Autoimmune liver diseases (AILDs) are uncommon, chronic, immune-mediated liver injuries characterized by predominate hepatic or biliary inflammation. They can be categorized into three major conditions based on prominent clinical, laboratory, and pathological characteristics [1]. Primary biliary cholangitis (PBC) is the most well-recognized AILDs, affecting 1 in 1000 women over the age of 40. Anti-mitochondrial antibodies (AMAs) are associated with lymphocytic and granulomatous cholangitis [2]. In contrast, primary sclerosing cholangitis (PSC) is uncommon and, due to its close association with inflammatory bowel disease (IBD), is best viewed as a hepatobiliary manifestation of IBD, with patients typically presenting with chronic fibrosing and sclerosing cholangitis of the mid-to-large bile ducts. No specific autoantibody correlations with PSC have been identified [3]. Unlike autoimmune biliary diseases, autoimmune hepatitis (AIH) is lymphoplasmacytic interface hepatitis characterized by increased globulins and frequent, mostly nonspecific autoantibody associations [4].

The link between AILDs and other extrahepatic autoimmune diseases has only been partially investigated. With most research focusing on rheumatologic disorders, a "kaleidoscope of autoimmunity" has been proposed to describe this scenario [5]. Although there have been extensive studies of animal models of AILDs and considerable data on the immunological mechanisms that underlie the effector pathways that drive liver injuries [6,7], there is still a significant knowledge gap regarding the genetic epidemiology of AILDs and extrahepatic autoimmune diseases. Moreover, the current clinical guidelines on AILDs recommend early identification and management of extrahepatic autoimmune diseases, which can enhance patient outcomes and quality of life [8].

Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease that affects the joints and causes cartilage degradation, bone destruction, and systemic complications. It is one of the most common autoimmune diseases, with a global frequency of 0.5%–1.0% and no signs of decline [9]. Patients with RA have a higher incidence of AILDs. Rheumatoid factor is increased in up to 27% of patients with AILDs. Concomitant arthritis is observed in patients with AILDs, raising the possibility of a shared etiology [10,11]. However, there is no compelling evidence that these diseases are correlated. Exploring the causality between these diseases is crucial, as it may enhance our understanding of the pathogenesis of AILDs and RA and help us develop more appropriate therapies.

Traditional case-control or cross-sectional studies have difficulties drawing a valid result because of the possibility of unadjusted confounding variables and reverse causality. As a novel statistical method, Mendelian randomization (MR) provides an opportunity to determine whether a causal effect can be inferred from an observational relationship between the exposure and outcome [12]. The rationale for MR lies in the equal, random, and independent genetic variation during meiosis, and it uses genetic variations as instrumental variants (IVs). When performing MR analysis, three basic assumptions should be made: the genetic variant (1) is related to the exposures, (2) is not related to the confounders, and (3) exclusively affects the outcomes through the exposure [13]. Confounding and reverse causality bias can be minimized because of the properties of MR analysis. Therefore, this study aimed to evaluate the causal association between RA and AILDs using a two-sample MR analysis.