Deciphering the Causal Relationships Between Low Back Pain Complications, Metabolic Factors, and Comorbidities

Common Genetic Factors May Play a Role in the Relationships Between Body Composition, Adipokines, and Low-Back-Pain-Related Disability

In this study, we evaluated the contribution of the putative genetic factors into the established associations between selected circulating adipokine levels, body composition measurements, and low-back-pain-related disability scores (LBP_DS). A total of 1078 individuals from 98 nuclear families (with 1 to 11 siblings per family) were examined. A detailed self-report questionnaire was used to collect LBP disability data; body composition (fat, skeletal muscle mass, and extracellular water (ECW)) was assessed using the bioimpedance method; plasma levels of adipokines were measured by ELISA. Pedigree-based statistical analysis methods were used, including family-based variance component analysis (VCA) and principal phenotype analysis (PPA), to estimate the contribution of potential genetic and environmental factors. The VCA revealed a significant additive genetic component in LBP_DS and for the selected body composition phenotypes and adipokines. The study also revealed that both adipokines (GDF-15, chemerin, and follistatin) and body composition variables (BMI, fat mass/weight, waist circumference, and ECW) were genetically correlated with LBP_DS. Next, PPA generated two synthetic phenotypes: PPCT (combining cytokines) and PPBC (combining body composition variables). There was no significant correlation between the putative genetic factors underlying the created PPs. However, each of them displayed a significant genetic correlation with LBP_DS. These findings indicate that genetic factors that are assumingly common for several adipokine variations and several body composition measurements, respectively, presumably have a pleotropic genetic influence on the LBP_DS variation, independently from one another. This, in turn, suggests that the alleged genetic factors employing pleiotropic effects on LBP_DS have a complex and probably non-overlapping composition.

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.

Analysis of the Associations of Measurements of Body Composition and Inflammatory Factors with Cardiovascular Disease and Its Comorbidities in a Community-Based Study

The associations of cardiovascular disease (CVD) with comorbidities and biochemical and body composition measurements are repeatedly described but have not been studied simultaneously. In the present cross-sectional study, information on CVD and comorbidities [type 2 diabetes mellitus (T2DM), hypertension (HTN), and hyperlipidemia (HDL)], body composition, levels of soluble markers, and other measures were collected from 1079 individuals. When we examined the association of each comorbidity and CVD, controlling for other comorbidities, we observed a clear pattern of the comorbidity-related specific associations with tested covariates. For example, T2DM was significantly associated with GDF-15 levels and the leptin/adiponectin (L/A) ratio independently of two other comorbidities; HTN, similarly, was independently associated with extracellular water (ECW) levels, L/A ratio, and age; and HDL was independently related to age only. CVD showed very strong independent associations with each of the comorbidities, being associated most strongly with HTN (OR = 10.89, 6.46-18.38) but also with HDL (2.49, 1.43-4.33) and T2DM (1.93, 1.12-3.33). An additive Bayesian network analysis suggests that all three comorbidities, particularly HTN, GDF-15 levels, and ECW content, likely have a main role in the risk of CVD development. Other factors, L/A ratio, lymphocyte count, and the systemic inflammation response index, are likely indirectly related to CVD, acting through the comorbidities and ECW.

Relationships between Circulating Biomarkers and Body Composition Parameters in Patients with Metabolic Syndrome: A Community-Based Study

Metabolic syndrome (MetS) is a complex disease involving multiple physiological, biochemical, and metabolic abnormalities. The search for reliable biomarkers may help to better elucidate its pathogenesis and develop new preventive and therapeutic strategies. In the present population-based study, we looked for biomarkers of MetS among obesity- and inflammation-related circulating factors and body composition parameters in 1079 individuals (with age range between 18 and 80) belonging to an ethnically homogeneous population. Plasma levels of soluble markers were measured by using ELISA. Body composition parameters were assessed using bioimpedance analysis (BIA). Statistical analysis, including mixed-effects regression, with MetS as a dependent variable, revealed that the most significant independent variables were mainly adipose tissue-related phenotypes, including fat mass/weight (FM/WT) [OR (95% CI)], 2.77 (2.01-3.81); leptin/adiponectin ratio (L/A ratio), 1.50 (1.23-1.83); growth and differentiation factor 15 (GDF-15) levels, 1.32 (1.08-1.62); inflammatory markers, specifically monocyte to high-density lipoprotein cholesterol ratio (MHR), 2.53 (2.00-3.15), and a few others. Additive Bayesian network modeling suggests that age, sex, MHR, and FM/WT are directly associated with MetS and probably affect its manifestation. Additionally, MetS may be causing the GDF-15 and L/A ratio. Our novel findings suggest the existence of complex, age-related, and possibly hierarchical relationships between MetS and factors associated with obesity.

In search of biomarkers for low back pain: can traction therapy effectiveness be prognosed by surface electromyography or blood parameters?

Background: Lumbar traction therapy is a common method to reduce low back pain (LBP) but is not always effective. The search for biomarkers that would prognose the effectiveness of LBP management is one priority for improving patients' quality of life. Objectives: 1) To determine the phenotype of patients benefiting most from lumbar traction therapy. 2) To correlate systemic and electromyographic biomarkers with pain and pain-related disability. Methods: Data on muscle bioelectrical activity (surface electromyography [SEMG]) in the flexion-extension task, the concentrations of twelve systemic biochemical factors, LBP intensity (Visual Analog Scale), the Oswestry Disability Index, and the Roland-Morris Disability Questionnaire (RMDQ) were collected before and 72 h after 20 sessions of lumbar traction therapy. Patients were divided into responders and nonresponders based on the criterion of a 50% reduction in maximal pain. Results: The responders had lower maximal muscle bioactivity in the extension phase on the left side (p < 0.01) and higher flexion-extension ratios on both sides of the body in the SEMG (left: p < 0.05; right: p < 0.01), and higher adipsin, interleukin-2, interleukin-4, and interleukin-10 concentrations (p < 0.05) than nonresponders. Patients with higher interleukin-4 concentrations before therapy achieved greater reductions in maximal pain in the sitting position, bioelectrical muscle activity in flexion, and flexion-relaxation ratio on the left side of the body. Changes in adipsin and interleukin-4 concentrations correlated with changes in LBP intensity (r = 0.68; r = -0.77). Changes in stem cell growth factor and interleukin-17A correlated with changes in RMDQ (R = 0.53) and bioelectrical muscle activity in extension (left: R = -0.67; right: R = -0.76), respectively. Conclusion: Responders to traction therapy had SEMG indices of less favorable muscle activity in the flexion-extension task and elevated indices of inflammation before the study. For the first time, interleukin-4 was indicated as a potential biomarker for prognosing post-therapy changes in pain intensity and muscle activity.

Elevated circulating levels of IL-34 are strongly associated with osteoporosis

In this cross-sectional study, we observed a strong, age-independent association of circulating interleukin-34 (IL-34) levels with osteoporosis.

PURPOSE

The reported capacity of IL-34 to induce and enhance osteoclastogenesis suggests its potential involvement in the pathogenesis of osteoporosis. Our study aimed to evaluate whether there is an association between IL-34 expression and osteoporosis.

METHODS

We enrolled 30 women with osteoporosis and 230 age-matched non-osteoporotic women as a control group. Osteoporosis diagnosis was based on dual-energy X-ray absorptiometry (DXA) of the lumbar spine and femoral neck. Body composition parameters were assessed by the bioimpedance method. Plasma IL-34 levels were measured by ELISA.

RESULTS

In comparison with the control group, the mean plasma IL-34 levels were significantly higher in osteoporotic women (164.61 ± 36.40 pg/ml vs. 665.43 ± 253.67 pg/ml, p = 0.0002), whereas basal metabolic rate (BMR) was significantly lower (1422.03 ± 6.80 kcal vs. 1339.39 ± 17.52 kcal, p = 0.00007). Both variables remained statistically significant after adjustment for age (p < 0.001). We did not observe correlations between plasma IL-34 levels and body composition parameters in osteoporotic and control groups. Multiple logistic regression analysis with osteoporosis status as a dependent variable clearly showed that age, BMR and IL-34 levels were independently and significantly associated with osteoporosis. The calculated odds ratios (OR) were 1.66 (95% CI = 1.16-2.38) for IL-34 levels and 0.22 (95% CI = 0.07-0.65) for BMR.

CONCLUSION

The significant (fourfold) elevation of IL-34 plasma levels in osteoporosis patients suggests that circulating IL-34 could be used as a biomarker for osteoporosis.

Pro-Inflammatory Biomarkers Combined with Body Composition Display a Strong Association with Knee Osteoarthritis in a Community-Based Study

Knee osteoarthritis (KOA) is one of the most common progressive, age-dependent chronic degenerative joint diseases. KOA often develops as a result of a gradual articular cartilage loss caused by its wear and tear. Numerous studies suggest that the degradation of the knee joint involves inflammatory components. This process is also associated with body composition, particularly being overweight and muscle mass loss. The present study aimed to search for novel circulating KOA inflammatory biomarkers, taking into account body composition characteristics. To this aim, we recruited 98 patients diagnosed and radiologically confirmed with KOA and 519 healthy controls from the Arab community in Israel. A panel of soluble molecules, related to inflammatory, metabolic, and musculoskeletal disorders, was measured by ELISA in plasma samples, while several body composition parameters were assessed with bioimpedance analysis. Statistical analysis, including multivariable logistic regression, revealed a number of the factors significantly associated with KOA, independently of age and sex. The most significant independent associations [OR (95% CI)] were fat body mass/body weight index-1.56 (1.20-2.02), systemic immune-inflammation index-4.03 (2.23-7.27), circulating vaspin levels-1.39 (1.15-1.68), follistatin/FSTL1 ratio-1.32 (1.02-1.70), and activin A/FSTL1 ratio-1.33 (1.01-1.75). Further clinical studies are warranted to confirm the relevance of these KOA-associated biological factors. Hereafter, they could serve as reliable biomarkers for KOA in the general human population.

Insights into the pleiotropic relationships between chronic back pain and inflammation-related musculoskeletal conditions: rheumatoid arthritis and osteoporotic abnormalities

ABSTRACT

The ageing process includes the development of debilitating musculoskeletal (MSK) conditions, including chronic back pain (CBP), rheumatoid arthritis (RA), and osteoporosis (OP). The mechanisms involved in the genetic-epidemiological relationships between these MSK phenotypes are controversial and limited and thus require clarification, in particular, between CBP and the other MSK phenotypes. A cross-sectional statistical analysis was conducted using Europeans from the UK Biobank data collection, including 73,794 CBP, 4883 RA, and 7153 OP cases as well as 242,216 calcaneus bone mineral density scores. C-reactive protein (CRP) was measured for 402,165 subjects in this sample. Genetic correlations were assessed to evaluate shared genetic background between traits. Mendelian randomization was performed to assess a causal relationship between CBP and RA and OP along with other risk factors, such as CRP. Colocalization analysis was conducted to identify shared pleiotropic regions between the examined traits. Bayesian modelling was performed to determine a potential pathway that may explain the interrelationships among these traits. Mendelian randomization analyses revealed that CRP causally predicts CBP only (β = 0.183, 95% CI = 0.077-0.290, P -value = 0.001). Horizontally pleiotropy appeared to explain the relationship between CBP and RA and OP. Through colocalization analysis, several genomic regions emerged describing common genetic influences between CBP and its proposed risk factors, including HLA-DQA1/HLA-DQB1, APOE , SOX5, and MYH7B as well as Histone 1 genes. We speculate that among other factors, CBP and its MSK comorbidities may arise from common inflammatory mechanisms. Colocalized identified genes may aid in advancing or improving the mode of treatment in patients with CBP.

Andrographolide Inhibits Static Mechanical Pressure-Induced Intervertebral Disc Degeneration via the MAPK/Nrf2/HO-1 Pathway

Purpose

To explore the molecular mechanism by which andrographolide (ADR) inhibits static mechanical pressure-induced apoptosis in nucleus pulposus cells (NPCs) and to assess the role of ADR in inhibiting IDD.

Methods

Hematoxylin-eosin (HE), toluidine blue, and immunofluorescence staining were used to identify NPCs. An NPC apoptosis model was constructed using a homemade cell pressurization device. The proliferation activity, reactive oxygen species (ROS) content, and apoptosis rate were detected using kits. The expression of related proteins was detected using Western blot. A rat tailbone IDD model was constructed using a homemade tailbone stress device. HE staining and safranine O-fast green FCF cartilage staining were used to observe the degeneration degree of the intervertebral disk.

Results

ADR inhibits static mechanical pressure-induced apoptosis and ROS accumulation in NPCs and improves cell viability. ADR can promote the expression of Heme oxygenase-1 (HO-1), p-Nrf2, p-p38, p-Erk1/2, p-JNK, and other proteins, and its effects can be blocked by inhibitors of the above proteins.

Conclusion

ADR can inhibit IDD by activating the MAPK/Nrf2/HO-1 signaling pathway and suppressing static mechanical pressure-induced ROS accumulation in the NPCs.

The search for systemic biomarkers for monitoring degenerative lumbar spinal disorders

Objectives

In our previous study, we reported that low back pain (LBP) severity and disability significantly correlate with body composition and several blood biochemical factors. Herein, we tested the hypothesis that these covariates are associated with anatomical deformations of the lumbar spine, in particular, radiographic facet joint osteoarthritis (FJOA) and lumbar disc degeneration (LDD) features important contributors to LBP.

Methods

CT and MRI images of the lumbar spine were obtained from 200 individuals suffering from LBP-sciatica. We examined the FJOA and total LDD score - the sum of the scores of the three radiographic features (intervertebral disc herniation, osteophythosis and spondylolisthesis) at the L1 - S1 vertebral levels. By implementing a bioelectrical impedance analysis, we assessed the participants for body composition, specifically, extracellular water (ECW). Plasma levels of growth and differentiation factor 15 (GDF-15) and visceral adipose tissue-derived serine protease inhibitor (vaspin), were detected by ELISA.

Results

By conducting a series of multivariable regression analyses, we report that the circulating levels of GDF-15, vaspin, and ECW are significantly and independently associated with FJOA scores [β_GDF15 ​= ​0.38 ​± ​0.08, p ​= ​0.0001; β_VASPIN ​= ​0.36 ​± ​0.07, p ​= ​0.000004; β_ECW ​= ​0.24 ​± ​0.07, p ​= ​0.002]. The levels of GDF-15 (β ​= ​0.30 ​± ​0.10, p ​= ​0.007) and ECW (β ​= ​0.20 ​± ​0.09, p ​= ​0.03) were also found significantly associated with the LDD scores.

Conclusion

The obtained new data suggest that GDF-15, vaspin and ECW may serve as biomarkers for FJOA and LDD phenotypes.