SynthesisPloS one2015
A Computational Gene Expression Score for Predicting Immune Injury in Renal Allografts.
Synthesis in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02776111 (The Use of Microfluidics and Transcriptomics to Implement Precision Medicine in Post Solid Organ Transplant Patients), which is not on this map. Cited by 27 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
The Use of Microfluidics and Transcriptomics to Implement Precision Medicine in Post Solid Organ Transplant Patients
Who cites it
27 citing papers in PubMed, 47 citations in OpenAlex.
- Avoidance of CNI and steroids using belatacept-Results of the Clinical Trials in Organ Transplantation 16 trial.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2020Trial
- Exploring the functions of NKG7 in CD4+ and CD8+ T cells during malaria.PLoS pathogens · 2026Article
- Gene expression-based molecular scoring of pancreas transplant rejection for a quantitative assessment of rejection severity and resistance to treatment.American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons · 2025Article
- Runt-related transcription factors: from pathogenesis to therapeutic targets in multiple-organ fibrosis.Frontiers in cell and developmental biology · 2025Review
- RUNX3-activated apelin signaling inhibits cell proliferation and fibrosis in diabetic nephropathy by regulation of the SIRT1/FOXO pathway.Diabetology & metabolic syndrome · 2024Article
- Contemporary Biomarkers for Renal Transplantation: A Narrative Overview.Journal of personalized medicine · 2023Review
- Identification of Genes Associated with Decreasing Abundance of Monocytes in Long-Term Peritoneal Dialysis Patients.International journal of general medicine · 2023Article
- Molecular immune monitoring in kidney transplant rejection: a state-of-the-art review.Frontiers in immunology · 2023Review
- Markers of Bronchiolitis Obliterans Syndrome after Lung Transplant: Between Old Knowledge and Future Perspective.Biomedicines · 2022Review
- Identification of key biomarkers and immune infiltration in renal interstitial fibrosis.Annals of translational medicine · 2022Article
- T Cells With ActivatedFrontiers in immunology · 2022Article
- Can Gene Expression Analysis in Zero-Time Biopsies Predict Kidney Transplant Rejection?Frontiers in medicine · 2022Article
- Molecular Diversity of Clinically Stable Human Kidney Allografts.JAMA network open · 2021Article
- Tackling Chronic Kidney Transplant Rejection: Challenges and Promises.Frontiers in immunology · 2021Review
- Technical considerations when designing a gene expression panel for renal transplant diagnosis.Scientific reports · 2020Article
- Bioinformatics analyses on the immune status of renal transplant patients, a systemic research of renal transplantation.BMC medical genomics · 2020Article
- Use of the Tissue Common Rejection Module Score in Kidney Transplant as an Objective Measure of Allograft Inflammation.Frontiers in immunology · 2020Article
- Advances in Detection of Kidney Transplant Injury.Molecular diagnosis & therapy · 2019Review
- A urinary Common Rejection Module (uCRM) score for non-invasive kidney transplant monitoring.PloS one · 2019Article
- Assessment of 19 Genes and Validation of CRM Gene Panel for Quantitative Transcriptional Analysis of Molecular Rejection and Inflammation in Archival Kidney Transplant Biopsies.Frontiers in medicine · 2019Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundWhole genome microarray meta-analyses of 1030 kidney, heart, lung and liver allograft biopsies identified a common immune response module (CRM) of 11 genes that define acute rejection (AR) across different engrafted tissues. We evaluated if the CRM genes can provide a molecular microscope to quantify graft injury in acute rejection (AR) and predict risk of progressive interstitial fibrosis and tubular atrophy (IFTA) in histologically normal kidney biopsies.
methodsComputational modeling was done on tissue qPCR based gene expression measurements for the 11 CRM genes in 146 independent renal allografts from 122 unique patients with AR (n = 54) and no-AR (n = 92). 24 demographically matched patients with no-AR had 6 and 24 month paired protocol biopsies; all had histologically normal 6 month biopsies, and 12 had evidence of progressive IFTA (pIFTA) on their 24 month biopsies. Results were correlated with demographic, clinical and pathology variables.
resultsThe 11 gene qPCR based tissue CRM score (tCRM) was significantly increased in AR (5.68 ± 0.91) when compared to STA (1.29 ± 0.28; p < 0.001) and pIFTA (7.94 ± 2.278 versus 2.28 ± 0.66; p = 0.04), with greatest significance for CXCL9 and CXCL10 in AR (p <0.001) and CD6 (p<0.01), CXCL9 (p<0.05), and LCK (p<0.01) in pIFTA. tCRM was a significant independent correlate of biopsy confirmed AR (p < 0.001; AUC of 0.900; 95% CI = 0.705-903). Gene expression modeling of 6 month biopsies across 7/11 genes (CD6, INPP5D, ISG20, NKG7, PSMB9, RUNX3, and TAP1) significantly (p = 0.037) predicted the development of pIFTA at 24 months.
conclusionsGenome-wide tissue gene expression data mining has supported the development of a tCRM-qPCR based assay for evaluating graft immune inflammation. The tCRM score quantifies injury in AR and stratifies patients at increased risk of future pIFTA prior to any perturbation of graft function or histology.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.