Association of Biomarkers Such as CA, TP, TES and ALP With Osteoarthritis Risk: A Mendelian Randomized Study
1College of Medicine, Wuhan University of Science and Technology, Hubei, China.
Objective:
Osteoarthritis is a common joint disease caused by a variety of risk factors, and it has been found that many biochemical markers are abnormal in peripheral blood and urine of patients with OA. The aim of this study was to elucidate the causal relationship between biomarkers associated with these processes and OA using Mendelian randomization (MR) analysis.
Method:
The inverse variance weighted (IVW) approach to MR was primarily used to explore causal associations between exposures and outcomes using publicly available genetic variants from large genome-wide association studies (GWAS). That is, single nucleotide polymorphisms (SNPs) associated with 35 human blood and urine markers (363 228 healthy participants) were used as exposure, and osteoarthritis, hip osteoarthritis, and knee osteoarthritis were used as outcome variables, with the aim of exploring the causal relationship between 35 human blood and urine markers and osteoarthritis. MR-Egger, weighted median (WM), and simple and weighted models were used as complementary methods to IVW to assess the reliability of causality. Steiger's test was used to confirm whether the causal relationship between exposure and outcome was biased by reverse causality. Sensitivity analyses used Cochran's Q statistic and funnel plots to detect heterogeneity, and the MR-Egger intercept test and leave-one-out to assess horizontal multidimensionality.
Results:
Our MR analysis study identified the protective effects of CA, TP, ALB, SHBG, and VITD on OA and the pathogenic effects of TES, ALP, GGT, CRP, and CHOL on OA. It suggests that the above 10 hematological and urinary markers have the potential to be important indicators for the clinical diagnosis of OA as well as for the assessment of therapeutic efficacy and disease progression.
Conclusion:
This MR analysis reinforces the importance of biomarkers in the diagnosis and prediction of OA. Future studies should further investigate the mechanisms of these biomarkers and their potential as therapeutic targets for OA.
