IUCOM NOVEMBER 10TH

Introduction

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder

characterized by a spectrum of social, communication, and behavioral challenges that
vary significantly in severity among individuals. Recent reports indicate a rise in ASD
prevalence globally, with estimated rates currently ranging from 1 in 160 children
worldwide, though figures fluctuate due to differences in diagnostic criteria and
awareness levels across countries (1,2). In Iraq, where epidemiological data on ASD is
limited, the need to understand the prevalence and characteristics of ASD within local
populations has become increasingly pertinent. The Iraqi National Autism Center plays a
crucial role in diagnosing and supporting children with ASD, providing an ideal setting for
assessing the prevalence and traits associated with the disorder.

Advancements in genetic research have emphasized the potential role of specific

genetic markers, particularly single nucleotide polymorphisms (SNPs), in influencing
ASD symptom severity and presentation (3). Studies suggest that certain genetic
variations may contribute to a predisposition to ASD, potentially affecting the clinical
manifestation and prognosis of affected individuals (4). Given the potential of genetic
markers to serve as early indicators of ASD, there is a growing interest in integrating
genetic screening into ASD diagnostic processes. Identifying these markers may
enhance diagnostic accuracy, enable early intervention, and facilitate tailored
therapeutic approaches that address the unique needs of each child (5,6).

This study aims to assess the prevalence and characteristics of ASD symptoms among
children attending the Iraqi National Autism Center and to explore genetic associations
by incorporating genetic analysis, specifically SNP analysis. By establishing correlations
between specific genetic markers and symptom severity, this research seeks to provide
insights that could ultimately inform personalized intervention strategies. Early
identification of genetic risk factors may allow for more customized and timely
interventions, potentially improving developmental outcomes and quality of life for
children with ASD.

Objectives

1. Determine ASD Prevalence: Assess the prevalence of ASD among children at the
Iraqi National Autism Center.

2. Identify Genetic Markers: Investigate the presence of specific genetic mutations,

particularly single nucleotide polymorphisms (SNPs), associated with varying ASD
symptom severity.

3. Correlate Genetic Findings with Symptom Severity: Explore the relationship between
identified genetic markers and the severity of ASD symptoms to determine their potential
predictive value for clinical outcomes.

4. Advocate for Early Genetic Screening: Promote the importance of early genetic
screening to improve diagnostic accuracy and enable timely, customized intervention
plans for children with ASD.

Hypothesis

Early diagnosis of Autism Spectrum Disorder (ASD), especially when correlated

with specific genetic mutations such as single nucleotide polymorphisms (SNPs)
associated with ASD symptom severity, could provide significant insights into
personalized treatment approaches. By identifying these mutations early,
healthcare providers may be able to predict the severity of ASD symptoms and
tailor interventions accordingly. This genetic information could guide more targeted
therapies, enabling interventions to address the unique challenges associated with
each child’s genetic profile. Early detection of these mutations can potentially
improve developmental outcomes and overall quality of life by facilitating timely and
customized support strategies for children with ASD.

Patients and Methodology

Study Design Data Collection

This cross-sectional study aims to Clinical Assessment:

assess the prevalence and
characteristics of Autism Spectrum
Disorder (ASD) symptoms among
children attending the Iraqi National Data will be collected through
Autism Center, with an integrated genetic structured interviews and
analysis component to explore potential standardized assessment tools
genetic associations. administered by experienced
psychiatrists specializing in ASD. The
assessments will evaluate the severity
of symptoms and associated clinical
Study Population features.

The target population comprises children Genetic Analysis:

diagnosed with ASD, exhibiting varying
symptom severity levels—mild,
moderate, and severe —who are
receiving care at the National Autism Upon obtaining informed consent,
Center. blood samples will be collected from
participants for genetic analysis.
Genomic DNA will be extracted and
subjected to single nucleotide
Sample Size Determination polymorphisms (SNPs) associated
with ASD. This approach aligns with
current research indicating the
A sample size of 384 participants has significant role of SNPs in ASD
been calculated to ensure statistical etiology.
validity. This calculation is based on a
95% confidence level, a 5% margin of
error, and an estimated prevalence rate Ethical Considerations
of ASD symptoms within the population.

The study will adhere to ethical

Sampling Method guidelines, obtaining informed
consent from parents or guardians for
both clinical assessments and genetic
analyses. Confidentiality and
Participants will be selected using a anonymity of participants will be
stratified random sampling technique. maintained throughout the research
The strata will be defined by the severity process.
of ASD symptoms (mild, moderate,
severe), ensuring proportional
representation from each category. Data Analysis

Inclusion Criteria Clinical Data:

•​Children diagnosed with ASD.

•​Aged between 3 and 16 years. Descriptive statistics will summarize

the prevalence and distribution of
•​Currently receiving treatment or
ASD symptom severity. Inferential
services at the National Autism Center.
statistics, such as chi-square tests
•​Parental or guardian consent for and ANOVA, will be employed to
participation in clinical and genetic identify significant associations
assessments. between symptom severity and
demographic or clinical variables.

Exclusion Criteria
Genetic Data:
•​Children with comorbid psychiatric
conditions that may confound the
assessment of ASD symptoms.
Identified genetic variants will be
•​Non-consent from parents or guardians. analyzed to determine their frequency
and potential association with ASD
symptom severity. Statistical
analyses, including logistic regression
models, will assess the correlation
between specific genetic findings and
clinical presentations.

Quality Assurance

To ensure data reliability and validity,

all assessments will be conducted by
trained professionals using
 standardized instruments. Genetic
analyses will be performed in certified
laboratories following stringent quality
control protocols. Regular audits and
inter-rater reliability checks will be
implemented.

Limitations

Potential limitations include the cross-

sectional nature of the study, which
precludes causal inferences, and the
reliance on clinical records, which
may introduce information bias.
Additionally, genetic analyses may
identify variants of uncertain
significance, necessitating cautious
interpretation.

Expected Outcomes

This study aims to provide a comprehensive overview of ASD symptomatology

among children at the National Autism Center, integrating genetic analysis to
explore underlying genetic factors. The findings are expected to contribute valuable
insights for clinicians and policymakers, potentially informing personalized
intervention strategies.
 
References

1. World Health Organization. Autism spectrum disorders [Internet]. 2022. Available from:
https://www.who.int/news-room/fact-sheets/detail/autism-spectrum-disorders
2. Elsabbagh M, Divan G, Koh YJ, et al. Global prevalence of autism and other pervasive
developmental disorders. Autism Res. 2012;5(3):160–79.
3. Ramaswami G, Geschwind DH. Genetics of autism spectrum disorder. Handb Clin
Neurol. 2018;147:321–9.
4. Vorstman JA, Parr JR, Moreno-De-Luca D, Anney RJ, Nurnberger JI Jr, Hallmayer JF.
Autism genetics: opportunities and challenges for clinical translation. Nat Rev Genet.
2017;18(6):362–76.
5. Lai MC, Lombardo MV, Baron-Cohen S. Autism. Lancet. 2014;383(9920):896–910.
6. Toma C, Sousa I, Krall W, et al. Genetics of autism spectrum disorder. IntJ Mol Sci.
2019;20(21):509