Candidate biomarkers from the integration of methylation and gene expression in discordant autistic sibling pairs

Abstract

While the genetics of autism spectrum disorders (ASD) has been intensively studied, resulting in the identification of over 100 putative risk genes, the epigenetics of ASD has received less attention, and results have been inconsistent across studies. We aimed to investigate the contribution of DNA methylation (DNAm) to the risk of ASD and identify candidate biomarkers arising from the interaction of epigenetic mechanisms with genotype, gene expression, and cellular proportions. We performed DNAm differential analysis using whole blood samples from 75 discordant sibling pairs of the Italian Autism Network collection and estimated their cellular composition. We studied the correlation between DNAm and gene expression accounting for the potential effects of different genotypes on DNAm. We showed that the proportion of NK cells was significantly reduced in ASD siblings suggesting an imbalance in their immune system. We identified differentially methylated regions (DMRs) involved in neurogenesis and synaptic organization. Among candidate loci for ASD, we detected a DMR mapping to CLEC11A (neighboring SHANK1) where DNAm and gene expression were significantly and negatively correlated, independently from genotype effects. As reported in previous studies, we confirmed the involvement of immune functions in the pathophysiology of ASD. Notwithstanding the complexity of the disorder, suitable biomarkers such as CLEC11A and its neighbor SHANK1 can be discovered using integrative analyses even with peripheral tissues.

Fig. 1. Estimated cell-type proportions in ASD and non-ASD subjects.

Statistical significance was calculated using Dirichlet regression and only the proportions of NK cells were significantly different between ASD (green) and non-ASD (orange) subjects (*** meaning a P-value < 0.001). The error bars represent the standard deviation.

Fig. 2. Statistical significance of genome-wide differential methylation between ASD and non-ASD subjects.

Top-ranked DMP (red point) of each top 2% DMR and its corresponding gene (text box).

Fig. 3. Top 1% enriched gene sets.

Biological functions (y-axis) were extracted from four databases (x-axis) and they were ranked by FDR (red gradient) and Normalized Enrichment Score (values inside the tiles). Of the top 1% functions, seven may have an important contribution to the etiology of ASD (highlighted in blue).

Fig. 4. Gene expression and DNAm of CLEC11A.

Gene expression (y-axis) was normalized and adjusted for batch effects and demographic parameters [17]. Median DNAm (i-axis) was calculated for the DMPs that were significantly associated with CLEC11A. Mean (large and black circles) and 95% confidence intervals (black bars) of CLEC11A expression and DNAm are shown for ASD (green; DNAm = 0.514 (0.511–0.517); DGE = −0.151 (−0.307–0.005)) and non-ASD (orange; DNAm = 0.519 (0.516–0.522); DGE = 0.061 (−0.091–0.212)) siblings.