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Target genes were screened using protein\u2013protein interaction (PPI) network analysis and ROC curves to identify genes associated with AML. Finally, we analyzed the correlation between genes and immune cells and the relationship between toll-like receptor 4 (TLR4) and AML using MR.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>We compared peripheral blood expression profiles using an array of 62 healthy volunteers (GSE164191) and 65 patients with AML (GSE89565) (M0:25; M1:11; M2:10; M3:1; M4:7; M4 eo t [16;16] ou inv [16]:4; M5:6; M6:1) and obtained 7,339 DEGs (3,733 upregulated and 3,606 downregulated). We intersected these DEGs with 4,724 genes from WGCNA and 1,330 genes related to hemolysis that were identified in the GeneCards database to obtain 190 target genes. After further screening these genes using the PPI network, we identified TLR4, PTPRC, FCGR3B, STAT1, and APOE, which are closely associated with hemolysis in patients with AML. Finally, we found a causal relationship between TLR4 and AML occurrence using MR analysis (<jats:italic>p<\/jats:italic>\u2009&lt; 0.05).<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>We constructed a WGCNA-based co-expression network and identified hemolysis-associated AML genes.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1007\/s44313-025-00073-7","type":"journal-article","created":{"date-parts":[[2025,4,11]],"date-time":"2025-04-11T08:22:31Z","timestamp":1744359751000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Analysis of hemolysis-associated acute myeloid leukemia genes obtained using weighted gene co-expression network analysis and a Mendelian randomization study"],"prefix":"10.1007","volume":"60","author":[{"given":"Rui","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Zang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Linguo","family":"Wan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhanshan","family":"Cha","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haihui","family":"Gu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,4,11]]},"reference":[{"key":"73_CR1","doi-asserted-by":"publisher","unstructured":"Siegel RL, Miller KD, Jemal A (2019) Cancer statistics, 2019. 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