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Abstract

The current unidimensional paradigm of kidney disease detection is incompatible with the complexity and heterogeneity of renal pathology. The diagnosis of kidney disease has largely focused on glomerular filtration, while assessment of kidney tubular health has notably been absent. Following insult, the kidney tubular cells undergo a cascade of cellular responses that result in the production and accumulation of low-molecular-weight proteins in the urine and systemic circulation. Modern advancements in molecular analysis and proteomics have allowed the identification and quantification of these proteins as biomarkers for assessing and characterizing kidney diseases. In this review, we highlight promising biomarkers of kidney tubular health that have strong underpinnings in the pathophysiology of kidney disease. These biomarkers have been applied to various specific clinical settings from the spectrum of acute to chronic kidney diseases, demonstrating the potential to improve patient care.

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2019-02-10
2024-06-21
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Literature Cited

  1. 1.
    Uchino S, Kellum JA, Bellomo R, Doig GS, Morimatsu H et al. 2005. Acute renal failure in critically ill patients: a multinational, multicenter study. JAMA 294:813–18
    [Google Scholar]
  2. 2.
    Kampmann J, Siersbaek-Nielsen K, Kristensen M, Hansen JM 1974. Rapid evaluation of creatinine clearance. Acta Med. Scand. 196:517–20
    [Google Scholar]
  3. 3.
    Nickolas TL, Barasch J, Devarajan P 2008. Biomarkers in acute and chronic kidney disease. Curr. Opin. Nephrol. Hypertens. 17:127–32
    [Google Scholar]
  4. 4.
    Bosch JP. 1995. Renal reserve: a functional view of glomerular filtration rate. Semin. Nephrol. 15:381–85
    [Google Scholar]
  5. 5.
    Herrera J, Rodríguez-Iturbe B 1998. Stimulation of tubular secretion of creatinine in health and in conditions associated with reduced nephron mass. Evidence for a tubular functional reserve. Nephrol. Dial. Transplant. 13:623–29
    [Google Scholar]
  6. 6.
    Wu I, Parikh CR 2008. Screening for kidney diseases: older measures versus novel biomarkers. Clin. J. Am. Soc. Nephrol. 3:1895–901
    [Google Scholar]
  7. 7.
    Zurbig P, Dihazi H, Metzger J, Thongboonkerd V, Vlahou A 2011. Urine proteomics in kidney and urogenital diseases: moving towards clinical applications. Proteom. Clin. Appl. 5:256–68
    [Google Scholar]
  8. 8.
    Shao C, Wang Y, Gao Y 2011. Applications of urinary proteomics in biomarker discovery. Sci. China Live Sci. 54:409–17
    [Google Scholar]
  9. 9.
    Boudonck KJ, Rose DJ, Karoly ED, Lee DP, Lawton KA, Lapinskas PJ 2009. Metabolomics for early detection of drug-induced kidney injury: review of the current status. Bioanalysis 1:1645–63
    [Google Scholar]
  10. 10.
    Prunotto M, Ghiggeri GM, Candiano G, Lescuyer P, Hochstrasser D, Moll S 2011. Urinary proteomics and drug discovery in chronic kidney disease: a new perspective. J. Proteome Res. 10:126–32
    [Google Scholar]
  11. 11.
    Takaori K, Nakamura J, Yamamoto S, Nakata H, Sato Y et al. 2016. Severity and frequency of proximal tubule injury determines renal prognosis. J. Am. Soc. Nephrol. 27:2393–406
    [Google Scholar]
  12. 12.
    Woroniecki RP, Schnaper HW 2009. Progression of glomerular and tubular disease. Semin. Nephrol. 29:412–24
    [Google Scholar]
  13. 13.
    Flower DR. 1996. The lipocalin protein family: structure and function. Biochem. J. 318:Part 11–14
    [Google Scholar]
  14. 14.
    Soni SS, Cruz D, Bobek I, Chionh CY, Nalesso F et al. 2010. NGAL: a biomarker of acute kidney injury and other systemic conditions. Int. Urol. Nephrol. 42:141–50
    [Google Scholar]
  15. 15.
    Supavekin S, Zhang W, Kucherlapati R, Kaskel FJ, Moore LC, Devarajan P 2003. Differential gene expression following early renal ischemia/reperfusion. Kidney Int 63:1714–24
    [Google Scholar]
  16. 16.
    Yuen PST, Jo S-K, Holly MK, Hu X, Star RA 2006. Ischemic and nephrotoxic acute renal failure are distinguished by their broad transcriptomic responses. Physiol. Genom. 25:375–86
    [Google Scholar]
  17. 17.
    Mishra J, Ma Q, Prada A, Mitsnefes M, Zahedi K et al. 2003. Identification of neutrophil gelatinase-associated lipocalin as a novel early urinary biomarker for ischemic renal injury. J. Am. Soc. Nephrol. 14:2534–43
    [Google Scholar]
  18. 18.
    Mishra J, Dent C, Tarabishi R, Mitsnefes MM, Ma Q et al. 2005. Neutrophil gelatinase-associated lipocalin (NGAL) as a biomarker for acute renal injury after cardiac surgery. Lancet 365:1231–38
    [Google Scholar]
  19. 19.
    Nickolas TL, Forster CS, Sise ME, Barasch N, Valle DS et al. 2012. NGAL (Lcn2) monomer is associated with tubulointerstitial damage in chronic kidney disease. Kidney Int 82:718–22
    [Google Scholar]
  20. 20.
    Ichimura T, Bonventre JV, Bailly V, Wei H, Hession CA et al. 1998. Kidney injury molecule-1 (KIM-1), a putative epithelial cell adhesion molecule containing a novel immunoglobulin domain, is up-regulated in renal cells after injury. J. Biol. Chem. 273:4135–42
    [Google Scholar]
  21. 21.
    Hubank M, Schatz DG 1994. Identifying differences in mRNA expression by representational difference analysis of cDNA. Nucl. Acid Res. 22:5640–48
    [Google Scholar]
  22. 22.
    Han WK, Bailly V, Abichandani R, Thadhani R, Bonventre JV 2002. Kidney Injury Molecule-1 (KIM-1): a novel biomarker for human renal proximal tubule injury. Kidney Int 62:237–44
    [Google Scholar]
  23. 23.
    Vaidya VS, Ramirez V, Ichimura T, Bobadilla NA, Bonventre JV 2006. Urinary kidney injury molecule-1: a sensitive quantitative biomarker for early detection of kidney tubular injury. Am. J. Physiol. Ren. Physiol. 290:517–29
    [Google Scholar]
  24. 24.
    Zhou Y, Vaidya VS, Brown RP, Zhang J, Rosenzweig BA et al. 2008. Comparison of kidney injury molecule-1 and other nephrotoxicity biomarkers in urine and kidney following acute exposure to gentamicin, mercury, and chromium. Toxicol. Sci. 101:159–70
    [Google Scholar]
  25. 25.
    Prozialeck WC, Vaidya VS, Liu J, Waalkes MP, Edwards JR et al. 2007. Kidney injury molecule-1 is an early biomarker of cadmium nephrotoxicity. Kidney Int 72:985–93
    [Google Scholar]
  26. 26.
    Jost G, Pietsch H, Sommer J, Sandner P, Lengsfeld P et al. 2009. Retention of iodine and expression of biomarkers for renal damage in the kidney after application of iodinated contrast media in rats. Investig. Radiol. 44:114–23
    [Google Scholar]
  27. 27.
    Pérez-Rojas J, Blanco JA, Cruz C, Trujillo J, Vaidya VS et al. 2007. Mineralocorticoid receptor blockade confers renoprotection in preexisting chronic cyclosporine nephrotoxicity. Am. J. Physiol. Ren. Physiol. 292:131–39
    [Google Scholar]
  28. 28.
    van Timmeren MM, Bakker SJL, Vaidya VS, Bailly V, Schuurs TA et al. 2006. Tubular kidney injury molecule-1 in protein-overload nephropathy. Am. J. Physiol. Ren. Physiol. 291:456–64
    [Google Scholar]
  29. 29.
    Ko GJ, Grigoryev DN, Linfert D, Jang HR, Watkins T et al. 2010. Transcriptional analysis of kidneys during repair from AKI reveals possible roles for NGAL and KIM-1 as biomarkers of AKI-to-CKD transition. Am. J. Physiol. Ren. Physiol. 298:F1472–83
    [Google Scholar]
  30. 30.
    Price PM, Safirstein RL, Megyesi J 2009. The cell cycle and acute kidney injury. Kidney Int 76:604–13
    [Google Scholar]
  31. 31.
    Boonstra J, Post JA 2004. Molecular events associated with reactive oxygen species and cell cycle progression in mammalian cells. Gene 337:1–13
    [Google Scholar]
  32. 32.
    Seo DW, Li H, Qu CK, Oh J, Kim YS et al. 2006. Shp-1 mediates the antiproliferative activity of tissue inhibitor of metalloproteinase-2 in human microvascular endothelial cells. J. Biol. Chem. 281:3711–21
    [Google Scholar]
  33. 33.
    Kashani K, Al-Khafaji A, Ardiles T, Artigas A, Bagshaw SM et al. 2013. Discovery and validation of cell cycle arrest biomarkers in human acute kidney injury. Crit. Care 17:R25
    [Google Scholar]
  34. 34.
    Togashi Y, Sakaguchi Y, Miyamoto M, Miyamoto Y 2012. Urinary cystatin C as a biomarker for acute kidney injury and its immunohistochemical localization in kidney in the CDDP-treated rats. Exp. Toxicol. Pathol. 64:797–805
    [Google Scholar]
  35. 35.
    Koyner JL, Bennett MR, Worcester EM, Ma Q, Raman J et al. 2008. Urinary cystatin C as an early biomarker of acute kidney injury following adult cardiothoracic surgery. Kidney Int 74:1059–69
    [Google Scholar]
  36. 36.
    Penders J, Delanghe JR 2004. Alpha 1-microglobulin: clinical laboratory aspects and applications. Clin. Chim. Acta 346:107–18
    [Google Scholar]
  37. 37.
    Itoh Y, Kawai T 1990. Human α1-microglobulin: its measurement and clinical significance. J. Clin. Lab. Anal. 4:376–84
    [Google Scholar]
  38. 38.
    Yamamoto T, Noiri E, Ono Y, Doi K, Negishi K et al. 2007. Renal L-type fatty acid–binding protein in acute ischemic injury. J. Am. Soc. Nephrol. 18:2894–902
    [Google Scholar]
  39. 39.
    Portilla D, Dent C, Sugaya T, Nagothu KK, Kundi I et al. 2008. Liver fatty acid-binding protein as a biomarker of acute kidney injury after cardiac surgery. Kidney Int 73:465–72
    [Google Scholar]
  40. 40.
    Parikh CR, Thiessen-Philbrook H, Garg AX, Kadiyala D, Shlipak MG et al. 2013. Performance of kidney injury molecule-1 and liver fatty acid-binding protein and combined biomarkers of AKI after cardiac surgery. Clin. J. Am. Soc. Nephrol. 8:1079–88
    [Google Scholar]
  41. 41.
    Nakamura T, Sugaya T, Koide H 2009. Urinary liver-type fatty acid-binding protein in septic shock: effect of polymyxin B-immobilized fiber hemoperfusion. Shock 31:454–59
    [Google Scholar]
  42. 42.
    Kamijo A, Sugaya T, Hikawa A, Yamanouchi M, Hirata Y et al. 2006. Urinary liver-type fatty acid binding protein as a useful biomarker in chronic kidney disease. Mol. Cell. Biochem. 284:175–82
    [Google Scholar]
  43. 43.
    Devuyst O, Olinger E, Rampoldi L 2017. Uromodulin: from physiology to rare and complex kidney disorders. Nat. Rev. Nephrol. 13:525
    [Google Scholar]
  44. 44.
    Steubl D, Block M, Herbst V, Nockher WA, Schlumberger W et al. 2016. Plasma uromodulin correlates with kidney function and identifies early stages in chronic kidney disease patients. Medicine 95:e3011
    [Google Scholar]
  45. 45.
    Edelstein CL, Hoke TS, Somerset H, Fang W, Klein CL et al. 2007. Proximal tubules from caspase-1-deficient mice are protected against hypoxia-induced membrane injury. Nephrol. Dial. Transpl. 22:1052–61
    [Google Scholar]
  46. 46.
    Melnikov VY, Ecder T, Fantuzzi G, Siegmund B, Lucia MS et al. 2001. Impaired IL-18 processing protects caspase-1-deficient mice from ischemic acute renal failure. J. Clin. Investig. 107:1145–52
    [Google Scholar]
  47. 47.
    Wu H, Craft ML, Wang P, Wyburn KR, Chen G et al. 2008. IL-18 contributes to renal damage after ischemia-reperfusion. J. Am. Soc. Nephrol. 19:2331–41
    [Google Scholar]
  48. 48.
    Rovin BH, Yoshiumura T, Tan L 1992. Cytokine-induced production of monocyte chemoattractant protein-1 by cultured human mesangial cells. J. Immunol. 148:2148–53
    [Google Scholar]
  49. 49.
    Boring L, Gosling J, Chensue SW, Kunkel SL, Farese RV et al. 1997. Impaired monocyte migration and reduced type 1 (Th1) cytokine responses in C-C chemokine receptor 2 knockout mice. J. Clin. Investig. 100:2552–61
    [Google Scholar]
  50. 50.
    Leonard EJ, Yoshimura T 1990. Human monocyte chemoattractant protein-1 (MCP-1). Immunol. Today 11:97–101
    [Google Scholar]
  51. 51.
    Yoshimura T, Leonard EJ 1990. Secretion by human fibroblasts of monocyte chemoattractant protein-1, the product of gene JE. J. Immunol. 144:2377–83
    [Google Scholar]
  52. 52.
    Yoshimura T, Robinson EA, Tanaka S, Appella E, Leonard EJ 1989. Purification and amino acid analysis of two human monocyte chemoattractants produced by phytohemagglutinin-stimulated human blood mononuclear leukocytes. J. Immunol. 142:1956–62
    [Google Scholar]
  53. 53.
    Cushing SD, Berliner JA, Valente AJ, Territo MC, Navab M et al. 1990. Minimally modified low density lipoprotein induces monocyte chemotactic protein 1 in human endothelial cells and smooth muscle cells. PNAS 87:5134–38
    [Google Scholar]
  54. 54.
    Elner SG, Strieter RM, Elner VM, Rollins BJ, Del Monte MA, Kunkel SL 1991. Monocyte chemotactic protein gene expression by cytokine-treated human retinal pigment epithelial cells. Lab. Investig. 64:819–25
    [Google Scholar]
  55. 55.
    Wada T, Yokoyama H, Su SB, Mukaida N, Iwano M et al. 1996. Monitoring urinary levels of monocyte chemotactic and activating factor reflects disease activity of lupus nephritis. Kidney Int 49:761–67
    [Google Scholar]
  56. 56.
    Noris M, Bernasconi S, Casiraghi F, Sozzani S, Gotti E et al. 1995. Monocyte chemoattractant protein-1 is excreted in excessive amounts in the urine of patients with lupus nephritis. Lab. Investig. 73:804–9
    [Google Scholar]
  57. 57.
    Kiyici S, Erturk E, Budak F, Ersoy C, Tuncel E et al. 2006. Serum monocyte chemoattractant protein-1 and monocyte adhesion molecules in type 1 diabetic patients with nephropathy. Arch. Med. Res. 37:998–1003
    [Google Scholar]
  58. 58.
    Bae E, Cha R-H, Kim YC, An JN, Kim DK et al. 2017. Circulating TNF receptors predict cardiovascular disease in patients with chronic kidney disease. Medicine 96:e6666
    [Google Scholar]
  59. 59.
    Gohda T, Niewczas MA, Ficociello LH, Walker WH, Skupien J et al. 2012. Circulating TNF receptors 1 and 2 predict stage 3 CKD in type 1 diabetes. J. Am. Soc. Nephrol. 23:516–24
    [Google Scholar]
  60. 60.
    Niewczas MA, Gohda T, Skupien J, Smiles AM, Walker WH et al. 2012. Circulating TNF receptors 1 and 2 predict ESRD in type 2 diabetes. J. Am. Soc. Nephrol. 23:507–15
    [Google Scholar]
  61. 61.
    Hasegawa G, Nakano K, Sawada M, Uno K, Shibayama Y et al. 1991. Possible role of tumor necrosis factor and interleukin-1 in the development of diabetic nephropathy. Kidney Int 40:1007–12
    [Google Scholar]
  62. 62.
    Huang Y-S, Fu S-H, Lu K-C, Chen J-S, Hsieh H-Y et al. 2017. Inhibition of tumor necrosis factor signaling attenuates renal immune cell infiltration in experimental membranous nephropathy. Oncotarget 8:111631–41
    [Google Scholar]
  63. 63.
    Fernández‐Juárez G, Perez JV, Fernández JLL, Martinez‐Martinez E, Cachofeiro V et al. 2017. High levels of circulating TNFR1 increase the risk of all‐cause mortality and progression of renal disease in type 2 diabetic nephropathy. Nephrology 22:354–60
    [Google Scholar]
  64. 64.
    Neirynck N, Glorieux G, Schepers E, Verbeke F, Vanholder R 2015. Soluble tumor necrosis factor receptor 1 and 2 predict outcomes in advanced chronic kidney disease: a prospective cohort study. PLOS ONE 10:e0122073
    [Google Scholar]
  65. 65.
    Lee CG, Da Silva CA, Dela Cruz CS, Ahangari F, Ma B et al. 2011. Role of chitin and chitinase/chitinase-like proteins in inflammation, tissue remodeling, and injury. Annu. Rev. Physiol. 73:479–501
    [Google Scholar]
  66. 66.
    Sohn MH, Kang M-J, Matsuura H, Bhandari V, Chen N-Y et al. 2010. The chitinase-like proteins breast regression protein-39 and YKL-40 regulate hyperoxia-induced acute lung injury. Am. J. Respir. Crit. Care Med. 182:918–28
    [Google Scholar]
  67. 67.
    Schmidt IM, Hall IE, Kale S, Lee S, He C-H et al. 2013. Chitinase-like protein Brp-39/YKL-40 modulates the renal response to ischemic injury and predicts delayed allograft function. J. Am. Soc. Nephrol. 24:309–19
    [Google Scholar]
  68. 68.
    Ghoul BE, Squalli T, Servais A, Elie C, Meas-Yedid V et al. 2010. Urinary procollagen III aminoterminal propeptide (PIIINP): a fibrotest for the nephrologist. Clin. J. Am. Soc. Nephrol. 5:205–10
    [Google Scholar]
  69. 69.
    Torres DD, Rossini M, Manno C, Mattace-Raso F, D'Altri C et al. 2008. The ratio of epidermal growth factor to monocyte chemotactic peptide-1 in the urine predicts renal prognosis in IgA nephropathy. Kidney Int 73:327–33
    [Google Scholar]
  70. 70.
    Grandaliano G, Gesualdo L, Bartoli F, Ranieri E, Monno R et al. 2000. MCP-1 and EGF renal expression and urine excretion in human congenital obstructive nephropathy. Kidney Int 58:182–92
    [Google Scholar]
  71. 71.
    Ju W, Nair V, Smith S, Zhu L, Shedden K et al. 2015. Tissue transcriptome-driven identification of epidermal growth factor as a chronic kidney disease biomarker. Sci. Transl. Med. 7:316ra193
    [Google Scholar]
  72. 72.
    Mattila A-L, Viinikka L, Saario I, Perheentupa J 1988. Human epidermal growth factor: renal production and absence from plasma. Regul. Pept. 23:89–93
    [Google Scholar]
  73. 73.
    Lechner J, Malloth NA, Jennings P, Heckl D, Pfaller W, Seppi T 2007. Opposing roles of EGF in IFN-α-induced epithelial barrier destabilization and tissue repair. Am. J. Physiol. Cell Physiol. 293:C1843–50
    [Google Scholar]
  74. 74.
    Tang J, Liu N, Zhuang S 2013. Role of epidermal growth factor receptor in acute and chronic kidney injury. Kidney Int 83:804–10
    [Google Scholar]
  75. 75.
    Mathiesen ER, Nexø E, Hommel E, Parving HH 1989. Reduced urinary excretion of epidermal growth factor in incipient and overt diabetic nephropathy. Diabetic Med 6:121–26
    [Google Scholar]
  76. 76.
    Ranieri E, Gesualdo L, Petrarulo F, Schena FP 1996. Urinary IL-6/EGF ratio: a useful prognostic marker for the progression of renal damage in IgA nephropathy. Kidney Int 50:1990–2001
    [Google Scholar]
  77. 77.
    Weinstein T, Hwang D, Lev-Ran A, Ori Y, Korzets A, Levi J 1997. Excretion of epidermal growth factor in human adult polycystic kidney disease. Israel J. Med. Sci. 33:641–42
    [Google Scholar]
  78. 78.
    Tsau YK, Chen CH 1999. Urinary epidermal growth factor excretion in children with chronic renal failure. Am. J. Nephrol. 19:400–4
    [Google Scholar]
  79. 79.
    Supavekin S, Zhang W, Kucherlapati R, Kaskel FJ, Moore LC, Devarajan P 2003. Differential gene expression following early renal ischemia/reperfusion. Kidney Int 63:1714–24
    [Google Scholar]
  80. 80.
    Villanueva S, Céspedes C, Vio CP 2006. Ischemic acute renal failure induces the expression of a wide range of nephrogenic proteins. Am. J. Physiol. Regul. Integr. Comp. Physiol. 290:R861–70
    [Google Scholar]
  81. 81.
    Bonventre JV, Yang L 2011. Cellular pathophysiology of ischemic acute kidney injury. J. Clin. Investig. 121:4210–21
    [Google Scholar]
  82. 82.
    Koyner JL, Parikh CR 2013. Clinical utility of biomarkers of AKI in cardiac surgery and critical illness. Clin. J. Am. Soc. Nephrol. 8:1034–42
    [Google Scholar]
  83. 83.
    Parikh CR, Coca SG, Thiessen-Philbrook H, Shlipak MG, Koyner JL et al. 2011. Postoperative biomarkers predict acute kidney injury and poor outcomes after adult cardiac surgery. J. Am. Soc. Nephrol. 22:1748–57
    [Google Scholar]
  84. 84.
    Parikh CR, Devarajan P, Zappitelli M, Sint K, Thiessen-Philbrook H et al. 2011. Postoperative biomarkers predict acute kidney injury and poor outcomes after pediatric cardiac surgery. J. Am. Soc. Nephrol. 22:1737–47
    [Google Scholar]
  85. 85.
    Basile DP, Donohoe D, Roethe K, Osborn JL 2001. Renal ischemic injury results in permanent damage to peritubular capillaries and influences long-term function. Am. J. Physiol. Ren. Physiol. 281:F887–99
    [Google Scholar]
  86. 86.
    Basile DP, Fredrich K, Alausa M, Vio CP, Liang M et al. 2005. Identification of persistently altered gene expression in the kidney after functional recovery from ischemic acute renal failure. Am. J. Physiol. Ren. Physiol. 288:F953–63
    [Google Scholar]
  87. 87.
    Koyner JL, Garg AX, Coca SG, Sint K, Thiessen-Philbrook H et al. 2012. Biomarkers predict progression of acute kidney injury after cardiac surgery. J. Am. Soc. Nephrol. 23:905–14
    [Google Scholar]
  88. 88.
    Coca SG, Nadkarni GN, Garg AX, Koyner J, Thiessen-Philbrook H et al. 2016. First post-operative urinary kidney injury biomarkers and association with the duration of AKI in the TRIBE-AKI cohort. PLOS ONE 11:e0161098
    [Google Scholar]
  89. 89.
    Coca SG, Garg AX, Thiessen-Philbrook H, Koyner JL, Patel UD et al. 2014. Urinary biomarkers of AKI and mortality 3 years after cardiac surgery. J. Am. Soc. Nephrol. 25:1063–71
    [Google Scholar]
  90. 90.
    Thygesen K, Alpert JS, White HD 2007. Universal definition of myocardial infarction. Circulation 116:2634–53
    [Google Scholar]
  91. 91.
    Jotwani V, Katz R, Ix JH, Gutiérrez OM, Bennett M et al. 2018. Urinary biomarkers of kidney tubular damage and risk of cardiovascular disease and mortality in elders. Am. J. Kidney Dis. 72:205–13
    [Google Scholar]
  92. 92.
    Weinfeld MS, Chertow GM, Stevenson LW 1999. Aggravated renal dysfunction during intensive therapy for advanced chronic heart failure. Am. Heart J. 138:285–90
    [Google Scholar]
  93. 93.
    Knight EL, Glynn RJ, McIntyre KM, Mogun H, Avorn J 1999. Predictors of decreased renal function in patients with heart failure during angiotensin-converting enzyme inhibitor therapy: results from the Studies of Left Ventricular Dysfunction (SOLVD). Am. Heart J. 138:849–55
    [Google Scholar]
  94. 94.
    Krumholz HM, Chen Y-T, Vaccarino V, Wang Y, Radford MJ et al. 2000. Correlates and impact on outcomes of worsening renal function in patients ≥65 years of age with heart failure. Am. J. Cardiol. 85:1110–13
    [Google Scholar]
  95. 95.
    Smith GL, Vaccarino V, Kosiborod M, Lichtman JH, Cheng S et al. 2003. Worsening renal function: What is a clinically meaningful change in creatinine during hospitalization with heart failure?. J. Card. Failure 9:13–25
    [Google Scholar]
  96. 96.
    Testani JM, Brisco-Bacik MA 2017. Worsening renal function and mortality in heart failure. Causality confounding?. Circ. Heart Failure 10:e003835
    [Google Scholar]
  97. 97.
    Dupont M, Shrestha K, Singh D, Awad A, Kovach C et al. 2012. Lack of significant renal tubular injury despite acute kidney injury in acute decompensated heart failure. Eur. J. Heart Failure 14:597–604
    [Google Scholar]
  98. 98.
    Ahmad T, Jackson K, Rao VS, Tang WHW, Brisco-Bacik MA et al. 2018. Worsening renal function in acute heart failure patients undergoing aggressive diuresis is not associated with tubular injury. Circulation 137:2016–28
    [Google Scholar]
  99. 99.
    Velez JCQ, Kadian M, Taburyanskaya M, Bohm NM, Delay TA et al. 2015. Hepatorenal acute kidney injury and the importance of raising mean arterial pressure. Nephron 131:191–201
    [Google Scholar]
  100. 100.
    Dobre M, Demirjian S, Sehgal AR, Navaneethan SD 2011. Terlipressin in hepatorenal syndrome: a systematic review and meta-analysis. Int. Urol. Nephrol. 43:175–84
    [Google Scholar]
  101. 101.
    Junior APN, Farias AQ, d'Albuquerque LAC, Carrilho FJ, Malbouisson LMS 2014. Terlipressin versus norepinephrine in the treatment of hepatorenal syndrome: a systematic review and meta-analysis. PLOS ONE 9:e107466
    [Google Scholar]
  102. 102.
    Nadim MK, Genyk YS, Tokin C, Fieber J, Ananthapanyasut W et al. 2012. Impact of the etiology of acute kidney injury on outcomes following liver transplantation: acute tubular necrosis versus hepatorenal syndrome. Liver Transplant 18:539–48
    [Google Scholar]
  103. 103.
    Belcher JM, Sanyal AJ, Peixoto AJ, Perazella MA, Lim J et al. 2014. Kidney biomarkers and differential diagnosis of patients with cirrhosis and acute kidney injury. Hepatology 60:622–32
    [Google Scholar]
  104. 104.
    Fagundes C, Pépin M-N, Guevara M, Barreto R, Casals G et al. Urinary neutrophil gelatinase-associated lipocalin as biomarker in the differential diagnosis of impairment of kidney function in cirrhosis. J. Hepatol. 57:267–73
    [Google Scholar]
  105. 105.
    Belcher JM, Sanyal AJ, Peixoto AJ, Perazella MA, Lim J et al. 2014. Kidney biomarkers and differential diagnosis of patients with cirrhosis and acute kidney injury. Hepatology 60:622–32
    [Google Scholar]
  106. 106.
    Chu R, Li C, Wang S, Zou W, Liu G, Yang L 2014. Assessment of KDIGO definitions in patients with histopathologic evidence of acute renal disease. Clin. J. Am. Soc. Nephrol. 9:1175–82
    [Google Scholar]
  107. 107.
    Reese PP, Hall IE, Weng FL, Schröppel B, Doshi MD et al. 2015. Associations between deceased-donor urine injury biomarkers and kidney transplant outcomes. J. Am. Soc. Nephrol. 27:1534–43
    [Google Scholar]
  108. 108.
    Joo JD, Kim M, D'Agati VD, Lee HT 2006. Ischemic preconditioning provides both acute and delayed protection against renal ischemia and reperfusion injury in mice. J. Am. Soc. Nephrol. 17:3115–23
    [Google Scholar]
  109. 109.
    Puthumana J, Hall IE, Reese PP, Schröppel B, Weng FL et al. 2017. YKL-40 associates with renal recovery in deceased donor kidney transplantation. J. Am. Soc. Nephrol. 28:661–70
    [Google Scholar]
  110. 110.
    Peralta CA, Katz R, Bonventre JV, Sabbisetti V, Siscovick D et al. 2012. Associations of urinary levels of kidney injury molecule 1 (KIM-1) and neutrophil gelatinase-associated lipocalin (NGAL) with kidney function decline in the Multi-Ethnic Study of Atherosclerosis (MESA). Am. J. Kidney Dis. 60:904–11
    [Google Scholar]
  111. 111.
    Jungbauer CG, Uecer E, Stadler S, Birner C, Buchner S et al. 2016. N-acteyl-β-D-glucosaminidase and kidney injury molecule-1: new predictors for long-term progression of chronic kidney disease in patients with heart failure. Nephrology 21:490–98
    [Google Scholar]
  112. 112.
    Hsu C, Xie D, Waikar SS, Bonventre JV, Zhang X et al. 2017. Urine biomarkers of tubular injury do not improve on the clinical model predicting chronic kidney disease progression. Kidney Int 91:196–203
    [Google Scholar]
  113. 113.
    Foster MC, Coresh J, Bonventre JV, Sabbisetti VS, Waikar SS et al. 2015. Urinary biomarkers and risk of ESRD in the atherosclerosis risk in communities study. Clin. J. Am. Soc. Nephrol. 10:1956–63
    [Google Scholar]
  114. 114.
    Lin Hugo Y-H, Hwang D-Y, Lee Su C, Kuo H-T, Kuo M-C et al. 2015. Urinary neutrophil gelatinase-associated lipocalin and clinical outcomes in chronic kidney disease patients. Clin. Chem. Lab. Med. 53:73–83
    [Google Scholar]
  115. 115.
    Fufaa GD, Weil EJ, Nelson RG, Hanson RL, Bonventre JV et al. 2015. Association of urinary KIM-1, L-FABP, NAG and NGAL with incident end-stage renal disease and mortality in American Indians with type 2 diabetes mellitus. Diabetologia 58:188–98
    [Google Scholar]
  116. 116.
    Navarro-González JF, Mora-Fernández C 2008. The role of inflammatory cytokines in diabetic nephropathy. J. Am. Soc. Nephrol. 19:433–42
    [Google Scholar]
  117. 117.
    Mora C, Navarro JF 2006. Inflammation and diabetic nephropathy. Curr. Diabetes Rep. 6:463–68
    [Google Scholar]
  118. 118.
    Coca SG, Nadkarni GN, Huang Y, Moledina DG, Rao V et al. 2017. Plasma biomarkers and kidney function decline in early and established diabetic kidney disease. J. Am. Soc. Nephrol. 28:2786–93
    [Google Scholar]
  119. 119.
    Conway BR, Manoharan D, Manoharan D, Jenks S, Dear JW et al. 2012. Measuring urinary tubular biomarkers in type 2 diabetes does not add prognostic value beyond established risk factors. Kidney Int 82:812–18
    [Google Scholar]
  120. 120.
    Vaidya VS, Niewczas MA, Ficociello LH, Johnson AC, Collings FB et al. 2011. Regression of micro-albuminuria in type 1 diabetes is associated with lower levels of urinary tubular injury biomarkers, kidney injury molecule-1, and N-acetyl-β-d-glucosaminidase. Kidney Int 79:464–70
    [Google Scholar]
  121. 121.
    Al-Lamki RS, Mayadas TN 2015. TNF receptors: signaling pathways and contribution to renal dysfunction. Kidney Int 87:281–96
    [Google Scholar]
  122. 122.
    Ledo N, Ko Y-A, Park A-SD, Kang H-M, Han S-Y et al. 2015. Functional genomic annotation of genetic risk loci highlights inflammation and epithelial biology networks in CKD. J. Am. Soc. Nephrol. 26:692–714
    [Google Scholar]
  123. 123.
    Pavkov ME, Nelson RG, Knowler WC, Cheng Y, Krolewski AS, Niewczas MA 2015. Elevation of circulating TNF receptors 1 and 2 increases the risk of end-stage renal disease in American Indians with type 2 diabetes. Kidney Int 87:812–19
    [Google Scholar]
  124. 124.
    Krolewski AS, Niewczas MA, Skupien J, Gohda T, Smiles A et al. 2014. Early progressive renal decline precedes the onset of microalbuminuria and its progression to macroalbuminuria. Diabetes Care 37:226–34
    [Google Scholar]
  125. 125.
    Al-Lamki RS, Wang J, Vandenabeele P, Bradley JA, Thiru S et al. 2005. TNFR1- and TNFR2-mediated signaling pathways in human kidney are cell type-specific and differentially contribute to renal injury. FASEB J 19:1637–45
    [Google Scholar]
  126. 126.
    Banba N, Nakamura T, Matsumura M, Kuroda H, Hattori Y, Kasai K 2000. Possible relationship of monocyte chemoattractant protein-1 with diabetic nephropathy. Kidney Int 58:684–90
    [Google Scholar]
  127. 127.
    Chow FY, Nikolic-Paterson DJ, Ozols E, Atkins RC, Rollin BJ, Tesch GH 2006. Monocyte chemoattractant protein-1 promotes the development of diabetic renal injury in streptozotocin-treated mice. Kidney Int 69:73–80
    [Google Scholar]
  128. 128.
    Morii T, Fujita H, Narita T, Shimotomai T, Fujishima H et al. 2003. Association of monocyte chemoattractant protein-1 with renal tubular damage in diabetic nephropathy. J. Diabetes Complic. 17:11–15
    [Google Scholar]
  129. 129.
    Takebayashi K, Matsumoto S, Aso Y, Inukai T 2006. Aldosterone blockade attenuates urinary monocyte chemoattractant protein-1 and oxidative stress in patients with type 2 diabetes complicated by diabetic nephropathy. J. Clin. Endocrinol. Metab. 91:2214–17
    [Google Scholar]
  130. 130.
    Tam FWK, Riser BL, Meeran K, Rambow J, Pusey CD, Frankel AH 2009. Urinary monocyte chemoattractant protein-1 (MCP-1) and connective tissue growth factor (CCN2) as prognostic markers for progression of diabetic nephropathy. Cytokine 47:37–42
    [Google Scholar]
  131. 131.
    Canaud G, Dejucq-Rainsford N, Avettand-Fenoel V, Viard JP, Anglicheau D et al. 2014. The kidney as a reservoir for HIV-1 after renal transplantation. J. Am. Soc. Nephrol. 25:407–19
    [Google Scholar]
  132. 132.
    Jotwani V, Scherzer R, Abraham A, Estrella MM, Bennett M et al. 2015. Association of urine α1-microglobulin with kidney function decline and mortality in HIV-infected women. Clin. J. Am. Soc. Nephrol. 10:63–73
    [Google Scholar]
  133. 133.
    Shlipak MG, Scherzer R, Abraham A, Tien PC, Grunfeld C et al. 2012. Urinary markers of kidney injury and kidney function decline in HIV-infected women. J. Acquir. Immune Defic. Syndr. 61:565–73
    [Google Scholar]
  134. 134.
    Jotwani V, Scherzer R, Abraham A, Estrella MM, Bennett M et al. 2013. Does HIV infection promote early kidney injury in women?. Antivir. Ther. 19:79–87
    [Google Scholar]
  135. 135.
    Jotwani V, Scherzer R, Estrella MM, Jacobson LP, Witt MD et al. 2017. Association of HIV infection with biomarkers of kidney injury and fibrosis in the Multicenter AIDS Cohort Study. Antivir. Ther. 22:421–29
    [Google Scholar]
  136. 136.
    Kohler JJ, Hosseini SH, Hoying-Brandt A, Green E, Johnson DM et al. 2009. Tenofovir renal toxicity targets mitochondria of renal proximal tubules. Lab. Investig. 89:513–19
    [Google Scholar]
  137. 137.
    Herlitz LC, Mohan S, Stokes MB, Radhakrishnan J, D'Agati VD, Markowitz GS 2010. Tenofovir nephrotoxicity: acute tubular necrosis with distinctive clinical, pathological, and mitochondrial abnormalities. Kidney Int 78:1171–77
    [Google Scholar]
  138. 138.
    Jotwani V, Scherzer R, Estrella MM, Jacobson LP, Witt MD et al. 2016. Brief report: cumulative tenofovir disoproxil fumarate exposure is associated with biomarkers of tubular injury and fibrosis in HIV-infected men. JAIDS J. Acquir. Immune Defic. Syndr. 73:177–81
    [Google Scholar]
  139. 139.
    Jotwani V, Scherzer R, Estrella MM, Jacobson LP, Witt MD et al. 2016. HIV infection, tenofovir, and urine α1-microglobulin: a cross-sectional analysis in the multicenter AIDS cohort study. Am. J. Kidney Dis. 68:571–81
    [Google Scholar]
  140. 140.
    Parikh CR, Moledina DG, Coca SG, Thiessen-Philbrook HR, Garg AX 2016. Application of new acute kidney injury biomarkers in human randomized controlled trials. Kidney Int 89:1372–79
    [Google Scholar]
  141. 141.
    Molnar AO, Parikh CR, Coca SG, Thiessen-Philbrook H, Koyner JL et al. 2014. Association between preoperative statin use and acute kidney injury biomarkers in cardiac surgery. Ann. Thoracic Surg. 97:2081–87
    [Google Scholar]
  142. 142.
    Goodsaid F, Frueh F 2007. Biomarker qualification pilot process at the US Food and Drug Administration. AAPS J 9:E105–8
    [Google Scholar]
  143. 143.
    Sistare FD, Dieterle F, Troth S, Holder DJ, Gerhold D et al. 2010. Towards consensus practices to qualify safety biomarkers for use in early drug development. Nat. Biotechnol. 28:446–54
    [Google Scholar]
  144. 144.
    Dieterle F, Sistare F, Goodsaid F, Papaluca M, Ozer JS et al. 2010. Renal biomarker qualification submission: a dialog between the FDA-EMEA and Predictive Safety Testing Consortium. Nat. Biotechnol. 28:455–62
    [Google Scholar]
  145. 145.
    Kimura T, Yasuda K, Yamamoto R, Soga T, Rakugi H et al. 2016. Identification of biomarkers for development of end-stage kidney disease in chronic kidney disease by metabolomic profiling. Sci. Rep. 6:26138
    [Google Scholar]
  146. 146.
    Hocher B, Adamski J 2017. Metabolomics for clinical use and research in chronic kidney disease. Nat. Rev. Nephrol. 13:269–84
    [Google Scholar]
  147. 147.
    Kidney Precis. Med. Proj. 2018. Kidney Precision Medicine Project Natl. Inst. Diabetes Dig. Kidney Dis Bethesda, MD: https://www.niddk.nih.gov/research-funding/research-programs/kidney-precision-medicine-project-kpmp
    [Google Scholar]
  148. 148.
    Arthur JM, Hill EG, Alge JL, Lewis EC, Neely BA et al. 2014. Evaluation of 32 urine biomarkers to predict the progression of acute kidney injury after cardiac surgery. Kidney Int 85:431–38
    [Google Scholar]
  149. 149.
    McIlroy DR, Farkas D, Pan K, Pickering JW, Lee HT 2018. Combining novel renal injury markers with delta serum creatinine early after cardiac surgery and risk-stratification for serious adverse outcomes: an exploratory analysis. J. Cardiothorac. Vasc. Anesth. 32:2190–200
    [Google Scholar]
  150. 150.
    Basu RK, Wong HR, Krawczeski CD, Wheeler DS, Manning PB et al. 2014. Combining functional and tubular damage biomarkers improves diagnostic precision for acute kidney injury after cardiac surgery. J. Am. Coll. Cardiol. 64:2753–62
    [Google Scholar]
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