| Literature DB >> 28955906 |
Helle Glud Binderup1, Kim Houlind2,3, Jonna Skov Madsen1,3, Claus Lohman Brasen1.
Abstract
BACKGROUND: In the past few years, an increasing number of studies have reported the potential use of microRNAs (miRNA) as circulating biomarkers for diagnosis or prognosis of a wide variety of diseases. There is, however, a lack of reproducibility between studies. Due to the high miRNA content in platelets this may partly be explained by residual platelets in the plasma samples used. When collecting fresh plasma samples, it is possible to produce cell-free/platelet-poor plasma by centrifugation. In this study, we systematically investigated whether biobanked EDTA plasma samples could be processed to be suitable for miRNA analysis.Entities:
Keywords: Biobanking; Centrifugation; MicroRNA; PPP, platelet-poor-plasma; Preanalytical conditions; RT-qPCR, reverse transcription polymerase chain reaction; Residual platelets; °C, degrees Celcius
Year: 2016 PMID: 28955906 PMCID: PMC5613297 DOI: 10.1016/j.bbrep.2016.06.005
Source DB: PubMed Journal: Biochem Biophys Rep ISSN: 2405-5808
Fig. 1Schematic overview over the different plasma preparations. A total of 10 mL of whole blood was used for the preparation of platelet poor plasma (PPP). Two tubes of 10 mL whole blood were handled according to our laboratory protocol for preparation of biobank plasma. Plasma from one of the tubes was frozen for one week, thawed and further processed to eliminate platelet contamination (biobank A, A2, B and B2). As illustrated, after freezing and thawing of the biobank plasma we denote it biobank A. Plasma from the other tube was pipetted from the top of the tube mL by mL to investigate the distribution of platelets in the plasma phase (gradient A–D).
Fig. 2Residual platelet count in the different plasma preparations. Platelet count in the different plasma preparations from the 10 volunteers. It can be seen that the platelet count is relatively high and vary significantly in the biobank (equals biobank A, but has not been frozen) and 3000 g for 15 min preparations, and that the biobank B preparations still contain some platelets. After further processing of the samples the platelet count was 0–1×109/L in all PPP, all biobank B2 and six of the biobank A2 samples.
Fig. 3Platelet count in the four gradient samples from each of ten volunteers. For each of the ten volunteers are plotted the median platelet count of the four gradient samples A–D, and the lines illustrates the minimum and maximum value. The highest platelet count in samples from volunteer 3 and 7 were seen in gradient D, which is the plasma phase just above the buffy coat.
MiRNA levels in the different plasma preparations relative to PPP.
| MicroRNA | Plasma type | Normalized to cel-mir-39 | Normalized to miR-16 | ||
|---|---|---|---|---|---|
| Average fold change from PPP | P-value | Average fold change from PPP | P-value | ||
| miR-142–3p | Biobank A | 37.3 | <0.01 | 11.0 | <0.01 |
| BiobankA2 | 5.2 | <0.05 | 2.8 | <0.05 | |
| Biobank B | 4.7 | <0.01 | 5.8 | <0.01 | |
| BiobankB2 | 4.1 | <0.01 | 2.4 | <0.01 | |
| miR-145 | Biobank A | 68.4 | <0.01 | 22.5 | <0.01 |
| BiobankA2 | 4.9 | <0.05 | 2.3 | <0.05 | |
| Biobank B | 6.6 | <0.01 | 6.2 | <0.01 | |
| BiobankB2 | 3.0 | <0.01 | 1.8 | <0.01 | |
| miR-16 | Biobank A | 2.6 | <0.01 | ||
| BiobankA2 | 1.9 | <0.05 | |||
| Biobank B | 1.2 | 0.43 | |||
| BiobankB2 | 1.6 | <0.01 | |||
| miR-26a | Biobank A | 92.3 | <0.01 | 24.1 | <0.01 |
| BiobankA2 | 2.4 | <0.05 | 0.9 | 0.35 | |
| Biobank B | 9.2 | <0.01 | 7.2 | <0.01 | |
| BiobankB2 | 1.4 | 0.56 | 0.7 | <0.05 | |
| miR-28 | Biobank A | 102.5 | <0.01 | 34.2 | <0.01 |
| BiobankA2 | 13.2 | <0.05 | 6.8 | <0.05 | |
| Biobank B | 9.3 | <0.01 | 7.9 | <0.01 | |
| BiobankB2 | 6.3 | <0.01 | 3.0 | <0.01 | |
| miR-301 | Biobank A | 84.0 | <0.01 | 24.4 | <0.01 |
| BiobankA2 | 14.2 | <0.05 | 6.2 | <0.05 | |
| Biobank B | 11.8 | <0.01 | 8.4 | <0.01 | |
| BiobankB2 | 13.0 | <0.01 | 5.9 | <0.01 | |
| miR-30a-5p | Biobank A | 9.8 | <0.01 | 4.7 | <0.01 |
| BiobankA2 | 3.7 | <0.05 | 2.2 | 0.17 | |
| Biobank B | 2.5 | <0.05 | 2.8 | <0.01 | |
| BiobankB2 | 2.4 | <0.01 | 1.7 | <0.01 | |
| miR-30d | Biobank A | 14.9 | <0.01 | 5.7 | <0.01 |
| BiobankA2 | 2.8 | <0.05 | 1.4 | 0.25 | |
| Biobank B | 3.8 | <0.01 | 4.0 | <0.01 | |
| BiobankB2 | 2.4 | <0.01 | 1.4 | <0.01 | |
| miR-328 | Biobank A | 94.1 | <0.01 | 30.7 | <0.01 |
| BiobankA2 | 368 | <0.05 | 233 | <0.05 | |
| Biobank B | 23.0 | <0.01 | 16.9 | <0.01 | |
| BiobankB2 | 97.4 | <0.01 | 53.6 | <0.01 | |
| miR-331 | Biobank A | 63.5 | <0.01 | 20.9 | <0.01 |
| BiobankA2 | 113.1 | <0.05 | 48.9 | <0.05 | |
| Biobank B | 8.4 | <0.01 | 6.6 | <0.01 | |
| BiobankB2 | 55.8 | <0.01 | 31.3 | <0.01 | |
| miR-335 | Biobank A | 95.1 | <0.01 | 28.4 | <0.01 |
| BiobankA2 | 26.9 | <0.05 | 11.4 | <0.05 | |
| Biobank B | 17.1 | <0.01 | 14.4 | <0.01 | |
| BiobankB2 | 19.1 | <0.01 | 9.3 | <0.01 | |
| miR-340 | Biobank A | 53.7 | <0.01 | 18.4 | <0.01 |
| BiobankA2 | 8.3 | <0.05 | 4.1 | <0.05 | |
| Biobank B | 11.4 | <0.01 | 10.5 | <0.01 | |
| BiobankB2 | 5.2 | <0.01 | 3.8 | <0.01 | |
| miR-92a | Biobank A | 8.4 | <0.01 | 2.7 | <0.01 |
| BiobankA2 | 13.8 | <0.05 | 6.5 | <0.05 | |
| Biobank B | 2.5 | <0.05 | 2.1 | <0.01 | |
| BiobankB2 | 8.6 | <0.01 | 3.9 | <0.01 | |
| miR-93 | Biobank A | 13.1 | <0.01 | 4.3 | <0.01 |
| BiobankA2 | 4.9 | <0.05 | 2.6 | <0.05 | |
| Biobank B | 3.5 | <0.01 | 2.8 | <0.01 | |
| BiobankB2 | 3.8 | <0.01 | 1.9 | <0.01 | |
Average fold change in miRNA level relative to PPP are given for biobank A, A2, B and B2 samples. MiRNA levels are normalized to cel-miR-39 and miR-16, respectively. Biobank A preparations represent the standard biobank plasma (centrifuged at 2000 g for 10 min) after one freezing/thawing cycle. P-values were calculated using the Wilcoxon signed rank test, and were considered significant if <0.05.