Possible graft‐versus‐host disease involving the central nervous system soon after cord blood transplantation
Authors: Hisashi Yamamoto, Naoyuki Uchida, Kazuya Ishiwata, Hideki Araoka, Shinsuke Takagi, Masanori Tsuji, Daisuke Kato, Yoshiko Matsuhashi, Sachiko Seo, Naofumi Matsuno, Kazuhiro Masuoka, Atsushi Wake, Akiko Yoneyama, Shigeyoshi Makino, Shuichi Taniguchi
Journal: American Journal of Hematology (2009)

Enhanced oxygen delivery to tissues has been shown to improve endurance performance [1].This has led to widespread abuse of erythropoiesis-stimulating agents (ESA) in elite sport.It is conceivable that athletes have even learned how to continue illicit ESA doping [2].This possibility has fuelled the search for novel methods to detect and deter ESA abuse using ''indirect'' markers.It is now widely accepted that drugs influence gene expression [3,4].In this study, we envisage its use as a means to detect ESA doping.We obtained a global view of the transcriptome of total blood cells both before and after treatment with darbepoetin alpha using the serial analysis of gene expression (SAGE) method.In silico analysis identified 95 genes whose differential expression was subsequently tested by quantitative real-time polymerase chain reaction (PCR) in two athletes.The athletes were treated first with high doses of recombinant human erythropoietin (rHuEpo) to increase their hemoglobin concentration and then with microdoses to maintain the high concentration of hemoglobin.Significance analysis of microarrays (SAM) at a delta ratio greater than 1.5 indicated that 33 genes could be significant markers of ESA administration.Interestingly, when high and microdoses were taken into account together, five genes could still be considered as significant markers.It is well known that the interaction of a drug with a biological system can result in a gene expression profile or signature that is characteristic of the event.The more recently developed methods that estimate quantitative and qualitative differences in mRNA are microarray analysis [5] and SAGE [6].We used the SAGE technique to obtain a global view of the blood transcriptome to observe gene profiles before, during and after ESA treatment and to determine indirect markers of ESA abuse.Indeed, although ESAs differ in pharmacokinetic, pharmacodynamic and receptor-binding properties, they all share the same mechanism of action: binding and activating the Epo receptor [7].Three SAGE libraries were constructed by pooling blood samples from 14 athletes (seven males and seven females) before (J-1), during (J10) and after (P17) darbepoietin administration.The mean hemoglobin concentration values were 14.8 ± 0.3 g/dl (J-1), 15.7 ± 0.4 g/dl (J10), 16.2 ± 0.6 g/dl (P17) for males and 13.1 ± 0.4 g/dl (J-1), 13.9 ± 0.6 g/dl (J10), 15.1 ± 0.3 g/dl (P17) for females.SAGE allows quantitative analysis of genome-wide expression profiles of tissues or cell lines [8][9][10][11].We sequenced 60,000 tags from the three libraries.Among the 19,713 unique transcripts that were identified, 55% corresponded to known genes, 12% to ESTs, and 33% to unidentified genes.Next, genes were classified according to their profiles during the three periods using the K-means clustering (KMC) algorithm.Thus, according to these criteria, 360 downregulated and 240 upregulated SAGE-tags were selected (Fig. 1).The three SAGE librairies were integrated onto a Biotag bioinformatics platform, which incorporates SAGE transcriptome data from the scientific community on a monthly basis.One of the advantages of SAGE data is that pathological and normal cells/tissues can be compared [12].Thus, the bioinformatics analyzes of the Epo SAGE libraries were compared first with the 25 available blood cell SAGE libraries and then with the 960 SAGE libraries of pathological and normal cells/tissues [13].The final in silico step of selection was to discard those genes whose expression could be misinterpreted in the final analysis (Fig. 1).For example, we identified a similar induction of the RAD23B (NM_002874) gene.