103 research outputs found

    Characterizing pre-transplant and post-transplant kidney rejection risk by B cell immune repertoire sequencing.

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    Studying immune repertoire in the context of organ transplant provides important information on how adaptive immunity may contribute and modulate graft rejection. Here we characterize the peripheral blood immune repertoire of individuals before and after kidney transplant using B cell receptor sequencing in a longitudinal clinical study. Individuals who develop rejection after transplantation have a more diverse immune repertoire before transplant, suggesting a predisposition for post-transplant rejection risk. Additionally, over 2 years of follow-up, patients who develop rejection demonstrate a specific set of expanded clones that persist after the rejection. While there is an overall reduction of peripheral B cell diversity, likely due to increased general immunosuppression exposure in this cohort, the detection of specific IGHV gene usage across all rejecting patients supports that a common pool of immunogenic antigens may drive post-transplant rejection. Our findings may have clinical implications for the prediction and clinical management of kidney transplant rejection

    A Five-coordinate Metal Center in Co(II)-substituted VanX

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    In an effort to structurally probe the metal binding site in VanX, electronic absorption, EPR, and extended x-ray absorption fine structure (EXAFS) spectroscopic studies were conducted on Co(II)-substituted VanX. Electronic spectroscopy revealed the presence of Co(II) ligand field transitions that had molar absorptivities of ∼100 m–1 cm–1, which suggests that Co(II) is five-coordinate in Co(II)-substituted VanX. Low temperature EPR spectra of Co(II)-substituted VanX were simulated using spin Hamiltonian parameters of M = |±½〉, E/D = 0.14, greal(x,y) = 2.37, and grealS(z) = 2.03. These parameters lead to the prediction that Co(II) in the enzyme is five-coordinate and that there may be at least one solvent-derived ligand. Single scattering fits of EXAFS data indicate that the metal ions in both native Zn(II)-containing and Co(II)-substituted VanX have the same coordination number and that the metal ions are coordinated by 5 nitrogen/oxygen ligands at ∼ 2.0 Å. These data demonstrate that Co(II) (and Zn(II) from EXAFS studies) is five-coordinate in VanX in contrast to previous crystallographic studies (Bussiere, D. E., Pratt, S. D., Katz, L., Severin, J. M., Holzman, T., and Park, C. H. (1998) Mol. Cell 2, 75–84). These spectroscopic studies also demonstrate that the metal ion in Co(II)-substituted VanX when complexed with a phosphinate analog of substrate d-Ala-d-Ala is also five-coordinate

    A urinary Common Rejection Module (uCRM) score for non-invasive kidney transplant monitoring.

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    A Common Rejection Module (CRM) consisting of 11 genes expressed in allograft biopsies was previously reported to serve as a biomarker for acute rejection (AR), correlate with the extent of graft injury, and predict future allograft damage. We investigated the use of this gene panel on the urine cell pellet of kidney transplant patients. Urinary cell sediments collected from patients with biopsy-confirmed acute rejection, borderline AR (bAR), BK virus nephropathy (BKVN), and stable kidney grafts with normal protocol biopsies (STA) were analyzed for expression of these 11 genes using quantitative polymerase chain reaction (qPCR). We assessed these 11 CRM genes for their abundance, autocorrelation, and individual expression levels. Expression of 10/11 genes were elevated in AR when compared to STA. Psmb9 and Cxcl10could classify AR versus STA as accurately as the 11-gene model (sensitivity = 93.6%, specificity = 97.6%). A uCRM score, based on the geometric mean of the expression levels, could distinguish AR from STA with high accuracy (AUC = 0.9886) and correlated specifically with histologic measures of tubulitis and interstitial inflammation rather than tubular atrophy, glomerulosclerosis, intimal proliferation, tubular vacuolization or acute glomerulitis. This urine gene expression-based score may enable the non-invasive and quantitative monitoring of AR

    Cell-Free DNA and CXCL10 Derived from Bronchoalveolar Lavage Predict Lung Transplant Survival.

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    Standard methods for detecting chronic lung allograft dysfunction (CLAD) and rejection have poor sensitivity and specificity and have conventionally required bronchoscopies and biopsies. Plasma cell-free DNA (cfDNA) has been shown to be increased in various types of allograft injury in transplant recipients and CXCL10 has been reported to be increased in the lung tissue of patients undergoing CLAD. This study used a novel cfDNA and CXCL10 assay to evaluate the noninvasive assessment of CLAD phenotype and prediction of survival from bronchoalveolar lavage (BAL) fluid. A total of 60 BAL samples (20 with bronchiolitis obliterans (BOS), 20 with restrictive allograft syndrome (RAS), and 20 with stable allografts (STA)) were collected from 60 unique lung transplant patients; cfDNA and CXCL10 were measured by the ELISA-based KIT assay. Median cfDNA was significantly higher in BOS patients (6739 genomic equivalents (GE)/mL) versus STA (2920 GE/mL) and RAS (4174 GE/mL) (p < 0.01 all comparisons). Likelihood ratio tests revealed a significant association of overall survival with cfDNA (p = 0.0083), CXCL10 (p = 0.0146), and the interaction of cfDNA and CXCL10 (p = 0.023) based on multivariate Cox proportional hazards regression. Dichotomizing patients based on the median cfDNA level controlled for the mean level of CXCL10 revealed an over two-fold longer median overall survival time in patients with low levels of cfDNA. The KIT assay could predict allograft survival with superior performance compared with traditional biomarkers. These data support the pursuit of larger prospective studies to evaluate the predictive performance of cfDNA and CXCL10 prior to lung allograft failure

    Urinary virome perturbations in kidney transplantation

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    The human microbiome is important for health and plays a role in essential metabolic functions and protection from certain pathogens. Conversely, dysbiosis of the microbiome is seen in the context of various diseases. Recent studies have highlighted that a complex microbial community containing hundreds of bacteria colonizes the healthy urinary tract, but little is known about the human urinary viruses in health and disease. To evaluate the human urinary virome in the context of kidney transplantation (tx), variations in the composition of the urinary virome were evaluated in urine samples from normal healthy volunteers as well as patients with kidney disease after they had undergone kidney tx. Liquid chromatography-mass spectrometry/mass spectrometry analysis was undertaken on a selected cohort of 142 kidney tx patients and normal healthy controls, from a larger biobank of 770 kidney biopsy matched urine samples. In addition to analysis of normal healthy control urine, the cohort of kidney tx patients had biopsy confirmed phenotype classification, coincident with the urine sample analyzed, of stable grafts (STA), acute rejection, BK virus nephritis, and chronic allograft nephropathy. We identified 37 unique viruses, 29 of which are being identified for the first time in human urine samples. The composition of the human urinary virome differs in health and kidney injury, and the distribution of viral proteins in the urinary tract may be further impacted by IS exposure, diet and environmental, dietary, or cutaneous exposure to various insecticides and pesticides

    A computational gene expression score for predicing immune injury in renal allografts

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    Background Whole genome microarray meta-analyses of 1030 kidney, heart, lung and liver allograft biopsies identified a common immune response module (CRM) of 11 genes that define acute rejection (AR) across different engrafted tissues. We evaluated if the CRM genes can provide a molecular microscope to quantify graft injury in acute rejection (AR) and predict risk of progressive interstitial fibrosis and tubular atrophy (IFTA) in histologically normal kidney biopsies. Methods Computational modeling was done on tissue qPCR based gene expression measurements for the 11 CRM genes in 146 independent renal allografts from 122 unique patients with AR (n = 54) and no-AR (n = 92). 24 demographically matched patients with no-AR had 6 and 24 month paired protocol biopsies; all had histologically normal 6 month biopsies, and 12 had evidence of progressive IFTA (pIFTA) on their 24 month biopsies. Results were correlated with demographic, clinical and pathology variables. Results The 11 gene qPCR based tissue CRM score (tCRM) was significantly increased in AR (5.68 ± 0.91) when compared to STA (1.29 ± 0.28; p < 0.001) and pIFTA (7.94 ± 2.278 versus 2.28 ± 0.66; p = 0.04), with greatest significance for CXCL9 and CXCL10 in AR (p <0.001) and CD6 (p<0.01), CXCL9 (p<0.05), and LCK (p<0.01) in pIFTA. tCRM was a significant independent correlate of biopsy confirmed AR (p < 0.001; AUC of 0.900; 95% CI = 0.705-903). Gene expression modeling of 6 month biopsies across 7/11 genes (CD6, INPP5D, ISG20, NKG7, PSMB9, RUNX3, and TAP1) significantly (p = 0.037) predicted the development of pIFTA at 24 months. Conclusions Genome-wide tissue gene expression data mining has supported the development of a tCRM-qPCR based assay for evaluating graft immune inflammation. The tCRM score quantifies injury in AR and stratifies patients at increased risk of future pIFTA prior to any perturbation of graft function or histology
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