Causal relationships between rheumatoid arthritis and neurodegenerative diseases: a two-sample univariable and multivariable Mendelian randomization study.

Xingyu Chen, Li Cai, Weibing Fan, Qian Yang, Xinfa Mao, Liping Yao
Author Information
  1. Xingyu Chen: Department of Neurology, Hunan Provincial People's Hospital, The First Affiliated Hospital of Hunan Normal University, Changsha, China.
  2. Li Cai: Department of Neurology, The Third Hospital of Changsha, Changsha, China.
  3. Weibing Fan: Department of Neurology, The Third Hospital of Changsha, Changsha, China.
  4. Qian Yang: Department of Neurology, The Third Hospital of Changsha, Changsha, China.
  5. Xinfa Mao: Department of Neurology, The Third Hospital of Changsha, Changsha, China.
  6. Liping Yao: Department of Neurology, The Third Hospital of Changsha, Changsha, China.

Abstract

Background: Observational research has highlighted a potential relationship between rheumatoid arthritis (RA) and neurodegenerative diseases (NDs). However, the confirmation of a causal connection is impeded by the inherent limitations of such studies, including vulnerability to confounding factors and the possibility of reverse causality. This study employs a two-sample Mendelian randomization (MR) approach to assess the causal impact of RA on three NDs, including Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS).
Methods: We aggregated data from genome-wide association studies (GWASs) targeting RA or NDs within populations of European descent. Single nucleotide polymorphisms (SNPs) with robust associations to RA were identified as instrumental variables (IVs). To estimate the association between RA and AD, PD, and ALS, we utilized the inverse variance weighted (IVW) method in our univariable MR (UVMR) analysis. Validation of the IVW results ensued through supplementary analyses using MR-Egger and weighted median methods. The multivariable MR (MVMR) analysis was conducted, adjusting for body mass index (BMI), alcohol drinking, and type 2 diabetes mellitus (T2DM).
Results: The UVMR analysis, based on the IVW method, revealed a significantly positive causal association between RA and late-onset (LO) AD (OR [95% CI] = 1.084 [1.020-1.153]; = 9.980 × 10), while suggesting a possible inverse relationship with PD (OR [95% CI] = 0.727 [0.563-0.938]; = 0.014). Our study did not detect any causal connections between RA and early-onset (EO) AD, atypical or mixed (AM) AD, and ALS (all > 0.05). The MVMR analysis results indicated that after adjusting for alcohol drinking, RA remains a risk factor for LOAD (OR [95% CI] = 1.094 [1.024-1.169]; = 0.008). However, MVMR analysis revealed no causal connections between RA and PD after adjustments for BMI, alcohol drinking, or T2DM (all > 0.05). Sensitivity analyses showed no evidence of heterogeneity and horizontal pleiotropy.
Conclusions: This research provides genetic evidence indicating that RA potentially causes an increased risk of developing LOAD and PD. Such a revelation underscores the importance for individuals suffering from RA to be vigilant about the potential emergence of LOAD and PD. Ongoing monitoring and prompt detection are essential for successfully managing and intervening in this possible risk.

Keywords

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Word Cloud

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