3.9.1 Autism

Autism

In 1911 Eugen Bleuler coined the term autism as a characteristic feature of schizophrenia. Over a decade later in 1926 Grunya Sukhareva (in her paper, ‘Schizoid Psychopathy in Childhood’) described the first attempt to describe autism spectrum disorder (ASD) as a distinct diagnostic entity. In her paper, she refers to ASD as “schizoid personality disorder”. Her work remained largely unknown until translated from Russian and German to English many years later in 1996 (Posar, 2017).

A wide range of diseases collectively known as autism, or ASD are complex neurological disorders. They are characterised by difficulties with social skills, repetitive activities, speech, and nonverbal communication. The Centres for Disease Control estimate that 1 in 44 American children currently suffer from ASD. In the UK, 1 in 100 children and adults are on the autistic spectrum.

Aetiology of autism:

The aetiology is complex and has associations with:

• Neurological pathways
• Neurotransmitters
• Genes
• Environmental influences

There is ongoing research to understand whether there are any possible causal factors of ASD.

Based on the available epidemiological data, it has been concluded that there is no evidence to support the claim that the measles, mumps, and rubella vaccine causes autism. Previous studies claiming a causal relationship were found to have numerous methodological flaws.

The cause of Autism Spectrum Disorder (ASD) can be attributed to several factors, and it often coincides with sensory sensitivities, physical issues such as gastrointestinal problems, seizures, and sleep disorders, as well as psychological challenges like anxiety, depression, and attention deficits.

Early signs of ASD may be present, but the disorder is frequently not diagnosed until later in life.

Co-occurring disorders such as epilepsy, depression, anxiety, and attention deficit hyperactivity disorder are common in individuals with autism, along with challenging behaviors like difficulty sleeping and self-harm. The intellectual functioning levels of those with autism can range greatly, from severe impairment to exceptional abilities.

Genetics:

Siblings of autistic people are 50 to 100 times more likely to have autism than people in the general population.

Autism twin studies show an extremely high heritability:

• 60-90% monozygotic concordance (Castelbaum, 2020)
• 30% dizygotic concordance 2014 (Frazier, 2014)

Weak central coherence model:

The weak central coherence model proposed in 1994 asserts that ASD is presented as a cognitive bias towards local processing over global processing. Consequently, individuals with ASD lack the ability to automatically use context to aid their understanding of the surrounding environment.

This theory is supported by an increased performance in block design tasks, figure tasks and illusion tasks that are associated with the influence of context.

Integrated neurobiology approach:

Brain region:	Summary:
Cerebellum	Hypoplasia of cerebellar vermis. Aside from the known regulation of sequenced movement that the cerebellum is associated with. Other functions include procedural learning, emotion, thought, and attention. Specifically, attention shifting is implicated in the cerebellum.
Frontal lobe	The prefrontal cortex is involved in executive functioning. This affects working memory, inhibition, planning, organization, set shiting, cognitive flexibility, and disengaging attention. All of these functions are deficient to some degree in ASD.
Temporal lobe	The temporal lobe is known for its involvement in audition, memory, and object perception. Its involvement in receptive language processing via Wernicke’s area can specifically affect joint attention, action observation, and empathy. Again all of these functions are deficient to some degree in ASD.
Neocortex	Inconsistent changes noted. Some studies suggest increased cortical volume, probably related to reduced pruning.

(Schroeder, 2010).

Challenges for the future:

There are several challenges that will need to be addressed in order to effectively manage autism in the future, including:

1. Early diagnosis and intervention: Early diagnosis and intervention are key to improving outcomes for individuals with autism, but there are still many barriers to early identification, including lack of awareness, limited resources, and long wait times for assessments.
2. Individualized support: Autism affects individuals differently, and therefore it is important to provide individualized support and interventions to meet each person’s unique needs. This requires a flexible and tailored approach to treatment.
3. Integration into mainstream society: Individuals with autism often face challenges in accessing education, employment, and other mainstream services, and there is a need for more inclusive and accessible options.
4. Addressing co-occurring conditions: Many individuals with autism also have co-occurring conditions such as anxiety, depression, and epilepsy, and it is important to address these conditions in a holistic manner to improve overall well-being.
5. Addressing the needs of aging individuals with autism: As the number of individuals with autism continues to grow, there will be an increasing need for support and services for those with autism as they age.
6. Improving access to care: There are still significant disparities in access to care for individuals with autism, particularly for those from underserved communities, and efforts are needed to address these disparities and improve access to care for all.
7. Research and innovation: Ongoing research is needed to improve our understanding of autism, develop new interventions, and improve quality of life for individuals with autism.
8. Diversity of the disorder: The diversity of the disorder’s causes, symptoms, severity, and designations are one of the most difficult issues in ASD research. Sample descriptions range from “pure” autism to ASD and pervasive developmental disorder (PDD), which includes a wide spectrum of problems. This range makes it difficult to generalise across research with widely disparate samples (Bebko et al., 2008).

References:

(1) Bebko, J.M., Schroeder, J.H., Weiss, J.A., Wells, K., McFee, K. and Goldstein, G.M. (2008). The face of Autism research as reflected in the IMFAR looking glass. Research in Autism Spectrum Disorders, 2(3), pp.385–394. doi:10.1016/j.rasd.2007.06.005.

(2) Castelbaum, L., Sylvester, C.M., Zhang, Y., Yu, Q. and Constantino, J.N. (2019). On the Nature of Monozygotic Twin Concordance and Discordance for Autistic Trait Severity: A Quantitative Analysis. Behavior Genetics, 50(4), pp.263–272. doi:10.1007/s10519-019-09987-2.

‌(3) Frazier, T.W., Thompson, L., Youngstrom, E.A., Law, P., Hardan, A.Y., Eng, C. and Morris, N. (2014). A Twin Study of Heritable and Shared Environmental Contributions to Autism. Journal of Autism and Developmental Disorders, [online] 44(8), pp.2013–2025. doi:10.1007/s10803-014-2081-2.

(4) Frith, U. and Happé, F. (1994). Autism: beyond ‘theory of mind’. Cognition, 50(1-3), pp.115–132. doi:10.1016/0010-0277(94)90024-8.

(5) Posar, A. and Visconti, P. (2017). Tribute to Grunya Efimovna Sukhareva, the woman who first described infantile autism. Journal of Pediatric Neurosciences, 12(3), p.300. doi:10.4103/jpn.jpn_46_17.

(6) Schroeder, J.H., Desrocher, M., Bebko, J.M. and Cappadocia, M.C. (2010). The neurobiology of autism: Theoretical applications. Research in Autism Spectrum Disorders, 4(4), pp.555–564. doi:10.1016/j.rasd.2010.01.004.