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Capturing the Kidney Transcriptome by Urinary Extracellular Vesicles—From Pre-Analytical Obstacles to Biomarker Research
Urinary extracellular vesicles (uEV) hold non-invasive RNA biomarkers for genitourinary tract diseases. However, missing knowledge about reference genes and effects of preanalytical choices hinder biomarker studies. We aimed to assess how preanalytical variables (urine storage temperature, isolation...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10379145/ https://www.ncbi.nlm.nih.gov/pubmed/37510317 http://dx.doi.org/10.3390/genes14071415 |
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author | Barreiro, Karina Dwivedi, Om Prakash Rannikko, Antti Holthöfer, Harry Tuomi, Tiinamaija Groop, Per-Henrik Puhka, Maija |
author_facet | Barreiro, Karina Dwivedi, Om Prakash Rannikko, Antti Holthöfer, Harry Tuomi, Tiinamaija Groop, Per-Henrik Puhka, Maija |
author_sort | Barreiro, Karina |
collection | PubMed |
description | Urinary extracellular vesicles (uEV) hold non-invasive RNA biomarkers for genitourinary tract diseases. However, missing knowledge about reference genes and effects of preanalytical choices hinder biomarker studies. We aimed to assess how preanalytical variables (urine storage temperature, isolation workflow) affect diabetic kidney disease (DKD)—linked miRNAs or kidney—linked miRNAs and mRNAs (kidney-RNAs) in uEV isolates and to discover stable reference mRNAs across diverse uEV datasets. We studied nine raw and normalized sequencing datasets including healthy controls and individuals with prostate cancer or type 1 diabetes with or without albuminuria. We focused on kidney-RNAs reviewing literature for DKD-linked miRNAs from kidney tissue, cell culture and uEV/urine experiments. RNAs were analyzed by expression heatmaps, hierarchical clustering and selecting stable mRNAs with normalized counts (>200) and minimal coefficient of variation. Kidney-RNAs were decreased after urine storage at −20 °C vs. −80 °C. Isolation workflows captured kidney-RNAs with different efficiencies. Ultracentrifugation captured DKD -linked miRNAs that separated healthy and diabetic macroalbuminuria groups. Eleven mRNAs were stably expressed across the datasets. Hence, pre-analytical choices had variable effects on kidney-RNAs—analyzing kidney-RNAs complemented global correlation, which could fade differences in some relevant RNAs. Replicating prior DKD-marker results and discovery of candidate reference mRNAs encourages further uEV biomarker studies. |
format | Online Article Text |
id | pubmed-10379145 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-103791452023-07-29 Capturing the Kidney Transcriptome by Urinary Extracellular Vesicles—From Pre-Analytical Obstacles to Biomarker Research Barreiro, Karina Dwivedi, Om Prakash Rannikko, Antti Holthöfer, Harry Tuomi, Tiinamaija Groop, Per-Henrik Puhka, Maija Genes (Basel) Article Urinary extracellular vesicles (uEV) hold non-invasive RNA biomarkers for genitourinary tract diseases. However, missing knowledge about reference genes and effects of preanalytical choices hinder biomarker studies. We aimed to assess how preanalytical variables (urine storage temperature, isolation workflow) affect diabetic kidney disease (DKD)—linked miRNAs or kidney—linked miRNAs and mRNAs (kidney-RNAs) in uEV isolates and to discover stable reference mRNAs across diverse uEV datasets. We studied nine raw and normalized sequencing datasets including healthy controls and individuals with prostate cancer or type 1 diabetes with or without albuminuria. We focused on kidney-RNAs reviewing literature for DKD-linked miRNAs from kidney tissue, cell culture and uEV/urine experiments. RNAs were analyzed by expression heatmaps, hierarchical clustering and selecting stable mRNAs with normalized counts (>200) and minimal coefficient of variation. Kidney-RNAs were decreased after urine storage at −20 °C vs. −80 °C. Isolation workflows captured kidney-RNAs with different efficiencies. Ultracentrifugation captured DKD -linked miRNAs that separated healthy and diabetic macroalbuminuria groups. Eleven mRNAs were stably expressed across the datasets. Hence, pre-analytical choices had variable effects on kidney-RNAs—analyzing kidney-RNAs complemented global correlation, which could fade differences in some relevant RNAs. Replicating prior DKD-marker results and discovery of candidate reference mRNAs encourages further uEV biomarker studies. MDPI 2023-07-08 /pmc/articles/PMC10379145/ /pubmed/37510317 http://dx.doi.org/10.3390/genes14071415 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Barreiro, Karina Dwivedi, Om Prakash Rannikko, Antti Holthöfer, Harry Tuomi, Tiinamaija Groop, Per-Henrik Puhka, Maija Capturing the Kidney Transcriptome by Urinary Extracellular Vesicles—From Pre-Analytical Obstacles to Biomarker Research |
title | Capturing the Kidney Transcriptome by Urinary Extracellular Vesicles—From Pre-Analytical Obstacles to Biomarker Research |
title_full | Capturing the Kidney Transcriptome by Urinary Extracellular Vesicles—From Pre-Analytical Obstacles to Biomarker Research |
title_fullStr | Capturing the Kidney Transcriptome by Urinary Extracellular Vesicles—From Pre-Analytical Obstacles to Biomarker Research |
title_full_unstemmed | Capturing the Kidney Transcriptome by Urinary Extracellular Vesicles—From Pre-Analytical Obstacles to Biomarker Research |
title_short | Capturing the Kidney Transcriptome by Urinary Extracellular Vesicles—From Pre-Analytical Obstacles to Biomarker Research |
title_sort | capturing the kidney transcriptome by urinary extracellular vesicles—from pre-analytical obstacles to biomarker research |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10379145/ https://www.ncbi.nlm.nih.gov/pubmed/37510317 http://dx.doi.org/10.3390/genes14071415 |
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