Team:NJMU-China/Description

Can you hear the Sound of Silence ?

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Introduction to ASD

Autism Spectrum Disorder(ASD) is common neurodevelopmental disorder which is defined by three core clinical features ¹:

(1) Impairment in social interaction;

(2) Impairment in communication in social situations;

(3) Restricted and repetitive patterns of behaviors, with considerable phenotypic heterogeneity among individuals.

The prevalence of ASD has been rising remarkably for the last several years, which is thought to affect 1 in 68 in the United States² , a global median of prevalence estimating of 62 per 10,000³ . However, in low-income and middle-income countries (LMIC), most individuals with ASD remain undiagnosed and have no access to support or education⁴ .

Early Intervention is Effective

Back to just a decade ago, children diagnosed with autism were left with almost no help available. But nowadays, autistic children could find a way to live somewhat normal lives as early intensive behavior intervention is proved to be effective. Actually, only about 31% of autistic children suffer from impaired intellectual ability 5. While others enjoy clinical benefits of relieving social adaptation, IQ and language ability after early intervention^6,7.

Problems about the Detection of ASD

Based on researches stated before, ASD should be detected as soon as possible so that early, intensive behavioral intervention can be implemented. However, even though ASD can be diagnosed as early as 6 months, the average age of detection in the USA is as late as 4.5 years old ⁸

The reason for delayed average detection partly relies on its complex etiology. ASD is well recognized to be biologically heterogeneous where various factors are associated, including genetic, metabolic, and environmental ones ⁹. However, despite extensive efforts on the underlying biology, ASD remains defined largely by behavior ¹⁰. And related detection (e.g. M-CHAT Scale) is rather difficult as it mainly bases on recalled information gathered from parents about the child’s development and current situation, along with first-hand observations by an experienced clinician ^11,12. Besides, abnormal behaviors may not emerge until the disorder is well established ¹³.

Other reasons behind the delayed average detection could be social-psychological. Being afraid of the blames from family members or discriminations from others against their child makes parents reluctant to send their child to the hospital for further evaluation and diagnosis ¹⁴.

Our Purpose

There needs to be a better detection plan that satisfies:

(1) As for the complex etiology of ASD, the plan should base not only on behavioral changes, but also on genetic and metabolic alterations.

(2) As for the social-psychological factors that hinder parents, the plan should beprivate, convenient and easy to approach .

(3) Overall, as a screening plan rather than a diagnostic method, it would be better if the plan has higher sensitivity.

Description of Our Plan

Our project consists of two parts: a test strip for domestic tests based on urinary metabolites and further, a parallel screening strategy that increases sensitivity.

PartA: SOS, The Test Strip

The test strip, SOS (Sound of Silence) is embedded withwhole-cell biosensors of elevated urinary serotonin , which was previously reported to play a critical role in ASD development ^15-17. And the biosensor was constructed utilizing the Qurom-Sensing system in Pseudomonas aeruginosa in this project ¹⁸.

Firstly, elevated urinary serotonin level reflects not only metabolic alterations (tryptophan metabolism disorder 19),but also genetic mutations (Ala56, gain-of-function mutation of SERT, a gene that encodes serotonin transporter 20). Meanwhile, the design of biosensorutilizing synthetic biology in our screening plan has unreplaceable economic advantages due to low material costs , which makes our plan easy to approach.

Moreover, our hardware, which is a paper strip, has wide usage scenarios including domestic testing, that has satisfied the requirement of both privacy and convenience ²¹.

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Part B: SOS+, The Parallel Screening Strategy

We employed amachine learning algorithm and find a combination of metabolites for screening that performs best by representing most of the heterogeneous patient population. As for the output metabolites list, we would further investigate according to biosensors in a high-throughput way based on systems-level Escherichia coli genome library construction and screening. The systematic biosensor design was referred to a published pipeline that utilizes next-generation sequencing and computational analysis ²².

Behind this Project

We decided to work on this project mainly because one of our team members was frustrated by his nephew’s delayed diagnosis of autism. We were impressed that the family was held by economic and many other social-psychological factors. So, we decided to work on the early screening of autism, hoping that we could develop a domestic, economic and sensitive method that will contribute to the whole community of ASD patients.

References

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2 Matelski, L. & Van de Water, J. Risk factors in autism: Thinking outside the brain. J Autoimmun 67, 1-7, doi:10.1016/j.jaut.2015.11.003 (2016).
3 Elsabbagh, M. et al. Global prevalence of autism and other pervasive developmental disorders. Autism Res 5, 160-179, doi:10.1002/aur.239 (2012).
4 Kieling, C. et al. Child and adolescent mental health worldwide: evidence for action. The Lancet 378, 1515-1525, doi:10.1016/s0140-6736(11)60827-1 (2011).
5 Shaw, K. A. et al. Early Identification of Autism Spectrum Disorder Among Children Aged 4 Years - Early Autism and Developmental Disabilities Monitoring Network, Six Sites, United States, 2016. Morbidity and mortality weekly report. Surveillance summaries (Washington, D.C. : 2002) 69, 1-11, doi:10.15585/mmwr.ss6903a1 (2020).
6 Weitlauf, A. S. et al. in Therapies for Children With Autism Spectrum Disorder: Behavioral Interventions Update (Agency for Healthcare Research and Quality (US), 2014).
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15 Gevi, F., Zolla, L., Gabriele, S. & Persico, A. M. Urinary metabolomics of young Italian autistic children supports abnormal tryptophan and purine metabolism. Mol Autism 7, 47, doi:10.1186/s13229-016-0109-5 (2016).
16 Qureshi, F., Adams, J., Coleman, D., Quig, D. & Hahn, J. Urinary Essential Elements of Young Children with Autism Spectrum Disorder and their Mothers. Res Autism Spectr Disord 72, doi:10.1016/j.rasd.2020.101518 (2020).
17 Nakai, N. et al. Serotonin rebalances cortical tuning and behavior linked to autism symptoms in 15q11-13 CNV mice. Sci Adv 3, e1603001, doi:10.1126/sciadv.1603001 (2017).
18 Saeidi, N. et al. Engineering microbes to sense and eradicate Pseudomonas aeruginosa, a human pathogen. Mol Syst Biol 7, 521, doi:10.1038/msb.2011.55 (2011).
19 Agus, A., Planchais, J. & Sokol, H. Gut Microbiota Regulation of Tryptophan Metabolism in Health and Disease. Cell Host Microbe 23, 716-724, doi:10.1016/j.chom.2018.05.003 (2018). 20 Israelyan, N. & Margolis, K. G. Reprint of: Serotonin as a link between the gut-brain-microbiome axis in autism spectrum disorders. Pharmacol Res 140, 115-120, doi:10.1016/j.phrs.2018.12.023 (2019).
21 Struss, A., Pasini, P., Ensor, C. M., Raut, N. & Daunert, S. Paper strip whole cell biosensors: a portable test for the semiquantitative detection of bacterial quorum signaling molecules. Anal Chem 82, 4457-4463, doi:10.1021/ac100231a (2010).
22 Naydich, A. D. et al. Synthetic Gene Circuits Enable Systems-Level Biosensor Trigger Discovery at the Host-Microbe Interface. mSystems 4, doi:10.1128/mSystems.00125-19 (2019).