A test that could predict ageing and death in humans and animals

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Photo by RODOLFO BARRETTO on Unsplash
Photo by RODOLFO BARRETTO on Unsplash

While some of us might feel older than our years, researchers in the US think they have found a new way to accurately estimate how fast your body is ageing compared to your actual chronological age. This new measurement of how fast the cells in our bodies are ageing works across a range of mammals, including mice, rats, macaques, and humans. The team identified genes that were turned up in ageing cells, and others that were turned down, and the researchers created a 'molecular clock' which could predict time to death as accurately as current 'biological clocks'. It might also allow researchers to detect changes based on lifespan-extending interventions or disease, which is something existing methods can't do.

News release

From: Springer Nature

Ageing: ‘Clocks’ to predict ageing and lifespan in mammals

Molecular clocks that can provide accurate estimates of both molecular age and lifespan across multiple mammalian species and tissue types are presented in Nature this week. An analysis of more than 11,000 human, rodent, and primate samples reveals conserved signatures of ageing. This framework may aid the development of targeted interventions to improve longevity.

Ageing is characterized by the accumulation of cellular damage and functional decline, eventually leading to death. Individuals with the same chronological age may age differently on a molecular level, and identifying biomarkers associated with these differences has long interested researchers. Existing methods involve analysing epigenetic modifications (non-genetic alterations) to an individual’s DNA over time, known as their epigenetic clock. However, these clocks can still be difficult to interpret as they do not reflect the activity of specific genes.

Alexander Tyshkovskiy, Vadim Gladyshev and colleagues analyse more than 11,000 genetic transcripts (transcriptomic signatures) from more than 25 tissue types from mice, rats, macaques, and humans. Ageing-related changes to the transcriptome were conserved across species and cell types, enabling the identification of several biomarkers of mammalian ageing. Genes associated with senescence (the decline of cell division), inflammation and apoptosis (programmed cell death) were upregulated in ageing cells. Genes associated with wound healing, cell differentiation and extracellular matrix synthesis were downregulated across species and cell types with chronological ageing.

The authors used these data to develop their own multi-tissue and multi-species molecular clocks to both assess chronological age and predict expected mortality. These models were validated using statistical approaches and against existing animal and cellular models of ageing. The clocks predicted time to death with accuracy comparable to second-generation epigenetic clocks. The real-time nature of transcriptomes over epigenetic data also enables the efficacy of life-extending interventions to be assessed on a molecular level.

In an accompanying News & Views article, João Pedro de Magalhães notes that the markers identified in this study “could help researchers to pinpoint which processes are modulated by interventions or diseases”, a valuable measure that is not visible through existing methods. However, further research is needed to disentangle exactly how these biomarkers are related to ageing and whether they are causative or simply by-products of the process.

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Organisation/s: Harvard Medical School, USA
Funder: The study was supported by NIA grants to V.N.G., D.E.H. and R.S. V.N.G. was also supported by Hevolution and the James Fickel and Michael Antonov Foundations. R.S. was supported by a Senior Research Career Scientist Award from the Department of Veterans Affairs Office of Research and Development. T.A. was supported by the Japan Agency for Medical Research and Development (AMED) 24zf0127001h0004. T.K. was supported by JST, ACT-X (JPMJAX24L4), JSPS KAKENHI Grant-in-Aid for Early-Career Scientists (JP22K15354), Takeda Science Foundation, The Uehara Memorial Foundation, The Naito Foundation, Astellas Foundation for Research on Metabolic Disorders, and Y.T. was supported by Okinaka Memorial Institute for Medical Research. The research has been conducted using the UK Biobank Resource under application number 21988. Molecular data for the Trans-Omics in Precision Medicine (TOPMed) programme was supported by the National Heart, Lung and Blood Institute (NHLBI). Core support including centralized genomic read mapping and genotype calling, along with variant quality metrics and filtering were provided by the TOPMed Informatics Research Center (3R01HL-117626-02S1; contract HHSN268201800002I). Core support including phenotype harmonization, data management, sample-identity quality control, and general programme coordination were provided by the TOPMed Data Coordinating Center (R01HL-120393; U01HL-120393; contract HHSN268201800001I).
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