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      Effects of storage temperature, storage time, and hemolysis on the RNA quality of blood specimens: A systematic quantitative assessment

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          Abstract

          Introduction

          Blood samples are the most common biospecimen in biobanks, and RNA from such blood samples is an important material for biomedical research. High-quality RNA is essential for consistent, reliable results. Preanalytical environmental conditions can affect the quality of blood RNA. Here, we carried out a quantitative assessment of the influence of storage temperature, storage time, and hemolysis on the RNA quality of blood specimens in biobanks.

          Methods

          Before RNA purification, blood samples from volunteers were exposed to 4 °C for 2, 6, 12, 24, or 48 h, 3 days, or 1 week, or exposed to room temperature (22–30 °C) for 1, 2, 6, 12, or 24 h. Hemolyzed samples were collected from laboratory department and some of them were prepared using the freeze-thaw method. After exposure to different preanalytical environmental conditions, the RNA simple Total RNA Kit was used to purify the RNA, following which a NanoDrop™ One and Qsep 100 Bio-Fragment Analyzer were used to assess RNA concentration, purity, and integrity. In addition, a part of the RNA was immediately reverse transcribed into cDNA when it was purified, then the relative expression levels of 18S, ACTB, HIF1α, HMOX1, and MKI67 were determined by real-time quantitative PCR. Finally, 30 blood samples were collected from the surplus samples in our laboratory department to assess their RNA quality without knowledge of their storage conditions (duration/temperature).

          Results

          For blood samples stored at 4 °C, there was a significant difference between the RNA integrity after 1 week compared to after 2 h. For blood samples stored at room temperature (22–30 °C), the RNA integrity was also significantly different at 6 h and 0 h. Hemolysis caused by freeze-thawing severely affected RNA quality, whereas clinical hemolysis generally produced no significant effects. Moreover, expression of 18S, ACTB, HIF1α, HMOX1, and MKI67 in whole blood stored under different conditions showed irregular changes, suggesting that preservation conditions are also important for gene expression.

          Conclusion

          RNA integrity was qualified for blood samples stored at 4 °C for up to 72 h or at room temperature (22–30 °C) for up to 2 h. Hemolysis usually does not affect the RNA quality of blood samples unless the hemolysis method damages leukocytes.

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          Most cited references32

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          The RIN: an RNA integrity number for assigning integrity values to RNA measurements

          Background The integrity of RNA molecules is of paramount importance for experiments that try to reflect the snapshot of gene expression at the moment of RNA extraction. Until recently, there has been no reliable standard for estimating the integrity of RNA samples and the ratio of 28S:18S ribosomal RNA, the common measure for this purpose, has been shown to be inconsistent. The advent of microcapillary electrophoretic RNA separation provides the basis for an automated high-throughput approach, in order to estimate the integrity of RNA samples in an unambiguous way. Methods A method is introduced that automatically selects features from signal measurements and constructs regression models based on a Bayesian learning technique. Feature spaces of different dimensionality are compared in the Bayesian framework, which allows selecting a final feature combination corresponding to models with high posterior probability. Results This approach is applied to a large collection of electrophoretic RNA measurements recorded with an Agilent 2100 bioanalyzer to extract an algorithm that describes RNA integrity. The resulting algorithm is a user-independent, automated and reliable procedure for standardization of RNA quality control that allows the calculation of an RNA integrity number (RIN). Conclusion Our results show the importance of taking characteristics of several regions of the recorded electropherogram into account in order to get a robust and reliable prediction of RNA integrity, especially if compared to traditional methods.
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            Comparison of relative mRNA quantification models and the impact of RNA integrity in quantitative real-time RT-PCR.

            Relative quantification in quantitative real-time RT-PCR is increasingly used to quantify gene expression changes. In general, two different relative mRNA quantification models exist: the delta-delta Ct and the efficiency-corrected Ct model. Both models have their advantages and disadvantages in terms of simplification on the one hand and efficiency correction on the other. The particular problem of RNA integrity and its effect on relative quantification in qRT-PCR performance was tested in different bovine tissues and cell lines (n = 11). Therefore different artificial and standardized RNA degradation levels were used. Currently fully automated capillary electrophoresis systems have become the new standard in RNA quality assessment. RNA quality was rated according the RNA integrity number (RIN). Furthermore, the effect of different length of amplified products and RNA integrity on expression analyses was investigated. We found significant impact of RNA integrity on relative expression results, mainly on cycle threshold (Ct) values and a minor effect on PCR efficiency. To minimize the interference of RNA integrity on relative quantification models, we can recommend to normalize gene expression by an internal reference gene and to perform an efficiency correction. Results demonstrate that innovative new quantification methods and normalization models can improve future mRNA quantification.
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              A blood based 12-miRNA signature of Alzheimer disease patients

              Background Alzheimer disease (AD) is the most common form of dementia but the identification of reliable, early and non-invasive biomarkers remains a major challenge. We present a novel miRNA-based signature for detecting AD from blood samples. Results We apply next-generation sequencing to miRNAs from blood samples of 48 AD patients and 22 unaffected controls, yielding a total of 140 unique mature miRNAs with significantly changed expression levels. Of these, 82 have higher and 58 have lower abundance in AD patient samples. We selected a panel of 12 miRNAs for an RT-qPCR analysis on a larger cohort of 202 samples, comprising not only AD patients and healthy controls but also patients with other CNS illnesses. These included mild cognitive impairment, which is assumed to represent a transitional period before the development of AD, as well as multiple sclerosis, Parkinson disease, major depression, bipolar disorder and schizophrenia. miRNA target enrichment analysis of the selected 12 miRNAs indicates an involvement of miRNAs in nervous system development, neuron projection, neuron projection development and neuron projection morphogenesis. Using this 12-miRNA signature, we differentiate between AD and controls with an accuracy of 93%, a specificity of 95% and a sensitivity of 92%. The differentiation of AD from other neurological diseases is possible with accuracies between 74% and 78%. The differentiation of the other CNS disorders from controls yields even higher accuracies. Conclusions The data indicate that deregulated miRNAs in blood might be used as biomarkers in the diagnosis of AD or other neurological diseases.
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                Author and article information

                Contributors
                Journal
                Heliyon
                Heliyon
                Heliyon
                Elsevier
                2405-8440
                24 May 2023
                June 2023
                24 May 2023
                : 9
                : 6
                : e16234
                Affiliations
                [a ]Biobank, Jiangxi Provincial Children's Hospital, Nanchang, China
                [b ]Central Laboratory, Jiangxi Provincial Children's Hospital, Nanchang, China
                [c ]Pediatric Heart Disease Treatment Center, Jiangxi Provincial Children's Hospital, Nanchang, China
                Author notes
                []Corresponding author. jxsetyyhjy@ 123456163.com
                [∗∗ ]Corresponding author. yeduanjk@ 123456163.com
                [1]

                These authors contributed equally to this work.

                Article
                S2405-8440(23)03441-2 e16234
                10.1016/j.heliyon.2023.e16234
                10227325
                389b4ba2-5afd-43fd-b53a-5344af0774a5
                © 2023 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 28 November 2022
                : 5 May 2023
                : 10 May 2023
                Categories
                Research Article

                blood sample,rna integrity,preanalytical variables
                blood sample, rna integrity, preanalytical variables

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