Integrative Transcriptomics and Machine Learning Identify Temporal Stress Signatures and Astrocytic Neurocan Associated With Hypothalamic Injury.
- 1Hebei Medical University Postdoctoral Research Station in Basic Medicine, Shijiazhuang, China.
- 2Hebei Key Laboratory of Forensic Medicine, Collaborative Innovation Center of Forensic Medical Molecular Identification, College of Forensic Medicine, Hebei Medical University, Shijiazhuang, China.
- 3Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University, Shenzhen, China.
Abstract
Background
Stress-related neurological dysfunction evolves dynamically, but molecular markers distinguishing stress stages remain limited. We aimed to characterize temporal hypothalamic transcriptomic changes and identify molecular signatures for stress-stage discrimination.Methods
Whole-transcriptome sequencing was performed in mouse hypothalami after stress. Differential expression, temporal clustering, co-expression network analysis, and machine learning were integrated to identify stress-associated mRNA and miRNA signatures. Candidate markers were validated by RT-qPCR and single-nucleus RNA sequencing. Ncan function was further evaluated by protein supplementation, perineuronal net analysis, behavioral testing, and regulatory network analysis.Results
mRNAs exhibited strong temporal sensitivity and captured stage-specific transcriptional remodeling, whereas miRNAs primarily reflected stress regardless of duration. A six-mRNA signature (Ncan, Mt2, Nab2, Ptch1, and Catspere1/Catspere2) accurately distinguished control, acute stress, and chronic stress (accuracy, 1.000), while an 11-miRNA signature robustly classified stress states (accuracy, 0.944). Both signatures were validated by RT-qPCR and nested cross-validation, with accuracies of 0.898 and 0.890, respectively. Ncan was consistently top-ranked, predominantly expressed in astrocytes, progressively downregulated by stress, and its supplementation restored PNNs and alleviated depressive-like behaviors. Virtual Ncan knockout disrupted the stress network, with Ctcf predicted as its upstream regulator.Conclusion
Our study identifies distinct stress-stage and stress-state transcriptomic signatures and highlights astrocytic Ncan as a candidate biomarker that may contribute to stress-induced neural injury by regulating PNN homeostasis.
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BibTeX
@article{zhu2026integrative,
title = {{Integrative Transcriptomics and Machine Learning Identify Temporal Stress Signatures and Astrocytic Neurocan Associated With Hypothalamic Injury.}},
author = {Weihao Zhu and Chenyu Li and Mengting He and Rui Shi and Xia Liu and Weibo Shi and Bin Cong},
journal = {CNS neuroscience \& therapeutics},
year = {2026},
month = oct,
doi = {10.1002/cns.71219},
url = {https://europepmc.org/article/MED/42924589},
note = {CC BY},
}
RIS
TY - JOUR
TI - Integrative Transcriptomics and Machine Learning Identify Temporal Stress Signatures and Astrocytic Neurocan Associated With Hypothalamic Injury.
AU - Weihao Zhu
AU - Chenyu Li
AU - Mengting He
AU - Rui Shi
AU - Xia Liu
AU - Weibo Shi
AU - Bin Cong
PY - 2026
DA - 2026/10/01
JO - CNS neuroscience & therapeutics
DO - 10.1002/cns.71219
UR - https://europepmc.org/article/MED/42924589
AB - Background Stress-related neurological dysfunction evolves dynamically, but molecular markers distinguishing stress stages remain limited. We aimed to characterize temporal hypothalamic transcriptomic changes and identify molecular signatures for stress-stage discrimination.Methods Whole-transcriptome sequencing was performed in mouse hypothalami after stress. Differential expression, temporal clustering, co-expression network analysis, and machine learning were integrated to identify stress-associated mRNA and miRNA signatures. Candidate markers were validated by RT-qPCR and single-nucleus RNA sequencing. Ncan function was further evaluated by protein supplementation, perineuronal net analysis, behavioral testing, and regulatory network analysis.Results mRNAs exhibited strong temporal sensitivity and captured stage-specific transcriptional remodeling, whereas miRNAs primarily reflected stress regardless of duration. A six-mRNA signature (Ncan, Mt2, Nab2, Ptch1, and Catspere1/Catspere2) accurately distinguished control, acute stress, and chronic stress (accuracy, 1.000), while an 11-miRNA signature robustly classified stress states (accuracy, 0.944). Both signatures were validated by RT-qPCR and nested cross-validation, with accuracies of 0.898 and 0.890, respectively. Ncan was consistently top-ranked, predominantly expressed in astrocytes, progressively downregulated by stress, and its supplementation restored PNNs and alleviated depressive-like behaviors. Virtual Ncan knockout disrupted the stress network, with Ctcf predicted as its upstream regulator.Conclusion Our study identifies distinct stress-stage and stress-state transcriptomic signatures and highlights astrocytic Ncan as a candidate biomarker that may contribute to stress-induced neural injury by regulating PNN homeostasis.
SN - 1755-5930
SN - 1755-5949
ER -