Autism-Associated DNA Methylation at Birth From Multiple Tissues Is Enriched for Autism Genes in the Early Autism Risk Longitudinal Investigation

Single-cell DNA methylation analysis tool Amethyst reveals distinct noncanonical methylation patterns in human glial cells

Single-cell sequencing technologies have revolutionized biomedical research by enabling deconvolution of cell type-specific properties in highly heterogeneous tissue. While robust tools have been developed to handle bioinformatic challenges posed by single-cell RNA and ATAC data, options for emergent modalities such as methylation are much more limited, impeding the utility of results. Here we present Amethyst, a comprehensive R package for atlas-scale single-cell methylation sequencing data analysis. Amethyst begins with base-level methylation calls and expedites batch integration, doublet detection, dimensionality reduction, clustering, cell type annotation, differentially methylated region calling, and interpretation of results, facilitating rapid data interaction in a local environment. We introduce the workflow using published single-cell methylation human peripheral blood mononuclear cell (PBMC) and human cortex data. We further leverage Amethyst on an atlas-scale brain dataset to describe a noncanonical methylation pattern in human astrocytes and oligodendrocytes, challenging the notion that this form of methylation is principally relevant to neurons in the brain. Tools such as Amethyst will increase accessibility to single-cell methylation data analysis, catalyzing research progress across diverse contexts.

Females with autism spectrum disorders show stronger DNA methylation signatures than males in perinatal tissues

Autism spectrum disorder (ASD) comprises a group of neurodevelopmental conditions currently diagnosed by behavioral assessment in childhood, with reported underdiagnosis in females. Though diagnosis in early life is linked to improved outcomes, we currently lack objective screening tools for newborns. To address this gap, we sought to identify a sex-specific DNA methylation signature for ASD using perinatal tissues that reflect dysregulation in the brain. DNA methylation was assayed from ASD and typically developing (TD) newborn blood, umbilical cord blood, placenta, and post-mortem cortex samples using whole genome bisulfite sequencing (WGBS) in a total of 511 samples. We found that methylation levels of differentially methylated regions (DMRs) differentiated samples by ASD diagnosis in females more than males across the perinatal tissues. We tested three theories for ASD sex differences in newborn blood, finding epigenetic support for an X chromosome-related female protective effect, as well as a high replication rate of DMRs (48.1%) in females across two independent cohorts. In our pan-tissue analysis, three genes (X-linked BCOR, GALNT9, OPCML) mapped to ASD DMRs replicated in all four female tissues. ASD DMRs from all tissues were enriched for neuro-related processes (females) and SFARI ASD-risk genes (females and males). Overall, we found a highly replicated methylation signature of ASD in females across perinatal tissues that reflected dysregulation in the brain and involvement of X chromosome epigenetics. This comparative study of perinatal tissues shows the promise of newborn blood DNA methylation biomarkers for early detection of females at risk for ASD and emphasizes the importance of sex-stratification in ASD studies.

Hippocampal and peripheral blood DNA methylation signatures correlate at the gene and pathway level in a mouse model of autism

Autism spectrum disorders (ASD) are polygenic multifactorial disorders influenced by environmental factors. ASD-related differential DNA methylation has been found in human peripheral tissues, such as placenta, paternal sperm, buccal epithelium, and blood. However, these data lack direct comparison of DNA methylation levels with brain tissue from the same individual to determine the extent that peripheral tissues are surrogates for behavior-related disorders. Here, whole genome methylation profiling at all the possible sites throughout the mouse genome (>25 million) from both brain and blood tissues revealed novel insights into the systemic contributions of DNA methylation to ASD. Sixty-six differentially methylated regions (DMRs) share the same genomic coordinates in these two tissues, many of which are linked to risk genes for neurodevelopmental disorders and intellectual disabilities (e.g. Prkch, Ptn, Hcfc1, Mid1, and Nfia). Gene ontological pathways revealed a significant number of common terms between brain and blood (N = 65 terms), and nearly half (30/65) were associated with brain/neuronal development. Furthermore, seven DMR-associated genes among these terms contain methyl-sensitive transcription factor sequence motifs within the DMRs of both tissues; four of them (Cux2, Kcnip2, Fgf13, and Mrtfa) contain the same methyl-sensitive transcription factor binding sequence motifs (HES1/2/5, TBX2 and TFAP2C), suggesting DNA methylation influences the binding of common transcription factors required for gene expression. Together, these findings suggest that peripheral blood is a good surrogate tissue for brain and support that DNA methylation contributes to altered gene regulation in the pathogenesis of ASD.

Differential DNA Methylation from Autistic Children Enriches Evidence for Genes Associated with ASD and New Candidate Genes

The etiology of Autism Spectrum Disorders (ASD) is a result of the interaction between genes and the environment. The study of epigenetic factors that affect gene expression, such as DNA methylation, has become an important area of research in ASD. In recent years, there has been an increasing body of evidence pointing to epigenetic mechanisms that influence brain development, as in the case of ASD, when gene methylation dysregulation is present. Our analysis revealed 853 differentially methylated CpG in ASD patients, affecting 509 genes across the genome. Enrichment analysis showed five related diseases, including autistic disorder and mental disorders, which are particularly significant. In this work, we identified 64 genes that were previously reported in the SFARI gene database, classified according to their impact index. Additionally, we identified new genes that have not been previously reported as candidates with differences in the methylation patterns of Mexican children with ASD.

Prenatal delta-9-tetrahydrocannabinol exposure is associated with changes in rhesus macaque DNA methylation enriched for autism genes

BACKGROUND

With the growing availability of cannabis and the popularization of additional routes of cannabis use beyond smoking, including edibles, the prevalence of cannabis use in pregnancy is rapidly increasing. However, the potential effects of prenatal cannabis use on fetal developmental programming remain unknown.

RESULTS

We designed this study to determine whether the use of edible cannabis during pregnancy is deleterious to the fetal and placental epigenome. Pregnant rhesus macaques consumed a daily edible containing either delta-9-tetrahydrocannabinol (THC) (2.5 mg/7 kg/day) or placebo. DNA methylation was measured in 5 tissues collected at cesarean delivery (placenta, lung, cerebellum, prefrontal cortex, and right ventricle of the heart) using the Illumina MethylationEPIC platform and filtering for probes previously validated in rhesus macaque. In utero exposure to THC was associated with differential methylation at 581 CpGs, with 573 (98%) identified in placenta. Loci differentially methylated with THC were enriched for candidate autism spectrum disorder (ASD) genes from the Simons Foundation Autism Research Initiative (SFARI) database in all tissues. The placenta demonstrated greatest SFARI gene enrichment, including genes differentially methylated in placentas from a prospective ASD study.

CONCLUSIONS

Overall, our findings reveal that prenatal THC exposure alters placental and fetal DNA methylation at genes involved in neurobehavioral development that may influence longer-term offspring outcomes. The data from this study add to the limited existing literature to help guide patient counseling and public health polices focused on prenatal cannabis use in the future.

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.

Machine Learning-Based Blood RNA Signature for Diagnosis of Autism Spectrum Disorder

Early diagnosis of autism spectrum disorder (ASD) is crucial for providing appropriate treatments and parental guidance from an early age. Yet, ASD diagnosis is a lengthy process, in part due to the lack of reliable biomarkers. We recently applied RNA-sequencing of peripheral blood samples from 73 American and Israeli children with ASD and 26 neurotypically developing (NT) children to identify 10 genes with dysregulated blood expression levels in children with ASD. Machine learning (ML) analyzes data by computerized analytical model building and may be applied to building diagnostic tools based on the optimization of large datasets. Here, we present several ML-generated models, based on RNA expression datasets collected during our recently published RNA-seq study, as tentative tools for ASD diagnosis. Using the random forest classifier, two of our proposed models yield an accuracy of 82% in distinguishing children with ASD and NT children. Our proof-of-concept study requires refinement and independent validation by studies with far larger cohorts of children with ASD and NT children and should thus be perceived as starting point for building more accurate ML-based tools. Eventually, such tools may potentially provide an unbiased means to support the early diagnosis of ASD.

Placental DNA methylation profile as predicting marker for autism spectrum disorder (ASD)

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that impairs normal brain development and socio-cognitive abilities. The pathogenesis of this condition points out the involvement of genetic and environmental factors during in-utero life. Placenta, as an interface tissue between mother and fetus, provides developing fetus requirements and exposes it to maternal environment as well. Therefore, the alteration of DNA methylation as epigenetic consequence of gene-environmental interaction in the placenta could shed light on ASD pathogenesis. In this study, we reviewed the current findings on placental methylation status and its association with ASD. Differentially methylated regions (DMRs) in ASD-developing placenta were found to be mainly enriched in ASD gene loci affecting synaptogenesis, microtubule dynamics, neurogenesis and neuritogenesis. In addition, non-genic DMRs in ASD-placenta proposes an alternative contributing mechanism for ASD development. Our study highlights the importance of placental DNA methylation signature as a biomarker for ASD prediction.

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.

Folate in maternal rheumatoid arthritis-filial autism spectrum disorder continuum

Rheumatoid Arthritis (RA) is an inflammatory autoimmune disease that affects women three times more than men. Epidemiological studies found that the incidence of Autism Spectrum Disorder (ASD), a neurological and developmental disorder, in children born to mothers suffering from RA is higher compared with the control population. Considering that the pathogenesis of ASD could be traced back to pregnancy and in uterine conditions, and the evidence of reduced folate levels in the brain of ASD-affected children, we aimed to study the role of folate, as an important nutritional factor during pregnancy, in associating maternal RA to ASD development in the offspring. Folate balance during RA could be influenced twice, initially during the immune activation associated with disease onset, and later during the treatment with anti-folate drugs, with a potential consequence of folate deficiency. Maternal folate deficiency during pregnancy could increase homocysteine levels, oxidative stress, and global DNA hypomethylation, all known risk factors in ASD pathogenesis. These effects could be intensified by genetic polymorphisms in the folate system, which were also found as genetic risk factors for both RA and ASD. The available evidence suggests that folate level as an important factor during RA, pregnancy and ASD could have pathological and therapeutical significance and should be carefully monitored and investigated in the RA-pregnancy-ASD axis.

Social attention during object engagement: toward a cross-species measure of preferential social orienting

BACKGROUND

A central challenge in preclinical research investigating the biology of autism spectrum disorder (ASD) is the translation of ASD-related social phenotypes across humans and animal models. Social orienting, an observable, evolutionarily conserved behavior, represents a promising cross-species ASD phenotype given that disrupted social orienting is an early-emerging ASD feature with evidence for predicting familial recurrence. Here, we adapt a competing-stimulus social orienting task from domesticated dogs to naturalistic play behavior in human toddlers and test whether this approach indexes decreased social orienting in ASD.

METHODS

Play behavior was coded from the Autism Diagnostic Observation Schedule (ADOS) in two samples of toddlers, each with and without ASD. Sample 1 (n = 16) consisted of community-ascertained research participants, while Sample 2 involved a prospective study of infants at a high or low familial liability for ASD (n = 67). Coding quantified the child's looks towards the experimenter and caregiver, a social stimulus, while playing with high-interest toys, a non-social stimulus. A competing-stimulus measure of "Social Attention During Object Engagement" (SADOE) was calculated by dividing the number of social looks by total time spent playing with toys. SADOE was compared based on ASD diagnosis and differing familial liability for ASD.

RESULTS

In both samples, toddlers with ASD exhibited significantly lower SADOE compared to toddlers without ASD, with large effect sizes (Hedges' g ≥ 0.92) driven by a lower frequency of child-initiated spontaneous looks. Among toddlers at high familial likelihood of ASD, toddlers with ASD showed lower SADOE than toddlers without ASD, while SADOE did not differ based on presence or absence of familial ASD risk alone. SADOE correlated negatively with ADOS social affect calibrated severity scores and positively with the Communication and Symbolic Behavior Scales social subscale. In a binary logistic regression model, SADOE alone correctly classified 74.1% of cases, which rose to 85.2% when combined with cognitive development.

CONCLUSIONS

This work suggests that a brief behavioral measure pitting a high-interest nonsocial stimulus against the innate draw of social partners can serve as a feasible cross-species measure of social orienting, with implications for genetically informative behavioral phenotyping of social deficits in ASD and other neurodevelopmental disorders.

The Soluble Folate Receptor in Autism Spectrum Disorder: Relation to Autism Severity and Leucovorin Treatment

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder with life-long consequences that affects up to 1 in 44 children. Treatment with leucovorin (folinic acid), a reduced form of folate, has been shown to improve symptoms in those with ASD and folate pathway abnormalities in controlled clinical trials. Although soluble folate binding proteins (sFBPs) have been observed in the serum of some patients with ASD, the significance of this finding has not been studied. Here, we present a cohort of ASD patients with sFBPs. These patients had severe ASD and were medically complex. Using baseline controlled open-label methodology and standardized assessments, these patients were found to improve in both core and associated ASD symptoms with leucovorin treatment. No adverse effects were related to leucovorin treatment. This is the first report of the sFBPs in ASD. This study complements ongoing controlled clinical trials and suggests that leucovorin may be effective for children with ASD who are positive for sFBPs. Further, sFBPs might be important biomarkers for treatment response to leucovorin in children with ASD. This study paves the way for further controlled studies for patients with sFBPs.

Associations between accelerated parental biologic age, autism spectrum disorder, social traits, and developmental and cognitive outcomes in their children

Parental age is a known risk factor for autism spectrum disorder (ASD), however, studies to identify the biologic changes underpinning this association are limited. In recent years, "epigenetic clock" algorithms have been developed to estimate biologic age and to evaluate how the epigenetic aging impacts health and disease. In this study, we examined the relationship between parental epigenetic aging and their child's prospective risk of ASD and autism related quantitative traits in the Early Autism Risk Longitudinal Investigation study. Estimates of epigenetic age were computed using three robust clock algorithms and DNA methylation measures from the Infinium HumanMethylation450k platform for maternal blood and paternal blood specimens collected during pregnancy. Epigenetic age acceleration was defined as the residual of regressing chronological age on epigenetic age while accounting for cell type proportions. Multinomial logistic regression and linear regression models were completed adjusting for potential confounders for both maternal epigenetic age acceleration (n = 163) and paternal epigenetic age acceleration (n = 80). We found accelerated epigenetic aging in mothers estimated by Hannum's clock was significantly associated with lower cognitive ability and function in offspring at 12 months, as measured by Mullen Scales of Early Learning scores (β = -1.66, 95% CI: -3.28, -0.04 for a one-unit increase). We also observed a marginal association between accelerated maternal epigenetic aging by Horvath's clock and increased odds of ASD in offspring at 36 months of age (aOR = 1.12, 95% CI: 0.99, 1.26). By contrast, fathers accelerated aging was marginally associated with decreased ASD risk in their offspring (aOR = 0.83, 95% CI: 0.68, 1.01). Our findings suggest epigenetic aging could play a role in parental age risks on child brain development.

Blood RNA Sequencing Indicates Upregulated BATF2 and LY6E and Downregulated ISG15 and MT2A Expression in Children with Autism Spectrum Disorder

Mutations in over 100 genes are implicated in autism spectrum disorder (ASD). DNA SNPs, CNVs, and epigenomic modifications also contribute to ASD. Transcriptomics analysis of blood samples may offer clues for pathways dysregulated in ASD. To expand and validate published findings of RNA-sequencing (RNA-seq) studies, we performed RNA-seq of whole blood samples from an Israeli discovery cohort of eight children with ASD compared with nine age- and sex-matched neurotypical children. This revealed 10 genes with differential expression. Using quantitative real-time PCR, we compared RNAs from whole blood samples of 73 Israeli and American children with ASD and 26 matched neurotypical children for the 10 dysregulated genes detected by RNA-seq. This revealed higher expression levels of the pro-inflammatory transcripts BATF2 and LY6E and lower expression levels of the anti-inflammatory transcripts ISG15 and MT2A in the ASD compared to neurotypical children. BATF2 was recently reported as upregulated in blood samples of Japanese adults with ASD. Our findings support an involvement of these genes in ASD phenotypes, independent of age and ethnicity. Upregulation of BATF2 and downregulation of ISG15 and MT2A were reported to reduce cancer risk. Implications of the dysregulated genes for pro-inflammatory phenotypes, immunity, and cancer risk in ASD are discussed.

Prenatal Exposure to Ambient Air Pollution and Epigenetic Aging at Birth in Newborns

In utero air pollution exposure has been associated with adverse birth outcomes, yet effects of air pollutants on regulatory mechanisms in fetal growth and critical windows of vulnerability during pregnancy are not well understood. There is evidence that epigenetic alterations may contribute to these effects. DNA methylation (DNAm) based age estimators have been developed and studied extensively with health outcomes in recent years. Growing literature suggests environmental factors, such as air pollution and smoking, can influence epigenetic aging. However, little is known about the effect of prenatal air pollution exposure on epigenetic aging. In this study, we leveraged existing data on prenatal air pollution exposure and cord blood DNAm from 332 mother-child pairs in the Early Autism Risk Longitudinal Investigation (EARLI) and Markers of Autism Risk in Babies-Learning Early Signs (MARBLES), two pregnancy cohorts enrolling women who had a previous child diagnosed with autism spectrum disorder, to assess the relationship of prenatal exposure to air pollution and epigenetic aging at birth. DNAm age was computed using existing epigenetic clock algorithms for cord blood tissue-Knight and Bohlin. Epigenetic age acceleration was defined as the residual of regressing chronological gestational age on DNAm age, accounting for cell type proportions. Multivariable linear regression models and distributed lag models (DLMs), adjusting for child sex, maternal race/ethnicity, study sites, year of birth, maternal education, were completed. In the single-pollutant analysis, we observed exposure to PM2.5, PM10, and O3 during preconception period and pregnancy period were associated with decelerated epigenetic aging at birth. For example, pregnancy average PM10 exposure (per 10 unit increase) was associated with epigenetic age deceleration at birth (weeks) for both Knight and Bohlin clocks (β = -0.62, 95% CI: -1.17, -0.06; β = -0.32, 95% CI: -0.63, -0.01, respectively). Weekly DLMs revealed that increasing PM2.5 during the first trimester and second trimester were associated with decelerated epigenetic aging and that increasing PM10 during the preconception period was associated with decelerated epigenetic aging, using the Bohlin clock estimate. Prenatal ambient air pollution exposure, particularly in early and mid-pregnancy, was associated with decelerated epigenetic aging at birth.

Modern Biomarkers for Autism Spectrum Disorder: Future Directions

Autism spectrum disorder is an increasingly prevalent neurodevelopmental disorder in the world today, with an estimated 2% of the population being affected in the USA. A major complicating factor in diagnosing, treating, and understanding autism spectrum disorder is that defining the disorder is solely based on the observation of behavior. Thus, recent research has focused on identifying specific biological abnormalities in autism spectrum disorder that can provide clues to diagnosis and treatment. Biomarkers are an objective way to identify and measure biological abnormalities for diagnostic purposes as well as to measure changes resulting from treatment. This current opinion paper discusses the state of research of various biomarkers currently in development for autism spectrum disorder. The types of biomarkers identified include prenatal history, genetics, neurological including neuroimaging, neurophysiologic, and visual attention, metabolic including abnormalities in mitochondrial, folate, trans-methylation, and trans-sulfuration pathways, immune including autoantibodies and cytokine dysregulation, autonomic nervous system, and nutritional. Many of these biomarkers have promising preliminary evidence for prenatal and post-natal pre-symptomatic risk assessment, confirmation of diagnosis, subtyping, and treatment response. However, most biomarkers have not undergone validation studies and most studies do not investigate biomarkers with clinically relevant comparison groups. Although the field of biomarker research in autism spectrum disorder is promising, it appears that it is currently in the early stages of development.

Future Prospects for Epigenetics in Autism Spectrum Disorder

Despite decades of investigation into the genetics of autism spectrum disorder (ASD), a current consensus in the field persists that ASD risk is too heterogeneous to be diagnosed by a single set of genetic variants. As such, ASD research has broadened to include assessment of other molecular biomarkers implicated in the condition that may be reflective of environmental exposures or gene by environment interactions. Epigenetic variance, and specifically differential DNA methylation, have emerged as areas of particularly high interest to ASD, as the epigenetic markers from specific chromatin loci collectively can reflect influences of multiple genetic and environmental factors and can also result in differential gene expression patterns. This review examines recent studies of the ASD epigenome, detailing common gene pathways found to be differentially methylated in people with ASD, and considers how these discoveries may inform our understanding of ASD etiology. We also consider future applications of epigenetics in ASD research and clinical practice, focusing on substratification, biomarker development, and experimental preclinical models of ASD that test causality. In combination with other -omics approaches, epigenomics allows an improved conceptualization of the multifactorial nature of ASD, and opens future lines of inquiry for both basic research and clinical practice.