目的:导致CKD患者尿毒症症状的毒素未知。我们试图将互补的统计建模方法应用于来自非靶向血浆代谢组学分析的数据,以识别与CKD患者尿毒症症状相关的溶质。
方法:横断面。
方法:1,761名慢性肾功能不全队列(CRIC)患者CKD未进行透析。
方法:测定448种已知血浆代谢物。
结果:尿毒症症状疲劳,厌食症,瘙痒,恶心,感觉异常,通过肾脏疾病生活质量-36(KDQOL)仪器上的单个项目评估疼痛。
方法:多变量调整线性回归,Lasso线性回归,和随机森林模型用于识别与症状严重程度相关的代谢物。经过多次比较调整后,在三种建模方法中至少有两种选择的代谢物被认为是“整体”显著的。
结果:参与者平均eGFR为43mL/min/1.73m2,其中44%自我识别为女性,41%为非西班牙裔黑人。尿毒症症状的患病率为22-55%。我们确定了17种代谢物,其中较高水平与至少一种尿毒症症状的严重程度有关。和9种代谢物与尿毒症症状严重程度成反比。这些代谢物中的许多与eGFR至少有中等相关性(皮尔逊的r≥0.5),在多变量校正Cox回归模型中,部分患者也与发生肾衰竭或死亡的风险相关.
结论:缺乏第二个独立队列对我们的研究结果进行外部验证。
结论:代谢组学分析用于鉴定与CKD成人尿毒症症状相关的多种溶质,但需要未来的验证和机理研究。
The toxins that contribute to uremic symptoms in patients with chronic kidney disease (CKD) are unknown. We sought to apply complementary statistical modeling approaches to data from untargeted plasma metabolomic profiling to identify solutes associated with uremic symptoms in patients with CKD.
Cross-sectional.
1,761 Chronic Renal Insufficiency Cohort (CRIC) participants with CKD not treated with dialysis.
Measurement of 448 known plasma metabolites.
The uremic symptoms of fatigue, anorexia, pruritus, nausea, paresthesia, and pain were assessed by single items on the Kidney Disease Quality of Life-36 instrument.
Multivariable adjusted linear regression, least absolute shrinkage and selection operator linear regression, and random forest models were used to identify metabolites associated with symptom severity. After adjustment for multiple comparisons, metabolites selected in at least 2 of the 3 modeling approaches were deemed \"overall significant.\"
Participant mean estimated glomerular filtration rate was 43mL/min/1.73m2, with 44% self-identifying as female and 41% as non-Hispanic Black. The prevalence of uremic symptoms ranged from 22% to 55%. We identified 17 metabolites for which a higher level was associated with greater severity of at least one uremic symptom and 9 metabolites inversely associated with uremic symptom severity. Many of these metabolites exhibited at least a moderate correlation with estimated glomerular filtration rate (Pearson\'s r≥0.5), and some were also associated with the risk of developing kidney failure or death in multivariable adjusted Cox regression models.
Lack of a second independent cohort for external validation of our findings.
Metabolomic profiling was used to identify multiple solutes associated with uremic symptoms in adults with CKD, but future validation and mechanistic studies are needed.
Individuals living with chronic kidney disease (CKD) often experience symptoms related to CKD, traditionally called uremic symptoms. It is likely that CKD results in alterations in the levels of numerous circulating substances that, in turn, cause uremic symptoms; however, the identity of these solutes is not known. In this
study, we used metabolomic profiling in patients with CKD to gain insights into the pathophysiology of uremic symptoms. We identified 26 metabolites whose levels were significantly associated with at least one of the symptoms of fatigue, anorexia, itchiness, nausea, paresthesia, and pain. The results of this
study lay the groundwork for future research into the biological causes of symptoms in patients with CKD.