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. 2018 Jan 30;9(1):327.
doi: 10.1038/s41467-017-02395-2.

Transcriptomic alterations during ageing reflect the shift from cancer to degenerative diseases in the elderly

Peer Aramillo Irizar  1 , Sascha Schäuble  2   3 , Daniela Esser  1 , Marco Groth  3   4 , Christiane Frahm  3   5 , Steffen Priebe  3   6 , Mario Baumgart  3   7 , Nils Hartmann  3   8 , Shiva Marthandan  3   9 , Uwe Menzel  3   6 , Jule Müller  5 , Silvio Schmidt  3   5 , Volker Ast  10   11 , Amke Caliebe  12 , Rainer König  10   11 , Michael Krawczak  12 , Michael Ristow  3   13 , Stefan Schuster  3   14 , Alessandro Cellerino  3   7   15 , Stephan Diekmann  3   16 , Christoph Englert  3   8   17 , Peter Hemmerich  3   9 , Jürgen Sühnel  3   18 , Reinhard Guthke  3   6 , Otto W Witte  3   5 , Matthias Platzer  3   4 , Eytan Ruppin  19 , Christoph Kaleta  20   21
Affiliations

Transcriptomic alterations during ageing reflect the shift from cancer to degenerative diseases in the elderly

Peer Aramillo Irizar et al. Nat Commun. .

Erratum in

Abstract

Disease epidemiology during ageing shows a transition from cancer to degenerative chronic disorders as dominant contributors to mortality in the old. Nevertheless, it has remained unclear to what extent molecular signatures of ageing reflect this phenomenon. Here we report on the identification of a conserved transcriptomic signature of ageing based on gene expression data from four vertebrate species across four tissues. We find that ageing-associated transcriptomic changes follow trajectories similar to the transcriptional alterations observed in degenerative ageing diseases but are in opposite direction to the transcriptomic alterations observed in cancer. We confirm the existence of a similar antagonism on the genomic level, where a majority of shared risk alleles which increase the risk of cancer decrease the risk of chronic degenerative disorders and vice versa. These results reveal a fundamental trade-off between cancer and degenerative ageing diseases that sheds light on the pronounced shift in their epidemiology during ageing.

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Conflict of interest statement

The authors declare no competing financial interests.

Figures

Fig. 1
Fig. 1
Epidemiology of ageing-associated diseases. a Contribution of different disease categories to total human mortality (Supplementary Note 1). b First diagnosis (incidence) of ageing-associated diseases and several cancer types (inset) across age groups. Lines across several age groups indicate cases in which only data combining several age groups was available (Supplementary Note 1). c Malignant transformation rates across 34 types of cancer across age groups. The center line corresponds to the median, box limits to 25th and 75th percentiles and whiskers to 1.5 times the interquartile range
Fig. 2
Fig. 2
Ageing-associated transcriptional changes across species and tissues. The top 50 differentially expressed processes between young and old individuals in the cross-species comparison are shown across all three ontologies (indicated in front of the labels). The first column displays the main processes altered across all samples followed by columns presenting the results for individual species and tissues across species (only significantly ageing-regulated processes are displayed). Processes are grouped into functional categories and ordered in each category separately according to the p-value of ageing (see Methods). Abbreviations: HMP human metabolic pathways, H.s. Homo sapiens, GO gene ontology, KEGG Kyoto Encyclopedia of Genes and Genome
Fig. 3
Fig. 3
Association of ageing-associated gene expression changes with ageing diseases and lifespan. a Ageing-mediated disease alignment scores (AMDA scores) for different ageing (x axis) and disease data sets (y axis). Abbreviations: AD Alzheimer’s disease, CAD coronary artery disease, CPI cancer proliferation index, cross-cohort cross-cohort study of blood ageing, HMP human metabolic pathways, IR insulin resistance, LL longitudinal ageing data, MCI mild cognitive impairment; SAFHS, San Antonio Family Heart Study. b, c Correlations between activity changes of processes during ageing (x axis) and their lifespan-associations (y axis, Pearson correlation) for N. furzeri (b) and mouse (c). The corresponding test statistics are provided in Supplementary Data 1
Fig. 4
Fig. 4
Role of ageing-regulated processes in disease signature alignment. a For each process, mean foldchanges of genes belonging to that process in the ageing and disease data sets are shown. Processes are sorted by average absolute DAC scores . b DAC scores of 30 top scoring processes across the four major disease categories for all ageing data (first column) and for human ageing data solely (second column). c, d Multi-dimensional scaling plot of disease and ageing-associated gene expression changes based on (c) process foldchanges and (d) gene expression foldchanges. Each point corresponds to a condition (disease or ageing data set); distances indicate similarity in gene expression changes between conditions. Numbers in brackets denote the variance explained by each axis. Abbreviations: CVD cardiovascular diseases, NDD neurodegenerative diseases, T2D type 2 diabetes
Fig. 5
Fig. 5
Antagonism between cancer and degenerative ageing diseases on the genetic level. a Shared synergistic and antagonistic risk SNPs between cancer and degenerative ageing diseases (DAD). “DAD total” indicates the total number of synergistic and antagonistic risk SNPs in the pairwise comparison between all three categories of degenerative ageing diseases. The total number of independent genomic loci in which the shared SNPs are contained is displayed on top of the bars. CVD cardiovascular diseases, NDD neurodegenerative diseases, T2D type 2 diabetes. b Randomization tests. Distributions depict the frequency at which the corresponding number of synergistic, antagonistic and total number of shared risk SNPs were encountered between cancer risk SNPs and randomly drawn risk SNPs from non-ageing-associated traits in 10,000 repetitions. Arrows indicate the actual observed number of antagonistic and total shared risk SNPs between cancer and degenerative ageing diseases. c Same as in b for degenerative ageing diseases instead of cancer
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References

    1. Lopez AD, Mathers CD, Ezzati M, Jamison DT, Murray CJ. Global and regional burden of disease and risk factors, 2001: Systematic analysis of population health data. Lancet. 2006;367:1747–1757. doi: 10.1016/S0140-6736(06)68770-9. - DOI - PubMed
    1. Lopez-Otin C, Blasco MA, Partridge L, Serrano M, Kroemer G. The Hallmarks of Aging. Cell. 2013;153:1194–1217. doi: 10.1016/j.cell.2013.05.039. - DOI - PMC - PubMed
    1. Pettan-Brewer, C. & Treuting, P. M. Practical pathology of aging mice. Pathobiol. Aging Age Relat. Dis. 1, 7202 (2011). - PMC - PubMed
    1. Dean RL, 3rd, et al. Age-Related Differences in Behavior across the Life Span of the C57bl/6j Mouse. Exp. Aging Res. 1981;7:427–451. doi: 10.1080/03610738108259823. - DOI - PubMed
    1. Cellerino A, Valenzano DR, Reichard M. From the bush to the bench: The annual nothobranchius fishes as a new model system in biology. Biol. Rev. Camb. Philos. Soc. 2016;91:511–533. doi: 10.1111/brv.12183. - DOI - PubMed

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