The analysis of the transcriptome as a new approach for biomarker development to trace the abuse of anabolic steroid hormones.

Abstract

The abuse of anabolic steroid hormones in human sports and animal husbandry is an ubiquitous problem and therefore a tight control program in both areas is very important. Within these control programs, hormone residues are detected by immunoassays or chromatographical methods in combination with mass spectrometry. With these methods, all known substances can be detected; yet new xenobiotic growth promoters and new ways of application are difficult to detect. Therefore it is important to develop new sensitive screening methods to enable an efficient control for misused anabolic substances. The detection of their physiological action is a promising approach. Anabolic steroid hormones directly influence the expression of specific genes and thus the analysis of the transcriptome of different target tissues and matrices is of great interest. This review describes our recent efforts made concerning the analysis of gene expression changes in different tissues, different species and under different anabolic treatments.

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Review
Drug Testing
and Analysis
Received: 18 March 2011Revised: 2 May 2011Accepted: 4 May 2011Published online in Wiley Online Library:
(www.drugtestinganalysis.com) DOI 10.1002/dta.304
The analysis of thetranscriptome as a new
approach for biomarker development to trace
the abuse of anabolic steroid hormones
IrmgardRiedmaier,∗MichaelW. PfafflandHeinrich H. D. Meyer
The abuse of anabolic steroid hormones in human sports and animal husbandry is an ubiquitous problem and therefore
a tight control program in both areas is very important. Within these control programs, hormone residues are detected
by immunoassays or chromatographical methods in combination with mass spectrometry. With these methods, all known
substancescanbedetected;yetnewxenobioticgrowthpromotersandnewwaysofapplicationaredifficulttodetect.Therefore
it is important to develop new sensitivescreening methods to enable an efficient control for misused anabolic substances. The
detectionof theirphysiological actionis apromisingapproach. Anabolicsteroidhormonesdirectlyinfluencetheexpressionof
specificgenesandthustheanalysisofthetranscriptomeofdifferenttargettissuesandmatricesisofgreatinterest.Thisreview
describesourrecenteffortsmadeconcerningtheanalysisofgeneexpressionchangesindifferenttissues,differentspeciesand
under differentanabolictreatments. Copyright c ? 2011 John Wiley& Sons,Ltd.
Keywords: anabolic steroids; gene expression biomarkers; RT-qPCR
Introduction
Steroid hormones, like testosterone and estradiol, are involved in
endocrine and paracrine regulation of growth in different tissues.
In vertebrates, the number of skeletal muscle fibres is fixed at
birth. Postnatal muscle growth results from hypertrophy of ex-
isting muscle fibres. During muscle hypertrophy, mononucleated
satellite cells located on the periphery of the muscle fibres fuse
with the muscle fibre cells providing the nuclei needed for an
increased production of muscle proteins.[1–3]Insulin-like growth
factor1(IGF-1)anditsbindingproteins(IGFBP)playacrucialrolein
muscle growth, for example by increasing the number of satellite
cellsandsoenhancingmuscle hypertrophy.[1]Treatmentwith an-
abolic steroid hormones increases the production of IGF-1 in the
liverandalsoinskeletalmuscletissue.[4]Thisresultsinanincreased
growth rate and so IGF-1 is a mediator of the growth-promoting
effect of steroid hormones in muscle.
Bone remodelling is a process that includes different kinds
of cells and proteins. Osteoclasts, secret proteolytic enzymes
which are responsible for bone tissue loss. Osteoblasts differ from
osteocytes,whichincombinationwithdifferentminerals,formthe
bonematrix.Steroidhormoneslikeestrogensandalsoandrogens
inhibit bone breakdown by stimulation of proliferation and
differentiation of osteoblasts or by stimulating the generation of
extracellularbonematrixproteinslikeTypeIcollagen,osteocalcin,
or osteonektin. Anabolic steroid hormones show pro-apoptotic
effects on osteoclasts and anti-apoptotic effects on osteoblasts
and osteocytes. Hence they positively affect bone density.[5]The
decreaseoftheendogenousproductionofanabolicsexhormones
after menopause has a negative effect on bone mineral density
leading to osteoporosis.[6]
Steroid hormones, mainly estrogens, show direct effects
on adipose tissue by down-regulating lipogenesis and up-
regulating lipolysis and the β-oxidation. Estrogens also decrease
the differentiation rate of adipocyte-precursor cells to mature
adipocytes.[7–9]
These positive effects on muscle mass and bone density and
the mobilization of adipose tissue by anabolic steroid hormones
are responsible for their misuse as growth promoters in sports
and animal husbandry. To uncover this abuse, hormone residues
areroutinelydetectedusingimmunoassaysorchromatographical
methodsincombinationwithmassspectrometry.[10–13]Withthese
methods, only known substances can be discovered but new
xenobiotic anabolic agents or hormone cocktails can hardly be
detected. Therefore the development of new, sensitive detection
methods is a permanent challenge for scientists.
In molecular medicine – for example, in cancer research – the
development of molecular biomarkers is already a common ap-
proach for diagnostic purpose. Plasma biomarkers are developed
for prognostic use and tumour biomarkers are applied to develop
treatment strategies for each individual patient.[14,15]A promising
way for the development of such biomarkers for the detection
of the abuse of anabolic steroids is the analysis of physiological
changescausedbytreatment using‘-omictechnologies’like tran-
scriptomics, proteomics, and metabolomics.[15–18]The choice of
the right -omic technology for the specific application is a big
challenge.
Steroid hormone receptors belong to the family of nuclear
receptors and show a high affinity to their corresponding
hormone.[19,20]Afterbindingofthehormoneoractiveanaloga,the
hormone-receptorcomplexdirectlyinfluencesthetranscriptionof
∗Correspondence to: IrmgardRiedmaier, Physiology Weihenstephan, TU
MuenchenWeihenstephanerBerg3,85354Freising,Germany.
E-mail:irmgard.riedmaier@wzw.tum.de
Physiology Weihenstephan, Technische Universitaet Muenchen, Weihen-
stephanerBerg3,85354Freising,Germany
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I. Riedmaier, M. W. Pfaffl and H. H. D. Meyer
specific genes either by binding to specific DNA sequences in the
promoter region of the genes or by activating other transcription
factors which then activate the expression of specific genes.[18]
Due to this direct effect on gene transcription, the analysis of
changes in the transcriptome is a promising way for detecting
physiological changes caused by treatment with anabolic steroid
hormones.
This review reflects our in-house data obtained from different
studies regarding the effects of anabolic steroid hormones on
the transcriptome in different tissues and species. In all studies,
analyzed target genes were chosen by screening the actual
literature for steroidal effects on the physiology of the specific
organs and their expression was quantified using RT-qPCR.
Tissue distributionof steroid hormone
receptors
Thefirststepinestablishingphysiologicalbiomarkersisthechoice
of the ideal tissue. Therefore physiological knowledge about
effects of steroid hormones in different tissues is needed. The
precondition of direct steroidal action on a tissue is the presence
of the specific receptors especially of the androgen receptor
(AR) and the two isoforms of the estrogen receptor (ERα and
ERβ). The primary group of tissues that are directly influenced
by sex steroids are parts of the reproductive tract. In females,
uterus, ovary, mammary gland, and vaginal epithelial cells will
be of interest. All these organs express all three types of steroid
receptorswhereasinuterus,mammaryglandandvaginalepithelial
cellsERα andinovaryERβ istheprevalentisoformoftheestrogen
receptor.[21–26]Inthemaleorganism,testisandprostate willbeof
major interest. In both tissues the androgen receptor expression
is very high and estrogens mainly act via ERβ.[21,22,27–29]Other
tissues that seem to be interesting are different kinds of muscles,
because they are target organs for growth-promoting treatment
with anabolic steroids. In different studies, mRNA expression of
steroidreceptorswasquantifiedindifferentandrogendependent
muscles, for example, neck muscle, hind limb muscle or shoulder
muscle.Thesestudiesshowthatallanalyzedmuscletypesexpress
the androgen receptor and that ERα is the main isoform of the
estrogen receptor, pointing out that estrogens mainly act via ERα
in muscle tissue.[25,26]Pfaffl etal. quantified the mRNA expression
of steroid receptors in 10 different parts of the gastrointestinal
tract. In all gastrointestinal parts, the expression of each receptor
could be quantified, whereas apart from ileum and rectum, ERα is
the main expressed isoform of the estrogen receptor.[25,30]There
are many other tissues expressing steroid hormone receptors,
like liver, kidney, spleen, thymus, bone, skin, lung, and blood
leukocytes,[21,22,25,27,31,32]and therefore all these tissues are also
potentialcandidatesfortheanalysisofgeneexpressionbiomarkers
for treatment with anabolic steroids.
Analyticalmethods
There are different methods available for the quantification of
geneexpression.Themaindifferencebetweenthemethodsisthe
amount of quantifiable genes. Up to now in most studies where
a broad range of gene expression changes shall be quantified,
microarray technology is the method of choice. With these
arrays it is possible to screen for the expression of all known
mRNAs. A holistic approach for gene expression analysis is RNA
Sequencing(RNA-Seq),anewmethodwhichsequencesthewhole
transcriptome of a biological sample and thereby quantifies all
RNA sequences present. This method is very sensitive because
only one transcript of a gene is detectable.[33,34]In most of these
experiments, gene expression changes are validated by single
gene assays using RT-qPCR. Another way for finding candidate
genesfor biomarkerdevelopmentisthe so-calledcandidate gene
approach. Within this approach, candidate genes are determined
byscreeningtheactualliteratureforphysiologicalchangescaused
by the specific treatment and thereby identifying key factors of
these processes, whose expression is then quantified using RT-
qPCR. In the presented experiments 30–45 genes were chosen
for each tissue using this candidate gene approach. In our lab,
the method of RT-qPCR is well established and we are working
according to the MIQE guidelines.[35]
Effects of androgenson human hair follicle
Developing gene expression biomarkers for the detection of the
abuse of anabolic steroids in human sports is a big challenge,
due to dependence ontissues thatareavailable fromhumansina
non-invasiveform.Onepromisingtissueishumanhairrootcellsas
it is already known that steroid hormones, especially androgens,
act via the dermal papilla cells by influencing different growth
factors and enzymes.[36]
In a first invitro pilot study, female and male human hair follicle
dermal papilla cells were treated with stanozolol, a xenobiotic
androgen. Cells were harvested at different time points after
treatment, RNA was extracted, and gene expression analysis was
done via RT-qPCR for quantifying 13 different genes. Genes like
the androgen receptor (AR), the apoptosis factors Fas receptor
(FasR) and caspase 8, the fibroblast growth factor FGF7 and
the 5α-Steroidreductase SRD5A2 were detected as significantly
regulated, whereas only AR and FasR were significantly regulated
in both female and male cells and the other genes were
significantly regulated either in female (FGF7, Caspase 8) or
in male cells (SRD5A2).[37]In another study, the expression of
different genes in plucked hair follicle samples was quantified
in female and male hair follicles and also in a small number
of hair samples from weightlifters under doping conditions.
Thereby no gender dependent differences in gene expression
could be quantified. Hair follicles from weightlifters under doping
conditions showed significant differences in the expression of the
glucocorticoid receptor and the fibroblast growth factor FGF7.[38]
These results indicate that it may be possible to find differences
ingeneexpressionofhairfolliclesbetweentreatedanduntreated
individualsandfutureexperimentshavetoshowifmoregenesare
regulated by treatment with anabolic steroids. It has to be proven
ifthese changescouldactasspecific geneexpression biomarkers,
in order that abuses can be uncovered.
Effects of androgens on primate muscle and
blood cells
Asalreadymentioned,thedecreaseoftheendogenousproduction
of anabolic steroid hormones (mainly estradiol and testosterone)
after menopause has a negative effect on bone mineral density
leading to osteoporosis.[6]Another problem is sarcopenia, the
loss of muscle mass also caused by the decrease in estradiol and
testosterone levels. The standard therapy is the replacement of
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testosterone or estadiol but these therapies show negative side
effectslikeanincreasedriskofcancer.[39–41]Alternatively,patients
can be treated with selective androgen receptor modulators
(SARM) or selective estrogen receptor modulators (SERM). SARM
and SERM are synthetic molecules which bind to the steroid
hormone receptors exhibiting predominantly tissue selective
effects.[42]As these substances positively affect bone density and
muscle mass, the risk of misuse in sports and animal husbandry
is always present. Therefore a study was designed to compare
the effects of a new SARM with those of natural testosterone on
gene expression in muscle tissue and whole blood. In this study
cynomolgous monkeys were treated either with two different
doses of the SARM or with natural testosterone.[43,44]Significant
differencesingeneexpressioncouldbemeasuredforcathepsinL,
calpain 3, and IGFBP3 in biopsies of musculus quadriceps 90 days
after treatment.[44]In whole blood, changes in gene expression
could be observed for IL-15 and TNFR2 16 days after treatment
started and for IL-12b, IL-15, CD30L, FasR, TNFR1, and TNFR2
90 days after treatment started.[43]In both tissues, no different
effects of the SARM and testosterone could be identified.[43,44]
Effects of steroid hormoneson bovinetissues
Inanimalhusbandry,steroidhormonesareadministeredasgrowth
promoters as they lead to lean meat due to nitrogen retention
and a decrease in total body fat.[4]In the EU, the use of growth
promoters is forbidden due to negative side effects of hormone
residues for the human consumer.
Fortheidentification ofgeneexpressionbiomarkersinanimals,
almost all tissues are available at slaughter. Reproductive organs
like uterus, ovary, and vaginal epithelial cells in female animals
and testis and prostate in male animals are primary-hormone-
dependent tissues and are therefore promising organs to identify
physiologicaleffectsontheleveloftranscription.[23,24,26,45]Butalso
other organs like liver, muscle, or blood seem very interesting for
the identification of gene expression biomarkers. In two different
invivo studies, heifers were treated with steroid hormones and
different tissue samples were taken either at slaughter or during
treatment time (blood andvaginal smear). In the first study (study
1) the effect of Ralgro(Zeranol) and Finaplix H(Trenbolone
Acetate) on the expression of different genes in muscle, liver, and
uterus was investigated. In a second study (study 2) nine Nguni
heifersweretreatedwithRevalorH,acombinationofTrenbolone
Acetate plus Estradiol. Blood and vaginal smear samples were
taken during treatment time and uterus, ovary, and liver samples
weretakenatslaughter.Inthesetissues,geneexpressionchanges
wereanalyzedandcomparedwithnineuntreatedcontrolanimals.
Interesting target genes were chosen by screening the actual
literature for steroidal effects on the physiology of the specific
organs and their expression was quantified using RT-qPCR. Gene
expressionchangeswerestatisticallyanalyzedbetweenuntreated
controls and treated animals.
Effects of steroid hormoneson reproductive organs
The effect of anabolic treatment on gene expression in uterine
tissue of treated heifers was analyzed in both studies. In the first
study,11outof29testedgenesweresignificantlyregulatedeither
byRalgroorbyFinaplixHwhereasonlytheapoptosisregulator
FasLwasregulatedbybothtreatments.[26]Inthesecondstudy,the
analyzeduterusendometrialtissuewasseparatedbetweenuterus
horn and uterus corpus. In the uterus horn, 9 genes were found
to be differentially regulated; in the uterus corpus 12 regulated
genes were identified.[23]Only four genes showed regulations
in both regions of the uterus: the androgen receptor, the bone
morphogenic factor 4, the apoptosis factor caspase 3, and the
complement factor 7.[23]These genes could act as first biomarker
candidatesforuterineendometrium.Inthesamestudy,theeffects
ofTrenboloneAcetateplusEstradiolongeneexpressioninbovine
ovarywereanalyzedand22significantlyregulatedgenescouldbe
identified.[23]This indicates that the ovaries are more promising
forbiomarkerdevelopmentthantheuterineendometrium.Athird
reproductive organ that has been taken into account in this study
was vaginal smear containing vaginal epithelial cells. This was a
really new approach because there are no publications available
regardinggeneexpressioninbovinevaginalsmear.However,gene
expressionassayscouldbeestablishedfor27candidategenesand
13ofthemcouldbeidentifiedassignificantlyregulated.[24]Vaginal
smearseemstobeapromisingtissueforbiomarkerdevelopment,
becauseitisavailableinanon-invasivewayfromthelivinganimal
and so controls could also take place directly on animal farmsand
not only at the slaughter house.
These results indicate that reproductive organs are promising
tissues for the development of gene expression biomarkers for
anabolic steroid hormones. But the disadvantage is that the use
of these biomarkers is dependent on gender. Due to that, other
tissues showing physiological effects caused by treatment with
anabolic steroids should been taken into account.
Effects of steroid hormoneson other bovine tissues
One interesting tissue for gene expression analysis is muscle,
because it is one of the primary physiological target tissues
of treatment with growth promoters. In the study regarding
the effects of Ralgro(Zeranol) and Finaplix H(Trenbolone
Acetate) on gene expression in different tissues, the effects on
two different muscles (neck muscle and hind limb muscle) were
quantified. Treatment with Finaplix Hsignificantly influenced
6 genes in the neck muscle and also 6 genes in the hind limb
muscle, whereas only hexokinase and lactate-dehydrogenase,
key enzymes in glycolysis, were regulated in both muscle types.
Ralgroinfluenced the expression of 3 genes in the neck
muscle and 4 genes in the hind limb muscle whereas only
IGF-1 was significantly up-regulated in both tissues.[26]These
three genes could act as potential biomarkers for the different
treatments.
The liver plays an important role in steroid metabolism. It is
involved in hormone decomposition and in the production of
cholesterol, the precursor for all steroid hormones. Therefore
liver is also an interesting target organ for analyzing the effects
of steroid hormones on its transcriptome. It could be shown
that Finaplixinfluenced the expression of 9 out of 18 measured
genesandRalgroinfluenced4genesontheleveloftranscription,
whereasonlytheapoptosisregulatorFasLandtheinsulinreceptor
α (IRα) were influenced by both treatments.[26]This indicates that
androgens affect the liver in a higher manner than estrogens. The
combinationofbothEstradiolplusTrenboloneAcetate,influenced
the expression of 11 out of 4 analyzed genes in the liver of
heifers.[31]IRα that was already regulated in study 1 also showed
significant changes in gene expression caused by the treatment,
and thus it is a promising biomarker candidate. In study 2, the
expression profile of microRNA (miRNA) was also regarded in the
liver. miRNAs belong to the class of non-coding small RNAs and
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I. Riedmaier, M. W. Pfaffl and H. H. D. Meyer
(A)(B)
Figure 1. PCA and HCA of results obtained from vaginal smear combined with results obtained from blood. (A) PCA: grey diamonds represent samples
of untreated controls,black stars representsamples of treated animals; (B) HCA.
are approximately 22bp of length. They are part of the post-
transcriptional regulation of different important physiological
processes like differentiation, proliferation, and apoptosis by
inhibiting translation or degradation of specific mRNAs.[46]In
molecular medicine, for example, cancer research, miRNAs have
shown to be specifically expressed in different diseases and
tissues and can so act as potential biomarkers.[47–49]There is
little knowledge about the expression and the physiological
function of miRNA in cattle. Thus finding miRNA biomarker
candidates by screening the literature for interesting miRNAs is
notapromisingapproach.Thereforeaholisticapproachanalyzing
many miRNAs in one run was taken. miRNA expression of three
randomly picked samples from each treatment group (untreated
control and treated animals) was analyzed using a ready-to-use
PCR Array with 730 human miRNAs. This Array was chosen,
because no such possibilities for bovine miRNA exist and it is
known that miRNAs are highly conserved between the different
species.[46]Promising significantly regulated miRNA candidates
were then analyzed in all 18 samples (9 untreated controls and
9 treated animals) using single assay miRNA RT-PCR. From the
730 quantified miRNAs, 22 were significantly up-regulated and 14
were significantly down-regulated whereas 7 additional miRNAs
showed a trend to up-regulation and also 7 additional miRNAs
showedatrendtodown-regulation.FromtheseregulatedmiRNAs,
11 were quantified with single assay PCR. They were chosen
by their fold regulation, their physiological relevance and their
homologytobovinemiRNA.Fiveofthesegenesshowedsignificant
regulation regarding all 18 samples and these miRNAs can act as
first miRNA biomarker candidates for treatment of heifers with
Revalor H.[46]
As in human sports, blood will also be an interesting matrix
for biomarker screening in farm animals, because blood can be
taken from the living individual in a non-invasive form and so
controls could take place already at the farms and not only at the
slaughter house. The effects of Trenbolone Acetate plus Estradiol
(Revalor H) on gene expression in whole blood of heifers were
investigated. Eleven out of 36 tested genes showed significant
changes, whereas only the glucocorticoid receptor (GRα) and
interleukin 1α (IL-1α) were significantly regulated at more than
one sampling time point.[32]
The usefulness of biostatistical tools for the
development of geneexpression biomarkers
All these results indicate that it will be hardly possible to detect
one or two specific biomarkers whose expression will be changed
under treatment with steroid hormones. But the identification of
a pattern of regulated genes seems to be auspicious. The most
important question is how to extract the needed information
from these data. There are different biostatistical methods for
dimensionality reduction available to represent those sets of data
in far fewer dimensions.[50]These methods have to be combined
withpatternrecognitiontechnologiestoidentifyandvisualizethe
desired information.[18]
To take more than three genes into account, multivariate
analysis methods like principal components analysis (PCA)
or hierarchical cluster analysis (HCA) are required. Principal
componentsanalysisreducesmultidimensionaldata setstolower
dimensions called ‘principal components’.[51,52]Each analyzed
sample will be represented by one spot which results from
diminishingallsignificantlyregulatedgenesofonespecificsample
to two principal components. This method has effectively been
employedtovisualizeatreatmentpatterninprimateblood,bovine
liver, uterus, ovaries and vaginal smear.[23,24,31,32,43,46]In uterine
endometriumandovary,PCAresultsobtainedfrombothtissuesin
combinationshowedabetterseparationbetweenthegroupsthan
by employing the data obtained from each individual tissue.[23]
In bovine liver, the combination of mRNA and miRNA data also
resulted in a better visible separation between the treatment
groups.[46]In bovine vaginal smear, it could be observed that the
incorporationofallanalyzedgenesshowedbetterseparationthan
only regarding significantly regulated genes.[24]In combination
withtheresultsobtainedinbloodcells,aneffectivevisualizationof
a treatment pattern could be achieved(Figure 1A). These findings
indicate that PCA is a good tool for pattern recognition in gene
expression biomarker research.
A further promising method for the visualization of treatment
patternsinthesestudiesishierarchicalclusteranalysis(HCA).Using
HCA, the hierarchical order is represented by a tree dendogram
in which related samples are more closely together than samples
that are more different.[52]The results obtained in vaginal smear
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Figure 2. Workflowofthetranscriptomicapproachtofindgeneexpression
biomarkers to trace the abuse of anabolic steroids.
were additionally analyzed using this method resulting in a tree
where the treated or the untreated samples respectively are close
together and the group of treated samples is separated from the
group of untreated samples.[24]Here again the combination with
the results of vaginal smear and blood in one HCA resulted in a
clear separation of treated and untreated animals (Figure 1B).
Due to high biological variance between individuals caused
by environmental conditions or genetic diversity that can be
observed by the high spread of the control animals in PCA,[53]
a higher number of control animals will be required in future
experiments.
Conclusions
All these results indicate that the use of transcriptomics is
a promising way to develop new screening methods for the
detectionofthemisuseofanabolicsteroidsbasedonphysiological
changes caused by these substances. Figure 2 displays the
workflow for a successful identification of gene expression
biomarkers to screen for the abuse of anabolic agents. Most
of the presented studies were performed in cattle, as the abuse
of growth promoters is also a problem in animal husbandry. The
results obtained in human hair papilla cells or in primate and
bovine blood indicate that this approach is also a promising way
to develop new screening methods useful in doping control. The
choice of the target tissue or matrixfor humans isa big challenge,
because the analyzed tissue/matrix has to been taken in a non-
invasive form. Body fluids like blood or urine, which are already
used in doping control, will be good candidates. The influence
of steroid hormones on blood cells in cattle and primates were
alreadyshowninourlab.Afuturechallengewillbetoestablishan
RNA extraction method for urine samples and afterwards analyze
gene expression.
Another important observation is that there are no genes
regulated in all analyzed tissue. This indicates that each tissue
hastobeanalyzedseparatelyandthatgeneexpressionbiomarker
patterns will be tissue specific.
For the identification of more potential candidate genes, a
holisticapproachforgeneexpressionanalysiswillbehelpful.Avery
new approach to screen for changes in gene expression is RNA-
Sequencing(RNA-Seq).Withthismethodthewholetranscriptome
of a biological sample is sequenced and the quantity of each RNA
sequencepresentcanbedetermined.Thismethodisverysensitive
because only one transcript of a specific gene is detectable.[33,34]
Even with this method, it seems hardly possible to identify
one specific biomarker; rather will there be a pattern of genes
whose expression is influenced by treatment with anabolic
steroid hormones. Using biostatistical tools, like PCA or HCA
theidentificationofatreatmentspecificexpressionpatternseems
promising. Another possibility is to combine the transcriptomic
approach with other -omic technologies, like proteomics and
metabolomics to find more biomarker candidates on other
biological levels.[18]
A future challenge will be the detection of gene expression
biomarkers for newly designed substances, hormone cocktails,
the illegal use of erythropoietin, or other kinds of manipulation
like gene or blood doping.
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