Casanova dives into the ancient origins of autism susceptibility genes. She outlines periods of rapid gene evolution in early vertebrates and provides an introduction to basic genetics. The presenter characterizes autism genes by length, age, conservation, and protein interaction. Casanova considers variation/mutation tolerance of autism genes compared to nervous and developmental gene groups. She ultimately demonstrates that most autism-related genes are integral to protein complexes and radiated more than half a billion years ago during a phase of rapid brain evolution in vertebrates. Casanova provides a presentation summary before the Q&A.

Take the knowledge quiz for this presentation HERE.

In this webinar: 

1:54 – Introduction
2:58 – Background: Gene radiations over time
4:30 – Histogram of autism gene age
5:45 – Evolutionary period of early vertebrates
9:02 – Gene conservation
11:35 – Basics aspects of autism genes
14:23 – Genetics 101
17:11 – Study: Autism gene characteristics
19:25 – Results: Gene length
21:24 – Gene length vs protein length
23:16 – Transposable elements, conserved noncoding sequences, and autism gene complexity
29:25 – Results: Gene conservation
36:00 – Evolutionary rate and inheritance patterns
40:45 – Dosage sensitivity – Gene balance hypothesis
43:50 – Analogy: Complex ratios and cars
45:50 – Characteristics of dosage sensitive genes
47:00 – Metabolic genes
50:10 – Protein to protein interactions
53:10 – Study and data limitations
55:00 – Gene age and ohnolog genes
58:30 – True brain evolution
1:02:00 – Nervous system evolution
1:03:00 – Functional enrichment in autism genes
1:05:00 – Summary
1:07:15 – Q&A

Introduction to gene evolution and genetics

Casanova provides a brief history of human genome evolution, highlighting periods of intense gene radiation (gene evolution). She explains that around the time of early fish (~530 mya), there was a significant increase in the number of radiating genes which coincides with two rounds of whole genome duplication (WGD) (5:45). Casanova asserts that such an increase in total gene number across this period is suggestive because WGDs are linked to other major gene radiation periods (7:40). Gene radiation dramatically slowed after the tetrapods (four-limbed vertebrates) appeared (4:30), and tetrapod (including human) genes are relatively conserved compared to other animals (9:02). She defines the basic components of genes as (14:23): 

• Promoter region, which regulates gene expression
• Exons that code for proteins
• Introns sit between exons and are spliced out before the protein is produced – they can affect gene expression

Proteins are the basic building blocks of cells in the body, and transcripts produced from each gene determine which proteins are made (16:24). Casanova introduces a 2019 study that examined characteristics of autism genes, including length, conservation, protein interaction, and age. She explains that understanding what genes do and when and why they evolved can help us understand a protein’s most basic function. She asserts that this may help us understand autism susceptibility genes more than studying people will (17:11). 

Autism susceptibility gene characteristics

The study found that autism genes are generally longer than control genes in the nervous, developmental, regulatory, and innate immune systems. Autism genes also tend to produce unusually large proteins, which suggests functional complexity (19:25). Casanova explains that autism genes are gigantic compared to the relative size of the proteins they are creating, which is not the case in any other gene group (21:24). She defines

• Transposable elements (TE): small segments of DNA that can cut/copy themselves around the genome. 
• Conserved noncoding sequences (CNE): conserved sequences that do not code for proteins but can be gene regulators. They are tucked inside the introns of genes. 

The total number of TE and CNE in autism genes is significantly greater compared to other groups (23:16). Many CNE, she continues, are frequently borrowed from TE, suggesting that TE are turned into regulatory sequences (CNE) at a much higher rate than is usual in the genome (28:17). Casanova states that this abundance of potential regulatory sequences within autism genes means that “the complexity of expression and capacity is significantly different from what we see in the genome as a whole” (25:08).

The speaker outlines different measurements of gene conservation or how conserved a given gene sequence is across groups. Measures included ExAC pLI scores, RVIS scores, and frequency of number-specific sections of DNA (copy number variant) (29:25). Both ExAC pLI (31:55) and RVIS scores (33:05) revealed that autism genes are very intolerant to gene variation and mutation. They also found that copy number variants (CNV) target fewer autism susceptibility genes than others in the genome (33:40). Casanova highlights that CNVs are more deleterious (deadly) within autism genes and asserts that these findings suggest another level of mutation intolerance in autism-related genes (34:55). 

Autism gene evolutionary rate was significantly lower than controls, suggesting that autism genes have been more tightly conserved than the genome background across the animal kingdom. Casanova underscores that these genes have been tightly conserved for more than half a billion years (36:00). The speaker presents another study that investigated the inheritance patterns of intellectual disability (ID) and ID associated with autism (ID+autism) (37:31). They found that about 60% of the mutations associated with ID+autism are inherited dominantly, meaning only one version of the gene needs to be inherited for expression (39:04). 

Dosage sensitivity and the age of autism genes

Dosage sensitivity measures how sensitive a given gene is to subtle changes in expression (40:45). Casanova explains that proteins are often involved in complexes or critical signal pathways. The proper functionality of these complexes/pathways depends on the ratio of protein components produced by the genes. If a single protein dosage is altered, the entire complex/pathway is also modified (41:45). These variations are, therefore, strongly selected against, and mutations tend to be expressed dominantly. Dosage-sensitive genes do not like to be duplicated or deleted in single-gene scenarios due to ratio disruption. They are, therefore, underrepresented in CNVs and overrepresented in genes derived and retained from WGD (45:50). Contrastingly, less sensitive genes are not likely to form complexes/pathways and so are less vulnerable to small/single dosage changes and are overrepresented in CNV (47:00). Casanova reiterates that autism susceptibility genes are highly dosage sensitive, highly conserved, and essential in complex/pathway creation. Therefore, they exhibit significantly more protein-protein interactions (PPI) than control groups (50:10). 

The speaker underscores that at least 50% of autism genes arose more than half a billion years ago, likely due to WGD. (58:30). Casanova discusses the functional enrichment of autism genes compared to controls across time. She notes that a large percent of autism-related genes are associated with synaptic components and radiated between early animals and bony fishes (1:03:00). She highlights that the true brain (which humans have) developed around this time, which explains the concentration of synaptic and neural genes in the autism group (1:00:32). Casanova provides the following summary points before the Q&A session. 

Autism genes 

• Are usually long
• Produce larger, potentially more complex proteins
• Contain greater total TE and CNE in their introns
• Contain high density of CNE in introns
• Are highly intolerant to variation
• Are older, on average, than the rest of the genome
• Have more PPI, are highly dosage-sensitive, are tightly conserved across animals, and are often inherited in a dominant fashion
• Radiated during early animal evolution, many as the result of WGD, and may have played essential roles in critical steps in the evolution of the early nervous system
• Are enriched for functions at the synapse, neural projections, and processes surrounding neurogenesis, all of which were rapidly evolving in early animals up through the evolution of bony fishes. 

Hannah Belcher, Ph.D., Autistic researcher, speaker, and author, discusses the often late and missed diagnosis of autistic females. She dives into the gender gap inherent in autism research, assessments, and clinical understanding, demonstrating how this has led to late and misdiagnosis of autism in women. The speaker presents contemporary research working to uncover a female autism phenotype and discusses masking as implicated in mental health and diagnosis. Belcher continually asserts the societal need for greater understanding and accommodation of autistic womens’ lived experiences and outlines what needs to change before the question and answer session.

Learn more about our speaker Hannah Belcher, Ph.D. HERE

Take the knowledge quiz for this presentation HERE

In this webinar: 

1:27 – About Hannah Belcher
3:09 – Taking off the Mask book highlight
3:36 – Language, terminology, and content warning
5:38 – Key content
6:00 – What do we know about autistic women?
7:30 – Missed diagnosis and current diagnostic basis
8:54 – Autism Quotient background
9:48 – Study: Autism quotient gender bias
11:11 – Study: Assessment measures gender bias
12:45 – Changing prevalence rates
13:30 – Autism gender gap
14:25 – Female phenotype theory
17:30 – Study: Diagnosed vs potentially undiagnosed autistic women
19:30 – Masking and hiding traits
22:45 – Why do autistic people mask?
24:40 – Study: First impressions of autistic women and men
27:29 – Effects of masking on mental health (personal flowchart)
30:05 – Why masking has this effect
34:23 – Clinician bias
37:28 – A hidden population
38:50 – Borderline Personality Disorder
41:38 – What needs to change?
45:10 – Closing, thanks, and Q & A

Belcher provides terminology and underscores identity-first language (autistic person(s)) (3:36). She uses the terms ‘male’ and ‘female’ because the majority of available research uses this binary lens. However, she notes that many autistic people do not identify with these labels. The speaker outlines key content (5:38) and notes that these topics have been discussed anecdotally for decades. However, she states that today, we don’t deal with anecdotes; it’s time for real numbers and research.

What we know about autistic females:

Autism has historically been considered a male disease, and consequently, the voices of women are largely absent from the research literature (7:38). Due to this imbalance in literature and, subsequently, in our foundational understanding of autism, an accurate description of autistic females does not exist (6:00). 

“From the beginning, we have not included women in the research or built our systems and conceptions of autism around their experiences.” 

The foundations of current diagnostic systems:

The speaker describes gender imbalances in the original description of autism and the validation of the Autism Quotient (AQ), the primary diagnostic screening tool in the UK (8:54). She outlines recent studies that revealed the AQ does not measure identical traits in males and females (9:48) and that the ADOS-2, a golden standard assessment, shows signs of significant gender bias (11:11). Therefore, Belcher states the very foundations of current diagnostic systems innately lack the female perspective.

The female phenotype theory:

The Female Phenotype Theory asserts that autistic males and females express autistic traits differently (13:20). Belcher briefs findings that support this theory and concludes that autistic females present as much more social than their male counterparts, which contrasts the idea of autism as a “social disorder” (15:25) and supports the gender biases revealed in the AQ and ADOS-2. 

To determine if there is a female phenotype, researchers investigated 243 diagnosed autistic women and 767 potentially undiagnosed women (PUW), hypothesizing that PUW would present as more exaggerated in these social areas (missed by assessments) (17:30). PUW scored significantly higher on empathy and general functioning measures than diagnosed women. This suggests, Belcher states, that social abilities may be an aspect of the different autism phenotypes. This challenges the idea that autistic people lack empathy and always have a talent for systemizing things (18:20). 

Masking and mental health

Masking is when autistic individuals hide or compensate for their autistic traits to appear more “normal” and fit in with others (19:30). The speaker describes a study assessing differences in first impressions of autistic men and women in a group of people who didn’t know their diagnoses (24:40). Results showed that autistic females rated better than males, that self-reported masking was not related to impressions, and that better first impressions are related to age at diagnosis. Belcher posits that these findings suggest some unconscious physical presentation of autism that affects the age of diagnosis and that non-autistic people pick up on these behaviors (25:40). 

Masking significantly predicts suicidal behaviors in autistic individuals and positively correlates with depression and anxiety. Belcher describes how relentless self-monitoring (conscious or not) and adapting to social situations with different people all day is exhausting and leaves little time for self-expression or care (30:05). Therefore, Belcher insists, 

“We need to minimize and move the onus of fitting in from autistic people masking toward non-autistic people learning to accept autistic people as they are. Consequences are severe if this is not the case… masking natural behaviors and traits denies expression of our true selves and identity.”

Misdiagnosis

Atypical autism presentations (not reported in the research or clinical knowledge) often lead to increased mental health issues and, subsequently, a diagnosis of other psychiatric conditions instead of autism (32:48). In fact, the speaker explains, autistic women often receive their diagnosis as the last in a series of mental health conditions, which is not the case for men (37:28). Borderline Personality Disorder (BPD) (aka emotion regulation disorder) is of particular concern for autistic women as the symptomology significantly overlaps with autism. Belcher describes a study that found 15% of patients attending a clinic for BPD fulfilled the criteria for autism (38:50). Such symptom overlap, coupled with the fact that BPD more often occurs in females, has created a clinical bias toward diagnosing BPD, leaving these individuals without the help and support they need (39:40). 

What needs to change:

To successfully support autistic women moving forward, Belcher says that clinicians need to have more awareness of different autism presentations and how the current tools may miss some cases or look like other conditions (41:38). Similarly, research must address the intersectionality among autistic adults. And finally, as a society, we need to help autistic people reduce the need to mask (42:55). Belcher gives thanks and acknowledgments before opening the question and answer session (45:10).  

Kaustubh Supekar, Ph.D., examines recent findings about gender/sex differences in autism phenotypes and brain organization. He highlights the underrepresentation of females in autism and underscores the need for a large-scale science approach. The speaker details contemporary research methods and outcomes which revealed gender differences in autism symptom presentation and structural and functional brain organization. Supekar provides study implications, discusses limitations, and outlines future research, diagnosis, and treatment priorities.

Learn more about our speaker Kaustubh Supekar, Ph.D. HERE
Take the knowledge quiz for this webinar HERE

In this webinar:

1:00 – Autism and gender heterogeneity
3:45 – Why are there fewer females with autism?
5:23 – Questions of interest and implications
7:15 – Why we know so little
9:40 – Large-scale science approach
12:40 – Question 1
14:00 – Findings and replication studies
17:25 – Study: Co-occurring conditions
19:10 – Age and gendered socio-ecological effects
19:53 – Interim summary
20:27 – Question 2
23:33 – Findings
25:10 – Study: Correlation of symptom presentation and brain structure
27:04 – Interim summary
29:30 – Question 3
32:00 – Clinical vs functional MRI
36:52 – Findings
37:25 – Major finding: Visual-spatial attention systems
38:15 – Robustness and specificity to autism
40:30 – Study: Functional organization patterns associated with RRB
42:02 – Interim summary
44:40 – Overall summary
46:53 – Limitations and priorities for future research
49:35 – Acknowledgments and Q & A

Autism is a highly heterogeneous neurodevelopmental disorder (1:00). Supekar discusses the skewed gender ratio of women to men (ratio of 1 to 4) in autism diagnoses and asserts that this lack of female representation is a key source of heterogeneity in autism symptom presentation, treatments, and research (2:20). He stresses the historical consistency of the sex/gender bias (7:15) and discusses why we know so little about behavioral symptoms and brain signatures of females with autism (4:00). Supekar presents the unanswered question of why there are fewer females with autism as a fundamental building block for the future of autism research and treatments (3:45). 

The speaker describes the large-scale science approach, which collects publicly available data from multiple studies, sites, languages, populations, and investigators (9:40). Such datasets provide large sample sizes, robust and replicable findings, and population variance (10:15). Supekar uses the large-scale science approach to address three research questions (12:04): 

1. What are the behavioral/symptom presentations of autism in females, and how do they differ from those in males (12:40)?

Supekar and his colleagues compared female and male clinical data (13:00) and found that girls with autism exhibit less severe restricted/repetitive behavior (RRB) than autistic boys (14:00). These findings have been replicated in multiple large-scale studies (15:20). The presenter outlines subsequent research on co-occurring conditions (17:25), which revealed a lower prevalence of ADHD and a higher prevalence of epilepsy in autistic females compared to males (18:03). He also describes evidence suggesting an influence of age and gendered socio-ecological contexts on symptom presentation in autistic females (19:10). Supekar states that these findings show significantly different phenotypes between autistic males and females where the female presentation is more nuanced (19:53). 

2. What is the structural organization of autistic brains in females, and how do they differ from those in males (20:27)? 

Researchers applied multivariate pattern analysis (MVPA) (22:18) to clinical and structural MRI data to assess gray matter volume maps. Their findings revealed that structural brain organization in females with autism is significantly different from that of autistic males, especially in brain regions belonging to the motor, language, and visual-motor systems (23:33). Supekar’s team subsequently correlated those brain regions with clinical scores and found a relationship between RRB domains and gray matter volume in girls with autism (25:10). The speaker suggests these results reveal gender discrepancies in autistic structural brain organization that are associated with significantly different sex/gender phenotypes (27:04). 

3. What is the functional organization of autistic brains in females, and how do they differ from those in males (29:30)?

Supekar and his colleagues used deep learning neural networks (33:16) to assess differences in clinical and functional MRIs in multiple brain regions (32:00). Despite the heterogeneity of the dataset, the model was consistently (86%) accurate in differentiating males and females with autism (36:28). Further, this study revealed sex/gender differences in brain systems associated with visual-spatial attention in autistic individuals (37:25). Such findings had never been recorded in autism literature before and have since been replicated in a fully-independent cohort (38:15). 

Brain regions showing differences were subsequently correlated with clinical scores, which revealed that regions belonging to motor systems predicted the severity of RRB in autistic females (40:30) but not in autistic males. Supekar asserts that these findings suggest the presence of domain-specific effects associated with RRB in females and some level of female protective effect (5:54) in those brain regions (41:35).

Supekar summarizes the research findings (44:40), noting that gender differences in autistic structural and functional brain organization significantly differed from normative sex differences (24:16; 39:20). He lists the implications of their results, including the need for sex-specific diagnostic instruments and treatments. The presenter outlines priorities for future research (46:53) before the question and answer session (50:12). 

Gregory Wallace, Ph.D., discusses eating-related behaviors in autism. He examines potential drivers of food neophobia and presents novel studies on the cognitive/behavioral correlates of eating in the absence of hunger (EAH). Wallace defines selective overeating as a new subtype of autism and details recent studies on taste perception and cortical taste pathways in ASD compared to typically developing groups. The presenter highlights limitations to current research and the need for longitudinal studies. Wallace closes with a Q&A discussing picky eating, GI difficulties, ASD and anorexia, and more.

The presenter’s slides are online HERE (English)
Learn more about our speaker Gregory Wallace, Ph.D. HERE
Take the knowledge quiz for this webinar HERE

A Spanish translation of this webinar will be available at a later date.

In this webinar: 

2:50 – Why study eating in ASD?
4:00 – Nutritional intake and focus on exercise
5:00 – Appetitive traits
5:40 – Food neophobia and “picky” eating is autism
8:15 – Studies: Food neophobia in ASD during childhood & FN in adolescents and adults with autism
9:18 – Study: Possible underpinnings of food selectivity
11:40 – Clinical significance and ARFID
12:38 – Summary of findings
14:10 – Eating in the absence of hunger in autism
15:00 – Study: Cognitive/behavioral correlates of EAH in ASD
17:55 – Study: Relationship between EAH and BMI in children with ASD
21:18 – Summary of findings
25:56 – Selective overeating in autism – a new subtype & study
28:50 – Study – Infrequency of food type consumption by eating subtype in children with ASD
29:53 – Neural correlates of eating-related behaviors in ASD
31:13 – Study: Taste perception in autism
33:37 – Cortical taste pathway explanation
37:02 – Study: fMRI self-report and gustatory mapping
41:24 – Summary of findings
42:50 – Presentation summary, study limitations, and links to more information
45:16 – Q & A

Suboptimal health outcomes are common in individuals with autism. Studies have found an increased risk for obesity, high cholesterol, hypertension, and diabetes in individuals with ASD compared to the general population (2:50). Wallace discusses diminished nutritional intake (4:00), hyperfocus on exercise (4:10), and appetitive traits as contributors to poor health outcomes. Food neophobia (FN), or a fear of trying new foods, is a common and seemingly adaptive appetitive trait of early eating that generally diminishes across child development (5:40). However, FN and other selective eating symptoms often persist into adulthood in autistic individuals and interfere with everyday function (7:20). 

Wallace examines sensory processing differences and behavioral/cognitive inflexibility as potential drivers of persistent selective eating in autism (9:18). He presents studies on the possible causes of food selectivity (9:50) and the clinical significance of Avoidant Restrictive Food Intake Disorder (ARFID) in autism (11:40). Other selective eating symptoms like eating in the absence of hunger (EAH) are scarcely studied in ASD (14:10). The speaker outlines two new studies that assess the relationship between EAH and 1) cognitive/behavioral correlates in ASD (15:00) and 2) body mass index (BMI) (17:55). Findings reveal that EAH is positively associated with behavioral inflexibility and BMI and that EAH is more prevalent in individuals with ASD than the general population (21:18).  

The speaker defines selective overeating (a new autism subtype) as the co-occurrence of picky eating and overeating (25:56). A novel study using parent ratings of autistic versus typically developing children found a greater number of children with ASD linked to selective eating and selective overeating. Further, Wallace explains, autistic children with EAH had significantly higher rates of selective eating than children without EAH (26:00). Combining these findings with those of the first two studies, Wallace asserts that increased behavioral inflexibility is most elevated for individuals who engage in selective overeating (28:50). 

Individuals with autism have divergent sensory processing experiences across all sensory systems. Therefore, Wallace states, taste perception/processing is a prime candidate for assessing neural correlates related to eating behaviors (30:20). Multiple studies suggest that while individuals with ASD can perceive taste, they struggle with taste identification or sensory integration (31:13). The speaker defines sensory integration difficulties as a cortical issue and briefly describes the cortical taste pathway (33:37) and using functional magnetic resonance imaging (fMRI) to assess brain blood flow in response to stimuli (34:33). Wallace outlines a 2018 study using gustatory mapping (fMRI) (37:45) and self-reports (37:02) to assess (35:50) response to tastants (taste samples) in the gustatory cortex and their relation to self-reported taste reactivity in autism. 

Researchers found no differences in neural response to tastants between ASD and typically developing age-matched groups (39:15). They also found no association between self-rated taste reactivity and brain response to sweet tastants in the neurotypical group. However, autistic individuals who self-rated as highly taste-reactive showed a strong positive relationship with gustatory response to the sweet tastants relative to the neutral flavor (40:13). Wallace explains that although there is no evidence of overall atypical gustatory cortical function in ASD, findings suggest that individual differences in self-rated taste reactivity modulate activity in the gustatory cortex. The speaker posits that these findings also suggest atypical brain functions for individuals with autism and food selectivity that could impact BMI through diet variation (41:24). 

Wallace summarizes his presentation, noting that more work is needed to establish longitudinal relationships between eating-related behaviors, their causes, and their outcomes. He touches on the need for more interventions for food-related behaviors to improve physical health and overall quality of life for individuals with autism (42:50). Wallace discusses the limitations of the presented studies (43:50) and provides links to more information (44:50) before the question and answer session (45:16). 

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. 

Learn more about our speaker HERE
Take the knowledge quiz for this presentation HERE

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!