Abstract
Genetic and environmental factors, alone or in combination, contribute to the pathogenesis of autism spectrum disorder (ASD). Although many protein-coding genes have now been identified as disease risk genes for ASD, a detailed illustration of long non-coding RNAs (lncRNAs) associated with ASD remains elusive. In this study, we first identified ASD-related lncRNAs based on genomic variant data of individuals with ASD from a twin study. In total, 532 ASD-related lncRNAs were identified, and 86.7% of these ASD-related lncRNAs were further validated by an independent copy number variant (CNV) dataset. Then, the functions and associated biological pathways of ASD-related lncRNAs were explored by enrichment analysis of their three different types of functional neighbor genes (i.e., genomic neighbors, competing endogenous RNA (ceRNA) neighbors, and gene co-expression neighbors in the cortex). The results have shown that most of the functional neighbor genes of ASD-related lncRNAs were enriched in nervous system development, inflammatory responses, and transcriptional regulation. Moreover, we explored the differential functions of ASD-related lncRNAs in distinct brain regions by using gene co-expression network analysis based on tissue-specific gene expression profiles. As a set, ASD-related lncRNAs were mainly associated with nervous system development and dopaminergic synapse in the cortex, but associated with transcriptional regulation in the cerebellum. In addition, a functional network analysis was conducted for the highly reliable functional neighbor genes of ASD-related lncRNAs. We found that all the highly reliable functional neighbor genes were connected in a single functional network, which provided additional clues for the action mechanisms of ASD-related lncRNAs. Finally, we predicted several potential drugs based on the enrichment of drug-induced pathway sets in the ASD-altered biological pathway list. Among these drugs, several (e.g., amoxapine, piperine, and diflunisal) were partly supported by the previous reports. In conclusion, ASD-related lncRNAs participated in the pathogenesis of ASD through various known biological pathways, which may be differential in distinct brain regions. Detailed investigation into ASD-related lncRNAs can provide clues for developing potential ASD diagnosis biomarkers and therapy.
Highlights
Autism spectrum disorders (ASDs) are a group of heterogeneous neurodevelopmental disorders characterized by deficits in reciprocal social interaction and communication, and restricted interests and repetitive stereotypical behavior, with male-tofemale prevalence nearly 3:1 (Constantino and Charman, 2016; Loomes et al, 2017)
We found that more than a half of ASD-related long non-coding RNAs (lncRNAs) came from genome intergenic regions, and lncRNAs which were generated from the antisense strand of protein-coding genes, occupied a large proportion (Figure 1A)
We found that ASD-related lncRNAs identified using lncRNA genes as reference genomic annotations included 100 and 83.52% of the ASD-related lncRNAs identified using lncRNA exons and lncRNA genes with promoters, respectively
Summary
Autism spectrum disorders (ASDs) are a group of heterogeneous neurodevelopmental disorders characterized by deficits in reciprocal social interaction and communication, and restricted interests and repetitive stereotypical behavior, with male-tofemale prevalence nearly 3:1 (Constantino and Charman, 2016; Loomes et al, 2017). Long non-coding RNAs (lncRNAs), which are defined as non-coding transcripts with more than 200 nucleotides in length, perform diverse regulation functions through a variety of mechanisms, including cell cycle regulation, RNA processing and editing, molecular scaffold, chromatin remodeling, genome imprinting, miRNA sponges, and transcriptional regulation (Mercer and Mattick, 2013; Marchese et al, 2017). It has been shown that the mutation and dysregulation of lncRNAs are involved in a wide variety of diseases, including cancer, neurological disorders, and cardiovascular diseases (Uchida and Dimmeler, 2015; Bhan et al, 2017; Chen et al, 2017; Tang et al, 2017).
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