The expression signature of in vitrosenescence resembles mouse but not human aging

Wennmalm Kristian, Wahlestedt Claes, Larsson Ola, Larsson

Description

The biological mechanisms that underlie aging have not yet been fully identified. Senescence, a phenomenon occurring in vitro , limits the number of cell divisions in mammalian cell cultures and has been suggested to contribute to aging. Results We investigated whether the changes in gene expression that occur during mammalian aging and induction of cellular senescence are similar. We compared changes of gene expression in seven microarray datasets from aging human, mouse and rat, as well as four microarray datasets from senescent cells of man and mouse. The datasets were publicly available or obtained from other laboratories. Correlation measures were used to establish similarities of the expression profiles and gene ontology analyses to identify functional groups of genes that are co-regulated. Robust similarities were established between aging in different species and tissues, indicating that there is an aging transcriptome. Although some cross-species comparisons displayed high correlation, intra-species similarities were more reliable. Similarly, a senescence transcriptome was demonstrated that is conserved across cell types. A similarity between the expression signatures of cellular senescence and aging could be established in mouse, but not in human. Conclusion Our study is the first to use microarray data from several studies and laboratories for dissection of a complex biological phenotype. We demonstrate the presence of a mammalian aging transcriptome, and discuss why similarity between cellular senescence and aging is apparent in aging mice only.

Informations

• Publié par: biomed
• Publié le: 01 janvier 2005
• Nombre de lectures: 1
• Langue: English

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comment reviews reports deposited research refereed research interactions information
Open AccessWee2005Vto allumennmal. 6,m Issue 13, Article R109Research
The expression signature of in vitro senescence resembles mouse
but not human aging
* * *†Kristian Wennmalm , Claes Wahlestedt and Ola Larsson
* †Addresses: Center for Genomics and Bioinformatics, Karolinska Institutet, Berzelius väg 35, 171 77 Stockholm, Sweden. University of
Minnesota, Department of Medicine, Minneapolis, MN 55455, USA.
Correspondence: Ola Larsson. E-mail: [e-mail]
Published: 16 December 2005 Received: 16 May 2005
Revised: 25 July 2005
Genome Biology 2005, 6:R109 (doi:10.1186/gb-2005-6-13-r109)
Accepted: 17 November 2005
The electronic version of this article is the complete one and can be
found online at http://genomebiology.com/2005/6/13/R109
© 2005 Wennmalm et al.; licensee BioMed Central Ltd.
This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which
permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Abstract
Background: The biological mechanisms that underlie aging have not yet been fully identified.
Senescence, a phenomenon occurring in vitro, limits the number of cell divisions in mammalian cell
cultures and has been suggested to contribute to aging.
Results: We investigated whether the changes in gene expression that occur during mammalian
aging and induction of cellular senescence are similar. We compared changes of gene expression in
seven microarray datasets from aging human, mouse and rat, as well as four microarray datasets
from senescent cells of man and mouse. The datasets were publicly available or obtained from
other laboratories. Correlation measures were used to establish similarities of the expression
profiles and gene ontology analyses to identify functional groups of genes that are co-regulated.
Robust similarities were established between aging in different species and tissues, indicating that
there is an aging transcriptome. Although some cross-species comparisons displayed high
correlation, intra-species similarities were more reliable. Similarly, a senescence transcriptome was
demonstrated that is conserved across cell types. A similarity between the expression signatures
of cellular senescence and aging could be established in mouse, but not in human.
Conclusion: Our study is the first to use microarray data from several studies and laboratories
for dissection of a complex biological phenotype. We demonstrate the presence of a mammalian
aging transcriptome, and discuss why similarity between cellular senescence and aging is apparent
in aging mice only.
eral studies have shown a correlation between in vivo and inBackground
In vitro senescence was discovered as a phenomenon that vitro life span, these results have been questioned and re-
limits the replicative lifespan of cells grown in culture, and evaluated [4]. A more convincing approach to establish a link
was immediately hypothesised to be a possible cause of between cellular senescence and aging would be to detect
human aging [1,2]. During several decades, attempts have senescent cells in vivo. Unfortunately, no good senescence
been made to establish a link between the age and the replica- marker exists, except for senescence-associated β-galactosi-
tive potential of cells derived from humans [3]. Although sev- dase (SAβ-gal) staining [5]. This technique has been used
Genome Biology 2005, 6:R109R109.2 Genome Biology 2005, Volume 6, Issue 13, Article R109 Wennmalm et al. http://genomebiology.com/2005/6/13/R109
Table 1
Included aging studies
Study Chip type Species Tissue Age
Welle et al. [26] HG U133 A+B Human Skeletal muscle Old (n = 16) 66-77 years
Young (n = 15) 21-24 years
Lu et al. [27] HG U95 Av2 Human Frontal cortex of brain Old (n = 11) 73-106 years
Young (n = 10) 26-42 years
Rodwell et al. [28] HG U133 A+B Human Kidney cortex and medulla Old (n = 28) 72-92 years
Young (n = 11) 27-45 years
Lee et al. [25] MU 6500 Mouse Cerebellum and neocortex Old (n = 2/3*) 30 months
of brain
Young (n = 3) 5 months
Lee et al. [29] MG U74 A Mouse Heart Old (n = 5) 30 months
Young (n = 5) 5 months
Blalock et al. [30] RG U34 A Rat Hippocampus, brain Old (n = 10) 24 months
Young (n = 9) 4 months
All studies of aging that were used in the aging to aging, and the aging to senescence comparisons are listed. Platform, species, tissues and grouping
details for each study are shown. The Lee et al. [25] data was analyzed as two separate datasets, as it contained data from two different tissues -
cerebellum and neocortex, and data on the aging CNS of other species was available for comparison.
extensively but its specificity has been questioned [6]. A cor- human. This indicates differences between human and
relation between human age and an accumulation of SA-β mouse aging and suggests that senescence might contribute
GAL staining cells has been reported [5] but, for unknown to aging in mice but not humans.
reasons, could not be repeated [4]. In mice, increased SAβ-
GAL staining has been reported in animals harbouring the
Werner mutation and short telomeres, which gives rise to an Results
aging phenotype [7], following chemotherapeutic treatment A shared expression profile of aging in mammals
[8], in liver regeneration after partial hepatectomy in animals Previous studies have indicated that there is a conserved
with short telomeres [9] and upon aging [10]. These studies genetic program for aging across species of low complexity
indicate that senescent cells could exist in vivo but do not pro- [11]. To date, however, no comprehensive data have indicated
vide any measure of their relative contribution to the aging that aging in mammals is conserved across species. If a
process. genetic program for aging exists in mammals, it could be con-
served across species independent of tissue type, or it could
In the current study, publicly available microarray data be organ specific. Given the expansion of the microarray field
describing both aging and in vitro senescence were used. By during the past years, resulting in an accumulation of expres-
comparing the expression changes that occur during aging in sion datasets in the literature and public databases, we
human, mouse and rat across several tissues, we conclude thought that sufficient data were present to enable a study of
that there is a mammalian aging expression signature. This gene expression signatures during mammalian aging. The
expression signature is mainly conserved within species, multitude of different platforms used to study global expres-
independent of organ, but also highly conserved between sion changes makes such an approach challenging from a
some organs between species. Using a similar approach, we data analysis perspective. To make our study possible, we had
also establish that the expression signature of in vitro senes- to control for a possible bias across platforms and species. To
cence has similarity to that of in vivo aging in mouse but not achieve this, we calculated a log-transformed ratio of change
FigMetuhroed 1 fo (ser qu e following page)antifying similarity between gene expression profiles and assessing significance
Method for quantifying similarity between gene expression profiles and assessing significance. (a) The aging to young ratio of gene expression is calculated
and log-transformed for all genes or orthologous genes present on both of the compared microarrays. Ortholog pairs need to be identified in cross-
species comparisons. (b) Two example scatter plots for comparisons of change in gene expression with age. The calculated correlations (Pearson; R) are
displayed to the lower right in the plots. (c-e) A distribution of correlations is produced by randomly pairing the genes present on both microarrays
10,000 times and calculating the Pearson correlation for each permutation. The distribution of random correlations (Monte Carlo simulation) is displayed
as a density curve in (e). The actual correlation, indicated by an arrow in (e), can then be compared to the random distribution of correlations.
Genome Biology 2005, 6:R109comment reviews reports deposited research refereed research interactions information
http://genomebiology.com/2005/6/13/R109 Genome Biology 2005, Volume 6, Issue 13, Article R109 Wennmalm et al. R109.3
(a) Aging study yAging study x
log2 (aging/young) log2 (aging/young)
Gene 1, 0.562 Gene 1, 1.312
2, 0.023 2, - 0.19
Find --, -- --, -- corresponding
--, --,genes/orthologous
--, -- --, --genes
between studies --, --,
--, -- --, --
Gene n