The tumour immune microenvironment (TIME) is critical for lymphoma progression and therapy resistance, yet causal relationships between specific immune cell types and lymphoma subtypes remain poorly defined. In this study, using bidirectional Mendelian randomization (MR), genetic correlation (LDSC), and expression‐QTL integration (SMR), we systematically evaluated causal relationships and genetic
... [Show full abstract] correlation between immune cells and various lymphomas. Additionally, we utilised the Mendelian randomization‐based method of summary data‐based MR (SMR), which incorporated genome‐wide association studies (GWAS) and expression quantitative trait loci (eQTL) data from immune cells to identify genes associated with lymphoma. Furthermore, colocalization analysis and genetic correlation analysis were conducted for further validation of our findings. The two‐sample mendelian randomization approach was employed to identify the immune cell types that exhibit a causal relationship with different lymphomas. Additionally, the genetic correlation between these immune cells and lymphomas was further analysed using the linked disequilibrium score regression method, thereby enhancing the reliability of our findings. The SMR and colocalisation analyses revealed several genes associated with these immune cells, thereby providing additional support for their putative role in the pathogenesis of lymphoma. Our study elucidates the intricate interplay between immune cells by employing genetic methodologies, thus suggesting novel therapeutic candidates that warrant experimental validation and risk predictors in different subtypes of lymphoma treatments.
