Causality between immunocytes and polymyositis: A Mendelian randomization analysis

免疫细胞与多发性肌炎之间的因果关系:孟德尔随机化分析

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Abstract

Polymyositis is a prominent subgroup of idiopathic inflammatory myopathy, considered to have an autoimmune etiology. However, research exploring the condition between immunocytes and polymyositis remains limited, indicating the need for further investigation to unravel these intricate associations. We employed bidirectional Mendelian randomization (MR) analysis to ascertain causality between 731 immunocytes and polymyositis. We also compared the positive immunocytes with dermatomyositis. Our primary analytical method was inverse variance weighted, supplemented by 4 other MR techniques. Additionally, Cochran Q test was performed to assess heterogeneity, MR-Egger to appraise pleiotropy, and MR-PRESSO to identify and eliminate potential outliers. Furthermore, the leave-one-out test evaluated the impact of each instrumental variable (IV) on the causal effect. The inverse variance weighted results revealed that 10 immunocytes exert a protective effect against polymyositis (P < .05, OR < 1), while 16 immunocytes are connected with an elevated risk of the disease (P < .05, OR > 1). In reverse MR, polymyositis was found to decrease the levels of 2 immune cells (P < .05, OR < 1) and elevate the expression of 5 immune cell phenotypes (P < .05, OR > 1). A complex correlation was found between polymyositis and the immunocyte phenotypes CD8, CD33dim, HLA-DR, CD11b, and CD45. Additionally, it was discovered that 15 types of immune cells share a causal relationship between polymyositis and dermatomyositis. All analyses demonstrated no heterogeneity or horizontal pleiotropy (P > .05). Our study provides compelling evidence regarding the intricate causal relationships between immunocytes and polymyositis. Polymyositis and dermatomyositis share common immunocytes' regulatory mechanisms. CD8, CD33dim, HLA-DR, CD11b, and CD45 may represent potential immune cell markers for polymyositis. These findings hold implications for planning prognosis and therapeutic strategies for polymyositis, offering novel insights for drug development.

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