Copyright
©The Author(s) 2016.
World J Transplant. Mar 24, 2016; 6(1): 28-41
Published online Mar 24, 2016. doi: 10.5500/wjt.v6.i1.28
Published online Mar 24, 2016. doi: 10.5500/wjt.v6.i1.28
Table 1 Proteomic studies on renal allograft rejection
Ref. | B/U | Training set | n | Validation set | n | Proteomic method | Performance | Identified molecules | Remarks |
Akkina et al[35] | U | C (bx) | 13 | None | iTRAQ- | NR | None | Study included healthy individuals. Study concentrates on longitudinal stability of peptides in rejecting and non-rejecting patients | |
BL | 1 | MALDI- | |||||||
IIa | 1 | MS/MS | |||||||
aABMR | 1 | ||||||||
Clarke et al[36] | U | C (st) | 15 | None | SELDI- | Accuracy 91% Sensitivity 83% Specificity 100% (2-marker classifier) | None | ||
AR | 15 | TOF-MS | |||||||
Freue et al[37] | B | C (bx) | 21 | None | iTRAQ- | AUC 0.86 Sensitivity 80% specificity 90% (4-marker classifier) | Up-regulated: TTN, LBP, PI16, CFD, MBL2, SERPINA10, B2M Down-regulated: KNG1, AFM, SERPINA5, LCAT, SHBG | ELISA was performed on 4 of the identified markers (coagulation factor IX, SHBG, CFD, LCAT) in blood | |
Ia | 7 | MALDI- | |||||||
Ib | 1 | MS/MS | |||||||
IIa | 3 | ||||||||
Günther et al[38] | B | C (st) | 13 | C (st) | 7 | iTRAQ- | AUC 0.76 | 21 peptides | Different statistical approaches to integrate proteomics and transcriptomic results are presented |
AR | 13 | AR | 7 | MALDI- | Sensitivity 57% | ||||
MS/MS | specificity 86% | ||||||||
Jahnukainen et al[39] | U | C (st) | 29 | None | SELDI- | Sensitivity 81% Specificity 84% (100-marker classifier) | None | 21 of the 28 rejection samples showed also signs of chronic rejection Article concentrates on differentiation of AR and BKV-NP | |
Ia-IIb | 28 | TOF-MS | |||||||
BKV | 21 | ||||||||
Ling et al[40] | U | C (bx) | 10 | C (bx) | 10 | LC-MALDI- | AUC 0.96 (40-marker classifier) | COL1A2, COL3A1, UMOD, MMP-7, SERPING1, TIMP1 | Study included healthy individuals and patients with native kidney disease (nephrotic syndrome). Results of proteomic analysis are related to mRNA expression profiling of corresponding biopsies |
AR | 10 | AR | 10 | TOF-MS | |||||
BKV | 10 | BKV | 4 | LC-MS/MS | |||||
Loftheim et al[41] | U | C (st) | 6 | None | 2D LC- | NR | Up-regulated: IGFBP7, VASN, EGF, LGALS3BP | Study collected sequential urines from the beginning after Tx. Analysed samples for rejection patterns were taken 7-11 d before biopsy | |
BL | 1 | MS/MS | |||||||
Ia | 4 | ||||||||
IIa | 1 | ||||||||
Mao et al[42] | U | C (bx) | 22 | C (bx) | 14 | SELDI- | Sensitivity 90% Specificity 71% (4-marker classifier) | None | All TCMR cases were subclinical rejections with grades ≥ Ia |
TCMR | 27 | TCMR | 10 | TOF-MS | |||||
Metzger et al[43] | U | C (bx) | 23 | C (bx) | 36 | CE-MS | AUC 0.91 Sensitivity 93% Specificity 78% (14-marker classifier) | 3 fragments of COL1A1, 1 fragment of COL3A1 | Rejections in the training set were all subclinical. The validation set contained 10 clinical and 18 subclinical rejection cases. Confounder like ATI in biopsies, urinary tract infection and CMV infection were considered |
Ia | 13 | Ia | 23 | LC-MS/MS | |||||
Ib | 3 | Ib | 5 | ||||||
O’Riordan et al[44] | U | C (st) | 22 | None | SELDI- | AUC 0.91 Sensitivity 91% Specificity 77% (2-marker classifier) | Up-regulated: SERPINA3 Downregulated: DEFB1 | Study included healthy individuals | |
AR | 23 | TOF-MS | |||||||
O’Riordan et al[45] | U | C (st) | 22 | None | SELDI- | AUC 0.91 Sensitivity 91% Specificity 77% (2-marker classifier) | Up-regulated: SERPINA3 Downregulated: DEFB1 | ||
BL | 3 | TOF MS | |||||||
Ia | 6 | LC-MS/MS | |||||||
Ib | 4 | ||||||||
IIa | 7 | ||||||||
IIb | 3 | ||||||||
Pisitkun et al[46] | U | C (bx) | 2 | None | LC-MS/MS | NR | Numerous molecules | ||
Ia | 4 | ||||||||
Ib | 1 | ||||||||
IIa | 2 | ||||||||
ATI | 7 | ||||||||
Quintana et al[47] | U | C (st) | 8 | a/cABMR | 8 | MALDI- | IFTA vs cABMR AUC 1.0 Sensitivity 100% Specificity 100% (6-marker classifier) | None | Study included healthy individuals |
a/cABMR | 10 | IFTA | 6 | TOF-MS | |||||
IFTA | 8 | ||||||||
Quintana et al[48] | U | C (st) | 5 | C (st) | 9 | LC-MS/MS | C vs IFTA/ABMR: AUC 0.82 IFTA vs ABMR 100% correct IFTA, 90% correct ABMR (2-markers) | Down-regulated: UMOD Differentiation between controls and IFTA/ABMR: KNG1 | Study included healthy individuals Two unidentified peptides could differentiate between IFTA and ABMR, based on quantitative differences of the peptides (higher in ABMR) |
a/cABMR | 10 | a/cABMR | 11 | ||||||
IFTA | 8 | IFTA | 8 | ||||||
Reichelt et al[49] | U | C (bx) | 10 | None | SELDI- | SAX2 protein chip: Sensitivity 90% Specificity 80% CM10 protein chip: Sensitivity 92% Specificity 85% (2-marker classifier) | None | ||
Ia | 7 | TOF-MS | |||||||
Ib | 3 | ||||||||
IIa | 1 | ||||||||
IIb | 2 | ||||||||
Schaub et al[13] | U | C (bx) | 22 | None | SELDI- | Sensitivity 94% Specificity 82% (3-marker classifier) | Cleaved B2M Cleaved B2M | Study included healthy individuals. The clinical confounder CMV viremia was assessed. Longitudinal evaluation of urine proteome patterns differentiated between patients with stable course and rejection | |
Ia | 7 | TOF-MS | |||||||
Ib | 8 | ||||||||
IIa | 3 | ||||||||
ATI | 5 | ||||||||
GL | 5 | ||||||||
Schaub et al[15] | U | C (bx) | 22 | None | SELDI- | NR | Study included healthy individuals. Study concentrated on cleavage mechanisms for b2-microglobulin | ||
Ia | 7 | TOF-MS, | |||||||
Ib | 8 | LC-MALDI- | |||||||
IIa | 3 | MS | |||||||
ATI | 5 | ||||||||
GL | 5 | ||||||||
Sigdel et al[14] | U | C (bx) | 10 | None | LC-MALDI- | NR | List of 73 candidates, incl. fragments of collagens, UMOD, B2M, PTGDS | Study included healthy individuals | |
AR | 10 | MS/MS | |||||||
Sigdel et al[50] | U | C (bx) | 10 | None | LC-MS/MS | AUC 0.84-0.97 for 3 single molecules (by ELISA) | Upregulated: SERPINF1 Down-regulated: UMOD, CD44 | Study included healthy individuals and patients with native kidney disease (proteinuria) | |
AR | 10 | ||||||||
Sigdel et al[51] | U | C (bx) | 30 | None | iTRAQ- | AUC 0.8 for 3 single molecules (by ELISA) | HLA-DRB1, KRT14, HIST1H4B, FGG, ACTB, FGB, FGA, KRT7, DPP4, cleaved B2M | In ELISA studies, FGG could also segregate AR from BKV-nephropathy Validation set for detection of FGG, HLA DRB1, FGB by ELISA included 44 stable transplant patients and 44 patients with rejection | |
Ia-IIb | 30 | LC-MS/MS | |||||||
aABMR | 2 | ||||||||
IFTA | 30 | ||||||||
BKV | 18 | ||||||||
Sigdel et al[52] | U | C (bx) | 20 | None | iTRAQ- | NR | Enriched in exosomal fraction in AR: A2M, APOA2, APOM, CD5L, CLCA1, FGA, FGB, IGHM, DEFA5, PROS1, KIAA0753 Exclusively in the exosomal fraction in AR: CLCA1, PROS1, KIAA0753 | Study concentrated on differences between the whole proteome in urine (non-fractionated) and the exosomal fraction | |
≥ Ia | 20 | LC-MS/MS | |||||||
Stubendorff et al[53] | U | C (st) | 16 | C (st) | 16 | SELDI- | Sensitivity 94% Specificity 44% (4-marker classifier) Sensitivity 80% Specificity 81% for 2 molecules (by ELISA) | Up-regulated: A1MG, HP | Results on longitudinally collected samples suggest that alpha-1-microglobulin and haptoglobin indicate upcoming AR early |
AR | 16 | AR | 16 | TOF MS | |||||
Sui et al[54] | B | C (bx) | 12 | None | MALDI- | Recognition capability for AR 90% | None | Study included healthy individuals. Sample clean-up was performed with magnetic beads | |
AR | 12 | TOF-MS | |||||||
CR | 12 | ||||||||
Wang et al[55] | B | C (bx) | 19 | C (bx) | 10 | SELDI- | C vs subclinical ≥ Ia Sensitivity 100% Specificity 90% (3-marker classifier) C vs TCMR Sensitivity 90% Specificity 90% (7-marker classifier) AR vs subclinical Sensitivity 100% Specificity 100% (4-marker classifier) | None | ≥ Ia refers to subclinical rejections only. All (non-graded) TCMR cases were clinical rejections |
≥ Ia | 14 | ≥ Ia | 10 | TOF-MS | |||||
TCMR | 28 | ||||||||
ATI | 10 | ||||||||
Wittke et al[56] | U | C (bx) | 29 | C (bx) | 10 | CE-MS, | Sensitivity 67% Specificity 80% (17-marker classifier) | COL4A5 | Transplant patients with urinary tract infection were included, with biopsy-confirmed absence of rejection. Of the rejection cases, 13 were subclinical and 6 clinical |
Ia | 11 | Ia | 6 | LC-MS/MS | |||||
Ib | 6 | Ib | 3 | ||||||
IIa | 1 | ||||||||
IIb | 1 | UTI | 7 | ||||||
UTI | 10 | ||||||||
Wu et al[57] | B | C (st) | 8 | None | iTRAQ- | NR | Numerous molecules belonging to different pathways: e.g., inflammatory response, complement, defence response, protein maturation and processing, humoral immune response | ||
Ib | 1 | 2D LC- | |||||||
IIa | 2 | MS/MS | |||||||
IIb | 1 | ||||||||
III | 1 | ||||||||
Yang et al[58] | U | C (bx) | 36 | C (bx) | 14 | SELDI- | C vs TCMR/ABMR Sensitivity 100% Specificity 78% (3-marker classifier) ABMR vs TCMR Sensitivity 80% Specificity 95% (5-marker classifier) | None | |
TCMR | 30 | TCMR | 10 | TOF-MS | |||||
aABMR | 25 | aABMR | 10 | ||||||
ATI | 10 | ||||||||
Zhang et al[59] | U | C (bx) | 41 | None | MALDI- | Different classifier combinations: Sensitivity 73%-88% Specificity 53%-62% | Up-regulated: B2M, SERPINA1. Down-regulated: PSAP | Study included healthy individuals and patients with native kidney disease (nephrotic syndrome). Saposin B was high in transplant patients with stable course over 280 d and low in patients with subsequent graft failure | |
CR/(AR) | 90 | TOF-MS | |||||||
MALDI- | |||||||||
MS/MS | |||||||||
Ziegler et al[60] | B | C | 48 | None | SELDI- | Sensitivity 100% Specificity 94% for 2 molecules (by ELISA) | Out of 22 candidates decreased: APOA1, SERPINA3 | Two patients with TCMR had also signs of additional ABMR. The 2 markers for rejection were not informative in samples collected a few days before the rejection | |
Ia | 10 | TOF-MS | |||||||
Ib | 7 | MALDI- | |||||||
MS/MS |
- Citation: Gwinner W, Metzger J, Husi H, Marx D. Proteomics for rejection diagnosis in renal transplant patients: Where are we now? World J Transplant 2016; 6(1): 28-41
- URL: https://www.wjgnet.com/2220-3230/full/v6/i1/28.htm
- DOI: https://dx.doi.org/10.5500/wjt.v6.i1.28