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Updated: Jul 16, 2026

Lipidomics and Transcriptomics in Neurological Diseases
Published on: March 18, 2022
Exploratory Analysis of Autophagy-related Genes and Immune Infiltration in Human Hippocampal Tissue of Temporal Lobe
Jing Liu1,2, Yiting Wang1,2, Dandan Sheng1,2
1Department of Neurology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China.
Abstract:
Epilepsy results from an imbalance between excitation and inhibition of neurons, with 30-40% of cases being temporal lobe epilepsy (TLE). This study aimed to prioritize autophagy-related genes and explore their potential links to immune features in human hippocampal tissue of TLE. Two hippocampal transcriptomic datasets (GSE202101 and GSE11882) were analyzed to identify autophagy-related differentially expressed genes (ARDEGs). Functional enrichment, regulatory network, and immune cell infiltration analyses were performed. LASSO regression and consensus clustering were applied. Exploratory assessment of the candidate gene signature was conducted in an independent dataset (GSE256068). Immunohistochemistry (IHC) on clinical specimens assessed protein expression of candidate signature genes. An eight‑gene candidate signature was derived, and subsequent PPI network analysis revealed LARP1, EIF4G1, and TSC2 as hub genes among them. Exploratory assessment in an independent dataset partially replicated the expression patterns of PYCARD, EIF4G1, and TSC2, whereas LARP1 showed an opposite expression trend; overall model performance remained modest. Increased activated mast cells were observed in TLE samples, while higher levels of plasma cells, CD8⁺ T cells, and regulatory T cells were observed in controls. Two exploratory clusters with distinct immune correlation patterns were identified. IHC showed upregulation of ABL1, TSC2, and SPP1 protein levels in TLE tissue. This study prioritizes a set of autophagy-related candidate genes in human hippocampal tissue and provides an exploratory framework linking them to local immune features in TLE. Further validation in larger independent cohorts is warranted before any clinical interpretation.
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