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Updated: Aug 14, 2026

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions
Published on: March 5, 2022
Cross-Omic Comparative Analysis Identifies Transcriptomic Signatures and Exploratory Gene Set-Level Signals in
Ramandeep Kaur Oberoi1,2, Deepti Gurung2, Laura K Harris2
1Department of Health Informatics, School of Health Professions, Rutgers, The State University of New Jersey, Newark, NJ 07107, USA.
Abstract:
Sporadic Creutzfeldt-Jakob disease (sCJD) is a rapidly progressive fatal neurodegenerative disease whose basis of pathogenesis remains incompletely defined. Public datasets allow molecular changes to be compared across transcriptomic, post-transcriptional, and epigenomic layers, but comparisons are limited by differences in tissue source and platform. We performed a cross-omic comparative analysis of four sCJD case-control datasets spanning mRNA, miRNA, and DNA methylation layers. In this study, cross-omic refers to comparison of independently analyzed molecular datasets rather than joint multi-omic modeling of matched molecular layers from the same samples. Differential feature analysis, overrepresentation analysis, and gene set enrichment analysis were conducted within each layer. Reproducibility was evaluated across discovery and validation cohorts, followed by cross-layer comparison at the gene level and GO-BP gene set level. FDR-controlled overlap was treated as the primary analysis, whereas nominal p < 0.05 overlap was considered exploratory. Gene-level overlap across molecular layers was limited, consistent with tissue and platform heterogeneity. Under FDR-controlled criteria, cross-omic GO-BP gene set overlap was not observed. Exploratory nominal-threshold analyses identified recurrent gene set-level signals, mainly between transcriptomic and DNA methylation datasets, including GO-BP terms related to cell-substrate adhesion. These findings support cross-omic comparative analysis as a framework for identifying hypothesis-generating patterns in rare neurodegenerative diseases.
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