AUTHOR=Ji Zhongkai , Shen Yucheng , Chen Dong , Liu Zhidong , Dai Jiuming , Dai Bin , Deng Wei TITLE=Effect of caffeine intake on self-reported and genetic prediction of osteoarthritis: an epidemiological study and Mendelian randomization analysis JOURNAL=Frontiers in Nutrition VOLUME=11 YEAR=2024 URL=https://www.frontiersin.org/journals/nutrition/articles/10.3389/fnut.2024.1405161 DOI=10.3389/fnut.2024.1405161 ISSN=2296-861X ABSTRACT=Background

Osteoarthritis (OA) holds the distinction of being the most widespread musculoskeletal disorder. Any disruptions in the integrity of the articular cartilage can result in joint malfunction, discomfort, and impaired physical functioning. Increasing evidence indicates the negative impacts of caffeine intake on hyaline cartilage. The primary objective of this study was to delve deeper into understanding the potential link between the consumption of caffeine and the risk of developing OA.

Methods

In this study, we constructed logistic regression models to evaluate the correlation between caffeine consumption and the risk of osteoarthritis using data from the National Health and Nutrition Examination Survey. Following that, we utilized genome-wide association studies to conduct a Mendelian randomization (MR) analysis investigating the association between coffee consumption and the likelihood of developing knee OA. We employed various statistical methods, including inverse variance weighting (IVW), weighted median, weighted mode, simple mode, and MR-Egger regression, to ensure comprehensive analysis and robust conclusions. To evaluate heterogeneity and the potential impact of pleiotropy, we conducted several statistical tests, including Cochran's Q test, MR-Egger intercept test, MR Pleiotropy RESidual Sum and Outlier test (MR-PRESSO), and MR Steiger test.

Results

The weighted multivariate logistic regression analysis showed that the relationship between high caffeine intake (95–206 and ≥206 mg/day) and OA prevalence remained significantly high even after adjusting for covariates using the lowest caffeine intake (< 11 mg/day) as reference: Model 1—OR (95% Cl) = 1.365 (1.18–1.58) and 1.59 (1.38–1.83); Model 2—OR (95% Cl) = 1.21 (1.04–1.42) and 1.44 (1.23–1.68); and Model 3—OR (95% Cl) = 1.19 (1.01–1.40) and 1.30 (1.10–1.52), respectively (p < 0.05). The findings from the fixed effects inverse variance weighted (IVW) analysis revealed a statistically significant link between coffee intake and the likelihood of developing knee osteoarthritis: OR = 1.94; 95% confidence interval (Cl) =1.471–2.517; (p < 0.001). Consistent findings were obtained across various other methods, including MR-Egger regression, weighted median, weighted mode, and simple mode analyses.

Conclusion

Our study showed a positive correlation between OA prevalence and high caffeine intake (≥95 mg/day).