Kadir, Zara 

Nick Rosenfield 

3/6/24 

Biomarkers For Autistic Spectrum Disorder (ASD) 

Imagine the power of unraveling the complexities of ASD, as a variety of specific biological signatures. There are many challenges associated with ASD that range from difficulties in social interaction to communication. This field has seen many significant advancements, however, through the use of biomarkers. Genetics, neuroimaging, epigenetic modifications, cognitive repairments, and much more data could be used in order to understand behaviors for autism. Researchers are currently exploring different types of biomarkers to improve diagnostic accuracy and treatment strategies for autism. The wealth of data generated through biomarker research contributes to aim for ASD diagnosis, as well as monitoring progression, treatment decisions, and preventing/predicting certain aspects of this disorder. Therefore, identifying biomarkers for Autism Spectrum Disorder (ASD) is a crucial step in developing effective treatment plans and intervention strategies for many individuals, however it stands as a challenge due to inaccurate representations of an “accurate” diagnosis. 

Identifying the limitations or challenges within ASD Biomarkers is the first step into looking through the misconceptions of data. For starters, we need to observe individuals through trained and untrained perspectives. “In order to identify studies of biomarkers in ASD, we conducted a review of the common medical literature databases PUBMED, Ovid Medline, Google Scholar, CINAHL, EmBase, Scopus, Cochrane and ERIC databases, from inception through June 2019.” (Source A) The process for identifying biomarkers in ASD involved an extensive search on many medical literature databases. While biomarkers hold great promise for understanding medical conditions, there are many controversies that exist, like ethical concerns regarding privacy and consent, or the absence of standardized procedures for biomarker identification. The reliance of diverse sources for ASD biomarker studies has introduced bias from varying levels of expertise. The quality of observations may differ significantly, and impact the reliability of biomarkers itself. In addition, the authors emphasize that there should be a better understanding when trying to treat ASD. Without clinical data, biomarkers are excluded from the evaluation process, creating a potential challenge in obtaining a comprehensive look into ASD. For instance, “Other filter terms such as "Human" or "Clinical Trials” were not uncommonly used. References in publications identified by the search were also reviewed to identify any relevant publications.” (Source A) Overall, to address the challenge of excluding biomarkers, a systematic approach has allowed for a focus in generating clinical data for biomarkers. Ongoing efforts to standardize observation protocols and enhance clinical data collections will be very valuable in overcoming limitations, and refining the accuracy of biomarker-based ASD research. 

There are many approaches in identifying biomarkers for ASD in children. Understanding the role of genetics and structural DNA/RNA alternations is crucial in identifying potential biomarkers for ASD. The focus is recognizing chromosomes and addressing alterations of DNA structure as well. Studies show that, “16% of children with ASD use both a chromosomal microarray and whole exome sequencing.” (Source B) meaning, that genetic alterations are evidenced from this study looking into the association of ASD risks with mothers, and not their children. This can emphasize the need to study a genetic perspective, recognizing that genetic biomarkers allow for early identification at birth. Furthermore, the knowledge from genetic studies may lead to targeted interventions as well. Neurology and brain scanning for

children also may indicate ASD. Brain scanning techniques contribute to the recognition of specific connectivity patterns that give valuable information on intervention strategies based on the individual’s profile of the brain. For example, “Promising results from the Autism Biomarker Consortium for Clinical Trials (ABC-CT), a large multi-site study led by the Yale Child Study Center has leading to the acceptance of N170 latency to upright human faces as an identifier of biological subgroups of ASD into the US Food and Drug Administration’s Biomarker Qualification Program [65].” (Source B) This shows that identifying biomarkers uses a multifaceted approach, encompassing genetic factors and neurological characteristics. The genetics and understanding DNA/RNA alterations contribute to early stages in seeing how biomarkers can positively/negatively impact a person’s wellbeing. These approaches have the potential to revolutionize treatment plans, and as research progresses, we’ll be able to soon understand and possibly improve the precision for interventions within ASD in children. 

Moreover, there are many techniques used for identifying ASD in children, exploring both transcriptomics and metabolomics. Biomarkers within Metabolites are investigated through the byproducts of metabolism, creating potential for precise diagnosis and neuropsychiatric diseases like ASD. “Metabolism-based analysis has the merit of being sensitive to interactions among the genome, gut microbiome, diet, and environmental factors.” (Source C) The impact that metabolomic-based analysis enhances sensitivity to the intricacies of genetics. Environmental, and dietary factors. By identifying metabolic factors in our body, clinicians and specialists can gain an insight of the physiological processes associated with ASD. There are many diagnosis and intervention strategies that can be associated with metabolics, however, there is much more evidence that can be seen through the comprehensive views of transcriptomics. Transcriptomics are a field of study that analyzes the development of RNA transcripts and looks into gene expression patterns, helping to see which genes are active. However, studies can only be done through an extent. This approach helps understand involvement of various biological processes at a certain limit. “These approaches yield information about transcript abundance and can be applied to mRNA and small or long noncoding RNA (lncRNA) transcripts.” Methods such as alternative splicing offer an insight as to unraveling gene expression in ASD. Discovering the transcriptomic analyses of RNA transcripts can help us learn more about the molecular processes underlying ASD, which develops the aid of learning more on treatment plans for ASD. Researchers gain more of an understanding by delving into this area as well, since it can determine the accuracy of gene expression patterns and look into unique metabolic signatures. 

To conclude, a proper way to identify ASD can be through the potential use of biomarkers. Nevertheless, an intensive understanding emerges through genetic studies, neurology, and exploring the molecular and metabolic processes. Therefore, these approaches show cognitive indicators, and biomarkers that contribute to a more nuanced comprehension of ASD. The investigation of relationships for biomarkers and ASD’s remains crucial in understanding the evolving field. Hence, with collaborative efforts of researchers worldwide, the validation of biomarkers holds great promise. The pursuit in enhancing the lives for individuals with ASD biomarkers will allow us to find solutions in order to create a better future for those that are affected by this complex condition being Autism.

Sources and Description: 

Source A: Emerging biomarkers in autism spectrum disorder: a systematic review 

The discovery of biomarkers however, shows great potential in identifying ASD’s side effects, which can therefore lead patients to properly be categorized into subgroups and receive proper therapeutic responses needed as well.  

Source B: Modern Biomarkers for Autism Spectrum Disorder: Future Directions - Molecular Diagnosis & Therapy 

This article addresses the increasing prevalence of ASD globally, and looks into the challenges for behavioral observations in children. Biomarkers look into the prenatal history, immune factors, genetics, and much more. Most biomarkers lack validation and appropriate comparisons, therefore more comprehensive research is still yet to be uncovered.  

Source C: Biomarkers in autism spectrum disorders: Current progress  

The significance of early interventions are emphasized, however once again, biomarkers are in need of in-depth research for potential effects in  genetics & environmental factors.