Autism Spectrum Disorder (ASD) is an acronym used to describe a group of developmental conditions characterized by, among other things, difficulties in social functioning and the occurrence of repetitive behaviors. The term ‘spectrum’ points to enormous heterogeneity that is present within the disorder’s manifestations. Office of Genomics and Precision Public Health (2021) reports that even though the causes of ASD are still generally unknown, biology, genetics, and environmental factors are all considered to play a particular role. Older parents, obstructed labor, or infection during pregnancy are examples of influences that may increase the risk of a child contracting ASD. Moreover, among those at risk are people who have certain genetic disorders, such as Down syndrome, fragile X syndrome, and tuberous sclerosis. However, scientists and researchers keep trying to determine specific changes that people with ASD might have that could help them be diagnosed as early and as accurately as possible. The two most popular laboratory methods that are currently utilized are genetic testing and blood tests. To establish how accurate both of these are and whether one is more accurate than the other, I applied to most recent research papers.
In searching for the works for this literature review, I turned to databases such as ProQuest and Frontiers in Psychiatry. After having examined a number of papers to ensure they meet the research criteria, I selected five for a more thorough exploration of their contents. Genovese and Butler (2020) reviewed the role of various genetic and metabolic factors which might contribute to ASD causation with the help of new genetic technology. Roberts et al. (2020) used a multi-method approach to determine the ASD rate in preschoolers with fragile X syndrome and investigate the trajectories of ASD predictors in them. Rubenstein and Chawla (2018) conducted a review of studies that quantified a percentage of parents of ASD children with the broader autism phenotype. Barone et al. (2018) investigated blood metabolic profile connected to ASD diagnosis through analyzing samples from dried blood spots. Qin et al. (2018) collected blood samples of children with ASD to compare their blood plasma metals to those in unaffected kids in the city of Shenzhen. Some of the findings could be considered meaningful; however, many of them are too ambiguous for definite conclusions to be drawn.
Synthesis of Evidence
For instance, Barone et al. (2018) explicitly state that they are not certain whether distinct metabolite differences – found in autistic children and used as a research subject – are actually related to ASD. According to them, these could be a product of co-morbid undiagnosed medical condition or a vitamin D deficiency, often observed in children with ASD (Barone et al., 2018). Qin et al. (2018) come to the same conclusion in regard to their study: they investigated that autistic children had higher levels of concentration of harmful metals in blood than their neurotypical folks. However, there is a number of other factors it could be related to and, therefore, these metals cannot be with full confidence considered risk factors for ASD (Qin et al., 2018). In terms of sample groups, lack of diversity is concerning: research subjects of Barone et al. (2018) were exclusively Caucasian, whereas Qin et al. (2018), although expectedly, studied Chinese kids only. The authors of both these works, as well as Rubenstein and Chawla (2018) admit that their studies’ sample types do not allow for more convincing results.
Sample groups of other studies, however, were large and diverse enough for their conclusions to be deemed relevant in that regard; this is where some papers differ from others. The one thing that all of them have in common, though, is their emphasis on the necessity of an integrated approach. Genovese and Butler (2020) note that advances in genomic testing, bioinformatic approaches, and computational predictions must all be combined in helping recognize possible distinctive patterns of ASD in the future. Roberts et al. (2020) speak about how a number of various ASD-specific measures implemented by them in their study is the reason why they are so confident in the legitimacy of their outcomes. Barone et al. (2018), Qin et al. (2018), and Rubenstein and Chawla (2018) all speak about the necessity to conduct further research to confirm or refute the conclusions they arrived at in their works. One thing is clear: in attempting to diagnose and treat the autistic spectrum disorder, comprehensiveness is key. It might be considered the main theme that appears in all the works and unites them together, despite the papers using different methods and approaches.
It is evident that, in order for integrated approach to be ensured, a large number of resources needs to be utilized, including time and money. Seeing how autistic people, though not without some problems, are still integrated into society, and many of them quite successfully, one might wonder why so much effort is put into identifying the causes of ASD. One should not forget that ASD, even if it manifests itself in a light form, is still a disorder – and there is no disorder that makes a person happy. From a Biblical standpoint, everyone deserves to be healthy and each child of God’s body is a temple that should be taken care of and cherished. As per 1 Corinthians 3:16-17 (n.d.), “Do you not know that you are God’s temple and that God’s Spirit dwells in you? […] God’s temple is holy, and you are that temple”. A person should always strive to health and if there is even a slight chance that cure for a disorder can be found, humanity should never stop searching for that cure.
However, the cure can only be found if the cause of the disease is known. While now there are treatments that alleviate autistic people’s condition, ASD is considered to not be fully curable. The research shows that the earlier the intervention of treatment services occurs for autistic children, the more likely their development is enhanced. It might be possible that if we were to find definite causes of ASD, the treatment that could prevent the disease from developing at all would be designed. Therefore, scientists and researchers have to join their efforts – and healthcare establishments and programs have to provide them with the resources for the opportunities to determine the causes for the emergence of ASD symptoms. Sample groups are to be bigger and more diverse, methods and approaches are to vary and the results of studies are to be confirmed by the findings of related research. Then, it is possible that a day when we know what causes ASD comes – and, therefore, better treatments will be invented and the lives of millions of people will be improved.
1 Corinthians 3:16-17. (n.d.). Bible Gateway. Web.
Barone, R., Alaimo, S., Messina, M., Pulvirenti, A., Bastin, J., Ferro, A., Frye, R. E., & Tabbì, G. (2018). A subset of patients with autism spectrum disorders show a distinctive metabolic profile by dried blood spot analyses. Frontiers in Psychiatry, 9(636), 1-11. Web.
Genovese, A., & Butler, M. G. (2020). Clinical assessment, genetics, and treatment approaches in autism spectrum disorder (ASD). International Journal of Molecular Sciences, 21(13), 4726. Web.
Office of Genomics and Precision Public Health. (2021). Autism spectrum disorder, family health history, and genetics. Centers for Disease Control and Prevention. Web.
Qin, Y. Y., Jian, B., Wu, C., Jiang, C. Z., Kang, Y., Zhou, J. X., Yang, F., & Liang, Y. (2018). A comparison of blood metal levels in autism spectrum disorder and unaffected children in Shenzhen of China and factors involved in bioaccumulation of metals. Environmental Science and Pollution Research, 25(18), 17950-17956. Web.
Roberts, J. E., Bradshaw, J., Will, E., Hogan, A. L., McQuillin, S., & Hills, K. (2020). Emergence and rate of autism in fragile X syndrome across the first years of life. Development and Psychopathology, 32(4), 1335-1352. Web.
Rubenstein, E., & Chawla, D. (2018). Broader autism phenotype in parents of children with autism: A systematic review of percentage estimates. Journal of Child and Family Studies, 27(6), 1705-1720. Web.