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      Interactions of TTV with BKV, CMV, EBV, and HHV-6A and their impact on post-transplant graft function in kidney transplant recipients

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          Abstract

          Background

          Mono and combined reactivation of latent viruses occurs frequently under immunosuppressive therapy in kidney transplant patients. Recently, monitoring torque teno virus (TTV) reactivation came more into focus as a potential biomarker for immune status. The surrogate characteristics of TTV reactivation on acute rejection, and the combined reactivation with other latent viruses such as cytomegalovirus (CMV), human BK virus (BKV), Epstein–Barr virus (EBV), and human herpes virus-6A (HHV-6A) on allograft function, are unknown so far.

          Methods

          Blood samples from 93 kidney transplant recipients obtained during the first post-transplant year were analyzed for TTV/BKV/CMV/EBV/HHV-6A load. Clinical characteristics, including graft function [glomerular filtration rate (GFR)], were collected in parallel.

          Results

          TTV had the highest prevalence and viral loads at 100% and a mean of 5.72 copies/ml (cp/ml) (log 10). We found 28.0%, 26.9%, 7.5%, and 51.6% of simultaneous reactivation of TTV with BKV, CMV, EBV, and HHV-6, respectively. These combined reactivations were not associated with a significantly reduced estimated GFR at month 12. Of interest, patients with lower TTV loads <5.0 cp/ml (log 10) demonstrated not only a higher incidence of acute rejection, but also an unexpected significantly earlier occurrence and higher incidence of BKV and HHV-6A reactivation. Correlations between TTV loads, other latent viruses, and immunosuppressive medication were only significant from 6 months after transplant.

          Conclusion

          We were able to observe and support previously introduced TTV load thresholds predicting kidney allograft rejection. However, due to a possible delayed relation between immunosuppressive medication and TTV viral load adaptation, the right time points to start using TTV as a biomarker might need to be further clarified by other and better designed studies.

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          Most cited references27

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          A new equation to estimate glomerular filtration rate.

          Equations to estimate glomerular filtration rate (GFR) are routinely used to assess kidney function. Current equations have limited precision and systematically underestimate measured GFR at higher values. To develop a new estimating equation for GFR: the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation. Cross-sectional analysis with separate pooled data sets for equation development and validation and a representative sample of the U.S. population for prevalence estimates. Research studies and clinical populations ("studies") with measured GFR and NHANES (National Health and Nutrition Examination Survey), 1999 to 2006. 8254 participants in 10 studies (equation development data set) and 3896 participants in 16 studies (validation data set). Prevalence estimates were based on 16,032 participants in NHANES. GFR, measured as the clearance of exogenous filtration markers (iothalamate in the development data set; iothalamate and other markers in the validation data set), and linear regression to estimate the logarithm of measured GFR from standardized creatinine levels, sex, race, and age. In the validation data set, the CKD-EPI equation performed better than the Modification of Diet in Renal Disease Study equation, especially at higher GFR (P < 0.001 for all subsequent comparisons), with less bias (median difference between measured and estimated GFR, 2.5 vs. 5.5 mL/min per 1.73 m(2)), improved precision (interquartile range [IQR] of the differences, 16.6 vs. 18.3 mL/min per 1.73 m(2)), and greater accuracy (percentage of estimated GFR within 30% of measured GFR, 84.1% vs. 80.6%). In NHANES, the median estimated GFR was 94.5 mL/min per 1.73 m(2) (IQR, 79.7 to 108.1) vs. 85.0 (IQR, 72.9 to 98.5) mL/min per 1.73 m(2), and the prevalence of chronic kidney disease was 11.5% (95% CI, 10.6% to 12.4%) versus 13.1% (CI, 12.1% to 14.0%). The sample contained a limited number of elderly people and racial and ethnic minorities with measured GFR. The CKD-EPI creatinine equation is more accurate than the Modification of Diet in Renal Disease Study equation and could replace it for routine clinical use. National Institute of Diabetes and Digestive and Kidney Diseases.
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            UpSetR: an R package for the visualization of intersecting sets and their properties

            Abstract Motivation: Venn and Euler diagrams are a popular yet inadequate solution for quantitative visualization of set intersections. A scalable alternative to Venn and Euler diagrams for visualizing intersecting sets and their properties is needed. Results: We developed UpSetR, an open source R package that employs a scalable matrix-based visualization to show intersections of sets, their size, and other properties. Availability and implementation: UpSetR is available at https://github.com/hms-dbmi/UpSetR/ and released under the MIT License. A Shiny app is available at https://gehlenborglab.shinyapps.io/upsetr/. Contact: nils@hms.harvard.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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              Adjusting for multiple testing--when and how?

              Multiplicity of data, hypotheses, and analyses is a common problem in biomedical and epidemiological research. Multiple testing theory provides a framework for defining and controlling appropriate error rates in order to protect against wrong conclusions. However, the corresponding multiple test procedures are underutilized in biomedical and epidemiological research. In this article, the existing multiple test procedures are summarized for the most important multiplicity situations. It is emphasized that adjustments for multiple testing are required in confirmatory studies whenever results from multiple tests have to be combined in one final conclusion and decision. In case of multiple significance tests a note on the error rate that will be controlled for is desirable.
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                Author and article information

                Contributors
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                Journal
                Front Transplant
                Front Transplant
                Front. Transplant.
                Frontiers in Transplantation
                Frontiers Media S.A.
                2813-2440
                11 June 2024
                2024
                : 3
                : 1393838
                Affiliations
                [ 1 ]Berlin Center for Advanced Therapies (BeCAT), Charité — Universitätsmedizin Berlin , Berlin, Germany
                [ 2 ]Center for Translational Medicine, Universitätsklinikum der Ruhr-Universität Bochum, Medizinische Klinik I , Herne, Germany
                [ 3 ]MicroDiscovery GmbH , Berlin, Germany
                [ 4 ]Institute of Medical Immunology, Charité — Universitätsmedizin Berlin , Berlin, Germany
                [ 5 ]Chirurgische Klinik, Universitätsklinikum Knappschaftskrankenhaus Bochum , Bochum, Germany
                [ 6 ]Universitätsklinikum Carl Gustav Carus, Medizinische Klinik III — Bereich Nephrologie , Dresden, Germany
                Author notes

                Edited by: Friedrich Thaiss, University of Hamburg, Germany

                Reviewed by: Magdalena Durlik, Medical University of Warsaw, Poland

                Louise Benning, University of Heidelberg, Germany

                [* ] Correspondence: Nina Babel nina.babel@ 123456charite.de
                Article
                10.3389/frtra.2024.1393838
                11235294
                38993745
                e085056c-8a3d-4fe0-b991-253797439c6b
                © 2024 Rosiewicz, Blazquez-Navarro, Kaliszczyk, Bauer, Or-Guil, Viebahn, Zgoura, Reinke, Roch, Hugo, Westhoff, Thieme, Stervbo and Babel.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 29 February 2024
                : 24 May 2024
                Page count
                Figures: 4, Tables: 3, Equations: 0, References: 27, Pages: 10, Words: 0
                Funding
                The authors declare financial support was received for the research, authorship, and/or publication of this article.
                This study was funded by the BMBF Sysmed Consortium project eKID and the BMBF project CORONA-VirAN.
                Categories
                Transplantation
                Brief Research Report
                Custom metadata
                Transplantation Immunology

                ttv,ktx,bkv,cmv,epstein–barr virus (ebv),hhv-6a
                ttv, ktx, bkv, cmv, epstein–barr virus (ebv), hhv-6a

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