A New Plasma Quality Control Assay
A New Plasma Quality Control Assay
Researchers from IBBL (Integrated BioBank of Luxembourg) and the Luxembourg Centre for Systems Biomedicine (LCSB) of the University of Luxembourg have investigated the impact of variations in temperature and delays during blood sample processing on downstream metabolomics applications. Based on these results, they developed a quality control (QC) assay that will enable researchers to assess the quality of plasma samples and their suitability for metabolomics research.(1)
To ensure they are using biological samples of good quality for their analyses, researchers rely on two main options. For studies with prospective sample collections, they can use Standardised Operating Procedures (SOP) that cover all the pre-analytical steps. Before starting the sample collection, these procedures should be validated for their robustness and reproducibility. In addition, these samples should be annotated with the SPREC (Standard PRE-analytical Code), which enables any researcher using the samples in the future to trace back the pre-analytical steps.
Alternatively, if a researcher wants to use an existing sample collection that is not annotated with SPREC and thus of unknown quality, he/she can employ quality control (QC) assays. There are thousands of these legacy collections stored at biobanks and laboratories all across the world. These legacy collections have enormous potential value, if appropriate quality control assays exist to determine whether these samples are of good enough quality for researchers to use them without potentially compromising their results. While a number of QC assays have already been described(2), there are big gaps and QC assessments for certain sample types and certain downstream applications are not available.
The main goal of the research team at IBBL (Integrated BioBank of Luxembourg) is to study the impact of pre-analytical variations on downstream analyses and to discover and validate markers for biospecimen quality control. For one of its QC marker projects, IBBL has teamed up with the metabolomics research group at the Luxembourg Centre for Systems Biomedicine (LCSB) of the University of Luxembourg to benefit from its complementary expertise and develop a plasma QC assay for downstream metabolomics applications. Due to its downstream position of genomics, transcriptomics and proteomics applications, metabolomics is sensitively capturing changes in the collected samples.
In addition, metabolites undergo rapid dynamic changes resulting from pre-analytical variations. The collaborative project is part of the PhD of Jean-Pierre Trezzi and jointly led by Dr Fay Betsou, Chief Scientific Officer of IBBL and Dr Karsten Hiller, Principal Investigator of the Metabolomics group of the LCSB. Together they set out to investigate the impact of pre-centrifugation conditions, more specifically delay and temperature variations, on the fitness-for-purpose for metabolomics analyses with the ultimate goal of developing a QC assay for EDTA plasma samples intended for metabolomics research.
The team from IBBL and LCSB was reinforced by members of the International Society for Biological and Environmental Repositories (ISBER) Biospecimen Science Working Group and recently published their results in the Metabolomics journal. Their initial experiments revealed that if you keep the delay before blood sample processing below 60 minutes, there is no real impact on metabolites. However, even within such a short timeframe, the temperature at which the blood samples are kept makes a big difference: the levels of 20% of metabolites were altered depending on whether samples were stored on ice or at room temperature. Thus, the authors recommend that samples intended for metabolomics research be kept on ice and processed within no more than 3 hours.
For the second phase of the project, the researchers expanded the delay to 3 hours and beyond. They then developed a QC assay based on the most significantly altered metabolites. The LacaScore, as the authors call their assay, is based on the ratio of ascorbic acid to lactic acid levels in plasma. While ascorbic acid levels decrease the longer sample processing is delayed, lactic acid increases. The quality of a sample with a low LacaScore is equivalent to a pre-centrifugation delay at room temperature longer than 3h, making the sample unfit for metabolomics analysis.
The results were validated in two independent datasets from the Sérothèque Centrale of the Geneva University Hospitals and the Integrated BioBank Jena (IBBJ). In addition, the assay was validated on samples under “extreme conditions”, in this case samples from donors that had run a semi-marathon, since intense physical activity is known to increase lactic acid levels and hence likely to interfere with the assay.
More to come
The LacaScore proved to have an 88% diagnostic accuracy in identifying samples with compromised pre-analytical conditions. It is thus a fantastic new QC tool for metabolomics researchers and biobanks to employ before proceeding with their actual experiments to avoid wasting time and resources. Indeed, this is an especially important concept when applying for grants, where evaluators want to see that the samples a researcher intends to use are actually suitable. The researchers behind the LacaScore for their part continue working on the development of other QC assays. IBBL has several QC assays in the pipeline for the coming years, for example a QC assay for DNA extracted from FFPE tissue and a blood QC assay for gene expression studies.
• LacaScore: a novel plasma sample quality control tool based on ascorbic acid and lactic acid levels.-P. Trezzi, A. Bulla, C. Bellora, M. Rose, P. Lescuyer, M. Kiehntopf, K. Hiller, F. Betsou. Metabolomics, Volume 12, Issue 6, Page: 1-11
• Assays for Qualification and Quality Stratification of Clinical Biospecimens Used in Research: A Technical Report from the ISBER Biospecimen Science Working Group Betsou, A. Bulla, S. Yun Cho, J. Clements, R. Chuaqui, D. Coppola, Y. De Souza, A. De Wilde, W. Grizzle, F. Guadagni, E. Gunter, S. Heil, V. Hodgkinson, J. Kessler, M. Kiehntopf, H. Sung Kim, I. Koppandi, K. Shea, R. Singh, M. Sobel, S. Somiari, D. Spyropoulos, M. Stone, G. Tybring, K. Valyi-Nagy, G. Van den Eynden, L. Wadhwa Biopreservation and Biobanking, April 2016.