{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,11]],"date-time":"2026-07-11T05:56:07Z","timestamp":1783749367629,"version":"3.55.0"},"reference-count":87,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,7,26]],"date-time":"2023-07-26T00:00:00Z","timestamp":1690329600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Genet."],"abstract":"<jats:p><jats:bold>Background:<\/jats:bold> Lactate, as an essential clinical evaluation index of septic shock, is crucial in the incidence and progression of septic shock. This study aims to investigate the differential expression, regulatory relationship, clinical diagnostic efficacy, and immune infiltration of lactate metabolism-related genes (LMGs) in septic shock.<\/jats:p><jats:p><jats:bold>Methods:<\/jats:bold> Two sepsis shock datasets (GSE26440 and GSE131761) were screened from the GEO database, and the common differentially expressed genes (DEGs) of the two datasets were screened out. LMGs were selected from the GeneCards database, and lactate metabolism-related DEGs (LMDEGs) were determined by integrating DEGs and LMGs. Protein-protein interaction networks, mRNA-miRNA, mRNA-RBP, and mRNA-TF interaction networks were constructed using STRING, miRDB, ENCORI, and CHIPBase databases, respectively. Receiver operating characteristic (ROC) curves were constructed for each of the LMDEGs to evaluate the diagnostic efficacy of the expression changes in relation to septic shock. Finally, immune infiltration analysis was performed using ssGSEA and CIBERSORT.<\/jats:p><jats:p><jats:bold>Results:<\/jats:bold> This study identified 10 LMDEGs, including <jats:italic>LDHB, STAT3, LDHA, GSR, FOXM1, PDP1, GCDH, GCKR, ABCC1<\/jats:italic>, and <jats:italic>CDKN3<\/jats:italic>. Enrichment analysis revealed that DEGs were significantly enriched in pathways such as pyruvate metabolism, hypoxia pathway, and immune-inflammatory pathways. PPI networks based on LMDEGs, as well as 148 pairs of mRNA-miRNA interactions, 243 pairs of mRNA-RBP interactions, and 119 pairs of mRNA-TF interactions were established. ROC curves of eight LMDEGs (<jats:italic>LDHA, GSR, STAT3, CDKN3, FOXM1, GCKR, PDP1<\/jats:italic>, and <jats:italic>LDHB<\/jats:italic>) with consistent expression patterns in two datasets had an area under the curve (AUC) ranging from 0.662 to 0.889. The results of ssGSEA and CIBERSORT both showed significant differences in the infiltration of various immune cells, including CD8 T cells, T regulatory cells, and natural killer cells, and LMDEGs such as <jats:italic>STAT3, LDHB, LDHA, PDP1, GSR, FOXM1<\/jats:italic>, and <jats:italic>CDKN3<\/jats:italic> were significantly associated with various immune cells.<\/jats:p><jats:p><jats:bold>Conclusion:<\/jats:bold> The LMDEGs are significantly associated with the immune-inflammatory response in septic shock and have a certain diagnostic accuracy for septic shock.<\/jats:p>","DOI":"10.3389\/fgene.2023.1223243","type":"journal-article","created":{"date-parts":[[2023,7,26]],"date-time":"2023-07-26T09:49:11Z","timestamp":1690364951000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Analysis of lactate metabolism-related genes and their association with immune infiltration in septic shock via bioinformatics method"],"prefix":"10.3389","volume":"14","author":[{"given":"Huimin","family":"Jiang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yun","family":"Ren","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiale","family":"Yu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sheng","family":"Hu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jihui","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2023,7,26]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1189\/jlb.4MR0216-066R","article-title":"Cellular metabolism of myeloid cells in sepsis","volume":"101","author":"Arts","year":"2017","journal-title":"J. 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