Redefining Critical Autism Studies: a more inclusive interpretation

Redefining Critical Autism Studies: a more inclusive interpretation

ABSTRACT
This article explores the definition of Critical Autism Studies
and its inclusion in autistic scholarship. There has been critique
of recent non-autistic literature for lacking autistic authorship,
leading to doubts about its epistemological integrity due to
misrepresentations of autistic culture and the neurodiversity
movement. This article utilises the work of Arnold, Milton
and O’Dell et al. to introduce an emancipatory definition to
ensure the discipline is autistic led. In the process, we discuss
the nature of autism studies and what constitutes critical
literature. We propose Waltz’s interpretation of Critical Autism
Studies as a working definition.

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EEG Analytics for Early Detection of Autism Spectrum Disorder: A data-driven approach

 EEG Analytics for Early Detection of Autism Spectrum Disorder: A data-driven approach

Autism spectrum disorder (ASD) is a complex and heterogeneous disorder, diagnosed on the basis
of behavioral symptoms during the second year of life or later. Finding scalable biomarkers for early
detection is challenging because of the variability in presentation of the disorder and the need for
simple measurements that could be implemented routinely during well-baby checkups. EEG is a
relatively easy-to-use, low cost brain measurement tool that is being increasingly explored as a
potential clinical tool for monitoring atypical brain development. EEG measurements were collected
from 99 infants with an older sibling diagnosed with ASD, and 89 low risk controls, beginning at 3
months of age and continuing until 36 months of age. Nonlinear features were computed from EEG
signals and used as input to statistical learning methods. Prediction of the clinical diagnostic outcome
of ASD or not ASD was highly accurate when using EEG measurements from as early as 3 months of age. Specificity, sensitivity and PPV were high, exceeding 95% at some ages. Prediction of ADOS calibrated severity scores for all infants in the study using only EEG data taken as early as 3 months of age was strongly correlated with the actual measured scores. This suggests that useful digital biomarkers might be extracted from EEG measurements

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Epigenetics and Autism Spectrum Disorder: Is There a Correlation?

Epigenetics and Autism Spectrum Disorder: Is There a Correlation?

Autism spectrum disorder (ASD) is the term for a range of development disorders caused by
a combination of genetic and environmental factors (Kubota et al., 2012; Loke et al., 2015;
Constantino and Marrus, 2017). ASD includes a “spectrum” of effects, skill detriments, and
disability—including communication issues, limited interest in activities, and other aspects of
work and life functionality. The current occurrence of ASD in the United States is about 1 in
68 children—an astonishing increase of over a factor of 100 compared to 2,000 (https://www.
cdc.gov/ncbddd/autism/addm.html) (Zablotsky et al., 2015). Thus, it is imperative to develop
novel treatment modalities for which understanding the pathogenetic factors underlying ASD
is of utmost importance. Recently, the multigenic condition of ASD has been speculated to be
dependent on epigenetic effects (Loke et al., 2015), although such exact factors remain unclear.
Epigenetics refers to the heritable changes in gene expression without changing the underlying
DNA sequence (Schiele and Domschke, 2017). In this opinion article, we will briefly discuss the
recent advancements in understanding the contribution of epigenetic factors that can play a role in
determining the predisposition to autism (Table 1). We emphasize that there is a need to include
greater sample size and appropriate tissue type in order to better understand the role of epigenetics
in ASD.

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Progress in the genetics of autism spectrum disorder

Progress in the genetics of autism spectrum disorder

A genetic basis for autism spectrum disorder (ASD) is now well established, and with the
availability of high-throughput microarray and sequencing platforms, major advances have
been made in our understanding of genetic risk factors. Rare, often de novo, copy number
and single nucleotide variants are both implicated, with many ASD-implicated genes showing
pleiotropy and variable penetrance. Additionally, common variants are also known to play a
role in ASD’s genetic etiology. These new insights into the architecture of ASD’s genetic
etiology offer opportunities for the identification of molecular targets for novel interventions,
and provide new insight for families seeking genetic counseling.

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