Gene expression in the detection of autologous blood transfusion in sports – a pilot study

The reinfusion of autologous blood to enhance performance remains a significant problem in sports. Although allogeneic blood transfusions can be detected since 2003 [1], there is at present no detection method for autologous blood transfusions, although indirect approaches such as the biological passport [2] might give indications on the illicit use of blood transfusions. It is well-documented that several molecular changes occur in stored red blood cells (RBCs), commonly referred to as the ‘storage lesion’[3–5]. We therefore hypothesize that autologous transfusion will lead to a sudden exposure of cell detritus to the immune system causing a cellular and molecular immune response including gene expression alterations of white blood cells such as T-lymphocytes. Hence, the primary objective of this study was to investigate the transcriptional response of T-lymphocytes after reinfusion of autologous RBCs in order to search for a theoretical model for an unequivocal detection method of autologous blood doping. The most significant Gene Ontology (GO) clusters of regulated genes at 72 h after autologous transfusion included leucocyte immunoglobulin receptors, toll-like receptor (TLR) pathway [6], adaptive immune response and cell death/apoptosis as well as regulation of endocytosis of surface receptors and the TLR pathway at 96 h, respectively. The quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) confirmed significant up-regulation of TLR4, TLR5, TLR6, apoptosis-associated tyrosine kinase (AATK) [7,8] and low density lipoprotein receptor related protein (LRP1) [9,10] at 72 h as well as TLR6 at 96 h. Therefore, the main finding of our pilot study is the fact that the transfusion of autologous blood triggers a distinct immune reaction within the T-lymphocytes of the recipient and may aid in the development of a practicable method to detect autologous blood doping based on molecular immune response measurements. Six healthy male volunteers [age 24 ± 1 years (mean ± SD), height 182 ± 7 cm, weight 71·0 ± 3·7 kg] were included in the study. All donors were free from medication during the study course. Written informed consent was obtained from all subjects prior to participation in the study. Anti-doping regulations were not violated since none of the subjects was a licence holder in any sports discipline. The ethics committee at the University of Freiburg approved the study procedures. The international standards of transfusion medicine were respected to obtain one autologous erythrocyte concentrate (EC) for each volunteer from a whole-blood sample as previously described [11]. Phosphate, adenine, guanosine, glucose, saline, mannitol (PAGGS-M) was used as the storage solution. The ECs were stored at 4°C and reinfused after a mean interval of 35 ± 3 days. Ten ml of whole blood was collected from each volunteer directly before and 72 h and 96 h after reinfusion. T-lymphocytes were separated from whole blood before (n = 6) and in the course after autologous reinfusion at 72 h (n = 4) and 96 h (n = 4), the two remaining subjects were tested at 24 h and 144 h after transfusion (data not shown). Isolation of T-lymphocytes was performed as previously described [12]. Briefly, RosetteSep T-cell enrichment cocktail (Stemcell Technologies, Vancouver, Canada) was added to whole blood and cells were separated by subsequent Ficoll density gradient centrifugation. Purity of isolated T-cells was confirmed by flow cytometry. Total RNA of T-lymphocytes was subsequently isolated using TRIzol lysis and Qiagen RNeasy kit (Qiagen, Hilden, Germany) as previously described [13] and stored at –20°C for further processing. Gene expression profiles (GEP) were measured using whole human genome 4 × 44 k microarrays (Agilent Technologies, Waldbronn, Germany) according to the manufacturer's recommendations. Quantitative RT-PCR was performed on an ABI 7300 qRT-PCR system (Applied Biosystems, Darmstadt, Germany) using Qiagen QuantiTect Reverse Trascription kit, QuantiTect Sybr Green PCR kit and QuantiTect Primer assays (Qiagen, Hilden, Germany) according to the manufacturer's recommendations. Expression levels of genes validated by qRT-PCR were normalized to endogenous glyceraldehyde-3-phosphate dehydrogenase expression. Raw data were loaded into GeneSpring GX 10 (Agilent Technologies), log2-transformed and normalized to the 75th percentile of all transcripts. Transcripts were considered as expressed when the normalized expression value was higher than the 20th percentile of all transcripts and it was flagged ‘present’ or ‘marginal’ in at least one of all measured arrays. For statistical analysis of differentially expressed transcripts between all three groups, an anova test with asymptotic P-value computation was performed. Only transcripts that exhibited a more than twofold change in expression level compared to the pre-transfusion samples were considered for further analysis. To filtre for biological pathways that were predominately regulated after reinfusion in T-lymphocytes, we performed a GO cluster analysis using the web-based program DAVID 2008 [14,15]. Using this system, transcripts were first allocated to the corresponding GO group. Subsequently, statistically overrepresented GO categories were clustered together with respect to their similar biological functions. A gene expression score (GES) was assigned to the functional clusters, representing the statistical significance (high GES represents a high significance [14,15]). For qRT-PCR expression analysis, a two-sided Student's t-test for paired data was performed using SPSS Version 15·0·1·1 (SPSS, Chicago, IL, USA). Based on the selection criteria, 30 664 transcripts were considered for further evaluation. Statistical analysis revealed that 728 transcripts were significantly regulated 72 h post-transfusion (639 transcripts up-regulated, 89 transcripts down-regulated). Among the genes, the most significant clusters were formed by genes coding for leucocyte immunoglobulin receptors (GES = 7·44) and genes involved in the leucocyte and lymphocyte activation (GES = 2·37), TLR (GES = 2·25), adaptive immune response (GES = 2·21) and cell death and apoptosis (GES = 2·21). At 96 h post-transfusion, 659 transcripts were differentially expressed. As after 72 h, a majority of those transcripts was up-regulated (594 transcripts up-regulated, 65 transcripts down-regulated). The most significant functional GO clusters were formed by genes coding for proteins involved in the regulation of endocytosis of surface receptors (GES = 2·51) and the TLR pathway (GES = 1·62). To confirm the microarray expression findings, we utilized gene expression measurement by quantitative real-time PCR. For validation of TLR pathway regulation through EC transfusion, we selected TLR4, TLR5 and TLR6 as well characterized representatives of the TLR family that were found up-regulated in T-lymphocytes 72 h and 96 h post-transfusion by microarray analysis (Fig. 1a). The qRT-PCR measurements validated an increased expression of all three TLRs 72 h post-transfusion. At 96 h post-transfusion only TLR6 was found significantly up-regulated (Fig. 1b). Expression of TLR4, TLR5 and TLR6 as well as LRP1 and apoptosis-associated tyrosine kinase in T-lymphocytes before (n = 6) and at 72 h (n = 4) and 96 h (n = 4) after autologous blood transfusion (y-axis: arbitrary units). (a) Normalized expression data obtained by microarray measurement. (b) Validation of gene expression by quantitative reverse transcriptase polymerase chain reaction. Expression values were normalized to glyceraldehyde-3-phosphate dehydrogenase (GAPDH) expression (y-axis: a value of 1·0 indicates a gene expression value equal to GADPH expression). Bars show the mean expression, error bars indicate standard deviation of the mean. (*P < 0·05; **P < 0·01). To verify apoptotic signalling in T-lymphocytes, gene expression of AATK was measured. An increased expression of AATK was confirmed by qRT-PCR in lymphocytes 72 h, but not 96 h post-transfusion. A similar pattern was applied to the LRP1 where an increased expression of LRP1 was confirmed 72 h after transfusion but could not be validated 96 h after EC transfusion. The key finding of our pilot study is the fact that the transfusion of autologous blood triggers a distinct immune reaction within the T-lymphocytes of the recipient. Transcripts regulated in T-lymphocytes by reinfusion of autologous EC could be allocated to functional GO clusters of genes coding for proteins that regulate T-lymphocyte activation, adaptive immune response, TLR pathways, endocytosis of surface receptors and cell apoptosis. These findings may be related to processes occurring during storage of RBCs, the so-called ‘storage lesion’. In this context, it has been described that the suspending fluid of stored RBCs exhibits an increased number of vesicles [4] and that RBCs are subject to various membrane changes including disturbed phospholipid asymmetry and modifications of Band 3 protein [3,5] marking cells for removal. As these modifications are an unequivocal feature of stored RBCs (autologous as well as allogeneic EC), they have a potential immunomodulatory effect upon transfusion and lead to a distinct immune response as revealed by GEP analysis in our study, which did not include a control group as the design had pilot character. The receptors TLR4, TLR5 and TLR6 showed the most significant results 72 h after transfusion by microarray analysis. In T-lymphocytes, TLRs are involved in the mediation of initiate immune response, activation of T-lymphocytes and induction of apoptosis [6], which are three biological processes observed by GEP cluster analysis 72 h post-transfusion. TLRs are also able to recognize endogenous cells, modified in their appearance, like tumour cells [16]. In this context, LRP1, a surface receptor known to recognize apoptotic cells and to regulate T-cell adhesion [9,10], was also found to be up-regulated after transfusion of stored autologous ECs. Further on, we verified the induction of apoptosis by validation of an increased expression of AATK, a kinase playing a crucial role in the positive regulation of apoptosis in a number of different cells [7,8]. This characteristic expression profile was evident 72 h after reinfusion, although lost significance for certain genes 96 h after reinfusion when verified using qRT-PCR. Although the ultimate goal of our approach would resemble a ‘stand-alone’ laboratory based test system for the detection of autologous blood transfusion, it might also add to the growing portfolio of indirect anti-doping testing procedures and could perhaps be used in combination with other indirect techniques such as the biological passport [2], the total RBC mass determination [11] or the detection of plasticizers [17]. In order to exclude false-positive results, subsequent research will also have to be focused on various settings (e.g. immune reactions to infections, haemolysis) to ensure the highest possible sensitivity and specificity of the described immune response. In conclusion, our results suggest a framework for a potential mechanism for the detection of autologous blood transfusion. Following autologous application of stored RBCs, a sudden immune response results in an activation of T-lymphocytes. The observed cellular responses to autologous blood transfusion may be useful for further development of appropriate assays including flow cytometry and application of specific antibodies binding to up-regulated cell surface receptors, which would not be traceable to the same extent under physiological (non-transfused) conditions. Although the present investigation is only a pilot study involving a limited number of subjects and time points, it paves the way for more extensive research that might ultimately lead to a practicable method to detect autologous blood doping. This study was supported by the ‘Nenad-Keul-Foundation’.

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