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

Cindy Dowd Greene,Cheryl Tierney-Aves,Frank A. Middleton,Kayla E. Wagner,Mark Barros,Rachel Pauley,Randall L. Carpenter,Steven D. Hicks,Sarah Barns

doi:10.1016/j.jaac.2019.03.017

Abstract

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. 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= 187), TD (n= 125), and DD (n= 69) groups in the training set (n= 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= 37; TD, n= 8; DD, n= 17). Relations between microRNA levels and ASD phenotypes were explored. 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= 0.725) and validation (area under the curve= 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. 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. A Salivary miRNA Diagnostic Test for Autism; https://clinicaltrials.gov/; NCT02832557.

Highlights

Has been limited by several factors: no miRNA study has used more than 55 participants with autism spectrum disorder (ASD),[21] despite the broad, heterogeneous nature of the disorder; no miRNA study has enrolled children at the ages (2–6 years) when ASD diagnosis first occurs; no miRNA study has compared children with ASD to peers with nonautism developmental delay (DD)—a comparison required to develop a robust diagnostic toolset; and no study has examined the ability of miRNA signatures to differentiate ASD phenotypes, a priority for the autism community
Secondary analyses investigated the mRNA targets for 2 sets of miRNAs: the miRNAs “altered” between ASD, typical development (TD), and DD groups based on initial Kruskal-Wallis testing and the miRNAs associated with ASD features at ADOS testing
A panel of 4 miRNAs that controlled for sex, disordered sleep, attention-deficit/hyperactivity disorder (ADHD), family history (Hx) of ASD, gastrointestinal (GI) disturbance, and chronic medical conditions demonstrated an area under the curve (AUC) of 0.725 in the training set (n 1⁄4 381) using a 100-fold cross-validation (CV) approach

Summary

Objective

Clinical diagnosis of autism spectrum disorder (ASD) relies on time-consuming subjective assessments. The clinical applicability of miRNA studies in persons with ASD has been limited by several factors: no miRNA study has used more than 55 participants with ASD,[21] despite the broad, heterogeneous nature of the disorder; no miRNA study has enrolled children at the ages (2–6 years) when ASD diagnosis first occurs (ie, when a diagnostic biomarker panel would have the most clinical utility); no miRNA study has compared children with ASD to peers with nonautism developmental delay (DD)—a comparison required to develop a robust diagnostic toolset; and no study has examined the ability of miRNA signatures to differentiate ASD phenotypes, a priority for the autism community. We hypothesized that characterization of salivary miRNA concentrations in children with ASD, DD, and typical development (TD) would identify a panel of miRNAs with diagnostic potential We posited that these miRNAs would exhibit brain-related targets on functional pathway analyses and display associations with specific autism phenotypes (assessed through standard measures of communication, socialization, and repetitive behavior)

METHOD

Participants

RESULTS

Training Set

Test Set

DISCUSSION