Karger Amy B, Inker Lesley A, Coresh Josef, Levey Andrew S, Eckfeldt John H
Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA.
William B. Schwartz Division of Nephrology, Tufts Medical Center, Department of Medicine, Tufts University School of Medicine, Boston, MA, USA.
EJIFCC. 2017 Dec 19;28(4):277-288. eCollection 2017 Dec.
Creatinine-based glomerular filtration rate estimation (eGFR) has been improved and refined since the 1970s through both the Modification of Diet in Renal Disease (MDRD) Study equation in 1999 and the CKD Epidemiology Collaboration (CKD-EPI) equation in 2009, with current clinical practice dependent primarily on eGFR for accurate assessment of GFR. However, researchers and clinicians have recognized limitations of relying on creatinine as the only filtration marker, which can lead to inaccurate GFR estimates in certain populations due to the influence of non-GFR determinants of serum or plasma creatinine. Therefore, recent literature has proposed incorporation of multiple serum or plasma filtration markers into GFR estimation to improve precision and accuracy and decrease the impact of non-GFR determinants for any individual biomarker. To this end, the CKD-EPI combined creatinine-cystatin C equation (eGFR) was developed in 2012 and demonstrated superior accuracy to equations relying on creatinine or cystatin C alone (eGFR or eGFR). Now, the focus has broadened to include additional novel filtration markers to further refine and improve GFR estimation. Beta-2-microglobulin (B2M) and beta-trace-protein (BTP) are two filtration markers with established assays that have been proposed as candidates for improving both GFR estimation and risk prediction. GFR estimating equations based on B2M and BTP have been developed and validated, with the CKD-EPI combined BTP-B2M equation (eGFR) demonstrating similar performance to eGFR and eGFR. Additionally, several studies have demonstrated that both B2M and BTP are associated with outcomes in CKD patients, including cardiovascular events, ESRD and mortality. This review will primarily focus on these two biomarkers, and will highlight efforts to identify additional candidate biomarkers through metabolomics-based approaches.
自20世纪70年代以来,基于肌酐的肾小球滤过率估计值(eGFR)不断改进和完善,1999年通过肾脏病饮食改良(MDRD)研究方程,2009年通过慢性肾脏病流行病学协作组(CKD-EPI)方程,目前临床实践主要依靠eGFR来准确评估肾小球滤过率(GFR)。然而,研究人员和临床医生已经认识到仅依靠肌酐作为唯一滤过标志物的局限性,由于血清或血浆肌酐的非GFR决定因素的影响,这可能导致某些人群的GFR估计不准确。因此,最近的文献提出将多种血清或血浆滤过标志物纳入GFR估计中,以提高精度和准确性,并减少任何单个生物标志物的非GFR决定因素的影响。为此,CKD-EPI联合肌酐-胱抑素C方程(eGFR)于2012年开发,其准确性优于仅依赖肌酐或胱抑素C的方程(eGFR或eGFR)。现在,关注点已经扩大到包括其他新型滤过标志物,以进一步完善和改进GFR估计。β2微球蛋白(B2M)和β-微量蛋白(BTP)是两种有既定检测方法的滤过标志物,已被提议作为改善GFR估计和风险预测的候选标志物。基于B2M和BTP的GFR估计方程已经开发并验证,CKD-EPI联合BTP-B2M方程(eGFR)表现出与eGFR和eGFR相似的性能。此外,多项研究表明,B2M和BTP均与CKD患者的预后相关,包括心血管事件、终末期肾病(ESRD)和死亡率。本综述将主要关注这两种生物标志物,并将重点介绍通过基于代谢组学的方法识别其他候选生物标志物的努力。