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Aprahamian, F.

Publications and source records attributed to Aprahamian, F..

2 recordsLinked to original sources

Smurfness-based two-phase model of ageing helps deconvolve the ageing transcriptional signature

Ageing is characterised at the molecular level by six transcriptional hallmarks of ageing, that are commonly described as progressively affected as time passes. By contrast, the Smurf assay separates high-and-constant-mortality risk individuals from healthy, zero-mortality risk individuals, based on increased intestinal permeability. Performing whole body total RNA sequencing, we found that Smurfness distinguishes transcriptional changes associated with chronological age from those associated with biological age. We show that transcriptional heterogeneity increases with chronological age in non-Smurf individuals preceding the other five hallmarks of ageing, that are specifically associated with the Smurf state. Using this approach, we also devise targeted pro-longevity genetic interventions delaying entry in the Smurf state. We anticipate that increased attention to the evolutionary conserved Smurf phenotype will bring about significant advances in our understanding of the mechanisms of ageing. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=150 HEIGHT=200 SRC="FIGDIR/small/517330v5_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@37b39org.highwire.dtl.DTLVardef@8ef8f0org.highwire.dtl.DTLVardef@797299org.highwire.dtl.DTLVardef@1529b0d_HPS_FORMAT_FIGEXP M_FIG The two-phase model of ageing allows to study separately the effect of chronological and physiological age. (A) Classic approaches for studying ageing tend to consider it as a black box affecting all individuals progressively from birth to death. Instead, the Smurf phenotype shows that life can be divided into two consecutive phases separated by an abrupt transition. (B) All individuals undergo this transition at a different moment in their life, prior to death. This allows us to switch from population based approaches, comparing bulks of age-matched individuals through time, to individuals-centred approaches relying on direct access to their transition status. (C) Such paradigm shift shows that hallmarks of ageing long thought to progressively change with age are actually mostly affected in a growing proportion of Smurfs, allowing for the identification of the chain of events accompanying ageing and death from natural causes. (D) By studying the behaviour of the ageing transcriptome as a function of chronological age and Smurfness separately, we demonstrate that the progressively changing transcriptional ageing signature, as described in Frenk & Houseley (2018), is in fact the convolution changes accompanying chronological age signature (increased transcriptional noise) and changes associated with Smurfness (or biological age) signature (increased stress response and inflammation, decreased expression of ribosomal and mitochondrial genes). We also identified a hallmark partially associated with only old Smurfs (ATH5), suggesting that chronological age can affect, late in life, the Smurf response. C_FIG

systems biology↗

Multi-omic rejuvenation of naturally aged tissues by a single cycle of transient reprogramming

The expression of the pluripotency factors OCT4, SOX2, KLF4 and MYC (OSKM) can convert somatic differentiated cells into pluripotent stem cells in a process known as reprogramming. Notably, cycles of brief OSKM expression do not change cell identity but can reverse markers of aging in cells and extend longevity in progeroid mice. However, little is known about the mechanisms involved. Here, we have studied changes in the DNA methylome, transcriptome and metabolome in naturally aged mice subject to a single period of transient OSKM expression. We found that this is sufficient to reverse DNA methylation changes that occur upon aging in the pancreas, liver, spleen and blood. Similarly, we observed reversion of transcriptional changes, especially regarding biological processes known to change during aging. Finally, some serum metabolites altered with aging were also restored to young levels upon transient reprogramming. These observations indicate that a single period of OSKM expression can drive epigenetic, transcriptomic and metabolomic changes towards a younger configuration in multiple tissues and in the serum.

cell biology↗