Aging · 2021 · 26 citations · 38 references
Life SciencesMolecular BiologyNeuroscienceGene ExpressionMolecular NeuroscienceTranscriptomicsAlzheimer DiseaseBiomarkers Of NeurodegenerationDementia BiomarkersGene Expression ProfilingNeurodegenerative DiseasesNeurodegenerative DisordersAlzheimer Disease ProgressionAlzheimer Disease Tau PathologyBiomarkersMessenger Rna BiomarkersMicrorna BiomarkersNeurodegenerative Disease BiomarkersTranscriptome AnalysisTranscriptome Biomarkers
Dysregulation of transcriptome expression has been reported to play an increasingly significant role in AD. In this study, we firstly identified a vital gene module associated with the accumulation of β-amyloid (Aβ) and phosphorylated tau (p-tau) using the WGCNA method. The vital module, named target module, was then employed for the identification of key transcriptome biomarkers. For coding RNA, GNA13 and GJA1 were identified as key biomarkers based on ROC analysis. As for non-coding RNA, MEG3, miR-106a-3p, and miR-24-3p were determined as key biomarkers based on analysis of a ceRNA network and ROC analysis. Experimental analyses firstly confirmed that GNA13, GJA1, and ROCK2, a downstream effector of GNA13, were all increased in 5XFAD mice, compared to littermate mice. Moreover, their expression was increased with aging in 5XFAD mice, as Aβ and p-tau pathology developed. Besides, the expression of key ncRNA biomarkers was verified to be decreased in 5XFAD mice. GSEA results indicated that GNA13 and GJA1 were respectively involved in ribosome and spliceosome dysfunction. MEG3, miR-106a-3p, and miR-24-3p were identified to be involved in MAPK pathway and PI3K-Akt pathway based on enrichment analysis. In summary, we identified several key transcriptome biomarkers, which promoted the prediction and diagnosis of AD.
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