Urinary Cell Transcriptome Profiling and Identification of ITM2A, SLAMF6, and IKZF3 as Biomarkers of Acute Rejection in Human Kidney Allografts

Abstract

Background. Identification of a shared gene expression pattern between T cell–mediated rejection (TCMR) and antibody-mediated rejection (AMR) in human kidney allografts may help prioritize targets for the treatment of both types of acute rejection. Methods. We performed RNA sequencing and bioinformatics of genome-wide transcriptome profiles of urinary cells to identify novel mRNAs shared between TCMR and AMR and of mechanistic relevance. Customized RT-QPCR assays were then used to validate their abundance in urinary cells. Urinary cell transcriptome profiles and mRNA abundance were assessed in 22 urine samples matched to 22 TCMR biopsies, 7 samples matched to 7 AMR biopsies, and 24 samples matched to 24 No Rejection (NR) biopsies and correlated with biopsy diagnosis. Results. RNA sequencing data and bioinformatics identified 127 genes in urine to be shared between TCMR and AMR. We selected 3 novel mRNAs—ITM2A, SLAMF6, and IKZF3—for absolute quantification and validation by customized RT-QPCR assays. The abundance of all 3 mRNAs was significantly higher in urine matched to TCMR or AMR than in urine matched to NR biopsies. Receiver-operating-characteristic curve analysis showed that all 3 mRNAs distinguished TCMR or AMR from NR. Their abundance was similar in patients with TCMR and those with AMR. Conclusions. State-of-the-art antirejection therapies are mostly effective to treat TCMR but not AMR. Our identification of mRNAs shared between TCMR and AMR and contributing to T cell–B cell interactions may help prioritize therapeutic targets for the simultaneous treatment of TCMR and AMR.

Standardization and Interpretation of RNA-sequencing for Transplantation

“…Additionally, the ability to profile the entire genome makes it a powerful tool for biomarker discovery. 4 Nonetheless, downstream analyses require experienced data scientists. Also, bioinformatic tools developed for interrogating such large datasets inevitably obscure biological nuances that may or may not be relevant to the research question at hand.…”

“…3 Urinary cell transcriptome profiling helped discover novel biomarkers for AR, whose abundance in urinary cells was validated by customized PCR assays. 4 In an earlier study, our group did exome sequencing (sequencing of protein-coding regions in the genome) of DNA from kidney recipients and their living donors and estimated all possible cell surface antigens mismatches for a given donor/recipient pair by computing the number of amino acid mismatches in transmembrane proteins. This tally, designated as the allogenomics mismatch score, was significantly associated with long-term allograft function, independent of HLA matching, donor age, and time posttransplantation.…”

“…3 Urinary cell transcriptome profiling helped discover novel biomarkers for AR, whose abundance in urinary cells was validated by customized PCR assays. 4…”

Applications of Transcriptomics in the Research of Antibody-Mediated Rejection in Kidney Transplantation: Progress and Perspectives

“…One study performing RNA-seq on biopsy-paired peripheral blood samples from patient cohorts with different types of rejection identified 102 genes with enrichment in the regulation of endoplasmic reticulum stress, adaptive immunity, and Ig class-switching to be associated with ABMR, including the SIGLEC17P pseudogene and the related coding genes, 49 of which the expression is almost exclusively in NK cells. 50 Dooley et al 51 performed RNA-seq with human urine samples matched to TCMR, ABMR, as well as non-rejection biopsies and identified three novel mRNAs ( ITM2A, SLAMF6 , and IKZF3 ) of which the expressions were significantly higher in urine matched to TCMR or ABMR than in the non-rejection biopsies.…”

Urinary Cell mRNA Profiles Predictive of Human Kidney Allograft Status

“…Our RNA sequencing of urinary cells and bioinformatics identified, at a false discovery rate <0.01 and log 2 fold change ≥2, 180 genes that were differentially expressed in urine matched to T cell–mediated rejection biopsy specimens versus urine matched to specimens showing no rejection, and 544 genes that were differentially expressed in urine matched to antibody-mediated rejection biopsy specimens versus urine matched to biopsy specimens showing no rejection (38). RNA sequencing—in addition to validating the diagnostic accuracy of urinary cell levels of mRNA for CD3 ε , IP-10, granzyme B, perforin, CXCR3, CD103, and PI-9—identified several novel biomarkers of T cell–mediated rejection, including CD2, CD8A, CCL5, GZMA, NKG7, CTLA4, ITM2A, SLAM F6, and IKZF3 (38,39).…”