Three autophagy-associated genes—CDKN1A, HSPA5, and NR4A1—were identified as crucial pathogenic biomarkers and potential therapeutic targets for sleep deprivation through integrated transcriptomic analysis and experimental validation.
Key Findings
Results
Three autophagy-associated differentially expressed genes (CDKN1A, HSPA5, and NR4A1) were identified as key predictor genes in sleep deprivation through machine learning algorithms.
Primary SD transcriptomic datasets GSE33302 and GSE9442 derived from murine brain tissue were retrieved from GEO to identify DEGs.
Murine gene symbols were mapped to human orthologs and intersected with autophagy-related genes (ARGs) from the GeneCards database to identify autophagy-associated DEGs.
Candidate predictor genes were selected using machine learning (ML) algorithms from among the autophagy-associated DEGs.
The three genes were described as 'significantly dysregulated predictor genes.'
Results
A diagnostic model incorporating CDKN1A, HSPA5, and NR4A1 demonstrated strong predictive performance for sleep deprivation.
Diagnostic performance was evaluated through nomogram construction and receiver operating characteristic (ROC) curve analysis.
Expression was validated in both internal and external datasets: GSE9441 (murine brain tissue) and GSE3767 (human peripheral blood samples).
The model was described as demonstrating 'strong predictive performance' across both internal and external validation cohorts.
Results
RT-qPCR validation in a rat sleep deprivation model confirmed expression changes of the candidate gene orthologs in brain tissue.
An SD rat model was established using male Sprague-Dawley rats exposed to continuous sleep deprivation for seven consecutive days.
Brain tissues were harvested from the prefrontal cortex and hippocampus.
Expression levels of rat orthologs of CDKN1A, HSPA5, and NR4A1 were quantified using reverse transcription-quantitative PCR (RT-qPCR).
Results
Single-cell RNA sequencing revealed that CDKN1A, HSPA5, and NR4A1 are preferentially expressed in distinct cell types in the brain.
Single-cell transcriptomic profiling was performed using dataset GSE37665.
CDKN1A was preferentially and highly expressed in endothelial cells.
HSPA5 was preferentially and highly expressed in glial cells.
NR4A1 was preferentially and highly expressed in neurons.
The distinct cellular distribution implies 'distinct functional roles across different cellular subpopulations.'
Results
Immune cell infiltration analysis indicated a potential association between the three key predictor genes and modifications in the immune microenvironment in sleep deprivation.
The immune landscape associated with SD was inferred using single-sample gene set enrichment analysis (ssGSEA).
Bioinformatic analysis indicated 'a potential association between the three key predictor genes and modifications in the immune microenvironment.'
Gene set enrichment analysis (GSEA) was also used to explore functional roles of the candidate genes.
Results
Potential therapeutic targets associated with CDKN1A, HSPA5, and NR4A1 were predicted through bioinformatic analysis.
Potential therapeutic targets associated with these genes were predicted as part of the study's analytical pipeline.
The three genes were described as 'crucial pathogenic biomarkers and potential therapeutic targets for SD.'
The study identified these genes as providing 'novel molecular targets for elucidating the mechanisms underlying SD-induced autophagy modulation, immune response, and neurovascular injury.'
What This Means
This research suggests that sleep deprivation affects specific biological processes in the brain involving autophagy—the cellular 'self-cleaning' process by which cells break down and recycle damaged components. By analyzing gene expression data from mice and humans and running machine learning algorithms, researchers identified three genes (CDKN1A, HSPA5, and NR4A1) that are significantly altered during sleep deprivation and are linked to autophagy. These findings were confirmed in multiple datasets and in a rat model where animals were kept awake continuously for seven days, with gene expression measured directly in brain regions associated with cognition and memory.
The study also found that these three genes are active in different types of brain cells: CDKN1A in blood vessel cells (endothelial cells), HSPA5 in support cells (glial cells), and NR4A1 in nerve cells (neurons). This suggests that sleep deprivation may affect the brain through several distinct cellular pathways simultaneously. Additionally, the analysis indicated that these gene changes may be connected to alterations in how the immune system functions in the brain.
This research suggests that CDKN1A, HSPA5, and NR4A1 could serve as biological markers to identify or diagnose sleep deprivation-related conditions, and may represent targets for future treatments aimed at protecting the brain from the harmful effects of sleep loss. A diagnostic model combining these three genes showed strong ability to distinguish sleep-deprived from non-sleep-deprived individuals in both animal and human datasets.
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Gan L, You Z, Tan W, Feng S, Cai Y, Shi X, et al.. (2026). Integrated transcriptomic identification and validation reveal key autophagy-associated biomarkers in sleep deprivation.. PeerJ. https://doi.org/10.7717/peerj.21426