The recent discovery of epigenetic aging clocks – which are highly-accurate aging biomarkers – is having a transformational effect on anti-aging science. Now scientists have access to tools that let them quantify one or more aging processes with an unprecedented level of precision and reproducibility across different tissues.
In 2011, Bocklandt & Horvath at UCLA provided the first strong evidence that DNA methylation levels could generate an accurate biomarker of an aging process. Two years later, Steve Horvath described a novel multi-tissue epigenetic clock based on a set of 353 CpG markers [link to paper]. The background of Shift Bioscience’s founders in mitochondrial biology has given us a unique insight into the biological mechanisms that may underpin multi-tissue epigenetic aging clocks.
THE SHIFT STATE MODEL
It’s been known for some time that cells adapt their transcriptional state and morphological shape in response to stressors. Examples of stressors include DNA damage, mitochondrial dysfunction, toxins, infections and vitamin or mineral deficits.
Picard & Wallace demonstrated in 2014 that increasing the level of pathogenic mitochondrial DNA mutations in a cell triggers an abrupt transcriptional reprogramming. They characterised four discrete states of cells, each with a distinctive morphology and transcriptional profile. Shifts between these states were triggered first at a level of 20%, then at 50% and finally at a 90% level of mutant mtDNA. Fibroblasts also show a distinct morphology change in response to aging, with a substantial loss of dendrites and surface area.
We believe that an underlying shift in cellular functional state drives changes in transcriptional profile, cell morphology and also methylation change in the CpGs sites that make up the epigenetic aging clock. The first of these functional state shifts is from fully functional ‘pristine’ cells, which we possess at birth, to a less metabolically-active protective state. Over time, more and more cells reconfigure their functional state as a protective response to stressors, and we believe this drives epigenetic ageing.
Free radicals are continually created through OXPHOS and cause damage to mitochondria and to mitochondrial DNA. This damage acts as a continuous driver of state shifts (though it is not the only driver). Supporting this model, we demonstrated that acute mitochondrial dysfunction (an intracellular internal stressor) causes an unprecedented acceleration of the epigenetic aging clock.
Our model proposes a second state shift that can be induced by a number of different stessors. In this second shift, cells transition from the protective state to the SASP state. (SASP is short for Senescence-Associated Secretory Phenotype and is a previously described state of senescent cells)
State shifts are proposed to change the shape, epigenetic profile and transcriptional profile of the cell, but do not affect the biological role of the cell. A fibroblast undergoing a state shift remains a fibroblast. Because it is less metabolically active, it is unable to contribute to overall tissue function at the same level as it did in the original pristine state. State shifts are sticky. They can be reversed but it takes a large, sustained effort to do so. Like quicksand, the longer a cell exists in the newly-adopted state, the harder it is to escape.
EFFECTS OF SMALL MOLECULES
Shift Bioscience has identified small molecules which can modulate these state shifts. We are using the epigenetic clock to measure the magnitude of these shift effects. We are developing a platform that allows us to run standardised comparisons of molecules more quickly and conveniently. This will help us to identify novel molecules (and combinations of molecules) which will be even more effective in restoring cellular function.
Once identified, the efficacy of these shift molecules or combinations can then be validated with model systems which mimic more closely a particular cosmetic or clinical application in vitro.
CAN THE AGING PROCESS BE REVERSED IN HUMANS?
Three studies provide early evidence that epigenetic age can be reversed in humans.
The first was Chen & Zhu’s 2018 study. A randomised clinical trial had been previously conducted with 70 overweight/obese African Americans of average age 26 with serum vitamin D3 deficiency. Subjects were treated with vitamin D3 supplements or placebo over a 16 week period. The DNA methylation age of 51 participants was measured using the Hannum and Horvath locks. The high dose group showed a reduction in Horvath epigenetic aging of 1.85 years (p =0.046).
The second was the Pavanello & Iliceto study published in 2019. 20 subjects took part in intensive relaxation training for 60 days. In the younger cohort (6 subjects aged 28 – 39) a reduction in epigenetic age of 4.66 years (p=0.053).
Most recently, in September 2019 Fahy and Horath reported the results of the TRIIM trial. 9 subjects were treated with a cocktail of drugs (HGH, DHEA and metformin) intended to regenerate the thymus. Over a 12 month period this led to a reduction in epigenetic age of 2.5 years (p=0.005) as measured by the Horvath clock.
APPLICATIONS OF SHIFT MOLECULES – COSMETICS
Molecules identified by our state shift platform show the potential to reverse the fundamental rate of aging of the skin as measured by the epigenetic clock. Two types of skin aging usually occur in parallel – photo-aging which is caused by excessive sun exposure and chronological aging, which manifests as loss of elasticity and thinning of the skin and is caused by the passage of time.
The effects of photo-aging can be mitigated by suncream or reversed by application of skin care products containing retinol. The molecular basis of this effect was described by Shao & Quan in the International Journal of Cosmetics Science in 2017. Our aim is to develop the first molecules for cosmetic applications that show a robust effect in reversing the chronological aging of the skin.
In U2OS cells (human cancer cells) mitochondria (red) form extensive, interconnected networks. Nuclei are stained blue and cells are transfected with GFP (green).
Dr Alan Huett, Huett Lab, University of Nottingham
Visit source page
Please enter your email address to download the white paper.