Parent-of-origin effects in autism identified through genome-wide linkage analysis of 16,000 SNPs

Comprehensive exploration of multi-modal and multi-branch imaging markers for autism diagnosis and interpretation: insights from an advanced deep learning model

Autism spectrum disorder is a complex neurodevelopmental condition with diverse genetic and brain involvement. Despite magnetic resonance imaging advances, autism spectrum disorder diagnosis and understanding its neurogenetic factors remain challenging. We propose a dual-branch graph neural network that effectively extracts and fuses features from bimodalities, achieving 73.9% diagnostic accuracy. To explain the mechanism distinguishing autism spectrum disorder from healthy controls, we establish a perturbation model for brain imaging markers and perform a neuro-transcriptomic joint analysis using partial least squares regression and enrichment to identify potential genetic biomarkers. The perturbation model identifies brain imaging markers related to structural magnetic resonance imaging in the frontal, temporal, parietal, and occipital lobes, while functional magnetic resonance imaging markers primarily reside in the frontal, temporal, occipital lobes, and cerebellum. The neuro-transcriptomic joint analysis highlights genes associated with biological processes, such as "presynapse," "behavior," and "modulation of chemical synaptic transmission" in autism spectrum disorder's brain development. Different magnetic resonance imaging modalities offer complementary information for autism spectrum disorder diagnosis. Our dual-branch graph neural network achieves high accuracy and identifies abnormal brain regions and the neuro-transcriptomic analysis uncovers important genetic biomarkers. Overall, our study presents an effective approach for assisting in autism spectrum disorder diagnosis and identifying genetic biomarkers, showing potential for enhancing the diagnosis and treatment of this condition.

UBE3A: The Role in Autism Spectrum Disorders (ASDs) and a Potential Candidate for Biomarker Studies and Designing Therapeutic Strategies

Published reports from the CDC's Autism and Development Disabilities Monitoring Networks have shown that an average of 1 in every 44 (2.3%) 8-year-old children were estimated to have ASD in 2018. Many of the ASDs exhibiting varying degrees of autism-like phenotypes have chromosomal anomalies in the Chr15q11-q13 region. Numerous potential candidate genes linked with ASD reside in this chromosomal segment. However, several clinical, in vivo, and in vitro studies selected one gene more frequently than others randomly and unbiasedly. This gene codes for UBE3A or Ubiquitin protein ligase E3A [also known as E6AP ubiquitin-protein ligase (E6AP)], an enzyme involved in the cellular degradation of proteins. This gene has been listed as one of the several genes with a high potential of causing ASD in the Autism Database. The gain of function mutations, triplication, or duplication in the UBE3A gene is also associated with ASDs like Angelman Syndrome (AS) and Dup15q Syndrome. The genetic imprinting of UBE3A in the brain and a preference for neuronal maternal-specific expression are the key features of various ASDs. Since the UBE3A gene is involved in two main important diseases associated with autism-like symptoms, there has been widespread research going on in understanding the link between this gene and autism. Additionally, since no universal methodology or mechanism exists for identifying UBE3A-mediated ASD, it continues to be challenging for neurobiologists, neuroscientists, and clinicians to design therapies or diagnostic tools. In this review, we focus on the structure and functional aspects of the UBE3A protein, discuss the primary relevance of the 15q11-q13 region in the cause of ASDs, and highlight the link between UBE3A and ASD. We try to broaden the knowledge of our readers by elaborating on the possible mechanisms underlying UBE3A-mediated ASDs, emphasizing the usage of UBE3A as a prospective biomarker in the preclinical diagnosis of ASDs and discuss the positive outcomes, advanced developments, and the hurdles in the field of therapeutic strategies against UBE3A-mediated ASDs. This review is novel as it lays a very detailed and comprehensive platform for one of the most important genes associated with diseases showing autistic-like symptoms. Additionally, this review also attempts to lay optimistic feedback on the possible steps for the diagnosis, prevention, and therapy of these UBE3A-mediated ASDs in the upcoming years.

Analysis of convergence of linkage and association studies in autism spectrum disorders

Autism spectrum disorder (ASD) is a clinically and genetically heterogeneous group of pervasive neurodevelopmental disorders with a strong hereditary component. Although genome-wide linkage studies (GWLS) and [genome-wide association studies (GWAS)] have previously identified hundreds of ASD risk gene loci, the results remain inconclusive. In this study, a genomic convergence approach of GWAS and GWLS for ASD was implemented for the first time in order to identify genomic loci supported by both methods. A database with 32 GWLS and five GWAS for ASD was created. Convergence was quantified as the proportion of significant GWAS markers located within linked regions. Convergence was not found to be significantly higher than expected by chance (z-test = 1,177, P = 0,239). Although convergence is supportive of genuine effects, the lack of agreement between GWLS and GWAS is also indicative that these studies are designed to answer different questions and are not equally well suited for deciphering the genetics of complex traits.

Epigenetic Interface of Autism Spectrum Disorders (ASDs): Implications of Chromosome 15q11-q13 Segment

Autism spectrum disorders (ASDs) are multifactorial in nature and include both genetic and environmental factors. The increasing evidence advocates an important role of epigenetics in ASD etiology. One of the most common forms of epigenetic changes observed in the case of neurodevelopmental disorders is imprinting which is tightly regulated by developmental and tissue-specific mechanisms. Interestingly, many of these disorders that demonstrate autism-like phenotypes at varying degrees have found involvement of chromosome 15q11-q13 segment. Numerous studies demonstrate occurrence of ASD in the presence of chromosomal abnormalities located mainly in Chr15q11-q13 region. Several plausible candidate genes associated with ASD are in this chromosomal segment, including gamma aminobutyric acid A (GABA_A) receptor genes GABRB3, GABRA5 and GABRG3, UBE3A, ATP 10A, MKRN3, ZNF, MAGEL2, Necdin (NDN), and SNRPN. The main objective of this review is to highlight the contribution of epigenetic modulations in chromosome 15q11-q13 segment toward the genetic etiology and pathophysiology of ASD. The present review reports the abnormalities in epigenetic regulation on genes and genomic regions located on chromosome 15 in relation to either syndromic (15q11-q13 maternal duplication) or nonsyndromic forms of ASD. Furthermore, studies reviewed in this article demonstrate conditions in which epigenetic dysregulation has been found to be a pathological factor for ASD development, thereby supporting a role for epigenetics in the multifactorial etiologies of ASD. Also, on the basis of the evidence found so far, we strongly emphasize the need to develop future therapeutic strategies as well as screening procedures for ASD that target mechanisms involving genes located on the chromosomal 15q11-q13 segment.

Identification of Chromosomal Regions Linked to Autism-Spectrum Disorders: A Meta-Analysis of Genome-Wide Linkage Scans

Background: Autism spectrum disorder (ASD) is a clinically and genetically heterogeneous group of pervasive neurodevelopmental disorders with a strong hereditary component. Although, genome-wide linkage scans (GWLS) and association studies (GWAS) have previously identified hundreds of ASD risk gene loci, the results remain inconclusive. Method: We performed a heterogeneity-based genome search meta-analysis (HEGESMA) of 15 genome scans of autism and ASD. Results: For strictly defined autism, data were analyzed across six separate genome scans. Region 7q22-q34 reached statistical significance in both weighted and unweighted analyses, with evidence of significantly low between-scan heterogeneity. For ASDs (data from 12 separate scans), chromosomal regions 5p15.33-5p15.1 and 15q22.32-15q26.1 reached significance in both weighted and unweighted analyses but did not reach significance for either low or high heterogeneity. Region 1q23.2-1q31.1 was significant in unweighted analyses with low between-scan heterogeneity. Finally, region 8p21.1-8q13.2 reached significant linkage peak in all our meta-analyses. When we combined all available genome scans (15), the same results were produced. Conclusions: This meta-analysis suggests that these regions should be further investigated for autism susceptibility genes, with the caveat that autism spectrum disorders have different linkage signals across genome scans, possibly because of the high genetic heterogeneity of the disease.

Incorporating information from markers in LD with test locus for detecting imprinting and maternal effects

Numerous statistical methods have been developed to explore genomic imprinting and maternal effects by identifying parent-of-origin patterns in complex human diseases. However, because most of these methods only use available locus-specific genotype data, it is sometimes impossible for them to infer the distribution of parental origin of a variant allele, especially when some genotypes are missing. In this article, we propose a two-step approach, LIMEhap, to improve upon a recent partial likelihood inference method. In the first step, the distribution of the missing genotypes is inferred through the construction of haplotypes by using information from nearby loci. In the second step, a partial likelihood method is applied to the inferred data. To substantiate the validity of the proposed procedures, we simulated data in a genomic region of gene GPX1. The results show that, by borrowing genetic information from nearby loci, the power of the proposed method can be close to that with complete genotype data at the locus of interest. Since the inference on the genotype distribution is made under the assumption of Hardy-Weinberg Equilibrium (HWE), we further studied the robustness of LIMEhap to violation of HWE. Finally, we demonstrate the utility of LIMEhap by applying it to an autism dataset.

Increased risk of ADHD in families with ASD

Attention Deficit and Hyperactive Disorder (ADHD) and Autism Spectrum Disorders (ASD) are frequent comorbid neurodevelopmental conditions and the overlap between both disorders remains to be delineated. A more complete understanding of the shared genetic and environmental factors is needed. Using a family-based method, we evaluated the risk of ADHD in a group of relatives with an ASD proband (ASD-) and a group of relatives with an ASD and ADHD proband (ASD+). We enrolled 1245 individuals in the study: 499 probands, their 746 first-degree relatives and 140 controls. We used a multivariate generalized estimating equation (GEE) model, in which the dependent variable was the ADHD diagnosis in the relatives and the independent variable the ASD+ or ASD- in probands. We adjusted for sociodemographic factors (age, sex, IQ) and for the nature of the familial relationship with the affected proband (parent or sibling). Among the probands, there were 287 ASD- and 212 ASD+ individuals. ADHD was more frequent in relatives (19%) than in the control group (7%) (p = 0.001). The risk of ADHD was higher in the ASD+ relatives group than in the ASD- relatives group (GEE model OR 1.58 [95% CI 1.04-2.38], p = 0.032). This result was found in parents (OR 1.96 [95% CI  1.14-3.36], but not in siblings (OR 1.28 [95% CI 0.84-1.94], p = 0.434). Our study provides a representative estimate of the family distribution of ADHD in relatives of ASD probands but supports the modest effect of shared genetic and environmental factors between both disorders.

Bio-collections in autism research

Autism spectrum disorder (ASD) is a group of complex neurodevelopmental disorders with diverse clinical manifestations and symptoms. In the last 10 years, there have been significant advances in understanding the genetic basis for ASD, critically supported through the establishment of ASD bio-collections and application in research. Here, we summarise a selection of major ASD bio-collections and their associated findings. Collectively, these include mapping ASD candidate genes, assessing the nature and frequency of gene mutations and their association with ASD clinical subgroups, insights into related molecular pathways such as the synapses, chromatin remodelling, transcription and ASD-related brain regions. We also briefly review emerging studies on the use of induced pluripotent stem cells (iPSCs) to potentially model ASD in culture. These provide deeper insight into ASD progression during development and could generate human cell models for drug screening. Finally, we provide perspectives concerning the utilities of ASD bio-collections and limitations, and highlight considerations in setting up a new bio-collection for ASD research.

Sexual selection modulates genetic conflicts and patterns of genomic imprinting

Recent years have seen a surge of interest in linking the theories of kin selection and sexual selection. In particular, there is a growing appreciation that kin selection, arising through demographic factors such as sex-biased dispersal, may modulate sexual conflicts, including in the context of male-female arms races characterized by coevolutionary cycles. However, evolutionary conflicts of interest need not only occur between individuals, but may also occur within individuals, and sex-specific demography is known to foment such intragenomic conflict in relation to social behavior. Whether and how this logic holds in the context of sexual conflict-and, in particular, in relation to coevolutionary cycles-remains obscure. We develop a kin-selection model to investigate the interests of different genes involved in sexual and intragenomic conflict, and we show that consideration of these conflicting interests yields novel predictions concerning parent-of-origin specific patterns of gene expression and the detrimental effects of different classes of mutation and epimutation at loci underpinning sexually selected phenotypes.

In Pursuit of New Imprinting Syndromes by Epimutation Screening in Idiopathic Neurodevelopmental Disorder Patients

Alterations of epigenetic mechanisms, and more specifically imprinting modifications, could be responsible of neurodevelopmental disorders such as intellectual disability (ID) or autism together with other associated clinical features in many cases. Currently only eight imprinting syndromes are defined in spite of the fact that more than 200 genes are known or predicted to be imprinted. Recent publications point out that some epimutations which cause imprinting disorders may affect simultaneously different imprinted loci, suggesting that DNA-methylation may have been altered more globally. Therefore, we hypothesised that the detection of altered methylation patterns in known imprinting loci will indirectly allow identifying new syndromes due to epimutations among patients with unexplained ID. In a screening for imprinting alterations in 412 patients with syndromic ID/autism we found five patients with altered methylation in the four genes studied: MEG3, H19, KCNQ1OT1, and SNRPN. Remarkably, the cases with partial loss of methylation in KCNQ1OT1 and SNRPN present clinical features different to those associated with the corresponding imprinting syndromes, suggesting a multilocus methylation defect in accordance with our initial hypothesis. Consequently, our results are a proof of concept that the identification of epimutations in known loci in patients with clinical features different from those associated with known syndromes will eventually lead to the definition of new imprinting disorders.

The variation game: Cracking complex genetic disorders with NGS and omics data

Tremendous advances in Next Generation Sequencing (NGS) and high-throughput omics methods have brought us one step closer towards mechanistic understanding of the complex disease at the molecular level. In this review, we discuss four basic regulatory mechanisms implicated in complex genetic diseases, such as cancer, neurological disorders, heart disease, diabetes, and many others. The mechanisms, including genetic variations, copy-number variations, posttranscriptional variations, and epigenetic variations, can be detected using a variety of NGS methods. We propose that malfunctions detected in these mechanisms are not necessarily independent, since these malfunctions are often found associated with the same disease and targeting the same gene, group of genes, or functional pathway. As an example, we discuss possible rewiring effects of the cancer-associated genetic, structural, and posttranscriptional variations on the protein-protein interaction (PPI) network centered around P53 protein. The review highlights multi-layered complexity of common genetic disorders and suggests that integration of NGS and omics data is a critical step in developing new computational methods capable of deciphering this complexity.

Clinical genetic research 2: Genetic epidemiology of complex phenotypes

Genetic factors play a substantive role in the susceptibility to common diseases. Due to recent and rapid advancements in characterization of genetic variants and large-scale genotyping platforms, multiple genes and genetic variants have now been identified for common, complex diseases. The most efficient method for gene identification at present appears to be large-scale association-based studies, which integrate genetic and epidemiological principles. As the strategy for gene identification studies has shifted towards genetic association-based methods rather than traditional linkage analysis, epidemiological methods are increasingly being integrated into genetic investigations. Consequently, the disciplines of genetics and epidemiology, which historically have functioned separately, have been integrated into a discipline referred to as genetic epidemiology. In this chapter, we review methods for establishing the genetic burden of complex genetic disease, followed by methods for gene and/or genetic variant identification and when appropriate we highlight the epidemiological issues that guide these methods.

Screening individuals with intellectual disability, autism and Tourette's syndrome for KCNK9 mutations and aberrant DNA methylation within the 8q24 imprinted cluster

The phenotype overlap between autism spectrum disorders (ASD) & intellectual disabilities (ID) is mirrored at the genetic level, with common genes being reported mutated in variety of developmental disabilities. However despite widespread genetic screening for mutations, in approximately 40-60% of childhood developmental disorders the genetic cause remains unknown. Several genome-wide linkage screens in ASD have identified a locus mapping to distal 8q. We have recently identified a novel brain-specific imprinted cluster at this location, which contains the reciprocally expressed maternal KCNK9 and paternally expressed non-coding PEG13 transcripts, the latter located within an intron of TRAPPC9. Interestingly, mutations of KCNK9 and TRAPPC9 have been reported in Birk-Barel mental retardation and non-syndromic familial forms of ID, respectively. Here, we report a genetic screen for KCNK9 coding mutations and potential epigenetic aberrations that could result in deregulated imprinting in a cohort of 120 ID, 86 ASD and 86 Tourette syndrome patients. Fifteen of the ID patients had clinical characteristics overlapping with Birk-Barel syndrome. Sequencing of the two coding exons of KCNK9 failed to identify pathologic mutations, with only one variant, rs2615374, being present with allele frequencies similar to those described in dbSNP database. DNA methylation profiling of the KCNK9 and TRAPPC9 promoters, the maternally methylated PEG13 DMR and a long-range enhancer region were normal in all patients. Our findings suggest that mutations of KCNK9 or epigenetic disturbances within the PEG13 imprinted cluster do not significantly contribute to the cause of the developmental disabilities tested in this study.

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.

The role of genomic imprinting in biology and disease: an expanding view

Genomic imprinting is an epigenetic phenomenon that results in monoallelic gene expression according to parental origin. It has long been established that imprinted genes have major effects on development and placental biology before birth. More recently, it has become evident that imprinted genes also have important roles after birth. In this Review, I bring together studies of the effects of imprinted genes from the prenatal period onwards. Recent work on postnatal stages shows that imprinted genes influence an extraordinarily wide-ranging array of biological processes, the effects of which extend into adulthood, and play important parts in common diseases that range from obesity to psychiatric disorders.

Parental obesity and risk of autism spectrum disorder

OBJECTIVES

The objective of the study was to investigate the associations among maternal prepregnancy BMI, paternal BMI, and the risk of autism spectrum disorders (ASDs) in children.

METHODS

The study sample of 92 909 children was derived from the population-based, prospective Norwegian Mother and Child Cohort Study. The age range was 4.0 through 13.1 (mean 7.4) years. Relative risks of ASDs were estimated by odds ratios (ORs) and 95% confidence intervals (CIs) from logistic regression models.

RESULTS

At the end of follow-up on December 31, 2012, 419 children in the study sample had been diagnosed with ASDs: 162 with autistic disorder, 103 with Asperger disorder, and 154 with pervasive developmental disorder not otherwise specified. Maternal obesity (BMI ≥30) was only weakly associated with ASD risk, whereas paternal obesity was associated with an increased risk of autistic disorder and Asperger disorder. The risk of autistic disorder was 0.27% (25 of 9267) in children of obese fathers and 0.14% (59 of 41 603) in children of fathers with normal weight (BMI <25), generating an adjusted OR of 1.73 (95% CI: 1.07-2.82). For Asperger disorder, analyses were limited to children aged ≥7 years (n = 50 116). The risk was 0.38% (18 of 4761) in children of obese fathers and 0.18% (42 of 22 736) in children of normal-weight fathers, and the adjusted OR was 2.01 (95% CI: 1.13-3.57). No associations were found for pervasive developmental disorder not otherwise specified.

CONCLUSIONS

Paternal obesity is an independent risk factor for ASDs in children. The associations should be investigated further in genetic and epigenetic studies.

Epigenetic epidemiology: promises for public health research

Epigenetic changes underlie developmental and age related biology. Promising epidemiologic research implicates epigenetics in disease risk and progression, and suggests epigenetic status depends on environmental risks as well as genetic predisposition. Epigenetics may represent a mechanistic link between environmental exposures, or genetics, and many common diseases, or may simply provide a quantitative biomarker for exposure or disease for areas of epidemiology currently lacking such measures. This great promise is balanced by issues related to study design, measurement tools, statistical methods, and biological interpretation that must be given careful consideration in an epidemiologic setting. This article describes the promises and challenges for epigenetic epidemiology, and suggests directions to advance this emerging area of molecular epidemiology.

Genome-wide association analyses of child genotype effects and parent-of-origin effects in specific language impairment

Specific language impairment (SLI) is a neurodevelopmental disorder that affects linguistic abilities when development is otherwise normal. We report the results of a genome-wide association study of SLI which included parent-of-origin effects and child genotype effects and used 278 families of language-impaired children. The child genotype effects analysis did not identify significant associations. We found genome-wide significant paternal parent-of-origin effects on chromosome 14q12 (P = 3.74 × 10⁻⁸) and suggestive maternal parent-of-origin effects on chromosome 5p13 (P = 1.16 × 10⁻⁷). A subsequent targeted association of six single-nucleotide-polymorphisms (SNPs) on chromosome 5 in 313 language-impaired individuals and their mothers from the ALSPAC cohort replicated the maternal effects, albeit in the opposite direction (P = 0.001); as fathers’ genotypes were not available in the ALSPAC study, the replication analysis did not include paternal parent-of-origin effects. The paternally-associated SNP on chromosome 14 yields a non-synonymous coding change within the NOP9 gene. This gene encodes an RNA-binding protein that has been reported to be significantly dysregulated in individuals with schizophrenia. The region of maternal association on chromosome 5 falls between the PTGER4 and DAB2 genes, in a region previously implicated in autism and ADHD. The top SNP in this association locus is a potential expression QTL of ARHGEF19 (also called WGEF) on chromosome 1. Members of this protein family have been implicated in intellectual disability. In summary, this study implicates parent-of-origin effects in language impairment, and adds an interesting new dimension to the emerging picture of shared genetic etiology across various neurodevelopmental disorders.

The human imprintome: regulatory mechanisms, methods of ascertainment, and roles in disease susceptibility

Imprinted genes form a special subset of the genome, exhibiting monoallelic expression in a parent-of-origin-dependent fashion. This monoallelic expression is controlled by parental-specific epigenetic marks, which are established in gametogenesis and early embryonic development and are persistent in all somatic cells throughout life. We define this specific set of cis-acting epigenetic regulatory elements as the imprintome, a distinct and specially tasked subset of the epigenome. Imprintome elements contain DNA methylation and histone modifications that regulate monoallelic expression by affecting promoter accessibility, chromatin structure, and chromatin configuration. Understanding their regulation is critical because a significant proportion of human imprinted genes are implicated in complex diseases. Significant species variation in the repertoire of imprinted genes and their epigenetic regulation, however, will not allow model organisms solely to be used for this crucial purpose. Ultimately, only the human will suffice to accurately define the human imprintome.

Haplotype structure enables prioritization of common markers and candidate genes in autism spectrum disorder

Autism spectrum disorder (ASD) is a neurodevelopmental condition that results in behavioral, social and communication impairments. ASD has a substantial genetic component, with 88-95% trait concordance among monozygotic twins. Efforts to elucidate the causes of ASD have uncovered hundreds of susceptibility loci and candidate genes. However, owing to its polygenic nature and clinical heterogeneity, only a few of these markers represent clear targets for further analyses. In the present study, we used the linkage structure associated with published genetic markers of ASD to simultaneously improve candidate gene detection while providing a means of prioritizing markers of common genetic variation in ASD. We first mined the literature for linkage and association studies of single-nucleotide polymorphisms, copy-number variations and multi-allelic markers in Autism Genetic Resource Exchange (AGRE) families. From markers that reached genome-wide significance, we calculated male-specific genetic distances, in light of the observed strong male bias in ASD. Four of 67 autism-implicated regions, 3p26.1, 3p26.3, 3q25-27 and 5p15, were enriched with differentially expressed genes in blood and brain from individuals with ASD. Of 30 genes differentially expressed across multiple expression data sets, 21 were within 10 cM of an autism-implicated locus. Among them, CNTN4, CADPS2, SUMF1, SLC9A9, NTRK3 have been previously implicated in autism, whereas others have been implicated in neurological disorders comorbid with ASD. This work leverages the rich multimodal genomic information collected on AGRE families to present an efficient integrative strategy for prioritizing autism candidates and improving our understanding of the relationships among the vast collection of past genetic studies.

Epigenetic factors and autism spectrum disorders

Autism is a complex neurodevelopmental disorder that has significant phenotypic overlap with several diseases, many of which fall within the broader category of autism spectrum disorders (ASDs). The etiology of the disorder is unclear and seems to involve a complex interplay of polygenic as well as environmental factors. We discuss evidence that suggests that epigenetic dysregulation is highly implicated as a contributing cause of ASDs and autism. Specifically, we examine neurodevelopmental disorders that share significant phenotypic overlap with ASDs and feature the dysregulation of epigenetically modified genes including UBE3A, GABA receptor genes, and RELN. We then look at the dysregulated expression of implicated epigenetic modifiers, namely MeCP2, that yield complex and varied downstream pleiotropic effects. Finally, we examine epigenetically mediated parent-of-origin effects through which paternal gene expression dominates that of maternal contributing to contrasting phenotypes implicated in ASDs. Such preliminary evidence suggests that elucidating the complex role of epigenetic regulations involved in ASDs could prove vital in furthering our understanding of the complex etiology of autism and ASDs.

DELISHUS: an efficient and exact algorithm for genome-wide detection of deletion polymorphism in autism

Motivation: The understanding of the genetic determinants of complex disease is undergoing a paradigm shift. Genetic heterogeneity of rare mutations with deleterious effects is more commonly being viewed as a major component of disease. Autism is an excellent example where research is active in identifying matches between the phenotypic and genomic heterogeneities. A considerable portion of autism appears to be correlated with copy number variation, which is not directly probed by single nucleotide polymorphism (SNP) array or sequencing technologies. Identifying the genetic heterogeneity of small deletions remains a major unresolved computational problem partly due to the inability of algorithms to detect them.

Results: In this article, we present an algorithmic framework, which we term DELISHUS, that implements three exact algorithms for inferring regions of hemizygosity containing genomic deletions of all sizes and frequencies in SNP genotype data. We implement an efficient backtracking algorithm—that processes a 1 billion entry genome-wide association study SNP matrix in a few minutes—to compute all inherited deletions in a dataset. We further extend our model to give an efficient algorithm for detecting de novo deletions. Finally, given a set of called deletions, we also give a polynomial time algorithm for computing the critical regions of recurrent deletions. DELISHUS achieves significantly lower false-positive rates and higher power than previously published algorithms partly because it considers all individuals in the sample simultaneously. DELISHUS may be applied to SNP array or sequencing data to identify the deletion spectrum for family-based association studies.

Availability: DELISHUS is available at http://www.brown.edu/Research/Istrail_Lab/.

Contact:Eric_Morrow@brown.edu and Sorin_Istrail@brown.edu

Supplementary information:Supplementary data are available at Bioinformatics online.

The co-occurrence of autism spectrum disorder and attention-deficit/hyperactivity disorder symptoms in parents of children with ASD or ASD with ADHD

BACKGROUND

Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) share about 50-72% of their genetic factors, which is the most likely explanation for their frequent co-occurrence within the same patient or family. An additional or alternative explanation for the co-occurrence may be (cross-)assortative mating, e.g., the tendency to choose a partner that is similar or dissimilar to oneself. Another issue is that of parent-of-origin effect which refers to the possibility of parents differing in the relative quantity of risk factors they transmit to the offspring. The current study sets out to examine (cross-)assortative mating and (cross-)parent-of-origin effects of ASD and ADHD in parents of children with either ASD or ASD with ADHD diagnosis.

METHODS

In total, 121 families were recruited in an ongoing autism-ADHD family genetics project. Participating families consisted of parents and at least one child aged between 2 and 20 years, with either autistic disorder, Asperger disorder or PDD-NOS, and one or more biological siblings. All children and parents were carefully screened for the presence of ASD and ADHD.

RESULTS

No correlations were found between maternal and paternal ASD and ADHD symptoms. Parental ASD and ADHD symptoms were predictive for similar symptoms in the offspring, but with maternal hyperactive-impulsive symptoms, but not paternal symptoms, predicting similar symptoms in daughters. ASD pathology in the parents was not predictive for ADHD pathology in the offspring, but mother's ADHD pathology was predictive for offspring ASD pathology even when corrected for maternal ASD pathology.

CONCLUSIONS

Cross-assortative mating for ASD and ADHD does not form an explanation for the frequent co-occurrence of these disorders within families. Given that parental ADHD is predictive of offspring' ASD but not vice versa, risk factors underlying ASD may overlap to a larger degree with risk factors underlying ADHD than vice versa. However, future research is needed to clarify this issue.

Allele-biased expression in differentiating human neurons: implications for neuropsychiatric disorders

Stochastic processes and imprinting, along with genetic factors, lead to monoallelic or allele-biased gene expression. Stochastic monoallelic expression fine-tunes information processing in immune cells and the olfactory system, and imprinting plays an important role in development. Recent studies suggest that both stochastic events and imprinting may be more widespread than previously considered. We are interested in allele-biased gene expression occurring in the brain because parent-of-origin effects suggestive of imprinting appear to play a role in the transmission of schizophrenia (SZ) and autism spectrum disorders (ASD) in some families. In addition, allele-biased expression could help explain monozygotic (MZ) twin discordance and reduced penetrance. The ability to study allele-biased expression in human neurons has been transformed with the advent of induced pluripotent stem cell (iPSC) technology and next generation sequencing. Using transcriptome sequencing (RNA-Seq) we identified 801 genes in differentiating neurons that were expressed in an allele-biased manner. These included a number of putative SZ and ASD candidates, such as A2BP1 (RBFOX1), ERBB4, NLGN4X, NRG1, NRG3, NRXN1, and NLGN1. Overall, there was a modest enrichment for SZ and ASD candidate genes among those that showed evidence for allele-biased expression (chi-square, p = 0.02). In addition to helping explain MZ twin discordance and reduced penetrance, the capacity to group many candidate genes affecting a variety of molecular and cellular pathways under a common regulatory process – allele-biased expression – could have therapeutic implications.

Genetic overlap of schizophrenia and bipolar disorder in a high-density linkage survey in the Portuguese Island population

Recent family and genome-wide association studies strongly suggest shared genetic risk factors for schizophrenia (SZ) and bipolar disorder (BP). However, linkage studies have not been used to test for statistically significant genome-wide overlap between them. Forty-seven Portuguese families with sibpairs concordant for SZ, BP, or psychosis (PSY, which includes either SZ or psychotic BP) were genotyped for over 57,000 markers using the Affymetrix 50K Xba SNP array. NPL and Kong and Cox LOD scores were calculated in Merlin for all three phenotypes. Empirical significance was determined using 1,000 gene-dropping simulations. Significance of genome-wide genetic overlap between SZ and BP was determined by the number of simulated BP scans having the same number of loci jointly linked with the real SZ scan, and vice versa. For all three phenotypes, a number of regions previously linked in this sample remained so. For BP, chromosome 1p36 achieved significance (11.54-15.71 MB, LOD = 3.51), whereas it was not even suggestively linked at lower marker densities, as did chromosome 11q14.1 (89.32-90.15 MB, NPL = 4.15). Four chromosomes had loci at which both SZ and BP had NPL ≥ 1.98, which was more than would be expected by chance (empirical P = 0.01 using simulated SZ scans; 0.07 using simulated BP scans), although they did not necessarily meet criteria for suggestive linkage individually. These results suggest that high-density marker maps may provide greater power and precision in linkage studies than lower density maps. They also further support the hypothesis that SZ and BP share at least some risk alleles.

Is there a genomically imprinted social brain?

Imprinted genes (IGs) are expressed or silenced according to their parent-of-origin. These genes are known to play a role in regulating offspring growth, development and infant behaviors such as suckling and ultrasonic calls. In adults, neurally expressed IGs coordinate several behaviors including maternal care, sex, feeding, emotionality, and cognition. However, despite evidence from human psychiatric disorders and evolutionary theory that maternally and paternally expressed genes should also regulate social behavior, little empirical data from mouse research exists. This paper discusses data from a recent study (Garfield et al., 2011) that the IG Grb10 governs unique aspects of mouse social behavior and interprets the relevance of these findings for the future of this field.