Markers of biobank sample quality Rainer Lehmann
Symposium 4 Biospecimen Science Markers of biobank sample quality Rainer Lehmann Div. of Clinical Chemistry and Pathobiochemistry University Hospital Tuebingen and Institute for Diabetes Research and Metabolic Diseases German Center for Diabetes Research (DZD) Germany Rainer Lehmann, University Hospital Tübingen, Germany The general opinion is, that essential pre-requisites for the success of research projects are - good experimental design - precise, robust and reproducible analytical techniques (wet lab) - sophisticated data analysis (dry lab) and interpretation Rainer Lehmann, University Hospital Tübingen, Germany 1 Biobank sample quality „….the quality of biospecimen is of paramount importance for the reliability and validity of research results and all downstream applications.“ Fay Betsou (ISBER President 2013-2014) Î pre-analytical phase! Rainer Lehmann, University Hospital Tübingen, Germany Biobanking / Blood collection blood collection clinical study transport centrifugation freezer plasma / serum Unfortunately, in general the interest of many investigators for the pre-analytical phase is only minor In complex clinical studies blood collection is often entitled as the easy part Rainer Lehmann, University Hospital Tübingen, Germany 2 Biobanking / Blood collection blood collection transport centrifugation freezer plasma / serum clinical study Typical questions of investigators (frequently asked after the end of their studies) are: The centrifuge of our ward was highly frequented, consequently the processing of some blood samples was delayed. Is this a problem? One third of the blood of our study was drawn by inexperienced medical students. Unfortunately this resulted in several more or less hemolytic samples. Can we still use the sample set? Several biobank samples of my study have been thawed one or two times. Are they still suitable e.g. for metabolomics investigations? The centrifuge was in another building. We could not process the blood samples before 2 h, is this a problem? ... . Rainer Lehmann, University Hospital Tübingen, Germany Biobanking / Blood collection blood collection clinical study transport centrifugation freezer plasma / serum Typical questions of investigators (frequently after the end of their studies) are: Variable The centrifuge and prolongated of our wardexposure was highly time frequented, of blood tothat room is way temperature the processing before of some samples in centrifugation was occasional delayed. instances Hemolytic sera/plasma are instudy the sample set by medical students, which unfortunately One third of the blood of the was drawn resulted in several more or less hemolytic samples. Can we use the samples? Repetitive freezesamples and thawofcycles had have been been performed with samples Several biobank my study thawed onesome or two times. Are they still suitable e.g. for metabolomics investigations? Systematic prolongation of thebuilding. exposureI could time of blood before The centrifuge was in another not process theprocessing blood samples before 2 h, is this a problem? ... . Rainer Lehmann, University Hospital Tübingen, Germany 3 Markers of biobank sample quality Î we applied metabolomics to investigated these preanalytical steps Blood collection hemolysis Transportation delayed processing Storage repetitive freeze/thaw cycles Rainer Lehmann, University Hospital Tübingen, Germany Metabolomics TARGETED Metabolomics NON-TARGETED Metabolomics analysis of selected, well-known metabolites non-hypothesis driven, comprehensive approach 20 - 300 metabolites per sample > 2.000 metabolite-ion masses per sample automation (commercial kits available) quantitative Î identification of most important metabolites time consuming and labor intensive semi-quantitative Î population based studies > 500 samples / week possible 2 weeks until final result Î well selected and characterized samples ≥ 4 months until final result Rainer Lehmann, University Hospital Tübingen, Germany 4 Metabolomics data processing primary note for the coming slides: Scheme of data evalution Rainer Lehmann, University Hospital Tübingen, Germany Markers of biobank sample quality blood collection transport centrifugation analysis plasma / serum clinical study pre-analytical process biobank sample preparation data evaluation / bioinformatics valid results Analytical specialists (wet lab) Æ blood collection / hemolysis Æ transportation Æ storage Hemolytic specimens occur frequently in clinical laboratories Æ as high as 3.3% of all of the routine samples, that means e.g. around 100 – 130 samples / day in our lab Æ they account for up to 40%–70% of all unsuitable specimens identified Rainer Lehmann, University Hospital Tübingen, Germany G. Lippi et al. CCLM (2008) 5 Blood drawing Hemolysis blood drawing non-targeted metabolomics classical parameters n = 10 Rainer Lehmann, University Hospital Tübingen, Germany Blood drawing Hemolysis PCA scores plot High Intensity no hemolysis moderate hemolysis strong hemolysis 18% of all metabolite ion masses were significantly altered (p<0.05, FDR<0.1) Rainer Lehmann, University Hospital Tübingen, Germany 6 Crucial point in non-targeted metabolomics nontargeted Metabolomics Bioinformatics Æ canditate list of features / ion masses Elucidation of the metabolite identity Data base searches / MSn / confirmation by a standard compound Rainer Lehmann, University Hospital Tübingen, Germany Blood drawing Hemolysis Identified metabolites (sign. changed): Lyso-PC 16:0 Lyso-PC 18:0 Lyso-PC 18:1 Tryptophan Sphingosine 1-phosphate (S-1-P) N-acetylornithine C8-carnitine Suggestions: - hemolytic samples should be excluded, at least from high resolution -omics research projects - S-1-P, Trp, LPC C16:0,…. should only carefully be nominated as biomarker candidates in research studies and must be thoroughly validated for robustness - All biobank samples should be tested for hemolysis before storage Î free Hb can easily be measured by a two wavelenght method Rainer Lehmann, University Hospital Tübingen, Germany Golf-SW et al. J Clin Chem Clin Biochem (1985) 7 Markers of biobank sample quality blood collection transport centrifugation clinical study analysis plasma / serum biobank sample preparation data evaluation / bioinformatics valid results Æ blood collection Æ transportation / processing of blood Æ storage Rainer Lehmann, University Hospital Tübingen, Germany Markers of biobank sample quality © Universitätsklinikum Ulm A 9 ml sample of blood from an adult subject contains 5 × 1010 red blood cells 3 × 109 platelets „liquid tissue“ 8 × 107 leukocytes Rainer Lehmann, University Hospital Tübingen, Germany 8 Transportation / processing of blood Experimental design - 2h to 4 h exposure of blood to room temperature or ice water Î clinic internal handling / transportation - 8h and 24 h exposure to room temperature Î external transportation n = 10 n = 10 2h, 4h, 8h and 24h 2h and 4h non-targeted metabolomics by LC/MS Rainer Lehmann, University Hospital Tübingen, Germany Transportation / processing of blood Transport of whole blood (EDTA-blood) room temperature Peiyuan Yin ice water 80 control 20 2h 4h 10 70 1 60 50 40 30 5 20 10 6 4 10 0 0 -10 -30 -10 2 8 7 -20 9 -40 3 -50 -60 -20 -70 -40 -30 -20 -10 0 10 20SIMCA-P 11 - 2012/1/10 30 11:29:47 40 n = 10 Rainer Lehmann, University Hospital Tübingen, Germany -100 -80 -60 -40 -20 0 20 40 60 80 100 n = 10 Yin P, ….Xu G., Lehmann R.: Clin Chem 2013; 59:833-45 9 Transportation / processing of blood Exposure of EDTA blood samples to room temperature 24h external transports 8h 1.0 4h 2h time needed for clinical internal handling / transport 0h 0.1 fold change of peak area 10 (m/z) Peiyuan Yin Rainer Lehmann, University Hospital Tübingen, Germany Yin P, ….Xu G., Lehmann R.: Clin Chem 2013; 59:833-45 10 (m/z) Transportation / processing of blood fold change of peak area 0.1 1.0 24h external transports 8h 4h 2h 0h time needed for clinical internal handling / transport Identified metabolites C2-carnitine C8-carnitine C12-carnitine N-acetylornithine Hypoxanthine Proline betaine Palmitic amide Sphingosine 1-phosphate Indole Tryptophan LPC 16:0 LPC 18:0 LPC 18:1 LPC C20:3 Oleamide L-Methionine Biliverdine Rainer Lehmann, University Hospital Tübingen, Germany 10 10 (m/z) Transportation / processing of blood external transports 8h peak area 0.1 1.0 fold change of 24h 4h 2h time needed for clinical internal handling / transport 0h A targeted metabolomics approach which included several of these metabolites confirmed the findings B. Kamlage, et al. Clin. Chem. 2014 Identified metabolites C2-carnitine C8-carnitine C12-carnitine N-acetylornithine Hypoxanthine Proline betaine Palmitic amide Sphingosine 1-phosphate Indole Tryptophan LPC 16:0 LPC 18:0 LPC 18:1 LPC C20:3 Oleamide L-Methionine Biliverdine Rainer Lehmann, University Hospital Tübingen, Germany Transportation / processing of blood New (ongoing) studie Goal: - define confidence intervals for good and poor quality of blood samples in ca. 100 samples (samples were selected at random in a metabolic ward in our outpatient clinic) - receive an impression of the number of changed metabolites Æ modern, more sensitive mass spec (triple TOF-MS), new analytical strategy Analytical approaches Î non-targeted metabolomics Î targeted metabolomics Rainer Lehmann, University Hospital Tübingen, Germany 11 NON-targeted metabolomics positive mode detected ion masses：3137 negative mode detected ion masses：2910 Significant changed metabolite ion masses Xinyu Liu Î 262 metabolite ion masses were significantly altered 2h ESI + ESI - 4h room temp. 0.64 % 3.6 % ice water 0.13 % 0.29 % room temp. 1.48 % 5.09 % ice water 0.82 % 0.14 % 114 metabolite ions 148 metabolite ions n = 30 p < 0.05, FDR 0.05 unpublished data Rainer Lehmann, University Hospital Tübingen, Germany NON-targeted metabolomics Potential markers of biobank sample quality Xinyu Liu metabolite ion mass A metabolite ion mass D 50000 40000 30000 20000 10000 0 0h Ice 2h Ice 4h RT 2h RT 4h 0h Ice 2h Ice 4h RT 2h RT 4h n = 30 Rainer Lehmann, University Hospital Tübingen, Germany unpublished data 12 NON-targeted metabolomics ? blood processing delayed by 4 h metabolite (B) metabolite (D) metabolite (C) Lactate %-Sensitivity %-Specificity metabolite ion mass (A) = lactic acid 98.3 76.7 metabolite ion mass (B) 91.7 98.9 metabolite ion mass (C) 96.7 100 metabolite ion mass (D) 100 100 n = 30 unpublished data Rainer Lehmann, University Hospital Tübingen, Germany Markers of biobank sample quality blood collection transport centrifugation analysis plasma / serum clinical study biobank sample preparation data evaluation / bioinformatics valid results Æ blood collection Æ transportation / processing of blood Æ storage Æ repetitive freeze and thaw cycles Rainer Lehmann, University Hospital Tübingen, Germany 13 Biobanking / stored samples Problem: the number of aliquots is limited Î leads unavoidable to repetitive freeze and thaw cycles aiming to save sample material we investigated EDTA plasma by non-targeted metabolomics: controls (metabolomics sample pretreatment was performed at once after drawing blood) 1x frozen (= common biobank sample) 2x thawed / frozen 4 x thawed / frozen Rainer Lehmann, University Hospital Tübingen, Germany Biobanking / stored samples Î no significant alterations of metabolite ion masses between fresh controls and 1x frozen plasma samples were detected Î unexpectedly, only 4 masses changed significantly after 2x and 4x freeze/thaw cycles! Î we detected individual differences in the sample stability! instabilities of the metabolite pattern were detected in plasma samples of 2 out of 10 individuals, even in 1x frozen aliquots! Rainer Lehmann, University Hospital Tübingen, Germany 14 Planning phase of studies and another aspect…. relevant for biobank samples intended for MSdriven –omics analyses Additives included in the sample collectors may affect the ionization process during an LC-MS run thereby suppressing the ionization of metabolites or introduce interfering compounds. Rainer Lehmann, University Hospital Tübingen, Germany Planning phase of studies different S-Monovetten (Sarstedt) were investigated Î consequently, the first important step in the planning and preparation of a study is to check Yinbe P, used ….Häring H.-U., Lehmann R.:ofClin Chem 2013;59:833-45 to for the generation biobank samples specific sample planned Rainereach Lehmann, University Hospitalcollector Tübingen, Germany 15 Summary (1) Blood collection/storage is the easy part of complex clinical studies, BUT may heavily affect the quality of biobank samples and consequently the outcome and success of research projects SOPs strictly regulate the exposure time of whole blood to room temperature or cooling (as well as the further processing), BUT this exposure time may vary from SOP to SOP, e.g. based on logistical problems and resulting compromises in the SOP and the exposure time may be prolonged in occasional instances Rainer Lehmann, University Hospital Tübingen, Germany Summary (2) The discovered pre-analytical biomarkers may help to identify a) systematic inaccuracies that arise during processing of whole blood that affect the quality of biobank samples b) random errors leading to particular outliers in the sample set and Investigators should be careful in nominating metabolites identified to be sensitive to preanalytical alterations as biomarker candidates in their research studies P. Yin, et al. Clin. Chem. 2013 B. Kamlage, et al. Clin. Chem. 2014 Rainer Lehmann, University Hospital Tübingen, Germany 16 Summary (3) - Recommendations 1.) the suitability of sample collectors should be tested before starting sample collection 2.) hemolytic samples must be excluded 3.) place blood immediately in ice water after drawing until further processing (for a fixed time; ideally not longer than 2 hours) Î we prefer (EDTA-)plasma instead of serum as the favorable sample material Î processing: centrifugation at 4°C, for 10 min, at 2000 × g 4.) the quality of biobank samples should be tested by using EDTA plasma aliquots before the samples are used in expensive and time consuming analytical projects 5.) handling of biobank samples: - samples should be thawed in ice water - non refrozen plasma aliquots of biobank samples are recommended - mix-up of samples exposed to different freeze and thaw cycles should be avoided Rainer Lehmann, University Hospital Tübingen, Germany Summary (4) - Recommendations Poor sample quality does not necessarily mean that the biobank sample has to be discarded, but these samples should not be used for high resolution analyses, like metabolomics analysis Stability in whole blood at room temperature Stability in serum / plasma at room temperature Albumin Alk. Phosph. Ammonia Rainer Lehmann, University Hospital Tübingen, Germany W. Guder et al., J. Lab. Med. 2002 17 Hans-Ulrich Häring Andreas Fritsche Norbert Stefan Robert Wagner Erwin Schleicher Andreas Peter Ann Kathrin Pohl Heike Runge Mareike Walenta Miriam Hoene Sabine Neukamm Magnus Wolf Christian Klingler Cora Weigert current Bente K. Pedersen Peter Plomgaard Jakob Hansen Oliver Kohlbacher Erhan Kenar Holger Franken Lars Rosenbaum Andreas Zell Dalian University of Technology Xiaohui Lin Hai Wei Dalian Institute of Chemical Physics - CAS - Guowang Xu Xinjie Zhao Perry Yin Xinyu Liu Shili Chen Zhongda Zeng Jia Li NSFC funding: Rainer Lehmann, University Hospital Tübingen, Germany 18
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