Lipid metabolism disorders and albuminuria risk: insights from National Health and Nutrition Examination Survey 2001–2018 and Mendelian randomization analyses

Previous studies have revealed an underlying connection between abnormal lipid metabolism and albuminuria. We aim to investigate the causal relationship between lipid metabolism disorders and the risk of albuminuria from both a population and genetic perspective. A cross-sectional study was conducted by using data from the National Health and Nutrition Examination Survey (NHANES) 2001-2018. Multivariable-adjusted logistic regression, subgroup analysis, interaction tests and restricted cubic spline (RCS) were employed statistically. Mendelian randomization (MR) analysis was performed to validate the causal relationship between exposure and outcome to mitigate confounding factors and reverse causation interference. After adjusting for confounders, HDL levels (1.03-2.07 nmol/L) were associated with a reduced risk of albuminuria. In contrast, elevated cholesterol levels (>6.2 nmol/L) and triglyceride levels (>2.3 nmol/L) were associated with an increased risk of albuminuria. Serum triglyceride concentration emerged as a potential risk factor for albuminuria. In MR analysis, a reduced risk of albuminuria was associated with serum total HDL level (IVW: OR = 0.91, 95% CI = 0.86-0.97, p = 0.002). In contrast, cholesterol esters in medium VLDL (IVW: OR = 1.05, 95% CI = 1.00-1.10, p = 0.032), chylomicrons and extremely large VLDL (IVW: OR = 1.08, 95% CI = 1.03-1.14, p = 0.003), and triglycerides (IVW: OR = 1.14, 95% CI = 1.09-1.19, p A causal relationship exists between serum lipid metabolism disorder and albuminuria risk. Further validation of additional blood lipid metabolism biomarkers is imperative for future studies.

既往研究已揭示脂质代谢异常与白蛋白尿之间存在潜在关联。本研究旨在从人群与遗传学视角，探究脂质代谢紊乱与白蛋白尿发病风险之间的因果关联。本研究借助2001-2018年美国国家健康与营养调查（National Health and Nutrition Examination Survey, NHANES）的数据开展了一项横断面研究，统计分析方法采用多变量校正logistic回归、亚组分析、交互作用检验以及限制性立方样条（restricted cubic spline, RCS）模型。为控制混杂因素并消除反向因果干扰，本研究开展了孟德尔随机化（Mendelian randomization, MR）分析以验证暴露因素与结局间的因果关联。在校正混杂因素后，高密度脂蛋白（high-density lipoprotein, HDL）水平处于1.03~2.07 nmol/L区间时，与白蛋白尿发病风险降低相关。与之相反，胆固醇水平升高（＞6.2 nmol/L）与甘油三酯水平升高（＞2.3 nmol/L）均与白蛋白尿发病风险升高相关。血清甘油三酯浓度可作为白蛋白尿的潜在危险因素。孟德尔随机化分析结果显示，血清总高密度脂蛋白水平与白蛋白尿发病风险降低相关（逆方差加权法[inverse variance weighted, IVW]：比值比OR=0.91，95%置信区间CI=0.86~0.97，P=0.002）。与之相反，中等密度极低密度脂蛋白（very low-density lipoprotein, VLDL）中的胆固醇酯（逆方差加权法：OR=1.05，95%CI=1.00~1.10，P=0.032）、乳糜微粒及超大极低密度脂蛋白（逆方差加权法：OR=1.08，95%CI=1.03~1.14，P=0.003）以及甘油三酯（逆方差加权法：OR=1.14，95%CI=1.09~1.19，P）。血清脂质代谢紊乱与白蛋白尿发病风险存在因果关联。未来研究需进一步验证更多血脂代谢生物标志物的相关价值。