Zhang Chuchu, Ren Jiajia, Xu Xi, Lei Hua, Deng Guorong, Liu Jueheng, Gao Xiaoming, Li Jiamei, Wang Xiaochuang, Wang Gang
Department of Critical Care Medicine, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Key Laboratory of Surgical Critical Care and Life Support, Ministry of Education, Xi'an Jiaotong University, Xi'an, China.
Front Nutr. 2024 Sep 23;11:1433754. doi: 10.3389/fnut.2024.1433754. eCollection 2024.
Previous studies have reported an association between obesity and risk of sepsis. However, the results have been inconsistent, and no causal inference can be drawn from them. Therefore, we conducted a Mendelian-randomization (MR) study to investigate causal relationships between available obesity-related anthropometric indicators and sepsis risk.
We performed MR analyses using genome-wide association study (GWAS) summary statistics on 14 anthropometric indicators [namely body mass index (BMI), waist and hip circumferences (WC, HC), basal metabolic rate (BMR), whole-body fat mass (WBFM), trunk fat mass (TFM), leg fat mass (LFM), arm fat mass (AFM), body fat percentage (BFP), whole-body fat-free mass (WBFFM), trunk fat-free mass (TFFM), leg fat-free mass (LFFM), arm fat-free mass (AFFM), and whole-body water mass (WBWM)], sepsis, critical care sepsis, and 28-day death due to sepsis from the UK Biobank and FinnGen cohort. The primary method of MR analysis was inverse variance-weighted average method. Sensitivity analyses, including heterogeneity and horizontal-pleiotropy tests, were conducted to assess the stability of the MR results. Additionally, we applied multiple-variable MR (MVMR) to evaluate the effect of BMI on the relationship between each anthropometric indicator and sepsis risk.
Our MR analysis demonstrated causal relationships between 14 anthropometric indicators and sepsis of different severities. After we adjusted for BMI, MVMR analyses indicated that WC, BMR, LFM, WBFFM, TFFM, AFFM, and WBWM remained significantly associated with the presence of sepsis (all < 0.05). A sensitivity analysis confirmed the reliability of our MR results, and no significant horizontal pleiotropy was detected.
This MR study revealed that increases in obesity-related anthropometric indicators had causal associations with a higher risk of sepsis, which might provide important insights for the identification of individuals at risk for sepsis in community and hospital settings.
既往研究报道了肥胖与脓毒症风险之间的关联。然而，结果并不一致，无法从中得出因果推断。因此，我们进行了一项孟德尔随机化（MR）研究，以探讨可用的肥胖相关人体测量指标与脓毒症风险之间的因果关系。
我们使用全基因组关联研究（GWAS）汇总统计数据，对来自英国生物银行和芬兰基因队列的14项人体测量指标[即体重指数（BMI）、腰围和臀围（WC、HC）、基础代谢率（BMR）、全身脂肪量（WBFM）、躯干脂肪量（TFM）、腿部脂肪量（LFM）、手臂脂肪量（AFM）、体脂百分比（BFP）、全身去脂体重（WBFFM）、躯干去脂体重（TFFM）、腿部去脂体重（LFFM）、手臂去脂体重（AFFM）和全身水含量（WBWM）]、脓毒症、重症监护脓毒症以及因脓毒症导致的28天死亡进行了MR分析。MR分析的主要方法是逆方差加权平均法。进行了敏感性分析，包括异质性和水平多效性检验，以评估MR结果的稳定性。此外，我们应用多变量MR（MVMR）来评估BMI对各人体测量指标与脓毒症风险之间关系的影响。
我们的MR分析显示了14项人体测量指标与不同严重程度脓毒症之间的因果关系。在调整BMI后，MVMR分析表明，WC、BMR、LFM、WBFFM、TFFM、AFFM和WBWM仍与脓毒症的存在显著相关（均P<0.05）。敏感性分析证实了我们MR结果的可靠性，未检测到显著的水平多效性。
这项MR研究表明，肥胖相关人体测量指标的增加与脓毒症风险升高存在因果关联，这可能为在社区和医院环境中识别脓毒症高危个体提供重要见解。
