Functional DNA methylation signatures for autism spectrum disorder genomic risk loci: 16p11.2 deletions and CHD8 variants

Maternal Immune Activation and Autism in Offspring: What Is the Evidence for Causation?

The maternal immune activation hypothesis has gained attention over the past 2 decades as a potential contributor to the etiology of autism. This hypothesis posits that maternal conditions associated with inflammation during pregnancy may increase the risk of autism in offspring. Autism is highly heritable, and causal environmental contributors to autism largely remain elusive. We review studies on maternal conditions during pregnancy, all associated with some degree of systemic inflammation, namely maternal infections, autoimmunity, and high body mass index. We also review studies of inflammatory markers in biological samples collected from mothers during pregnancy or from neonates and their relationship with autism assessed in children later in life. Recent reports indicate familial clustering of autism, autoimmunity, and infections, as well as genetic correlations between autism and aspects of immune function. Given this literature, there is an apparent risk of confounding of the reported associations between inflammatory exposures and autism by familial genetic factors in both clinical and epidemiological cohort studies. We highlight recent studies that have attempted to address potential confounding to assess evidence of causal effects of inflammation during early life in autism.

Association of CHD8 Gene Polymorphic Variants with the Clinical Phenotype of Autism Spectrum Disorder

Background: The CHD8 gene encodes chromodomain helicase DNA-binding protein 8 (CHD8), which is a transcriptional regulator involved in neuron development, myelination, and synaptogenesis. Some CHD8 gene mutations lead to neurodevelopmental syndromes with core symptoms of autism. The aim of this study was to perform an analysis of the family-based association of CHD8 gene polymorphisms with the occurrence and clinical phenotype of autism spectrum disorder (ASD). Methods: We analyzed 210 Caucasian children with ASD and their biological parents. The genotyping of specified polymorphisms, i.e., rs7148741, rs35057134, and rs10467770, was performed using TaqMan-PCR and compared with specific symptoms of ASD. Results: The G allele (rs7148741) was associated with muscle hypotonia as compared with the AA homozygotes. AA homozygosity (rs35057134) predisposed an individual to the use of an incubator, heart rate fluctuations, and the necessity of hospitalization. Moreover, the alleles and genotypes of this polymorphism were characterized by different Apgar scores and distributions. Additionally, CC homozygotes of rs10467770 were more often predisposed to the use of an incubator and hospitalization relative to T allele carriers. The average Apgar score was higher in TT homozygotes. Conclusions: Polymorphisms of the CHD8 gene may determine specific clinical phenotypes of ASD.

Evaluation of 100 Dutch cases with 16p11.2 deletion and duplication syndromes; from clinical manifestations towards personalized treatment options

The 16p11.2 deletion syndrome is a clinically heterogeneous disorder, characterized by developmental delay, intellectual disability, hyperphagia, obesity, macrocephaly and psychiatric problems. Cases with 16p11.2 duplication syndrome have similar neurodevelopmental problems, but typically show a partial 'mirror phenotype' with underweight and microcephaly. Various copy number variants (CNVs) of the chromosomal 16p11.2 region have been described. Most is known about the 'typical' 16p11.2 BP4-BP5 (29.6-30.2 Mb; ~600 kb) deletions and duplications, but there are also several published cohorts with more distal 16p11.2 BP2-BP3 CNVs (28.8-29.0 Mb; ~220 kb), who exhibit clinical overlap. We assessed 100 cases with various pathogenic 16p11.2 CNVs and compared their clinical characteristics to provide more clear genotype-phenotype correlations and raise awareness of the different 16p11.2 CNVs. Neurodevelopmental and weight issues were reported in the majority of cases. Cases with distal 16p11.2 BP2-BP3 deletion showed the most severe obesity phenotype (73.7% obesity, mean BMI SDS 3.2). In addition to the more well defined typical 16p11.2 BP4-BP5 and distal 16p11.2 BP2-BP3 CNVs, we describe the clinical features of five cases with other, overlapping, 16p11.2 CNVs in more detail. Interestingly, four cases had a second genetic diagnosis and 18 cases an additional gene variant of uncertain significance, that could potentially help explain the cases' phenotypes. In conclusion, we provide an overview of our Dutch cohort of cases with various pathogenic 16p11.2 CNVs and relevant second genetic findings, that can aid in adequately recognizing, diagnosing and counseling of individuals with 16p11.2 CNVs, and describe the personalized medicine for cases with these conditions.

The expanding diagnostic toolbox for rare genetic diseases

Genomic technologies, such as targeted, exome and short-read genome sequencing approaches, have revolutionized the care of patients with rare genetic diseases. However, more than half of patients remain without a diagnosis. Emerging approaches from research-based settings such as long-read genome sequencing and optical genome mapping hold promise for improving the identification of disease-causal genetic variants. In addition, new omic technologies that measure the transcriptome, epigenome, proteome or metabolome are showing great potential for variant interpretation. As genetic testing options rapidly expand, the clinical community needs to be mindful of their individual strengths and limitations, as well as remaining challenges, to select the appropriate diagnostic test, correctly interpret results and drive innovation to address insufficiencies. If used effectively - through truly integrative multi-omics approaches and data sharing - the resulting large quantities of data from these established and emerging technologies will greatly improve the interpretative power of genetic and genomic diagnostics for rare diseases.

Episignatures in practice: independent evaluation of published episignatures for the molecular diagnostics of ten neurodevelopmental disorders

Variants of uncertain significance (VUS) are a significant issue for the molecular diagnosis of rare diseases. The publication of episignatures as effective biomarkers of certain Mendelian neurodevelopmental disorders has raised hopes to help classify VUS. However, prediction abilities of most published episignatures have not been independently investigated yet, which is a prerequisite for an informed and rigorous use in a diagnostic setting. We generated DNA methylation data from 101 carriers of (likely) pathogenic variants in ten different genes, 57 VUS carriers, and 25 healthy controls. Combining published episignature information and new validation data with a k-nearest-neighbour classifier within a leave-one-out scheme, we provide unbiased specificity and sensitivity estimates for each of the signatures. Our procedure reached 100% specificity, but the sensitivities unexpectedly spanned a very large spectrum. While ATRX, DNMT3A, KMT2D, and NSD1 signatures displayed a 100% sensitivity, CREBBP-RSTS and one of the CHD8 signatures reached <40% sensitivity on our dataset. Remaining Cornelia de Lange syndrome, KMT2A, KDM5C and CHD7 signatures reached 70-100% sensitivity at best with unstable performances, suffering from heterogeneous methylation profiles among cases and rare discordant samples. Our results call for cautiousness and demonstrate that episignatures do not perform equally well. Some signatures are ready for confident use in a diagnostic setting. Yet, it is imperative to characterise the actual validity perimeter and interpretation of each episignature with the help of larger validation sample sizes and in a broader set of episignatures.

Autistic spectrum disorder (ASD) - Gene, molecular and pathway signatures linking systemic inflammation, mitochondrial dysfunction, transsynaptic signalling, and neurodevelopment

Background

Despite advances in autism spectrum disorder (ASD) research and the vast genomic, transcriptomic, and proteomic data available, there are still controversies regarding the pathways and molecular signatures underlying the neurodevelopmental disorders leading to ASD.

Purpose

To delineate these underpinning signatures, we examined the two largest gene expression meta-analysis datasets obtained from the brain and peripheral blood mononuclear cells (PBMCs) of 1355 ASD patients and 1110 controls.

Methods

We performed network, enrichment, and annotation analyses using the differentially expressed genes, transcripts, and proteins identified in ASD patients.

Results

Transcription factor network analyses in up- and down-regulated genes in brain tissue and PBMCs in ASD showed eight main transcription factors, namely: BCL3, CEBPB, IRF1, IRF8, KAT2A, NELFE, RELA, and TRIM28. The upregulated gene networks in PBMCs of ASD patients are strongly associated with activated immune-inflammatory pathways, including interferon-α signaling, and cellular responses to DNA repair. Enrichment analyses of the upregulated CNS gene networks indicate involvement of immune-inflammatory pathways, cytokine production, Toll-Like Receptor signalling, with a major involvement of the PI3K-Akt pathway. Analyses of the downregulated CNS genes suggest electron transport chain dysfunctions at multiple levels. Network topological analyses revealed that the consequent aberrations in axonogenesis, neurogenesis, synaptic transmission, and regulation of transsynaptic signalling affect neurodevelopment with subsequent impairments in social behaviours and neurocognition. The results suggest a defense response against viral infection.

Conclusions

Peripheral activation of immune-inflammatory pathways, most likely induced by viral infections, may result in CNS neuroinflammation and mitochondrial dysfunction, leading to abnormalities in transsynaptic transmission, and brain neurodevelopment.

Epigenomic signatures reveal mechanistic clues and predictive markers for autism spectrum disorder

Autism spectrum disorder (ASD) comprises a heterogeneous group of neurodevelopmental outcomes in children with a commonality in deficits in social communication and language combined with repetitive behaviors and interests. The etiology of ASD is heterogeneous, as several hundred genes have been implicated as well as multiple in utero environmental exposures. Over the past two decades, epigenetic investigations, including DNA methylation, have emerged as a novel way to capture the complex interface of multivariate ASD etiologies. More recently, epigenome-wide association studies using human brain and surrogate accessible tissues have revealed some convergent genes that are epigenetically altered in ASD, many of which overlap with known genetic risk factors. Unlike transcriptomes, epigenomic signatures defined by DNA methylation from surrogate tissues such as placenta and cord blood can reflect past differences in fetal brain gene transcription, transcription factor binding, and chromatin. For example, the discovery of NHIP (neuronal hypoxia inducible, placenta associated) through an epigenome-wide association in placenta, identified a common genetic risk for ASD that was modified by prenatal vitamin use. While epigenomic signatures are distinct between different genetic syndromic causes of ASD, bivalent chromatin and some convergent gene pathways are consistently epigenetically altered in both syndromic and idiopathic ASD, as well as some environmental exposures. Together, these epigenomic signatures hold promising clues towards improved early prediction and prevention of ASD as well genes and gene pathways to target for pharmacological interventions. Future advancements in single cell and multi-omic technologies, machine learning, as well as non-invasive screening of epigenomic signatures during pregnancy or newborn periods are expected to continue to impact the translatability of the recent discoveries in epigenomics to precision public health.

Neurodevelopmental disorders, like cancer, are connected to impaired chromatin remodelers, PI3K/mTOR, and PAK1-regulated MAPK

Neurodevelopmental disorders (NDDs) and cancer share proteins, pathways, and mutations. Their clinical symptoms are different. However, individuals with NDDs have higher probabilities of eventually developing cancer. Here, we review the literature and ask how the shared features can lead to different medical conditions and why having an NDD first can increase the chances of malignancy. To explore these vital questions, we focus on dysregulated PI3K/mTOR, a major brain cell growth pathway in differentiation, and MAPK, a critical pathway in proliferation, a hallmark of cancer. Differentiation is governed by chromatin organization, making aberrant chromatin remodelers highly likely agents in NDDs. Dysregulated chromatin organization and accessibility influence the lineage of specific cell brain types at specific embryonic development stages. PAK1, with pivotal roles in brain development and in cancer, also regulates MAPK. We review, clarify, and connect dysregulated pathways with dysregulated proliferation and differentiation in cancer and NDDs and highlight PAK1 role in brain development and MAPK regulation. Exactly how PAK1 activation controls brain development, and why specific chromatin remodeler components, e.g., BAF170 encoded by SMARCC2 in autism, await clarification.

CpG methylation patterns in placenta and neonatal blood are differentially associated with neonatal inflammation

BACKGROUND

Infants born extremely premature are at increased risk for health complications later in life for which neonatal inflammation may be a contributing biological driver. Placental CpG methylation provides mechanistic information regarding the relationship between prenatal epigenetic programming, prematurity, neonatal inflammation, and later-in-life health.

METHODS

We contrasted CpG methylation in the placenta and neonatal blood spots in relation to neonatal inflammation in the Extremely Low Gestational Age Newborn (ELGAN) cohort. Neonatal inflammation status was based on the expression of six inflammation-related proteins, assessed as (1) day-one inflammation (DOI) or (2) intermittent or sustained systemic inflammation (ISSI, inflammation on ≥2 days in the first 2 postnatal weeks). Epigenome-wide CpG methylation was assessed in 354 placental samples and 318 neonatal blood samples.

RESULTS

Placental CpG methylation displayed the strongest association with ISSI (48 CpG sites) but was not associated with DOI. This was in contrast to CpG methylation in blood spots, which was associated with DOI (111 CpG sites) and not with ISSI (one CpG site).

CONCLUSIONS

Placental CpG methylation was strongly associated with ISSI, a measure of inflammation previously linked to later-in-life cognitive impairment, while day-one neonatal blood methylation was associated with DOI.

IMPACT

Neonatal inflammation increases the risk of adverse later-life outcomes, especially in infants born extremely preterm. CpG methylation in the placenta and neonatal blood spots were evaluated in relation to neonatal inflammation assessed via circulating proteins as either (i) day-one inflammation (DOI) or (ii) intermittent or sustained systemic inflammation (ISSI, inflammation on ≥2 days in the first 2 weeks). Tissue specificity was observed in epigenetic-inflammatory relationships: placental CpG methylation was associated with ISSI, neonatal blood CpG methylation was associated with DOI. Supporting the placental origins of disease framework, placental epigenetic patterns are associated with a propensity for ISSI in neonates.

Epigenetics of Autism Spectrum Disorders: A Multi-level Analysis Combining Epi-signature, Age Acceleration, Epigenetic Drift and Rare Epivariations Using Public Datasets

BACKGROUND

Epigenetics of Autism Spectrum Disorders (ASD) is still an understudied field. The majority of the studies on the topic used an approach based on mere classification of cases and controls.

OBJECTIVE

The present study aimed at providing a multi-level approach in which different types of epigenetic analysis (epigenetic drift, age acceleration) are combined.

METHODS

We used publicly available datasets from blood (n = 3) and brain tissues (n = 3), separately. Firstly, we evaluated for each dataset and meta-analyzed the differential methylation profile between cases and controls. Secondly, we analyzed age acceleration, epigenetic drift and rare epigenetic variations.

RESULTS

We observed a significant epi-signature of ASD in blood but not in brain specimens. We did not observe significant age acceleration in ASD, while epigenetic drift was significantly higher compared to controls. We reported the presence of significant rare epigenetic variations in 41 genes, 35 of which were never associated with ASD. Almost all genes were involved in pathways linked to ASD etiopathogenesis (i.e., neuronal development, mitochondrial metabolism, lipid biosynthesis and antigen presentation).

CONCLUSION

Our data support the hypothesis of the use of blood epi-signature as a potential tool for diagnosis and prognosis of ASD. The presence of an enhanced epigenetic drift, especially in brain, which is linked to cellular replication, may suggest that alteration in epigenetics may occur at a very early developmental stage (i.e., fetal) when neuronal replication is still high.

Loss of autism-candidate CHD8 perturbs neural crest development and intestinal homeostatic balance

Individuals with mutations in CHD8 present with gastrointestinal complaints, yet the underlying mechanisms are understudied. Here, using a stable constitutive chd8 mutant zebrafish model, we found that the loss of chd8 leads to a reduced number of vagal neural crest cells (NCCs), enteric neural and glial progenitors, emigrating from the neural tube, and that their early migration capability was altered. At later stages, although the intestinal colonization by NCCs was complete, we found the decreased numbers of both serotonin-producing enterochromaffin cells and NCC-derived serotonergic neurons, suggesting an intestinal hyposerotonemia in the absence of chd8 Furthermore, transcriptomic analyses revealed an altered expression of key receptors and enzymes in serotonin and acetylcholine signaling pathways. The tissue examination of chd8 mutants revealed a thinner intestinal epithelium accompanied by an accumulation of neutrophils and the decreased numbers of goblet cells and eosinophils. Last, single-cell sequencing of whole intestines showed a global disruption of the immune balance with a perturbed expression of inflammatory interleukins and changes in immune cell clusters. Our findings propose a causal developmental link between chd8, NCC development, intestinal homeostasis, and autism-associated gastrointestinal complaints.

Identification of differentially methylated regions in rare diseases from a single-patient perspective

BACKGROUND

DNA methylation (5-mC) is being widely recognized as an alternative in the detection of sequence variants in the diagnosis of some rare neurodevelopmental and imprinting disorders. Identification of alterations in DNA methylation plays an important role in the diagnosis and understanding of the etiology of those disorders. Canonical pipelines for the detection of differentially methylated regions (DMRs) usually rely on inter-group (e.g., case versus control) comparisons. However, these tools might perform suboptimally in the context of rare diseases and multilocus imprinting disturbances due to small cohort sizes and inter-patient heterogeneity. Therefore, there is a need to provide a simple but statistically robust pipeline for scientists and clinicians to perform differential methylation analyses at the single patient level as well as to evaluate how parameter fine-tuning may affect differentially methylated region detection.

RESULT

We implemented an improved statistical method to detect differentially methylated regions in correlated datasets based on the Z-score and empirical Brown aggregation methods from a single-patient perspective. To accurately assess the predictive power of our method, we generated semi-simulated data using a public control population of 521 samples and investigated how the size of the control population, methylation difference, and region size affect DMR detection. In addition, we validated the detection of methylation events in patients suffering from rare multi-locus imprinting disturbance and evaluated how this method could complement existing tools in the context of clinical diagnosis.

CONCLUSION

In this study, we present a robust statistical method to perform differential methylation analysis at the single patient level and describe its optimal parameters to increase DMRs identification performance. Finally, we show its diagnostic utility when applied to rare disorders.

Genomic architecture of autism from comprehensive whole-genome sequence annotation

Fully understanding autism spectrum disorder (ASD) genetics requires whole-genome sequencing (WGS). We present the latest release of the Autism Speaks MSSNG resource, which includes WGS data from 5,100 individuals with ASD and 6,212 non-ASD parents and siblings (total n = 11,312). Examining a wide variety of genetic variants in MSSNG and the Simons Simplex Collection (SSC; n = 9,205), we identified ASD-associated rare variants in 718/5,100 individuals with ASD from MSSNG (14.1%) and 350/2,419 from SSC (14.5%). Considering genomic architecture, 52% were nuclear sequence-level variants, 46% were nuclear structural variants (including copy-number variants, inversions, large insertions, uniparental isodisomies, and tandem repeat expansions), and 2% were mitochondrial variants. Our study provides a guidebook for exploring genotype-phenotype correlations in families who carry ASD-associated rare variants and serves as an entry point to the expanded studies required to dissect the etiology in the ∼85% of the ASD population that remain idiopathic.

Functional correlation of genome-wide DNA methylation profiles in genetic neurodevelopmental disorders

An expanding range of genetic syndromes are characterized by genome-wide disruptions in DNA methylation profiles referred to as episignatures. Episignatures are distinct, highly sensitive, and specific biomarkers that have recently been applied in clinical diagnosis of genetic syndromes. Episignatures are contained within the broader disorder-specific genome-wide DNA methylation changes, which can share significant overlap among different conditions. In this study, we performed functional genomic assessment and comparison of disorder-specific and overlapping genome-wide DNA methylation changes related to 65 genetic syndromes with previously described episignatures. We demonstrate evidence of disorder-specific and recurring genome-wide differentially methylated probes (DMPs) and regions (DMRs). The overall distribution of DMPs and DMRs across the majority of the neurodevelopmental genetic syndromes analyzed showed substantial enrichment in gene promoters and CpG islands, and under-representation of the more variable intergenic regions. Analysis showed significant enrichment of the DMPs and DMRs in gene pathways and processes related to neurodevelopment, including neurogenesis, synaptic signaling and synaptic transmission. This study expands beyond the diagnostic utility of DNA methylation episignatures by demonstrating correlation between the function of the mutated genes and the consequent genomic DNA methylation profiles as a key functional element in the molecular etiology of genetic neurodevelopmental disorders.

LINE-1 and Alu methylation signatures in autism spectrum disorder and their associations with the expression of autism-related genes

Long interspersed nucleotide element-1 (LINE-1) and Alu elements are retrotransposons whose abilities cause abnormal gene expression and genomic instability. Several studies have focused on DNA methylation profiling of gene regions, but the locus-specific methylation of LINE-1 and Alu elements has not been identified in autism spectrum disorder (ASD). Here we interrogated locus- and family-specific methylation profiles of LINE-1 and Alu elements in ASD whole blood using publicly-available Illumina Infinium 450 K methylation datasets from heterogeneous ASD and ASD variants (Chromodomain Helicase DNA-binding 8 (CHD8) and 16p11.2del). Total DNA methylation of repetitive elements were notably hypomethylated exclusively in ASD with CHD8 variants. Methylation alteration in a family-specific manner including L1P, L1H, HAL, AluJ, and AluS families were observed in the heterogeneous ASD and ASD with CHD8 variants. Moreover, LINE-1 and Alu methylation within target genes is inversely related to the expression level in each ASD variant. The DNA methylation signatures of the LINE-1 and Alu elements in ASD whole blood, as well as their associations with the expression of ASD-related genes, have been identified. If confirmed in future larger studies, these findings may contribute to the identification of epigenomic biomarkers of ASD.

DNA Methylation Episignatures in Neurodevelopmental Disorders Associated with Large Structural Copy Number Variants: Clinical Implications

Large structural chromosomal deletions and duplications, referred to as copy number variants (CNVs), play a role in the pathogenesis of neurodevelopmental disorders (NDDs) through effects on gene dosage. This review focuses on our current understanding of genomic disorders that arise from large structural chromosome rearrangements in patients with NDDs, as well as difficulties in overlap of clinical presentation and molecular diagnosis. We discuss the implications of epigenetics, specifically DNA methylation (DNAm), in NDDs and genomic disorders, and consider the implications and clinical impact of copy number and genomic DNAm testing in patients with suspected genetic NDDs. We summarize evidence of global methylation episignatures in CNV-associated disorders that can be used in the diagnostic pathway and may provide insights into the molecular pathogenesis of genomic disorders. Finally, we discuss the potential for combining CNV and DNAm assessment into a single diagnostic assay.

DNA methylation signature associated with Bohring-Opitz syndrome: a new tool for functional classification of variants in ASXL genes

The additional sex combs-like (ASXL) gene family-encoded by ASXL1, ASXL2, and ASXL3-is crucial for mammalian development. Pathogenic variants in the ASXL gene family are associated with three phenotypically distinct neurodevelopmental syndromes. Our previous work has shown that syndromic conditions caused by pathogenic variants in epigenetic regulatory genes show consistent patterns of genome-wide DNA methylation (DNAm) alterations, i.e., DNAm signatures in peripheral blood. Given the role of ASXL1 in chromatin modification, we hypothesized that pathogenic ASXL1 variants underlying Bohring-Opitz syndrome (BOS) have a unique DNAm signature. We profiled whole-blood DNAm for 17 ASXL1 variants, and 35 sex- and age-matched typically developing individuals, using Illumina's Infinium EPIC array. We identified 763 differentially methylated CpG sites in individuals with BOS. Differentially methylated sites overlapped 323 unique genes, including HOXA5 and HOXB4, supporting the functional relevance of DNAm signatures. We used a machine-learning classification model based on the BOS DNAm signature to classify variants of uncertain significance in ASXL1, as well as pathogenic ASXL2 and ASXL3 variants. The DNAm profile of one individual with the ASXL2 variant was BOS-like, whereas the DNAm profiles of three individuals with ASXL3 variants were control-like. We also used Horvath's epigenetic clock, which showed acceleration in DNAm age in individuals with pathogenic ASXL1 variants, and the individual with the pathogenic ASXL2 variant, but not in individuals with ASXL3 variants. These studies enhance our understanding of the epigenetic dysregulation underpinning ASXL gene family-associated syndromes.

Identification of DCAF1 by Clinical Exome Sequencing and Methylation Analysis as a Candidate Gene for Autism and Intellectual Disability: A Case Report

Autism spectrum disorder (ASD) comprises a heterogeneous group of neurodevelopmental disorders and occurs in all racial, ethnic, and socioeconomic groups. Cutting-edge technologies are contributing to understanding genetic underpinnings in ASD. The reported patient is a 32-year-old male and as an infant was noted to have microcephaly, hypospadias, pulmonary vascular anomaly, and small stature. He was diagnosed with Cornelia De Lange Syndrome (CDLS) at that time based on the clinical features. As a child, he had autistic features and intellectual disabilities and as diagnoses with autism and intellectual disability. He was referred as an adult to our neurodiversity clinic and a full exome trio sequencing with reflex to mitochondrial genes identified a de novo variant of uncertain significance in a candidate gene, DCAF1. The specific variant was c.137 C > T (p.Thr46Ile) in exon 4 in the DCAF1 gene. In silico analysis supports a deleterious effect on protein structure/function. DCAF1 participates with DDB1 and CUL4 as a part of the E3 ubiquitin ligase complex. The E3 ligase complex has been associated with a syndromic form of X-linked intellectual disability. The DDB1/CUL4 E3 ubiquitination complex plays a role in methylation-dependent ubiquitination. Next, a methylation study identified a signature similar to the methylation pattern found in X- linked intellectual disability type 93. This is associated with variants of the BRWD3 gene, which is linked with the functioning of the DDB1/CUL4 E3 ubiquitination complex. Taken together, this suggests that the de novo DCAF1 variant may be a newly identified molecular cause of autism and intellectual disability.

Accelerated epigenetic age and shortened telomere length based on DNA methylation in Nicolaides-Baraitser syndrome

BACKGROUND

Nicolaides-Baraitser syndrome (NCBRS) is a rare disorder characterized by neurodevelopmental delays, seizures, and diverse physical characteristics. The DNA methylation (DNAm) profile in NCBRS is significantly different. DNAm is linked to the biological aging of cells and the health risks associated with biological aging. In this study, we examined changes in biological ages in NCBRS to provide insights into the prognosis and health risks of NCBRS.

METHODS

We used a publicly available dataset to examine biological aging in NCBRS using DNAm-based epigenetic ages, such as PhenoAge and GrimAge, as well as DNAm-based estimator of telomere length (DNAmTL). We investigated 12 cases, clinically diagnosed as NCBRS, and 27 controls.

RESULTS

Compared to controls, NCBRS cases exhibited significantly accelerated PhenoAge and GrimAge as well as significantly shortened DNAmTL.

CONCLUSION

These results suggest an acceleration of biological aging in NCBRS and provide insights into the prognosis and health risks of NCBRS.

Novel diagnostic DNA methylation episignatures expand and refine the epigenetic landscapes of Mendelian disorders

Overlapping clinical phenotypes and an expanding breadth and complexity of genomic associations are a growing challenge in the diagnosis and clinical management of Mendelian disorders. The functional consequences and clinical impacts of genomic variation may involve unique, disorder-specific, genomic DNA methylation episignatures. In this study, we describe 19 novel episignature disorders and compare the findings alongside 38 previously established episignatures for a total of 57 episignatures associated with 65 genetic syndromes. We demonstrate increasing resolution and specificity ranging from protein complex, gene, sub-gene, protein domain, and even single nucleotide-level Mendelian episignatures. We show the power of multiclass modeling to develop highly accurate and disease-specific diagnostic classifiers. This study significantly expands the number and spectrum of disorders with detectable DNA methylation episignatures, improves the clinical diagnostic capabilities through the resolution of unsolved cases and the reclassification of variants of unknown clinical significance, and provides further insight into the molecular etiology of Mendelian conditions.

The diagnostic potential of the epigenome in autism spectrum disorders

Tweetable abstract The diagnostic application of genome-wide methylation signatures is increasing in various syndromic forms of autism, but further studies are warranted to clarify whether epigenetic biomarkers can be of diagnostic utility in idiopathic ASD.

Genetic contributions to autism spectrum disorder

Autism spectrum disorder (autism) is a heterogeneous group of neurodevelopmental conditions characterized by early childhood-onset impairments in communication and social interaction alongside restricted and repetitive behaviors and interests. This review summarizes recent developments in human genetics research in autism, complemented by epigenetic and transcriptomic findings. The clinical heterogeneity of autism is mirrored by a complex genetic architecture involving several types of common and rare variants, ranging from point mutations to large copy number variants, and either inherited or spontaneous (de novo). More than 100 risk genes have been implicated by rare, often de novo, potentially damaging mutations in highly constrained genes. These account for substantial individual risk but a small proportion of the population risk. In contrast, most of the genetic risk is attributable to common inherited variants acting en masse, each individually with small effects. Studies have identified a handful of robustly associated common variants. Different risk genes converge on the same mechanisms, such as gene regulation and synaptic connectivity. These mechanisms are also implicated by genes that are epigenetically and transcriptionally dysregulated in autism. Major challenges to understanding the biological mechanisms include substantial phenotypic heterogeneity, large locus heterogeneity, variable penetrance, and widespread pleiotropy. Considerable increases in sample sizes are needed to better understand the hundreds or thousands of common and rare genetic variants involved. Future research should integrate common and rare variant research, multi-omics data including genomics, epigenomics, and transcriptomics, and refined phenotype assessment with multidimensional and longitudinal measures.

Functional annotation of genomic variation: DNA methylation episignatures in neurodevelopmental Mendelian disorders

The breadth and complexity of genetic testing in patients with suspected Mendelian neurodevelopmental disorders has rapidly expanded in the past two decades. However, in spite of advances in genomic technologies, genetic diagnosis remains elusive in more than half of these patients. Epigenomics, and in particular genomic DNA methylation profiles, are now known to be associated with the underpinning genetic defects in a growing number of Mendelian disorders. These often highly specific and sensitive molecular biomarkers have been used to screen these patient populations, resolve ambiguous clinical cases and interpret genetic variants of unknown clinical significance. Increasing the diagnostic yield beyond genomic sequencing technologies has rapidly propelled epigenomics to clinical utilization, with recent introduction of DNA methylation 'EpiSign' analysis in clinical diagnostic laboratories. This review provides an overview of the principles, applications and limitations of DNA methylation episignature analysis in patients with neurodevelopmental Mendelian disorders, and discusses clinical implications of this emerging diagnostic technology.

Anatomy of DNA methylation signatures: Emerging insights and applications

DNA methylation (DNAm) signatures are unique patterns of DNAm alterations defined for rare disorders caused by pathogenic variants in epigenetic regulatory genes. The potential of DNAm signatures (also known as "episignatures") is just beginning to emerge as there are >300 known epigenetic regulatory genes, ∼100 of which are linked to neurodevelopmental disorders. To date, approximately 50 signatures have been identified, which have proven unexpectedly successful as predictive tools for classifying variants of uncertain significance as pathogenic or benign. The molecular basis of these signatures is poorly understood. Furthermore, their relationships to primary disease pathophysiology have yet to be adequately investigated, despite clear demonstrations of potential connections. There are currently no published guidelines for signature development. As signatures are highly dependent on the samples and methods used to derive them, we propose a framework for consideration in signature development including sample size, statistical parameters, cell type of origin, and the value of detailed clinical and molecular information. We illustrate the relationship between signature output/efficacy and sample size by generating and testing 837 DNAm signatures of Kleefstra syndrome using downsampling analysis. Our findings highlight that no single DNAm signature encompasses all DNAm alterations present in a rare disorder, and that a substandard study design can generate a DNAm signature that misclassifies variants. Finally, we discuss the importance of further investigating DNAm signatures to inform disease pathophysiology and broaden their scope as a functional assay.

Cataloging recent advances in epigenetic alterations in major mental disorders and autism

During the last two decades, diverse epigenetic modifications including DNA methylation, histone modifications, RNA editing and miRNA dysregulation have been associated with psychiatric disorders. A few years ago, in a review we outlined the most common epigenetic alterations in major psychiatric disorders (e.g., aberrant DNA methylation of DTNBP1, HTR2A, RELN, MB-COMT and PPP3CC, and increased expression of miR-34a and miR-181b). Recent follow-up studies have uncovered other DNA methylation aberrations affecting several genes in mental disorders, in addition to dysregulation of many miRNAs. Here, we provide an update on new epigenetic findings and highlight potential origin of the diversity and inconsistencies, focusing on drug effects, tissue/cell specificity of epigenetic landscape and discuss shortcomings of the current diagnostic criteria in mental disorders.

The Mechanisms of CHD8 in Neurodevelopment and Autism Spectrum Disorders

Chromodomain-helicase-DNA-binding protein 8 (CHD8) has been identified as one of the genes with the strongest association with autism. The CHD8 protein is a transcriptional regulator that is expressed in nearly all cell types and has been implicated in multiple cellular processes, including cell cycle, cell adhesion, neuronal development, myelination, and synaptogenesis. Considering the central role of CHD8 in the genetics of autism, a deeper understanding of the physiological functions of CHD8 is important to understand the development of the autism phenotype and potential therapeutic targets. Different CHD8 mutant mouse models were developed to determine autism-like phenotypes and to fully understand their mechanisms. Here, we review the current knowledge on CHD8, with an emphasis on mechanistic lessons gained from animal models that have been studied.

Truncating SRCAP variants outside the Floating-Harbor syndrome locus cause a distinct neurodevelopmental disorder with a specific DNA methylation signature

Truncating variants in exons 33 and 34 of the SNF2-related CREBBP activator protein (SRCAP) gene cause the neurodevelopmental disorder (NDD) Floating-Harbor syndrome (FLHS), characterized by short stature, speech delay, and facial dysmorphism. Here, we present a cohort of 33 individuals with clinical features distinct from FLHS and truncating (mostly de novo) SRCAP variants either proximal (n = 28) or distal (n = 5) to the FLHS locus. Detailed clinical characterization of the proximal SRCAP individuals identified shared characteristics: developmental delay with or without intellectual disability, behavioral and psychiatric problems, non-specific facial features, musculoskeletal issues, and hypotonia. Because FLHS is known to be associated with a unique set of DNA methylation (DNAm) changes in blood, a DNAm signature, we investigated whether there was a distinct signature associated with our affected individuals. A machine-learning model, based on the FLHS DNAm signature, negatively classified all our tested subjects. Comparing proximal variants with typically developing controls, we identified a DNAm signature distinct from the FLHS signature. Based on the DNAm and clinical data, we refer to the condition as “non-FLHS SRCAP-related NDD.” All five distal variants classified negatively using the FLHS DNAm model while two classified positively using the proximal model. This suggests divergent pathogenicity of these variants, though clinically the distal group presented with NDD, similar to the proximal SRCAP group. In summary, for SRCAP, there is a clear relationship between variant location, DNAm profile, and clinical phenotype. These results highlight the power of combined epigenetic, molecular, and clinical studies to identify and characterize genotype-epigenotype-phenotype correlations.

An Epigenetically Distinct Subset of Children With Autism Spectrum Disorder Resulting From Differences in Blood Cell Composition

Background: Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that often involves impaired cognition, communication difficulties and restrictive, repetitive behaviors. ASD is extremely heterogeneous both clinically and etiologically, which represents one of the greatest challenges in studying the molecular underpinnings of ASD. While hundreds of ASD-associated genes have been identified that confer varying degrees of risk, no single gene variant accounts for >1% of ASD cases. Notably, a large number of ASD-risk genes function as epigenetic regulators, indicating potential epigenetic dysregulation in ASD. As such, we compared genome-wide DNA methylation (DNAm) in the blood of children with ASD (n = 265) to samples from age- and sex-matched, neurotypical controls (n = 122) using the Illumina Infinium HumanMethylation450 arrays. Results: While DNAm patterns did not distinctly separate ASD cases from controls, our analysis identified an epigenetically unique subset of ASD cases (n = 32); these individuals exhibited significant differential methylation from both controls than the remaining ASD cases. The CpG sites at which this subset was differentially methylated mapped to known ASD risk genes that encode proteins of the nervous and immune systems. Moreover, the observed DNAm differences were attributable to altered blood cell composition, i.e., lower granulocyte proportion and granulocyte-to-lymphocyte ratio in the ASD subset, as compared to the remaining ASD cases and controls. This ASD subset did not differ from the rest of the ASD cases in the frequency or type of high-risk genomic variants. Conclusion: Within our ASD cohort, we identified a subset of individuals that exhibit differential methylation from both controls and the remaining ASD group tightly associated with shifts in immune cell type proportions. This is an important feature that should be assessed in all epigenetic studies of blood cells in ASD. This finding also builds on past reports of changes in the immune systems of children with ASD, supporting the potential role of altered immunological mechanisms in the complex pathophysiology of ASD. The discovery of significant molecular and immunological features in subgroups of individuals with ASD may allow clinicians to better stratify patients, facilitating personalized interventions and improved outcomes.

Diagnostic Classification and Prognostic Prediction Using Common Genetic Variants in Autism Spectrum Disorder: Genotype-Based Deep Learning

Background

In the United States, about 3 million people have autism spectrum disorder (ASD), and around 1 out of 59 children are diagnosed with ASD. People with ASD have characteristic social communication deficits and repetitive behaviors. The causes of this disorder remain unknown; however, in up to 25% of cases, a genetic cause can be identified. Detecting ASD as early as possible is desirable because early detection of ASD enables timely interventions in children with ASD. Identification of ASD based on objective pathogenic mutation screening is the major first step toward early intervention and effective treatment of affected children.

Objective

Recent investigation interrogated genomics data for detecting and treating autism disorders, in addition to the conventional clinical interview as a diagnostic test. Since deep neural networks perform better than shallow machine learning models on complex and high-dimensional data, in this study, we sought to apply deep learning to genetic data obtained across thousands of simplex families at risk for ASD to identify contributory mutations and to create an advanced diagnostic classifier for autism screening.

Methods

After preprocessing the genomics data from the Simons Simplex Collection, we extracted top ranking common variants that may be protective or pathogenic for autism based on a chi-square test. A convolutional neural network–based diagnostic classifier was then designed using the identified significant common variants to predict autism. The performance was then compared with shallow machine learning–based classifiers and randomly selected common variants.

Results

The selected contributory common variants were significantly enriched in chromosome X while chromosome Y was also discriminatory in determining the identification of autistic individuals from nonautistic individuals. The ARSD, MAGEB16, and MXRA5 genes had the largest effect in the contributory variants. Thus, screening algorithms were adapted to include these common variants. The deep learning model yielded an area under the receiver operating characteristic curve of 0.955 and an accuracy of 88% for identifying autistic individuals from nonautistic individuals. Our classifier demonstrated a considerable improvement of ~13% in terms of classification accuracy compared to standard autism screening tools.

Conclusions

Common variants are informative for autism identification. Our findings also suggest that the deep learning process is a reliable method for distinguishing the diseased group from the control group based on the common variants of autism.

Exposure to Gestational Diabetes Mellitus (GDM) alters DNA methylation in placenta and fetal cord blood

BACKGROUND

Fetal exposure to maternal GDM increases offspring risk for adult-onset metabolic syndromes. Epigenetic modifications such as DNA methylation are modulators for fetal metabolic programming and susceptibility to adult-onset disease. This study investigates genome-wide DNA methylation in GDM exposed cord blood and placenta.

METHODS

Oral glucose tolerance testing between 24 and 28 weeks of pregnancy was used to determine severity of glucose intolerance. We measured DNA methylation (DNAm) using the Illumina Infinium 450 K array in 42 fetal cord blood and 36 placenta samples.

RESULTS

We identified 662 and 99 CpG sites in GDM placenta and cord blood, respectively at p-value <0.01 and a methylation difference >5% after adjustment for confounders. Annotated sites for AHRR and PTPRN2 were common to cord blood and placenta. Adding published GDM cord blood DNAm data we segregated patients based on treatment (Diet Only vs. +Insulin) and identified altered CpG sites to be unique to each GDM treatment group.

CONCLUSION

Consistency in findings with other studies provides evidence for the role of DNAm in placental and fetal responses to hyperglycemia. However, segregating DNAm analysis of GDM samples based on treatment may help delineate whether observed DNAm alterations are reflective of adaptive responses or treatment effects in utero.

Detection of a DNA Methylation Signature for the Intellectual Developmental Disorder, X-Linked, Syndromic, Armfield Type

A growing number of genetic neurodevelopmental disorders are known to be associated with unique genomic DNA methylation patterns, called episignatures, which are detectable in peripheral blood. The intellectual developmental disorder, X-linked, syndromic, Armfield type (MRXSA) is caused by missense variants in FAM50A. Functional studies revealed the pathogenesis to be a spliceosomopathy that is characterized by atypical mRNA processing during development. In this study, we assessed the peripheral blood specimens in a cohort of individuals with MRXSA and detected a unique and highly specific DNA methylation episignature associated with this disorder. We used this episignature to construct a support vector machine model capable of sensitive and specific identification of individuals with pathogenic variants in FAM50A. This study contributes to the expanding number of genetic neurodevelopmental disorders with defined DNA methylation episignatures, provides an additional understanding of the associated molecular mechanisms, and further enhances our ability to diagnose patients with rare disorders.

Diagnostic Utility of Genome-Wide DNA Methylation Analysis in Mendelian Neurodevelopmental Disorders

Mendelian neurodevelopmental disorders customarily present with complex and overlapping symptoms, complicating the clinical diagnosis. Individuals with a growing number of the so-called rare disorders exhibit unique, disorder-specific DNA methylation patterns, consequent to the underlying gene defects. Besides providing insights to the pathophysiology and molecular biology of these disorders, we can use these epigenetic patterns as functional biomarkers for the screening and diagnosis of these conditions. This review summarizes our current understanding of DNA methylation episignatures in rare disorders and describes the underlying technology and analytical approaches. We discuss the computational parameters, including statistical and machine learning methods, used for the screening and classification of genetic variants of uncertain clinical significance. Describing the rationale and principles applied to the specific computational models that are used to develop and adapt the DNA methylation episignatures for the diagnosis of rare disorders, we highlight the opportunities and challenges in this emerging branch of diagnostic medicine.

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.

Innovations in 3-Dimensional Tissue Models of Human Brain Physiology and Diseases

3-dimensional (3D) laboratory tissue cultures have emerged as an alternative to traditional 2-dimensional (2D) culture systems that do not recapitulate native cell behavior. The discrepancy between in vivo and in vitro tissue-cell-molecular responses impedes understanding of human physiology in general and creates roadblocks for the discovery of therapeutic solutions. Two parallel approaches have emerged for the design of 3D culture systems. The first is biomedical engineering methodology, including bioengineered materials, bioprinting, microfluidics and bioreactors, used alone or in combination, to mimic the microenvironments of native tissues. The second approach is organoid technology, in which stem cells are exposed to chemical and/or biological cues to activate differentiation programs that are reminiscent of human (prenatal) development. This review article describes recent technological advances in engineering 3D cultures that more closely resemble the human brain. The contributions of in vitro 3D tissue culture systems to new insights in neurophysiology, neurological diseases and regenerative medicine are highlighted. Perspectives on designing improved tissue models of the human brain are offered, focusing on an integrative approach merging biomedical engineering tools with organoid biology.

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.

Integration of CRISPR-engineering and hiPSC-based models of psychiatric genomics

Neuropsychiatric disorders are highly heritable polygenic disorders arising from the complex interplay of highly penetrant rare variants and common variants of small effect. There is a large index of comorbidity and shared genetic risk between disorders, reflecting the pleiotropy of individual variants as well as predicted downstream pathway-level convergence. Importantly, the mechanism(s) through which psychiatric disease-associated variants interact to contribute to disease risk remains unknown. Human induced pluripotent stem cell (hiPSC)-based models are increasingly useful for the systematic study of the complex genetics associated with brain diseases, particularly when combined with CRISPR-mediated genomic engineering, which together facilitate isogenic comparisons of defined neuronal cell types. In this review, we discuss the latest CRISPR technologies and consider how they can be successfully applied to the functional characterization of the growing list genetic variants linked to psychiatric disease.

Obsessive-compulsive disorder and attention-deficit/hyperactivity disorder: distinct associations with DNA methylation and genetic variation

BACKGROUND

A growing body of research has demonstrated associations between specific neurodevelopmental disorders and variation in DNA methylation (DNAm), implicating this molecular mark as a possible contributor to the molecular etiology of these disorders and/or as a novel disease biomarker. Furthermore, genetic risk variants of neurodevelopmental disorders have been found to be enriched at loci associated with DNAm patterns, referred to as methylation quantitative trait loci (mQTLs).

METHODS

We conducted two epigenome-wide association studies in individuals with attention-deficit/hyperactivity disorder (ADHD) or obsessive-compulsive disorder (OCD) (aged 4-18 years) using DNA extracted from saliva. DNAm data generated on the Illumina Human Methylation 450 K array were used to examine the interaction between genetic variation and DNAm patterns associated with these disorders.

RESULTS

Using linear regression followed by principal component analysis, individuals with the most endorsed symptoms of ADHD or OCD were found to have significantly more distinct DNAm patterns from controls, as compared to all cases. This suggested that the phenotypic heterogeneity of these disorders is reflected in altered DNAm at specific sites. Further investigations of the DNAm sites associated with each disorder revealed that despite little overlap of these DNAm sites across the two disorders, both disorders were significantly enriched for mQTLs within our sample.

CONCLUSIONS

Our DNAm data provide insights into the regulatory changes associated with genetic variation, highlighting their potential utility both in directing GWAS and in elucidating the pathophysiology of neurodevelopmental disorders.

EpigenCentral: Portal for DNA methylation data analysis and classification in rare diseases

Epigenetic processes play a key role in regulating gene expression. Genetic variants that disrupt chromatin-modifying proteins are associated with a broad range of diseases, some of which have specific epigenetic patterns, such as aberrant DNA methylation (DNAm), which may be used as disease biomarkers. While much of the epigenetic research has focused on cancer, there is a paucity of resources devoted to neurodevelopmental disorders (NDDs), which include autism spectrum disorder and many rare, clinically overlapping syndromes. To address this challenge, we created EpigenCentral, a free web resource for biomedical researchers, molecular diagnostic laboratories, and clinical practitioners to perform the interactive classification and analysis of DNAm data related to NDDs. It allows users to search for known disease-associated patterns in their DNAm data, classify genetic variants as pathogenic or benign to assist in molecular diagnostics, or analyze patterns of differential methylation in their data through a simple web form. EpigenCentral is freely available at http://epigen.ccm.sickkids.ca/.

Histone demethylase KDM5C is a SAHA-sensitive central hub at the crossroads of transcriptional axes involved in multiple neurodevelopmental disorders

A disproportional large number of neurodevelopmental disorders (NDDs) is caused by variants in genes encoding transcription factors and chromatin modifiers. However, the functional interactions between the corresponding proteins are only partly known. Here, we show that KDM5C, encoding a H3K4 demethylase, is at the intersection of transcriptional axes under the control of three regulatory proteins ARX, ZNF711 and PHF8. Interestingly, mutations in all four genes (KDM5C, ARX, ZNF711 and PHF8) are associated with X-linked NDDs comprising intellectual disability as a core feature. in vitro analysis of the KDM5C promoter revealed that ARX and ZNF711 function as antagonist transcription factors that activate KDM5C expression and compete for the recruitment of PHF8. Functional analysis of mutations in these genes showed a correlation between phenotype severity and the reduction in KDM5C transcriptional activity. The KDM5C decrease was associated with a lack of repression of downstream target genes Scn2a, Syn1 and Bdnf in the embryonic brain of Arx-null mice. Aiming to correct the faulty expression of KDM5C, we studied the effect of the FDA-approved histone deacetylase inhibitor suberanilohydroxamic acid (SAHA). In Arx-KO murine ES-derived neurons, SAHA was able to rescue KDM5C depletion, recover H3K4me3 signalling and improve neuronal differentiation. Indeed, in ARX/alr-1-deficient Caenorhabditis elegans animals, SAHA was shown to counteract the defective KDM5C/rbr-2-H3K4me3 signalling, recover abnormal behavioural phenotype and ameliorate neuronal maturation. Overall, our studies indicate that KDM5C is a conserved and druggable effector molecule across a number of NDDs for whom the use of SAHA may be considered a potential therapeutic strategy.

Genomics, transcriptomics, proteomics and big data analysis in the discovery of new diagnostic markers and targets for therapy development

Highly complex endophenotypes and underlying molecular mechanisms have prevented effective diagnosis and treatment of autism spectrum disorder. Despite extensive studies to identify relevant biosignatures, no biomarker and therapeutic targets are available in the current clinical practice. While our current knowledge is still largely incomplete, -omics technology and machine learning-based big data analysis have provided novel insights on the etiology of autism spectrum disorders, elucidating systemic impairments that can be translated into biomarker and therapy target candidates. However, more integrated and sophisticated approaches are vital to realize molecular stratification and individualized treatment strategy. Ultimately, systemic approaches based on -omics and big data analysis will significantly contribute to more effective biomarker and therapy development for autism spectrum disorder.

DNA Methylation Signature for EZH2 Functionally Classifies Sequence Variants in Three PRC2 Complex Genes

Weaver syndrome (WS), an overgrowth/intellectual disability syndrome (OGID), is caused by pathogenic variants in the histone methyltransferase EZH2, which encodes a core component of the Polycomb repressive complex-2 (PRC2). Using genome-wide DNA methylation (DNAm) data for 187 individuals with OGID and 969 control subjects, we show that pathogenic variants in EZH2 generate a highly specific and sensitive DNAm signature reflecting the phenotype of WS. This signature can be used to distinguish loss-of-function from gain-of-function missense variants and to detect somatic mosaicism. We also show that the signature can accurately classify sequence variants in EED and SUZ12, which encode two other core components of PRC2, and predict the presence of pathogenic variants in undiagnosed individuals with OGID. The discovery of a functionally relevant signature with utility for diagnostic classification of sequence variants in EZH2, EED, and SUZ12 supports the emerging paradigm shift for implementation of DNAm signatures into diagnostics and translational research.

Novel and de novo point and large microdeletion mutation in PRRT2-related epilepsy

BACKGROUND

Point and copy number variant mutations in the PRRT2 gene have been identified in a variety of paroxysmal disorders and different types of epilepsy. In this study, we analyzed the phenotypes and PRRT2-related mutations in Chinese epilepsy children.

METHODS

A total of 492 children with epilepsy were analyzed by whole exome sequencing (WES) and low-coverage massively parallel CNV sequencing (CNV-seq) to find the single nucleotide variants and copy number variations (CNVs). And quantitative polymerase chain reaction was utilized to verify the CNVs. Their clinical information was followed up.

RESULTS

We found PRRT2-related mutations in 19 patients (10 males and nine females, six sporadic cases and 13 family cases). Twelve point mutations, four whole gene deletion, and three 16p11.2 deletions were detected. The clinical features of 39 patients in 19 families included one early childhood myoclonic epilepsy (ECME), one febrile seizure (FS), two infantile convulsions with paroxysmal choreoathetosis (ICCA), six paroxysmal kinesigenic dyskinesias (PKD), 12 benign infantile epilepsy (BIE), and 17 benign familial infantile epilepsy (BFIE). All patients had normal brain MRI. Interictal EEG showed only one patient had generalized polyspike wave and five patients had focal transient discharges. Focal seizures originating in the frontal region were recorded in one patient, two from the temporal region, and two from the occipital region. Most patients were treated effectively with VPA or OXC, and the child with myoclonic seizures was not sensitive to antiepileptic drugs.

CONCLUSION

PRRT2 mutations can be inherited or de novo, mainly inherited. The clinical spectrum of PRRT2 mutation includes BIE, BFIE, ICCA, PKD, FS, and ECME. The PRRT2-related mutations contained point mutation, whole gene deletion and 16p11.2 deletions, and large microdeletion mutations mostly de novo. It is the first report of PRRT2 mutation found in ECME. Our report expands the mutation and clinical spectrum of PRRT2-related epilepsy.

BioDog, biomarker detection for improving identification power of breast cancer histologic grade in methylomics

Aim: Breast cancer histologic grade (HG) is a well-established prognostic factor. This study aimed to select methylomic biomarkers to predict breast cancer HGs. Materials & methods: The proposed algorithm BioDog firstly used correlation bias reduction strategy to eliminate redundant features. Then incremental feature selection was applied to find the features with a high HG prediction accuracy. The sequential backward feature elimination strategy was employed to further refine the biomarkers. A comparison with existing algorithms were conducted. The HG-specific somatic mutations were investigated. Results & conclusions: BioDog achieved accuracy 0.9973 using 92 methylomic biomarkers for predicting breast cancer HGs. Many of these biomarkers were within the genes and lncRNAs associated with the HG development in breast cancer or other cancer types.

Epigenetic signatures in overgrowth syndromes: Translational opportunities

In recent years, numerous overgrowth syndromes have been found to be caused by pathogenic DNA sequence variants in "epigenes," genes that encode proteins that function in epigenetic regulation. Epigenetic marks, including DNA methylation (DNAm), histone modifications and chromatin conformation, have emerged as a vital genome-wide regulatory mechanism that modulate the transcriptome temporally and spatially to drive normal developmental and cellular processes. Evidence suggests that epigenetic marks are layered and engage in crosstalk, in that disruptions of any one component of the epigenetic machinery impact the others. This interdependence of epigenetic marks underpins the recent identification of gene-specific DNAm signatures for a variety of disorders caused by pathogenic variants in epigenes. Here, we discuss the power of DNAm signatures with respect to furthering our understanding of disease pathophysiology, enhancing the efficacy of molecular diagnostics and identifying new targets for therapeutics of overgrowth syndromes. These findings highlight the promise of the field of epigenomics to provide unprecedented insights into disease mechanisms generating a host of opportunities to advance precision medicine.

New insights into DNA methylation signatures: SMARCA2 variants in Nicolaides-Baraitser syndrome

BACKGROUND

Nicolaides-Baraitser syndrome (NCBRS) is a neurodevelopmental disorder caused by pathogenic sequence variants in SMARCA2 which encodes the catalytic component of the chromatin remodeling BAF complex. Pathogenic variants in genes that encode epigenetic regulators have been associated with genome-wide changes in DNA methylation (DNAm) in affected individuals termed DNAm signatures.

METHODS

Genome-wide DNAm was assessed in whole-blood samples from the individuals with pathogenic SMARCA2 variants and NCBRS diagnosis (n = 8) compared to neurotypical controls (n = 23) using the Illumina MethylationEPIC array. Differential methylated CpGs between groups (DNAm signature) were identified and used to generate a model enabling classification variants of uncertain significance (VUS; n = 9) in SMARCA2 as "pathogenic" or "benign". A validation cohort of NCBRS cases (n = 8) and controls (n = 96) demonstrated 100% model sensitivity and specificity.

RESULTS

We identified a DNAm signature of 429 differentially methylated CpG sites in individuals with NCBRS. The genes to which these CpG sites map are involved in cell differentiation, calcium signaling, and neuronal function consistent with NCBRS pathophysiology. DNAm model classifications of VUS were concordant with the clinical phenotype; those within the SMARCA2 ATPase/helicase domain classified as "pathogenic". A patient with a mild neurodevelopmental NCBRS phenotype and a VUS distal to the ATPase/helicase domain did not score as pathogenic, clustering away from cases and controls. She demonstrated an intermediate DNAm profile consisting of one subset of signature CpGs with methylation levels characteristic of controls and another characteristic of NCBRS cases; each mapped to genes with ontologies consistent with the patient's unique clinical presentation.

CONCLUSIONS

Here we find that a DNAm signature of SMARCA2 pathogenic variants in NCBRS maps to CpGs relevant to disorder pathophysiology, classifies VUS, and is sensitive to the position of the variant in SMARCA2. The patient with an intermediate model score demonstrating a unique genotype-epigenotype-phenotype correlation underscores the potential utility of this signature as a functionally relevant VUS classification system scalable beyond binary "benign" versus "pathogenic" scoring. This is a novel feature of DNAm signatures that could enable phenotypic predictions from genotype data. Our findings also demonstrate that DNAm signatures can be domain-specific, highlighting the precision with which they can reflect genotypic variation.