor learning deficits. The objective of this study was to pilot IGF-1 treatment in children with PMS to evaluate safety, tolerability, and efficacy for core deficits of ASD, including social impairment and restricted and repetitive behaviors.
Nine children with PMS aged 5 to 15 were enrolled in a placebo-controlled, double-blind, crossover design study, with 3 months of treatment with IGF-1 and 3 months of placebo in random order, separated by a 4-week wash-out period.
Compared to the placebo phase, the IGF-1 phase was associated with significant improvement in both social impairment and restrictive behaviors, as measured by the Aberrant Behavior Checklist and the Repetitive Behavior Scale, respectively. IGF-1 was found to be well tolerated and there were no serious adverse events in any participants.
This study establishes the feasibility of IGF-1 treatment in PMS and contributes pilot data from the first controlled treatment trial in the syndrome. Results also provide proof of concept to advance knowledge about developing targeted treatments for additional causes of ASD associated with impaired synaptic development and function.
Pinpointing the small number of causal variants among the abundant naturally occurring genetic variation is a difficult challenge, but a crucial one for understanding precise molecular mechanisms of disease and follow-up functional studies. We propose and investigate two complementary statistical approaches for identification of rare causal variants in sequencing studies: a backward elimination procedure based on groupwise association tests, and a hierarchical approach that can integrate sequencing data with diverse functional and evolutionary conservation annotations for individual variants. Using simulations, we show that incorporation of multiple bioinformatic predictors of deleteriousness, such as PolyPhen-2, SIFT and GERP++ scores, can improve the power to discover truly causal variants. As proof of principle, we apply the proposed methods to VPS13B, a gene mutated in the rare neurodevelopmental disorder called Cohen syndrome, and recently reported with recessive variants in autism. We identify a small set of promising candidates for causal variants, including two loss-of-function variants and a rare, homozygous probably-damaging variant that could contribute to autism risk.
Sequencing technologies allow identification of genetic variants down to single base resolution for a whole human genome. The vast majority of these variants (over 90%) are rare, with population frequencies less than 1%. Furthermore, in a specific study, many of the variants identified are not associated with the disease of interest, and identification of the small proportion of truly causal variants is a difficult task. Clearly, for causal variants that are rare enough to only appear a few times in a study, observed frequencies in cases and controls are not enough to distinguish them from the vast majority of random variation, and rich functional annotations can help identify the causal variants. Here we propose to develop a set of statistical methods that leverage diverse functional genomics annotations with sequencing data to identify a small set of potentially causal variants and estimate their effects. Pinpointing a subset of potentially causal variants is crucial for understanding precise biological mechanisms, and for further experimental functional studies.
SLC25A12, a susceptibility gene for autism spectrum disorders (ASDs) that is mutated in a neurodevelopmental syndrome, encodes a mitochondrial aspartate/glutamate carrier (AGC1). AGC1 is an important component of the malate/aspartate shuttle, a crucial system supporting oxidative phosphorylation and ATP production.
We characterized mice with a disruption of the Slc25a12 gene, followed by confirmatory in vitro studies.
Slc25a12-knockout mice, which showed no AGC1 by immunoblotting, were born normally but displayed delayed development and died around 3 weeks after birth. In P13-14 knockout brains, the brains were smaller with no obvious alteration in gross structure. However, we found a reduction in myelin basic protein (MBP)-positive fibers, consistent with a previous report. Furthermore, the neocortex of knockout mice contained abnormal neurofilamentous accumulations in neurons, suggesting defective axonal transport and/or neurodegeneration. Slice cultures prepared from knockout mice also showed a myelination defect, and reduction of Slc25a12 in rat primary oligodendrocytes led to a cellautonomous reduction in MBP expression. Myelin deficits in slice cultures from knockout mice could be reversed by administration of pyruvate, indicating that reduction in AGC1 activity leads to reduced production of aspartate/N-acetyl aspartate (NAA) and/or alterations in the NADH/NAD+ ratio, resulting in myelin defects.
Our data implicate AGC1 activity in myelination and in neuronal structure, and indicate that while loss of AGC1 leads to hypomyelination and neuronal changes, subtle alterations in AGC1 expression could affect brain development contributing to increased autism susceptibility.
Malate/aspartate shuttle; mitochondria; N-acetyl aspartate (NAA); neuron-oligodendrocyte interactions; pyruvate
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 of 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.
FCMTE; Whole Exome Sequencing; ACMSD; Kynurenine Pathway
Response to endotoxins is an important part of the organismal reaction to Gram-negative bacteria and plays a critical role in sepsis and septic shock, as well as other conditions such as metabolic endotoxemia. Humans are generally more sensitive to endotoxins when compared with experimental animals such as mice. Inflammatory caspases mediate endotoxin-induced IL-1β secretion and lethality in mice, and caspase-4 is an inflammatory caspase that is found in the human, and not mouse, genome. To test whether caspase-4 is involved in endotoxin sensitivity, we developed a transgenic mouse expressing human caspase-4 in its genomic context. Caspase-4 transgenic mice exhibited significantly higher endotoxin sensitivity, as measured by enhanced cytokine secretion and lethality following LPS challenge. Using bone marrow–derived macrophages, we then observed that caspase-4 can support activation of caspase-1 and secretion of IL-1β and IL-18 in response to priming signals (LPS or Pam3CSK4) alone, without the need for second signals to stimulate the assembly of the inflammasome. These findings indicate that the regulation of caspase-1 activity by human caspase-4 could represent a unique mechanism in humans, as compared with laboratory rodents, and may partially explain the higher sensitivity to endotoxins observed in humans. Regulation of the expression, activation, or activity of caspase-4 therefore represents targets for systemic inflammatory response syndrome, sepsis, septic shock, and related disorders.
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.
family- and population-based association tests; sequence data; burden and variance-component tests
Two common sources of DNA for whole exome sequencing (WES) are whole blood (WB) and immortalized lymphoblastoid cell line (LCL). However, it is possible that LCLs have a substantially higher rate of mutation than WB, causing concern for their use in sequencing studies. We compared results from paired WB and LCL DNA samples for 16 subjects, using LCLs of low passage number (<5). Using a standard analysis pipeline we detected a large number of discordant genotype calls (approximately 50 per subject) that we segregated into categories of “confidence” based on read-level quality metrics. From these categories and validation by Sanger sequencing, we estimate that the vast majority of the candidate differences were false positives and that our categories were effective in predicting valid sequence differences, including LCLs with putative mosaicism for the non-reference allele (3–4 per exome). These results validate the use of DNA from LCLs of low passage number for exome sequencing.
graphical diagnostics; lymphoblastoid cell line; mosaicism; sequence variant call; strand bias; somatic mutation
Alzheimer's disease (AD) and related dementias are a major public health challenge and present a therapeutic imperative for which we need additional insight into molecular pathogenesis. We performed a genome-wide association study and analysis of known genetic risk loci for AD dementia using neuropathologic data from 4,914 brain autopsies. Neuropathologic data were used to define clinico-pathologic AD dementia or controls, assess core neuropathologic features of AD (neuritic plaques, NPs; neurofibrillary tangles, NFTs), and evaluate commonly co-morbid neuropathologic changes: cerebral amyloid angiopathy (CAA), Lewy body disease (LBD), hippocampal sclerosis of the elderly (HS), and vascular brain injury (VBI). Genome-wide significance was observed for clinico-pathologic AD dementia, NPs, NFTs, CAA, and LBD with a number of variants in and around the apolipoprotein E gene (APOE). GalNAc transferase 7 (GALNT7), ATP-Binding Cassette, Sub-Family G (WHITE), Member 1 (ABCG1), and an intergenic region on chromosome 9 were associated with NP score; and Potassium Large Conductance Calcium-Activated Channel, Subfamily M, Beta Member 2 (KCNMB2) was strongly associated with HS. Twelve of the 21 non-APOE genetic risk loci for clinically-defined AD dementia were confirmed in our clinico-pathologic sample: CR1, BIN1, CLU, MS4A6A, PICALM, ABCA7, CD33, PTK2B, SORL1, MEF2C, ZCWPW1, and CASS4 with 9 of these 12 loci showing larger odds ratio in the clinico-pathologic sample. Correlation of effect sizes for risk of AD dementia with effect size for NFTs or NPs showed positive correlation, while those for risk of VBI showed a moderate negative correlation. The other co-morbid neuropathologic features showed only nominal association with the known AD loci. Our results discovered new genetic associations with specific neuropathologic features and aligned known genetic risk for AD dementia with specific neuropathologic changes in the largest brain autopsy study of AD and related dementias.
Alzheimer's disease (AD) and related dementias are a major public health challenge and present a therapeutic imperative for which we need additional insight into molecular pathogenesis. We performed a genome-wide association study (GWAS), as well as an analysis of known genetic risk loci for AD dementia, using data from 4,914 brain autopsies. Genome-wide significance was observed for 7 genes and pathologic features of AD and related diseases. Twelve of the 22 genetic risk loci for clinically-defined AD dementia were confirmed in our pathologic sample. Correlation of effect sizes for risk of AD dementia with effect size for hallmark pathologic features of AD were strongly positive and linear. Our study discovered new genetic associations with specific pathologic features and aligned known genetic risk for AD dementia with specific pathologic changes in a large brain autopsy study of AD and related dementias.
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 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.
Homozygosity mapping; whole exome sequencing; SYNJ1; autosomal recessive parkinsonism
Central arginine vasopressin receptor 1A (AVPR1A) modulates a wide range of behaviors, including stress management and territorial aggression, as well as social bonding and recognition. Inter- and intra-species variations in the expression pattern of AVPR1A in the brain and downstream differential behavioral phenotypes have been attributed to differences in the non-coding regions of the AVPR1A gene, including polymorphic elements within upstream regulatory areas. Gene association studies have suggested a link between AVPR1A polymorphisms and autism, and AVPR1A has emerged as a potential pharmacological target for treatment of social cognitive impairments and mood and anxiety disorders. To further investigate the genetic mechanism giving rise to species differences in AVPR1A expression patterns and associated social behaviors, and to create a preclinical mouse model useful for screening drugs targeting AVPR1A, we engineered and extensively characterized bacterial artificial chromosome (BAC) transgenic mice harboring the entire human AVPR1A locus with the surrounding regulatory elements. Compared with wild-type animals, the humanized mice displayed a more widely distributed ligand-AVPR1A binding pattern, which overlapped with that of primates. Furthermore, humanized AVPR1A mice displayed increased reciprocal social interactions compared with wild-type animals, but no differences in social approach and preference for social novelty were observed. Aspects of learning and memory, specifically novel object recognition and spatial relocation recognition, were unaffected. The biological alterations in humanized AVPR1A mice resulted in the rescue of the prepulse inhibition impairments that were observed in knockout mice, indicating conserved functionality. Although further behavioral paradigms and additional cohorts need to be examined in humanized AVPR1A mice, the results demonstrate that species-specific variations in the genomic content of regulatory regions surrounding the AVPR1A locus are responsible for differential receptor protein expression patterns across species and that they are likely to contribute to species-specific behavioral variation. The humanized AVPR1A mouse is a potential preclinical model for further understanding the regulation of receptor gene expression and the impact of variation in receptor expression on behaviors, and should be useful for screening drugs targeting human AVPR1A, taking advantage of the expression of human AVPR1A in human-relevant brain regions.
AVPR1A; Humanized mouse; Social behavior; Species-specific; Microsatellite; Autism
What gives an organism the ability to regrow tissues and to recover function where another organism fails is the central problem of regenerative biology. The challenge is to describe the mechanisms of regeneration at the molecular level, delivering detailed insights into the many components that are cross-regulated. In other words, a broad, yet deep dissection of the system-wide network of molecular interactions is needed. Functional genomics has been used to elucidate gene regulatory networks (GRNs) in developing tissues, which, like regeneration, are complex systems. Therefore, we reason that the GRN approach, aided by next generation technologies, can also be applied to study the molecular mechanisms underlying the complex functions of regeneration. We ask what characteristics a model system must have to support a GRN analysis. Our discussion focuses on regeneration in the central nervous system, where loss of function has particularly devastating consequences for an organism. We examine a cohort of cells conserved across all vertebrates, the reticulospinal (RS) neurons, which lend themselves well to experimental manipulations. In the lamprey, a jawless vertebrate, there are giant RS neurons whose large size and ability to regenerate make them particularly suited for a GRN analysis. Adding to their value, a distinct subset of lamprey RS neurons reproducibly fail to regenerate, presenting an opportunity for side-by-side comparison of gene networks that promote or inhibit regeneration. Thus, determining the GRN for regeneration in RS neurons will provide a mechanistic understanding of the fundamental cues that lead to success or failure to regenerate.
The Alzheimer amyloid protein precursor (APP) is subject to proteolysis by ADAM10 and ADAM17, precluding the formation of Aβ. Recently, coding variations in ADAM10 resulting in altered function have been reported in familial Alzheimer disease (AD). We carried out a large-scale (n=576: Controls, 271; AD, 305) resequencing study of ADAM10 in sporadic AD. Our results do not support a significant role for ADAM10 mutations in AD. Our results also make it clear that the careful examination of ancestry required in any case-control comparison is especially true with rare variations, where even a very small number of variations might form the basis of scientific conclusions.
Mutation; rare variation; genetics; association
Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 m genotypes from 25,580 Alzheimer's cases and 48,466 controls.
In addition to earlier reported genes, we detected genome-wide significant loci on chromosomes 8 (TP53INP1, p = 1.4×10−6) and 14 (IGHV1-67 p = 7.9×10−8) which indexed novel susceptibility loci.
The additional genes identified in this study, have an array of functions previously implicated in Alzheimer's disease, including aspects of energy metabolism, protein degradation and the immune system and add further weight to these pathways as potential therapeutic targets in Alzheimer's disease.
Eleven susceptibility loci for late-onset Alzheimer’s disease (LOAD) were identified by previous studies; however, a large portion of the genetic risk for this disease remains unexplained. We conducted a large, two-stage meta-analysis of genome-wide association studies (GWAS) in individuals of European ancestry. In stage 1, we used genotyped and imputed data (7,055,881 SNPs) to perform meta-analysis on 4 previously published GWAS data sets consisting of 17,008 Alzheimer’s disease cases and 37,154 controls. In stage 2,11,632 SNPs were genotyped and tested for association in an independent set of 8,572 Alzheimer’s disease cases and 11,312 controls. In addition to the APOE locus (encoding apolipoprotein E), 19 loci reached genome-wide significance (P < 5 × 10−8) in the combined stage 1 and stage 2 analysis, of which 11 are newly associated with Alzheimer’s disease.
Haploinsufficiency of SHANK3, caused by chromosomal abnormalities or mutations that disrupt one copy of the gene, leads to a neurodevelopmental syndrome called Phelan-McDermid syndrome, symptoms of which can include absent or delayed speech, intellectual disability, neurological changes and autism spectrum disorders. The SHANK3 protein forms a key structural part of the post-synaptic density. We previously generated and characterized mice with a targeted disruption of Shank3 in which exons coding for the ankyrin-repeat domain were deleted and expression of full-length Shank3 was disrupted. We documented specific deficits in synaptic function and plasticity, along with reduced reciprocal social interactions, in Shank3 heterozygous mice. Changes in phenotype owing to a mutation at a single locus are quite frequently modulated by other loci, most dramatically when the entire genetic background is changed. In mice, each strain of laboratory mouse represents a distinct genetic background and alterations in phenotype owing to gene knockout or transgenesis are frequently different across strains, which can lead to the identification of important modifier loci. We have investigated the effect of genetic background on phenotypes of Shank3 heterozygous, knockout and wild-type mice, using C57BL/6, 129SVE and FVB/Ntac strain backgrounds. We focused on observable behaviors with the goal of carrying out subsequent analyses to identify modifier loci. Surprisingly, there were very modest strain effects over a large battery of analyses. These results indicate that behavioral phenotypes associated with Shank3 haploinsufficiency are largely strain-independent.
Shank3; Phelan-McDermid syndrome; Autism spectrum disorders; 22q13; Mouse strain; Genetic modifier; Behavior
DNA mutational events are increasingly being identified in autism spectrum disorder (ASD), but the potential additional role of dysregulation of the epigenome in the pathogenesis of the condition remains unclear. The epigenome is of interest as a possible mediator of environmental effects during development, encoding a cellular memory reflected by altered function of progeny cells. Advanced maternal age (AMA) is associated with an increased risk of having a child with ASD for reasons that are not understood. To explore whether AMA involves covert aneuploidy or epigenetic dysregulation leading to ASD in the offspring, we tested a homogeneous ectodermal cell type from 47 individuals with ASD compared with 48 typically developing (TD) controls born to mothers of ≥35 years, using a quantitative genome-wide DNA methylation assay. We show that DNA methylation patterns are dysregulated in ectodermal cells in these individuals, having accounted for confounding effects due to subject age, sex and ancestral haplotype. We did not find mosaic aneuploidy or copy number variability to occur at differentially-methylated regions in these subjects. Of note, the loci with distinctive DNA methylation were found at genes expressed in the brain and encoding protein products significantly enriched for interactions with those produced by known ASD-causing genes, representing a perturbation by epigenomic dysregulation of the same networks compromised by DNA mutational mechanisms. The results indicate the presence of a mosaic subpopulation of epigenetically-dysregulated, ectodermally-derived cells in subjects with ASD. The epigenetic dysregulation observed in these ASD subjects born to older mothers may be associated with aging parental gametes, environmental influences during embryogenesis or could be the consequence of mutations of the chromatin regulatory genes increasingly implicated in ASD. The results indicate that epigenetic dysregulatory mechanisms may complement and interact with DNA mutations in the pathogenesis of the disorder.
Older mothers have a higher than expected risk of having a child with an autism spectrum disorder (ASD). The reason for this increased risk is unknown. The eggs of older mothers are more prone to abnormalities of chromosome numbers, suggesting this as one possible mechanism of the increased ASD risk. Age is also associated with a loss of control of epigenetic regulatory patterns that govern gene expression, indicating a second potential mechanism. To test both possibilities, we sampled cells from the same developmental origin as the brain, and performed genome-wide tests looking for unusual chromosome numbers and DNA methylation patterns. The studies were performed on individuals with ASD and typically developing controls, all born to mothers at least 35 years of age at the time of birth. We found the cells from individuals with ASD to have changes in DNA methylation at a number of loci, especially near genes encoding proteins known to interact with those already implicated in ASD. We conclude that epigenetic dysregulation occurring in gametes or early embryonic life may be one of the contributors to the development of ASD.
There is an urgent need for expanding and enhancing autism spectrum disorder (ASD) samples, in order to better understand causes of ASD.
In a unique public-private partnership, 13 sites with extensive experience in both the assessment and diagnosis of ASD embarked on an ambitious, 2-year program to collect samples for genetic and phenotypic research and begin analyses on these samples. The program was called The Autism Simplex Collection (TASC). TASC sample collection began in 2008 and was completed in 2010, and included nine sites from North America and four sites from Western Europe, as well as a centralized Data Coordinating Center.
Over 1,700 trios are part of this collection, with DNA from transformed cells now available through the National Institute of Mental Health (NIMH). Autism Diagnostic Interview-Revised (ADI-R) and Autism Diagnostic Observation Schedule-Generic (ADOS-G) measures are available for all probands, as are standardized IQ measures, Vineland Adaptive Behavioral Scales (VABS), the Social Responsiveness Scale (SRS), Peabody Picture Vocabulary Test (PPVT), and physical measures (height, weight, and head circumference). At almost every site, additional phenotypic measures were collected, including the Broad Autism Phenotype Questionnaire (BAPQ) and Repetitive Behavior Scale-Revised (RBS-R), as well as the non-word repetition scale, Communication Checklist (Children’s or Adult), and Aberrant Behavior Checklist (ABC). Moreover, for nearly 1,000 trios, the Autism Genome Project Consortium (AGP) has carried out Illumina 1 M SNP genotyping and called copy number variation (CNV) in the samples, with data being made available through the National Institutes of Health (NIH). Whole exome sequencing (WES) has been carried out in over 500 probands, together with ancestry matched controls, and this data is also available through the NIH. Additional WES is being carried out by the Autism Sequencing Consortium (ASC), where the focus is on sequencing complete trios. ASC sequencing for the first 1,000 samples (all from whole-blood DNA) is complete and data will be released in 2014. Data is being made available through NIH databases (database of Genotypes and Phenotypes (dbGaP) and National Database for Autism Research (NDAR)) with DNA released in Dist 11.0. Primary funding for the collection, genotyping, sequencing and distribution of TASC samples was provided by Autism Speaks and the NIH, including the National Institute of Mental Health (NIMH) and the National Human Genetics Research Institute (NHGRI).
TASC represents an important sample set that leverages expert sites. Similar approaches, leveraging expert sites and ongoing studies, represent an important path towards further enhancing available ASD samples.
Autism spectrum disorders (ASD) are a group of related neurodevelopmental disorders with significant combined prevalence (~1%) and high heritability. Dozens of individually rare genes and loci associated with high-risk for ASD have been identified, which overlap extensively with genes for intellectual disability (ID). However, studies indicate that there may be hundreds of genes that remain to be identified. The advent of inexpensive massively parallel nucleotide sequencing can reveal the genetic underpinnings of heritable complex diseases, including ASD and ID. However, whole exome sequencing (WES) and whole genome sequencing (WGS) provides an embarrassment of riches, where many candidate variants emerge. It has been argued that genetic variation for ASD and ID will cluster in genes involved in distinct pathways and protein complexes. For this reason, computational methods that prioritize candidate genes based on additional functional information such as protein-protein interactions or association with specific canonical or empirical pathways, or other attributes, can be useful. In this study we applied several supervised learning approaches to prioritize ASD or ID disease gene candidates based on curated lists of known ASD and ID disease genes. We implemented two network-based classifiers and one attribute-based classifier to show that we can rank and classify known, and predict new, genes for these neurodevelopmental disorders. We also show that ID and ASD share common pathways that perturb an overlapping synaptic regulatory subnetwork. We also show that features relating to neuronal phenotypes in mouse knockouts can help in classifying neurodevelopmental genes. Our methods can be applied broadly to other diseases helping in prioritizing newly identified genetic variation that emerge from disease gene discovery based on WES and WGS.
High-throughput sequencing; massively parallel sequencing; gene discovery; networks; pathways; neurodevelopmental disorders; classifiers; support vector machine
Multiple lines of evidence in schizophrenia, from brain imaging, studies in postmortem brains, and genetic association studies, have implicated oligodendrocyte and myelin dysfunction in this disease. Recent studies suggest that oligodendrocyte and myelin dysfunction leads to changes in synaptic formation and function, which could lead to cognitive dysfunction, a core symptom of schizophrenia. Furthermore, there is accumulating data linking oligodendrocyte and myelin dysfunction with dopamine and glutamate abnormalities, both of which are found in schizophrenia. These findings implicate oligodendrocyte and myelin dysfunction as a primary change in schizophrenia, not only as secondary consequences of the illness or treatment. Strategies targeting oligodendrocyte and myelin abnormalities could therefore provide therapeutic opportunities for patients suffering from schizophrenia.
myelin; gene expression; genetic association; brain imaging; oligodendrocyte; synaptic plasticity; dopamine; glutamate
SCN2A is a gene that codes for the alpha subunit of voltage-gated, type II sodium channels, and is highly expressed in the brain. Sodium channel disruptions, such as mutations in SCN2A, may play an important role in psychiatric disorders. Recently, de novo SCN2A mutations in autism spectrum disorder (ASD) have been identified. The current study characterizes a de novo splice site mutation in SCN2A that alters mRNA and protein products.
We describe results from clinical and genetic characterizations of a seven-year-old boy with ASD. Psychiatric interview and gold standard autism diagnostic instruments (ADOS and ADI-R) were used to confirm ASD diagnosis, in addition to performing standardized cognitive and adaptive functioning assessments (Leiter-R and Vineland Adaptive Behavior Scale), and sensory reactivity assessments (Sensory Profile and Sensory Processing Scales). Genetic testing by whole exome sequencing revealed four de novo events, including a splice site mutation c.476 + 1G > A in SCN2A, a missense mutation (c.2263G > A) causing a p.V755I change in the TLE1 gene, and two synonymous mutations (c.2943A > G in the BUB1 gene, and c.1254 T > A in C10orf68 gene). The de novo SCN2A splice site mutation produced a stop codon 10 amino acids downstream, possibly resulting in a truncated protein and/or a nonsense-mediated mRNA decay. The participant met new DSM-5 criteria for ASD, presenting with social and communication impairment, repetitive behaviors, and sensory reactivity issues. The participant’s adaptive and cognitive skills fell in the low range of functioning.
This report indicates that a splice site mutation in SCN2A might be contributing to the risk of ASD. Describing the specific phenotype associated with SCN2A mutations might help to reduce heterogeneity seen in ASD.
DSM-5; autism spectrum disorder; de novo SCN2A splice site mutation
De novo loss-of-function (dnLoF) mutations are found twofold more often in autism spectrum disorder (ASD) probands than their unaffected siblings. Multiple independent dnLoF mutations in the same gene implicate the gene in risk and hence provide a systematic, albeit arduous, path forward for ASD genetics. It is likely that using additional non-genetic data will enhance the ability to identify ASD genes.
To accelerate the search for ASD genes, we developed a novel algorithm, DAWN, to model two kinds of data: rare variations from exome sequencing and gene co-expression in the mid-fetal prefrontal and motor-somatosensory neocortex, a critical nexus for risk. The algorithm casts the ensemble data as a hidden Markov random field in which the graph structure is determined by gene co-expression and it combines these interrelationships with node-specific observations, namely gene identity, expression, genetic data and the estimated effect on risk.
Using currently available genetic data and a specific developmental time period for gene co-expression, DAWN identified 127 genes that plausibly affect risk, and a set of likely ASD subnetworks. Validation experiments making use of published targeted resequencing results demonstrate its efficacy in reliably predicting ASD genes. DAWN also successfully predicts known ASD genes, not included in the genetic data used to create the model.
Validation studies demonstrate that DAWN is effective in predicting ASD genes and subnetworks by leveraging genetic and gene expression data. The findings reported here implicate neurite extension and neuronal arborization as risks for ASD. Using DAWN on emerging ASD sequence data and gene expression data from other brain regions and tissues would likely identify novel ASD genes. DAWN can also be used for other complex disorders to identify genes and subnetworks in those disorders.
Autism; Risk prediction; Gene discovery; Weighted gene co-expression network analysis; Network; Hidden Markov random field; Neurite extension; Neuronal arborization