Elizaveta E Elgaeva1,2, Yakov Tsepilov1,2,3, Maxim B Freidin4, Frances M K Williams4, Yurii Aulchenko1,3,5, Pradeep Suri6,7,8. 1. Laboratory of Theoretical and Applied Functional Genomics, Novosibirsk State University, Novosibirsk, Russia. 2. Laboratory of Recombination and Segregation Analysis, Institute of Cytology and Genetics, Novosibirsk, Russia. 3. PolyOmica, 's-Hertogenbosch, The Netherlands. 4. Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, London, UK. 5. Kurchatov Genomics Center, Institute of Cytology and Genetics, Novosibirsk, Russia. 6. Seattle Epidemiologic Research and Information Center, VA Puget Sound Health Care System, S-152-ERIC, 1660 S. Columbian Way, Seattle, WA, 98108, USA. pradeep.suri@va.gov. 7. Division of Rehabilitation Care Services, VA Puget Sound Health Care System, Seattle, USA. pradeep.suri@va.gov. 8. Department of Rehabilitation Medicine, University of Washington, Seattle, USA. pradeep.suri@va.gov.
Abstract
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.
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.
Entities:
Keywords:
Epidemiology; Low back pain; Obesity; Prognosis; Risk factor
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