MCVAE-based multi-omic anomaly detection in Fragile X Syndrome

Fragile X Syndrome (FXS) is a neurodevelopmental disorder caused by mutations in the FMR1 gene, resulting in the loss of FMRP, an RNA-binding protein regulating translation of hundreds of mRNAs. The Fmr1 knock-out mouse models this deficiency and is used to study molecular perturbations in the FXS brain. Omics analysis shows that FMRP loss disrupts coordination between transcriptomic and translatomic layers. But limited sample availability and dataset heterogeneity hinder detection of subtle, coordinated multi-omic dysregulations. To address this, we trained a Multi-Channel Variational Autoencoder (MCVAE) on wild-type samples to learn a shared latent representation of transcriptomic and translatomic modalities via cross-modal reconstruction. Testing MCVAE on Fmr1-knock-out samples revealed deviations from wild-type as anomalies, uncovering known and novel perturbations. Compared to alternative methods, MCVAE shows stronger enrichment for FMRP mRNA targets and improved genotype discriminative power in post-hoc tests. Translatomic anomalies exhibited coordinated relationships with transcriptomic anomalies, as supported by publicly available databases exploration. Moreover, these anomalies mapped to validated FMRP regulators and neurodevelopmental pathways, establishing MCVAE as a framework to uncover coordinated molecular perturbations underlying the FXS pathophysiology and guide biomarker and therapeutic target identification.