A78: Urine Biomarkers Role in Predicting the Future Development of Renal Functional Loss With Lupus...
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ARTHRITIS & RHEUMATOLOGY Vol. 66, No. S3, March 2014, p S111 DOI 10.1002/art.38494 © 2014, American College of Rheumatology A78: Urine Biomarkers Role in Predicting the Future Development of Renal Functional Loss With Lupus Nephritis in Children and Adults Khalid Abulaban, 1 Hermine Brunner, 2 Shannen L. Nelson, 1 Michael Bennett, 1 Jun Ying, 3 Huijuan Song, 4 Paul Kimmel, 5 John Kusek, 5 Harold Feldman, 6 Vasan Ramachandran, 7 and Brad H. Rovin 4 Background/Purpose: Lupus nephritis (LN) is frequently associated with a poor long-term prognosis. Current non-invasive blood and urine tests do not reliably predict the course of LN. The objective of this study was to evaluate the performance of candidate urine biomarkers in predicting future kidney function in adults and children with LN. The biomarker candidates studies were liver-type fatty acid binding protein (L-FABP), albumin (Alb), monocyte chemoattractant protein 1 (MCP-1), Uromodulin, Transferrin and Hepcidin. Methods: L-FABP, Alb, MCP-1, Uromodulin, Transferrin and Hepcidin were measured by ELISA in urine from 70 adults and 42 children collected at the time of enrollment into prospective observational LN cohorts. Urine analytes were normalized to urine creat- inine and logarithmically transformed. The association of each analyte to renal function loss (RFL), defined as a sustained increase of 25% in serum creatinine (SCr; adults) or a decrease in eGFR of 20% (children), was determined using a fixed effect model after adjusting for the age group (adult vs. child). In addition, the results were confirmed using Wilcoxon Rank Sum tests. Logis- tical models were used to predict the presence of RFL using each biomarker or a combination of the bio- markers. Biomarker performance in predicting RFL was assessed as the area under a ROC curve (AUC) corre- sponding to the logistical model. Results: 13 children and 22 adults had RFL during the mean follow-up period of 6.1 months and 60 months, respectively. Overall patients with RFL showed significantly higher levels ALB than those without RFL (p 0.05, Table). In addition, the levels of L-FABP, MCP-1, and Transferrin were also marginally higher in RFL (p-values 0.1). The AUC using the combination of urine L-FABP, Alb, MCP-1 and Utransferrin was 0.66, slightly higher than those using any single bio- marker as the predictor (ranging from 0.52–0.63). Patient type Biomarker/Cr$ Renal function loss$ Preserved renal function$ p (Fixed effect model/ Wilcoxon) N 35 77 – LFABP 1.75 1.58 1.17 1.62 0.084 / 0.066 Albumin 5.58 2.31 4.46 2.19 0.017 / 0.030 MCP-1 5.77 1.63 4.89 2.45 0.064 / 0.034 UROMODULIN 2.04 1.30 2.14 1.14 0.683 / 0.644 UTRANSFERRIN 2.27 2.27 1.49 1.98 0.073 / 0.070 All patients with LN HEPCIDIN 3.85 1.15 3.57 1.67 0.378 / 0.656 N 22 48 – LFABP 1.69 1.26 1.28 1.69 0.326 / 0.229 Albumin 5.90 2.14 5.01 2.01 0.100 / 0.147 MCP-1 5.98 1.16 4.80 2.70 0.061 / 0.057 UROMODULIN 1.33 1.06 1.65 1.08 0.261 / 0.274 UTRANSFERRIN 1.98 1.76 1.41 1.96 0.255 / 0.177 Adults with LN HEPCIDIN 3.80 0.95 3.28 1.71 0.197 / 0.368 N 13 29 – LFABP 1.84 2.05 0.98 1.50 0.136 / 0.218 Albumin 5.05 2.57 3.55 2.21 0.060 / 0.116 MCP-1 5.38 2.30 5.02 2.02 0.634 / 0.402 UROMODULIN 3.19 0.68 2.96 0.69 0.314 / 0.589 UTRANSFERRIN 2.73 2.94 1.64 2.04 0.170 / 0.199 Children with LN HEPCIDIN 3.91 1.45 4.02 1.51 0.830 / 0.803 Conclusion: Urine biomarkers L-FABP, Alb and MCP-1 are likely predictive to RFL. Other biomarkers such as Uromodulin,Transferrin and Hepcidin are mark- ers of disease activity, but not predictive of RFL. Disclosure: K. Abulaban, None; H. Brunner, Novartis, Genentech, MedImmune, EMD Serono, AMS, Pfizer, UCB, Janssen, 5, Genentech and Biogen IDEC Inc., 8; S. L. Nelson, None; M. Bennett, None; J. Ying, None; H. Song, None; P. Kimmel, None; J. Kusek, None; H. Feldman, None; V. Ramachandran, None; B. H. Rovin, None. 1 Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, 3 University of Cincinnati, Cincinnati, OH, 4 Ohio State University Medical Center, Columbus, OH, 5 NIDDK, National Institutes of Health, Bethesda, MD, 6 The University of Pennsylvania, Philadelphia, PA, 7 Boston University School of Medicine, Boston, MA. S111
Transcript of A78: Urine Biomarkers Role in Predicting the Future Development of Renal Functional Loss With Lupus...
ARTHRITIS & RHEUMATOLOGYVol. 66, No. S3, March 2014, p S111DOI 10.1002/art.38494© 2014, American College of Rheumatology
A78: Urine Biomarkers Role in Predicting theFuture Development of Renal Functional LossWith Lupus Nephritis in Children and Adults
Khalid Abulaban,1 Hermine Brunner,2 Shannen L. Nelson,1 Michael Bennett,1 Jun Ying,3
Huijuan Song,4 Paul Kimmel,5 John Kusek,5 Harold Feldman,6
Vasan Ramachandran,7 and Brad H. Rovin4
Background/Purpose: Lupus nephritis (LN) isfrequently associated with a poor long-term prognosis.Current non-invasive blood and urine tests do not reliablypredict the course of LN. The objective of this studywas to evaluate the performance of candidate urinebiomarkers in predicting future kidney function in adultsand children with LN. The biomarker candidates studieswere liver-type fatty acid binding protein (L-FABP),albumin (Alb), monocyte chemoattractant protein 1(MCP-1), Uromodulin, Transferrin and Hepcidin.
Methods: L-FABP, Alb, MCP-1, Uromodulin,Transferrin and Hepcidin were measured by ELISA inurine from 70 adults and 42 children collected at thetime of enrollment into prospective observational LNcohorts. Urine analytes were normalized to urine creat-inine and logarithmically transformed. The associationof each analyte to renal function loss (RFL), defined asa sustained increase of �25% in serum creatinine (SCr;adults) or a decrease in eGFR of �20% (children), wasdetermined using a fixed effect model after adjusting forthe age group (adult vs. child). In addition, the resultswere confirmed using Wilcoxon Rank Sum tests. Logis-tical models were used to predict the presence of RFLusing each biomarker or a combination of the bio-markers. Biomarker performance in predicting RFL wasassessed as the area under a ROC curve (AUC) corre-sponding to the logistical model.
Results: 13 children and 22 adults had RFLduring the mean follow-up period of 6.1 months and 60months, respectively. Overall patients with RFL showedsignificantly higher levels ALB than those without RFL
(p � 0.05, Table). In addition, the levels of L-FABP,MCP-1, and Transferrin were also marginally higher inRFL (p-values � 0.1). The AUC using the combinationof urine L-FABP, Alb, MCP-1 and Utransferrin was0.66, slightly higher than those using any single bio-marker as the predictor (ranging from 0.52–0.63).
Patienttype Biomarker/Cr$
Renal functionloss$
Preserved renalfunction$
p(Fixed effect
model/Wilcoxon)
N 35 77 –LFABP 1.75 � 1.58 1.17 � 1.62 0.084 / 0.066Albumin 5.58 � 2.31 4.46 � 2.19 0.017 / 0.030MCP-1 5.77 � 1.63 4.89 � 2.45 0.064 / 0.034UROMODULIN 2.04 � 1.30 2.14 � 1.14 0.683 / 0.644UTRANSFERRIN 2.27 � 2.27 1.49 � 1.98 0.073 / 0.070
All patientswith LN
HEPCIDIN 3.85 � 1.15 3.57 � 1.67 0.378 / 0.656
N 22 48 –LFABP 1.69 � 1.26 1.28 � 1.69 0.326 / 0.229Albumin 5.90 � 2.14 5.01 � 2.01 0.100 / 0.147MCP-1 5.98 � 1.16 4.80 � 2.70 0.061 / 0.057UROMODULIN 1.33 � 1.06 1.65 � 1.08 0.261 / 0.274UTRANSFERRIN 1.98 � 1.76 1.41 � 1.96 0.255 / 0.177
Adults withLN
HEPCIDIN 3.80 � 0.95 3.28 � 1.71 0.197 / 0.368
N 13 29 –LFABP 1.84 � 2.05 0.98 � 1.50 0.136 / 0.218Albumin 5.05 � 2.57 3.55 � 2.21 0.060 / 0.116MCP-1 5.38 � 2.30 5.02 � 2.02 0.634 / 0.402UROMODULIN 3.19 � 0.68 2.96 � 0.69 0.314 / 0.589UTRANSFERRIN 2.73 � 2.94 1.64 � 2.04 0.170 / 0.199
Childrenwith LN
HEPCIDIN 3.91 � 1.45 4.02 � 1.51 0.830 / 0.803
Conclusion: Urine biomarkers L-FABP, Alb andMCP-1 are likely predictive to RFL. Other biomarkerssuch as Uromodulin,Transferrin and Hepcidin are mark-ers of disease activity, but not predictive of RFL.
Disclosure: K. Abulaban, None; H. Brunner, Novartis, Genentech, MedImmune,EMD Serono, AMS, Pfizer, UCB, Janssen, 5, Genentech and Biogen IDEC Inc., 8;S. L. Nelson, None; M. Bennett, None; J. Ying, None; H. Song, None; P.Kimmel, None; J. Kusek, None; H. Feldman, None; V. Ramachandran, None;B. H. Rovin, None.
1Cincinnati Children’s Hospital Medical Center, Cincinnati,OH, 3University of Cincinnati, Cincinnati, OH, 4Ohio State UniversityMedical Center, Columbus, OH, 5NIDDK, National Institutes ofHealth, Bethesda, MD, 6The University of Pennsylvania, Philadelphia,PA, 7Boston University School of Medicine, Boston, MA.
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