Integrated genetic and methylomic analyses identify shared biology between autism and autistic traits

Superior temporal sulcus folding, functional network connectivity, and autistic-like traits in a non-clinical population

BACKGROUND

Autistic-like traits (ALT) are prevalent across the general population and might be linked to some facets of a broader autism spectrum disorder (ASD) phenotype. Recent studies suggest an association of these traits with both genetic and brain structural markers in non-autistic individuals, showing similar spatial location of findings observed in ASD and thus suggesting a potential neurobiological continuum.

METHODS

In this study, we first tested an association of ALTs (assessed with the AQ questionnaire) with cortical complexity, a cortical surface marker of early neurodevelopment, and then the association with disrupted functional connectivity. We analysed structural T1-weighted and resting-state functional MRI scans in 250 psychiatrically healthy individuals without a history of early developmental disorders, in a first step using the CAT12 toolbox for cortical complexity analysis and in a second step we used regional cortical complexity findings to apply the CONN toolbox for seed-based functional connectivity analysis.

RESULTS

Our findings show a significant negative correlation of both AQ total and AQ attention switching subscores with left superior temporal sulcus (STS) cortical folding complexity, with the former being significantly correlated with STS to left lateral occipital cortex connectivity, while the latter showed significant positive correlation of STS to left inferior/middle frontal gyrus connectivity (n = 233; all p < 0.05, FWE cluster-level corrected). Additional analyses also revealed a significant correlation of AQ attention to detail subscores with STS to left lateral occipital cortex connectivity.

LIMITATIONS

Phenotyping might affect association results (e.g. choice of inventories); in addition, our study was limited to subclinical expressions of autistic-like traits.

CONCLUSIONS

Our findings provide further evidence for biological correlates of ALT even in the absence of clinical ASD, while establishing a link between structural variation of early developmental origin and functional connectivity.

Modelling the overlap and divergence of autistic and schizotypal traits on hippocampal subfield volumes and regional cerebral blood flow

Psychiatric disorders show high co-morbidity, including co-morbid expressions of subclinical psychopathology across multiple disease spectra. Given the limitations of classical case-control designs in elucidating this overlap, new approaches are needed to identify biological underpinnings of spectra and their interaction. We assessed autistic-like traits (using the Autism Quotient, AQ) and schizotypy - as models of subclinical expressions of disease phenotypes and examined their association with volumes and regional cerebral blood flow (rCBF) of anterior, mid- and posterior hippocampus segments from  structural MRI scans in 318 and arterial spin labelling (ASL) in 346 nonclinical subjects, which overlapped with the structural imaging sample (N = 298). We demonstrate significant interactive effects of positive schizotypy and AQ social skills as well as of positive schizotypy and AQ imagination on hippocampal subfield volume variation. Moreover, we show that AQ attention switching modulated hippocampal head rCBF, while positive schizotypy by AQ attention to detail interactions modulated hippocampal tail rCBF. In addition, we show significant correlation of hippocampal volume and rCBF in both region-of-interest and voxel-wise analyses, which were robust after removal of variance related to schizotypy and autistic traits. These findings provide empirical evidence for both the modulation of hippocampal subfield structure and function through subclinical traits, and in particular how only the interaction of phenotype facets leads to significant reductions or variations in these parameters. This makes a case for considering the synergistic impact of different (subclinical) disease spectra on transdiagnostic biological parameters in psychiatry.

Understanding the relationship between asthma and autism spectrum disorder: a population-based family and twin study

BACKGROUND

There is some evidence that autism spectrum disorder (ASD) frequently co-occurs with immune-mediated conditions including asthma. We aimed to explore the familial co-aggregation of ASD and asthma using different genetically informed designs.

METHODS

We first examined familial co-aggregation of asthma and ASD in individuals born in Sweden from 1992 to 2007 (n = 1 569 944), including their full- and half-siblings (n = 1 704 388 and 356 544 pairs) and full cousins (n = 3 921 890 pairs), identified using Swedish register data. We then applied quantitative genetic modeling to siblings (n = 620 994 pairs) and twins who participated in the Child and Adolescent Twin Study in Sweden (n = 15 963 pairs) to estimate the contribution of genetic and environmental factors to the co-aggregation. Finally, we estimated genetic correlations between traits using linkage disequilibrium score regression (LDSC).

RESULTS

We observed a within-individual association [adjusted odds ratio (OR) 1.33, 95% confidence interval (CI) 1.28-1.37] and familial co-aggregation between asthma and ASD, and the magnitude of the associations decreased as the degree of relatedness decreased (full-siblings: OR 1.44, 95% CI 1.38-1.50, maternal half-siblings: OR 1.28, 95% CI 1.18-1.39, paternal half-siblings: OR 1.05, 95% CI 0.96-1.15, full cousins: OR 1.06, 95% CI 1.03-1.09), suggesting shared familial liability. Quantitative genetic models estimated statistically significant genetic correlations between ASD traits and asthma. Using the LDSC approach, we did not find statistically significant genetic correlations between asthma and ASD (coefficients between -0.09 and 0.12).

CONCLUSIONS

Using different genetically informed designs, we found some evidence of familial co-aggregation between asthma and ASD, suggesting the weak association between these disorders was influenced by shared genetics.

Can the "female protective effect" liability threshold model explain sex differences in autism spectrum disorder?

Male sex is a strong risk factor for autism spectrum disorder (ASD). The leading theory for a "female protective effect" (FPE) envisions males and females have "differing thresholds" under a "liability threshold model" (DT-LTM). Specifically, this model posits that females require either a greater number or larger magnitude of risk factors (i.e., greater liability) to manifest ASD, which is supported by the finding that a greater proportion of females with ASD have highly penetrant genetic mutations. Herein, we derive testable hypotheses from the DT-LTM for ASD, investigating heritability, familial recurrence, correlation between ASD penetrance and sex ratio, population traits, clinical features, the stability of the sex ratio across diagnostic changes, and highlight other key prerequisites. Our findings reveal that several key predictions of the DT-LTM are not supported by current data, requiring us to establish a different conceptual framework for evaluating alternate models that explain sex differences in ASD.

Epigenetic profiling of social communication trajectories and co-occurring mental health problems: a prospective, methylome-wide association study

While previous studies suggest that both genetic and environmental factors play an important role in the development of autism-related traits, little is known about potential biological mechanisms underlying these associations. Using data from the Avon Longitudinal Study of Parents and Children (ALSPAC), we examined prospective associations between DNA methylation (DNAm: n_birth = 804, n_{age 7} = 877) and trajectories of social communication deficits at age 8-17 years. Methylomic variation at three loci across the genome (false discovery rate = 0.048) differentiated children following high (n = 80) versus low (n = 724) trajectories of social communication deficits. This differential DNAm was specific to the neonatal period and not observed at 7 years of age. Associations between DNAm and trajectory membership remained robust after controlling for co-occurring mental health problems (i.e., hyperactivity/inattention, conduct problems). The three loci identified at birth were not replicated in the Generation R Study. However, to the best of our knowledge, ALSPAC is the only study to date that is prospective enough to examine DNAm in relation to longitudinal trajectories of social communication deficits from childhood to adolescence. Although the present findings might point to potentially novel sites that differentiate between a high versus low trajectory of social communication deficits, the results should be considered tentative until further replicated.

Meta-analysis of epigenome-wide associations between DNA methylation at birth and childhood cognitive skills

Cognitive skills are a strong predictor of a wide range of later life outcomes. Genetic and epigenetic associations across the genome explain some of the variation in general cognitive abilities in the general population and it is plausible that epigenetic associations might arise from prenatal environmental exposures and/or genetic variation early in life. We investigated the association between cord blood DNA methylation at birth and cognitive skills assessed in children from eight pregnancy cohorts within the Pregnancy And Childhood Epigenetics (PACE) Consortium across overall (total N = 2196), verbal (total N = 2206) and non-verbal cognitive scores (total N = 3300). The associations at single CpG sites were weak for all of the cognitive domains investigated. One region near DUSP22 on chromosome 6 was associated with non-verbal cognition in a model adjusted for maternal IQ. We conclude that there is little evidence to support the idea that variation in cord blood DNA methylation at single CpG sites is associated with cognitive skills and further studies are needed to confirm the association at DUSP22.

Maternal diabetes-mediated RORA suppression in mice contributes to autism-like offspring through inhibition of aromatase

Retinoic acid-related orphan receptor alpha (RORA) suppression is associated with autism spectrum disorder (ASD) development, although the mechanism remains unclear. In this study, we aim to investigate the potential effect and mechanisms of RORA suppression on autism-like behavior (ALB) through maternal diabetes-mediated mouse model. Our in vitro study in human neural progenitor cells shows that transient hyperglycemia induces persistent RORA suppression through oxidative stress-mediated epigenetic modifications and subsequent dissociation of octamer-binding transcription factor 3/4 from the RORA promoter, subsequently suppressing the expression of aromatase and superoxide dismutase 2. The in vivo mouse study shows that prenatal RORA deficiency in neuron-specific RORA null mice mimics maternal diabetes-mediated ALB; postnatal RORA expression in the amygdala ameliorates, while postnatal RORA knockdown mimics, maternal diabetes-mediated ALB in offspring. In addition, RORA mRNA levels in peripheral blood mononuclear cells decrease to 34.2% in ASD patients (n = 121) compared to the typically developing group (n = 118), and the related Receiver Operating Characteristic curve shows good sensitivity and specificity with a calculated 84.1% of Area Under the Curve for ASD diagnosis. We conclude that maternal diabetes contributes to ALB in offspring through suppression of RORA and aromatase, RORA expression in PBMC could be a potential marker for ASD screening.

Hong Yu, Yanbin Niu, Guohua Jia et al. integrate in vitro, in vivo, and human experiments to examine a link between RORA expression on autism-like behavior. Their results suggest that maternal diabetes may contribute to autism-like behavior via RORA suppression.

Predictive waves in the autism-schizophrenia continuum: A novel biobehavioral model

The brain is a predictive machine. Converging data suggests a diametric predictive strategy from autism spectrum disorders (ASD) to schizophrenic spectrum disorders (SSD). Whereas perceptual inference in ASD is rigidly shaped by incoming sensory information, the SSD population is prone to overestimate the precision of their priors' models. Growing evidence considers brain oscillations pivotal biomarkers to understand how top-down predictions integrate bottom-up input. Starting from the conceptualization of ASD and SSD as oscillopathies, we introduce an integrated perspective that ascribes the maladjustments of the predictive mechanism to dysregulation of neural synchronization. According to this proposal, disturbances in the oscillatory profile do not allow the appropriate trade-off between descending predictive signal, overweighted in SSD, and ascending prediction errors, overweighted in ASD. These opposing imbalances both result in an ill-adapted reaction to external challenges. This approach offers a neuro-computational model capable of linking predictive coding theories with electrophysiological findings, aiming to increase knowledge on the neuronal foundations of the two spectra features and stimulate hypothesis-driven rehabilitation/research perspectives.

Biological implications of genetic variations in autism spectrum disorders from genomics studies

Autism spectrum disorder (ASD) is a highly heterogeneous neurodevelopmental condition characterized by atypical social interaction and communication together with repetitive behaviors and restricted interests. The prevalence of ASD has been increased these years. Compelling evidence has shown that genetic factors contribute largely to the development of ASD. However, knowledge about its genetic etiology and pathogenesis is limited. Broad applications of genomics studies have revealed the importance of gene mutations at protein-coding regions as well as the interrupted non-coding regions in the development of ASD. In this review, we summarize the current evidence for the known molecular genetic basis and possible pathological mechanisms as well as the risk genes and loci of ASD. Functional studies for the underlying mechanisms are also implicated. The understanding of the genetics and genomics of ASD is important for the genetic diagnosis and intervention for this condition.

Autistic traits are associated with faster pace of aging: Evidence from the Dunedin study at age 45

Growing evidence indicates that the defining characteristics of autism spectrum disorder (ASD) are distributed throughout the general population; hence, understanding the correlates of aging in people with high autistic traits could shed light on ASD and aging. 915 members of the Dunedin longitudinal birth cohort completed a measure of autistic traits at age 45. A composite measure of the "pace of aging" was derived by tracking the decline in 19 biomarkers across ages 26, 32, 38, and 45 years. Facial age was also assessed. Reports of perceived health were collected from participants themselves, informants, and interviewers. Higher self-reported autistic traits significantly correlated with a faster pace of aging, older facial age, and poorer self-, informant-, and interviewer-rated health. After control for sex, SES and IQ, autistic traits were significantly associated with each variable: pace of aging (β = 0.09), facial age (β = 0.08), self- (β = -0.15), informant (β = -0.12), and interviewer-rated (β = -0.17) health. Autistic traits measured at age 45 are associated with faster aging. Participants with high autistic traits appear to be more vulnerable to poor health outcomes, as previously reported for those clinically diagnosed with ASD. Therefore, autistic traits may have important health implications. Replicating these findings in samples of autistic people is needed to identify the mechanism of their effect on aging and physical health to improve outcomes for those with ASD diagnoses or high autistic traits. LAY SUMMARY: The role that autistic traits have in relation to health outcomes has not been investigated. We looked at how physical health and aging (measured with self-reported questions and decline in multiple biological measures) were related to autistic traits (measured with a questionnaire, at age 45). We found that higher autistic traits were associated with poorer reports of physical health, and a faster pace of aging. This suggests that both those with autism and those with higher autistic traits may be more likely to experience poorer health outcomes.

Subclinical schizotypal vs. autistic traits show overlapping and diametrically opposed facets in a non-clinical population

BACKGROUND

The overlap of autism spectrum disorder (ASD) and psychosis or schizophrenia spectrum disorders (SSD) has exposed problems central to conceptualising and understanding co-morbidity in psychiatric disorders.

METHODS

In the present study, we demonstrate that a deep phenotyping approach aids clarification of both overlapping and diametrically opposed features of ASD and SSD on the level of trait facets.

RESULTS

We first show overlap of negative and disorganised (but not positive) features of schizotypy with autistic traits in a sample of n = 376 German non-clinical subjects using multiple psychometric measures of schizotypy (MSS multidimensional schizotypy scale, OLIFE Oxford-Liverpool Inventory of Feelings and Experiences, and SPQ-B schizotypal personality questionnaire - brief) and the AQ autism spectrum quotient, with control measures for affective spectrum pathology (BDI). Findings were then replicated in a French-Swiss sample (n = 264) using MSS, OLIFE, AQ, and in addition the Community Assessment of Psychic Experiences (CAPE). Additional principal component analysis confirmed our finding of the co-existence of both overlapping (loss of function, social communication deficit, and negative schizotypy) as well as diametrically opposed features (AQ attention to detail, positive schizotypy) across the two spectra. Results were validated with Horn's parallel analyses, affirming two component solutions, and PCA using sample-specific, factor-analysis-derived schizotypy scores.

CONCLUSIONS

Providing a framework for multi-dimensional transdiagnostic characterisation of ASD vs. SSD phenotypes we point out overlapping vs. discriminating facets. In addition to the use of novel multidimensional schizotypy scales, it also shows transcultural consistency of findings, and highlights a particular role for the attention to detail AQ subscale.

Sperm DNA methylation epimutation biomarker for paternal offspring autism susceptibility

BACKGROUND

Autism spectrum disorder (ASD) has increased over tenfold over the past several decades and appears predominantly associated with paternal transmission. Although genetics is anticipated to be a component of ASD etiology, environmental epigenetics is now also thought to be an important factor. Epigenetic alterations, such as DNA methylation, have been correlated with ASD. The current study was designed to identify a DNA methylation signature in sperm as a potential biomarker to identify paternal offspring autism susceptibility.

METHODS AND RESULTS

Sperm samples were obtained from fathers that have children with or without autism, and the sperm then assessed for alterations in DNA methylation. A genome-wide analysis (> 90%) for differential DNA methylation regions (DMRs) was used to identify DMRs in the sperm of fathers (n = 13) with autistic children in comparison with those (n = 13) without ASD children. The 805 DMR genomic features such as chromosomal location, CpG density and length of the DMRs were characterized. Genes associated with the DMRs were identified and found to be linked to previously known ASD genes, as well as other neurobiology-related genes. The potential sperm DMR biomarkers/diagnostic was validated with blinded test sets (n = 8-10) of individuals with an approximately 90% accuracy.

CONCLUSIONS

Observations demonstrate a highly significant set of 805 DMRs in sperm that can potentially act as a biomarker for paternal offspring autism susceptibility. Ancestral or early-life paternal exposures that alter germline epigenetics are anticipated to be a molecular component of ASD etiology.

An Exploratory Study of a Dimensional Assessment of the Diagnostic Criteria for Autism

Prevalence rates of autism based upon child samples have shown a consistent increase over the past three decades, suggesting that many autistic adults are undiagnosed. Adult diagnostic pathways typically are initiated with measures of autistic-like traits. Whilst autistic-like traits represent a continuous dimension across the general population, autism is a categorical diagnosis and the relationship between the two is unclear. A self-report dimensional reflection upon the two diagnostic criteria for autism was developed and reflected upon by 1076 participants embedded within two online surveys. Those with an informal (self) diagnosis of autism self-reported comparable social difficulties but fewer restricted and repetitive behaviour difficulties than those with a formal diagnosis of autism. The new items also significantly correlated with autistic-like traits.

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.

Annual Research Review: Looking back to look forward - changes in the concept of autism and implications for future research

The concept of autism is a significant contribution from child psychiatry that has entered wider culture and public consciousness, and has evolved significantly over the last four decades. Taking a rather personal retrospective, reflecting on our own time in autism research, this review explores changes in the concept of autism and the implications of these for future research. We focus on seven major changes in how autism is thought of, operationalised, and recognised: (1) from a narrow definition to wide diagnostic criteria; (2) from a rare to a relatively common condition, although probably still under-recognised in women; (3) from something affecting children, to a lifelong condition; (4) from something discreet and distinct, to a dimensional view; (5) from one thing to many 'autisms', and a compound or 'fractionable' condition; (6) from a focus on 'pure' autism, to recognition that complexity and comorbidity is the norm; and finally, (7) from conceptualising autism purely as a 'developmental disorder', to recognising a neurodiversity perspective, operationalised in participatory research models. We conclude with some challenges for the field and suggestions for areas currently neglected in autism research.