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Purpose: Measures of body fat accumulation are associated with back pain, but a causal association is unclear. We hypothesized that BMI would have causal effects on back pain. We conducted a two-sample Mendelian randomization (MR) study to assess the causal effect of body mass index (BMI) on the outcomes of (1) back pain and (2) chronic back pain (duration > 3 months).
Methods: We identified genetic instrumental variables for BMI (n = 60 variants) from a meta-analysis of genome-wide association studies (GWAS) conducted by the Genetic Investigation of ANthropometric Traits consortium in individuals of European ancestry (n = 322,154). We conducted GWAS of back pain and chronic back pain (n = 453,860) in a non-overlapping sample of individuals of European ancestry. We used inverse-variance weighted (IVW) meta-analysis as the primary method to estimate causal effects.
Results: The IVW analysis showed evidence supporting a causal association of BMI on back pain, with a 1-standard deviation (4.65 kg/m2) increase in BMI conferring 1.15 times the odds of back pain (95% confidence interval [CI]: 1.06-1.25, p = 0.001]; effects were directionally consistent in secondary analysis and sensitivity analyses. The IVW analysis supported a causal association of BMI on chronic back pain (OR 1.20 per 1 SD deviation increase in BMI [95% CI 1.09-1.32; p = 0.0002]), and effects were directionally consistent in secondary analysis and sensitivity analyses.
Conclusion: In this first MR study of BMI and back pain, we found a significant causal effect of BMI on both back pain and chronic back pain. These slides can be retrieved under Electronic Supplementary Material.
Genetic and epidemiological analyses of low back pain
We wish to perform genetic analysis and meta-analysis to identify markers associated with low back pain as part of the FP7 Pain_omics study. In addition, we would like to examine environmental risk factors for low back pain. Using the phenotypes reported in the UK biobank database we wish to study the detailed low back pain phenotype and associated genotype of all volunteers. We will classify subjects as cases who report low back pain and controls who don't. From GWAS analysis we hope to improve the knowledge of this common health condition and ultimately improve treatment of low back pain. We will perform epidemiological and genetic epidemiological studies of low back pain (LBP) by comparing profiles of individuals presenting with back pain to those who do not present with back pain. We note that many more people report LBP than don't. As such, it might be appropriate to a. consider a combined phenotype with other chronic pain such as leg pain b. consider the 'controls' as cases and regard the GWAS as a search for variants which protect against LBP. We will also examine variables influencing LBP such as sex, age, BMI, alcohol consumption, socioeconomic status, smoking, exercise, occupation. The full cohort (>500,000) and more as available.