PDF(Pubmed)
Abstract：
UNASSIGNED: Malnutrition is strongly associated with heart failure (HF); however, the causal link remains unclear. We used Mendelian randomization (MR) to infer causal associations between different nutritional assessment phenotypes and HF and to analyze whether these associations were mediated by common HF risk factors.
UNASSIGNED: Two-sample bidirectional MR was used to infer causal associations between nutritional assessment phenotypes and HF. Mutual influences between different nutritional assessment phenotypes and potential correlations were estimated using multivariate MR methods. Two-step MR was used to quantify the mediating effects of common HF risk factors on the causal associations.
UNASSIGNED: Three phenotypes were positively associated with the development of HF: waist circumference (WC) (odds ratio [OR] = 1.74; 95% confidence interval [CI], 1.60-1.90; P = 3.95 × 10-39), body mass index (BMI) (OR = 1.70; 95%CI, 1.60-1.80; P = 1.35 × 10-73), and whole body fat mass (WBFM) (OR = 1.54; 95%CI, 1.44-1.65; P = 4.82 × 10-37). Multivariate MR indicated that WBFM remained positively associated with HF after conditioning on BMI and WC (OR = 2.05; 95%CI, 1.27-3.31; P = 0.003). Three phenotypes were negatively correlated with the development of HF: usual walking pace (UWP) (OR = 0.40; 95%CI, 0.27-0.60; P = 8.41 × 10-6), educational attainment (EA) (OR = 0.73; 95%CI, 0.67-0.79; P = 2.27 × 10-13), and total cholesterol (TC) (OR = 0.90; 95%CI, 0.84-0.96; P = 4.22 × 10-3). There was a bidirectional causality between HF and UWP (Effect estimate = -0.03; 95%CI, -0.05 to -0.01; P = 1.95 × 10-3). Mediation analysis showed that common risk factors for HF (hypertension, coronary artery disease, cardiomyopathy, and valvular heart disease) mediated these causal associations (all P < 0.05).
UNASSIGNED: BMI, WC, and WBFM are potential risk factors for HF, and the correlation between WBFM and HF was significantly stronger than that between BMI and WC, and HF. EA, UWP, and TC are potential protective factors against HF. Common risk factors for HF mediate these causal pathways. Early identification of potential risk or protective factors for HF patients from the dimension of nutritional status is expected to further improve patient outcomes.
UNASSIGNED: Two-sample bidirectional MR was used to infer causal associations between nutritional assessment phenotypes and HF. Mutual influences between different nutritional assessment phenotypes and potential correlations were estimated using multivariate MR methods. Two-step MR was used to quantify the mediating effects of common HF risk factors on the causal associations.
UNASSIGNED: Three phenotypes were positively associated with the development of HF: waist circumference (WC) (odds ratio [OR] = 1.74; 95% confidence interval [CI], 1.60-1.90; P = 3.95 × 10-39), body mass index (BMI) (OR = 1.70; 95%CI, 1.60-1.80; P = 1.35 × 10-73), and whole body fat mass (WBFM) (OR = 1.54; 95%CI, 1.44-1.65; P = 4.82 × 10-37). Multivariate MR indicated that WBFM remained positively associated with HF after conditioning on BMI and WC (OR = 2.05; 95%CI, 1.27-3.31; P = 0.003). Three phenotypes were negatively correlated with the development of HF: usual walking pace (UWP) (OR = 0.40; 95%CI, 0.27-0.60; P = 8.41 × 10-6), educational attainment (EA) (OR = 0.73; 95%CI, 0.67-0.79; P = 2.27 × 10-13), and total cholesterol (TC) (OR = 0.90; 95%CI, 0.84-0.96; P = 4.22 × 10-3). There was a bidirectional causality between HF and UWP (Effect estimate = -0.03; 95%CI, -0.05 to -0.01; P = 1.95 × 10-3). Mediation analysis showed that common risk factors for HF (hypertension, coronary artery disease, cardiomyopathy, and valvular heart disease) mediated these causal associations (all P < 0.05).
UNASSIGNED: BMI, WC, and WBFM are potential risk factors for HF, and the correlation between WBFM and HF was significantly stronger than that between BMI and WC, and HF. EA, UWP, and TC are potential protective factors against HF. Common risk factors for HF mediate these causal pathways. Early identification of potential risk or protective factors for HF patients from the dimension of nutritional status is expected to further improve patient outcomes.
摘要：
■营养不良与心力衰竭（HF）密切相关；然而，因果关系尚不清楚。我们使用孟德尔随机化（MR）来推断不同营养评估表型与HF之间的因果关系，并分析这些关联是否由常见的HF危险因素介导。
■使用双样本双向MR来推断营养评估表型与HF之间的因果关系。使用多变量MR方法估计不同营养评估表型和潜在相关性之间的相互影响。使用两步MR来量化常见HF危险因素对因果关系的中介作用。
■三种表型与HF的发展呈正相关：腰围（WC）（优势比[OR]=1.74；95％置信区间[CI]，1.60-1.90；P=3.95×10-39），体重指数（BMI）（OR=1.70；95CI，1.60-1.80；P=1.35×10-73），和全身脂肪量（WBFM）（OR=1.54；95CI，1.44-1.65；P=4.82×10-37）。多变量MR显示，在BMI和WC调节后，WBFM与HF呈正相关（OR=2.05；95CI，1.27-3.31；P=0.003）。三种表型与HF的发展呈负相关：通常步行速度（UWP）（OR=0.40；95CI，0.27-0.60；P=8.41×10-6），受教育程度（EA）（OR=0.73；95CI，0.67-0.79；P=2.27×10-13），总胆固醇（TC）（OR=0.90；95CI，0.84-0.96；P=4.22×10-3）。HF和UWP之间存在双向因果关系（效应估计=-0.03；95CI，-0.05至-0.01；P=1.95×10-3）。中介分析显示，HF的常见危险因素(高血压，冠状动脉疾病,心肌病,和瓣膜性心脏病）介导了这些因果关系（均P<0.05）。
■BMI，WC,WBFM是HF的潜在危险因素，WBFM与HF的相关性明显强于BMI与WC,和HF。EA,UWP,和TC是针对HF的潜在保护因素。HF的常见危险因素介导这些因果途径。从营养状况的角度早期识别HF患者的潜在风险或保护因素有望进一步改善患者预后。
■使用双样本双向MR来推断营养评估表型与HF之间的因果关系。使用多变量MR方法估计不同营养评估表型和潜在相关性之间的相互影响。使用两步MR来量化常见HF危险因素对因果关系的中介作用。
■三种表型与HF的发展呈正相关：腰围（WC）（优势比[OR]=1.74；95％置信区间[CI]，1.60-1.90；P=3.95×10-39），体重指数（BMI）（OR=1.70；95CI，1.60-1.80；P=1.35×10-73），和全身脂肪量（WBFM）（OR=1.54；95CI，1.44-1.65；P=4.82×10-37）。多变量MR显示，在BMI和WC调节后，WBFM与HF呈正相关（OR=2.05；95CI，1.27-3.31；P=0.003）。三种表型与HF的发展呈负相关：通常步行速度（UWP）（OR=0.40；95CI，0.27-0.60；P=8.41×10-6），受教育程度（EA）（OR=0.73；95CI，0.67-0.79；P=2.27×10-13），总胆固醇（TC）（OR=0.90；95CI，0.84-0.96；P=4.22×10-3）。HF和UWP之间存在双向因果关系（效应估计=-0.03；95CI，-0.05至-0.01；P=1.95×10-3）。中介分析显示，HF的常见危险因素(高血压，冠状动脉疾病,心肌病,和瓣膜性心脏病）介导了这些因果关系（均P<0.05）。
■BMI，WC,WBFM是HF的潜在危险因素，WBFM与HF的相关性明显强于BMI与WC,和HF。EA,UWP,和TC是针对HF的潜在保护因素。HF的常见危险因素介导这些因果途径。从营养状况的角度早期识别HF患者的潜在风险或保护因素有望进一步改善患者预后。
