In this webinar: 

1:05 – New way of looking at autism
2:55 – Goals of autism research
4:17 –  Maternal Autoantibody Related Autism (MAR-ASD)
6:35 – Initial studies and findings
9:29 – MAR target proteins
13:24 – ADOS and SCQ
15:05 – Modifiable risk factors
16:03 – Pathogenic autoantibodies
17:05 – Passive transfer models
19:35 – Rhesus Monkeys – atypical social development and brain volume
20:57 – Maternal autoantibody model
21:00 – MAR antibodies localize in the brain
23:38 – MAR antibodies taken up into developing neurons
26:03 – Golgi strain of mature neurons
27:25 – Development of rodent model
31:32 – Clarity imaging of MAR-ASD offspring
33:43 – Video: decreased sociability in juvenile MAR-ASD mice
36:10 – Voice prints of MAR-ASD male mice
37:40 – Development of preclinical rat model
40:25 – Video: rat behavior
42:00 – Commonalities across models
42:35 – Conclusions
45:05 – Q&A

Summary

Over the last two decades, autism researchers have shifted focus to studying immune systems and their role in autism and development (1:05). Van de Water outlines Maternal Autoantibody Related Autism (MAR-ASD), a new subtype characterized by the maternal transfer of autoantibodies to the gestational immune environment (4:30). Autoantibodies are antibodies that mistakenly bind to self-proteins instead of foreign bodies (2:00). In MAR-ASD, autoantibodies cross the placenta and bind to targets in the developing brain, changing neuronal development. MAR-ASD cases make up 18-26% of autism diagnoses, and individuals in this subgroup have more severe behaviors, pronounced stereotypy, and significantly larger brain volume (6:11). 

Van de Water outlines the initial findings of a subset of mothers who produced anti-brain antibodies and have children with autism (7:00). She lists subsequent studies relating autoantibodies to autism behavior, genetics, animal models, and more (6:35). Eight MAR target proteins have been identified (9:25) as potential biomarkers associated with autism (100% accuracy) (12:55). Studies have also found that MAR+ children score significantly higher on the ADOS and SCQ compared to MAR- groups (13:24). Specifically, when the CRMP1 autoantibody is present, ADOS severity increases by 2.3 points. The speaker lists modifiable risk factors for mothers (15:05) and outlines her research approach to assessing whether these autoantibodies are pathogenic (16:00). 

She describes Passive Transfer models where human IgG reactive to target proteins are injected into an animal during pregnancy (17:04). A Rhesus Monkey study (17:18) found mothers to be overprotective, and offspring showed evidence of impaired social behaviors (18:10). The same study revealed that monkeys with MAR antibodies (LDH, STIP1, CRMP1) had larger brains (20:30). These findings replicate a previous brain volume study on human children with MAR-ASD (20:57), suggesting that these antibodies have some physiologic effect on brain development. 

A passive transfer rodent model of MAR-ASD found that autoantibodies localize to the brain during gestation and up to 12 hours after birth (21:00). Van de Water outlines similar findings that show MAR antibodies taken up into developing neurons (23:38) and change the way neurons mature (26:03). She describes the development of a MAR autism rodent model using active immunization before breeding (27:05) and discusses the lack of behavioral differences between males and females and the revealed relationship between brain size and severity of behaviors (29:00). A clarity imaging (3-D) study of postnatal mice brains found autoantibodies bound to target proteins inside dividing cells (31:32). 

The speaker presents video studies showing decreased sociability in juvenile MAR-ASD mice offspring compared to stimulus mice (33:43) and highlights the fact that these antibodies are causing differences in brain development and pathology (35:26). Similarly, MAR-ASD male mice recorded significantly smaller voice prints when first exposed to estrus (ready to breed) females compared to the control (36:10). Comparable studies conducted with rats (37:40) reported the same outcomes for social interaction, increased repetitive behaviors, and reduced vocalization (38:50). Dr. Van de Water highlights commonalities across the models presented (42:00) and summarizes the main findings (42:35). 

She emphasizes that gestational immune dysregulation may be an underlying mechanism linked to infections during pregnancy and that humans, mice, monkeys, and rats exposed to MAR autoantibodies all have enlarged brains. The presenter notes that rodent MAR-ASD models capture all three domains of autism (social, communication, and repetitive behavior) and that autoantibodies have structural effects on neurodevelopment and cerebral volume. Van de Water closes with a Q & A session where she discusses details of current studies and more (45:05). 

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Dr. Matthew D. Lerner, Ph.D., discusses social development in individuals with autism. He emphasizes understanding theoretical mechanisms that underly processes generally accepted as social “skills.” The presenter outlines recent findings and discusses their implication in treatments and personal understanding. Lerner highlights the importance of enabling individuals to create meaningful connections and relationships instead of focusing on how people act in social situations. He presents a new model for understanding social development in autism and closes with a question-and-answer session.  

In this presentation

2:50 – Background and outline
3:20 – How to understand social “skills” problems
5:30 – Why study adolescents with autism
10:00 – Story: I want to be a psychic
12:30 – Populations that may have social difficulties
15:00 – Mechanisms
16:08 – Social skills mechanisms
25:30 – Social knowledge
28:00 – Social cognition
32:12 – Insight/self-awareness
37:00 – Social motivation
39:54 – Social information processing
45:00 – Social creativity
47:42 – Quantity of social interaction
52:25 – New model for understanding social development in autism
54:30 – Practical/intervention implications and questions
56:30 – Q & A 

Summary

Lerner differentiates between social “skills” and theoretical mechanisms related to social engagement. He posits that we should consider how individuals present in social contexts and how theoretical mechanisms relate to social engagement (3:20). The presenter highlights that this is not a new idea – we understand pathways of medication in our bodies and the mechanisms they impact (15:20). Therefore, we can create more supportive and direct treatments when equivalent mechanical processes for social functioning are understood.  

Dr. Lerner emphasizes that treatments should aim to enhance individual abilities to create and maintain deep relationships instead of how individuals act in social situations (13:30). He outlines research on eight theoretical mechanisms generally understood as social skills. He defines each “skill,” outlines study methods and findings, and discusses their implication in treatments and research (16:08): 

Social knowledge (SK) 

Studies have found no correlation between the amount of SK and successful social interaction. Findings also revealed no significant difference in SK between individuals with autism and their neurotypical peers (25:30).  

Take home: Social knowledge may not be as important as we thought.

Social cognition (SC)

A digital multi-site study looking at aspects of social cognition across domains in individual patients showed slight variation between groups and significant variability within and between participants (28:00). 

Take home: Individual profiles matter in social cognition and treatment development.

Insight/self-awareness 

Multiple studies reveal that children with autism generally rate their own social skills considerably higher than their peers or parents/caretakers rate them (32:12). He defines positive illusory bias as it occurs in ADHD and notes its importance in building self-esteem (33:08). Lerner states that we need to focus on things individuals are doing well instead of the things they are not doing well enough.

Take home: Self-awareness may matter more than previously thought.

Social motivation (SM)

Studies have shown that children with autism and high SM generally have poorer emotion recognition (ER). In some cases, individuals are so motivated to interact that it overwhelms their ability to read the response of others (37:00). 

Take home: Social motivation is important – but complicated.

Social information processing (SIP)

EEG results show the speed of initial brain processing relates to better ER and a meta-analysis revealed the n170 blip (41:10) occurs between 30 – 50 milliseconds slower in individuals with autism (42:15). A third study revealed that individuals with and without autism can effectively decode emotional information (43:30). Therefore, treatments should make SIP mechanisms work well for individual patients. 

Take home: SIP is encoded but not always translated.

Social creativity (SC) ­– flexibility in thinking (opposite of social knowledge)

Survey and questionnaire studies reveal SC as one of the only mechanisms related to successful social interactions (47:42). Therefore, if we can find ways to promote SC, we could support more effective social interaction.

Take home: Social creativity is very promising.

Quantity of social interaction

Studies have found that individuals who can effectively read their own emotions engage in significantly more social situations (47:42). Therefore, Lerner posits that effective social interactions may naturally progress if practitioners aim to help individuals identify their own emotions. 

Take home message: Quantity of social interaction is not necessarily reduced in autism, and we should consider other factors.

Contextual variability

A recent study found that the ability to adjust behaviors in different social contexts may matter even more than symptom/behavior severity (50:33).  

Take home: Contextual variability is more important than symptom/behavior severity.

Lerner concludes by outlining a model for supporting effective social interactions in individuals with autism (52:25). He describes current research aims and objectives (54:30) before opening a question-and-answer session (56:30).