Download Multifarious microarray-based gene expression patterns in response

J Appl Physiol 102: 7– 8, 2007;
doi:10.1152/japplphysiol.01079.2006.
Invited Editorial
Multifarious microarray-based gene expression patterns in response
to exercise
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striction, and asthma [arachidonate 5-lipoxgenase (ALOX5);
ALOX5-activating-protein (2)] were significantly affected.
New findings in Büttner et al. (1) were regulations of matrix
metalloproteinase-9, potassium channel-associated-proteins,
S100P, YES-1 oncogene, and natural killer cell receptor
CD160. For a number of the significant genes, they suggest a
nice interaction model. These results have the potential to
provide novel insights into the molecular mechanisms of exercise.
Despite these interesting results, there are some methodological influencing conditions (different microarray platforms,
RNA and array preparation methods, sampling points, cell
populations) that make the comparison of the real exerciserelated responses difficult. Cross-platform comparisons identify only a small fraction of genes similarly affected by exercise. Matching Büttner et al. (1) (whole gene array) with Zieker
et al. (8) (homemade cDNA array) revealed only seven similarly affected genes. A list of just 11 concordant genes was the
result comparing Büttner with Hilberg et al. (4) (custom-made
oligo array), and only three genes in Connolly et al. (2) (whole
gene array) vs. Zieker et al. (8).
Using the same microarray platform makes comparisons
easier. Connolly et al. (2) vs. Büttner et al. (1) results in more
coincident expression changes (53 significant genes) despite
different exercise protocols, subjects, sampling points, cell
populations, and RNA preparation methods. It is interesting to
note that only a rather limited number of genes of the 14,500
sequences on the whole gene chip were significantly altered by
exercise. This indicates the existence of particular exerciseresponsive genes. All concordant genes may be accounted for
as exercise specific and used to design a special “exercise stress
chip.” Customized arrays will allow one to quickly apply
experimental results obtained with one big array to subsequent,
specified experiments. Such an application-specific stress chip
may be used to monitor the physiological and pathophysiological exercise response (8).
However, more interesting are the unequal expression profiles that may be associated with the different exercise protocols. One of the aims of microarray analysis is to differentiate
samples according to their pattern of regulated genes. At this
point, the procedure of Büttner et al. (1) becomes eminently
important. Gene expression in response to two exercise protocols exclusively differing in maximal O2 uptake (60 vs. 80 %)
but otherwise identical conditions was investigated. This design specifically allows one to analyze the influence of exercise
intensity. The magnitude of the changes of a pattern of genes
could be related to the strength of exercise. Furthermore, the
reproducibility of the technology was illustrated by comparable
basal gene expression before both runs.
Despite differences in methodology and findings, the exercise-microarray studies demonstrate acute bouts of exercise
produced time- and intensity-dependent patterns of gene expression that are easily detectable in circulating peripheral
blood cells, which can be easily obtained. Significant new
exercise-specific candidate genes may give hints to regulatory
pathways that were activated by exercise stress. The analysis of
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responses of leukocytes to physical
exercise are well known. They are dependent on type, intensity, and duration of exercise; training status of athletes; and
environmental conditions. Nevertheless, we are far away from
having a complete list of changed genes and from the complete
understanding of the regulatory mechanisms. Microarrays are
widely used tools for the comprehensive analysis of gene
expression and may be applied to investigate this issue in a
systematic way. They enable the analysis of hundreds to
thousands of genes simultaneously. Specific patterns of gene
expression, so-called gene expression fingerprints, and/or new
candidate genes in a certain situation can be found. Whole
genome arrays may even facilitate the analysis of genes that
were until that time not associated with exercise. These data
may help to characterize and define the complex stress response to acute and chronic exercise on the molecular level.
In humans, the easiest accessible source to perform measurements of stress parameters on the cellular and molecular
level is peripheral blood. The microarray analysis of leukocytes after exercise allows the genetic profiling of immunocompetent cells in response to exercise to gain more insight
into mechanisms through which exercise changes immune
function. Moreover, changes of certain genes in leukocytes
may serve as surrogate markers for systemic or local exerciseinduced modifications (7) and will potentially obviate the need
of muscle biopsies.
The study of Büttner et al. (1) in this issue of the Journal of
Applied Physiology presents a very well-designed study using
the microarray technology. They analyzed the gene expression
of leukocytes in response to both moderate and exhaustive
treadmill runs in the same individuals. Notable interindividual
similarities specify characteristic and intensity-dependent gene
expression fingerprints. Some hitherto unknown exercise-responsive genes were revealed. Furthermore, the study confirms
some results of earlier reports.
There are only few previous studies that investigated leukocyte gene expression after physical exercise on a large scale
using microarrays (2– 6, 8, 9). They revealed several interesting candidate genes and component parts that might be important in the exercise response. Inflammatory and heat shock
response genes were mainly affected [heat shock proteins (1, 2,
8), IL-1 receptor antagonist (2, 8), interferon-induced sequences (5), ubiquitin C (5), dual-specific phosphatase-1 (2, 5),
inflammatory protein-1 (2), RANTES (regulated upon activation, normal T-cell expressed, and secreted) (2)] which indicates that exercise-induced hyperthermia and inflammation
might account for at least some of the observed changes in
leukocyte gene expression. However, consistently in all array
studies, IL-6 does not appear to be one of them, in agreement
with the hypothesis that mainly muscle cells produce circulating IL-6 during exercise. Furthermore, genes grouped to cellular communication [CD11c, CD81 (8)], signal transduction
[mitogen-activated protein kinase activating protein kinase 2
(8)], cellular protection [thioredoxin (8)], tumor suppression
[glutathione S-transferase M (8)], growth and repair [epiregulin
(2), PDGF (2), hypoxia-inducible factor-1 (2, 8)], bronchocon-
MULTIPLE GENE EXPRESSION
Invited Editorial
8
J Appl Physiol • VOL
specialized problem-directed chips. Performing longitudinal
and multicenter studies with corresponding specialized chips
may prove and improve microarrays as a valuable diagnostic
tool. Adjusting protocols and compiling common databanks
will make results more readily comparable. The organization
of cooperations or workshops of interested research groups will
help to achieve those goals.
REFERENCES
1. Büttner P, Mosig S, Lechtermann A, Funke H, Mooren FC. Exercise
affects the gene expression profiles of human white blood cells. J Appl
Physiol 102: 26 –36, 2007.
2. Connolly PH, Caiozzo VJ, Zaldivar F, Nemet D, Larson J, Hung SP,
Heck JD, Hatfield GW, Cooper DM. Effects of exercise on gene expression in human peripheral blood mononuclear cells. J Appl Physiol 97:
1461–1469, 2004.
3. Fehrenbach E, Zieker D, Niess AM, Moeller E, Russwurm S, Northoff
H. Microarray technology—the future analyses tool in exercise physiology?
Exerc Immunol Rev 9: 49 –58, 2003.
4. Hilberg T, Deigner HP, Moller E, Claus RA, Ruryk A, Glaser D,
Landre J, Brunkhorst FM, Reinhart K, Gabriel HH, Russwurm S.
Transcription in response to physical stress— clues to the molecular mechanisms of exercise-induced asthma. FASEB J 19: 1492–1494, 2005.
5. Sonna LA, Wenger CB, Flinn S, Sheldon HK, Sawka MN, Lilly CM.
Exertional heat injury and gene expression changes: a DNA microarray
analysis study. J Appl Physiol 96: 1943–1953, 2004.
6. Whistler T, Jones JF, Unger ER, Vernon SD. Exercise responsive genes
measured in peripheral blood of women with chronic fatigue syndrome and
matched control subjects. BMC Physiol 5: 5, 2005.
7. Zeibig J, Karlic H, Lohninger A, Damsgaard R, Smekal G. Do blood
cells mimic gene expression profile alterations known to occur in muscular
adaptation to endurance training? Eur J Appl Physiol 95: 96 –104, 2005.
8. Zieker D, Fehrenbach E, Dietzsch J, Fliegner J, Waidmann M, Nieselt
K, Gebicke-Haerter P, Spanagel R, Simon P, Niess AM, Northoff H.
cDNA microarray analysis reveals novel candidate genes expressed in
human peripheral blood following exhaustive exercise. Physiol Genomics
23: 287–294, 2005.
9. Zieker D, Zieker J, Dietzsch J, Burnet M, Northoff H, Fehrenbach E.
cDNA-microarray analysis as a research tool for expression profiling in
human peripheral blood following exercise. Exerc Immunol Rev 11: 86 –96,
2005.
Elvira Fehrenbach
Institute of Clinical and Experimental Transfusion Medicine
University of Tübingen
Tübingen, Germany
e-mail: [email protected]
102 • JANUARY 2007 •
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exercise-related gene expression profiles or surrogate marker
genes in leukocytes may replace, e.g., muscle biopsies. Especially the study by Büttner et al. (1) verifies that microarray
analysis of leukocytes is a valuable tool to monitor different
training protocols.
Nevertheless, there are also some disadvantages of the
microarray technology: analyzing whole leukocytes is an important limitation in that they represent a heterogeneous cell
population. Measured changes of expression can result from
either actual changes in transcript level within individual cells
or from exercise-induced shifts of subpopulations (8).
Cut-off problems are produced by stringent statistics used to
avoid false-positive results. Out of hundreds to thousands of
genes only the most significant will become relevant. This
problem becomes more obvious as the number of genes on the
chip grows. Last, but not least, gene expression analysis is only
one cornerstone in the exercise response. Additional analysis
of corresponding proteins, functions, and pathways is necessary to yield further information about functional relevance in
exercise.
Conclusively, microarray analysis is applicable to discriminate exercise intensity-dependent gene expression profiles in
human leukocytes. Using a whole genome chip gives novel
insights into the molecular mechanisms of exercise and defines
a group of exercise-specific genes. A subsequently designed
particular “exercise stress chip” will cover individual gene
responses to exercise stress, minimizing cut-off problems and
reducing costs. An exercise-related gene expression fingerprint
may become helpful to characterize the immune response to
different types of exercise and may mirror in part the whole
body response. A better understanding of the pathways associated with normal responses to exercise will provide the basis
for diagnosis and treatment of diseases such as overtraining,
chronic fatigue syndrome (6), asthma (4), and exercise-induced
immune suppression or for evaluating individual training regimes. Potentially, microarray analysis may also be helpful in
doping analysis, which is actually tested in some research
projects (http://www.wada-ama.org/).
In the future, microarray researchers in exercise physiology
should identify compact problems for practice. Meta-analyses
may assist to define clusters of informative genes to make