Lyu Haoyuan, Fan Na, Wen Hao, Zhang Xin, Mao Herong, Bian Qinglai, Chen Jiaxu
School of Basic Medical Sciences, Hubei University of Chinese Medicine, Wuhan, Hubei, 430065, China.
Huangjiahu Hospital, Hubei University of Chinese Medicine, Wuhan, Hubei, 430065, China.
Nutr Metab (Lond). 2025 Jan 28;22(1):7. doi: 10.1186/s12986-025-00896-2.
This study aims to explore the interplay between body mass index (BMI), neutrophils, triglyceride levels, and uric acid (UA). Understanding the causal correlation between UA and health indicators, specifically its association with the body's inflammatory conditions, is crucial for preventing and managing various diseases.
A retrospective analysis was conducted on 4,286 cases utilizing the Spearman correlation method. BMI, neutrophil count, and triglyceride levels were determined as key exposure factors. To further investigate the causal correlation, a two-sample Mendelian randomization(MR) design was utilized, leveraging data from genome-wide association study (GWAS). Within this framework, and multivariable Mendelian randomization(MVMR) was applied to explore the linkage between multiple genetic variants and complex traits.
The study primarily focused on UA, employing genetic variation as a natural tool to assess the causal impact of various factors on UA. Spearman correlation analysis revealed significant association between UA and BMI (ρ = 0.230,p<0.01), neutrophils (ρ = 0.164,p<0.01), and triglyceride levels (ρ = 0.154,p<0.01). Additionally, two-sample MR analysis affirmed a reciprocal causal association between neutrophils and UA (OR = 1.035,95%CI:1.009-1.061,p = 0.008), as well as positive causal connection between UA and both BMI (OR = 1.083,95%CI:1.042-1.126,p<0.001) and triglyceride levels (OR = 1.090,95%CI:1.037-1.146,p<0.001). Neutrophils also demonstrated a positive causal linkage with BMI (OR = 1.034,95%CI:1.009-1.078,p = 0.012) and triglyceride levels (OR = 1.077,95%CI:1.033-1.122,p<0.001), and BMI exhibited a similar causal association with triglyceride levels (OR = 1.300,95%CI:1.212-1.385,p<0.001). These findings shed light on the causal networks connecting UA, BMI, neutrophils, and triglyceride levels. By integrating Spearman correlation analysis with various MR study designs, this study provided a robust framework for identifying key factors influencing hyperuricemia and related health issues, thereby enhancing our understanding of the interplay between inflammatory markers and these health indicators.
Our study presents strong evidence of the complex interconnection between BMI, neutrophils, triglyceride, and UA, revealing complex causal links and highlighting potential inflammatory states as key mediators. The findings may contribute to a better understanding of these factors and potentially lead to improved clinical outcomes and patients' health.
本研究旨在探讨体重指数(BMI)、中性粒细胞、甘油三酯水平和尿酸(UA)之间的相互作用。了解尿酸与健康指标之间的因果关系,特别是其与身体炎症状态的关联,对于预防和管理各种疾病至关重要。
采用Spearman相关方法对4286例病例进行回顾性分析。将BMI、中性粒细胞计数和甘油三酯水平确定为关键暴露因素。为进一步研究因果关系,利用全基因组关联研究(GWAS)的数据,采用两样本孟德尔随机化(MR)设计。在此框架内,应用多变量孟德尔随机化(MVMR)来探索多个基因变异与复杂性状之间的联系。
该研究主要关注尿酸,采用基因变异作为自然工具来评估各种因素对尿酸的因果影响。Spearman相关分析显示,尿酸与BMI(ρ = 0.230,p < 0.01)、中性粒细胞(ρ = 0.164,p < 0.01)和甘油三酯水平(ρ = 0.154,p < 0.01)之间存在显著关联。此外,两样本MR分析证实中性粒细胞与尿酸之间存在相互因果关系(OR = 1.035,95%CI:1.009 - 1.061,p = 0.008),尿酸与BMI(OR = 1.083,95%CI:1.042 - 1.126,p < 0.001)和甘油三酯水平(OR = 1.090,95%CI:1.037 - 1.146,p < 0.001)之间存在正向因果关系。中性粒细胞与BMI(OR = 1.034,95%CI:1.009 - 1.078,p = 0.012)和甘油三酯水平(OR = 1.077,95%CI:1.033 - 1.122,p < 0.001)也存在正向因果联系,BMI与甘油三酯水平也存在类似的因果关系(OR = 1.300,95%CI:1.212 - 1.385,p < 0.001)。这些发现揭示了连接尿酸、BMI、中性粒细胞和甘油三酯水平的因果网络。通过将Spearman相关分析与各种MR研究设计相结合,本研究为识别影响高尿酸血症及相关健康问题的关键因素提供了一个强大的框架,从而增进了我们对炎症标志物与这些健康指标之间相互作用的理解。
我们的研究提供了有力证据,证明BMI、中性粒细胞、甘油三酯和尿酸之间存在复杂的相互联系,揭示了复杂的因果关系,并突出了潜在的炎症状态作为关键调节因子。这些发现可能有助于更好地理解这些因素,并有可能改善临床结果和患者健康。