Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/136070
Citations | ||
Scopus | Web of Science® | Altmetric |
---|---|---|
?
|
?
|
Type: | Journal article |
Title: | Haemolysis Detection in MicroRNA-Seq from Clinical Plasma Samples |
Author: | Smith, M.D. Leemaqz, S.Y. Jankovic-Karasoulos, T. McAninch, D. McCullough, D. Breen, J. Roberts, C.T. Pillman, K.A. |
Citation: | Genes, 2022; 13(7):1288-1-1288-15 |
Publisher: | MDPI AG |
Issue Date: | 2022 |
ISSN: | 2073-4425 2073-4425 |
Statement of Responsibility: | Melanie D. Smith, Shalem Y. Leemaqz, Tanja Jankovic-Karasoulos, Dale McAninch, Dylan McCullough, James Breen, Claire T. Roberts, and Katherine A. Pillman |
Abstract: | The abundance of cell-free microRNA (miRNA) has been measured in blood plasma and proposed as a source of novel, minimally invasive biomarkers for several diseases. Despite improvements in quantification methods, there is no consensus regarding how haemolysis affects plasma miRNA content. We propose a method for haemolysis detection in miRNA high-throughput sequencing (HTS) data from libraries prepared using human plasma. To establish a miRNA haemolysis signature we tested differential miRNA abundance between plasma samples with known haemolysis status. Using these miRNAs with statistically significant higher abundance in our haemolysed group, we further refined the set to reveal high-confidence haemolysis association. Given our specific context, i.e., women of reproductive age, we also tested for significant differences between pregnant and nonpregnant groups. We report a novel 20-miRNA signature used to identify the presence of haemolysis in silico in HTS miRNA-sequencing data. Further, we validated the signature set using firstly an all-male cohort (prostate cancer) and secondly a mixed male and female cohort (radiographic knee osteoarthritis). Conclusion: Given the potential for haemolysis contamination, we recommend that assays for haemolysis detection become standard pre-analytical practice and provide here a simple method for haemolysis detection. |
Keywords: | microRNA; plasma; biomarker; prediction; haemolysis; bioinformatics |
Rights: | © 2022 by the authors. 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/). |
DOI: | 10.3390/genes13071288 |
Grant ID: | http://purl.org/au-research/grants/nhmrc/GNT1174971 |
Published version: | http://dx.doi.org/10.3390/genes13071288 |
Appears in Collections: | Medicine publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
hdl_136070.pdf | Published version | 1.32 MB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.