Multicenter validation of urinary CXCL9 as a risk-stratifying biomarker for kidney transplant injury

American Journal of Transplantation

Volumn 13, Issue 10, 2013, Pages 2634-2644

  Hricik, D E ^a   Nickerson, P ^b   Formica, R N ^c   Poggio, E D ^d   Rush, D ^b   Newell, K A ^e   Goebel, J ^f   Gibson, I W ^b   Fairchild, R L ^d   Riggs, M ^g   Spain, K ^g   Ikle, D ^g   Bridges, N D ^h   Heeger, P S ⁱ  

^a UNIVERSITY HOSPITALS OF CLEVELAND   (United States)

^b UNIVERSITY OF MANITOBA   (Canada)

^c YALE UNIVERSITY SCHOOL OF MEDICINE   (United States)

^d LERNER RESEARCH INSTITUTE   (United States)

^e EMORY UNIVERSITY SCHOOL OF MEDICINE   (United States)

^f CINCINNATI CHILDREN'S HOSPITAL MEDICAL CENTER   (United States)

^g Rho   (United States)

^h NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES   (United States)

ⁱ MOUNT SINAI SCHOOL OF MEDICINE   (United States)

Author keywords

Acute rejection; biomarker; chemokines; kidney allograft; kidney graft function

Indexed keywords

BIOLOGICAL MARKER; CXCL9 CHEMOKINE; MESSENGER RNA;

ACUTE GRAFT REJECTION; ADULT; ALLOGRAFT; ARTICLE; CLINICAL DECISION MAKING; FEMALE; GLOMERULUS FILTRATION RATE; HUMAN; HUMAN TISSUE; IMMUNE INJURY; KIDNEY DYSFUNCTION; KIDNEY GRAFT; KIDNEY INJURY; MAJOR CLINICAL STUDY; MALE; MULTICENTER STUDY; OBSERVATIONAL STUDY; PREDICTIVE VALUE; PRIORITY JOURNAL; PROSPECTIVE STUDY; VALIDATION STUDY;

ACUTE REJECTION; BIOMARKER; CHEMOKINES; KIDNEY ALLOGRAFT; KIDNEY GRAFT FUNCTION;

ACUTE KIDNEY INJURY; ADULT; BIOLOGICAL MARKERS; CHEMOKINE CXCL9; ENZYME-LINKED IMMUNOSORBENT ASSAY; FEMALE; FLOW CYTOMETRY; FOLLOW-UP STUDIES; GLOMERULAR FILTRATION RATE; GRAFT REJECTION; HUMANS; KIDNEY FUNCTION TESTS; KIDNEY TRANSPLANTATION; MALE; PROGNOSIS; PROSPECTIVE STUDIES; RISK FACTORS;

EID: 84884907939     PISSN: 16006135     EISSN: 16006143     Source Type: Journal    
DOI: 10.1111/ajt.12426     Document Type: Article

References (30)

1. Hauser IA, Spiegler S, Kiss E, et al. Prediction of acute renal allograft rejection by urinary monokine induced by IFN-gamma (MIG). J Am Soc Nephrol 2005; 16: 1849-1858.
2. Ho J, Wiebe C, Gibson IW, Rush DN, Nickerson PW., Immune monitoring of kidney allografts. Am J Kidney Dis 2012; 60: 629-640.
3. Hu H, Aizenstein BD, Puchalski A, Burmania JA, Hamawy MM, Knechtle SJ., Elevation of CXCR3-binding chemokines in urine indicates acute renal-allograft dysfunction. Am J Transplant 2004; 4: 432-437.
4. Lazzeri E, Rotondi M, Mazzinghi B, et al. High CXCL10 expression in rejected kidneys and predictive role of pretransplant serum CXCL10 for acute rejection and chronic allograft nephropathy. Transplantation 2005; 79: 1215-1220.
5. Li B, Hartono C, Ding R, et al. Noninvasive diagnosis of renal-allograft rejection by measurement of messenger RNA for perforin and granzyme B in urine. N Engl J Med 2001; 344: 947-954.
6. Matz M, Beyer J, Wunsch D, et al. Early post-transplant urinary IP-10 expression after kidney transplantation is predictive of short- and long-term graft function. Kidney Int 2006; 69: 1683-1690.
7. Panzer U, Reinking RR, Steinmetz OM, et al. CXCR3 and CCR5 positive T-cell recruitment in acute human renal allograft rejection. Transplantation 2004; 78: 1341-1350.
8. Qin S, Rottman JB, Myers P, et al. The chemokine receptors CXCR3 and CCR5 mark subsets of T cells associated with certain inflammatory reactions. J Clin Invest 1998; 101: 746-754.
9. Schaub S, Nickerson P, Rush D, et al. Urinary CXCL9 and CXCL10 levels correlate with the extent of subclinical tubulitis. Am J Transplant 2009; 9: 1347-1353.
10. Schaub S, Rush D, Wilkins J, et al. Proteomic-based detection of urine proteins associated with acute renal allograft rejection. J Am Soc Nephrol 2004; 15: 219-227.
11. Schaub S, Wilkins JA, Antonovici M, et al. Proteomic-based identification of cleaved urinary beta2-microglobulin as a potential marker for acute tubular injury in renal allografts. Am J Transplant 2005; 5: 729-738.
12. Tatapudi RR, Muthukumar T, Dadhania D, et al. Noninvasive detection of renal allograft inflammation by measurements of mRNA for IP-10 and CXCR3 in urine. Kidney Int 2004; 65: 2390-2397.
13. Wang T, Dai H, Wan N, Moore Y, Dai Z., The role for monocyte chemoattractant protein-1 in the generation and function of memory CD8+ T cells. J Immunol 2008; 180: 2886-2893.
14. Hirt-Minkowski P, Amico P, Ho J, et al. Detection of clinical and subclinical tubulo-interstitial inflammation by the urinary CXCL10 chemokine in a real-life setting. Am J Transplant 2012; 12: 1811-1823.
15. Ho J, Rush DN, Karpinski M, et al. Validation of urinary CXCL10 as a marker of borderline, subclinical, and clinical tubulitis. Transplantation 2011; 92: 878-882.
16. Solez K, Colvin RB, Racusen LC, et al. Banff 07 classification of renal allograft pathology: Updates and future directions. Am J Transplant 2008; 8: 753-760.
17. Mengel M, Sis B, Haas M, et al. Banff 2011 Meeting Report: New concepts in antibody-mediated rejection. Am J Transplant 2012; 12: 563-570.
18. Muthukumar T, Dadhania D, Ding R, et al. Messenger RNA for FOXP3 in the urine of renal-allograft recipients. N Engl J Med 2005; 353: 2342-2351.
19. Kawai T, Cosimi AB, Spitzer TR, et al. HLA-mismatched renal transplantation without maintenance immunosuppression. N Engl J Med 2008; 358: 353-361.
20. Ho J, Lucy M, Krokhin O, et al. Mass spectrometry-based proteomic analysis of urine in acute kidney injury following cardiopulmonary bypass: A nested case-control study. Am J Kidney Dis 2009; 53: 584-595.
21. Levey AS, Coresh J, Greene T, et al. Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Ann Intern Med 2006; 145: 247-254.
22. Schwartz GJ, Munoz A, Schneider MF, et al. New equations to estimate GFR in children with CKD. J Am Soc Nephrol 2009; 20: 629-637.
23. Harrell FE Jr., Lee KL, Mark DB., Multivariable prognostic models: Issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med 1996; 15: 361-387.
24. Austin PC, Tu JV., Bootstrap methods for developing predictive models. Am Statistician 2004; 58: 131-137.
25. Cox DR., Two further applications of a model for binary regression. Biometrika 1958; 45: 562-565.
26. Steyerberg EW., Clinical prediction models. A practical approach to development, validation, and updating. New York: Springer, 2009.
27. Steyerberg EW, Vickers AJ, Cook NR, et al. Assessing the performance of prediction models: A framework for traditional and novel measures. Epidemiology 2010; 21: 128-138.
28. Tripepi G, Jager KJ, Dekker FW, Zoccali C., Statistical methods for the assessment of prognostic biomarkers (part II): Calibration and re-classification. Nephrol Dial Transplant 2010; 25: 1402-1405.
29. Efron B, Tibshirani RJ., An introduction to the bootstrap. Monographs on statistics and applied probability. New York: Chapman and Hall/CRC Press, LLC, 1993.
30. Jackson JA, Kim EJ, Begley B, et al. Urinary chemokines CXCL9 and CXCL10 are noninvasive markers of renal allograft rejection and BK viral infection. Am J Transplant 2011; 11: 2228-2234.