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Peripheral Blood RNA Sequencing Unravels a Differential Signature of Coding and Noncoding Genes by Types of Kidney Allograft Rejection

INTRODUCTION: Peripheral blood (PB) molecular patterns characterizing the different effector immune pathways driving distinct kidney rejection types remain to be fully elucidated. We hypothesized that transcriptome analysis using RNA sequencing (RNAseq) in samples of kidney transplant patients would...

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Autores principales: Pineda, Silvia, Sur, Swastika, Sigdel, Tara, Nguyen, Mark, Crespo, Elena, Torija, Alba, Meneghini, Maria, Gomà, Montse, Sirota, Marina, Bestard, Oriol, Sarwal, Minnie M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7569686/
https://www.ncbi.nlm.nih.gov/pubmed/33102963
http://dx.doi.org/10.1016/j.ekir.2020.07.023
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author Pineda, Silvia
Sur, Swastika
Sigdel, Tara
Nguyen, Mark
Crespo, Elena
Torija, Alba
Meneghini, Maria
Gomà, Montse
Sirota, Marina
Bestard, Oriol
Sarwal, Minnie M.
author_facet Pineda, Silvia
Sur, Swastika
Sigdel, Tara
Nguyen, Mark
Crespo, Elena
Torija, Alba
Meneghini, Maria
Gomà, Montse
Sirota, Marina
Bestard, Oriol
Sarwal, Minnie M.
author_sort Pineda, Silvia
collection PubMed
description INTRODUCTION: Peripheral blood (PB) molecular patterns characterizing the different effector immune pathways driving distinct kidney rejection types remain to be fully elucidated. We hypothesized that transcriptome analysis using RNA sequencing (RNAseq) in samples of kidney transplant patients would enable the identification of unique protein-coding and noncoding genes that may be able to segregate different rejection phenotypes. METHODS: We evaluated 37 biopsy-paired PB samples from the discovery cohort, with stable (STA), antibody-mediated rejection (AMR), and T cell–mediated rejection (TCMR) by RNAseq. Advanced machine learning tools were used to perform 3-way differential gene expression analysis to identify gene signatures associated with rejection. We then performed functional in silico analysis and validation by Fluidigm (San Francisco, CA) in 62 samples from 2 independent kidney transplant cohorts. RESULTS: We found 102 genes (63 coding genes and 39 noncoding genes) associated with AMR (54 upregulated), TCMR (23 upregulated), and STA (25 upregulated) perfectly clustered with each rejection phenotype and highly correlated with main histologic lesions (ρ = 0.91). For the genes associated with AMR, we found enrichment in regulation of endoplasmic reticulum stress, adaptive immunity, and Ig class-switching. In the validation, we found that the SIGLEC17P pseudogene and 9 SIGLEC17P-related coding genes were highly expressed among AMR but not in TCMR and STA samples. CONCLUSIONS: This analysis identifies a critical gene signature in PB in kidney transplant patients undergoing AMR, sufficient to differentiate them from patients with TCMR and immunologically quiescent kidney allografts. Our findings provide the basis for new studies dissecting the role of noncoding genes in the pathophysiology of kidney allograft rejection and their potential value as noninvasive biomarkers of the rejection process.
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spelling pubmed-75696862020-10-23 Peripheral Blood RNA Sequencing Unravels a Differential Signature of Coding and Noncoding Genes by Types of Kidney Allograft Rejection Pineda, Silvia Sur, Swastika Sigdel, Tara Nguyen, Mark Crespo, Elena Torija, Alba Meneghini, Maria Gomà, Montse Sirota, Marina Bestard, Oriol Sarwal, Minnie M. Kidney Int Rep Clinical Research INTRODUCTION: Peripheral blood (PB) molecular patterns characterizing the different effector immune pathways driving distinct kidney rejection types remain to be fully elucidated. We hypothesized that transcriptome analysis using RNA sequencing (RNAseq) in samples of kidney transplant patients would enable the identification of unique protein-coding and noncoding genes that may be able to segregate different rejection phenotypes. METHODS: We evaluated 37 biopsy-paired PB samples from the discovery cohort, with stable (STA), antibody-mediated rejection (AMR), and T cell–mediated rejection (TCMR) by RNAseq. Advanced machine learning tools were used to perform 3-way differential gene expression analysis to identify gene signatures associated with rejection. We then performed functional in silico analysis and validation by Fluidigm (San Francisco, CA) in 62 samples from 2 independent kidney transplant cohorts. RESULTS: We found 102 genes (63 coding genes and 39 noncoding genes) associated with AMR (54 upregulated), TCMR (23 upregulated), and STA (25 upregulated) perfectly clustered with each rejection phenotype and highly correlated with main histologic lesions (ρ = 0.91). For the genes associated with AMR, we found enrichment in regulation of endoplasmic reticulum stress, adaptive immunity, and Ig class-switching. In the validation, we found that the SIGLEC17P pseudogene and 9 SIGLEC17P-related coding genes were highly expressed among AMR but not in TCMR and STA samples. CONCLUSIONS: This analysis identifies a critical gene signature in PB in kidney transplant patients undergoing AMR, sufficient to differentiate them from patients with TCMR and immunologically quiescent kidney allografts. Our findings provide the basis for new studies dissecting the role of noncoding genes in the pathophysiology of kidney allograft rejection and their potential value as noninvasive biomarkers of the rejection process. Elsevier 2020-07-26 /pmc/articles/PMC7569686/ /pubmed/33102963 http://dx.doi.org/10.1016/j.ekir.2020.07.023 Text en © 2020 Published by Elsevier, Inc., on behalf of the International Society of Nephrology. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Clinical Research
Pineda, Silvia
Sur, Swastika
Sigdel, Tara
Nguyen, Mark
Crespo, Elena
Torija, Alba
Meneghini, Maria
Gomà, Montse
Sirota, Marina
Bestard, Oriol
Sarwal, Minnie M.
Peripheral Blood RNA Sequencing Unravels a Differential Signature of Coding and Noncoding Genes by Types of Kidney Allograft Rejection
title Peripheral Blood RNA Sequencing Unravels a Differential Signature of Coding and Noncoding Genes by Types of Kidney Allograft Rejection
title_full Peripheral Blood RNA Sequencing Unravels a Differential Signature of Coding and Noncoding Genes by Types of Kidney Allograft Rejection
title_fullStr Peripheral Blood RNA Sequencing Unravels a Differential Signature of Coding and Noncoding Genes by Types of Kidney Allograft Rejection
title_full_unstemmed Peripheral Blood RNA Sequencing Unravels a Differential Signature of Coding and Noncoding Genes by Types of Kidney Allograft Rejection
title_short Peripheral Blood RNA Sequencing Unravels a Differential Signature of Coding and Noncoding Genes by Types of Kidney Allograft Rejection
title_sort peripheral blood rna sequencing unravels a differential signature of coding and noncoding genes by types of kidney allograft rejection
topic Clinical Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7569686/
https://www.ncbi.nlm.nih.gov/pubmed/33102963
http://dx.doi.org/10.1016/j.ekir.2020.07.023
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