Comparing plasma donor-derived cell-free DNA to gene expression in endomyocardial biopsies in the Trifecta-Heart study.
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PROVIDER: PRJNA1137896 | ENA |
REPOSITORIES: ENA
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Project description:Background. Plasma donor-derived cell-free DNA (dd-cfDNA) is used to screen for rejection in heart transplants. We launched the Trifecta-Heart (ClinicalTrials.gov #NCT04707872), an investigator-initiated, prospective trial, to examine the correlations between genome-wide molecular changes in endomyocardial biopsies (EMBs) and plasma dd-cfDNA. The present report analyzes the correlation of plasma dd-cfDNA with the gene expression in EMBs from 4 vanguard centers and compared these correlations with those in 604 kidney transplant biopsies in the Trifecta-Kidney study (ClinicalTrials.gov #NCT04239703). Results. Top transcripts correlating with dd-cfDNA were related to genes increased in rejection such as IFNG-inducible genes (e.g., HLA-DMA), but also with genes induced by injury and expressed in macrophages (e.g., SERPINA1, HMOX1). In gene enrichment analysis, the top dd-cfDNA-correlated genes reflected inflammation and rejection pathways. Dd-cfDNA correlations with rejection genes in EMB were similar to those seen in kidney transplant biopsies, with somewhat stronger correlations for TCMR genes in hearts and ABMR genes in kidneys. However, the correlations with parenchymal injury-induced genes and macrophage genes were much stronger in hearts. Conclusions: In heart transplants in the Trifecta-Heart study, dd-cfDNA correlates significantly with molecular rejection but also with injury and macrophage infiltration, reflecting the proinflammatory properties of injured cardiomyocytes. The relationship supports the utility of dd-cfDNA in the clinical management of heart transplant recipients.
2024-07-19 | GSE272655 | GEO
Project description:The Trifecta study: comparing plasma donor-derived cell-free DNA levels with the molecular phenotype of kidney transplant biopsies
| PRJNA791412 | ENA
Project description:Background. The Trifecta study (ClinicalTrials.gov #NCT04239703) is a prospective investigator-initiated trial to evaluate the relationship between plasma %dd-cfDNA at the time of indication biopsy and the molecular phenotype of the biopsy. Results. Median time of biopsy post-transplant was 455 days (5 days - 32 years), with case-mix similar to previous studies: 180 (60%) no rejection, 89 (30%) antibody-mediated rejection (ABMR), and 31 (10%) T cell-mediated rejection (TCMR) and mixed. In genome-wide mRNA measurements, all 20 top probesets correlating with %dd-cfDNA were previously annotated for association with ABMR and all rejection, either NK cell-expressed (e.g. GNLY, CCL4, TRDC, and S1PR5) or IFNG-inducible (e.g. PLA1A, IDO1, CXCL11, and WARS). Among gene set and classifier scores, %dd-cfDNA correlated very strongly with ABMR and all rejection, reasonably strongly with active TCMR, and weakly with inactive TCMR, kidney injury and atrophy-fibrosis. %dd-cfDNA was highest in active ABMR, mixed, and active TCMR but lower in late-stage ABMR and less active TCMR. By multivariate random forests and logistic regression, molecular rejection variables predicted %dd-cfDNA better than histologic variables. Conclusions. %dd-cfDNA at time of indication biopsy strongly correlates with active molecular rejection and has potential to reduce unnecessary biopsies.
2021-12-23 | GSE192444 | GEO
Project description:Background: Among all biopsies in the Trifecta kidney study (ClinicalTrials.gov #NCT04239703), elevated plasma dd-cfDNA correlated most strongly with molecular antibody-mediated rejection (ABMR) (JASN 33:387, 2022), but was also elevated in other states: T cell-mediated rejection (TCMR), acute kidney injury (AKI), and some apparently normal biopsies. The present study aimed to define the molecular correlates of plasma dd-cfDNA within specific states. Results: In all 604 biopsies, dd-cfDNA was elevated in ABMR, TCMR, and AKI. Within ABMR biopsies, dd-cfDNA correlated with ABMR activity and stage. Within AKI, the correlations reflected acute parenchymal injury, including cell cycling. Within biopsies classified as NRNI, dd-cfDNA still correlated significantly with rejection- and injury-related genes. TCMR activity (e.g., the TCMRProb classifier) correlated with dd-cfDNA, but within TCMR biopsies, top gene correlations were complex and not the top TCMR-selective genes. Conclusions. In kidney transplants, elevated plasma dd-cfDNA is associated with three distinct molecular states in the donor tissue: ABMR, recent parenchymal injury, including cell cycling, and TCMR, potentially complicated by parenchymal disruption. Moreover, subtle rejection- and injury-related changes in the donor tissue can contribute to dd-cfDNA elevations in transplants considered to have no rejection or injury.
2025-08-22 | GSE305222 | GEO
Project description: Not available
| S-EPMC8819982 | biostudies-literature
Project description:Liquid biopsies provide a means for the profiling of cell-free RNAs secreted by cells throughout the body. Although well-annotated coding and noncoding transcripts in blood are readily detectable and can serve as biomarkers of disease, the overall diagnostic utility of the cell-free transcriptome remains unclear. Here we show that transposable elements and other repeat RNA elements are enriched in the cell-free transcriptome of patients with cancer, and that they serve as signatures for the accurate classification of the disease. We used repeat-element-aware sequencing and analysis technology and single-molecule nanopore sequencing to profile the cell-free transcriptome in plasma from patients with cancer and to examine millions of genomic features comprised of all annotated genes and of repeat elements throughout the genome. By aggregating individual repeat elements to the subfamily level, we found that samples with pancreatic cancer are enriched with specific Alu subfamilies, whereas other cancers exhibit their own characteristic cell-free RNA profile. Our findings show that repetitive RNA sequences are abundant in blood and can be used as disease-specific diagnostic biomarkers.
2023-09-01 | GSE136651 | GEO
Project description:Donor organ shortage, growing waiting lists and organ discard rates are key problems in kidney transplantation. Donor organ quality is a critical factor determining post-transplant graft outcomes. However, organ quality is difficult to predict. Balancing the use of marginal donors without affecting outcomes is a main issue in the transplant field. The decision of acceptance of a kidney organ for transplantation is mainly based on donor organ biopsy findings, even though there are recognized limitations. The lack of better measures of organ quality at the time of transplantation as a predictor of performance graft outcome is a serious clinical challenge. Herein, we propose the use of a limited set of genes that captures intrinsic biology of kidney donor organs to improve available scoring systems. We studied gene expression in 192 deceased donor kidney biopsies and evaluated short-term outcomes which included delayed graft function and eGFR (high versus low) at 24 months for 168 kidney transplant recipients.
2022-06-13 | GSE147451 | GEO
Project description:Liquid biopsies that measure circulating cell-free RNA (cfRNA) offer an unprecedented opportunity to noninvasively study the development of pregnancy-related complications and to bridge gaps in clinical care. Here, we sequenced cfRNA from 404 blood plasma samples (199 pregnant mothers) to identify and validate cfRNA transcriptomic changes that are associated with preeclampsia (PE), a multi-organ syndrome which is the second largest cause of maternal death globally. For each individual, samples were collected at one or more timepoints across gestation. For some, samples were also collected at least once post-partum.
2022-01-03 | GSE192902 | GEO
Project description:Gene expression in donor kidney biopsies prior to kidney transplantation
| PRJNA614905 | ENA
Project description:summary : Tubulointerstitial transcriptome from ERCB subjects with chronic kidney disease and living donor biopsies. Samples included in this analysis have been previously analyzed using older CDF definitions and are included under previous GEO submissions - GSE47184 (chronic kidney disease samples), and GSE32591 (IgA nephropathy samples).
2018-01-24 | GSE104954 | GEO