Qi Liu ¹ Xintong Zhou ¹ Kunjing Liu ² Yimin Wang ¹ Cun Liu ³ Chundi Gao ⁴ Qingqing Cai ^5,6 Changgang Sun ^4,7*

• ¹ First College of Clinical Medicine, Shandong University of Traditional Chinese Medicine, Jinan, Shandong Province, China
• ² School of Traditional Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China
• ³ College of Traditional Chinese Medicine, Shandong Second Medical University., Weifang, China
• ⁴ College of Traditional Chinese Medicine, Shandong Second Medical University, Weifang, China
• ⁵ Department of Medical Oncology, Sun Yat-sen University Cancer Center (SYSUCC), Guangzhou, Guangdong Province, China
• ⁶ State Key Laboratory of Oncology in South China, Guangdong Provincial Clinical Research Center for Cancer, Collaborative Innovation Center of Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
• ⁷ Department of Oncology, Weifang Traditional Chinese Hospital, Weifang, Shandong Province, China

Background: The effect of immune cells on autoimmune diseases (ADs) complicated by non-Hodgkin lymphoma (NHL) has been widely recognized, but a causal relationship between regulatory T cell (Treg) immune traits and ADs complicated by NHL remains debated. Methods: Aggregate data for 84 Treg-related immune traits were downloaded from the Genome-Wide Association Study (GWAS) catalog, and GWAS data for diffuse large B-cell lymphoma (DLBCL; n=315243), follicular lymphoma (FL; n=325831), sjögren's syndrome (SS; n=402090), rheumatoid arthritis (RA; n=276465), dermatopolymyositis (DM; n=311640), psoriasis (n=407876), atopic dermatitis (AD; n=382254), ulcerative colitis (UC; n=411317), crohn's disease(CD; n=411973) and systemic lupus erythematosus (SLE; n=307587) were downloaded from the FinnGen database. The inverse variance weighting (IVW) method was mainly used to infer any causal association between Treg-related immune traits and DLBCL, FL, SS, DM, RA, Psoriasis, AD, UC, CD and SLE, supplemented by MR-Egger, weighted median, simple mode, and weighted mode. Moreover, we performed sensitivity analyses to assess the validity of the causal relationships. Results: There was a potential genetic predisposition association identified between CD39+ CD8br AC, CD39+ CD8br % T cell, and the risk of DLBCL (OR=1.51, p<0.001; OR=1.25, p=0.001) (adjusted FDR<0.1). Genetic prediction revealed potential associations between CD25++ CD8br AC, CD28- CD25++ CD8br % T cell, CD39+ CD8br % CD8br, and the risk of FL (OR=1.13, p=0.022; OR=1.28, p=0.042; OR=0.90, p=0.016) (adjusted FDR>0.1). Furthermore, SLE and CD exhibited a genetically predicted potential association with the CD39+ CD8+ Tregs subset. SS and DM were possibly associated with an increase in the quantity of the CD4+ Tregs subset; RA may have reduced the quantity of the CD39+ CD8+ Tregs subset, although no causal relationship was identified. Sensitivity analyses supported the robustness of our findings. Conclusions: There existed a genetically predicted potential association between the CD39+ CD8+ Tregs subset and the risk of DLBCL, while SLE and CD were genetically predicted to be potentially associated with the CD39+ CD8+ Tregs subset. The CD39+ CD8+ Tregs subset potentially aided in the clinical diagnosis and treatment of SLE or CD complicated by DLBCL.