Early Urinary CCL2 is Associated With the Later Development of Interstitial Fibrosis and Tubular Atrophy in Renal Allografts

Abstract

This study demonstrates that early urinary CCL2 is an independent predictor for the subsequent development of IFTA at 24 months.

Renal Allograft Fibrosis: Biology and Therapeutic Targets

“…Several other molecules are under investigation as biomarkers in CKD, including asymmetric dimethylarginine, an endogenous inhibitor of NO synthase (396), Creactive protein (CRP), tumor necrosis factor receptor (TNF-R) II, pentraxin-3, adiponectin and apolipoprotein A-IV, as metabolic factors involved in the regulation of kidney metabolism, or endostatin as an anti-angiogenic factor (396,397). In kidney allografts, increased urinary CCL-2 was associated with renal fibrosis (317). It should be mentioned, however, that most of the mentioned markers are not kidney specific, perhaps except FGF-23, and the true diagnostic value in CKD has not yet been established (379,392).…”

“…In association studies, urinary CCL2 best predicted allograft renal fibrosis at 2 years, whereas CXCL9 and CXCL10 were not associated with late graft outcomes (317,318). Low urinary CXCL9 was the best predictor of longterm kidney graft stability (319).…”

Chemokines and transplant outcome

“…Also CCL2 urinary detection seems to be helpful for severe interstitial fibrosis, tubular atrophy and graft dysfunction at 24 months [87,88]. Furthermore, post-transplant CXCL10 detected as transcript in urinary cells predicts kidney acute rejection with a cut-off value of 9.11 mRNA [89], while high CXCL10 plasma level measured after lung transplantation associated with grade 3 graft dysfunction [90].…”

Untitled

“…Urinary CCL2 was measured and protocol biopsies performed prospectively in 111 RT recipients at 0, 6, and 24 months, which demonstrated urinary CCL2 at 6 months as an independent risk factor for subsequent development of interstitial fibrosis and tubular atrophy (IFTA)at 24 months, both in univariate and multivariate analyses. 32 Proteomic analysis of blood samples, using mass spectrometry, has identified several unique signatures of transcript and protein biomarkers with high predictive accuracies for mild and moderate/severe CAI, which can be used for proteogenomics classification of CAI based on peripheral blood profiling, although validity remains to be proven. 33 In 2003 Scherer and associates, using microarray technology, detected upregulation of several genes, which could predict the development of CAI.…”