Dr. Judy Van de Water, Ph.D., explores the role of gestational factors in the development of autism. She explains how maternal immune activation, antibody patterns, and immune markers play significant roles in neurodevelopment and may contribute to the etiology and phenotypic variation of autism. The speaker presents various investigations and critical findings. She asserts the need for further research on the interaction of these gestational influences with other genetic and environmental factors. Van de Water provides thanks and acknowledgments before the Q&A.

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In this webinar:

1:02 – Potential etiologies of autism
3:03 – Maternal Immune Activation Model
5:30 – Research sample characteristics
7:40 – Study: Maternal prenatal cytokines
11:05 – Study: Newborn immune markers
15:06 – Study: Effect of sex on newborn immune system profile
17:30 – Maternal autoantibody related autism subtype (MARA)
19:25 – Target proteins and brain development
20:46 – Study: MAR antibody test
24:26 – Study: Early markers of autism – prenatal validation
27:40 – MAR antibody patterns phenotypes
29:30 – Summary of clinical findings
31:03 – Study: Translational animal model
34:15 – Rodent model findings
38:40 – Conclusions
41:55 – Q & A

Introduction

Van de Water lists potential etiologies for autism, including genetic predisposition, immune dysregulation, and infections during gestation. She explains that maternal infection, specifically inflammation resulting from infection, has been implicated as a risk factor for autism and schizophrenia (1:02). The speaker introduces the Maternal Immune Activation Model, which proposes that when an inflammatory event occurs during pregnancy, the mother’s immune response may be more active, leading to the transfer of different factors to the fetal compartment (e.g., cytokines) Such immune dysregulation can increase the risk of altered fetal neurodevelopment (3:03). Van de Water notes that genetic susceptibility, gestational timing, intensity of immune response and other postnatal events all play a role in autism etiology (5:00). 

Inflammatory response during pregnancy

The presenter describes recent investigations into risk factors for autism and developmental delays (5:30). She summarizes sample collection and research methods for a study that assessed maternal prenatal cytokines in mothers of autistic children with intellectual delays (ID), mothers of autistic children without ID, and mothers of children with ID but not autism (7:40). Researchers found that mothers of autistic children with ID had the highest levels of inflammatory cytokines and chemokines compared to all other groups. This suggests, Van de Water continues, a lack of selective immune regulation in these women and a potential link between immune activation and ID in autistic individuals (10:08). A second study found that newborns diagnosed with autism and delayed development (DD) had lower levels of specific cytokines and chemokines at birth compared to those with typical development or DD without autism (11:05). Van de Water discusses particular chemokines and cytokines that may impact autism etiology (13:30). 

The speaker details another study investigating the effect of offspring sex on immune profiles at birth (15:06). Researchers found that neonatal immune signatures differ by sex regardless of the neurodevelopmental outcome. However, control males had higher levels of certain immune markers than females, and autistic females with DD had higher levels than males with autism (17:20). The speaker asserts that such sex-specific differences in immune markers may contribute to the variability in autism phenotypes, highlighting the need for individualized treatments (16:15). 

Maternal autoantibody-related autism

Van de Water discusses the maternal autoantibody-related autism subtype (MAR) (around 20% of cases), where mothers have antibodies that are reactive against proteins in the developing brain (17:30). She explains that during fetal development, the mother’s antibodies cross the placenta to provide immune protection for the fetus. In the case of MAR, some antibodies can bind to pre-neuronal cells, which leads to different brain development. The speaker presents a MAR antibody test designed by her team (20:46). Initial findings revealed antibody patterns specific to autism in 20% of the sample and that mothers with these antibodies were 31 times more likely to have a child with autism (22:30). 

The presenter outlines a second study that validated the MAR antibody test with prenatal data (24:26). They also found that specific MAR antibody patterns were associated with phenotypic differences in autism. Van de Water therefore asserts that these patterns could not only serve as autism biomarkers but could also inform more specific and individualized interventions (27:40). She summarizes clinical findings from the previous studies and notes that as autism incidence increases, they see an increase in MAR as well (29:30). 

Translational animal models 

The speaker details translational animal models and why they are essential in preclinical trials. She explains how they used animal models to determine whether MAR autoantibodies are related to etiology or are just biomarkers (31:03). Animal studies generally include measures of behavior, brain scans, and cell cultures (32:15). Van de Water outlines an antibody study that found both mice and rats showed altered social behavior, self-grooming, and increased repetitive behaviors and produced the same antibodies found in humans with autism (34:15). These data, she continues, also exhibit differences in brain volume, with males and females displaying distinct patterns of brain development (37:30). 

Van de Water summarizes the main conclusions from the animal models. She highlights that gestational immune dysregulation may contribute to altered neurodevelopment and that antibodies localize to developing animals’ brains. The speaker emphasizes that we see enlarged brains in humans, mice, monkeys, and rats with gestational exposure to MAR autoantibodies and underscores the structural effects of MAR antibodies and the usefulness of animal models (38:40). She provides acknowledgments and thanks to collaborators before the Q & A (41:55). 

Valerie W. Hu, Ph.D., discusses gene-environmental interactions pertaining to autism. She describes how integrative genomics studies on autism led to investigating endocrine disrupting compounds (EDCs) as environmental risk factors for autism and presents findings on the impact of specific EDCs on gene expression in autism subgroups. The speaker describes studies on DNA methylation in human sperm associated with long-term exposure to EDCs and posits how EDC-dependent epigenomic alterations may contribute to increased risk for autism. Hu repeatedly underscores that these studies aim to create targeted therapy and personalized medical care for autistic individuals. She summarizes the presented studies and findings before the question-and-answer session. 

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In this webinar: 

0:34 – Presenter introduction
1:35 – Presentation objectives
2:45 – What is autism?
3:48 – Autism prevalence
4:23 – The Autism Pyramid – Intro to gene-environment interactions
6:43 – Research lab goals
7:40 – Underlying hypothesis and experimental strategy
9:40 – Study: Clinical phenotypes
13:02 – Research questions and subgroup approach
14:07 – Results: Differentially expressed genes in autism subgroups
15:38 – Results:  Autism subgroups via gene expression profiles
16:03 – Results:  Gene expression and biology of autism subgroups
18:36 – Circadian rhythm
20:30 – Specific treatments for identified genetic deficiencies
22:42 – Study: Epigenetics and methylation
24:44 – Results: Differentially expressed genes
25:43 – RORA and autism
27:36 – How is RORA regulated?
32:08 – RORA, the master regulator
33:58 – RORA deficiencies and endocrine-disrupting chemicals
34:49 – EDCs
36:21 – Study: Short-term Atrazine exposure
40:30 – EDC-dysregulated RORA expression
41:17 – Study: Cross-generational Atrazine exposure effects
44:43 – Results: Differentially methylated region patterns
46:47 – Results: SNORD115 methylation across generations
48:22 – Presentation summary
51:03 – Acknowledgements and references
51:20 – Q & A

A brief intro to gene-environmental interactions 

Hu outlines presentation objectives (1:35) and briefs the history of autism descriptions, the current definition as reflected in the DSM-5 (2:45), and autism prevalence (3:48). She uses the Autism Pyramid to describe what causes autism where each titled layer controls those below (4:23):

• Environmental triggers
• Genetics & epigenetics (equally important)
• Gene expression profile (level of gene activity)
• Autism phenotypes (observed behaviors and brain circuitry)

Gene expression, she continues, determines the function of cells and tissues that give rise to certain behaviors and symptoms (phenotypes). The presenter describes genetics as encoded in our DNA (hardware) and epigenetics as the regulatory mechanisms (software) that determine gene expression and that are affected by surrounding environments (5:45). Environmental triggers can be intrinsic (e.g., hormones) and extrinsic (e.g., pesticides). However, we don’t understand much about how they work.

Studies on gene expression profiles of autistic individuals

Based on this understanding of gene-environment interactions (7:40), Hu and her lab set out to identify genes and pathways for targeted therapies, discover diagnostic biomarkers, and develop a systems-level understanding of autism pathobiology (6:43). To account for the phenotypic heterogeneity (diversity) within autism (8:00), researchers ran cluster analyses of raw ADI-R scores (9:48) and found four distinct clinical subgroups: severe language impaired (SLI), savant skills (SK), intermediate severity (IS), and mild severity (MS) (11:15). Researchers compared the underlying biology of these autistic subgroups to the non-autistic population (13:02) and found different patterns of gene activity across groups with the most significant difference between SLI and controls. Beyond this, they observed that MS had gene expression patterns that resembled the controls (14:07). Principal components analysis also revealed that gene expression profiles could separate the apparent autism subtypes into distinct subgroups (15:38). The speaker and her colleagues also found overlapping and unique genes associated with each autism subgroup compared to controls (16:03). While associated genes related to what we already know of autism (17:00), unique genes in the SLI group were not present in MS or SK groups. 

DNA methylation, an epigenetic mechanism

DNA methylation is an epigenetic mechanism that involves placing a chemical mark that alters gene function (when marked on or off) on a particular base in a DNA sequence. To discover if DNA methylation contributes to gene dysregulation, researchers conducted large-scale microarray analyses of cells from discordant twins and siblings (23:27). Results revealed 25 genes whose expression level might be related to specific methylation. The speaker notes a pathway analysis that identified methylation-regulated genes involved in steroid biosynthesis, digestion, fetal development, and more (24:44). Hu details the results of a RORA-deficient mouse model (25:43) and outlines its implications for autism (26:48), including circadian rhythm genes, neuroinflammation, and cell deficiencies (26:48). 

Circadian rhythm and the RORA gene

The speaker describes circadian rhythm genes (clock genes) (18:36) as they apply to functions and disorders associated with autism such as memory, sleep-wake cycle, learning, cell proliferation, and more (19:50). Regulation of the RORA gene, she explains, directly affects circadian outcomes and so has specifically linked autism to environmental triggers (19:35). Hu discusses sex hormones as possible regulators of the RORA gene and posits that the extreme male brain theory may explain hormonal regulation differences in sex cells (29:08)* 

RORA is a “master regulator of [over 400] autism-relevant genes. Therefore, any mechanisms that disrupt RORA expression could be implicated in increased risk for autism” (32:08).

RORA deficiency and endocrine-disrupting chemicals (EDCs)

Endocrine-disrupting chemicals (EDCs) can also dysregulate RORA expression (33:58). EDCs mimic or antagonize endogenous hormones (produced inside the cell), therefore disrupting homeostasis. Examples of EDCs include herbicides like Atrazine, pesticides like DDT, plastics like Bisphenol A (BPA), and Phthalates like air fresheners and soft toys (34:49). Hu outlines studies on the effects of Atrazine (a common herbicide) on sexual differentiation in wildlife (36:21), noting how ‘“low-dose” amounts have a bidirectional impact on RORA expression in neuronal cell cultures (38:00). Another gene expression profiling study showed an overlap of differentially expressed genes and transcriptional targets for RORA (39:00). Hu asserts that these studies reveal how EDC-dysregulated RORA expression is a potential mechanism for gene-environment interactions that may increase the risk for autism (40:30).

How is the impact of environmental agents transferred across generations?

Hu outlines a study that revealed increasingly altered DNA methylation in each generation of offspring from a mouse who experienced long-term exposure to Atrazine. She highlights the significant increase in the number of autism genes present in the F2 and F3 generations (41:17). Similarly, she continues, a discovery study on the impact of endocrine disruptors on human sperm methylome (43:05) found that differentially methylated regions (DMRs) of expression clearly separated groups by exposure amount (low and high). Further, fourteen overlapping genes across three study sets were implicated in central nervous system development, synaptic transmissions, social behaviors, hormones, and more (44:46).

Hu details a final study that revealed the methylation of SNORD115, a paternally imprinted chromosome, was significantly differentially methylated across all study groups (46:47). Specifically, SNORD115 was significantly differentially methylated in the sperm of fathers of autistic children compared to the fathers of non-autistic children (47:30). These findings, Hu asserts, suggest the existence of environmentally induced autism-associated epigenetic alterations that may be transmitted transgenerationally through germline cells (48:00).

Summary and conclusions

The speaker summarizes the findings discussed in the presentation and underscores the need for integrative genomic discovery paths to environmental contributors of autism (48:22). The presented studies evidence environment-dependent life-long genetic and epigenetic effects specific to autism that may be transmitted transgenerationally. Therefore, creating targeted treatments and accommodations via continued research and awareness is paramount. Hu provides acknowledgments and references before beginning the question and answer session (51:20).

*According to 2022 studies on gender and diagnosis in autism, extreme male brain theory may no longer explain these or other gender-based differences observed in autism. You can learn about these studies here!