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. 2021 Dec 19;13(24):25694-25716.
doi: 10.18632/aging.203788. Epub 2021 Dec 19.

Age-dependent expression changes of circadian system-related genes reveal a potentially conserved link to aging

Affiliations

Age-dependent expression changes of circadian system-related genes reveal a potentially conserved link to aging

Emanuel Barth et al. Aging (Albany NY). .

Abstract

The circadian clock system influences the biology of life by establishing circadian rhythms in organisms, tissues, and cells, thus regulating essential biological processes based on the day/night cycle. Circadian rhythms change over a lifetime due to maturation and aging, and disturbances in the control of the circadian system are associated with several age-related pathologies. However, the impact of chronobiology and the circadian system on healthy organ and tissue aging remains largely unknown. Whether aging-related changes of the circadian system's regulation follow a conserved pattern across different species and tissues, hence representing a common driving force of aging, is unclear. Based on a cross-sectional transcriptome analysis covering 329 RNA-Seq libraries, we provide indications that the circadian system is subjected to aging-related gene alterations shared between evolutionarily distinct species, such as Homo sapiens, Mus musculus, Danio rerio, and Nothobranchius furzeri. We discovered differentially expressed genes by comparing tissue-specific transcriptional profiles of mature, aged, and old-age individuals and report on six genes (per2, dec2, cirp, klf10, nfil3, and dbp) of the circadian system, which show conserved aging-related expression patterns in four organs of the species examined. Our results illustrate how the circadian system and aging might influence each other in various tissues over a long lifespan and conceptually complement previous studies tracking short-term diurnal and nocturnal gene expression oscillations.

Keywords: RNA-Seq; aging; circadian clock system; circadian rhythm; inter-species comparison; longevity.

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Conflict of interest statement

CONFLICTS OF INTEREST: The authors declare no conflicts of interest related to this study.

Figures

Figure 1
Figure 1
(A) Lifespan comparison: to align the species-specific chronological ages to biological age categories comparable between different species, the total individual’s lifetime, represented by the length of the lifetime axis, was subdivided by index stages. These stages were the biological stages corresponding to maturation, the mean survival age, the 10% survival rate, and the highest age reported for an individual belonging to the respective species. The time intervals between the resulting intersections were normalized linearly for the mean survival age. Thus, the sampling time points examined in this study for a specific species (blue circles) matched the biological age category in all the other species. (B) Data sampling scheme and categorization of the high-throughput transcriptomic data according to age parameters: for each of the 4 species of interest, up to 4 tissue types were sampled at mature, aged and old-age stages, from which 3 comparisons were deduced to identify DEGs during early aging (mature vs. aged), late aging (mature vs. old-age), and longevity (aged vs. old-age).
Figure 2
Figure 2
Regulatory network of vertebrate core CR genes, including their transcriptional, post-transcriptional, and post-translational interaction partners that constitute activating and inhibitory feedback loops. Further information is accessible in the online supplement https://osf.io/ctv2r/.
Figure 3
Figure 3
Heatmap representing log2 fold changes of the CR-related genes for the species, tissues and age categories investigated. DEG up-regulations in the course of aging are indicated by positive values displayed in blue, whereas down-regulations are shown by negative values in red. Significant gene expression alterations are highlighted in bold. The abbreviation longe. stands for the longevity age comparison (aged vs. old-age samples). For details, see the online supplement https://osf.io/9c3j4/.
Figure 4
Figure 4
Inter-species overlap of CR-related genes regulated by aging. Of the 42 identified DEGs, 28 were identified within 2 or more species, and 14 DEGs to be species-specific. Tissue-specific Venn diagrams can be found in the online supplement: https://osf.io/3mgc6/.
Figure 5
Figure 5
Age-dependent alterations in the robustness of CR-related gene expression. For the 3 age comparisons, different tissues, and species, the measured variance in the expression of CR-related genes is displayed as change in standard deviation. The extrema of the box plots represent the respective 2.5% percentiles. Age groups (M – mature, A – aged, OA – old-age) are compared for their statistical significance: *p-value ≤ 0.01, **p-value ≤ 0.001, ***p-value ≤ 0.0001. Details can be found in the online supplement: https://osf.io/g9uqz/.
Figure 6
Figure 6
Matching of our CR-related DEGs evidenced to be regulated with aging with a curated human CR network. The core clock network (CCN; inner ring) is comprised of a positive (orange) and negative (purple) branch of core clock regulators and has been expanded to an extended core clock network (ECCN; middle ring) as determined by chronobiological meta-analyses in humans [84]. The majority of CR-related genes identified in the present study overlaps (represented in bold) with the human CCN (100% overlap) and ECCN (65.5% overlap). The ECCN was complemented by 13 CR-related genes defined by our aging-related interspecies approach (outer ring), two of which overlapped with newly designated CR genes (bold in outer ring [84]). By mapping to a curated biomedical aging database [101], 85% of the presented interspecies (dark blue background) or human (light blue background) CR-related genes were identified to be aging-associated. The remaining factors (white background) have not yet been annotated to aging but might represent new candidates. *, curated CR-related genes without age-related differential expression within the interspecies comparison.

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