The field of neurodevelopmental genetics is tasked with unraveling the biological underpinnings of conditions that are defined by behavior but have their roots in the genome. Among these, Autism Spectrum Disorder (ASD) presents one of the most formidable challenges due to its profound clinical and etiological heterogeneity. The diagnostic journey for a family with a child with ASD often involves a broad, multi-step genomic investigation that can be costly, lengthy, and frequently inconclusive. It is interesting, then, to examine the unique relationship between ASD and Fragile X Syndrome (FXS). FXS stands as the most common single-gene cause of ASD. This well-defined molecular link has established the targeted genetic test for FXS as a standard, cost-effective, and high-yield component of the initial diagnostic workup for individuals with autism spectrum disorder (ASD). The practice of using this specific, targeted test provides a fascinating point of diagnostic clarity within the otherwise vast and often uncertain genetic landscape of ASD.

ASD is characterized by a core set of symptoms, including deficits in social communication and the presence of restricted and repetitive behaviors (Pyeritz, Korf, & Grody, 2019). FXS, while having its own distinct set of physical and cognitive features, frequently presents with behaviors that fall squarely within the autism spectrum. Research has shown that approximately 60% of males with FXS also meet the full diagnostic criteria for ASD, making the behavioral presentation of the two conditions often indistinguishable in a clinical setting (Kaufmann, et al., 2017). The phenotypic overlap is rooted in a shared underlying neurobiology. FXS is caused by the silencing of the FMR1 gene, resulting in the absence of the FMRP protein.

Having shared biology misrepresents a fundamental difference in their genetic architectures. FXS is a monogenic disorder, caused almost exclusively by the expansion of a CGG trinucleotide repeat in the FMR1 gene (Hunter, Berry-Kravis, Hipp, & Todd, 1998). ASD, on the other hand, is polygenic and genetically heterogeneous. There is no single “autism gene.” Instead, hundreds of genes have been implicated, and a large number of cases are attributed to rare, de novo mutations that are not inherited from the parents. The genetic complexity of ASD necessitated the creation of large-scale research initiatives, such as the Simons Simplex Collection, which gathered data from thousands of families to begin identifying these rare genetic risk factors (Fischbach & Lord, 2010). The fact that such a massive undertaking was required for ASD, while the cause of FXS was pinpointed to a single gene, perfectly illustrates the difference in their genetic landscapes.

It is this difference that makes the FXS test such a valuable tool in the ASD diagnostic process. Given that a significant percentage of individuals with an ASD diagnosis—between 2% and 6%—will test positive for the FMR1 mutation, it represents the most common, currently identifiable genetic cause of autism (Kaufmann, et al., 2017). From a clinical and economic perspective, it is far more efficient to first test for this single, relatively common cause with a targeted and inexpensive molecular test. A positive result provides a definitive etiological diagnosis, which can eliminate the need for a more extensive and costly “diagnostic odyssey” involving chromosomal microarrays and whole-exome sequencing (Shen, et al., 2010).

For a family, receiving a definitive diagnosis of FXS as the cause of their child’s autism provides immediate clarity. It gives a specific prognosis, enables accurate genetic counseling regarding recurrence risk for future children, and connects them to a well-established community of families and researchers focused on a single condition (Finucane, et al., 2012). This stands in contrast to the experience of most families with idiopathic ASD, whose extensive genetic testing often yields no clear answer. The standard practice of including an FXS test in the initial workup for autism is a model of how clinical genetics can use population data to create an efficient, logical, and cost-effective diagnostic pathway.

References

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Finucane, B., Abrams, L., Cronister, A., Archibald, A. D., Bennett, R. L., & McConkie-Rosell, A. (2012). Genetic counseling and testing for FMR1 gene mutations: practice guidelines of the national society of genetic counselors. Journal of genetic counseling, 21(6), 752–760. https://doi.org/10.1007/s10897-012-9524-8.

Fischbach, G. D., & Lord, C. (2010). The Simons Simplex Collection: A Resource for Identification of Autism Genetic Risk Factors. Cell, 192-195. https://www.cell.com/action/showPdf?pii=S0896-6273%2810%2900830-5.

Hunter, J. E., Berry-Kravis, E., Hipp, H., & Todd, P. K. (1998, 06 16). FMR1 Disorders. Retrieved from National Library of Medicine: https://www.ncbi.nlm.nih.gov/books/NBK1384/

Kaufmann, W. E., Kidd, S. A., Andrews, H. F., Budimirovic, D. B., Esler, A., Haas-Givler, B., . . . Berry-Kravis, E. (2017). Autism Spectrum Disorder in Fragile X Syndrome: Cooccurring Conditions and Current Treatment. Pediatrics, Supp(3). S194–S206. https://doi.org/10.1542/peds.2016-1159F.

NORD. (2022, 04 18). Fragile X Syndrome. Retrieved from National Organization of Rare Disorders: https://rarediseases.org/rare-diseases/fragile-x-syndrome/

Pyeritz, R. E., Korf, B. R., & Grody, W. W. (2019). Principles and Practice of medical genetics and genomics, 7th ed. Oxford: Elsevier.

Quartier, A., Poquet, H., B. G.-D., & … (2017). Intragenic FMR1 disease-causing variants: a significant mutational mechanism leading to Fragile-X syndrome. European journal of human genetics : EJHG, 25(4), 423–431. https://doi.org/10.1038/ejhg.2016.204.

Shen, Y., Dies, K. A., Holm, I. A., Bridgemohan, C., Sobeih, M. M., Caronna, E. B., . . . al., e. (2010). Clinical Genetic Testing for Patients With Autism Spectrum Disorders. Pediatrics, 125(4), e727–e735. https://doi.org/10.1542/peds.2009-1684.

Tick, B., Bolton, P., Happé, F., Rutter, M., & Rijsdijk, F. (2016). Heritability of autism spectrum disorders: a meta-analysis of twin studies. Journal of child psychology and psychiatry, and allied disciplines, 57(5),, 585–595. https://doi.org/10.1111/jcpp.12499.