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Abstract Number: 637

Proteomic Approach and Validation Of Urinary Biomarkers In Lupus Nephritis

Joo Youn Lee1, Sung Hae Chang2, Hye Jin Oh3, Yong Yook Lee1, Min Jueng Kang1, Eun Young Lee4, Eun Bong Lee5, Eugene C. Yi1 and Young Wook Song1,5, 1Department of Molecular Medicine and Biopharmaceutical Sciences, Seoul National University, Seoul, South Korea, 2Internal Medicine Rheumatology, Seoul National University Bundang Hospital, Seongnam-si, South Korea, 3Seoul National University, Seoul, South Korea, 4Internal medicine, Division of Rheumatology, Department of Internal Medicine, Seoul National University, Seoul, South Korea, 5Division of Rheumatology, Department of Internal Medicine, Seoul National University, Seoul, South Korea

Meeting: 2013 ACR/ARHP Annual Meeting

Keywords: SLE, Urinary Biomarkers and proteomics

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Session Information

Title: Systemic Lupus Erythematosus - Human Etiology and Pathogenesis: Mechanisms and Biomarkers

Session Type: Abstract Submissions (ACR)

Background/Purpose:

Renal involvement occurs in about half of systemic lupus erythematosus (SLE) patients. A number of biochemical markers are currently used to clinically assess lupus nephritis (LN) activity. Nevertheless, the correlation between these markers and LN is not satisfactory. / We screened urinary biomarkers of LN using LTQ-Velos hybrid mass spectrometer and validated the biomarkers in a cohort of SLE patients.

Methods:

Urine samples from SLE patients with nephritis (n=5) and without nephritis (n=5) were obtained from Seoul National University Hospital. We employed a nanospray interfaced LTQ-Velos hybrid mass spectrometer. Data were processed using SorcererTM –SEQUEST. The searched data entered into Scaffold software (Proteome Software) for compilation, and the datasets were imported into the R to generate Power Law Global Error Model (PLGEM, www.bioconductor.org) values for each protein identified (FDR < 1%). The spectral count was used for Gene Ontology, and pathway analysis using Ingenuity Pathway Analysis.

In 124 SLE patients (20 LN, 104 non-LN), 21 healthy controls, and 31 disease controls (IgA nephropathy and membraneous glomerulonephritis), urinary levels of retinol binding protein 4 (RBP4), vitamin D binding protein (VDBP), complement factor H (CFH), transthyretin (TTR), and prostaglandin D synthase, lipocalin type (PGDS) were measured by ELISA. Urinary levels of biomarkers were normalized against urine creatinine. Patient global assessment (PtGA), physician global assessment (PhGA) and SLE disease activity index 2K (SLEDAI 2K) were measured at the time of urine sampling.

Results:

487 unique proteins and 3550 unique peptides were identified in urine of SLE patients by MS spectroscopy. We selected five biomarker candidates with high confident level. SLE patients with LN showed significantly higher urinary levels of RBP4, VDBP, CFH, TTR, and PGDS compared with those without LN (p = 0.0003, p < 0.0001, p = 0.0001, p = 0.0015 and p = 0.0001, respectively) or healthy controls. Urinary level of PGDS was significantly higher in LN than disease controls (mean±SE, 7190.7 ± 2621.0 vs 1001.2 ± 126.3 ng/mgCr, p = 0.0181). Other biomarkers tended to be higher in LN compare to disease controls ( RBP4, 22820.0 ± 17650.0 vs 2534.2 ± 983.8, P = 0.2591; VDBP, 413.5 ± 216.8 vs 186.6 ± 49.33, p = 0.7589; CFH, 100.4 ± 51.8 vs 55.5 ± 16.0, p = 0.9923; TTR, 267.0 ± 142.5 vs 126.3 ± 50.7, p = 0.4813).

Urinary levels of VDBP, CFH, TTR, and PGDS were significantly correlated with Ph GA in LN (p = 0.0322, p = 0.0233, p = 0.0318 and p = 0.0009, respectively). Urinary levels of TTR and PGDS were significantly correlated with SLEDAI 2K in LN (p = 0.0042 and p = 0.0016, respectively).

Conclusion:

Urinary PGDS may serve as a biomarker for LN. It was significantly correlated with physician global assessment and SLEDAI 2K in LN.


Disclosure:

J. Y. Lee,
None;

S. H. Chang,
None;

H. J. Oh,
None;

Y. Y. Lee,
None;

M. J. Kang,
None;

E. Y. Lee,
None;

E. B. Lee,
None;

E. C. Yi,
None;

Y. W. Song,
None.

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