Abstract：
Previous studies indicate a strong correlation between the incidence of chronic kidney disease (CKD) and lower economic status. However, these studies often struggle to delineate a clear cause-effect relationship, leaving healthcare providers uncertain about how to manage kidney disease in a way that improves patients\' financial outcomes. Our study aimed to explore and establish a causal relationship between CKD and socioeconomic status, identifying critical influencing factors. We utilized summary meta-analysis data from the CKDGen Consortium and UK Biobank. Genetic variants identified from these sources served as instrumental variables (IVs) to estimate the association between CKD and socioeconomic status. The presence or absence of CKD, estimated glomerular filtration rate (eGFR), and albuminuria were used as exposures, while income and regional deprivation were analyzed as outcomes. We employed the R packages \'TwoSampleMR\' and \'Mendelianrandomization\' to conduct both univariable and multivariable Mendelian randomization (MR) analyses, assessing for potential pleiotropy and heterogeneity. Our univariable MR analysis revealed a significant causal relationship between high levels of albuminuria and lower income (OR = 0.84, 95% CI: 0.73-0.96, p = 0.013), with no significant pleiotropy detected. In the multivariable MR analysis, both CKD (OR = 0.867, 95% CI: 0.786-0.957, p = 0.0045) and eGFR (OR = 0.065, 95% CI: 0.010-0.437, p = 0.0049) exhibited significant effects on income. This study underscores that higher albuminuria levels in CKD patients are associated with decreased income and emphasizes the importance of effective management and treatment of albuminuria in CKD patients to mitigate both social and personal economic burdens.
摘要：
先前的研究表明，慢性肾脏病（CKD）的发病率与较低的经济状况之间存在很强的相关性。然而,这些研究往往很难描述一个明确的因果关系，让医疗保健提供者不确定如何以改善患者财务结果的方式管理肾脏疾病。我们的研究旨在探索和建立CKD与社会经济地位之间的因果关系。确定关键影响因素。我们利用了CKDGen联盟和英国生物银行的汇总荟萃分析数据。从这些来源鉴定的遗传变异用作工具变量(IVs)以估计CKD与社会经济状况之间的关联。CKD的存在与否，估计肾小球滤过率(eGFR)，和蛋白尿被用作暴露，而收入和地区剥夺作为结果进行分析。我们使用R包\'TwoSampleMR\'和\'孟德尔随机化\'进行单变量和多变量孟德尔随机化（MR）分析，评估潜在的多效性和异质性。我们的单变量MR分析揭示了高水平白蛋白尿和低收入之间的显著因果关系(OR=0.84,95%CI:0.73-0.96,p=0.013),没有检测到显著的多效性。在多变量MR分析中，CKD(OR=0.867,95%CI:0.786-0.957,p=0.0045)和eGFR(OR=0.065,95%CI:0.010-0.437,p=0.0049)对收入均有显著影响。这项研究强调了CKD患者的高蛋白尿水平与收入减少有关，并强调了有效管理和治疗CKD患者的蛋白尿以减轻社会和个人经济负担的重要性。
