Artificial joint replacement is an effective surgical technique for correcting joint deformity, restoring joint function, relieving pain, and improving quality of life. And it is a revolutionary advance in the field of orthopaedics in the 20th century. The number of patients undergoing arthroplasty is on the rise as the population ages and the number of young people with high-energy injuries increases. Steven et al. project that the United States will see around 572,000 total hip arthroplasties and 3.48 million total knee arthroplasties by 2030 [34]. with the application of artificial intelligence–designed patient-specific prosthesis and computer navigation arthroplasty, artificial joint replacement achieves good functional outcomes and improves patient satisfaction. But, complications following total joint replacement are still not negligible, and understanding the risk factors for postoperative complications is important for improving prosthesis survival and patient prognosis.
Obesity is considered a modifiable risk factor for mechanical complications of prosthesis after arthroplasty, and preoperative weight management may help reduce the risk of periprosthetic joint
Infection [35,36]. Research indicates that obesity can lead to a chronic inflammatory state, compromising immune function and making obese patients more susceptible to postoperative infections [37,38]. This is often attributed to the necessity of removing more soft tissue during surgery, leaving less soft tissue to cover the prosthesis surface. Previous retrospective and other studies have consistently identified obesity as a significant factor in post-arthroplasty infections [39-41]. Shohat et al. demonstrated a positive correlation between body mass index and the risk of infection, with a 10% increase in risk for every 2-unit increase in BMI [42]. Subsequent studies have further supported this finding, showing a 9% increase in infection risk for hip replacement patients with a BMI >25 and a 7% increase for knee replacement patients with a BMI >35 [43,44]. Patients with a BMI >50 were found to be 18 times more likely to develop PJI compared to those with a normal BMI [45]. In addition, obesity has been found to impact the stability of acetabular prostheses, increase mechanical stress on joints, and raise the risk of avulsion of the medial collateral ligament of the knee by 8%, potentially leading to prosthesis dislocation [46-48]. Aderinto et al. findings further support obesity as a direct contributor to prosthetic dislocation following total knee arthroplasty [49]. Furthermore, a retrospective study showed that obesity as a risk factor for periprosthetic fractures, this may be related to the increased load in physical activity in obese patients [50].
Observational studies are prone to reverse causation bias and confounding factors, which restrict their ability to provide causal estimates of the effect of exposures and outcomes, thereby reducing their ability to inform prevention and treatment strategies against the disease [51]. Unlike observational studies, MR uses exceptional genetic variants that are assumed to satisfy the IVs hypothesis to investigate the question of causality in epidemiological studies, which minimizes the possibility of inherent bias [52]. Moreover, MR analysis is cost-effective and feasible when compared to randomized controlled trials [53].
To ensure the reliability of our results, we screened SNPs with gene-wide association (P < 5×10-8) and removed any linkage disequilibrium (r2 < 0.001, kb = 10,000). Additionally, we accounted for horizontal pleiotropy, which refers to the possibility that SNPs may affect outcomes through other pathways rather than exposure. The consistency across three MR analysis methods, namely IVW, MR-Egger, and MM provides robust evidence to support our conclusions. Additionally, to address potential bias and account for ethnic differences, we exclusively utilized GWAS data from European populations for both the exposure and outcome variables.
Despite the validity and stability of our MR results, there are several limitations of the current study. Firstly, this study focused solely on the causal relationship between obesity and joint prosthesis complications, but it is unclear whether patients' own factors, genetic factors, and environmental factors play a role in this relationship. Second, the GWAS data used in this study were exclusively from a European population. Therefore, caution must be exercised when generalising our findings to other ethnicities and populations. Finally, we cannot exclude that our analyses were confounded by intermediation effects.
In this study, the risk of obesity and joint prosthesis complications was explored using MR analysis, and the results showed a causal relationship between obesity and prosthesis complications, suggesting that the perioperative period of arthroplasty should be optimised to manage the patient's body weight and to reduce the incidence of prosthesis complications.