Association of cancers with the occurrence and 28-day mortality of sepsis: a mendelian randomization and mediator analysis

癌症与脓毒症发生及28天死亡率的关联:孟德尔随机化和中介分析

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Abstract

Observational studies have indicated an association between cancer and the occurrence of sepsis, with an increased risk of mortality in cancer-related sepsis. However, whether a causal relationship exists between the two remains unknown. Summary statistics of thirteen cancers from the largest available genome-wide association studies (GWAS) of GWAS catalog and FinnGen biobank were extracted for the MR analysis. GWAS data for sepsis and its 28-day mortality were obtained from MRC-IEU. Univariable, multivariable, and reverse MR analyses were employed to explore potential associations between cancers and sepsis and its 28-day mortality. Moreover, a two-step mediation MR analysis was performed to investigate independent positive causal relationships between cancers and sepsis and its 28-day mortality. In univariable Mendelian randomization (MR) analysis, significant causal relationships were found between genetically predicted lung cancer (OR = 1.17, 95% CI = 1.08-1.26, adjusted p = 0.001), squamous cell lung carcinoma (OR = 1.10, 95% CI = 1.02-1.18, adjusted p = 0.042), lung adenocarcinoma (OR = 1.12, 95% CI = 1.03-1.21, adjusted p = 0.032), small cell lung carcinoma (OR = 1.07, 95% CI = 1.02-1.12, adjusted p = 0.031), and sepsis. Subsequent multivariable MR analysis revealed that these three types of lung cancer were independently associated with the risk of sepsis. Additionally, a causal relationship was found between lung cancer and 28-day mortality from sepsis, while no causal link was observed between non-solid tumors and the onset or death of sepsis. Reverse MR analysis did not indicate a potential for sepsis to trigger the onset of cancers. Furthermore, TRAIL was found to have promotive effects on the occurrence and mortality of sepsis. Lung cancer causally correlates with increased sepsis occurrence and 28-day mortality, as evidenced by Mendelian Randomization analysis. Genetic predispositions enhance this risk, underscoring the potential of genetic profiling to guide early, precise sepsis interventions in these patients.

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