Our study analyzed the genetic similarity of height and OA risk based on the latest GWAS data, and the conclusions drawn were consistent with previous observational studies18. Furthermore, we analyzed the correlation between height-related anthropometric measurements and osteoarthritis, comparing the contribution of different exposures to the risk of developing OA. Finally, we performed an MVMR analysis, which did not yield positive results but can be explained by the excessively strong effects of each exposure factor.
The large-scale meta-analysis of genome-wide association studies (GWAS) has identified numerous loci for human anthropometric traits, including over 600 loci for height and more than 160 loci for obesity-related outcomes, primarily for common traits such as body mass index (BMI), waist-to-hip ratio (WHR), and percentage of body fat19. The relationship between advanced age, obesity, and the increased incidence of knee OA has been well understood. However, a study by Wallace et al. suggests that these major risk factors are insufficient to explain the exponential increase in the prevalence of knee OA. The study utilized skeletal samples from adults aged 50 and above living in urban areas of the United States. They compared the skeletons of individuals who died between 1905 and 1940 with those who died between 1976 and 2015. A prehistoric skeletal sample from a North American archaeological site was also included as a comparative group. The researchers found evidence of knee osteoarthritis in both prehistoric and modern skeletons. However, since the mid-20th century, even after controlling for age and body mass index (BMI), the prevalence of knee joint osteoarthritis has doubled compared to modern times. This finding suggests that using BMI alone to control body size is not enough to assess the risk of osteoarthritis. We need a more comprehensive and systematic evaluation of anthropometric data on its impact on the disease. These anthropometric data include height, sitting height, weight, body fat percentage, trunk fat mass, waist circumference, hip circumference, and other directly measurable body measurements10. The results of this study also confirm the necessity of this approach. We discovered an interesting result that sitting height has a protective effect on overall osteoarthritis. There are currently credible interpretations in the theoretical framework regarding this result.
Sitting height at a higher level often indicates a shorter leg proportion. From a mechanical perspective, longer legs can lead to greater torque at the knee joint20. Additionally, body length is associated with higher total weight, particularly in the upper body21. Therefore, this increased mass related to length and body size can increase dynamic and static mechanical stress on the knee joint, resulting in an increased susceptibility to OA22. Analysis of knee joint height, knee pain, and knee OA in Beijing's osteoarthritis research has shown that higher knee joint height is associated with an increased prevalence of radiographic and symptomatic knee OA.23
Our research findings also demonstrate a correlation between height and the risk of knee osteoarthritis (OA) and hip OA. Increased height is associated with an increased risk of developing both knee and hip OA. These results align with previous observational studies. A study on middle-aged women in the UK accidentally discovered that taller women have a higher risk of developing knee OA24. Another study reported that taller men and women have a higher risk of hip osteoarthritis, but no similar association was found with knee OA25. A large-scale queue study in Norway has shown a dose-response relationship between height and later total hip replacement surgery for both men and women. In a study of middle-aged British women, the highest group (≥ 170cm) had a relative risk of 1.9 (95% CI 1.6–2.3) compared to the shortest group (< 155cm) for hip replacement surgery26. However, research on OA in Americans aged 40 and above found that being short is a risk factor for hand, foot, and cervical spine OA in women, while it is a risk factor for hand and cervical spine OA in men. This also explains why the overall height does not have any significance in terms of total OA according to this study27.
The genetic contribution to OA includes many risk variants, with each variant having a small impact on the disease. A logical next step is to combine the identified OA risk variants into a risk score that can be used to predict the occurrence and severity of OA. As a small team, we currently lack the capacity for large-scale analysis work. However, we are committed to exploring the feasibility of methods. Based on a two-sample MR analysis, we attempted to investigate the contribution of body measurements including height to the risk of developing OA. Compared to height, obesity-related factors such as body fat percentage and waist circumference contribute more significantly to the risk of developing OA. Furthermore, different exposure factors have varying effects on knee and hip OA. These research findings will provide foundational data support for further constructing an OA risk prediction model based on genetic research data. It is also expected that machine learning-based clinical prediction models for different sites of OA will be developed, making predictions of OA occurrence more accurate. As Michelle S. stated, now is the golden time for clinical prediction models in OA28.
There are limitations to our study. Firstly, due to the availability of data, the data used in this paper cannot perfectly cover all sites of osteoarthritis and there are also limitations in body measurement data. Secondly, the sample duplication rate in this paper is 12%, which may introduce certain biases due to sample repetition29,30. Thirdly, GWAS summary data only includes individuals of European ancestry, so our findings may not fully represent the entire population. More research should be conducted to validate the applicability of these results to other ethnicities.
In conclusion, this study provides evidence supporting the detrimental effects of standing height on the risk of knee osteoarthritis and hip osteoarthritis, while also suggesting a protective effect of sitting height on knee osteoarthritis. These research findings will provide a foundation for future gene-based risk prediction models for OA by providing essential data support regarding its fundamental risks.