Assessing the causal relationship between genetically determined inflammatory biomarkers and low back pain risk: a bidirectional two-sample Mendelian randomization study

BackgroundObservational studies have suggested an association between inflammatory markers and low back pain (LBP), but the causal relationship between these factors remains uncertain.MethodsWe conducted a bidirectional two-sample Mendelian randomization analysis (MR) study to investigate whether there is a causal relationship between inflammatory markers and low back pain. We obtained genetic data for CRP, along with its upstream inflammatory markers IL-6, IL-8, and IL-10, as well as low back pain from publicly available genome-wide association studies (GWAS). We applied several MR methods, including inverse variance weighting, weighted median, MR-Egger, Wald Ratio, and MR-PRESSO, to test for causal relationships. Sensitivity analyses were also conducted to assess the robustness of the results.ResultsOur analyses utilizing the Inverse Variance Weighted (IVW) method, the MR-Egger method, and the weighted median method indicated that IL-6 may be associated with an increased risk of LBP (Effect Size: -0.009, 95% Confidence Interval: -0.013–0.006, p = 9.16e-08); however, in the reverse direction, there was no significant causal effect of LBP on inflammatory markers.ConclusionOur study used a Mendelian randomization approach and found that elevated IL-6 levels may reduce the risk of LBP

Detection of Potential Mutated Genes Associated with Common Immunotherapy Biomarkers in Non-Small-Cell Lung Cancer Patients

Microsatellite instability (MSI), high tumor mutation burden (TMB-H) and programmed cell death 1 ligand 1 (PD-L1) expression are hot biomarkers related to the improvement of immunotherapy response. Two cohorts of non-small-cell lung cancer (NSCLC) were collected and sequenced via targeted next-generation sequencing. Drug analysis was then performed on the shared genes using three different databases: Drugbank, DEPO and DRUGSURV. A total of 27 common genes were mutated in at least two groups of TMB-H-, MSI- and PD-L1-positive groups. AKT1, SMAD4, SCRIB and AXIN2 were severally involved in PI3K-activated, transforming growth factor beta (TGF-β)-activated, Hippo-repressed and Wnt-repressed pathways. This study provides an understanding of the mutated genes related to the immunotherapy biomarkers of NSCLC