A summary of the recent evidence, by Thomas Frazier, PhD and Stelios Georgiades, PhD.


Stelios Georgiades, PhD

Some family members of people with ASD often share many autism traits, but don’t have or show the number or severity of symptoms needed to be diagnosed. A recent study using the Interactive Autism Network looked at some features of autism in over 5500 individuals, some with multiple siblings with autism, some only one sibling. They wanted to determine if number of siblings with autism or sex of the sibling with autism influenced how these symptoms presented, if at all.

What did the researchers do?

Frazier_Thomas_724336 headshot

Thomas Frazier, PhD

When a family enrolls in the Interactive Autism Network not only do they enter in information about the person diagnosed with autism, they also fill out a form called the Social Responsiveness Scale on all family members. This is a quantitative measure of autism traits. Instead of saying autism: yes-or-no, the scale gives a number that corresponds to the presentation of features. It is used in people with autism, but has also been used to study features of autism of those without a diagnosis. Some people have higher levels than others but most people score around the middle.   The higher the number, the more features of autism that person exhibits. In this study, the analysis consisted of 5515 brothers and sisters, 2858 with ASD and 2657 without ASD. They looked at how autism symptoms occur in male-only ASD-affected families vs. female-only affected families or in families with single vs. multiple cases of ASD. They also looked at the siblings of ASD children who did not have the condition but who had language delay or speech patterns usually seen in children with ASD. The sex of the siblings was also taken into account in the analysis.

What did the researchers find?

The research found that

  • the non-ASD brothers and sisters (siblings) of children with ASD were more likely to show higher levels of symptoms if they were many members of their family with ASD,
  • the non-ASD boys in these families were more likely to have a higher number of symptoms, as were boys with language delay or speech patterns usually seen in children with ASD,
  • the children with ASD in families with several members with ASD had lower levels of symptoms than did the ASD children if they were the only child in the family with the condition, and
  • the likelihood of having more than one child with ASD in a family was higher if that family had female members with ASD, and
  • it is likely that girls need a much greater number of the genes related to ASD to produce the symptoms needed to warrant a diagnosis of ASD.

 What does this mean?

Both the sex and the number of children with ASD in a family strongly influence the risk of their non-ASD siblings having a high number of autism symptoms.  This again, links genetics to the causes of autism. These preliminary data suggest that siblings from certain families may have a higher likelihood of having children with ASD, but it is too early to base any family planning decisions on this data. It also emphasizes that girls have a higher genetic load, and that girls may be in some way, protected against some symptoms of autism.



Frazier TWYoungstrom EAHardan AYGeorgiades SConstantino JNEng C. (2015)  Quantitative autism patterns recapitulate differential mechanisms of genetic transmission in single and multiple incidence families.  Molecular Autism, 6:58.  Full text here:  http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4623917/

A new study published this month in the Journal of Developmental and Behavioral Pediatrics confirms current belief that many children with Autism also have Apraxia of Speech.

Cheryl Tierney, MD, MPH of Penn State University, Susan Meyes, PhD and others investigated the efficacy of the Checklist for Autism Spectrum Disorder (CASD), a screening tool developed to determine if children should undergo complete diagnostic testing for autism (1). The researchers found that the screening tool does effectively indicate which children are at risk for autism, but they also came to another interesting conclusion (2).

Intervention approaches for autism and apraxia address different features of communication, therefore, it is important for clinicians to be aware that kids with autism may have undiagnosed apraxia of speech as well.

Intervention approaches for autism and apraxia address different features of communication, therefore, it is important for clinicians to be aware that kids with autism may have undiagnosed apraxia of speech as well.

Autism spectrum disorders are diagnosed by neuropsychologists and developmental-behavioral pediatricians. Language impairments present in autism are partially characterized by difficulties with taking the perspective of another person, with  non-literal language and with appropriately maintaining a topic (3).

Apraxia of Speech, however, is typically diagnosed by a speech-language pathologist, and is characterized by difficulty coordinating volitional motor movements required for clear and intelligible speech.

While autism and apraxia clearly have different features, a child with autism who has profound language delays such that he or she is minimally verbal or non-verbal may have undiagnosed childhood apraxia of speech, masked by his or her language deficits.

The study concluded that “autism and apraxia are highly comorbid. Thus, it is important to monitor all children diagnosed with apraxia for signs of autism and all children diagnosed with autism for signs of apraxia. This will help identify children as early as possible and allow them access to services appropriate to their needs.”

In evaluating children with autism, speech-language pathologists should rule out apraxia of speech. In requesting services or evaluations for their children, parents should also consider the intelligibility of any language the child may produce.

This post was authored by Stephanie Millman-Dorsch, ASF’s Community Relations Manager. Stephanie is a Master’s of Science Candidate in Communicative Sciences and Disorders at NYU, expecting to graduate this December.

NB: Dr. Mayes, who co-authored the study, is the primary developer of the CASD

(1) CASD: Mayes, S. (2015). Checklist for Autism Spectrum Discorder (CASD). Retrieved October 23, 2015.

(2) Tierney, C., Mayes, S., Lohs, S. R., Black, A., Gisin, E., & Veglia, M. (2015). How Valid Is the Checklist for Autism Spectrum Disorder When a Child Has Apraxia of Speech?. Journal of Developmental & Behavioral Pediatrics36(8), 569-574.

(3) DSM-5: American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.).

Manuel Casanova, PhD, University of South Carolina

Manuel Casanova, PhD, University of South Carolina

Steven Chance, PhD, University of Oxford

Steven Chance, PhD, University of Oxford

Studies using brain tissues have revealed brain cells in the area called the cerebral cortex are organized in a specific way called “minicolumns”. In people with autism, this organization is different than those without autism. This has led scientists to ask what these columns do and how is it related to autism symptoms?

We asked two of the worlds leading researchers, Steven Chance of Oxford University and Manny Casanova at the University of South Carolina, who have studied the brains of people with autism, to weigh in on this topic. Specifically, we interviewed them to explain how the minicolumnar findings have impacted the field of autism research and led to discoveries that are important for families.


So, what is a cortical minicolumn and what do they do?

Steven Chance:  There are cells in the cerebral cortex that are arranged in columns. These ‘mini’-columns of cells are typically about one third the width of a human hair. In the typically developed brain, wider minicolumns seem to be associated with processing more individual features of incoming information.

Manny Casanova:  Minicolumns are a basic template that is used by neurons to figure out where neurons should go and where they should connect. They also help process the connections of different brain cells. Some people think of minicolumns as the microprocessor of a computer. Indeed, Vernon Mountcastle thoughtof minicolumns as the basic unit of information processing in the brain. More recent experiments have proven that these minicolumns help people to think and to act.

How are they different in people with autism?

Steven Chance: In ASD these minicolumns are between 5% and 10% wider than in those without autism. . This difference may not sound like much, but multiplied over hundreds of thousands of minicolumns throughout the brain it may contribute to a significant difference in brain organization. In addition to cognition and thinking like Manny Casanova pointed out, our lab has recently found these minicolumns in brain areas involved in basic sound and word processing, as well as in areas involved in complex social behavior.

Manny Casanova: Yes, minicolumns affect different aspects of behaviour. We have also found variability in the size of mini columns according to brain area. These changes are consistent with other neuropathological findings and indicate that the minicolumnopathy of autism is part of a process called cortical dysplasia. The presence of cortical dysplasia provides an explanation for intractable seizures and sensory abnormalities commonly observed in ASD. The pathology may be selective as to whom it affects as, on occasion, involved individuals have either a specific genetic or immunological profile.

What does this mean for people with autism?

Steven Chance: The differences in width and spacing of the minicolumns means that they may become too independent and overly focused on individual features in the environment.  This may explain the altered cognitive style or focus in many people with autism, and possibly explain the strengths of some people with autism in certain situations.

Manny Casanova: The findings help explain many of the symptoms observed in ASD. We are using the findings to provide new ways for screening for diagnosis, to provide for severity dependent outcome measures that do not rely on behavioral screening, and to introduce a possible therapeutic intervention.

Larger or smaller, what is it?

Steven Chance: The findings depend on the age of the individual. In other words, when the data from studies are compared while accounting for subject age, they suggest that minicolumns are wider in youth in autism but then become narrower in later life. This is interesting because it is consistent across the studies and reinforces tha autism as a developmental condition which changes across the lifespan. It also makes sense in the light of other MRI studies which have shown larger brains in ASD in early life, followed by a loss of this enlargement later on.

Manny Casanova: It may be that the age-related changes in the minicolumnopathy of autism may constitute an adaptive response meant to correct early changes in the cortex; or or it could be the beginning of a neurodegenerative process whose manifestation may appear later on in life.  We don’t know, we need more research using brains of people with autism at all ages and abilities.

These questions can only be answered with more brain tissue from individuals across the lifespan. You can help with the discoveries. Register to donate your amazing brain when you don’t need it anymore by going to www.takesbrains.org.


ASF accelerator grant awardee, Jennifer Foss-Feig, PhD

2015 ASF accelerator grant awardee, Jennifer Foss-Feig, PhD

“If you’ve met one person with autism, then you’ve met one person with autism.” This adage has become often-repeated in the autism community. It speaks to the uniqueness of each individual with autism and to the fact that no individual can be captured or fully described by his or her diagnosis. At the same time, it reflects what has become one of the greatest challenges facing autism science: variability in symptoms across people diagnosed with autism, otherwise known as heterogeneity. No one feature is reliably seen in every individual with autism, and any research sample can reflect only a subset of the diverse individuals who fall along the autism spectrum. In the latest diagnostic manual of the APA, a new, broader diagnostic category – Autism Spectrum Disorder (ASD) – replaced the categories we had all become familiar with: Autistic Disorder, Asperger’s, and PDD-NOS. For my colleagues at the Yale Child Study Center and I, the new DSM-5 umbrella “ASD” category opened the door for developing novel ways of conceptualizing and clustering heterogeneity among ASD features.


In a commentary published in the Journal of Autism and Developmental Disorders1 this month, we suggest a new way to consider autism symptoms. Borrowing concepts from the schizophrenia literature, we propose a new framework within which ASD-related features can be categorized. We introduce the idea of positive, negative, and cognitive feature clusters as a novel way to conceptualize ASD symptoms. Positive features include behaviors not present in typical development, but present in ASD, such as circumscribed interests or stereotyped motor movements. The negative feature dimension captures behaviors that are present in typical development, but delayed, deficient, or absent in some individuals with ASD, such as eye contact, social engagement, and spoken language. Finally, the cognitive dimension reflects patterns of thinking, behavior, and relating that are cognitively-driven and common among individuals with ASD, such as rigidity of thinking and difficulty with switching between tasks. These categories cut across social-communication and repetitive behavior domains that are currently the primary means of clustering symptoms in the DSM-5, which translates to how ASD is thought of and its features are grouped in both clinic and research settings. It may be easier to conceptualize this by looking at the table below.


DSM-5 Social Communication


DSM-5 Restricted/Repetitive Behaviors
Positive Features Intrusive social initiatives; Exaggerated prosody or intonation of speech; Pronoun reversal Echolalia and stereotyped speech; Repetitive use of objects;

Repetitive hand mannerisms

Negative Features Difficulty with conversation; Lack of pointing; Reduced eye contact and range of facial expressions Non-functional play with toys; Narrowed range of interests;

Lack of imagination

Cognitive Features Difficulties with theory of mind and taking another’s perspective; Difficulty with non-literal language Insistence on sameness;

Rigid adherence to routines;

Black-and-white thinking


In this way, we offer new ways to conceptualize and organize hallmark symptoms of ASD. In addition, this way of thinking offers an opportunity to describe specific characteristics with new precision. For example, instead of indicating a child has “atypical facial expressions,” the new dimensions would allow separating of children who have exaggerated affect from others who show limited range of facial expressions.


In schizophrenia, the notion of positive, negative, and cognitive feature clusters has been quite useful to both clinical and research communities. In the clinic, assessing and labeling symptoms along these dimensions has been useful for deciding which medications to prescribe, predicting which patients will continue to struggle versus which will have quick remittance of symptoms, and identifying individuals in a “prodromal” phase before the onset of more acute symptoms. In the lab, this framework has been useful for clustering symptom dimensions in ways that correspond with experimental task performance and underlying brain differences. In other words, positive, negative, and cognitive symptom dimensions help researchers understand which underlying brain differences or cognitive and social processes are most affected in patients showing more positive versus more negative symptoms. This, in turn, provides clues to genetic underpinnings of different symptoms as well as new leads from which to develop treatments.


In the future, with further research, we hope to use what has been learned in schizophrenia and apply it to autism. It is our hope that the dimensions we propose offer new ways to capture and organize the heterogeneity that makes each individual with ASD unique in a way that makes us better able to talk about what we see, provide good clinical care, and solve the remaining puzzles of autism.


1 Foss-Feig, J. H., McPartland, J. C., Anticevic, A., & Wolf, J. (2015). Re-conceptualizing ASD Within a Dimensional Framework: Positive, Negative, and Cognitive Feature Clusters. Journal of Autism and Developmental Disorders, 1-10. http://link.springer.com/article/10.1007/s10803-015-2539-x



At a time when 1 in 68 children is diagnosed with autism, early identification, diagnosis and treatment is crucial to give children the best opportunity to reach their full potential. The ambiguity of the statement offered by the US Preventative Services Task Force (USPSTF) on autism screening is troubling and unfortunately, may be easily misinterpreted. While the task force does not explicitly recommend against screening for autism, they state there is insufficient evidence to support autism-specific screening in clinical settings. Instead, they have called for more research in this area.

As a result, the task force has failed to fully endorse screening despite an abundance of research that demonstrates it is effective in a variety of settings1-3, leads to earlier identification of autism4, and that this earlier identification provides opportunities for early intervention which improves the lives of children with autism5. Research has demonstrated that formal screening is more effective than relying on clinician judgement alone1,6. This is especially important in reducing racial and ethnic disparities in access to care7,8 Moreover, screening is quick, affordable and has no substantial risk. We intend to review the USPSTF report and its methodology to understand why it differs from other evidence-based recommendations from the American Academy of Pediatrics and from experts in the field of autism spectrum disorders. Every child deserves an early, accurate diagnosis and we are hopeful that after the review period the USPSTF reconsider their conclusions.  You can read more about the recommendations and response here.

There are a number of world renowned autism researchers who agree with this position.  They include:

The High Risk Baby Siblings Research Consortium (https://www.autismspeaks.org/science/science-news/bsrc-response-uspstf-call-more-research-universal-autism-screening)

Jill Harris, Children’s Specialized Hospital of NJ

Bryan King, Seattle Childrens Hospital

Ami Klin, Emory University

David Mandell, University of Pennsylvania

James McPartland, Yale University

Diana Robins, Drexel University

Celine Saulnier, Emory University

Amy Wetherby, Florida State University

  1. Robins DL. Screening for autism spectrum disorders in primary care settings. Autism : the international journal of research and practice. 2008;12(5):537-556.
  2. Miller JS, Gabrielsen T, Villalobos M, et al. The each child study: systematic screening for autism spectrum disorders in a pediatric setting. Pediatrics. 2011;127(5):866-871.
  3. Robins DL, Casagrande K, Barton M, Chen CM, Dumont-Mathieu T, Fein D. Validation of the modified checklist for Autism in toddlers, revised with follow-up (M-CHAT-R/F). Pediatrics. 2014;133(1):37-45.
  4. Herlihy LE, Brooks B, Dumont-Mathieu T, et al. Standardized screening facilitates timely diagnosis of autism spectrum disorders in a diverse sample of low-risk toddlers. Journal of developmental and behavioral pediatrics : JDBP. 2014;35(2):85-92.
  5. Pierce K, Carter C, Weinfeld M, et al. Detecting, studying, and treating autism early: the one-year well-baby check-up approach. The Journal of pediatrics. 2011;159(3):458-465 e451-456.
  6. Wetherby AM, Brosnan-Maddox S, Peace V, Newton L. Validation of the Infant-Toddler Checklist as a broadband screener for autism spectrum disorders from 9 to 24 months of age. Autism : the international journal of research and practice. 2008;12(5):487-511.
  7. Khowaja MK, Hazzard AP, Robins DL. Sociodemographic Barriers to Early Detection of Autism: Screening and Evaluation Using the M-CHAT, M-CHAT-R, and Follow-Up. Journal of autism and developmental disorders. 2015;45(6):1797-1808.
  8. Daniels AM, Halladay AK, Shih A, Elder LM, Dawson G. Approaches to enhancing the early detection of autism spectrum disorders: a systematic review of the literature. Journal of the American Academy of Child and Adolescent Psychiatry. 2014;53(2):141-152.

By Russell Port

While the symptoms of ASD are well known, the changes in the brain that cause these disorders still remain a mystery for scientists. In an attempt to understand the neurological differences of someone on the autism spectrum, scientists have looked at brains from multiple angles, from within single cells to how large parts of the brain communicate with each other.

The brain can be considered a series of circuits that connect different sub-types of cells; when properly aligned, these circuits allow for healthy neural activity (Figure 1). Due to the complexity of neural connections, multiple different types of alterations to cells can produce similar consequences in neural functioning, either through turning off activity or turning on activity so cells can talk to one another.  In fact, one of the many things that cause autism is an imbalance of too much activity vs. too little activity of brain cells during critical periods of development when brain cells rely on each other to develop.  This imbalance would affect the way neurons communicate.  One way communication is affected is with special brain waves as known as “gamma oscillatory activity”.  We see this in the clinic, where people with ASD exhibit less gamma-band activity in response to numerous stimuli, including faces, while more gamma-band activity at rest.

Figure 1

Screen Shot 2015-07-15 at 8.41.59 PM

Recently, we suggested a new approach to understanding these neural circuits (Port, Gandal, Roberts, Siegel, & Carlson, 2014).  This approach starts with parts of this neural circuit and progresses up to look at activity of the whole brain – translating findings found in an animal model up to people with autism.  In this article,  we suggest that brain waves are the ideal way to allow researchers to study a similar measure across different types of studies. For example, brain activity could be the common language the ties together animal model research with studies of treatments.  This translational approach is critical to understanding the potential role of genetic and cellular changes that are suggested by studies of ASD. In other words, by looking at brain waves reflecting core circuit function, whether by imaging voltage changes in brain slices, direct electrode recording, EEG or MEG, we see promise in integrating the multiple different insults seen in ASD into common circuit effects.

Being a pre-doctoral fellow for the ASF has helped support world-class mentorship in neuroscience research and began my career as an autism research scientist. I was given the opportunity to form a research project under the guidance of two mentors, both of whom are leaders in their respective fields. Together we have created a new research project that crosses back and forth between human and animal studies, letting the findings from one inform other. We are publishing work suggesting that neural circuits are potentially a key region of integration for all the different changes seen in ASD. By looking at the function of these neural circuits, we can study the same entity in animals as we measure in people with ASD. This approach is crucial to making sure that discoveries in the lab turn into treatments in a clinic.

Russell Port presenting at IMFAR

Russell Port presenting at IMFAR

  1. Port RG, Gandal MJ, Roberts TPL, Siegel SJ, Carlson GC. Convergence of circuit dysfunction in ASD: a common bridge between diverse genetic and environmental risk factors and common clinical electrophysiology. Frontiers in Cellular Neuroscience; Dec 8 2014. (8): 414.
Veronica Kang and her mentor Sara Jane Webb at IMFAR in May, 2015

Veronica Kang and her mentor Sara Jane Webb at IMFAR in May, 2015

In the summer 2014, I was fortunate to receive the Autism Science Foundation Undergraduate Summer Research Fellowship to work with Dr. Sara Jane Webb at the University of Washington. During my summer research, I was able to complete my honors thesis: A Study of Twins of Individuals with Autism: Heritability of Pragmatic Language Ability in Autism Spectrum Disorder. I was also involved in two other projects in the lab: one focusing on brain activity and genetics in girls with autism, and the other to identify a potential biomarker for treatment response in adults with ASD.

For my ASF research and honors thesis, I studied language in twins with and without autism and found that twins who both had ASD had more difficulty grammar and pronunciation compared to twin pairs where both did not have ASD. If one of the twins had ASD, their language ability was not as impaired, but still not to the levels seen in those without autism. Also, the better social communication skill in the twin with ASD predicted better language ability in his or her twin non ASD twin. These results show that the genetic determinants of language may be shared by social communication. It opens up new areas of study to look at social communication skills as a target of interventions for language. I presented these data (A Study of Siblings of Individuals with ASD: Comparison of Pragmatic Language Ability) as first author at the International Meeting for Autism Research in Salt Lake City in May 2015. I was also awarded, the University of Washington (UW) Undergraduate Research Conference Travel Award and the UW Psychology Honors Travel Award.

In June, I graduated with a B.S. in Psychology with Honors. I am currently working with Dr. Wendy Stone, also at the University of Washington. I will be primarily working on research projects that focus on early detection and intervention for children with autism. I hope to pursue a Ph.D. in Child Clinical Psychology in order to continue research on intervention for social communication skills in children with autism, and potentially incorporating EEG to look at the effectiveness of the intervention.

The ASF Undergraduate Summer Research Fellowship made a huge impact on my career. It opened the doorways to additional opportunities in research, and has advanced my professional goals.  The presentation, the travel award, and my direction in autism research would not have been possible at all without the support from ASF and the mentorship by Dr. Webb. I am very excited to contribute what I have learned from this experience. Thank you, ASF, for supporting my research, and thank you, Dr. Webb, for your sincere and continuous mentorship!


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