Title |
PD1-Expressing T Cell Subsets Modify the Rejection Risk in Renal Transplant Patients
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Published in |
Frontiers in immunology, April 2016
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DOI | 10.3389/fimmu.2016.00126 |
Pubmed ID | |
Authors |
Rebecca Pike, Niclas Thomas, Sarita Workman, Lyn Ambrose, David Guzman, Shivajanani Sivakumaran, Margaret Johnson, Douglas Thorburn, Mark Harber, Benny Chain, Hans J. Stauss |
Abstract |
We tested whether multi-parameter immune phenotyping before or after renal -transplantation can predict the risk of rejection episodes. Blood samples collected before and weekly for 3 months after transplantation were analyzed by multi-parameter flow cytometry to define 52 T cell and 13 innate lymphocyte subsets in each sample, producing more than 11,000 data points that defined the immune status of the 28 patients included in this study. Principle component analysis suggested that the patients with histologically confirmed rejection episodes segregated from those without rejection. Protein death 1 (PD-1)-expressing subpopulations of regulatory and conventional T cells had the greatest influence on the principal component segregation. We constructed a statistical tool to predict rejection using a support vector machine algorithm. The algorithm correctly identified 7 out of 9 patients with rejection, and 14 out of 17 patients without rejection. The immune profile before transplantation was most accurate in determining the risk of rejection, while changes of immune parameters after transplantation were less accurate in discriminating rejection from non-rejection. The data indicate that pretransplant immune subset analysis has the potential to identify patients at risk of developing rejection episodes, and suggests that the proportion of PD1-expressing T cell subsets may be a key indicator of rejection risk. |
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United Kingdom | 2 | 33% |
United States | 1 | 17% |
Switzerland | 1 | 17% |
Unknown | 2 | 33% |
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Mendeley readers
Geographical breakdown
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Demographic breakdown
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Professor | 5 | 14% |
Other | 4 | 11% |
Student > Master | 4 | 11% |
Student > Ph. D. Student | 2 | 6% |
Other | 4 | 11% |
Unknown | 10 | 28% |
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Computer Science | 1 | 3% |
Other | 3 | 8% |
Unknown | 10 | 28% |