Dataset Information

ISSLS Prize in Clinical Science 2020. Examining causal effects of body mass index on back pain: a Mendelian randomization study.

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.

SUBMITTER: Elgaeva EE

PROVIDER: S-EPMC7108959 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

ISSLS Prize in Clinical Science 2020. Examining causal effects of body mass index on back pain: a Mendelian randomization study.

Elgaeva Elizaveta E EE Tsepilov Yakov Y Freidin Maxim B MB Williams Frances M K FMK Aulchenko Yurii Y Suri Pradeep P

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society 20191203 4

<h4>Purpose</h4>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).<h4>Methods</h4>We identified genetic instrumental variables for BMI (n = 60 variants) from a meta-analysis of genome-wide ...[more]

PMID: 31797139

Similar Datasets

Project description:BackgroundRecent studies have reported associations between body mass index (BMI) and various autoimmune disorders. However, it is still uncertain whether there exists a direct cause-and-effect relationship between BMI and autoimmune thyroiditis (AIT). The aim of our study is to investigate the causal association between BMI and AIT.MethodsWe conducted a two-sample summary data Mendelian randomization (MR) analysis using genome-wide association studies (GWAS) summary statistics data related to BMI as exposure, and GWAS summary statistic data sets for AIT as the outcome. Robustly associated single-nucleotide polymorphisms (SNPs) for BMI were selected as instrumental variables (IVs). We used the inverse variance weighted (IVW) method as the primary method and performed other MR methods such as MR-Egger regression, weighted median, simple mode, and weighted mode analyses for further validation. The slope of MR-Egger regression was used to correct for pleiotropy and provide estimates of causality. The p-value for the intercept in MR-Egger was utilized to detect any directional pleiotropic effects. Heterogeneity and sensitivity analyses were performed to assess the robustness of our findings.ResultsSeventy-eight SNPs were selected from GWAS on BMI as the IVs. Our MR analysis using the IVW method showed a potential causal association between BMI and AIT (OR = 3.071, 95% CI 1.324-7.118). Findings from other MR methods are non-significant, although the direction of effect is consistent. There was no evidence that the result was affected by genetic pleiotropy (MR-Egger regression intercept = 0.01, SE = 0.00025, p = 0.719). Heterogeneity and sensitivity analyses revealed no significant heterogeneity among SNPs, and no single SNP drove the observed associations.ConclusionOur findings suggest a potential causal association between BMI and AIT, which may provide a basis for further investigation into the relationship between BMI and AIT. Further studies are required as only the IVW method shows significant results, and the case sample size is small.

Project description:PurposeDegenerative spondylolisthesis (DS) in the setting of symptomatic lumbar spinal stenosis is commonly treated with spinal fusion in addition to decompression with laminectomy. However, recent studies have shown similar clinical outcomes after decompression alone, suggesting that a subset of DS patients may not require spinal fusion. Identification of dynamic instability could prove useful for predicting which patients are at higher risk of post-laminectomy destabilization necessitating fusion. The goal of this study was to determine if static clinical radiographs adequately characterize dynamic instability in patients with lumbar degenerative spondylolisthesis (DS) and to compare the rotational and translational kinematics in vivo during continuous dynamic flexion activity in DS versus asymptomatic age-matched controls.MethodsSeven patients with symptomatic single level lumbar DS (6 M, 1 F; 66 ± 5.0 years) and seven age-matched asymptomatic controls (5 M, 2 F age 63.9 ± 6.4 years) underwent biplane radiographic imaging during continuous torso flexion. A volumetric model-based tracking system was used to track each vertebra in the radiographic images using subject-specific 3D bone models from high-resolution computed tomography (CT). In vivo continuous dynamic sagittal rotation (flexion/extension) and AP translation (slip) were calculated and compared to clinical measures of intervertebral flexion/extension and AP translation obtained from standard lateral flexion/extension radiographs.ResultsStatic clinical radiographs underestimate the degree of AP translation seen on dynamic in vivo imaging (1.0 vs 3.1 mm; p = 0.03). DS patients demonstrated three primary motion patterns compared to a single kinematic pattern in asymptomatic controls when analyzing continuous dynamic in vivo imaging. 3/7 (42%) of patients with DS demonstrated aberrant mid-range motion.ConclusionContinuous in vivo dynamic imaging in DS reveals a spectrum of aberrant motion with significantly greater kinematic heterogeneity than previously realized that is not readily seen on current clinical imaging.Level of evidenceLevel V data These slides can be retrieved under Electronic Supplementary Material.

Project description:Background Previous observational studies have shown that low back pain (LBP) often coexists with sleep disturbances, however, the causal relationship remains unclear. In the present study, the causal relationship between sleep disturbances and LBP was investigated and the importance of sleep improvement in the comprehensive management of LBP was emphasized. Methods Genetic variants were extracted as instrumental variables (IVs) from the genome-wide association study (GWAS) of insomnia, sleep duration, short sleep duration, long sleep duration, and daytime sleepiness. Information regarding genetic variants in LBP was selected from a GWAS dataset and included 13,178 cases and 164,682 controls. MR-Egger, weighted median, inverse-variance weighted (IVW), penalized weighted median, and maximum likelihood (ML) were applied to assess the causal effects. Cochran’s Q test and MR-Egger intercept were performed to estimate the heterogeneity and horizontal pleiotropy, respectively. Outliers were identified and eliminated based on MR-PRESSO analysis to reduce the effect of horizontal pleiotropy on the results. Removing each genetic variant using the leave-one-out analysis can help evaluate the stability of results. Finally, the reverse causal inference involving five sleep traits was implemented. Results A causal relationship was observed between insomnia-LBP (OR = 1.954, 95% CI: 1.119–3.411), LBP-daytime sleepiness (OR = 1.011, 95% CI: 1.004–1.017), and LBP-insomnia (OR = 1.015, 95% CI: 1.004–1.026), however, the results of bidirectional MR analysis between other sleep traits and LBP were negative. The results of most heterogeneity tests were stable and specific evidence was not found to support the disturbance of horizontal multiplicity. Only one outlier was identified based on MR-PRESSO analysis. Conclusion The main results of our research showed a potential bidirectional causal association of genetically predicted insomnia with LBP. Sleep improvement may be important in comprehensive management of LBP.

Dataset Information

ISSLS Prize in Clinical Science 2020. Examining causal effects of body mass index on back pain: a Mendelian randomization study.

Purpose

Methods

Results

Conclusion

Publications

ISSLS Prize in Clinical Science 2020. Examining causal effects of body mass index on back pain: a Mendelian randomization study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets