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They manage to diagnose autism through a single hair

Autism spectrum disorder (ASD) is characterized by disturbances in communication and social interactions, restricted behavior patterns, hypersensitivity, and hyposensitivity. It is associated with significant impairment in social, occupational, and other important areas of adaptive functioning. It is commonly diagnosed from 14 months to three years of age; however, it can be present from birth. Its assessment is carried out through the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), which has clinically validated scales and checklists. Although genetic factors are usually the main reason for the appearance of ASD in most cases, in recent years various prenatal (viral infections, alterations in the immune system, zinc deficiency) and postnatal (exposures to drugs, certain foods or heavy metals) environmental risk factors have been studied alternately, which have also been significantly interrelated to the development of autism.

In a Japanese national prospective study called JECS, focused on the investigation of environmental factors that could affect the health and development of children, where 82,413 participants were followed from conception to three years of age, of which 220 (and 110 cases with ASD) were selected; in parallel, studies were conducted in Swedish participants (national cross-sectional study with twins, n = 138 and 42 cases with ASD) and American (cross-sectional study of a single clinical center with neurotypical population, n = 128 and 23 cases with ASD). The collected hair samples were analyzed by mass spectrometry of elemental metabolism to identify biomarkers of ASD and then a machine learning algorithm was trained with 80% of the generated data and tested on an exclusion set of the remaining 20% of randomly selected data, to compare the diagnostic result of the algorithm with respect to the reference of the current gold standard of formal clinical diagnosis of ASD according to the DSM-5.

To characterize the model’s performance, they constructed receiver operating characteristic (ROC) curves. According to the optimal criterion, the model yielded a sensitivity of 96% (95% CI: 82-100%), specificity of 75% (95% CI: 64-85%), specificity of 81% (95% CI: 72-89%) and overall accuracy (Youden index) of 0.71. Regarding the performance of the model stratified by sex and age categories, there was no statistical significance regarding the overall performance of the device.

The findings of Austin et al., emphasize that the dynamics of elemental metabolism are systemically dysregulated in patients with ASD and that the biomarker signatures generated allow identifying the onset of ASD with as little as one month of age. More than a year after the launch of StrandDx-ASD (as the model has been named), it has FDA approval, and its sponsor Linus Biotechnology has received 16 million dollars for the financing of the generation of more clinical data to demonstrate its diagnostic accuracy.

Abbreviations:

DSM-5: Diagnostic and Statistical Manual of Mental Disorders, fifth edition.

JECS: The Japan Environment and Children’s Study.

ROC: Receiver Operating Characteristic.

CI: Confidence Interval.

Dr. Wendy López Romero

Research and Development Analyst at Drox Health Science. PhD in Innovation in Medical and Pharmaceutical Biotechnology. Master in Molecular Biology.

Sources

Murray, M. J., Mayes, S. D., & Smith, L. A. (2011). Brief report: excellent agreement between two brief autism scales (Checklist for Autism Spectrum Disorder and Social Responsiveness Scale) completed independently by parents and the Autism Diagnostic Interview-Revised. Journalofautismanddevelopmentaldisorders , 41(11), 1586-1590.

Grabrucker, A. M. (2013). Environmental factors in autism. Frontiersinpsychiatry 3, 118.

Austin, C., Curtin, P., Arora, M., Reichenberg, A., Curtin, A., Iwai-Shimada, M., ... & Nakayama, S. F. (2022). Elemental dynamics in hair accurately predict future autism spectrum disorder diagnosis: an international multi-center study. Journalofclinical medicine 11(23), 7154.