Unraveling the genetic and molecular landscape of sepsis and acute kidney injury: A comprehensive GWAS and machine learning approach

作者全名：Yang, Sha; Guo, Jing; Xiong, Yunbiao; Han, Guoqiang; Luo, Tao; Peng, Shuo; Liu, Jian; Hu, Tieyi; Zha, Yan; Lin, Xin; Tan, Ying; Zhang, Jiqin

作者地址：[Yang, Sha; Guo, Jing; Liu, Jian; Zha, Yan] Guizhou Univ, Med Coll, Guiyang 550025, Guizhou Prov, Peoples R China; [Xiong, Yunbiao; Han, Guoqiang; Luo, Tao; Peng, Shuo; Liu, Jian; Tan, Ying] Guizhou Prov Peoples Hosp, Dept Neurosurg, Guiyang, Peoples R China; [Zha, Yan; Lin, Xin] Guizhou Prov Peoples Hosp, Dept Nephrol, Guiyang, Peoples R China; [Hu, Tieyi] Chongqing Med Univ, Affiliated Dazu Hosp, Dept Neurol, Chongqing, Peoples R China; [Zhang, Jiqin] Guizhou Prov Peoples Hosp, Dept Anesthesiol, Guiyang, Peoples R China

通信作者：Tan, Y (通讯作者)，Guizhou Prov Peoples Hosp, Dept Neurosurg, Guiyang, Peoples R China.; Lin, X (通讯作者)，Guizhou Prov Peoples Hosp, Dept Nephrol, Guiyang, Peoples R China.; Zhang, JQ (通讯作者)，Guizhou Prov Peoples Hosp, Dept Anesthesiol, Guiyang, Peoples R China.

来源：INTERNATIONAL IMMUNOPHARMACOLOGY

ESI学科分类：PHARMACOLOGY & TOXICOLOGY

WOS号：WOS:001251827000001

JCR分区：Q1

影响因子：4.8

年份：2024

卷号：137

期号：　

开始页：　

结束页：　

文献类型：Article

关键词：Machine learning; Sepsis; Acute kidney injury; Diagnostic model; Prognostic model

摘要：Objectives: This study aimed to explore the underlying mechanisms of sepsis and acute kidney injury (AKI), including sepsis -associated AKI (SA-AKI), a frequent complication in critically ill sepsis patients. Methods: GWAS data was analyzed for genetic association between AKI and sepsis. Then, we systematically applied three distinct machine learning algorithms (LASSO, SVM-RFE, RF) to rigorously identify and validate signature genes of SA-AKI, assessing their diagnostic and prognostic value through ROC curves and survival analysis. The study also examined the functional and immunological aspects of these genes, potential drug targets, and ceRNA networks. A mouse model of sepsis was created to test the reliability of these signature genes. Results: LDSC confirmed a positive genetic correlation between AKI and sepsis, although no significant shared loci were found. Bidirectional MR analysis indicated mutual increased risks of AKI and sepsis. Then, 311 key genes common to sepsis and AKI were identified, with 42 significantly linked to sepsis prognosis. Six genes, selected through LASSO, SVM-RFE, and RF algorithms, showed excellent predictive performance for sepsis, AKI, and SAAKI. The models demonstrated near -perfect AUCs in both training and testing datasets, and a perfect AUC in a sepsis mouse model. Significant differences in immune cells, immune -related pathways, HLA, and checkpoint genes were found between high- and low -risk groups. The study identified 62 potential drug treatments for sepsis and AKI and constructed a ceRNA network. Conclusions: The identified signature genes hold potential clinical applications, including prognostic evaluation and targeted therapeutic strategies for sepsis and AKI. However, further research is needed to confirm these findings.

基金机构：National Natural Science Foundation of China [82360376, 81960344, 82360482, 82260533, 81960454]; Guizhou Provincial Science and Technology Projects [ZK[2024]483, [2020]1Z066]; Guizhou Province's funding for the cultivation of high-level innovative talents through the Thousand Talents Program [GZSYQCC[2023]001]; Chongqing regional medical key discipline construction project [zdxk201606]; Chongqing Dazu District Science and Technology Bureau major project of science and technology development [DZKJ2023JSYJ-KWXM1002]; Chongqing Education Committee project [KJQN202300470]

基金资助正文：This work was supported by the National Natural Science Foundation of China (82360376, 81960344, 82360482, 82260533 and 81960454) , Guizhou Provincial Science and Technology Projects (ZK[2024]483) , Guizhou Provincial Science and Technology Projects ( [2020]1Z066) , Guizhou Province's funding for the cultivation of high-level innovative talents through the Thousand Talents Program (GZSYQCC[2023]001) . Chongqing regional medical key discipline construction project (zdxk201606) , Chongqing Dazu District Science and Technology Bureau major project of science and technology development (DZKJ2023JSYJ-KWXM1002) , Chongqing Education Committee project (KJQN202300470) .