Oral microbiome activity in children with autism spectrum disorder

Hicks, Steven D.; Uhlig, Richard; Afshari, Parisa; Williams, Jeremy; Chroneos, Maria Z; Tierney‐Aves, Cheryl; Wagner, Kayla E.; Middleton, Frank A.

doi:10.1002/aur.1972

Cited by 52 publications

(68 citation statements)

References 43 publications

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“…In the present study, the salivary miRNA content and the oral microbiome were evaluated in a group of pediatric patients with ASD syndrome, compared with neurotypical subjects. MiRnome and microbiome dysregulation in saliva of ASD patients was previously reported by other groups, but there is only a partial concordance with the data presented here [ 47 , 59 , 60 , 61 ]. The salivary microbiome structure in human beings is strongly affected by the geographical, climatic and ethnic origin of samples [ 62 , 63 , 64 ].…”

Section: Discussionsupporting

confidence: 92%

Potential Associations Among Alteration of Salivary miRNAs, Saliva Microbiome Structure, and Cognitive Impairments in Autistic Children

Ragusa

Santagati

Mirabella

et al. 2020

IJMS

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Recent evidence has demonstrated that salivary molecules, as well as bacterial populations, can be perturbed by several pathological conditions, including neuro-psychiatric diseases. This relationship between brain functionality and saliva composition could be exploited to unveil new pathological mechanisms of elusive diseases, such as Autistic Spectrum Disorder (ASD). We performed a combined approach of miRNA expression profiling by NanoString technology, followed by validation experiments in qPCR, and 16S rRNA microbiome analysis on saliva from 53 ASD and 27 neurologically unaffected control (NUC) children. MiR-29a-3p and miR-141-3p were upregulated, while miR-16-5p, let-7b-5p, and miR-451a were downregulated in ASD compared to NUCs. Microbiome analysis on the same subjects revealed that Rothia, Filifactor, Actinobacillus, Weeksellaceae, Ralstonia, Pasteurellaceae, and Aggregatibacter increased their abundance in ASD patients, while Tannerella, Moryella and TM7-3 decreased. Variations of both miRNAs and microbes were statistically associated to different neuropsychological scores related to anomalies in social interaction and communication. Among miRNA/bacteria associations, the most relevant was the negative correlation between salivary miR-141-3p expression and Tannerella abundance. MiRNA and microbiome dysregulations found in the saliva of ASD children are potentially associated with cognitive impairments of the subjects. Furthermore, a potential cross-talking between circulating miRNAs and resident bacteria could occur in saliva of ASD.

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Section: Discussionsupporting

confidence: 92%

Potential Associations Among Alteration of Salivary miRNAs, Saliva Microbiome Structure, and Cognitive Impairments in Autistic Children

Ragusa

Santagati

Mirabella

et al. 2020

IJMS

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“…Microbial transcripts were employed in favor of a 16S approach to simplify and streamline nucleic acid extraction and analysis, and facilitate downstream clinical application. In addition, previous studies have demonstrated the potential for microbial RNA to differentiate children with ASD ( Hicks et al, 2018 ).…”

Section: Methodsmentioning

confidence: 99%

Validation of a Salivary RNA Test for Childhood Autism Spectrum Disorder

Hicks

Rajan²,

Wagner

et al. 2018

Front. Genet.

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Background: The diagnosis of autism spectrum disorder (ASD) relies on behavioral assessment. Efforts to define biomarkers of ASD have not resulted in an objective, reliable test. Studies of RNA levels in ASD have demonstrated potential utility, but have been limited by a focus on single RNA types, small sample sizes, and lack of developmental delay controls. We hypothesized that a saliva-based poly-“omic” RNA panel could objectively distinguish children with ASD from their neurotypical peers and children with non-ASD developmental delay.Methods: This multi-center cross-sectional study included 456 children, ages 19–83 months. Children were either neurotypical (n = 134) or had a diagnosis of ASD (n = 238), or non-ASD developmental delay (n = 84). Comprehensive human and microbial RNA abundance was measured in the saliva of all participants using unbiased next generation sequencing. Prior to analysis, the sample was randomly divided into a training set (82% of subjects) and an independent validation test set (18% of subjects). The training set was used to develop an RNA-based algorithm that distinguished ASD and non-ASD children. The validation set was not used in model development (feature selection or training) but served only to validate empirical accuracy.Results: In the training set (n = 372; mean age 51 months; 75% male; 51% ASD), a set of 32 RNA features (controlled for demographic and medical characteristics), identified ASD status with a cross-validated area under the curve (AUC) of 0.87 (95% CI: 0.86–0.88). In the completely separate validation test set (n = 84; mean age 50 months; 85% male; 60% ASD), the algorithm maintained an AUC of 0.88 (82% sensitivity and 88% specificity). Notably, the RNA features were implicated in physiologic processes related to ASD (axon guidance, neurotrophic signaling).Conclusion: Salivary poly-omic RNA measurement represents a novel, non-invasive approach that can accurately identify children with ASD. This technology could improve the specificity of referrals for ASD evaluation or provide objective support for ASD diagnoses.

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“…33 For this reason, this study specifically excluded children with active dental infections or decay. There are alterations in the oral microbiome of children with ASD 34 that can drive a portion of salivary miRNA changes, but oral microbiome differences in children with ASD are largely unrelated to the bacteria implicated in dental carries. 35 Children with ASD experience difficulties with oralmotor (speech apraxia) and oral-sensory (food texture sensitivity) processing.…”

Section: Discussionmentioning

confidence: 99%

Saliva MicroRNA Differentiates Children With Autism From Peers With Typical and Atypical Development

Hicks

Carpenter

Wagner³

et al. 2020

Journal of the American Academy of Child & Adolescent Psych

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Objective: Clinical diagnosis of autism spectrum disorder (ASD) relies on time-consuming subjective assessments. The primary purpose of this study was to investigate the utility of salivary microRNAs for differentiating children with ASD from peers with typical development (TD) and non-autism developmental delay (DD). The secondary purpose was to explore microRNA patterns among ASD phenotypes. Method: This multicenter, prospective, case-control study enrolled 443 children (2-6 years old). ASD diagnoses were based on DSM-5 criteria. Children with ASD or DD were assessed with the Autism Diagnostic Observation Schedule II and Vineland Adaptive Behavior Scales II. MicroRNAs were measured with high-throughput sequencing. Differential expression of microRNAs was compared among the ASD (n ¼ 187), TD (n ¼ 125), and DD (n ¼ 69) groups in the training set (n ¼ 381). Multivariate logistic regression defined a panel of microRNAs that differentiated children with ASD and those without ASD. The algorithm was tested in a prospectively collected naïve set of 62 samples (ASD, n ¼ 37; TD, n ¼ 8; DD, n ¼ 17). Relations between microRNA levels and ASD phenotypes were explored. Result: Fourteen microRNAs displayed differential expression (false discovery rate < 0.05) among ASD, TD, and DD groups. A panel of 4 microRNAs (controlling for medical/demographic covariates) best differentiated children with ASD from children without ASD in training (area under the curve ¼ 0.725) and validation (area under the curve ¼ 0.694) sets. Eight microRNAs were associated (R > 0.25, false discovery rate < 0.05) with social affect, and 10 microRNAs were associated with restricted/repetitive behavior. Conclusion: Salivary microRNAs are "altered" in children with ASD and associated with levels of ASD behaviors. Salivary microRNA collection is noninvasive, identifying ASD-status with moderate accuracy. A multi-"omic" approach using additional RNA families could improve accuracy, leading to clinical application. Clinical trial registration information: A Salivary miRNA Diagnostic Test for Autism; https://clinicaltrials.gov/; NCT02832557.

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Oral microbiome activity in children with autism spectrum disorder

Cited by 52 publications

References 43 publications

Potential Associations Among Alteration of Salivary miRNAs, Saliva Microbiome Structure, and Cognitive Impairments in Autistic Children

Potential Associations Among Alteration of Salivary miRNAs, Saliva Microbiome Structure, and Cognitive Impairments in Autistic Children

Validation of a Salivary RNA Test for Childhood Autism Spectrum Disorder

Saliva MicroRNA Differentiates Children With Autism From Peers With Typical and Atypical Development

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