Females with autism show opposite neurobiological features of autism, while alsopossessing some of the same core features of ASD. In females, these differences may be foundinthe way symptoms present or in associated features of ASD.Lack of differentiationclouds important scientific discoveries, which is why treatments and services should besex specific.
Over the past five years, ASD research has increasingly focused more attention on identifying and understanding how autism manifests in females; this includes, but is not limited, to: genetic makeup, symptom presentation, long term trajectory and mental health issues. Females are diagnosed 4x less often but also have an increased load of genetic mutations, including recessive mutations47. This year, results of studies have been mixed in terms of the magnitude and nature of sex and gender related symptom presentation in males vs. females, noting a problem plaguing ASD research mentioned earlier: heterogeneity48. Differences across sex and gender are not seen in terms of presence or absence of symptoms, but rather in the way they present across different ages49,50. On the whole, differences are few in infants and toddlers but are magnified during adolescence, even in the way people perceive ASD symptoms in males and females51. Some scientists suggest that associated symptoms are most likely to present differently than core symptoms of ASD52, with females showing a higher prevalence of ADHD53and OCD, leading to differences in the way males and females appear.
In addition to findings of increased numbers of recessive mutations in the genome of females47, analysis of brain structure has revealed sex differences further suggestive of the female protective effect. Focused study of the cerebellum has revealed that female activation patterns oppose those of males with ASD 54and fail to evince similar patterns of connectivity across different brain regions55,56, i.e. females with ASD show reduced connectivity compared to females without ASD, an effect not seen in males with ASD55. In addition, when comparing twins, females had more profound differences in the sizes of brain regions compared to males57. These findings have led researchers to refine how they examine the role gender plays in basic science research.
Animal model research suggests that environmental exposures may not produce the same impairments in male vs. female offspring58. Taken together, these biological findings demonstrate that females, despite demonstrating a lower prevalence of ASD, also show complicated behavioral features and more biological markers for ASD. Future research must focus on why females are diagnosed less often than males and why, when they are diagnosed, they present more behavioral markers than their male counterparts.
Researchers have determined that of the over 100 autism genes that exist, all act on early developmental functions and lead to diverse, overlapping outcomes, including psychiatric disorders, autism, and related conditions. Some genetic influences, while rare, can help define the mechanisms that lead to brain cells in autism developing over time. Although a link has been established connecting environmental influences to this same spectrum of conditions, few studies have successfully defined their interaction. These findings have implications for interventions and could lead to strategies for mitigating symptoms.
Given the comorbidity of mental health disorders with autism spectrum disorder, it should come as no surprise that new research reveals that ASD relevant genes act in fundamental ways that may influence multiple outcomes, ranging from ASD to schizophrenia, to ADHD27-30, neurodevelopmental disorders and intellectual disability31-33. Genes that act on such early and fundamental brain pathways have downstream effects on a number of brain functions, ASD being one of them. This might explain why there are so many ASD genes and why they are pleiotropic, meaning they have different functions. In fact, the list of genes associated with ASD keeps growing, as larger studies and better technology have revealed over 150 ASD associated genes34. Infant siblings of children with autism also show rare and common gene variants in ASD genes that can aid in a diagnosis9.
In addition, the presence of certain genetic mutations in ASD relevant genes can produce profound disabilities, which alone work to explain an ASD diagnosis. These mutations, referred to as rare genetic variants, are important to the community because their discovery has led to the creation of Patient Advocacy Groups that provide support and resources for focused research, as well as offer pathways to better understanding the basic circuitry of certain ASD behaviors35. Scientists are studying these rare genetic forms of ASD to understand all forms of ASD, particularly gene expression in the brain36,37. When compared to studies of the brains of people with bipolar disorder and schizophrenia, studies of brain tissue in people with ASD reveal overlapping genetic activity in genes that control synaptic signaling, neurotransmitter release, and immune response.36,37. The abnormal immune signaling in the brain might result in cell damage, as evidenced by accumulation of T-cells in brain tissue38. Studying the brains of people with ASD is the best way to understand the basic cellular and molecular basis of ASD, and is only possible through families who decide at the most difficult time to make the decision to donate. If you would like to learn more about the Autism BrainNet, which made these studies possible, visit www.takesbrains.org/signup.
While genetic factors are incredibly important in the diagnosis and presentation of symptoms of ASD, understanding the role of environmental factors in both the diagnosis and presentation of symptoms of ASD is crucial. One of the most studied environmental factors in ASD is exposure to air pollution during pregnancy. This year, ancillary evidence taken from additional locations via different methodologies shows a particular effect for a component in air pollution called PM (particulate matter) 2.5 (2.5 microns)39. Air pollution exposure may interact with maternal diabetes, which also increases the probability of ASD40. Air pollution also seems to influence an ASD diagnosis more strongly in boys41. It is important that public health policy address established, scientifically based environmental factors to address even smaller, but preventable, environmental factors.
There have been spurious reports of other environmental factors, but rather than look at factors in isolation, it is crucial to understand how these factors collectively influence brain development and interact with genetic susceptibility, either rare genetic or polygenic influences36. Another area of convergence of environmental and genetic factors is epigenetics, often called the “second genome”. The epigenome is a multitude of chemicals and tags on the DNA genome that is responsive to environmental factors that can turn on or turn off DNA expression, as early as when the embryo is formed. ASD risk genes identified in genetic studies can also work epigenetically42-46. The next generation of research will hopefully focus on understanding the multifactorial influences of an ASD diagnosis, how these factors affect symptoms and influence long term trajectories across neuropsychiatric diagnoses, including ASD.
The high rate of mental health disorders in both children and adults with ASD means that a large percentage of this population and their families are burdened with enormous challenges Training community providers to deliver mental health interventions shows promise for alleviating these comorbidities. Clinicians need to be on the lookout for these psychiatric issues so people with autism receive the much-needed services they deserve.
While the core symptoms of ASD often lead to challenges in daily functioning, across the lifetime and spectrum of many individuals with ASD, co-occurring mental health conditions are a huge concern. Several older but smaller international studies provide a wide range of estimates of the prevalence of co-occurring conditions. A met- analysis and systematic review of these studies conducted in 2019 has helped to decipher the findings20. The findings revealed 28% comorbidity of ADHD (higher in kids than adults), 20% for anxiety disorders, 11% for depression and 9% for obsessive-compulsive disorder20. There is even overlap in brain based profiles of different diagnoses, both in terms of genetic activity21and structure22. These mental health issues, particularly anxiety, can lead to an acute crisis requiring hospitalization23. Unfortunately, clinicians have limited knowledge and understanding of the nature of these mental health conditions in ASD24, making intervention difficult. However, ASD researchers have had luck training community mental health providers to deliver interventions focused on addressing these mental health challenges25. Training community based providers is a move in a promising direction, allowing more people to receive services in a variety of settings, but the efficacy of these interventions still lags behind those delivered in clinics26. Understanding the high co-occurrence of mental health issues helps families and individuals both plan for later health care needs and anticipate potential mental health problems before they occur.
New technologies contribute to greater use of standardized measures in different community settings. At the same time, clinicians and scientists have developed new ways to use common records and tools, resulting in better identification of concerns at even earlier stages. Families and care providers should confidently screen early and often.
Biological based markers hold promise for even earlier detection of features, especially in those with a family history. However, to make predictions about not just a diagnosis but future expectations of needs as well, most care providers, physicians and clinicians rely on behavioral concerns. Right now, most families lack access to EEG machines and MRIs and expensive genetic testing is most often not covered by insurance. The reality of early detection of ASD in 2019 is that it occurs mostly in primary care settings, where physicians help to interpret results for the family. In 2019, the AAP published an update to their 2007 guidelines for screening for autism and it continues to recommend autism-specific screening at 18 and 24 months12. Researchers continue to explore new ways to make this tool more accessible via technology, such as electronic tablets, whereas scientists continue to refine and improve accuracy screening tools using machine learning13.
One challenge of current screening practices (and in fact, in all of ASD research) is the disparity in screening and screening results amongst distinct racial and ethnic groups14. In order to address these differences, scientists are analyzing a variety of approaches fashioned to deal with these disparities and to increase access to screening tools. This includes remotely employing video based tools to capture ASD features to help identify and diagnosis ASD15-17. These video based tools help parents identify signs by providing real life examples of parent-child interactions18and by examining existing reports of developmental milestones from electronic medical records19, with the goal of identifying early signs of developmental concerns as soon as possible, in as many infants as possible, regardless of race or ethnicity . Doing so will increase early diagnosis, leading to earlier intervention and increased understanding of ASD, self-awareness of symptoms and long-term improvement of services.
This year, to make predictions about future ASD features, more studies used a longitudinal study design. This design is critical to autism research because it follows a group comprised of individuals diagnosed with ASD and, at times, individuals without a diagnosis in order to determine how they are affected as adolescents and adults. Whereas a longitudinal study can be expensive, complex and does not produce immediate results, the nature of its design provides clinicians invaluable data, affording deeper insights that allow them to more fully educate families by managing expectations, identifying focus areas and providing coping strategies that serve to help those with ASD live their best lives.
Longitudinal studies help parents understand their child’s reality and manage future expectations, as well as help scientists refine interventions according to the variability of groups of people with ASD. Multiple research studies have used data to group children based on trajectory, i.e. the progression from commencement, through adolescent development to adult functioning. The composition of these groups consists of those who show fewer symptoms and continue to improve vs. those less functioning who continue to decline. This year, two longitudinal studies, one conducted in the United States and one in Canada, closely examined toddlers to pinpoint and study specific factors that influence outcomes, from childhood to adulthood. In these studies, two patterns emerged: those possessing lower levels of symptoms who improve vs. those with more profound symptoms who decline.
While all groups showed improvement in daily living skills, those who presented less severe symptoms in toddlerhood and showed marked progression during adolescence also had the highest adaptive abilities as adults2. Although most participants showed improvement in social communication with age, improvement varied, based on individual language ability as toddlers. Social communication impairments in 19 year olds was found to correlate with differences in language ability as early as age two. As speech improved, so did this core symptom of ASD3: those with early minimal language ability showed the greatest functioning impairments as adults. Likewise, fine motor skills in infancy4is a predictor of language at age 19, in that better fine motor skills in early childhood is a predictor of better command of language in adulthood. Together, these findings demonstrate that poor early motor skills and decreased language function are related to later ASD symptoms. This is a crucial identification, considering that both fine motor skills and language are target areas of early intervention and that intervention may improve ASD through adulthood.
The study of early motor function is not only vital to further understanding how it affects those diagnosed, it also offers insight pre-diagnosis in terms of how early motor function may predict a later ASD diagnosis. The Baby Siblings Research Consortium (BSRC) is a group of researchers that studies initial features of ASD in siblings of children with ASD as young as 6 weeks of age. Siblings of children with ASD have a 15x greater probability of having ASD themselves than do other children. Similar to previously mentioned studies, BSRC also concludes that fine motor abilities at 6 months can predict an ASD diagnosis in siblings and expressive language ability in younger siblings at 3 years6,7.
Another factor BSRC researchers have employed to estimate the probability of diagnosis in children is number of siblings previously diagnosed with ASD. Those with at least 2 older siblings with ASD were found to have a higher probability of a diagnosis, as well as increased severe cognitive disabilities8. Based on family history, this information is vital in helping families better understand the probability of an ASD diagnosis in future children, as well as predicting strengths and limitations future children may face.
In addition to identifying behavioral markers, the past decade of research has revealed a blossoming of early biological factors that may serve as additional predictors of diagnosis, ranging from genetic tests9, salivary hormone markers and other reflections of altered development. Studies of brain structure, activity and connectivity have also proven valuable; when measured non-invasively, identified changes in activity in the frontal lobe of the brain during the first year of life have served to predict an ASD diagnosis in infant siblings10. Because brain wavelengths vary, identifying and monitoring changes in the size of each different type of wavelength over the course of a year serves as valuable information in terms of not just determining an ASD diagnosis but also for further understanding brain fluctuations during that time period10.
Complementary to brain activity, previous studies from the Infant Brain Imaging Network (IBIS) revealed different approaches to more accurately predicting ASD diagnosis by using measurements of brain structure and connectivity, in addition to mathematical algorithms based on the shape and function of different brain regions, as potential predictors of a later diagnosis. This year, the analysis of early brain based ASD markers has afforded scientists more precision in determining an association with brain connectivity in critical ASD brain regions, as well as an insistence on sameness and stereotyped behaviors at 12 – 24 months11. Not only do these biological based markers aide in predicting later diagnosis and identifying features of ASD within a diagnosis, they have the potential to serve as objective ways to help determine specific interventions, both medical and behavioral.