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Bayesian-weighted Mendelian randomization reveals sleep apnea syndrome mediates the BMI-chronic pain link
Wenbao Shi1, Jing Luo1, Liu Yang2
1Department of Anesthesiology, Affiliated Hospital of Kunming University of Science and Technology, the First People's Hospital of Yunnan Province, Kunming, China.
Background:
Body mass index (BMI) has a complex association with a variety of chronic pain conditions, which may be influenced by sleep apnea syndrome (SAS). However, the role of SAS within the causal pathway linking BMI to chronic pain remains unconfirmed. This study explored whether and to what extent SAS serves as a mediator between BMI and chronic pain using Bayesian-weighted Mendelian randomization (BWMR) techniques.
Methods:
This study utilized genome-wide association study (GWAS) summary data for BMI (N=461,460) and SAS (N=476,853; based on ICD-10 code diagnostic registries) from the IEU OpenGWAS database, along with chronic pain GWAS data (ICD-10 code-based diagnostic registries) from the FinnGen database. Utilizing BWMR and inverse-variance weighted (IVW) methods, a two-step, two-sample Mendelian randomization (MR) design was employed to investigate the causal relationships between BMI and various types of chronic pain and to assess the mediating role of SAS in the BMI-chronic pain link. Additionally, a suite of sensitivity analyses, including the use of MR-PRESSO to remove outliers, MR-Egger regression to assess horizontal pleiotropy, and Cochran's Q test to evaluate heterogeneity, thereby ensuring the robustness and reliability of the MR study findings.
Results:
The GWAS data for BMI, SAS, and chronic pain were all derived from European populations, comprising 9,851,867 BMI-associated single-nucleotide polymorphisms (SNPs), 24,183,940 SAS-related SNPs, and 19,680,346 to 19,682,705 chronic pain-linked SNPs in the respective datasets. BWMR revealed significant genetic associations between BMI and various types of chronic pain, including limb pain [odds ratio (OR) =1.34, 95% confidence interval (CI): 1.25-1.44, P<0.001], low back pain (OR =1.34, 95% CI: 1.25-1.43, P<0.001), low back pain with or without sciatica (OR =1.28, 95% CI: 1.21-1.36, P<0.001), and thoracic spine pain (OR =1.18, 95% CI: 1.03-1.36, P=0.02). Additionally, the genetic predisposition of BMI was also strongly associated with the risk of SAS (OR =2.34, 95% CI: 2.12-2.59, P<0.001). Mediation analysis revealed that SAS mediated 15.3% (β=0.045) of BMI's causal effect on limb pain, 26.8% (β=0.078) on low back pain, and 26.8% (β=0.067) on low back pain with or without sciatica.
Conclusions:
There is a causal relationship between BMI and chronic pain, with SAS acting as a mediator for a portion of the causal effects of BMI on conditions such as limb pain, low back pain, and low back pain with or without sciatica. Therefore, clinical strategies should focus on modulating BMI levels to maintain them within the normal range, which may effectively reduce the incidence risk of chronic pain. Furthermore, in patients with elevated BMI and comorbid SAS, targeted SAS treatment could potentially mitigate BMI-associated chronic pain burden.
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