Literature DB >> 28873014

Impact of Preanalytical Variations in Blood-Derived Biospecimens on Omics Studies: Toward Precision Biobanking?

Jae-Eun Lee1, Young-Youl Kim1.   

Abstract

Research data and outcomes do vary across populations and persons, but this is not always due to experimental or true biological variation. Preanalytical components of experiments, be they biospecimen acquisition, preparation, storage, or transportation to the laboratory, may all contribute to apparent variability in research data, outcomes, and interpretation. The present review article and biobanking innovation analysis offer new insights with a summary of such preanalytical variables, for example, the type of blood collection tube, centrifugation conditions, long-term sample storage temperature, and duration, on output of omics analyses of blood-derived biospecimens: whole blood, serum, plasma, buffy coat, and peripheral blood mononuclear cells. Furthermore, we draw parallels from the field of precision medicine in this study, with a view to the future of "precision biobanking" wherein such preanalytical variations are carefully taken into consideration so as to minimize their influence on outcomes of omics data, analyses, and sensemaking, particularly in clinical omics applications. We underscore the need for using broadly framed, critical, independent, social and political science, and humanities research so as to understand the multiple possible future trajectories of, and the motivations and values embedded in, precision biobanking that is increasingly relevant in the current age of Big Data.

Entities:  

Keywords:  Big Data; blood-derived biospecimens; multi-omics; preanalytical variation; precision biobanking

Mesh:

Year:  2017        PMID: 28873014     DOI: 10.1089/omi.2017.0109

Source DB:  PubMed          Journal:  OMICS        ISSN: 1536-2310


  10 in total

Review 1.  Data integration strategies for predictive analytics in precision medicine.

Authors:  Lewis J Frey
Journal:  Per Med       Date:  2018-11-02       Impact factor: 2.512

2.  How Should Biobanks Prioritize and Diversify Biosample Collections? A 40-Year Scientific Publication Trend Analysis by the Type of Biosample.

Authors:  Jae-Eun Lee; Young-Youl Kim
Journal:  OMICS       Date:  2018-03-27

Review 3.  Omics for the future in asthma.

Authors:  Mahmoud I Abdel-Aziz; Anne H Neerincx; Susanne J Vijverberg; Aletta D Kraneveld; Anke H Maitland-van der Zee
Journal:  Semin Immunopathol       Date:  2020-01-15       Impact factor: 9.623

4.  Impact of Time Delay in Processing Blood Sample on Next Generation Sequencing for Transcriptome Analysis.

Authors:  Jae-Eun Lee; So-Young Jung; So-Youn Shin; Young-Youl Kim
Journal:  Osong Public Health Res Perspect       Date:  2018-06

5.  Impact of long-term storage and freeze-thawing on eight circulating microRNAs in plasma samples.

Authors:  Pamela R Matias-Garcia; Rory Wilson; Veronika Mussack; Eva Reischl; Melanie Waldenberger; Christian Gieger; Gabriele Anton; Annette Peters; Andrea Kuehn-Steven
Journal:  PLoS One       Date:  2020-01-14       Impact factor: 3.240

6.  Effect of serum sample storage temperature on metabolomic and proteomic biomarkers.

Authors:  Erkka Valo; Marco Colombo; Niina Sandholm; Stuart J McGurnaghan; Luke A K Blackbourn; David B Dunger; Paul M McKeigue; Carol Forsblom; Per-Henrik Groop; Helen M Colhoun; Charles Turner; R Neil Dalton
Journal:  Sci Rep       Date:  2022-03-17       Impact factor: 4.379

7.  Circular RNAs in peripheral blood mononuclear cells are more stable than linear RNAs upon sample processing delay.

Authors:  Guoxia Wen; Wanjun Gu
Journal:  J Cell Mol Med       Date:  2022-08-30       Impact factor: 5.295

8.  Comparison of miRNA quantitation by Nanostring in serum and plasma samples.

Authors:  Catherine Foye; Irene K Yan; Waseem David; Neha Shukla; Yacob Habboush; Lori Chase; Kristen Ryland; Vivek Kesari; Tushar Patel
Journal:  PLoS One       Date:  2017-12-06       Impact factor: 3.240

9.  How Should Biobanks Collect Biosamples for Clinical Application? A 20-year Biomarker-related Publication and Patent Trend Analysis.

Authors:  Jae-Eun Lee
Journal:  Osong Public Health Res Perspect       Date:  2018-06

Review 10.  A Checklist for Reproducible Computational Analysis in Clinical Metabolomics Research.

Authors:  Xinsong Du; Juan J Aristizabal-Henao; Timothy J Garrett; Mathias Brochhausen; William R Hogan; Dominick J Lemas
Journal:  Metabolites       Date:  2022-01-17
  10 in total

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