Molecular Investigation and Preliminary Validation of Candidate Genes Associated with Neurological Damage in Heat Stroke

Heat stroke (HS) is a severe medical condition characterized by a systemic inflammatory response that may precipitate multi-organ dysfunction, with a particular predilection for inducing profound central nervous system impairments. We aim to employ bioinformatics techniques for the retrieval and analysis of genes associated with heat stroke-induced neurological damage. We performed a comprehensive analysis of the GSE64778 dataset from the Sequence Read Archive, resulting in the identification of 1178 significantly differentially expressed genes (DEGs). We retrieved 2914 genes associated with heat stroke from the GeneCards database and 2377 genes associated with heat stroke from the Comparative Toxicogenomics Database (CTD). The intersection of the top 300 DEGs in the GSE64778 dataset intersected with the search results of GeneCards and CTD, yielding 25 final candidates for DEGs associated with heat stroke. Gene Ontology functional annotation results indicated that the target genes were mainly involved in apoptosis, stress response, and negative regulation of cellular processes and function in processes such as protein dimerization and protein binding. The Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis revealed a predominant enrichment of candidate target genes within the PI3K-AKT signaling pathway. Subsequent protein-protein interaction network analysis highlighted HSP90aa1 as a central gene, indicating its pivotal role by possessing the highest number of edges among the genes enriched in the PI3K-AKT signaling pathway. Quantitative reverse transcription-polymerase chain reaction analysis performed on blood samples from patients validated the expression of Hsp90aa1 in individuals exhibiting early neurological damage in HS, consistent with the findings from the mRNA bioinformatics analysis. Additionally, the bioinformatics analysis of the upstream microRNAs (miRNAs) regulating HSP90aa1 and the target miRNAs associated with candidate long non-coding RNAs (lncRNAs) identified three lncRNAs, eight miRNAs, and one mRNA in the regulatory network. The DIANA Tools database and algorithms were employed for pathway enrichment and correlation analysis, revealing a significant association between LOC102547734 and MIR-206-3p, with the latter being identified as a target binding site Moreover, the analysis unveiled a correlation between MIR-206-3p and HSP90aa1, implicating the latter as a potential target binding site within the regulatory network.