Connie Kasari, PhD, details what contemporary research reveals about supporting non-speaking or minimally verbal autistic children. She highlights how far the field has come in the past two decades and emphasizes the need for contemporary research to focus on what strategies benefit whom and why. The speaker discusses JASPER, a modular intervention based on social communication. She outlines recent studies and video examples showing positive language outcomes for JASPER on its own and in tandem with other interventions. Kasari underscores the usefulness of AAC devices in spoken language development, noting the lack of interventions that use even low-tech augmentative supports. The speaker summarizes her presentation and focus for future research before the Q&A.

Handouts are online HERE

In this webinar

2:00 – Early intervention in autism
7:00 – Core challenges: Video
14:16 – Study: JASPER intervention outcomes
26:00 – Intervention trajectories
31:50 – Study: Intervention combinations and AAC
36:11 – Implications for practice
45:45 – AAC case studies
46:45 – Summary
48:00 – Q&A

Early intervention and social communication

Kasari explains that nearly all autistic children will require support/intervention on engagement, imitation, joint attention, and play (2:00). She states that the goal of early intervention is to reduce the number of autistic children who have significant language impairment by the time they start school. Language ability remains one of the strongest predictors of positive long-term outcomes, making support strategies that target social communication skills—such as joint attention, engagement, and play—especially critical (4:00). Importantly, Kasari notes that research hasn’t focused on for whom an intervention works or why a particular intervention provides benefit for certain people. Understanding this is critical to expanding care and assessment across the board (5:30).

The speaker discusses core challenges that may trigger an intervention and shows videos comparing social communication in an autistic and a non-autistic child at 18 months old. Kasari highlights differences between the videos, noting the child with autism is more interested in looking at the objects than communicating (7:00). She explains how this pattern often translates to parent play, making it feel frustrating or not enjoyable for many parents/caregivers, and discusses two video examples of this (9:30).

Social Communication Research

The speaker says we know the least about children who are most delayed in development, who have limited language skills, and those whose families have less access to information about studies in their communities. She explains that most autistic children have never been in a research study. As a result, our evidence base does not represent the entire spectrum of autism (13:15). Kasari and her team focus on researching interventions for non-speaking and minimally verbal autistic children that can be conducted in community settings.

JASPER: Joint Attention, Symbolic Play, Engagement, and Regulation

The presenter describes JASPER, a comprehensive social communication/language intervention that can float inside other interventions, be used on its own or used sequentially (14:60). Kasari presents one of her recent publications comparing outcomes in 164 children, 3 -5 years old, across three sites after four months receiving Discrete Trial Training (DTT) or JASPER (video examples) (19:00). Results from the study show that both groups made significant language gains, and 45% moved toward phrased speech (putting words together).

Intervention trajectories

The goal of the intervention was to avoid the label of minimally verbal or profound autism by school age. Kasari defines profound autism as children with a developmental quotient (DQ) below 50, aged 8 or older, with poor adaptive skills (often minimally verbal or non-speaking). She notes that this is a relatively new term and considers how early we can predict these outcomes (26:00). The speaker reviews DQ data for a group of 264 children at very young ages. By age 8, 47% did not meet criteria for profound autism, although 25% of this group had a DQ lower than 50 at age 4 (28:30).

Kasari summarizes study takeaways, noting that DQ can help predict later development but is not a perfect predictor on its own. She reiterates the importance of early intervention and highlights understanding the 25% who moved off trajectory as a critical next step (29:25).

Combination interventions and assistive technology (AAC)

The presenter reiterates the heterogeneity in response to interventions, underscoring the need to personalize, tailor, and target interventions according to each person. This will also help us address for whom the intervention works and why. Kasari defines adaptive intervention designs as a sequence of decision rules that specify whether, how, when (timing), and based on which measures, to alter the dosage (duration, frequency, or amount), type, or delivery of treatment(s) at decision stages in the course of care – this is what her group employs (29:45).

Kasari details a study with 61 children, 5-8 years old, who are minimally verbal and had received 2 years of intensive early intervention (most ABA). All children received JASPER plus EMT, a spoken language intervention. Half of the children were randomized to receive AAC devices to test if these supports help with spoken language. Children attended two sessions per week, and at the 12-week follow-up, those assessed as slow responders were re-randomized to either add AAC or to up to 3 sessions per week. Outcomes for socially communicative utterances were assessed after another 12 weeks (31:50). Those who used AAC devices from the beginning showed significant increases and also had more novel words and joint attention language. Those with only JASPER and EMT made slow but steady progress. Researchers also found that from entry to midpoint to exit, parent-initiated engagement stayed the same while child-initiated engagement increased (34:15).

Implications for practice

The speaker notes that assistive technology are still not used regularly with children, be it a device, sign language, or another low-tech augmentative device; they are not being used as much as they should (36:11). Kasari returns to the child from the first video and describes how they changed tactics the second day by lowering the play level and adding an AAC device with button-words (video provided) (40:00). She notes that this child entered regular education at age 7, speaking full sentences. He used the AAC for a few years as a transition to spoken language. The presenter describes another case in which a child used AAC to support communication. He made progress over time, eventually asking the therapist to put phrases that he hears in the AAC device so he can listen to them and learn the sounds. In a follow-up video, the child is speaking in full sentences (45:45).

Kasari summarizes her presentation, highlighting that we can improve social communication and language outcomes for delayed autistic children and that these early skills need to be direct targets for support/intervention strategies. She reiterates how research must inform practice and, therefore, focus on answering questions about personalized interventions (how long do we wait, what do we change to?) (46:45) before the Q&A (48:00).

Dr. Jennifer Frankovich reviews what we know about the underlying mechanisms, trajectories, and symptoms of Pediatric Acute Neuropsychiatric Syndrome (PANS). She discusses the role of the Basal Ganglia in PANS symptoms and cites contemporary research that highlights this connection. Frankovich touches on the disruption of the blood-brain barrier and auto-antibody regulation in PANS. 

Playback of Dr. Mondal’s presentation and Dr. Hussein’s presentation will be available at a future date.

In this webinar:

1:30 – PANS/PANDAS overview
3:10 – Underlying mechanisms
5:00 – Common symptoms
7:55 – PANS trajectories
9:35 – Basal Ganglia
13:12 – Antibodies and the blood-brain barrier

PANS/PANDAS

Frankovich outlines Pediatric Acute Neuropsychiatric Syndrome (PANS) and Pediatric Acute Neuropsychiatric Disorders Associated with Strep (PANDAS), underscoring the different triggers attributed to both conditions (1:30). Classification criteria for both PANS and PANDAS include a sudden onset of obsessive-compulsive disorder or eating restrictions along with at least two other co-occurring conditions like anxiety, sensory dysregulation, motor abnormalities, developmental regression, and deterioration of cognitive functioning (2:15). 

Underlying mechanisms

Children with PANS-related symptoms often have some form of immune predisposition. The speaker explains that PANS occurs after a person gets an infection, which, due to predisposition, causes a systemic inflammatory response. She notes that these inflammatory responses may lead to Basal Ganglia inflammation, altered neuronal signaling, microbial activation, and more (3:10). 

Common symptoms

The presenter describes classic PANS experiences, such as swelling in the knees, hips, and heel bones, back pain and inflammation, and evidence of psoriasis. She explains that children who experience their first case between the ages of five and ten will likely have arthritis by the time they are 14 (5:00). Frankovich highlights our bodies’ abilities to self-regulate inflammation, noting that in many cases, PANS symptoms are resolved on their own (7:15). 

PANS Trajectories

There are generally four different trajectories for PANS:

• Relapsing and remitting – returning to the same baseline
• Relapsing and remitting – worsening baseline across time
• Primary persistent – no return to baseline, remains in chronic episode
• Secondary persistent – multiple episodes with increasing baseline until it reaches a chronic episode. 

Frankovich asserts that the primary and secondary persistent trajectories are likely more related to autoimmune predispositions than the others. Therefore, she continues, these trajectories require the most intense treatments and assessments (7:55). 

Basal Ganglia

The Basal Ganglia (BG), a group of nuclei located beneath the cerebral cortex, has an inhibitory influence on motor and behavior systems. The speaker notes that inflammation, autoantibodies, and injury can disrupt the BG, affecting movements, mood, emotion, behavior, procedural learning, and cognition (9:35). 

Frankovich briefly presents four brain imaging studies suggesting BG inflammation in PANS. She also discusses three studies indicating that patients experience abnormal movements during REM sleep cycles. These REM movements predict Parkinson’s in adults, making this a critical area of research and care (10:25). 

Other physical signs of BG disruption include specific tongue and mouth movements. For example, a positive glabellar tap reflex is present in children with PANS, though it should disappear after infancy. Other abnormal tongue movements, like milkmaid grip, are discussed (11:55). The speaker notes that between 80 and 92% of patients in her clinic exhibit at least one sign of BG disruption (12:25).

19% of autistic youth also have a positive glabellar tap, and 27% have milkmaid grip tongue movements. The presenter, therefore, asserts that these BG signs are not unique to PANS and should be investigated carefully across groups (12:38). 

Antibodies and the blood-brain barrier

PANS autoantibodies target interneurons and have been found in healthy kids and children with PANDAS. Frankovich explains that if these antibodies are causing problems in the body, it is because they are crossing the blood-brain barrier (BBB) (13:12). She highlights that current research suggests local disruptions to the BBB are associated with PANS symptoms (13:50).

Originally published on June 14, 2024

Dr. Waizbard-Bartov discusses changes in autism symptoms across childhood. She outlines the Autism Phenome Project and study methods for her recent work. The speaker presents findings on the frequency, patterns, and predictors of symptom severity changes across childhood periods in autism. Waizbard-Bartov touches on the intersection of autism symptom severity, assigned sex, and environmental factors. She summarizes presentation findings and considers pathways of future research before the Q&A. 

In this webinar:

1:09 – What is autism
5:00 – Social communication and RRB
12:06 – Autism Phenome Project
16:15 – Study methods
20:15 – Changes in autism symptom severity across childhood
24:30 – Variations in patterns of symptom change
28:05 – Predictors of changes in severity across childhood
30:25 – Sex differences
35:40 – Adaptive function
37:44 – Parental characteristics
39:10 – Co-occurring mental health conditions

What is autism?

Waizbard-Bartov describes autism as a neurodevelopmental condition broadly defined by difficulties with social communication and restrictive, repetitive behaviors (RRB) (1:09). For an autism assessment, social communication differences are subcategorized into social-emotional behavior, atypical nonverbal social behavior, and difficulty creating and maintaining relationships (2:15). RRBs are also subcategorized into stereotyped repetitive speech or actions, excessive adherence to non-functional routines, restricted/fixated interests, and atypical sensory behaviors (4:19). The speaker draws on her time working with preschoolers to illustrate how core characteristics/symptoms of autism range in presentation and severity across individuals and time (8:00). 

Study methods

The presenter outlines the Autism Phenome Project (APP), a longitudinal study of nearly 700 autistic and non-autistic children across five time points from early childhood to early adulthood (12:06). At each time point, the ongoing study assesses blood, MRI, language development, memory and attention, co-occurring conditions, and parental perspectives (14:20). Waizbard-Bartov describes her recent work on autism symptom trajectories across early (ages 3 – 6) and middle childhood (ages 6 – 11.5) (11:25). Her team used APP data for 183 autistic children (30% female-presenting) at three times points: between ages two and three and a half (2 – 3.5 yrs), between ages four and six (4 – 6 yrs), and again between ages nine and twelve (9 – 12 yrs) (16:15). Researchers used the calibrated severity scores from the Autism Diagnostic Observation Schedule (ADOS) to track symptom severity across time and domains (17:50). 

Q1: How common is change in autism symptom severity across childhood?

Researchers divided children into three groups based on observed changes in symptom severity across the first two time points (early childhood; ages 3 – 6). Of these, 54% remained stable, 29% significantly decreased, and 17% increased dramatically in symptom severity across early childhood (20:15). Correlations between behaviors and brain development were also found, where children with increased severity had slower white matter development compared to those with decreased symptom severity (21:43). When assessments were extended to the third time point (middle childhood; around age 11.5), the same three groups were identified, where 49% remained stable, 27% experienced a consistent decrease, and 24% experienced a consistent increase in symptom severity (22:55). Waizbard-Bartov reiterates that about half of children in the study demonstrated changes in severity across early and middle childhood, suggesting that such changes may be expected in autism (24:00). 

Q2: Do patterns of change vary across periods of childhood?

To understand patterns of symptom change across time, the presenter and her team compared early childhood severity changes to those of middle childhood (third time point). Results showed increases in symptom severity are equally as likely to occur during early and middle childhood, while decreases in severity are significantly more likely to occur in early childhood only (24:30). Researchers also found that more than 60% of the sample showed different patterns of change across childhood periods (i.e., decreased in early childhood and stable or increasing during middle childhood) (25:35). Waizbard-Bartov summarizes these findings, asserting that patterns of severity change across periods of childhood in autism (27:15). 

Q3: What predicts directional changes in symptoms across childhood?

To assess predictors of symptom severity changes in autism, Waizbard-Bartov and her team assessed related variables:

Cognitive ability/IQ

Results showed that children with decreased severity in early childhood had a higher IQ at the first two time points and exhibited IQ gains over time (28:45). Comparatively, those with increased severity had lower IQ at both time points that remained stable across time (29:30). The speaker asserts that these findings suggest a strong association between cognitive abilities and symptom severity during early development. 

Sex differences

Researchers found in female-presenting participants, symptom severity is likely to decrease or remain stable. However, for male-presenting participants, increases and decreases in severity are equally likely to occur (30:25). Further, calibrated severity scores revealed that female-presenting individuals show significant severity decreases in total symptoms and, more specifically, in RRB, especially during middle school. Conversely, male-presenting individuals show stable total symptom and RRB scores across childhood (31:15). The presenter discusses sex-compared changes across ADOS items, highlighting the stark trajectory differences between sex groups (33:15).  

Adaptive function

Adaptive functioning is meaningful for everyday life, and all three groups had the same score at age one. However, by age six, those experiencing decreases in severity had significantly higher adaptive functioning than those with increasing severity (35:40). The presenter explains how those with increasing severity did not necessarily lose adaptive function skills but that their rate of progress steadily slowed over time (36:40). 

Parental characteristics

Waizbard-Bartov and her team also found that fathers and mothers of children with decreasing severity were generally older and more educated. Contrastingly, parents of children with increasing severity were younger and less educated. The speaker notes the intersectionality of education and socioeconomic status and its impact on resource accessibility and self-advocacy (37:44). 

Co-occurring mental health conditions

Results showed a significant correlation between aspects of mental health and autism symptom domains (39:10). For example, 21% of participants had significant increases in both the severity of social communication issues and anxiety as they entered elementary school. ADHD levels also rose across middle school, and by age eleven, 84% of participants met the clinical requirements for an anxiety disorder (41:25). In female-presenting participants, improvements in RRB overtime ran parallel to increases in anxiety, where 94% had clinical anxiety disorders by age eleven (44:26). Waizbard-Bartov and her team found no evidence that initial symptom severity can predict changes across childhood, meaning everyone has the same potential for change (45:05). The presenter summarizes the findings for question three, noting that severity changes are correlated with assigned sex, IQ, adaptive functioning, parental characteristics, and mental health conditions (46:45).

• Trajectories of Autism Symptom Severity Change During Early Childhood (Waizbard-Bartov et al., 2021)
• Identifying autism symptom severity trajectories across childhood (Waizbard-Bartov et al., 2022)
• Changes in the severity of autism symptom domains are related to mental health challenges during middle childhood (Waizbard-Bartov et al., 2023)

Conclusion

Waizbard-Bartov summarizes research findings, underscoring that the severity of autism symptoms can change substantially across childhood periods and that patterns of change are not linear. She highlights that a child’s characteristics and environment can predict directional changes and that children have the potential for different severity trajectories regardless of their initial levels (47:55). 

She outlines future research directions, including how severity is affected during adolescence and how interactions between symptom severity and other characteristics play out over time (49:15). The presenter highlights current research around the impact of sex on symptom severity, underscoring the potential effects of camouflaging specific to female-presenting individuals (51:10). The speaker provides thanks and acknowledgments before the Q&A (53:25). 

Originally published on May 15, 2024