Causal effects of psychosocial factors on chronic back pain: a bidirectional Mendelian randomisation study

Chronic low back pain causal risk factors identified by Mendelian randomization: a cross-sectional cohort analysis

BACKGROUND CONTEXT

There are a number of risk factors- from biological, psychological, and social domains- for nonspecific chronic low back pain (cLBP). Many cLBP treatments target risk factors on the assumption that the targeted factor is not just associated with cLBP but is also a cause (ie, a causal risk factor). In most cases this is a strong assumption, primarily due to the possibility of confounding variables. False assumptions about the causal relationships between risk factors and cLBP likely contribute to the generally marginal results from cLBP treatments.

PURPOSE

The objectives of this study were to a) using rigorous confounding control compare associations between modifiable causal risk factors identified by Mendelian randomization (MR) studies with associations in a cLBP population and b) estimate the association of these risk factors with cLBP outcomes.

STUDY DESIGN/SETTING

Cross sectional analysis of a longitudinal, online, observational study.

PATIENT SAMPLE

A total of 1,376 participants in BACKHOME, a longitudinal observational e-Cohort of U.S. adults with cLBP that is part of the NIH Back Pain Consortium (BACPAC) Research Program.

OUTCOME MEASURES

Pain, Enjoyment of Life, and General Activity (PEG) Scale.

METHODS

Five risk factors were selected based on evidence from MR randomization studies: sleep disturbance, depression, BMI, alcohol use, and smoking status. Confounders were identified using the ESC-DAG approach, a rigorous method for building directed acyclic graphs based on causal criteria. Strong evidence for confounding was found for age, female sex, education, relationship status, financial strain, anxiety, fear avoidance and catastrophizing. These variables were used to determine the adjustment sets for the primary analysis. Potential confounders with weaker evidence were used for a sensitivity analysis.

RESULTS

Participants had the following characteristics: age 54.9±14.4 years, 67.4% female, 60% never smokers, 29.9% overweight, 39.5% obese, PROMIS sleep disturbance T-score 54.8±8.0, PROMIS depression T-score 52.6±10.1, Fear-avoidance Beliefs Questionnaire 11.6±5.9, Patient Catastrophizing Scale 4.5±2.6, PEG 4.4±2.2. In the adjusted models, alcohol use, sleep disturbance, depression, and obesity were associated with PEG, after adjusting for confounding variables identified via a DAG constructed using a rigorous protocol. The adjusted effect estimates- the expected change in the PEG outcome for every standard deviation increase or decrease in the exposure (or category shift for categorical exposures) were the largest for sleep disturbance and obesity. Each SD increase in the PROMIS sleep disturbance T-score resulted in a mean 0.77 (95% CI: 0.66, 0.88) point increase in baseline PEG score. Compared to participants with normal BMI, adjusted mean PEG score was slightly higher by 0.37 points (95% CI: 0.09, 0.65) for overweight participants, about 0.8 to 0.9 points higher for those in obesity classes I and II, and 1.39 (95% CI: 0.98, 1.80) points higher for the most obese participants. Each SD increase in the PROMIS depression T-score was associated with a mean 0.28 (95% CI: 0.17, 0.40) point increase in baseline PEG score, while each SD decrease in number of alcoholic drinks per week resulted in a mean 0.12 (95% CI: 0.01, 0.23) increase in baseline PEG score in the adjusted model.

CONCLUSIONS

Several modifiable causal risk factors for cLBP - alcohol use, sleep disturbance, depression, and obesity- are associated with PEG, after adjusting for confounding variables identified via a DAG constructed using a rigorous protocol. Convergence of our findings for sleep disturbance, depression, and obesity with the results from MR studies, which have different designs and biases, strengthens the evidence for causal relationships between these risk factors and cLBP. The estimated effect of change in a risk factor on change in PEG were the largest for sleep disturbance and obesity. Future analyses will evaluate these relationships with longitudinal data.

Integrating HiTOP and RDoC frameworks part II: shared and distinct biological mechanisms of externalizing and internalizing psychopathology

BACKGROUND

The Hierarchical Taxonomy of Psychopathology (HiTOP) and Research Domain Criteria (RDoC) frameworks emphasize transdiagnostic and mechanistic aspects of psychopathology. We used a multi-omics approach to examine how HiTOP's psychopathology spectra (externalizing [EXT], internalizing [INT], and shared EXT + INT) map onto RDoC's units of analysis.

METHODS

We conducted analyses across five RDoC units of analysis: genes, molecules, cells, circuits, and physiology. Using genome-wide association studies from the companion Part I article, we identified genes and tissue-specific expression patterns. We used drug repurposing analyses that integrate gene annotations to identify potential therapeutic targets and single-cell RNA sequencing data to implicate brain cell types. We then used magnetic resonance imaging data to examine brain regions and circuits associated with psychopathology. Finally, we tested causal relationships between each spectrum and physical health conditions.

RESULTS

Using five gene identification methods, EXT was associated with 1,759 genes, INT with 454 genes, and EXT + INT with 1,138 genes. Drug repurposing analyses identified potential therapeutic targets, including those that affect dopamine and serotonin pathways. Expression of EXT genes was enriched in GABAergic, cortical, and hippocampal neurons, while INT genes were more narrowly linked to GABAergic neurons. EXT + INT liability was associated with reduced gray matter volume in the amygdala and subcallosal cortex. INT genetic liability showed stronger causal effects on physical health - including chronic pain and cardiovascular diseases - than EXT.

CONCLUSIONS

Our findings revealed shared and distinct pathways underlying psychopathology. Integrating genomic insights with the RDoC and HiTOP frameworks advanced our understanding of mechanisms that underlie EXT and INT psychopathology.

Causal Relationship Between Psychosocial Factors and Neck Pain: A Two-Sample Mendelian Randomization Study

Purpose

Neck pain (NP) is a multifactorial disorder that leads to severe disability. This study aimed to investigate whether potential risk factors have a causal effect on NP at the genetic level using a two-sample Mendelian randomization (MR) analysis.

Methods

Summary-level data for potential risk factors, including distress, anxiety disorder, depression, mood, sleep disorder, loneliness, education, alcohol consumption, smoking, time spent using the computer, and physical activity, as well as NP, were obtained from multiple large-scale Genome-Wide Association Studies (GWAS). Instrumental variables (IVs) were extracted from these datasets. We employed inverse variance weighting (IVW), weighted median, and MR-Egger regression methods to assess causal effects. Heterogeneity was evaluated using MR-Egger regression and IVW, while horizontal pleiotropy was assessed using MR-PRESSO analysis and MR-Egger regression.

Results

The IVW results showed that major depressive disorder (OR = 1.51, 95% CI: 1.15, 1.98, p = 3.40×10-3) and experiencing mood swings (OR = 2.73, 95% CI: 1.57, 4.75, p = 3.86×10-4) were positively associated with NP and years of schooling (OR = 0.504, 95% CI: 0.410, 0.619, p = 6.55×10-11) was negatively associated with NP. Additionally, loneliness (OR = 16.0, 95% CI: 1.29-198, p = 0.0307) showed a suggestive association with NP. As for the other factors we did not find a clear causal relationship (All p-values > 0.05).

Conclusion

This two-sample MR study provides genetic evidence supporting a causal relationship between major depressive disorder, mood swings, and years of schooling with NP, while loneliness showed a potential association. These findings highlight the critical role of psychosocial factors, such as depression, mood swings, and education level, in the prevention and management of NP. Our results may offer new insights for clinicians to develop targeted intervention strategies aimed at reducing the incidence of NP.

Mendelian Randomization Analysis Identifies Causal Effects of Multi-Site Chronic Pain on Obstructive Sleep Apnea

Background

Observational studies have suggested an association between obstructive sleep apnea (OSA) and chronic pain disorders, but causal evidence have not been confirmed.

Methods

Here we performed Mendelian randomization (MR) study to explore the potential causal association and mediating roles of modifiable factors between multi-site chronic pain (MCP) and OSA. Independent single nucleotide polymorphisms (SNPs) (N=26) from MCP GWAS (n=387,649) in the UK Biobank were used as instrumental variables to test associations with OSA from the FinnGen consortium, which encompassed 16,761 individuals with OSA cases and 201,194 individuals without OSA.

Results

MR analyses provide genetic evidence to predict MCP on the risk of OSA. Specifically, a per-site increase in multi-site chronic pain was linked to a 184% higher risk of OSA (ORIVW = 1.84, 95% CI = 1.29-2.63, p = 7.24×10-4). However, we also performed reverse association analyses and found no significant casual effect of OSA on MCP. MR estimates were in agreement regardless of the method used, such as MR-egger, weighted median and weighted mode, thereby demonstrating the accuracy of the causal associations. Through mediation analyses, we found that body mass index (BMI), waist circumference, and educational attainment explained a substantial proportion of the association between MCP and OSA (proportion mediated=21.13%; 26.57% and 9.66% respectively).

Conclusion

Our findings suggest that both pain management interventions, prevention of obesity and health education are likely to be effective strategies to reduce OSA risk in individuals with MCP.

Understanding the comorbidities among psychiatric disorders, chronic low-back pain, and spinal degenerative disease using observational and genetically informed analyses

Psychiatric disorders and symptoms are associated with differences in pain perception and sensitivity. These differences can have important implications in treating spinal degenerative disease (SDD) and chronic low-back pain (CLBP). Leveraging data from the UK Biobank (UKB) and the All of Us Research Program (AoU), we investigated the effects linking psychiatric disorders (alcohol use disorder, anxiety, attention deficit hyperactivity disorder, bipolar disorder, cannabis use disorder, depression, opioid use disorder, posttraumatic stress disorder, and schizophrenia) to SDD and CLBP. We applied multi-nominal regression models, polygenic risk scoring (PRS), and one-sample Mendelian randomization (MR) to triangulate the effects underlying the associations observed. We also performed gene ontology and drug-repurposing analyses to dissect the biology shared among mental illnesses, SDD, and CLBP. Comparing individuals affected only by SDD (UKB N=37,745, AoU N=3,477), those affected only by CLBP (UKB N=15,496, AoU N=23,325), and those affected by both conditions (UKB N=11,463, AoU N= 13,451) to controls (UKB N=337,362, AoU N= 117,162), observational and genetically informed analyses highlighted that the strongest effects across the three case groups were observed for alcohol use disorder, anxiety, depression, and posttraumatic stress disorder. Additionally, schizophrenia and its PRS appeared to have an inverse relationship with CLBP, SDD, and their comorbidity. One-sample MR highlighted a potential direct effect of internalizing disorders on the outcomes investigated that was particularly strong on SDD. Our drug-repurposing analyses identified histone deacetylase inhibitors as targeting molecular pathways shared among psychiatric disorders, SDD, and CLBP. In conclusion, these findings support that the comorbidity among psychiatric disorders, SDD, and CLBP is due to the contribution of direct effects and shared biology linking these health outcomes. These pleiotropic mechanisms together with sociocultural factors play a key role in shaping the SDD-CLBP comorbidity patterns observed across the psychopathology spectrum.

Bidirectional relationships between pain and patterns of cannabis and tobacco use in a US nationally representative sample

ABSTRACT

One-fifth of US adults experience chronic pain, which is associated with increased tobacco and cannabis use. Although bidirectional relationships between tobacco and pain have been demonstrated, pathways between pain, cannabis use, and co-use of cannabis and tobacco are understudied. We aimed to estimate the effects of (1) substance use (exclusive and co-use of cannabis and tobacco) on later pain intensity, and (2) pain intensity on later substance use. Data were from 31,983 adults in biennial surveys (2015-2021) of the US nationally representative longitudinal Population Assessment of Tobacco and Health Study (n = 71,055 pairs of consecutive surveys; T1 and T2). Past-week pain intensity was dichotomized (≤4/10 no/low pain; >4/10 moderate/severe pain). Mutually exclusive substance use categories (past 30 days) were no cannabis/tobacco use; exclusive cannabis/tobacco use; and co-use. Logistic regression assessed whether T1 substance use affected moderate/severe pain at T2. Multinomial models assessed whether pain status at T1 affected substance use at T2. Compared with no cannabis/tobacco use at T1, co-use (OR: 2.29 [95% CI: 2.09-2.51]), exclusive tobacco use (2.00 [1.86-2.14]), and exclusive cannabis use (1.35 [1.13-1.61]) were all associated with moderate/severe pain at T2. Moderate/severe pain at T1 increased odds of co-use (2.43 [2.22-2.66]), exclusive tobacco (2.12 [1.98-2.28]), and exclusive cannabis use (1.46 [1.29-1.65]) compared with no cannabis/tobacco use at T2, and increased odds of co-use at T2 compared with exclusive cannabis/tobacco use. Findings demonstrated bidirectional relationships between pain and the exclusive use and co-use of cannabis and tobacco and indicate potential synergy in the co-use of cannabis and tobacco with respect to pain.

Integrating HiTOP and RDoC Frameworks Part I: Genetic Architecture of Externalizing and Internalizing Psychopathology

Background

There is considerable comorbidity between externalizing (EXT) and internalizing (INT) psychopathology. Understanding the shared genetic underpinnings of these spectra is crucial for advancing knowledge of their biological bases and informing empirical models like the Research Domain Criteria (RDoC) and Hierarchical Taxonomy of Psychopathology (HiTOP).

Methods

We applied genomic structural equation modeling to summary statistics from 16 EXT and INT traits in European-ancestry individuals (n = 16,400 to 1,074,629). Traits included clinical (e.g., major depressive disorder, alcohol use disorder) and subclinical measures (e.g., risk tolerance, irritability). We tested five confirmatory factor models to identify the best fitting and most parsimonious genetic architecture and then conducted multivariate genome-wide association studies (GWAS) of the resulting latent factors.

Results

A two-factor correlated model, representing EXT and INT spectra, provided the best fit to the data. There was a moderate genetic correlation between EXT and INT (r = 0.37, SE = 0.02), with bivariate causal mixture models showing extensive overlap in causal variants across the two spectra (94.64%, SE = 3.27). Multivariate GWAS identified 409 lead genetic variants for EXT, 85 for INT, and 256 for the shared traits.

Conclusions

The shared genetic liabilities for EXT and INT identified here help to characterize the genetic architecture underlying these frequently comorbid forms of psychopathology. The findings provide a framework for future research aimed at understanding the shared and distinct biological mechanisms underlying psychopathology, which will help to refine psychiatric classification systems and potentially inform treatment approaches.

Integration of Conventional and Virtual Reality Approaches in Augmented Reality for Theory-Based Psychoeducational Intervention Design for Chronic Low Back Pain: Scoping Review

BACKGROUND

Psychoeducation positively influences the psychological components of chronic low back pain (CLBP) in conventional treatments. The digitalization of health care has led to the discussion of virtual reality (VR) interventions. However, CLBP treatments in VR have some limitations due to full immersion. In comparison, augmented reality (AR) supplements the real world with virtual elements involving one's own body sensory perception and can combine conventional and VR approaches.

OBJECTIVE

The aim of this study was to review the state of research on the treatment of CLBP through psychoeducation, including immersive technologies, and to formulate suggestions for psychoeducation in AR for CLBP.

METHODS

A scoping review following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines was performed in August 2024 by using Livivo ZB MED, PubMed, Web of Science, American Psychological Association PsycINFO (PsycArticle), and PsyArXiv Preprints databases. A qualitative content analysis of the included studies was conducted based on 4 deductively extracted categories.

RESULTS

We included 12 studies published between 2019 and 2024 referring to conventional and VR-based psychoeducation for CLBP treatment, but no study referred to AR. In these studies, educational programs were combined with physiotherapy, encompassing content on pain biology, psychological education, coping strategies, and relaxation techniques. The key outcomes were pain intensity, kinesiophobia, pain catastrophizing, degree of disability, quality of life, well-being, self-efficacy, depression, attrition rate, and user experience. Passive, active, and gamified strategies were used to promote intrinsic motivation from a psychological point of view. Regarding user experience from a software development perspective, user friendliness, operational support, and application challenges were recommended.

CONCLUSIONS

For the development of a framework for an AR-based psychoeducational intervention for CLBP, the combination of theories of acceptance and use of technologies with insights from health psychological behavior change theories appears to be of great importance. An example of a theory-based design of a psychoeducation intervention in AR for CLBP is proposed and discussed.

Chronic Low Back Pain Causal Risk Factors Identified by Mendelian Randomization: a Cross-Sectional Cohort Analysis

Background Context

There are a number of risk factors- from biological, psychological, and social domains- for non-specific chronic low back pain (cLBP). Many cLBP treatments target risk factors on the assumption that the targeted factor is not just associated with cLBP but is also a cause (i.e, a causal risk factor). In most cases this is a strong assumption, primarily due to the possibility of confounding variables. False assumptions about the causal relationships between risk factors and cLBP likely contribute to the generally marginal results from cLBP treatments.

Purpose

The objectives of this study were to a) using rigorous confounding control compare associations between modifiable causal risk factors identified by Mendelian randomization (MR) studies with associations in a cLBP population and b) estimate the association of these risk factors with cLBP outcomes.

Study Design/Setting

Cross sectional analysis of a longitudinal, online, observational study.

Patient Sample

1,376 participants in BACKHOME, a longitudinal observational e-Cohort of U.S. adults with cLBP that is part of the NIH Back Pain Consortium (BACPAC) Research Program.

Outcome Measures

Pain, Enjoyment of Life, and General Activity (PEG) Scale.

Methods

Five risk factors were selected based on evidence from MR randomization studies: sleep disturbance, depression, BMI, alcohol use, and smoking status. Confounders were identified using the ESC-DAG approach, a rigorous method for building directed acyclic graphs based on causal criteria. Strong evidence for confounding was found for age, female sex, education, relationship status, financial strain, anxiety, fear avoidance and catastrophizing. These variables were used to determine the adjustment sets for the primary analysis. Potential confounders with weaker evidence were used for a sensitivity analysis.

Results

Participants had the following characteristics: age 54.9 ± 14.4 years, 67.4% female, 60% never smokers, 29.9% overweight, 39.5% obese, PROMIS sleep disturbance T-score 54.8 ± 8.0, PROMIS depression T-score 52.6 ± 10.1, Fear-avoidance Beliefs Questionnaire 11.6 ± 5.9, Patient Catastrophizing Scale 4.5 ± 2.6, PEG 4.4 ± 2.2. In the adjusted models alcohol use, sleep disturbance, depression, and obesity were associated with PEG, after adjusting for confounding variables identified via a DAG constructed using a rigorous protocol. The adjusted effect estimates- the expected change in the PEG outcome for every standard deviation increase or decrease in the exposure (or category shift for categorical exposures) were the largest for sleep disturbance and obesity. Each SD increase in the PROMIS sleep disturbance T-score resulted in a mean 0.77 (95% CI: 0.66, 0.88) point increase in baseline PEG score. Compared to participants with normal BMI, adjusted mean PEG score was slightly higher by 0.37 points (95% CI: 0.09, 0.65) for overweight participants, about 0.8 to 0.9 points higher for those in obesity classes I and II, and 1.39 (95% CI: 0.98, 1.80) points higher for the most obese participants. Each SD increase in the PROMIS depression T-score was associated with a mean 0.28 (95% CI: 0.17, 0.40) point increase in baseline PEG score, while each SD decrease in number of alcoholic drinks per week resulted in a mean 0.12 (95%CI: 0.01, 0.23) increase in baseline PEG score in the adjusted model.

Conclusions

Several modifiable causal risk factors for cLBP - alcohol use, sleep disturbance, depression, and obesity- are associated with PEG, after adjusting for confounding variables identified via a DAG constructed using a rigorous protocol. Convergence of our findings for sleep disturbance, depression, and obesity with the results from MR studies, which have different designs and biases, strengthens the evidence for causal relationships between these risk factors and cLBP (1). The estimated effect of change in a risk factors on change in PEG were the largest for sleep disturbance and obesity. Future analyses will evaluate these relationships with longitudinal data.

The Combined Effect Between Sleep Disorders and Depression Symptoms on Chronic Low Back Pain: A Cross-Sectional Study of NHANES

Purpose

To explore the combined effects of sleep disorders and depression on chronic low back pain (CLBP) in American adults.

Material and methods

In this cross-sectional study, the data of all participants were obtained from the National Health and Nutrition Examination Survey (NAHNES) between 2009 and 2010. CLBP was defined as persistent LBP for a consecutive three-month period. Sleep disorders were self-reported and were diagnosed by a doctor before. The Patient Health Questionnaire-9 (PHQ-9) was used to assess depressive symptoms by trained personnel. Potential covariates were selected using weighted univariate logistic regression models. Weighted univariate and multivariate logistic regression models were used to evaluate the separate and combined effects of sleep disorders and depression on CLBP, respectively. Results were presented as odds ratios (ORs) and 95% confidence intervals (CIs). Associations were further explored in the subgroups of age, chronic kidney disease (CKD), diabetes, and having pain outside the low back.

Results

A total of 5275 participants were included. Among them, 542 (10.28%) had CLBP. The mean age of all participants was 47.19 (0.53), and 50.65% (n=2668) were female. Sleep disorder (OR=1.52, 95% CI: 1.17-1.98) or depressive symptoms (OR=3.06, 95% CI: 2.41-3.88) were associated with higher odds of CLBP. Compared to participants without sleep disorders and depression symptoms, participants in both conditions had an increased risk of CLBP (OR=3.95, 95% CI: 2.58-6.05, P for trend <0.001). The combined effects of sleep disorders and depressive symptoms were also found in the population aged <45 years, ≥45 years, with and without CKD, with and without diabetes, and no pain outside the low back.

Conclusion

Sleep disorders and depressive symptoms may increase the odds of reporting CLBP. Further research is necessary to explore the effectiveness of multidisciplinary interventions targeting sleep disorders, depressive symptoms, and CLBP.

Associations between lifestyle-related risk factors and back pain: a systematic review and meta-analysis of Mendelian randomization studies

BACKGROUND

Mendelian randomization (MR) studies have an advantage over conventional observational studies when studying the causal effect of lifestyle-related risk factors on back pain. However, given the heterogeneous design of existing MR studies on back pain, the reported causal estimates of these effects remain equivocal, thus obscuring the true extent of the biological effects of back pain lifestyle-risk factors.

PURPOSE

The purpose of this study was to conduct a systematic review with multiple meta-analyses on the associations between various lifestyle factors and low back pain.

METHODS

We conducted a PRISMA systematic review and specifically included MR studies to investigate the associations between lifestyle factors-specifically, BMI, insomnia, smoking, alcohol consumption, and leisure sedentary behavior-and various back pain outcomes. Each meta-analysis synthesized data from three or more studies to assess the causal impact of these exposures on distinct back pain outcomes, including chronic pain, disability, and pain severity. Quality of studies was assessed according to STROBE-MR guidelines.

RESULTS

A total of 1576 studies were evaluated and 20 were included. Overall, the studies included were of high quality and had a low risk of bias. Our meta-analysis demonstrates the positive causal effect of BMI (OR IVW-random effects models: 1.18 [1.08-1.30]), insomnia(OR IVW-random effects models: 1.38 [1.10-1.74]), smoking(OR IVW-fixed effects models: 1.30 [1.23-1.36]), alcohol consumption(OR IVW-fixed effects models: 1.31 [1.21-1.42]) and leisure sedentary behaviors(OR IVW-random effects models: 1.52 [1.02-2.25]) on back pain.

CONCLUSION

In light of the disparate designs and causal effect estimates presented in numerous MR studies, our meta-analysis establishes a compelling argument that lifestyle-related risk factors such as BMI, insomnia, smoking, alcohol consumption, and leisure sedentary behaviors genuinely contribute to the biological development of back pain.

No evidence for causal effects of C-reactive protein (CRP) on chronic pain conditions: a Mendelian randomization study

Objective

We conducted a Mendelian randomization (MR) study to examine causal associations of C-reactive protein (CRP) with (1) spinal pain; (2) extent of multisite chronic pain; and (3) chronic widespread musculoskeletal pain.

Design

Two-sample MR study.

Setting/Subjects

We used summary statistics from publicly available genome-wide association studies (GWAS) conducted in multiple cohorts and biobanks. Genetic instrumental variables were taken from an exposure GWAS of CRP (n=204,402). Outcome GWASs examined spinal pain (n=1,028,947), extent of multisite chronic pain defined as the number of locations with chronic pain (n=387,649), and chronic widespread pain (n=249,843).

Methods

We examined MR evidence for causal associations using inverse-variance weighted (IVW) analysis and sensitivity analyses using other methods. We calculated odds ratios (ORs), 95% confidence intervals (95% CIs), and p-values, using a Bonferroni correction (p<0.0166) to account for 3 primary comparisons.

Results

Greater serum CRP (mg/L) was not significantly causally associated with spinal pain (OR=1.04, 95% CI 1.00-1.08; p=0.07) in IVW analysis. Greater serum CRP also showed no significant causal association with extent of multisite chronic pain in IVW analysis (beta coefficient= 0.014, standard error=0.011; p=0.19). CRP also showed no significant causal association with chronic widespread pain in IVW analysis (OR=1.00, 95% CI 1.00-1.00; p=0.75). All secondary and sensitivity analyses also showed no significant associations.

Conclusions

This MR study found no causal association of CRP on spinal pain, the extent of chronic pain, or chronic widespread pain. Future studies examining mechanistic biomarkers for pain conditions should consider other candidates besides CRP.

A Multivariate Genome-Wide Association Study Reveals Neural Correlates and Common Biological Mechanisms of Psychopathology Spectra

There is considerable comorbidity across externalizing and internalizing behavior dimensions of psychopathology. We applied genomic structural equation modeling (gSEM) to genome-wide association study (GWAS) summary statistics to evaluate the factor structure of externalizing and internalizing psychopathology across 16 traits and disorders among European-ancestry individuals (n's = 16,400 to 1,074,629). We conducted GWAS on factors derived from well-fitting models. Downstream analyses served to identify biological mechanisms, explore drug repurposing targets, estimate genetic overlap between the externalizing and internalizing spectra, and evaluate causal effects of psychopathology liability on physical health. Both a correlated factors model, comprising two factors of externalizing and internalizing risk, and a higher-order single-factor model of genetic effects contributing to both spectra demonstrated acceptable t. GWAS identified 409 lead single nucleotide polymorphisms (SNPs) associated with externalizing and 85 lead SNPs associated with internalizing, while the second-order GWAS identified 256 lead SNPs contributing to broad psychopathology risk. In bivariate causal mixture models, nearly all externalizing and internalizing causal variants overlapped, despite a genetic correlation of only 0.37 (SE = 0.02) between them. Externalizing genes showed cell-type specific expression in GABAergic, cortical, and hippocampal neurons, and internalizing genes were associated with reduced subcallosal cortical volume, providing insight into the neurobiological underpinnings of psychopathology. Genetic liability for externalizing, internalizing, and broad psychopathology exerted causal effects on pain, general health, cardiovascular diseases, and chronic illnesses. These findings underscore the complex genetic architecture of psychopathology, identify potential biological pathways for the externalizing and internalizing spectra, and highlight the physical health burden of psychiatric comorbidity.

Causal associations between modifiable risk factors and intervertebral disc degeneration

BACKGROUND

Intervertebral disc degeneration (IVDD) is a common degenerative condition, which is thought to be a major cause of lower back pain (LBP). However, the etiology and pathophysiology of IVDD are not yet completely clear.

PURPOSE

To examine potential causal effects of modifiable risk factors on IVDD.

STUDY DESIGN

Bidirectional Mendelian randomization (MR) study.

PATIENT SAMPLE

Genome-wide association studies (GWAS) with sample sizes between 54,358 and 766,345 participants.

OUTCOME MEASURES

Outcomes included (1) modifiable risk factors associated with IVDD use in the forward MR; and (2) modifiable risk factors that were determined to have a causal association with IVDD in the reverse MR, including smoking, alcohol intake, standing height, education level, household income, sleeplessness, hypertension, hip osteoarthritis, HDL, triglycerides, apolipoprotein A-I, type 2 diabetes, fasting glucose, HbA1c, BMI and obesity trait.

METHODS

We obtained genetic variants associated with 33 exposure factors from genome-wide association studies. Summary statistics for IVDD were obtained from the FinnGen consortium. The risk factors of IVDD were analyzed by inverse variance weighting method, MR-Egger method, weighted median method, MR-PRESSO method and multivariate MR Method. Reverse Mendelian randomization analysis was performed on risk factors found to be caustically associated with IVDD in the forward Mendelian randomization analysis. The heterogeneity of instrumental variables was quantified using Cochran's Q statistic.

RESULTS

Genetic predisposition to smoking (OR=1.221, 95% CI: 1.068-1.396), alcohol intake (OR=1.208, 95% CI: 1.056-1.328) and standing height (OR=1.149, 95% CI: 1.072-1.231) were associated with increased risk of IVDD. In addition, education level (OR=0.573, 95%CI: 0.502-0.654)and household income (OR=0.614, 95%CI: 0.445-0.847) had a protective effect on IVDD. Sleeplessness (OR=1.799, 95%CI: 1.162-2.783), hypertension (OR=2.113, 95%CI: 1.132-3.944) and type 2 diabetes (OR=1.069, 95%CI: 1.024-1.115) are three important risk factors causally associated with the IVDD. In addition, we demonstrated that increased levels of triglycerides (OR=1.080, 95%CI:1.013-1.151), fasting glucose (OR=1.189, 95%CI:1.007-1.405), and HbA1c (OR=1.308, 95%CI:1.017-1.683) could significantly increase the odds of IVDD. Hip osteoarthritis, HDL, apolipoprotein A-I, BMI and obesity trait factors showed bidirectional causal associations with IVDD, therefore we considered the causal associations between these risk factors and IVDD to be uncertain.

CONCLUSIONS

This MR study provides evidence of complex causal associations between modifiable risk factors and IVDD. It is noteworthy that metabolic disturbances appear to have a more significant effect on IVDD than biomechanical alterations, as individuals with type 2 diabetes, elevated triglycerides, fasting glucose, and elevated HbA1c are at higher risk for IVDD, and the causal association of obesity-related characteristics with IVDD incidence is unclear. These findings provide new insights into potential therapeutic and prevention strategies. Further research is needed to clarify the mechanisms of these risk factors on IVDD.

Genome wide association joint analysis reveals 99 risk loci for pain susceptibility and pleiotropic relationships with psychiatric, metabolic, and immunological traits

Chronic pain is at epidemic proportions in the United States, represents a significant burden on our public health system, and is coincident with a growing opioid crisis. While numerous genome-wide association studies have been reported for specific pain-related traits, many of these studies were underpowered, and the genetic relationship among these traits remains poorly understood. Here, we conducted a joint analysis of genome-wide association study summary statistics from seventeen pain susceptibility traits in the UK Biobank. This analysis revealed 99 genome-wide significant risk loci, 65 of which overlap loci identified in earlier studies. The remaining 34 loci are novel. We applied leave-one-trait-out meta-analyses to evaluate the influence of each trait on the joint analysis, which suggested that loci fall into four categories: loci associated with nearly all pain-related traits; loci primarily associated with a single trait; loci associated with multiple forms of skeletomuscular pain; and loci associated with headache-related pain. Overall, 664 genes were mapped to the 99 loci by genomic proximity, eQTLs, and chromatin interaction and ~15% of these genes showed differential expression in individuals with acute or chronic pain compared to healthy controls. Risk loci were enriched for genes involved in neurological and inflammatory pathways. Genetic correlation and two-sample Mendelian randomization indicated that psychiatric, metabolic, and immunological traits mediate some of these effects.

Bidirectional Mendelian Randomization Study of Personality Traits Reveals a Positive Feedback Loop Between Neuroticism and Back Pain

We conducted a bidirectional Mendelian randomization study to examine the causal effects of six personality traits (anxiety, neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness) on back pain associated with health care use and the causal effect of back pain on the same risk factors. Genetic instruments for the personality traits and back pain were obtained from the largest published genome-wide association studies conducted in individuals of European ancestry. We used inverse weighted variance meta-analysis and Causal Analysis Using Summary Effect for primary analyses and sensitivity analyses to examine evidence for causal associations. We interpreted exposure-outcome associations as being consistent with a causal relationship if results of at least one primary analysis were statistically significant after accounting for multiple statistical testing (P-value < .0042), and the direction and magnitude of effect estimates were concordant between primary and sensitivity analyses. We found evidence for statistically significant bidirectional causal associations between neuroticism and back pain, with odds ratio 1.51 (95% confidence interval 1.37; 1.67) of back pain per neuroticism sum score standard deviation, P-value = 7.80e-16; and beta = .12, se = .04 of neuroticism sum score standard deviation per log odds of back pain, P-value = 2.48e-03. Other relationships did not meet our predefined criteria for causal association. PERSPECTIVE: The significant positive feedback loop between neuroticism and back pain highlights the importance of considering neuroticism in the management of patients with back pain.

Focus on the impact of social factors and lifestyle on the disease burden of low back pain: findings from the global burden of disease study 2019

BACKGROUND

Low back pain (LBP) is one of the leading causes of disability worldwide. Differences in social backgrounds and lifestyles in various regions and countries may contribute to the discrepancies in the disease burden of LBP.

METHODS

Based on the GBD 2019, we collected and analyzed numbers and age-standardized rates (ASR) of LBP disability-adjusted life years (DALYs). Temporal trends in ASR were also analyzed using estimated annual percentage change (EAPC). The Age-period-cohort (APC) model was used to estimate age, period and cohort trends in DALYs of LBP. An autoregressive integrated moving average (ARIMA) model was used to forecast DALYs of LBP trends from 2020 to 2035.

RESULTS

The DALYs due to LBP increased from 1990 to 2019. The APC model showed that the risk of DALYs for global LBP increased with age and year and that the risk of DALYs was lower in the later-born cohort than in the earlier-born cohort. The main risk factors which GBD estimates were available for DALYs of LBP include smoking, occupational ergonomic factors and high BMI. It is expected that DALYs of LBP will continue to rise until 2035.

CONCLUSION

From 1990 to 2019, the global disease burden of LBP remained high. It is necessary to pay attention to the influence of social factors and lifestyle on LBP. Focusing on the impact of social factors as well as lifestyle on the prognosis of LBP and targeting interventions may further reduce the disease burden of LBP.

Evidence of causal effects of blood pressure on back pain and back pain on type II diabetes provided by a bidirectional Mendelian randomization study

BACKGROUND CONTEXT

Cardiovascular risk factors (hypertension, dyslipidemia, and type II diabetes) have been proposed as risk factors for back pain. However, few longitudinal studies have found significant associations between cardiovascular risk factors and back pain, and these may be explained by confounding or reverse causation.

PURPOSE

To examine potential causal effects of cardiovascular risk factors on back pain, and vice versa.

STUDY DESIGN

Bidirectional Mendelian randomization (MR) study.

PATIENT SAMPLES

Genome-wide association studies (GWAS) with sample sizes between 173,082 and 1,028,947 participants.

OUTCOME MEASURES

Outcomes included (1) back pain associated with health care use (BP-HC) in the forward MR; and (2) seven cardiovascular phenotypes in the reverse MR, including 2 measurements used for the evaluation of hypertension (diastolic blood pressure and systolic blood pressure), 4 phenotypes related to dyslipidemia (LDL cholesterol, HDL cholesterol, total cholesterol, and triglycerides), and type II diabetes.

METHODS

We used summary statistics from large, publicly available GWAS for BP-HC and the 7 cardiovascular phenotypes to obtain genetic instrumental variables. We examined MR evidence for causal associations using inverse-variance weighted (IVW) analysis, Causal Analysis Using Summary Effect (CAUSE), and sensitivity analyses.

RESULTS

In forward MR analyses of seven cardiovascular phenotypes, diastolic blood pressure was associated with BP-HC across all analyses (IVW estimate: OR = 1.10 per 10.5 mm Hg increase [1.04-1.17], p-value = .001), and significant associations of systolic blood pressure with BP-HC were also found (IVW estimate: OR = 1.09 per 19.3 mm Hg increase [1.04-1.15], p-value = .0006). In reverse MR analyses, only type II diabetes was associated with BP-HC across all analyses (IVW estimate: OR = 1.40 [1.13-1.73], p-value = .002).

CONCLUSIONS

These findings from analyses of large, population-based samples indicate that higher blood pressure increases the risk of BP-HC, and BP-HC itself increases the risk of type II diabetes.

Genotype-by-environment interactions in chronic back pain

BACKGROUND CONTEXT

Chronic back pain (CBP) is a common debilitating condition with substantial societal impact. While understanding genotype-by-environment (GxE) interactions may be crucial to achieving the goals of personalized medicine, there are few large-scale studies investigating this topic for CBP. None of them systematically explore multiple CBP risk factors.

PURPOSE

To estimate the extent to which genetic effects on CBP are modified by known demographic and clinical risk factors.

RESEARCH DESIGN

Case-control study, genome-wide GxE interaction study.

PATIENT SAMPLE

Data on up to 331,610 unrelated participants (57,881 CBP cases and 273,729 controls) from the UK Biobank cohort were used. UK Biobank is a prospective cohort with collected deep genetic and phenotypic data on approximately 500,000 individuals across the UK.

OUTCOME MEASURES

Self-reported chronic back pain.

METHODS

We applied a whole-genome approach to estimate the proportion of phenotypic variance explained by interactions between genotype and 12 known risk factors. We also analyzed if effects of common single-nucleotide polymorphisms on CBP are changed in presence of known risk factors.

RESULTS

The results indicate a modest, if any, modification of genetic effects by examined risk factors in CBP. Our estimates suggest that detecting such weak effects would require a sample size of millions of individuals.

CONCLUSIONS

The GxE interactions with examined common risk factors for CBP are either weak or absent. Interactions of such magnitude are unlikely to have the potential to inform and influence treatment strategies. Risk estimation models may use common genetic variation and the considered risk factors as independent predictors, without accounting for GxE.

Development and Replication of a Genome-Wide Polygenic Risk Score for Chronic Back Pain

Chronic back pain (CBP) is a complex heritable trait and a major cause of disability worldwide. We developed and validated a genome-wide polygenic risk score (PRS) for CBP using a large-scale GWAS based on UK Biobank participants of European ancestry (N = 265,000). The PRS showed poor overall predictive ability (AUC = 0.56 and OR = 1.24 per SD, 95% CI: 1.22-1.26), but individuals from the 99th percentile of PRS distribution had a nearly two-fold increased risk of CBP (OR = 1.82, 95% CI: 1.60-2.06). We validated the PRS on an independent TwinsUK sample, obtaining a similar magnitude of effect. The PRS was significantly associated with various ICD-10 and OPCS-4 diagnostic codes, including chronic ischemic heart disease (OR = 1.1, p-value = 4.8 × 10^-15), obesity, metabolism-related traits, spine disorders, disc degeneration, and arthritis-related disorders. PRS and environment interaction analysis with twelve known CBP risk factors revealed no significant results, suggesting that the magnitude of G × E interactions with studied factors is small. The limited predictive ability of the PRS that we developed is likely explained by the complexity, heterogeneity, and polygenicity of CBP, for which sample sizes of a few hundred thousand are insufficient to estimate small genetic effects robustly.

The influence of cultural and religious factors on cross-national variations in the prevalence of chronic back and neck pain: an analysis of data from the global burden of disease 2019 study

Introduction

Low back pain and neck pain are among the most commonly reported forms of chronic pain worldwide, and are associated with significant distress, disability and impairment in quality of life. Though these categories of pain can be analyzed and treated from a biomedical perspective, there is evidence that they are both related to psychological variables such as depression and anxiety. The experience of pain can be significantly influenced by cultural values. For example, cultural beliefs and attitudes can influence the meaning attached to the experience of pain, the responses of others to a sufferer's pain, and the likelihood of seeking medical care for particular symptoms. Likewise, religious beliefs and practices can influence the both experience of pain and the responses to it. These factors have also been associated with variations in the severity of depression and anxiety.

Methods

In the current study, data on the estimated national prevalence of both low back pain and neck pain, obtained from the 2019 Global Burden of Disease Study (GBD 2019), is analyzed in relation to cross-national variations in cultural values, as measured using Hofstede's model (n =115 countries) and in religious belief and practice, based on the most recent Pew Research Center survey (n = 105 countries). To address possible confounding factors, these analyses were adjusted for variables known to be associated with chronic low back or neck pain, namely smoking, alcohol use, obesity, anxiety, depression and insufficient physical activity.

Results

It was found that the cultural dimensions of Power Distance and Collectivism were inversely correlated with the prevalence of chronic low back pain, and Uncertainty Avoidance was inversely correlated with the prevalence of chronic neck pain, even after adjustment for potential confounders. Measures of religious affiliation and practice were negatively correlated with the prevalence of both conditions, but these associations were not significant after adjusting for cultural values and confounders.

Discussion

These results highlight the existence of meaningful cross-cultural variations in the occurrence of common forms of chronic musculoskeletal pain. Psychological and social factors that could account for these variations are reviewed, along with their implications for the holistic management of patients with these disorders.

A Shared Genetic Signature for Common Chronic Pain Conditions and its Impact on Biopsychosocial Traits

The multiple comorbidities & dimensions of chronic pain present a formidable challenge in disentangling its aetiology. Here, we performed genome-wide association studies of 8 chronic pain types using UK Biobank data (N =4,037-79,089 cases; N = 239,125 controls), followed by bivariate linkage disequilibrium-score regression and latent causal variable analyses to determine (respectively) their genetic correlations and genetic causal proportion (GCP) parameters with 1,492 other complex traits. We report evidence of a shared genetic signature across chronic pain types as their genetic correlations and GCP directions were broadly consistent across an array of biopsychosocial traits. Across 5,942 significant genetic correlations, 570 trait pairs could be explained by a causal association (|GCP| >0.6; 5% false discovery rate), including 82 traits affected by pain while 410 contributed to an increased risk of chronic pain (cf. 78 with a decreased risk) such as certain somatic pathologies (eg, musculoskeletal), psychiatric traits (eg, depression), socioeconomic factors (eg, occupation) and medical comorbidities (eg, cardiovascular disease). This data-driven phenome-wide association analysis has demonstrated a novel and efficient strategy for identifying genetically supported risk & protective traits to enhance the design of interventional trials targeting underlying causal factors and accelerate the development of more effective treatments with broader clinical utility. PERSPECTIVE: Through large-scale phenome-wide association analyses of >1,400 biopsychosocial traits, this article provides evidence for a shared genetic signature across 8 common chronic pain types. It lays the foundation for further translational studies focused on identifying causal genetic variants and pathophysiological pathways to develop novel diagnostic & therapeutic technologies and strategies.

Toward a causal model of chronic back pain: Challenges and opportunities

Chronic low back pain (cLBP) afflicts 8. 2% of adults in the United States, and is the leading global cause of disability. Neuropsychiatric co-morbidities including anxiety, depression, and substance abuse- are common in cLBP patients. In particular, cLBP is a risk factor for opioid addiction, as more than 50% of opioid prescriptions in the United States are for cLBP. Misuse of these prescriptions is a common precursor to addiction. While associations between cLBP and neuropsychiatric disorders are well established, causal relationships for the most part are unknown. Developing effective treatments for cLBP, and associated co-morbidities, requires identifying and understanding causal relationships. Rigorous methods for causal inference, a process for quantifying causal effects from observational data, have been developed over the past 30 years. In this review we first discuss the conceptual model of cLBP that current treatments are based on, and how gaps in causal knowledge contribute to poor clinical outcomes. We then present cLBP as a "Big Data" problem and identify how advanced analytic techniques may close knowledge gaps and improve clinical outcomes. We will focus on causal discovery, which is a data-driven method that uses artificial intelligence (AI) and high dimensional datasets to identify causal structures, discussing both constraint-based (PC and Fast Causal Inference) and score-based (Fast Greedy Equivalent Search) algorithms.

Dried fruit intake causally protects against low back pain: A Mendelian randomization study

Background

Low back pain is the leading cause of years lived with disability worldwide. The aim of this study was to evaluate whether dried fruit intake causally protects against low back pain using two-sample Mendelian randomization (MR).

Methods

We obtained summary-level data for dried fruit intake (N = 421,764) from the IEU Open GWAS Project. Forty-one independent genetic variants proxied dried fruit intake. The corresponding data for low back pain were derived from the FinnGen project (13,178 cases and 164,682 controls; discovery data) and the Neale lab (5,423 cases and 355,771 controls; replication data). We conducted univariable and multivariable MR analyses.

Results

In the univariable MR analysis, the inverse variance weighted estimate showed that greater dried fruit intake was associated with decreased risk of low back pain [odds ratio (OR) = 0.435, 95% confidence interval (CI): 0.287-0.659, P = 8.657 × 10^-5]. Sensitivity analyses using the MR-Egger (OR = 0.078, 95% CI: 0.013-0.479, P = 0.009), maximum likelihood (OR = 0.433, 95% CI: 0.295-0.635, P = 1.801 × 10^-5), weighted median (OR = 0.561, 95% CI: 0.325-0.967, P = 0.038) and Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) (OR = 0.454, 95% CI: 0.302-0.683, P = 4.535 × 10^-4) methods showed consistent results. No evidence of directional pleiotropy was identified according to the Egger intercept (intercept P-value = 0.065) or applying the MR-PRESSO method (global test P-value = 0.164). The replication analysis yielded similar results. The multivariable MR revealed that the inverse association between dried fruit intake and low back pain was consistent after adjustment for fresh fruit intake, body mass index, current tobacco smoking, alcohol intake frequency, total body bone mineral density, serum 25-hydroxyvitamin D levels, and vigorous physical activity.

Conclusion

This MR study provides evidence to support that dried fruit intake causally protects against low back pain.