Observational studies play a crucial role in understanding the relationship between phenotypes and diseases. In these studies, human chromosomes are identified before birth, and genome-wide association studies (GWAS) are commonly used to identify sequence variants across the human genome. GWAS involves the identification of specific SNPs associated with diseases. These SNPs can then be used as instrumental variables in an analysis. The reason for using SNPs as instrumental variables is that the alleles in SNPs follow the principle of random assignment, meaning they are not influenced by environmental factors. This random assignment helps to reduce bias compared to observational studies such as cohort studies. By utilizing instrumental variables, GWAS can provide a more robust assessment of the causal effect between exposure and outcome. This approach helps researchers determine whether a specific exposure, such as a phenotype, has a causal effect on the development of a disease. Please note that these methods have been widely used and are valuable in studying causal relationships. However, it is important to consider the limitations and assumptions that come with these analyses and to interpret the results cautiously.
In this study, researchers analyzed SNP data related to depression and low back pain. Their MR analysis, IVW analysis (OR=1.713), WME (OR=2.134), and MR‒Egger regression (OR=2.293) all indicated a positive correlation between depression and the onset of low back pain. This suggests that as the prevalence of depression increases, the incidence of low back pain also increases, implying a causal relationship between the two. Depression and pain are both common and debilitating conditions that impose significant economic and social burdens. The relationship between these two disorders has been extensively studied for many years. Previous research suggests that higher rates of depression may influence the occurrence of low back pain. Researchers have identified common neural mechanisms between depression and low back pain, highlighting their potential interconnection. Studies have also revealed that individuals with depression often exhibit abnormal immune responses, and the immune system plays a significant role in the development of depression. Specific cytokine levels, such as interleukin-1 (IL-1), interleukin-6 (IL-6), and tumor necrosis factor (TNF-α), are elevated in the blood plasma or serum of patients with depression compared to the healthy population. These markers have long been recognized as contributing factors to low back pain. The presence of these inflammatory biomarkers provides supporting evidence for the clinical observation that chronic pain frequently coexists with depressive disorders. In a study conducted in the United States, it was found that over 40% of individuals with depression also experience disabling chronic pain.
The present study has the following advantages. First, unlike traditional epidemiological survey studies, Mendelian randomization utilizes germline genetic variation as an instrumental variable for exposure to study the relationship between the exposure phenotype and the outcome phenotype, avoiding the interference of confounding factors such as social environment and lifestyle. and outcome phenotypes, avoiding the interference of confounding factors such as social environment and lifestyle, and realizing the true sense of It avoids the interference of confounding factors such as social environment and lifestyle, and realizes the true sense of random assignment without violating moral ethics. Second, the data were pooled using the public GWAS, saving time and research costs. Second, the use of public GWAS pooled data saves time and research costs, and the data consist of people of European ancestry, reducing potential bias. bias; third, compared to a single SNP, 25 SNPs were used as instrumental variables in this study, increasing the proportion of genetic variation that can be explained.
This study also has some limitations. First, exposure and outcome studies used in two-sample MR analyses should not involve overlapping participants. Instead, the study was unable to estimate the extent of overlap in this study, and bias due to sample overlap was minimized by using tools (e.g., F-statistics much larger than 10) [35]. Second, the pooled data from the GWAS only relate to the European population, which has limited extrapolation and needs to be validated in other populations. Third, this study used the pooled database of 2 GWAS, and due to the lack of individual data, further subgroup analyses such as age or gender could not be performed to further refine the outcome variables for analysis. Fourth. MR can only explore the linear relationship between exposure and outcome variables and cannot perform nonlinear analysis.
In conclusion, this study applied a two-sample Mendelian randomization method to infer a causal relationship between depression and low back pain, and the results suggest that there is a causal relationship between depression and low back pain, that depression may be a risk factor for low back pain, and that interventions related to depression can be included in the prevention, treatment, and prognostic assessment strategies for low back pain.