International Journal of Molecular SciencesNeurosciencePeer-reviewed journal article
Integration of transcriptional signatures from brain tissue and plasma extracellular vesicles of a preclinical tauopathy mouse model
Tanzima Tarannum LucyiD, A. N. M. Mamun-Or-RashidiD, Daniel C. LeeiD, Iliya M. LefteroviD, Radosveta P. KoldamovaiD, Nicholas Francis FitziD
Abstract
Tauopathies, including Alzheimers disease, involve progressive neurodegeneration and sustained neuroinflammation. We present a multi-compartment transcriptomic atlas of 9.6-month-old PS19 tauopathy mice compared with wild-type (WT) controls (n=8/group), profiling cortical mRNA, cortical non-coding RNA (ncRNA), and plasma small extracellular vesicle (pEV) ncRNA. In the PS19 cortex, mRNA sequencing identified 917 differentially expressed genes (DEGs), with microglial deconvolution revealing a robust transition toward disease-associated microglia (DAM) gene signature and downregulation of genes involved in oxidative phosphorylation and cholesterol biosynthesis relative to WT. Cortical ncRNA profiling identified 466 differentially expressed ncRNAs, primarily circular RNAs (circRNAs; n=331). In pEVs, 822 ncRNAs were differentially abundant, of which 657 circRNAs were identified in PS19 compared to WT mice. Cross-compartment integration demonstrated that pEV miRNA gene targets functionally mirrored genes involved in the brains inflammatory and metabolic failure. We identified a core shared signature of 33 ncRNAs, including miR-5114 (up in brain, down in pEV), circ_0008242 and circ_0002153 (up in brain and pEV), and circ_0007688 (down in brain and pEV) differentially enriched across both brain and periphery in PS19 compared to WT mice. These results demonstrate that the pEV non-coding landscape effectively tracks central tau-mediated changes in the brain transcriptional response. This study identifies circRNAs as the most numerically perturbed ncRNA class and provides a foundation for non-invasive biomarker development in tauopathy.
- organism: mouse
- assay: bulk RNA-seq
- assay: spatial transcriptomics
- research focus: differential expression
- research focus: benchmarking
- approach: statistical model
- Citations
- 0
- FWCI
- 0.00
- Field percentile
- 38th percentile
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