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  • 1
    In: Journal of the American Society of Nephrology, Ovid Technologies (Wolters Kluwer Health), Vol. 32, No. 5 ( 2021-5), p. 1210-1226
    Abstract: Urinary extracellular vesicles (uEVs) are a promising noninvasive source of kidney biomarkers, but the optimal approaches for normalization, quantification, and characterization in spot urines are unclear. To address the hypothesis that urine creatinine can be used as a normalization variable, urine particles were quantified in dilute and concentrated urines (water deprivation–loading study) and randomly from healthy subjects and patients with kidney disease. In these various settings, urine creatinine was highly correlated with particle counts, suggesting it can be used as a normalization variable. Additional findings relevant for future uEV studies include interference of Tamm-Horsfall protein with nanoparticle tracking analysis, excretion of larger uEVs in dilute urine, and the ability to treat uEVs with detergent to enhance intracellular epitope recognition. Background Urinary extracellular vesicles (uEVs) are a promising source for biomarker discovery, but optimal approaches for normalization, quantification, and characterization in spot urines are unclear. Methods Urine samples were analyzed in a water-loading study, from healthy subjects and patients with kidney disease. Urine particles were quantified in whole urine using nanoparticle tracking analysis (NTA), time-resolved fluorescence immunoassay (TR-FIA), and EVQuant, a novel method quantifying particles via gel immobilization. Results Urine particle and creatinine concentrations were highly correlated in the water-loading study ( R 2 0.96) and in random spot urines from healthy subjects ( R 2 0.47–0.95) and patients ( R 2 0.41–0.81). Water loading reduced aquaporin-2 but increased Tamm-Horsfall protein (THP) and particle detection by NTA. This finding was attributed to hypotonicity increasing uEV size (more EVs reach the NTA size detection limit) and reducing THP polymerization. Adding THP to urine also significantly increased particle count by NTA. In both fluorescence NTA and EVQuant, adding 0.01% SDS maintained uEV integrity and increased aquaporin-2 detection. Comparison of intracellular- and extracellular-epitope antibodies suggested the presence of reverse topology uEVs. The exosome markers CD9 and CD63 colocalized and immunoprecipitated selectively with distal nephron markers. Conclusions uEV concentration is highly correlated with urine creatinine, potentially replacing the need for uEV quantification to normalize spot urines. Additional findings relevant for future uEV studies in whole urine include the interference of THP with NTA, excretion of larger uEVs in dilute urine, the ability to use detergent to increase intracellular-epitope recognition in uEVs, and CD9 or CD63 capture of nephron segment–specific EVs.
    Type of Medium: Online Resource
    ISSN: 1046-6673 , 1533-3450
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2021
    detail.hit.zdb_id: 2029124-3
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  • 2
    Online Resource
    Online Resource
    Ovid Technologies (Wolters Kluwer Health) ; 2021
    In:  Transplantation Direct Vol. 7, No. 7 ( 2021-07), p. e717-
    In: Transplantation Direct, Ovid Technologies (Wolters Kluwer Health), Vol. 7, No. 7 ( 2021-07), p. e717-
    Type of Medium: Online Resource
    ISSN: 2373-8731
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2021
    detail.hit.zdb_id: 2890276-2
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  • 3
    In: Transplantation, Ovid Technologies (Wolters Kluwer Health), Vol. 107, No. 4 ( 2023-04), p. 903-912
    Abstract: Transcriptome analysis could be an additional diagnostic parameter in diagnosing kidney transplant (KTx) rejection. Here, we assessed feasibility and potential of NanoString nCounter analysis of KTx biopsies to aid the classification of rejection in clinical practice using both the Banff-Human Organ Transplant (B-HOT) panel and a customized antibody-mediated rejection (AMR)–specific NanoString nCounter Elements (Elements) panel. Additionally, we explored the potential for the classification of KTx rejection building and testing a classifier within our dataset. Methods. Ninety-six formalin-fixed paraffin-embedded KTx biopsies were retrieved from the archives of the ErasmusMC Rotterdam and the University Hospital Cologne. Biopsies with AMR, borderline or T cell–mediated rejections (BLorTCMR), and no rejection were compared using the B-HOT and Elements panels. Results. High correlation between gene expression levels was found when comparing the 2 chemistries pairwise (r = 0.76–0.88). Differential gene expression (false discovery rate; P   〈  0.05) was identified in biopsies diagnosed with AMR (B-HOT: 294; Elements: 76) and BLorTCMR (B-HOT: 353; Elements: 57) compared with no rejection. Using the most predictive genes from the B-HOT analysis and the Element analysis, 2 least absolute shrinkage and selection operators–based regression models to classify biopsies as AMR versus no AMR (BLorTCMR or no rejection) were developed achieving an receiver-operating–characteristic curve of 0.994 and 0.894, sensitivity of 0.821 and 0.480, and specificity of 1.00 and 0.979, respectively, during cross-validation. Conclusions. Transcriptomic analysis is feasible on KTx biopsies previously used for diagnostic purposes. The B-HOT panel has the potential to differentiate AMR from BLorTCMR or no rejection and could prove valuable in aiding kidney transplant rejection classification.
    Type of Medium: Online Resource
    ISSN: 0041-1337
    RVK:
    Language: English
    Publisher: Ovid Technologies (Wolters Kluwer Health)
    Publication Date: 2023
    detail.hit.zdb_id: 2035395-9
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