Session Time: 6:00pm-7:00pm
Presentation Time: 6:00pm-7:00pm
Location: Hall 4EF
Background: Optimizing immunosuppression requires individualized rejection-risk assessment in children with liver transplantation (LTx). PBL transcripts are a desirable non-invasive solution. Purpose: To characterize PBL transcriptome of rejection-prone pediatric LTx recipients. Methods: RNA sequencing (Illumina), 50 million paired end reads, was performed on 75, 55 and 55 blood samples obtained from 152 children, before, within 60 days, and between months 12-60 months after LTx (Groups A, B and C), respectively. Differentially expressed transcripts (DETs, fold-change cutoff 1.5-fold, p<0.05) distinguishing children who developed rejection within 60 days after sampling from those who did not were evaluated with Ingenuity Pathway Analysis software. Enriched pathways (-log10 pv >1.3) and representative pathway-associated transcripts were compared between groups. Results: Groups A, B and C featured 125, 65 and 55 DETs, of which BEX1, HLA-H and RNU6ATAC were shared between Groups A and C, and HLA-DRB5 and MIR1282 were shared between Groups B and C. Top-ranked pathways unique to each group were Group A-Interferon signaling (-log pv 6.2, ISG15, IFI35, MX1, IF16), Group B-NFAT regulation of Immune Response (-log pv 2.6, GNG11, HLA-DRB5), and Group C-Granulocyte adhesion and diapedesis (-log pv 2.7, CCL4L1, CCL3). Among significant shared immune pathways between Group B and C, 1) Antigen presentation (-log pv 1.8 vs 1.3) and B-cell development (-logpv 1.8 vs 1.3) became less significant, while 2) Communication between innate and adaptive immune cells (-log pv 1.4 vs 2.2), Allograft rejection signaling (-log pv 1.4 vs 2.2) and Crosstalk between dendritic cells and NK cells (-log pv 1.4 vs 3.6) became more significant with time, based on unique DETs in respective groups. Conclusions: Rejection-risk is associated with interferon-rich proinflammatory signaling before LTx, Calcium- and NFAT-signaling early after LTx, and innate immune cell recruitment late after LTx, likely due to limited concordance between rejection-associated PBL transcripts seen at different time periods. These unique differentially expressed genes also participate in signaling pathways shared by early and late rejection, and add to the complexity of designing a universal predictive molecular algorithm for early and late rejection.
CITATION INFORMATION: Ningappa M., Ashokkumar C., Sun Q., Higgs B., Soltys K., Bond G., Mazariegos G., Sindhi R. Predicting Pediatric Liver Transplant Rejection with Peripheral Blood Leukocyte (PBL) Transcripts-Considerations and Design Limitations Am J Transplant. 2017;17 (suppl 3).
To cite this abstract in AMA style:Ningappa M, Ashokkumar C, Sun Q, Higgs B, Soltys K, Bond G, Mazariegos G, Sindhi R. Predicting Pediatric Liver Transplant Rejection with Peripheral Blood Leukocyte (PBL) Transcripts-Considerations and Design Limitations [abstract]. https://atcmeetingabstracts.com/abstract/predicting-pediatric-liver-transplant-rejection-with-peripheral-blood-leukocyte-pbl-transcripts-considerations-and-design-limitations/. Accessed December 13, 2019.
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