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You are at:Home » Why Autism could soon be identifiable through stool samples – the breakthrough explained
Why Autism Could Soon Be Identifiable Through Stool Samples
Science July 18, 2024

Why Autism could soon be identifiable through stool samples – the breakthrough explained

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New Research has introduced an innovative and cost-effective method for diagnosing autism, potentially simplifying and speeding up the diagnostic process. Surprisingly, the new diagnostic test might involve analyzing stool samples rather than brain scans or psychiatric evaluations. Researchers have discovered consistent differences in the gut microbiome – the population of microorganisms in the intestine – between individuals with autism and those without.

Regularly collecting and analyzing stool samples could potentially enable doctors to identify autism at an earlier stage than current methods allow. This new approach is especially important given the diverse range of symptoms associated with autism, making diagnosis challenging.


“There is a pressing need to delay the diagnosis of autism in children, as the symptoms can vary widely,” according to the co-authors of the study. Professor Shu Qian Ng told BBC Science Focus.

Autism is a common condition, affecting approximately 1 in 100 individuals worldwide. While genetics is thought to play a significant role in autism, other factors such as birth complications, exposure to air pollution, and gender differences may also contribute.

Diagnosing autism currently relies on subjective behavioral assessments and developmental screenings, which can be time-consuming and depend on the availability of trained professionals. The average age of diagnosis in the United States is around 5 years old, resulting in delays in essential care and support for children with autism during crucial developmental stages.

The study, published in Nature Microbiology, analyzed stool samples from 1,627 children between 1 and 13 years of age, some of whom had autism. The researchers identified significant differences in gut bacteria between children with autism and those without, resulting in the identification of specific biomarkers for autism.

Utilizing machine learning algorithms, scientists could determine autism in children with up to 82% accuracy based on the biological function of several microorganisms in the digestive system. This innovative approach offers hope for a non-invasive and efficient diagnostic test for autism, expected to be available by the end of the year.

Read more:

How is the gut microbiome linked to autism?

Dr. Ng explains two primary differences in the gut microbiome of individuals with autism compared to neurotypical individuals. Firstly, individuals with autism tend to have reduced diversity in their gut microbiome, with fewer types of bacteria and viruses. Secondly, children with autism often have an abundance of pathogens in their gut, potentially contributing to their condition.

The ongoing research aims to determine whether interventions such as dietary modifications or probiotics can help improve gut diversity and health, potentially influencing autism symptoms. Early indications suggest that adjusting the microbiome can lead to symptom improvements in children with autism.

While promising, the research does not establish causation between gut biomarkers and autism. Clinical trials are underway to explore the potential of using stool samples as a diagnostic tool for autism in young children.

The study participants were predominantly Chinese, highlighting the need for further global studies to enhance diagnostic accuracy across diverse populations. Despite potential dietary influences, preliminary findings suggest consistent diagnostic performance regardless of dietary habits.

About our experts

Dr. Shu N, a Professor and Associate Dean at The Chinese University of Hong Kong, specializes in investigating the potential of gut microbiota for diagnosing and treating various diseases, including autism. Her research focuses on using microbial markers to predict disease risks and develop personalized interventions for improving health outcomes.

Read more:

Source: www.sciencefocus.com

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