Correlations between Psychological Assessments and RNA Concentrations in Saliva of Adolescents and Adults with ASD

Background: The prevalence rates of autism spectrum disorder (ASD) have steadily increased over the past two decades, nearly tripling since 2002. Current assessment procedures rely on behavioral assessments and parent-report surveys that can be influenced by situational variables. An objective molecular indicator of ASD symptom severity could inform treatment plans. Recent literature suggests that epigenetic factors, such as poly-omic RNA levels in saliva, can accurately distinguish school-aged children with ASD from their peers. We examined concentrations of salivary RNAs in a cohort of adolescents and young adults with ASD and compared RNA patterns with non-ASD peers to determine whether saliva RNA markers informed symptom severity and adaptive functioning.

Objectives: The current study compared ASD symptom severity and adaptive functioning to concentrations of human saliva RNAs, including mature/precursor microRNA (miRNA), piwi-interacting RNA (piRNA), long intergenic non-coding RNA (lincRNA), and ribosomal RNA (rRNA), to identify saliva RNA markers that correlate with behavioral phenotypes.

Methods: 53 individuals (26 ASD, 26 non-ASD; M = 12 yrs) were assessed using the Autism Diagnostic Observation Schedule (ADOS) and the Vineland Adaptive Behavior Scales 2nd Edition (VABS-II). Approximately 3 mLs of saliva were collected during a non-fasting state via expectoration into an Oragene RNA collection kit (DNA Genotek, Ottawa Canada). RNA was sequenced using an Illumina TruSeq Small RNA Prep protocol and a NextSeq500 instrument (Illumina; San Diego, CA, United States). Quantification of RNA reads were determined using the SHRiMP2 and Bowtie aligners in Partek Flow (Partek; St. Louis, MO, United States). Reference databases used for transcript assignment included miRBase version 21, RefSeq Transcripts 84, and the Human piRNA sequence v1.0 reference index. After alignment, a data transformation was applied to reduce batch effects and to study the full expression range of the RNAs. Sequencing data was transformed by applying an inverse hyperbolic sine transformation followed by cumulative sum scaling normalization. Associations between behavioral assessment scores and miRNA concentrations were performed using Spearman’s Rank Correlation. In total, about 200 transcripts per RNA category were compared to 9 independent behavioral scores derived from the ADOS and VABS-II assessments.

Results: Results show significant correlations (p < .05) between sequencing data and both the VABS-II Socialization score and the ADOS-2 composite score. Spearman correlation coefficients ranged from +/- 0.5, suggesting relationships of weak to moderate strengths. Statistically significant correlations were found in each RNA category investigated (miRNA, piRNA, lincRNA, and rRNA), with mature/precursor microRNAs containing the strongest relationships between transcript counts and behavioral scores. Some of these microRNAs were the same as those identified in our previous pilot study of salivary microRNAs from an independent cohort of ASD and control subjects.

Conclusions: Poly-omic RNA levels are associated with both symptom severity and adaptive functioning in adolescents and young adults with ASD. This finding suggests that RNA profiles are a promising molecular marker with the potential to provide useful clinical data informing patient management and treatment plans.