Epigenetic and Molecular Biomarkers in Chronic Low Back Pain and Modic Changes
Epigenetic and Molecular Biomarkers in Chronic Low Back Pain and Modic Changes
In the present study the investigators aim to examine the presence of bacteria in the disc and Modic Changes (MCs) (bone). A prospective study with 1-year follow-up of two patient populations undergoing elective spinal surgery (spinal fusion or disc herniation surgery) will be conducted. Patients previously operated on at index level will also be included, and evaluated as sub-groups.
The following tissues are collected: dermis, sub-fascial tissue, nucleus pulposus, annulus fibrosus, and endplates. Endplate and annular biopsies are only performed in patients undergoing fusion surgery. In addition, air samples from the operating theatre during surgery are collected as negative controls.
All tissue samples undergoing culturing should be processed within 4 hours of sampling. The time for sampling and culture processing is noted for each sample. Details are available in a published Method article.
For each tissue sample, bacterial growth is recorded and the bacteria are identified at species level. Initially, the microbiologist grades the plates as "no growth", "possible contamination", and "significant growth".
"Possible contamination" means that the bacteria may be derived from the environment and could have been introduced at any step from the sample is taken to the analyses in the laboratory. Therefore, we have included negative controls in each step.
The investigators will perform direct 16S rDNA amplicon nanopore sequencing on all frozen tissue samples and air samples. Nanopore sequence reads are searched against a 16S rDNA database and the read counts per bacterium are evaluated for each sequencing batch containing 96 samples with regard to the included negative and positive controls.
Other broad metagenomic methods may be considered, e.g. Illumina sequencing.
Since Cutibacterium acnes is considered the main pathogen in this setting, the investigators will also use a specific PCR on all samples. To validate any positive findings, negative DNA extraction control and negative PCR control will be included in each run. Since C. acnes DNA is known to be highly prevalent within the air and environment generally, the negative controls may give a late positive signal due to environmental contamination. To reach a conclusion on either positive or negative finding for the C. acnes PCR, we will use a cutoff of 37 cycle threshold (Ct) values which is the lowest Ct value for any negative controls.
In addition, the investigators will use whole genome sequencing on C. acnes isolates for phylogenetic analyses to compare isolates found in different samples from the same patient.
In cases of a culture-negative but 16S rDNA nanopore-positive biopsy, the sample is classified as "no growth" when we find the same bacterial species in the air control sample as in the biopsy.
After the study was designed and the method article was prepared, nanopore sequencing technology became available and was incorporated into the present analysis. Although not part of the original protocol, 16S rDNA nanopore sequencing was applied to all samples to complement the diagnostic approach.
The results derived from 16S rDNA nanopore sequencing will be included as part of prespecified sensitivity analyses to evaluate the robustness of the main finding. These analyses allow assessment of whether the inclusion of sequencing-based detection influences the overall estimates and conclusions, while maintaining the original study design.
Based on cultivation alone, samples will be graded as "significant growth", "possible contamination" or "no growth". Before unblinding, in preparation for the sensitivity analyses, all samples of nucleus and annulus will be classified into a final categorization of "significant growth", "possible significant growth", "nanopore positive" or "no growth" based on cultivation and PCR (see Table 1 under Study Documents "Final categorization of bacterial growth and PCR-based methods for each tissue sample").
The microbiologists, pathologist, statistician and clinicians are blinded until end of study, April 22th 2026.
Blood-samples are collected to characterize gene expression patterns and related markers.
Planned analyses
The investigators will perform the following analyses, with terms based on final categorization above:
Primary analyses:
I. Dependent variable (outcome): positive = significant growth, negative = no growth or possible significant growth. Main explanatory variable (group): MC1 vs. control II. Dependent variable (outcome): positive = significant growth, negative = no growth or possible significant growth. Main explanatory variable (group): MC2 vs. control
For each of the primary analyses (I and II), we will perform the following sensitivity analyses:
Exploratory analyses:
The investigators will perform exploratory analyses using the following as main explanatory variables (using the same dependent variable as the primary analysis):
I - MC1 and MC2 in previously operated vs. control II - Large MCs vs. control (significant growth from disc, yes/no). Large MCs are defined as MCs with volume ≥ 25 % of vertebral body volume or height > 50 % of vertebral body height.
III - MC1 and MC2 vs. control in fusion group (significant growth from vertebral body biopsy, yes/no). Vertebral body biopsies are not performed in the disc herniation group.
For each of these three exploratory analyses, the investigators will consider to perform similar sensitivity analyses as for the primary analyses, depending on the results of those.
Statistics and power:
The main aim of this study is to investigate if the proportions of patients with significant bacterial growth from perioperative disc biopsies differ between cases (MC1 patients or MC2 patients) vs controls without MCs. The null hypothesis is that there is no difference between cases and controls. The alternative hypothesis is that there is a difference.
The sample size calculation is based on previously published data and a pre-specified relevant difference in proportions of bacterial growth among cases vs. controls
The investigators calculated the sample size using a two-sided Pearson's chi-squared test. For the primary analysis, with two primary endpoints, the investigators aim to achieve 80 % power to detect a difference in bacterial growth in 25 % of cases with MC1 or MC2 vs. 5% of controls. Due to multiple testing the investigators use Bonferroni correction (alfa 0.025). The investigators therefore plan to analyze at least 60 cases with MC1, 60 cases with MC2 and 60 controls.
The MC2 sample is likely to become larger than n = 60, since the investigators recruit MC1 and MC2 patients consecutively and MC2 is more common than MC1.
The primary endpoint will be analyzed with a logistic regression model with bacterial growth (positive/negative) as the outcome and group (MC1 or MC2 vs. control) as the main explanatory variable.
After fitting the model, the model-predicted marginal probabilities of positive bacterial findings will be estimated for both groups. The effect measure will be the difference between the two probabilities, and will be reported with a 95 % confidence interval and a P-value for the null hypothesis of a zero difference. The standard error of the difference will be estimated using the delta method.
The exploratory and sensitivity analyses will be carried out with the same model, after replacing outcome and main explanatory variable as appropriate. The subgroup analysis of previously operated will be carried out by adding previously operated as an interaction term between groups, and previously operated as covariates in the logistic model. A significant coefficient for the interaction term will indicate a subgroup effect.
Inclusion Criteria:
Exclusion Criteria: