An integrative analysis of non-coding regulatory DNA variations associated with autism spectrum disorder

Towards understanding sex differences in autism spectrum disorders

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by social deficits, repetitive behaviours and lack of empathy. Its significant genetic heritability and potential comorbidities often lead to diagnostic and therapeutic challenges. This review addresses the biological basis of ASD, focusing on the sex differences in gene expression and hormonal influences. ASD is more commonly diagnosed in males at a ratio of 4:1, indicating a potential oversight in female-specific ASD research and a risk of underdiagnosis in females. We consider how ASD manifests differently across sexes by exploring differential gene expression in female and male brains and consider how variations in steroid hormones influence ASD characteristics. Synaptic function, including excitation/inhibition ratio imbalance, is influenced by gene mutations and this is explored as a key factor in the cognitive and behavioural manifestations of ASD. We also discuss the role of micro RNAs (miRNAs) and highlight a novel mutation in miRNA-873, which affects a suite of key synaptic genes, neurexin, neuroligin, SHANK and post-synaptic density proteins, implicated in the pathology of ASD. Our review suggests that genetic predisposition, sex differences in brain gene expression, and hormonal factors significantly contribute to the presentation, identification and severity of ASD, necessitating sex-specific considerations in diagnosis and treatments. These findings advocate for personalized interventions to improve the outcomes for individuals with ASD.

Allelic heterogeneity and abnormal vesicle recycling in PLAA-related neurodevelopmental disorders

The human PLAA gene encodes Phospholipase-A2-Activating-Protein (PLAA) involved in trafficking of membrane proteins. Through its PUL domain (PLAP, Ufd3p, and Lub1p), PLAA interacts with p97/VCP modulating synaptic vesicles recycling. Although few families carrying biallelic PLAA variants were reported with progressive neurodegeneration, consequences of monoallelic PLAA variants have not been elucidated. Using exome or genome sequencing we identified PLAA de-novo missense variants, affecting conserved residues within the PUL domain, in children affected with neurodevelopmental disorders (NDDs), including psychomotor regression, intellectual disability (ID) and autism spectrum disorders (ASDs). Computational and in-vitro studies of the identified variants revealed abnormal chain arrangements at C-terminal and reduced PLAA-p97/VCP interaction, respectively. These findings expand both allelic and phenotypic heterogeneity associated to PLAA-related neurological disorders, highlighting perturbed vesicle recycling as a potential disease mechanism in NDDs due to genetic defects of PLAA.

Landscape of NRXN1 Gene Variants in Phenotypic Manifestations of Autism Spectrum Disorder: A Systematic Review

Background: Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by social communication challenges and repetitive behaviors. Recent research has increasingly focused on the genetic underpinnings of ASD, with the Neurexin 1 (NRXN1) gene emerging as a key player. This comprehensive systematic review elucidates the contribution of NRXN1 gene variants in the pathophysiology of ASD. Methods: The protocol for this systematic review was designed a priori and was registered in the PROSPERO database (CRD42023450418). A risk of bias analysis was conducted using the Joanna Briggs Institute (JBI) critical appraisal tool. We examined various studies that link NRXN1 gene disruptions with ASD, discussing both the genotypic variability and the resulting phenotypic expressions. Results: Within this review, there was marked heterogeneity observed in ASD genotypic and phenotypic manifestations among individuals with NRXN1 mutations. The presence of NRXN1 mutations in this population emphasizes the gene's role in synaptic function and neural connectivity. Conclusion: This review not only highlights the role of NRXN1 in the pathophysiology of ASD but also highlights the need for further research to unravel the complex genetic underpinnings of the disorder. A better knowledge about the multifaceted role of NRXN1 in ASD can provide crucial insights into the neurobiological foundations of autism and pave the way for novel therapeutic strategies.

Delayed Graft Function in Pediatric Kidney Transplant: Risk Factors and Outcomes

OBJECTIVES

We aimed to identify risk factors and outcomes of delayed graft function in pediatric kidney transplant.

MATERIALS AND METHODS

This retrospective study included all kidney transplant recipients ≤19 years old followed up in our department for a period of 34 years, from January 1989 to December 2022.

RESULTS

We included 113 kidney transplant recipients. Delayed graft function occurred in 17 cases (15%). Posttransplant red blood cell transfusion was strongly associated with delayed graft function (adjusted odds ratio = 23.91; 95% CI, 2.889-197.915). Use of allografts with multiple arteries and cold ischemia time >20 hours were risk factors for delayed graft function (adjusted odds ratio = 52.51 and 49.4; 95% CI, 2.576-1070.407 and 1.833-1334.204, respectively). Sex-matched transplants and living donors were protective factors for delayed graft function (adjusted odds ratio = 0.043 and 0.027; 95% CI, 0.005-0.344 and 0.003-0.247, respectively). Total HLA mismatches <3 played a protective role for delayed graft function (adjusted odds ratio = 0.114; 95% CI, 0.020-0.662), whereas transplant within compatible but different blood types increased the risk of delayed graft function (adjusted odds ratio = 20.54; 95% CI, 1.960- 215.263). No significant correlation was shown between delayed graft function and allograft survival (P = .190). Our study suggested delayed graft function as a key factor in allograft rejection-free survival (adjusted odds ratio = 3.832; 95% CI, 1.186-12.377). Delayed graft function was a negative factor for early graft function; patients with delayed graft function had a lower estimated glomerular filtration rate at discharge (P = .024) and at 3 (P = .034), 6 (P = .019), and 12 months (P = .011) posttransplant.

CONCLUSIONS

Delayed graft function is a major determinant of early graft function and allograft rejection-free survival. Further research is required to establish proper preventive measures.

Diversity and Classification of Genetic Variations in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental condition with symptoms that affect the whole personality and all aspects of life. Although there is a high degree of heterogeneity in both its etiology and its characteristic behavioral patterns, the disorder is well-captured along the autistic triad. Currently, ASD status can be confirmed following an assessment of behavioral features, but there is a growing emphasis on conceptualizing autism as a spectrum, which allows for establishing a diagnosis based on the level of support need, free of discrete categories. Since ASD has a high genetic predominance, the number of genetic variations identified in the background of the condition is increasing exponentially as genetic testing methods are rapidly evolving. However, due to the huge amount of data to be analyzed, grouping the different DNA variations is still challenging. Therefore, in the present review, a multidimensional classification scheme was developed to accommodate most of the currently known genetic variants associated with autism. Genetic variations have been grouped according to six criteria (extent, time of onset, information content, frequency, number of genes involved, inheritance pattern), which are themselves not discrete categories, but form a coherent continuum in line with the autism spectrum approach.

Prediction accuracy of regulatory elements from sequence varies by functional sequencing technique

Introduction

Various sequencing based approaches are used to identify and characterize the activities of cis-regulatory elements in a genome-wide fashion. Some of these techniques rely on indirect markers such as histone modifications (ChIP-seq with histone antibodies) or chromatin accessibility (ATAC-seq, DNase-seq, FAIRE-seq), while other techniques use direct measures such as episomal assays measuring the enhancer properties of DNA sequences (STARR-seq) and direct measurement of the binding of transcription factors (ChIP-seq with transcription factor-specific antibodies). The activities of cis-regulatory elements such as enhancers, promoters, and repressors are determined by their sequence and secondary processes such as chromatin accessibility, DNA methylation, and bound histone markers.

Methods

Here, machine learning models are employed to evaluate the accuracy with which cis-regulatory elements identified by various commonly used sequencing techniques can be predicted by their underlying sequence alone to distinguish between cis-regulatory activity that is reflective of sequence content versus secondary processes.

Results and discussion

Models trained and evaluated on D. melanogaster sequences identified through DNase-seq and STARR-seq are significantly more accurate than models trained on sequences identified by H3K4me1, H3K4me3, and H3K27ac ChIP-seq, FAIRE-seq, and ATAC-seq. These results suggest that the activity detected by DNase-seq and STARR-seq can be largely explained by underlying DNA sequence, independent of secondary processes. Experimentally, a subset of DNase-seq and H3K4me1 ChIP-seq sequences were tested for enhancer activity using luciferase assays and compared with previous tests performed on STARR-seq sequences. The experimental data indicated that STARR-seq sequences are substantially enriched for enhancer-specific activity, while the DNase-seq and H3K4me1 ChIP-seq sequences are not. Taken together, these results indicate that the DNase-seq approach identifies a broad class of regulatory elements of which enhancers are a subset and the associated data are appropriate for training models for detecting regulatory activity from sequence alone, STARR-seq data are best for training enhancer-specific sequence models, and H3K4me1 ChIP-seq data are not well suited for training and evaluating sequence-based models for cis-regulatory element prediction.

The non-coding genome in Autism Spectrum Disorders

Autism Spectrum Disorders (ASD) are a group of neurodevelopmental disorders (NDDs) characterized by difficulties in social interaction and communication, repetitive behavior, and restricted interests. While ASD have been proven to have a strong genetic component, current research largely focuses on coding regions of the genome. However, non-coding DNA, which makes up for ∼99% of the human genome, has recently been recognized as an important contributor to the high heritability of ASD, and novel sequencing technologies have been a milestone in opening up new directions for the study of the gene regulatory networks embedded within the non-coding regions. Here, we summarize current progress on the contribution of non-coding alterations to the pathogenesis of ASD and provide an overview of existing methods allowing for the study of their functional relevance, discussing potential ways of unraveling ASD's "missing heritability".

The role of microRNAs in the molecular link between circadian rhythm and autism spectrum disorder

Circadian rhythm regulates physiological cycles of awareness and sleepiness. Melatonin production is primarily regulated by circadian regulation of gene expression and is involved in sleep homeostasis. If the circadian rhythm is abnormal, sleep disorders, such as insomnia and several other diseases, can occur. The term 'autism spectrum disorder (ASD)' is used to characterize people who exhibit a certain set of repetitive behaviors, severely constrained interests, social deficits, and/or sensory behaviors that start very early in life. Because many patients with ASD suffer from sleep disorders, sleep disorders and melatonin dysregulation are attracting attention for their potential roles in ASD. ASD is caused by abnormalities during the neurodevelopmental processes owing to various genetic or environmental factors. Recently, the role of microRNAs (miRNAs) in circadian rhythm and ASD have gained attraction. We hypothesized that the relationship between circadian rhythm and ASD could be explained by miRNAs that can regulate or be regulated by either or both. In this study, we introduced a possible molecular link between circadian rhythm and ASD. We performed a thorough literature review to understand their complexity.

Whole Genome Analysis of Dizygotic Twins With Autism Reveals Prevalent Transposon Insertion Within Neuronal Regulatory Elements: Potential Implications for Disease Etiology and Clinical Assessment

Transposable elements (TEs) have been implicated in autism spectrum disorder (ASD). However, our understanding of their roles is far from complete. Herein, we explored de novo TE insertions (dnTEIs) and de novo variants (DNVs) across the genomes of dizygotic twins with ASD and their parents. The neuronal regulatory elements had a tendency to harbor dnTEIs that were shared between twins, but ASD-risk genes had dnTEIs that were unique to each twin. The dnTEIs were 4.6-fold enriched in enhancers that are active in embryonic stem cell (ESC)-neurons (p < 0.001), but DNVs were 1.5-fold enriched in active enhancers of astrocytes (p = 0.0051). Our findings suggest that dnTEIs and DNVs play a role in ASD etiology by disrupting enhancers of neurons and astrocytes.

Cntnap2-dependent molecular networks in autism spectrum disorder revealed through an integrative multi-omics analysis

Autism spectrum disorder (ASD) is a major neurodevelopmental disorder in which patients present with core symptoms of social communication impairment, restricted interest, and repetitive behaviors. Although various studies have been performed to identify ASD-related mechanisms, ASD pathology is still poorly understood. CNTNAP2 genetic variants have been found that represent ASD genetic risk factors, and disruption of Cntnap2 expression has been associated with ASD phenotypes in mice. In this study, we performed an integrative multi-omics analysis by combining quantitative proteometabolomic data obtained with Cntnap2 knockout (KO) mice with multi-omics data obtained from ASD patients and forebrain organoids to elucidate Cntnap2-dependent molecular networks in ASD. To this end, a mass spectrometry-based proteometabolomic analysis of the medial prefrontal cortex in Cntnap2 KO mice led to the identification of Cntnap2-associated molecular features, and these features were assessed in combination with multi-omics data obtained on the prefrontal cortex in ASD patients to identify bona fide ASD cellular processes. Furthermore, a reanalysis of single-cell RNA sequencing data obtained from forebrain organoids derived from patients with CNTNAP2-associated ASD revealed that the aforementioned identified ASD processes were mainly linked to excitatory neurons. On the basis of these data, we constructed Cntnap2-associated ASD network models showing mitochondrial dysfunction, axonal impairment, and synaptic activity. Our results may shed light on the Cntnap2-dependent molecular networks in ASD.

Analysis of miRNA rare variants in amyotrophic lateral sclerosis and in silico prediction of their biological effects

Background: Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease affecting upper and/or lower motor neurons and characterized by complex etiology. Familial cases show high genetic heterogeneity and sporadic cases (90%) are associated with several genetic and environmental risk factors. Among the genetic risk factors, the contribution of non-coding elements, such as microRNAs (miRNAs), to ALS disease susceptibility remains largely unexplored. Aim: This work aims to identify rare variants in miRNA genes in sporadic ALS (sALS) patients which may cause a defective miRNA maturation or altered target gene recognition by changing miRNA secondary structure or seed sequence, respectively. Methods: Rare variants located in miRNA loci with a minor allele frequency (MAF) < 0.01 were extracted from whole genome sequencing (WGS) data of 100 sALS patients. The secondary pre-miRNA structures were predicted using MiRVas to evaluate the impact of the variants on RNA folding process. Human TargetScan was used to retrieve all the potential target genes of miRNAs with variants in the seed region. Over Representation Analysis (ORA) was conducted to compare the lists of target genes for the reference and mutated miRNAs in the seed sequence. Results: Our analysis identified 86 rare variants in 77 distinct miRNAs and distributed in different parts of the miRNA precursors. The presence of these variants changed miRNA secondary structures in ∼70% of MiRVas predictions. By focusing on the 6 rare variants mapping within the seed sequence, the predicted target genes increased in number compared to the reference miRNA and included novel targets in a proportion ranging from 30 to 82%. Interestingly, ORA revealed significant changes in gene set enrichment only for mutated miR-509-1 and miR-941-3 for which the Gene Ontology term related to "nervous system development" was absent and present, respectively, compared to target lists of the reference miRNA. Conclusion: We here developed a workflow to study miRNA rare variants from WGS data and to predict their biological effects on miRNA folding, maturation and target gene recognition. Although this in silico approach certainly needs functional validation in vitro and in vivo, it may help define the role of miRNA variability in ALS and complex diseases.

Non-coding de novo mutations in chromatin interactions are implicated in autism spectrum disorder

Three-dimensional chromatin interactions regulate gene expressions. The significance of de novo mutations (DNMs) in chromatin interactions remains poorly understood for autism spectrum disorder (ASD). We generated 813 whole-genome sequences from 242 Korean simplex families to detect DNMs, and identified target genes which were putatively affected by non-coding DNMs in chromatin interactions. Non-coding DNMs in chromatin interactions were significantly involved in transcriptional dysregulations related to ASD risk. Correspondingly, target genes showed spatiotemporal expressions relevant to ASD in developing brains and enrichment in biological pathways implicated in ASD, such as histone modification. Regarding clinical features of ASD, non-coding DNMs in chromatin interactions particularly contributed to low intelligence quotient levels in ASD probands. We further validated our findings using two replication cohorts, Simons Simplex Collection (SSC) and MSSNG, and showed the consistent enrichment of non-coding DNM-disrupted chromatin interactions in ASD probands. Generating human induced pluripotent stem cells in two ASD families, we were able to demonstrate that non-coding DNMs in chromatin interactions alter the expression of target genes at the stage of early neural development. Taken together, our findings indicate that non-coding DNMs in ASD probands lead to early neurodevelopmental disruption implicated in ASD risk via chromatin interactions.

Connecting phenotype to genotype: PheWAS-inspired analysis of autism spectrum disorder

Autism Spectrum Disorder (ASD) is extremely heterogeneous clinically and genetically. There is a pressing need for a better understanding of the heterogeneity of ASD based on scientifically rigorous approaches centered on systematic evaluation of the clinical and research utility of both phenotype and genotype markers. This paper presents a holistic PheWAS-inspired method to identify meaningful associations between ASD phenotypes and genotypes. We generate two types of phenotype-phenotype (p-p) graphs: a direct graph that utilizes only phenotype data, and an indirect graph that incorporates genotype as well as phenotype data. We introduce a novel methodology for fusing the direct and indirect p-p networks in which the genotype data is incorporated into the phenotype data in varying degrees. The hypothesis is that the heterogeneity of ASD can be distinguished by clustering the p-p graph. The obtained graphs are clustered using network-oriented clustering techniques, and results are evaluated. The most promising clusterings are subsequently analyzed for biological and domain-based relevance. Clusters obtained delineated different aspects of ASD, including differentiating ASD-specific symptoms, cognitive, adaptive, language and communication functions, and behavioral problems. Some of the important genes associated with the clusters have previous known associations to ASD. We found that clusters based on integrated genetic and phenotype data were more effective at identifying relevant genes than clusters constructed from phenotype information alone. These genes included five with suggestive evidence of ASD association and one known to be a strong candidate.

MicroRNA and MicroRNA-Target Variants Associated with Autism Spectrum Disorder and Related Disorders

Autism spectrum disorder (ASD) is a childhood neurodevelopmental disorder with a complex and heterogeneous genetic etiology. MicroRNA (miRNA), a class of small non-coding RNAs, could regulate ASD risk genes post-transcriptionally and affect broad molecular pathways related to ASD and associated disorders. Using whole-genome sequencing, we analyzed 272 samples in 73 families in the New Jersey Language and Autism Genetics Study (NJLAGS) cohort. Families with at least one ASD patient were recruited and were further assessed for language impairment, reading impairment, and other associated phenotypes. A total of 5104 miRNA variants and 1,181,148 3′ untranslated region (3′ UTR) variants were identified in the dataset. After applying several filtering criteria, including population allele frequency, brain expression, miRNA functional regions, and inheritance patterns, we identified high-confidence variants in five brain-expressed miRNAs (targeting 326 genes) and 3′ UTR miRNA target regions of 152 genes. Some genes, such as SCP2 and UCGC, were identified in multiple families. Using Gene Ontology overrepresentation analysis and protein–protein interaction network analysis, we identified clusters of genes and pathways that are important for neurodevelopment. The miRNAs and miRNA target genes identified in this study are potentially involved in neurodevelopmental disorders and should be considered for further functional studies.

MiRLog and dbmiR: prioritization and functional annotation tools to study human microRNA sequence variants

The recent identification of noncoding variants with pathogenic effects suggests that these variations could underlie a significant number of undiagnosed cases. Several computational methods have been developed to predict the functional impact of noncoding variants, but they exhibit only partial concordance and are not integrated with functional annotation resources, making the interpretation of these variants still challenging. MicroRNAs (miRNAs) are small noncoding RNA molecules that act as fine regulators of gene expression and play crucial functions in several biological processes, such as cell proliferation and differentiation. An increasing number of studies demonstrate a significant impact of miRNA single nucleotide variants (SNVs) both in Mendelian diseases and complex traits. To predict the functional effect of miRNA SNVs, we implemented a new meta‐predictor, MiRLog, and we integrated it into a comprehensive database, dbmiR, which includes a precompiled list of all possible miRNA allelic SNVs, providing their biological annotations at nucleotide and miRNA levels. MiRLog and dbmiR were used to explore the genetic variability of miRNAs in 15,708 human genomes included in the gnomAD project, finding several ultra‐rare SNVs with a potentially deleterious effect on miRNA biogenesis and function representing putative contributors to human phenotypes.

NeuroSCORE is a genome-wide omics-based model that identifies candidate disease genes of the central nervous system

To identify candidate disease genes of central nervous system (CNS) phenotypes, we created the Neurogenetic Systematic Correlation of Omics-Related Evidence (NeuroSCORE). We identified five genome-wide metrics highly associated with CNS phenotypes to score 19,601 protein-coding genes. Genes scored one point per metric (range: 0-5), identifying 8298 scored genes (scores ≥ 1) and 1601 "high scoring" genes (scores ≥ 3). Using logistic regression, we determined the odds ratio that genes with a NeuroSCORE from 1 to 5 would be associated with known CNS-related phenotypes compared to genes that scored zero. We tested NeuroSCORE using microarray copy number variants (CNVs) in case-control cohorts and aggregate mouse model data. High scoring genes are associated with CNS phenotypes (OR = 5.5, p < 2E-16), enriched in case CNVs, and mouse ortholog genes that cause behavioral and nervous system abnormalities. We identified 1058 high scoring genes with no disease association in OMIM. Transforming the logistic regression results indicates high scoring genes have an 84-92% chance of being associated with a CNS phenotype. Top scoring genes include GRIA1, MAP4K4, SF1, TNPO2, and ZSWIM8. Finally, we interrogated CNVs in the Clinical Genome Resource, finding the majority of clinically significant CNVs contain high scoring genes. These findings can direct future research and improve molecular diagnostics.

A Next Generation Sequencing-Based Protocol for Screening of Variants of Concern in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with strong genetic influences. There is an increasing demand for ASD genetic testing beyond the traditionally recommended microarray and syndromic autism testing; however, the current whole genome sequencing (WGS) and whole exome sequencing (WES) methods are lacking an academic standard for WGS variant annotation, reporting, and interpretation, tailored towards patients with ASD and offer very limited interpretation for clinical significance. Using WGS data from six family trios, we demonstrate the clinical feasibility and technical implementation of an evidence-based, fully transparent bioinformatics pipeline and report framework for an ASD-focused WGS genetic report. We confirmed a portion of the key variants with Sanger sequencing and provided interpretation with consideration of patients’ clinical symptoms and detailed literature review. Furthermore, we showed that identification of the genetic contributions of ASD core symptoms and comorbidities may promote a better understanding of the ASD pathophysiology, lead to early detection of associated comorbidities, and facilitate pharmacologic intervention based on pathological pathways inferred from the genetic information. We will make the bioinformatics pipeline and interpretation framework publicly available, in an easily accessible format, after validation with a larger cohort. We hope that the present proposed protocol can serve as a starting point to invite discourse and debate to further improve approaches in WGS-based genetic consultation for patients with ASD.

Experiment level curation of transcriptional regulatory interactions in neurodevelopment

To facilitate the development of large-scale transcriptional regulatory networks (TRNs) that may enable in-silico analyses of disease mechanisms, a reliable catalogue of experimentally verified direct transcriptional regulatory interactions (DTRIs) is needed for training and validation. There has been a long history of using low-throughput experiments to validate single DTRIs. Therefore, we reason that a reliable set of DTRIs could be produced by curating the published literature for such evidence. In our survey of previous curation efforts, we identified the lack of details about the quantity and the types of experimental evidence to be a major gap, despite the theoretical importance of such details for the identification of bona fide DTRIs. We developed a curation protocol to inspect the published literature for support of DTRIs at the experiment level, focusing on genes important to the development of the mammalian nervous system. We sought to record three types of low-throughput experiments: Transcription factor (TF) perturbation, TF-DNA binding, and TF-reporter assays. Using this protocol, we examined a total of 1,310 papers to assemble a collection of 1,499 unique DTRIs, involving 251 TFs and 825 target genes, many of which were not reported in any other DTRI resource. The majority of DTRIs (965; 64%) were supported by two or more types of experimental evidence and 27% were supported by all three. Of the DTRIs with all three types of evidence, 170 had been tested using primary tissues or cells and 44 had been tested directly in the central nervous system. We used our resource to document research biases among reports towards a small number of well-studied TFs. To demonstrate a use case for this resource, we compared our curation to a previously published high-throughput perturbation screen and found significant enrichment of the curated targets among genes differentially expressed in the developing brain in response to Pax6 deletion. This study demonstrates a proof-of-concept for the assembly of a high resolution DTRI resource to support the development of large-scale TRNs.

The capacity to computationally reconstruct gene regulatory networks using large-scale biological data is currently limited by the absence of a high confidence set of one-to-one regulatory interactions. Given the lengthy history of using small scale experimental assays to investigate individual interactions, we reason that a reliable collection of gene regulatory interactions could be compiled by systematically inspecting the published literature. To this end, we developed a curation protocol to examine and record evidence of regulatory interactions at the individual experiment level. Focusing on the area of brain development, we applied our pipeline to 1,310 publications. We identified 3,601 individual experiments, providing detailed information about 1,499 regulatory interactions. Many of these interactions have verified activity specifically in the embryonic brain. By capturing reports of regulatory interactions at this level of detail, we equip the users with more granular information than other similar resources, enabling more informed assessments of reliability.

Application of single cell genomics to focal epilepsies: A call to action

Focal epilepsies are the largest epilepsy subtype and associated with significant morbidity. Somatic variation is a newly recognized genetic mechanism underlying a subset of focal epilepsies, but little is known about the processes through which somatic mosaicism causes seizures, the cell types carrying the pathogenic variants, or their developmental origin. Meanwhile, the inception of single cell biology has completely revolutionized the study of neurological diseases and has the potential to answer some of these key questions. Focusing on single cell genomics, transcriptomics, and epigenomics in focal epilepsy research, circumvents the averaging artifact associated with studying bulk brain tissue and offers the kind of granularity that is needed for investigating the consequences of somatic mosaicism. Here we have provided a brief overview of some of the most developed single cell techniques and the major considerations around applying them to focal epilepsy research.

Longitudinal stability of salivary microRNA biomarkers in children and adolescents with autism spectrum disorder

BACKGROUND

Autism spectrum disorder (ASD) is a complex neurological condition with increasing prevalence. Few tools accurately predict the developmental trajectory of children with ASD. Such tools would allow clinicians to provide accurate prognoses and track the efficacy of therapeutic interventions. Salivary RNAs that reflect the genetic-environmental interactions underlying ASD may provide objective measures of symptom severity and developmental outcomes. This study investigated whether salivary RNAs previously identified in childhood ASD remain perturbed in older children. We also explored whether RNA candidates changed with therapeutic intervention.

METHOD

A case-control design was used to characterize levels of 78 saliva RNA candidates among 96 children (48 ASD, 48 non-ASD, mean age: 11 years). Thirty-one children (22 ASD, 9 non-ASD developmental delay, mean age: 4 years) were followed longitudinally to explore changes of RNA candidates during early intervention. Saliva RNA and standardized behavioral assessments were collected for each participant. Associations between candidate RNAs and behavioral scores were determined in both groups via Spearman Correlation. Changes in candidate RNAs across two time-points were assessed in the younger cohort via Wilcoxon rank-sum test.

RESULTS

Seven RNAs were associated with VABS-II and BASC scores in the older group ([R] >0.25, FDR< 0.15). Within the younger cohort, 12 RNAs displayed significant changes over time (FDR< 0.05). Three microRNAs were associated with behavioral scores and changed over time (miR-182-5p, miR-146b-5p, miR-374a-5p).

CONCLUSION

Several salivary RNAs are strongly associated with autistic behaviors in older individuals with ASD and change as early as three months after therapy initiation in younger children. These molecules could be used to track treatment effectiveness and provide prognoses. Further validation is necessary.

Novel treatments for autism spectrum disorder based on genomics and systems biology

BACKGROUND

Autism spectrum disorder (ASD) is a highly heterogeneous neurodevelopmental disorder with a complex underlying genetic architecture. There are currently no known pharmacologic treatments for the core ASD symptoms of social deficits and restricted/ repetitive behavior. However, there are dozens of clinical trials currently underway that are testing the impact of novel and existing agents on core and associated symptoms in ASD.

METHODS

We present a narrative synthesis of the historical and contemporary challenges to drug discovery in ASD. We then provide an overview of novel treatments currently under investigation from a genomics and systems biology perspective.

RESULTS

Data driven network and cluster analyses suggest alterations in transcriptional regulation, chromatin remodelling, synaptic transmission, neuropeptide signalling, and/or immunological mechanisms may contribute to or underlie the development of ASD. Agents and upcoming trials targeting each of the above listed systems are reviewed.

CONCLUSION

Identifying effective pharmacologic treatments for the core and associated symptom domains in ASD will require further collaboration and innovation in the areas of outcome measurement, biomarker research, and genomics, as well as systematic efforts to identify and treat subgroups of individuals with ASD who may be differentially responsive to specific treatments.

MicroRNA-210 Regulates Dendritic Morphology and Behavioural Flexibility in Mice

MicroRNAs are known to be critical regulators of neuronal plasticity. The highly conserved, hypoxia-regulated microRNA-210 (miR-210) has been shown to be associated with long-term memory in invertebrates and dysregulated in neurodevelopmental and neurodegenerative disease models. However, the role of miR-210 in mammalian neuronal function and cognitive behaviour remains unexplored. Here we generated Nestin-cre-driven miR-210 neuronal knockout mice to characterise miR-210 regulation and function using in vitro and in vivo methods. We identified miR-210 localisation throughout neuronal somas and dendritic processes and increased levels of mature miR-210 in response to neural activity in vitro. Loss of miR-210 in neurons resulted in higher oxidative phosphorylation and ROS production following hypoxia and increased dendritic arbour density in hippocampal cultures. Additionally, miR-210 knockout mice displayed altered behavioural flexibility in rodent touchscreen tests, particularly during early reversal learning suggesting processes underlying updating of information and feedback were impacted. Our findings support a conserved, activity-dependent role for miR-210 in neuroplasticity and cognitive function.

The landscape of somatic mutation in cerebral cortex of autistic and neurotypical individuals revealed by ultra-deep whole-genome sequencing

We characterize the landscape of somatic mutations-mutations occurring after fertilization-in the human brain using ultra-deep (~250×) whole-genome sequencing of prefrontal cortex from 59 donors with autism spectrum disorder (ASD) and 15 control donors. We observe a mean of 26 somatic single-nucleotide variants per brain present in ≥4% of cells, with enrichment of mutations in coding and putative regulatory regions. Our analysis reveals that the first cell division after fertilization produces ~3.4 mutations, followed by 2-3 mutations in subsequent generations. This suggests that a typical individual possesses ~80 somatic single-nucleotide variants present in ≥2% of cells-comparable to the number of de novo germline mutations per generation-with about half of individuals having at least one potentially function-altering somatic mutation somewhere in the cortex. ASD brains show an excess of somatic mutations in neural enhancer sequences compared with controls, suggesting that mosaic enhancer mutations may contribute to ASD risk.

Autism-associated miR-873 regulates ARID1B, SHANK3 and NRXN2 involved in neurodevelopment

Autism spectrum disorders (ASD) are highly heritable neurodevelopmental disorders with significant genetic heterogeneity. Noncoding microRNAs (miRNAs) are recognised as playing key roles in development of ASD albeit the function of these regulatory genes remains unclear. We previously conducted whole-exome sequencing of Australian families with ASD and identified four novel single nucleotide variations in mature miRNA sequences. A pull-down transcriptome analysis using transfected SH-SY5Y cells proposed a mechanistic model to examine changes in binding affinity associated with a unique mutation found in the conserved 'seed' region of miR-873-5p (rs777143952: T > A). Results suggested several ASD-risk genes were differentially targeted by wild-type and mutant miR-873 variants. In the current study, a dual-luciferase reporter assay confirmed miR-873 variants have a 20-30% inhibition/dysregulation effect on candidate autism risk genes ARID1B, SHANK3 and NRXN2 and also confirmed the affected expression with qPCR. In vitro mouse hippocampal neurons transfected with mutant miR-873 showed less morphological complexity and enhanced sodium currents and excitatory neurotransmission compared to cells transfected with wild-type miR-873. A second in vitro study showed CRISPR/Cas9 miR-873 disrupted SH-SY5Y neuroblastoma cells acquired a neuronal-like morphology and increased expression of ASD important genes ARID1B, SHANK3, ADNP2, ANK2 and CHD8. These results represent the first functional evidence that miR-873 regulates key neural genes involved in development and cell differentiation.

The role of glutathione redox imbalance in autism spectrum disorder: A review

The role of glutathione in autism spectrum disorder (ASD) is emerging as a major topic, due to its role in the maintenance of the intracellular redox balance. Several studies have implicated glutathione redox imbalance as a leading factor in ASD, and both ASD and many other neurodevelopmental disorders involve low levels of reduced glutathione (GSH), high levels of oxidized glutathione (GSSG), and abnormalities in the expressions of glutathione-related enzymes in the blood or brain. Glutathione metabolism, through its impact on redox environment or redox-independent mechanisms, interferes with multiple mechanisms involved in ASD pathogenesis. Glutathione-mediated regulation of glutamate receptors [e.g., N-methyl-d-aspartate (NMDA) receptor], as well as the role of glutamate as a substrate for glutathione synthesis, may be involved in the regulation of glutamate excitotoxicity. However, the interaction between glutathione and glutamate in the pathogenesis of brain diseases may vary from synergism to antagonism. Modulation of glutathione is also associated with regulation of redox-sensitive transcription factors nuclear factor kappa B (NF-κB) and activator protein 1 (AP-1) and downstream signaling (proinflammatory cytokines and inducible enzymes), thus providing a significant impact on neuroinflammation. Mitochondrial dysfunction, as well as neuronal apoptosis, may also provide a significant link between glutathione metabolism and ASD. Furthermore, it has been recently highlighted that glutathione can affect and modulate DNA methylation and epigenetics. Review analysis including research studies meeting the required criteria for analysis showed statistically significant differences between the plasma GSH and GSSG levels as well as GSH:GSSG ratio in autistic patients compared with healthy individuals (P = 0.0145, P = 0.0150 and P = 0.0202, respectively). Therefore, the existing data provide a strong background on the role of the glutathione system in ASD pathogenesis. Future research is necessary to investigate the role of glutathione redox signaling in ASD, which could potentially also lead to promising therapeutics.

Brain Organoids as Model Systems for Genetic Neurodevelopmental Disorders

Neurodevelopmental disorders (NDDs) are a group of disorders in which the development of the central nervous system (CNS) is disturbed, resulting in different neurological and neuropsychiatric features, such as impaired motor function, learning, language or non-verbal communication. Frequent comorbidities include epilepsy and movement disorders. Advances in DNA sequencing technologies revealed identifiable genetic causes in an increasingly large proportion of NDDs, highlighting the need of experimental approaches to investigate the defective genes and the molecular pathways implicated in abnormal brain development. However, targeted approaches to investigate specific molecular defects and their implications in human brain dysfunction are prevented by limited access to patient-derived brain tissues. In this context, advances of both stem cell technologies and genome editing strategies during the last decade led to the generation of three-dimensional (3D) in vitro-models of cerebral organoids, holding the potential to recapitulate precise stages of human brain development with the aim of personalized diagnostic and therapeutic approaches. Recent progresses allowed to generate 3D-structures of both neuronal and non-neuronal cell types and develop either whole-brain or region-specific cerebral organoids in order to investigate in vitro key brain developmental processes, such as neuronal cell morphogenesis, migration and connectivity. In this review, we summarized emerging methodological approaches in the field of brain organoid technologies and their application to dissect disease mechanisms underlying an array of pediatric brain developmental disorders, with a particular focus on autism spectrum disorders (ASDs) and epileptic encephalopathies.

Recent Progress on Relevant microRNAs in Autism Spectrum Disorders

Autism spectrum disorder (ASD) is a neurodevelopmental disorder whose pathogenesis is unclear and is affected by both genetic and environmental factors. The microRNAs (miRNAs) are a kind of single-stranded non-coding RNA with 20-22 nucleotides, which normally inhibit their target mRNAs at a post-transcriptional level. miRNAs are involved in almost all biological processes and are closely related to ASD and many other diseases. In this review, we summarize relevant miRNAs in ASD, and analyze dysregulated miRNAs in brain tissues and body fluids of ASD patients, which may contribute to the pathogenesis and diagnosis of ASD.

Epigenomics and genotype-phenotype association analyses reveal conserved genetic architecture of complex traits in cattle and human

Background

Lack of comprehensive functional annotations across a wide range of tissues and cell types severely hinders the biological interpretations of phenotypic variation, adaptive evolution, and domestication in livestock. Here we used a combination of comparative epigenomics, genome-wide association study (GWAS), and selection signature analysis, to shed light on potential adaptive evolution in cattle.

Results

We cross-mapped 8 histone marks of 1300 samples from human to cattle, covering 178 unique tissues/cell types. By uniformly analyzing 723 RNA-seq and 40 whole genome bisulfite sequencing (WGBS) datasets in cattle, we validated that cross-mapped histone marks captured tissue-specific expression and methylation, reflecting tissue-relevant biology. Through integrating cross-mapped tissue-specific histone marks with large-scale GWAS and selection signature results, we for the first time detected relevant tissues and cell types for 45 economically important traits and artificial selection in cattle. For instance, immune tissues are significantly associated with health and reproduction traits, multiple tissues for milk production and body conformation traits (reflecting their highly polygenic architecture), and thyroid for the different selection between beef and dairy cattle. Similarly, we detected relevant tissues for 58 complex traits and diseases in humans and observed that immune and fertility traits in humans significantly correlated with those in cattle in terms of relevant tissues, which facilitated the identification of causal genes for such traits. For instance, PIK3CG, a gene highly specifically expressed in mononuclear cells, was significantly associated with both age-at-menopause in human and daughter-still-birth in cattle. ICAM, a T cell-specific gene, was significantly associated with both allergic diseases in human and metritis in cattle.

Conclusion

Collectively, our results highlighted that comparative epigenomics in conjunction with GWAS and selection signature analyses could provide biological insights into the phenotypic variation and adaptive evolution. Cattle may serve as a model for human complex traits, by providing additional information beyond laboratory model organisms, particularly when more novel phenotypes become available in the near future.

Rare variant association testing in the non-coding genome

The development of next-generation sequencing technologies has opened-up some new possibilities to explore the contribution of genetic variants to human diseases and in particular that of rare variants. Statistical methods have been developed to test for association with rare variants that require the definition of testing units and, in these testing units, the selection of qualifying variants to include in the test. In the coding regions of the genome, testing units are usually the different genes and qualifying variants are selected based on their functional effects on the encoded proteins. Extending these tests to the non-coding regions of the genome is challenging. Testing units are difficult to define as the non-coding genome organisation is still rather unknown. Qualifying variants are difficult to select as the functional impact of non-coding variants on gene expression is hard to predict. These difficulties could explain why very few investigators so far have analysed the non-coding parts of their whole genome sequencing data. These non-coding parts yet represent the vast majority of the genome and some studies suggest that they could play a major role in disease susceptibility. In this review, we discuss recent experimental and statistical developments to gain knowledge on the non-coding genome and how this knowledge could be used to include rare non-coding variants in association tests. We describe the few studies that have considered variants from the non-coding genome in association tests and how they managed to define testing units and select qualifying variants.

Recent Advances in Understanding the Genetic Architecture of Autism

Recent advances in understanding the genetic architecture of autism spectrum disorder have allowed for unprecedented insight into its biological underpinnings. New studies have elucidated the contributions of a variety of forms of genetic variation to autism susceptibility. While the roles of de novo copy number variants and single-nucleotide variants-causing loss-of-function or missense changes-have been increasingly recognized and refined, mosaic single-nucleotide variants have been implicated more recently in some cases. Moreover, inherited variants (including common variants) and, more recently, rare recessive inherited variants have come into greater focus. Finally, noncoding variants-both inherited and de novo-have been implicated in the last few years. This work has revealed a convergence of diverse genetic drivers on common biological pathways and has highlighted the ongoing importance of increasing sample size and experimental innovation. Continuing to synthesize these genetic findings with functional and phenotypic evidence and translating these discoveries to clinical care remain considerable challenges for the field.

Modeling neuronal consequences of autism-associated gene regulatory variants with human induced pluripotent stem cells

Genetic factors contribute to the development of autism spectrum disorder (ASD), and although non-protein-coding regions of the genome are being increasingly implicated in ASD, the functional consequences of these variants remain largely uncharacterized. Induced pluripotent stem cells (iPSCs) enable the production of personalized neurons that are genetically matched to people with ASD and can therefore be used to directly test the effects of genomic variation on neuronal gene expression, synapse function, and connectivity. The combined use of human pluripotent stem cells with genome editing to introduce or correct specific variants has proved to be a powerful approach for exploring the functional consequences of ASD-associated variants in protein-coding genes and, more recently, long non-coding RNAs (lncRNAs). Here, we review recent studies that implicate lncRNAs, other non-coding mutations, and regulatory variants in ASD susceptibility. We also discuss experimental design considerations for using iPSCs and genome editing to study the role of the non-protein-coding genome in ASD.

Spatio-Temporal Roles of ASD-Associated Variants in Human Brain Development

Transcriptional regulation of the genome arguably provides the basis for the anatomical elaboration and dynamic operation of the human brain. It logically follows that genetic variations affecting gene transcription contribute to mental health disorders, including autism spectrum disorder (ASD). A number of recent studies have shown the role of de novo variants (DNVs) in disrupting early neurodevelopment. However, there is limited knowledge concerning the role of inherited variants during the early brain development of ASD. In this study, we investigate the role of rare inherited variations in neurodevelopment. We conducted co-expression network analyses using an anatomically comprehensive atlas of the developing human brain and examined whether rare coding and regulatory variants, identified from our genetic screening of Australian families with ASD, work in different spatio-temporal functions.

Whole genome investigation of an atypical autism case identifies a novel ANOS1 mutation with subsequent diagnosis of Kallmann syndrome

We report an actionable secondary finding from whole-genome sequencing (WGS) of a 10-year-old boy with autism. WGS identified non-synonymous variants in several genes, including a nonsense mutation in the ANOS1 gene which is an X-linked cause of Kallmann syndrome. WGS can provide insights into complex genetic disorders such as autism, and actionable incidental findings can offer the potential for therapeutic interventions.

Genomics and the future of psychopharmacology: MicroRNAs offer novel therapeutics

MicroRNAs (miRNAs) are short, noncoding RNAs functioning as regulators of the transcription of protein-coding genes in eukaryotes. During the last two decades, studies on miRNAs indicate that they have potential as diagnostic and prognostic biomarkers for a wide range of cancers. Research interest in miRNAs has moved to embrace further medical disciplines, including neuropsychiatric disorders, comparing miRNA expression and mRNA targets between patient and control blood samples and postmortem brain tissues, as well as in animal models of neuropsychiatric disorders. This manuscript reviews recent findings on miRNAs implicated in the pathology of mood disorders, schizophrenia, and autism, as well as their diagnostic potential, and their potential as tentative targets for future therapeutics. The plausible contribution of X chromosome miRNAs to the larger prevalence of major depression among women is also evaluated.


A 2020 View on the Genetics of Developmental and Epileptic Encephalopathies

Developmental and epileptic encephalopathies (DEEs) can be primarily attributed to genetic causes. The genetic landscape of DEEs has been largely shaped by the rise of high-throughput sequencing, which led to the discovery of new DEE-associated genes and helped identify de novo pathogenic variants. We discuss briefly the contribution of de novo variants to DEE and also focus on alternative inheritance models that contribute to DEE. First, autosomal recessive inheritance in outbred populations may have a larger contribution than previously appreciated, accounting for up to 13% of DEEs. A small subset of genes that typically harbor de novo variants have been associated with recessive inheritance, and often these individuals have more severe clinical presentations. Additionally, pathogenic variants in X-linked genes have been identified in both affected males and females, possibly due to a lack of X-chromosome inactivation skewing. Collectively, exome sequencing has resulted in a molecular diagnosis for many individuals with DEE, but this still leaves many cases unsolved. Multiple factors contribute to the missing etiology, including nonexonic variants, mosaicism, epigenetics, and oligogenic inheritance. Here, we focus on the first 2 factors. We discuss the promises and challenges of genome sequencing, which allows for a more comprehensive analysis of the genome, including interpretation of structural and noncoding variants and also yields a high number of de novo variants for interpretation. We also consider the contribution of genetic mosaicism, both what it means for a molecular diagnosis in mosaic individuals and the important implications for genetic counseling.

Cellular and molecular characterization of multiplex autism in human induced pluripotent stem cell-derived neurons

Background

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with pronounced heritability in the general population. This is largely attributable to the effects of polygenic susceptibility, with inherited liability exhibiting distinct sex differences in phenotypic expression. Attempts to model ASD in human cellular systems have principally involved rare de novo mutations associated with ASD phenocopies. However, by definition, these models are not representative of polygenic liability, which accounts for the vast share of population-attributable risk.

Methods

Here, we performed what is, to our knowledge, the first attempt to model multiplex autism using patient-derived induced pluripotent stem cells (iPSCs) in a family manifesting incremental degrees of phenotypic expression of inherited liability (absent, intermediate, severe). The family members share an inherited variant of uncertain significance (VUS) in GPD2, a gene that was previously associated with developmental disability but here is insufficient by itself to cause ASD. iPSCs from three first-degree relatives and an unrelated control were differentiated into both cortical excitatory (cExN) and cortical inhibitory (cIN) neurons, and cellular phenotyping and transcriptomic analysis were conducted.

Results

cExN neurospheres from the two affected individuals were reduced in size, compared to those derived from unaffected related and unrelated individuals. This reduction was, at least in part, due to increased apoptosis of cells from affected individuals upon initiation of cExN neural induction. Likewise, cIN neural progenitor cells from affected individuals exhibited increased apoptosis, compared to both unaffected individuals. Transcriptomic analysis of both cExN and cIN neural progenitor cells revealed distinct molecular signatures associated with affectation, including the misregulation of suites of genes associated with neural development, neuronal function, and behavior, as well as altered expression of ASD risk-associated genes.

Conclusions

We have provided evidence of morphological, physiological, and transcriptomic signatures of polygenic liability to ASD from an analysis of cellular models derived from a multiplex autism family. ASD is commonly inherited on the basis of additive genetic liability. Therefore, identifying convergent cellular and molecular phenotypes resulting from polygenic and monogenic susceptibility may provide a critical bridge for determining which of the disparate effects of rare highly deleterious mutations might also apply to common autistic syndromes.

Genetic insights and neurobiological implications from NRXN1 in neuropsychiatric disorders

Many neuropsychiatric and neurodevelopmental disorders commonly share genetic risk factors. To date, the mechanisms driving the pathogenesis of these disorders, particularly how genetic variations affect the function of risk genes and contribute to disease symptoms, remain largely unknown. Neurexins are a family of synaptic adhesion molecules, which play important roles in the formation and establishment of synaptic structure, as well as maintenance of synaptic function. Accumulating genomic findings reveal that genetic variations within genes encoding neurexins are associated with a variety of psychiatric conditions such as schizophrenia, autism spectrum disorder, and some developmental abnormalities. In this review, we focus on NRXN1, one of the most compelling psychiatric risk genes of the neurexin family. We performed a comprehensive survey and analysis of current genetic and molecular data including both common and rare alleles within NRXN1 associated with psychiatric illnesses, thus providing insights into the genetic risk conferred by NRXN1. We also summarized the neurobiological evidences, supporting the function of NRXN1 and its protein products in synaptic formation, organization, transmission and plasticity, as well as disease-relevant behaviors, and assessed the mechanistic link between the mutations of NRXN1 and synaptic and behavioral pathology in neuropsychiatric disorders.

Essential genetic findings in neurodevelopmental disorders

Neurodevelopmental disorders (NDDs) represent a growing medical challenge in modern societies. Ever-increasing sophisticated diagnostic tools have been continuously revealing a remarkably complex architecture that embraces genetic mutations of distinct types (chromosomal rearrangements, copy number variants, small indels, and nucleotide substitutions) with distinct frequencies in the population (common, rare, de novo). Such a network of interacting players creates difficulties in establishing rigorous genotype-phenotype correlations. Furthermore, individual lifestyles may also contribute to the severity of the symptoms fueling a large spectrum of gene-environment interactions that have a key role on the relationships between genotypes and phenotypes.Herein, a review of the genetic discoveries related to NDDs is presented with the aim to provide useful general information for the medical community.

Gene regulation and the architecture of complex human traits in the genomics era

Virtually all human psychological and behavioral traits are at least partially heritable. For nearly a century, classical genetic studies have sought to understand how genetic variation contributes to human variation in these traits. More recently, genome-wide association studies have identified large numbers of specific genetic variants linked with complex traits. Many of these variants fall outside of protein-coding genes, in putative gene regulatory elements. This suggests that some fraction of causal human genetic variation acts through gene regulation. New developments in the field of regulatory genomics offer resources and methods to understand how genetic variants that alter gene expression contribute to human psychology and risk for psychiatric disease.

Adverse drug event-related hospitalisation in persons with neurodevelopmental disorders: a state-wide retrospective cohort study

BACKGROUND

Little is known about the sociodemographic and clinical characteristics of adverse drug events (ADEs) in patients with neurodevelopmental disorders (NDD).

OBJECTIVE

The objective of this study was to describe and compare the demographic details of people with and without NDD hospitalised due to ADEs.

METHODS

The all-inclusive New South Wales Admitted Patient Data Collection from 2001 to 2014 was employed to identify ADE-related hospitalisations in patients with NDD using the International Classification of Diseases 10th revision Australian modification codes. We derived case sets specific to different clinical groups and patient characteristics and compared proportional differences between patients with and without intellectual disability using chi squared tests.

RESULTS

A total of 2173 patients with NDD were admitted for acute care of ADEs, accounting for 0.7% of all ADE-related hospitalisations. Hospitalised ADEs among patients with NDD increased by twofold over the 14-year study period. Psychotropic medications and opioid analgesic medications were leading causes of ADE-related hospitalisations in patients with NDD. Compared with their counterparts, patients with NDD were younger, experienced more socio-economic disadvantage and less private insurance coverage, suffered with less severe but different co-morbid clinical conditions and incurred more challenges in the acute hospital care setting.

CONCLUSION

Although the pattern of ADE-related hospitalisations in patients with NDD differed from that in patients without NDD, there is a lack of targeted healthcare programmes to meet their special needs. This study suggests the need for countermeasures in primary healthcare settings to reduce the burden of ADEs in this vulnerable group.

Autism risk genes are evolutionarily ancient and maintain a unique feature landscape that echoes their function

Previous research on autism risk (ASD), developmental regulatory (DevReg), and central nervous system (CNS) genes suggests they tend to be large in size, enriched in nested repeats, and mutation intolerant. The relevance of these genomic features is intriguing yet poorly understood. In this study, we investigated the feature landscape of these gene groups to discover structural themes useful in interpreting their function, developmental patterns, and evolutionary history. ASD, DevReg, CNS, housekeeping, and whole genome control (WGC) groups were compiled using various resources. Multiple gene features of interest were extracted from NCBI/UCSC Bioinformatics. Residual variation intolerance scores, Exome Aggregation Consortium pLI scores, and copy number variation data from Decipher were used to estimate variation intolerance. Gene age and protein-protein interactions (PPI) were estimated using Ensembl and EBI Intact databases, respectively. Compared to WGC: ASD, DevReg, and CNS genes are longer, produce larger proteins, maintain greater numbers/density of conserved noncoding elements and transposable elements, produce more transcript variants, and are comparatively variation intolerant. After controlling for gene size, mutation tolerance, and clinical association, ASD genes still retain many of these same features. In addition, we also found that ASD genes that are extremely mutation intolerant have larger PPI networks. These data support many of the recent findings within the field of autism genetics but also expand our understanding of the evolution of these broad gene groups, their potential regulatory complexity, and the extent to which they interact with the cellular network. Autism Res 2019, 12: 860-869. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Autism risk genes are more ancient compared to other genes in the genome. As such, they exhibit physical features related to their age, including long gene and protein size and regulatory sequences that help to control gene expression. They share many of these same features with other genes that are expressed in the brain and/or are associated with prenatal development.

The within-subject application of diffusion tensor MRI and CLARITY reveals brain structural changes in Nrxn2 deletion mice

Background

Of the many genetic mutations known to increase the risk of autism spectrum disorder, a large proportion cluster upon synaptic proteins. One such family of presynaptic proteins are the neurexins (NRXN), and recent genetic and mouse evidence has suggested a causative role for NRXN2 in generating altered social behaviours. Autism has been conceptualised as a disorder of atypical connectivity, yet how single-gene mutations affect such connectivity remains under-explored. To attempt to address this, we have developed a quantitative analysis of microstructure and structural connectivity leveraging diffusion tensor MRI (DTI) with high-resolution 3D imaging in optically cleared (CLARITY) brain tissue in the same mouse, applied here to the Nrxn2α knockout (KO) model.

Methods

Fixed brains of Nrxn2α KO mice underwent DTI using 9.4 T MRI, and diffusion properties of socially relevant brain regions were quantified. The same tissue was then subjected to CLARITY to immunolabel axons and cell bodies, which were also quantified.

Results

DTI revealed increases in fractional anisotropy in the amygdala (including the basolateral nuclei), the anterior cingulate cortex, the orbitofrontal cortex and the hippocampus. Axial diffusivity of the anterior cingulate cortex and orbitofrontal cortex was significantly increased in Nrxn2α KO mice, as were tracts between the amygdala and the orbitofrontal cortex. Using CLARITY, we find significantly altered axonal orientation in the amygdala, orbitofrontal cortex and the anterior cingulate cortex, which was unrelated to cell density.

Conclusions

Our findings demonstrate that deleting a single neurexin gene (Nrxn2α) induces atypical structural connectivity within socially relevant brain regions. More generally, our combined within-subject DTI and CLARITY approach presents a new, more sensitive method of revealing hitherto undetectable differences in the autistic brain.

Electronic supplementary material

The online version of this article (10.1186/s13229-019-0261-9) contains supplementary material, which is available to authorized users.

The Role of De Novo Noncoding Regulatory Mutations in Neurodevelopmental Disorders

Advances in sequencing technology have significantly expanded our understanding of the genetics of autism and neurodevelopmental disorders (NDDs). Continued technological improvements and cost reductions have now shifted the focus to investigations into the functional noncoding portions of the genome. There is a patient trend toward an excess of de novo and potentially disruptive mutations among conserved noncoding sequences implicated in the regulation of genes. The signals become stronger when restricted to genes already implicated in NDDs, but de novo mutation in such elements is estimated to account for <5% of patients. Larger sample sizes, improved variant detection, functional testing, and better approaches to classify noncoding variation will be required to identify specific pathogenic variants underlying disease.

MicroRNA Cross-Involvement in Autism Spectrum Disorders and Atopic Dermatitis: A Literature Review

Autism Spectrum Disorder (ASD) is a category of neurodevelopmental disturbances seriously affecting social skills, to which the scientific community has paid great attention in last decades. To date, their pathogenesis is still unknown, but several studies highlighted the relevance of gene-environment interactions in the onset of ASD. In addition, an immune involvement was seen in a wide number of ASD subjects, leading several researchers to hypothesize a possible common pathogenesis between ASD and immune disturbances, including Atopic Dermatitis (AD). In general, among potential contributing factors, microRNAs (miRNAs), small molecules capable of controlling gene expression and targeting mRNA transcripts, might represent one of the major circulating link, possibly unraveling the connections between neurodevelopmental and immune conditions. Under such premises, we conducted a systematic literature review, under the PRISMA guidelines, trying to define the panel of common miRNAs involved in both ASD and AD. The review retrieved articles published between January 1, 2005, and December 13, 2018, in PubMed, ScienceDirect, PsycARTICLES, and Google Scholar. We found a handful of works dealing with miRNAs in ASD and AD, with the most overlapping dysregulated miRNAs being miR-146 and miR-155. Two possible compounds are abnormally regulated in both ASD and AD subjects, possibly cross-contributing to the interactions between the two disorders, setting the basis to investigate more precisely the possible link between ASD and AD from another, not just clinical, perspective.