ASD Phenotype-Genotype Associations in Concordant and Discordant Monozygotic and Dizygotic Twins Stratified by Severity of Autistic Traits

Inhibitory dysfunction and social processing difficulties in autism: A comprehensive narrative review

The primary inhibitory neurotransmitter γ-aminobutyric acid (GABA) has a prominent role in regulating neural development and function, with disruption to GABAergic signalling linked to behavioural phenotypes associated with neurodevelopmental disorders, particularly autism. Such neurochemical disruption, likely resulting from diverse genetic and molecular mechanisms, particularly during early development, can subsequently affect the cellular balance of excitation and inhibition in neuronal circuits, which may account for the social processing difficulties observed in autism and related conditions. This comprehensive narrative review integrates diverse streams of research from several disciplines, including molecular neurobiology, genetics, epigenetics, and systems neuroscience. In so doing it aims to elucidate the relevance of inhibitory dysfunction to autism, with specific focus on social processing difficulties that represent a core feature of this disorder. Many of the social processing difficulties experienced in autism have been linked to higher levels of the excitatory neurotransmitter glutamate and/or lower levels of inhibitory GABA. While current therapeutic options for social difficulties in autism are largely limited to behavioural interventions, this review highlights the psychopharmacological studies that explore the utility of GABA modulation in alleviating such difficulties.

The association between prenatal psychosocial factors and autism spectrum disorder in offspring at 3 years: a prospective cohort study

PURPOSE

Few studies of risk factors for autism spectrum disorder (ASD) have been prospective in design or investigated the role of psychosocial factors measured during pregnancy. We aimed to investigate associations between prenatal psychosocial factors and risk of ASD in offspring, as part of a multicenter prospective cohort study of more than 2000 mother-child pairs.

METHODS

Nulliparous women aged 18-35 years, living in Pennsylvania, USA, were interviewed during pregnancy and multiple times postpartum over the course of a 3-year period. There were 2388 mothers who completed the Screen for Social Interaction Toddler Version (SSI-T), a measure of risk of ASD, when their child was 3-years old. Multivariable logistic regression models were used to investigate the associations between prenatal psychosocial factors-including total scores on three scales (social-support, stress and depression), trouble paying for basic needs, mental illness diagnosis and use of antidepressants-and risk of ASD in offspring at the age of 3-years, controlling for relevant confounding variables.

RESULTS

There were 102 children (4.3%) who were scored as at-risk of ASD at 3-years. Prenatal psychosocial factors that were significantly associated with risk of ASD in the adjusted models were lower social-support (p < 0.001); stress (p = 0.003): depression (< 0.001), trouble paying for basic needs (p = 0.012), mental illness diagnosis (p = 0.016), and use of antidepressants (p < 0.001).

CONCLUSION

These findings suggest that maternal experience of adverse psychosocial factors during pregnancy may be important intrauterine exposures related to the pathogenesis of ASD.

A multi-omic approach identifies an autism spectrum disorder (ASD) regulatory complex of functional epimutations in placentas from children born preterm

Children born preterm are at heightened risk of neurodevelopmental impairments, including Autism Spectrum Disorder (ASD). The placenta is a key regulator of neurodevelopmental processes, though the precise underlying molecular mechanisms remain unclear. Here, we employed a multi-omic approach to identify placental transcriptomic and epigenetic modifications related to ASD diagnosis at age 10, among children born preterm. Working with the extremely low gestational age (ELGAN) cohort, we hypothesized that a pro-inflammatory placental environment would be predictive of ASD diagnosis at age 10. Placental messenger RNA (mRNA) expression, CpG methylation, and microRNA (miRNA) expression were compared among 368 ELGANs (28 children diagnosed with ASD and 340 children without ASD). A total of 111 genes displayed expression levels in the placenta that were associated with ASD. Within these ASD-associated genes is an ASD regulatory complex comprising key genes that predicted ASD case status. Genes with expression that predicted ASD case status included Ewing Sarcoma Breakpoint Region 1 (EWSR1) (OR: 6.57 (95% CI: 2.34, 23.58)) and Bromodomain Adjacent To Zinc Finger Domain 2A (BAZ2A) (OR: 0.12 (95% CI: 0.03, 0.35)). Moreover, of the 111 ASD-associated genes, nine (8.1%) displayed associations with CpG methylation levels, while 14 (12.6%) displayed associations with miRNA expression levels. Among these, LRR Binding FLII Interacting Protein 1 (LRRFIP1) was identified as being under the control of both CpG methylation and miRNAs, displaying an OR of 0.42 (95% CI: 0.17, 0.95). This gene, as well as others identified as having functional epimutations, plays a critical role in immune system regulation and inflammatory response. In summary, a multi-omic approach was used to identify functional epimutations in the placenta that are associated with the development of ASD in children born preterm, highlighting future avenues for intervention.

KnockoffTrio: A knockoff framework for the identification of putative causal variants in genome-wide association studies with trio design

Family-based designs can eliminate confounding due to population substructure and can distinguish direct from indirect genetic effects, but these designs are underpowered due to limited sample sizes. Here, we propose KnockoffTrio, a statistical method to identify putative causal genetic variants for father-mother-child trio design built upon a recently developed knockoff framework in statistics. KnockoffTrio controls the false discovery rate (FDR) in the presence of arbitrary correlations among tests and is less conservative and thus more powerful than the conventional methods that control the family-wise error rate via Bonferroni correction. Furthermore, KnockoffTrio is not restricted to family-based association tests and can be used in conjunction with more powerful, potentially nonlinear models to improve the power of standard family-based tests. We show, using empirical simulations, that KnockoffTrio can prioritize causal variants over associations due to linkage disequilibrium and can provide protection against confounding due to population stratification. In applications to 14,200 trios from three study cohorts for autism spectrum disorders (ASDs), including AGP, SPARK, and SSC, we show that KnockoffTrio can identify multiple significant associations that are missed by conventional tests applied to the same data. In particular, we replicate known ASD association signals with variants in several genes such as MACROD2, NRXN1, PRKAR1B, CADM2, PCDH9, and DOCK4 and identify additional associations with variants in other genes including ARHGEF10, SLC28A1, ZNF589, and HINT1 at FDR 10%.

SFARI genes and where to find them; modelling Autism Spectrum Disorder specific gene expression dysregulation with RNA-seq data

Autism Spectrum Disorders (ASD) have a strong, yet heterogeneous, genetic component. Among the various methods that are being developed to help reveal the underlying molecular aetiology of the disease one approach that is gaining popularity is the combination of gene expression and clinical genetic data, often using the SFARI-gene database, which comprises lists of curated genes considered to have causative roles in ASD when mutated in patients. We build a gene co-expression network to study the relationship between ASD-specific transcriptomic data and SFARI genes and then analyse it at different levels of granularity. No significant evidence is found of association between SFARI genes and differential gene expression patterns when comparing ASD samples to a control group, nor statistical enrichment of SFARI genes in gene co-expression network modules that have a strong correlation with ASD diagnosis. However, classification models that incorporate topological information from the whole ASD-specific gene co-expression network can predict novel SFARI candidate genes that share features of existing SFARI genes and have support for roles in ASD in the literature. A statistically significant association is also found between the absolute level of gene expression and SFARI's genes and Scores, which can confound the analysis if uncorrected. We propose a novel approach to correct for this that is general enough to be applied to other problems affected by continuous sources of bias. It was found that only co-expression network analyses that integrate information from the whole network are able to reveal signatures linked to ASD diagnosis and novel candidate genes for the study of ASD, which individual gene or module analyses fail to do. It was also found that the influence of SFARI genes permeates not only other ASD scoring systems, but also lists of genes believed to be involved in other neurodevelopmental disorders.

Dynamic and Systemic Perspective in Autism Spectrum Disorders: A Change of Gaze in Research Opens to A New Landscape of Needs and Solutions

The first step for a harmonious bio-psycho-social framework in approaching autism spectrum disorders (ASD) is overcoming the conflict between the biological and the psychosocial perspective. Biological research can provide clues for a correct approach to clinical practice, assuming that it would lead to the conceptualization of a pathogenetic paradigm able to account for epidemiologic and clinical findings. The upward trajectory in ASD prevalence and the systemic involvement of other organs besides the brain suggest that the epigenetic paradigm is the most plausible one. The embryo-fetal period is the crucial window of opportunity for keeping neurodevelopment on the right tracks, suggesting that women's health in pregnancy should be a priority. Maladaptive molecular pathways beginning in utero, in particular, a vicious circle between the immune response, oxidative stress/mitochondrial dysfunction, and dysbiosis-impact neurodevelopment and brain functioning across the lifespan and are the basis for progressive multisystemic disorders that account for the substantial health loss and the increased mortality in ASD. Therefore, the biological complexity of ASD and its implications for health requires the enhancement of clinical skills on these topics, to achieve an effective multi-disciplinary healthcare model. Well-balanced training courses could be a promising starting point to make a change.

Family-Based Genome-Wide Association Study of Autism Spectrum Disorder in Middle Eastern Families

Autism spectrum disorder (ASD) is a neurodevelopmental disease characterized by abnormalities in language and social communication with substantial clinical heterogeneity. Genetic factors play an important role in ASD with heritability estimated between 70% to 80%. Genome-wide association studies (GWAS) have identified multiple loci associated with ASD. However, most studies were performed on European populations and little is known about the genetic architecture of ASD in Middle Eastern populations. Here, we report the first GWAS of ASD in the Middle eastern population of Qatar. We analyzed 171 families with ASD, using linear mixed models adjusting for relatedness and other confounders. Results showed that common single nucleotide polymorphisms (SNP) in seven loci are associated with ASD (p < 1 × 10-5). Although the identified loci did not reach genome-wide significance, many of the top associated SNPs are located within or near genes that have been implicated in ASD or related neurodevelopmental disorders. These include GORASP2, GABBR2, ANKS6, THSD4, ERCC6L, ARHGEF6, and HDAC8. Additionally, three of the top associated SNPs were significantly associated with gene expression. We also found evidence of association signals in two previously reported ASD-susceptibility loci (rs10099100 and rs4299400). Our results warrant further functional studies and replication to provide further insights into the genetic architecture of ASD.

Advancing Autism Research From Mice to Marmosets: Behavioral Development of Offspring Following Prenatal Maternal Immune Activation

Understanding the mechanism(s) by which maternal immune activation (MIA) during gestation may disrupt neurodevelopment and increase the susceptibility for disorders such as autism spectrum disorder (ASD) or schizophrenia is a critical step in the development of better treatments and preventive measures. A large body of literature has investigated the pathophysiology of MIA in rodents. However, a translatability gap plagues pre-clinical research of complex behavioral/developmental diseases and those diseases requiring clinical diagnosis, such as ASD. While ideal for their genetic flexibility, vast reagent toolkit, and practicality, rodent models often lack important elements of ethological validity. Hence, our study aimed to develop and characterize the prenatal MIA model in marmosets. Here, we adapted the well-characterized murine maternal immune activation model. Pregnant dams were administered 5 mg/kg poly-L-lysine stabilized polyinosinic-polycytidylic acid (Poly ICLC) subcutaneously three times during gestation (gestational day 63, 65, and 67). Dams were allowed to deliver naturally with no further experimental treatments. After parturition, offspring were screened for general health and vigor, and individual assessment of communication development and social behavior was measured during neonatal or adolescent periods. Similar to rodent models, offspring subjected to MIA exhibited a disruption in patterns of communication during early development. Assessment of social behavior in a marmoset-modified 3-chamber test at 3 and 9 months of age revealed alterations in social behavior that, in some instances, was sex-dependent. Together, our data indicate that marmosets are an excellent non-human primate model for investigating the neurodevelopmental and behavioral consequences of exposure to prenatal challenges, like MIA. Additional studies are necessary to more completely characterize the effect of prenatal inflammation on marmoset development and explore therapeutic intervention strategies that may be applicable in a clinical setting.

Phenotypic Subtyping and Re-analyses of Existing Transcriptomic Data from Autistic Probands in Simplex Families Reveal Differentially Expressed and ASD Trait-Associated Genes

Autism spectrum disorder (ASD) describes a collection of neurodevelopmental disorders characterized by core symptoms that include social communication deficits and repetitive, stereotyped behaviors often coupled with restricted interests. Primary challenges to understanding and treating ASD are the genetic and phenotypic heterogeneity of cases that complicates all omics analyses as well as a lack of information on relationships among genes, pathways, and autistic traits. In this study, we re-analyze existing transcriptomic data from simplex families by subtyping individuals with ASD according to multivariate cluster analyses of clinical ADI-R scores that encompass a broad range of behavioral symptoms. We also correlate multiple ASD traits, such as deficits in verbal and non-verbal communication, play and social skills, ritualistic behaviors, and savant skills, with expression profiles using Weighted Gene Correlation Network Analyses (WGCNA). Our results show that subtyping greatly enhances the ability to identify differentially expressed genes involved in specific canonical pathways and biological functions associated with ASD within each phenotypic subgroup. Moreover, using WGCNA, we identify gene modules that correlate significantly with specific ASD traits. Network prediction analyses of the genes in these modules reveal canonical pathways as well as neurological functions and disorders relevant to the pathobiology of ASD. Finally, we compare the WGCNA-derived data on autistic traits in simplex families with analogous data from multiplex families using transcriptomic data from our previous studies. The comparison reveals overlapping trait-associated pathways as well as upstream regulators of the module-associated genes that may serve as useful targets for a precision medicine approach to ASD.

An Overview of the Main Genetic, Epigenetic and Environmental Factors Involved in Autism Spectrum Disorder Focusing on Synaptic Activity

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that affects social interaction and communication, with restricted interests, activity and behaviors. ASD is highly familial, indicating that genetic background strongly contributes to the development of this condition. However, only a fraction of the total number of genes thought to be associated with the condition have been discovered. Moreover, other factors may play an important role in ASD onset. In fact, it has been shown that parental conditions and in utero and perinatal factors may contribute to ASD etiology. More recently, epigenetic changes, including DNA methylation and micro RNA alterations, have been associated with ASD and proposed as potential biomarkers. This review aims to provide a summary of the literature regarding ASD candidate genes, mainly focusing on synapse formation and functionality and relevant epigenetic and environmental aspects acting in concert to determine ASD onset.

Phenotypic Subtyping and Re-Analysis of Existing Methylation Data from Autistic Probands in Simplex Families Reveal ASD Subtype-Associated Differentially Methylated Genes and Biological Functions

Autism spectrum disorder (ASD) describes a group of neurodevelopmental disorders with core deficits in social communication and manifestation of restricted, repetitive, and stereotyped behaviors. Despite the core symptomatology, ASD is extremely heterogeneous with respect to the severity of symptoms and behaviors. This heterogeneity presents an inherent challenge to all large-scale genome-wide omics analyses. In the present study, we address this heterogeneity by stratifying ASD probands from simplex families according to the severity of behavioral scores on the Autism Diagnostic Interview-Revised diagnostic instrument, followed by re-analysis of existing DNA methylation data from individuals in three ASD subphenotypes in comparison to that of their respective unaffected siblings. We demonstrate that subphenotyping of cases enables the identification of over 1.6 times the number of statistically significant differentially methylated regions (DMR) and DMR-associated genes (DAGs) between cases and controls, compared to that identified when all cases are combined. Our analyses also reveal ASD-related neurological functions and comorbidities that are enriched among DAGs in each phenotypic subgroup but not in the combined case group. Moreover, relational gene networks constructed with the DAGs reveal signaling pathways associated with specific functions and comorbidities. In addition, a network comprised of DAGs shared among all ASD subgroups and the combined case group is enriched in genes involved in inflammatory responses, suggesting that neuroinflammation may be a common theme underlying core features of ASD. These findings demonstrate the value of phenotype definition in methylomic analyses of ASD and may aid in the development of subtype-directed diagnostics and therapeutics.

From putative brain tumor marker to high cognitive abilities: Emerging roles of a disintegrin and metalloprotease (ADAM) 12 in the brain

ADAM (a disintergin and metalloprotease) 12 is a member of the large family of multidomain metalloprotease-disintegrins, which possess cell-binding and metalloprotease properties. The enzyme is responsible for the shedding of a number of membrane-bound proteins (heparin-binding-EGF, insulin-like growth factor 2-binding proteins 3 and 5, oxytocinase, glycoprotein non-metastatic melanoma protein B and basigin). In rat and human CNS, ADAM12 is predominantly localized in white and gray matter oligodendrocytes. In addition it can be detected in astrocytes, neurons and endothelial cells. Its function in healthy brain is not well established yet, but prominent roles in CNS development, myelination and high cognitive abilities are discussed. There is increasing evidence that ADAM12 is involved in numerous major diseases of the CNS, which are summarized in the present review (brain tumors, multiple sclerosis, amyotrophic lateral sclerosis, Alzheimer´s disease, stroke, schizophrenia, autism and bipolar disorder).