Dataset Information

Validation of a Salivary RNA Test for Childhood Autism Spectrum Disorder.

ABSTRACT: 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.

SUBMITTER: Hicks SD

PROVIDER: S-EPMC6237842 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Validation of a Salivary RNA Test for Childhood Autism Spectrum Disorder.

Hicks Steven D SD Rajan Alexander T AT Wagner Kayla E KE Barns Sarah S Carpenter Randall L RL Middleton Frank A FA

Frontiers in genetics 20181109

<b>Background:</b> 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 pe ...[more]

PMID: 30473705

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Project description:The Rapid Interactive screening Test for Autism in Toddlers (RITA-T) is a fast and inexpensive early screening measure for autism spectrum disorder (ASD) that was tested previously in children 18-36 months-old; the current validation study compared the RITA-T with the Autism Diagnostic Observation Schedule™ Second Edition (ADOS-2). The hypothesis is to validate the RITA-T with comparison to the ADOS-2. Thirty-five individuals (18-84 months-old) identified as at risk for ASD received the RITA-T and the ADOS-2 during a single visit. Participants were split into two age groups and both whole-group and sub-group data analysis were conducted. With all participants, RITA-T scores correlated significantly with ADOS-2 total scores (P < 0.001), social affect (SA) sub-scores (P < 0.001), and restrictive and repetitive behavior (RRB) sub-scores (P < 0.05). Similarly, ADOS-2 total and SA scores were significantly correlated in both age groups, while the RRB sub-score was only significant in females (P < 0.05). Lastly, correlations using subgroups based on ethnicity were only significant in the minority ("Other") group for ADOS-2 total scores and in the Asian group for SA sub-scores (P < 0.05). Our receiver operating characteristic analysis showed that the optimal cut-off score of the RITA-T was consistently at 14, with a sensitivity of 81% and a specificity of 89% in the combined age group with the ADOS-2 and with a sensitivity 74% and specificity 50% with the DSM-5; The area under the curve was 0.84 (95%CI: 0.69-0.99) for ASD classified by ADOS-2 and 0.89 (95%CI: 0.79-0.99) for ASD diagnosed by DSM-5. The RITA-T performed similarly to the ADOS-2 when both were administered in a single visit. Significant correlations between the measures help validate the potential usefulness of the RITA-T as a rapid early screening measure of ASD. This study helps to show that the RITA-T may be used in a larger age range than originally reported and in different ethnic groups. The study involves human participants and was reviewed and approved by the Institutional Review Board (IRB) of Massachusetts General Hospital (MGH, 2017P0000857).

Project description:Reliable molecular signatures are needed to improve the early and accurate diagnosis of autism spectrum disorder (ASD), and indicate physicians to provide timely intervention. This study aimed to identify a robust blood small nuclear RNA (snRNA) signature in diagnosing ASD. 186 blood samples in the microarray dataset were randomly divided into the training set (n = 112) and validation set (n = 72). Then, the microarray probe expression profiles were re-annotated into the expression profiles of 1253 snRNAs though probe sequence mapping. In the training set, least absolute shrinkage and selection operator (LASSO) penalized generalized linear model was adopted to identify the 9-snRNA signature (RNU1-16P, RNU6-1031P, RNU6-258P, RNU6-335P, RNU6-485P, RNU6-549P, RNU6-98P, RNU6ATAC26P, and RNVU1-15), and a diagnostic score was calculated for each sample according to the snRNA expression levels and the model coefficients. The score demonstrated a good diagnostic ability for ASD in the training set (area under receiver operating characteristic curve (AUC) = 0.90), validation set (AUC = 0.87), and the overall (AUC = 0.88). Moreover, the blood samples of 23 ASD patients and 23 age- and gender-matched controls were collected as the external validation set, in which the signature also showed a good diagnostic ability for ASD (AUC = 0.88). In subgroup analysis, the signature was robust when considering the confounders of gender, age, and disease subtypes, and displayed a significantly better performance among the female and younger cases (P = .039; P = .002). In comparison with a 55-gene signature deriving from the same dataset, the snRNA signature showed a better diagnostic ability (AUC: 0.88 vs 0.80, P = .049). In conclusion, this study identified a novel and robust blood snRNA signature in diagnosing ASD, which might help improve the diagnostic accuracy for ASD in clinical practice. Nevertheless, a large-scale prospective study was needed to validate our results.

Dataset Information

Validation of a Salivary RNA Test for Childhood Autism Spectrum Disorder.

Publications

Validation of a Salivary RNA Test for Childhood Autism Spectrum Disorder.

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