MOLECULAR MECHANISMS OF CHRONIC KIDNEY GRAFT INJURY

D. Maluf¹, M.J. Scian², K.J. Archer³, L.J. Suh⁴, R. Fassnacht², B.C. Whitehill¹, A. Cotterell¹, A. Sharma⁵, D.H. Massey⁶, A. King⁷, T.W. Gehr⁷, M.P. Posner¹, V. Mas^8
1Transplantation Surgery, Virginia Commonwealth University, Richmond/UNITED STATES OF AMERICA, ²Surgery, VCUHS, Richmond/UNITED STATES OF AMERICA, ³Biostatistics, VCU, Richmond/VA/UNITED STATES OF AMERICA, ⁴Surgery, VCUHS, Richmond/VA/UNITED STATES OF AMERICA, ⁵Transplantation Surgery, Virginia Commonwealth University, Richmond/VA/UNITED STATES OF AMERICA, ⁶Pathology, VCUHS, Richmond/VA/UNITED STATES OF AMERICA, ⁷Nephrology, VCUHS, Richmond/UNITED STATES OF AMERICA, ⁸Surgery And Pathology, VCUHS, Richmond/VA/UNITED STATES OF AMERICA

Body: Background. Interstitial fibrosis (IF) and tubular atrophy (TA) are integral parts of chronic allograft dysfunction and represent in the new classification a separate entity with or without the identification of a specific etiology. Systematic analysis of gene expression (GE) patterns will provide a window into the biology and pathogenesis of allograft fibrosis development. Time-dependent associations among GE profiling, histological allograft damage and donor/recipients factors were evaluated at different time periods post kidney transplantation (KTx). Patients and Methods. Prospective GE profiling of protocol allograft biopsies (Bx) (N=155) from kidney transplant recipients (KTRs) at pre-implantation (PI), post-reperfusion (PR), 3 (K3) and 9 mo (K9) post-KTx was evaluated. To identify genes associated with short term outcome, probe set level two-sample t-tests were used to compare expression by delayed graft function (Yes/No). As another measure of short term outcome, univariable probe set level linear models were fit whereby creatinine at 1 week and at 1 month post-KTx were modeled using probe set expression as the independent variable. For the purpose of evaluating long term graft changes (IF/TA) KTRs were classified as with IF/TA (N=11) (group 1: G1) or without IF/TA (N=27) (group 2: G2) changes based on Banff score at K9. The RMA method was used to obtain probe set expression summaries. To identify probe sets exhibiting differential expression between G1 vs. G2, a two sample t-test was performed. Probe sets were considered significant when P<0.001. Additionally, p-values from the t-test were subsequently used in obtaining the false discovery rate using the q-value method. For comparing PI to 3 mo Bx GE profiles, Probe set level paired t-tests were performed. The least absolute shrinkage and selection operator (LASSO) model was fit where the dependent variable predicted was G1 and G2. Results. Pre-implantation Bx GE profiling identified 413 probe sets associated with donor (age, gender, race, CIT, WIT) and KTRs (DGF, Cr1 week and 1 mo) characteristics (FDR<5%). The top molecular and cellular functions associated with these genes were cell death and protein synthesis. Apoptosis signaling was up regulated in the PI biopsies. Growth factors signaling were also up regulated. Cytotoxic T lymphocyte mediated apoptosis of target cells, CD28 signaling in T helper cells and T helper cells differentiation signaling were up regulated in 3mo Bx. GE at 3mo post-KTx (G1 vs. G2 at 9mo post-KTx,) showed 143 significant Psets (p<0.001). HGF and FGF signaling and THBS1 expression were up-regulated in IF/TA Bxs. IL10 signaling were up-regulated in patients without IF/TA at 9 mo post-KTx. The final LASSO model included 17 probe sets and had 100% training set accuracy. Conclusions. PI GE profiling provides information of early events (DGF, Cr 1 mo) post-KTx. GE profiling in early protocol graft biopsies was associated with progression to IF/TA. The evaluation of these signatures might result in disease progression biomarker discovery.

Disclosure: All authors have declared no conflicts of interest.