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Salivary miRNA profiles identify children with autism spectrum disorder, correlate with adaptive behavior, and implicate ASD candidate genes involved in neurodevelopment

Overview of attention for article published in BMC Pediatrics, April 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (84th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

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13 X users
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2 patents
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1 Facebook page

Citations

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223 Mendeley
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Title
Salivary miRNA profiles identify children with autism spectrum disorder, correlate with adaptive behavior, and implicate ASD candidate genes involved in neurodevelopment
Published in
BMC Pediatrics, April 2016
DOI 10.1186/s12887-016-0586-x
Pubmed ID
Authors

Steven D. Hicks, Cherry Ignacio, Karen Gentile, Frank A. Middleton

Abstract

Autism spectrum disorder (ASD) is a common neurodevelopmental disorder that lacks adequate screening tools, often delaying diagnosis and therapeutic interventions. Despite a substantial genetic component, no single gene variant accounts for >1 % of ASD incidence. Epigenetic mechanisms that include microRNAs (miRNAs) may contribute to the ASD phenotype by altering networks of neurodevelopmental genes. The extracellular availability of miRNAs allows for painless, noninvasive collection from biofluids. In this study, we investigated the potential for saliva-based miRNAs to serve as diagnostic screening tools and evaluated their potential functional importance. Salivary miRNA was purified from 24 ASD subjects and 21 age- and gender-matched control subjects. The ASD group included individuals with mild ASD (DSM-5 criteria and Autism Diagnostic Observation Schedule) and no history of neurologic disorder, pre-term birth, or known chromosomal abnormality. All subjects completed a thorough neurodevelopmental assessment with the Vineland Adaptive Behavior Scales at the time of saliva collection. A total of 246 miRNAs were detected and quantified in at least half the samples by RNA-Seq and used to perform between-group comparisons with non-parametric testing, multivariate logistic regression and classification analyses, as well as Monte-Carlo Cross-Validation (MCCV). The top miRNAs were examined for correlations with measures of adaptive behavior. Functional enrichment analysis of the highest confidence mRNA targets of the top differentially expressed miRNAs was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID), as well as the Simons Foundation Autism Database (AutDB) of ASD candidate genes. Fourteen miRNAs were differentially expressed in ASD subjects compared to controls (p <0.05; FDR <0.15) and showed more than 95 % accuracy at distinguishing subject groups in the best-fit logistic regression model. MCCV revealed an average ROC-AUC value of 0.92 across 100 simulations, further supporting the robustness of the findings. Most of the 14 miRNAs showed significant correlations with Vineland neurodevelopmental scores. Functional enrichment analysis detected significant over-representation of target gene clusters related to transcriptional activation, neuronal development, and AutDB genes. Measurement of salivary miRNA in this pilot study of subjects with mild ASD demonstrated differential expression of 14 miRNAs that are expressed in the developing brain, impact mRNAs related to brain development, and correlate with neurodevelopmental measures of adaptive behavior. These miRNAs have high specificity and cross-validated utility as a potential screening tool for ASD.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 223 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Czechia 1 <1%
Unknown 222 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 34 15%
Researcher 25 11%
Student > Bachelor 20 9%
Student > Ph. D. Student 18 8%
Other 12 5%
Other 43 19%
Unknown 71 32%
Readers by discipline Count As %
Medicine and Dentistry 30 13%
Psychology 27 12%
Biochemistry, Genetics and Molecular Biology 24 11%
Neuroscience 20 9%
Agricultural and Biological Sciences 20 9%
Other 27 12%
Unknown 75 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 November 2022.
All research outputs
#2,970,263
of 24,736,359 outputs
Outputs from BMC Pediatrics
#432
of 3,316 outputs
Outputs of similar age
#45,602
of 304,622 outputs
Outputs of similar age from BMC Pediatrics
#6
of 28 outputs
Altmetric has tracked 24,736,359 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,316 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done well, scoring higher than 86% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 304,622 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 84% of its contemporaries.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.