Peschard Vanessa-Giselle, Scherzer Rebecca, Estrella Michelle M, Sarnak Mark J, Ascher Simon B, Lash James, Bonventre Joseph V, Greenberg Jason H, Gutierrez Orlando M, Schelling Jeffrey R, Katz Ronit, Cheung Katharine L, Levitan Emily B, Schrauben Sarah J, Cushman Mary, Ilori Titilayo O, Parikh Chirag R, Kimmel Paul L, Rao Panduranga S, Taliercio Jonathan J, Sondheimer James, Shulman Rachel, Coca Steven G, Chen Jing, Ramachandran Vasan S, Ix Joachim H, Shlipak Michael G
Division of Nephrology, Department of Medicine, University of California, San Francisco, San Francisco, California.
Kidney Health Research Collaborative, San Francisco Veterans Affairs Health Care System, University of California, San Francisco, San Francisco, California.
Clin J Am Soc Nephrol. 2025 May 1;20(5):665-675. doi: 10.2215/CJN.0000000676. Epub 2025 Mar 14.
We identified three kidney health dimensions using 17 urine and plasma biomarkers across two cohorts of persons with diabetes and CKD. Worse scores for tubule injury, tubule function, and systemic inflammation/filtration were associated with a higher risk of CKD progression and death. A multibiomarker approach could help capture tubulointerstitial health in persons with diabetes and CKD.
Individual kidney tubule biomarkers are associated with risks of CKD progression and mortality in persons with diabetes. Integrating multiple kidney biomarkers using a latent variable method of exploratory factor analysis could define distinct dimensions of kidney health and their associations with adverse outcomes.
We conducted a factor analysis of 17 candidate urine and plasma biomarkers in 1256 participants with diabetes and eGFR <60 ml/min per 1.73 m from the Chronic Renal Insufficiency Cohort (CRIC; =701) and the REasons for Geographic And Racial Differences in Stroke (REGARDS; =555) studies. We used Cox proportional hazards models to evaluate the associations of identified factors with CKD progression and mortality, adjusting for baseline clinical risk factors, eGFR, and albuminuria.
Three factor scores comprising ten biomarkers were identified: (plasma TNF receptor-1 and TNF receptor-2, plasma soluble urokinase plasminogen activator receptor, and plasma symmetric dimethylarginine), (urine EGF, urine asymmetric dimethylarginine, and urine symmetric dimethylarginine), and (urine -1 microglobulin, urine kidney injury molecule-1, and urine monocyte chemoattractant protein-1). In CRIC, there were 244 incident ESKD events, 102 with ≥40% eGFR decline from baseline, and 259 deaths; in REGARDS, there were 121 incident ESKD events and 462 deaths. In CRIC, lower (hazard ratio per 1-SD, 0.36; 95% confidence interval, 0.25 to 0.52) and higher (1.45; 1.18 to 1.78) scores were independently associated with higher CKD progression risk. Associations in REGARDS were weaker but directionally consistent ( score [0.81; 0.47 to 1.39] and score [1.12; 0.73 to 1.72]). Higher (1.47; 1.15 to 1.87) scores were associated with higher mortality risk in CRIC, but not REGARDS (1.15; 0.96 to 1.38). Higher factor scores were associated with higher mortality risk in both cohorts (CRIC: 1.35; 1.07 to 1.71; REGARDS: 1.41; 1.20 to 1.65).
Three distinct kidney health dimensions were identified, and each associated with CKD progression and/or all-cause mortality in persons with diabetes and CKD.
我们通过对两组糖尿病和慢性肾脏病患者使用17种尿液和血浆生物标志物，确定了三个肾脏健康维度。肾小管损伤、肾小管功能以及全身炎症/滤过方面得分越差，慢性肾脏病进展和死亡风险越高。多生物标志物方法有助于了解糖尿病和慢性肾脏病患者的肾小管间质健康状况。
个体肾小管生物标志物与糖尿病患者慢性肾脏病进展及死亡风险相关。采用探索性因子分析的潜在变量方法整合多种肾脏生物标志物，可明确肾脏健康的不同维度及其与不良结局的关联。
我们对来自慢性肾功能不全队列研究（CRIC；n = 701）和中风地理和种族差异原因研究（REGARDS；n = 555）的1256例糖尿病且估算肾小球滤过率（eGFR）<60 ml/min/1.73 m²的参与者的17种候选尿液和血浆生物标志物进行了因子分析。我们使用Cox比例风险模型评估所确定因子与慢性肾脏病进展和死亡的关联，并对基线临床风险因素、eGFR和蛋白尿进行了校正。
确定了由十种生物标志物组成的三个因子得分：F1（血浆肿瘤坏死因子受体-1和肿瘤坏死因子受体-2、血浆可溶性尿激酶型纤溶酶原激活剂受体以及血浆对称二甲基精氨酸）、F2（尿表皮生长因子、尿不对称二甲基精氨酸和尿对称二甲基精氨酸）和F3（尿β2-微球蛋白、尿肾脏损伤分子-1和尿单核细胞趋化蛋白-1）。在CRIC研究中，有244例终末期肾病事件、102例eGFR自基线下降≥40%的事件以及259例死亡；在REGARDS研究中，有121例终末期肾病事件和462例死亡。在CRIC研究中，较低的F2得分（每降低1个标准差的风险比为0.36；95%置信区间为0.25至0.52）和较高的F3得分（1.45；1.18至1.78）与更高的慢性肾脏病进展风险独立相关。REGARDS研究中的关联较弱但方向一致（F2得分[0.81；0.47至1.39]和F3得分[1.12；0.73至1.72]）。较高的F1得分（1.47；1.15至1.87）与CRIC研究中的较高死亡风险相关，但在REGARDS研究中无此关联（1.15；0.96至1.38）。较高的F3因子得分在两个队列中均与较高的死亡风险相关（CRIC研究：1.35；1.07至1.71；REGARDS研究：1.41；1.20至1.65）。
确定了三个不同的肾脏健康维度，且每个维度都与糖尿病和慢性肾脏病患者的慢性肾脏病进展和/或全因死亡率相关。
