PDF(Pubmed)
Abstract：
UNASSIGNED: In recent years, the prevalence of obesity has continued to increase as a global health concern. Numerous epidemiological studies have confirmed the long-term effects of exposure to ambient air pollutant particulate matter 2.5 (PM2.5) on obesity, but their relationship remains ambiguous.
UNASSIGNED: Utilizing large-scale publicly available genome-wide association studies (GWAS), we conducted univariate and multivariate Mendelian randomization (MR) analyses to assess the causal effect of PM2.5 exposure on obesity and its related indicators. The primary outcome given for both univariate MR (UVMR) and multivariate MR (MVMR) is the estimation utilizing the inverse variance weighted (IVW) method. The weighted median, MR-Egger, and maximum likelihood techniques were employed for UVMR, while the MVMR-Lasso method was applied for MVMR in the supplementary analyses. In addition, we conducted a series of thorough sensitivity studies to determine the accuracy of our MR findings.
UNASSIGNED: The UVMR analysis demonstrated a significant association between PM2.5 exposure and an increased risk of obesity, as indicated by the IVW model (odds ratio [OR]: 6.427; 95% confidence interval [CI]: 1.881-21.968; P FDR = 0.005). Additionally, PM2.5 concentrations were positively associated with fat distribution metrics, including visceral adipose tissue (VAT) (OR: 1.861; 95% CI: 1.244-2.776; P FDR = 0.004), particularly pancreatic fat (OR: 3.499; 95% CI: 2.092-5.855; PFDR =1.28E-05), and abdominal subcutaneous adipose tissue (ASAT) volume (OR: 1.773; 95% CI: 1.106-2.841; P FDR = 0.019). Furthermore, PM2.5 exposure correlated positively with markers of glucose and lipid metabolism, specifically triglycerides (TG) (OR: 19.959; 95% CI: 1.269-3.022; P FDR = 0.004) and glycated hemoglobin (HbA1c) (OR: 2.462; 95% CI: 1.34-4.649; P FDR = 0.007). Finally, a significant negative association was observed between PM2.5 concentrations and levels of the novel obesity-related biomarker fibroblast growth factor 21 (FGF-21) (OR: 0.148; 95% CI: 0.025-0.89; P FDR = 0.037). After adjusting for confounding factors, including external smoke exposure, physical activity, educational attainment (EA), participation in sports clubs or gym leisure activities, and Townsend deprivation index at recruitment (TDI), the MVMR analysis revealed that PM2.5 levels maintained significant associations with pancreatic fat, HbA1c, and FGF-21.
UNASSIGNED: Our MR study demonstrates conclusively that higher PM2.5 concentrations are associated with an increased risk of obesity-related indicators such as pancreatic fat content, HbA1c, and FGF-21. The potential mechanisms require additional investigation.
UNASSIGNED: Utilizing large-scale publicly available genome-wide association studies (GWAS), we conducted univariate and multivariate Mendelian randomization (MR) analyses to assess the causal effect of PM2.5 exposure on obesity and its related indicators. The primary outcome given for both univariate MR (UVMR) and multivariate MR (MVMR) is the estimation utilizing the inverse variance weighted (IVW) method. The weighted median, MR-Egger, and maximum likelihood techniques were employed for UVMR, while the MVMR-Lasso method was applied for MVMR in the supplementary analyses. In addition, we conducted a series of thorough sensitivity studies to determine the accuracy of our MR findings.
UNASSIGNED: The UVMR analysis demonstrated a significant association between PM2.5 exposure and an increased risk of obesity, as indicated by the IVW model (odds ratio [OR]: 6.427; 95% confidence interval [CI]: 1.881-21.968; P FDR = 0.005). Additionally, PM2.5 concentrations were positively associated with fat distribution metrics, including visceral adipose tissue (VAT) (OR: 1.861; 95% CI: 1.244-2.776; P FDR = 0.004), particularly pancreatic fat (OR: 3.499; 95% CI: 2.092-5.855; PFDR =1.28E-05), and abdominal subcutaneous adipose tissue (ASAT) volume (OR: 1.773; 95% CI: 1.106-2.841; P FDR = 0.019). Furthermore, PM2.5 exposure correlated positively with markers of glucose and lipid metabolism, specifically triglycerides (TG) (OR: 19.959; 95% CI: 1.269-3.022; P FDR = 0.004) and glycated hemoglobin (HbA1c) (OR: 2.462; 95% CI: 1.34-4.649; P FDR = 0.007). Finally, a significant negative association was observed between PM2.5 concentrations and levels of the novel obesity-related biomarker fibroblast growth factor 21 (FGF-21) (OR: 0.148; 95% CI: 0.025-0.89; P FDR = 0.037). After adjusting for confounding factors, including external smoke exposure, physical activity, educational attainment (EA), participation in sports clubs or gym leisure activities, and Townsend deprivation index at recruitment (TDI), the MVMR analysis revealed that PM2.5 levels maintained significant associations with pancreatic fat, HbA1c, and FGF-21.
UNASSIGNED: Our MR study demonstrates conclusively that higher PM2.5 concentrations are associated with an increased risk of obesity-related indicators such as pancreatic fat content, HbA1c, and FGF-21. The potential mechanisms require additional investigation.
摘要：
■近年来，作为全球健康问题，肥胖症的患病率持续上升。大量流行病学研究证实了暴露于环境空气污染物颗粒物2.5(PM2.5)对肥胖的长期影响,但是他们的关系仍然模棱两可。
■利用大规模公开的全基因组关联研究（GWAS），我们进行了单因素和多因素孟德尔随机化(MR)分析,以评估PM2.5暴露对肥胖及其相关指标的因果效应.单变量MR（UVMR）和多变量MR（MVMR）的主要结果是利用逆方差加权（IVW）方法进行估计。加权中位数，MR-Egger,最大似然技术用于UVMR，而MVMR-Lasso方法在补充分析中应用于MVMR。此外,我们进行了一系列全面的敏感性研究,以确定我们的MR检查结果的准确性.
■UVMR分析表明，PM2.5暴露与肥胖风险增加之间存在显着关联，如IVW模型所示（比值比[OR]：6.427；95％置信区间[CI]：1.881-21.968；PFDR=0.005）。此外,PM2.5浓度与脂肪分布指标呈正相关，包括内脏脂肪组织（VAT）（OR：1.861;95％CI：1.244-2.776;PFDR=0.004），尤其是胰腺脂肪（OR：3.499；95%CI：2.092-5.855；PFDR=1.28E-05），和腹部皮下脂肪组织（ASAT）体积（OR：1.773；95％CI：1.106-2.841；PFDR=0.019）。此外，PM2.5暴露与糖脂代谢标志物呈正相关,特别是甘油三酯(TG)(OR:19.959;95%CI:1.269-3.022;PFDR=0.004)和糖化血红蛋白(HbA1c)(OR:2.462;95%CI:1.34-4.649;PFDR=0.007).最后,在PM2.5浓度和新型肥胖相关生物标志物成纤维细胞生长因子21(FGF-21)水平之间观察到显著负相关(OR:0.148;95%CI:0.025-0.89;PFDR=0.037).在调整混杂因素后，包括外部烟雾暴露，身体活动,教育程度（EA），参加体育俱乐部或健身房休闲活动，和汤森德招聘剥夺指数(TDI)，MVMR分析显示，PM2.5水平与胰腺脂肪保持显著关联，HbA1c,FGF-21
■我们的MR研究最终证明，较高的PM2.5浓度与肥胖相关指标（如胰腺脂肪含量）的风险增加有关。HbA1c,FGF-21潜在的机制需要额外的调查。
■利用大规模公开的全基因组关联研究（GWAS），我们进行了单因素和多因素孟德尔随机化(MR)分析,以评估PM2.5暴露对肥胖及其相关指标的因果效应.单变量MR（UVMR）和多变量MR（MVMR）的主要结果是利用逆方差加权（IVW）方法进行估计。加权中位数，MR-Egger,最大似然技术用于UVMR，而MVMR-Lasso方法在补充分析中应用于MVMR。此外,我们进行了一系列全面的敏感性研究,以确定我们的MR检查结果的准确性.
■UVMR分析表明，PM2.5暴露与肥胖风险增加之间存在显着关联，如IVW模型所示（比值比[OR]：6.427；95％置信区间[CI]：1.881-21.968；PFDR=0.005）。此外,PM2.5浓度与脂肪分布指标呈正相关，包括内脏脂肪组织（VAT）（OR：1.861;95％CI：1.244-2.776;PFDR=0.004），尤其是胰腺脂肪（OR：3.499；95%CI：2.092-5.855；PFDR=1.28E-05），和腹部皮下脂肪组织（ASAT）体积（OR：1.773；95％CI：1.106-2.841；PFDR=0.019）。此外，PM2.5暴露与糖脂代谢标志物呈正相关,特别是甘油三酯(TG)(OR:19.959;95%CI:1.269-3.022;PFDR=0.004)和糖化血红蛋白(HbA1c)(OR:2.462;95%CI:1.34-4.649;PFDR=0.007).最后,在PM2.5浓度和新型肥胖相关生物标志物成纤维细胞生长因子21(FGF-21)水平之间观察到显著负相关(OR:0.148;95%CI:0.025-0.89;PFDR=0.037).在调整混杂因素后，包括外部烟雾暴露，身体活动,教育程度（EA），参加体育俱乐部或健身房休闲活动，和汤森德招聘剥夺指数(TDI)，MVMR分析显示，PM2.5水平与胰腺脂肪保持显著关联，HbA1c,FGF-21
■我们的MR研究最终证明，较高的PM2.5浓度与肥胖相关指标（如胰腺脂肪含量）的风险增加有关。HbA1c,FGF-21潜在的机制需要额外的调查。
