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Vasculitis - large vessel vasculitis
AB0708 PHYSICAL ACTIVITY AND POLYMYALGIA RHEUMATICA RISK: A MENDELIAN RANDOMIZATION STUDY
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  1. J. Y. Chen1,2,
  2. Z. Jing1,2,
  3. Q. Feng1,2,
  4. Y. Feng1,2,
  5. Q. Yu3,
  6. P. F. He3,
  7. X. Li1,2,4,
  8. S. X. Zhang1,2,4
  1. 1Shanxi Provincial Key Laboratory of Rheumatism Immune Microecology, Shanxi Medical University, Taiyuan, Shanxi Province, China
  2. 2Key Laboratory of Cellular Physiology at Shanxi Medical University, Ministry of Education, Taiyuan, Shanxi Province, China
  3. 3Shanxi Key Laboratory of Big Data for Clinical Decision Research, Shanxi Medical University, Taiyuan, Shanxi Province, China
  4. 4The Second Hospital of Shanxi Medical University, Department of Rheumatology, Taiyuan, Shanxi Province, China

Abstract

Background Polymyalgia rheumatica (PRM)is a chronic inflammatory disorder characterized by pain and long-term morning stiffness of the neck, shoulders, hips, upper arms, and thighs [1]. Prolonged unaccustomed exercise involving muscle lengthening (eccentric) movements can lead to ultrastructural muscle destruction, impaired excitation-contraction coupling, inflammation, and muscle protein degradation to produce muscle pain [2]. This muscle pain due to exercise may be associated with muscle pain in PRM.

Objectives This study aims to discover whether physical activity affects PRM.

Methods We obtained GWAS data for sedentary: Time spent watching television (n=91,084), time spent using a computer (n=360,895), and time spent driving (n=310,555). Types of physical activity included moderate physical activity 10+ minutes (n= 440,266), vigorous physical exercise 10+ minutes (n=440,512), tachometer-based physical activity, Vigorous physical activity, and moderate to vigorous physical activity (UK Biobank). GWAS of PRM included 213,145 European individuals. Single nucleotide polymorphisms (SNPs) that were independent (r2 < 0.001) and were strongly related to accelerometer-measured physical activity (p < 5×10-8, F＞10) were selected as instrumental variables. The inverse-variance weighted (IVW) method was the primary method, to evaluate the causal association. The weighted median, and MR-Egger were applied for further MR analysis. Cochran’s Q test, MR-Egger intercept analysis, the funnel plot, and the leave-one-out analysis were used for sensitivity analysis.

Results There was an inverse association between time spent using a computer with PRM (IVW OR: 0.32, 95% CI: 0.15–0.70, p: 0.004). No directional pleiotropy was revealed by the MR-Egger intercept analysis (p: 0.797). On the flip side, tachometer-based physical activity, vigorous physical activity, moderate to vigorous physical activity, moderate physical activity 10+ minutes, vigorous physical activity 10+ minutes, time spent watching TV (TV), and driving time were not associated with PRM(p>0.05). (Figure 1)

Figure 1.
Figure 1.

The causal associations between PA and PRM were evaluated by the odds ratio (OR) values of IVW, MR-Egger, and Weighted median. (A)Funnel plot, (B)scatter plot, (C)leave-one-out analysis, and (D)forest plot.

Conclusion Computer time spent is a protective factor for PRM. Conversely, excessive exercise may be a risk factor, providing new insights into the pathogenesis of PRM.

References [1]Kermani TA, Warrington KJ. Polymyalgia rheumatica. Lancet. 2013 Jan 5;381(9860):63-72. doi: 10.1016/S0140-6736(12)60680-1. Epub 2012 Oct 8. Erratum in: Lancet. 2013 Jan 5;381(9860):28.

[2]Baumert P, Lake MJ, Stewart CE, Drust B, Erskine RM. Genetic variation and exercise-induced muscle damage: implications for athletic performance, injury and ageing. Eur J Appl Physiol. 2016 Sep;116(9):1595-625. doi: 10.1007/s00421-016-3411-1. Epub 2016 Jun 13.

Acknowledgements: NIL.

Disclosure of Interests None Declared.

  • Fibromyalgia
  • Non-pharmacological interventions
  • Genetics/epigenetics

https://doi.org/10.1136/annrheumdis-2023-eular.4717

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